National Library of Energy BETA

Sample records for knowledge network cdkn

  1. Climate and Development Knowledge Network (CDKN) | Open Energy...

    Open Energy Info (EERE)

    Mozambique-Accrediation of NIE Nepal-Sectoral Climate Impacts Economic Assessment Pakistan-Technical Assistance to PDMA Punjab in Incorporating Climate Compatibility...

  2. Climate and Development Knowledge Network (CDKN) Feed | Open...

    Open Energy Info (EERE)

    Tejerina of Servicios Ambientales highlights the challenges, enabling factors, lessons learned and implications for climate compatible development - as illustrated by a project to...

  3. United Nations Energy Knowledge Network (UN-Energy) | Open Energy...

    Open Energy Info (EERE)

    Energy Knowledge Network (UN-Energy) Jump to: navigation, search Logo: United Nations Energy Knowledge Network (UN-Energy) Name: United Nations Energy Knowledge Network (UN-Energy)...

  4. CDKN-CARICOM-Trinidad and Tobago-A Regional Implementation Plan...

    Open Energy Info (EERE)

    CDKN-CARICOM-Trinidad and Tobago-A Regional Implementation Plan for CARICOM's Regional Climate Change Resilience Framework Redirect page Jump to: navigation, search REDIRECT...

  5. Abnormal event identification in nuclear power plants using a neural network and knowledge processing

    SciTech Connect (OSTI)

    Ohga, Yukiharu; Seki, Hiroshi (Hitachi, Ltd. Energy Research Lab., Ibarakiken (Japan))

    1993-02-01

    The combination of a neural network and knowledge processing have been used to identify abnormal events that cause a reactor to scram in a nuclear power plant. The neural network recognizes the abnormal event from the change pattern of analog data for state variables, and this result is confirmed from digital data using a knowledge base of plant status when each event occurs. The event identification method is tested using test data based on simulated results of a transient analysis program for boiling water reactors. It is confirmed that a neural network can identify an event in which it has been trained even when the plant conditions, such as fuel burnup, differ from those used in the training and when the analog data contain white noise. The network does not mistakenly identify the nontrained event as a trained one. The method is feasible for event identification, and knowledge processing improves the reliability of the identification.

  6. Designing optimal transportation networks: a knowledge-based computer-aided multicriteria approach

    SciTech Connect (OSTI)

    Tung, S.I.

    1986-01-01

    The dissertation investigates the applicability of using knowledge-based expert systems (KBES) approach to solve the single-mode (automobile), fixed-demand, discrete, multicriteria, equilibrium transportation-network-design problem. Previous works on this problem has found that mathematical programming method perform well on small networks with only one objective. Needed is a solution technique that can be used on large networks having multiple, conflicting criteria with different relative importance weights. The KBES approach developed in this dissertation represents a new way to solve network design problems. The development of an expert system involves three major tasks: knowledge acquisition, knowledge representation, and testing. For knowledge acquisition, a computer aided network design/evaluation model (UFOS) was developed to explore the design space. This study is limited to the problem of designing an optimal transportation network by adding and deleting capacity increments to/from any link in the network. Three weighted criteria were adopted for use in evaluating each design alternative: cost, average V/C ratio, and average travel time.

  7. System and method for knowledge based matching of users in a network

    DOE Patents [OSTI]

    Verspoor, Cornelia Maria; Sims, Benjamin Hayden; Ambrosiano, John Joseph; Cleland, Timothy James

    2011-04-26

    A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

  8. Low Emission Development Strategies: The Role of Networks and Knowledge Platforms

    SciTech Connect (OSTI)

    Benioff, Ron; Bazilian, Morgan; Cox, Sadie; Uriarte, Caroline; Kecman, Ana; De Simone, Giuseppe; Kitaoka, Kazuki; Ploutakhina, Marina; Radka, M.

    2013-09-01

    Considerable effort has been made to address the transition to low-carbon economy. A key focus of these efforts has been on the development of national low-emissions developments strategies (LEDS). One enabler of these plans is the existence of well-functioning national, regional and international low-emission development networks and knowledge platforms. To better understand the role of LEDS, weexamine this area in relation to network theory. We present a review of strengths and weaknesses of existing LEDS networks that builds on the findings of a study conducted by the Coordinated Low Emission Assistance Network (CLEAN). Based on the insights from theory and a mapping of the climate-related network space, we identify opportunities for further refinement of LEDS networks.

  9. CDKN2B expression and subcutaneous adipose tissue expandability: Possible influence of the 9p21 atherosclerosis locus

    SciTech Connect (OSTI)

    Svensson, Per-Arne; Wahlstrand, Björn; Olsson, Maja; Froguel, Philippe; Falchi, Mario; Bergman, Richard N.; McTernan, Philip G.; Hedner, Thomas; Carlsson, Lena M.S.; Jacobson, Peter

    2014-04-18

    Highlights: • The tumor suppressor gene CDKN2B is highly expressed in human adipose tissue. • Risk alleles at the 9p21 locus modify CDKN2B expression in a BMI-dependent fashion. • There is an inverse relationship between expression of CDKN2B and adipogenic genes. • CDKN2B expression influences to postprandial triacylglycerol clearance. • CDKN2B expression in adipose tissue is linked to markers of hepatic steatosis. - Abstract: Risk alleles within a gene desert at the 9p21 locus constitute the most prevalent genetic determinant of cardiovascular disease. Previous research has demonstrated that 9p21 risk variants influence gene expression in vascular tissues, yet the biological mechanisms by which this would mediate atherosclerosis merits further investigation. To investigate possible influences of this locus on other tissues, we explored expression patterns of 9p21-regulated genes in a panel of multiple human tissues and found that the tumor suppressor CDKN2B was highly expressed in subcutaneous adipose tissue (SAT). CDKN2B expression was regulated by obesity status, and this effect was stronger in carriers of 9p21 risk alleles. Covariation between expression of CDKN2B and genes implemented in adipogenesis was consistent with an inhibitory effect of CDKN2B on SAT proliferation. Moreover, studies of postprandial triacylglycerol clearance indicated that CDKN2B is involved in down-regulation of SAT fatty acid trafficking. CDKN2B expression in SAT correlated with indicators of ectopic fat accumulation, including markers of hepatic steatosis. Among genes regulated by 9p21 risk variants, CDKN2B appears to play a significant role in the regulation of SAT expandability, which is a strong determinant of lipotoxicity and therefore might contribute to the development of atherosclerosis.

  10. The Network of Excellence 'Knowledge-based Multicomponent Materials for Durable and Safe Performance'

    SciTech Connect (OSTI)

    Moreno, Arnaldo

    2008-02-15

    The Network of Excellence 'Knowledge-based Multicomponent Materials for Durable and Safe Performance' (KMM-NoE) consists of 36 institutional partners from 10 countries representing leading European research institutes and university departments (25), small and medium enterprises, SMEs (5) and large industry (7) in the field of knowledge-based multicomponent materials (KMM), more specifically in intermetallics, metal-ceramic composites, functionally graded materials and thin layers. The main goal of the KMM-NoE (currently funded by the European Commission) is to mobilise and concentrate the fragmented scientific potential in the KMM field to create a durable and efficient organism capable of developing leading-edge research while spreading the accumulated knowledge outside the Network and enhancing the technological skills of the related industries. The long-term strategic goal of the KMM-NoE is to establish a self-supporting pan-European institution in the field of knowledge-based multicomponent materials--KMM Virtual Institute (KMM-VIN). It will combine industry oriented research with educational and training activities. The KMM Virtual Institute will be founded on three main pillars: KMM European Competence Centre, KMM Integrated Post-Graduate School, KMM Mobility Programme. The KMM-NoE is coordinated by the Institute of Fundamental Technological Research (IPPT) of the Polish Academy of Sciences, Warsaw, Poland.

  11. Prior knowledge driven Granger causality analysis on gene regulatory network discovery

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Yao, Shun; Yoo, Shinjae; Yu, Dantong

    2015-08-28

    Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

  12. miR-4295 promotes cell proliferation and invasion in anaplastic thyroid carcinoma via CDKN1A

    SciTech Connect (OSTI)

    Shao, Mingchen; Geng, Yiwei; Lu, Peng; Xi, Ying; Wei, Sidong; Wang, Liuxing; Fan, Qingxia; Ma, Wang

    2015-09-04

    MicroRNAs (miRNAs) play important roles in the pathogenesis of many types of cancers by negatively regulating gene expression at posttranscriptional level. However, the role of microRNAs in anaplastic thyroid carcinoma (ATC), has remained elusive. Here, we identified that miR-4295 promotes ATC cell proliferation by negatively regulates its target gene CDKN1A. In ATC cell lines, CCK-8 proliferation assay indicated that the cell proliferation was promoted by miR-4295, while miR-4295 inhibitor significantly inhibited the cell proliferation. Transwell assay showed that miR-4295 mimics significantly promoted the migration and invasion of ATC cells, whereas miR-4295 inhibitors significantly reduced cell migration and invasion. luciferase assays confirmed that miR-4295 directly bound to the 3'untranslated region of CDKN1A, and western blotting showed that miR-4295 suppressed the expression of CDKN1A at the protein levels. This study indicated that miR-4295 negatively regulates CDKN1A and promotes proliferation and invasion of ATC cell lines. Thus, miR-4295 may represent a potential therapeutic target for ATC intervention. - Highlights: • miR-4295 mimics promote the proliferation and invasion of ATC cells. • miR-4295 inhibitors inhibit the proliferation and invasion of ATC cells. • miR-4295 targets 3′UTR of CDKN1A in ATC cells. • miR-4295 negatively regulates CDKN1A in ATC cells.

  13. German Aerospace Center (DLR)Feed | Open Energy Information

    Open Energy Info (EERE)

    (CER) The Children's Investment Fund Foundation (CIFF) Climate and Development Knowledge Network (CDKN) Climate Technology Initiative (CTI) ClimateWorks Foundation Coalition...

  14. Zimbabwe-Terms of Reference for Future LEDS | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Name Zimbabwe-Terms of Reference for Future LEDS AgencyCompany Organization Climate and Development Knowledge Network (CDKN), United Kingdom...

  15. WEF-Green Growth Partnerships Initiative | Open Energy Information

    Open Energy Info (EERE)

    World Economic Forum Partner Global Green Growth Institute, Climate and Development Knowledge Network (CDKN), United Kingdom Government Sector Energy, Land, Climate Topics...

  16. Ghana-Support for Future National Climate Change Policy Framework...

    Open Energy Info (EERE)

    Jump to: navigation, search Name CDKN-Ghana-Support for Future National Climate Change Policy Framework AgencyCompany Organization Climate and Development Knowledge Network...

  17. Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ESnet About ESnet Our Mission The Network ESnet History Governance & Policies Career Opportunities ESnet Staff & Org Chart Contact Us Contact Us Technical Assistance: 1 800-33-ESnet (Inside US) 1 800-333-7638 (Inside US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net About ESnet A Platform for Science Discovery The Energy Sciences Network (ESnet) is a high-performance, unclassified network built to

  18. Mozambique-Accrediation of NIE | Open Energy Information

    Open Energy Info (EERE)

    Knowledge Network1 CDKN is providing support to the Government of Mozambique (GoM) to work towards the accreditation of the Fundo do Ambiente (FUNAB) as an NIE. If successful...

  19. The Bioenergy Knowledge Discovery Framework (KDF) | Department...

    Office of Environmental Management (EM)

    The KDF harnesses Web 2.0 and social networking technologies to build a collective knowledge system that facilitates collaborative production, integration, and analysis of ...

  20. Network Maps

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Network Maps Engineering Services The Network Network Maps Network Traffic Volume Historical Network Maps Network Facts & Stats Connected Sites Peering Connections ESnet...

  1. Bioenergy Knowledge Discovery Framework (KDF) Fact Sheet

    SciTech Connect (OSTI)

    2013-07-29

    The Bioenergy Knowledge Discovery Framework (KDF) is an online collaboration and geospatial analysis tool that allows researchers, policymakers, and investors to explore and engage the latest bioenergy research. This publication describes how the KDF harnesses Web 2.0 and social networking technologies to build a collective knowledge system that facilitates collaborative production, integration, and analysis of bioenergy-related information.

  2. Seven Deadliest Network Attacks

    SciTech Connect (OSTI)

    Prowell, Stacy J; Borkin, Michael; Kraus, Robert

    2010-05-01

    Do you need to keep up with the latest hacks, attacks, and exploits effecting networks? Then you need "Seven Deadliest Network Attacks". This book pinpoints the most dangerous hacks and exploits specific to networks, laying out the anatomy of these attacks including how to make your system more secure. You will discover the best ways to defend against these vicious hacks with step-by-step instruction and learn techniques to make your computer and network impenetrable. Attacks detailed in this book include: Denial of Service; War Dialing; Penetration 'Testing'; Protocol Tunneling; Spanning Tree Attacks; Man-in-the-Middle; and, Password Replay. Knowledge is power, find out about the most dominant attacks currently waging war on computers and networks globally. Discover the best ways to defend against these vicious attacks; step-by-step instruction shows you how. Institute countermeasures, don't be caught defenseless again, learn techniques to make your computer and network impenetrable.

  3. ARM - Traditional Knowledge

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    HomeroomTraditional Knowledge Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Traditional Knowledge An elder from Nauru is interviewed for the TWP kiosks. An elder from Nauru is interviewed for the TWP kiosks. Traditional knowledge can be defined as a cumulative body of knowledge and

  4. Network Activity

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Statistics Network Activity Network Activity PDSF Network Uplinks to NERSC (dual 10 Gbps) NERSC Uplink to ESnet Last edited: 2011-03-31 22:20:59...

  5. The Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Network Engineering Services The Network Network Maps Network Facts & Stats Connected Sites Peering Connections ESnet Site Availabiliy OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Contact Us Technical Assistance: 1 800-33-ESnet (Inside US) 1 800-333-7638 (Inside US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net The Network A Nationwide Platform for Science Discovery The

  6. New York Network Members Join Forces to Create Green Jobs

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network member Rural Ulster Preservation Company (RUPCO) is using its knowledge of the housing market to create energy efficiency contracting jobs with fellow...

  7. Joint Implementation Network (JIN) | Open Energy Information

    Open Energy Info (EERE)

    2.2 JIN Programs 3 References About Joint Implementation Network (JIN) was established in 1995 as knowledge centre for climate change policy issues in general and the concept of...

  8. Spatial Knowledge Capture Library

    Energy Science and Technology Software Center (OSTI)

    2005-05-16

    The Spatial Knowledge Capture Library is a set of algorithms to capture regularities in shapes and trajectories through space and time. We have applied Spatial Knowledge Capture to model the actions of human experts in spatial domains, such as an AWACS Weapons Director task simulation. The library constructs a model to predict the expert’s response to sets of changing cues, such as the movements and actions of adversaries on a battlefield, The library includes amore » highly configurable feature extraction functionality, which supports rapid experimentation to discover causative factors. We use k-medoid clustering to group similar episodes of behavior, and construct a Markov model of system state transitions induced by agents’ actions.« less

  9. Velo: Knowledge and Tool

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Velo: Knowledge and Tool Integration for Collaborative Scientific Projects Carina Lansing, Kerstin Kleese van Dam 1 Scientific Project Life Cycle 2 Conceptual Modeling Simulation Execution Visualization & Analytics Data Input Data Uncertainty Quantification Validation, Diagnostics, & Monitoring Reference Data / Data Mining Challenges to Scientists ! Has someone done something similar before? Is there a good example? ! How do I find the information I need? ! What are the best tools to

  10. Nothing But Networking for Residential Network Members

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Peer Exchange Call: Nothing But Networking for Residential Network Members, Call Slides and Discussion Summary, March 12, 2015.

  11. Robust automated knowledge capture.

    SciTech Connect (OSTI)

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt

    2011-10-01

    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  12. Sentient networks

    SciTech Connect (OSTI)

    Chapline, G.

    1998-03-01

    The engineering problems of constructing autonomous networks of sensors and data processors that can provide alerts for dangerous situations provide a new context for debating the question whether man-made systems can emulate the cognitive capabilities of the mammalian brain. In this paper we consider the question whether a distributed network of sensors and data processors can form ``perceptions`` based on sensory data. Because sensory data can have exponentially many explanations, the use of a central data processor to analyze the outputs from a large ensemble of sensors will in general introduce unacceptable latencies for responding to dangerous situations. A better idea is to use a distributed ``Helmholtz machine`` architecture in which the sensors are connected to a network of simple processors, and the collective state of the network as a whole provides an explanation for the sensory data. In general communication within such a network will require time division multiplexing, which opens the door to the possibility that with certain refinements to the Helmholtz machine architecture it may be possible to build sensor networks that exhibit a form of artificial consciousness.

  13. Passport to Knowledge | Open Energy Information

    Open Energy Info (EERE)

    Passport to Knowledge Jump to: navigation, search Logo: Passport to Knowledge Name: Passport to Knowledge Place: Morristown, New Jersey Region: Northeast - NY NJ CT PA Area...

  14. Network Policies

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Acceptable Use Policy About ESnet Our Mission The Network ESnet History Governance & Policies ESnet Policy Board ESCC Acceptable Use Policy Data Privacy Policy Facility Data Policy Career Opportunities ESnet Staff & Org Chart Contact Us Contact Us Technical Assistance: 1 800-33-ESnet (Inside US) 1 800-333-7638 (Inside US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net ESnet Acceptable Use Policy The

  15. Historical Network Maps

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Network Maps Network Traffic Volume Historical Network Maps Network Facts & Stats Connected Sites Peering Connections ESnet Site Availabiliy OSCARS Fasterdata IPv6 Network Network Performance Tools The ESnet Engineering Team Network R&D Software-Defined Networking (SDN) Experimental Network Testbeds Performance (perfSONAR) Software & Tools Development Data for Researchers Partnerships Publications Workshops Science Engagement Move your data Programs & Workshops Science

  16. Nothing But Networking for Residential Network Members | Department...

    Energy Savers [EERE]

    Nothing But Networking for Residential Network Members Nothing But Networking for Residential Network Members Better Buildings Residential Network Peer Exchange Call: Nothing But ...

  17. Knowledge Signatures for Information Integration

    SciTech Connect (OSTI)

    Thomson, Judi; Cowell, Andrew J.; Paulson, Patrick R.; Butner, R. Scott; Whiting, Mark A.

    2003-10-25

    This paper introduces the notion of a knowledge signature: a concise, ontologically-driven representation of the semantic characteristics of data. Knowledge signatures provide programmatic access to data semantics while allowing comparisons to be made across different types of data such as text, images or video, enabling efficient, automated information integration. Through observation, which determines the degree of association between data and ontological concepts, and refinement, which uses the axioms and structure of the domain ontology to place the signature more accurately within the context of the domain, knowledge signatures can be created. A comparison of such signatures for two different pieces of data results in a measure of their semantic separation. This paper discusses the definition of knowledge signatures along with the design and prototype implementation of a knowledge signature generator.

  18. HPSS Yearly Network Traffic

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    HPSS Yearly Network Traffic HPSS Yearly Network Traffic Yearly Summary of IO Traffic Between Storage and Network Destinations These bar charts show the total transfer traffic for...

  19. Feedstock Logistics Datasets from DOE's Bioenergy Knowledge Discovery Framework (KDF)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. Holdings include datasets, models, and maps. [from https://www.bioenergykdf.net/content/about

  20. Biofuel Production Datasets from DOE's Bioenergy Knowledge Discovery Framework (KDF)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about]

    Holdings include datasets, models, and maps and the collections arel growing due to both DOE contributions and data uploads from individuals.

  1. Biofuel Distribution Datasets from the Bioenergy Knowledge Discovery Framework

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about] Holdings include datasets, models, and maps and the collections are growing due to both DOE contributions and individuals' data uploads.

  2. Feedstock Production Datasets from the Bioenergy Knowledge Discovery Framework

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about] Holdings include datasets, models, and maps and the collections are growing due to both DOE contributions and data uploads from individuals.

  3. Computationally Efficient Neural Network Intrusion Security Awareness

    SciTech Connect (OSTI)

    Todd Vollmer; Milos Manic

    2009-08-01

    An enhanced version of an algorithm to provide anomaly based intrusion detection alerts for cyber security state awareness is detailed. A unique aspect is the training of an error back-propagation neural network with intrusion detection rule features to provide a recognition basis. Network packet details are subsequently provided to the trained network to produce a classification. This leverages rule knowledge sets to produce classifications for anomaly based systems. Several test cases executed on ICMP protocol revealed a 60% identification rate of true positives. This rate matched the previous work, but 70% less memory was used and the run time was reduced to less than 1 second from 37 seconds.

  4. Wellbore Integrity Network

    SciTech Connect (OSTI)

    Carey, James W.; Bachu, Stefan

    2012-06-21

    In this presentation, we review the current state of knowledge on wellbore integrity as developed in the IEA Greenhouse Gas Programme's Wellbore Integrity Network. Wells are one of the primary risks to the successful implementation of CO{sub 2} storage programs. Experimental studies show that wellbore materials react with CO{sub 2} (carbonation of cement and corrosion of steel) but the impact on zonal isolation is unclear. Field studies of wells in CO{sub 2}-bearing fields show that CO{sub 2} does migrate external to casing. However, rates and amounts of CO{sub 2} have not been quantified. At the decade time scale, wellbore integrity is driven by construction quality and geomechanical processes. Over longer time-scales (> 100 years), chemical processes (cement degradation and corrosion) become more important, but competing geomechanical processes may preserve wellbore integrity.

  5. NetworkX

    Energy Science and Technology Software Center (OSTI)

    2004-05-17

    NetworkX (abbreviated NX in the software and documentation) is a package for studying network structure using graph theory.

  6. Deactivation & Decommissioning Knowledge Management Information...

    Energy Savers [EERE]

    The D&D Knowledge Management Information Tool (KM-IT) is a web-based information tool to ... The D&D KM-IT has been developed through the application of state-of-the-art web ...

  7. Vector Network Analysis

    Energy Science and Technology Software Center (OSTI)

    1997-10-20

    Vector network analyzers are a convenient way to measure scattering parameters of a variety of microwave devices. However, these instruments, unlike oscilloscopes for example, require a relatively high degree of user knowledge and expertise. Due to the complexity of the instrument and of the calibration process, there are many ways in which an incorrect measurement may be produced. The Microwave Project, which is part of Sandia National Laboratories Primary Standards Laboratory, routinely uses check standardsmore » to verify that the network analyzer is operating properly. In the past, these measurements were recorded manually and, sometimes, interpretation of the results was problematic. To aid our measurement assurance process, a software program was developed to automatically measure a check standard and compare the new measurements with an historical database of measurements of the same device. The program acquires new measurement data from selected check standards, plots the new data against the mean and standard deviation of prior data for the same check standard, and updates the database files for the check standard. The program is entirely menu-driven requiring little additional work by the user.« less

  8. Central Characterization Program (CCP), Acceptable Knowledge...

    Office of Environmental Management (EM)

    , Acceptable Knowledge Summary Report for Los Alamos National Laboratory, TA-55 Mixed Transuranic Waste Streams Central Characterization Program (CCP), Acceptable Knowledge Summary...

  9. UCEAO: Energy Knowledge Bank | Open Energy Information

    Open Energy Info (EERE)

    UCEAO: Energy Knowledge Bank Jump to: navigation, search Name: UCEAO: Energy Knowledge Bank Place: Ohio Website: knowledgebank.uso.edu References: University Clean Energy Alliance...

  10. Groundwater Monitoring Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Groundwater Monitoring Network Groundwater Monitoring Network The network includes 92 natural sources, 102 regional aquifer wells, 41 intermediate-depth wells and springs, and 67 wells in alluvium in canyons. August 1, 2013 Map of LANL's groundwater monitoring network Map of LANL's groundwater monitoring network

  11. Improving Cyber-Security of Smart Grid Systems via Anomaly Detection and Linguistic Domain Knowledge

    SciTech Connect (OSTI)

    Ondrej Linda; Todd Vollmer; Milos Manic

    2012-08-01

    The planned large scale deployment of smart grid network devices will generate a large amount of information exchanged over various types of communication networks. The implementation of these critical systems will require appropriate cyber-security measures. A network anomaly detection solution is considered in this work. In common network architectures multiple communications streams are simultaneously present, making it difficult to build an anomaly detection solution for the entire system. In addition, common anomaly detection algorithms require specification of a sensitivity threshold, which inevitably leads to a tradeoff between false positives and false negatives rates. In order to alleviate these issues, this paper proposes a novel anomaly detection architecture. The designed system applies the previously developed network security cyber-sensor method to individual selected communication streams allowing for learning accurate normal network behavior models. Furthermore, the developed system dynamically adjusts the sensitivity threshold of each anomaly detection algorithm based on domain knowledge about the specific network system. It is proposed to model this domain knowledge using Interval Type-2 Fuzzy Logic rules, which linguistically describe the relationship between various features of the network communication and the possibility of a cyber attack. The proposed method was tested on experimental smart grid system demonstrating enhanced cyber-security.

  12. ESnet Network Operating System (ENOS)

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Experimental Network Testbeds Performance (perfSONAR) Software & Tools Development Data ... Blog ESnet Live Home Network R&D Software-Defined Networking (SDN) ENOS Network ...

  13. Knowledge information management toolkit and method

    DOE Patents [OSTI]

    Hempstead, Antoinette R.; Brown, Kenneth L.

    2006-08-15

    A system is provided for managing user entry and/or modification of knowledge information into a knowledge base file having an integrator support component and a data source access support component. The system includes processing circuitry, memory, a user interface, and a knowledge base toolkit. The memory communicates with the processing circuitry and is configured to store at least one knowledge base. The user interface communicates with the processing circuitry and is configured for user entry and/or modification of knowledge pieces within a knowledge base. The knowledge base toolkit is configured for converting knowledge in at least one knowledge base from a first knowledge base form into a second knowledge base form. A method is also provided.

  14. Interconnection networks

    DOE Patents [OSTI]

    Faber, V.; Moore, J.W.

    1988-06-20

    A network of interconnected processors is formed from a vertex symmetric graph selected from graphs GAMMA/sub d/(k) with degree d, diameter k, and (d + 1)exclamation/ (d /minus/ k + 1)exclamation processors for each d greater than or equal to k and GAMMA/sub d/(k, /minus/1) with degree d /minus/ 1, diameter k + 1, and (d + 1)exclamation/(d /minus/ k + 1)exclamation processors for each d greater than or equal to k greater than or equal to 4. Each processor has an address formed by one of the permutations from a predetermined sequence of letters chosen a selected number of letters at a time, and an extended address formed by appending to the address the remaining ones of the predetermined sequence of letters. A plurality of transmission channels is provided from each of the processors, where each processor has one less channel than the selected number of letters forming the sequence. Where a network GAMMA/sub d/(k, /minus/1) is provided, no processor has a channel connected to form an edge in a direction delta/sub 1/. Each of the channels has an identification number selected from the sequence of letters and connected from a first processor having a first extended address to a second processor having a second address formed from a second extended address defined by moving to the front of the first extended address the letter found in the position within the first extended address defined by the channel identification number. The second address is then formed by selecting the first elements of the second extended address corresponding to the selected number used to form the address permutations. 9 figs.

  15. CDKN-Green Growth: Implications for Development Planning | Open...

    Open Energy Info (EERE)

    of national and local stakeholders. Planners rarely find the planning process straightforward and rely on economic principles and tools to inform the process. Conventional...

  16. Impact of Network Activity Levels on the Performance of Passive Network Service Dependency Discovery

    SciTech Connect (OSTI)

    Carroll, Thomas E.; Chikkagoudar, Satish; Arthur-Durett, Kristine M.

    2015-11-02

    Network services often do not operate alone, but instead, depend on other services distributed throughout a network to correctly function. If a service fails, is disrupted, or degraded, it is likely to impair other services. The web of dependencies can be surprisingly complex---especially within a large enterprise network---and evolve with time. Acquiring, maintaining, and understanding dependency knowledge is critical for many network management and cyber defense activities. While automation can improve situation awareness for network operators and cyber practitioners, poor detection accuracy reduces their confidence and can complicate their roles. In this paper we rigorously study the effects of network activity levels on the detection accuracy of passive network-based service dependency discovery methods. The accuracy of all except for one method was inversely proportional to network activity levels. Our proposed cross correlation method was particularly robust to the influence of network activity. The proposed experimental treatment will further advance a more scientific evaluation of methods and provide the ability to determine their operational boundaries.

  17. Valley Entrepreneurs' Network (VEN) Monthly Network Meeting

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    VEN Monthly Network Meeting Valley Entrepreneurs' Network (VEN) Monthly Network Meeting WHEN: Mar 05, 2015 5:30 PM - 7:00 PM WHERE: Anthony's At the Delta North Paseo De Onate, Española, NM CATEGORY: Community INTERNAL: Calendar Login Event Description An evening of exciting enterprise networking with like-minded entrepreneurs. For more information, contact Alejandro, VEN Coordinator, at (505) 410-0959

  18. Hydrogen Knowledge and Opinions Assessment

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

    2008-2009 DOE Hydrogen Program: Hydrogen Knowledge and Opinions Assessment Rick Schmoyer Oak Ridge National Laboratory May 21, 2009 Project ID # edp_02_schmoyer This presentation does not contain any proprietary, confidential, or otherwise restricted information 2 Managed by UT-Battelle for the Department of Energy Overview * Start: April 2003 * End: 2012 (currently in "Phase II") * Percent complete: ~75% B. Mixed Messages E. Regional Differences F. Difficulty of Measuring Success *

  19. Uncertainty Quantification of Hypothesis Testing for the Integrated Knowledge Engine

    SciTech Connect (OSTI)

    Cuellar, Leticia

    2012-05-31

    The Integrated Knowledge Engine (IKE) is a tool of Bayesian analysis, based on Bayesian Belief Networks or Bayesian networks for short. A Bayesian network is a graphical model (directed acyclic graph) that allows representing the probabilistic structure of many variables assuming a localized type of dependency called the Markov property. The Markov property in this instance makes any node or random variable to be independent of any non-descendant node given information about its parent. A direct consequence of this property is that it is relatively easy to incorporate new evidence and derive the appropriate consequences, which in general is not an easy or feasible task. Typically we use Bayesian networks as predictive models for a small subset of the variables, either the leave nodes or the root nodes. In IKE, since most applications deal with diagnostics, we are interested in predicting the likelihood of the root nodes given new observations on any of the children nodes. The root nodes represent the various possible outcomes of the analysis, and an important problem is to determine when we have gathered enough evidence to lean toward one of these particular outcomes. This document presents criteria to decide when the evidence gathered is sufficient to draw a particular conclusion or decide in favor of a particular outcome by quantifying the uncertainty in the conclusions that are drawn from the data. The material in this document is organized as follows: Section 2 presents briefly a forensics Bayesian network, and we explore evaluating the information provided by new evidence by looking first at the posterior distribution of the nodes of interest, and then at the corresponding posterior odds ratios. Section 3 presents a third alternative: Bayes Factors. In section 4 we finalize by showing the relation between the posterior odds ratios and Bayes factors and showing examples these cases, and in section 5 we conclude by providing clear guidelines of how to use these

  20. Damselfly Network Simulator

    Energy Science and Technology Software Center (OSTI)

    2014-04-01

    Damselfly is a model-based parallel network simulator. It can simulate communication patterns of High Performance Computing applications on different network topologies. It outputs steady-state network traffic for a communication pattern, which can help in studying network congestion and its impact on performance.

  1. HPSS Yearly Network Traffic

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    HPSS Yearly Network Traffic HPSS Yearly Network Traffic Yearly Summary of I/O Traffic Between Storage and Network Destinations These bar charts show the total transfer traffic for each year between storage and network destinations (systems within and outside of NERSC). Traffic for the current year is an estimate derived by scaling the known months traffic up to 12 months. The years shown are calendar years. The first graph shows the overall growth in network traffic to storage over the years.

  2. D&D Knowledge Management Information Tool

    Office of Environmental Management (EM)

    Directory Web Conference D&D Knowledge Management Information Tool www.dndkm.org Himanshu Upadhyay Research Scientist June 27, 2012 D&D KM-IT WWW.DNDKM.ORG A web-based knowledge ...

  3. Biofuel Enduse Datasets from the Bioenergy Knowledge Discovery Framework (KDF)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about]

    Holdings include datasets, models, and maps. This is a very new resource, but the collections will grow due to both DOE contributions and individuals data uploads. Currently the Biofuel Enduse collection includes 133 items. Most of these are categorized as literature, but 36 are listed as datasets and ten as models.

  4. Biofuel Enduse Datasets from the Bioenergy Knowledge Discovery Framework (KDF)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about]

    Holdings include datasets, models, and maps. This is a very new resource, but the collections will grow due to both DOE contributions and individualsÆ data uploads. Currently the Biofuel Enduse collection includes 133 items. Most of these are categorized as literature, but 36 are listed as datasets and ten as models.

  5. Class network routing

    DOE Patents [OSTI]

    Bhanot, Gyan; Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

    2009-09-08

    Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

  6. Network II Database

    Energy Science and Technology Software Center (OSTI)

    1994-11-07

    The Oak Ridge National Laboratory (ORNL) Rail and Barge Network II Database is a representation of the rail and barge system of the United States. The network is derived from the Federal Rail Administration (FRA) rail database.

  7. BES Science Network Requirements

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Network Requirements Report of the Basic Energy Sciences Network Requirements Workshop Conducted June 4-5, 2007 BES Science Network Requirements Workshop Basic Energy Sciences Program Office, DOE Office of Science Energy Sciences Network Washington, DC - June 4 and 5, 2007 ESnet is funded by the US Dept. of Energy, Office of Science, Advanced Scientific Computing Research (ASCR) program. Dan Hitchcock is the ESnet Program Manager. ESnet is operated by Lawrence Berkeley National Laboratory, which

  8. Science-Driven Network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Science-Driven Network Requirements for ESnet Update to the 2002 Office of Science Networking Requirements Workshop Report February 21, 2006 1-1 Science-Driven Network Requirements for ESnet Update to the 2002 Office of Science Networking Requirements Workshop Report February 21, 2006 Contributors Paul Adams, LBNL (Advanced Light Source) Shane Canon, ORNL (NLCF) Steven Carter, ORNL (NLCF) Brent Draney, LBNL (NERSC) Martin Greenwald, MIT (Magnetic Fusion Energy) Jason Hodges, ORNL (Spallation

  9. Metallic nanowire networks

    DOE Patents [OSTI]

    Song, Yujiang; Shelnutt, John A.

    2012-11-06

    A metallic nanowire network synthesized using chemical reduction of a metal ion source by a reducing agent in the presence of a soft template comprising a tubular inverse micellar network. The network of interconnected polycrystalline nanowires has a very high surface-area/volume ratio, which makes it highly suitable for use in catalytic applications.

  10. Calorimetry Network Program

    Energy Science and Technology Software Center (OSTI)

    1998-01-30

    This is a Windows NT based program to run the SRTC designed calorimeters. The network version can communicate near real time data and final data values over the network. This version, due to network specifics, can function in a stand-alone operation also.

  11. LBNL Transactional Network Applications

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

    Transactional Network Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory LBNL Team: Mary Ann Piette, Richard Brown, Phil Price, Janie Page, Stephen Czarnecki, Anna Liao, Stephen Lanzisera, Jessica Granderson . LBNL Transactional Network Applications 2 | Building Technologies Office eere.energy.gov LBNL Transactional Network Applications Baseline Load Shape provides basis for measuring change in peak demand and energy use Demand Response Event Scheduler coordinates

  12. Genetic Algorithm Based Neural Networks for Nonlinear Optimization

    Energy Science and Technology Software Center (OSTI)

    1994-09-28

    This software develops a novel approach to nonlinear optimization using genetic algorithm based neural networks. To our best knowledge, this approach represents the first attempt at applying both neural network and genetic algorithm techniques to solve a nonlinear optimization problem. The approach constructs a neural network structure and an appropriately shaped energy surface whose minima correspond to optimal solutions of the problem. A genetic algorithm is employed to perform a parallel and powerful search ofmore » the energy surface.« less

  13. Enerlogics Networks | Open Energy Information

    Open Energy Info (EERE)

    Networks Name: Enerlogics Networks Place: Pittsburgh, Pennsylvania Product: buidling automation control systems to utility software solutions to telecommunication systems...

  14. Data structures and apparatuses for representing knowledge

    DOE Patents [OSTI]

    Hohimer, Ryan E; Thomson, Judi R; Harvey, William J; Paulson, Patrick R; Whiting, Mark A; Tratz, Stephen C; Chappell, Alan R; Butner, Robert S

    2014-02-18

    Data structures and apparatuses to represent knowledge are disclosed. The processes can comprise labeling elements in a knowledge signature according to concepts in an ontology and populating the elements with confidence values. The data structures can comprise knowledge signatures stored on computer-readable media. The knowledge signatures comprise a matrix structure having elements labeled according to concepts in an ontology, wherein the value of the element represents a confidence that the concept is present in an information space. The apparatus can comprise a knowledge representation unit having at least one ontology stored on a computer-readable medium, at least one data-receiving device, and a processor configured to generate knowledge signatures by comparing datasets obtained by the data-receiving devices to the ontologies.

  15. Climate Knowledge Brokers Group | Open Energy Information

    Open Energy Info (EERE)

    development information. It brings together a diverse set of information players, from international organisations to research institutes, NGOs and good practice networks, and...

  16. Internet protocol network mapper

    DOE Patents [OSTI]

    Youd, David W.; Colon III, Domingo R.; Seidl, Edward T.

    2016-02-23

    A network mapper for performing tasks on targets is provided. The mapper generates a map of a network that specifies the overall configuration of the network. The mapper inputs a procedure that defines how the network is to be mapped. The procedure specifies what, when, and in what order the tasks are to be performed. Each task specifies processing that is to be performed for a target to produce results. The procedure may also specify input parameters for a task. The mapper inputs initial targets that specify a range of network addresses to be mapped. The mapper maps the network by, for each target, executing the procedure to perform the tasks on the target. The results of the tasks represent the mapping of the network defined by the initial targets.

  17. The Digital Road to Scientific Knowledge Diffusion

    Office of Scientific and Technical Information (OSTI)

    ... data and textual information; and 4. Modeling scientific exchange in the research process. ... for conceptual context and the importance of reviewing the body of knowledge that exists. ...

  18. SEB Secretariat and Knowledge Manager | Department of Energy

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

    SEB Secretariat and Knowledge Manager SEB Secretariat and Knowledge Manager PDF icon SEB Secretariat and Knowledge Manager More Documents & Publications Source Selection Chapter 15...

  19. World Bank-Climate Change Knowledge Portal | Open Energy Information

    Open Energy Info (EERE)

    Climate Change Knowledge Portal Jump to: navigation, search Logo: World Bank-Climate Change Knowledge Portal Name World Bank-Climate Change Knowledge Portal AgencyCompany...

  20. An evidential path logic for multi-relational networks

    SciTech Connect (OSTI)

    Rodriguez, Marko A; Geldart, Joe

    2008-01-01

    Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Description Framework (RDF). One of the primary purposes of a knowledge network is to reason; that is, to alter the topology of the network according to an algorithm that uses the existing topological structure as its input. There exist many such reasoning algorithms. With respect to the Semantic Web, the bivalent, axiomatic reasoners of the RDF Schema (RDFS) and the Web Ontology Language (OWL) are the most prevalent. However, nothing prevents other forms of reasoning from existing in the Semantic Web. This article presents a non-bivalent, non-axiomatic, evidential logic and reasoner that is an algebraic ring over a multi-relational network and two binary operations that can be composed to perform various forms of inference. Given its multi-relational grounding, it is possible to use the presented evidential framework as another method for structuring knowledge and reasoning in the Semantic Web. The benefits of this framework are that it works with arbitrary, partial, and contradictory knowledge while, at the same time, supporting a tractable approximate reasoning process.

  1. Integrating large-scale functional genomics data to dissect metabolic networks for hydrogen production

    SciTech Connect (OSTI)

    Harwood, Caroline S

    2012-12-17

    The goal of this project is to identify gene networks that are critical for efficient biohydrogen production by leveraging variation in gene content and gene expression in independently isolated Rhodopseudomonas palustris strains. Coexpression methods were applied to large data sets that we have collected to define probabilistic causal gene networks. To our knowledge this a first systems level approach that takes advantage of strain-to strain variability to computationally define networks critical for a particular bacterial phenotypic trait.

  2. Knowledge Framework Implementation with Multiple Architectures - 13090

    SciTech Connect (OSTI)

    Upadhyay, H.; Lagos, L.; Quintero, W.; Shoffner, P.; DeGregory, J.

    2013-07-01

    Multiple kinds of knowledge management systems are operational in public and private enterprises, large and small organizations with a variety of business models that make the design, implementation and operation of integrated knowledge systems very difficult. In recent days, there has been a sweeping advancement in the information technology area, leading to the development of sophisticated frameworks and architectures. These platforms need to be used for the development of integrated knowledge management systems which provides a common platform for sharing knowledge across the enterprise, thereby reducing the operational inefficiencies and delivering cost savings. This paper discusses the knowledge framework and architecture that can be used for the system development and its application to real life need of nuclear industry. A case study of deactivation and decommissioning (D and D) is discussed with the Knowledge Management Information Tool platform and framework. D and D work is a high priority activity across the Department of Energy (DOE) complex. Subject matter specialists (SMS) associated with DOE sites, the Energy Facility Contractors Group (EFCOG) and the D and D community have gained extensive knowledge and experience over the years in the cleanup of the legacy waste from the Manhattan Project. To prevent the D and D knowledge and expertise from being lost over time from the evolving and aging workforce, DOE and the Applied Research Center (ARC) at Florida International University (FIU) proposed to capture and maintain this valuable information in a universally available and easily usable system. (authors)

  3. Reconfigureable network node

    DOE Patents [OSTI]

    Vanderveen, Keith B.; Talbot, Edward B.; Mayer, Laurence E.

    2008-04-08

    Nodes in a network having a plurality of nodes establish communication links with other nodes using available transmission media, as the ability to establish such links becomes available and desirable. The nodes predict when existing communications links will fail, become overloaded or otherwise degrade network effectiveness and act to establish substitute or additional links before the node's ability to communicate with the other nodes on the network is adversely affected. A node stores network topology information and programmed link establishment rules and criteria. The node evaluates characteristics that predict existing links with other nodes becoming unavailable or degraded. The node then determines whether it can form a communication link with a substitute node, in order to maintain connectivity with the network. When changing its communication links, a node broadcasts that information to the network. Other nodes update their stored topology information and consider the updated topology when establishing new communications links for themselves.

  4. National Highway Planning Network

    Energy Science and Technology Software Center (OSTI)

    1992-02-02

    NHPN, the National Highway Planning Network, is a database of major highways in the continental United States that is used for national-level analyses of highway transportation issues that require use of a network, such as studies of highway performance, network design, social and environmental impacts of transportation, vehicle routing and scheduling, and mapping. The network is based on a set of roadways digitized by the U. S. Geological Survey (USGS) from the 1980 National Atlasmore » and has been enhanced with additional roads, attribute detail, and topological error corrections to produce a true analytic network. All data have been derived from or checked against information obtained from state and Federal governmental agencies. Two files comprise this network: one describing links and the other nodes. This release, NHPN1.0, contains 44,960 links and 28,512 nodes representing approximately 380,000 miles of roadway.« less

  5. Networking and Application Strategies

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Networking and Application Strategies Networking and Application Strategies Los Alamos Lab recruits the best minds on the planet and offers job search information and assistance to our dual career spouses or partners. Contact Us dualcareers@lanl.gov You know more people than you think Having strong existing connections and building new ones is essential to finding a job-especially for a dual career family that is new to the Los Alamos area. Networking is a proven and effective way to increase

  6. BER Science Network Requirements

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ... However, once this step is completed, the network transfers of data or documentation may not need the same level of protection accorded to the authentication credentials. For the ...

  7. LBNL Transactional Network Applications

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

    Load Shape provides basis for measuring change in peak demand and energy use Demand Response Event Scheduler coordinates DR signals from outside server with available network ...

  8. battery electrode percolating network

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    battery electrode percolating network - Sandia Energy Energy Search Icon Sandia Home ... Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel ...

  9. Rooftop Unit Network Project

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

    part load performance - equipment maintenance * RTUs cannot easily interact with the ... Diagnostics - RTU Network Platform * Smart Monitoring and Diagnostics - Cloud * Autonomous ...

  10. Network Requirements Reviews

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Reviews Network Requirements Reviews Documents and Background Materials FAQ for Case Study Authors BER Requirements Review 2015 ASCR Requirements Review 2015 Previous...

  11. Energy Sciences Network (ESnet)

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    making it the standard for research institutions today. Read More ESnet Releases Open Source Software from MyESnet Portal for Building Online Interactive Network Portals ESnet...

  12. DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

    SciTech Connect (OSTI)

    McDermott, Jason E.; Costa, Michelle N.; Stevens, S.L.; Stenzel-Poore, Mary; Sanfilippo, Antonio P.

    2011-01-20

    A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks that are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a

  13. Knowledge Representation Issues in Semantic Graphs for Relationship Detection

    SciTech Connect (OSTI)

    Barthelemy, M; Chow, E; Eliassi-Rad, T

    2005-02-02

    An important task for Homeland Security is the prediction of threat vulnerabilities, such as through the detection of relationships between seemingly disjoint entities. A structure used for this task is a ''semantic graph'', also known as a ''relational data graph'' or an ''attributed relational graph''. These graphs encode relationships as typed links between a pair of typed nodes. Indeed, semantic graphs are very similar to semantic networks used in AI. The node and link types are related through an ontology graph (also known as a schema). Furthermore, each node has a set of attributes associated with it (e.g., ''age'' may be an attribute of a node of type ''person''). Unfortunately, the selection of types and attributes for both nodes and links depends on human expertise and is somewhat subjective and even arbitrary. This subjectiveness introduces biases into any algorithm that operates on semantic graphs. Here, we raise some knowledge representation issues for semantic graphs and provide some possible solutions using recently developed ideas in the field of complex networks. In particular, we use the concept of transitivity to evaluate the relevance of individual links in the semantic graph for detecting relationships. We also propose new statistical measures for semantic graphs and illustrate these semantic measures on graphs constructed from movies and terrorism data.

  14. Better Buildings Residential Network | Department of Energy

    Energy Savers [EERE]

    Residential Buildings Better Buildings Residential Network Better Buildings Residential Network Better Buildings Residential Network Explore Latest Peer Exchange Call Summaries ...

  15. Form:Networking Organization | Open Energy Information

    Open Energy Info (EERE)

    Networking Organization Jump to: navigation, search Add a Networking Organization Input your networking organization name below to add to the registry. If your networking...

  16. Collective network routing

    DOE Patents [OSTI]

    Hoenicke, Dirk

    2014-12-02

    Disclosed are a unified method and apparatus to classify, route, and process injected data packets into a network so as to belong to a plurality of logical networks, each implementing a specific flow of data on top of a common physical network. The method allows to locally identify collectives of packets for local processing, such as the computation of the sum, difference, maximum, minimum, or other logical operations among the identified packet collective. Packets are injected together with a class-attribute and an opcode attribute. Network routers, employing the described method, use the packet attributes to look-up the class-specific route information from a local route table, which contains the local incoming and outgoing directions as part of the specifically implemented global data flow of the particular virtual network.

  17. Offshore Energy Knowledge Exchange Workshop Report

    SciTech Connect (OSTI)

    none,

    2012-04-12

    A report detailing the presentations and topics discussed at the Offshore Energy Knowledge Exchange Workshop, an event designed to bring together offshore energy industry representatives to share information, best practices, and lessons learned.

  18. Residential Network Members Unite to Form Green Bank Network...

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

    The NY Green Bank logo. Residential Network members Connecticut Green Bank and NY Green Bank, a division of Residential Network member New York State Energy Research and ...

  19. Hydroacoustic propagation grids for the CTBT knowledge databaes BBN technical memorandum W1303

    SciTech Connect (OSTI)

    J. Angell

    1998-05-01

    The Hydroacoustic Coverage Assessment Model (HydroCAM) has been used to develop components of the hydroacoustic knowledge database required by operational monitoring systems, particularly the US National Data Center (NDC). The database, which consists of travel time, amplitude correction and travel time standard deviation grids, is planned to support source location, discrimination and estimation functions of the monitoring network. The grids will also be used under the current BBN subcontract to support an analysis of the performance of the International Monitoring System (IMS) and national sensor systems. This report describes the format and contents of the hydroacoustic knowledgebase grids, and the procedures and model parameters used to generate these grids. Comparisons between the knowledge grids, measured data and other modeled results are presented to illustrate the strengths and weaknesses of the current approach. A recommended approach for augmenting the knowledge database with a database of expected spectral/waveform characteristics is provided in the final section of the report.

  20. Hydrogen Safety Knowledge Tools | Department of Energy

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

    Safety Knowledge Tools Hydrogen Safety Knowledge Tools 2009 DOE Hydrogen Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting, May 18-22, 2009 -- Washington D.C. scs_04_fassbender.pdf (985.09 KB) More Documents & Publications What Can We Learn from Hydrogen Safety Event Databases? H2 Safety Snapshot, Vol. 1, Issue 1, April 2009 H2 Refuel H-Prize Safety Guidance Webinar H2 Refuel H-Prize Safety Guidance

  1. Thermal network reduction

    SciTech Connect (OSTI)

    Balcomb, J.D.

    1983-01-01

    A method is presented for reducing the number of elements required in a thermal network representation of a building. The method is based on matching the actual building response at two frequencies, the diurnal response and 3-day response. The procedure provides a straightforward methodology for combining all the various materials inside a discrete building zone into a few nodes while retaining a high degree of accuracy in the dynamic response. An example is given showing a comparison between a large network and the reduced network.

  2. Thermal network reduction

    SciTech Connect (OSTI)

    Balcomb, J.D.

    1983-06-01

    A method is presented for reducing the number of elements required in a thermal network representation of a building. The method is based on matching the actual building response at two frequencies, the diurnal response and 3-day response. The procedure provides a straightforward methodology for combining all the various materials inside a discrete building zone into a few nodes while retaining a high degree of accuracy in the dynamic response. An example is given showing a comparison between a large network and the reduced network.

  3. BES Science Network Requirements

    SciTech Connect (OSTI)

    Biocca, Alan; Carlson, Rich; Chen, Jackie; Cotter, Steve; Tierney, Brian; Dattoria, Vince; Davenport, Jim; Gaenko, Alexander; Kent, Paul; Lamm, Monica; Miller, Stephen; Mundy, Chris; Ndousse, Thomas; Pederson, Mark; Perazzo, Amedeo; Popescu, Razvan; Rouson, Damian; Sekine, Yukiko; Sumpter, Bobby; Dart, Eli; Wang, Cai-Zhuang -Z; Whitelam, Steve; Zurawski, Jason

    2011-02-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivityfor the US Department of Energy Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of the Office ofScience programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years.

  4. NP Science Network Requirements

    SciTech Connect (OSTI)

    Dart, Eli; Rotman, Lauren; Tierney, Brian

    2011-08-26

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. To support SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In August 2011, ESnet and the Office of Nuclear Physics (NP), of the DOE SC, organized a workshop to characterize the networking requirements of the programs funded by NP. The requirements identified at the workshop are summarized in the Findings section, and are described in more detail in the body of the report.

  5. Energy Efficient Digital Networks

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

    and rising * About 7% of all U.S. electricity consumption -Much of this digitally networked already Our Future? Media room in high-end home Electronics are Different - Service ...

  6. Energy Materials Network Overview

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

    30 th , 2016 2 MGI - Framework New Material Innovations for Clean Energy 2X Faster and 2X Cheaper Predictive Simulation Across Scales Synthesis & Characterization Rapid Screening End Use Performance Process Scalability Process Control Real-time Characterization Reliability Validation Data Management & Informatics Coordinated resource network with a suite of capabilities for advanced materials R&D In Support of the Materials Genome Initiative (MGI) 3 Network Requirements 1. WORLD

  7. Complex Networks - A Key to Understanding Brain Function

    ScienceCinema (OSTI)

    Olaf Sporns

    2010-01-08

    The brain is a complex network of neurons, engaging in spontaneous and evoked activity that is thought to be the main substrate of mental life.  How this complex system works together to process information and generate coherent cognitive states, even consciousness, is not yet well understood.  In my talk I will review recent studies that have revealed characteristic structural and functional attributes of brain networks, and discuss efforts to build computational models of the brain that are informed by our growing knowledge of brain anatomy and physiology.

  8. Complex Networks - A Key to Understanding Brain Function

    SciTech Connect (OSTI)

    Olaf Sporns

    2008-01-23

    The brain is a complex network of neurons, engaging in spontaneous and evoked activity that is thought to be the main substrate of mental life.  How this complex system works together to process information and generate coherent cognitive states, even consciousness, is not yet well understood.  In my talk I will review recent studies that have revealed characteristic structural and functional attributes of brain networks, and discuss efforts to build computational models of the brain that are informed by our growing knowledge of brain anatomy and physiology.

  9. Knowledge Encapsulation Framework for Collaborative Social Modeling

    SciTech Connect (OSTI)

    Cowell, Andrew J.; Gregory, Michelle L.; Marshall, Eric J.; McGrath, Liam R.

    2009-03-24

    This paper describes the Knowledge Encapsulation Framework (KEF), a suite of tools to enable knowledge inputs (relevant, domain-specific facts) to modeling and simulation projects, as well as other domains that require effective collaborative workspaces for knowledge-based task. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.

  10. Exploration Best Practices and the OpenEI Knowledge Exchange...

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

    Best Practices and the OpenEI Knowledge Exchange Webinar Exploration Best Practices and the OpenEI Knowledge Exchange Webinar Exploration Best Practices and the OpenEI Knowledge ...

  11. Automated Knowledge Annotation for Dynamic Collaborative Environments

    SciTech Connect (OSTI)

    Cowell, Andrew J.; Gregory, Michelle L.; Marshall, Eric J.; McGrath, Liam R.

    2009-05-19

    This paper describes the Knowledge Encapsulation Framework (KEF), a suite of tools to enable automated knowledge annotation for modeling and simulation projects. This framework can be used to capture evidence (e.g., facts extracted from journal articles and government reports), discover new evidence (from similar peer-reviewed material as well as social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks.

  12. Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

    ScienceCinema (OSTI)

    Danuso, Francesco [University of Udine, Italy

    2010-01-08

    A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed.  SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Jørgensen, 1994) in which systems are modelled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower  management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

  13. Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

    SciTech Connect (OSTI)

    Danuso, Francesco

    2008-06-18

    A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed. SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Joergensen, 1994) in which systems are modeled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

  14. Knowledge Integration to Make Decisions About Complex Systems: Sustainability of Energy Production from Agriculture

    SciTech Connect (OSTI)

    Danuso, Francesco

    2008-06-18

    A major bottleneck for improving the governance of complex systems, rely on our ability to integrate different forms of knowledge into a decision support system (DSS). Preliminary aspects are the classification of different types of knowledge (a priori or general, a posteriori or specific, with uncertainty, numerical, textual, algorithmic, complete/incomplete, etc.), the definition of ontologies for knowledge management and the availability of proper tools like continuous simulation models, event driven models, statistical approaches, computational methods (neural networks, evolutionary optimization, rule based systems etc.) and procedure for textual documentation. Following these views at University of Udine, a computer language (SEMoLa, Simple, Easy Modelling Language) for knowledge integration has been developed.  SEMoLa can handle models, data, metadata and textual knowledge; it implements and extends the system dynamics ontology (Forrester, 1968; Jørgensen, 1994) in which systems are modelled by the concepts of material, group, state, rate, parameter, internal and external events and driving variables. As an example, a SEMoLa model to improve management and sustainability (economical, energetic, environmental) of the agricultural farms is presented. The model (X-Farm) simulates a farm in which cereal and forage yield, oil seeds, milk, calves and wastes can be sold or reused. X-Farm is composed by integrated modules describing fields (crop and soil), feeds and materials storage, machinery management, manpower  management, animal husbandry, economic and energetic balances, seed oil extraction, manure and wastes management, biogas production from animal wastes and biomasses.

  15. Software-Defined Networking (SDN)

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    ENOS Experimental Network Testbeds Performance (perfSONAR) Software & Tools Development Data for Researchers Partnerships Publications Workshops Science Engagement Move your data Programs & Workshops Science Requirements Reviews Case Studies News & Publications ESnet News Publications and Presentations Galleries ESnet Awards and Honors Blog ESnet Live Home » Network R&D » Software-Defined Networking (SDN) Network R&D Software-Defined Networking (SDN) ENOS Experimental

  16. The Digital Road to Scientific Knowledge Diffusion; A Faster...

    Office of Scientific and Technical Information (OSTI)

    The Digital Road to Scientific Knowledge Diffusion; A Faster, Better Way to Scientific Progress? Citation Details In-Document Search Title: The Digital Road to Scientific Knowledge ...

  17. Knowledge Partnership for Measuring Air Pollution and Greenhouse...

    Open Energy Info (EERE)

    Knowledge Partnership for Measuring Air Pollution and Greenhouse Gas Emissions in Asia Jump to: navigation, search Name Knowledge Partnership for Measuring Air Pollution and...

  18. Template:Climate Knowledge Brokers Navigation | Open Energy Informatio...

    Open Energy Info (EERE)

    Climate Knowledge Brokers Navigation Jump to: navigation, search This is the Climate Knowledge Brokers Navigation template. It generates the navigation displayed at the top of all...

  19. New Jersey Institute of Technology Center for Building Knowledge...

    Open Energy Info (EERE)

    Institute of Technology Center for Building Knowledge Jump to: navigation, search Name: New Jersey Institute of Technology Center for Building Knowledge Place: University Heights...

  20. MHK Technologies/New Knowledge Wind and Wave Renewable Mobile...

    Open Energy Info (EERE)

    New Knowledge Wind and Wave Renewable Mobile Wind and Wave Power Plant Platform < MHK Technologies Jump to: navigation, search << Return to the MHK database homepage New Knowledge...

  1. Energy and Interior Departments Host Offshore Energy Knowledge...

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

    and Interior Departments Host Offshore Energy Knowledge Exchange Workshop Energy and Interior Departments Host Offshore Energy Knowledge Exchange Workshop May 1, 2012 - 2:52pm ...

  2. Recovering START institutional knowledge (Conference) | SciTech...

    Office of Scientific and Technical Information (OSTI)

    Recovering START institutional knowledge Citation Details In-Document Search Title: Recovering START institutional knowledge You are accessing a document from the Department of ...

  3. Study Builds Knowledge of Nuclear Waste Glass, Provides Insight...

    Office of Environmental Management (EM)

    Study Builds Knowledge of Nuclear Waste Glass, Provides Insight to Facility Design Study Builds Knowledge of Nuclear Waste Glass, Provides Insight to Facility Design April 14, 2016 ...

  4. A knowledge continuity management program for the energy, infrastructure and knowledge systems center, Sandia National Laboratories.

    SciTech Connect (OSTI)

    Menicucci, David F.

    2006-07-01

    A growing recognition exists in companies worldwide that, when employees leave, they take with them valuable knowledge that is difficult and expensive to recreate. The concern is now particularly acute as the large ''baby boomer'' generation is reaching retirement age. A new field of science, Knowledge Continuity Management (KCM), is designed to capture and catalog the acquired knowledge and wisdom from experience of these employees before they leave. The KCM concept is in the final stages of being adopted by the Energy, Infrastructure, and Knowledge Systems Center and a program is being applied that should produce significant annual cost savings. This report discusses how the Center can use KCM to mitigate knowledge loss from employee departures, including a concise description of a proposed plan tailored to the Center's specific needs and resources.

  5. High Density Sensor Network Development | The Ames Laboratory

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    High Density Sensor Network Development

  6. Network topology mapper

    DOE Patents [OSTI]

    Quist, Daniel A.; Gavrilov, Eugene M.; Fisk, Michael E.

    2008-01-15

    A method enables the topology of an acyclic fully propagated network to be discovered. A list of switches that comprise the network is formed and the MAC address cache for each one of the switches is determined. For each pair of switches, from the MAC address caches the remaining switches that see the pair of switches are located. For each pair of switches the remaining switches are determined that see one of the pair of switches on a first port and the second one of the pair of switches on a second port. A list of insiders is formed for every pair of switches. It is determined whether the insider for each pair of switches is a graph edge and adjacent ones of the graph edges are determined. A symmetric adjacency matrix is formed from the graph edges to represent the topology of the data link network.

  7. Self-Configuring Network Monitor

    Energy Science and Technology Software Center (OSTI)

    2004-05-01

    Self-Configuring Network Monitor (SCNM) is a passive monitoring that can collect packet headers from any point in a network path. SCNM uses special activation packets to automatically activate monitors deployed at the layer three ingress and egress routers of the wide-area network, and at critical points within the site networks. Monitoring output data is sent back to the application data source or destination host. No modifications are required to the application or network routing infrastructuremore » in order to activate monitoring of traffic for an application. This ensures that the monitoring operation does not add a burden to the networks administrator.« less

  8. ASCR Science Network Requirements

    SciTech Connect (OSTI)

    Dart, Eli; Tierney, Brian

    2009-08-24

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In April 2009 ESnet and the Office of Advanced Scientific Computing Research (ASCR), of the DOE Office of Science, organized a workshop to characterize the networking requirements of the programs funded by ASCR. The ASCR facilities anticipate significant increases in wide area bandwidth utilization, driven largely by the increased capabilities of computational resources and the wide scope of collaboration that is a hallmark of modern science. Many scientists move data sets between facilities for analysis, and in some cases (for example the Earth System Grid and the Open Science Grid), data distribution is an essential component of the use of ASCR facilities by scientists. Due to the projected growth in wide area data transfer needs, the ASCR supercomputer centers all expect to deploy and use 100 Gigabit per second networking technology for wide area connectivity as soon as that deployment is financially feasible. In addition to the network connectivity that ESnet provides, the ESnet Collaboration Services (ECS) are critical to several science communities. ESnet identity and trust services, such as the DOEGrids certificate authority, are widely used both by the supercomputer centers and by collaborations such as Open Science Grid (OSG) and the Earth System Grid (ESG). Ease of use is a key determinant of the scientific utility of network-based services. Therefore, a key enabling aspect for scientists beneficial use of high

  9. Network resilience; A measure of network fault tolerance

    SciTech Connect (OSTI)

    Najjar, W. . Dept. of Computer Science); Gaudoit, J.L. . Dept. of Electrical Engineering)

    1990-02-01

    The failure of a node in a multicomputer system will not only reduce the computational power but also alter the network's topology. Network fault tolerance is a measure of the number of failures the network can sustain before a disconnection occurs. It is expressed traditionally as the network's node degree. In this paper, the authors propose a probabilistic measure of network fault tolerance expressed as the probability f a disconnection. Qualitative evaluation of this measure is presented. As expected, the single-node disconnection probability is the dominant factor irrespective of the topology under consideration. They derive an analytical approximation of the disconnection probability and verify it with Monte Carlo simulation. Based on this model, the measures of network resilience and relative network resilience are proposed as probabilistic measures of network fault tolerance. These are then used to evaluate the effects of the disconnection probability on the reliability of the system.

  10. Advancing the hydrogen safety knowledge base

    SciTech Connect (OSTI)

    Weiner, S. C.

    2014-08-29

    The International Energy Agency's Hydrogen Implementing Agreement (IEA HIA) was established in 1977 to pursue collaborative hydrogen research and development and information exchange among its member countries. Information and knowledge dissemination is a key aspect of the work within IEA HIA tasks, and case studies, technical reports and presentations/publications often result from the collaborative efforts. The work conducted in hydrogen safety under Task 31 and its predecessor, Task 19, can positively impact the objectives of national programs even in cases for which a specific task report is not published. As a result, the interactions within Task 31 illustrate how technology information and knowledge exchange among participating hydrogen safety experts serve the objectives intended by the IEA HIA.

  11. Advancing the hydrogen safety knowledge base

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Weiner, S. C.

    2014-08-29

    The International Energy Agency's Hydrogen Implementing Agreement (IEA HIA) was established in 1977 to pursue collaborative hydrogen research and development and information exchange among its member countries. Information and knowledge dissemination is a key aspect of the work within IEA HIA tasks, and case studies, technical reports and presentations/publications often result from the collaborative efforts. The work conducted in hydrogen safety under Task 31 and its predecessor, Task 19, can positively impact the objectives of national programs even in cases for which a specific task report is not published. As a result, the interactions within Task 31 illustrate how technologymore » information and knowledge exchange among participating hydrogen safety experts serve the objectives intended by the IEA HIA.« less

  12. Using a neural network for abnormal event identification in BWRs

    SciTech Connect (OSTI)

    Ohga, Yukiharu; Seki, Hiroshi (Hitachi Ltd., Ibaraki (Japan))

    1991-01-01

    Information on anomalies such as abnormal events is considered to be important for operation support when choosing information to be offered to operators. The authors have applied neural network techniques to identify an abnormal event that causes a reactor scram in boiling water reactors. A primary feature of the method is that the result of the neural network is confirmed using the knowledge base on plant status when each event occurs. This improves the result's reliability. A second feature is that the neural network uses analog data such as reactor pressure, the acquisition of which is triggered by the scram signal. The event identification method is shown. The event identification method is tested using a workstation.

  13. The Digital Road to Scientific Knowledge Diffusion

    Office of Scientific and Technical Information (OSTI)

    Digital Road to Scientific Knowledge Diffusion A Faster, Better Way to Scientific Progress? By David E. Wojick, Walter L. Warnick, Bonnie C. Carroll, and June Crowe Introduction With the United States federal government spending over $130 billion annually for research and development, ways to increase the productivity of that research can have a significant return on investment. It is well known that all scientific advancement is based on work that has come before. Isaac Newton expressed this

  14. Vehicle Technologies Office: National Idling Reduction Network...

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

    National Idling Reduction Network News Archives Vehicle Technologies Office: National Idling Reduction Network News Archives The National Idling Reduction Network brings together ...

  15. Clean Economy Network Foundation | Open Energy Information

    Open Energy Info (EERE)

    Clean Economy Network Foundation Jump to: navigation, search Logo: Clean Economy Network Foundation Name: Clean Economy Network Foundation Address: 1301 Pennsylvania Ave NW, Suite...

  16. Northwest Biodiesel Network | Open Energy Information

    Open Energy Info (EERE)

    Biodiesel Network Jump to: navigation, search Logo: Northwest Biodiesel Network Name: Northwest Biodiesel Network Address: 6532 Phinney Ave N Place: Seattle, Washington Zip: 98103...

  17. Sustainable Agriculture Network | Open Energy Information

    Open Energy Info (EERE)

    Agriculture Network Jump to: navigation, search Logo: Sustainable Agriculture Network Name: Sustainable Agriculture Network Website: clima.sanstandards.org References: Sustainable...

  18. Solar Instructor Training Network | Department of Energy

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

    Instructor Training Network Solar Instructor Training Network The Solar Instructor Training Network promotes high-quality training in the installation of solar technologies. Nine ...

  19. Benefits of Better Buildings Residential Network Reporting |...

    Energy Savers [EERE]

    Benefits of Better Buildings Residential Network Reporting Benefits of Better Buildings Residential Network Reporting Better Buildings Residential Network All-Member Peer Exchange ...

  20. Better Buildings Residential Network Orientation Webinar Call...

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

    ... Residential Network (Residential Network) Better Buildings Residential Network: Connects energy efficiency programs and partners to share best practices to increase the ...

  1. Knowledge Discovery, Knowledge Management and Enterprise-Wide Information Technology Tools Final Report

    SciTech Connect (OSTI)

    Patton, Robert M; Symons, Christopher T; Gorman, Bryan L; Treadwell, Jim N

    2012-04-01

    A final report on an ORNL task to establish a knowledge discovery and management tool to retrieve and recommend information from existing S&T documents for the Office of Naval Research Global.

  2. Microsystem process networks

    DOE Patents [OSTI]

    Wegeng, Robert S [Richland, WA; TeGrotenhuis, Ward E [Kennewick, WA; Whyatt, Greg A [West Richland, WA

    2010-01-26

    Various aspects and applications or microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  3. Microsystem process networks

    DOE Patents [OSTI]

    Wegeng, Robert S.; TeGrotenhuis, Ward E.; Whyatt, Greg A.

    2006-10-24

    Various aspects and applications of microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having exergetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  4. Microsystem process networks

    DOE Patents [OSTI]

    Wegeng, Robert S.; TeGrotenhuis, Ward E.; Whyatt, Greg A.

    2007-09-18

    Various aspects and applications of microsystem process networks are described. The design of many types of Microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  5. Transactional Network Platform: Applications

    SciTech Connect (OSTI)

    Katipamula, Srinivas; Lutes, Robert G.; Ngo, Hung; Underhill, Ronald M.

    2013-10-31

    In FY13, Pacific Northwest National Laboratory (PNNL) with funding from the Department of Energy’s (DOE’s) Building Technologies Office (BTO) designed, prototyped and tested a transactional network platform to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). Initially, in FY13, the concept demonstrated transactions between packaged rooftop air conditioners and heat pump units (RTUs) and the electric grid using applications or "agents" that reside on the platform, on the equipment, on a local building controller or in the Cloud. The transactional network project is a multi-lab effort with Oakridge National Laboratory (ORNL) and Lawrence Berkeley National Laboratory (LBNL) also contributing to the effort. PNNL coordinated the project and also was responsible for the development of the transactional network (TN) platform and three different applications associated with RTUs. This document describes two applications or "agents" in details, and also summarizes the platform. The TN platform details are described in another companion document.

  6. BER Science Network Requirements

    SciTech Connect (OSTI)

    Alapaty, Kiran; Allen, Ben; Bell, Greg; Benton, David; Brettin, Tom; Canon, Shane; Dart, Eli; Cotter, Steve; Crivelli, Silvia; Carlson, Rich; Dattoria, Vince; Desai, Narayan; Egan, Richard; Tierney, Brian; Goodwin, Ken; Gregurick, Susan; Hicks, Susan; Johnston, Bill; de Jong, Bert; Kleese van Dam, Kerstin; Livny, Miron; Markowitz, Victor; McGraw, Jim; McCord, Raymond; Oehmen, Chris; Regimbal, Kevin; Shipman, Galen; Strand, Gary; Flick, Jeff; Turnbull, Susan; Williams, Dean; Zurawski, Jason

    2010-11-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In April 2010 ESnet and the Office of Biological and Environmental Research, of the DOE Office of Science, organized a workshop to characterize the networking requirements of the science programs funded by BER. The requirements identified at the workshop are summarized and described in more detail in the case studies and the Findings section. A number of common themes emerged from the case studies and workshop discussions. One is that BER science, like many other disciplines, is becoming more and more distributed and collaborative in nature. Another common theme is that data set sizes are exploding. Climate Science in particular is on the verge of needing to manage exabytes of data, and Genomics is on the verge of a huge paradigm shift in the number of sites with sequencers and the amount of sequencer data being generated.

  7. Energy Materials Network Workshop

    Office of Energy Efficiency and Renewable Energy (EERE)

    The Energy Materials Network (EMN) is a national lab-led initiative that aims to dramatically decrease the time-to-market for advanced materials innovations critical to many clean energy technologies. Through targeted consortia offering accessible suites of advanced research and development capabilities, EMN is accelerating materials development to address U.S. manufacturers' most pressing materials challenges.

  8. Residential Network Members Unite to Form Green Bank Network

    Broader source: Energy.gov [DOE]

    Residential Network members Connecticut Green Bank and NY Green Bank, a division of Residential Network member New York State Energy Research and Development Authority, have helped launch the Green Bank Network, a new international organization focused on collaborating to scale up private financing to meet the challenge of climate change.

  9. A Framework for Incorporating General Domain Knowledge into Latent Dirichlet Allocation using First-Order Logic

    SciTech Connect (OSTI)

    Andrzejewski, D; Zhu, X; Craven, M; Recht, B

    2011-01-18

    Topic models have been used successfully for a variety of problems, often in the form of application-specific extensions of the basic Latent Dirichlet Allocation (LDA) model. Because deriving these new models in order to encode domain knowledge can be difficult and time-consuming, we propose the Fold-all model, which allows the user to specify general domain knowledge in First-Order Logic (FOL). However, combining topic modeling with FOL can result in inference problems beyond the capabilities of existing techniques. We have therefore developed a scalable inference technique using stochastic gradient descent which may also be useful to the Markov Logic Network (MLN) research community. Experiments demonstrate the expressive power of Fold-all, as well as the scalability of our proposed inference method.

  10. Software Defined Networking (SDN) Project

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

    Software Defined Networking (SDN) Project Energy sector-focused SDN flow controller to manage control system networks centrally and securely Background Traditional information technology (IT) approaches to network administration and packet delivery are not always appropriate for electric industry applications. The nondeterministic latency and configuration complexity make network design difficult for the deterministic, static control systems of the energy sector. In the electric industry, it is

  11. Multiple network interface core apparatus and method

    DOE Patents [OSTI]

    Underwood, Keith D.; Hemmert, Karl Scott

    2011-04-26

    A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

  12. Renewable Energy Nongovernmental Organization Network (RENOVE...

    Open Energy Info (EERE)

    Nongovernmental Organization Network (RENOVE) Jump to: navigation, search Name: Renewable Energy Nongovernmental Organization Network (RENOVE) Place: Brasilia, Brazil Phone Number:...

  13. Instructions for Using Virtual Private Network (VPN)

    Broader source: Energy.gov [DOE]

    Virtual Private Network (VPN) provides access to network drives and is recommended for use only from a EITS provided laptop.

  14. Better Buildings Network View | February 2015

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  15. Better Buildings Network View | November 2015

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  16. Better Buildings Network View | May 2014

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  17. Better Buildings Network View | September 2014

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  18. Better Buildings Network View | June 2014

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  19. Better Buildings Network View | May 2015

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  20. Better Buildings Network View | June 2015

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  1. Better Buildings Network View | October 2014

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  2. Better Buildings Network View | October 2015

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  3. Better Buildings Network View | January 2016

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  4. Better Buildings Network View | February 2016

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  5. Better Buildings Network View | January 2014

    Broader source: Energy.gov [DOE]

    The Better Buildings Network View monthly newsletter from the U.S. Department of Energy's Better Buildings Residential Network.

  6. Modular sensor network node

    DOE Patents [OSTI]

    Davis, Jesse Harper Zehring; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick; Kyker, Ronald Dean

    2008-06-10

    A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

  7. Exploiting Network Parallelism

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Exploiting Network Parallelism for Improving Data Transfer Performance Dan Gunter ∗ , Raj Kettimuthu † , Ezra Kissel ‡ , Martin Swany ‡ , Jun Yi § , Jason Zurawski ¶ ∗ Advanced Computing for Science Department, Lawrence Berkeley National Laboratory, Berkeley, CA † Mathematics and Computer Science Division, Argonne National Laboratory Argonne, IL ‡ School of Informatics and Computing, Indiana University, Bloomington, IN § Computation Institute, University of Chicago/Argonne

  8. Experimental Network Testbeds

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    100G SDN Testbed Dark Fiber Testbed Test Circuit Service Testbed Results Current Testbed Research Previous Testbed Research Performance (perfSONAR) Software & Tools Development Data for Researchers Partnerships Publications Workshops Science Engagement Move your data Programs & Workshops Science Requirements Reviews Case Studies News & Publications ESnet News Publications and Presentations Galleries ESnet Awards and Honors Blog ESnet Live Home » Network R&D » Experimental

  9. Insecurity of Wireless Networks

    SciTech Connect (OSTI)

    Sheldon, Frederick T; Weber, John Mark; Yoo, Seong-Moo; Pan, W. David

    2012-01-01

    Wireless is a powerful core technology enabling our global digital infrastructure. Wi-Fi networks are susceptible to attacks on Wired Equivalency Privacy, Wi-Fi Protected Access (WPA), and WPA2. These attack signatures can be profiled into a system that defends against such attacks on the basis of their inherent characteristics. Wi-Fi is the standard protocol for wireless networks used extensively in US critical infrastructures. Since the Wired Equivalency Privacy (WEP) security protocol was broken, the Wi-Fi Protected Access (WPA) protocol has been considered the secure alternative compatible with hardware developed for WEP. However, in November 2008, researchers developed an attack on WPA, allowing forgery of Address Resolution Protocol (ARP) packets. Subsequent enhancements have enabled ARP poisoning, cryptosystem denial of service, and man-in-the-middle attacks. Open source systems and methods (OSSM) have long been used to secure networks against such attacks. This article reviews OSSMs and the results of experimental attacks on WPA. These experiments re-created current attacks in a laboratory setting, recording both wired and wireless traffic. The article discusses methods of intrusion detection and prevention in the context of cyber physical protection of critical Internet infrastructure. The basis for this research is a specialized (and undoubtedly incomplete) taxonomy of Wi-Fi attacks and their adaptations to existing countermeasures and protocol revisions. Ultimately, this article aims to provide a clearer picture of how and why wireless protection protocols and encryption must achieve a more scientific basis for detecting and preventing such attacks.

  10. Bicriteria network design problems

    SciTech Connect (OSTI)

    Marathe, M.V.; Ravi, R.; Sundaram, R.; Ravi, S.S.; Rosenkrantz, D.J.; Hunt, H.B. III

    1997-11-20

    The authors study a general class of bicriteria network design problems. A generic problem in this class is as follows: Given an undirected graph and two minimization objectives (under different cost functions), with a budget specified on the first, find a subgraph from a given subgraph class that minimizes the second objective subject to the budget on the first. They consider three different criteria -- the total edge cost, the diameter and the maximum degree of the network. Here, they present the first polynomial-time approximation algorithms for a large class of bicriteria network design problems for the above mentioned criteria. The following general types of results are presented. First, they develop a framework for bicriteria problems and their approximations. Second, when the two criteria are the same they present a black box parametric search technique. This black box takes in as input an (approximation) algorithm for the criterion situation and generates an approximation algorithm for the bicriteria case with only a constant factor loss in the performance guarantee. Third, when the two criteria are the diameter and the total edge costs they use a cluster based approach to devise approximation algorithms. The solutions violate both the criteria by a logarithmic factor. Finally, for the class of treewidth-bounded graphs, they provide pseudopolynomial-time algorithms for a number of bicriteria problems using dynamic programming. The authors show how these pseudopolynomial-time algorithms can be converted to fully polynomial-time approximation schemes using a scaling technique.

  11. Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks

    SciTech Connect (OSTI)

    Ziaul Huque

    2007-08-31

    This is the final technical report for the project titled 'Mathematically Reduced Chemical Reaction Mechanism Using Neural Networks'. The aim of the project was to develop an efficient chemistry model for combustion simulations. The reduced chemistry model was developed mathematically without the need of having extensive knowledge of the chemistry involved. To aid in the development of the model, Neural Networks (NN) was used via a new network topology known as Non-linear Principal Components Analysis (NPCA). A commonly used Multilayer Perceptron Neural Network (MLP-NN) was modified to implement NPCA-NN. The training rate of NPCA-NN was improved with the GEneralized Regression Neural Network (GRNN) based on kernel smoothing techniques. Kernel smoothing provides a simple way of finding structure in data set without the imposition of a parametric model. The trajectory data of the reaction mechanism was generated based on the optimization techniques of genetic algorithm (GA). The NPCA-NN algorithm was then used for the reduction of Dimethyl Ether (DME) mechanism. DME is a recently discovered fuel made from natural gas, (and other feedstock such as coal, biomass, and urban wastes) which can be used in compression ignition engines as a substitute for diesel. An in-house two-dimensional Computational Fluid Dynamics (CFD) code was developed based on Meshfree technique and time marching solution algorithm. The project also provided valuable research experience to two graduate students.

  12. Exploration Best Practices and the OpenEI Knowledge Exchange...

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

    Exploration Best p Practices & The OpenEI Knowledge Exchange Knowledge Exchange G th l T h l i P W bi Geothermal Technologies Program Webinar Katherine R. Young Timothy Reber ...

  13. New America Foundation: Eric Isaacs - Can our knowledge enterprise...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    New America Foundation: Eric Isaacs - Can our knowledge enterprise seed the industries of tomorrow? Share Topic Operations Technology transfer...

  14. A situated knowledge representation of geographical information

    SciTech Connect (OSTI)

    Gahegan, Mark N.; Pike, William A.

    2006-11-01

    In this paper we present an approach to conceiving of, constructing and comparing the concepts developed and used by geographers, environmental scientists and other earth science researchers to help describe, analyze and ultimately understand their subject of study. Our approach is informed by the situations under which concepts are conceived and applied, captures details of their construction, use and evolution and supports their ultimate sharing along with the means for deep exploration of conceptual similarities and differences that may arise among a distributed network of researchers. The intent here is to support different perspectives onto GIS resources that researchers may legitimately take, and to capture and compute with aspects of epistemology, to complement the ontologies that are currently receiving much attention in the GIScience community.

  15. Workplan and Annex: Solar Resource Knowledge Management

    SciTech Connect (OSTI)

    Renne, D.

    2005-01-01

    ''Solar Resource Knowledge Management'' will be a new task under the International Energy Agency's Solar Heating and Cooling Programme. The task development has involved researchers from Germany, France, Switzerland, Spain, Portugal, Italy, Canada, the U.S. that have been engaged in the use of satellite imagery to develop solar resource maps and datasets around the world. The task will address three major areas: (1) ''Benchmarking'' of satellite-based solar resource methods so that resource information derived from approaches developed in one country or based on a specific satellite can be quantitatively intercompared with methods from other countries using different satellites, as well as with ground data; (2) Data archiving and dissemination procedures, especially focusing on access to the data by end users; and (3) basic R&D for improving the reliability and usability of the data, and for examining new types of products important to the solar industry, such as solar resource forecasts.

  16. Operating Innovative Networks Workshop Series

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Operating Innovative Networks Workshop Series Science Engagement Move your data Programs & Workshops CrossConnects Workshop Series Operating Innovative Networks Workshop Series Enlighten Your Research Global Program Science Requirements Reviews Case Studies Contact Us Technical Assistance: 1 800-33-ESnet (Inside US) 1 800-333-7638 (Inside US) 1 510-486-7600 (Globally) 1 510-486-7607 (Globally) Report Network Problems: trouble@es.net Provide Web Site Feedback: info@es.net Operating Innovative

  17. United States National Seismographic Network

    SciTech Connect (OSTI)

    Buland, R.

    1993-09-01

    The concept of a United States National Seismograph Network (USNSN) dates back nearly 30 years. The idea was revived several times over the decades. but never funded. For, example, a national network was proposed and discussed at great length in the so called Bolt Report (U. S. Earthquake Observatories: Recommendations for a New National Network, National Academy Press, Washington, D.C., 1980, 122 pp). From the beginning, a national network was viewed as augmenting and complementing the relatively dense, predominantly short-period vertical coverage of selected areas provided by the Regional Seismograph Networks (RSN`s) with a sparse, well-distributed network of three-component, observatory quality, permanent stations. The opportunity finally to begin developing a national network arose in 1986 with discussions between the US Geological Survey (USGS) and the Nuclear Regulatory Commission (NRC). Under the agreement signed in 1987, the NRC has provided $5 M in new funding for capital equipment (over the period 1987-1992) and the USGS has provided personnel and facilities to develop. deploy, and operate the network. Because the NRC funding was earmarked for the eastern United States, new USNSN station deployments are mostly east of 105{degree}W longitude while the network in the western United States is mostly made up of cooperating stations (stations meeting USNSN design goals, but deployed and operated by other institutions which provide a logical extension to the USNSN).

  18. Network interdiction with budget constraints

    SciTech Connect (OSTI)

    Santhi, Nankakishore; Pan, Feng

    2009-01-01

    Several scenarios exist in the modern interconnected world which call for efficient network interdiction algorithms. Applications are varied, including computer network security, prevention of spreading of Internet worms, policing international smuggling networks, controlling spread of diseases and optimizing the operation of large public energy grids. In this paper we consider some natural network optimization questions related to the budget constrained interdiction problem over general graphs. Many of these questions turn out to be computationally hard to tackle. We present a particularly interesting practical form of the interdiction question which we show to be computationally tractable. A polynomial time algorithm is then presented for this problem.

  19. Regional Networks for Energy Efficiency

    Broader source: Energy.gov [DOE]

    Better Buildings Neighborhood Program Sustainability Peer Exchange Call: Regional Networks for Energy Efficiency, call slides and discussion summary, December 6, 2012.

  20. High Performance Network Monitoring

    SciTech Connect (OSTI)

    Martinez, Jesse E

    2012-08-10

    Network Monitoring requires a substantial use of data and error analysis to overcome issues with clusters. Zenoss and Splunk help to monitor system log messages that are reporting issues about the clusters to monitoring services. Infiniband infrastructure on a number of clusters upgraded to ibmon2. ibmon2 requires different filters to report errors to system administrators. Focus for this summer is to: (1) Implement ibmon2 filters on monitoring boxes to report system errors to system administrators using Zenoss and Splunk; (2) Modify and improve scripts for monitoring and administrative usage; (3) Learn more about networks including services and maintenance for high performance computing systems; and (4) Gain a life experience working with professionals under real world situations. Filters were created to account for clusters running ibmon2 v1.0.0-1 10 Filters currently implemented for ibmon2 using Python. Filters look for threshold of port counters. Over certain counts, filters report errors to on-call system administrators and modifies grid to show local host with issue.

  1. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  2. Network Upgrade for the SLC: PEP II Network

    SciTech Connect (OSTI)

    Crane, M.; Call, M.; Clark, S.; Coffman, F.; Himel, T.; Lahey, T.; Miller, E.; Sass, R.; /SLAC

    2011-09-09

    The PEP-II control system required a new network to support the system functions. This network, called CTLnet, is an FDDI/Ethernet based network using only TCP/IP protocols. An upgrade of the SLC Control System micro communications to use TCP/IP and SLCNET would allow all PEP-II control system nodes to use TCP/IP. CTLnet is private and separate from the SLAC public network. Access to nodes and control system functions is provided by multi-homed application servers with connections to both the private CTLnet and the SLAC public network. Monitoring and diagnostics are provided using a dedicated system. Future plans and current status information is included.

  3. Knowledge Discovery from Massive Healthcare Claims Data

    SciTech Connect (OSTI)

    Chandola, Varun; Sukumar, Sreenivas R; Schryver, Jack C

    2013-01-01

    The role of big data in addressing the needs of the present healthcare system in US and rest of the world has been echoed by government, private, and academic sectors. There has been a growing emphasis to explore the promise of big data analytics in tapping the potential of the massive healthcare data emanating from private and government health insurance providers. While the domain implications of such collaboration are well known, this type of data has been explored to a limited extent in the data mining community. The objective of this paper is two fold: first, we introduce the emerging domain of big"healthcare claims data to the KDD community, and second, we describe the success and challenges that we encountered in analyzing this data using state of art analytics for massive data. Specically, we translate the problem of analyzing healthcare data into some of the most well-known analysis problems in the data mining community, social network analysis, text mining, and temporal analysis and higher order feature construction, and describe how advances within each of these areas can be leveraged to understand the domain of healthcare. Each case study illustrates a unique intersection of data mining and healthcare with a common objective of improving the cost-care ratio by mining for opportunities to improve healthcare operations and reducing hat seems to fall under fraud, waste,and abuse.

  4. Better Buildings Network View | February 2015 | Department of...

    Office of Environmental Management (EM)

    newsletter from the U.S. Department of Energy's Better Buildings Residential Network. ... Better Buildings Network View | June 2015 Nothing But Networking for Residential Network ...

  5. Global interrupt and barrier networks

    DOE Patents [OSTI]

    Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E; Heidelberger, Philip; Kopcsay, Gerard V.; Steinmacher-Burow, Burkhard D.; Takken, Todd E.

    2008-10-28

    A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected by multiple independent networks, with each node including one or more processing elements for performing computation or communication activity as required when performing parallel algorithm operations. One multiple independent network includes a global tree network for enabling high-speed global tree communications among global tree network nodes or sub-trees thereof. The global interrupt and barrier network may operate in parallel with the global tree network for providing global asynchronous sideband signals.

  6. RNEDE: Resilient Network Design Environment

    SciTech Connect (OSTI)

    Venkat Venkatasubramanian, Tanu Malik, Arun Giridh; Craig Rieger; Keith Daum; Miles McQueen

    2010-08-01

    Modern living is more and more dependent on the intricate web of critical infrastructure systems. The failure or damage of such systems can cause huge disruptions. Traditional design of this web of critical infrastructure systems was based on the principles of functionality and reliability. However, it is increasingly being realized that such design objectives are not sufficient. Threats, disruptions and faults often compromise the network, taking away the benefits of an efficient and reliable design. Thus, traditional network design parameters must be combined with self-healing mechanisms to obtain a resilient design of the network. In this paper, we present RNEDEa resilient network design environment that that not only optimizes the network for performance but tolerates fluctuations in its structure that result from external threats and disruptions. The environment evaluates a set of remedial actions to bring a compromised network to an optimal level of functionality. The environment includes a visualizer that enables the network administrator to be aware of the current state of the network and the suggested remedial actions at all times.

  7. Distributed downhole drilling network

    DOE Patents [OSTI]

    Hall, David R.; Hall, Jr., H. Tracy; Fox, Joe; Pixton, David S.

    2006-11-21

    A high-speed downhole network providing real-time data from downhole components of a drilling strings includes a bottom-hole node interfacing to a bottom-hole assembly located proximate the bottom end of a drill string. A top-hole node is connected proximate the top end of the drill string. One or several intermediate nodes are located along the drill string between the bottom-hole node and the top-hole node. The intermediate nodes are configured to receive and transmit data packets transmitted between the bottom-hole node and the top-hole node. A communications link, integrated into the drill string, is used to operably connect the bottom-hole node, the intermediate nodes, and the top-hole node. In selected embodiments, a personal or other computer may be connected to the top-hole node, to analyze data received from the intermediate and bottom-hole nodes.

  8. Network Information System

    Energy Science and Technology Software Center (OSTI)

    1996-05-01

    The Network Information System (NWIS) was initially implemented in May 1996 as a system in which computing devices could be recorded so that unique names could be generated for each device. Since then the system has grown to be an enterprise wide information system which is integrated with other systems to provide the seamless flow of data through the enterprise. The system Iracks data for two main entities: people and computing devices. The following aremore » the type of functions performed by NWIS for these two entities: People Provides source information to the enterprise person data repository for select contractors and visitors Generates and tracks unique usernames and Unix user IDs for every individual granted cyber access Tracks accounts for centrally managed computing resources, and monitors and controls the reauthorization of the accounts in accordance with the DOE mandated interval Computing Devices Generates unique names for all computing devices registered in the system Tracks the following information for each computing device: manufacturer, make, model, Sandia property number, vendor serial number, operating system and operating system version, owner, device location, amount of memory, amount of disk space, and level of support provided for the machine Tracks the hardware address for network cards Tracks the P address registered to computing devices along with the canonical and alias names for each address Updates the Dynamic Domain Name Service (DDNS) for canonical and alias names Creates the configuration files for DHCP to control the DHCP ranges and allow access to only properly registered computers Tracks and monitors classified security plans for stand-alone computers Tracks the configuration requirements used to setup the machine Tracks the roles people have on machines (system administrator, administrative access, user, etc...) Allows systems administrators to track changes made on the machine (both hardware and software) Generates an

  9. Network Information System

    SciTech Connect (OSTI)

    1996-05-01

    The Network Information System (NWIS) was initially implemented in May 1996 as a system in which computing devices could be recorded so that unique names could be generated for each device. Since then the system has grown to be an enterprise wide information system which is integrated with other systems to provide the seamless flow of data through the enterprise. The system Iracks data for two main entities: people and computing devices. The following are the type of functions performed by NWIS for these two entities: People Provides source information to the enterprise person data repository for select contractors and visitors Generates and tracks unique usernames and Unix user IDs for every individual granted cyber access Tracks accounts for centrally managed computing resources, and monitors and controls the reauthorization of the accounts in accordance with the DOE mandated interval Computing Devices Generates unique names for all computing devices registered in the system Tracks the following information for each computing device: manufacturer, make, model, Sandia property number, vendor serial number, operating system and operating system version, owner, device location, amount of memory, amount of disk space, and level of support provided for the machine Tracks the hardware address for network cards Tracks the P address registered to computing devices along with the canonical and alias names for each address Updates the Dynamic Domain Name Service (DDNS) for canonical and alias names Creates the configuration files for DHCP to control the DHCP ranges and allow access to only properly registered computers Tracks and monitors classified security plans for stand-alone computers Tracks the configuration requirements used to setup the machine Tracks the roles people have on machines (system administrator, administrative access, user, etc...) Allows systems administrators to track changes made on the machine (both hardware and software) Generates an adjustment

  10. Collective network for computer structures

    DOE Patents [OSTI]

    Blumrich, Matthias A; Coteus, Paul W; Chen, Dong; Gara, Alan; Giampapa, Mark E; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd E; Steinmacher-Burow, Burkhard D; Vranas, Pavlos M

    2014-01-07

    A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to the needs of a processing algorithm.

  11. Collective network for computer structures

    DOE Patents [OSTI]

    Blumrich, Matthias A.; Coteus, Paul W.; Chen, Dong; Gara, Alan; Giampapa, Mark E.; Heidelberger, Philip; Hoenicke, Dirk; Takken, Todd E.; Steinmacher-Burow, Burkhard D.; Vranas, Pavlos M.

    2011-08-16

    A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

  12. Simplifying Probability Elicitation and Uncertainty Modeling in Bayesian Networks

    SciTech Connect (OSTI)

    Paulson, Patrick R; Carroll, Thomas E; Sivaraman, Chitra; Neorr, Peter A; Unwin, Stephen D; Hossain, Shamina S

    2011-04-16

    In this paper we contribute two methods that simplify the demands of knowledge elicitation for particular types of Bayesian networks. The first method simplify the task of providing probabilities when the states that a random variable takes can be described by a new, fully ordered state set in which a state implies all the preceding states. The second method leverages Dempster-Shafer theory of evidence to provide a way for the expert to express the degree of ignorance that they feel about the estimates being provided.

  13. Phoebus: Network Middleware for Next-Generation Network Computing

    SciTech Connect (OSTI)

    Martin Swany

    2012-06-16

    The Phoebus project investigated algorithms, protocols, and middleware infrastructure to improve end-to-end performance in high speed, dynamic networks. The Phoebus system essentially serves as an adaptation point for networks with disparate capabilities or provisioning. This adaptation can take a variety of forms including acting as a provisioning agent across multiple signaling domains, providing transport protocol adaptation points, and mapping between distributed resource reservation paradigms and the optical network control plane. We have successfully developed the system and demonstrated benefits. The Phoebus system was deployed in Internet2 and in ESnet, as well as in GEANT2, RNP in Brazil and over international links to Korea and Japan. Phoebus is a system that implements a new protocol and associated forwarding infrastructure for improving throughput in high-speed dynamic networks. It was developed to serve the needs of large DOE applications on high-performance networks. The idea underlying the Phoebus model is to embed Phoebus Gateways (PGs) in the network as on-ramps to dynamic circuit networks. The gateways act as protocol translators that allow legacy applications to use dedicated paths with high performance.

  14. Processes, data structures, and apparatuses for representing knowledge

    DOE Patents [OSTI]

    Hohimer, Ryan E.; Thomson, Judi R.; Harvey, William J.; Paulson, Patrick R.; Whiting, Mark A.; Tratz, Stephen C.; Chappell, Alan R.; Butner, R. Scott

    2011-09-20

    Processes, data structures, and apparatuses to represent knowledge are disclosed. The processes can comprise labeling elements in a knowledge signature according to concepts in an ontology and populating the elements with confidence values. The data structures can comprise knowledge signatures stored on computer-readable media. The knowledge signatures comprise a matrix structure having elements labeled according to concepts in an ontology, wherein the value of the element represents a confidence that the concept is present in an information space. The apparatus can comprise a knowledge representation unit having at least one ontology stored on a computer-readable medium, at least one data-receiving device, and a processor configured to generate knowledge signatures by comparing datasets obtained by the data-receiving devices to the ontologies.

  15. Feedstock Logistics Datasets from DOE's Bioenergy Knowledge Discovery...

    Office of Scientific and Technical Information (OSTI)

    access to research data and literature, GIS mapping tools, and collaborative networks. ... (EERE) Country of Publication: United States Language: English Subject: 9 - BIOMASS FUELS

  16. Capturing Process Knowledge for Facility Deactivation and Decommissioning |

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

    Department of Energy Capturing Process Knowledge for Facility Deactivation and Decommissioning Capturing Process Knowledge for Facility Deactivation and Decommissioning The Office of Environmental Management (EM) is responsible for the disposition of a vast number of facilities at numerous sites around the country which have been declared excess to current mission needs. Capturing Process Knowledge for Facility Deactivation and Decommissioning (252.61 KB) More Documents & Publications

  17. Essential Body of Knowledge (EBK) | Department of Energy

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

    Services » Training » Cybersecurity Training Warehouse » DOE Training & Education » Essential Body of Knowledge (EBK) Essential Body of Knowledge (EBK) Train12.jpg The OCIO has developed a DOE-specific Essential Body of Knowledge (EBK) using DOE cybersecurity policy, industry best practices and lessons learned, and comprehensive internal needs assessments to identify fundamental cybersecurity roles and associated responsibilities. Core competencies, as identified and documented in the

  18. Capturing Process Knowledge for Facility Deactivation and Decommission...

    Office of Environmental Management (EM)

    Tech Assistance Savannah River National Laboratory- Assess Adequacy of Process Knowledge ... Gaseous Diffusion Plant and phone discussions were held with personnel at several sites. ...

  19. Essential Body of Knowledge (EBK) | Department of Energy

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

    More Documents & Publications Essential Body of Knowledge (EBK) DOE CYBER SECURITY EBK: CORE COMPETENCY TRAINING REQUIREMENTS: CA DOE CYBER SECURITY EBK: MINIMUM CORE COMPETENCY ...

  20. OSTIblog Articles in the scientific knowledge Topic | OSTI, US...

    Office of Scientific and Technical Information (OSTI)

    knowledge Topic The Benefits of Investments in Basic Research by Peter Lincoln 01 Nov, 2009 in Science Communications Long-term investments in basic research produce the major ...

  1. Indigenous Environmental Network | Open Energy Information

    Open Energy Info (EERE)

    Indigenous Environmental Network Name: Indigenous Environmental Network Address: PO Box 485 Place: Bemidji, MN Year Founded: 1990 Phone Number: (218) 751-4967 Website:...

  2. Silver Spring Networks Inc | Open Energy Information

    Open Energy Info (EERE)

    Spring Networks Inc Jump to: navigation, search Name: Silver Spring Networks Inc Place: Redwood City, California Zip: 94063 Product: California-based, developer of utility...

  3. Clean Economy Network | Open Energy Information

    Open Energy Info (EERE)

    Network Jump to: navigation, search Name: Clean Economy Network Place: Washington, Washington, DC Zip: 20004 Product: Washingt (DC-based advocacy group focused on clean energy and...

  4. Residential Energy Services Network (RESNET) Conference | Department...

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

    Residential Energy Services Network (RESNET) Conference Residential Energy Services Network (RESNET) Conference February 29, 2016 9:00AM EST to March 2, 2016 5:0

  5. Better Buildings Network View, April 2015

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

    ... Laboratory) announcement emails sent to Residential Network members or via the Residential Network Group on Home Energy Pros. To receive emails about upcoming calls, contact ...

  6. Better Buildings Network View, July 2014

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

    ... summaries through announcement emails sent to Residential Network members or via the Residential Network Group on Home Energy Pros. To receive emails about upcoming calls email ...

  7. Networks, smart grids: new model for synchronization

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    Networks, smart grids: new model for synchronization Networks, smart grids: new model for synchronization Researchers developed a surprisingly simple mathematical model that ...

  8. Structure Learning in Power Distribution Networks (Technical...

    Office of Scientific and Technical Information (OSTI)

    Structure Learning in Power Distribution Networks Citation Details In-Document Search Title: Structure Learning in Power Distribution Networks You are accessing a document from ...

  9. Rural Innovations Network | Open Energy Information

    Open Energy Info (EERE)

    Network Jump to: navigation, search Name: Rural Innovations Network Place: India Sector: Services Product: General Financial & Legal Services ( Charity Non-profit Association...

  10. Creative Environmental Networks | Open Energy Information

    Open Energy Info (EERE)

    Environmental Networks Jump to: navigation, search Name: Creative Environmental Networks Place: United Kingdom Zip: CR7 7JG Sector: Biomass, Renewable Energy, Services Product:...

  11. Grencubator. Ukrainian energy innovation network | Open Energy...

    Open Energy Info (EERE)

    Grencubator. Ukrainian energy innovation network Jump to: navigation, search Name: Greencubator. Ukrainian energy innovation network Place: Kyiv, Ukraine Number of Employees: 1-10...

  12. EA-1964: National Ecological Observation Network (NEON)

    Broader source: Energy.gov [DOE]

    The National Science Foundation (NSF) prepared an EA that evaluated potential environmental impacts of the proposed National Ecological Observation Network (NEON), a continental-scale network of...

  13. Better Buildings Residential Network Membership Form | Department...

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

    of Energy's Better Buildings Residential Network. BBRN Membership Form (138.55 KB) More Documents & Publications Better Buildings Residential Network Orientation Fact Sheet: ...

  14. Better Buildings Residential Network Program Sustainability Peer...

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

    11, 2014 Better Buildings Residential Network Better Buildings Residential Network: Connects energy efficiency programs and partners to share best practices to increase the ...

  15. Better Buildings Residential Network Case Study: Partnerships...

    Energy Savers [EERE]

    Better Buildings Residential Network Case Study: Partnerships Better Buildings Residential Network Case Study: Partnerships, from the U.S. Department of Energy's Office of Energy ...

  16. Better Buildings Residential Network Orientation Webinar | Department...

    Energy Savers [EERE]

    September 11, 2014. Call Slides and Discussion Summary (2.44 MB) More Documents & Publications Better Buildings Residential Network Orientation Better Buildings Residential Network ...

  17. Better Buildings Residential Network Orientation Webinar, Call...

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

    BBNP Grantee Sectors 9 BBNP Accomplishments 10 Better Buildings Residential Network Better Buildings Residential Network: Connects energy efficiency programs and partners to ...

  18. Better Buildings Residential Network Orientation | Department...

    Energy Savers [EERE]

    Orientation Better Buildings Residential Network Orientation Better Buildings Residential Network (BBRN) Orientation Call Slides and Summary, March 27, 2014. Call Slides and ...

  19. Better Buildings Residential Network | Department of Energy

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

    Better Buildings Residential Network Better Buildings Residential Network Explore Peer ... programs can implement and leverage to quickly show energy and utility dollar savings. ...

  20. Better Buildings Network View December 2015

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

    News From the Field New Case Study Highlights Network Member's Community Engagement Better Buildings Residential Network member Community Home Energy Retrofit Project (CHERP) is a ...

  1. Better Buildings Residential Network (BBRN) Orientation Call...

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

    ... 11 Better Buildings Residential Network (BBRN) Better Buildings Residential Network: Connects energy efficiency programs and partners to share best practices to increase the ...

  2. Better Buildings Residential Network Social Media Toolkit

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

    Social Media Toolkit BETTER BUILDINGS RESIDENTIAL NETWORK Learn more at betterbuildings.energy.govbbrn 1 T his Better Buildings Residential Network toolkit can be used to help ...

  3. Structure Learning in Power Distribution Networks (Technical...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Structure Learning in Power Distribution Networks Citation Details In-Document Search Title: Structure Learning in Power Distribution Networks Authors: Deka, ...

  4. SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

    SciTech Connect (OSTI)

    Kalet, A; Phillips, M; Gennari, J

    2014-06-01

    Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the

  5. Towards A Network-of-Networks Framework for Cyber Security

    SciTech Connect (OSTI)

    Halappanavar, Mahantesh; Choudhury, Sutanay; Hogan, Emilie A.; Hui, Peter SY; Johnson, John R.; Ray, Indrajit; Holder, Lawrence B.

    2013-06-07

    Networks-of-networks (NoN) is a graph-theoretic model of interdependent networks that have distinct dynamics at each network (layer). By adding special edges to represent relationships between nodes in different layers, NoN provides a unified mechanism to study interdependent systems intertwined in a complex relationship. While NoN based models have been proposed for cyber-physical systems, in this paper we build towards a three-layer NoN model for an enterprise cyber system. Each layer captures a different facet of a cyber system. We then discuss the potential benefits of graph-theoretic analysis enabled from such a model. Our goal is to provide a novel and powerful tool for modeling and analyzing problems in cyber security.

  6. Biomass Rapid Analysis Network (BRAN)

    SciTech Connect (OSTI)

    Not Available

    2003-10-01

    Helping the emerging biotechnology industry develop new tools and methods for real-time analysis of biomass feedstocks, process intermediates and The Biomass Rapid Analysis Network is designed to fast track the development of modern tools and methods for biomass analysis to accelerate the development of the emerging industry. The network will be led by industry and organized and coordinated through the National Renewable Energy Lab. The network will provide training and other activities of interest to BRAN members. BRAN members will share the cost and work of rapid analysis method development, validate the new methods, and work together to develop the training for the future biomass conversion workforce.

  7. EIA - Natural Gas Pipeline Network - Network Configuration & System Design

    U.S. Energy Information Administration (EIA) Indexed Site

    Network Configuration & System Design About U.S. Natural Gas Pipelines - Transporting Natural Gas based on data through 2007/2008 with selected updates Network Configuration and System Design Overview | Transmission/Storage | Design Criteria | Importance of Storage| Overall Pipeline System Configuration Overview A principal requirement of the natural gas transmission system is that it be capable of meeting the peak demand of its shippers who have contracts for firm service. To meet this

  8. NUCLEAR INCIDENT CAPABILITIES, KNOWLEDGE & ENABLER LEVERAGING

    SciTech Connect (OSTI)

    Kinney, J.; Newman, J.; Goodwyn, A.; Dewes, J.

    2011-04-18

    action. Much work needs to be accomplished to enhance nuclear preparedness and to substantially bolster and clarify the capacity to deploy competent resources. Until detailed plans are scripted, and personnel and other resources are postured, and exercised, IND specific planning remains an urgent need requiring attention and action. Although strategic guidance, policies, concepts of operations, roles, responsibilities, and plans governing the response and consequence management for the IND scenario exist, an ongoing integration challenge prevails regarding how best to get capable and competent surge capacity personnel (disaster reservists) and other resources engaged and readied in an up-front manner with pre-scripted assignments to augment the magnitude of anticipated demands of expertise. With the above in mind, Savannah River National Laboratory (SRNL) puts science to work to create and deploy practical, high-value, cost-effective nuclear solutions. As the Department of Energy's (DOE) applied research and development laboratory, SRNL supports Savannah River Site (SRS) operations, DOE, national initiatives, and other federal agencies, across the country and around the world. SRNL's parent at SRS also employs more than 8,000 personnel. The team is a great asset that seeks to continue their service in the interest of national security and stands ready to accomplish new missions. Overall, an integral part of the vision for SRNL's National and Homeland Security Directorate is the establishment of a National Security Center at SRNL, and development of state of the science capabilities (technologies and trained technical personnel) for responding to emergency events on local, regional, or national scales. This entails leveraging and posturing the skills, knowledge and experience base of SRS personnel to deliver an integrated capability to support local, state, and federal authorities through the development of pre-scripted requests for assistance, agreements, and plans. It

  9. Program for Online Network Inversion

    Energy Science and Technology Software Center (OSTI)

    2009-12-21

    PONI determines the source location of a contamination incident in a water distribution network. PONI uses large scale optimization methods to predict likely source locations by reconciling the differences between observations and numerical predictions of possible contamination incidents.

  10. The Ad Lucem Research Network

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

    The Ad Lucem Research Network Lada Adamic Associate Professor, School of Information & Center for the Study of Complex Systems University of Michigan Research interests: structure and dynamics of social and information networks, with a particular emphasis on information diffusion, expertise sharing, and online communities D. Lazer et al. "Computational Social Science." Science 323, 5915 (2009). J. Leskovec, L. A. Adamic, and B. A. Huberman. "The dynamics of viral

  11. Fact Sheet: Better Buildings Residential Network

    Broader source: Energy.gov [DOE]

    Fact Sheet: Better Buildings Residential Network, increasing the number of American Homes that are energy efficient.

  12. Better Buildings Residential Network Orientation Webinar

    Office of Energy Efficiency and Renewable Energy (EERE)

    Better Buildings Residential Network Orientation Webinar, call slides and discussion summary, May 14, 2015.

  13. Anomaly Detection in Dynamic Networks

    SciTech Connect (OSTI)

    Turcotte, Melissa

    2014-10-14

    Anomaly detection in dynamic communication networks has many important security applications. These networks can be extremely large and so detecting any changes in their structure can be computationally challenging; hence, computationally fast, parallelisable methods for monitoring the network are paramount. For this reason the methods presented here use independent node and edge based models to detect locally anomalous substructures within communication networks. As a first stage, the aim is to detect changes in the data streams arising from node or edge communications. Throughout the thesis simple, conjugate Bayesian models for counting processes are used to model these data streams. A second stage of analysis can then be performed on a much reduced subset of the network comprising nodes and edges which have been identified as potentially anomalous in the first stage. The first method assumes communications in a network arise from an inhomogeneous Poisson process with piecewise constant intensity. Anomaly detection is then treated as a changepoint problem on the intensities. The changepoint model is extended to incorporate seasonal behavior inherent in communication networks. This seasonal behavior is also viewed as a changepoint problem acting on a piecewise constant Poisson process. In a static time frame, inference is made on this extended model via a Gibbs sampling strategy. In a sequential time frame, where the data arrive as a stream, a novel, fast Sequential Monte Carlo (SMC) algorithm is introduced to sample from the sequence of posterior distributions of the change points over time. A second method is considered for monitoring communications in a large scale computer network. The usage patterns in these types of networks are very bursty in nature and don’t fit a Poisson process model. For tractable inference, discrete time models are considered, where the data are aggregated into discrete time periods and probability models are fitted to the

  14. The data dictionary: A view into the CTBT knowledge base

    SciTech Connect (OSTI)

    Shepherd, E.R.; Keyser, R.G.; Armstrong, H.M.

    1997-08-01

    The data dictionary for the Comprehensive Test Ban Treaty (CTBT) knowledge base provides a comprehensive, current catalog of the projected contents of the knowledge base. It is written from a data definition view of the knowledge base and therefore organizes information in a fashion that allows logical storage within the computer. The data dictionary introduces two organization categories of data: the datatype, which is a broad, high-level category of data, and the dataset, which is a specific instance of a datatype. The knowledge base, and thus the data dictionary, consist of a fixed, relatively small number of datatypes, but new datasets are expected to be added on a regular basis. The data dictionary is a tangible result of the design effort for the knowledge base and is intended to be used by anyone who accesses the knowledge base for any purpose, such as populating the knowledge base with data, or accessing the data for use with automatic data processing (ADP) routines, or browsing through the data for verification purposes. For these two reasons, it is important to discuss the development of the data dictionary as well as to describe its contents to better understand its usefulness; that is the purpose of this paper.

  15. Office of Nuclear Energy Knowledge Management Program Situational Analysis Report

    SciTech Connect (OSTI)

    Kimberlyn C. Mousseau

    2011-12-01

    Knowledge management (KM) has been a high priority for the Department of Energy (DOE) Office of Nuclear Energy (NE) for the past several years. NE Programs are moving toward well-established knowledge management practices and a formal knowledge management program has been established. Knowledge management is being practiced to some level within each of the NE programs. Although it continues to evolve as NE programs evolve, a formal strategic plan that guides the implementation of KM has been developed. Despite the acceptance of KM within DOE NE, more work is necessary before the NE KM program can be considered fully successful. Per Dr. David J. Skyrme[1], an organization typically moves through the following evolutionary phases: (1) Ad-hoc - KM is being practiced to some level in some parts of the organization; (2) Formal - KM is established as a formal project or program; (3) Expanding - the use of KM as a discipline grows in practice across different parts of the organization; (4) Cohesive - there is a degree of coordination of KM; (5) Integrated - there are formal standards and approaches that give every individual access to most organizational knowledge through common interfaces; and (6) Embedded - KM is part-and-parcel of everyday tasks; it blends seamlessly into the background. According to the evolutionary phases, the NE KM program is operating at the two lower levels, Ad-hoc and Formal. Although KM is being practiced to some level, it is not being practiced in a consistent manner across the NE programs. To be fully successful, more emphasis must be placed on establishing KM standards and processes for collecting, organizing, sharing and accessing NE knowledge. Existing knowledge needs to be prioritized and gathered on a routine basis, its existence formally recorded in a knowledge inventory. Governance to ensure the quality of the knowledge being used must also be considered. For easy retrieval, knowledge must be organized according to a taxonomy that

  16. Sustaining knowledge in the neutron generator community and benchmarking study.

    SciTech Connect (OSTI)

    Barrentine, Tameka C.; Kennedy, Bryan C.; Saba, Anthony W.; Turgeon, Jennifer L.; Schneider, Julia Teresa; Stubblefield, William Anthony; Baldonado, Esther

    2008-03-01

    In 2004, the Responsive Neutron Generator Product Deployment department embarked upon a partnership with the Systems Engineering and Analysis knowledge management (KM) team to develop knowledge management systems for the neutron generator (NG) community. This partnership continues today. The most recent challenge was to improve the current KM system (KMS) development approach by identifying a process that will allow staff members to capture knowledge as they learn it. This 'as-you-go' approach will lead to a sustainable KM process for the NG community. This paper presents a historical overview of NG KMSs, as well as research conducted to move toward sustainable KM.

  17. Flexible network wireless transceiver and flexible network telemetry transceiver

    DOE Patents [OSTI]

    Brown, Kenneth D.

    2008-08-05

    A transceiver for facilitating two-way wireless communication between a baseband application and other nodes in a wireless network, wherein the transceiver provides baseband communication networking and necessary configuration and control functions along with transmitter, receiver, and antenna functions to enable the wireless communication. More specifically, the transceiver provides a long-range wireless duplex communication node or channel between the baseband application, which is associated with a mobile or fixed space, air, water, or ground vehicle or other platform, and other nodes in the wireless network or grid. The transceiver broadly comprises a communication processor; a flexible telemetry transceiver including a receiver and a transmitter; a power conversion and regulation mechanism; a diplexer; and a phased array antenna system, wherein these various components and certain subcomponents thereof may be separately enclosed and distributable relative to the other components and subcomponents.

  18. A network biology approach to denitrification in Pseudomonas aeruginosa

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Arat, Seda; Bullerjahn, George S.; Laubenbacher, Reinhard

    2015-02-23

    Pseudomonas aeruginosa is a metabolically flexible member of the Gammaproteobacteria. Under anaerobic conditions and the presence of nitrate, P. aeruginosa can perform (complete) denitrification, a respiratory process of dissimilatory nitrate reduction to nitrogen gas via nitrite (NO₂), nitric oxide (NO) and nitrous oxide (N₂O). This study focuses on understanding the influence of environmental conditions on bacterial denitrification performance, using a mathematical model of a metabolic network in P. aeruginosa. To our knowledge, this is the first mathematical model of denitrification for this bacterium. Analysis of the long-term behavior of the network under changing concentration levels of oxygen (O₂), nitrate (NO₃),more » and phosphate (PO₄) suggests that PO₄ concentration strongly affects denitrification performance. The model provides three predictions on denitrification activity of P. aeruginosa under various environmental conditions, and these predictions are either experimentally validated or supported by pertinent biological literature. One motivation for this study is to capture the effect of PO₄ on a denitrification metabolic network of P. aeruginosa in order to shed light on mechanisms for greenhouse gas N₂O accumulation during seasonal oxygen depletion in aquatic environments such as Lake Erie (Laurentian Great Lakes, USA). Simulating the microbial production of greenhouse gases in anaerobic aquatic systems such as Lake Erie allows a deeper understanding of the contributing environmental effects that will inform studies on, and remediation strategies for, other hypoxic sites worldwide.« less

  19. An application of neural networks to process and materials control

    SciTech Connect (OSTI)

    Howell, J.A.; Whiteson, R. )

    1991-01-01

    Process control consists of two basic elements: a model of the process and knowledge of the desired control algorithm. In some cases the level of the control algorithm is merely supervisory, as in an alarm-reporting or anomaly-detection system. If the model of the process is known, then a set of equations may often be solved explicitly to provide the control algorithm. Otherwise, the model has to be discovered through empirical studies. Neural networks have properties that make them useful in this application. The problems of anomaly detection in nuclear materials control systems fits well into this general control framework. To successfully model a process with a neutral network, a good set of observable must be chosen. These observable just in some sense adequately span the space of representable events, so that a signature metric can be built for normal operation. In this way, a non-normal event, one that does not fit within the signature, can be detected. In this paper, the authors discuss the issues involved in applying a neural network model to anomaly detection in materials control systems.

  20. Application of neural networks to waste site screening

    SciTech Connect (OSTI)

    Dabiri, A.E.; Kraft, T.; Hilton, J.M.

    1993-03-01

    Waste site screening requires knowledge of the actual concentrations of hazardous materials and rates of flow around and below the site with time. The present approach to site screening consists primarily of drilling, boreholes near contaminated site and chemically analyzing the extracted physical samples and processing the data. In addition, hydraulic and geochemical soil properties are obtained so that numerical simulation models can be used to interpret and extrapolate the field data. The objective of this work is to investigate the feasibility of using neural network techniques to reduce the cost of waste site screening. A successful technique may lead to an ability to reduce the number of boreholes and the number of samples analyzed from each borehole to properly screen the waste site. The analytic tool development described here is inexpensive because it makes use of neural network techniques that can interpolate rapidly and which can learn how to analyze data rather than having to be explicitly programmed. In the following sections, data collection and data analyses will be described, followed by a section on different neural network techniques used. The results will be presented and compared with mathematical model. Finally, the last section will summarize the research work performed and make several recommendations for future work.

  1. The Olympics of science knowledge at PPPL's NJ Regional Science...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Olympics of science knowledge at PPPL's NJ Regional Science Bowl By Jeanne Jackson DeVoe March 3, 2014 Tweet Widget Google Plus One Share on Facebook The J Droids, a science ...

  2. The Olympics of science knowledge at DOE's New Jersey Regional...

    Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

    The Olympics of science knowledge at DOE's New Jersey Regional Science Bowl at PPPL By Jeanne Jackson DeVoe March 3, 2014 Tweet Widget Google Plus One Share on Facebook The J ...

  3. Energy Efficiency Exchange 2015: Federal Training and Knowledge

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

    Energy Efficiency Exchange 2015: Federal Training and Knowledge Overview Webinars: March 25 & April 8, 2015 Timothy D. Unruh PhD, PE, CEM Program Director DOE FEMP 2 Energy...

  4. The Importance of Traditional Ecological Knowledge in Adaptation Planning

    Broader source: Energy.gov [DOE]

    The National Adaptation Forum is hosting a webinar to focus on the importance and role of traditional ecological knowledge in adaptation planning at the local, regional, and national level.

  5. Synchronized Biological Knowledge and Data Management: A Hybrid Approach

    SciTech Connect (OSTI)

    Stephan, Eric G.; Chin, George; Corrigan, Abbie L.; Klicker, Kyle R.; Sofia, Heidi J.

    2004-06-23

    The new systems approach to biology has created a great need for innovative database technologies. Biologists need new ways to integrate large scale data and concepts they form about the data during experimental and computational research. The Heuristic Entity Relationship Building Environment (HERBE) is a new prototypical architecture fusing data management technologies with knowledge management components. This hybrid approach enables the scientist to manage both their concepts and related data in a synchronized fashion. HERBE is currently being used for microbial research and in this paper we will describe how HERBE is used to capture microbial protein concepts grouped by organism, how the microbial proteins are reengineered into a combined knowledge on multiple microbial organisms, and how the data associated with the organisms can be mined. This paper also describes how the scientist’s evolving knowledge can be annotated by connecting the biologist’s knowledge to community resources such as the Gene Ontology.

  6. The Path to Transforming Knowledge into Energy Projects: DOE Tribal

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

    Renewable Energy Webinar Series 2015 | Department of Energy The Path to Transforming Knowledge into Energy Projects: DOE Tribal Renewable Energy Webinar Series 2015 The Path to Transforming Knowledge into Energy Projects: DOE Tribal Renewable Energy Webinar Series 2015 Learn more about the 2015 Tribal Renewable Energy Webinar Series and read detailed descriptions about each of the monthly webinars in the flier below. DOE Tribal Renewable Energy Webinar Series 2015 Flier (613.37 KB) More

  7. To the Cloud! Apidae Helps Modelers Turn Information into Knowledge |

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

    Department of Energy To the Cloud! Apidae Helps Modelers Turn Information into Knowledge To the Cloud! Apidae Helps Modelers Turn Information into Knowledge October 26, 2015 - 2:41pm Addthis Apidae is a collection of cloud-based simulation and data analysis tools that help modelers better understand their models. Image credit: BUILDlab. Apidae is a collection of cloud-based simulation and data analysis tools that help modelers better understand their models. Image credit: BUILDlab. Apidae

  8. Bioenergy Knowledge Discovery Framework Recognized at National Conference |

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

    Department of Energy Knowledge Discovery Framework Recognized at National Conference Bioenergy Knowledge Discovery Framework Recognized at National Conference December 17, 2014 - 4:14pm Addthis The paper and poster presentation "Bioenergy KDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration" was awarded second place for best paper at the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, held November 4-7 in Dallas, Texas. It

  9. The process for integrating the NNSA knowledge base.

    SciTech Connect (OSTI)

    Wilkening, Lisa K.; Carr, Dorthe Bame; Young, Christopher John; Hampton, Jeff; Martinez, Elaine

    2009-03-01

    From 2002 through 2006, the Ground Based Nuclear Explosion Monitoring Research & Engineering (GNEMRE) program at Sandia National Laboratories defined and modified a process for merging different types of integrated research products (IRPs) from various researchers into a cohesive, well-organized collection know as the NNSA Knowledge Base, to support operational treaty monitoring. This process includes defining the KB structure, systematically and logically aggregating IRPs into a complete set, and verifying and validating that the integrated Knowledge Base works as expected.

  10. 'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

    SciTech Connect (OSTI)

    Sukumar, Sreenivas R; Ferrell, Regina Kay

    2013-01-01

    As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elements of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.