National Library of Energy BETA

Sample records for understood sanyal classification

  1. Sanyal Temperature Classification | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report UrlNM-bRenewableSMUD WindI JumpTexas: EnergyIsabelSanyal

  2. Grid Security and Integration with Minimal Performance Degradation Sugata Sanyal

    E-Print Network [OSTI]

    Sanyal, Sugata

    Grid Security and Integration with Minimal Performance Degradation Sugata Sanyal School of computational grids becoming a reality. However, the question of grid security remains one of the important open research issues. Here, we present some novel ideas about how to implement grid security, without

  3. Category:Sanyal Temperature Classification | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmentalBowerbank,CammackFLIR Jump to:RAPID Roadmap ContactRock Density JumpSAR JumpSWIR

  4. Property:SanyalTempWellhead | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report Url Jump to:ProgrammableYear Jump to:SanyalTempWellhead Jump

  5. Zachary Hensley, Jibonananda Sanyal, Joshua New Energy and Transportation Sciences Division

    E-Print Network [OSTI]

    Wang, Xiaorui "Ray"

    Zachary Hensley, Jibonananda Sanyal, Joshua New Energy and Transportation Sciences Division@ornl.gov Provenance In the scientific world, it is important for researchers to know where their data came from approach this property via a contextual outlook. The granularity of our system can change depending on how

  6. Data Management Policy The guidelines below describe Data Management procedures, processes and resources that need to be understood by both

    E-Print Network [OSTI]

    Data Management Policy The guidelines below describe Data Management procedures, processes and resources that need to be understood by both user projects and in-house research. 1. Limited data management at CNMS to meet funding agency requirements for a Data Management Plan. 3. The standard User Agreement

  7. Classification Documents and Publications

    Broader source: Energy.gov [DOE]

    Certain documents and publications created or issued by the Office of Classification are available from this page.

  8. Top Ten Tips for Creating Funder-Useful Impact Statements 1. Write your statement in simple, plain English that can be understood by a non-technical reader.

    E-Print Network [OSTI]

    Tullos, Desiree

    communication and need not comply with technical writing standards. As much as possible, write in the active English that can be understood by a non-technical reader. 2. Avoid "wiggle" words. Academics equivocate an element of weakness or improbability to the impact statement. 3. The impact statement is not a technical

  9. Security classification of information

    SciTech Connect (OSTI)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  10. National Geothermal Resource Assessment and Classification |...

    Office of Environmental Management (EM)

    Resource Assessment and Classification National Geothermal Resource Assessment and Classification National Geothermal Resource Assessment and Classification presentation at the...

  11. Standard Subject Classification System

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1979-08-14

    The order establishes the DOE Standard Subject Classification System for classifying documents and records by subject, including correspondence, directives, and forms.Cancels DOE O 0000.1.

  12. Engineering rock mass classifications

    SciTech Connect (OSTI)

    Bieniawski, Z.T.

    1989-01-01

    This book is a reference on rock mass classification, consolidating into one handy source information widely scattered through the literature. Includes new, unpublished material and case histories. Presents the fundamental concepts of classification schemes and critically appraises their practical application in industrial projects such as tunneling and mining.

  13. AUTOMATIC MIXED PIXEL CLASSIFICATION (AMPC): UNSUPERVISED MIXED PIXEL CLASSIFICATION

    E-Print Network [OSTI]

    Chang, Chein-I

    13 AUTOMATIC MIXED PIXEL CLASSIFICATION (AMPC): UNSUPERVISED MIXED PIXEL CLASSIFICATION The automatic mixed pixel classification (AMPC) considered in this chapter is fully computer automated and can be implemented to automatically detect and classify targets with no human intervention. Like the automatic

  14. Lecture outline Classification

    E-Print Network [OSTI]

    Terzi, Evimaria

    ;Naïve Bayes Classifier: Example · X' = (HomeOwner = No, MaritalStatus = Married, Income=120K) · Need on training data · Test phase: ­ For test record X', compute the class Y' that maximizes the posterior probability Pr(Y'|X') Wednesday, October 30, 13 #12;Bayes Classification: Example X'=(Home Owner=No, Marital

  15. Lecture outline Classification

    E-Print Network [OSTI]

    Terzi, Evimaria

    Classification: Example X'=(Home Owner=No, Marital Status=Married, AnnualIncome=120K) Compute: Pr(Yes|X'), Pr discretize? #12;Naïve Bayes Classifier: Example · X' = (HomeOwner = No, MaritalStatus = Married, Income=120K: ­ For test record X', compute the class Y' that maximizes the posterior probability Pr(Y'|X') #12;Bayes

  16. Classification of Information Manual

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1985-05-08

    To specify responsibilities, authorities, policy, and procedures for the management of the Department of Energy (DOE) classification system. Cancels DOE O 5650.2, dated 12-12-1978. Canceled by DOE O 5650.2B, dated 12-31-1991.

  17. Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2015-04-01

    The order establishes departmental requirements and responsibilities for classifying positions using the general schedule (GS) and federal wage system (FWS) standards and to develop and administer a sound position management and classification program. Supersedes DOE O 325.2, dated 4-1-15.

  18. Position Management and Classification

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    2015-04-01

    The order establishes departmental requirements and responsibilities for classifying positions using general schedule (GS) and federal wage system (FWS) standards and for developing and administering a sound position management and classification program within the Department. Cancels Chapter VII of DOE O 320.1. Canceled by DOE O 325.2 Chg 1 (Admin Chg), 9-1-15.

  19. Materials Classification & Accelerated Property Predictions using...

    Office of Scientific and Technical Information (OSTI)

    Materials Classification & Accelerated Property Predictions using Machine Learning Citation Details In-Document Search Title: Materials Classification & Accelerated Property...

  20. Office of Classification | Department of Energy

    Office of Environmental Management (EM)

    Classification Officers, HQ Classification Representatives, Secret Original Classifiers, Top Secret Derivative Classifiers, HQ Derivative Classifiers and HQ UCNI Reviewing...

  1. Classification of Information

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1978-12-12

    To provide specific responsibilities, standards, and procedures for the management of the Department of Energy (DOE) classification system. Cancels DOE O 5650.1, dated 7-18-78; DOE N 5650.1, dated 8-7-78; DOE N 5650.2, dated 8-7-78; DOE N 5650.3, dated 8-7-78. Canceled by DOE O 5650.2A, dated 5-8-95

  2. Classification | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergy Webinar:I DueBETOoffor use with DOEClassification Classification

  3. Seismic event classification system

    DOE Patents [OSTI]

    Dowla, Farid U. (Castro Valley, CA); Jarpe, Stephen P. (Brentwood, CA); Maurer, William (Livermore, CA)

    1994-01-01

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

  4. Seismic event classification system

    DOE Patents [OSTI]

    Dowla, F.U.; Jarpe, S.P.; Maurer, W.

    1994-12-13

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities. 21 figures.

  5. Property:SanyalTempReservoir | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EIS Report Url Jump to:ProgrammableYear Jump to:

  6. Hierarchical Classification Web Content Susan Dumais

    E-Print Network [OSTI]

    Chen, Hao

    organizations. Since th century, librarians classification systems Dewey and Library Congress subject headings classification methods to supplement human effort in creating structured knowledge hierarchies. A wide rangeHierarchical Classification Web Content Susan Dumais Microsoft Research One Microsoft Way Redmond

  7. Short Papers___________________________________________________________________________________________________ Automatic Classification of

    E-Print Network [OSTI]

    Lyons, Michael J.

    ___________________________________________________________________________________________________ Automatic Classification of Single Facial Images Michael J. Lyons, Julien Budynek, and Shigeru Akamatsu image sets are presented for the classification of sex, ªrace,º and expression. A visual interpretation single digital images. The examples chosen to demonstrate our method are facial expression, sex

  8. Incremental Accelerated Gradient Methods for SVM Classification ...

    E-Print Network [OSTI]

    2013-05-02

    SVM Classification: Study of the Constrained ... Vector Machines (SVM) for online classification tasks. ...... A Library for Support Vector Machines [8]. 11.

  9. Burning Down the Shelf: Standardized Classification, Folksonomies, and Ontological Politics

    E-Print Network [OSTI]

    Lau, Andrew J.

    2008-01-01

    of Dewey Decimal Classification (DDC), Library of Congressstudies in critical classification. Library Resources and

  10. The many uses of classification: Enriched thesauri

    E-Print Network [OSTI]

    Soergel, Dagobert

    The many uses of classification: Enriched thesauri as knowledge sources Dagobert Soergel College of Information Studies University of Maryland ds52@umail.umd.edu #12;Classification everywhere concept maps Ontologies, Taxonomies Classification under any other name is still classification #12;Is SIG/CR everywhere

  11. Hierarchical classification of modulation signals 

    E-Print Network [OSTI]

    Kim, Nam Jin

    2002-01-01

    This thesis addresses the problem of classifying both analog and digital modulation signals using different kinds of classifiers. The classification of modulation signals has both civilian and military applications. A total of 31 statistical signal...

  12. Refining the classification of the irreps of the 1D N-Extended Supersymmetry

    E-Print Network [OSTI]

    Kuznetsova, Z; Kuznetsova, Zhanna; Toppan, Francesco

    2007-01-01

    In hep-th/0511274 the classification of the fields content of the linear finite irreducible representations of the algebra of the 1D N-Extended Supersymmetric Quantum Mechanics was given. In hep-th/0611060 it was pointed out that certain irreps with the same fields content can be regarded as inequivalent. This result can be understood in terms of the "connectivity" properties of the graphs associated to the irreps. We present here a classification of the connectivity of the irreps, refining the hep-th/0511274 classification based on fields content. As a byproduct, we find a counterexample to the hep-th/0611060 claim that the connectivity is uniquely specified by the "sources" and "targets" of an irrep graph. We produce one pair of N=5 irreps and three pairs of N=6 irreps with the same number of sources and targets which, nevertheless, differ in connectivity.

  13. HIV classification using coalescent theory

    SciTech Connect (OSTI)

    Zhang, Ming; Letiner, Thomas K; Korber, Bette T

    2008-01-01

    Algorithms for subtype classification and breakpoint detection of HIV-I sequences are based on a classification system of HIV-l. Hence, their quality highly depend on this system. Due to the history of creation of the current HIV-I nomenclature, the current one contains inconsistencies like: The phylogenetic distance between the subtype B and D is remarkably small compared with other pairs of subtypes. In fact, it is more like the distance of a pair of subsubtypes Robertson et al. (2000); Subtypes E and I do not exist any more since they were discovered to be composed of recombinants Robertson et al. (2000); It is currently discussed whether -- instead of CRF02 being a recombinant of subtype A and G -- subtype G should be designated as a circulating recombination form (CRF) nd CRF02 as a subtype Abecasis et al. (2007); There are 8 complete and over 400 partial HIV genomes in the LANL-database which belong neither to a subtype nor to a CRF (denoted by U). Moreover, the current classification system is somehow arbitrary like all complex classification systems that were created manually. To this end, it is desirable to deduce the classification system of HIV systematically by an algorithm. Of course, this problem is not restricted to HIV, but applies to all fast mutating and recombining viruses. Our work addresses the simpler subproblem to score classifications of given input sequences of some virus species (classification denotes a partition of the input sequences in several subtypes and CRFs). To this end, we reconstruct ancestral recombination graphs (ARG) of the input sequences under restrictions determined by the given classification. These restritions are imposed in order to ensure that the reconstructed ARGs do not contradict the classification under consideration. Then, we find the ARG with maximal probability by means of Markov Chain Monte Carlo methods. The probability of the most probable ARG is interpreted as a score for the classification. To our knowledge, this particular problem was not addressed up to now. The software package Lamarc Kuhner et al. (2000) allows for sampling ARGs, but it assumes that recombination events only involve one breakpoint. However, in HIV recombinants usually have more than one breakpoint. Moreover, Lamarc does not perform an explicit breakpoint detection, but tries to find them by chance. Although this approach is suitable for most situations, it will not lead to satisfying results in case of highly recombining viruses with multiple breakpoints.

  14. Quantum computing for pattern classification

    E-Print Network [OSTI]

    Maria Schuld; Ilya Sinayskiy; Francesco Petruccione

    2014-12-11

    It is well known that for certain tasks, quantum computing outperforms classical computing. A growing number of contributions try to use this advantage in order to improve or extend classical machine learning algorithms by methods of quantum information theory. This paper gives a brief introduction into quantum machine learning using the example of pattern classification. We introduce a quantum pattern classification algorithm that draws on Trugenberger's proposal for measuring the Hamming distance on a quantum computer (CA Trugenberger, Phys Rev Let 87, 2001) and discuss its advantages using handwritten digit recognition as from the MNIST database.

  15. Maturing Software Engineering Knowledge through Classifications

    E-Print Network [OSTI]

    Basili, Victor R.

    Maturing Software Engineering Knowledge through Classifications: A Case Study on Unit Testing contribution to advancing knowledge in both science and engineering. It is a way of investigating Engineering knowledge, as classifications constitute an organized structure of knowledge items. Till date

  16. Updating the Classification of Geothermal Resources- Presentation

    Office of Energy Efficiency and Renewable Energy (EERE)

    USGS is working with DOE, the geothermal industry, and academic partners to develop a new geothermal resource classification system.

  17. Updating the Classification of Geothermal Resources

    Office of Energy Efficiency and Renewable Energy (EERE)

    USGS is working with DOE, the geothermal industry, and academic partners to develop a new geothermal resource classification system.

  18. FEATURE SELECTION AND CLASSIFICATION OF

    E-Print Network [OSTI]

    Kuncheva, Ludmila I.

    in the veterinary domain is important with regard to agriculture, the health sector and the economy, various feature selection techniques were applied and compared in this study in order to select a reducedFEATURE SELECTION AND CLASSIFICATION OF NON-TRADITIONAL DATA. EXAMPLES FROM VETERINARY MEDICINE Zo

  19. Flying Insect Classification with Inexpensive Yanping Chen

    E-Print Network [OSTI]

    Zordan, Victor

    Flying Insect Classification with Inexpensive Sensors Yanping Chen Department of Computer Science and extrinsic to the insect's flight behavior, and that a Bayesian classification approach allows us to efficiently learn classification models that are very robust to overfitting. We demonstrate our findings

  20. Creating and Visualizing Fuzzy Document Classification

    E-Print Network [OSTI]

    Fink, Eugene

    Creating and Visualizing Fuzzy Document Classification Judith Gelernter Dong Cao Raymond Lu Eugene@cs.cmu.edu Abstract--Fuzzy classification ranks items by degree rather than assigning them either within or without of a category. The novelty of our work is in integrating fuzzy classification algorithms with an interface

  1. Acclimatizing Taxonomic Semantics for Hierarchical Content Classification

    E-Print Network [OSTI]

    Liu, Huan

    Acclimatizing Taxonomic Semantics for Hierarchical Content Classification Lei Tang Dept. of Comp in con- tent classification. However, we observe through empirical study that the performance semantics-based hierarchy does not work well in con- tent classification, and how it could be improved

  2. Sequential Pattern Classification Without Explicit Feature Extraction

    E-Print Network [OSTI]

    Krovi, Venkat

    classification framework of SVM. We present experiments with off­line digit images where the pixels are simplySequential Pattern Classification Without Explicit Feature Extraction by Hansheng Lei October 21st. A suitable similarity measure can also be used to increase the classification efficiency of traditional

  3. Style Consistent Classification of Isogenous Patterns

    E-Print Network [OSTI]

    Nagy, George

    a basis for more accurate classification of a group (field) of digitized characters from the same sourceStyle Consistent Classification of Isogenous Patterns Prateek Sarkar, Member, IEEE Computer Society they share the same, albeit unknown, style. Style constrained classifiers achieve higher classification

  4. Automatic Detection and Classification of Sunspot Images

    E-Print Network [OSTI]

    Wolfe, Patrick J.

    Automatic Detection and Classification of Sunspot Images Thomas C. M. Lee tlee with Alex Young and the SaFeDe Solar Imaging Group JSM 2007 ­ p. 1/2 #12;Outline Title: Automatic Detection and Classification of Sunspot Images JSM 2007 ­ p. 2/2 #12;Outline Title: Automatic Detection and Classification

  5. Featureless Classification of Light Curves

    E-Print Network [OSTI]

    Kügler, Sven Dennis; Polsterer, Kai Lars

    2015-01-01

    In the era of rapidly increasing amounts of time series data, classification of variable objects has become the main objective of time-domain astronomy. Classification of irregularly sampled time series is particularly difficult because the data can not be represented naturally as a plain vector which directly can be fed into a classifier. In the literature, various statistical features derived from time series serve as a representation. Typically, the usefulness of the derived features is judged in an empirical fashion according to their predictive power. In this work, an alternative to the feature-based approach is investigated. In this new representation the time series is described by a density model. Similarity between each pair of time series is quantified by the distance between their respective models. The density model captures all the information available, also including measurement errors. Hence, we view this model as a generalisation to the static features which directly can be derived, e.g., as ...

  6. Topological classification of RNA structures

    E-Print Network [OSTI]

    Michael Bon; Graziano Vernizzi; Henri Orland; A. Zee

    2006-07-21

    We present a novel topological classification of RNA secondary structures with pseudoknots. It is based on the topological genus of the circular diagram associated to the RNA base-pair structure. The genus is a positive integer number, whose value quantifies the topological complexity of the folded RNA structure. In such a representation, planar diagrams correspond to pure RNA secondary structures and have zero genus, whereas non planar diagrams correspond to pseudoknotted structures and have higher genus. We analyze real RNA structures from the databases wwPDB and Pseudobase, and classify them according to their topological genus. We compare the results of our statistical survey with existing theoretical and numerical models. We also discuss possible applications of this classification and show how it can be used for identifying new RNA structural motifs.

  7. University Policy No.: AD2530 Classification: Administration

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: AD2530 Classification: Administration PHOTOCOPY AND FACSIMILE (FAX may be obtained through library managed machines or through the use of personal accounts. 1

  8. ON THE CLASSIFICATION OF NUCLEAR C -ALGEBRAS

    E-Print Network [OSTI]

    2002-05-28

    ON THE CLASSIFICATION OF NUCLEAR C?-ALGEBRAS. MARIUS DADARLAT and S?REN EILERS. 1. Introduction. Two of the most influential works on ...

  9. Discriminant forest classification method and system

    DOE Patents [OSTI]

    Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

    2012-11-06

    A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

  10. University Policy No.: AD2210 Classification: Administration

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: AD2210 Classification: Administration FIELDWORK AND INTERNATIONAL: includes all University of Victoria administrators, faculty, staff, and students while such individuals

  11. University Policy No.: AD2215 Classification: Administration

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: AD2215 Classification: Administration Approving Authority: Board Review: 1. This statement applies to the policies and administration of trademarks registered

  12. OROZCO et al.: HEAD POSE CLASSIFICATION IN CROWDED SCENES 1 Head Pose Classification in Crowded Scenes

    E-Print Network [OSTI]

    Gong, Shaogang

    attempts have been made on head pose estimation in low-resolution images by treating the problem as a multi for head pose classification given low resolution images. In their approach, 360 head pose in c 2009OROZCO et al.: HEAD POSE CLASSIFICATION IN CROWDED SCENES 1 Head Pose Classification in Crowded

  13. Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis

    E-Print Network [OSTI]

    Lawrence, Rick L.

    trees) are increasingly being used for analysis and classification of remotely sensed digital imageryClassification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis Rick Lawrencea,*, Andrew Bunna , Scott Powellb , Michael Zambona a Department

  14. Multiclass Support Vector Classification via Regression Multiclass Support Vector Classification via Regression

    E-Print Network [OSTI]

    Huang, Su-Yun

    Multiclass Support Vector Classification via Regression Multiclass Support Vector Classification via Regression Pei-Chun Chen peichun@stat.sinica.edu.tw Institute of Statistical Science Academia classification is considered and resolved through the mul- tiresponse linear regression approach. Scores are used

  15. Seoul, South Korea -classification deteriorating slope stability -Robert Hack 1 SLOPE STABILITY CLASSIFICATION

    E-Print Network [OSTI]

    Hack, Robert

    Seoul, South Korea - classification deteriorating slope stability - Robert Hack 1 SLOPE STABILITY CLASSIFICATION OF TIME DEPENDENT DETERIORATING SLOPES Seoul, Korea, 29 February 2008 Robert Hack Engineering) The Netherlands #12;Seoul, South Korea - classification deteriorating slope stability - Robert Hack 2 Jan van

  16. Rule-based classification using classification tree analysis (CTA) is increasingly applied to remotely sensed data. CTA

    E-Print Network [OSTI]

    Lawrence, Rick L.

    for classification of remotely sensed data. Introduction The classification of digital imagery to extract useful theAbstract Rule-based classification using classification tree analysis (CTA) is increasingly applied. Results are then used for image classification. Software implementations of CTA offer differ- ent

  17. Expression Microarray Classification using Topic Models Manuele Bicego

    E-Print Network [OSTI]

    Bicego, Manuele

    Expression Microarray Classification using Topic Models Manuele Bicego , Pietro Lovato, Barbara - Verona, Italy ABSTRACT Classification of samples in expression microarray experi- ments represents the expression microarray classification task is cast into this probabilistic context, providing a parallelism

  18. Automatic Musical Genre Classification Of Audio Signals

    E-Print Network [OSTI]

    Tzanetakis, George

    genre classification for digitally available music has been performed manually. Therefore techniquesAutomatic Musical Genre Classification Of Audio Signals George Tzanetakis Computer Science to structure the increasing amounts of music available in digital form on the Web and are important for music

  19. Classification of Unexploded Ordnance Laurens Sander Beran

    E-Print Network [OSTI]

    Oldenburg, Douglas W.

    Classification of Unexploded Ordnance by Laurens Sander Beran B.Sc., The University of Victoria degree at the University of British Columbia, I agree that the Library shall make it freely available and clutter. In the statistical classification framework, model parameters are basis vectors within a multi

  20. A Thermodynamic Classification of Real Numbers

    E-Print Network [OSTI]

    Thomas Garrity

    2009-03-15

    A new classification scheme for real numbers is given, motivated by ideas from statistical mechanics in general and work of Knauf and of Fiala and Kleban in particular. Critical for this classification of a real number will be the Diophantine properties of its continued fraction expansion.

  1. On learning hierarchical classifications Russell Greiner

    E-Print Network [OSTI]

    Schuurmans, Dale

    On learning hierarchical classifications Russell Greiner Siemens Corporate Research 755 College in Cognitive Science University of Pennsylvania Philadelphia, PA 19104­6228 daes@linc.cis.upenn.edu Abstract Many significant real­world classification tasks involve a large number of categories which

  2. Hierarchical Classification of Web Content Susan Dumais

    E-Print Network [OSTI]

    Fan, Jianping

    classification methods to supplement human effort in creating structured knowledge hierarchies. A wide rangeHierarchical Classification of Web Content Susan Dumais Microsoft Research One Microsoft Way Redmond, WA 99802 USA sdumais@microsoft.com Hao Chen Computer Science Division University of California

  3. On learning hierarchical classifications Russell Greiner

    E-Print Network [OSTI]

    Greiner, Russell

    On learning hierarchical classifications Russell Greiner Siemens Corporate Research 755 College in Cognitive Science University of Pennsylvania Philadelphia, PA 19104-6228 daes@linc.cis.upenn.edu Abstract Many significant real-world classification tasks involve a large number of categories which

  4. Mismatch String Kernels for SVM Protein Classification

    E-Print Network [OSTI]

    Noble, William Stafford

    machines (SVMs) in a discriminative approach to the protein classification problem. These kernels measure efficiently using a mismatch tree data structure and report experiments on a benchmark SCOP dataset, where we savings. 1 Introduction A fundamental problem in computational biology is the classification of proteins

  5. AUTOMATIC MIXED PIXEL CLASSIFICATIO (AMPC): ANOMALY CLASSIFICATION

    E-Print Network [OSTI]

    Chang, Chein-I

    14 AUTOMATIC MIXED PIXEL CLASSIFICATIO (AMPC): ANOMALY CLASSIFICATION In Chapter 13, one type of AMPC, automatic target detection and classification (ATDC) is investigated, which does not require any, an automatic thresholding method and four target discrimination measures are introduced in this chapter

  6. Oil Classification with Fluorescence Spectroscopy Engineering Physics

    E-Print Network [OSTI]

    Oldenburg, Carl von Ossietzky Universität

    detected by these channels. The investigation used three methods to examine crude oil, heavy oil, sludge1 Oil Classification with Fluorescence Spectroscopy Engineering Physics Master of Engineering and classification of oil spills on water surfaces. It is an overview of the laser remote sensor technique

  7. Integrated Pedestrian Classification and Orientation Estimation

    E-Print Network [OSTI]

    Gavrila, Dariu M.

    Integrated Pedestrian Classification and Orientation Estimation Markus Enzweiler1 Dariu M. Gavrila2, The Netherlands Abstract This paper presents a novel approach to single-frame pedestrian classification) in a Bayesian fashion. This mixture-of-experts formulation approximates the probability density of pedestrian

  8. Visual Exploration of Uncertainty in Remotesensing Classification

    E-Print Network [OSTI]

    Utrecht, Universiteit

    Visual Exploration of Uncertainty in Remote­sensing Classification Frans J.M. van der Wel Utrecht analysis of remotely­sensed data aims at acquiring insight as to the stability of possible classifications for an overwhelming flow of data on the appearance and condition of our planet. The data yielded by remote sensing can

  9. Marine and Estuarine Ecosystem and Habitat Classification

    E-Print Network [OSTI]

    Marine and Estuarine Ecosystem and Habitat Classification Rebecca J. Allee Megan Dethier Dail Brown Administration National Marine Fisheries Service NOAA Technical Memorandum NMFS-F/SPO-43 July 2000 #12;A copy-WestHighway Silver Spring, MD 20910 #12;Marine and Estuarine Ecosystem and Habitat Classification Rebecca J. Allee

  10. A complete electrical hazard classification system and its application

    SciTech Connect (OSTI)

    Gordon, Lloyd B; Cartelli, Laura

    2009-01-01

    The Standard for Electrical Safety in the Workplace, NFPA 70E, and relevant OSHA electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. This leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. Examples include lasers, accelerators, capacitor banks, electroplating systems, induction and dielectric heating systems, etc. Although all such systems are fed by 50/60 Hz alternating current (ac) power, we find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50160 Hz power. Over the past 10 years there has been an effort to develop a method of classifying all of the electrical hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Initially, national electrical safety codes required the qualified worker only to know the source voltage to determine the shock hazard. Later, as arc flash hazards were understood, the fault current and clearing time were needed. These items are still insufficient to fully characterize all types of electrical hazards. The new comprehensive electrical hazard classification system uses a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards. Based on this electrical hazard classification system, many new tools have been developed, including (a) work controls for these hazards, (b) better selection of PPE for R&D work, (c) improved training, and (d) a new Severity Ranking Tool that is used to rank electrical accidents and incidents with various forms of electrical energy.

  11. Modifying Kernels Using Label Information Improves SVM Classification Performance

    E-Print Network [OSTI]

    Toronto, University of

    , we solve protein remote homology detec- tion problem and handwritten digit classification problem digit classification and two mismatch-string kernels as base ker- nels [6] for protein classification. We present our experi- mental results for digit classification and protein homology detection

  12. Tags vs Shelves: From Social Tagging to Social Classification

    E-Print Network [OSTI]

    Hammerton, James

    mechanism and (iii) existing classification systems such as the Library of Congress Classification System libraries and librarians have performed the task of classification for centuries, the process of man- uallyTags vs Shelves: From Social Tagging to Social Classification Arkaitz Zubiaga NLP & IR Group

  13. A Comparison of Evolvable Hardware Architectures for Classification Tasks

    E-Print Network [OSTI]

    Glette, Kyrre

    accuracy. For the electromyographic (EMG) signal classification, [5] showed that EHW approaches can perform

  14. Audio Classification using Extended Baum-Welch Transformations

    E-Print Network [OSTI]

    of sources, including speech, music, coughing, laughter, etc. Classification has become an important tool

  15. Real-time Classification for The Palomar Transient Factory

    E-Print Network [OSTI]

    Real-time Classification for The Palomar Transient Factory Joseph Richards UC Berkeley Department;Transient Classification Project (TCP) J. Richards Classification for PTF 2 #12;Outline 1 Palomar Transient for PTF? J. Richards Classification for PTF 3 #12;Palomar Transient Factory (PTF) Fully-automated survey

  16. Representation, Organization, Classification, and Meaning-Making

    E-Print Network [OSTI]

    Toronto, University of

    1 Representation, Organization, Classification, and Meaning-Making Description Fundamental epistemological and ontological issues in the use of knowledge and information in human activities. Analysis, department store, grocery store, children's library, a menu, a store catalogue) and analyze that organization

  17. IDENTIFYING ROOF FALL PREDICTORS USING FUZZY CLASSIFICATION

    SciTech Connect (OSTI)

    Bertoncini, C. A.; Hinders, M. K.

    2010-02-22

    Microseismic monitoring involves placing geophones on the rock surfaces of a mine to record seismic activity. Classification of microseismic mine data can be used to predict seismic events in a mine to mitigate mining hazards, such as roof falls, where properly bolting and bracing the roof is often an insufficient method of preventing weak roofs from destabilizing. In this study, six months of recorded acoustic waveforms from microseismic monitoring in a Pennsylvania limestone mine were analyzed using classification techniques to predict roof falls. Fuzzy classification using features selected for computational ease was applied on the mine data. Both large roof fall events could be predicted using a Roof Fall Index (RFI) metric calculated from the results of the fuzzy classification. RFI was successfully used to resolve the two significant roof fall events and predicted both events by at least 15 hours before visual signs of the roof falls were evident.

  18. Multivariate Approaches to Classification in Extragalactic Astronomy

    E-Print Network [OSTI]

    Fraix-Burnet, Didier; Chattopadhyay, Asis Kumar

    2015-01-01

    Clustering objects into synthetic groups is a natural activity of any science. Astrophysics is not an exception and is now facing a deluge of data. For galaxies, the one-century old Hubble classification and the Hubble tuning fork are still largely in use, together with numerous mono-or bivariate classifications most often made by eye. However, a classification must be driven by the data, and sophisticated multivariate statistical tools are used more and more often. In this paper we review these different approaches in order to situate them in the general context of unsupervised and supervised learning. We insist on the astrophysical outcomes of these studies to show that multivariate analyses provide an obvious path toward a renewal of our classification of galaxies and are invaluable tools to investigate the physics and evolution of galaxies.

  19. A material segmentation and classification system

    E-Print Network [OSTI]

    Wong, Jennifer L

    2013-01-01

    In this thesis, I developed a material segmentation and classification system that takes in images of an object and identifies the material composition of the object's surface. The 3D surface is first segmented into regions ...

  20. Photon level chemical classification using digital compressive ...

    E-Print Network [OSTI]

    David S. Wilcox

    2012-11-09

    Oct 12, 2012 ... programmable binary optical filters designed to minimize the error in the chemical classification (or con- ...... troscopy, thus highlighting the power of compressive detection. ... Since the mirror switching time of our DMD.

  1. Vapor Retarder Classification - Building America Top Innovation...

    Broader source: Energy.gov (indexed) [DOE]

    vapor retarder classification. Air-tight and well-insulated homes have little or no tolerance for drying if they get wet; moisture control is critical. This Top Innovation profile...

  2. On the Consistency of Multiclass Classification Methods

    E-Print Network [OSTI]

    Tewari, Ambuj

    On the Consistency of Multiclass Classification Methods Ambuj Tewari1 and Peter L. Bartlett2 1 Springer-Verlag Berlin Heidelberg 2005 #12;144 A. Tewari and P.L. Bartlett guarantee that if the -risk of f

  3. Linear feature selection for multipopulation classification 

    E-Print Network [OSTI]

    Havens, Kathryn Anne

    1974-01-01

    ) December 1974 ABSTRACT Linear Feature Selection for Multipopulation Classification. (December 1974) Kathryn A. Havens, B. S. , Lamar University Chairman of Advisory Committee: Dr. L. F. Guseman, Jr. A classification procedure for n...-dimensional normally distributed observation vectors which belong to one of three populations is de- scribed. In particular, a computational procedure is presented for finding a lxn vector B which minimizes the probability of misclassification with respect...

  4. Materials and methods Evolutionary classification of C. elegans proteins. For classification of C. ele-

    E-Print Network [OSTI]

    Yu, Haiyuan

    Materials and methods Evolutionary classification of C. elegans proteins. For classification of C the ORFeome library (1) and transformed into E. coli strain DH5 in 96 well format. Up to 12 single colonies- propriate concentration. AD-ORFeome 1.0 and AD-wrmcDNA libraries. The two Gal4 activation do- main (AD

  5. A Dynamical Classification of the Cosmic Web

    E-Print Network [OSTI]

    J. E. Forero-Romero; Y. Hoffman; S. Gottloeber; A. Klypin; G. Yepes

    2008-09-24

    A dynamical classification of the cosmic web is proposed. The large scale environment is classified into four web types: voids, sheets, filaments and knots. The classification is based on the evaluation of the deformation tensor, i.e. the Hessian of the gravitational potential, on a grid. The classification is based on counting the number of eigenvalues above a certain threshold, lambda_th at each grid point, where the case of zero, one, two or three such eigenvalues corresponds to void, sheet, filament or a knot grid point. The collection of neighboring grid points, friends-of-friends, of the same web attribute constitutes voids, sheets, filaments and knots as web objects. A simple dynamical consideration suggests that lambda_th should be approximately unity, upon an appropriate scaling of the deformation tensor. The algorithm has been applied and tested against a suite of (dark matter only) cosmological N-body simulations. In particular, the dependence of the volume and mass filling fractions on lambda_th and on the resolution has been calculated for the four web types. Also, the percolation properties of voids and filaments have been studied. Our main findings are: (a) Already at lambda_th = 0.1 the resulting web classification reproduces the visual impression of the cosmic web. (b) Between 0.2 web. (c) The dynamical nature of the suggested classification provides a robust framework for incorporating environmental information into galaxy formation models, and in particular the semi-analytical ones.

  6. The Classification of M1-78

    E-Print Network [OSTI]

    G. T. Gussie

    1994-09-15

    The published properties of M1-78 are discussed with the purpose to resolve the object's classification as either a planetary nebula or an ultracompact HII region. A classification as a planetary nebula is rejected primarily because of the high luminosity of the object, but because of the chemical composition and expansion velocity of the nebula, a novel classification is proposed instead: that of an ultracompact HII region with a post-main sequence central star (possibly a WN star). It must therefore follow that observable ultracompact HII regions persist beyond the main sequence lifetimes of at least some massive stars, and so cannot be transient phenomena that are seen only during pre-main sequence or early main sequence evolution.

  7. Classification rule with simple select SQL statement

    E-Print Network [OSTI]

    H, Spits Warnars H L

    2010-01-01

    A simple sql statement can be used to search learning or rule in relational database for data mining purposes particularly for classification rule. With just only one simple sql statement, characteristic and classification rule can be created simultaneously. Collaboration sql statement with any other application software will increase the ability for creating t-weight as measurement the typicality of each record in the characteristic rule and d-weight as measurement the discriminating behavior of the learned classification/discriminant rule, specifically for further generalization in characteristic rule. Handling concept hierarchy into tables based on concept tree will influence for the successful simple sql statement and by knowing the right standard knowledge to transform each of concept tree in concept hierarchy into one table as to transform concept hierarchy into table, the simple sql statement can be run properly.

  8. Classification and reconstruction of three-dimensional microstructures using

    E-Print Network [OSTI]

    Zabaras, Nicholas J.

    Classification and reconstruction of three-dimensional microstructures using support vector of reconstructed microstructures with available experimental re- sults. Combination of classification methodology-dimensional microstructures experimentally characterized by combining digitized serial sections or through methods like X

  9. Perceptually Based Techniques for Semantic Image Classification and Retrieval

    E-Print Network [OSTI]

    Pappas, Thrasyvoulos N.

    Perceptually Based Techniques for Semantic Image Classification and Retrieval Dejan Depalov, Schaumburg, IL, 60196 ABSTRACT The accumulation of large collections of digital images has created the need semantically, according to meaningful categories. We present a new approach for semantic classification

  10. Cell-Graph Mining for Breast Tissue Modelling and Classification

    E-Print Network [OSTI]

    Bystroff, Chris

    metrics for tissue characteriza- tion and classification. We segmented the digital images of histopaCell-Graph Mining for Breast Tissue Modelling and Classification C.C¸ agatay Bilgin a, C¸ igdem

  11. 163 SDSU Curriculum Guide 2010 COURSE CLASSIFICATION SYSTEM --EXAMPLES

    E-Print Network [OSTI]

    Ponce, V. Miguel

    163 SDSU Curriculum Guide 2010 COURSE CLASSIFICATION SYSTEM -- EXAMPLES Course Classification of business and other machines; accounting, geography, foreign languages, home economics, psychology, library, cartography, audiovisual, mathematics, library science, police science. C-16 Science laboratories Laboratories

  12. Seismic Facies Classification And Identification By Competitive Neural Networks

    E-Print Network [OSTI]

    Saggaf, Muhammad M.

    2000-01-01

    We present an approach based on competitive networks for the classification and identification of reservoir facies from seismic data. This approach can be adapted to perform either classification of the seismic facies based ...

  13. Automatic Fish Classification for Underwater Species Behavior Understanding

    E-Print Network [OSTI]

    Fisher, Bob

    Automatic Fish Classification for Underwater Species Behavior Understanding Concetto Spampinato an automatic fish classi- fication system that operates in the natural underwater en- vironment to assist marine biologists in understanding fish behavior. Fish classification is performed by combining two types

  14. Abductive Network Committees for Improved Classification of Medical Data

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Abductive Network Committees for Improved Classification of Medical Data R. E. Abdel-Aal Center standard medical datasets. Methods: Two standard 2-class medical datasets (Pima Indians Diabetes and Heart mining and machine learning techniques for classification, association detection, sequential

  15. Automatic classification of eclipsing binaries light curves using neural networks

    E-Print Network [OSTI]

    L. M. Sarro; C. Sánchez-Fernández; A. Giménez

    2005-11-11

    In this work we present a system for the automatic classification of the light curves of eclipsing binaries. This system is based on a classification scheme that aims to separate eclipsing binary sistems according to their geometrical configuration in a modified version of the traditional classification scheme. The classification is performed by a Bayesian ensemble of neural networks trained with {\\em Hipparcos} data of seven different categories including eccentric binary systems and two types of pulsating light curve morphologies.

  16. Classification and Utilization of Abstractions for Optimization

    E-Print Network [OSTI]

    Yi, Qing

    Classification and Utilization of Abstractions for Optimization Dan Quinlan1 , Markus Schordan2.sabjornsen@fys.uio.no Abstract. We define a novel approach to optimize the use of libraries within applications. We propose that library-defined abstractions be clas- sified to support their automated optimization and by leveraging

  17. Learning of Optimal Illumination for Material Classification

    E-Print Network [OSTI]

    Hamprecht, Fred A.

    Learning of Optimal Illumination for Material Classification Markus Jehle, Christoph Sommer, Bernd.Jehle, Christoph.Sommer, Bernd.Jaehne}@iwr.uni-heidelberg.de Abstract. We present a method to classify materials classifier different materials, which vary in appearance (which itself depends on the patterns of incoming

  18. North Carolina State Residence Classification Manual

    E-Print Network [OSTI]

    McLaughlin, Richard M.

    North Carolina State Residence Classification Manual A Manual to Assist the Public Higher Education Institutions of North Carolina in the Matter of State Residence Fall 2011 #12;North Carolina State Residence. Ross pursuant to The University of North Carolina Policy Manual Sec. 900.1 for use by con- stituent

  19. Workload State Classification With Automation During Simulated

    E-Print Network [OSTI]

    Kaber, David B.

    Workload State Classification With Automation During Simulated Air Traffic Control David B. Kaber to dynamically apply automation to information pro- cessing functions in aviation systems. This research examined manual control or 1 of 4 different forms of automation. Traffic volume was either low (3 aircraft

  20. University Policy No.: RH8205 Classification: Research

    E-Print Network [OSTI]

    Victoria, University of

    which requires, as a condition of deducting expenses, that the type of research carried out under the #12;research project be a type of research that is different from the type of research work ordinarilyUniversity Policy No.: RH8205 Classification: Research RESEARCH GRANTS IN LIEU OF Approving

  1. CLASSIFICATION OF DIVISION -GRADED ALTERNATIVE ALGEBRAS

    E-Print Network [OSTI]

    Yoshii, Yoji

    CLASSIFICATION OF DIVISION Zn -GRADED ALTERNATIVE ALGEBRAS Yoji Yoshii Department of Mathematical division Zn-graded alternative algebras, is classified in this paper. Using the result, we can complete -graded alternative algebras. It turns out that they are strongly prime, and so one can apply Slater

  2. Investigating a Breach of Research Integrity Classification

    E-Print Network [OSTI]

    Calgary, University of

    hi Investigating a Breach of Research Integrity Classification Research Table of Contents Purpose 1 of this procedure is to outline the process by which an allegation of a breach of Research integrity, as defined, post- doctoral fellows, and any other person who conducts research under the auspices or jurisdiction

  3. Multivariate Autoregressive Models for Classification of Spontaneous

    E-Print Network [OSTI]

    Anderson, Charles W.

    Multivariate Autoregressive Models for Classification of Spontaneous Electroencephalogram During University Fort Collins, CO 80523 Abstract This article explores the use of scalar and multivariate, eigenvalues of a correlation matrix, and the Karhunen­Loâ??eve trans­ form of the multivariate AR coefficients

  4. Multivariate Statistical Tests for Comparing Classification Algorithms

    E-Print Network [OSTI]

    Alpaydýn, Ethem

    Multivariate Statistical Tests for Comparing Classification Algorithms Olcay Taner Yildiz1 , ¨Ozlem these in a single number, we propose to collect multivariate statistics and use multivariate tests on them rate (tpr) and false positive rate (fpr) and a multivariate test can also use such two values instead

  5. Light-water reactor accident classification

    SciTech Connect (OSTI)

    Washburn, B.W.

    1980-02-01

    The evolution of existing classifications and definitions of light-water reactor accidents is considered. Licensing practice and licensing trends are examined with respect to terms of art such as Class 8 and Class 9 accidents. Interim definitions, consistent with current licensing practice and the regulations, are proposed for these terms of art.

  6. Bayesian fluorescence in situ hybridisation signal classification

    E-Print Network [OSTI]

    Lerner, Boaz

    hybridisation (FISH) signals for the detection of genetic abnormalities. Based on well-discriminating features hybridisation (FISH); Gaussian mixture model; Naive Bayesian classifier; Signal classification Artificial.artmed.2003.11.005 #12;1. Introduction Fluorescence in situ hybridisation (FISH) allows selective staining

  7. Entanglement classification with matrix product states

    E-Print Network [OSTI]

    M. Sanz; I. L. Egusquiza; R. Di Candia; H. Saberi; L. Lamata; E. Solano

    2015-04-28

    Entanglement is widely considered the cornerstone of quantum information and an essential resource for relevant quantum effects, such as quantum teleportation, quantum cryptography, or the speed-up of quantum computing, as in Shor's algorithm. However, up to now, there is no general characterization of entanglement for many-body systems. In this sense, it is encouraging that quantum states connected by stochastic local operations assisted with classical communication (SLOCC), which perform probabilistically the same quantum tasks, can be collected into entanglement classes. Nevertheless, there is an infinite number of classes for four or more parties that may be gathered, in turn, into a finite number of entanglement families. Unfortunately, we have not been able to relate all classes and families to specific properties or quantum information tasks, although a few of them have certainly raised experimental interest. Here, we present a novel entanglement classification for quantum states according to their matrix-product-state structure, exemplified for the symmetric subspace. The proposed classification relates entanglement families to the interaction length of Hamiltonians, establishing the first connection between entanglement classification and condensed matter. Additionally, we found a natural nesting property in which the families for $N$ parties carry over to the $N+1$ case. We anticipate our proposal to be a starting point for the exploration of the connection between entanglement classification properties and condensed-matter models.

  8. SUPPORT VECTOR MACHINE CLASSIFICATION 18th July, 2006

    E-Print Network [OSTI]

    Wand, Matt

    of research is computer- aided mail sorting. Figure 1 shows 3 sets of handwritten digits. Suppose that someSUPPORT VECTOR MACHINE CLASSIFICATION M.P. Wand1 18th July, 2006 Support vector machines emerged in the mid-1990s as a flexible and powerful means of classification. Classification is a very old problem

  9. Matrix Completion for Multi-label Image Classification

    E-Print Network [OSTI]

    Instituto de Sistemas e Robotica

    Matrix Completion for Multi-label Image Classification Ricardo S. Cabral, Fernando De la Torre and browse digital images via semantic keywords. This paper for- mulates image categorization as a multi-label classification problem using recent advances in matrix completion. Under this setting, classification of testing

  10. A multiscale texture analysis procedure for improved forest stand classification

    E-Print Network [OSTI]

    Coburn, Craig

    classes from digital remotely sensed data based on their spectral properties alone. These classificationA multiscale texture analysis procedure for improved forest stand classification C. A. COBURN of image texture in image classification has increased. Current approaches to image texture analysis rely

  11. Compressive Video Classification for Decision Systems with Limited Resources

    E-Print Network [OSTI]

    Tsakalides, Panagiotis

    by the introduction of efficient computational models is video classification. With the advent of digital TVCompressive Video Classification for Decision Systems with Limited Resources George Tzagkarakis}@ics.forth.gr Abstract--In this paper, we address the problem of video classification from a set of compressed features

  12. Generic Image Classification Using Visual Knowledge on the Web

    E-Print Network [OSTI]

    Yanai, Keiji

    mining, image gathering, image classification 1. INTRODUCTION Permission to make digital or hard copiesGeneric Image Classification Using Visual Knowledge on the Web Keiji Yanai Department of Computer@cs.uec.ac.jp ABSTRACT In this paper, we describe a generic image classification sys- tem with an automatic knowledge

  13. DISCRIMINATION AND CLASSIFICATION OF UXO USING MAGNETOMETRY: INVERSION AND ERROR

    E-Print Network [OSTI]

    Oldenburg, Douglas W.

    DISCRIMINATION AND CLASSIFICATION OF UXO USING MAGNETOMETRY: INVERSION AND ERROR ANALYSIS USING for the different solutions didn't even overlap. Introduction A discrimination and classification strategy-UXOs dug per UXO). The discrimination and classification methodology depends on the magnitude of the recov

  14. Experiments in Multimodality Image Classification and Data Fusion

    E-Print Network [OSTI]

    Farag, Aly A.

    Experiments in Multimodality Image Classification and Data Fusion Aly A. Farag, Refaat M. Mohamed report the results of some experiments on image classification and data fusion of remote sensing images different algorithms for image classification, and an image fusion algorithm have been implemented

  15. Introduction/Motivation Fuchsian Groups -Background Classification Program Results/References Classification of Pairs of Fuchsian Groups

    E-Print Network [OSTI]

    Broughton, S. Allen

    Introduction/Motivation Fuchsian Groups - Background Classification Program Results Seminar - March 2, 2009 #12;Introduction/Motivation Fuchsian Groups - Background Classification Program Results/References Outline 1 Introduction/Motivation Motivation 1 - extension of actions Motivation 2

  16. AUTOTUNE E+ BUILDING ENERGY MODELS Joshua New, Jibonananda Sanyal, Mahabir Bhandari, and Som Shrestha

    E-Print Network [OSTI]

    Wang, Xiaorui "Ray"

    through federal, state, local, and utility tax incentives, rebates, and loan programs. Nearly all energy

  17. Geothermal Literature Review At General Us Region (Sanyal, Et Al., 2004) |

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QAsource History View New PagesSustainable UrbanKentucky:Bore Technologies Inc JumpFacilityInformation2008)Open

  18. W.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 1 A classification of electronic signal-processing

    E-Print Network [OSTI]

    Serdijn, Wouter A.

    W.A. SERDIJN: "A CLASSIFICATION OF ELECTRONIC SIGNAL-PROCESSING FUNCTIONS" 1 A classification classification of electronic signal-processing functions is proposed. Electronic signals can either be 1 sources, wave- shaping circuits, digital logic functions, digital memories, power supplies, and converters

  19. Lagrangian Methods Of Cosmic Web Classification

    E-Print Network [OSTI]

    Fisher, J D; Johnson, M S T

    2015-01-01

    The cosmic web defines the large scale distribution of matter we see in the Universe today. Classifying the cosmic web into voids, sheets, filaments and nodes allows one to explore structure formation and the role environmental factors have on halo and galaxy properties. While existing studies of cosmic web classification concentrate on grid based methods, this work explores a Lagrangian approach where the V-web algorithm proposed by Hoffman et al. (2012) is implemented with techniques borrowed from smoothed particle hydrodynamics. The Lagrangian approach allows one to classify individual objects (e.g. particles or halos) based on properties of their nearest neighbours in an adaptive manner. It can be applied directly to a halo sample which dramatically reduces computational cost and potentially allows an application of this classification scheme to observed galaxy samples. Finally, the Lagrangian nature admits a straight forward inclusion of the Hubble flow negating the necessity of a visually defined thresh...

  20. CLASSIFICATION OF GRAPH C -ALGEBRAS AND LEAVITT

    E-Print Network [OSTI]

    Tomforde, Mark

    with the position of the unit. They accomplished this classification by describing moves on matrices that preserve that if A and B are irreducible square {0, 1} matrices, with coker(I-A) = coker(I- A) and det(I -A) = det(I -B), then XA is flow equivalent to XB. Since K0(OA) = coker(I - At ) = coker(I - A) and det(I - At ) = det

  1. Complexity Classification of Local Hamiltonian Problems

    E-Print Network [OSTI]

    Cubitt, Toby; Montanaro, Ashley

    2015-06-02

    constraint satisfaction problems. Index Terms—Hamiltonian complexity; QMA-completeness. I. INTRODUCTION Constraint satisfaction problems (CSPs) are ubiquitous in computer science and have been intensively studied since the early days of complexity theory. A... Complexity classification of local Hamiltonian problems Toby Cubitt Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK. tsc25@cam.ac.uk Ashley Montanaro Department of Computer Science, University...

  2. Cross-ontological analytics for alignment of different classification schemes

    DOE Patents [OSTI]

    Posse, Christian (Seattle, WA); Sanfilippo, Antonio P (Richland, WA); Gopalan, Banu (Cleveland, OH); Riensche, Roderick M (Richland, WA); Baddeley, Robert L (Richland, WA)

    2010-09-28

    Quantification of the similarity between nodes in multiple electronic classification schemes is provided by automatically identifying relationships and similarities between nodes within and across the electronic classification schemes. Quantifying the similarity between a first node in a first electronic classification scheme and a second node in a second electronic classification scheme involves finding a third node in the first electronic classification scheme, wherein a first product value of an inter-scheme similarity value between the second and third nodes and an intra-scheme similarity value between the first and third nodes is a maximum. A fourth node in the second electronic classification scheme can be found, wherein a second product value of an inter-scheme similarity value between the first and fourth nodes and an intra-scheme similarity value between the second and fourth nodes is a maximum. The maximum between the first and second product values represents a measure of similarity between the first and second nodes.

  3. Combining Supervised and Unsupervised Learning for GIS Classification

    E-Print Network [OSTI]

    Torres-Moreno, Juan-Manuel; Alexandre, Frdéric

    2009-01-01

    This paper presents a new hybrid learning algorithm for unsupervised classification tasks. We combined Fuzzy c-means learning algorithm and a supervised version of Minimerror to develop a hybrid incremental strategy allowing unsupervised classifications. We applied this new approach to a real-world database in order to know if the information contained in unlabeled features of a Geographic Information System (GIS), allows to well classify it. Finally, we compared our results to a classical supervised classification obtained by a multilayer perceptron.

  4. University Policy No.: AC1110 Classification: Academic and Students

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: AC1110 Classification: Academic and Students EDUCATIONAL SERVICE services and includes: · Development of educational materials in any form, including digital · Management

  5. University Policy No.: AC1145 Classification: Academic and Students

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: AC1145 Classification: Academic and Students Approving Authority, interdisciplinary programs, divisions, and the library) will undergo a review every five to seven years

  6. University Policy No.: IM7400 Classification: Information Management

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: IM7400 Classification: Information Management POLICY ON THE DISTRIBUTIONPherson Library · Petch · Sedgewick · Student Union · Theatre · University Centre · Visual Arts 1.2 Off

  7. Alternating local search based VNS for linear classification

    E-Print Network [OSTI]

    2007-06-29

    We consider the linear classification method consisting of separating two sets of points in d-space ..... code called. CPLEX 9 by way of the CPLEXINT library [4].

  8. University Policy No.: AC1150 Classification: Academic and Students

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: AC1150 Classification: Academic and Students TEACHING, portfolios, references, library resources, laboratories and equipment) related to the subject matter

  9. Minimal dynamics and the classification of C*-algebras

    E-Print Network [OSTI]

    2009-09-26

    Oct 6, 2009 ... noncommutative partitions of unity. It generalizes the usual .... Toms AS (2008) On the classification problem for nuclear C?-algebras. Ann Math.

  10. North American Industry Classification System (NAICS) Search Tool

    Broader source: Energy.gov [DOE]

    The North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and...

  11. Classification of multifluid CP world models

    E-Print Network [OSTI]

    Jens Thomas; Hartmut Schulz

    2000-12-20

    Various classification schemes exist for homogeneous and isotropic (CP) world models, which include pressureless matter (so-called dust) and Einstein's cosmological constant Lambda. We here classify the solutions of more general world models consisting of up to four non-interacting fluids, each with pressure P, energy density epsilon and an equation of state P = (gamma - 1) epsilon with 0 0) tends to yield the smoothest fits of the Supernova Ia data from Perlmutter et al. (1999). Adopting the SN Ia constraints, exotic negative energy density components can be fittingly included only if the universe consists of four or more fluids.

  12. Classification of Fermi Gamma-RAY Bursts

    E-Print Network [OSTI]

    Horvath, I; Hakkila, J; Bagoly, Z; Preece, R D

    2015-01-01

    The Fermi GBM Catalog has been recently published. Previous classification analyses of the BATSE, RHESSI, BeppoSAX, and Swift databases found three types of gamma-ray bursts. Now we analyzed the GBM catalog to classify the GRBs. PCA and Multiclustering analysis revealed three groups. Validation of these groups, in terms of the observed variables, shows that one of the groups coincides with the short GRBs. The other two groups split the long class into a bright and dim part, as defined by the peak flux. Additional analysis is needed to determine whether this splitting is only a mathematical byproduct of the analysis or has some real physical meaning.

  13. Classification Training Institute Catalog | Department of Energy

    Broader source: Energy.gov (indexed) [DOE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustmentsShirleyEnergy A plug-in electric vehicle (PEV) charging stationConstructionPolicyClassification

  14. Using Unlabelled Data To Update Classification Rules With Applications In Food Authenticity Studies

    E-Print Network [OSTI]

    Washington at Seattle, University of

    library . . . . . . . . . . . 3 2 Average correct classification rates for the five meat groupsUsing Unlabelled Data To Update Classification Rules With Applications In Food Authenticity Studies programme. #12;Abstract A classification method is developed to classify samples when both labelled

  15. Classification of integrable super-systems using the SsTools environment ?

    E-Print Network [OSTI]

    Wolf, Thomas

    Program Library, Queen's University of Belfast, N. Ireland; see also [1] _______ ? Subject classification Classification of integrable super-systems using the SsTools environment. ____________________________________________________________________________ Abstract A classification problem is proposed for supersymmetric evolutionary PDE that s* *at- isfy

  16. header for SPIE use Evolving forest fire burn severity classification algorithms

    E-Print Network [OSTI]

    Fernandez, Thomas

    header for SPIE use Evolving forest fire burn severity classification algorithms for multi, to the classification of forest fire burn severity using Landsat 7 ETM+ multispectral imagery. The details. Keywords: Multispectral imagery, Genetic programming, Supervised classification, Forest fire, Wildfire. 1

  17. Colour Invariant Head Pose Classification in Low Resolution Video

    E-Print Network [OSTI]

    Oxford, University of

    Colour Invariant Head Pose Classification in Low Resolution Video Ben Benfold and Ian Reid,ian}@robots.ox.ac.uk Abstract This paper presents an algorithm for the classification of head pose in low res- olution video, a pose estimation from a low resolution head image can be used to determine whether or not a close

  18. SEMI-AUTOMATIC WEB SERVICE GENERATION AND CLASSIFICATION

    E-Print Network [OSTI]

    SEMI-AUTOMATIC WEB SERVICE GENERATION AND CLASSIFICATION Automated assistance to the web service of semantic web techniques with web service technologies has enabled the emergence of so-called semantic web and classification of web services. Key words: semantic web services; web service generation; web service

  19. Discovering Discriminative Cell Attributes for HEp-2 Specimen Image Classification

    E-Print Network [OSTI]

    Sanderson, Conrad

    Discovering Discriminative Cell Attributes for HEp-2 Specimen Image Classification Arnold Wiliem1 in developing Computer Aided Diagnostic (CAD) systems for improving the reliability and consistency of pathology- ther step by focussing on the specimen image classification problem itself. Our system is able

  20. Classification of Signature-only Signature Models Zhengjun Cao

    E-Print Network [OSTI]

    International Association for Cryptologic Research (IACR)

    Classification of Signature-only Signature Models Zhengjun Cao Department of Mathematics, Shanghai classification. Keywords signing party, verifying party, lucidity of a message's content, method of producing Pk, consequence of updating Sk. 1 Introduction There are about sixty digital signature models introduced

  1. Information Analysis of a Spatial Database for Ecological Land classification

    E-Print Network [OSTI]

    Dozier, Jeff

    Information Analysis of a Spatial Database for Ecological Land classification Frank W. Davis:An ecologicalland classification was developed for a complex region in southern California using geographic. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless

  2. Automated Text Classification in the DMOZ Lachlan Henderson

    E-Print Network [OSTI]

    Sanner, Scott

    Automated Text Classification in the DMOZ Hierarchy Lachlan Henderson November 6, 2009 Abstract The growth in the availability of on-line digital text documents has prompted considerable interest in Information Retrieval and Text Classification. Automation of the management of this wealth of textual data

  3. Texture Classification and Verification Using Bispectral Estimates at All

    E-Print Network [OSTI]

    Sidorov, Nikita

    Texture Classification and Verification Using Bispectral Estimates at All the Frequencies and Statistics Group School of Mathematics, The University of Manchester #12;1 Texture Classification 3220 Email: jingsong.yuan@manchester.ac.uk Abstract Digitized texture images can often be considered

  4. Multi-Evidence, Multi-Criteria, Lazy Associative Document Classification

    E-Print Network [OSTI]

    Zaki, Mohammed Javeed

    Multi-Evidence, Multi-Criteria, Lazy Associative Document Classification Adriano Velosoa , Wagner to be applied at classification time. Our method is able to perform evidence enhancement by link forwarding approach using documents from the ACM Digital Library and from a Brazilian Web directory. Our approach

  5. SHADOW IDENTIFICATION AND CLASSIFICATION USING INVARIANT COLOR MODELS

    E-Print Network [OSTI]

    Cavallaro, Andrea

    SHADOW IDENTIFICATION AND CLASSIFICATION USING INVARIANT COLOR MODELS Elena Salvador, Andrea in digital images. The proce- dure is divided into two levels: first, shadow candidate regions are extracted of the classification stage. Experimental results show that the method succeeds in detecting and classifying shadows

  6. MUSIC GENRE CLASSIFICATION WITH TAXONOMY School of Computer Science

    E-Print Network [OSTI]

    Li, Tao

    MUSIC GENRE CLASSIFICATION WITH TAXONOMY Tao Li School of Computer Science Florida International Rochester, NY, 14627 ABSTRACT Automatic music genre classification is a fundamental compo- nent of music with the emergence of digital music on the Internet. Although consider- able research has been conducted in automatic

  7. Database Classification by Hybrid Method combining Supervised and Unsupervised Learnings

    E-Print Network [OSTI]

    Avignon et des Pays de Vaucluse, Université de

    contained in unlabeled signals of a Geographic Information System (GIS), allow to well classify it. Finally : Minimerror, hybrid method, classification, un- supervised learning, Geographic Information System. I classifications. We applied this new approach to a real-world database in order to know if the information

  8. Towards Automatic Classification of Discourse Elements in Essays Jill Burstein

    E-Print Network [OSTI]

    Marcu, Daniel

    Towards Automatic Classification of Discourse Elements in Essays Jill Burstein ETS Technologies MS classification to identify thesis statements. This method yields results that are much closer to human improve their writing skills, writing evaluation systems need to provide feedback that is specific to each

  9. Vibration-based Terrain Classification Using Support Vector Machines

    E-Print Network [OSTI]

    Zell, Andreas

    Vibration-based Terrain Classification Using Support Vector Machines Christian Weiss, Holger Fr a method for terrain classification based on vibration induced in the vehicle's body. An accelerometer mounted on the vehicle measures the vibration perpendicular to the ground surface. We experimentally

  10. ON FEATURE BASED AUTOMATIC CLASSIFICATION OF SINGLE AND MULTITONE SIGNALS

    E-Print Network [OSTI]

    Arabshahi, Payman

    ON FEATURE BASED AUTOMATIC CLASSIFICATION OF SINGLE AND MULTITONE SIGNALS Arindam K. Das, Payman of interest has not been previ- ously observed; it is not part of a library of known signals; and no automated demonstrating the feasibility of the above features for au- tomatic classification purposes of single

  11. DISCRIMINATION AND CLASSIFICATION OF UXO USING MAGNETOMETRY: INVERSION AND ERROR

    E-Print Network [OSTI]

    Sambridge, Malcolm

    DISCRIMINATION AND CLASSIFICATION OF UXO USING MAGNETOMETRY: INVERSION AND ERROR ANALYSIS USING for the different solutions didn't even overlap. Introduction A discrimination and classification strategy ambiguity and possible remanent magnetization the recovered dipole moment is compared to a library

  12. CLASSIFICATION OF EXPRESSION PATTERNS USING ARTIFICIAL NEURAL NETWORKS

    E-Print Network [OSTI]

    Ringnér, Markus

    understanding of how and why classification of a partic- ular problem gives good results. We hope this chapter a classification procedure shown to give good results and use the publicly available data set of small round blue on how to reduce high-dimensional array data to make the search for good ANNs more efficient. This is fol

  13. Examining the Evolution and Distribution of Patent Classifications

    E-Print Network [OSTI]

    Börner, Katy

    Examining the Evolution and Distribution of Patent Classifications Daniel O. Kutz School of Library and Information Science Indiana University 1320 E. 10th St., LI 011 Bloomington, IN 47405 dokutz the classification of more than 2.5 million patents in an attempt to improve understanding of how an assignee

  14. Environmental and Pollution Spatial Data Classification with Support Vector Machines

    E-Print Network [OSTI]

    Gilardi, Nicolas

    Environmental and Pollution Spatial Data Classification with Support Vector Machines and pollution spatial data analysis and modeling. The main attention is paid to classification of spatially be chosen by minimizing testing error. Real data on sediments pollution in the Geneva lake are used. 1

  15. Improving the Fisher Kernel for Large-Scale Image Classification

    E-Print Network [OSTI]

    Kim, Tae-Kyun

    classification the FK was shown to extend the popular bag-of-visual-words (BOV) by going beyond count statistics. However, in practice, this enriched representation has not yet shown its superiority over the BOV classification to date has been to describe images with bag-of-visual-words (BOV) histograms and to classify them

  16. Channel-aware Distributed Classification in Wireless Sensor Networks

    E-Print Network [OSTI]

    Valenti, Matthew C.

    University, Morgantown, WV, USA 2011 SPIE Defense, Security, and Sensing Signal Processing, Sensor Fusion, and Problem Statement 2 System Model of Our Distributed Classification WSN 3 Fusion Rule Derivation 4 Distributed Classification WSN 3 Fusion Rule Derivation 4 Numerical Analysis 5 Conclusions M. Fanaei et al

  17. Multivariate classification of infrared spectra of cell and tissue samples

    DOE Patents [OSTI]

    Haaland, David M. (Albuquerque, NM); Jones, Howland D. T. (Albuquerque, NM); Thomas, Edward V. (Albuquerque, NM)

    1997-01-01

    Multivariate classification techniques are applied to spectra from cell and tissue samples irradiated with infrared radiation to determine if the samples are normal or abnormal (cancerous). Mid and near infrared radiation can be used for in vivo and in vitro classifications using at least different wavelengths.

  18. A Thesaurus-Based Semantic Classification of English Collocations

    E-Print Network [OSTI]

    A Thesaurus-Based Semantic Classification of English Collocations Chung-chi Huang, Chiung-hui Tseng.jschang}@gmail.com Abstract We propose a new method for organizing the numerous collocates into semantic thesaurus categories. The approach introduces a thesaurus-based semantic classification model automatically learning semantic

  19. Detection and Classification of Ash Dieback on Large-Scale

    E-Print Network [OSTI]

    Detection and Classification of Ash Dieback on Large-Scale Color Aerial Photographs Ralph J of Agriculture 1966 #12;Croxton, Ralph J. 1966. Detection and classification of ash dieback on large- scale. Forest Serv. Res. Paper PSW-35) Aerial color photographs were taken at two scales over ash stands in New

  20. AutoODC: Automated Generation of Orthogonal Defect Classifications

    E-Print Network [OSTI]

    Ng, Vincent

    data are reported by users or developers during system development, operation and maintenance valuable in-process feedback to system development and maintenance. Conducting ODC classification classification and analysis of defect data bridge the gap between causal analysis and statistical quality control

  1. Treatment-Based Traffic Classification for Residential Wireless Networks

    E-Print Network [OSTI]

    Kinicki, Robert E.

    provide no QoS support (e.g., the 5th generation Apple Airport Extreme IEEE 802.11n wireless router [101 Treatment-Based Traffic Classification for Residential Wireless Networks Feng Li, Mark Claypool concurrently over bottlenecked wireless access points (APs). This paper presents Classification and Treatment

  2. Program Transformation Mechanics A Classification of Mechanisms for Program Transformation

    E-Print Network [OSTI]

    Utrecht, Universiteit

    Program Transformation Mechanics A Classification of Mechanisms for Program Transformation with a Survey of Existing Transformation Systems Jonne van Wijngaarden Eelco Visser UU-CS-2003-048 Institute Transformation Mechanics A Classification of Mechanisms for Program Transformation with a Survey of Existing

  3. Automatic Computation of the Complete Root Classification for a Parametric

    E-Print Network [OSTI]

    Jeffrey, David

    Automatic Computation of the Complete Root Classification for a Parametric Polynomial Songxin Liang, Canada Abstract An improved algorithm, together with its implementation, is presented for the automatic) for references. Our present goal is to compute automat- ically the Complete Root Classification (CRC

  4. Business Plans Classification with Locally Pruned Lazy Learning Models

    E-Print Network [OSTI]

    Verleysen, Michel

    1 Business Plans Classification with Locally Pruned Lazy Learning Models Antti Sorjamaa1 , Amaury linéaire par morceaux connue sous le nom de Locally Pruned Lazy Learning Model. Mots clefs : Lazy Learning, Classification, Leave-one-Out, Elagage. Abstract : A business plan is a document presenting in a concise form

  5. Ancient Ceramics: Computer aided Classification Dorrit Porter1

    E-Print Network [OSTI]

    Hamburg,.Universität

    Ancient Ceramics: Computer aided Classification Dorrit Porter1 , Peter Werner2 und Sven Utcke1 1 Objekte 1 #12;Ancient Ceramics: Computer aided Classification Dorrit Porter1 , Peter Werner2 , and Sven; rotationally symmetric objects 1 Introduction Ceramics usually have a short period of life, while at the same

  6. KINSHIP CLASSIFICATION BY MODELING FACIAL FEATURE HEREDITY Ruogu Fang1

    E-Print Network [OSTI]

    Chen, Tsuhan

    Company ABSTRACT We propose a new, challenging, problem in kinship classification: recognizing the family are interested in the problem of kinship family classification: Given a set of families, each with a set that a query person belongs to from a set of families. We propose a novel framework for recognizing kinship

  7. Information-Theoretic Measures for Objective Evaluation of Classifications

    E-Print Network [OSTI]

    Hu, Bao-Gang; Yuan, XiaoTong

    2011-01-01

    This work presents a systematic study of objective evaluations of abstaining classifications using Information-Theoretic Measures (ITMs). First, we define objective measures for which they do not depend on any free parameter. This definition provides technical simplicity for examining "objectivity" or "subjectivity" directly to classification evaluations. Second, we propose twenty four normalized ITMs, derived from either mutual information, divergence, or cross-entropy, for investigation. Contrary to conventional performance measures that apply empirical formulas based on users' intuitions or preferences, the ITMs are theoretically more sound for realizing objective evaluations of classifications. We apply them to distinguish "error types" and "reject types" in binary classifications without the need for input data of cost terms. Third, to better understand and select the ITMs, we suggest three desirable features for classification assessment measures, which appear more crucial and appealing from the viewpoi...

  8. DOE Publishes Petition of CSA Group for Classification as a Nationally...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    for Classification as a Nationally Recognized Certification Program for Small Electric Motors DOE Publishes Petition of CSA Group for Classification as a Nationally Recognized...

  9. Tea classification based on artificial olfaction using bionic olfactory neural network

    E-Print Network [OSTI]

    Yang, X L; Fu, J; Lou, Z G; Wang, L Y; Li, G; Freeman, Walter J III

    2006-01-01

    J.W. : Electronic Nose Based Tea Quality Standardization.Tea Classification Based on Artificial Olfaction Usingof elec- tronic nose-brain for tea classification using the

  10. A classification of multiple antenna channels Joseph J. Boutros, Fatma KharratKammoun, and Hugues Randriambololona

    E-Print Network [OSTI]

    Randriam, Hugues

    antenna digital transmissions [1] made us focus the application of our Hermitian forms classificationA classification of multiple antenna channels Joseph J. Boutros, Fatma Kharrat­Kammoun, and Hugues,fkharrat,randriam}@enst.fr Abstract--- We propose a new classification of multiple antenna channels. The classification is performed

  11. A classification of multiple antenna channels Joseph J. Boutros, Fatma Kharrat-Kammoun, and Hugues Randriambololona

    E-Print Network [OSTI]

    Randriam, Hugues

    antenna digital transmissions [1] made us focus the application of our Hermitian forms classificationA classification of multiple antenna channels Joseph J. Boutros, Fatma Kharrat-Kammoun, and Hugues,fkharrat,randriam}@enst.fr Abstract-- We propose a new classification of multiple antenna channels. The classification is performed

  12. Journal of Classification 27 (2010) DOI: 10.1007/s00357-010--

    E-Print Network [OSTI]

    Wand, Matt

    2010-01-01

    on digitized images and financial credit approval based on applicant attributes. Classification has an enormousJournal of Classification 27 (2010) DOI: 10.1007/s00357-010- - Parsimonious Classification Via a classification algorithm based on generalized linear mixed model (GLMM) technology. The algorithm incorporates

  13. Intelligent Fusion of Structural and Citation-Based Evidence for Text Classification

    E-Print Network [OSTI]

    Fernandez, Thomas

    . Our empirical experiments using documents from the ACM digital library and the ACM classification classification effectiveness. Experiments were performed on the ACM Digital Library using the ACM classificationIntelligent Fusion of Structural and Citation-Based Evidence for Text Classification Baoping Zhang

  14. Automatic Parallelization of Classification Systems based on Support Vector Machines: Comparison and Application to JET Database

    E-Print Network [OSTI]

    Automatic Parallelization of Classification Systems based on Support Vector Machines: Comparison and Application to JET Database

  15. A Characteristics-Based Approach to Radioactive Waste Classification in Advanced Nuclear Fuel Cycles

    E-Print Network [OSTI]

    Djokic, Denia

    2013-01-01

    International   Atomic   Energy   Agency,   General   Safety   Guide   No.   GSG-­?1,   “Classification  of  Radioactive  Waste”,  

  16. Experiments in Web Page Classification for Semantic Web Asad Satti, Nick Cercone, Vlado Keselj

    E-Print Network [OSTI]

    Keselj, Vlado

    Experiments in Web Page Classification for Semantic Web Asad Satti, Nick Cercone, Vlado Keselj address the problem of web page classification within the framework of automatic annotation for Semantic-known classification algorithms are evaluated on the task of web-page classification using the text of web pages. When

  17. GIS Framework for Large River Geomorphic Classification to Aid...

    Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

    GIS Framework for Large River Geomorphic Classification to Aid in the Evaluation of Flow-Ecology Relationships CR Vernon EV Arntzen MC Richmond RA McManamay 1 TP Hanrahan CL...

  18. Classification of Certain Compact Riemannian Manifolds with Harmonic Curvature a...

    E-Print Network [OSTI]

    Derdzinski, Andrzej

    Classification of Certain Compact Riemannian Manifolds with Harmonic Curvature a... Derdzinski and University Library provides access to digitized documents strictly for noncommercial educational, research) requires prior written permission from the Goettingen State- and University Library. Each copy of any part

  19. SPECTRAL-SPATIAL CLASSIFICATION OF HYPERSPECTRAL IMAGES USING HIERARCHICAL OPTIMIZATION

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    classified. In this work, we propose to use a Hierarchical Step-Wise Optimization (HSWO) method for including spatial depen- dencies into a classification procedure. HSWO is a segmen- tation approach, which

  20. Classification of distressed couples: implications for clinical intervention 

    E-Print Network [OSTI]

    Cozzi, Jebber Jake

    1998-01-01

    This study relates marital therapy outcome to an empirically-derived classification system for distressed marriages, based on measures of individual and marital functioning. Results of a hierarchical agglomerative cluster analysis identified four...

  1. Classification of London's public transport users using smart card data

    E-Print Network [OSTI]

    Ortega-Tong, Meisy A. (Meisy Andrea)

    2013-01-01

    Understanding transit users in terms of their travel patterns can support the planning and design of better services. User classification can improve market research through more targeted access to groups of interest. It ...

  2. Multi-Class Classification with Maximum Margin Multiple Kernel

    E-Print Network [OSTI]

    Mohri, Mehryar

    (named OBSCURE and UFO-MKL, respectively) are used to optimize primal versions of equivalent problems), the OBSCURE and UFO-MKL algorithms are compared against MCMKL #12;Multi-Class Classification with Maximum

  3. Title/Topic: Research Misconduct Functional Classification: Research

    E-Print Network [OSTI]

    Harms, Kyle E.

    1 Title/Topic: Research Misconduct Number: 69 Functional Classification: Research Monitoring Unit: Initially Issued: March 1, 2006 Last Revised: Last Reviewed: RESEARCH MISCONDUCT I. Introduction* *Federal law requires Federal agencies sponsoring research to require an awardee institution to have

  4. A framework for a coarse aggregate classification system 

    E-Print Network [OSTI]

    Peapully, Srikrishna

    1994-01-01

    Coarse aggregates are the major constituents of concrete or asphalt mixtures and are widely used in various construction purposes. A classification system for these aggregates would provide a systematic means of aggregate identification which could...

  5. Quantum Support Vector Machine for Big Data Classification

    E-Print Network [OSTI]

    Mohseni, Masoud

    Supervised machine learning is the classification of new data based on already classified training examples. In this work, we show that the support vector machine, an optimized binary classifier, can be implemented on a ...

  6. An Analytical Method For Multi-class Molecular Cancer Classification

    E-Print Network [OSTI]

    Poggio, Tomaso

    Institute / Massachusetts Institute of Technology Center for Genome Research, Cambridge, MA 02139 Vector Machines. We apply this methodology to the diagnosis of multiple common adult malignancies using using standard clinical and histopathologic approaches. Molecular approaches to cancer classification

  7. Invariant classification of orthogonally separable Hamiltonian systems in Euclidean space

    E-Print Network [OSTI]

    Joshua T. Horwood; Raymond G. McLenaghan; Roman G. Smirnov

    2006-05-07

    The problem of the invariant classification of the orthogonal coordinate webs defined in Euclidean space is solved within the framework of Felix Klein's Erlangen Program. The results are applied to the problem of integrability of the Calogero-Moser model.

  8. Particle Size Classification of Glass Particles Using Aerodynamic Jet Vectoring

    E-Print Network [OSTI]

    Smith, Barton L.

    Particle Size Classification of Glass Particles Using Aerodynamic Jet Vectoring Zachary E. Humes blowing and suction control flows­flows that are a fraction of the jet flow rate­to sharply change

  9. Land capability classification of minesoils in East Texas 

    E-Print Network [OSTI]

    Barth, Amy Kristen

    2002-01-01

    for the post-mine land. A land capability classification specific to minesoils will facilitate the design of appropriate land uses or alternative uses for reclaimed mine areas based on observed limitations. The proposed system is similar to the Land...

  10. Machine Learning and Rule-based Approaches to Assertion Classification

    E-Print Network [OSTI]

    Uzuner, Ozlem

    2009-01-01

    Objectives The authors study two approaches to assertion classification. One of these approaches, Extended NegEx (ENegEx), extends the rule-based NegEx algorithm to cover alter-association assertions; the other, Statistical ...

  11. Atomic Classification of 6D SCFTs

    E-Print Network [OSTI]

    Jonathan J. Heckman; David R. Morrison; Tom Rudelius; Cumrun Vafa

    2015-07-11

    We use F-theory to classify possibly all six-dimensional superconformal field theories (SCFTs). This involves a two step process: We first classify all possible tensor branches allowed in F-theory (which correspond to allowed collections of contractible spheres) and then classify all possible configurations of seven-branes wrapped over them. We describe the first step in terms of "atoms" joined into "radicals" and "molecules," using an analogy from chemistry. The second step has an interpretation via quiver-type gauge theories constrained by anomaly cancellation. A very surprising outcome of our analysis is that all of these tensor branches have the structure of a linear chain of intersecting spheres with a small amount of possible decoration at the two ends. The resulting structure of these SCFTs takes the form of a generalized quiver consisting of ADE-type nodes joined by conformal matter. A collection of highly non-trivial examples involving E8 small instantons probing an ADE singularity is shown to have an F-theory realization. This yields a classification of homomorphisms from ADE subgroups of SU(2) into E8 in purely geometric terms, largely matching results obtained in the mathematics literature from an intricate group theory analysis.

  12. Atomic Classification of 6D SCFTs

    E-Print Network [OSTI]

    Jonathan J. Heckman; David R. Morrison; Tom Rudelius; Cumrun Vafa

    2015-05-04

    We use F-theory to classify possibly all six-dimensional superconformal field theories (SCFTs). This involves a two step process: We first classify all possible tensor branches allowed in F-theory (which correspond to allowed collections of contractible spheres) and then classify all possible configurations of seven-branes wrapped over them. We describe the first step in terms of "atoms" joined into "radicals" and "molecules," using an analogy from chemistry. The second step has an interpretation via quiver-type gauge theories constrained by anomaly cancellation. A very surprising outcome of our analysis is that all of these tensor branches have the structure of a linear chain of intersecting spheres with a small amount of possible decoration at the two ends. The resulting structure of these SCFTs takes the form of a generalized quiver consisting of ADE-type nodes joined by conformal matter. A collection of highly non-trivial examples involving E8 small instantons probing an ADE singularity is shown to have an F-theory realization. This yields a classification of homomorphisms from ADE subgroups of SU(2) into E8 in purely geometric terms, largely matching results obtained in the mathematics literature from an intricate group theory analysis.

  13. Classification and waterfowl use of ponds in south Texas 

    E-Print Network [OSTI]

    McAdams, Matthew Stephen

    1987-01-01

    CLASSIFICATION AND WATERFOWL USE OF PONDS IN SOUTH TEXAS A Thesis . by MATTHEW STEPHEN McADAMS Submitted to the Graduate College of Texas A&M University in partial fulfillment of the recpxirements for the degree of MASTER OF SCIENCE August... 1987 Major Subject: Wildlife and Fisheries Sciences CLASSIFICATION AND WATERFOWL USE OF PONDS IN SOUTH TEXAS A Thesis by MATTHEW STEPHEN M ADAMS Approved as to style and content by: William H. Kiel, Jr. (Chair of Committee) Robert D. Baker...

  14. New Approaches to Object Classification in Synoptic Sky Surveys

    E-Print Network [OSTI]

    C. Donalek; A. Mahabal; S. G. Djorgovski; S. Marney; A. Drake; E. Glikman; M. J. Graham; R. Williams

    2008-10-27

    Digital synoptic sky surveys pose several new object classification challenges. In surveys where real-time detection and classification of transient events is a science driver, there is a need for an effective elimination of instrument-related artifacts which can masquerade as transient sources in the detection pipeline, e.g., unremoved large cosmic rays, saturation trails, reflections, crosstalk artifacts, etc. We have implemented such an Artifact Filter, using a supervised neural network, for the real-time processing pipeline in the Palomar-Quest (PQ) survey. After the training phase, for each object it takes as input a set of measured morphological parameters and returns the probability of it being a real object. Despite the relatively low number of training cases for many kinds of artifacts, the overall artifact classification rate is around 90%, with no genuine transients misclassified during our real-time scans. Another question is how to assign an optimal star-galaxy classification in a multi-pass survey, where seeing and other conditions change between different epochs, potentially producing inconsistent classifications for the same object. We have implemented a star/galaxy multipass classifier that makes use of external and a priori knowledge to find the optimal classification from the individually derived ones. Both these techniques can be applied to other, similar surveys and data sets.

  15. Morphological Classification of Galaxies by Shapelet Decomposition in the Sloan Digital Sky Survey II: Multiwavelength Classification

    E-Print Network [OSTI]

    B. C. Kelly; T. A. McKay

    2004-12-15

    We describe the application of the `shapelet' linear decomposition of galaxy images to multi-wavelength morphological classification using the $u,g,r,i,$ and $z$-band images of 1519 galaxies from the Sloan Digital Sky Survey. We utilize elliptical shapelets to remove to first-order the effect of inclination on morphology. After decomposing the galaxies we perform a principal component analysis on the shapelet coefficients to reduce the dimensionality of the spectral morphological parameter space. We give a description of each of the first ten principal component's contribution to a galaxy's spectral morphology. We find that galaxies of different broad Hubble type separate cleanly in the principal component space. We apply a mixture of Gaussians model to the 2-dimensional space spanned by the first two principal components and use the results as a basis for classification. Using the mixture model, we separate galaxies into three classes and give a description of each class's physical and morphological properties. We find that the two dominant mixture model classes correspond to early and late type galaxies, respectively. The third class has, on average, a blue, extended core surrounded by a faint red halo, and typically exhibits some asymmetry. We compare our method to a simple cut on $u-r$ color and find the shapelet method to be superior in separating galaxies. Furthermore, we find evidence that the $u-r=2.22$ decision boundary may not be optimal for separation between early and late type galaxies, and suggest that the optimal cut may be $u-r \\sim 2.4$.

  16. Classification of fossil fuels according to structural-chemical characteristics

    SciTech Connect (OSTI)

    A.M. Gyul'maliev; G.S. Golovin; S.G. Gagarin [Institute for Fossil Fuels, Moscow (Russian Federation)

    2007-10-15

    On the basis of a set of linear equations that relate the amount of major elements n{sub E} (E = C, H, O, N, S) in the organic matter of fossil fuels to structural characteristics, such as the number of cycles R, the number of atoms n{sub E}, the number of mutual chemical bonds, the degree of unsaturation of the structure {delta}, and the extent of its reduction B, a structural-chemical classification of fossil coals that is closely related to the parameters of the industrial-genetic classification (GOST 25543-88) is proposed. Structural-chemical classification diagrams are constructed for power-generating coals of Russia; coking coals; and coals designed for nonfuel purposes including the manufacture of adsorbents, synthetic liquid fuel, ion exchangers, thermal graphite, and carbon-graphite materials.

  17. A Brief Summary of Dictionary Learning Based Approach for Classification

    E-Print Network [OSTI]

    Shu, Kong

    2012-01-01

    This note presents some representative methods which are based on dictionary learning (DL) for classification. We do not review the sophisticated methods or frameworks that involve DL for classification, such as online DL and spatial pyramid matching (SPM), but rather, we concentrate on the direct DL-based classification methods. Here, the "so-called direct DL-based method" is the approach directly deals with DL framework by adding some meaningful penalty terms. By listing some representative methods, we can roughly divide them into two categories, i.e. (1) directly making the dictionary discriminative and (2) forcing the sparse coefficients discriminative to push the discrimination power of the dictionary. From this taxonomy, we can expect some extensions of them as future researches.

  18. ALGORITHMIC CLASSIFICATION OF DRAINAGE NETWORKS ON MARS AND ITS RELATION TO MARTIAN GEOLOGICAL UNITS. T. F. Stepinski1

    E-Print Network [OSTI]

    Vilalta, Ricardo

    ALGORITHMIC CLASSIFICATION OF DRAINAGE NETWORKS ON MARS AND ITS RELATION TO MARTIAN GEOLOGICAL locations covering 16 major geological units. The classification is quantitative and objective with an existing division into geological units. A morphological interpretation for this emergent classification

  19. Feature Shape and Elevation Based Road Classification and Extraction on High Spatial

    E-Print Network [OSTI]

    Carbonara, Joaquin

    Feature Shape and Elevation Based Road Classification and Extraction on High Spatial Resolution #12; 2 Abstract: Classification and extraction of geospatial features from high spatial resolution. However, the conventional method of human interpretation and digitizing cannot fulfill the requirements

  20. Sporocarp Ontogeny in Panus (Basidiomycotina): Evolution and Classification David S. Hibbett; Shigeyuki Murakami; Akihiko Tsuneda

    E-Print Network [OSTI]

    Hibbett, David S.

    Sporocarp Ontogeny in Panus (Basidiomycotina): Evolution and Classification David S. Hibbett on the screen or printed page of such transmission. The JSTOR Archive is a trusted digital repository providing. SPOROCARPONTOGENY IN PANUS(BASIDIOMYCOTINA): EVOLUTION AND CLASSIFICATION' DAVIDS. HIBBETT,~ MURAKAMI

  1. Efficient Packet Classification with Digest Caches Francis Chang, Wu-chang Feng, Wu-chi Feng

    E-Print Network [OSTI]

    3-1 Chapter 3 Efficient Packet Classification with Digest Caches Francis Chang, Wu-chang Feng, Wu of digest caches for efficient packet classification. The goal of digest caches is similar to Bloom. Digest caches, however, allow tradi

  2. Predicting Library of Congress Classifications From Library of Congress Subject Headings

    E-Print Network [OSTI]

    Frank, Eibe

    Predicting Library of Congress Classifications From Library of Congress Subject Headings Eibe Frank Gordon W. Paynter Department of Computer Science The INFOMINE Project, Science Library University This paper addresses the problem of automatically assigning a Library of Congress Classification (LCC

  3. Applications (Classification, Advisory, and License) and Documentation Part 748page 1 Export Administration Regulations

    E-Print Network [OSTI]

    Bernstein, Daniel

    Applications (Classification, Advisory, and License) and Documentation Part 748­page 1 Export in writing or electronically, for classifications, advisory opinions or licenses subject to the Export Consistent with section 12(c) of the Export Administration Act, as amended, information obtained

  4. AUDIO GENRE CLASSIFICATION USING PERCUSSIVE PATTERN CLUSTERING COMBINED WITH TIMBRAL FEATURES

    E-Print Network [OSTI]

    Tzanetakis, George

    characterize different genres and styles of music directly from audio signals. In previous research, timbralAUDIO GENRE CLASSIFICATION USING PERCUSSIVE PATTERN CLUSTERING COMBINED WITH TIMBRAL FEATURES Emiru features. Index Terms-- Audio genre classification, Percussive sound, Dynamic programming, Pattern

  5. Molecular cancer classification using an meta-sample-based regularized robust coding method

    E-Print Network [OSTI]

    Wang, Shu-Lin; Sun, Liuchao; Fang, Jianwen

    2014-12-03

    , its efficiency needs to be improved when analyzing large-scale GEP data. Results In this paper we present the meta-sample-based regularized robust coding classification (MRRCC), a novel effective cancer classification technique that combines the idea...

  6. University Policy No.: FM5510 Classification: Financial Management

    E-Print Network [OSTI]

    Victoria, University of

    Services operation are to provide consistent high quality, efficient food service to the University and Operations by March 1 for the following fiscal year. 1.4 The General Manager of Housing, FoodUniversity Policy No.: FM5510 Classification: Financial Management Approving Authority: Vice

  7. Fingerprinting the Datacenter: Automated Classification of Performance Crises

    E-Print Network [OSTI]

    Woodard, Dawn B.

    Fingerprinting the Datacenter: Automated Classification of Performance Crises Peter Bod´ik1, Berkeley 2 Microsoft Research 3 Cornell University 4 Microsoft Abstract Contemporary datacenters comprise on a new and efficient representation of the datacenter's state called a fingerprint, constructed by statis

  8. The Legal Classification of Identity-Based Christoph Sorge

    E-Print Network [OSTI]

    International Association for Cryptologic Research (IACR)

    The Legal Classification of Identity-Based Signatures Christoph Sorge University of Paderborn 33098 of future identity-based signature schemes. 1 Introduction Digital signatures are among the most widely used verification of a digital signature guarantees integrity and authenticity of the corresponding message. Non

  9. University Policy No.: IM7305 Classification: Information Management

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: IM7305 Classification: Information Management COPYRIGHT AND THE USE OF VIDEO of Victoria Libraries, McPherson Library Loan Policy (Policy 2550, section 2.1.2); "Fair Dealing" means a fair as it has in the University of Victoria Libraries, McPherson Library Loan Policy (Policy 2550, section 2

  10. University Policy No.: IM7300 Classification: Information Management

    E-Print Network [OSTI]

    Victoria, University of

    University Policy No.: IM7300 Classification: Information Management POLICY ON COPYRIGHT. The Act is available for you to read at the reference desks of the McPherson Library, the Diana Priestly Law Library, and the Curriculum Laboratory. Computer programs are usually licensed rather than

  11. Automatic Classification of Digestive Organs in Wireless Capsule Endoscopy Videos

    E-Print Network [OSTI]

    Lee, Jeongkyu

    Automatic Classification of Digestive Organs in Wireless Capsule Endoscopy Videos Jeongkyu Lee1. University of North Texas Denton, TX 76203 {jhoh,xyuan}@cse.unt.edu 3 Division of Digestive Diseases UTSW the assessment time, it is critical to develop a technique to automatically discriminate digestive organs

  12. Archives Research Assistant Classification: Student Assistant 3 (LSA 3)

    E-Print Network [OSTI]

    Archives Research Assistant Classification: Student Assistant 3 (LSA 3) Salary: $9.50 - $9.69 Hours: 15-20 per week The University of Oregon Libraries invites application for a part-time, temporary Archives Research Assistant in Knight Library's Special Collections and University Archives. The student

  13. Wind speed PDF classification using Dirichlet mixtures Rudy CALIF1

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Wind speed PDF classification using Dirichlet mixtures Rudy CALIF1 , Richard EMILION2 , Ted'Orléans), UMR CNRS 6628 Université d'Orléans, France. Abstract: Wind energy production is very sensitive to instantaneous wind speed fluctuations. Thus rapid variation of wind speed due to changes in the local

  14. Industrial Steam Power Cycles Final End-Use Classification 

    E-Print Network [OSTI]

    Waterland, A. F.

    1983-01-01

    Final end uses of steam include two major classifications: those uses that condense the steam against heat transfer surfaces to provide heat to an item of process or service equipment; and those that require a mass flow of steam for stripping...

  15. Test-Cost Sensitive Classification on Data with Missing Values

    E-Print Network [OSTI]

    Yang, Qiang

    values on several data sets. Index Terms--Cost-sensitive learning, decision trees, naive Bayes. æ 1Test-Cost Sensitive Classification on Data with Missing Values Qiang Yang, Senior Member, IEEE, Charles Ling, Xiaoyong Chai, and Rong Pan Abstract--In the area of cost-sensitive learning, inductive

  16. A Classification of SQL Injection Attacks and Countermeasures

    E-Print Network [OSTI]

    Orso, Alessandro "Alex"

    A Classification of SQL Injection Attacks and Countermeasures William G.J. Halfond, Jeremy Viegas|jeremyv|orso}@cc.gatech.edu ABSTRACT SQL injection attacks pose a serious security threat to Web appli- cations: they allow attackers methods to address the SQL injection problem, current approaches either fail to address the full scope

  17. Letter to the Editor Ecosystem services: Multiple classification systems

    E-Print Network [OSTI]

    Vermont, University of

    population's information about the world, especially when it comes to ecosystem services, is extremelyLetter to the Editor Ecosystem services: Multiple classification systems are needed In a recent to enrich our thinking about ecosystem services rather than a problem to be defined away. Let us start

  18. What's the Code? Automatic Classification of Source Code Archives

    E-Print Network [OSTI]

    Giles, C. Lee

    show that source code can be accurately and automatically classified into topical categories and canWhat's the Code? Automatic Classification of Source Code Archives Secil Ugurel1, Robert Krovetz2, C.psu.edu 2NECResearchInstitute 4 IndependenceWay, Princeton,NJ 08540 {krovetz, dpennock, compuman} @research

  19. Relational Classification Through ThreeState Epidemic Aram Galstyan

    E-Print Network [OSTI]

    Information Sciences Institute University of Southern California Marina del Rey, CA, U.S.A. cohen of scientists is a challeng- ing task that requires fusing information from var- ious heterogeneous sourcesRelational Classification Through Three­State Epidemic Dynamics Aram Galstyan Information Sciences

  20. What's the code? Automatic Classification of Source Code Archives

    E-Print Network [OSTI]

    Giles, C. Lee

    What's the code? Automatic Classification of Source Code Archives Secil Ugurel 1 , Robert Krovetz 2, zha} @cse.psu.edu 2 NEC Research Institute 4 Independence Way, Princeton, NJ 08540 {krovetz, dpennock, compuman} @research.nj.nec.com 3 School of Information Sciences and Technology The Pennsylvania State

  1. Harmonium Models for Semantic Video Representation and Classification

    E-Print Network [OSTI]

    keywords and color-histogram features, and perform classification using these latent topics under a unified. Video data contain multifari- ous data types including image frames, transcript text, speech, audio signal, each bearing correlated and com- plementary information essential to the analysis and re- trieval

  2. A Comparative Study on Content-Based Music Genre Classification

    E-Print Network [OSTI]

    Li, Tao

    and composers have been influenced by music in other genres. However, it has been observed that audio signals classification, DWCHs1 . DWCHs capture the local and global information of music signals simultaneously by computing histograms on their Daubechies wavelet coefficients. Effectiveness of this new feature

  3. THE CLASSIFICATION OF DEHN SURGERIES ON 2-BRIDGE KNOTS

    E-Print Network [OSTI]

    Brittenham, Mark

    THE CLASSIFICATION OF DEHN SURGERIES ON 2-BRIDGE whether a given surgery on a 2-bridge knot is * *reducible, toroidal, Seifert fibered, or hyperbolic are non-hyperbolic. Let Kp=q be a 2-bridge* * knot associated to the rational number p=q. When p 1

  4. THE CLASSIFICATION OF DEHN SURGERIES ON 2-BRIDGE KNOTS

    E-Print Network [OSTI]

    Brittenham, Mark

    THE CLASSIFICATION OF DEHN SURGERIES ON 2-BRIDGE KNOTS Mark Brittenham and Ying-Qing Wu Abstract. We will determine whether a given surgery on a 2-bridge knot is reducible, toroidal, Seifert bered-hyperbolic. Let Kp=q be a 2-bridge knot associated to the rational number p=q. When p 1 mod q, K is a torus knot

  5. Classification of Sweden's Forest and Alpine Vegetation Using Optical

    E-Print Network [OSTI]

    Classification of Sweden's Forest and Alpine Vegetation Using Optical Satellite and Inventory Data of Sweden's Forest and Alpine Vegetation Using Optical Satellite and Inventory Data. Abstract Creation of accurate vegetation maps from optical satellite data requires use of reference data to aid

  6. Support Vector Machine Classification of Microarray Gene Expression Data

    E-Print Network [OSTI]

    Noble, William Stafford

    using expression data. In addition, SVM performance is compared to four standard machine learningSupport Vector Machine Classification of Microarray Gene Expression Data UCSC-CRL-99-09 Michael P 95065 mpbrown,bgrundy,dave,haussler @cse.ucsc.edu ß Center for Molecular Biology of RNA Department

  7. Classification of perturbations for membranes with bending 10October 1996

    E-Print Network [OSTI]

    Wiese, Kay Jörg

    EISEVIER Classification of perturbations for membranes with bending 10October 1996 Physics a manifold with van- ishing tension but with bending rigidity. In this case r(x) is the amplitude structure. The goal is to find the eigen- operators of the renormalization-group flow. The paper

  8. Group classification of heat conductivity equations with a nonlinear source

    E-Print Network [OSTI]

    Zhdanov, Renat

    Group classification of heat conductivity equations with a nonlinear source R.Z. Zhdanov Institute. It is shown that there are three, seven, twenty eight and twelve inequivalent classes of partial differential to the class under study and admitting symmetry group of the dimension higher than four is locally equivalent

  9. HIGH PRECISION FREQUENCY ESTIMATION FOR HARPSICHORD TUNING CLASSIFICATION

    E-Print Network [OSTI]

    Dixon, Simon

    HIGH PRECISION FREQUENCY ESTIMATION FOR HARPSICHORD TUNING CLASSIFICATION Dan Tidhar, Matthias of conservative transcription, and show that existing high-precision pitch estimation techniques are sufficient that "sound good" together) is de- rived from the sharing of partial frequencies. As musical instruments

  10. OUTLIER ESTIMATION AND DETECTION APPLICATION TO SKIN LESION CLASSIFICATION

    E-Print Network [OSTI]

    OUTLIER ESTIMATION AND DETECTION APPLICATION TO SKIN LESION CLASSIFICATION S. Sigurdsson£ , J the project Signal and Image Processing for Telemedicine (SITE). Outliers are defined as an input pattern be rewritten as Ô´ Рܵ Ô¼´ Рܵ´½ ¬ µ·¬ (2) where ¬ ¼ ½ ´ ½µ . 3. NETWORK ARCHITECTURE AND INFERENCE

  11. Bayesian network models for hierarchical text classification from a thesaurus

    E-Print Network [OSTI]

    de Campos, Luis M.

    Bayesian network models for hierarchical text classification from a thesaurus Luis M. de Campos to be classified, automatically generates an ordered set of appropriate descriptors extracted from a thesaurus. The method creates a Bayesian network to model the thesaurus and uses probabilistic inference to select

  12. Geometrical classification of Killing tensors on bidimensional flat manifolds

    E-Print Network [OSTI]

    C. Chanu; L. Degiovanni; R. G. McLenaghan

    2006-08-31

    Valence two Killing tensors in the Euclidean and Minkowski planes are classified under the action of the group which preserves the type of the corresponding Killing web. The classification is based on an analysis of the system of determining partial differential equations for the group invariants and is entirely algebraic. The approach allows to classify both characteristic and non characteristic Killing tensors.

  13. AutoODC: Automated Generation of Orthogonal Defect Classifications

    E-Print Network [OSTI]

    Ng, Vincent

    data are reported by users or developers during system development, operation and maintenance and analysis, provides valuable in­process feedback to system development and maintenance. Conducting ODC classification and analysis of defect data bridge the gap between causal analysis and statistical quality control

  14. FRAME BASED KERNEL METHODS FOR AUTOMATIC CLASSIFICATION IN HYPERSPECTRAL DATA

    E-Print Network [OSTI]

    Hirn, Matthew

    FRAME BASED KERNEL METHODS FOR AUTOMATIC CLASSIFICATION IN HYPERSPECTRAL DATA John J. Benedetto, instead of (orthonormal) bases. Our frames are data-dependent and are based on endmember demixing schemes propose a new kernel and frame based dimension reduc- ing algorithm by exploiting the synergy between

  15. A Rule-Based Classification Algorithm for Uncertain Data

    E-Print Network [OSTI]

    Tu, Yicheng

    A Rule-Based Classification Algorithm for Uncertain Data Biao Qin, Yuni Xia Department of Computer uncertain data interval and probability distribution function. Based on the new measures, the optimal and decision errors, unreliable data transmission and data staling. For example, in location based services

  16. The Software Invention Cube: a Classification Scheme for Software Inventions

    E-Print Network [OSTI]

    Klint, Paul

    The Software Invention Cube: a Classification Scheme for Software Inventions Jan A. Bergstra.science.uva.nl/~janb and Paul Klint Centrum voor Wiskunde en Informatica (CWI), Software Engineering Department and Informatics system aims at protecting inventions. The requirement that a software invention should make `a technical

  17. Hierarchical classification with reject option for live fish recognition

    E-Print Network [OSTI]

    Fisher, Bob

    Hierarchical classification with reject option for live fish recognition Phoenix X. Huang@inf.ed.ac.uk Robert B. Fisher University of Edinburgh rbf@inf.ed.ac.uk Abstract A live fish recognition system. We present a novel Balance-Enforced Optimized Tree with Reject op- tion (BEOTR) for live fish

  18. Interactive Multiscale Classification of High-Resolution Remote Sensing Images

    E-Print Network [OSTI]

    Gosselin, Philippe-Henri

    1 Interactive Multiscale Classification of High-Resolution Remote Sensing Images Jefersson Alex dos~ao Abstract The use of remote sensing images (RSIs) as a source of information in agribusiness applications in space occupation. However, the identification and recognition of crop regions in remote sensing images

  19. ReportTechnical Classification of Semantic Concepts to Support

    E-Print Network [OSTI]

    . For the classification of studio vs. non-studio, football vs. ice hockey, computer graphics vs. nat- ural scenes as the high spread of these representations make them interesting for comparison across countries or years. 1- bolic connotation from the annotation scheme. The items are studio/non-studio, football/ice hockey

  20. Classification of prostate magnetic resonance spectra using support vector machine

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    to Biomedical Signal Processing and Control December 12, 2011 hal-00650862,version1-12Dec2011 Author manuscript, published in "Biomedical Signal Processing and Control (2011) 1-8" DOI : 10.1016/j.bspc.2011.09.003 #12;pre-processed- tomatic classification with and without quantification of metabolite signals. The dataset is composed

  1. Tissue Classification of Noisy MR Brain Images Using Constrained GMM

    E-Print Network [OSTI]

    Goldberger, Jacob

    Tissue Classification of Noisy MR Brain Images Using Constrained GMM Amit Ruf1 , Hayit Greenspan1. The presented algorithm is used to segment 3D, T1­weighted, simulated and real MR images of the brain into three , and Jacob Goldberger2 1 Department of Biomedical Engineering, Tel-Aviv University, ISRAEL, 2 School

  2. A Conceptual Framework for ERP Benefit Classification: A Literature Review

    E-Print Network [OSTI]

    Wieringa, Roel

    A Conceptual Framework for ERP Benefit Classification: A Literature Review Silja Eckartz*, Maya resource planning (ERP) benefits, carried out according to the guidelines by Webster et al. (2002 in the identification, realization and assessment of ERP benefits. Special focus is put on benefits management in cross

  3. Itemset Based Sequence Classification Cheng Zhou1,2

    E-Print Network [OSTI]

    Antwerpen, Universiteit

    of Antwerp, Belgium 2 National University of Defense Technology, China Cheng.Zhou@student.ua.ac.be Abstract. Sequence classification is an important task in data mining. We address the problem of sequence has been an important problem in statistical machine learning and data mining. The sequence

  4. SIC (MUltiple SIgnal Classification) CSP (Cross-power Spectrum Phase)

    E-Print Network [OSTI]

    Takiguchi, Tetsuya

    2ch CSP ( ) 1 MU- SIC (MUltiple SIgnal Classification) CSP (Cross- power Spectrum Phase) [1, 2, 3, 4] [5, 6] [7, 8, 9, 10] [7] CSP CSP [8] [9] CSP [10] Estimation of talker's head orientation based (Kobe univ.) [11] 2ch CSP CSP CSP CSP 2 CSP GCC-PHAT (Generalized Cross- Correlation PHAse Transform

  5. THE CLASSIFICATION OF EXCEPTIONAL CDQL WEBS ON COMPACT COMPLEX SURFACES

    E-Print Network [OSTI]

    Pereira, Jorge Vitório

    THE CLASSIFICATION OF EXCEPTIONAL CDQL WEBS ON COMPACT COMPLEX SURFACES J. V. PEREIRA AND L. PIRIO Abstract. Codimension one webs are configurations of finitely many codi- mension one foliations in general equation among the first integrals of the foliations defining the web reminiscent of Abel's addition the

  6. Classification of Commodity Price Forecast With Random Forests and Bayesian

    E-Print Network [OSTI]

    Freitas, Nando de

    on the sentiment of price39 forecasts and reports for commodities such as gold, natural gas or most commonly oil or natural gas can impact everything from the21 critical business decisions made within nationsClassification of Commodity Price Forecast Sentiment With Random Forests and Bayesian Optimization

  7. Classification of Energy Consumption in Buildings with Outlier Detection

    E-Print Network [OSTI]

    Yao, Xin

    1 Classification of Energy Consumption in Buildings with Outlier Detection Xiaoli Li, Chris P is to enable a building management system to be used for forecasting and detection of abnormal energy use. First, an outlier detection method is proposed to identify abnormally high or low energy use in building

  8. ENHANCED CLOUD REGIME CLASSIFICATION FOR EVALUATION OF MODEL FAST PHYSICS

    E-Print Network [OSTI]

    ENHANCED CLOUD REGIME CLASSIFICATION FOR EVALUATION OF MODEL FAST PHYSICS Wuyin Lin1 , Yangang Liu1 of Energy under Contract No. DE-AC02-98CH10886 ABSTRACT Distinct cloud regimes exist locally and globally helps identify the meteorological conditions that are closely associated with specific cloud regimes

  9. Land Cover Classification with Multi-Sensor Fusion of Partly Missing Data

    E-Print Network [OSTI]

    Aksoy, Selim

    Land Cover Classification with Multi-Sensor Fusion of Partly Missing Data We describe how decision a system that uses decision tree-based tools for seamless acquisition of knowledge for classification during both training and classification to handle cases where one or more measurements do not exist

  10. 3DString: A Feature String Kernel for 3D Object Classification on Voxelized Data

    E-Print Network [OSTI]

    Kriegel, Hans-Peter

    3DString: A Feature String Kernel for 3D Object Classification on Voxelized Data Johannes AÃ?falg-Maximilians-University Munich, Germany {assfalg|kb|kriegel}@dbs.ifi.lmu.de ABSTRACT Classification of 3D objects remains which allows to combine it with an M-tree for handling of large volumes of data. Classification

  11. ReVision: Automated Classification, Analysis and Redesign of Chart Images

    E-Print Network [OSTI]

    O'Brien, James F.

    ReVision: Automated Classification, Analysis and Redesign of Chart Images Manolis Savva, Nicholas an image classification ac- curacy of 96% across ten chart categories. It also accurately extracts marks alternative chart designs and retarget content to different visual styles. ACM Classification: H5

  12. Mammography Classification by an Association Rule-based Osmar R. Zaiane

    E-Print Network [OSTI]

    Zaiane, Osmar R.

    Mammography Classification by an Association Rule-based Classifier Osmar R. Za¨iane Department: acoman@cs.ualberta.ca ABSTRACT This paper proposes a new classification method based on association rule in a classification model. The experimen- tal results show that the method performs well reaching over 80% in accuracy

  13. Comparison of Kernel Estimators, Perceptrons, and RadialBasis Functions for OCR and Speech Classification

    E-Print Network [OSTI]

    Alpaydýn, Ethem

    ­basis functions for the problems of classification of handwritten digits and speech phonemes. By taking two Classification Ethem Alpaydin, Fikret G¨urgen Department of Computer Engineering, Boâ??gazi¸ci University, TR­80815 networks. Four criteria are taken for comparison: Correct classification of the test set, network size

  14. Monitoring urban land cover change: An expert system approach to land cover classification

    E-Print Network [OSTI]

    Ramsey, Michael

    such as land use data, spatial texture, and digital elevation models (DEMs) to obtain greater classificationMonitoring urban land cover change: An expert system approach to land cover classification with Landsat Thematic Mapper (TM) data to derive a land cover classification for the semiarid Phoenix

  15. A Fingerprint Classification Technique Using Directional Images Meltem Ballan and F. Ayhan Sakarya

    E-Print Network [OSTI]

    Evans, Brian L.

    A Fingerprint Classification Technique Using Directional Images Meltem Ballan and F. Ayhan Sakarya directional histograms. The technique enhances the digitized image using adaptive clipping and image matching classification methods, such as Galton and Henry Classification [2], rely on point patterns in fingerprints which

  16. Acyclic Subgraph based Descriptor Spaces for Chemical Compound Retrieval and Classification

    E-Print Network [OSTI]

    Minnesota, University of

    Acyclic Subgraph based Descriptor Spaces for Chemical Compound Retrieval and Classification Nikil Wale and George Karypis Department of Computer Science/Digital Technology Center , University of the new descriptors in the context of SVM-based classification and ranked-retrieval on 28 classification

  17. Spatial Contextual Noise Removal for Post Classification Smoothing of Remotely Sensed Images

    E-Print Network [OSTI]

    Zhang, Kang

    context. The strategy is demonstrated through the classification of a benchmark digital aerial photographSpatial Contextual Noise Removal for Post Classification Smoothing of Remotely Sensed Images Yu information in remote sensing imagery and the limited classification ability based on spectral analysis

  18. On the integration of regional classification systems for the National Map

    E-Print Network [OSTI]

    Bittner, Thomas

    : Ontology, Classification and delineation systems, National Map 1 Introduction Categorial (digital or non-digital (Omernik, 2004). For the integration of digital maps from different sources, classification systemsOn the integration of regional classification systems for the National Map Thomas Bittner

  19. YouTubeEvent: on Large-Scale Video Event Classification Bingbing Ni

    E-Print Network [OSTI]

    Cortes, Corinna

    YouTubeEvent: on Large-Scale Video Event Classification Bingbing Ni Advanced Digital Sciences the problem of general event classification from uncontrolled YouTube videos. It is a challenging task due from YouTube to represent these categories. To improve classification per- formance, video content

  20. MUSIC GENRES CLASSIFICATION USING TEXT CATEGORIZATION METHOD Kai Chen, Sheng Gao, Yongwei Zhu, Qibin Sun

    E-Print Network [OSTI]

    Sun, Qibin

    the large digital music database has arisen as a crucial problem. Automatic music type classification couldMUSIC GENRES CLASSIFICATION USING TEXT CATEGORIZATION METHOD Kai Chen, Sheng Gao, Yongwei Zhu.a-star.edu.sg ABSTRACT Automatic music genre classification is one of the most challenging problems in music information

  1. Unsupervised Classification Strategies How much forest cover exists along the Illinois River?

    E-Print Network [OSTI]

    Frank, Thomas D.

    ;#12;#12;Digital Image Classification The objective of digital image classification is to partition feature spaceUnsupervised Classification Strategies How much forest cover exists along the Illinois River into decision regions, then to assign pixels in an image to the most likely feature category. #12;Digital Image

  2. A Universal Source Thesaurus as a Classification Generator The construction of a Universal Source Thesaurus (UST)

    E-Print Network [OSTI]

    Soergel, Dagobert

    Thesaurus (UST) is suggested. Unlike a universal classification, UST's main purpose would not be to serveA Universal Source Thesaurus as a Classification Generator The construction of a Universal Source in the construction of special schemes; (b) serve as a concordance between a great many classification schemes

  3. Automatic Model Classification of Measured Internet Traffic Yi Zeng and Thomas M. Chen

    E-Print Network [OSTI]

    Chen, Thomas M.

    issues for future work. II. MODEL-LIBRARY TRAFFIC CLASSIFICATION Many traffic models have been developed Model 2 module ... Model library Fig. 1. General model classification system In the general case with NAutomatic Model Classification of Measured Internet Traffic Yi Zeng and Thomas M. Chen Department

  4. U.S. Geological Survey Library Classification By R. Scott Sasscer

    E-Print Network [OSTI]

    Torgersen, Christian

    U.S. Geological Survey Library Classification System By R. Scott Sasscer U.S. Geological Survey classification system is a tool for classifying and retrieving geoscience library materials. The index promotes.S. Geological Survey Library classification system / by R. Scott Sasscer. p. cm. ­ (U.S. Geological Survey

  5. Effective Graph Classification Based on Topological and Label Attributes , Murat Semerci2

    E-Print Network [OSTI]

    Zaki, Mohammed Javeed

    online 12 June 2012 in Wiley Online Library (wileyonlinelibrary.com). Abstract: Graph classificationEffective Graph Classification Based on Topological and Label Attributes Geng Li1 , Murat Semerci2 propose an alternative approach to graph classification that is based on feature vectors constructed from

  6. What Those Call Numbers Mean: The Library of Congress Classification System

    E-Print Network [OSTI]

    Hutcheon, James M.

    What Those Call Numbers Mean: The Library of Congress Classification System The call number system that we use in this library, which is called the Library of Congress Classification System subject areas. If you know what letter indicates the classification for the subject you need, you can find

  7. The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using Semi-

    E-Print Network [OSTI]

    Cohen, William W.

    The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using: Semi-Supervised Political Blog Classification and Ranking Using Semi-Supervised Link Classification present a new, intuitive semi-supervised learning algo- rithm for classifying political blogs in a blog

  8. Cost-Sensitive Classification with Genetic Programming Jin Li, Xiaoli Li and Xin Yao

    E-Print Network [OSTI]

    Yao, Xin

    Cost-Sensitive Classification with Genetic Programming Jin Li, Xiaoli Li and Xin Yao The Centre.Yao}@cs.bham.ac.uk Abstract- Cost-sensitive classification is an attractive topic in data mining. Although genetic programming exploited to ad- dress cost-sensitive classification in the literature, where the costs of misclassification

  9. Word Classification: An Experimental Approach with Nave Bayes ding@cs.umb.edu

    E-Print Network [OSTI]

    Ding, Wei

    Word Classification: An Experimental Approach with Naïve Bayes Wei Ding ding@cs.umb.edu University 77058 USA Abstract Word classification is of significant interest in the domain of natural language presents an experimental method using Naïve Bayes for word classification. The method is based on combing

  10. IBLStreams: A System for Instance-Based Classification and Regression on Data Streams

    E-Print Network [OSTI]

    Hüllermeier, Eyke

    IBLStreams: A System for Instance-Based Classification and Regression on Data Streams Ammar Shaker to classification and regression problems. In comparison to model-based methods for learning on data streams. Keywords: Data streams, classification, regression, instance-based learn- ing, concept drift. 1 #12

  11. Cancer classification by gradient LDA technique using microarray gene expression data

    E-Print Network [OSTI]

    Cancer classification by gradient LDA technique using microarray gene expression data Alok Sharma a) Dimensionality reduction Cancer classification Feature selection Feature extraction a b s t r a c t Cancer techniques are applied for cancer classification, they face the small sample size (SSS) problem of gene

  12. Target-dependent Churn Classification in Microblogs Hadi Amiri and Hal Daume III

    E-Print Network [OSTI]

    Daume III, Hal

    Target-dependent Churn Classification in Microblogs Hadi Amiri and Hal Daume III Computational regression) do not perform as well on churn classification as on other text classification problems. We investigate demographic, content, and context churn indicators in microblogs and examine factors that make

  13. The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using Semi-Supervised Link Classification

    E-Print Network [OSTI]

    Murphy, Robert F.

    The MultiRank Bootstrap Algorithm: Semi-Supervised Political Blog Classification and Ranking Using-supervised learning algorithm for classifying political blogs in a blog network and ranking them within predicted.6% using only 2 seed blogs. Introduction We propose a novel algorithm that both classifies political blogs

  14. KHAMIS, LAMPERT: CO-CLASSIFICATION WITH OUTPUT SPACE REGULARIZATION 1 CoConut: Co-Classification with Output

    E-Print Network [OSTI]

    Daume III, Hal

    KHAMIS, LAMPERT: CO-CLASSIFICATION WITH OUTPUT SPACE REGULARIZATION 1 CoConut: Co, otherwise independent, data samples. The method we present, named CoConut, is based on the idea of adding on the class labels. CoConut can build on existing classi- fiers without making any assumptions on how

  15. Spinors and the Weyl Tensor Classification in Six Dimensions

    E-Print Network [OSTI]

    Carlos Batista; Bruno Carneiro da Cunha

    2013-06-05

    A spinorial approach to 6-dimensional differential geometry is constructed and used to analyze tensor fields of low rank, with special attention to the Weyl tensor. We perform a study similar to the 4-dimensional case, making full use of the SO(6) symmetry to uncover results not easily seen in the tensorial approach. Using spinors, we propose a classification of the Weyl tensor by reinterpreting it as a map from 3-vectors to 3-vectors. This classification is shown to be intimately related to the integrability of maximally isotropic subspaces, establishing a natural framework to generalize the Goldberg-Sachs theorem. We work in complexified spaces, showing that the results for any signature can be obtained by taking the desired real slice.

  16. Towards a Real-time Transient Classification Engine

    SciTech Connect (OSTI)

    Nugent, Peter E; Bloom, Josh; Starr, Dan; Butler, Nat; Nugent, Peter; Rischard, M.; Eads, D.; Poznanski, Dovi

    2008-02-22

    Temporal sampling does more than add another axis to the vector of observables. Instead, under the recognition that how objects change (and move) in time speaks directly to the physics underlying astronomical phenomena, next-generation wide-field synoptic surveys are poised to revolutionize our understanding of just about anything that goes bump in the night (which is just about everything at some level). Still, even the most ambitious surveys will require targeted spectroscopic follow-up to fill in the physical details of newly discovered transients. We are now building a new system intended to ingest and classify transient phenomena in near real-time from high-throughput imaging data streams. Described herein, the Transient Classification Project at Berkeley will be making use of classification techniques operating on"features" extracted from time series and contextual (static) information. We also highlight the need for a community adoption of a standard representation of astronomical time series data (i.e.,"VOTimeseries").

  17. A Multi-Dimensional Classification Model for Scientific Workflow Characteristics

    SciTech Connect (OSTI)

    Ramakrishnan, Lavanya; Plale, Beth

    2010-04-05

    Workflows have been used to model repeatable tasks or operations in manufacturing, business process, and software. In recent years, workflows are increasingly used for orchestration of science discovery tasks that use distributed resources and web services environments through resource models such as grid and cloud computing. Workflows have disparate re uirements and constraints that affects how they might be managed in distributed environments. In this paper, we present a multi-dimensional classification model illustrated by workflow examples obtained through a survey of scientists from different domains including bioinformatics and biomedical, weather and ocean modeling, astronomy detailing their data and computational requirements. The survey results and classification model contribute to the high level understandingof scientific workflows.

  18. One goal of examing satellite images is to derive maps of earth Digital Image Classification Has Two Components

    E-Print Network [OSTI]

    Frank, Thomas D.

    One goal of examing satellite images is to derive maps of earth #12;Digital Image Classification Image Classification The objective of digital image classification is to partition feature space Has Two Components The training stage supervised unsupervised The classification stage parallelepiped

  19. Abstract--Classification of power quality (PQ) related voltage and current waveform disturbances is a key task for power

    E-Print Network [OSTI]

    Mamishev, Alexander

    and the classification performance of proposed system is evaluated. Fourth, a digital signal processor (DSP) based1 Abstract--Classification of power quality (PQ) related voltage and current waveform disturbances paper) presents a case study of PQ event classification with the proposed method. The classification

  20. AUTOMATED DEFECT CLASSIFICATION USING AN ARTIFICIAL NEURAL NETWORK

    SciTech Connect (OSTI)

    Chady, T.; Caryk, M. [Szczecin University of Technology, Department of Electrical Engineering (Poland); Piekarczyk, B. [Technic-Control, Szczecin (Poland)

    2009-03-03

    The automated defect classification algorithm based on artificial neural network with multilayer backpropagation structure was utilized. The selected features of flaws were used as input data. In order to train the neural network it is necessary to prepare learning data which is representative database of defects. Database preparation requires the following steps: image acquisition and pre-processing, image enhancement, defect detection and feature extraction. The real digital radiographs of welded parts of a ship were used for this purpose.

  1. THE CLASSIFICATION OF DEHN SURGERIES ON 2BRIDGE KNOTS

    E-Print Network [OSTI]

    Brittenham, Mark

    THE CLASSIFICATION OF DEHN SURGERIES ON 2­BRIDGE KNOTS Mark Brittenham and Ying­Qing Wu Abstract. We will determine whether a given surgery on a 2­bridge knot is reducible, toroidal, Seifert fibered surgeries are non­hyperbolic. Let K p=q be a 2­bridge knot associated to the rational number p=q. When p j

  2. Reconstruction-classification method for quantitative photoacoustic tomography

    E-Print Network [OSTI]

    Malone, Emma; Cox, Ben T; Arridge, Simon R

    2015-01-01

    We propose a combined reconstruction-classification method for simultaneously recovering absorption and scattering in turbid media from images of absorbed optical energy. This method exploits knowledge that optical parameters are determined by a limited number of classes to iteratively improve their estimate. Numerical experiments show that the proposed approach allows for accurate recovery of absorption and scattering in 2 and 3 dimensions, and delivers superior image quality with respect to traditional reconstruction-only approaches.

  3. CLASSIFICATION OF THE MGR WASTE TREATMENT BUILDING VENTILATION SYSTEM

    SciTech Connect (OSTI)

    S.E. Salzman

    1999-08-31

    The purpose of this analysis is to document the Quality Assurance (QA) classification of the Monitored Geologic Repository (MGR) waste treatment building ventilation system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P, ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998).

  4. CLASSIFICATION OF FIRST-ORDER FLEXIBLE REGULAR BICYCLE POLYGONS

    E-Print Network [OSTI]

    Connelly, Robert

    CLASSIFICATION OF FIRST-ORDER FLEXIBLE REGULAR BICYCLE POLYGONS ROBERT CONNELLY AND BAL´AZS CSIK´OS Abstract. A bicycle (n, k)-gon is an equilateral n-gon whose k-diagonals are equal. S. Tabachnikov proved that a regular n-gon is first-order flexible as a bicycle (n, k)-gon if and only if there is an integer 2 r n

  5. Various forms of indexing HDMR for modelling multivariate classification problems

    SciTech Connect (OSTI)

    Aksu, Ça?r?; Tunga, M. Alper

    2014-12-10

    The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled. In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.

  6. UAS Detection Classification and Neutralization: Market Survey 2015

    SciTech Connect (OSTI)

    Birch, Gabriel Carisle; Griffin, John Clark; Erdman, Matthew Kelly

    2015-07-01

    The purpose of this document is to briefly frame the challenges of detecting low, slow, and small (LSS) unmanned aerial systems (UAS). The conclusion drawn from internal discussions and external reports is the following; detection of LSS UAS is a challenging problem that can- not be achieved with a single detection modality for all potential targets. Classification of LSS UAS, especially classification in the presence of background clutter (e.g., urban environment) or other non-threating targets (e.g., birds), is under-explored. Though information of avail- able technologies is sparse, many of the existing options for UAS detection appear to be in their infancy (when compared to more established ground-based air defense systems for larger and/or faster threats). Companies currently providing or developing technologies to combat the UAS safety and security problem are certainly worth investigating, however, no company has provided the statistical evidence necessary to support robust detection, identification, and/or neutralization of LSS UAS targets. The results of a market survey are included that highlights potential commercial entities that could contribute some technology that assists in the detection, classification, and neutral- ization of a LSS UAS. This survey found no clear and obvious commercial solution, though recommendations are given for further investigation of several potential systems.

  7. LibShortText: A Library for Short-text Classification and Analysis LibShortText: A Library for Short-text Classification and

    E-Print Network [OSTI]

    Lin, Chih-Jen

    LibShortText: A Library for Short-text Classification and Analysis LibShortText: A Library for Short-text Classification and Analysis Hsiang-Fu Yu rofuyu@cs.utexas.edu Department of Computer Science University, Taipei 106, Taiwan Editor: Editor name Abstract LibShortText is an open source library for short

  8. February 8, 2015 16:49 World Scientific Review Volume -9in x 6in "time-series classification" page 1 Sparse Representation for Time-Series Classification

    E-Print Network [OSTI]

    Ray, Asok

    February 8, 2015 16:49 World Scientific Review Volume - 9in x 6in "time-series classification" page:49 World Scientific Review Volume - 9in x 6in "time-series classification" page 2 2 S. Bahrampour and N. M

  9. Improved Correlation of the Neuropathologic Classification According to Adapted World Health Organization Classification and Outcome After Radiotherapy in Patients With Atypical and Anaplastic Meningiomas

    SciTech Connect (OSTI)

    Combs, Stephanie E., E-mail: Stephanie.Combs@med.uni-heidelberg.de [Department of Radiation Oncology, University Hospital of Heidelberg, Heidelberg (Germany); Schulz-Ertner, Daniela [Radiologisches Institut, Markuskrankenhaus Frankfurt, Frankfurt am Main (Germany); Debus, Juergen [Department of Radiation Oncology, University Hospital of Heidelberg, Heidelberg (Germany); Deimling, Andreas von; Hartmann, Christian [Department of Neuropathology, Institute for Pathology, University Hospital of Heidelberg, Heidelberg (Germany); Clinical Cooperation Unit Neuropathology, German Cancer Research Center, Heidelberg (Germany)

    2011-12-01

    Purpose: To evaluate the correlation between the 1993 and 2000/2007 World Health Organization (WHO) classification with the outcome in patients with high-grade meningiomas. Patients and Methods: Between 1985 and 2004, 73 patients diagnosed with atypical or anaplastic meningiomas were treated with radiotherapy. Sections from the paraffin-embedded tumor material from 66 patients (90%) from 13 different pathology departments were re-evaluated according to the first revised WHO classification from 1993 and the revised classifications from 2000/2007. In 4 cases, the initial diagnosis meningioma was not reproducible (5%). Therefore, 62 patients with meningiomas were analyzed. Results: All 62 tumors were reclassified according to the 1993 and 2000/2007 WHO classification systems. Using the 1993 system, 7 patients were diagnosed with WHO grade I meningioma (11%), 23 with WHO grade II (37%), and 32 with WHO grade III meningioma (52%). After scoring using the 2000/2007 system, we found 17 WHO grade I meningiomas (27%), 32 WHO grade II meningiomas (52%), and 13 WHO grade III meningiomas (21%). According to the 1993 classification, the difference in overall survival was not statistically significant among the histologic subgroups (p = .96). Using the 2000/2007 WHO classifications, the difference in overall survival became significant (p = .02). Of the 62 reclassified patients 29 developed tumor progression (47%). No difference in progression-free survival was observed among the histologic subgroups (p = .44). After grading according to the 2000/2007 WHO classifications, significant differences in progression-free survival were observed among the three histologic groups (p = .005). Conclusion: The new 2000/2007 WHO classification for meningiomas showed an improved correlation between the histologic grade and outcome. This classification therefore provides a useful basis to determine the postoperative indication for radiotherapy. According to our results, a comparison of the published data for future treatment decision-making remains difficult when the histologic diagnosis has not been based on the new improved classification system.

  10. Weyl Tensor Classification in Four-dimensional Manifolds of All Signatures

    E-Print Network [OSTI]

    Carlos Batista

    2013-02-07

    It is well known that the classification of the Weyl tensor in Lorentzian manifolds of dimension four, the so called Petrov classification, was a great tool to the development of general relativity. Using the bivector approach it is shown in this article a classification for the Weyl tensor in all four-dimensional manifolds, including all signatures and the complex case, in an unified and simple way. The important Petrov classification then emerges just as a particular case in this scheme. The boost weight classification is also extended here to all signatures as well to complex manifolds. For the Weyl tensor in four dimensions it is established that this last approach produces a classification equivalent to the one generated by the bivector method.

  11. Tip sheet: Expanded Library of Congress Call Number Classification system Call Number Subject Matter

    E-Print Network [OSTI]

    Kambhampati, Patanjali

    Tip sheet: Expanded Library of Congress Call Number Classification system Call Number Subject R: Medicine T: Technology U: Military Science Z: Bibliography. Library Science. Information

  12. Machine Learning Approaches for High-resolution Urban Land Cover Classification: A Comparative Study

    SciTech Connect (OSTI)

    Vatsavai, Raju [ORNL] [ORNL; Chandola, Varun [ORNL] [ORNL; Cheriyadat, Anil M [ORNL] [ORNL; Bright, Eddie A [ORNL] [ORNL; Bhaduri, Budhendra L [ORNL] [ORNL; Graesser, Jordan B [ORNL] [ORNL

    2011-01-01

    The proliferation of several machine learning approaches makes it difficult to identify a suitable classification technique for analyzing high-resolution remote sensing images. In this study, ten classification techniques were compared from five broad machine learning categories. Surprisingly, the performance of simple statistical classification schemes like maximum likelihood and Logistic regression over complex and recent techniques is very close. Given that these two classifiers require little input from the user, they should still be considered for most classification tasks. Multiple classifier systems is a good choice if the resources permit.

  13. Symmetry classification of quasi-linear PDE's containing arbitrary functions

    E-Print Network [OSTI]

    Giampaolo Cicogna

    2007-02-02

    We consider the problem of performing the preliminary "symmetry classification'' of a class of quasi-linear PDE's containing one or more arbitrary functions: we provide an easy condition involving these functions in order that nontrivial Lie point symmetries be admitted, and a "geometrical'' characterization of the relevant system of equations determining these symmetries. Two detailed examples will elucidate the idea and the procedure: the first one concerns a nonlinear Laplace-type equation, the second a generalization of an equation (the Grad-Schl\\"uter-Shafranov equation) which is used in magnetohydrodynamics.

  14. Complete Classification of 1+1 Gravity Solutions

    E-Print Network [OSTI]

    T. Kloesch; T. Strobl

    1997-11-25

    A classification of the maximally extended solutions for 1+1 gravity models (comprising e.g. generalized dilaton gravity as well as models with non-trivial torsion) is presented. No restrictions are placed on the topology of the arising solutions, and indeed it is found that for generic models solutions on non-compact surfaces of arbitrary genus with an arbitrary non-zero number of holes can be obtained. The moduli space of classical solutions (solutions of the field equations with fixed topology modulo gauge transformations) is parametrized explicitly.

  15. CLASSIFICATION OF THE MGR SITE ELECTRICAL POWER SYSTEM

    SciTech Connect (OSTI)

    J.A. Ziegler

    1999-08-31

    The purpose of this analysis is to document the Quality As.surance (QA) classification of the Monitored Geologic Repository (MGR) site fire protection system structures, systems and components (SSCs) performed by the MGR Safety Assurance Department. This analysis also provides the basis for revision of YMP/90-55Q, Q-List (YMP 1998). The Q-List identifies those MGR SSCs subject to the requirements of DOE/RW-0333P7 ''Quality Assurance Requirements and Description'' (QARD) (DOE 1998b).

  16. Quantum support vector machine for big data classification

    E-Print Network [OSTI]

    Patrick Rebentrost; Masoud Mohseni; Seth Lloyd

    2014-07-10

    Supervised machine learning is the classification of new data based on already classified training examples. In this work, we show that the support vector machine, an optimized binary classifier, can be implemented on a quantum computer, with complexity logarithmic in the size of the vectors and the number of training examples. In cases when classical sampling algorithms require polynomial time, an exponential speed-up is obtained. At the core of this quantum big data algorithm is a non-sparse matrix exponentiation technique for efficiently performing a matrix inversion of the training data inner-product (kernel) matrix.

  17. Classification of Energy Flow Observables in Narrow Jets

    E-Print Network [OSTI]

    Guy Gur-Ari; Michele Papucci; Gilad Perez

    2011-01-14

    We present a classification of energy flow variables for highly collimated jets. Observables are constructed by taking moments of the energy flow and forming scalars of a suitable Lorentz subgroup. The jet shapes are naturally arranged in an expansion in both angular and energy resolution, allowing us to derive the natural observables for describing an N-particle jet. We classify the leading variables that characterize jets with up to 4 particles. We rediscover the familiar jet mass, angularities, and planar flow, which dominate the lowest order substructure variables. We also discover several new observables and we briefly discuss their physical interpretation.

  18. Automatic Fault Characterization via Abnormality-Enhanced Classification

    SciTech Connect (OSTI)

    Bronevetsky, G; Laguna, I; de Supinski, B R

    2010-12-20

    Enterprise and high-performance computing systems are growing extremely large and complex, employing hundreds to hundreds of thousands of processors and software/hardware stacks built by many people across many organizations. As the growing scale of these machines increases the frequency of faults, system complexity makes these faults difficult to detect and to diagnose. Current system management techniques, which focus primarily on efficient data access and query mechanisms, require system administrators to examine the behavior of various system services manually. Growing system complexity is making this manual process unmanageable: administrators require more effective management tools that can detect faults and help to identify their root causes. System administrators need timely notification when a fault is manifested that includes the type of fault, the time period in which it occurred and the processor on which it originated. Statistical modeling approaches can accurately characterize system behavior. However, the complex effects of system faults make these tools difficult to apply effectively. This paper investigates the application of classification and clustering algorithms to fault detection and characterization. We show experimentally that naively applying these methods achieves poor accuracy. Further, we design novel techniques that combine classification algorithms with information on the abnormality of application behavior to improve detection and characterization accuracy. Our experiments demonstrate that these techniques can detect and characterize faults with 65% accuracy, compared to just 5% accuracy for naive approaches.

  19. Pattern classification and associative recall by neural networks

    SciTech Connect (OSTI)

    Chiueh, Tzi-Dar.

    1989-01-01

    The first part of this dissertation discusses a new classifier based on a multilayer feed-forward network architecture. The main idea is to map irregularly-distributed prototypes in a classification problem to codewords that are organized in some way. Then the pattern classification problem is transformed into a threshold decoding problem, which is easily solved using simple hard-limiter neurons. At first the author proposes the new model and introduce two families of good internal representation codes. Then some analyses and software simulation concerning the storage capacity of this new model are done. The results show that the new classifier is much better than the classifier based on the Hopfield model in terms of both the storage capacity and the ability to classify correlated prototypes. A general model for neural network associative memories with a feedback structure is proposed. Many existing neural network associative memories can be expressed as special cases of this general model. Among these models, there is a class of associative memories, called correlation associative memories, that are capable of storing a large number of memory patterns. If the function used in the evolution equation is monotonically nondecreasing, then a correlation associative memory can be proved to be asymptotically stable in both the synchronous and asynchronous updating modes. Of these correlation associative memories, one stands out because of its VLSI implementation feasibility and large storage capacity. This memory uses the exponentiation function in its evolution equation; hence it is called exponential correlation associative memory (ECAM).

  20. Investigating the effects of scale in MRF texture classification Scott Blunsden1, Louis Atallah2

    E-Print Network [OSTI]

    Atallah, Louis

    in Dubai/ University of Edinburgh, PO Box 502216, Dubai, UAE, latallah@inf.ed.ac.uk Keywords:Texture, Classification, Scale, MRF Abstract This work sheds the light on an important problem that faces real-world of real-world data classification is given with a summary and future directions. 1 Introduction The use

  1. A fast, large-scale learning method for protein sequence classification

    E-Print Network [OSTI]

    Pavlovic, Vladimir

    A fast, large-scale learning method for protein sequence classification Pavel Kuksa, Pai-Hsi Huang spatial sample kernels (SSSK). The approach offers state-of-the-art accuracy for sequence classification]: Applications; I.5.2. [Pattern Recognition]: De- corresponding author Permission to make digital or hard copies

  2. Automatic classification of the acrosome status of boar spermatozoa using digital image processing and LVQ

    E-Print Network [OSTI]

    Petkov, Nicolai

    Automatic classification of the acrosome status of boar spermatozoa using digital image processing-intact (class 1) or acrosome- damaged (class 2). Such classification is important for the estimation for semen quality control in an artificial insemination center. Keywords: acrosome assessment, digital image

  3. Mutual information-based SVM-RFE for diagnostic classification of digitized mammograms

    E-Print Network [OSTI]

    Kim, Saejoon

    Mutual information-based SVM-RFE for diagnostic classification of digitized mammograms Sejong Yoon diagnosis (CADx) systems for digitized mammograms solve the problem of classification between benign Received in revised form 15 June 2009 Available online 7 July 2009 Communicated by Y. Ma Keywords: Digital

  4. HARMONY: Efficiently Mining the Best Rules for Classification Jianyong Wang and George Karypis

    E-Print Network [OSTI]

    Minnesota, University of

    HARMONY: Efficiently Mining the Best Rules for Classification Jianyong Wang and George Karypis Department of Computer Science, Digital Technology Center, & Army HPC Research Center University of Minnesota. However, a fundamental limitation with many rule-based classifiers is that they find the classification

  5. EXPLORING THE EFFECT OF RHYTHMIC STYLE CLASSIFICATION ON AUTOMATIC TEMPO ESTIMATION

    E-Print Network [OSTI]

    Plumbley, Mark

    EXPLORING THE EFFECT OF RHYTHMIC STYLE CLASSIFICATION ON AUTOMATIC TEMPO ESTIMATION Matthew E. P. Davies and Mark D. Plumbley Centre for Digital Music, Queen Mary, University of London Mile End Rd, E1 4 audio signals. We demonstrate how the use of a simple 1-NN classification method, able to determine

  6. PERCEPTUAL FEATURE SELECTION FOR SEMANTIC IMAGE CLASSIFICATION Dejan Depalov, Thrasyvoulos N. Pappas

    E-Print Network [OSTI]

    Pappas, Thrasyvoulos N.

    PERCEPTUAL FEATURE SELECTION FOR SEMANTIC IMAGE CLASSIFICATION Dejan Depalov, Thrasyvoulos N collections of digital images. The goal is to organize the contents semantically, according to mean- ingful categories. In recent papers we introduced a new approach for semantic image classification that relies

  7. Statistical Classification for Discrimination of Unexploded Ordnance: A Tutorial L. S. Beran*

    E-Print Network [OSTI]

    Oldenburg, Douglas W.

    Statistical Classification for Discrimination of Unexploded Ordnance: A Tutorial L. S. Beran* , D to approximately $16 billion. These methods require the acquisition of digital geophysical data and subsequent to discriminate between UXO and clutter. We describe classification algorithms which have been applied

  8. Image Set Classification Using Holistic Multiple Order Statistics Features and Localized Multi-Kernel Metric Learning

    E-Print Network [OSTI]

    Moulin, Pierre

    Image Set Classification Using Holistic Multiple Order Statistics Features and Localized Multi-Kernel Metric Learning Jiwen Lu1 , Gang Wang1,2 , and Pierre Moulin3 1 Advanced Digital Sciences Center viewpoints or under varying illuminations. While a number of image set classification methods have been

  9. SONG-LEVEL FEATURES AND SUPPORT VECTOR MACHINES FOR MUSIC CLASSIFICATION

    E-Print Network [OSTI]

    Ellis, Dan

    ,dpwe}@ee.columbia.edu ABSTRACT Searching and organizing growing digital music collec- tions requires automatic classificationSONG-LEVEL FEATURES AND SUPPORT VECTOR MACHINES FOR MUSIC CLASSIFICATION Michael I. Mandel improves clas- sification. Further gains are also seen when using Sup- Permission to make digital or hard

  10. SUPERVISED AND UNSUPERVISED MRF BASED 3D SCENE CLASSIFICATION IN MULTIPLE VIEW

    E-Print Network [OSTI]

    SUPERVISED AND UNSUPERVISED MRF BASED 3D SCENE CLASSIFICATION IN MULTIPLE VIEW AIRBORNE OBLIQUE Classification in 3D object space Basic idea Supervised approach Unsupervised approah Experiments: data and results Discussion CONTENTS #12; State-of-the-Art digital camera hardware and processing stimuate

  11. THE CLASSIFICATION OF DIGITAL COVERING SPACES Laurence Boxer and Ismet KARACA

    E-Print Network [OSTI]

    Boxer, Laurence

    THE CLASSIFICATION OF DIGITAL COVERING SPACES Laurence Boxer and Ismet KARACA Abstract Classification. Primary 55N35, 68R10, 68U05, 68U10. Key words and phrases. digital image, digital topology. In this paper we classify digital covering spaces using the conjugacy class corre- sponding to a digital

  12. Theoretical and Experimental Analysis of a Two-Stage System for Classification

    E-Print Network [OSTI]

    Sperduti, Alessandro

    Theoretical and Experimental Analysis of a Two-Stage System for Classification Nicola Giusti a popular approach to multicategory classification tasks: a two-stage system based on a first (global to the recognition of handwritten digits. In one system, the first classifier is a fuzzy basis functions network

  13. Tissue Classification using Cluster Features for Lesion Detection in Digital Cervigrams

    E-Print Network [OSTI]

    Huang, Xiaolei

    Tissue Classification using Cluster Features for Lesion Detection in Digital Cervigrams Xiaolei, tissue classification, lesion detection, digital cervigrams, cervical cancer 1. INTRODUCTION To make of different tissue types in digitized uterine cervix images using mean-shift clustering and support vector

  14. Exploring the effect of rhythmic style classification on automatic tempo estimation

    E-Print Network [OSTI]

    Plumbley, Mark

    Exploring the effect of rhythmic style classification on automatic tempo estimation Matthew E. P. Davies and Mark D. Plumbley Centre for Digital Music, Queen Mary, University of London Mile End Rd, E1 4 in musical audio signals. We demonstrate how the use of a simple 1-NN classification method, able

  15. Feature Set Reduction for Document Classification Problems Karel Fuka, Rudolf Hanka

    E-Print Network [OSTI]

    McCallum, Andrew

    Feature Set Reduction for Document Classification Problems Karel Fuka, Rudolf Hanka Medical With a growing amount of electronic documents available, there is a need to classify documents automatically. In growing text classification applications, important-term selection is a critical task for the classifier

  16. Automatic classification of citation function Simone Teufel Advaith Siddharthan Dan Tidhar

    E-Print Network [OSTI]

    Teufel, Simone

    Automatic classification of citation function Simone Teufel Advaith Siddharthan Dan Tidhar Natural relationship between citation func- tion and sentiment classification. 1 Introduction Why do researchers cite of science, and in- formation sciences (library sciences) for decades (Garfield, 1979; Small, 1982; White

  17. AISEC: an Artificial Immune System for E-mail Classification Andrew Secker

    E-Print Network [OSTI]

    Timmis, Jon

    of continuous learning for the purposes of two-class classification and is illustrated here on the taskAISEC: an Artificial Immune System for E-mail Classification Andrew Secker Computing Laboratory-interesting without the need for re-training. Comparisons are drawn with a naïve Bayesian classifier and it is shown

  18. English and Chinese Bilingual Topic Aspect Classification: Exploring Similarity Measures, Optimal LSA Dimensions,

    E-Print Network [OSTI]

    Oard, Doug

    analysis thus leads directly to a need for bilingual topic aspect classification as a prerequisite taskEnglish and Chinese Bilingual Topic Aspect Classification: Exploring Similarity Measures, Optimal LSA Dimensions, and Centroid Correction of Translated Training Examples Yejun Wu School of Library

  19. Enhancing the detection and classification of coral reef and associated benthic habitats

    E-Print Network [OSTI]

    Rundquist, Donald C.

    Enhancing the detection and classification of coral reef and associated benthic habitats. Rundquist, M. Lawson, and R. Perk (2007), Enhancing the detection and classification of coral reef and Atkinson, 2000]. Holden and LeDrew [1999] have shown that a high-resolution in situ spectral library can

  20. A Source Classification Algorithm for Astronomical X-ray Imagery of Stellar Clusters

    E-Print Network [OSTI]

    Salvaggio, Carl

    A Source Classification Algorithm for Astronomical X-ray Imagery of Stellar Clusters by Susan M of Dissertation: A Source Classification Algorithm for Astronomical X-ray Imagery of Stellar Clusters I, Susan M. Hojnacki, hereby grant permission to Wallace Memorial Library of R.I.T. to reproduce my dissertation

  1. Simultaneous Segmentation and Grading of Hippocampus for Patient Classification with Alzheimer's

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Simultaneous Segmentation and Grading of Hippocampus for Patient Classification with Alzheimer library used during our experiments was composed by 2 populations, 50 Cognitively Normal subjects (CN of the HC at the same time resulted in an efficient patient classification with a success rate of 90

  2. On the synergy between texture classification and deformation process sequence selection for

    E-Print Network [OSTI]

    Zabaras, Nicholas J.

    On the synergy between texture classification and deformation process sequence selection properties. This paper demonstrates the synergy between classification of FCC polycrystal tex- ture and multi are adaptively selected from the database is employed. Key words: Texture library, materials-by-design, data

  3. Computational analysis of microarray gene expression profiles: clustering, classification, and beyond

    E-Print Network [OSTI]

    Dai, Yang

    Computational analysis of microarray gene expression profiles: clustering, classification) the discovery of gene clusters, and (3) the classification of biological samples. In addition, we discuss how inch, and a library of thousands of genes is placed on a single chip. To probe the global gene

  4. VEGETATION CLASSIFICATION USING SEASONAL VARIATIONS OF SCATTEROMETER DATA AT C-BAND AND

    E-Print Network [OSTI]

    Long, David G.

    VEGETATION CLASSIFICATION USING SEASONAL VARIATIONS OF SCATTEROMETER DATA AT C-BAND AND KU for submission to the university library. Date Dr. David Long Chair, Graduate Committee Accepted of Engineering and Technology #12;ABSTRACT VEGETATION CLASSIFICATION USING SEASONAL VARIATIONS OF SCATTEROMETER

  5. EPA`s program for risk assessment guidelines: Cancer classification issues

    SciTech Connect (OSTI)

    Wiltse, J.

    1990-12-31

    Issues presented are related to classification of weight of evidence in cancer risk assessments. The focus in this paper is on lines of evidence used in constructing a conclusion about potential human carcinogenicity. The paper also discusses issues that are mistakenly addressed as classification issues but are really part of the risk assessment process. 2 figs.

  6. An Automatic Hierarchical Image Classification Scheme Jing Huang S Ravi Kumar y Ramin Zabih z

    E-Print Network [OSTI]

    Zabih, Ramin

    in such a process. Image Classification. One approach to this problem is to orga- nize the digital libraryAn Automatic Hierarchical Image Classification Scheme Jing Huang S Ravi Kumar y Ramin Zabih z Department of Computer Science Cornell University Ithaca, NY 14853. Abstract Organizing images into semantic

  7. Multi-modal Classification in Digital News Libraries Ming-yu Chen

    E-Print Network [OSTI]

    Multi-modal Classification in Digital News Libraries Ming-yu Chen School of Computer Science School of Computer Science Carnegie Mellon University Pittsburgh PA, USA 15213 +1 412 268 1448 alex@cs.cmu.edu ABSTRACT This paper describes a comprehensive approach to construct robust multi-modal video classification

  8. Image Classification by a Probabilistic Model Learned from Imperfect Training Data on the Web

    E-Print Network [OSTI]

    Yanai, Keiji

    Image Classification by a Probabilistic Model Learned from Imperfect Training Data on the Web Keiji Yanai Department of Computer Science, The University of Electro-Communications 1-5-1 Chofugaoka, Chofu-shi, Tokyo, 182-8585 JAPAN yanai@cs.uec.ac.jp ABSTRACT Current approaches to image classification require

  9. Discriminating Against New Classes: One-Class versus Multi-Class Classification

    E-Print Network [OSTI]

    Frank, Eibe

    Discriminating Against New Classes: One-Class versus Multi-Class Classification Kathryn Hempstalk group of observations, in the sense of belonging to a new, previously unseen `attacker' class. One possible approach to this kind of verification problem is one-class classification, learning a description

  10. A Generic Machine-Learning Tool for Online Whole Brain Classification from fMRI

    E-Print Network [OSTI]

    Koppel, Moshe

    A Generic Machine-Learning Tool for Online Whole Brain Classification from fMRI Ori Cohen1 generic machine learning (ML) tool for real- time fMRI whole brain classification, which can be used informa- tion gain for isolating the most relevant voxels in the brain and a support vector machine

  11. STRUCTURAL DAMAGE CLASSIFICATION COMPARISON USING SUPPORT VECTOR MACHINE AND BAYESIAN MODEL SELECTION

    E-Print Network [OSTI]

    Boyer, Edmond

    STRUCTURAL DAMAGE CLASSIFICATION COMPARISON USING SUPPORT VECTOR MACHINE AND BAYESIAN MODEL, CA, USA 92093-0085 mdtodd@ucsd.edu ABSTRACT Since all damage identification strategies inevitably in the decision-making process of damage detection, classification, and prognosis, which employs training data (or

  12. Utilizing a Value of Information Framework to Improve Ore Collection and Classification Procedures

    E-Print Network [OSTI]

    Utilizing a Value of Information Framework to Improve Ore Collection and Classification Procedures utilizes a value of information decision framework to provide mine managers guidance regarding the purchase and subsequent classification. We utilize a value of information framework that can potentially enable a decision

  13. Incorporating Camera Metadata for Attended Region Detection and Consumer Photo Classification

    E-Print Network [OSTI]

    Fan, Jianping

    Incorporating Camera Metadata for Attended Region Detection and Consumer Photo Classification Zhong significantly differ from the pictures that are taken by a surveillance camera or a vi- sion sensor on a robot. Keywords Camera metadata, attended regions, image classification. 1. INTRODUCTION The consumer photos

  14. Large-Scale Patent Classification with Min-Max Modular Support Vector Machines

    E-Print Network [OSTI]

    Lu, Bao-Liang

    Large-Scale Patent Classification with Min-Max Modular Support Vector Machines Xiao-Lei Chu, Chao Ma, Jing Li, Bao-Liang Lu Senior Member, IEEE, Masao Utiyama, and Hitoshi Isahara Abstract-- Patent-world patent classification typically exceeds one million, and this number increases every year. An effective

  15. Semantic Film Preview Classification Using Low-Level Computable Features Zeeshan Rasheed Yaser Sheikh Mubarak Shah

    E-Print Network [OSTI]

    Sheikh, Yaser Ajmal

    Semantic Film Preview Classification Using Low-Level Computable Features Zeeshan Rasheed Yaser Orlando, Fl 32826, USA Abstract This paper presents a framework for the classification of feature films- mantic film interpretation, currently using low-level video features and knowledge of ubiquitous

  16. EVALUATION OF FREQUENTLY USED AUDIO FEATURES FOR CLASSIFICATION OF MUSIC INTO PERCEPTUAL CATEGORIES

    E-Print Network [OSTI]

    Widmer, Gerhard

    extra-musical) sources of information for useful music classification. 1. INTRODUCTION Music InformationEVALUATION OF FREQUENTLY USED AUDIO FEATURES FOR CLASSIFICATION OF MUSIC INTO PERCEPTUAL CATEGORIES Tim Pohle1 , Elias Pampalk1 and Gerhard Widmer1,2 1 Austrian Research Institute for Artificial

  17. PRE-FIGHT DETECTION Classification of Fighting Situations Using Heirachical AdaBoost

    E-Print Network [OSTI]

    Fisher, Bob

    PRE-FIGHT DETECTION Classification of Fighting Situations Using Heirachical AdaBoost Scott J@inf.ed.ac.uk Keywords: Fight, Pre Fight, Cuboid, AdaBoost. Abstract: Abstract: This paper investigates the detection and classification of fighting and pre and post fighting events when viewed from a video camera. Specifically we

  18. Machine Learning for Seismic Signal Processing: Seismic Phase Classification on a Manifold

    E-Print Network [OSTI]

    Meyer, Francois

    Machine Learning for Seismic Signal Processing: Seismic Phase Classification on a Manifold Juan--In this research, we consider the supervised learning problem of seismic phase classification. In seismology, knowledge of the seismic activity arrival time and phase leads to epicenter localization and surface

  19. Automatic classification of mammography reports by BI-RADS breast tissue composition class

    E-Print Network [OSTI]

    Rubin, Daniel L.

    Automatic classification of mammography reports by BI-RADS breast tissue composition class Bethany tissue composition partially predicts breast cancer risk, classification of mammography reports by breast for using the unstructured text of mammography reports to classify them into BI-RADS breast tissue

  20. Flow Classification by Histograms or How to Go on Safari in the Internet

    E-Print Network [OSTI]

    Emilion, Richard

    Flow Classification by Histograms or How to Go on Safari in the Internet Augustin Soule , Kavé aggregated Internet traffic flows efficiently, we need to be able to categorize flows into distinct classes method for Internet flow classification. We show that our method is powerful in that it is capable

  1. Combination of Multiple Distance Measures for Protein Fold Classification Chendra Hadi Suryanto, Hideitsu Hino, Kazuhiro Fukui

    E-Print Network [OSTI]

    Fukui, Kazuhiro

    Combination of Multiple Distance Measures for Protein Fold Classification Chendra Hadi Suryanto. In this paper, we propose a new approach to protein fold classification, by introducing the concept of large demonstrate the effectiveness of the proposed method by classifying 27 fold classes of proteins in the Ding

  2. Data-driven classification of ventilated lung tissues using electrical impedance tomography

    E-Print Network [OSTI]

    Adler, Andy

    Data-driven classification of ventilated lung tissues using electrical impedance tomography Camille for identifying ventilated lung regions utilizing electrical impedance tomography (EIT) images rely on dividing of a data-driven classification method to identify ventilated lung ROI based on forming k clusters from

  3. Multi-Cue Pedestrian Classification With Partial Occlusion Handling Markus Enzweiler1

    E-Print Network [OSTI]

    Gavrila, Dariu M.

    Multi-Cue Pedestrian Classification With Partial Occlusion Handling Markus Enzweiler1 Angela for pedestrian classification with partial occlusion handling. The framework involves a set of component sets, with both partially occluded and non-occluded pedestrians, we obtain significant performance

  4. REMOTE SENSING TECHNIQUES FOR LAND USE CLASSIFICATION OF RIO JAUCA WATERSHED USING IKONOS IMAGES

    E-Print Network [OSTI]

    Gilbes, Fernando

    REMOTE SENSING TECHNIQUES FOR LAND USE CLASSIFICATION OF RIO JAUCA WATERSHED USING IKONOS IMAGES-Mayagüez E-mail: edwinmm80@yahoo.com Key words: GIS, remote sensing, land use, supervised classification resource and supplies water to the metropolitan area. Remote sensing techniques can be used to assess

  5. CLASSIFICATION OF BIOMEDICAL HIGH-RESOLUTION MICRO-CT IMAGES FOR DIRECT VOLUME RENDERING

    E-Print Network [OSTI]

    López-Sánchez, Maite

    CLASSIFICATION OF BIOMEDICAL HIGH-RESOLUTION MICRO-CT IMAGES FOR DIRECT VOLUME RENDERING Maite L of biomedical high- resolution 3D images. More concretely, it proposes a learn- ing pipeline process and refinements. KEYWORDS Machine Learning, Biomedical 3D Images, Classification, CRF (Conditional Random Fields

  6. Classification with Artificial Neural Networks and Support Vector Machines: application to oil fluorescence spectra

    E-Print Network [OSTI]

    Oldenburg, Carl von Ossietzky Universität

    be applied to predict the profit, market movements, and price level based on the market's historical datasetClassification with Artificial Neural Networks and Support Vector Machines: application to oil, and Oil fluorescence ABSTRACT: This paper reports on oil classification with fluorescence spectroscopy

  7. Invariant Action Classification with Volumetric Data Fabio Cuzzolin, Augusto Sarti and Stefano Tubaro

    E-Print Network [OSTI]

    Cuzzolin, Fabio

    Invariant Action Classification with Volumetric Data Fabio Cuzzolin, Augusto Sarti and Stefano a volumetric representation of the body by means of volumetric intersection. Classification is then performed to pose the problem in the volumetric context [1], [2], action recognition and activity detection

  8. Survey of Related Work The world cannot be understood from a single point of view.

    E-Print Network [OSTI]

    Antón, Annie I.

    are either formal or informal. Formal techniques address the specification of declarations and assertions through a series of concrete examples. These examples serve as a rich source of information system to offer the formal underpinnings needed to bridge the gap between formal and informal methods. The general

  9. Efficient Packet Classification with Digest This work supported by the National Science Foundation under Grant EIA-0130344 and the generous

    E-Print Network [OSTI]

    Efficient Packet Classification with Digest Caches This work supported by the National Science a digest cache-based algorithm for efficient packet classification in network devices. The digest cache

  10. A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

    SciTech Connect (OSTI)

    Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)

    2012-02-01

    New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

  11. The normalization of citation counts based on classification systems

    E-Print Network [OSTI]

    Bornmann, Lutz; Barth, Andreas

    2013-01-01

    If we want to assess whether the paper in question has had a particularly high or low citation impact compared to other papers, the standard practice in bibliometrics is to normalize citations in respect of the subject category and publication year. A number of proposals for an improved procedure in the normalization of citation impact have been put forward in recent years. Against the background of these proposals this study describes an ideal solution for the normalization of citation impact: in a first step, the reference set for the publication in question is collated by means of a classification scheme, where every publication is associated with a single principal research field or subfield entry (e. g. via Chemical Abstracts sections) and a publication year. In a second step, percentiles of citation counts are calculated for this set and used to assign the normalized citation impact score to the publications (and also to the publication in question).

  12. Classification of interstitial lung disease patterns with topological texture features

    E-Print Network [OSTI]

    Huber, Markus B; Leinsinger, Gerda; Ray, Lawrence A; Wismüller, Axel; 10.1117/12.844318

    2010-01-01

    Topological texture features were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honey-combing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. A set of 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and three Minkowski Functionals (MFs, e.g. MF.euler). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characteriza...

  13. A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

    SciTech Connect (OSTI)

    Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)

    2013-01-01

    New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today s increasing complex, multivariate data sets. In this paper, a visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today s data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. This chapter provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

  14. CLASSIFICATION OF DIGITAL MODULATIONS BY MCMC SAMPLING Stphane Lesage*, Jean-Yves Tourneret* and Petar M. Djuric

    E-Print Network [OSTI]

    Djuriæ, Petar M.

    CLASSIFICATION OF DIGITAL MODULATIONS BY MCMC SAMPLING Stéphane Lesage*, Jean-Yves Tourneret addresses the problem of classification of digital mod- ulations. The proposed solution uses the Bayes. INTRODUCTION AND PROBLEM FORMULATION The digital modulation classification problem consists of deter- mining

  15. 3816 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 61, NO. 9, SEPTEMBER 2013 Likelihood-Based Modulation Classification for

    E-Print Network [OSTI]

    Kim, Il-Min

    , IEEE Abstract--Likelihood-based algorithms for the classification of linear digital modulations-Based Modulation Classification for Multiple-Antenna Receiver Ali Ramezani-Kebrya, Student Member, IEEE, Il-Min Kim are systematically investigated for a multiple receive antennas configuration. Existing modulation classification (MC

  16. Abstract--Better software and hardware for automatic classification of power quality (PQ) disturbances are desired for

    E-Print Network [OSTI]

    Mamishev, Alexander

    1 Abstract--Better software and hardware for automatic classification of power quality (PQ. The flexibility of this method allows classification of a very broad range of power quality events of this two-paper series [1]. Index Terms--Power Quality, Classification-Optimal TFR, Time-Frequency Ambiguity

  17. Road Type Classification through Data Mining Phillip Taylor, Sarabjot Singh Anand, Nathan Griffiths, Fatimah Adamu-Fika

    E-Print Network [OSTI]

    Griffiths, Nathan

    Road Type Classification through Data Mining Phillip Taylor, Sarabjot Singh Anand, Nathan Griffiths In this paper we investigate data mining approaches to road type classification based on CAN (controller area network) bus data collected from vehicles on UK roads. We consider three related classification problems

  18. Classification of generalized quantum statistics associated with the exceptional Lie (super)algebras

    SciTech Connect (OSTI)

    Stoilova, N. I.; Jeugt, J. van der

    2007-04-15

    Generalized quantum statistics (GQS) associated with a Lie algebra or Lie superalgebra extends the notion of para-Bose or para-Fermi statistics. Such GQS have been classified for all classical simple Lie algebras and basic classical Lie superalgebras. In the current paper we finalize this classification for all exceptional Lie algebras and superalgebras. Since the definition of GQS is closely related to a certain Z grading of the Lie (super)algebra G, our classification reproduces some known Z gradings of exceptional Lie algebras. For exceptional Lie superalgebras such a classification of Z gradings has not been given before.

  19. Tea classification based on artificial olfaction using bionic olfactory neural network

    E-Print Network [OSTI]

    Yang, X L; Fu, J; Lou, Z G; Wang, L Y; Li, G; Freeman, Walter J III

    2006-01-01

    a classification between green tea and black tea. To buildtains three samples of green tea and three samples of blackln(R odor ) R odor /R air Green tea 53.3% Black tea 50% ln(R

  20. An Efficient Automatic Mass Classification Method In Digitized Mammograms Using Artificial Neural Network

    E-Print Network [OSTI]

    Islam, Mohammed J; Sid-Ahmed, Maher A; 10.5121/ijaia.2010.1301

    2010-01-01

    In this paper we present an efficient computer aided mass classification method in digitized mammograms using Artificial Neural Network (ANN), which performs benign-malignant classification on region of interest (ROI) that contains mass. One of the major mammographic characteristics for mass classification is texture. ANN exploits this important factor to classify the mass into benign or malignant. The statistical textural features used in characterizing the masses are mean, standard deviation, entropy, skewness, kurtosis and uniformity. The main aim of the method is to increase the effectiveness and efficiency of the classification process in an objective manner to reduce the numbers of false-positive of malignancies. Three layers artificial neural network (ANN) with seven features was proposed for classifying the marked regions into benign and malignant and 90.91% sensitivity and 83.87% specificity is achieved that is very much promising compare to the radiologist's sensitivity 75%.

  1. Fact #623: May 17, 2010 Classification Changes in the CAFE Standards

    Broader source: Energy.gov [DOE]

    Beginning with model year (MY) 2011, the classification of cars or light trucks has changed for the purposes of the Corporate Average Fuel Economy (CAFE) Standards. Two-wheel-drive (2wd) sport...

  2. Copyright 2003 by the Genetics Society of America Quantitative Classification and Natural Clustering of Caenorhabditis elegans

    E-Print Network [OSTI]

    Schafer, William R.

    Copyright 2003 by the Genetics Society of America Quantitative Classification and Natural'saccessibility to germline transformation, these animals movements over long time periods and save digital im-are highly

  3. Rock Classification in Organic Shale Based on Petrophysical and Elastic Rock Properties Calculated from Well Logs 

    E-Print Network [OSTI]

    Aranibar Fernandez, Alvaro A

    2015-01-05

    Organic Content (TOC), fluid saturation, volumetric concentrations of mineral constituents, and elastic properties facilitated identification of different rock classes, using an unsupervised artificial neural network. A good rock classification technique...

  4. FUNDRAISING AND GIFT ACCEPTANCE University Policy No: ER4105 Classification: External Relations

    E-Print Network [OSTI]

    Victoria, University of

    1 FUNDRAISING AND GIFT ACCEPTANCE University Policy No: ER4105 Classification: External Relations.01 For Gifts-in-kind to the Library or to the University of Victoria Art Collection, authority may be delegated

  5. Active Online Confidence Boosting for E cient Object Classification Dennis Mund Rudolph Triebel Daniel Cremers

    E-Print Network [OSTI]

    Cremers, Daniel

    ¨at M¨unchen, Germany {dennis.mund,rudolph.triebel,daniel.cremers}@in.tum.de True Label = lightbulb 0 0 ->lightbulb Fig. 1: Object classification with active online Confidence Boosting: The image on the left

  6. Classification of power quality disturbances using time-frequency ambiguity plane and

    E-Print Network [OSTI]

    Mamishev, Alexander

    shows promise for further development of a fully automated power quality monitoring system equipment places increasingly more stringent demands on the quality of electric power suppliedClassification of power quality disturbances using time-frequency ambiguity plane and neural

  7. Some computations for the exceptional groups relevant to the classification of p-compact groups

    E-Print Network [OSTI]

    Møller, Jesper Michael

    Some computations for the exceptional groups relevant to the classification of p-compact Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .* * . . . 46 II Fusion, Solvability and Swan's theorem 48 2 Fusion, Solvability and Swan's theorem

  8. From Classification to Indexing: How Automation Transforms the Way we Think

    E-Print Network [OSTI]

    Hanson, F. Allan

    2004-01-01

    that are currently in widespread use at a loss to deal effectively with classification. Indexing conveys nothing about relationships; it pinpoints information on particular topics without reference to anything else. Keyword searching is a form of indexing, and here...

  9. The Classification, Packaging and Labelling of Dangerous Substances (Amendment) Regulations 1986 

    E-Print Network [OSTI]

    Her Majesty's Stationary Office

    1986-01-01

    These Regulations amend the Classification, Packagmg and Labelling of Dangcrous Substances Regulations 1984 ("the principal Regulations") to give effect with respect to Great Britain to the provisions of- (a) Commission ...

  10. A predictive model for particle size distribution and yield for Bayer precipitation and classification 

    E-Print Network [OSTI]

    Kapraun, Christopher Michael

    1996-01-01

    This project implements a dynamic alumina hydrate continuous precipitation and classification model in an alumina refining operation to allow the forecasting of a number of relevant process parameters, such as the particle size distribution...

  11. A Field Demonstration of an Instrument Performing Automatic Classification of Geologic

    E-Print Network [OSTI]

    -sensitive classifications of geologic surfaces in mesoscale scenes. A series of tests at the Cima Volcanic Fields in the Mojave Desert, California demonstrate mesoscale surficial mapping at two distinct sites of geologic

  12. An elitist approach to automatic articulatory-acoustic feature classification for phonetic characterization of spoken language. 

    E-Print Network [OSTI]

    Chang, Shuangyu; Wester, Mirjam; Greenberg, Steven

    2005-01-01

    A novel framework for automatic articulatory-acoustic feature extraction has been developed for enhancing the accuracy of place- and manner-of-articulation classification in spoken language. The elitist approach provides ...

  13. Detection, classification and localization of seabed objects with a virtual time reversal mirror

    E-Print Network [OSTI]

    Dumortier, Alexis Jean Louis

    2009-01-01

    The work presented in this thesis addresses the problem of the detection, classification and localization of seabed objects in shallow water environments using a time reversal approach in a bistatic configuration. The ...

  14. A Dutch treatment of an elitist approach to articulatory-acoustic feature classification

    E-Print Network [OSTI]

    Wester, Mirjam; Greenberg, Steven; Chang, Shuangyu

    2001-01-01

    A novel approach to articulatory-acoustic feature extraction has been developed for enhancing the accuracy of classification associated with place and manner of articulation information. This elitist approach is tested on ...

  15. A global typology of cities : classification tree analysis of urban resource consumption

    E-Print Network [OSTI]

    Saldivar-Sali, Artessa Niccola D., 1980-

    2010-01-01

    A study was carried out to develop a typology of urban metabolic (or resource consumption) profiles for 155 globally representative cities. Classification tree analysis was used to develop a model for determining how certain ...

  16. The Effect of OCR Errors on Stylistic Text Classification Sterling Stuart Stein

    E-Print Network [OSTI]

    The Effect of OCR Errors on Stylistic Text Classification Sterling Stuart Stein Linguistic retrieval; Taghva and Coombs [1] found that a search engine could be made to work well over OCR documents

  17. Comparing and Combining Semantic Verb Classifications Oliver Culo, Katrin Erk, Sebastian Pado+,

    E-Print Network [OSTI]

    Padó, Sebastian

    Comparing and Combining Semantic Verb Classifications Oliver Culo, Katrin Erk, Sebastian Pad version of FrameNet (Erk et al., 2003); however, while Schulte im Walde classifies the manner of motion

  18. Investigating Evolvable Hardware Classification for the BioSleeve Electromyographic Interface

    E-Print Network [OSTI]

    Glette, Kyrre

    Investigating Evolvable Hardware Classification for the BioSleeve Electromyographic Interface Kyrre signals. The BioSleeve is equipped with a high number of electromyographic (EMG) channels, with more

  19. Solar wind and geomagnetism: toward a standard classification of geomagnetic activity from 1868 to 2009

    E-Print Network [OSTI]

    Zerbo, J. L.

    We examined solar activity with a large series of geomagnetic data from 1868 to 2009. We have revisited the geomagnetic activity classification scheme of Legrand and Simon (1989) and improve their scheme by lowering the ...

  20. Classification of subsurface objects using singular values derived from signal frames

    DOE Patents [OSTI]

    Chambers, David H; Paglieroni, David W

    2014-05-06

    The classification system represents a detected object with a feature vector derived from the return signals acquired by an array of N transceivers operating in multistatic mode. The classification system generates the feature vector by transforming the real-valued return signals into complex-valued spectra, using, for example, a Fast Fourier Transform. The classification system then generates a feature vector of singular values for each user-designated spectral sub-band by applying a singular value decomposition (SVD) to the N.times.N square complex-valued matrix formed from sub-band samples associated with all possible transmitter-receiver pairs. The resulting feature vector of singular values may be transformed into a feature vector of singular value likelihoods and then subjected to a multi-category linear or neural network classifier for object classification.

  1. Data driven process monitoring based on neural networks and classification trees 

    E-Print Network [OSTI]

    Zhou, Yifeng

    2005-11-01

    of this dissertation is to develop process monitoring schemes that can be applied to complex process systems. Neural networks have been a popular tool for modeling and pattern classification for monitoring of process systems. However, due to the prohibitive...

  2. CLASSIFICATION OF FOOD KERNELS WITH IMPACT ACOUSTICS TIME-1 FREQUENCY PATTERNS2

    E-Print Network [OSTI]

    Minnesota, University of

    , Classification.24 25 INTRODUCTION26 Food kernel damage caused by insects, fungi and mold are major sources degrades the quality and value of wheat and is one of the most difficult29 #12;2 defects to detect

  3. Early F-type stars - refined classification, confrontation with Stromgren photometry, and the effects of rotation

    SciTech Connect (OSTI)

    Gray, R.O.; Garrison, R.F.

    1989-02-01

    The classification for early F-type stars in the MK spectral classification system presented by Gray and Garrison (1987) is refined. The effect of rotation on spectral classification and ubvy-beta photometry of early F-type stars is examined. It is found that the classical luminosity criterion, the 4417 A/4481 A ratio gives inconsistent results. It is shown that most of the stars in the Delta Delphini class of metallic-line stars are either normal or are indistinguishable from proto-Am stars. It is suggested that the designation Delta Delphini should be dropped. The classifications are compared with Stromgren photometry. The effects of rotation on the delta-c sub 1 index in the early-F field dwarfs is demonstrated. 55 references.

  4. Modifed Minimum Classification Error Learning and Its Application to Neural Networks 

    E-Print Network [OSTI]

    Shimodaira, Hiroshi; Rokui, Jun; Nakai, Mitsuru

    A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learning proposed by Juang and Katagiri in 1992 ...

  5. Model comparison for automatic characterization and classification of average ERPs using visual oddball paradigm

    E-Print Network [OSTI]

    Polikar, Robi

    Model comparison for automatic characterization and classification of average ERPs using visual December 2008 Keywords: EEG ERP Attention P300 N200 Oddball Pattern recognition Linear discriminant responses from averaged event-related potentials (ERPs) along with identifying appropriate features

  6. J-model: an open and social ensemble learning architecture for classification 

    E-Print Network [OSTI]

    Kim, Jinhan

    2012-11-29

    Ensemble learning is a promising direction of research in machine learning, in which an ensemble classifier gives better predictive and more robust performance for classification problems by combining other learners. ...

  7. Classification and volumetric analysis of temporal bone pneumatization using cone beam computed tomography

    E-Print Network [OSTI]

    Terasaki, Mark

    Classification and volumetric analysis of temporal bone pneumatization using cone beam computed Objective. This study performed volumetric analysis and classified different repeated patterns of temporal. Volumetric analysis of the pneumatization was performed using a window thresholding procedure on multiplanar

  8. Developmental defects in zebrafish for classification of EGF pathway inhibitors

    SciTech Connect (OSTI)

    Pruvot, Benoist; Curé, Yoann; Djiotsa, Joachim; Voncken, Audrey; Muller, Marc

    2014-01-15

    One of the major challenges when testing drug candidates targeted at a specific pathway in whole animals is the discrimination between specific effects and unwanted, off-target effects. Here we used the zebrafish to define several developmental defects caused by impairment of Egf signaling, a major pathway of interest in tumor biology. We inactivated Egf signaling by genetically blocking Egf expression or using specific inhibitors of the Egf receptor function. We show that the combined occurrence of defects in cartilage formation, disturbance of blood flow in the trunk and a decrease of myelin basic protein expression represent good indicators for impairment of Egf signaling. Finally, we present a classification of known tyrosine kinase inhibitors according to their specificity for the Egf pathway. In conclusion, we show that developmental indicators can help to discriminate between specific effects on the target pathway from off-target effects in molecularly targeted drug screening experiments in whole animal systems. - Highlights: • We analyze the functions of Egf signaling on zebrafish development. • Genetic blocking of Egf expression causes cartilage, myelin and circulatory defects. • Chemical inhibition of Egf receptor function causes similar defects. • Developmental defects can reveal the specificity of Egf pathway inhibitors.

  9. Historical literature review on waste classification and categorization

    SciTech Connect (OSTI)

    Croff, A.G.; Richmond, A.A.; Williams, J.P.

    1995-03-01

    The Staff of the Waste Management Document Library (WMDL), in cooperation with Allen Croff have been requested to provide information support for a historical search concerning waste categorization/classification. This bibliography has been compiled under the sponsorship of Oak Ridge National Laboratory`s Chemical Technology Division to help in Allen`s ongoing committee work with the NRC/NRCP. After examining the search, Allen Croff saw the value of the search being published. Permission was sought from the database providers to allow limited publication (i.e. 20--50 copies) of the search for internal distribution at the Oak Ridge National Laboratory and for Allen Croff`s associated committee. Citations from the database providers who did not grant legal permission for their material to be published have been omitted from the literature review. Some of the longer citations have been included in an abbreviated form in the search to allow the format of the published document to be shortened from approximately 1,400 pages. The bibliography contains 372 citations.

  10. System diagnostics using qualitative analysis and component functional classification

    DOE Patents [OSTI]

    Reifman, J.; Wei, T.Y.C.

    1993-11-23

    A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

  11. System diagnostics using qualitative analysis and component functional classification

    DOE Patents [OSTI]

    Reifman, Jaques (Lisle, IL); Wei, Thomas Y. C. (Downers Grove, IL)

    1993-01-01

    A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

  12. A thermodynamic classification of pairs of real numbers via the Triangle Multi-dimensional continued fraction

    E-Print Network [OSTI]

    Thomas Garrity

    2012-05-25

    A new classification scheme for pairs of real numbers is given, generalizing earlier work of the author that used continued fraction, which in turn was motivated by ideas from statistical mechanics in general and work of Knauf and Fiala and Kleban in particular. Critical for this classification are the number theoretic and geometric properties of the triangle map, a type of multi-dimensional continued fraction.

  13. Invariant Classification and Limits of Maximally Superintegrable Systems in 3D

    E-Print Network [OSTI]

    Joshua J. Capel; Jonathan M. Kress; Sarah Post

    2015-05-08

    The invariant classification of superintegrable systems is reviewed and utilized to construct singular limits between the systems. It is shown, by construction, that all superintegrable systems on conformally flat, 3D complex Riemannian manifolds can be obtained from singular limits of a generic system on the sphere. By using the invariant classification, the limits are geometrically motivated in terms of transformations of roots of the classifying polynomials.

  14. Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS

    SciTech Connect (OSTI)

    Ivezic, Z.; /Washington U., Seattle, Astron. Dept.; Axelrod, T.; /Large Binocular Telescope, Tucson; Becker, A.C.; /Washington U., Seattle, Astron. Dept.; Becla, J.; /SLAC; Borne, K.; /George Mason U.; Burke, David L.; /SLAC; Claver, C.F.; /NOAO, Tucson; Cook, K.H.; /LLNL, Livermore; Connolly, A.; /Washington U., Seattle, Astron. Dept.; Gilmore, D.K.; /SLAC; Jones, R.L.; /Washington U., Seattle, Astron. Dept.; Juric, M.; /Princeton, Inst. Advanced Study; Kahn, Steven M.; /SLAC; Lim, K-T.; /SLAC; Lupton, R.H.; /Princeton U.; Monet, D.G.; /Naval Observ., Flagstaff; Pinto, P.A.; /Arizona U.; Sesar, B.; /Washington U., Seattle, Astron. Dept.; Stubbs, Christopher W.; /Harvard U.; Tyson, J.Anthony; /UC, Davis

    2011-11-10

    The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg{sup 2} region about 1000 times during the anticipated 10 years of operations (distributed over six bands, ugrizy). Each 30-second long visit will deliver 5{sigma} depth for point sources of r {approx} 24.5 on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital-color classification of asteroid families, and the recognition of main Galaxy components based on the distribution of stars in the position-metallicity-kinematics space. Guided by these examples, we anticipate that two grand classification challenges for LSST will be (1) rapid and robust classification of sources detected in difference images, and (2) simultaneous treatment of diverse astrometric and photometric time series measurements for an unprecedentedly large number of objects.

  15. ACRR: Ad-hoc On-Demand Distance Vector Routing with Controlled Route Requests Jayesh Kataria*

    E-Print Network [OSTI]

    Sanyal, Sugata

    * Mumbai University, India, jayeshkataria@gmail.com P.S. Dhekne BARC, Mumbai, India, dhekne@barc.gov.in Sugata Sanyal TIFR, Mumbai, India, sanyal@tifr.res.in *Corresponding Author Abstract Reactive routing

  16. International Conference on Computers and Devices for Communication (CODEC-06) Institute of Radio Physics and Electronics, University of Calcutta, December 18-20, 2006.

    E-Print Network [OSTI]

    Sanyal, Sugata

    Flooding of Fake Route Requests in Ad-hoc Networks Jayesh Kataria Mumbai University, India, jayeshkataria@gmail.com P.S. Dhekne BARC, Mumbai, India, dhekne@barc.gov.in Sugata Sanyal TIFR, Mumbai, India, sanyal

  17. Steganography and Steganalysis: Different Approaches Soumyendu Das

    E-Print Network [OSTI]

    Sanyal, Sugata

    , bbandy@vsnl.com Sugata Sanyal Tata Institute of Fundamental Research Mumbai, India, sanyal of extra blank spaces are inserted between consecutive words of cover text. This numbers are mapped

  18. STATISTICAL DAMAGE CLASSIFICATION USING SEQUENTIAL PROBABILITY RATIO TESTS.

    SciTech Connect (OSTI)

    SOHN, HOON; ALLEN, DAVID W; WORDEN, KEITH; FARRAR, CHARLES R

    2002-02-16

    The primary objective of damage detection is to ascertain with confidence if damage is present or not within a structure of interest. In this study, a damage classification problem is cast in the context of the statistical pattern recognition paradigm. First, a time prediction model, called an autoregressive and autoregressive with exogenous inputs (AR-ARX) model, is fit to a vibration signal measured during a normal operating condition of the structure. When a new time signal is recorded from an unknown state of the system, the prediction errors are computed for the new data set using the time prediction model. When the structure undergoes structural degradation, it is expected that the prediction errors will increase for the damage case. Based on this premise, a damage classifier is constructed using a sequential hypothesis testing technique called the sequential probability ratio test (SPRT). The SPRT is one form of parametric statistical inference tests, and the adoption of the SPRT to damage detection problems can improve the early identification of conditions that could lead to performance degradation and safety concerns. The sequential test assumes a probability distribution of the sample data sets, and a Gaussian distribution of the sample data sets is often used. This assumption, however, might impose potentially misleading behavior on the extreme values of the data, i.e. those points in the tails of the distribution. As the problem of damage detection specifically focuses attention on the tails, the assumption of normality is likely to lead the analysis astray. To overcome this difficulty, the performance of the SPRT is improved by integrating extreme values statistics, which specifically models behavior in the tails of the distribution of interest into the SPRT.

  19. Giant Planet Formation: A First Classification of Isothermal Protoplanetary Equilibria

    E-Print Network [OSTI]

    B. Pecnik; G. Wuchterl

    2005-01-17

    We present a model for the equilibrium of solid planetary cores embedded in a gaseous nebula. From this model we are able to extract an idealized roadmap of all hydrostatic states of the isothermal protoplanets. The complete classification of the isothermal protoplanetary equilibria should improve the understanding of the general problem of giant planet formation, within the framework of the nucleated instability hypothesis. We approximate the protoplanet as a spherically symmetric, isothermal, self-gravitating classical ideal gas envelope in equilibrium, around a rigid body of given mass and density, with the gaseous envelope required to fill the Hill-sphere. Starting only with a core of given mass and an envelope gas density at the core surface, the equilibria are calculated without prescribing the total protoplanetary mass or nebula density. The static critical core masses of the protoplanets for the typical orbits of 1, 5.2, and 30 AU, around a parent star of 1 solar mass are found to be 0.1524, 0.0948, and 0.0335 Earth masses, respectively, for standard nebula conditions (Kusaka et al. 1970). These values are much lower than currently admitted ones primarily because our model is isothermal and the envelope is in thermal equilibrium with the nebula. For a given core, multiple solutions (at least two) are found to fit into the same nebula. We extend the concept of the static critical core mass to the local and global critical core mass. We conclude that the 'global static critical core mass' marks the meeting point of all four qualitatively different envelope regions.

  20. Point Vortices: Finding Periodic Orbits and their Topological Classification

    E-Print Network [OSTI]

    Spencer A. Smith

    2015-10-22

    The motion of point vortices constitutes an especially simple class of solutions to Euler's equation for two dimensional, inviscid, incompressible, and irrotational fluids. In addition to their intrinsic mathematical importance, these solutions are also physically relevant. Rotating superfluid helium can support rectilinear quantized line vortices, which in certain regimes are accurately modeled by point vortices. Depending on the number of vortices, it is possible to have either regular integrable motion or chaotic motion. Thus, the point vortex model is one of the simplest and most tractable fluid models which exhibits some of the attributes of weak turbulence. The primary aim of this work is to find and classify periodic orbits, a special class of solutions to the point vortex problem. To achieve this goal, we introduce a number of algorithms: Lie transforms which ensure that the equations of motion are accurately solved; constrained optimization which reduces close return orbits to true periodic orbits; object-oriented representations of the braid group which allow for the topological comparison of periodic orbits. By applying these ideas, we accumulate a large data set of periodic orbits and their associated attributes. To render this set tractable, we introduce a topological classification scheme based on a natural decomposition of mapping classes. Finally, we consider some of the intriguing patterns which emerge in the distribution of periodic orbits in phase space. Perhaps the most enduring theme which arises from this investigation is the interplay between topology and geometry. The topological properties of a periodic orbit will often force it to have certain geometric properties.

  1. RAMAN SANYAL, FRANK SOTTILE, AND BERND STURMFELS Abstract. An orbitope is the convex hull of an orbit of a compact group acting linearly

    E-Print Network [OSTI]

    Sottile, Frank

    of an orbit of a compact group acting linearly on a vector space. These highly symmetric convex bodies lie of an orbit of a compact algebraic group G acting linearly on a real vector space. The orbit has the structure orbitopes lies at the heart of convex algebraic geometry ­ the fusion of convex geometry and (real

  2. Quiz # 7, STAT 383, Prof. Suman Sanyal, April 8, 2009 (Q2, Page 354) To decide whether the pipe welds in a nuclear power plant meet

    E-Print Network [OSTI]

    Sanyal, Suman

    welds in a nuclear power plant meet specifications, a random sample of welds is to be selected : µ nuclear power plants is to determine if welds

  3. A modified version of the geomechanics classification for entry design in underground coal mines

    SciTech Connect (OSTI)

    Newman, D.A.; Bieniawski, Z.T.

    1985-01-01

    The Geomechanics Classification was modified for entry and roof support design in underground room-and-pillar coal mines. Adjustment multipliers were introduced to incorporate the influence of strata weatherability, high horizontal stresses, and the roof support reinforcement factor into the existing classification system. Sixty-two case histories of both standing and fallen mine roof were collected from two mines in the northern Appalachian coalfield. Twenty-seven engineering and geologic parameters were recorded for each case. A partial correlation analysis was carried out on the cases to establish which parameters have a significant impact upon the supported stand-up time of coal mine roof. Survival analysis, a statistical technique used in medical research to assess the effect of a drug or treatment on a patient's life expectancy, was conducted together with stepwise multiple regression to derive values for the adjustment multipliers. A practical example is included to illustrate the application of the modified Geomechanics Classification to underground coal mine design.

  4. Automated Classification of ELODIE Stellar Spectral Library Using Probabilistic Artificial Neural Networks

    E-Print Network [OSTI]

    Mahdi Bazarghan

    2008-04-17

    A Probabilistic Neural Network model has been used for automated classification of ELODIE stellar spectral library consisting of about 2000 spectra into 158 known spectro-luminosity classes. The full spectra with 561 flux bins and a PCA reduced set of 57, 26 and 16 components have been used for the training and test sessions. The results shows a spectral type classification accuracy of 3.2 sub-spectral type and luminosity class accuracy of 2.7 for the full spectra and an accuracy of 3.1 and 2.6 respectively with the PCA set. This technique will be useful for future upcoming large data bases and their rapid classification.

  5. Automated Classification of ELODIE Stellar Spectral Library Using Probabilistic Artificial Neural Networks

    E-Print Network [OSTI]

    Bazarghan, Mahdi

    2008-01-01

    A Probabilistic Neural Network model has been used for automated classification of ELODIE stellar spectral library consisting of about 2000 spectra into 158 known spectro-luminosity classes. The full spectra with 561 flux bins and a PCA reduced set of 57, 26 and 16 components have been used for the training and test sessions. The results shows a spectral type classification accuracy of 3.2 sub-spectral type and luminosity class accuracy of 2.7 for the full spectra and an accuracy of 3.1 and 2.6 respectively with the PCA set. This technique will be useful for future upcoming large data bases and their rapid classification.

  6. A Brief Summary of Dictionary Learning Based Approach for Classification (revised)

    E-Print Network [OSTI]

    Kong, Shu

    2012-01-01

    This note presents some representative methods which are based on dictionary learning (DL) for classification. We do not review the sophisticated methods or frameworks that involve DL for classification, such as online DL and spatial pyramid matching (SPM), but rather, we concentrate on the direct DL-based classification methods. Here, the "so-called direct DL-based method" is the approach directly deals with DL framework by adding some meaningful penalty terms. By listing some representative methods, we can roughly divide them into two categories, i.e. (1) directly making the dictionary discriminative and (2) forcing the sparse coefficients discriminative to push the discrimination power of the dictionary. From this taxonomy, we can expect some extensions of them as future researches.

  7. Automated Classification of Sloan Digital Sky Survey (SDSS) Stellar Spectra using Artificial Neural Networks

    E-Print Network [OSTI]

    Mahdi Bazarghan; Ranjan Gupta

    2008-04-26

    Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated techniques for analysis of such large datasets which are now available to the community. Sloan Digital Sky Survey (SDSS) is one of such surveys releasing massive datasets. We use Probabilistic Neural Network (PNN) for automatic classification of about 5000 SDSS spectra into 158 spectral type of a reference library ranging from O type to M type stars.

  8. Solubility Classification of Airborne Uranium Products from LWR-Fuel Plants

    SciTech Connect (OSTI)

    kalkwarf, D. R.

    1980-08-01

    Airborne dust samples were obtained from various locations within plants manufacturing fuel elements for light-water reactors, and the dissolution rates of uranium from these samples into simulated lung fluid at 37°C were measured. These measurements were used to classify the solubilities of the samples in terms of the lung clearance model proposed by the International Commission on Radiological Protection. Similar evaluations were performed for samples of pure uranium compounds expected as components in plant dust. The variation in solubility classifications of dust encountered along the fuel production lines is described and correlated with the process chemistry and the solubility classifications of the pure uranium compounds.

  9. IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 21, NO. 12, DECEMBER 2002 1461 Edge Displacement Field-Based Classification for

    E-Print Network [OSTI]

    Tomasi, Carlo

    -Based Classification for Improved Detection of Polyps in CT Colonography Burak Acar*, Christopher F. Beaulieu, Salih B invasive alternative to FOC. It would be desirable to have computer-aided detection (CAD) algorithms tomography data by classification of the changes in the location of the edges in the two-dimensional plane

  10. 10th International Society for Music Information Retrieval Conference (ISMIR 2009) GENRE CLASSIFICATION USING HARMONY RULES INDUCED FROM

    E-Print Network [OSTI]

    Dixon, Simon

    for the 3-way classification tasks. 1. INTRODUCTION To deal with the ever-increasing amount of digital music CLASSIFICATION USING HARMONY RULES INDUCED FROM AUTOMATIC CHORD TRANSCRIPTIONS Am´elie Anglade Queen Mary University of London Centre for Digital Music amelie.anglade@elec.qmul.ac.uk Rafael Ramirez Universitat

  11. arXiv:astro-ph/0411406v115Nov2004 Classification and Characterization of Objects from the GALEX

    E-Print Network [OSTI]

    Bianchi, Luciana

    arXiv:astro-ph/0411406v115Nov2004 Classification and Characterization of Objects from the GALEX of the Internal Release 0.2 (Morrissey et al. 2004) substantially overlap with the Sloan Digital Sky Survey (SDSS, and of the characteristics of objects with previously available classification within the sample. Several other papers

  12. In Discovery Science 99. Revised November 5, 1999, with correct accuracy results. CAEP: Classification by Aggregating Emerging

    E-Print Network [OSTI]

    Dong, Guozhu

    : Classification by Aggregating Emerging Patterns Guozhu Dong 1 and Xiuzhen Zhang 2 and Limsoon Wong 3 and Jinyan of CSSE, Univ of Melbourne, Vic 3052, Australia. fxzhang,jylig@cs.mu.oz.au 3 Kent Ridge Digital Labs the performance of classifiers. CAEP is also very good under this measure. 1 Introduction Classification

  13. A UNIFIED NEAR-INFRARED SPECTRAL CLASSIFICATION SCHEME FOR T DWARFS Adam J. Burgasser,1,2

    E-Print Network [OSTI]

    Burgasser, Adam J.

    A UNIFIED NEAR-INFRARED SPECTRAL CLASSIFICATION SCHEME FOR T DWARFS Adam J. Burgasser,1,2 T. R 2005 October 3 ABSTRACT A revised near-infrared classification scheme for T dwarfs is presented, based identified largely in the Sloan Digital Sky Survey and the Two Micron All Sky Survey, nine primary spectral

  14. Introduction/Motivation Background/Notation Classification Results/Future Work/References Classifying Pairs of Fuchsian Groups

    E-Print Network [OSTI]

    Broughton, S. Allen

    Introduction/Motivation Background/Notation Classification Results/Future Work Regional Meeting at University of Tucson April 2007 #12;Introduction/Motivation Background/Notation Classification Results/Future Work/References Outline 1 Introduction/Motivation Motivation 1 - extension

  15. Taxonomic Classification of Planning Decisions in Health Care: a Review of the State of the Art in OR/MS

    E-Print Network [OSTI]

    Boucherie, Richard J.

    Taxonomic Classification of Planning Decisions in Health Care: a Review of the State of the Art Classification of Planning Decisions in Health Care: a Review of the State of the Art in OR/MS 2 1. Introduction a comprehensive bibliography on operating room management articles. `ORCHID' [181] is a reference library, which

  16. Implementing very high-speed hierarchical MLP-based classification systems in real-time industrial environments

    E-Print Network [OSTI]

    Masulli, Francesco

    Implementing very high-speed hierarchical MLP-based classification systems in real-time industrial-Perceptron-based "tree architecture" even in very high-speed industrial classification problems. In particular, the paper 64 input ­ 128 hidden ­ 64 output MLP on-chip), it has been possible to build an industrial board

  17. 1997 Oxford University Press236239 Nucleic Acids Research, 1997, Vol. 25, No. 1 SCOP: a Structural Classification of Proteins

    E-Print Network [OSTI]

    : a Structural Classification of Proteins database Tim J. P. Hubbard1, Alexey G. Murzin1, Steven E. Brenner and Cyrus Chothia MRC Laboratory of Molecular Biology and 1Cambridge Centre for Protein Engineering, Hills The Structural Classification of Proteins (SCOP) data- base provides a detailed and comprehensive descrip- tion

  18. Audio Classification of Bird Species: a Statistical Manifold Approach Forrest Briggs, Raviv Raich, and Xiaoli Z. Fern

    E-Print Network [OSTI]

    Fern, Xiaoli Zhang

    of organization. Audio classification systems typically begin by extract- ing acoustic features from audio signalsAudio Classification of Bird Species: a Statistical Manifold Approach Forrest Briggs, Raviv Raich}@eecs.oregonstate.edu Abstract Our goal is to automatically identify which species of bird is present in an audio recording using

  19. 1194 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 46, NO. 5, MAY 1998 Classification of Seismic Signals by

    E-Print Network [OSTI]

    Intrator, Nathan

    1194 IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 46, NO. 5, MAY 1998 Classification of Seismic--We examine a classification problem in which seismic waveforms of natural earthquakes are to be distinguished is a hierarchy of artificial neural networks (ANN's) that are trained to classify the seismic waveforms. In order

  20. EVALUATION OF GEOMETRIC FEATURE DESCRIPTORS FOR DETECTION AND CLASSIFICATION OF LUNG NODULES IN LOW DOSE CT SCANS OF THE CHEST

    E-Print Network [OSTI]

    Louisville, University of

    EVALUATION OF GEOMETRIC FEATURE DESCRIPTORS FOR DETECTION AND CLASSIFICATION OF LUNG NODULES IN LOW descriptors, common in computer vision, for false positive reduction and for classification of lung nodules in low dose CT (LDCT) scans. A data-driven lung nodule modeling approach creates templates for common

  1. Classification of Visual and Linguistic Tasks using Eye-movement Features

    E-Print Network [OSTI]

    Keller, Frank

    . A recent study by Greene, Liu, and Wolfe (2012), however, fails to achieve accurate classification such as language processing. We extract the eye-movement features used by Greene et. al., as well as additional the visual system in ecologically valid real-world tasks, such as making a tea or washing hands; sport activ

  2. Head-mounted mobility aid for low vision using scene classification techniques M R Everingham1

    E-Print Network [OSTI]

    Everingham, Mark

    Head-mounted mobility aid for low vision using scene classification techniques M R Everingham1 , B by over 100% using the system. Keywords: Low Vision, Mobility Aids, Head Mounted Display, Object-network classifier is used to identify objects in images from a head mounted camera so that scene content

  3. NOISE DETECTION AND CLASSIFICATION IN SPEECH SIGNALS WITH BOOSTING Nobuyuki Miyake, Tetsuya Takiguchi and Yasuo Ariki

    E-Print Network [OSTI]

    Takiguchi, Tetsuya

    NOISE DETECTION AND CLASSIFICATION IN SPEECH SIGNALS WITH BOOSTING Nobuyuki Miyake, Tetsuya to detect and classify sud- den noises in speech signals. There are many sudden and short-period noises in natural environments, such as inside a car. If a speech recognition system can detect sudden noises

  4. School of Library and Information Science, Indiana University Bloomington Comparing Classification Systems using Facets

    E-Print Network [OSTI]

    Priss, Uta

    Uta Priss School of Library and Information Science, Indiana University Bloomington Comparing concept analysis and are used as 'ground' on which the underlying conceptual facets of a classification retrieval systems. #12;2. Methodology: Formal Concept Analysis and Facets Formal concept analysis (Ganter

  5. English and Chinese Bilingual Topic Aspect Classification: Exploring Similarity Measures, Optimal LSA Dimensions,

    E-Print Network [OSTI]

    Oard, Doug

    LSA Dimensions, and Centroid Correction of Translated Training Examples Yejun Wu School of Library and Information Science, Louisiana State University 267 Coates Hall, Baton Rouge, LA 70803 wuyj@lsu.edu Douglas W@umd.edu ABSTRACT This paper explores topic aspect (i.e., subtopic or facet) classification for collections

  6. Logistic Regression and Artificial Neural Networks for Classification of Ovarian Tumors

    E-Print Network [OSTI]

    Logistic Regression and Artificial Neural Networks for Classification of Ovarian Tumors C. Lu1 , J to generate and evaluate both logistic regression models and artificial neural network (ANN) models to predict, including explorative univariate and multivariate analysis, and the development of the logistic regression

  7. A CLASSIFICATION OF DUCT MODES BASED ON SURFACE WAVES Sjoerd W. Rienstra

    E-Print Network [OSTI]

    Eindhoven, Technische Universiteit

    A CLASSIFICATION OF DUCT MODES BASED ON SURFACE WAVES Sjoerd W. Rienstra Department of Mathematics For the relatively high frequencies relevant in a turbofan engine duct the modes of a lined sec- tion may be classified in two categories: genuine acoustic 3D duct modes resulting from the finiteness of the duct

  8. A CLASSIFICATION OF DUCT MODES BASED ON SURFACE WAVES Sjoerd W. Rienstra

    E-Print Network [OSTI]

    Eindhoven, Technische Universiteit

    A CLASSIFICATION OF DUCT MODES BASED ON SURFACE WAVES Sjoerd W. Rienstra Department of Mathematics For the relatively high frequencies relevant in a turbofan engine duct the modes of a lined sec­ tion may be classified in two categories: genuine acoustic 3D duct modes resulting from the finiteness of the duct

  9. Soft Classification with Gaussian Mixture Model for Clinical Dual-Energy CT Reconstructions

    E-Print Network [OSTI]

    1 Soft Classification with Gaussian Mixture Model for Clinical Dual-Energy CT Reconstructions, and Ken D. Sauer, Member, IEEE Abstract--We study the distribution of the clinical dual-energy CT (DECT material separation. Index Terms--Computed tomography (CT), dual energy, sta- tistical method, Gaussian

  10. Automated Detection and Classification of Positive vs. Negative Robot Interactions With Children With Autism

    E-Print Network [OSTI]

    Mataric, Maja J.

    Automated Detection and Classification of Positive vs. Negative Robot Interactions With Children modeling Permission to make digital or hard copies of all or part of this work for personal or classroom endeavors is to develop robot systems that can aid in the di- agnosis and treatment of ASD, providing

  11. FACT SHEET 2014 ShoreZone is a mapping and classification system that

    E-Print Network [OSTI]

    FACT SHEET 2014 PAGE 1 ShoreZone is a mapping and classification system that specializes PAGE 2 Oblique low-altitude aerial video and digital still imagery of the shoreline is collected during elevation. Units are digitized as shoreline segments in ArcGIS software, and then integrated

  12. Real Time Video Scene Detection and Classification John M. Gauch, Susan Gauch, Sylvain Bouix, Xiaolan Zhu

    E-Print Network [OSTI]

    Kansas, University of

    Real Time Video Scene Detection and Classification John M. Gauch, Susan Gauch, Sylvain Bouix (Video Indexing for Searching Over Networks) digital video library system has been developed in our to provide access to video footage within seconds of broadcast, we have developed a new pipelined digital

  13. CLASSIFICATION OF SUMMARIZED VIDEOS USING HIDDEN MARKOV MODELS ON COMPRESSED CHROMATICITY

    E-Print Network [OSTI]

    Drew, Mark S.

    1 CLASSIFICATION OF SUMMARIZED VIDEOS USING HIDDEN MARKOV MODELS ON COMPRESSED CHROMATICITY Science Simon Fraser University Vancouver, B.C., CANADA ABSTRACT As digital libraries and video databases grow, we need methods to assist us in the synthesis and analysis of digital video. Since

  14. Raster based coastal marsh classification within the Galveston Bay ecosystem, Texas 

    E-Print Network [OSTI]

    Edwards, Aron Shaun

    2009-05-15

    within each image that was classified. The locations of ROIs were recorded using a GPS prior to classification, then each was added into ENVI as data points, and each ROI polygon was digitized according to its respective pixel color. Once all of the ROI...

  15. Ruler: high-speed traffic classification and rewriting using regular expressions

    E-Print Network [OSTI]

    Bos, Herbert

    Ruler: high-speed traffic classification and rewriting using regular expressions ­ Technical Report and usefulness of the anonymised data, flexibility is essential. For this purpose, Ruler allows matching privacy and security concerns on the one hand, and the information needs of the network monitoring

  16. A Framework for Creating a Facetted Classification for Genres: Addressing Issues of Multidimensionality

    E-Print Network [OSTI]

    Crowston, Kevin

    communicative purpose and common aspects of form" (p. 543). Scholars in fields such as rhetoric and libraryA Framework for Creating a Facetted Classification for Genres: Addressing Issues aspects of genre that we recognize as fundamental: content, form, and purpose. A document's genre

  17. Classification ofAttributes and Behavior in Risk Management Using Bayesian Networks

    E-Print Network [OSTI]

    Akl, Robert

    Classification ofAttributes and Behavior in Risk Management Using Bayesian Networks Ram Dantu path from the root to the end node suitable vulnerability analysis and risk management strategies-Attack Graphs, Behavior, Risk Management and risk management with these graph transitions. For many years

  18. Crowdsourcing Multi-Label Classification Jonathan Bragg Mausam Daniel S. Weld

    E-Print Network [OSTI]

    Mausam

    Crowdsourcing Multi-Label Classification Jonathan Bragg Mausam Daniel S. Weld Department of Computer Science and Engineering University of Washington Seattle, WA 98195 {jbragg, mausam, weld summarizes (Bragg, Mausam, and Weld 2013), to appear at HCOMP 2013. References Bragg, J.; Mausam; and Weld, D

  19. JOB AND POSITION TITLE LIST VERSION 2 Classification Project 2000 Job Title Position Title EEO

    E-Print Network [OSTI]

    Cui, Yan

    JOB AND POSITION TITLE LIST VERSION 2 Classification Project 2000 Job Title Position Title EEO Administrative Supervisor II Housing Supervisor 41 Library Supervisor I Library Departmental Supervisor 41 Library Supervisor III Library Supervisor 41 Administrative Support Supervisor II Mail Services Supervisor

  20. Multi-way Hierarchic Classification of Musical Instrument Sounds Alicja A. Wieczorkowska

    E-Print Network [OSTI]

    Ras, Zbigniew W.

    Multi-way Hierarchic Classification of Musical Instrument Sounds Alicja A. Wieczorkowska Polish 28223, USA ras@uncc.edu Abstract Musical instrument sounds can be classified in various ways, depending on the instrument or articulation classifi- cation. This paper reviews a number of possible general- izations

  1. Information-Processing Architectures in Multidimensional Classification: A Validation Test of the Systems Factorial Technology

    E-Print Network [OSTI]

    Townsend, James T.

    Information-Processing Architectures in Multidimensional Classification: A Validation Test of the Systems Factorial Technology Mario Fific, Robert M. Nosofsky, and James T. Townsend Indiana University A growing methodology, known as the systems factorial technology (SFT), is being developed to diagnose

  2. PROGRESSIVE CLASSIFICATION IN THE COMPRESSED DOMAIN FOR LARGE EOS SATELLITE DATABASES1

    E-Print Network [OSTI]

    Kontoyiannis, Ioannis

    directly on remote sensing data in the compressed domain. 2. PRELIMINARIES We investigate both blockPROGRESSIVE CLASSIFICATION IN THE COMPRESSED DOMAIN FOR LARGE EOS SATELLITE DATABASES1 Vittorio, such as multispectral satellite scenes, com- pressed with wavelet-based or block-transform-based trans- formations

  3. PROGRESSIVE CLASSIFICATION IN THE COMPRESSED DOMAIN FOR LARGE EOS SATELLITE DATABASES 1

    E-Print Network [OSTI]

    Kontoyiannis, Ioannis

    PROGRESSIVE CLASSIFICATION IN THE COMPRESSED DOMAIN FOR LARGE EOS SATELLITE DATABASES 1 Vittorio, such as multispectral satellite scenes, com­ pressed with wavelet­based or block­transform­based trans­ formations to a homo­ geneous block of pixels in the original image or to a hetero­ geneous block. In the first case

  4. SVMs for Vibration-based Terrain Classification Christian Weiss, Matthias Stark, and Andreas Zell

    E-Print Network [OSTI]

    Zell, Andreas

    SVMs for Vibration-based Terrain Classification Christian Weiss, Matthias Stark, and Andreas Zell mobile robot traverses different types of ground surfaces, different types of vibrations are induced in the body of the robot. These vibrations can be used to learn a discrimination between different surfaces

  5. Discrimination and Classification of Nonstationary Time Series using the SLEX Model

    E-Print Network [OSTI]

    Discrimination and Classification of Nonstationary Time Series using the SLEX Model Hsiao-Yun Huang scheme based on the SLEX (Smooth Localized Complex EXponential) library. The SLEX library forms domains. Thus, the SLEX library has the ability to extract local spectral features of the time series

  6. Discrimination and Classification of Nonstationary Time Series Using the SLEX Model

    E-Print Network [OSTI]

    Discrimination and Classification of Nonstationary Time Series Using the SLEX Model Hsiao-Yun HUANG a discriminant scheme based on the SLEX (smooth localized complex exponential) library. The SLEX library forms domains. Thus, the SLEX library has the ability to extract local spectral features of the time series

  7. Classification of urban & industrial soils in the World Reference Base for Soil Resources

    E-Print Network [OSTI]

    Classification of urban & industrial soils in the World Reference Base for Soil Resources: Working, Industrial, Traffic and Mining Areas (SUITMA) of the International Union of Soil Science (IUSS), 09­11 July . . . . . . . . . . . . . . . . . . . . . . . . . . 3 3 Urban and industrial soils in the current WRB 4 3.1 Natural Soils

  8. Dimension Reduction in Text Classification with Support Vector Hyunsoo Kim, Peg Howland, and Haesun Park

    E-Print Network [OSTI]

    Park, Haesun

    valuable information from a huge collection of text documents available in digital libraries, knowledgeDimension Reduction in Text Classification with Support Vector Machines Hyunsoo Kim, Peg Howland, and Haesun Park #3; Department of Computer Science and Engineering, University of Minnesota, 200 Union Street

  9. Automatic classification of citation function Simone Teufel Advaith Siddharthan Dan Tidhar

    E-Print Network [OSTI]

    Siddharthan, Advaith

    of science, and in- formation sciences (library sciences) for decades (Garfield, 1979; Small, 1982; WhiteAutomatic classification of citation function Simone Teufel Advaith Siddharthan Dan Tidhar Natural- knowledgement of the use of the cited method). The automatic recognition of the rhetorical function of citations

  10. Statistical Classification of Black-Capped (Poecile Atricapillus) and Mountain Chickadee (Poecile Gambeli) Call Notes

    E-Print Network [OSTI]

    Dawson, Michael

    Statistical Classification of Black-Capped (Poecile Atricapillus) and Mountain Chickadee (Poecile. Sturdy University of Alberta Both black-capped (Poecile atricapillus) and mountain chickadees (Poecile. Black-capped and mountain non-D notes were summarized as a set of 9 features and then analyzed by linear

  11. Refining the classification of the irreps of the 1D N-Extended Supersymmetry

    E-Print Network [OSTI]

    Zhanna Kuznetsova; Francesco Toppan

    2007-05-13

    The linear finite irreducible representations of the algebra of the 1D $N$-Extended Supersymmetric Quantum Mechanics are discussed in terms of their "connectivity" (a symbol encoding information on the graphs associated to the irreps). The classification of the irreducible representations with the same fields content and different connectivity is presented up to $N\\leq 8$.

  12. Retinal Blood Vessels Segmentation Using the Radial Projection and Supervised Classification

    E-Print Network [OSTI]

    Cheung, Yiu-ming

    Retinal Blood Vessels Segmentation Using the Radial Projection and Supervised Classification Qinmu: ymc@comp.hkbu.edu.hk Abstract The low-contrast and narrow blood vessels in retinal images of improving detection of such vessels, we propose the ra- dial projection method to locate the vessel

  13. Segmentation of retinal vessels with a hysteresis binary-classification paradigm

    E-Print Network [OSTI]

    Lübeck, Universität zu

    Segmentation of retinal vessels with a hysteresis binary-classification paradigm Alexandru P Building 64 D-23562 Luebeck, Germany Abstract Vessel segmentation in photographies of the retina is needed a paradigm of hysteresis- classifier design that we apply to the problem of vessel segmentation. Before

  14. On the segmentation and classification of water in videos Pascal Mettes1

    E-Print Network [OSTI]

    Veltkamp, Remco

    On the segmentation and classification of water in videos Pascal Mettes1 , Robby T. Tan1, Utrecht, the Netherlands P.S.M.Mettes@uva.nl, r.t.tan@uu.nl, R.C.Veltkamp@uu.nl Keywords: hybrid water recognition of water entails a wide range of applications, yet little attention has been paid to solve

  15. A Hierarchical Classification Scheme to Derive Interprocess Communication in Process Networks

    E-Print Network [OSTI]

    Kienhuis, Bart

    % of the cases, we still relay on integer linear programming while in the remaining 95%, the tests presented, an ILP test has still to be applied. Thus, we introduce a hierarchical classification scheme. In only 5% of the cases to classify, we still relay on integer linear programming while in the remaining

  16. Discriminative Illumination: Per-Pixel Classification of Raw Materials based on Optimal Projections of Spectral BRDF

    E-Print Network [OSTI]

    Gu, Jinwei

    Discriminative Illumination: Per-Pixel Classification of Raw Materials based on Optimal Projections the discriminative illumination method for classifying a variety of raw materials, including metal (aluminum, alloy], mineralogy, and recycling [10]. In computer vision, we primarily focus on uncoated or unpainted raw materials

  17. Material Classification By Drilling Diana LaBelle, John Bares, Illah Nourbakhsh

    E-Print Network [OSTI]

    Material Classification By Drilling Diana LaBelle, John Bares, Illah Nourbakhsh Robotics Institute based on the physical parameters of a roof bolting drill. This paper presents our methodology, as well as early results based on drilling experiments conducted in the laboratory using a custom poured concrete

  18. Topological Transformation Approaches to Optimizing TCAM-Based Packet Classification Systems

    E-Print Network [OSTI]

    Liu, Alex X.

    schemes have been proposed to mitigate the effect of range expansion and the limitations of small capacity, large power consumption, and high heat gen- eration of TCAM-based packet classification systems. How and prefix alignment. Our techniques significantly out- perform all previous reencoding techniques

  19. SPE 159255-PP Rock Classification from Conventional Well Logs in Hydrocarbon-Bearing

    E-Print Network [OSTI]

    Torres-Verdín, Carlos

    SPE 159255-PP Rock Classification from Conventional Well Logs in Hydrocarbon-Bearing Shale Andrew C typing method for application in hydrocarbon-bearing shale (specifically source rock) reservoirs using-hoc correlations where the interpretation becomes a core matching exercise. Scale effects on measurements

  20. Stress Classification by Separation of Respiratory Modulations in Heart Rate Variability using Orthogonal Subspace Projection*

    E-Print Network [OSTI]

    classification (accuracy = 97.88%). I. INTRODUCTION The variability of the heart rate (HRV) is widely studied the tachogram, several measures, such as spectral indices, that quantify HRV are defined [1]. The power volume, independently of changes in vagal control [3], [4]. This makes that the interpretation of HRV

  1. Automated classification of A/E/C web content R. Amor & K. Xu

    E-Print Network [OSTI]

    Amor, Robert

    purely on the search terms entered by the user. This means that the web pages which are found are often search en- gine. The premise behind this approach is that it is possible to accurately identify then a user searching for content in a particular area (e.g. by specifying a classification code

  2. PPE Certification of Hazard Assessment Dept: Area: Job Classification/Task

    E-Print Network [OSTI]

    Slatton, Clint

    PPE 7 Appendix A PPE Certification of Hazard Assessment Dept: Area: Job Classification/Task: HAZARDS (Circle Hazards) Describe Specific Hazards Identify Type of PPE Required for the Hazards Eye Hazard Impact Penetration Dust Chemical Radiation Heat Bioaerosols Projectiles Head Hazard Burn Electric

  3. CLASSIFICATION USING EFFICIENT LU DECOMPOSITION IN Zille Huma Kamal, Ajay Gupta, Leszek Lilien,

    E-Print Network [OSTI]

    Gupta, Ajay

    the stimulus, which could be an enemy combat vehicle or the spread of hazardous chemicals in our air or water and tracking enemy armored vehicles headed for an army base camp. Numerous vehicles and animals can of sensornet nodes will be consuming energy to identify the category (classification) that relates to the event

  4. 3.4 PROGRESSION RULES AND DEGREE CLASSIFICATION (Third and Fourth Year Students only)

    E-Print Network [OSTI]

    Sidorov, Nikita

    3.4 PROGRESSION RULES AND DEGREE CLASSIFICATION (Third and Fourth Year Students only) All students. In the academic year 2013-2014, they will apply to all Third and Fourth Year students in the School of Mathematics in Appendix C of this Handbook. Under these rules, to proceed to the Fourth Year of the MMath degree programme

  5. TOPOLOGICAL RAMSEY SPACES FROM FRAISSE CLASSES, RAMSEY-CLASSIFICATION THEOREMS, AND INITIAL STRUCTURES IN THE

    E-Print Network [OSTI]

    Dobrinen, Natasha

    TOPOLOGICAL RAMSEY SPACES FROM FRA¨ISS´E CLASSES, RAMSEY-CLASSIFICATION THEOREMS, AND INITIAL for constructing a new class of topological Ramsey spaces. Mem- bers of such spaces are infinite sequences of products of Fra¨iss´e classes of finite relational structures satisfying the Ramsey property. We extend

  6. CLASSIFICATION OF NON-HEAT GENERATING OUTDOOR OBJECTS IN THERMAL SCENES FOR AUTONOMOUS ROBOTS

    E-Print Network [OSTI]

    Shaw, Leah B.

    Evaluation, Degree: PhD Advisor: Mark Hinders, Professor of Applied Science Abstract This dissertation describes a physics-based adaptive Bayesian pattern classification model that uses a passive thermal infrared imaging system to automatically characterize non-heat generating objects in unstructured outdoor

  7. Multinomial Logistic Regression Ensembles This article proposes a method for multiclass classification problems using ensem-

    E-Print Network [OSTI]

    Ahn, Hongshik

    -dimensional data using the logistic regression model as a base clas- sifier. CERP is similar to random subspace (Ho classification problems using ensem- bles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit

  8. Clustering-based Active Learning on Sensor Type Classification in Buildings

    E-Print Network [OSTI]

    Weimer, Westley

    study on metadata collected from over 20 different sensor types and 2,500 sen- sor streams in threeClustering-based Active Learning on Sensor Type Classification in Buildings Dezhi Hong, Hongning- lenge. Based on the large deployment of sensors in modern commercial buildings, many organizations

  9. Using Classification to Evaluate the Output of ConfidenceBased Association Rule Mining

    E-Print Network [OSTI]

    Frank, Eibe

    Using Classification to Evaluate the Output of Confidence­Based Association Rule Mining Stefan Hamilton, New Zealand {mhall, eibe}@cs.waikato.ac.nz Abstract. Association rule mining is a data mining concerning both running time and size of rule sets. 1 Introduction Association rule mining is a widely

  10. Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining

    E-Print Network [OSTI]

    Frank, Eibe

    Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining Stefan, New Zealand {mhall, eibe}@cs.waikato.ac.nz Abstract. Association rule mining is a data mining concerning both running time and size of rule sets. 1 Introduction Association rule mining is a widely

  11. Web Page Segmentation with Structured Prediction and its Application in Web Page Classification

    E-Print Network [OSTI]

    Murphy, Robert F.

    Web Page Segmentation with Structured Prediction and its Application in Web Page Classification perform Web page seg- mentation with a structured prediction approach. It formu- lates the segmentation task as a structured labeling prob- lem on a transformed Web page segmentation graph (WPS- graph). WPS

  12. Cross-Domain Sentiment Classification Using a Two-Stage Kang Liu, Jun Zhao

    E-Print Network [OSTI]

    Zong, Chengqing

    Cross-Domain Sentiment Classification Using a Two-Stage Method Kang Liu, Jun Zhao Institute knowledge between different domains. Through these common topics, the features in the source domain different domains. In the second step, we use the classifier trained on the labeled examples in the source

  13. Classification of Cabo Frio (Brazil) three-dimensional ocean features using single-slice acoustic observations

    E-Print Network [OSTI]

    Jesus, Sérgio M.

    Classification of Cabo Frio (Brazil) three-dimensional ocean features using single-slice acoustic-000 Arraial do Cabo, RJ, Brazil, {lcalado, ana.claudia}@ieapm.mar.mil.br Acoustic tomography is now a well for an instantaneous sound speed field constructed from dynamical predictions for Cabo Frio, Brazil. The results show

  14. ARF @ MediaEval 2012: Multimodal Video Classification Bogdan Ionescu1,5

    E-Print Network [OSTI]

    - poral properties of the audio signal, we propose a set of audio descriptors that are computed from the integration of various audio, vi- sual and text-based descriptors for automatic video genre classification descriptor combinations. 1.1 Audio descriptors · block-based audio (11,242 values) - to capture the tem

  15. Automated Lung Nodule Segmentation Using Dynamic Programming and EM Based Classification

    E-Print Network [OSTI]

    Ahuja, Narendra

    Automated Lung Nodule Segmentation Using Dynamic Programming and EM Based Classification Ning Xua a robust and automated algorithm to segment lung nodules in three dimensional (3D) Computed Tomography (CT nodules but also the nodules attached to lung walls and vessels. Keywords: Lung nodule, Segmentation

  16. Wearable Mobility Aid for Low Vision Using Scene Classification in a Markov Random Field Model

    E-Print Network [OSTI]

    Everingham, Mark

    Wearable Mobility Aid for Low Vision Using Scene Classification in a Markov Random Field Model to vision enhancement for people with severe visual impairments. This approach utilizes computer vision. The scene classifi- cation technique uses an artificial neural network classifier within the framework

  17. Statebased Classification of Finger Gestures from Electromyographic Signals Peter Ju PJU@MIT.EDU

    E-Print Network [OSTI]

    Kaelbling, Leslie Pack

    State­based Classification of Finger Gestures from Electromyographic Signals Peter Ju PJU Electromyographic signals may provide an im­ portant new class of user interface for consumer electronics. In order that enables a user to control portable de­ vices with simple small finger gestures. Electromyographic (EMG

  18. Coarse-grained Classification of Web Sites by Their Structural Properties

    E-Print Network [OSTI]

    Lindemann, Christoph

    Coarse-grained Classification of Web Sites by Their Structural Properties Christoph Lindemann properties which reflect the functionality of a Web site. These structural properties consider the size, the organization, the composition of URLs, and the link structure of Web sites. Opposed to previous work, we

  19. Fusion de paramtres pour une classification automatique parole/musique robuste

    E-Print Network [OSTI]

    Pinquier, Julien

    RECHERCHE Fusion de paramètres pour une classification automatique parole/musique robuste corpus est utilisé afin de vérifier la robustesse des paramètres et du sys- tème de fusion proposé. Cette with the classical 4Hz modulation energy. The relevance of these features is studied in a first experiment based

  20. M-FISH IMAGE REGISTRATION AND CLASSIFICATION Yu-Ping Wang

    E-Print Network [OSTI]

    Poirazi, Yiota

    M-FISH IMAGE REGISTRATION AND CLASSIFICATION Yu-Ping Wang School of Computing and Engineering hybridization (M-FISH) imaging is a recently developed cytogenetic technique for cancer diagnosis and research on genetic disorders. By simultaneously viewing the multiple-labeled specimens in different color channels, M-FISH

  1. Classification of Sunspot Groups Using SOHO/MDI Magnetogram and White-Light

    E-Print Network [OSTI]

    Wolfe, Patrick J.

    Classification of Sunspot Groups Using SOHO/MDI Magnetogram and White-Light Images Tuesday Data (or, what I currently have available) · 1038 white-light images from May 19, 1996 through December procedure will be developed using SOHO/MDI magnetogram and white- light images. SOHO/MDI white-light image

  2. Anal. Chem. 1994,66,168-176 Classification of Countercurrent Chromatography Solvent

    E-Print Network [OSTI]

    Wesfreid, José Eduardo

    Anal. Chem. 1994,66,168-176 Classification of Countercurrent Chromatography Solvent Systems Cedex 05, France Solvent systems used for countercurrent chromatography (CCC) have been classified in a countercurrentchromatograph. To achievegoodretentionof one phase of a solvent system when the other one is pumped inthecolumn

  3. An Incremental Parallel Particle Swarm Approach for Classification Rule Discovery from Dynamic Data

    E-Print Network [OSTI]

    Lee, WonSook

    , we propose a novel incremental parallel Particle Swarm Optimization (PSO) approach for classification to extract the rules from data chunks, we introduce an incremental PSO algorithm in which the previously knowledge. To support the parallelism, we assign a PSO thread for each data chunk. As soon as all the PSO

  4. Pe t al, (2009) ``Classification of Patte rns of EEG Synchronization for

    E-Print Network [OSTI]

    LeCun, Yann

    2009-01-01

    Mirowski Pe t al, (2009) ``Classification of Patte rns of EEG Synchronization for Se izure Pre Processin g #12; Mirowski P e al, (2009) ``Classifica ion of Pae rns of EEG Synchroniza ion for Se izure ive ime poin s, o form pae rns. Pa ie n ­spe cific machine le arning­base d classifie rs (suppor

  5. Next Generation Nuclear Plant Structures, Systems, and Components Safety Classification White Paper

    SciTech Connect (OSTI)

    Pete Jordan

    2010-09-01

    This white paper outlines the relevant regulatory policy and guidance for a risk-informed approach for establishing the safety classification of Structures, Systems, and Components (SSCs) for the Next Generation Nuclear Plant and sets forth certain facts for review and discussion in order facilitate an effective submittal leading to an NGNP Combined Operating License application under 10 CFR 52.

  6. Knowledge Acqulsition= Classification of Terms in a thesaurus from~a Corpus

    E-Print Network [OSTI]

    Knowledge Acqulsition= Classification of Terms in a thesaurus from~a Corpus STA Jean-David EDF, discipline or branch of an existing thesaurus. This is the first step in positioning a term extracted from a corpus in the structure of a thesaurus (generic relations, synonymy relations ..). This is an important

  7. CoConut: Co-Classification with Output Space Regularization Sameh Khamis Christoph H. Lampert

    E-Print Network [OSTI]

    Daume III, Hal

    CoConut: Co-Classification with Output Space Regularization Sameh Khamis Christoph H. Lampert a combination of discrete optimization and Lagrangian Relaxation Approach We evaluated CoConut on six different datasets: four image and two network datasets We used the features provided by the original authors CoConut

  8. uRule: A Rule-based Classification System for Uncertain Data

    E-Print Network [OSTI]

    Tu, Yicheng

    uRule: A Rule-based Classification System for Uncertain Data Biao Qin, Yuni Xia, Rakesh Sathyesh. In this demo,we will show uRule, a new rule-based clas- sification and prediction system for uncertain data measures are computed considering uncertain data intervals and probability distribution functions. Based

  9. Automatic Classification of Image Registration Steve Oldridge, Gregor Miller, and Sidney Fels

    E-Print Network [OSTI]

    British Columbia, University of

    Automatic Classification of Image Registration Problems Steve Oldridge, Gregor Miller, and Sidney,gregor,ssfels}@ece.ubc.ca http://www.ece.ubc.ca/~hct Abstract. This paper introduces a system that automatically classifies and accuracy of automatic registration techniques. Key words: Image Registration, Computational Photography

  10. Bag-of-Visual-Words Models for Adult Image Classification and Filtering Thomas Deselaers1

    E-Print Network [OSTI]

    Deselaers, Thomas

    types of images are allowed. In the literature, different porn image filtering tech- niques were features for porn image classification are pre- sented and used in a retrieval/nearest neighbour clas model to discriminate between different classes of content-type. 2 Porn Image Identification For porn

  11. THE UNIVERSITY OF OKLAHOMA PETITION FOR IN-STATE TUITION CLASSIFICATION

    E-Print Network [OSTI]

    Oklahoma, University of

    THE UNIVERSITY OF OKLAHOMA PETITION FOR IN-STATE TUITION CLASSIFICATION Office of Admissions 1000 from an Oklahoma high school? YES NO NAME AND LOCATION OF HIGH SCHOOL Have you attended a college or university in Oklahoma during the past two years? YES NO IF YES, COMPLETE AREA BELOW. LIST INSTITUTIONS

  12. High-Level Fusion of Depth and Intensity for Pedestrian Classification

    E-Print Network [OSTI]

    Gavrila, Dariu M.

    High-Level Fusion of Depth and Intensity for Pedestrian Classification Marcus Rohrbach1,3 , Markus. This paper presents a novel approach to pedestrian classi- fication which involves a high-level fusion pedestrians and non-pedestrians. We refrain from the construction of a joint feature space, but instead employ

  13. Pedestrian Detection for Driving Assistance Systems: Single-frame Classification and System Level Performance

    E-Print Network [OSTI]

    Shashua, Amnon

    Pedestrian Detection for Driving Assistance Systems: Single-frame Classification and System Level breakdown of a monocular pedestrian detection system. We describe in detail our approach for single describes a monocular visual processing sys- tem for pedestrian detection targeting the niche of driving

  14. Classification of Duty Pulses Affecting Energy Storage Systems in Vehicular Applications

    E-Print Network [OSTI]

    Boyer, Edmond

    Classification of Duty Pulses Affecting Energy Storage Systems in Vehicular Applications Arnaud, the energy storage system (ESS) remains the most expensive and the most critical part among the entire in real-world conditions or blindly oversize the energy storage system in order to compensate for reduced

  15. Multi-class Biomedical Term Recognition and Classification Using Search Raul Rodriguez-Esteban

    E-Print Network [OSTI]

    Baeza-Yates, Ricardo

    Multi-class Biomedical Term Recognition and Classification Using Search Engines Raul Rodriguez-Esteban Columbia University, USA Abstract: The talk will have two parts: (1) Automatic curation of biomedical text mined data. Biomedical text mined data has a degree of quality sometimes unsuitable for real

  16. A simple classification tool for single-trial analysis of ERP components Christoph Bandt1

    E-Print Network [OSTI]

    Bandt, Christoph

    A simple classification tool for single-trial analysis of ERP components Christoph Bandt1 , Mathias: Single trial analysis of ERP components Corresponding author: Prof. Christoph Bandt Institute-mail: bandt@uni-greifswald.de #12;Single trial analysis of ERP components 2 Abstract Event-related potentials

  17. Fuzzy Classification of Genome Sequences Prior to Assembly Based on Similarity Measures*

    E-Print Network [OSTI]

    Nicolescu, Monica

    Fuzzy Classification of Genome Sequences Prior to Assembly Based on Similarity Measures* Sara number: 0447416). Abstract - Nucleotide sequencing of genomic data is an important step towards building into the overall genome. However, the existence of insertions, deletions and substitutions can complicate

  18. SEMI-AUTOMATIC SUPERVISED CLASSIFICATION OF MINERALS FROM X-RAY MAPPING IMAGES

    E-Print Network [OSTI]

    in siliciclastic and car- bonate rocks. Twelve chemical elements are mapped from thin sections by energy dispersive or energy dispersive spectroscopy (EDS) in a scanning electron microscope (SEM). Here, an x-ray spectrum, long image acquisition times has made use of EDS images for mineral classification difficult. #12;New

  19. Term Graph Model for Text Classification Wei Wang, Diep Bich Do, and Xuemin Lin

    E-Print Network [OSTI]

    Lin, Xuemin

    classification methods (and text mining methods at large) are based on representing the documents using the tra, text mining has become one of the most popular research areas in data mining, due to the rapid growth and evolution of digital text documents, such as Web pages, office documents, and E-mails. As the demand

  20. CLASSIFICATION OF HUMAN ACTIONS INTO DYNAMICS BASED PRIMITIVES WITH APPLICATION TO DRAWING

    E-Print Network [OSTI]

    Murray, Richard M.

    video- games and animation where virtual human motion is based on the learning and description of realCLASSIFICATION OF HUMAN ACTIONS INTO DYNAMICS BASED PRIMITIVES WITH APPLICATION TO DRAWING TASKS D Institute of Technology Pasadena, CA 91125 Abstract: We develop the study of primitives of human motion