Science.gov

Sample records for lcg mcdb-a knowledgebase

  1. LCG MCDB—a knowledgebase of Monte-Carlo simulated events

    NASA Astrophysics Data System (ADS)

    Belov, S.; Dudko, L.; Galkin, E.; Gusev, A.; Pokorski, W.; Sherstnev, A.

    2008-02-01

    In this paper we report on LCG Monte-Carlo Data Base (MCDB) and software which has been developed to operate MCDB. The main purpose of the LCG MCDB project is to provide a storage and documentation system for sophisticated event samples simulated for the LHC Collaborations by experts. In many cases, the modern Monte-Carlo simulation of physical processes requires expert knowledge in Monte-Carlo generators or significant amount of CPU time to produce the events. MCDB is a knowledgebase mainly dedicated to accumulate simulated events of this type. The main motivation behind LCG MCDB is to make the sophisticated MC event samples available for various physical groups. All the data from MCDB is accessible in several convenient ways. LCG MCDB is being developed within the CERN LCG Application Area Simulation project. Program summaryProgram title: LCG Monte-Carlo Data Base Catalogue identifier: ADZX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public Licence No. of lines in distributed program, including test data, etc.: 30 129 No. of bytes in distributed program, including test data, etc.: 216 943 Distribution format: tar.gz Programming language: Perl Computer: CPU: Intel Pentium 4, RAM: 1 Gb, HDD: 100 Gb Operating system: Scientific Linux CERN 3/4 RAM: 1 073 741 824 bytes (1 Gb) Classification: 9 External routines:perl >= 5.8.5; Perl modules DBD-mysql >= 2.9004, File::Basename, GD::SecurityImage, GD::SecurityImage::AC, Linux::Statistics, XML::LibXML > 1.6, XML::SAX, XML::NamespaceSupport; Apache HTTP Server >= 2.0.59; mod auth external >= 2.2.9; edg-utils-system RPM package; gd >= 2.0.28; rpm package CASTOR-client >= 2.1.2-4; arc-server (optional) Nature of problem: Often, different groups of experimentalists prepare similar samples of particle collision events or turn to the same group of authors of Monte-Carlo (MC

  2. LcgCAF: CDF access method to LCG resources

    NASA Astrophysics Data System (ADS)

    Compostella, Gabriele; Bauce, Matteo; Pagan Griso, Simone; Lucchesi, Donatella; Sgaravatto, Massimo; Cecchi, Marco

    2011-12-01

    Up to the early 2011, the CDF collaboration has collected more than 8 fb-1 of data from pbar p collisions at a center of mass energy TeV delivered by the Tevatron collider at Fermilab. Second generation physics measurements, like precision determinations of top properties or searches for the Standard Model higgs, require increasing computing power for data analysis and events simulation. Instead of expanding its set of dedicated Condor based analysis farms, CDF moved to Grid resources. While in the context of OSG this transition was performed using Condor glideins and keeping CDF custom middleware software almost intact, in LCG a complete rewrite of the experiment's submission and monitoring tools was realized, taking full advantage of the features offered by the gLite Workload Management System (WMS). This led to the development of a new computing facility called LcgCAF that CDF collaborators are using to exploit Grid resources in Europe in a transparent way. Given the opportunistic usage of the available resources, it is of crucial importance for CDF to maximize jobs efficiency from submission to output retrieval. This work describes how an experimental resubmisson feature implemented in the WMS was tested in LcgCAF with the aim of lowering the overall execution time of a typical CDF job.

  3. WHALE, a management tool for Tier-2 LCG sites

    NASA Astrophysics Data System (ADS)

    Barone, L. M.; Organtini, G.; Talamo, I. G.

    2012-12-01

    The LCG (Worldwide LHC Computing Grid) is a grid-based hierarchical computing distributed facility, composed of more than 140 computing centers, organized in 4 tiers, by size and offer of services. Every site, although indipendent for many technical choices, has to provide services with a well-defined set of interfaces. For this reason, different LCG sites need frequently to manage very similar situations, like jobs behaviour on the batch system, dataset transfers between sites, operating system and experiment software installation and configuration, monitoring of services. In this context we created WHALE (WHALE Handles Administration in an LCG Environment), a software actually used at the T2_IT_Rome site, an LCG Tier-2 for the CMS experiment. WHALE is a generic, site independent tool written in Python: it allows administrator to interact in a uniform and coherent way with several subsystems using a high level syntax which hides specific commands. The architecture of WHALE is based on the plugin concept and on the possibility of connecting the output of a plugin to the input of the next one, in a pipe-like system, giving the administrator the possibility of making complex functions by combining the simpler ones. The core of WHALE just handles the plugin orchestrations, while even the basic functions (eg. the WHALE activity logging) are performed by plugins, giving the capability to tune and possibly modify every component of the system. WHALE already provides many plugins useful for a LCG site and some more for a Tier-2 of the CMS experiment, especially in the field of job management, dataset transfer and analysis of performance results and availability tests (eg. Nagios tests, SAM tests). Thanks to its architecture and the provided plugins WHALE makes easy to perform tasks that, even if logically simple, are technically complex or tedious, like eg. closing all the worker nodes with a job-failure rate greater than a given threshold. Finally, thanks to the

  4. A lightweight high availability strategy for Atlas LCG File Catalogs

    NASA Astrophysics Data System (ADS)

    Martelli, Barbara; de Salvo, Alessandro; Anzellotti, Daniela; Rinaldi, Lorenzo; Cavalli, Alessandro; dal Pra, Stefano; dell'Agnello, Luca; Gregori, Daniele; Prosperini, Andrea; Ricci, Pier Paolo; Sapunenko, Vladimir

    2010-04-01

    The LCG File Catalog is a key component of the LHC Computing Grid middleware [1], as it contains the mapping between Logical File Names and Physical File Names on the Grid. The Atlas computing model foresees multiple local LFC housed in each Tier-1 and Tier-0, containing all information about files stored in the regional cloud. As the local LFC contents are presently not replicated anywhere, this turns out in a dangerous single point of failure for all of the Atlas regional clouds. In order to solve this problem we propose a novel solution for high availability (HA) of Oracle based Grid services, obtained by composing an Oracle Data Guard deployment and a series of application level scripts. This approach has the advantage of being very easy to deploy and maintain, and represents a good candidate solution for all Tier-2s which are usually little centres with little manpower dedicated to service operations. We also present the results of a wide range of functionality and performance tests run on a test-bed having characteristics similar to the ones required for production. The test-bed consists of a failover deployment between the Italian LHC Tier-1 (INFN - CNAF) and an Atlas Tier-2 located at INFN - Roma1. Moreover, we explain how the proposed strategy can be deployed on the present Grid infrastructure, without requiring any change to the middleware and in a way that is totally transparent to end users and applications.

  5. The Knowledgebase Kibbutz

    ERIC Educational Resources Information Center

    Singer, Ross

    2008-01-01

    As libraries' collections increasingly go digital, so too does their dependence on knowledgebases to access and maintain these electronic holdings. Somewhat different from other library-based knowledge management systems (catalogs, institutional repositories, etc.), the data found in the knowledgebases of link resolvers or electronic resource…

  6. The Knowledgebase Kibbutz

    ERIC Educational Resources Information Center

    Singer, Ross

    2008-01-01

    As libraries' collections increasingly go digital, so too does their dependence on knowledgebases to access and maintain these electronic holdings. Somewhat different from other library-based knowledge management systems (catalogs, institutional repositories, etc.), the data found in the knowledgebases of link resolvers or electronic resource…

  7. Knowledge-Based Abstracting.

    ERIC Educational Resources Information Center

    Black, William J.

    1990-01-01

    Discussion of automatic abstracting of technical papers focuses on a knowledge-based method that uses two sets of rules. Topics discussed include anaphora; text structure and discourse; abstracting techniques, including the keyword method and the indicator phrase method; and tools for text skimming. (27 references) (LRW)

  8. Space Environmental Effects Knowledgebase

    NASA Technical Reports Server (NTRS)

    Wood, B. E.

    2007-01-01

    This report describes the results of an NRA funded program entitled Space Environmental Effects Knowledgebase that received funding through a NASA NRA (NRA8-31) and was monitored by personnel in the NASA Space Environmental Effects (SEE) Program. The NASA Project number was 02029. The Satellite Contamination and Materials Outgassing Knowledgebase (SCMOK) was created as a part of the earlier NRA8-20. One of the previous tasks and part of the previously developed Knowledgebase was to accumulate data from facilities using QCMs to measure the outgassing data for satellite materials. The main object of this current program was to increase the number of material outgassing datasets from 250 up to approximately 500. As a part of this effort, a round-robin series of materials outgassing measurements program was also executed that allowed comparison of the results for the same materials tested in 10 different test facilities. Other programs tasks included obtaining datasets or information packages for 1) optical effects of contaminants on optical surfaces, thermal radiators, and sensor systems and 2) space environmental effects data and incorporating these data into the already existing NASA/SEE Knowledgebase.

  9. Experience with the gLite workload management system in ATLAS Monte Carlo production on LCG

    NASA Astrophysics Data System (ADS)

    Campana, S.; Rebatto, D.; Sciaba', A.

    2008-07-01

    The ATLAS experiment has been running continuous simulated events production since more than two years. A considerable fraction of the jobs is daily submitted and handled via the gLite Workload Management System, which overcomes several limitations of the previous LCG Resource Broker. The gLite WMS has been tested very intensively for the LHC experiments use cases for more than six months, both in terms of performance and reliability. The tests were carried out by the LCG Experiment Integration Support team (in close contact with the experiments) together with the EGEE integration and certification team and the gLite middleware developers. A pragmatic iterative and interactive approach allowed a very quick rollout of fixes and their rapid deployment, together with new functionalities, for the ATLAS production activities. The same approach is being adopted for other middleware components like the gLite and CREAM Computing Elements. In this contribution we will summarize the learning from the gLite WMS testing activity, pointing out the most important achievements and the open issues. In addition, we will present the current situation of the ATLAS simulated event production activity on the EGEE infrastructure based on the gLite WMS, showing the main improvements and benefits from the new middleware. Finally, the gLite WMS is being used by many other VOs, including the LHC experiments. In particular, some statistics will be shown on the CMS experience running WMS user analysis via the WMS

  10. Standard biological parts knowledgebase.

    PubMed

    Galdzicki, Michal; Rodriguez, Cesar; Chandran, Deepak; Sauro, Herbert M; Gennari, John H

    2011-02-24

    We have created the Knowledgebase of Standard Biological Parts (SBPkb) as a publically accessible Semantic Web resource for synthetic biology (sbolstandard.org). The SBPkb allows researchers to query and retrieve standard biological parts for research and use in synthetic biology. Its initial version includes all of the information about parts stored in the Registry of Standard Biological Parts (partsregistry.org). SBPkb transforms this information so that it is computable, using our semantic framework for synthetic biology parts. This framework, known as SBOL-semantic, was built as part of the Synthetic Biology Open Language (SBOL), a project of the Synthetic Biology Data Exchange Group. SBOL-semantic represents commonly used synthetic biology entities, and its purpose is to improve the distribution and exchange of descriptions of biological parts. In this paper, we describe the data, our methods for transformation to SBPkb, and finally, we demonstrate the value of our knowledgebase with a set of sample queries. We use RDF technology and SPARQL queries to retrieve candidate "promoter" parts that are known to be both negatively and positively regulated. This method provides new web based data access to perform searches for parts that are not currently possible.

  11. The Reactome pathway Knowledgebase

    PubMed Central

    Fabregat, Antonio; Sidiropoulos, Konstantinos; Garapati, Phani; Gillespie, Marc; Hausmann, Kerstin; Haw, Robin; Jassal, Bijay; Jupe, Steven; Korninger, Florian; McKay, Sheldon; Matthews, Lisa; May, Bruce; Milacic, Marija; Rothfels, Karen; Shamovsky, Veronica; Webber, Marissa; Weiser, Joel; Williams, Mark; Wu, Guanming; Stein, Lincoln; Hermjakob, Henning; D'Eustachio, Peter

    2016-01-01

    The Reactome Knowledgebase (www.reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations—an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression pattern surveys or somatic mutation catalogues from tumour cells. Over the last two years we redeveloped major components of the Reactome web interface to improve usability, responsiveness and data visualization. A new pathway diagram viewer provides a faster, clearer interface and smooth zooming from the entire reaction network to the details of individual reactions. Tool performance for analysis of user datasets has been substantially improved, now generating detailed results for genome-wide expression datasets within seconds. The analysis module can now be accessed through a RESTFul interface, facilitating its inclusion in third party applications. A new overview module allows the visualization of analysis results on a genome-wide Reactome pathway hierarchy using a single screen page. The search interface now provides auto-completion as well as a faceted search to narrow result lists efficiently. PMID:26656494

  12. ECOTOX knowledgebase: Search features and customized reports

    EPA Science Inventory

    The ECOTOXicology knowledgebase (ECOTOX) is a comprehensive, publicly available knowledgebase developed and maintained by ORD/NHEERL. It is used for environmental toxicity data on aquatic life, terrestrial plants and wildlife. ECOTOX has the capability to refine and filter search...

  13. ECOTOX knowledgebase: Search features and customized reports

    EPA Science Inventory

    The ECOTOXicology knowledgebase (ECOTOX) is a comprehensive, publicly available knowledgebase developed and maintained by ORD/NHEERL. It is used for environmental toxicity data on aquatic life, terrestrial plants and wildlife. ECOTOX has the capability to refine and filter search...

  14. Knowledge-Based Image Analysis.

    DTIC Science & Technology

    1981-04-01

    UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface

  15. Knowledge-based media adaptation

    NASA Astrophysics Data System (ADS)

    Leopold, Klaus; Jannach, Dietmar; Hellwagner, Hermann

    2004-10-01

    This paper introduces the principal approach and describes the basic architecture and current implementation of the knowledge-based multimedia adaptation framework we are currently developing. The framework can be used in Universal Multimedia Access scenarios, where multimedia content has to be adapted to specific usage environment parameters (network and client device capabilities, user preferences). Using knowledge-based techniques (state-space planning), the framework automatically computes an adaptation plan, i.e., a sequence of media conversion operations, to transform the multimedia resources to meet the client's requirements or constraints. The system takes as input standards-compliant descriptions of the content (using MPEG-7 metadata) and of the target usage environment (using MPEG-21 Digital Item Adaptation metadata) to derive start and goal states for the planning process, respectively. Furthermore, declarative descriptions of the conversion operations (such as available via software library functions) enable existing adaptation algorithms to be invoked without requiring programming effort. A running example in the paper illustrates the descriptors and techniques employed by the knowledge-based media adaptation system.

  16. Knowledge-based nursing diagnosis

    NASA Astrophysics Data System (ADS)

    Roy, Claudette; Hay, D. Robert

    1991-03-01

    Nursing diagnosis is an integral part of the nursing process and determines the interventions leading to outcomes for which the nurse is accountable. Diagnoses under the time constraints of modern nursing can benefit from a computer assist. A knowledge-based engineering approach was developed to address these problems. A number of problems were addressed during system design to make the system practical extended beyond capture of knowledge. The issues involved in implementing a professional knowledge base in a clinical setting are discussed. System functions, structure, interfaces, health care environment, and terminology and taxonomy are discussed. An integrated system concept from assessment through intervention and evaluation is outlined.

  17. Cooperating knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Feigenbaum, Edward A.; Buchanan, Bruce G.

    1988-01-01

    This final report covers work performed under Contract NCC2-220 between NASA Ames Research Center and the Knowledge Systems Laboratory, Stanford University. The period of research was from March 1, 1987 to February 29, 1988. Topics covered were as follows: (1) concurrent architectures for knowledge-based systems; (2) methods for the solution of geometric constraint satisfaction problems, and (3) reasoning under uncertainty. The research in concurrent architectures was co-funded by DARPA, as part of that agency's Strategic Computing Program. The research has been in progress since 1985, under DARPA and NASA sponsorship. The research in geometric constraint satisfaction has been done in the context of a particular application, that of determining the 3-D structure of complex protein molecules, using the constraints inferred from NMR measurements.

  18. The Coming of Knowledge-Based Business.

    ERIC Educational Resources Information Center

    Davis, Stan; Botkin, Jim

    1994-01-01

    Economic growth will come from knowledge-based businesses whose "smart" products filter and interpret information. Businesses will come to think of themselves as educators and their customers as learners. (SK)

  19. The Coming of Knowledge-Based Business.

    ERIC Educational Resources Information Center

    Davis, Stan; Botkin, Jim

    1994-01-01

    Economic growth will come from knowledge-based businesses whose "smart" products filter and interpret information. Businesses will come to think of themselves as educators and their customers as learners. (SK)

  20. Protective Effects of the Launch/Entry Suit (LES) and the Liquid Cooling Garment(LCG) During Re-entry and Landing After Spaceflight

    NASA Technical Reports Server (NTRS)

    Perez, Sondra A.; Charles, John B.; Fortner, G. William; Hurst, Victor, IV; Meck, Janice V.

    2002-01-01

    Heart rate and arterial pressure were measured during shuttle re-entry, landing and initial standing in crewmembers with and without inflated anti-g suits and with and without liquid cooling garments (LCG). Preflight, three measurements were obtained seated, then standing. Prior to and during re-entry, arterial pressure and heart rate were measured every five minutes until wheels stop (WS). Then crewmembers initiated three seated and three standing measurements. In subjects without inflated anti-g suits, SBP and DBP were significantly lower during preflight standing (P = 0.006; P = 0.001 respectively) and at touchdown (TD) (P = 0.001; P = 0.003 respectively); standing SBP was significantly lower after WS. on-LeG users developed significantly higher heart rates during re-entry (P = 0.029, maxG; P = 0.05, TD; P = 0.02, post-WS seated; P = 0.01, post-WS standing) than LCG users. Our data suggest that the anti-g suit is effective, but the combined anti-g suit with LCG is more effective.

  1. Distributed, cooperating knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Truszkowski, Walt

    1991-01-01

    Some current research in the development and application of distributed, cooperating knowledge-based systems technology is addressed. The focus of the current research is the spacecraft ground operations environment. The underlying hypothesis is that, because of the increasing size, complexity, and cost of planned systems, conventional procedural approaches to the architecture of automated systems will give way to a more comprehensive knowledge-based approach. A hallmark of these future systems will be the integration of multiple knowledge-based agents which understand the operational goals of the system and cooperate with each other and the humans in the loop to attain the goals. The current work includes the development of a reference model for knowledge-base management, the development of a formal model of cooperating knowledge-based agents, the use of testbed for prototyping and evaluating various knowledge-based concepts, and beginning work on the establishment of an object-oriented model of an intelligent end-to-end (spacecraft to user) system. An introductory discussion of these activities is presented, the major concepts and principles being investigated are highlighted, and their potential use in other application domains is indicated.

  2. Patient Dependency Knowledge-Based Systems.

    PubMed

    Soliman, F

    1998-10-01

    The ability of Patient Dependency Systems to provide information for staffing decisions and budgetary development has been demonstrated. In addition, they have become powerful tools in modern hospital management. This growing interest in Patient Dependency Systems has renewed calls for their automation. As advances in Information Technology and in particular Knowledge-Based Engineering reach new heights, hospitals can no longer afford to ignore the potential benefits obtainable from developing and implementing Patient Dependency Knowledge-Based Systems. Experience has shown that the vast majority of decisions and rules used in the Patient Dependency method are too complex to capture in the form of a traditional programming language. Furthermore, the conventional Patient Dependency Information System automates the simple and rigid bookkeeping functions. On the other hand Knowledge-Based Systems automate complex decision making and judgmental processes and therefore are the appropriate technology for automating the Patient Dependency method. In this paper a new technique to automate Patient Dependency Systems using knowledge processing is presented. In this approach all Patient Dependency factors have been translated into a set of Decision Rules suitable for use in a Knowledge-Based System. The system is capable of providing the decision-maker with a number of scenarios and their possible outcomes. This paper also presents the development of Patient Dependency Knowledge-Based Systems, which can be used in allocating and evaluating resources and nursing staff in hospitals on the basis of patients' needs.

  3. Knowledge-based systems and NASA's software support environment

    NASA Technical Reports Server (NTRS)

    Dugan, Tim; Carmody, Cora; Lennington, Kent; Nelson, Bob

    1990-01-01

    A proposed role for knowledge-based systems within NASA's Software Support Environment (SSE) is described. The SSE is chartered to support all software development for the Space Station Freedom Program (SSFP). This includes support for development of knowledge-based systems and the integration of these systems with conventional software systems. In addition to the support of development of knowledge-based systems, various software development functions provided by the SSE will utilize knowledge-based systems technology.

  4. Knowledge-based diagnosis for aerospace systems

    NASA Technical Reports Server (NTRS)

    Atkinson, David J.

    1988-01-01

    The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

  5. A knowledge-based approach to design

    NASA Astrophysics Data System (ADS)

    Mitchell, T. M.; Steinberg, L. I.; Shulman, J. S.

    1985-09-01

    The potential advantages of knowledge-based methods for computer-aided design are examined, and the organization of VEXED, a knowledge-based system for VLSI design, is described in detail. In particular, attention is given to the principles underlying the design of VEXED and several issues that have arisen from implementing and experimenting with the prototype system. The issues discussed include questions regarding the grainsize of rules, the possibility of learning new rules automatically, and issues related to constraint propagation and management.

  6. Knowledge-based commodity distribution planning

    NASA Technical Reports Server (NTRS)

    Saks, Victor; Johnson, Ivan

    1994-01-01

    This paper presents an overview of a Decision Support System (DSS) that incorporates Knowledge-Based (KB) and commercial off the shelf (COTS) technology components. The Knowledge-Based Logistics Planning Shell (KBLPS) is a state-of-the-art DSS with an interactive map-oriented graphics user interface and powerful underlying planning algorithms. KBLPS was designed and implemented to support skilled Army logisticians to prepare and evaluate logistics plans rapidly, in order to support corps-level battle scenarios. KBLPS represents a substantial advance in graphical interactive planning tools, with the inclusion of intelligent planning algorithms that provide a powerful adjunct to the planning skills of commodity distribution planners.

  7. Knowledge-Based Instructional Gaming: GEO.

    ERIC Educational Resources Information Center

    Duchastel, Philip

    1989-01-01

    Describes the design and development of an instructional game, GEO, in which the user learns elements of Canadian geography. The use of knowledge-based artificial intelligence techniques is discussed, the use of HyperCard in the design of GEO is explained, and future directions are suggested. (15 references) (Author/LRW)

  8. Knowledge-Based Instructional Gaming: GEO.

    ERIC Educational Resources Information Center

    Duchastel, Philip

    1989-01-01

    Describes the design and development of an instructional game, GEO, in which the user learns elements of Canadian geography. The use of knowledge-based artificial intelligence techniques is discussed, the use of HyperCard in the design of GEO is explained, and future directions are suggested. (15 references) (Author/LRW)

  9. Knowledge-Based Inferences Are Not General

    ERIC Educational Resources Information Center

    Shears, Connie; Chiarello, Christine

    2004-01-01

    Although knowledge-based inferences (Graesser, Singer, & Trabasso, 1994) depend on general knowledge, there may be differences across knowledge areas in how they support these processes. This study explored processing differences between 2 areas of knowledge (physical cause?effect vs. goals and planning) to establish (a) that each would support…

  10. Analysis of Unit-Level Changes in Operations with Increased SPP Wind from EPRI/LCG Balancing Study

    SciTech Connect

    Hadley, Stanton W

    2012-01-01

    Wind power development in the United States is outpacing previous estimates for many regions, particularly those with good wind resources. The pace of wind power deployment may soon outstrip regional capabilities to provide transmission and integration services to achieve the most economic power system operation. Conversely, regions such as the Southeastern United States do not have good wind resources and will have difficulty meeting proposed federal Renewable Portfolio Standards with local supply. There is a growing need to explore innovative solutions for collaborating between regions to achieve the least cost solution for meeting such a renewable energy mandate. The Department of Energy funded the project 'Integrating Midwest Wind Energy into Southeast Electricity Markets' to be led by EPRI in coordination with the main authorities for the regions: SPP, Entergy, TVA, Southern Company and OPC. EPRI utilized several subcontractors for the project including LCG, the developers of the model UPLAN. The study aims to evaluate the operating cost benefits of coordination of scheduling and balancing for Southwest Power Pool (SPP) wind transfers to Southeastern Electric Reliability Council (SERC) Balancing Authorities (BAs). The primary objective of this project is to analyze the benefits of regional cooperation for integrating mid-western wind energy into southeast electricity markets. Scenarios were defined, modeled and investigated to address production variability and uncertainty and the associated balancing of large quantities of wind power in SPP and delivery to energy markets in the southern regions of the SERC. DOE funded Oak Ridge National Laboratory to provide additional support to the project, including a review of results and any side analysis that may provide additional insight. This report is a unit-by-unit analysis of changes in operations due to the different scenarios used in the overall study. It focuses on the change in capacity factors and the number

  11. The importance of knowledge-based technology.

    PubMed

    Cipriano, Pamela F

    2012-01-01

    Nurse executives are responsible for a workforce that can provide safer and more efficient care in a complex sociotechnical environment. National quality priorities rely on technologies to provide data collection, share information, and leverage analytic capabilities to interpret findings and inform approaches to care that will achieve better outcomes. As a key steward for quality, the nurse executive exercises leadership to provide the infrastructure to build and manage nursing knowledge and instill accountability for following evidence-based practices. These actions contribute to a learning health system where new knowledge is captured as a by-product of care delivery enabled by knowledge-based electronic systems. The learning health system also relies on rigorous scientific evidence embedded into practice at the point of care. The nurse executive optimizes use of knowledge-based technologies, integrated throughout the organization, that have the capacity to help transform health care.

  12. Knowledge-Based Entrepreneurship in a Boundless Research System

    ERIC Educational Resources Information Center

    Dell'Anno, Davide

    2008-01-01

    International entrepreneurship and knowledge-based entrepreneurship have recently generated considerable academic and non-academic attention. This paper explores the "new" field of knowledge-based entrepreneurship in a boundless research system. Cultural barriers to the development of business opportunities by researchers persist in some academic…

  13. Knowledge-Based Entrepreneurship in a Boundless Research System

    ERIC Educational Resources Information Center

    Dell'Anno, Davide

    2008-01-01

    International entrepreneurship and knowledge-based entrepreneurship have recently generated considerable academic and non-academic attention. This paper explores the "new" field of knowledge-based entrepreneurship in a boundless research system. Cultural barriers to the development of business opportunities by researchers persist in some academic…

  14. Knowledge-based public health situation awareness

    NASA Astrophysics Data System (ADS)

    Mirhaji, Parsa; Zhang, Jiajie; Srinivasan, Arunkumar; Richesson, Rachel L.; Smith, Jack W.

    2004-09-01

    There have been numerous efforts to create comprehensive databases from multiple sources to monitor the dynamics of public health and most specifically to detect the potential threats of bioterrorism before widespread dissemination. But there are not many evidences for the assertion that these systems are timely and dependable, or can reliably identify man made from natural incident. One must evaluate the value of so called 'syndromic surveillance systems' along with the costs involved in design, development, implementation and maintenance of such systems and the costs involved in investigation of the inevitable false alarms1. In this article we will introduce a new perspective to the problem domain with a shift in paradigm from 'surveillance' toward 'awareness'. As we conceptualize a rather different approach to tackle the problem, we will introduce a different methodology in application of information science, computer science, cognitive science and human-computer interaction concepts in design and development of so called 'public health situation awareness systems'. We will share some of our design and implementation concepts for the prototype system that is under development in the Center for Biosecurity and Public Health Informatics Research, in the University of Texas Health Science Center at Houston. The system is based on a knowledgebase containing ontologies with different layers of abstraction, from multiple domains, that provide the context for information integration, knowledge discovery, interactive data mining, information visualization, information sharing and communications. The modular design of the knowledgebase and its knowledge representation formalism enables incremental evolution of the system from a partial system to a comprehensive knowledgebase of 'public health situation awareness' as it acquires new knowledge through interactions with domain experts or automatic discovery of new knowledge.

  15. Knowledge-based systems in Japan

    NASA Technical Reports Server (NTRS)

    Feigenbaum, Edward; Engelmore, Robert S.; Friedland, Peter E.; Johnson, Bruce B.; Nii, H. Penny; Schorr, Herbert; Shrobe, Howard

    1994-01-01

    This report summarizes a study of the state-of-the-art in knowledge-based systems technology in Japan, organized by the Japanese Technology Evaluation Center (JTEC) under the sponsorship of the National Science Foundation and the Advanced Research Projects Agency. The panel visited 19 Japanese sites in March 1992. Based on these site visits plus other interactions with Japanese organizations, both before and after the site visits, the panel prepared a draft final report. JTEC sent the draft to the host organizations for their review. The final report was published in May 1993.

  16. Systems Biology Knowledgebase (GSC8 Meeting)

    ScienceCinema

    Cottingham, Robert W [ORNL

    2016-07-12

    The Genomic Standards Consortium was formed in September 2005. It is an international, open-membership working body which promotes standardization in the description of genomes and the exchange and integration of genomic data. The 2009 meeting was an activity of a five-year funding "Research Coordination Network" from the National Science Foundation and was organized held at the DOE Joint Genome Institute with organizational support provided by the JGI and by the University of California - San Diego. Robert W. Cottingham of Oak Ridge National Laboratory discusses the DOE KnowledgeBase at the Genomic Standards Consortium's 8th meeting at the DOE JGI in Walnut Creek, Calif. on Sept. 9, 2009.

  17. Knowledge-based Autonomous Test Engineer (KATE)

    NASA Technical Reports Server (NTRS)

    Parrish, Carrie L.; Brown, Barbara L.

    1991-01-01

    Mathematical models of system components have long been used to allow simulators to predict system behavior to various stimuli. Recent efforts to monitor, diagnose, and control real-time systems using component models have experienced similar success. NASA Kennedy is continuing the development of a tool for implementing real-time knowledge-based diagnostic and control systems called KATE (Knowledge based Autonomous Test Engineer). KATE is a model-based reasoning shell designed to provide autonomous control, monitoring, fault detection, and diagnostics for complex engineering systems by applying its reasoning techniques to an exchangeable quantitative model describing the structure and function of the various system components and their systemic behavior.

  18. An Introduction to the Heliophysics Event Knowledgebase

    NASA Astrophysics Data System (ADS)

    Hurlburt, Neal E.; Cheung, M.; Schrijver, C.; Chang, L.; Freeland, S.; Green, S.; Heck, C.; Jaffey, A.; Kobashi, A.; Schiff, D.; Serafin, J.; Seguin, R.; Slater, G.; Somani, A.; Timmons, R.

    2010-05-01

    The immense volume of data generated by the suite of instruments on SDO requires new tools for efficiently identifying and accessing data that are most relevant to research investigations. We have developed the Heliophysics Events Knowledgebase (HEK) to fill this need. The system developed to support the HEK combines automated datamining using feature detection methods; high-performance visualization systems for data markup; and web-services and clients for searching the resulting metadata, reviewing results and efficient access to the data. We will review these components and present examples of their use with SDO data.

  19. Bioenergy Science Center KnowledgeBase

    DOE Data Explorer

    Syed, M. H.; Karpinets, T. V.; Parang, M.; Leuze, M. R.; Park, B. H.; Hyatt, D.; Brown, S. D.; Moulton, S. Galloway, M.D.; Uberbacher, E. C.

    The challenge of converting cellulosic biomass to sugars is the dominant obstacle to cost effective production of biofuels in s capable of significant enough quantities to displace U. S. consumption of fossil transportation fuels. The BioEnergy Science Center (BESC) tackles this challenge of biomass recalcitrance by closely linking (1) plant research to make cell walls easier to deconstruct, and (2) microbial research to develop multi-talented biocatalysts tailor-made to produce biofuels in a single step. [from the 2011 BESC factsheet] The BioEnergy Science Center (BESC) is a multi-institutional, multidisciplinary research (biological, chemical, physical and computational sciences, mathematics and engineering) organization focused on the fundamental understanding and elimination of biomass recalcitrance. The BESC Knowledgebase and its associated tools is a discovery platform for bioenergy research. It consists of a collection of metadata, data, and computational tools for data analysis, integration, comparison and visualization for plants and microbes in the center.The BESC Knowledgebase (KB) and BESC Laboratory Information Management System (LIMS) enable bioenergy researchers to perform systemic research. [http://bobcat.ornl.gov/besc/index.jsp

  20. Knowledge-based representations of risk beliefs.

    PubMed

    Tonn, B E; Travis, C B; Goeltz, R T; Phillippi, R H

    1990-03-01

    Beliefs about risks associated with two risk agents, AIDS and toxic waste, are modeled using knowledge-based methods and elicited from subjects via interactive computer technology. A concept net is developed to organize subject responses concerning the consequences of the risk agents. It is found that death and adverse personal emotional and sociological consequences are most associated with AIDS. Toxic waste is most associated with environmental problems. These consequence profiles are quite dissimilar, although past work in risk perception would have judged the risk agents as being quite similar. Subjects frequently used causal semantics to represent their beliefs and "% of time" instead of "probability" to represent likelihoods. The news media is the most prevalent source of risk information although experiences of acquaintances appear more credible. The results suggest that "broadly based risk" communication may be ineffective because people differ in their conceptual representation of risk beliefs. In general, the knowledge-based approach to risk perception representation has great potential to increase our understanding of important risk topics.

  1. Advances in knowledge-based software engineering

    NASA Technical Reports Server (NTRS)

    Truszkowski, Walt

    1991-01-01

    The underlying hypothesis of this work is that a rigorous and comprehensive software reuse methodology can bring about a more effective and efficient utilization of constrained resources in the development of large-scale software systems by both government and industry. It is also believed that correct use of this type of software engineering methodology can significantly contribute to the higher levels of reliability that will be required of future operational systems. An overview and discussion of current research in the development and application of two systems that support a rigorous reuse paradigm are presented: the Knowledge-Based Software Engineering Environment (KBSEE) and the Knowledge Acquisition fo the Preservation of Tradeoffs and Underlying Rationales (KAPTUR) systems. Emphasis is on a presentation of operational scenarios which highlight the major functional capabilities of the two systems.

  2. Knowledge-based scheduling of arrival aircraft

    NASA Technical Reports Server (NTRS)

    Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.

    1995-01-01

    A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

  3. Introduction: geoscientific knowledgebase of Chernobyl and Fukushima

    NASA Astrophysics Data System (ADS)

    Yamauchi, Masatoshi; Voitsekhovych, Oleg; Korobova, Elena; Stohl, Andreas; Wotawa, Gerhard; Kita, Kazuyuki; Aoyama, Michio; Yoshida, Naohiro

    2013-04-01

    Radioactive contamination after the Chernobyl (1986) and Fukushima (2011) accidents is a multi-disciplinary geoscience problem. Just this session (GI1.4) contains presentations of (i) atmospheric transport for both short and long distances, (ii) aerosol physics and chemistry, (ii) geophysical measurement method and logistics, (iv) inversion method to estimate the geophysical source term and decay, (v) transport, migration, and sedimentation in the surface water system, (vi) transport and sedimentation in the ocean, (vii) soil chemistry and physics, (viii) forest ecosystem, (ix) risk assessments, which are inter-related to each other. Because of rareness of a severe accident like Chernobyl and Fukushima, the Chernobyl's 27 years experience is the only knowledgebase that provides a good guidance for the Fukushima case in understanding the physical/chemical processes related to the environmental radioactive contamination and in providing future prospectives, e.g., what we should do next for the observation/remediation. Unfortunately, the multi-disciplinary nature of the radioactive contamination problem makes it very difficult for a single scientist to obtain the overview of all geoscientific aspects of the Chernobyl experience. The aim of this introductory talk is to give a comprehensive knowledge of the wide geoscientific aspects of the Chernobyl contamination to Fukushima-related geoscience community.

  4. Knowledge-based reusable software synthesis system

    NASA Technical Reports Server (NTRS)

    Donaldson, Cammie

    1989-01-01

    The Eli system, a knowledge-based reusable software synthesis system, is being developed for NASA Langley under a Phase 2 SBIR contract. Named after Eli Whitney, the inventor of interchangeable parts, Eli assists engineers of large-scale software systems in reusing components while they are composing their software specifications or designs. Eli will identify reuse potential, search for components, select component variants, and synthesize components into the developer's specifications. The Eli project began as a Phase 1 SBIR to define a reusable software synthesis methodology that integrates reusabilityinto the top-down development process and to develop an approach for an expert system to promote and accomplish reuse. The objectives of the Eli Phase 2 work are to integrate advanced technologies to automate the development of reusable components within the context of large system developments, to integrate with user development methodologies without significant changes in method or learning of special languages, and to make reuse the easiest operation to perform. Eli will try to address a number of reuse problems including developing software with reusable components, managing reusable components, identifying reusable components, and transitioning reuse technology. Eli is both a library facility for classifying, storing, and retrieving reusable components and a design environment that emphasizes, encourages, and supports reuse.

  5. IGENPRO knowledge-based operator support system.

    SciTech Connect

    Morman, J. A.

    1998-07-01

    Research and development is being performed on the knowledge-based IGENPRO operator support package for plant transient diagnostics and management to provide operator assistance during off-normal plant transient conditions. A generic thermal-hydraulic (T-H) first-principles approach is being implemented using automated reasoning, artificial neural networks and fuzzy logic to produce a generic T-H system-independent/plant-independent package. The IGENPRO package has a modular structure composed of three modules: the transient trend analysis module PROTREN, the process diagnostics module PRODIAG and the process management module PROMANA. Cooperative research and development work has focused on the PRODIAG diagnostic module of the IGENPRO package and the operator training matrix of transients used at the Braidwood Pressurized Water Reactor station. Promising simulator testing results with PRODIAG have been obtained for the Braidwood Chemical and Volume Control System (CVCS), and the Component Cooling Water System. Initial CVCS test results have also been obtained for the PROTREN module. The PROMANA effort also involves the CVCS. Future work will be focused on the long-term, slow and mild degradation transients where diagnoses of incipient T-H component failure prior to forced outage events is required. This will enhance the capability of the IGENPRO system as a predictive maintenance tool for plant staff and operator support.

  6. Cildb: a knowledgebase for centrosomes and cilia.

    PubMed

    Arnaiz, Olivier; Malinowska, Agata; Klotz, Catherine; Sperling, Linda; Dadlez, Michal; Koll, France; Cohen, Jean

    2009-01-01

    Ciliopathies, pleiotropic diseases provoked by defects in the structure or function of cilia or flagella, reflect the multiple roles of cilia during development, in stem cells, in somatic organs and germ cells. High throughput studies have revealed several hundred proteins that are involved in the composition, function or biogenesis of cilia. The corresponding genes are potential candidates for orphan ciliopathies. To study ciliary genes, model organisms are used in which particular questions on motility, sensory or developmental functions can be approached by genetics. In the course of high throughput studies of cilia in Paramecium tetraurelia, we were confronted with the problem of comparing our results with those obtained in other model organisms. We therefore developed a novel knowledgebase, Cildb, that integrates ciliary data from heterogeneous sources. Cildb links orthology relationships among 18 species to high throughput ciliary studies, and to OMIM data on human hereditary diseases. The web interface of Cildb comprises three tools, BioMart for complex queries, BLAST for sequence homology searches and GBrowse for browsing the human genome in relation to OMIM information for human diseases. Cildb can be used for interspecies comparisons, building candidate ciliary proteomes in any species, or identifying candidate ciliopathy genes.Database URL:http://cildb.cgm.cnrs-gif.fr.

  7. UniProt: the universal protein knowledgebase

    PubMed Central

    2017-01-01

    The UniProt knowledgebase is a large resource of protein sequences and associated detailed annotation. The database contains over 60 million sequences, of which over half a million sequences have been curated by experts who critically review experimental and predicted data for each protein. The remainder are automatically annotated based on rule systems that rely on the expert curated knowledge. Since our last update in 2014, we have more than doubled the number of reference proteomes to 5631, giving a greater coverage of taxonomic diversity. We implemented a pipeline to remove redundant highly similar proteomes that were causing excessive redundancy in UniProt. The initial run of this pipeline reduced the number of sequences in UniProt by 47 million. For our users interested in the accessory proteomes, we have made available sets of pan proteome sequences that cover the diversity of sequences for each species that is found in its strains and sub-strains. To help interpretation of genomic variants, we provide tracks of detailed protein information for the major genome browsers. We provide a SPARQL endpoint that allows complex queries of the more than 22 billion triples of data in UniProt (http://sparql.uniprot.org/). UniProt resources can be accessed via the website at http://www.uniprot.org/. PMID:27899622

  8. Knowledge-based system verification and validation

    NASA Technical Reports Server (NTRS)

    Johnson, Sally C.

    1990-01-01

    The objective of this task is to develop and evaluate a methodology for verification and validation (V&V) of knowledge-based systems (KBS) for space station applications with high reliability requirements. The approach consists of three interrelated tasks. The first task is to evaluate the effectiveness of various validation methods for space station applications. The second task is to recommend requirements for KBS V&V for Space Station Freedom (SSF). The third task is to recommend modifications to the SSF to support the development of KBS using effectiveness software engineering and validation techniques. To accomplish the first task, three complementary techniques will be evaluated: (1) Sensitivity Analysis (Worchester Polytechnic Institute); (2) Formal Verification of Safety Properties (SRI International); and (3) Consistency and Completeness Checking (Lockheed AI Center). During FY89 and FY90, each contractor will independently demonstrate the user of his technique on the fault detection, isolation, and reconfiguration (FDIR) KBS or the manned maneuvering unit (MMU), a rule-based system implemented in LISP. During FY91, the application of each of the techniques to other knowledge representations and KBS architectures will be addressed. After evaluation of the results of the first task and examination of Space Station Freedom V&V requirements for conventional software, a comprehensive KBS V&V methodology will be developed and documented. Development of highly reliable KBS's cannot be accomplished without effective software engineering methods. Using the results of current in-house research to develop and assess software engineering methods for KBS's as well as assessment of techniques being developed elsewhere, an effective software engineering methodology for space station KBS's will be developed, and modification of the SSF to support these tools and methods will be addressed.

  9. Integrating knowledge-based techniques into well-test interpretation

    SciTech Connect

    Harrison, I.W.; Fraser, J.L.

    1995-04-01

    The goal of the Spirit Project was to develop a prototype of next-generation well-test-interpretation (WTI) software that would include knowledge-based decision support for the WTI model selection task. This paper describes how Spirit makes use of several different types of information (pressure, seismic, petrophysical, geological, and engineering) to support the user in identifying the most appropriate WTI model. Spirit`s knowledge-based approach to type-curve matching is to generate several different feasible interpretations by making assumptions about the possible presence of both wellbore storage and late-time boundary effects. Spirit fuses information from type-curve matching and other data sources by use of a knowledge-based decision model developed in collaboration with a WTI expert. The sponsors of the work have judged the resulting prototype system a success.

  10. A Knowledge-Based Approach To Planning And Scheduling

    NASA Astrophysics Data System (ADS)

    Gilmore, John F.; Williams, D. Lamont; Thornton, Sheila

    1989-03-01

    Analyses of the shop scheduling domain indicate the objective of scheduling is the determination and satisfaction of a large number of diverse constraints. Many researchers have explored the possibilities of scheduling with the assistance of dispatching rules, algorithms, heuristics and knowledge-based systems. This paper describes the development of an experimental knowledge-based planning and scheduling system which marries traditional planning and scheduling algorithms with a knowledge-based problem solving methodology in an integrated blackboard architecture. This system embodies scheduling methods and techniques which attempt to minimize one or a combination of scheduling parameters including completion time, average completion time, lateness, tardiness, and flow time. Preliminary results utilizing a test case factory involved in part production are presented.

  11. A Knowledge-Based System Developer for aerospace applications

    NASA Technical Reports Server (NTRS)

    Shi, George Z.; Wu, Kewei; Fensky, Connie S.; Lo, Ching F.

    1993-01-01

    A prototype Knowledge-Based System Developer (KBSD) has been developed for aerospace applications by utilizing artificial intelligence technology. The KBSD directly acquires knowledge from domain experts through a graphical interface then builds expert systems from that knowledge. This raises the state of the art of knowledge acquisition/expert system technology to a new level by lessening the need for skilled knowledge engineers. The feasibility, applicability , and efficiency of the proposed concept was established, making a continuation which would develop the prototype to a full-scale general-purpose knowledge-based system developer justifiable. The KBSD has great commercial potential. It will provide a marketable software shell which alleviates the need for knowledge engineers and increase productivity in the workplace. The KBSD will therefore make knowledge-based systems available to a large portion of industry.

  12. A Knowledge-Based System Developer for aerospace applications

    NASA Technical Reports Server (NTRS)

    Shi, George Z.; Wu, Kewei; Fensky, Connie S.; Lo, Ching F.

    1993-01-01

    A prototype Knowledge-Based System Developer (KBSD) has been developed for aerospace applications by utilizing artificial intelligence technology. The KBSD directly acquires knowledge from domain experts through a graphical interface then builds expert systems from that knowledge. This raises the state of the art of knowledge acquisition/expert system technology to a new level by lessening the need for skilled knowledge engineers. The feasibility, applicability , and efficiency of the proposed concept was established, making a continuation which would develop the prototype to a full-scale general-purpose knowledge-based system developer justifiable. The KBSD has great commercial potential. It will provide a marketable software shell which alleviates the need for knowledge engineers and increase productivity in the workplace. The KBSD will therefore make knowledge-based systems available to a large portion of industry.

  13. The Knowledge-Based Economy and E-Learning: Critical Considerations for Workplace Democracy

    ERIC Educational Resources Information Center

    Remtulla, Karim A.

    2007-01-01

    The ideological shift by nation-states to "a knowledge-based economy" (also referred to as "knowledge-based society") is causing changes in the workplace. Brought about by the forces of globalisation and technological innovation, the ideologies of the "knowledge-based economy" are not limited to influencing the…

  14. The Knowledge-Based Economy and E-Learning: Critical Considerations for Workplace Democracy

    ERIC Educational Resources Information Center

    Remtulla, Karim A.

    2007-01-01

    The ideological shift by nation-states to "a knowledge-based economy" (also referred to as "knowledge-based society") is causing changes in the workplace. Brought about by the forces of globalisation and technological innovation, the ideologies of the "knowledge-based economy" are not limited to influencing the…

  15. Design of a knowledge-based report generator

    SciTech Connect

    Kukich, K.

    1983-01-01

    Knowledge-based report generation is a technique for automatically generating natural language reports from computer databases. It is so named because it applies knowledge-based expert systems software to the problem of text generation. The first application of the technique, a system for generating natural language stock reports from a daily stock quotes database, is partially implemented. Three fundamental principles of the technique are its use of domain-specific semantic and linguistic knowledge, its use of macro-level semantic and linguistic constructs (such as whole messages, a phrasal lexicon, and a sentence-combining grammar), and its production system approach to knowledge representation. 14 references.

  16. Online Knowledge-Based Model for Big Data Topic Extraction

    PubMed Central

    Khan, Muhammad Taimoor; Durrani, Mehr; Khalid, Shehzad; Aziz, Furqan

    2016-01-01

    Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced data dependency. With engineering the knowledge-base and introducing new knowledge features the learning pattern of the model is improved for data arriving in pieces. OAMC improves accuracy as topic coherence by 7% for streaming data while reducing the processing cost to half. PMID:27195004

  17. A knowledge-based decision support system for payload scheduling

    NASA Technical Reports Server (NTRS)

    Tyagi, Rajesh; Tseng, Fan T.

    1988-01-01

    This paper presents the development of a prototype Knowledge-based Decision Support System, currently under development, for scheduling payloads/experiments on space station missions. The DSS is being built on Symbolics, a Lisp machine, using KEE, a commercial knowledge engineering tool.

  18. Value Creation in the Knowledge-Based Economy

    ERIC Educational Resources Information Center

    Liu, Fang-Chun

    2013-01-01

    Effective investment strategies help companies form dynamic core organizational capabilities allowing them to adapt and survive in today's rapidly changing knowledge-based economy. This dissertation investigates three valuation issues that challenge managers with respect to developing business-critical investment strategies that can have…

  19. Dynamic Strategic Planning in a Professional Knowledge-Based Organization

    ERIC Educational Resources Information Center

    Olivarius, Niels de Fine; Kousgaard, Marius Brostrom; Reventlow, Susanne; Quelle, Dan Grevelund; Tulinius, Charlotte

    2010-01-01

    Professional, knowledge-based institutions have a particular form of organization and culture that makes special demands on the strategic planning supervised by research administrators and managers. A model for dynamic strategic planning based on a pragmatic utilization of the multitude of strategy models was used in a small university-affiliated…

  20. Big data analytics in immunology: a knowledge-based approach.

    PubMed

    Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

    2014-01-01

    With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

  1. CommonKADS models for knowledge-based planning

    SciTech Connect

    Kingston, J.; Shadbolt, N.; Tate, A.

    1996-12-31

    The CommonKADS methodology is a collection of structured methods for building knowledge-based systems. A key component of CommonKADS is the library of generic inference models which can be applied to tasks of specified types. These generic models can either be used as frameworks for knowledge acquisition, or to verify the completeness of models developed by analysis of the domain. However, the generic models for some task types, such as knowledge-based planning, are not well-developed. Since knowledge-based planning is an important commercial application of Artificial Intelligence, there is a clear need for the development of generic models for planning tasks. Many of the generic models which currently exist have been derived from modelling of existing AI systems. These models have the strength of proven applicability. There are a number of well-known and well-tried Al planning systems in existence; one of the best known is the Open Planning Architecture (O-Plan). This paper describes the development of a CommonKADS generic inference model for knowledge-based planning tasks, based on the capabilities of the O-Plan system. The paper also describes the verification of this model in the context of a real-life planning task: the assignment and management of Royal Air Force Search and Rescue operations.

  2. Malaysia Transitions toward a Knowledge-Based Economy

    ERIC Educational Resources Information Center

    Mustapha, Ramlee; Abdullah, Abu

    2004-01-01

    The emergence of a knowledge-based economy (k-economy) has spawned a "new" notion of workplace literacy, changing the relationship between employers and employees. The traditional covenant where employees expect a stable or lifelong employment will no longer apply. The retention of employees will most probably be based on their skills…

  3. PLAN-IT - Knowledge-based mission sequencing

    NASA Technical Reports Server (NTRS)

    Biefeld, Eric W.

    1987-01-01

    PLAN-IT (Plan-Integrated Timelines), a knowledge-based approach to assist in mission sequencing, is discussed. PLAN-IT uses a large set of scheduling techniques known as strategies to develop and maintain a mission sequence. The approach implemented by PLAN-IT and the current applications of PLAN-IT for sequencing at NASA are reported.

  4. CACTUS: Command and Control Training Using Knowledge-Based Simulations

    ERIC Educational Resources Information Center

    Hartley, Roger; Ravenscroft, Andrew; Williams, R. J.

    2008-01-01

    The CACTUS project was concerned with command and control training of large incidents where public order may be at risk, such as large demonstrations and marches. The training requirements and objectives of the project are first summarized justifying the use of knowledge-based computer methods to support and extend conventional training…

  5. Knowledge-Based Hierarchies: Using Organizations to Understand the Economy

    ERIC Educational Resources Information Center

    Garicano, Luis; Rossi-Hansberg, Esteban

    2015-01-01

    Incorporating the decision of how to organize the acquisition, use, and communication of knowledge into economic models is essential to understand a wide variety of economic phenomena. We survey the literature that has used knowledge-based hierarchies to study issues such as the evolution of wage inequality, the growth and productivity of firms,…

  6. Knowledge-Based Hierarchies: Using Organizations to Understand the Economy

    ERIC Educational Resources Information Center

    Garicano, Luis; Rossi-Hansberg, Esteban

    2015-01-01

    Incorporating the decision of how to organize the acquisition, use, and communication of knowledge into economic models is essential to understand a wide variety of economic phenomena. We survey the literature that has used knowledge-based hierarchies to study issues such as the evolution of wage inequality, the growth and productivity of firms,…

  7. Knowledge-Based Aid: A Four Agency Comparative Study

    ERIC Educational Resources Information Center

    McGrath, Simon; King, Kenneth

    2004-01-01

    Part of the response of many development cooperation agencies to the challenges of globalisation, ICTs and the knowledge economy is to emphasise the importance of knowledge for development. This paper looks at the discourses and practices of ''knowledge-based aid'' through an exploration of four agencies: the World Bank, DFID, Sida and JICA. It…

  8. CACTUS: Command and Control Training Using Knowledge-Based Simulations

    ERIC Educational Resources Information Center

    Hartley, Roger; Ravenscroft, Andrew; Williams, R. J.

    2008-01-01

    The CACTUS project was concerned with command and control training of large incidents where public order may be at risk, such as large demonstrations and marches. The training requirements and objectives of the project are first summarized justifying the use of knowledge-based computer methods to support and extend conventional training…

  9. Conventional and Knowledge-Based Information Retrieval with Prolog.

    ERIC Educational Resources Information Center

    Leigh, William; Paz, Noemi

    1988-01-01

    Describes the use of PROLOG to program knowledge-based information retrieval systems, in which the knowledge contained in a document is translated into machine processable logic. Several examples of the resulting search process, and the program rules supporting the process, are given. (10 references) (CLB)

  10. Value Creation in the Knowledge-Based Economy

    ERIC Educational Resources Information Center

    Liu, Fang-Chun

    2013-01-01

    Effective investment strategies help companies form dynamic core organizational capabilities allowing them to adapt and survive in today's rapidly changing knowledge-based economy. This dissertation investigates three valuation issues that challenge managers with respect to developing business-critical investment strategies that can have…

  11. Knowledge-Based Aid: A Four Agency Comparative Study

    ERIC Educational Resources Information Center

    McGrath, Simon; King, Kenneth

    2004-01-01

    Part of the response of many development cooperation agencies to the challenges of globalisation, ICTs and the knowledge economy is to emphasise the importance of knowledge for development. This paper looks at the discourses and practices of ''knowledge-based aid'' through an exploration of four agencies: the World Bank, DFID, Sida and JICA. It…

  12. Expansion of the Gene Ontology knowledgebase and resources

    PubMed Central

    2017-01-01

    The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our continued focus is on improving the quality and utility of the GO resources, and we welcome and encourage input from researchers in all areas of biology. In this update, we summarize the current contents of the GO knowledgebase, and present several new features and improvements that have been made to the ontology, the annotations and the tools. Among the highlights are 1) developments that facilitate access to, and application of, the GO knowledgebase, and 2) extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. To learn more, visit http://geneontology.org/. PMID:27899567

  13. Managing Project Landscapes in Knowledge-Based Enterprises

    NASA Astrophysics Data System (ADS)

    Stantchev, Vladimir; Franke, Marc Roman

    Knowledge-based enterprises are typically conducting a large number of research and development projects simultaneously. This is a particularly challenging task in complex and diverse project landscapes. Project Portfolio Management (PPM) can be a viable framework for knowledge and innovation management in such landscapes. A standardized process with defined functions such as project data repository, project assessment, selection, reporting, and portfolio reevaluation can serve as a starting point. In this work we discuss the benefits a multidimensional evaluation framework can provide for knowledge-based enterprises. Furthermore, we describe a knowledge and learning strategy and process in the context of PPM and evaluate their practical applicability at different stages of the PPM process.

  14. Expansion of the Gene Ontology knowledgebase and resources.

    PubMed

    2017-01-04

    The Gene Ontology (GO) is a comprehensive resource of computable knowledge regarding the functions of genes and gene products. As such, it is extensively used by the biomedical research community for the analysis of -omics and related data. Our continued focus is on improving the quality and utility of the GO resources, and we welcome and encourage input from researchers in all areas of biology. In this update, we summarize the current contents of the GO knowledgebase, and present several new features and improvements that have been made to the ontology, the annotations and the tools. Among the highlights are 1) developments that facilitate access to, and application of, the GO knowledgebase, and 2) extensions to the resource as well as increasing support for descriptions of causal models of biological systems and network biology. To learn more, visit http://geneontology.org/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Knowledge-based zonal grid generation for computational fluid dynamics

    NASA Technical Reports Server (NTRS)

    Andrews, Alison E.

    1988-01-01

    Automation of flow field zoning in two dimensions is an important step towards reducing the difficulty of three-dimensional grid generation in computational fluid dynamics. Using a knowledge-based approach makes sense, but problems arise which are caused by aspects of zoning involving perception, lack of expert consensus, and design processes. These obstacles are overcome by means of a simple shape and configuration language, a tunable zoning archetype, and a method of assembling plans from selected, predefined subplans. A demonstration system for knowledge-based two-dimensional flow field zoning has been successfully implemented and tested on representative aerodynamic configurations. The results show that this approach can produce flow field zonings that are acceptable to experts with differing evaluation criteria.

  16. A specialized framework for medical diagnostic knowledge-based systems.

    PubMed

    Lanzola, G; Stefanelli, M

    1992-08-01

    For a knowledge-based system (KBS) to exhibit an intelligent behavior, it must be endowed with knowledge enabling it to represent the expert's strategies. The elicitation task is inherently difficult for strategic knowledge, because strategy is often tacit, and, even when it has been made explicit, it is not an easy task to describe it in a form which may be directly translated and implemented into a program. This paper describes a Specialized Framework for Medical Diagnostic Knowledge-Based Systems that can help an expert in the process of building KBSs in a medical domain. The framework is based on an epistemological model of diagnostic reasoning which has proven to be helpful in describing the diagnostic process in terms of the tasks that it is composed of. It allows a straightforward modeling of diagnostic reasoning at the knowledge level by the domain expert, thus helping to convey domain-dependent strategies into the target KBS.

  17. TVS: An Environment For Building Knowledge-Based Vision Systems

    NASA Astrophysics Data System (ADS)

    Weymouth, Terry E.; Amini, Amir A.; Tehrani, Saeid

    1989-03-01

    Advances in the field of knowledge-guided computer vision require the development of large scale projects and experimentation with them. One factor which impedes such development is the lack of software environments which combine standard image processing and graphics abilities with the ability to perform symbolic processing. In this paper, we describe a software environment that assists in the development of knowledge-based computer vision projects. We have built, upon Common LISP and C, a software development environment which combines standard image processing tools and a standard blackboard-based system, with the flexibility of the LISP programming environment. This environment has been used to develop research projects in knowledge-based computer vision and dynamic vision for robot navigation.

  18. Impact of Knowledge-Based Techniques on Emerging Technologies

    DTIC Science & Technology

    2006-09-01

    coherent location (PCL), tracking in multistatic radar, and ‘spatial denial’ as a waveform diversity technique to prevent the exploitation by an enemy...performing a variety of surveillance and tracking tasks. Knowledge-based processing may be used to control the scheduling of tasks in such a radar, showing...techniques to bistatic and multistatic radar, including the use of information on waveform properties in passive coherent location (PCL), tracking

  19. Design of an opt-electronic knowledge-based system

    NASA Astrophysics Data System (ADS)

    Shen, Xuan-Jing; Qian, Qing-Ji; Liu, Ping-Ping

    2006-01-01

    In this paper, based on the analysis of the features of knowledge-based system and optical computing, a scheme of an opt-electronic hybrid system (OEHKBS) model and its hardware supporting system. The OEHKBS adopts a knowledge representation based on matrix and its inference and learning arithmetic which suitable for optical parallel processing. Finally, the paper analyses the performance of the OEHKBS, which can make the time complexity for solving Maze problem reduce to O(n).

  20. A knowledgebase system to enhance scientific discovery: Telemakus

    PubMed Central

    Fuller, Sherrilynne S; Revere, Debra; Bugni, Paul F; Martin, George M

    2004-01-01

    Background With the rapid expansion of scientific research, the ability to effectively find or integrate new domain knowledge in the sciences is proving increasingly difficult. Efforts to improve and speed up scientific discovery are being explored on a number of fronts. However, much of this work is based on traditional search and retrieval approaches and the bibliographic citation presentation format remains unchanged. Methods Case study. Results The Telemakus KnowledgeBase System provides flexible new tools for creating knowledgebases to facilitate retrieval and review of scientific research reports. In formalizing the representation of the research methods and results of scientific reports, Telemakus offers a potential strategy to enhance the scientific discovery process. While other research has demonstrated that aggregating and analyzing research findings across domains augments knowledge discovery, the Telemakus system is unique in combining document surrogates with interactive concept maps of linked relationships across groups of research reports. Conclusion Based on how scientists conduct research and read the literature, the Telemakus KnowledgeBase System brings together three innovations in analyzing, displaying and summarizing research reports across a domain: (1) research report schema, a document surrogate of extracted research methods and findings presented in a consistent and structured schema format which mimics the research process itself and provides a high-level surrogate to facilitate searching and rapid review of retrieved documents; (2) research findings, used to index the documents, allowing searchers to request, for example, research studies which have studied the relationship between neoplasms and vitamin E; and (3) visual exploration interface of linked relationships for interactive querying of research findings across the knowledgebase and graphical displays of what is known as well as, through gaps in the map, what is yet to be tested

  1. A Knowledge-Based Approach to Language Production

    DTIC Science & Technology

    1985-08-01

    systemic gramma rs--morphological, lexical, syntactic, and functional knowledge. The valu e of a feature may be a literal, special symbol, or a composite...A Knowledge-Based Approach to Language Prcxiuction By Paul Schafran Jacobs A.B. (Harvard University ) 1981 S.M. (Harvard University ) 1981...GRADUATE DIVISION OF ’THE UNIVERSITY OF CALIFORNIA, BERKELEY .. ~, ....-~- .. 9.!!.1’!.5 ’ i Date ..... 0. ~ •.. fi.:. -~- ..... f./..’(/ P.:’ .. ~ d

  2. Knowledge-Based Decision Support in Department of Defense Acquisitions

    DTIC Science & Technology

    2010-09-01

    2005) reviewed and analyzed the National Aeronautics and Space Administration ( NASA ) project management policies and compared them to the GAO’s best...practices on knowledge-based decision making. The study was primarily focused on the Goddard Space Flight Center, the Jet Propulsion Lab, Johnson ...Space Center, and Marshall Space Flight Center. During its investigation, the GAO found NASA deficient in key criteria and decision reviews to fully

  3. Knowledge-Based Production Management: Approaches, Results and Prospects

    DTIC Science & Technology

    1991-12-01

    In this paper we provide an overview of research in the field of knowledge-based production management . We begin by examining the important sources...of decision-making difficulty in practical production management domains, discussing the requirements implied by each with respect to the development...of effective production management tools, and identifying the general opportunities in this regard provided by AI-based technology. We then categorize

  4. Knowledge-based processing for aircraft flight control

    NASA Technical Reports Server (NTRS)

    Painter, John H.; Glass, Emily; Economides, Gregory; Russell, Paul

    1994-01-01

    This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area.

  5. Systems, methods and apparatus for verification of knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Hinchey, Michael G. (Inventor); Rash, James L. (Inventor); Erickson, John D. (Inventor); Gracinin, Denis (Inventor); Rouff, Christopher A. (Inventor)

    2010-01-01

    Systems, methods and apparatus are provided through which in some embodiments, domain knowledge is translated into a knowledge-based system. In some embodiments, a formal specification is derived from rules of a knowledge-based system, the formal specification is analyzed, and flaws in the formal specification are used to identify and correct errors in the domain knowledge, from which a knowledge-based system is translated.

  6. A comparison of LISP and MUMPS as implementation languages for knowledge-based systems.

    PubMed

    Curtis, A C

    1984-10-01

    Major components of knowledge-based systems are summarized, along with the programming language features generally useful in their implementation. LISP and MUMPS are briefly described and compared as vehicles for building knowledge-based systems. The paper concludes with suggestions for extensions to MUMPS that might increase its usefulness in artificial intelligence applications without affecting the essential nature of the language.

  7. Knowledge-Based Learning: Integration of Deductive and Inductive Learning for Knowledge Base Completion.

    ERIC Educational Resources Information Center

    Whitehall, Bradley Lane

    In constructing a knowledge-based system, the knowledge engineer must convert rules of thumb provided by the domain expert and previously solved examples into a working system. Research in machine learning has produced algorithms that create rules for knowledge-based systems, but these algorithms require either many examples or a complete domain…

  8. Knowledge-Based Learning: Integration of Deductive and Inductive Learning for Knowledge Base Completion.

    ERIC Educational Resources Information Center

    Whitehall, Bradley Lane

    In constructing a knowledge-based system, the knowledge engineer must convert rules of thumb provided by the domain expert and previously solved examples into a working system. Research in machine learning has produced algorithms that create rules for knowledge-based systems, but these algorithms require either many examples or a complete domain…

  9. Construction of dynamic stochastic simulation models using knowledge-based techniques

    NASA Technical Reports Server (NTRS)

    Williams, M. Douglas; Shiva, Sajjan G.

    1990-01-01

    Over the past three decades, computer-based simulation models have proven themselves to be cost-effective alternatives to the more structured deterministic methods of systems analysis. During this time, many techniques, tools and languages for constructing computer-based simulation models have been developed. More recently, advances in knowledge-based system technology have led many researchers to note the similarities between knowledge-based programming and simulation technologies and to investigate the potential application of knowledge-based programming techniques to simulation modeling. The integration of conventional simulation techniques with knowledge-based programming techniques is discussed to provide a development environment for constructing knowledge-based simulation models. A comparison of the techniques used in the construction of dynamic stochastic simulation models and those used in the construction of knowledge-based systems provides the requirements for the environment. This leads to the design and implementation of a knowledge-based simulation development environment. These techniques were used in the construction of several knowledge-based simulation models including the Advanced Launch System Model (ALSYM).

  10. Comparison of LISP and MUMPS as implementation languages for knowledge-based systems

    SciTech Connect

    Curtis, A.C.

    1984-01-01

    Major components of knowledge-based systems are summarized, along with the programming language features generally useful in their implementation. LISP and MUMPS are briefly described and compared as vehicles for building knowledge-based systems. The paper concludes with suggestions for extensions to MUMPS which might increase its usefulness in artificial intelligence applications without affecting the essential nature of the language. 8 references.

  11. Building validation tools for knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Stachowitz, R. A.; Chang, C. L.; Stock, T. S.; Combs, J. B.

    1987-01-01

    The Expert Systems Validation Associate (EVA), a validation system under development at the Lockheed Artificial Intelligence Center for more than a year, provides a wide range of validation tools to check the correctness, consistency and completeness of a knowledge-based system. A declarative meta-language (higher-order language), is used to create a generic version of EVA to validate applications written in arbitrary expert system shells. The architecture and functionality of EVA are presented. The functionality includes Structure Check, Logic Check, Extended Structure Check (using semantic information), Extended Logic Check, Semantic Check, Omission Check, Rule Refinement, Control Check, Test Case Generation, Error Localization, and Behavior Verification.

  12. Knowledge-based machine vision systems for space station automation

    NASA Technical Reports Server (NTRS)

    Ranganath, Heggere S.; Chipman, Laure J.

    1989-01-01

    Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

  13. Knowledge-based GIS techniques applied to geological engineering

    USGS Publications Warehouse

    Usery, E. Lynn; Altheide, Phyllis; Deister, Robin R.P.; Barr, David J.

    1988-01-01

    A knowledge-based geographic information system (KBGIS) approach which requires development of a rule base for both GIS processing and for the geological engineering application has been implemented. The rule bases are implemented in the Goldworks expert system development shell interfaced to the Earth Resources Data Analysis System (ERDAS) raster-based GIS for input and output. GIS analysis procedures including recoding, intersection, and union are controlled by the rule base, and the geological engineering map product is generted by the expert system. The KBGIS has been used to generate a geological engineering map of Creve Coeur, Missouri.

  14. Knowledge-based system for automatic MBR control.

    PubMed

    Comas, J; Meabe, E; Sancho, L; Ferrero, G; Sipma, J; Monclús, H; Rodriguez-Roda, I

    2010-01-01

    MBR technology is currently challenging traditional wastewater treatment systems and is increasingly selected for WWTP upgrading. MBR systems typically are constructed on a smaller footprint, and provide superior treated water quality. However, the main drawback of MBR technology is that the permeability of membranes declines during filtration due to membrane fouling, which for a large part causes the high aeration requirements of an MBR to counteract this fouling phenomenon. Due to the complex and still unknown mechanisms of membrane fouling it is neither possible to describe clearly its development by means of a deterministic model, nor to control it with a purely mathematical law. Consequently the majority of MBR applications are controlled in an "open-loop" way i.e. with predefined and fixed air scour and filtration/relaxation or backwashing cycles, and scheduled inline or offline chemical cleaning as a preventive measure, without taking into account the real needs of membrane cleaning based on its filtration performance. However, existing theoretical and empirical knowledge about potential cause-effect relations between a number of factors (influent characteristics, biomass characteristics and operational conditions) and MBR operation can be used to build a knowledge-based decision support system (KB-DSS) for the automatic control of MBRs. This KB-DSS contains a knowledge-based control module, which, based on real time comparison of the current permeability trend with "reference trends", aims at optimizing the operation and energy costs and decreasing fouling rates. In practice the automatic control system proposed regulates the set points of the key operational variables controlled in MBR systems (permeate flux, relaxation and backwash times, backwash flows and times, aeration flow rates, chemical cleaning frequency, waste sludge flow rate and recycle flow rates) and identifies its optimal value. This paper describes the concepts and the 3-level architecture

  15. "Chromosome": a knowledge-based system for the chromosome classification.

    PubMed

    Ramstein, G; Bernadet, M

    1993-01-01

    Chromosome, a knowledge-based analysis system has been designed for the classification of human chromosomes. Its aim is to perform an optimal classification by driving a tool box containing the procedures of image processing, pattern recognition and classification. This paper presents the general architecture of Chromosome, based on a multiagent system generator. The image processing tool box is described from the met aphasic enhancement to the fine classification. Emphasis is then put on the knowledge base intended for the chromosome recognition. The global classification process is also presented, showing how Chromosome proceeds to classify a given chromosome. Finally, we discuss further extensions of the system for the karyotype building.

  16. An Introduction to the Heliophysics Event Knowledgebase for SDO

    NASA Astrophysics Data System (ADS)

    Hurlburt, Neal; Schrijver, Carolus; Cheung, Mark

    The immense volume of data generated by the suite of instruments on SDO requires new tools for efficient identifying and accessing data that is most relevant to research investigations. We have developed the Heliophysics Events Knowledgebase (HEK) to fill this need. The system developed in support of the HEK combines automated datamining using feature detection methods; high-performance visualization systems for data markup; and web-services and clients for searching the resulting metadata, reviewing results and efficient access to the data. We will review these components and present examples of their use with SDO data.

  17. Knowledge-based vision and simple visual machines.

    PubMed Central

    Cliff, D; Noble, J

    1997-01-01

    The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong. PMID:9304684

  18. DMAK: A curated pan-cancer DNA methylation annotation knowledgebase

    PubMed Central

    Tang, Binhua

    2017-01-01

    ABSTRACT Pan-cancer analysis can identify cell- and tissue-specific genomic loci and regions with underlying biological functions. Here we present an online curated DNA Methylation Annotation Knowledgebase, DMAK, which includes the pan-cancer analysis results for differentially-methylated loci and regions by the Reduced Representation Bisulfite Sequencing profiling technology. DMAK contains 3 modules of curated information and analysis results on 688,445 CpG sites across 19 cancer and embryonic stem cell lines from ENCODE, and further analysis of survival associations with clinical sources retrieved from TCGA. The knowledgebase covers all identified differentially-methylated CpG sites and regions of interest, further annotated genomic information, together with tumor suppressor genes information and calculated methylation level. DMAK provides meaningful clues for deriving functional association network and related clinical association results based on protein-coding genes, including tumor suppressor genes, identified from differentially methylated regions of interest. Thus DMAK constitutes a comprehensive reference source for the current epigenetic research and clinical study. PMID:27645405

  19. Automated seeding of specialised wiki knowledgebases with BioKb

    PubMed Central

    2009-01-01

    Background Wiki technology has become a ubiquitous mechanism for dissemination of information, and places strong emphasis on collaboration. We aimed to leverage wiki technology to allow small groups of researchers to collaborate around a specific domain, for example a biological pathway. Automatically gathered seed data could be modified by the group and enriched with domain specific information. Results We describe a software system, BioKb, implemented as a plugin for the TWiki engine, and designed to facilitate construction of a field-specific wiki containing collaborative and automatically generated content. Features of this system include: query of publicly available resources such as KEGG, iHOP and MeSH, to generate 'seed' content for topics; simple definition of structure for topics of different types via an administration page; and interactive incorporation of relevant PubMed references. An exemplar is shown for the use of this system, in the creation of the RAASWiki knowledgebase on the renin-angiotensin-aldosterone system (RAAS). RAASWiki has been seeded with data by use of BioKb, and will be the subject of ongoing development into an extensive knowledgebase on the RAAS. Conclusion The BioKb system is available from http://www.bioinf.mvm.ed.ac.uk/twiki/bin/view/TWiki/BioKbPlugin as a plugin for the TWiki engine. PMID:19758431

  20. A knowledge-based care protocol system for ICU.

    PubMed

    Lau, F; Vincent, D D

    1995-01-01

    There is a growing interest in using care maps in ICU. So far, the emphasis has been on developing the critical path, problem/outcome, and variance reporting for specific diagnoses. This paper presents a conceptual knowledge-based care protocol system design for the ICU. It is based on the manual care map currently in use for managing myocardial infarction in the ICU of the Sturgeon General Hospital in Alberta. The proposed design uses expert rules, object schemas, case-based reasoning, and quantitative models as sources of its knowledge. Also being developed is a decision model with explicit linkages for outcome-process-measure from the care map. The resulting system is intended as a bedside charting and decision-support tool for caregivers. Proposed usage includes charting by acknowledgment, generation of alerts, and critiques on variances/events recorded, recommendations for planned interventions, and comparison with historical cases. Currently, a prototype is being developed on a PC-based network with Visual Basic, Level-Expert Object, and xBase. A clinical trial is also planned to evaluate whether this knowledge-based care protocol can reduce the length of stay of patients with myocardial infarction in the ICU.

  1. Hospital nurses' use of knowledge-based information resources.

    PubMed

    Tannery, Nancy Hrinya; Wessel, Charles B; Epstein, Barbara A; Gadd, Cynthia S

    2007-01-01

    The purpose of this study was to evaluate the information-seeking practices of nurses before and after access to a library's electronic collection of information resources. This is a pre/post intervention study of nurses at a rural community hospital. The hospital contracted with an academic health sciences library for access to a collection of online knowledge-based resources. Self-report surveys were used to obtain information about nurses' computer use and how they locate and access information to answer questions related to their patient care activities. In 2001, self-report surveys were sent to the hospital's 573 nurses during implementation of access to online resources with a post-implementation survey sent 1 year later. At the initiation of access to the library's electronic resources, nurses turned to colleagues and print textbooks or journals to satisfy their information needs. After 1 year of access, 20% of the nurses had begun to use the library's electronic resources. The study outcome suggests ready access to knowledge-based electronic information resources can lead to changes in behavior among some nurses.

  2. Portable Knowledge-Based Diagnostic And Maintenance Systems

    NASA Astrophysics Data System (ADS)

    Darvish, John; Olson, Noreen S.

    1989-03-01

    It is difficult to diagnose faults and maintain weapon systems because (1) they are highly complex pieces of equipment composed of multiple mechanical, electrical, and hydraulic assemblies, and (2) talented maintenance personnel are continuously being lost through the attrition process. To solve this problem, we developed a portable diagnostic and maintenance aid that uses a knowledge-based expert system. This aid incorporates diagnostics, operational procedures, repair and replacement procedures, and regularly scheduled maintenance into one compact, 18-pound graphics workstation. Drawings and schematics can be pulled up from the CD-ROM to assist the operator in answering the expert system's questions. Work for this aid began with the development of the initial knowledge-based expert system in a fast prototyping environment using a LISP machine. The second phase saw the development of a personal computer-based system that used videodisc technology to pictorially assist the operator. The current version of the aid eliminates the high expenses associated with videodisc preparation by scanning in the art work already in the manuals. A number of generic software tools have been developed that streamlined the construction of each iteration of the aid; these tools will be applied to the development of future systems.

  3. Network fingerprint: a knowledge-based characterization of biomedical networks

    PubMed Central

    Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen

    2015-01-01

    It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246

  4. Knowledge-based imaging-sensor fusion system

    NASA Astrophysics Data System (ADS)

    Westrom, George

    1989-11-01

    An imaging system which applies knowledge-based technology to supervise and control both sensor hardware and computation in the imaging system is described. It includes the development of an imaging system breadboard which brings together into one system work that we and others have pursued for LaRC for several years. The goal is to combine Digital Signal Processing (DSP) with Knowledge-Based Processing and also include Neural Net processing. The system is considered a smart camera. Imagine that there is a microgravity experiment on-board Space Station Freedom with a high frame rate, high resolution camera. All the data cannot possibly be acquired from a laboratory on Earth. In fact, only a small fraction of the data will be received. Again, imagine being responsible for some experiments on Mars with the Mars Rover: the data rate is a few kilobits per second for data from several sensors and instruments. Would it not be preferable to have a smart system which would have some human knowledge and yet follow some instructions and attempt to make the best use of the limited bandwidth for transmission. The system concept, current status of the breadboard system and some recent experiments at the Mars-like Amboy Lava Fields in California are discussed.

  5. Extensible knowledge-based architecture for segmenting CT data

    NASA Astrophysics Data System (ADS)

    Brown, Matthew S.; McNitt-Gray, Michael F.; Goldin, Jonathan G.; Aberle, Denise R.

    1998-06-01

    A knowledge-based system has been developed for segmenting computed tomography (CT) images. Its modular architecture includes an anatomical model, image processing engine, inference engine and blackboard. The model contains a priori knowledge of size, shape, X-ray attenuation and relative position of anatomical structures. This knowledge is used to constrain low-level segmentation routines. Model-derived constraints and segmented image objects are both transformed into a common feature space and posted on the blackboard. The inference engine then matches image to model objects, based on the constraints. The transformation to feature space allows the knowledge and image data representations to be independent. Thus a high-level model can be used, with data being stored in a frame-based semantic network. This modularity and explicit representation of knowledge allows for straightforward system extension. We initially demonstrate an application to lung segmentation in thoracic CT, with subsequent extension of the knowledge-base to include tumors within the lung fields. The anatomical model was later augmented to include basic brain anatomy including the skull and blood vessels, to allow automatic segmentation of vascular structures in CT angiograms for 3D rendering and visualization.

  6. Knowledge-based simulation using object-oriented programming

    NASA Technical Reports Server (NTRS)

    Sidoran, Karen M.

    1993-01-01

    Simulations have become a powerful mechanism for understanding and modeling complex phenomena. Their results have had substantial impact on a broad range of decisions in the military, government, and industry. Because of this, new techniques are continually being explored and developed to make them even more useful, understandable, extendable, and efficient. One such area of research is the application of the knowledge-based methods of artificial intelligence (AI) to the computer simulation field. The goal of knowledge-based simulation is to facilitate building simulations of greatly increased power and comprehensibility by making use of deeper knowledge about the behavior of the simulated world. One technique for representing and manipulating knowledge that has been enhanced by the AI community is object-oriented programming. Using this technique, the entities of a discrete-event simulation can be viewed as objects in an object-oriented formulation. Knowledge can be factual (i.e., attributes of an entity) or behavioral (i.e., how the entity is to behave in certain circumstances). Rome Laboratory's Advanced Simulation Environment (RASE) was developed as a research vehicle to provide an enhanced simulation development environment for building more intelligent, interactive, flexible, and realistic simulations. This capability will support current and future battle management research and provide a test of the object-oriented paradigm for use in large scale military applications.

  7. A proven knowledge-based approach to prioritizing process information

    NASA Technical Reports Server (NTRS)

    Corsberg, Daniel R.

    1991-01-01

    Many space-related processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect is rapid analysis of the changing process information. During a disturbance, this task can overwhelm humans as well as computers. Humans deal with this by applying heuristics in determining significant information. A simple, knowledge-based approach to prioritizing information is described. The approach models those heuristics that humans would use in similar circumstances. The approach described has received two patents and was implemented in the Alarm Filtering System (AFS) at the Idaho National Engineering Laboratory (INEL). AFS was first developed for application in a nuclear reactor control room. It has since been used in chemical processing applications, where it has had a significant impact on control room environments. The approach uses knowledge-based heuristics to analyze data from process instrumentation and respond to that data according to knowledge encapsulated in objects and rules. While AFS cannot perform the complete diagnosis and control task, it has proven to be extremely effective at filtering and prioritizing information. AFS was used for over two years as a first level of analysis for human diagnosticians. Given the approach's proven track record in a wide variety of practical applications, it should be useful in both ground- and space-based systems.

  8. Knowledge-based imaging-sensor fusion system

    NASA Technical Reports Server (NTRS)

    Westrom, George

    1989-01-01

    An imaging system which applies knowledge-based technology to supervise and control both sensor hardware and computation in the imaging system is described. It includes the development of an imaging system breadboard which brings together into one system work that we and others have pursued for LaRC for several years. The goal is to combine Digital Signal Processing (DSP) with Knowledge-Based Processing and also include Neural Net processing. The system is considered a smart camera. Imagine that there is a microgravity experiment on-board Space Station Freedom with a high frame rate, high resolution camera. All the data cannot possibly be acquired from a laboratory on Earth. In fact, only a small fraction of the data will be received. Again, imagine being responsible for some experiments on Mars with the Mars Rover: the data rate is a few kilobits per second for data from several sensors and instruments. Would it not be preferable to have a smart system which would have some human knowledge and yet follow some instructions and attempt to make the best use of the limited bandwidth for transmission. The system concept, current status of the breadboard system and some recent experiments at the Mars-like Amboy Lava Fields in California are discussed.

  9. Literature classification for semi-automated updating of biological knowledgebases

    PubMed Central

    2013-01-01

    Background As the output of biological assays increase in resolution and volume, the body of specialized biological data, such as functional annotations of gene and protein sequences, enables extraction of higher-level knowledge needed for practical application in bioinformatics. Whereas common types of biological data, such as sequence data, are extensively stored in biological databases, functional annotations, such as immunological epitopes, are found primarily in semi-structured formats or free text embedded in primary scientific literature. Results We defined and applied a machine learning approach for literature classification to support updating of TANTIGEN, a knowledgebase of tumor T-cell antigens. Abstracts from PubMed were downloaded and classified as either "relevant" or "irrelevant" for database update. Training and five-fold cross-validation of a k-NN classifier on 310 abstracts yielded classification accuracy of 0.95, thus showing significant value in support of data extraction from the literature. Conclusion We here propose a conceptual framework for semi-automated extraction of epitope data embedded in scientific literature using principles from text mining and machine learning. The addition of such data will aid in the transition of biological databases to knowledgebases. PMID:24564403

  10. Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction

    PubMed Central

    Grulke, Christopher M.; Chang, Daniel T.; Brooks, Raina D.; Leonard, Jeremy A.; Phillips, Martin B.; Hypes, Ethan D.; Fair, Matthew J.; Tornero-Velez, Rogelio; Johnson, Jeffre; Dary, Curtis C.; Tan, Yu-Mei

    2016-01-01

    Developing physiologically-based pharmacokinetic (PBPK) models for chemicals can be resource-intensive, as neither chemical-specific parameters nor in vivo pharmacokinetic data are easily available for model construction. Previously developed, well-parameterized, and thoroughly-vetted models can be a great resource for the construction of models pertaining to new chemicals. A PBPK knowledgebase was compiled and developed from existing PBPK-related articles and used to develop new models. From 2,039 PBPK-related articles published between 1977 and 2013, 307 unique chemicals were identified for use as the basis of our knowledgebase. Keywords related to species, gender, developmental stages, and organs were analyzed from the articles within the PBPK knowledgebase. A correlation matrix of the 307 chemicals in the PBPK knowledgebase was calculated based on pharmacokinetic-relevant molecular descriptors. Chemicals in the PBPK knowledgebase were ranked based on their correlation toward ethylbenzene and gefitinib. Next, multiple chemicals were selected to represent exact matches, close analogues, or non-analogues of the target case study chemicals. Parameters, equations, or experimental data relevant to existing models for these chemicals and their analogues were used to construct new models, and model predictions were compared to observed values. This compiled knowledgebase provides a chemical structure-based approach for identifying PBPK models relevant to other chemical entities. Using suitable correlation metrics, we demonstrated that models of chemical analogues in the PBPK knowledgebase can guide the construction of PBPK models for other chemicals. PMID:26871706

  11. Knowledge-Based Systems Approach to Wilderness Fire Management.

    NASA Astrophysics Data System (ADS)

    Saveland, James M.

    The 1988 and 1989 forest fire seasons in the Intermountain West highlight the shortcomings of current fire policy. To fully implement an optimization policy that minimizes the costs and net value change of resources affected by fire, long-range fire severity information is essential, yet lacking. This information is necessary for total mobility of suppression forces, implementing contain and confine suppression strategies, effectively dealing with multiple fire situations, scheduling summer prescribed burning, and wilderness fire management. A knowledge-based system, Delphi, was developed to help provide long-range information. Delphi provides: (1) a narrative of advice on where a fire might spread, if allowed to burn, (2) a summary of recent weather and fire danger information, and (3) a Bayesian analysis of long-range fire danger potential. Uncertainty is inherent in long-range information. Decision theory and judgment research can be used to help understand the heuristics experts use to make decisions under uncertainty, heuristics responsible both for expert performance and bias. Judgment heuristics and resulting bias are examined from a fire management perspective. Signal detection theory and receiver operating curve (ROC) analysis can be used to develop a long-range forecast to improve decisions. ROC analysis mimics some of the heuristics and compensates for some of the bias. Most importantly, ROC analysis displays a continuum of bias from which an optimum operating point can be selected. ROC analysis is especially appropriate for long-range forecasting since (1) the occurrence of possible future events is stated in terms of probability, (2) skill prediction is displayed, (3) inherent trade-offs are displayed, and (4) fire danger is explicitly defined. Statements on the probability of the energy release component of the National Fire Danger Rating System exceeding a critical value later in the fire season can be made early July in the Intermountain West

  12. Evolutionary potentials: structure specific knowledge-based potentials exploiting the evolutionary record of sequence homologs.

    PubMed

    Panjkovich, Alejandro; Melo, Francisco; Marti-Renom, Marc A

    2008-04-08

    We introduce a new type of knowledge-based potentials for protein structure prediction, called 'evolutionary potentials', which are derived using a single experimental protein structure and all three-dimensional models of its homologous sequences. The new potentials have been benchmarked against other knowledge-based potentials, resulting in a significant increase in accuracy for model assessment. In contrast to standard knowledge-based potentials, we propose that evolutionary potentials capture key determinants of thermodynamic stability and specific sequence constraints required for fast folding.

  13. A real-time multiprocessor system for knowledge-based target-tracking

    NASA Astrophysics Data System (ADS)

    Irwin, P. D. S.; Farson, S. A.; Wilkinson, A. J.

    1989-12-01

    A real-time processing architecture for implementation of knowledge-based algorithms employed in infrared-image interpretation is described. Three stages of image interpretation (image segmentation, feature extraction, and feature examination by a knowledge-based system) are outlined. Dedicated hardware for the image segmentation and feature extraction are covered, along with a multitransputer architecture for implementation of data-dependent processes. Emphasis is placed on implementation of the description, frame-hypothesis, and slot-filling algorithms. An optimal algorithm for scheduling various tasks involved in implementing the rule set of the knowledge-based system is presented.

  14. Knowledge-based systems: how will they affect manufacturing in the 80's

    SciTech Connect

    King, M.S.; Brooks, S.L.; Schaefer, R.M.

    1985-04-01

    Knowledge-based or ''expert'' systems have been in various stages of development and use for a long time in the academic world. Some of these systems have come out of the lab in recent years in the fields of medicine, geology, and computer system design. The use of knowledge-based systems in conjunction iwth manufacturing process planning and the emerging CAD/CAM/CAE technologies promises significant increases in engineering productivity. This paper's focus is on areas in manufacturing where knowledge-based systems could most benefit the engineer and industry. 13 refs., 3 figs.

  15. Installing a Local Copy of the Reactome Web Site and Knowledgebase.

    PubMed

    McKay, Sheldon J; Weiser, Joel

    2015-06-19

    The Reactome project builds, maintains, and publishes a knowledgebase of biological pathways. The information in the knowledgebase is gathered from the experts in the field, peer reviewed and edited by Reactome editorial staff, and then published to the Reactome Web site, http://www.reactome.org. The Reactome software is open source and builds on top of other open-source or freely available software. Reactome data and code can be freely downloaded in its entirety and the Web site installed locally. This allows for more flexible interrogation of the data and also makes it possible to add one's own information to the knowledgebase.

  16. The Knowledge-Based Software Assistant: Beyond CASE

    NASA Technical Reports Server (NTRS)

    Carozzoni, Joseph A.

    1993-01-01

    This paper will outline the similarities and differences between two paradigms of software development. Both support the whole software life cycle and provide automation for most of the software development process, but have different approaches. The CASE approach is based on a set of tools linked by a central data repository. This tool-based approach is data driven and views software development as a series of sequential steps, each resulting in a product. The Knowledge-Based Software Assistant (KBSA) approach, a radical departure from existing software development practices, is knowledge driven and centers around a formalized software development process. KBSA views software development as an incremental, iterative, and evolutionary process with development occurring at the specification level.

  17. Development of a knowledge-based electronic patient record.

    PubMed

    Safran, C; Rind, D M; Sands, D Z; Davis, R B; Wald, J; Slack, W V

    1996-01-01

    To help clinicians care for patients with HIV infection, we developed an interactive knowledge-based electronic patient record that integrates rule-based decision support and full-text information retrieval with an online patient record. This highly interactive clinical workstation now allows the clinicians at a large primary care practice (30,000 ambulatory visits per year) to use online information resources and fully electronic patient records during all patient encounters. The resulting practice database is continually updated with outcome data on a cohort of 700 patients with HIV infection. As a byproduct of this integrated system, we have developed improved statistical methods to measure the effects of electronic alerts and reminders.

  18. Knowledge-based fault diagnosis system for refuse collection vehicle

    SciTech Connect

    Tan, CheeFai; Juffrizal, K.; Khalil, S. N.; Nidzamuddin, M. Y.

    2015-05-15

    The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledge that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.

  19. Autonomous Cryogenics Loading Operations Simulation Software: Knowledgebase Autonomous Test Engineer

    NASA Technical Reports Server (NTRS)

    Wehner, Walter S., Jr.

    2013-01-01

    Working on the ACLO (Autonomous Cryogenics Loading Operations) project I have had the opportunity to add functionality to the physics simulation software known as KATE (Knowledgebase Autonomous Test Engineer), create a new application allowing WYSIWYG (what-you-see-is-what-you-get) creation of KATE schematic files and begin a preliminary design and implementation of a new subsystem that will provide vision services on the IHM (Integrated Health Management) bus. The functionality I added to KATE over the past few months includes a dynamic visual representation of the fluid height in a pipe based on number of gallons of fluid in the pipe and implementing the IHM bus connection within KATE. I also fixed a broken feature in the system called the Browser Display, implemented many bug fixes and made changes to the GUI (Graphical User Interface).

  20. A knowledge-based system for prototypical reasoning

    NASA Astrophysics Data System (ADS)

    Lieto, Antonio; Minieri, Andrea; Piana, Alberto; Radicioni, Daniele P.

    2015-04-01

    In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces framework). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorisation task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning 'conceptual' capabilities of standard ontology-based systems.

  1. Knowledge-based system for flight information management. Thesis

    NASA Technical Reports Server (NTRS)

    Ricks, Wendell R.

    1990-01-01

    The use of knowledge-based system (KBS) architectures to manage information on the primary flight display (PFD) of commercial aircraft is described. The PFD information management strategy used tailored the information on the PFD to the tasks the pilot performed. The KBS design and implementation of the task-tailored PFD information management application is described. The knowledge acquisition and subsequent system design of a flight-phase-detection KBS is also described. The flight-phase output of this KBS was used as input to the task-tailored PFD information management KBS. The implementation and integration of this KBS with existing aircraft systems and the other KBS is described. The flight tests are examined of both KBS's, collectively called the Task-Tailored Flight Information Manager (TTFIM), which verified their implementation and integration, and validated the software engineering advantages of the KBS approach in an operational environment.

  2. Knowledge-based fault diagnosis system for refuse collection vehicle

    NASA Astrophysics Data System (ADS)

    Tan, CheeFai; Juffrizal, K.; Khalil, S. N.; Nidzamuddin, M. Y.

    2015-05-01

    The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledge that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.

  3. Knowledge-Based Framework: its specification and new related discussions

    NASA Astrophysics Data System (ADS)

    Rodrigues, Douglas; Zaniolo, Rodrigo R.; Branco, Kalinka R. L. J. C.

    2015-09-01

    Unmanned Aerial Vehicle is a common application of critical embedded systems. The heterogeneity prevalent in these vehicles in terms of services for avionics is particularly relevant to the elaboration of multi-application missions. Besides, this heterogeneity in UAV services is often manifested in the form of characteristics such as reliability, security and performance. Different service implementations typically offer different guarantees in terms of these characteristics and in terms of associated costs. Particularly, we explore the notion of Service-Oriented Architecture (SOA) in the context of UAVs as safety-critical embedded systems for the composition of services to fulfil application-specified performance and dependability guarantees. So, we propose a framework for the deployment of these services and their variants. This framework is called Knowledge-Based Framework for Dynamically Changing Applications (KBF) and we specify its services module, discussing all the related issues.

  4. Knowledge-based navigation of complex information spaces

    SciTech Connect

    Burke, R.D.; Hammond, K.J.; Young, B.C.

    1996-12-31

    While the explosion of on-line information has brought new opportunities for finding and using electronic data, it has also brought to the forefront the problem of isolating useful information and making sense of large multi-dimension information spaces. We have built several developed an approach to building data {open_quotes}tour guides,{close_quotes} called FINDME systems. These programs know enough about an information space to be able to help a user navigate through it. The user not only comes away with items of useful information but also insights into the structure of the information space itself. In these systems, we have combined ideas of instance-based browsing, structuring retrieval around the critiquing of previously-retrieved examples, and retrieval strategies, knowledge-based heuristics for finding relevant information. We illustrate these techniques with several examples, concentrating especially on the RENTME system, a FINDME system for helping users find suitable rental apartments in the Chicago metropolitan area.

  5. Assessing an AI knowledge-base for asymptomatic liver diseases.

    PubMed

    Babic, A; Mathiesen, U; Hedin, K; Bodemar, G; Wigertz, O

    1998-01-01

    Discovering not yet seen knowledge from clinical data is of importance in the field of asymptomatic liver diseases. Avoidance of liver biopsy which is used as the ultimate confirmation of diagnosis by making the decision based on relevant laboratory findings only, would be considered an essential support. The system based on Quinlan's ID3 algorithm was simple and efficient in extracting the sought knowledge. Basic principles of applying the AI systems are therefore described and complemented with medical evaluation. Some of the diagnostic rules were found to be useful as decision algorithms i.e. they could be directly applied in clinical work and made a part of the knowledge-base of the Liver Guide, an automated decision support system.

  6. Knowledge-based assistance in costing the space station DMS

    NASA Technical Reports Server (NTRS)

    Henson, Troy; Rone, Kyle

    1988-01-01

    The Software Cost Engineering (SCE) methodology developed over the last two decades at IBM Systems Integration Division (SID) in Houston is utilized to cost the NASA Space Station Data Management System (DMS). An ongoing project to capture this methodology, which is built on a foundation of experiences and lessons learned, has resulted in the development of an internal-use-only, PC-based prototype that integrates algorithmic tools with knowledge-based decision support assistants. This prototype Software Cost Engineering Automation Tool (SCEAT) is being employed to assist in the DMS costing exercises. At the same time, DMS costing serves as a forcing function and provides a platform for the continuing, iterative development, calibration, and validation and verification of SCEAT. The data that forms the cost engineering database is derived from more than 15 years of development of NASA Space Shuttle software, ranging from low criticality, low complexity support tools to highly complex and highly critical onboard software.

  7. Autonomous Cryogenics Loading Operations Simulation Software: Knowledgebase Autonomous Test Engineer

    NASA Technical Reports Server (NTRS)

    Wehner, Walter S.

    2012-01-01

    The Simulation Software, KATE (Knowledgebase Autonomous Test Engineer), is used to demonstrate the automatic identification of faults in a system. The ACLO (Autonomous Cryogenics Loading Operation) project uses KATE to monitor and find faults in the loading of the cryogenics int o a vehicle fuel tank. The KATE software interfaces with the IHM (Integrated Health Management) systems bus to communicate with other systems that are part of ACLO. One system that KATE uses the IHM bus to communicate with is AIS (Advanced Inspection System). KATE will send messages to AIS when there is a detected anomaly. These messages include visual inspection of specific valves, pressure gauges and control messages to have AIS open or close manual valves. My goals include implementing the connection to the IHM bus within KATE and for the AIS project. I will also be working on implementing changes to KATE's Ul and implementing the physics objects in KATE that will model portions of the cryogenics loading operation.

  8. A knowledge-based multiple-sequence alignment algorithm.

    PubMed

    Nguyen, Ken D; Pan, Yi

    2013-01-01

    A common and cost-effective mechanism to identify the functionalities, structures, or relationships between species is multiple-sequence alignment, in which DNA/RNA/protein sequences are arranged and aligned so that similarities between sequences are clustered together. Correctly identifying and aligning these sequence biological similarities help from unwinding the mystery of species evolution to drug design. We present our knowledge-based multiple sequence alignment (KB-MSA) technique that utilizes the existing knowledge databases such as SWISSPROT, GENBANK, or HOMSTRAD to provide a more realistic and reliable sequence alignment. We also provide a modified version of this algorithm (CB-MSA) that utilizes the sequence consistency information when sequence knowledge databases are not available. Our benchmark tests on BAliBASE, PREFAB, HOMSTRAD, and SABMARK references show accuracy improvements up to 10 percent on twilight data sets against many leading alignment tools such as ISPALIGN, PADT, CLUSTALW, MAFFT, PROBCONS, and T-COFFEE.

  9. OpenKIM - Building a Knowledgebase of Interatomic Models

    NASA Astrophysics Data System (ADS)

    Bierbaum, Matthew; Tadmor, Ellad; Elliott, Ryan; Wennblom, Trevor; Alemi, Alexander; Chen, Yan-Jiun; Karls, Daniel; Ludvik, Adam; Sethna, James

    2014-03-01

    The Knowledgebase of Interatomic Models (KIM) is an effort by the computational materials community to provide a standard interface for the development, characterization, and use of interatomic potentials. The KIM project has developed an API between simulation codes and interatomic models written in several different languages including C, Fortran, and Python. This interface is already supported in popular simulation environments such as LAMMPS and ASE, giving quick access to over a hundred compatible potentials that have been contributed so far. To compare and characterize models, we have developed a computational processing pipeline which automatically runs a series of tests for each model in the system, such as phonon dispersion relations and elastic constant calculations. To view the data from these tests, we created a rich set of interactive visualization tools located online. Finally, we created a Web repository to store and share these potentials, tests, and visualizations which can be found at https://openkim.org along with futher information.

  10. Detection of infrastructure manipulation with knowledge-based video surveillance

    NASA Astrophysics Data System (ADS)

    Muench, David; Hilsenbeck, Barbara; Kieritz, Hilke; Becker, Stefan; Grosselfinger, Ann-Kristin; Huebner, Wolfgang; Arens, Michael

    2016-10-01

    We are living in a world dependent on sophisticated technical infrastructure. Malicious manipulation of such critical infrastructure poses an enormous threat for all its users. Thus, running a critical infrastructure needs special attention to log the planned maintenance or to detect suspicious events. Towards this end, we present a knowledge-based surveillance approach capable of logging visual observable events in such an environment. The video surveillance modules are based on appearance-based person detection, which further is used to modulate the outcome of generic processing steps such as change detection or skin detection. A relation between the expected scene behavior and the underlying basic video surveillance modules is established. It will be shown that the combination already provides sufficient expressiveness to describe various everyday situations in indoor video surveillance. The whole approach is qualitatively and quantitatively evaluated on a prototypical scenario in a server room.

  11. A knowledge-based agent prototype for Chinese address geocoding

    NASA Astrophysics Data System (ADS)

    Wei, Ran; Zhang, Xuehu; Ding, Linfang; Ma, Haoming; Li, Qi

    2009-10-01

    Chinese address geocoding is a difficult problem to deal with due to intrinsic complexities in Chinese address systems and a lack of standards in address assignments and usages. In order to improve existing address geocoding algorithm, a spatial knowledge-based agent prototype aimed at validating address geocoding results is built to determine the spatial accuracies as well as matching confidence. A portion of human's knowledge of judging the spatial closeness of two addresses is represented via first order logic and the corresponding algorithms are implemented with the Prolog language. Preliminary tests conducted using addresses matching result in Beijing area showed that the prototype can successfully assess the spatial closeness between the matching address and the query address with 97% accuracy.

  12. Knowledge-based architecture for airborne mine and minefield detection

    NASA Astrophysics Data System (ADS)

    Agarwal, Sanjeev; Menon, Deepak; Swonger, C. W.

    2004-09-01

    One of the primary lessons learned from airborne mid-wave infrared (MWIR) based mine and minefield detection research and development over the last few years has been the fact that no single algorithm or static detection architecture is able to meet mine and minefield detection performance specifications. This is true not only because of the highly varied environmental and operational conditions under which an airborne sensor is expected to perform but also due to the highly data dependent nature of sensors and algorithms employed for detection. Attempts to make the algorithms themselves more robust to varying operating conditions have only been partially successful. In this paper, we present a knowledge-based architecture to tackle this challenging problem. The detailed algorithm architecture is discussed for such a mine/minefield detection system, with a description of each functional block and data interface. This dynamic and knowledge-driven architecture will provide more robust mine and minefield detection for a highly multi-modal operating environment. The acquisition of the knowledge for this system is predominantly data driven, incorporating not only the analysis of historical airborne mine and minefield imagery data collection, but also other "all source data" that may be available such as terrain information and time of day. This "all source data" is extremely important and embodies causal information that drives the detection performance. This information is not being used by current detection architectures. Data analysis for knowledge acquisition will facilitate better understanding of the factors that affect the detection performance and will provide insight into areas for improvement for both sensors and algorithms. Important aspects of this knowledge-based architecture, its motivations and the potential gains from its implementation are discussed, and some preliminary results are presented.

  13. Risk Management of New Microelectronics for NASA: Radiation Knowledge-base

    NASA Technical Reports Server (NTRS)

    LaBel, Kenneth A.

    2004-01-01

    Contents include the following: NASA Missions - implications to reliability and radiation constraints. Approach to Insertion of New Technologies Technology Knowledge-base development. Technology model/tool development and validation. Summary comments.

  14. Structure for a Knowledge-Based System to Estimate Soviet Tactics in the Airland Battle.

    DTIC Science & Technology

    1988-03-01

    was developed as a knowledge-based system, which,. " . is a subset of artificial intelig ~ence (AI) technoiogy. Knowledge-based systems, including...and error adjustments using testcases (obtained from records of Soviet exer- % cises) . Dynamic. Low DSS Frame represen- tations of time, frequent...6). 16. Harmon, Paul and David King. Expert Systems -Artificial Intelligence in Business . New York NY: Wiley Press, 1985. * 17. Harrison, Major H

  15. A study of knowledge-based systems for the Space Station

    NASA Technical Reports Server (NTRS)

    Friedland, Peter; Swietek, Gregg; Bullock, Bruce

    1989-01-01

    A rapid turnaround study on the potential uses of knowledge-based systems for Space Station Freedom was conducted from October 1987 through January 1988. Participants included both NASA personnel and experienced industrial knowledge engineers. Major results of the study included five recommended systems for the Baseline Configuration of the Space Station, an analysis of sensor hooks and scars, and a proposed plan for evolutionary growth of knowledge-based systems on the Space Station.

  16. Validation of highly reliable, real-time knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Johnson, Sally C.

    1988-01-01

    Knowledge-based systems have the potential to greatly increase the capabilities of future aircraft and spacecraft and to significantly reduce support manpower needed for the space station and other space missions. However, a credible validation methodology must be developed before knowledge-based systems can be used for life- or mission-critical applications. Experience with conventional software has shown that the use of good software engineering techniques and static analysis tools can greatly reduce the time needed for testing and simulation of a system. Since exhaustive testing is infeasible, reliability must be built into the software during the design and implementation phases. Unfortunately, many of the software engineering techniques and tools used for conventional software are of little use in the development of knowledge-based systems. Therefore, research at Langley is focused on developing a set of guidelines, methods, and prototype validation tools for building highly reliable, knowledge-based systems. The use of a comprehensive methodology for building highly reliable, knowledge-based systems should significantly decrease the time needed for testing and simulation. A proven record of delivering reliable systems at the beginning of the highly visible testing and simulation phases is crucial to the acceptance of knowledge-based systems in critical applications.

  17. Selection of construction methods: a knowledge-based approach.

    PubMed

    Ferrada, Ximena; Serpell, Alfredo; Skibniewski, Miroslaw

    2013-01-01

    The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method' selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS) was developed and then validated with construction industry professionals. As a conclusion, the CMKS was perceived as a valuable tool for construction methods' selection, by helping companies to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The described benefits as provided by the system favor a better performance of construction projects.

  18. Hyperincursion and the Globalization of the Knowledge-Based Economy

    NASA Astrophysics Data System (ADS)

    Leydesdorff, Loet

    2006-06-01

    In biological systems, the capacity of anticipation—that is, entertaining a model of the system within the system—can be considered as naturally given. Human languages enable psychological systems to construct and exchange mental models of themselves and their environments reflexively, that is, provide meaning to the events. At the level of the social system expectations can further be codified. When these codifications are functionally differentiated—like between market mechanisms and scientific research programs—the potential asynchronicity in the update among the subsystems provides room for a second anticipatory mechanism at the level of the transversal information exchange among differently codified meaning-processing subsystems. Interactions between the two different anticipatory mechanisms (the transversal one and the one along the time axis in each subsystem) may lead to co-evolutions and stabilization of expectations along trajectories. The wider horizon of knowledgeable expectations can be expected to meta-stabilize and also globalize a previously stabilized configuration of expectations against the axis of time. While stabilization can be considered as consequences of interaction and aggregation among incursive formulations of the logistic equation, globalization can be modeled using the hyperincursive formulation of this equation. The knowledge-based subdynamic at the global level which thus emerges, enables historical agents to inform the reconstruction of previous states and to co-construct future states of the social system, for example, in a techno-economic co-evolution.

  19. Designing the Cloud-based DOE Systems Biology Knowledgebase

    SciTech Connect

    Lansing, Carina S.; Liu, Yan; Yin, Jian; Corrigan, Abigail L.; Guillen, Zoe C.; Kleese van Dam, Kerstin; Gorton, Ian

    2011-09-01

    Systems Biology research, even more than many other scientific domains, is becoming increasingly data-intensive. Not only have advances in experimental and computational technologies lead to an exponential increase in scientific data volumes and their complexity, but increasingly such databases themselves are providing the basis for new scientific discoveries. To engage effectively with these community resources, integrated analyses, synthesis and simulation software is needed, regularly supported by scientific workflows. In order to provide a more collaborative, community driven research environment for this heterogeneous setting, the Department of Energy (DOE) has decided to develop a federated, cloud based cyber infrastructure - the Systems Biology Knowledgebase (Kbase). Pacific Northwest National Laboratory (PNNL) with its long tradition in data intensive science lead two of the five initial pilot projects, these two focusing on defining and testing the basic federated cloud-based system architecture and develop a prototype implementation. Hereby the community wide accessibility of biological data and the capability to integrate and analyze this data within its changing research context were seen as key technical functionalities the Kbase needed to enable. In this paper we describe the results of our investigations into the design of a cloud based federated infrastructure for: (1) Semantics driven data discovery, access and integration; (2) Data annotation, publication and sharing; (3) Workflow enabled data analysis; and (4) Project based collaborative working. We describe our approach, exemplary use cases and our prototype implementation that demonstrates the feasibility of this approach.

  20. Knowledge-based control of an adaptive interface

    NASA Technical Reports Server (NTRS)

    Lachman, Roy

    1989-01-01

    The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

  1. Compiling knowledge-based systems from KEE to Ada

    NASA Technical Reports Server (NTRS)

    Filman, Robert E.; Bock, Conrad; Feldman, Roy

    1990-01-01

    The dominant technology for developing AI applications is to work in a multi-mechanism, integrated, knowledge-based system (KBS) development environment. Unfortunately, systems developed in such environments are inappropriate for delivering many applications - most importantly, they carry the baggage of the entire Lisp environment and are not written in conventional languages. One resolution of this problem would be to compile applications from complex environments to conventional languages. Here the first efforts to develop a system for compiling KBS developed in KEE to Ada (trademark). This system is called KATYDID, for KEE/Ada Translation Yields Development Into Delivery. KATYDID includes early prototypes of a run-time KEE core (object-structure) library module for Ada, and translation mechanisms for knowledge structures, rules, and Lisp code to Ada. Using these tools, part of a simple expert system was compiled (not quite automatically) to run in a purely Ada environment. This experience has given us various insights on Ada as an artificial intelligence programming language, potential solutions of some of the engineering difficulties encountered in early work, and inspiration on future system development.

  2. Matching sensors to missions using a knowledge-based approach

    NASA Astrophysics Data System (ADS)

    Preece, Alun; Gomez, Mario; de Mel, Geeth; Vasconcelos, Wamberto; Sleeman, Derek; Colley, Stuart; Pearson, Gavin; Pham, Tien; La Porta, Thomas

    2008-04-01

    Making decisions on how best to utilise limited intelligence, surveillance and reconnaisance (ISR) resources is a key issue in mission planning. This requires judgements about which kinds of available sensors are more or less appropriate for specific ISR tasks in a mission. A methodological approach to addressing this kind of decision problem in the military context is the Missions and Means Framework (MMF), which provides a structured way to analyse a mission in terms of tasks, and assess the effectiveness of various means for accomplishing those tasks. Moreover, the problem can be defined as knowledge-based matchmaking: matching the ISR requirements of tasks to the ISR-providing capabilities of available sensors. In this paper we show how the MMF can be represented formally as an ontology (that is, a specification of a conceptualisation); we also represent knowledge about ISR requirements and sensors, and then use automated reasoning to solve the matchmaking problem. We adopt the Semantic Web approach and the Web Ontology Language (OWL), allowing us to import elements of existing sensor knowledge bases. Our core ontologies use the description logic subset of OWL, providing efficient reasoning. We describe a prototype tool as a proof-of-concept for our approach. We discuss the various kinds of possible sensor-mission matches, both exact and inexact, and how the tool helps mission planners consider alternative choices of sensors.

  3. Knowledge-based graphical interfaces for presenting technical information

    NASA Technical Reports Server (NTRS)

    Feiner, Steven

    1988-01-01

    Designing effective presentations of technical information is extremely difficult and time-consuming. Moreover, the combination of increasing task complexity and declining job skills makes the need for high-quality technical presentations especially urgent. We believe that this need can ultimately be met through the development of knowledge-based graphical interfaces that can design and present technical information. Since much material is most naturally communicated through pictures, our work has stressed the importance of well-designed graphics, concentrating on generating pictures and laying out displays containing them. We describe APEX, a testbed picture generation system that creates sequences of pictures that depict the performance of simple actions in a world of 3D objects. Our system supports rules for determining automatically the objects to be shown in a picture, the style and level of detail with which they should be rendered, the method by which the action itself should be indicated, and the picture's camera specification. We then describe work on GRIDS, an experimental display layout system that addresses some of the problems in designing displays containing these pictures, determining the position and size of the material to be presented.

  4. KBGIS-2: A knowledge-based geographic information system

    NASA Technical Reports Server (NTRS)

    Smith, T.; Peuquet, D.; Menon, S.; Agarwal, P.

    1986-01-01

    The architecture and working of a recently implemented knowledge-based geographic information system (KBGIS-2) that was designed to satisfy several general criteria for the geographic information system are described. The system has four major functions that include query-answering, learning, and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial objects language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is currently performing all its designated tasks successfully, although currently implemented on inadequate hardware. Future reports will detail the performance characteristics of the system, and various new extensions are planned in order to enhance the power of KBGIS-2.

  5. Plant Protein Annotation in the UniProt Knowledgebase1

    PubMed Central

    Schneider, Michel; Bairoch, Amos; Wu, Cathy H.; Apweiler, Rolf

    2005-01-01

    The Swiss-Prot, TrEMBL, Protein Information Resource (PIR), and DNA Data Bank of Japan (DDBJ) protein database activities have united to form the Universal Protein Resource (UniProt) Consortium. UniProt presents three database layers: the UniProt Archive, the UniProt Knowledgebase (UniProtKB), and the UniProt Reference Clusters. The UniProtKB consists of two sections: UniProtKB/Swiss-Prot (fully manually curated entries) and UniProtKB/TrEMBL (automated annotation, classification and extensive cross-references). New releases are published fortnightly. A specific Plant Proteome Annotation Program (http://www.expasy.org/sprot/ppap/) was initiated to cope with the increasing amount of data produced by the complete sequencing of plant genomes. Through UniProt, our aim is to provide the scientific community with a single, centralized, authoritative resource for protein sequences and functional information that will allow the plant community to fully explore and utilize the wealth of information available for both plant and nonplant model organisms. PMID:15888679

  6. FunSecKB: the Fungal Secretome KnowledgeBase

    PubMed Central

    Lum, Gengkon; Min, Xiang Jia

    2011-01-01

    The Fungal Secretome KnowledgeBase (FunSecKB) provides a resource of secreted fungal proteins, i.e. secretomes, identified from all available fungal protein data in the NCBI RefSeq database. The secreted proteins were identified using a well evaluated computational protocol which includes SignalP, WolfPsort and Phobius for signal peptide or subcellular location prediction, TMHMM for identifying membrane proteins, and PS-Scan for identifying endoplasmic reticulum (ER) target proteins. The entries were mapped to the UniProt database and any annotations of subcellular locations that were either manually curated or computationally predicted were included in FunSecKB. Using a web-based user interface, the database is searchable, browsable and downloadable by using NCBI’s RefSeq accession or gi number, UniProt accession number, keyword or by species. A BLAST utility was integrated to allow users to query the database by sequence similarity. A user submission tool was implemented to support community annotation of subcellular locations of fungal proteins. With the complete fungal data from RefSeq and associated web-based tools, FunSecKB will be a valuable resource for exploring the potential applications of fungal secreted proteins. Database URL: http://proteomics.ysu.edu/secretomes/fungi.php PMID:21300622

  7. Knowledge-based approach to video content classification

    NASA Astrophysics Data System (ADS)

    Chen, Yu; Wong, Edward K.

    2000-12-01

    A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

  8. Knowledge-based approach to video content classification

    NASA Astrophysics Data System (ADS)

    Chen, Yu; Wong, Edward K.

    2001-01-01

    A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

  9. Knowledge-based inference engine for online video dissemination

    NASA Astrophysics Data System (ADS)

    Zhou, Wensheng; Kuo, C.-C. Jay

    2000-10-01

    To facilitate easy access to rich information of multimedia over the Internet, we develop a knowledge-based classification system that supports automatic Indexing and filtering based on semantic concepts for the dissemination of on-line real-time media. Automatic segmentation, annotation and summarization of media for fast information browsing and updating are achieved in the same time. In the proposed system, a real-time scene-change detection proxy performs an initial video structuring process by splitting a video clip into scenes. Motional and visual features are extracted in real time for every detected scene by using online feature extraction proxies. Higher semantics are then derived through a joint use of low-level features along with inference rules in the knowledge base. Inference rules are derived through a supervised learning process based on representative samples. On-line media filtering based on semantic concepts becomes possible by using the proposed video inference engine. Video streams are either blocked or sent to certain channels depending on whether or not the video stream is matched with the user's profile. The proposed system is extensively evaluated by applying the engine to video of basketball games.

  10. Knowledge-based planning model for courses of action generation

    SciTech Connect

    Collins, D.R.; Baucum, T.A.

    1986-04-07

    U.S. Army War College students of the Class of 1986 were solicited to participate in a Military Studies Program to develop a planning model for Courses of Action Generation. The Model was to be knowledge-based, i.e., drawn from the collective experience of officers with operational/planning backgrounds. The purpose of this document is to summarize the results of the four knowledge engineering sessions conducted. The detailed results are at enclosures 1-4, each enclosure acting as an agreed-upon record of that engineering session. Initial discussions between the CECLOM computer scientist and the AWC students concerned the potential for automation of the process of developing a scheme of maneuver. It was the opinion of the students that some aspects of the process would be extremely difficult to include in a computer program - the intent of the commander, for example. While neither student dismissed the potential of artificial intelligence on the battlefield, neither actively sought ways to incorporate it, either. What evolved, therefore, was and exposition by the students of what actually goes on in the minds of commanders and battlefield planners during an active operational environment.

  11. Verification of Legal Knowledge-base with Conflictive Concept

    NASA Astrophysics Data System (ADS)

    Hagiwara, Shingo; Tojo, Satoshi

    In this paper, we propose a verification methodology of large-scale legal knowledge. With a revision of legal code, we are forced to revise also other affected code to keep the consistency of law. Thus, our task is to revise the affected area properly and to investigate its adequacy. In this study, we extend the notion of inconsistency besides of the ordinary logical inconsistency, to include the conceptual conflicts. We obtain these conflictions from taxonomy data, and thus, we can avoid tedious manual declarations of opponent words. In the verification process, we adopt extended disjunctive logic programming (EDLP) to tolerate multiple consequences for a given set of antecedents. In addition, we employ abductive logic programming (ALP) regarding the situations to which the rules are applied as premises. Also, we restrict a legal knowledge-base to acyclic program to avoid the circulation of definitions, to justify the relevance of verdicts. Therefore, detecting cyclic parts of legal knowledge would be one of our objectives. The system is composed of two subsystems; we implement the preprocessor in Ruby to facilitate string manipulation, and the verifier in Prolog to exert the logical inference. Also, we employ XML format in the system to retain readability. In this study, we verify actual code of ordinances of Toyama prefecture, and show the experimental results.

  12. KBGIS-II: A knowledge-based geographic information system

    NASA Technical Reports Server (NTRS)

    Smith, Terence; Peuquet, Donna; Menon, Sudhakar; Agarwal, Pankaj

    1986-01-01

    The architecture and working of a recently implemented Knowledge-Based Geographic Information System (KBGIS-II), designed to satisfy several general criteria for the GIS, is described. The system has four major functions including query-answering, learning and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial object language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is performing all its designated tasks successfully. Future reports will relate performance characteristics of the system.

  13. Document Retrieval Using A Fuzzy Knowledge-Based System

    NASA Astrophysics Data System (ADS)

    Subramanian, Viswanath; Biswas, Gautam; Bezdek, James C.

    1986-03-01

    This paper presents the design and development of a prototype document retrieval system using a knowledge-based systems approach. Both the domain-specific knowledge base and the inferencing schemes are based on a fuzzy set theoretic framework. A query in natural language represents a request to retrieve a relevant subset of documents from a document base. Such a query, which can include both fuzzy terms and fuzzy relational operators, is converted into an unambiguous intermediate form by a natural language interface. Concepts that describe domain topics and the relationships between concepts, such as the synonym relation and the implication relation between a general concept and more specific concepts, have been captured in a knowledge base. The knowledge base enables the system to emulate the reasoning process followed by an expert, such as a librarian, in understanding and reformulating user queries. The retrieval mechanism processes the query in two steps. First it produces a pruned list of documents pertinent to the query. Second, it uses an evidence combination scheme to compute a degree of support between the query and individual documents produced in step one. The front-end component of the system then presents a set of document citations to the user in ranked order as an answer to the information request.

  14. Embedded knowledge-based system for automatic target recognition

    NASA Astrophysics Data System (ADS)

    Aboutalib, A. O.

    1990-10-01

    The development of a reliable Automatic Target Recognition (ATE) system is considered a very critical and challenging problem. Existing ATE Systems have inherent limitations in terms of recognition performance and the ability to learn and adapt. Artificial Intelligence Techniques have the potential to improve the performance of ATh Systems. In this paper, we presented a novel Knowledge-Engineering tool, termed, the Automatic Reasoning Process (ARP) , that can be used to automatically develop and maintain a Knowledge-Base (K-B) for the ATR Systems. In its learning mode, the ARP utilizes Learning samples to automatically develop the ATR K-B, which consists of minimum size sets of necessary and sufficient conditions for each target class. In its operational mode, the ARP infers the target class from sensor data using the ATh K-B System. The ARP also has the capability to reason under uncertainty, and can support both statistical and model-based approaches for ATR development. The capabilities of the ARP are compared and contrasted to those of another Knowledge-Engineering tool, termed, the Automatic Rule Induction (ARI) which is based on maximizing the mutual information. The AR? has been implemented in LISP on a VAX-GPX workstation.

  15. Knowledge-based computer systems for radiotherapy planning.

    PubMed

    Kalet, I J; Paluszynski, W

    1990-08-01

    Radiation therapy is one of the first areas of clinical medicine to utilize computers in support of routine clinical decision making. The role of the computer has evolved from simple dose calculations to elaborate interactive graphic three-dimensional simulations. These simulations can combine external irradiation from megavoltage photons, electrons, and particle beams with interstitial and intracavitary sources. With the flexibility and power of modern radiotherapy equipment and the ability of computer programs that simulate anything the machinery can do, we now face a challenge to utilize this capability to design more effective radiation treatments. How can we manage the increased complexity of sophisticated treatment planning? A promising approach will be to use artificial intelligence techniques to systematize our present knowledge about design of treatment plans, and to provide a framework for developing new treatment strategies. Far from replacing the physician, physicist, or dosimetrist, artificial intelligence-based software tools can assist the treatment planning team in producing more powerful and effective treatment plans. Research in progress using knowledge-based (AI) programming in treatment planning already has indicated the usefulness of such concepts as rule-based reasoning, hierarchical organization of knowledge, and reasoning from prototypes. Problems to be solved include how to handle continuously varying parameters and how to evaluate plans in order to direct improvements.

  16. ISPE: A knowledge-based system for fluidization studies

    SciTech Connect

    Reddy, S.

    1991-01-01

    Chemical engineers use mathematical simulators to design, model, optimize and refine various engineering plants/processes. This procedure requires the following steps: (1) preparation of an input data file according to the format required by the target simulator; (2) excecuting the simulation; and (3) analyzing the results of the simulation to determine if all specified goals'' are satisfied. If the goals are not met, the input data file must be modified and the simulation repeated. This multistep process is continued until satisfactory results are obtained. This research was undertaken to develop a knowledge based system, IPSE (Intelligent Process Simulation Environment), that can enhance the productivity of chemical engineers/modelers by serving as an intelligent assistant to perform a variety tasks related to process simulation. ASPEN, a widely used simulator by the US Department of Energy (DOE) at Morgantown Energy Technology Center (METC) was selected as the target process simulator in the project. IPSE, written in the C language, was developed using a number of knowledge-based programming paradigms: object-oriented knowledge representation that uses inheritance and methods, rulebased inferencing (includes processing and propagation of probabilistic information) and data-driven programming using demons. It was implemented using the knowledge based environment LASER. The relationship of IPSE with the user, ASPEN, LASER and the C language is shown in Figure 1.

  17. Selection of Construction Methods: A Knowledge-Based Approach

    PubMed Central

    Skibniewski, Miroslaw

    2013-01-01

    The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method' selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS) was developed and then validated with construction industry professionals. As a conclusion, the CMKS was perceived as a valuable tool for construction methods' selection, by helping companies to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The described benefits as provided by the system favor a better performance of construction projects. PMID:24453925

  18. SmartWeld: A knowledge-based approach to welding

    SciTech Connect

    Mitchiner, J.L.; Kleban, S.D.; Hess, B.V.; Mahin, K.W.; Messink, D.

    1996-07-01

    SmartWeld is a concurrent engineering system that integrates product design and processing decisions within an electronic desktop engineering environment. It is being developed to provide designers, process engineers, researchers and manufacturing technologists with transparent access to the right process information, process models, process experience and process experts, to realize``right the first time`` manufacturing. Empirical understanding along with process models are synthesized within a knowledge-based system to identify robust fabrication procedures based on cost, schedule, and performance. Integration of process simulation tools with design tools enables the designer to assess a number of design and process options on the computer rather than on the manufacturing floor. Task models and generic process models are being embedded within user friendly GUI`s to more readily enable the customer to use the SmartWeld system and its software tool set without extensive training. The integrated system architecture under development provides interactive communications and shared application capabilities across a variety of workstation and PC-type platforms either locally or at remote sites.

  19. A knowledge-based system design/information tool

    NASA Technical Reports Server (NTRS)

    Allen, James G.; Sikora, Scott E.

    1990-01-01

    The objective of this effort was to develop a Knowledge Capture System (KCS) for the Integrated Test Facility (ITF) at the Dryden Flight Research Facility (DFRF). The DFRF is a NASA Ames Research Center (ARC) facility. This system was used to capture the design and implementation information for NASA's high angle-of-attack research vehicle (HARV), a modified F/A-18A. In particular, the KCS was used to capture specific characteristics of the design of the HARV fly-by-wire (FBW) flight control system (FCS). The KCS utilizes artificial intelligence (AI) knowledge-based system (KBS) technology. The KCS enables the user to capture the following characteristics of automated systems: the system design; the hardware (H/W) design and implementation; the software (S/W) design and implementation; and the utilities (electrical and hydraulic) design and implementation. A generic version of the KCS was developed which can be used to capture the design information for any automated system. The deliverable items for this project consist of the prototype generic KCS and an application, which captures selected design characteristics of the HARV FCS.

  20. Framework Support For Knowledge-Based Software Development

    NASA Astrophysics Data System (ADS)

    Huseth, Steve

    1988-03-01

    The advent of personal engineering workstations has brought substantial information processing power to the individual programmer. Advanced tools and environment capabilities supporting the software lifecycle are just beginning to become generally available. However, many of these tools are addressing only part of the software development problem by focusing on rapid construction of self-contained programs by a small group of talented engineers. Additional capabilities are required to support the development of large programming systems where a high degree of coordination and communication is required among large numbers of software engineers, hardware engineers, and managers. A major player in realizing these capabilities is the framework supporting the software development environment. In this paper we discuss our research toward a Knowledge-Based Software Assistant (KBSA) framework. We propose the development of an advanced framework containing a distributed knowledge base that can support the data representation needs of tools, provide environmental support for the formalization and control of the software development process, and offer a highly interactive and consistent user interface.

  1. Knowledge-Based Query Construction Using the CDSS Knowledge Base for Efficient Evidence Retrieval

    PubMed Central

    Afzal, Muhammad; Hussain, Maqbool; Ali, Taqdir; Hussain, Jamil; Khan, Wajahat Ali; Lee, Sungyoung; Kang, Byeong Ho

    2015-01-01

    Finding appropriate evidence to support clinical practices is always challenging, and the construction of a query to retrieve such evidence is a fundamental step. Typically, evidence is found using manual or semi-automatic methods, which are time-consuming and sometimes make it difficult to construct knowledge-based complex queries. To overcome the difficulty in constructing knowledge-based complex queries, we utilized the knowledge base (KB) of the clinical decision support system (CDSS), which has the potential to provide sufficient contextual information. To automatically construct knowledge-based complex queries, we designed methods to parse rule structure in KB of CDSS in order to determine an executable path and extract the terms by parsing the control structures and logic connectives used in the logic. The automatically constructed knowledge-based complex queries were executed on the PubMed search service to evaluate the results on the reduction of retrieved citations with high relevance. The average number of citations was reduced from 56,249 citations to 330 citations with the knowledge-based query construction approach, and relevance increased from 1 term to 6 terms on average. The ability to automatically retrieve relevant evidence maximizes efficiency for clinicians in terms of time, based on feedback collected from clinicians. This approach is generally useful in evidence-based medicine, especially in ambient assisted living environments where automation is highly important. PMID:26343669

  2. Autonomous Cryogenic Load Operations: Knowledge-Based Autonomous Test Engineer

    NASA Technical Reports Server (NTRS)

    Schrading, J. Nicolas

    2013-01-01

    The Knowledge-Based Autonomous Test Engineer (KATE) program has a long history at KSC. Now a part of the Autonomous Cryogenic Load Operations (ACLO) mission, this software system has been sporadically developed over the past 20 years. Originally designed to provide health and status monitoring for a simple water-based fluid system, it was proven to be a capable autonomous test engineer for determining sources of failure in the system. As part of a new goal to provide this same anomaly-detection capability for a complicated cryogenic fluid system, software engineers, physicists, interns and KATE experts are working to upgrade the software capabilities and graphical user interface. Much progress was made during this effort to improve KATE. A display of the entire cryogenic system's graph, with nodes for components and edges for their connections, was added to the KATE software. A searching functionality was added to the new graph display, so that users could easily center their screen on specific components. The GUI was also modified so that it displayed information relevant to the new project goals. In addition, work began on adding new pneumatic and electronic subsystems into the KATE knowledge base, so that it could provide health and status monitoring for those systems. Finally, many fixes for bugs, memory leaks, and memory errors were implemented and the system was moved into a state in which it could be presented to stakeholders. Overall, the KATE system was improved and necessary additional features were added so that a presentation of the program and its functionality in the next few months would be a success.

  3. Minimizing proteome redundancy in the UniProt Knowledgebase

    PubMed Central

    Bursteinas, Borisas; Britto, Ramona; Bely, Benoit; Auchincloss, Andrea; Rivoire, Catherine; Redaschi, Nicole; O'Donovan, Claire; Martin, Maria Jesus

    2016-01-01

    Advances in high-throughput sequencing have led to an unprecedented growth in genome sequences being submitted to biological databases. In particular, the sequencing of large numbers of nearly identical bacterial genomes during infection outbreaks and for other large-scale studies has resulted in a high level of redundancy in nucleotide databases and consequently in the UniProt Knowledgebase (UniProtKB). Redundancy negatively impacts on database searches by causing slower searches, an increase in statistical bias and cumbersome result analysis. The redundancy combined with the large data volume increases the computational costs for most reuses of UniProtKB data. All of this poses challenges for effective discovery in this wealth of data. With the continuing development of sequencing technologies, it is clear that finding ways to minimize redundancy is crucial to maintaining UniProt's essential contribution to data interpretation by our users. We have developed a methodology to identify and remove highly redundant proteomes from UniProtKB. The procedure identifies redundant proteomes by performing pairwise alignments of sets of sequences for pairs of proteomes and subsequently, applies graph theory to find dominating sets that provide a set of non-redundant proteomes with a minimal loss of information. This method was implemented for bacteria in mid-2015, resulting in a removal of 50 million proteins in UniProtKB. With every new release, this procedure is used to filter new incoming proteomes, resulting in a more scalable and scientifically valuable growth of UniProtKB. Database URL: http://www.uniprot.org/proteomes/ PMID:28025334

  4. A knowledge-based information system for monitoring drug levels.

    PubMed

    Wiener, F; Groth, T; Mortimer, O; Hallquist, I; Rane, A

    1989-06-01

    The expert system shell SMR has been enhanced to include information system routines for designing data screens and providing facilities for data entry, storage, retrieval, queries and descriptive statistics. The data for inference making is abstracted from the data base record and inserted into a data array to which the knowledge base is applied to derive the appropriate advice and comments. The enhanced system has been used to develop an intelligent information system for monitoring serum drug levels which includes evaluation of temporal changes and production of specialized printed reports. The module for digoxin has been fully developed and validated. To demonstrate the extension to other drugs a module for phenytoin was constructed with only a rudimentary knowledge base. Data from the request forms together with the S-digoxin results are entered into the data base by the department secretary. The day's results are then reviewed by the clinical pharmacologist. For each case, previous results may be displayed and are taken into account by the system in the decision process. The knowledge base is applied to the data to formulate an evaluative comment on the report returned to the requestor. The report includes a semi-graphic presentation of the current and previous results and either the system's interpretation or one entered by the pharmacologist if he does not agree with it. The pharmacologist's comment is also recorded in the data base for future retrieval, analysis and possible updating of the knowledge base. The system is now undergoing testing and evaluation under routine operations in the clinical pharmacology service. It is a prototype for other applications in both laboratory and clinical medicine currently under development at Uppsala University Hospital. This system may thus provide a vehicle for a more intensive penetration of knowledge-based systems in practical medical applications.

  5. Knowledge-based nonuniform sampling in multidimensional NMR.

    PubMed

    Schuyler, Adam D; Maciejewski, Mark W; Arthanari, Haribabu; Hoch, Jeffrey C

    2011-07-01

    The full resolution afforded by high-field magnets is rarely realized in the indirect dimensions of multidimensional NMR experiments because of the time cost of uniformly sampling to long evolution times. Emerging methods utilizing nonuniform sampling (NUS) enable high resolution along indirect dimensions by sampling long evolution times without sampling at every multiple of the Nyquist sampling interval. While the earliest NUS approaches matched the decay of sampling density to the decay of the signal envelope, recent approaches based on coupled evolution times attempt to optimize sampling by choosing projection angles that increase the likelihood of resolving closely-spaced resonances. These approaches employ knowledge about chemical shifts to predict optimal projection angles, whereas prior applications of tailored sampling employed only knowledge of the decay rate. In this work we adapt the matched filter approach as a general strategy for knowledge-based nonuniform sampling that can exploit prior knowledge about chemical shifts and is not restricted to sampling projections. Based on several measures of performance, we find that exponentially weighted random sampling (envelope matched sampling) performs better than shift-based sampling (beat matched sampling). While shift-based sampling can yield small advantages in sensitivity, the gains are generally outweighed by diminished robustness. Our observation that more robust sampling schemes are only slightly less sensitive than schemes highly optimized using prior knowledge about chemical shifts has broad implications for any multidimensional NMR study employing NUS. The results derived from simulated data are demonstrated with a sample application to PfPMT, the phosphoethanolamine methyltransferase of the human malaria parasite Plasmodium falciparum.

  6. MetaShare: Enabling Knowledge-Based Data Management

    NASA Astrophysics Data System (ADS)

    Pennington, D. D.; Salayandia, L.; Gates, A.; Osuna, F.

    2013-12-01

    MetaShare is a free and open source knowledge-based system for supporting data management planning, now required by some agencies and publishers. MetaShare supports users as they describe the types of data they will collect, expected standards, and expected policies for sharing. MetaShare's semantic model captures relationships between disciplines, tools, data types, data formats, and metadata standards. As the user plans their data management activities, MetaShare recommends choices based on practices and decisions from a community that has used the system for similar purposes, and extends the knowledge base to capture new relationships. The MetaShare knowledge base is being seeded with information for geoscience and environmental science domains, and is currently undergoing testing on at the University of Texas at El Paso. Through time and usage, it is expected to grow to support a variety of research domains, enabling community-based learning of data management practices. Knowledge of a user's choices during the planning phase can be used to support other tasks in the data life cycle, e.g., collecting, disseminating, and archiving data. A key barrier to scientific data sharing is the lack of sufficient metadata that provides context under which data were collected. The next phase of MetaShare development will automatically generate data collection instruments with embedded metadata and semantic annotations based on the information provided during the planning phase. While not comprehensive, this metadata will be sufficient for discovery and will enable user's to focus on more detailed descriptions of their data. Details are available at: Salayandia, L., Pennington, D., Gates, A., and Osuna, F. (accepted). MetaShare: From data management plans to knowledge base systems. AAAI Fall Symposium Series Workshop on Discovery Informatics, November 15-17, 2013, Arlington, VA.

  7. Presidential Helicopter Acquisition: Program Established Knowledge-Based Business Case and Entered System Development with Plans for Managing Challenges

    DTIC Science & Technology

    2015-04-14

    Presidential Helicopter Acquisition: Program Established Knowledge-Based Business Case and Entered System Development with Plans for Managing Challenges ...Acquisition Reform Act of 2009 (WSARA), This report discusses the cost, schedule, and performance status of the program, challenges it will face in...Presidential Helicopter Acquisition: Program Established Knowledge-Based Business Case and Entered System Development with Plans for Managing

  8. A knowledge-based approach to automated flow-field zoning for computational fluid dynamics

    NASA Technical Reports Server (NTRS)

    Vogel, Alison Andrews

    1989-01-01

    An automated three-dimensional zonal grid generation capability for computational fluid dynamics is shown through the development of a demonstration computer program capable of automatically zoning the flow field of representative two-dimensional (2-D) aerodynamic configurations. The applicability of a knowledge-based programming approach to the domain of flow-field zoning is examined. Several aspects of flow-field zoning make the application of knowledge-based techniques challenging: the need for perceptual information, the role of individual bias in the design and evaluation of zonings, and the fact that the zoning process is modeled as a constructive, design-type task (for which there are relatively few examples of successful knowledge-based systems in any domain). Engineering solutions to the problems arising from these aspects are developed, and a demonstration system is implemented which can design, generate, and output flow-field zonings for representative 2-D aerodynamic configurations.

  9. Installing a Local Copy of the Reactome Web Site and Knowledgebase

    PubMed Central

    McKay, Sheldon J; Weiser, Joel

    2015-01-01

    The Reactome project builds, maintains, and publishes a knowledgebase of biological pathways. The information in the knowledgebase is gathered from the experts in the field, peer reviewed, and edited by Reactome editorial staff and then published to the Reactome Web site, http://www.reactome.org (see UNIT 8.7; Croft et al., 2013). The Reactome software is open source and builds on top of other open-source or freely available software. Reactome data and code can be freely downloaded in its entirety and the Web site installed locally. This allows for more flexible interrogation of the data and also makes it possible to add one’s own information to the knowledgebase. PMID:26087747

  10. Expert systems ''to go'': Laptop personal computers and knowledge-based software

    SciTech Connect

    Carr, K.R.

    1988-01-01

    There are many instances in the everyday activities of many fields in which the physically small, lightweight, battery-powered laptop personal computer with appropriate knowledge-based software can be a highly beneficial tool. For example, in chemical engineering field work, the easily portable laptop personal computer with expert system programs can provide expert assistance in troubleshooting equipment, tuning controllers, and installing various components. Laptop personal computers fill a particular niche in the use of knowledge-based software; at the Oak Ridge facilities of the US Department of Energy, knowledge-based software is being used on a wide range of computers, including a Cray X-MP/12, Digital Equipment Corp., VAX 8700, VAX 8200, and VAXstations, Symbolics, Inc., 3640 LISP machines, many IBM PC's and compatibles, as well as laptop personal computers. Factors considered include expert system transfer from larger computers, program execution speed, memory capacity, and options for utilization of non-volatile memory storage. 46 refs.

  11. Applying knowledge-based methods to design and implement an air quality workshop

    NASA Astrophysics Data System (ADS)

    Schmoldt, Daniel L.; Peterson, David L.

    1991-09-01

    In response to protection needs in class I wilderness areas, forest land managers of the USDA Forest Service must provide input to regulatory agencies regarding air pollutant impacts on air quality-related values. Regional workshops have been convened for land managers and scientists to discuss the aspects and extent of wilderness protection needs. Previous experience with a national workshop indicated that a document summarizing workshop discussions will have little operational utility. An alternative is to create a knowledge-based analytical system, in addition to the document, to aid land managers in assessing effects of air pollutants on wilderness. Knowledge-based methods were used to design and conduct regional workshops in the western United States. Extracting knowledge from a large number of workshop participants required careful planning of workshop discussions. Knowledge elicitation methods helped with this task. This knowledge-based approach appears to be effective for focusing group discussions and collecting knowledge from large groups of specialists.

  12. Multisensor detection and tracking of tactical ballistic missiles using knowledge-based state estimation

    NASA Astrophysics Data System (ADS)

    Woods, Edward; Queeney, Tom

    1994-06-01

    Westinghouse has developed and demonstrated a system that performs multisensor detection and tracking of tactical ballistic missiles (TBM). Under a USAF High Gear Program, we developed knowledge-based techniques to discriminate TBM targets from ground clutter, air breathing targets, and false alarms. Upon track initiation the optimal estimate of the target's launch point, impact point and instantaneous position was computed by fusing returns from noncollocated multiple sensors. The system also distinguishes different missile types during the boost phase and forms multiple hypotheses to account for measurement and knowledge base uncertainties. This paper outlines the salient features of the knowledge-based processing of the multisensor data.

  13. PRAIS: Distributed, real-time knowledge-based systems made easy

    NASA Technical Reports Server (NTRS)

    Goldstein, David G.

    1990-01-01

    This paper discusses an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS). PRAIS strives for transparently parallelizing production (rule-based) systems, even when under real-time constraints. PRAIS accomplishes these goals by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors.

  14. Interfaces for knowledge-base builders control knowledge and application-specific procedures

    SciTech Connect

    Hirsch, P.; Katke, W.; Meier, M.; Snyder, S.; Stillman, R.

    1986-01-01

    Expert System Environment/VM is an expert system shell-a general-purpose system for constructing and executing expert system applications. An application expert has both factual knowledge about an application and knowledge about how that factual knowledge should be organized and processed. In addition, many applications require application-dependent procedures to access databases or to do specialized processing. An important and novel part of Expert System Environment/VM is the technique used to allow the expert or knowledge-base builder to enter the control knowledge and to interface with application-dependent procedures. This paper discusses these high-level interfaces for the knowledge-base builder.

  15. Knowledge-based engineering of a PLC controlled telescope

    NASA Astrophysics Data System (ADS)

    Pessemier, Wim; Raskin, Gert; Saey, Philippe; Van Winckel, Hans; Deconinck, Geert

    2016-08-01

    demonstrate the added value that technologies such as soft-PLCs and DSL-scripts and design methodologies such as knowledge-based engineering can bring to astronomical instrumentation.

  16. A national knowledge-based crop recognition in Mediterranean environment

    NASA Astrophysics Data System (ADS)

    Cohen, Yafit; Shoshany, Maxim

    2002-08-01

    Population growth, urban expansion, land degradation, civil strife and war may place plant natural resources for food and agriculture at risk. Crop and yield monitoring is basic information necessary for wise management of these resources. Satellite remote sensing techniques have proven to be cost-effective in widespread agricultural lands in Africa, America, Europe and Australia. However, they have had limited success in Mediterranean regions that are characterized by a high rate of spatio-temporal ecological heterogeneity and high fragmentation of farming lands. An integrative knowledge-based approach is needed for this purpose, which combines imagery and geographical data within the framework of an intelligent recognition system. This paper describes the development of such a crop recognition methodology and its application to an area that comprises approximately 40% of the cropland in Israel. This area contains eight crop types that represent 70% of Israeli agricultural production. Multi-date Landsat TM images representing seasonal vegetation cover variations were converted to normalized difference vegetation index (NDVI) layers. Field boundaries were delineated by merging Landsat data with SPOT-panchromatic images. Crop recognition was then achieved in two-phases, by clustering multi-temporal NDVI layers using unsupervised classification, and then applying 'split-and-merge' rules to these clusters. These rules were formalized through comprehensive learning of relationships between crop types, imagery properties (spectral and NDVI) and auxiliary data including agricultural knowledge, precipitation and soil types. Assessment of the recognition results using ground data from the Israeli Agriculture Ministry indicated an average recognition accuracy exceeding 85% which accounts for both omission and commission errors. The two-phase strategy implemented in this study is apparently successful for heterogeneous regions. This is due to the fact that it allows

  17. GUIDON-WATCH: A Graphic Interface for Viewing a Knowledge-Based System. Technical Report #14.

    ERIC Educational Resources Information Center

    Richer, Mark H.; Clancey, William J.

    This paper describes GUIDON-WATCH, a graphic interface that uses multiple windows and a mouse to allow a student to browse a knowledge base and view reasoning processes during diagnostic problem solving. The GUIDON project at Stanford University is investigating how knowledge-based systems can provide the basis for teaching programs, and this…

  18. Extending the Learning Experience Using the Web and a Knowledge-Based Virtual Environment.

    ERIC Educational Resources Information Center

    Parkinson, B.; Hudson, P.

    2002-01-01

    Identifies problems associated with teaching and learning a complex subject such as engineering design within a restrictive educational environment. Describes the development of a Web-based computer aid in the United Kingdom which employs a multimedia virtual environment incorporating domain-specific knowledge-based systems to emulate a range of…

  19. Knowledge-Based Information Management for Watershed Analysis in the Pacific Northwest U.S.

    Treesearch

    Keith Reynolds; Richard Olson; Michael Saunders; Donald Latham; Michael Foster; Bruce Miller; Lawrence Bednar; Daniel Schmoldt; Patrick Cunningham; John Steffenson

    1996-01-01

    We are developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a variety of themes and other area-specific information, (2) an analysis...

  20. Knowledge-Based Indexing of the Medical Literature: The Indexing Aid Project.

    ERIC Educational Resources Information Center

    Humphrey, Suzanne; Miller, Nancy E.

    1987-01-01

    Describes the National Library of Medicine's (NLM) Indexing Aid Project for conducting research in knowledge representation and indexing for information retrieval, whose goal is to develop interactive knowledge-based systems for computer-assisted indexing of the periodical medical literature. Appendices include background information on NLM…

  1. Knowledge-Based Information Management in Decision Support for Ecosystem Management

    Treesearch

    Keith Reynolds; Micahel Saunders; Richard Olson; Daniel Schmoldt; Michael Foster; Donald Latham; Bruce Miller; John Steffenson; Lawrence Bednar; Patrick Cunningham

    1995-01-01

    The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The decision support system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a...

  2. The Knowledge-Based Reasoning of Physical Education Teachers: A Comparison between Groups with Different Expertise

    ERIC Educational Resources Information Center

    Reuker, Sabine

    2017-01-01

    The study addresses professional vision, including the abilities of selective attention and knowledge-based reasoning. This article focuses on the latter ability. Groups with different sport-specific and pedagogical expertise (n = 60) were compared according to their observation and interpretation of sport activities in a four-field design. The…

  3. The Spread of Contingent Work in the Knowledge-Based Economy

    ERIC Educational Resources Information Center

    Szabo, Katalin; Negyesi, Aron

    2005-01-01

    Permanent employment, typical of industrial societies and bolstered by numerous social guaranties, has been declining in the past 2 decades. There has been a steady expansion of various forms of contingent work. The decomposition of traditional work is a logical consequence of the characteristic patterns of the knowledge-based economy. According…

  4. Case-based reasoning for space applications: Utilization of prior experience in knowledge-based systems

    NASA Technical Reports Server (NTRS)

    King, James A.

    1987-01-01

    The goal is to explain Case-Based Reasoning as a vehicle to establish knowledge-based systems based on experimental reasoning for possible space applications. This goal will be accomplished through an examination of reasoning based on prior experience in a sample domain, and also through a presentation of proposed space applications which could utilize Case-Based Reasoning techniques.

  5. Universities and the Knowledge-Based Economy: Perceptions from a Developing Country

    ERIC Educational Resources Information Center

    Bano, Shah; Taylor, John

    2015-01-01

    This paper considers the role of universities in the creation of a knowledge-based economy (KBE) in a developing country, Pakistan. Some developing countries have moved quickly to develop a KBE, but progress in Pakistan is much slower. Higher education plays a crucial role as part of the triple helix model for innovation. Based on the perceptions…

  6. Universities and the Knowledge-Based Economy: Perceptions from a Developing Country

    ERIC Educational Resources Information Center

    Bano, Shah; Taylor, John

    2015-01-01

    This paper considers the role of universities in the creation of a knowledge-based economy (KBE) in a developing country, Pakistan. Some developing countries have moved quickly to develop a KBE, but progress in Pakistan is much slower. Higher education plays a crucial role as part of the triple helix model for innovation. Based on the perceptions…

  7. Learning and Innovation in the Knowledge-Based Economy: Beyond Clusters and Qualifications

    ERIC Educational Resources Information Center

    James, Laura; Guile, David; Unwin, Lorna

    2013-01-01

    For over a decade policy-makers have claimed that advanced industrial societies should develop a knowledge-based economy (KBE) in response to economic globalisation and the transfer of manufacturing jobs to lower cost countries. In the UK, this vision shaped New Labour's policies for vocational education and training (VET), higher education and…

  8. Learning Spaces: An ICT-Enabled Model of Future Learning in the Knowledge-Based Society

    ERIC Educational Resources Information Center

    Punie, Yves

    2007-01-01

    This article presents elements of a future vision of learning in the knowledge-based society which is enabled by ICT. It is not only based on extrapolations from trends and drivers that are shaping learning in Europe but also consists of a holistic attempt to envisage and anticipate future learning needs and requirements in the KBS. The…

  9. The Knowledge-Based Reasoning of Physical Education Teachers: A Comparison between Groups with Different Expertise

    ERIC Educational Resources Information Center

    Reuker, Sabine

    2017-01-01

    The study addresses professional vision, including the abilities of selective attention and knowledge-based reasoning. This article focuses on the latter ability. Groups with different sport-specific and pedagogical expertise (n = 60) were compared according to their observation and interpretation of sport activities in a four-field design. The…

  10. Improving Student Teachers' Knowledge-Base in Language Education through Critical Reading

    ERIC Educational Resources Information Center

    Mulumba, Mathias Bwanika

    2016-01-01

    The emergence of the digital era is redefining education and the pedagogical processes in an unpredictable manner. In the midst of the increased availability of print and online resources, the twenty-first century language teacher educator expects her (or his) student teachers to be reading beings if they are to improve their knowledge-base in…

  11. EMDS users guide (version 2.0): knowledge-based decision support for ecological assessment.

    Treesearch

    Keith M. Reynolds

    1999-01-01

    The USDA Forest Service Pacific Northwest Research Station in Corvallis, Oregon, has developed the ecosystem management decision support (EMDS) system. The system integrates the logical formalism of knowledge-based reasoning into a geographic information system (GIS) environment to provide decision support for ecological landscape assessment and evaluation. The...

  12. Learning Spaces: An ICT-Enabled Model of Future Learning in the Knowledge-Based Society

    ERIC Educational Resources Information Center

    Punie, Yves

    2007-01-01

    This article presents elements of a future vision of learning in the knowledge-based society which is enabled by ICT. It is not only based on extrapolations from trends and drivers that are shaping learning in Europe but also consists of a holistic attempt to envisage and anticipate future learning needs and requirements in the KBS. The…

  13. End-user oriented language to develop knowledge-based expert systems

    SciTech Connect

    Ueno, H.

    1983-01-01

    A description is given of the COMEX (compact knowledge based expert system) expert system language for application-domain users who want to develop a knowledge-based expert system by themselves. The COMEX system was written in FORTRAN and works on a microcomputer. COMEX is being used in several application domains such as medicine, education, and industry. 7 references.

  14. A knowledge-based object recognition system for applications in the space station

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.

    1988-02-01

    A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

  15. Learning and Innovation in the Knowledge-Based Economy: Beyond Clusters and Qualifications

    ERIC Educational Resources Information Center

    James, Laura; Guile, David; Unwin, Lorna

    2013-01-01

    For over a decade policy-makers have claimed that advanced industrial societies should develop a knowledge-based economy (KBE) in response to economic globalisation and the transfer of manufacturing jobs to lower cost countries. In the UK, this vision shaped New Labour's policies for vocational education and training (VET), higher education and…

  16. Small Knowledge-Based Systems in Education and Training: Something New Under the Sun.

    ERIC Educational Resources Information Center

    Wilson, Brent G.; Welsh, Jack R.

    1986-01-01

    Discusses artificial intelligence, robotics, natural language processing, and expert or knowledge-based systems research; examines two large expert systems, MYCIN and XCON; and reviews the resources required to build large expert systems and affordable smaller systems (intelligent job aids) for training. Expert system vendors and products are…

  17. A Comparison of Books and Hypermedia for Knowledge-based Sports Coaching.

    ERIC Educational Resources Information Center

    Vickers, Joan N.; Gaines, Brian R.

    1988-01-01

    Summarizes and illustrates the knowledge-based approach to instructional material design. A series of sports coaching handbooks and hypermedia presentations of the same material are described and the different instantiations of the knowledge and training structures are compared. Figures show knowledge structures for badminton and the architecture…

  18. Adding Learning to Knowledge-Based Systems: Taking the "Artificial" Out of AI

    Treesearch

    Daniel L. Schmoldt

    1997-01-01

    Both, knowledge-based systems (KBS) development and maintenance require time-consuming analysis of domain knowledge. Where example cases exist, KBS can be built, and later updated, by incorporating learning capabilities into their architecture. This applies to both supervised and unsupervised learning scenarios. In this paper, the important issues for learning systems-...

  19. A knowledge-based object recognition system for applications in the space station

    NASA Technical Reports Server (NTRS)

    Dhawan, Atam P.

    1988-01-01

    A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

  20. Improving Student Teachers' Knowledge-Base in Language Education through Critical Reading

    ERIC Educational Resources Information Center

    Mulumba, Mathias Bwanika

    2016-01-01

    The emergence of the digital era is redefining education and the pedagogical processes in an unpredictable manner. In the midst of the increased availability of print and online resources, the twenty-first century language teacher educator expects her (or his) student teachers to be reading beings if they are to improve their knowledge-base in…

  1. The Spread of Contingent Work in the Knowledge-Based Economy

    ERIC Educational Resources Information Center

    Szabo, Katalin; Negyesi, Aron

    2005-01-01

    Permanent employment, typical of industrial societies and bolstered by numerous social guaranties, has been declining in the past 2 decades. There has been a steady expansion of various forms of contingent work. The decomposition of traditional work is a logical consequence of the characteristic patterns of the knowledge-based economy. According…

  2. Small Knowledge-Based Systems in Education and Training: Something New Under the Sun.

    ERIC Educational Resources Information Center

    Wilson, Brent G.; Welsh, Jack R.

    1986-01-01

    Discusses artificial intelligence, robotics, natural language processing, and expert or knowledge-based systems research; examines two large expert systems, MYCIN and XCON; and reviews the resources required to build large expert systems and affordable smaller systems (intelligent job aids) for training. Expert system vendors and products are…

  3. New knowledge-based genetic algorithm for excavator boom structural optimization

    NASA Astrophysics Data System (ADS)

    Hua, Haiyan; Lin, Shuwen

    2014-03-01

    Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the configurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, are taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.

  4. Hidden Knowledge: Working-Class Capacity in the "Knowledge-Based Economy"

    ERIC Educational Resources Information Center

    Livingstone, David W.; Sawchuck, Peter H.

    2005-01-01

    The research reported in this paper attempts to document the actual learning practices of working-class people in the context of the much heralded "knowledge-based economy." Our primary thesis is that working-class peoples' indigenous learning capacities have been denied, suppressed, degraded or diverted within most capitalist schooling,…

  5. Knowledge-based extraction of adverse drug events from biomedical text

    PubMed Central

    2014-01-01

    Background Many biomedical relation extraction systems are machine-learning based and have to be trained on large annotated corpora that are expensive and cumbersome to construct. We developed a knowledge-based relation extraction system that requires minimal training data, and applied the system for the extraction of adverse drug events from biomedical text. The system consists of a concept recognition module that identifies drugs and adverse effects in sentences, and a knowledge-base module that establishes whether a relation exists between the recognized concepts. The knowledge base was filled with information from the Unified Medical Language System. The performance of the system was evaluated on the ADE corpus, consisting of 1644 abstracts with manually annotated adverse drug events. Fifty abstracts were used for training, the remaining abstracts were used for testing. Results The knowledge-based system obtained an F-score of 50.5%, which was 34.4 percentage points better than the co-occurrence baseline. Increasing the training set to 400 abstracts improved the F-score to 54.3%. When the system was compared with a machine-learning system, jSRE, on a subset of the sentences in the ADE corpus, our knowledge-based system achieved an F-score that is 7 percentage points higher than the F-score of jSRE trained on 50 abstracts, and still 2 percentage points higher than jSRE trained on 90% of the corpus. Conclusion A knowledge-based approach can be successfully used to extract adverse drug events from biomedical text without need for a large training set. Whether use of a knowledge base is equally advantageous for other biomedical relation-extraction tasks remains to be investigated. PMID:24593054

  6. A NASA/RAE cooperation in the development of a real-time knowledge-based autopilot

    NASA Technical Reports Server (NTRS)

    Daysh, Colin; Corbin, Malcolm; Butler, Geoff; Duke, Eugene L.; Belle, Steven D.; Brumbaugh, Randal W.

    1991-01-01

    As part of a US/UK cooperative aeronautical research program, a joint activity between the NASA Dryden Flight Research Facility and the Royal Aerospace Establishment on knowledge-based systems was established. This joint activity is concerned with tools and techniques for the implementation and validation of real-time knowledge-based systems. The proposed next stage of this research is described, in which some of the problems of implementing and validating a knowledge-based autopilot for a generic high-performance aircraft are investigated.

  7. A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

    USDA-ARS?s Scientific Manuscript database

    Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium...

  8. The Impact of Electronic Knowledge-Based Nursing Content and Decision-Support on Nursing-Sensitive Patient Outcomes

    DTIC Science & Technology

    2015-02-01

    Award Number: W81XWH-13-1-0034 TITLE: “The Impact of Electronic Knowledge-Based Nursing Content and Decision-Support on Nursing -Sensitive Patient...Impact of Electronic Knowledge-Based Nursing Content and Decision- 5a. CONTRACT NUMBER Support on Nursing -Sensitive Patient Outcomes 5b. GRANT NUMBER...decision support (CDS) tools in electronic health records (EHR) hold great promise, but are relatively untested for nurses . Researchers have suggested that

  9. Knowledge-Based Reinforcement Learning for Data Mining

    NASA Astrophysics Data System (ADS)

    Kudenko, Daniel; Grzes, Marek

    experts have developed heuristics that help them in planning and scheduling resources in their work place. However, this domain knowledge is often rough and incomplete. When the domain knowledge is used directly by an automated expert system, the solutions are often sub-optimal, due to the incompleteness of the knowledge, the uncertainty of environments, and the possibility to encounter unexpected situations. RL, on the other hand, can overcome the weaknesses of the heuristic domain knowledge and produce optimal solutions. In the talk we propose two techniques, which represent first steps in the area of knowledge-based RL (KBRL). The first technique [1] uses high-level STRIPS operator knowledge in reward shaping to focus the search for the optimal policy. Empirical results show that the plan-based reward shaping approach outperforms other RL techniques, including alternative manual and MDP-based reward shaping when it is used in its basic form. We showed that MDP-based reward shaping may fail and successful experiments with STRIPS-based shaping suggest modifications which can overcome encountered problems. The STRIPSbased method we propose allows expressing the same domain knowledge in a different way and the domain expert can choose whether to define an MDP or STRIPS planning task. We also evaluated the robustness of the proposed STRIPS-based technique to errors in the plan knowledge. In case that STRIPS knowledge is not available, we propose a second technique [2] that shapes the reward with hierarchical tile coding. Where the Q-function is represented with low-level tile coding, a V-function with coarser tile coding can be learned in parallel and used to approximate the potential for ground states. In the context of data mining, our KBRL approaches can also be used for any data collection task where the acquisition of data may incur considerable cost. In addition, observing the data collection agent in specific scenarios may lead to new insights into optimal data

  10. Increasing levels of assistance in refinement of knowledge-based retrieval systems

    NASA Technical Reports Server (NTRS)

    Baudin, Catherine; Kedar, Smadar; Pell, Barney

    1994-01-01

    The task of incrementally acquiring and refining the knowledge and algorithms of a knowledge-based system in order to improve its performance over time is discussed. In particular, the design of DE-KART, a tool whose goal is to provide increasing levels of assistance in acquiring and refining indexing and retrieval knowledge for a knowledge-based retrieval system, is presented. DE-KART starts with knowledge that was entered manually, and increases its level of assistance in acquiring and refining that knowledge, both in terms of the increased level of automation in interacting with users, and in terms of the increased generality of the knowledge. DE-KART is at the intersection of machine learning and knowledge acquisition: it is a first step towards a system which moves along a continuum from interactive knowledge acquisition to increasingly automated machine learning as it acquires more knowledge and experience.

  11. A knowledge-based framework for image enhancement in aviation security.

    PubMed

    Singh, Maneesha; Singh, Sameer; Partridge, Derek

    2004-12-01

    The main aim of this paper is to present a knowledge-based framework for automatically selecting the best image enhancement algorithm from several available on a per image basis in the context of X-ray images of airport luggage. The approach detailed involves a system that learns to map image features that represent its viewability to one or more chosen enhancement algorithms. Viewability measures have been developed to provide an automatic check on the quality of the enhanced image, i.e., is it really enhanced? The choice is based on ground-truth information generated by human X-ray screening experts. Such a system, for a new image, predicts the best-suited enhancement algorithm. Our research details the various characteristics of the knowledge-based system and shows extensive results on real images.

  12. Delivering spacecraft control centers with embedded knowledge-based systems: The methodology issue

    NASA Astrophysics Data System (ADS)

    Ayache, S.; Haziza, M.; Cayrac, D.

    1994-11-01

    Matra Marconi Space (MMS) occupies a leading place in Europe in the domain of satellite and space data processing systems. The maturity of the knowledge-based systems (KBS) technology, the theoretical and practical experience acquired in the development of prototype, pre-operational and operational applications, make it possible today to consider the wide operational deployment of KBS's in space applications. In this perspective, MMS has to prepare the introduction of the new methods and support tools that will form the basis of the development of such systems. This paper introduces elements of the MMS methodology initiatives in the domain and the main rationale that motivated the approach. These initiatives develop along two main axes: knowledge engineering methods and tools, and a hybrid method approach for coexisting knowledge-based and conventional developments.

  13. Delivering spacecraft control centers with embedded knowledge-based systems: The methodology issue

    NASA Technical Reports Server (NTRS)

    Ayache, S.; Haziza, M.; Cayrac, D.

    1994-01-01

    Matra Marconi Space (MMS) occupies a leading place in Europe in the domain of satellite and space data processing systems. The maturity of the knowledge-based systems (KBS) technology, the theoretical and practical experience acquired in the development of prototype, pre-operational and operational applications, make it possible today to consider the wide operational deployment of KBS's in space applications. In this perspective, MMS has to prepare the introduction of the new methods and support tools that will form the basis of the development of such systems. This paper introduces elements of the MMS methodology initiatives in the domain and the main rationale that motivated the approach. These initiatives develop along two main axes: knowledge engineering methods and tools, and a hybrid method approach for coexisting knowledge-based and conventional developments.

  14. Knowledge-based vision for space station object motion detection, recognition, and tracking

    NASA Technical Reports Server (NTRS)

    Symosek, P.; Panda, D.; Yalamanchili, S.; Wehner, W., III

    1987-01-01

    Computer vision, especially color image analysis and understanding, has much to offer in the area of the automation of Space Station tasks such as construction, satellite servicing, rendezvous and proximity operations, inspection, experiment monitoring, data management and training. Knowledge-based techniques improve the performance of vision algorithms for unstructured environments because of their ability to deal with imprecise a priori information or inaccurately estimated feature data and still produce useful results. Conventional techniques using statistical and purely model-based approaches lack flexibility in dealing with the variabilities anticipated in the unstructured viewing environment of space. Algorithms developed under NASA sponsorship for Space Station applications to demonstrate the value of a hypothesized architecture for a Video Image Processor (VIP) are presented. Approaches to the enhancement of the performance of these algorithms with knowledge-based techniques and the potential for deployment of highly-parallel multi-processor systems for these algorithms are discussed.

  15. Design and implementation of knowledge-based framework for ground objects recognition in remote sensing images

    NASA Astrophysics Data System (ADS)

    Chen, Shaobin; Ding, Mingyue; Cai, Chao; Fu, Xiaowei; Sun, Yue; Chen, Duo

    2009-10-01

    The advance of image processing makes knowledge-based automatic image interpretation much more realistic than ever. In the domain of remote sensing image processing, the introduction of knowledge enhances the confidence of recognition of typical ground objects. There are mainly two approaches to employ knowledge: the first one is scattering knowledge in concrete program and relevant knowledge of ground objects are fixed by programming; the second is systematically storing knowledge in knowledge base to offer a unified instruction for each object recognition procedure. In this paper, a knowledge-based framework for ground objects recognition in remote sensing image is proposed. This framework takes the second means for using knowledge with a hierarchical architecture. The recognition of typical airport demonstrated the feasibility of the proposed framework.

  16. Interpreting Segmented Laser Radar Images Using a Knowledge-Based System

    NASA Astrophysics Data System (ADS)

    Chu, Chen-Chau; Nandhakumar, Nagaraj; Aggarwal, Jake K.

    1990-03-01

    This paper presents a knowledge-based system (KBS) for man-made object recognition and image interpretation using laser radar (ladar) images. The objective is to recognize military vehicles in rural scenes. The knowledge-based system is constructed using KEE rules and Lisp functions, and uses results from pre-processing modules for image segmentation and integration of segmentation maps. Low-level attributes of segments are computed and converted to KEE format as part of the data bases. The interpretation modules detect man-made objects from the background using low-level attributes. Segments are grouped into objects and then man-made objects and background segments are classified into pre-defined categories (tanks, ground, etc.) A concurrent server program is used to enhance the performance of the KBS by serving numerical and graphics-oriented tasks for the interpretation modules. Experimental results using real ladar data are presented.

  17. The promise of a new technology: knowledge-based systems in radiation oncology and diagnostic radiology.

    PubMed

    Zink, S

    1989-01-01

    The revolutionary changes in computer capabilities in the last decade, both in software and hardware, have opened new doorways for the uses of computers in radiation oncology and diagnostic radiology. Knowledge-based systems offer the potential to function as aids, consultants and advisors in the differential diagnosis of disease, staging, selection of therapy and treatment management and delivery for cancer patients. These computer-based systems can also provide for the training and teaching of radiotherapy and diagnostic radiology residents, and act as advisors and teachers to the medical physicists, dosimetrists and technicians. Following a brief history of the development of knowledge-based systems, the general capabilities of computer-based physician workstations in a department of radiation oncology are described.

  18. Strategic Concept of Competition Model in Knowledge-Based Logistics in Machinebuilding

    NASA Astrophysics Data System (ADS)

    Medvedeva, O. V.

    2015-09-01

    A competitive labor market needs serious changing. Machinebuilding is one of the main problem domains. The current direction to promote human capital competition demands for modernization. Therefore, it is necessary to develop a strategy for social and economic promotion of competition in conditions of knowledge-based economy, in particularly, in machinebuilding. The necessity is demonstrated, as well as basic difficulties faced this strategy for machinebuilding.

  19. Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

    NASA Technical Reports Server (NTRS)

    Momoh, J. A.; Zhang, Z. Z.

    1990-01-01

    A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

  20. A knowledge-based artificial neural network classifier for pulmonary embolism diagnosis.

    PubMed

    Serpen, G; Tekkedil, D K; Orra, M

    2008-02-01

    This paper aims to demonstrate that knowledge-based hybrid learning algorithms are positioned to offer better performance in comparison with purely empirical machine learning algorithms for the automatic classification task associated with the diagnosis of a medical condition described as pulmonary embolism (PE). The main premise is that there exists substantial and significant specialized knowledge in the domain of PE, which can readily be leveraged for bootstrapping a knowledge-based hybrid classifier that employs both the explanation-based and the empirical learning. The modified prospective investigation of pulmonary embolism diagnosis (PIOPED) criteria, which represent the pre-eminent collective experiential knowledge base among nuclear radiologists as a diagnosis procedure for PE, are conveniently defined in terms of a set of if-then rules. As such, it lends itself to being captured into a knowledge base through instantiating a knowledge-based hybrid learning algorithm. This study shows the instantiation of a knowledge-based artificial neural network (KBANN) classifier through the modified PIOPED criteria for the diagnosis of PE. The development effort for the KBANN that captures the rule base associated with the PIOPED criteria as well as further refinement of the same rule base through highly specialized domain expertise is presented. Through a testing dataset generated with the help of nuclear radiologists, performance of the instantiated KBANN is profiled. Performances of a set of empirical machine learning algorithms, which are configured as classifiers and include the nai ve Bayes, the Bayesian Belief network, the multilayer perceptron neural network, the C4.5 decision tree algorithm, and two meta learners with boosting and bagging, are also profiled on the same dataset for the purpose of comparison with that of the KBANN. Simulation results indicate that the KBANN can effectively model and leverage the PIOPED knowledge base and its further refinements

  1. Volunteering Information - Enhancing the Communication Capabilities of Knowledge-Based Systems

    DTIC Science & Technology

    1987-09-01

    Conference on Artiicial Intelligence missing- in many cases this resistance will be based on the (Milan), 1987. limited communication capabilities...scientific foundations for the con- The use of knowledge-based systems will be severely limited I stiuction of intelligent systems which serve as amplifiers...locally, follow- be crucial for intelligent systems, the progress to achieve them ing a style as defined by its rules. The advice given is based on

  2. Towards knowledge-based retrieval of medical images. The role of semantic indexing, image content representation and knowledge-based retrieval.

    PubMed

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A

    1998-01-01

    Medicine is increasingly image-intensive. The central importance of imaging technologies such as computerized tomography and magnetic resonance imaging in clinical decision making, combined with the trend to store many "traditional" clinical images such as conventional radiographs, microscopic pathology and dermatology images in digital format present both challenges and an opportunities for the designers of clinical information systems. The emergence of Multimedia Electronic Medical Record Systems (MEMRS), architectures that integrate medical images with text-based clinical data, will further hasten this trend. The development of these systems, storing a large and diverse set of medical images, suggests that in the future MEMRS will become important digital libraries supporting patient care, research and education. The representation and retrieval of clinical images within these systems is problematic as conventional database architectures and information retrieval models have, until recently, focused largely on text-based data. Medical imaging data differs in many ways from text-based medical data but perhaps the most important difference is that the information contained within imaging data is fundamentally knowledge-based. New representational and retrieval models for clinical images will be required to address this issue. Within the Image Engine multimedia medical record system project at the University of Pittsburgh we are evolving an approach to representation and retrieval of medical images which combines semantic indexing using the UMLS Metathesuarus, image content-based representation and knowledge-based image analysis.

  3. Towards knowledge-based retrieval of medical images. The role of semantic indexing, image content representation and knowledge-based retrieval.

    PubMed Central

    Lowe, H. J.; Antipov, I.; Hersh, W.; Smith, C. A.

    1998-01-01

    Medicine is increasingly image-intensive. The central importance of imaging technologies such as computerized tomography and magnetic resonance imaging in clinical decision making, combined with the trend to store many "traditional" clinical images such as conventional radiographs, microscopic pathology and dermatology images in digital format present both challenges and an opportunities for the designers of clinical information systems. The emergence of Multimedia Electronic Medical Record Systems (MEMRS), architectures that integrate medical images with text-based clinical data, will further hasten this trend. The development of these systems, storing a large and diverse set of medical images, suggests that in the future MEMRS will become important digital libraries supporting patient care, research and education. The representation and retrieval of clinical images within these systems is problematic as conventional database architectures and information retrieval models have, until recently, focused largely on text-based data. Medical imaging data differs in many ways from text-based medical data but perhaps the most important difference is that the information contained within imaging data is fundamentally knowledge-based. New representational and retrieval models for clinical images will be required to address this issue. Within the Image Engine multimedia medical record system project at the University of Pittsburgh we are evolving an approach to representation and retrieval of medical images which combines semantic indexing using the UMLS Metathesuarus, image content-based representation and knowledge-based image analysis. PMID:9929345

  4. A new collaborative knowledge-based approach for wireless sensor networks.

    PubMed

    Canada-Bago, Joaquin; Fernandez-Prieto, Jose Angel; Gadeo-Martos, Manuel Angel; Velasco, Juan Ramón

    2010-01-01

    This work presents a new approach for collaboration among sensors in Wireless Sensor Networks. These networks are composed of a large number of sensor nodes with constrained resources: limited computational capability, memory, power sources, etc. Nowadays, there is a growing interest in the integration of Soft Computing technologies into Wireless Sensor Networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks. The objective of this work is to design a collaborative knowledge-based network, in which each sensor executes an adapted Fuzzy Rule-Based System, which presents significant advantages such as: experts can define interpretable knowledge with uncertainty and imprecision, collaborative knowledge can be separated from control or modeling knowledge and the collaborative approach may support neighbor sensor failures and communication errors. As a real-world application of this approach, we demonstrate a collaborative modeling system for pests, in which an alarm about the development of olive tree fly is inferred. The results show that knowledge-based sensors are suitable for a wide range of applications and that the behavior of a knowledge-based sensor may be modified by inferences and knowledge of neighbor sensors in order to obtain a more accurate and reliable output.

  5. SU-E-T-572: A Plan Quality Metric for Evaluating Knowledge-Based Treatment Plans.

    PubMed

    Chanyavanich, V; Lo, J; Das, S

    2012-06-01

    In prostate IMRT treatment planning, the variation in patient anatomy makes it difficult to estimate a priori the potentially achievable extent of dose reduction possible to the rectum and bladder. We developed a mutual information-based framework to estimate the achievable plan quality for a new patient, prior to any treatment planning or optimization. The knowledge-base consists of 250 retrospective prostate IMRT plans. Using these prior plans, twenty query cases were each matched with five cases from the database. We propose a simple DVH plan quality metric (PQ) based on the weighted-sum of the areas under the curve (AUC) of the PTV, rectum and bladder. We evaluate the plan quality of knowledge-based generated plans, and established a correlation between the plan quality and case similarity. The introduced plan quality metric correlates well (r2 = 0.8) with the mutual similarity between cases. A matched case with high anatomical similarity can be used to produce a new high quality plan. Not surprisingly, a poorly matched case with low degree of anatomical similarity tends to produce a low quality plan, since the adapted fluences from a dissimilar case cannot be modified sufficiently to yield acceptable PTV coverage. The plan quality metric is well-correlated to the degree of anatomical similarity between a new query case and matched cases. Further work will investigate how to apply this metric to further stratify and select cases for knowledge-based planning. © 2012 American Association of Physicists in Medicine.

  6. Can Croatia Join Europe as Competitive Knowledge-based Society by 2010?

    PubMed Central

    Petrovečki, Mladen; Paar, Vladimir; Primorac, Dragan

    2006-01-01

    The 21st century has brought important changes in the paradigms of economic development, one of them being a shift toward recognizing knowledge and information as the most important factors of today. The European Union (EU) has been working hard to become the most competitive knowledge-based society in the world, and Croatia, an EU candidate country, has been faced with a similar task. To establish itself as one of the best knowledge-based country in the Eastern European region over the next four years, Croatia realized it has to create an education and science system correspondent with European standards and sensitive to labor market needs. For that purpose, the Croatian Ministry of Science, Education, and Sports (MSES) has created and started implementing a complex strategy, consisting of the following key components: the reform of education system in accordance with the Bologna Declaration; stimulation of scientific production by supporting national and international research projects; reversing the “brain drain” into “brain gain” and strengthening the links between science and technology; and informatization of the whole education and science system. In this comprehensive report, we describe the implementation of these measures, whose coordination with the EU goals presents a challenge, as well as an opportunity for Croatia to become a knowledge-based society by 2010. PMID:17167853

  7. Response time satisfaction in a real-time knowledge-based system

    SciTech Connect

    Frank, D. ); Friesen, D.; Williams, G. . Dept. of Computer Science)

    1990-08-01

    Response to interrupts within a certain time frame is an important issue for all software operating in real-time environment. A knowledge-based system (KBS) is no exception. Prior work on real-time knowledge-based systems either concentrated on improving the performance of the KBS in order to meet these constraints or focused on producing a better solution as more time was allowed. However, a problem with much of the latter research was that it required inference-time costs to be hardcoded into the different branches of reasoning. This limited the type of reasoning possible and the size of the KBS. Furthermore, performing the analysis required to derive those numbers is very difficult in knowledge based systems. This research explored a model for overcoming these drawbacks. It is based on integrating conventional programming techniques used to control task processing with knowledge-based techniques used to actually produce task results. The C-Language Integrated Production System (CLIPS) was used for the inference engine in the KBS; using CLIPS for the inference engine simplified the rapid context switching required. Thus, the KBS could respond in a timely manner while maintaining the fullest spectrum of KBS functionality.

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

    SciTech Connect

    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.

  9. Knowledge-based indexing of the medical literature: the Indexing Aid Project.

    PubMed

    Humphrey, S M; Miller, N E

    1987-05-01

    This article describes the Indexing Aid Project for conducting research in the areas of knowledge representation and indexing for information retrieval in order to develop interactive knowledge-based systems for computer-assisted indexing of the periodical medical literature. The system uses an experimental frame-based knowledge representation language, FrameKit, implemented in Franz Lisp. The initial prototype is designed to interact with trained MEDLINE indexers who will be prompted to enter subject terms as slot values in filling in document-specific frame data structures that are derived from the knowledge-base frames. In addition, the automatic application of rules associated with the knowledge-base frames produces a set of Medical Subject Heading (MeSH) keyword indices to the document. Important features of the system are representation of explicit relationships through slots which express the relations; slot values, restrictions, and rules made available by inheritance through "is-a" hierarchies; slot values denoted by functions that retrieve values from other slots; and restrictions on slot values displayable during data entry.

  10. Knowledge-based approach to fault diagnosis and control in distributed process environments

    NASA Astrophysics Data System (ADS)

    Chung, Kwangsue; Tou, Julius T.

    1991-03-01

    This paper presents a new design approach to knowledge-based decision support systems for fault diagnosis and control for quality assurance and productivity improvement in automated manufacturing environments. Based on the observed manifestations, the knowledge-based diagnostic system hypothesizes a set of the most plausible disorders by mimicking the reasoning process of a human diagnostician. The data integration technique is designed to generate error-free hierarchical category files. A novel approach to diagnostic problem solving has been proposed by integrating the PADIKS (Pattern-Directed Knowledge-Based System) concept and the symbolic model of diagnostic reasoning based on the categorical causal model. The combination of symbolic causal reasoning and pattern-directed reasoning produces a highly efficient diagnostic procedure and generates a more realistic expert behavior. In addition, three distinctive constraints are designed to further reduce the computational complexity and to eliminate non-plausible hypotheses involved in the multiple disorders problem. The proposed diagnostic mechanism, which consists of three different levels of reasoning operations, significantly reduces the computational complexity in the diagnostic problem with uncertainty by systematically shrinking the hypotheses space. This approach is applied to the test and inspection data collected from a PCB manufacturing operation.

  11. Using CLIPS in the domain of knowledge-based massively parallel programming

    NASA Technical Reports Server (NTRS)

    Dvorak, Jiri J.

    1994-01-01

    The Program Development Environment (PDE) is a tool for massively parallel programming of distributed-memory architectures. Adopting a knowledge-based approach, the PDE eliminates the complexity introduced by parallel hardware with distributed memory and offers complete transparency in respect of parallelism exploitation. The knowledge-based part of the PDE is realized in CLIPS. Its principal task is to find an efficient parallel realization of the application specified by the user in a comfortable, abstract, domain-oriented formalism. A large collection of fine-grain parallel algorithmic skeletons, represented as COOL objects in a tree hierarchy, contains the algorithmic knowledge. A hybrid knowledge base with rule modules and procedural parts, encoding expertise about application domain, parallel programming, software engineering, and parallel hardware, enables a high degree of automation in the software development process. In this paper, important aspects of the implementation of the PDE using CLIPS and COOL are shown, including the embedding of CLIPS with C++-based parts of the PDE. The appropriateness of the chosen approach and of the CLIPS language for knowledge-based software engineering are discussed.

  12. 3DSwap: curated knowledgebase of proteins involved in 3D domain swapping.

    PubMed

    Shameer, Khader; Shingate, Prashant N; Manjunath, S C P; Karthika, M; Pugalenthi, Ganesan; Sowdhamini, Ramanathan

    2011-01-01

    Three-dimensional domain swapping is a unique protein structural phenomenon where two or more protein chains in a protein oligomer share a common structural segment between individual chains. This phenomenon is observed in an array of protein structures in oligomeric conformation. Protein structures in swapped conformations perform diverse functional roles and are also associated with deposition diseases in humans. We have performed in-depth literature curation and structural bioinformatics analyses to develop an integrated knowledgebase of proteins involved in 3D domain swapping. The hallmark of 3D domain swapping is the presence of distinct structural segments such as the hinge and swapped regions. We have curated the literature to delineate the boundaries of these regions. In addition, we have defined several new concepts like 'secondary major interface' to represent the interface properties arising as a result of 3D domain swapping, and a new quantitative measure for the 'extent of swapping' in structures. The catalog of proteins reported in 3DSwap knowledgebase has been generated using an integrated structural bioinformatics workflow of database searches, literature curation, by structure visualization and sequence-structure-function analyses. The current version of the 3DSwap knowledgebase reports 293 protein structures, the analysis of such a compendium of protein structures will further the understanding molecular factors driving 3D domain swapping.

  13. A knowledge-based flight status monitor for real-time application in digital avionics systems

    NASA Technical Reports Server (NTRS)

    Duke, E. L.; Disbrow, J. D.; Butler, G. F.

    1989-01-01

    The Dryden Flight Research Facility of the National Aeronautics and Space Administration (NASA) Ames Research Center (Ames-Dryden) is the principal NASA facility for the flight testing and evaluation of new and complex avionics systems. To aid in the interpretation of system health and status data, a knowledge-based flight status monitor was designed. The monitor was designed to use fault indicators from the onboard system which are telemetered to the ground and processed by a rule-based model of the aircraft failure management system to give timely advice and recommendations in the mission control room. One of the important constraints on the flight status monitor is the need to operate in real time, and to pursue this aspect, a joint research activity between NASA Ames-Dryden and the Royal Aerospace Establishment (RAE) on real-time knowledge-based systems was established. Under this agreement, the original LISP knowledge base for the flight status monitor was reimplemented using the intelligent knowledge-based system toolkit, MUSE, which was developed under RAE sponsorship. Details of the flight status monitor and the MUSE implementation are presented.

  14. Feasibility of using a knowledge-based system concept for in-flight primary flight display research

    NASA Technical Reports Server (NTRS)

    Ricks, Wendell R.

    1991-01-01

    A study was conducted to determine the feasibility of using knowledge-based systems architectures for inflight research of primary flight display information management issues. The feasibility relied on the ability to integrate knowledge-based systems with existing onboard aircraft systems. And, given the hardware and software platforms available, the feasibility also depended on the ability to use interpreted LISP software with the real time operation of the primary flight display. In addition to evaluating these feasibility issues, the study determined whether the software engineering advantages of knowledge-based systems found for this application in the earlier workstation study extended to the inflight research environment. To study these issues, two integrated knowledge-based systems were designed to control the primary flight display according to pre-existing specifications of an ongoing primary flight display information management research effort. These two systems were implemented to assess the feasibility and software engineering issues listed. Flight test results were successful in showing the feasibility of using knowledge-based systems inflight with actual aircraft data.

  15. Evaluating Social and National Education Textbooks Based on the Criteria of Knowledge-Based Economy from the Perspectives of Elementary Teachers in Jordan

    ERIC Educational Resources Information Center

    Al-Edwan, Zaid Suleiman; Hamaidi, Diala Abdul Hadi

    2011-01-01

    Knowledge-based economy is a new implemented trend in the field of education in Jordan. The ministry of education in Jordan attempts to implement this trend's philosophy in its textbooks. This study examined the extent to which the (1st-3rd grade) social and national textbooks reflect knowledge-based economy criteria from the perspective of…

  16. Evaluating Social and National Education Textbooks Based on the Criteria of Knowledge-Based Economy from the Perspectives of Elementary Teachers in Jordan

    ERIC Educational Resources Information Center

    Al-Edwan, Zaid Suleiman; Hamaidi, Diala Abdul Hadi

    2011-01-01

    Knowledge-based economy is a new implemented trend in the field of education in Jordan. The ministry of education in Jordan attempts to implement this trend's philosophy in its textbooks. This study examined the extent to which the (1st-3rd grade) social and national textbooks reflect knowledge-based economy criteria from the perspective of…

  17. The International Conference on Human Resources Development Strategies in the Knowledge-Based Society [Proceedings] (Seoul, South Korea, August 29, 2001).

    ERIC Educational Resources Information Center

    Korea Research Inst. for Vocational Education and Training, Seoul.

    This document contains the following seven papers, all in both English and Korean, from a conference on human resources development and school-to-work transitions in the knowledge-based society: "The U.S. Experience as a Knowledge-based Economy in Transition and Its Impact on Industrial and Employment Structures" (Eric Im); "Changes…

  18. The mouse age phenome knowledgebase and disease-specific inter-species age mapping.

    PubMed

    Geifman, Nophar; Rubin, Eitan

    2013-01-01

    Similarities between mice and humans lead to generation of many mouse models of human disease. However, differences between the species often result in mice being unreliable as preclinical models for human disease. One difference that might play a role in lowering the predictivity of mice models to human diseases is age. Despite the important role age plays in medicine, it is too often considered only casually when considering mouse models. We developed the mouse-Age Phenotype Knowledgebase, which holds knowledge about age-related phenotypic patterns in mice. The knowledgebase was extensively populated with literature-derived data using text mining techniques. We then mapped between ages in humans and mice by comparing the age distribution pattern for 887 diseases in both species. The knowledgebase was populated with over 9800 instances generated by a text-mining pipeline. The quality of the data was manually evaluated, and was found to be of high accuracy (estimated precision >86%). Furthermore, grouping together diseases that share similar age patterns in mice resulted in clusters that mirror actual biomedical knowledge. Using these data, we matched age distribution patterns in mice and in humans, allowing for age differences by shifting either of the patterns. High correlation (r(2)>0.5) was found for 223 diseases. The results clearly indicate a difference in the age mapping between different diseases: age 30 years in human is mapped to 120 days in mice for Leukemia, but to 295 days for Anemia. Based on these results we generated a mice-to-human age map which is publicly available. We present here the development of the mouse-APK, its population with literature-derived data and its use to map ages in mice and human for 223 diseases. These results present a further step made to bridging the gap between humans and mice in biomedical research.

  19. SU-E-J-71: Spatially Preserving Prior Knowledge-Based Treatment Planning

    SciTech Connect

    Wang, H; Xing, L

    2015-06-15

    Purpose: Prior knowledge-based treatment planning is impeded by the use of a single dose volume histogram (DVH) curve. Critical spatial information is lost from collapsing the dose distribution into a histogram. Even similar patients possess geometric variations that becomes inaccessible in the form of a single DVH. We propose a simple prior knowledge-based planning scheme that extracts features from prior dose distribution while still preserving the spatial information. Methods: A prior patient plan is not used as a mere starting point for a new patient but rather stopping criteria are constructed. Each structure from the prior patient is partitioned into multiple shells. For instance, the PTV is partitioned into an inner, middle, and outer shell. Prior dose statistics are then extracted for each shell and translated into the appropriate Dmin and Dmax parameters for the new patient. Results: The partitioned dose information from a prior case has been applied onto 14 2-D prostate cases. Using prior case yielded final DVHs that was comparable to manual planning, even though the DVH for the prior case was different from the DVH for the 14 cases. Solely using a single DVH for the entire organ was also performed for comparison but showed a much poorer performance. Different ways of translating the prior dose statistics into parameters for the new patient was also tested. Conclusion: Prior knowledge-based treatment planning need to salvage the spatial information without transforming the patients on a voxel to voxel basis. An efficient balance between the anatomy and dose domain is gained through partitioning the organs into multiple shells. The use of prior knowledge not only serves as a starting point for a new case but the information extracted from the partitioned shells are also translated into stopping criteria for the optimization problem at hand.

  20. A knowledge-based algorithm for automatic detection of cephalometric landmarks on CBCT images.

    PubMed

    Gupta, Abhishek; Kharbanda, Om Prakash; Sardana, Viren; Balachandran, Rajiv; Sardana, Harish Kumar

    2015-11-01

    Cone-beam computed tomography (CBCT) is now an established component for 3D evaluation and treatment planning of patients with severe malocclusion and craniofacial deformities. Precision landmark plotting on 3D images for cephalometric analysis requires considerable effort and time, notwithstanding the experience of landmark plotting, which raises a need to automate the process of 3D landmark plotting. Therefore, knowledge-based algorithm for automatic detection of landmarks on 3D CBCT images has been developed and tested. A knowledge-based algorithm was developed in the MATLAB programming environment to detect 20 cephalometric landmarks. For the automatic detection, landmarks that are physically adjacent to each other were clustered into groups and were extracted through a volume of interest (VOI). Relevant contours were detected in the VOI and landmarks were detected using corresponding mathematical entities. The standard data for validation were generated using manual marking carried out by three orthodontists on a dataset of 30 CBCT images as a reference. Inter-observer ICC for manual landmark identification was found to be excellent (>0.9) amongst three observers. Euclidean distances between the coordinates of manual identification and automatic detection through the proposed algorithm of each landmark were calculated. The overall mean error for the proposed method was 2.01 mm with a standard deviation of 1.23 mm for all the 20 landmarks. The overall landmark detection accuracy was recorded at 64.67, 82.67 and 90.33 % within 2-, 3- and 4-mm error range of manual marking, respectively. The proposed knowledge-based algorithm for automatic detection of landmarks on 3D images was able to achieve relatively accurate results than the currently available algorithm.

  1. A framework for knowledge acquisition, representation and problem-solving in knowledge-based planning

    NASA Astrophysics Data System (ADS)

    Martinez-Bermudez, Iliana

    This research addresses the problem of developing planning knowledge-based applications. In particular, it is concerned with the problems of knowledge acquisition and representation---the issues that remain an impediment to the development of large-scale, knowledge-based planning applications. This work aims to develop a model of planning problem solving that facilitates expert knowledge elicitation and also supports effective problem solving. Achieving this goal requires determining the types of knowledge used by planning experts, the structure of this knowledge, and the problem-solving process that results in the plan. While answering these questions it became clear that the knowledge structure, as well as the process of problem solving, largely depends on the knowledge available to the expert. This dissertation proposes classification of planning problems based on their use of expert knowledge. Such classification can help in the selection of the appropriate planning method when dealing with a specific planning problem. The research concentrates on one of the identified classes of planning problems that can be characterized by well-defined and well-structured problem-solving knowledge. To achieve a more complete knowledge representation architecture for such problems, this work employs the task-specific approach to problem solving. The result of this endeavor is a task-specific methodology that allows the representation and use of planning knowledge in a structural, consistent manner specific to the domain of the application. The shell for building a knowledge-based planning application was created as a proof of concept for the methodology described in this dissertation. This shell enabled the development of a system for manufacturing planning---COMPLAN. COMPLAN encompasses knowledge related to four generic techniques used in composite material manufacturing and, given the description of the composite part, creates a family of plans capable of producing it.

  2. Knowledge-based and statistically modeled relationships between residential moisture damage and occupant reported health symptoms

    NASA Astrophysics Data System (ADS)

    Haverinen, Ulla; Vahteristo, Mikko; Moschandreas, Demetrios; Nevalainen, Aino; Husman, Tuula; Pekkanen, Juha

    This study continues to develop a quantitative indicator of moisture damage induced exposure in relation to occupant health in residential buildings. Earlier, we developed a knowledge-based model that links moisture damage variables with health symptoms. This paper presents a statistical model in an effort to improve the knowledge-based model, and formulates a third, simplified model that combines aspects of the both two models. The database used includes detailed information on moisture damage from 164 houses and health questionnaire data from the occupants. Models were formulated using generalized linear model formulation procedures, with 10 moisture damage variables as possible covariates and a respiratory health symptom score as the dependent variable. An 80% random sample of the residences was used for the formulation of models and the remaining 20% were used to evaluate them. Risk ratios (RR) for the respiratory health symptom score among the 80% sample were between 1.32 (1.12-1.55) and 1.48 (1.19-1.83), calculated per 10 points index increase. For the 20% sample, RRs were between 1.71 (1.13-2.58) and 2.34 (1.69-3.23), respectively. Deviance values in relation to degrees of freedom were between 2.00-2.12 (80% sample) and 1.50-1.81 (20% sample). The models developed can be simulated as continuous variables and they all associated significantly with the symptom score, the association being verified with a subset of the database not employed in the model formulation. We concluded that the performance of all models was similar. Therefore, based on the knowledge-based and statistical models, we were able to construct a simple model that can be used in estimating the severity of moisture damage.

  3. Ligand-supported homology modelling of protein binding-sites using knowledge-based potentials.

    PubMed

    Evers, Andreas; Gohlke, Holger; Klebe, Gerhard

    2003-11-21

    A new approach, MOBILE, is presented that models protein binding-sites including bound ligand molecules as restraints. Initially generated, homology models of the target protein are refined iteratively by including information about bioactive ligands as spatial restraints and optimising the mutual interactions between the ligands and the binding-sites. Thus optimised models can be used for structure-based drug design and virtual screening. In a first step, ligands are docked into an averaged ensemble of crude homology models of the target protein. In the next step, improved homology models are generated, considering explicitly the previously placed ligands by defining restraints between protein and ligand atoms. These restraints are expressed in terms of knowledge-based distance-dependent pair potentials, which were compiled from crystallographically determined protein-ligand complexes. Subsequently, the most favourable models are selected by ranking the interactions between the ligands and the generated pockets using these potentials. Final models are obtained by selecting the best-ranked side-chain conformers from various models, followed by an energy optimisation of the entire complex using a common force-field. Application of the knowledge-based pair potentials proved efficient to restrain the homology modelling process and to score and optimise the modelled protein-ligand complexes. For a test set of 46 protein-ligand complexes, taken from the Protein Data Bank (PDB), the success rate of producing near-native binding-site geometries (rmsd<2.0A) with MODELLER is 70% when the ligand restrains the homology modelling process in its native orientation. Scoring these complexes with the knowledge-based potentials, in 66% of the cases a pose with rmsd <2.0A is found on rank 1. Finally, MOBILE has been applied to two case studies modelling factor Xa based on trypsin and aldose reductase based on aldehyde reductase.

  4. Defensins knowledgebase: a manually curated database and information source focused on the defensins family of antimicrobial peptides

    PubMed Central

    Seebah, Shalin; Suresh, Anita; Zhuo, Shaowei; Choong, Yong How; Chua, Hazel; Chuon, Danny; Beuerman, Roger; Verma, Chandra

    2007-01-01

    The defensins knowledgebase is a manually curated database and information source focused on the defensin family of antimicrobial peptides. The current version of the database holds a comprehensive collection of over 350 defensin records each containing sequence, structure and activity information. A web-based interface provides access to the information and allows for text-based searching on the data fields. In addition, the website presents information on patents, grants, research laboratories and scientists, clinical studies and commercial entities pertaining to defensins. With the rapidly increasing interest in defensins, we hope that the knowledgebase will prove to be a valuable resource in the field of antimicrobial peptide research. The defensins knowledgebase is available at . PMID:17090586

  5. Knowledge-based immunosuppressive therapy for kidney transplant patients--from theoretical model to clinical integration.

    PubMed

    Seeling, Walter; Plischke, Max; de Bruin, Jeroen S; Schuh, Christian

    2015-01-01

    Immunosuppressive therapy is a risky necessity after a patient received a kidney transplant. To reduce risks, a knowledge-based system was developed that determines the right dosage of the immunosuppresive agent Tacrolimus. A theoretical model, to classify medication blood levels as well as medication adaptions, was created using data from almost 500 patients, and over 13.000 examinations. This model was then translated into an Arden Syntax knowledge base, and integrated directly into the hospital information system of the Vienna General Hospital. In this paper we give an overview of the construction and integration of such a system.

  6. Knowledge-based approach for generating target system specifications from a domain model

    NASA Technical Reports Server (NTRS)

    Gomaa, Hassan; Kerschberg, Larry; Sugumaran, Vijayan

    1992-01-01

    Several institutions in industry and academia are pursuing research efforts in domain modeling to address unresolved issues in software reuse. To demonstrate the concepts of domain modeling and software reuse, a prototype software engineering environment is being developed at George Mason University to support the creation of domain models and the generation of target system specifications. This prototype environment, which is application domain independent, consists of an integrated set of commercial off-the-shelf software tools and custom-developed software tools. This paper describes the knowledge-based tool that was developed as part of the environment to generate target system specifications from a domain model.

  7. A knowledge-based approach to improving optimization techniques in system planning

    NASA Technical Reports Server (NTRS)

    Momoh, J. A.; Zhang, Z. Z.

    1990-01-01

    A knowledge-based (KB) approach to improve mathematical programming techniques used in the system planning environment is presented. The KB system assists in selecting appropriate optimization algorithms, objective functions, constraints and parameters. The scheme is implemented by integrating symbolic computation of rules derived from operator and planner's experience and is used for generalized optimization packages. The KB optimization software package is capable of improving the overall planning process which includes correction of given violations. The method was demonstrated on a large scale power system discussed in the paper.

  8. Using Unified Modeling Language for Conceptual Modelling of Knowledge-Based Systems

    NASA Astrophysics Data System (ADS)

    Abdullah, Mohd Syazwan; Benest, Ian; Paige, Richard; Kimble, Chris

    This paper discusses extending the Unified Modelling Language by means of a profile for modelling knowledge-based system in the context of Model Driven Architecture (MDA) framework. The profile is implemented using the eXecutable Modelling Framework (XMF) Mosaic tool. A case study from the health care domain demonstrates the practical use of this profile; with the prototype implemented in Java Expert System Shell (Jess). The paper also discusses the possible mapping of the profile elements to the platform specific model (PSM) of Jess and provides some discussion on the Production Rule Representation (PRR) standardisation work.

  9. Enroute flight-path planning - Cooperative performance of flight crews and knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Smith, Philip J.; Mccoy, Elaine; Layton, Chuck; Galdes, Deb

    1989-01-01

    Interface design issues associated with the introduction of knowledge-based systems into the cockpit are discussed. Such issues include not only questions about display and control design, they also include deeper system design issues such as questions about the alternative roles and responsibilities of the flight crew and the computer system. In addition, the feasibility of using enroute flight path planning as a context for exploring such research questions is considered. In particular, the development of a prototyping shell that allows rapid design and study of alternative interfaces and system designs is discussed.

  10. Facilitating superior chronic disease management through a knowledge-based systems development model.

    PubMed

    Wickramasinghe, Nilmini S; Goldberg, Steve

    2008-01-01

    To date, the adoption and diffusion of technology-enabled solutions to deliver better healthcare has been slow. There are many reasons for this. One of the most significant is that the existing methodologies that are normally used in general for Information and Communications Technology (ICT) implementations tend to be less successful in a healthcare context. This paper describes a knowledge-based adaptive mapping to realisation methodology to traverse successfully from idea to realisation rapidly and without compromising rigour so that success ensues. It is discussed in connection with trying to implement superior ICT-enabled approaches to facilitate superior Chronic Disease Management (CDM).

  11. Generating MEDLINE search strategies using a librarian knowledge-based system.

    PubMed Central

    Peng, P.; Aguirre, A.; Johnson, S. B.; Cimino, J. J.

    1993-01-01

    We describe a librarian knowledge-based system that generates a search strategy from a query representation based on a user's information need. Together with the natural language parser AQUA, the system functions as a human/computer interface, which translates a user query from free text into a BRS Onsite search formulation, for searching the MEDLINE bibliographic database. In the system, conceptual graphs are used to represent the user's information need. The UMLS Metathesaurus and Semantic Net are used as the key knowledge sources in building the knowledge base. PMID:8130544

  12. Hazard Expertise (HAZE) knowledge-based system: description and user guide. Final report

    SciTech Connect

    Mann, D.K.; Franczak, G.R.; Pritchard, L.

    1988-11-01

    The Hazard Expertise (HAZE) program is a knowledge-based system for military-installation personnel working with hazardous material/waste management. HAZE is an easy, informal way to share problems, ideas for solutions, and information on the latest technologies and environmental management strategies. The system allows self-contained updating, systematic analysis of alternatives, and selection of optimal technologies. The system provides a list of courses, meeting announcements, a personnel directory, a listing of pertinent literature and other special services. Example sessions demonstrate use of the commands.

  13. A knowledge-based expert system for scheduling of airborne astronomical observations

    NASA Technical Reports Server (NTRS)

    Nachtsheim, P. R.; Gevarter, W. B.; Stutz, J. C.; Banda, C. P.

    1985-01-01

    The Kuiper Airborne Observatory Scheduler (KAOS) is a knowledge-based expert system developed at NASA Ames Research Center to assist in route planning of a C-141 flying astronomical observatory. This program determines a sequence of flight legs that enables sequential observations of a set of heavenly bodies derived from a list of desirable objects. The possible flight legs are constrained by problems of observability, avoiding flyovers of warning and restricted military zones, and running out of fuel. A significant contribution of the KAOS program is that it couples computational capability with a reasoning system.

  14. Application of flight systems methodologies to the validation of knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Duke, Eugene L.

    1988-01-01

    Flight and mission-critical systems are verified, qualified for flight, and validated using well-known and well-established techniques. These techniques define the validation methodology used for such systems. In order to verify, qualify, and validate knowledge-based systems (KBS's), the methodology used for conventional systems must be addressed, and the applicability and limitations of that methodology to KBS's must be identified. An outline of how this approach to the validation of KBS's is being developed and used is presented.

  15. Application of flight systems methodologies to the validation of knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Duke, Eugene L.

    1988-01-01

    Flight and mission-critical systems are verified, qualified for flight, and validated using well-known and well-established techniques. These techniques define the validation methodology used for such systems. In order to verify, qualify, and validate knowledge-based systems (KBS's), the methodology used for conventional systems must be addressed, and the applicability and limitations of that methodology to KBS's must be identified. The author presents an outline of how this approach to the validation of KBS's is being developed and used at the Dryden Flight Research Facility of the NASA Ames Research Center.

  16. Use of metaknowledge in the verification of knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Morell, Larry J.

    1989-01-01

    Knowledge-based systems are modeled as deductive systems. The model indicates that the two primary areas of concern in verification are demonstrating consistency and completeness. A system is inconsistent if it asserts something that is not true of the modeled domain. A system is incomplete if it lacks deductive capability. Two forms of consistency are discussed along with appropriate verification methods. Three forms of incompleteness are discussed. The use of metaknowledge, knowledge about knowledge, is explored in connection to each form of incompleteness.

  17. A Knowledge-Based System For The Recognition Of Roads On SPOT Satellite Images

    NASA Astrophysics Data System (ADS)

    van Cleynenbreugel, J.; Suetens, Paul; Fierens, F.; Wambacq, Patrick; Oosterlinck, Andre J.

    1989-09-01

    Due to the resolution of current satellite imagery (e.g. SPOT), the extraction of roads and linear networks from satellite data has become a feasible - although labour-intensive - task for a human expert. This interpretation problem relies on structural image recognition as well as on expertise in combining data sources external to the image data (e.g. topography, landcover classification). In this paper different knowledge sources employed by human interpreters are discussed. Ways to implement these sources using current knowledge-based tools are suggested. A practical case study of knowledge integration is described.

  18. Recognition Of Partially Occluded Workpieces By A Knowledge-Based System

    NASA Astrophysics Data System (ADS)

    Serpico, S. B.; Vernazza, G.; Dellepiane, S.; Angela, P.

    1987-01-01

    A knowledge-based system is presented that is oriented toward partially occluded 2-D workpiece recognition in TV camera images. The generalized Hough transform is employed to extract elementary edge patterns. Intrinsic and relational information regarding elementary patterns is computed and then stored inside a net of frames. A similar net of frames is employed for workpiece model representation, for an easy matching with the previous net. A set of production rules provide the heuristics to find hints for locating focus-of-attention regions, while other production rules specify modalities for applying a hypothesis-generation-and-test process. Experimental results on a set of 20 workpieces are reported.

  19. SU-E-T-129: Are Knowledge-Based Planning Dose Estimates Valid for Distensible Organs?

    SciTech Connect

    Lalonde, R; Heron, D; Huq, M; Readshaw, A

    2015-06-15

    Purpose: Knowledge-based planning programs have become available to assist treatment planning in radiation therapy. Such programs can be used to generate estimated DVHs and planning constraints for organs at risk (OARs), based upon a model generated from previous plans. These estimates are based upon the planning CT scan. However, for distensible OARs like the bladder and rectum, daily variations in volume may make the dose estimates invalid. The purpose of this study is to determine whether knowledge-based DVH dose estimates may be valid for distensible OARs. Methods: The Varian RapidPlan™ knowledge-based planning module was used to generate OAR dose estimates and planning objectives for 10 prostate cases previously planned with VMAT, and final plans were calculated for each. Five weekly setup CBCT scans of each patient were then downloaded and contoured (assuming no change in size and shape of the target volume), and rectum and bladder DVHs were recalculated for each scan. Dose volumes were then compared at 75, 60,and 40 Gy for the bladder and rectum between the planning scan and the CBCTs. Results: Plan doses and estimates matched well at all dose points., Volumes of the rectum and bladder varied widely between planning CT and the CBCTs, ranging from 0.46 to 2.42 for the bladder and 0.71 to 2.18 for the rectum, causing relative dose volumes to vary between planning CT and CBCT, but absolute dose volumes were more consistent. The overall ratio of CBCT/plan dose volumes was 1.02 ±0.27 for rectum and 0.98 ±0.20 for bladder in these patients. Conclusion: Knowledge-based planning dose volume estimates for distensible OARs are still valid, in absolute volume terms, between treatment planning scans and CBCT’s taken during daily treatment. Further analysis of the data is being undertaken to determine how differences depend upon rectum and bladder filling state. This work has been supported by Varian Medical Systems.

  20. canSAR: an updated cancer research and drug discovery knowledgebase.

    PubMed

    Tym, Joseph E; Mitsopoulos, Costas; Coker, Elizabeth A; Razaz, Parisa; Schierz, Amanda C; Antolin, Albert A; Al-Lazikani, Bissan

    2016-01-04

    canSAR (http://cansar.icr.ac.uk) is a publicly available, multidisciplinary, cancer-focused knowledgebase developed to support cancer translational research and drug discovery. canSAR integrates genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and druggability data. canSAR is widely used to rapidly access information and help interpret experimental data in a translational and drug discovery context. Here we describe major enhancements to canSAR including new data, improved search and browsing capabilities, new disease and cancer cell line summaries and new and enhanced batch analysis tools.

  1. Studies in knowledge-based diagnosis of failures in robotic assembly

    NASA Technical Reports Server (NTRS)

    Lam, Raymond K.; Pollard, Nancy S.; Desai, Rajiv S.

    1990-01-01

    The telerobot diagnostic system (TDS) is a knowledge-based system that is being developed for identification and diagnosis of failures in the space robotic domain. The system is able to isolate the symptoms of the failure, generate failure hypotheses based on these symptoms, and test their validity at various levels by interpreting or simulating the effects of the hypotheses on results of plan execution. The implementation of the TDS is outlined. The classification of failures and the types of system models used by the TDS are discussed. A detailed example of the TDS approach to failure diagnosis is provided.

  2. Docking into knowledge-based potential fields: a comparative evaluation of DrugScore.

    PubMed

    Sotriffer, Christoph A; Gohlke, Holger; Klebe, Gerhard

    2002-05-09

    A new application of DrugScore is reported in which the knowledge-based pair potentials serve as objective function in docking optimizations. The Lamarckian genetic algorithm of AutoDock is used to search for favorable ligand binding modes guided by DrugScore grids as representations of the protein binding site. The approach is found to be successful in many cases where DrugScore-based re-ranking of already docked ligand conformations does not yield satisfactory results. Compared to the AutoDock scoring function, DrugScore yields slightly superior results in flexible docking.

  3. Knowledge-based monitoring of the pointing control system on the Hubble space telescope

    NASA Technical Reports Server (NTRS)

    Dunham, Larry L.; Laffey, Thomas J.; Kao, Simon M.; Schmidt, James L.; Read, Jackson Y.

    1987-01-01

    A knowledge-based system for the real time monitoring of telemetry data from the Pointing and Control System (PCS) of the Hubble Space Telescope (HST) that enables the retention of design expertise throughout the three decade project lifespan by means other than personnel and documentation is described. The system will monitor performance, vehicle status, success or failure of various maneuvers, and in some cases diagnose problems and recommend corrective actions using a knowledge base built using mission scenarios and the more than 4,500 telemetry monitors from the HST.

  4. Requirements for an on-line knowledge-based anatomy information system.

    PubMed Central

    Brinkley, J. F.; Rosse, C.

    1998-01-01

    User feedback from the Digital Anatomist Web-based anatomy atlases, together with over 20 years of anatomy teaching experience, were used to formulate the requirements and system design for a next-generation anatomy information system. The main characteristic of this system over current image-based approaches is that it is knowledge-based. A foundational model of anatomy is accessed by an intelligent agent that uses its knowledge about the available anatomy resources and the user types to generate customized interfaces. Current usage statistics suggest that even partial implementation of this design will be of great practical value for both clinical and educational needs. Images Figure 1 PMID:9929347

  5. DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis.

    PubMed

    Sherman, Brad T; Huang, Da Wei; Tan, Qina; Guo, Yongjian; Bour, Stephan; Liu, David; Stephens, Robert; Baseler, Michael W; Lane, H Clifford; Lempicki, Richard A

    2007-11-02

    Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis. The DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner. The DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://david.abcc.ncifcrf.gov/knowledgebase/.

  6. Feasibility of using a knowledge-based system concept for in-flight primary-flight-display research

    NASA Technical Reports Server (NTRS)

    Ricks, Wendell R.

    1991-01-01

    Flight test results have been obtained which demonstrate the feasibility and desirability of using knowledge-based systems architectures for flight test investigations of primary flight display information management-related issues. LISP-based software was used for real-time operation of the primary flight display. The two integrated knowledge-based systems designed to control the primary flight displays were implemented aboard a NASA-Langley B-737. The programmer is noted to be capable of more easily developing initial systems via the present method than with more conventional techniques.

  7. A knowledge-based control system for air-scour optimisation in membrane bioreactors.

    PubMed

    Ferrero, G; Monclús, H; Sancho, L; Garrido, J M; Comas, J; Rodríguez-Roda, I

    2011-01-01

    Although membrane bioreactors (MBRs) technology is still a growing sector, its progressive implementation all over the world, together with great technical achievements, has allowed it to reach a mature degree, just comparable to other more conventional wastewater treatment technologies. With current energy requirements around 0.6-1.1 kWh/m3 of treated wastewater and investment costs similar to conventional treatment plants, main market niche for MBRs can be areas with very high restrictive discharge limits, where treatment plants have to be compact or where water reuse is necessary. Operational costs are higher than for conventional treatments; consequently there is still a need and possibilities for energy saving and optimisation. This paper presents the development of a knowledge-based decision support system (DSS) for the integrated operation and remote control of the biological and physical (filtration and backwashing or relaxation) processes in MBRs. The core of the DSS is a knowledge-based control module for air-scour consumption automation and energy consumption minimisation.

  8. Knowledge-based goal-driven approach for information extraction and decision making for target recognition

    NASA Astrophysics Data System (ADS)

    Wilson, Roderick D.; Wilson, Anitra C.

    1996-06-01

    This paper presents a novel goal-driven approach for designing a knowledge-based system for information extraction and decision-making for target recognition. The underlying goal-driven model uses a goal frame tree schema for target organization, a hybrid rule-based pattern- directed formalism for target structural encoding, and a goal-driven inferential control strategy. The knowledge-base consists of three basic structures for the organization and control of target information: goals, target parameters, and an object-rulebase. Goal frames represent target recognition tasks as goals and subgoals in the knowledge base. Target parameters represent characteristic attributes of targets that are encoded as information atoms. Information atoms may have one or more assigned values and are used for information extraction. The object-rulebase consists of pattern/action assertional implications that describe the logical relationships existing between target parameter values. A goal realization process formulates symbolic patten expressions whose atomic values map to target parameters contained a priori in a hierarchical database of target state information. Symbolic pattern expression creation is accomplished via the application of a novel goal-driven inference strategy that logically prunes an AND/OR tree constructed object-rulebase. Similarity analysis is performed via pattern matching of query symbolic patterns and a priori instantiated target parameters.

  9. Analytical and knowledge-based redundancy for fault diagnosis in process plants

    SciTech Connect

    Fathi, Z.; Ramirez, W.F. ); Korbicz, J. )

    1993-01-01

    The increasing complexity of process plants and their reliability have necessitated the development of more powerful methods for detecting and diagnosing process abnormalities. Among the underlying strategies, analytical redundancy and knowledge-based system techniques offer viable solutions. In this work, the authors consider the adaptive inclusion of analytical redundancy models (state and parameter estimation modules) in the diagnostic reasoning loop of a knowledge-based system. This helps overcome the difficulties associated with each category. The design method is a new layered knowledge base that houses compiled/qualitative knowledge in the high levels and process-general estimation knowledge in the low levels of a hierarchical knowledge structure. The compiled knowledge is used to narrow the diagnostic search space and provide an effective way of employing estimation modules. The estimation-based methods that resort to fundamental analysis provide the rationale for a qualitatively-guided reasoning process. The overall structure of the fault detection and isolation system based on the combined strategy is discussed focusing on the model-based redundancy methods which create the low levels of the hierarchical knowledge base. The system has been implemented using the condensate-feedwater subsystem of a coal-fired power plant. Due to the highly nonlinear and mixed-mode nature of the power plant dynamics, the modified extended Kalman filter is used in designing local detection filters.

  10. HIstome--a relational knowledgebase of human histone proteins and histone modifying enzymes.

    PubMed

    Khare, Satyajeet P; Habib, Farhat; Sharma, Rahul; Gadewal, Nikhil; Gupta, Sanjay; Galande, Sanjeev

    2012-01-01

    Histones are abundant nuclear proteins that are essential for the packaging of eukaryotic DNA into chromosomes. Different histone variants, in combination with their modification 'code', control regulation of gene expression in diverse cellular processes. Several enzymes that catalyze the addition and removal of multiple histone modifications have been discovered in the past decade, enabling investigations of their role(s) in normal cellular processes and diverse pathological conditions. This sudden influx of data, however, has resulted in need of an updated knowledgebase that compiles, organizes and presents curated scientific information to the user in an easily accessible format. Here, we present HIstome, a browsable, manually curated, relational database that provides information about human histone proteins, their sites of modifications, variants and modifying enzymes. HIstome is a knowledgebase of 55 human histone proteins, 106 distinct sites of their post-translational modifications (PTMs) and 152 histone-modifying enzymes. Entries have been grouped into 5 types of histones, 8 types of post-translational modifications and 14 types of enzymes that catalyze addition and removal of these modifications. The resource will be useful for epigeneticists, pharmacologists and clinicians. HIstome: The Histone Infobase is available online at http://www.iiserpune.ac.in/∼coee/histome/ and http://www.actrec.gov.in/histome/.

  11. Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

    PubMed Central

    Bennett, Kristin P.

    2014-01-01

    We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

  12. An architecture for integrating distributed and cooperating knowledge-based Air Force decision aids

    NASA Technical Reports Server (NTRS)

    Nugent, Richard O.; Tucker, Richard W.

    1988-01-01

    MITRE has been developing a Knowledge-Based Battle Management Testbed for evaluating the viability of integrating independently-developed knowledge-based decision aids in the Air Force tactical domain. The primary goal for the testbed architecture is to permit a new system to be added to a testbed with little change to the system's software. Each system that connects to the testbed network declares that it can provide a number of services to other systems. When a system wants to use another system's service, it does not address the server system by name, but instead transmits a request to the testbed network asking for a particular service to be performed. A key component of the testbed architecture is a common database which uses a relational database management system (RDBMS). The RDBMS provides a database update notification service to requesting systems. Normally, each system is expected to monitor data relations of interest to it. Alternatively, a system may broadcast an announcement message to inform other systems that an event of potential interest has occurred. Current research is aimed at dealing with issues resulting from integration efforts, such as dealing with potential mismatches of each system's assumptions about the common database, decentralizing network control, and coordinating multiple agents.

  13. Integrated knowledge-based tools for documenting and monitoring damages to built heritage

    NASA Astrophysics Data System (ADS)

    Cacciotti, R.

    2015-08-01

    The advancements of information technologies as applied to the most diverse fields of science define a breakthrough in the accessibility and processing of data for both expert and non-expert users. Nowadays it is possible to evidence an increasingly relevant research effort in the context of those domains, such as that of cultural heritage protection, in which knowledge mapping and sharing constitute critical prerequisites for accomplishing complex professional tasks. The aim of this paper is to outline the main results and outputs of the MONDIS research project. This project focusses on the development of integrated knowledge-based tools grounded on an ontological representation of the field of heritage conservation. The scope is to overcome the limitations of earlier databases by the application of modern semantic technologies able to integrate, organize and process useful information concerning damages to built heritage objects. In particular MONDIS addresses the need for supporting a diverse range of stakeholders (e.g. administrators, owners and professionals) in the documentation and monitoring of damages to historical constructions and in finding related remedies. The paper concentrates on the presentation of the following integrated knowledgebased components developed within the project: (I) MONDIS mobile application (plus desktop version), (II) MONDIS record explorer, (III) Ontomind profiles, (IV) knowledge matrix and (V) terminology editor. An example of practical application of the MONDIS integrated system is also provided and finally discussed.

  14. Knowledge-based system for structured examination, diagnosis and therapy in treatment of traumatised teeth.

    PubMed

    Robertson, A; Norén, J G

    2001-02-01

    Dental trauma in children and adolescents is a common problem, and the prevalence of these injuries has increased in the last 10-20 years. A dental injury should always be considered an emergency and, thus, be treated immediately to relieve pain, facilitate reduction of displaced teeth, reconstruct lost hard tissue, and improve prognosis. Rational therapy depends upon a correct diagnosis, which can be achieved with the aid of various examination techniques. It must be understood that an incomplete examination can lead to inaccurate diagnosis and less successful treatment. Good knowledge of traumatology and models of treatments can also reduce stress and anxiety for both the patient and the dental team. Knowledge-based Systems (KBS) are a practical implementation of Artificial Intelligence. In complex domains which humans find difficult to understand, KBS can assist in making decisions and can also add knowledge. The aim of this paper is to describe the structure of a knowledge-based system for structured examination, diagnosis and therapy for traumatised primary and permanent teeth. A commercially available program was used as developmental tool for the programming (XpertRule, Attar, London, UK). The paper presents a model for a computerised decision support system for traumatology.

  15. Knowledge-based algorithm for satellite image classification of urban wetlands

    NASA Astrophysics Data System (ADS)

    Xu, Xiaofan; Ji, Wei

    2014-10-01

    It has been a challenge to accurately detect urban wetlands with remotely sensed data by means of pixel-based image classification. This technical difficulty results mainly from inadequate spatial resolutions of satellite imagery, spectral similarities between urban wetlands and adjacent land covers, and spatial complexity of wetlands in human transformed, heterogeneous urban landscapes. To address this issue, an image classification approach has been developed to improve the mapping accuracy of urban wetlands by integrating the pixel-based classification with a knowledge-based algorithm. The algorithm includes a set of decision rules of identifying wetland cover in relation to their elevation, spatial adjacencies, habitat conditions, hydro-geomorphological characteristics, and relevant geo-statistics. ERDAS Imagine software was used to develop the knowledge base and implement the classification. The study area is the metropolitan region of Kansas City, USA. SPOT satellite images of 1992, 2008, and 2010 were classified into four classes - wetland, farmland, built-up land, and forestland. The results suggest that the knowledge-based image classification approach can enhance urban wetland detection capabilities and classification accuracies with remotely sensed satellite imagery.

  16. A new approach to knowledge-based design of recurrent neural networks.

    PubMed

    Kolman, Eyal; Margaliot, Michael

    2008-08-01

    A major drawback of artificial neural networks (ANNs) is their black-box character. This is especially true for recurrent neural networks (RNNs) because of their intricate feedback connections. In particular, given a problem and some initial information concerning its solution, it is not at all obvious how to design an RNN that is suitable for solving this problem. In this paper, we consider a fuzzy rule base with a special structure, referred to as the fuzzy all-permutations rule base (FARB). Inferring the FARB yields an input-output (IO) mapping that is mathematically equivalent to that of an RNN. We use this equivalence to develop two new knowledge-based design methods for RNNs. The first method, referred to as the direct approach, is based on stating the desired functioning of the RNN in terms of several sets of symbolic rules, each one corresponding to a subnetwork. Each set is then transformed into a suitable FARB. The second method is based on first using the direct approach to design a library of simple modules, such as counters or comparators, and realize them using RNNs. Once designed, the correctness of each RNN can be verified. Then, the initial design problem is solved by using these basic modules as building blocks. This yields a modular and systematic approach for knowledge-based design of RNNs. We demonstrate the efficiency of these approaches by designing RNNs that recognize both regular and nonregular formal languages.

  17. Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

    NASA Technical Reports Server (NTRS)

    Hinchey, Mike; Rash, James; Erickson, John; Gracanin, Denis; Rouff, Chris

    2010-01-01

    Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

  18. Knowledge-Based Identification of Soluble Biomarkers: Hepatic Fibrosis in NAFLD as an Example

    PubMed Central

    Page, Sandra; Birerdinc, Aybike; Estep, Michael; Stepanova, Maria; Afendy, Arian; Petricoin, Emanuel; Younossi, Zobair; Chandhoke, Vikas; Baranova, Ancha

    2013-01-01

    The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD) as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1) NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2) biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases. PMID:23405244

  19. Knowledge-based video compression for search and rescue robots and multiple sensor networks

    NASA Astrophysics Data System (ADS)

    Williams, Chris; Murphy, Robin R.

    2006-05-01

    Robot and sensor networks are needed for safety, security, and rescue applications such as port security and reconnaissance during a disaster. These applications rely on real-time transmission of images, which generally saturate the available wireless network infrastructure. Knowledge-based compression is a method for reducing the video frame transmission rate between robots or sensors and remote operators. Because images may need to be archived as evidence and/or distributed to multiple applications with different post processing needs, lossy compression schemes, such as MPEG, H.26x, etc., are not acceptable. This work proposes a lossless video server system consisting of three classes of filters (redundancy, task, and priority) which use different levels of knowledge (local sensed environment, human factors associated with a local task, and relative global priority of a task) at the application layer of the network. It demonstrates the redundancy and task filters for a realistic robot search scenario. The redundancy filter is shown to reduce the overall transmission bandwidth by 24.07% to 33.42%, and, when combined with the task filter, reduces overall transmission bandwidth by 59.08%to 67.83%. By itself, the task filter has the capability to reduce transmission bandwidth by 32.95% to 33.78%. While knowledge-based compression generally does not reach the same levels of reduction as MPEG, there are instances where the system outperforms MPEG encoding.

  20. Dealing with difficult deformations: construction of a knowledge-based deformation atlas

    NASA Astrophysics Data System (ADS)

    Thorup, S. S.; Darvann, T. A.; Hermann, N. V.; Larsen, P.; Ólafsdóttir, H.; Paulsen, R. R.; Kane, A. A.; Govier, D.; Lo, L.-J.; Kreiborg, S.; Larsen, R.

    2010-03-01

    Twenty-three Taiwanese infants with unilateral cleft lip and palate (UCLP) were CT-scanned before lip repair at the age of 3 months, and again after lip repair at the age of 12 months. In order to evaluate the surgical result, detailed point correspondence between pre- and post-surgical images was needed. We have previously demonstrated that non-rigid registration using B-splines is able to provide automated determination of point correspondences in populations of infants without cleft lip. However, this type of registration fails when applied to the task of determining the complex deformation from before to after lip closure in infants with UCLP. The purpose of the present work was to show that use of prior information about typical deformations due to lip closure, through the construction of a knowledge-based atlas of deformations, could overcome the problem. Initially, mean volumes (atlases) for the pre- and post-surgical populations, respectively, were automatically constructed by non-rigid registration. An expert placed corresponding landmarks in the cleft area in the two atlases; this provided prior information used to build a knowledge-based deformation atlas. We model the change from pre- to post-surgery using thin-plate spline warping. The registration results are convincing and represent a first move towards an automatic registration method for dealing with difficult deformations due to this type of surgery.

  1. Autonomous Knowledge-Based Navigation In An Unkown Two-Dimensional Environment With Convex Polygon Obstacles

    NASA Astrophysics Data System (ADS)

    Cheng, Linfu; McKendrick, John D.

    1989-03-01

    Navigation of autonomous vehicles in environments where the exact locations of obstacles are know has been the focus of research for two decades. More recently, algorithms for controlling progress through unknown environments have been proposed. The utilization of knowledge-based systems for studying the behavior of an autonomous vehicles has not received much study. A knowledge-driven autonomous system simulation was developed which enabled an autonomous mobile system to move in a two-dimensional environment and to use a simulated ranging/vision sensor to test whether a selected goal position was visible or whether the goal was obscured by one of the multiple polygon obstacles. As the mobile system gains information about the location of obstacles, it is added to the system's knowledge-base. Considerable attention was given to the computation of what vertices were mutually visible in the multi-obstacle environment and that computation was carried out in Lisp. The study relied on a program implemented in a generalized decision-making paradigm, OPS5.

  2. Short term load forecasting of Taiwan power system using a knowledge-based expert system

    SciTech Connect

    Ho, K.L.; Hsu, Y.Y.; Chen, C.F.; Lee, T.E. . Dept. of Electrical Engineering); Liang, C.C.; Lai, T.S.; Chen, K.K. )

    1990-11-01

    A knowledge-based expert system is proposed for the short term load forecasting of Taiwan power system. The developed expert system, which was implemented on a personal computer, was written in PROLOG using a 5-year data base. To benefit from the expert knowledge and experience of the system operator, eleven different load shapes, each with different means of load calculations, are established. With these load shapes at hand, some peculiar load characteristics pertaining to Taiwan Power Company can be taken into account. The special load types considered by the expert system include the extremely low load levels during the week of the Chinese New Year, the special load characteristics of the days following a tropical storm or a typhoon, the partial shutdown of certain factories on Saturdays, and the special event caused by a holiday on Friday or on Tuesday, etc. A characteristic feature of the proposed knowledge-based expert system is that it is easy to add new information and new rules to the knowledge base. To illustrate the effectiveness of the presented expert system, short-term load forecasting is performed on Taiwan power system by using both the developed algorithm and the conventional Box-Jenkins statistical method. It is found that a mean absolute error of 2.52% for a year is achieved by the expert system approach as compared to an error of 3.86% by the statistical method.

  3. Integration of Cardiac Proteome Biology and Medicine by a Specialized Knowledgebase

    PubMed Central

    Zong, Nobel C.; Li, Haomin; Li, Hua; Lam, Maggie P.Y.; Jimenez, Rafael C.; Kim, Christina S.; Deng, Ning; Kim, Allen K.; Choi, Jeong Ho; Zelaya, Ivette; Liem, David; Meyer, David; Odeberg, Jacob; Fang, Caiyun; Lu, Hao-jie; Xu, Tao; Weiss, James; Duan, Huilong; Uhlen, Mathias; Yates, John R.; Apweiler, Rolf; Ge, Junbo; Hermjakob, Henning; Ping, Peipei

    2014-01-01

    Rationale Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. Objective The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. Methods and Results We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB), a centralized platform of high quality cardiac proteomic data, bioinformatics tools and relevant cardiovascular phenotypes. Currently, COPaKB features eight organellar modules, comprising 4,203 LC-MS/MS experiments from human, mouse, drosophila and C. elegans as well as expression images of 10,924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. Conclusions COPaKB (www.HeartProteome.org) provides an innovative and interactive resource, which connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified web server, non-proteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes. PMID:23965338

  4. Knowledge-based approach to multiple-transaction processing and distributed data-base design

    SciTech Connect

    Park, J.T.

    1987-01-01

    The collective processing of multiple transactions in a data-base system has recently received renewed attention due to its capability of improving the overall performance of a data-base system and its applicability to the design of knowledge-based expert systems and extensible data-base systems. This dissertation consists of two parts. The first part presents a new knowledge-based approach to the problems of processing multiple concurrent queries and distributing replicated data objects for further improvement of the overall system performance. The second part deals with distributed database design, i.e., designing horizontal fragments using a semantic knowledge, and allocating data in a distributed environment. The semantic knowledge on data such as functional dependencies and semantic-data-integrity constraints are newly exploited for the identification of subset relationships between intermediate results of query executions involving joins, such that the (intermediate) results of queries can be utilized for the efficient processing of other queries. The expertise on the collective processing of multiple transactions is embodied into the rules of a rule-based expert system, MTP (Multiple Transaction Processor). In the second part, MTP is applied for the determination of horizontal fragments exploiting the semantic knowledge. Heuristics for allocating data in local area networks are developed.

  5. Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

    PubMed

    Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

    2017-01-01

    Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

  6. A knowledge-based approach to automatic detection of the spinal cord in CT images.

    PubMed

    Archip, Neculai; Erard, Pierre-Jean; Egmont-Petersen, Michael; Haefliger, Jean-Marie; Germond, Jean-Francois

    2002-12-01

    Accurate planning of radiation therapy entails the definition of treatment volumes and a clear delimitation of normal tissue of which unnecessary exposure should be prevented. The spinal cord is a radiosensitive organ, which should be precisely identified because an overexposure to radiation may lead to undesired complications for the patient such as neuronal disfunction or paralysis. In this paper, a knowledge-based approach to identifying the spinal cord in computed tomography images of the thorax is presented. The approach relies on a knowledge-base which consists of a so-called anatomical structures map (ASM) and a task-oriented architecture called the plan solver. The ASM contains a frame-like knowledge representation of the macro-anatomy in the human thorax. The plan solver is responsible for determining the position, orientation and size of the structures of interest to radiation therapy. The plan solver relies on a number of image processing operators. Some are so-called atomic (e.g., thresholding and snakes) whereas others are composite. The whole system has been implemented on a standard PC. Experiments performed on the image material from 23 patients show that the approach results in a reliable recognition of the spinal cord (92% accuracy) and the spinal canal (85% accuracy). The lamina is more problematic to locate correctly (accuracy 72%). The position of the outer thorax is always determined correctly.

  7. IGENPRO knowledge-based digital system for process transient diagnostics and management

    SciTech Connect

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

    1997-12-31

    Verification and validation issues have been perceived as important factors in the large scale deployment of knowledge-based digital systems for plant transient diagnostics and management. Research and development (R&D) is being performed on the IGENPRO package to resolve knowledge base issues. The IGENPRO approach is to structure the knowledge bases on generic thermal-hydraulic (T-H) first principles and not use the conventional event-basis structure. This allows for generic comprehensive knowledge, relatively small knowledge bases and above all the possibility of T-H system/plant independence. To demonstrate concept feasibility the knowledge structure has been implemented in the diagnostic module PRODIAG. Promising laboratory testing results have been obtained using data from the full scope Braidwood PWR operator training simulator. This knowledge structure is now being implemented in the transient management module PROMANA to treat unanticipated events and the PROTREN module is being developed to process actual plant data. Achievement of the IGENPRO R&D goals should contribute to the acceptance of knowledge-based digital systems for transient diagnostics and management.

  8. A knowledge-based machine vision system for space station automation

    NASA Technical Reports Server (NTRS)

    Chipman, Laure J.; Ranganath, H. S.

    1989-01-01

    A simple knowledge-based approach to the recognition of objects in man-made scenes is being developed. Specifically, the system under development is a proposed enhancement to a robot arm for use in the space station laboratory module. The system will take a request from a user to find a specific object, and locate that object by using its camera input and information from a knowledge base describing the scene layout and attributes of the object types included in the scene. In order to use realistic test images in developing the system, researchers are using photographs of actual NASA simulator panels, which provide similar types of scenes to those expected in the space station environment. Figure 1 shows one of these photographs. In traditional approaches to image analysis, the image is transformed step by step into a symbolic representation of the scene. Often the first steps of the transformation are done without any reference to knowledge of the scene or objects. Segmentation of an image into regions generally produces a counterintuitive result in which regions do not correspond to objects in the image. After segmentation, a merging procedure attempts to group regions into meaningful units that will more nearly correspond to objects. Here, researchers avoid segmenting the image as a whole, and instead use a knowledge-directed approach to locate objects in the scene. The knowledge-based approach to scene analysis is described and the categories of knowledge used in the system are discussed.

  9. Young People's Management of the Transition from Education to Employment in the Knowledge-Based Sector in Shanghai

    ERIC Educational Resources Information Center

    Wang, Qi; Lowe, John

    2011-01-01

    This paper reports on a study of the transition from university to work by students/employees in the complex and rapidly changing socio-economic context of contemporary Shanghai. It aims at understanding how highly educated young people perceive the nature and mode of operation of the newly emerging labour market for knowledge-based jobs, and how…

  10. Transformative Pedagogy, Leadership and School Organisation for the Twenty-First-Century Knowledge-Based Economy: The Case of Singapore

    ERIC Educational Resources Information Center

    Dimmock, Clive; Goh, Jonathan W. P.

    2011-01-01

    Singapore has a high performing school system; its students top international tests in maths and science. Yet while the Singapore government cherishes its world class "brand", it realises that in a globally competitive world, its schools need to prepare students for the twenty-first-century knowledge-based economy (KBE). Accordingly,…

  11. Enhancing Student Learning in Knowledge-Based Courses: Integrating Team-Based Learning in Mass Communication Theory Classes

    ERIC Educational Resources Information Center

    Han, Gang; Newell, Jay

    2014-01-01

    This study explores the adoption of the team-based learning (TBL) method in knowledge-based and theory-oriented journalism and mass communication (J&MC) courses. It first reviews the origin and concept of TBL, the relevant theories, and then introduces the TBL method and implementation, including procedures and assessments, employed in an…

  12. Going beyond information management: using the Comprehensive Accreditation Manual for Hospitals to promote knowledge-based information services.

    PubMed

    Schardt, C M

    1998-10-01

    In 1987, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) initiated the Agenda for Change, a major revision in the evaluation process for hospitals. An essential component of that change was to shift the emphasis away from standards for individual departments to standards for hospital-wide functions. In recent years, hospital librarians have focused their energy and attention on complying with the standards for the "Management of Information" chapter, specifically the IM.9 section on knowledge-based information. However, the JCAHO has listed the health sciences librarian and library services as having responsibilities in six other chapters within the Comprehensive Accreditation Manual for Hospitals. These chapters can have a major impact on the services of the hospital library for two reasons: (1) they are being read by hospital leaders and other professionals in the organization, and (2) they articulate specific ways to apply knowledge-based information services to the major functions within the hospital. These chapters are "Education"; "Improving Organizational Performance"; "Leadership"; "Management of Human Resources"; "Management of the Environment of Care"; and "Surveillance, Prevention, and Control of Infection." The standards that these chapters promote present specific opportunities for hospital librarians to apply knowledge-based information resources and service to hospital-wide functions. This article reviews these chapters and discusses the standards that relate to knowledge-based information.

  13. SBexpert users guide (version 2.0): a knowledge-based decision-support system for spruce beetle management.

    Treesearch

    Keith M. Reynolds; Edward H. Holsten

    1997-01-01

    SBexpert version 2.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rufipennis (Kby.)) management developed for use in Microsoft (MS) Windows with the KnowledgePro Windows development language. Version 2.0 is a significant enhancement of version 1.0. The SBexpert users guide provides detailed instructions on the use of...

  14. SBexpert users guide (version 1.0): a knowledge-based decision-support system for spruce beetle management.

    Treesearch

    Keith M. Reynolds; Edward H. Holsten; Richard A. Werner

    1994-01-01

    SBexpert version 1.0 is a knowledge-based decision-support system for spruce beetle (Dendroctonus rutipennis (Kby.)) management developed for use in Microsoft Windows with the KnowledgePro Windows development language. The SBexpert users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main topics (...

  15. On the importance of the distance measures used to train and test knowledge-based potentials for proteins.

    PubMed

    Carlsen, Martin; Koehl, Patrice; Røgen, Peter

    2014-01-01

    Knowledge-based potentials are energy functions derived from the analysis of databases of protein structures and sequences. They can be divided into two classes. Potentials from the first class are based on a direct conversion of the distributions of some geometric properties observed in native protein structures into energy values, while potentials from the second class are trained to mimic quantitatively the geometric differences between incorrectly folded models and native structures. In this paper, we focus on the relationship between energy and geometry when training the second class of knowledge-based potentials. We assume that the difference in energy between a decoy structure and the corresponding native structure is linearly related to the distance between the two structures. We trained two distance-based knowledge-based potentials accordingly, one based on all inter-residue distances (PPD), while the other had the set of all distances filtered to reflect consistency in an ensemble of decoys (PPE). We tested four types of metric to characterize the distance between the decoy and the native structure, two based on extrinsic geometry (RMSD and GTD-TS*), and two based on intrinsic geometry (Q* and MT). The corresponding eight potentials were tested on a large collection of decoy sets. We found that it is usually better to train a potential using an intrinsic distance measure. We also found that PPE outperforms PPD, emphasizing the benefits of capturing consistent information in an ensemble. The relevance of these results for the design of knowledge-based potentials is discussed.

  16. Delivering Electronic Information in a Knowledge-Based Democracy. Summary of Proceedings (Washington, DC, July 14, 1993).

    ERIC Educational Resources Information Center

    Library of Congress, Washington, DC.

    The Library of Congress hosted a 1-day conference, "Delivering Electronic Information in a Knowledge-Based Democracy" to explore the public policy framework essential to creating electronic information resources and making them broadly available. Participants from a variety of sectors contributed to wide-ranging discussions on issues…

  17. Young People's Management of the Transition from Education to Employment in the Knowledge-Based Sector in Shanghai

    ERIC Educational Resources Information Center

    Wang, Qi; Lowe, John

    2011-01-01

    This paper reports on a study of the transition from university to work by students/employees in the complex and rapidly changing socio-economic context of contemporary Shanghai. It aims at understanding how highly educated young people perceive the nature and mode of operation of the newly emerging labour market for knowledge-based jobs, and how…

  18. Development of the Knowledge-Based Standard for the Written Certification Examination of the American Board of Anesthesiology.

    ERIC Educational Resources Information Center

    Slogoff, Stephen; And Others

    1992-01-01

    Application of a knowledge-based standard in evaluating a written certification examination developed by the American Board of Anesthesiology established a standard of 57 percent correct over two years' examinations. This process is recommended for developing mastery-based (rather than normative-based) success criteria for evaluation of medical…

  19. Development of the Knowledge-Based Standard for the Written Certification Examination of the American Board of Anesthesiology.

    ERIC Educational Resources Information Center

    Slogoff, Stephen; And Others

    1992-01-01

    Application of a knowledge-based standard in evaluating a written certification examination developed by the American Board of Anesthesiology established a standard of 57 percent correct over two years' examinations. This process is recommended for developing mastery-based (rather than normative-based) success criteria for evaluation of medical…

  20. A Comparative Analysis of New Governance Instruments in the Transnational Educational Space: A Shift to Knowledge-Based Instruments?

    ERIC Educational Resources Information Center

    Ioannidou, Alexandra

    2007-01-01

    In recent years, the ongoing development towards a knowledge-based society--associated with globalization, an aging population, new technologies and organizational changes--has led to a more intensive analysis of education and learning throughout life with regard to quantitative, qualitative and financial aspects. In this framework, education…

  1. A Knowledge-Based Information Management System for Watershed Analysis in the Pacific Northwest U.S.

    Treesearch

    Keith Reynolds; Patrick Cunningham; Larry Bednar; Michael Saunders; Michael Foster; Richard Olson; Daniel Schmoldt; Donald Latham; Bruce Miller; John Steffenson

    1996-01-01

    The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis. The system includes: (1) a GIS interface that allows users to navigate graphically to specific provinces and watersheds and display a variety of themes (vegetation, streams, roads, topography, etc...

  2. Transformative Pedagogy, Leadership and School Organisation for the Twenty-First-Century Knowledge-Based Economy: The Case of Singapore

    ERIC Educational Resources Information Center

    Dimmock, Clive; Goh, Jonathan W. P.

    2011-01-01

    Singapore has a high performing school system; its students top international tests in maths and science. Yet while the Singapore government cherishes its world class "brand", it realises that in a globally competitive world, its schools need to prepare students for the twenty-first-century knowledge-based economy (KBE). Accordingly,…

  3. Enhancing Student Learning in Knowledge-Based Courses: Integrating Team-Based Learning in Mass Communication Theory Classes

    ERIC Educational Resources Information Center

    Han, Gang; Newell, Jay

    2014-01-01

    This study explores the adoption of the team-based learning (TBL) method in knowledge-based and theory-oriented journalism and mass communication (J&MC) courses. It first reviews the origin and concept of TBL, the relevant theories, and then introduces the TBL method and implementation, including procedures and assessments, employed in an…

  4. Knowledge-based reconstruction for measurement of right ventricular volumes on cardiovascular magnetic resonance images in a mixed population.

    PubMed

    Pieterman, Elise D; Budde, Ricardo P J; Robbers-Visser, Daniëlle; van Domburg, Ron T; Helbing, Willem A

    2017-06-05

    Follow-up of right ventricular performance is important for patients with congenital heart disease. Cardiac magnetic resonance imaging is optimal for this purpose. However, observer-dependency of manual analysis of right ventricular volumes limit its use. Knowledge-based reconstruction is a new semiautomatic analysis tool that uses a database including knowledge of right ventricular shape in various congenital heart diseases. We evaluated whether knowledge-based reconstruction is a good alternative for conventional analysis. To assess the inter- and intra-observer variability and agreement of knowledge-based versus conventional analysis of magnetic resonance right ventricular volumes, analysis was done by two observers in a mixed group of 22 patients with congenital heart disease affecting right ventricular loading conditions (dextro-transposition of the great arteries and right ventricle to pulmonary artery conduit) and a group of 17 healthy children. We used Bland-Altman analysis and coefficient of variation. Comparison between the conventional method and the knowledge-based method showed a systematically higher volume for the latter group. We found an overestimation for end-diastolic volume (bias -40 ± 24 mL, r = .956), end-systolic volume (bias -34 ± 24 mL, r = .943), stroke volume (bias -6 ± 17 mL, r = .735) and an underestimation of ejection fraction (bias 7 ± 7%, r = .671) by knowledge-based reconstruction. The intra-observer variability of knowledge-based reconstruction varied with a coefficient of variation of 9% for end-diastolic volume and 22% for stroke volume. The same trend was noted for inter-observer variability. A systematic difference (overestimation) was noted for right ventricular size as assessed with knowledge-based reconstruction compared with conventional methods for analysis. Observer variability for the new method was comparable to what has been reported for the right ventricle in children and congenital

  5. Signaling network of dendritic cells in response to pathogens: a community-input supported knowledgebase

    PubMed Central

    2010-01-01

    Background Dendritic cells are antigen-presenting cells that play an essential role in linking the innate and adaptive immune systems. Much research has focused on the signaling pathways triggered upon infection of dendritic cells by various pathogens. The high level of activity in the field makes it desirable to have a pathway-based resource to access the information in the literature. Current pathway diagrams lack either comprehensiveness, or an open-access editorial interface. Hence, there is a need for a dependable, expertly curated knowledgebase that integrates this information into a map of signaling networks. Description We have built a detailed diagram of the dendritic cell signaling network, with the goal of providing researchers with a valuable resource and a facile method for community input. Network construction has relied on comprehensive review of the literature and regular updates. The diagram includes detailed depictions of pathways activated downstream of different pathogen recognition receptors such as Toll-like receptors, retinoic acid-inducible gene-I-like receptors, C-type lectin receptors and nucleotide-binding oligomerization domain-like receptors. Initially assembled using CellDesigner software, it provides an annotated graphical representation of interactions stored in Systems Biology Mark-up Language. The network, which comprises 249 nodes and 213 edges, has been web-published through the Biological Pathway Publisher software suite. Nodes are annotated with PubMed references and gene-related information, and linked to a public wiki, providing a discussion forum for updates and corrections. To gain more insight into regulatory patterns of dendritic cell signaling, we analyzed the network using graph-theory methods: bifan, feedforward and multi-input convergence motifs were enriched. This emphasis on activating control mechanisms is consonant with a network that subserves persistent and coordinated responses to pathogen detection

  6. Knowledge-Based Parallel Performance Technology for Scientific Application Competitiveness Final Report

    SciTech Connect

    Malony, Allen D; Shende, Sameer

    2011-08-15

    The primary goal of the University of Oregon's DOE "œcompetitiveness" project was to create performance technology that embodies and supports knowledge of performance data, analysis, and diagnosis in parallel performance problem solving. The target of our development activities was the TAU Performance System and the technology accomplishments reported in this and prior reports have all been incorporated in the TAU open software distribution. In addition, the project has been committed to maintaining strong interactions with the DOE SciDAC Performance Engineering Research Institute (PERI) and Center for Technology for Advanced Scientific Component Software (TASCS). This collaboration has proved valuable for translation of our knowledge-based performance techniques to parallel application development and performance engineering practice. Our outreach has also extended to the DOE Advanced CompuTational Software (ACTS) collection and project. Throughout the project we have participated in the PERI and TASCS meetings, as well as the ACTS annual workshops.

  7. Knowledge-based reasoning in the Paladin tactical decision generation system

    NASA Technical Reports Server (NTRS)

    Chappell, Alan R.

    1993-01-01

    A real-time tactical decision generation system for air combat engagements, Paladin, has been developed. A pilot's job in air combat includes tasks that are largely symbolic. These symbolic tasks are generally performed through the application of experience and training (i.e. knowledge) gathered over years of flying a fighter aircraft. Two such tasks, situation assessment and throttle control, are identified and broken out in Paladin to be handled by specialized knowledge based systems. Knowledge pertaining to these tasks is encoded into rule-bases to provide the foundation for decisions. Paladin uses a custom built inference engine and a partitioned rule-base structure to give these symbolic results in real-time. This paper provides an overview of knowledge-based reasoning systems as a subset of rule-based systems. The knowledge used by Paladin in generating results as well as the system design for real-time execution is discussed.

  8. Knowledge-based model of a glucosyltransferase from the oral bacterial group of mutans streptococci.

    PubMed Central

    Devulapalle, K. S.; Goodman, S. D.; Gao, Q.; Hemsley, A.; Mooser, G.

    1997-01-01

    Mutans streptococci glucosyltransferases catalyze glucosyl transfer from sucrose to a glucan chain. We previously identified an aspartyl residue that participates in stabilizing the glucosyl transition state. The sequence surrounding the aspartate was found to have substantial sequence similarity with members of alpha-amylase family. Because little is known of the protein structure beyond the amino acid sequence, we used a knowledge-based interactive algorithm, MACAW, which provided significant level of homology with alpha-amylases and glucosyltransferase from Streptococcus downei gtfI (GTF). The significance of GTF similarity is underlined by GTF/alpha-amylase residues conserved in all but one alpha-amylase invariant residues. Site-directed mutagenesis of the three GTF catalytic residues are homologous with the alpha-amylase catalytic triad. The glucosyltransferases are members of the 4/7-superfamily that have a (beta/alpha)8-barrel structure and belong to family 13 of the glycohydralases. PMID:9416598

  9. FTDD973: A multimedia knowledge-based system and methodology for operator training and diagnostics

    NASA Technical Reports Server (NTRS)

    Hekmatpour, Amir; Brown, Gary; Brault, Randy; Bowen, Greg

    1993-01-01

    FTDD973 (973 Fabricator Training, Documentation, and Diagnostics) is an interactive multimedia knowledge based system and methodology for computer-aided training and certification of operators, as well as tool and process diagnostics in IBM's CMOS SGP fabrication line (building 973). FTDD973 is an example of what can be achieved with modern multimedia workstations. Knowledge-based systems, hypertext, hypergraphics, high resolution images, audio, motion video, and animation are technologies that in synergy can be far more useful than each by itself. FTDD973's modular and object-oriented architecture is also an example of how improvements in software engineering are finally making it possible to combine many software modules into one application. FTDD973 is developed in ExperMedia/2; and OS/2 multimedia expert system shell for domain experts.

  10. A knowledge-based approach to generating diverse but energetically representative ensembles of ligand conformers

    NASA Astrophysics Data System (ADS)

    Dorfman, Roman J.; Smith, Karl M.; Masek, Brian B.; Clark, Robert D.

    2008-09-01

    This paper describes a new and efficient stochastic conformational sampling method for generating a range of low-energy molecule conformations. Sampling can be tailored to a specific structural domain (e.g., peptides) by extracting torsional profiles from specific datasets and subsequently applying them to target molecules outside the reference set. The programs that handle creation of the knowledge-based torsional profiles and conformer generation per se are separate and so can be used independently or sequentially, depending on the task at hand. The conformational ensembles produced are contrasted with those generated using local minimization approaches. They are also quantitatively compared with a broader range of techniques in terms of speed and the ability to reproduce bound ligand conformations found in complexes with proteins.

  11. A Knowledge-Based System for the Computer Assisted Diagnosis of Endoscopic Images

    NASA Astrophysics Data System (ADS)

    Kage, Andreas; Münzenmayer, Christian; Wittenberg, Thomas

    Due to the actual demographic development the use of Computer-Assisted Diagnosis (CAD) systems becomes a more important part of clinical workflows and clinical decision making. Because changes on the mucosa of the esophagus can indicate the first stage of cancerous developments, there is a large interest to detect and correctly diagnose any such lesion. We present a knowledge-based system which is able to support a physician with the interpretation and diagnosis of endoscopic images of the esophagus. Our system is designed to support the physician directly during the examination of the patient, thus prodving diagnostic assistence at the point of care (POC). Based on an interactively marked region in an endoscopic image of interest, the system provides a diagnostic suggestion, based on an annotated reference image database. Furthermore, using relevant feedback mechanisms, the results can be enhanced interactively.

  12. Cyanobacterial KnowledgeBase (CKB), a Compendium of Cyanobacterial Genomes and Proteomes

    PubMed Central

    Mohandass, Shylajanaciyar; Varadharaj, Sangeetha; Thilagar, Sivasudha; Abdul Kareem, Kaleel Ahamed; Dharmar, Prabaharan; Gopalakrishnan, Subramanian; Lakshmanan, Uma

    2015-01-01

    Cyanobacterial KnowledgeBase (CKB) is a free access database that contains the genomic and proteomic information of 74 fully sequenced cyanobacterial genomes belonging to seven orders. The database also contains tools for sequence analysis. The Species report and the gene report provide details about each species and gene (including sequence features and gene ontology annotations) respectively. The database also includes cyanoBLAST, an advanced tool that facilitates comparative analysis, among cyanobacterial genomes and genomes of E. coli (prokaryote) and Arabidopsis (eukaryote). The database is developed and maintained by the Sub-Distributed Informatics Centre (sponsored by the Department of Biotechnology, Govt. of India) of the National Facility for Marine Cyanobacteria, a facility dedicated to marine cyanobacterial research. CKB is freely available at http://nfmc.res.in/ckb/index.html. PMID:26305368

  13. Knowledge-based software system for fast yield loss detection in a semiconductor fab

    NASA Astrophysics Data System (ADS)

    Martin Santamaria, Victorino; Recio, Miguel; Merino, Miguel A.; Moreno, Julian; Fernandez, Almudena; Gonzalez, Gerardo; Sanchez, Guillermo; Barrios, Luis J.; del Castillo, Maria D.; Lemus, Lissette; Gonzalez, Angel L.

    1997-09-01

    The comparative analysis of process machines in terms of yield related metrics (such as probe and E-Test data, process and particle data,. ..) is a source of a great deal of information for yield improvement. With this aim we published on SPIE's Microelectronic Manufacturing an Advanced Software System to detect machine-related yield limitors using a comparative analysis. This paper presents the natural expansion of that Software System by converting it into a more knowledge-based tool for fast yield loss detection on a semiconductor fab. The new System performs, in an automatic mode, the comparison among machines for every single step selected in the fabrication routing. The detection of statistically significative differences among machines at every step is performed using algorithms that incorporate the overall analysts experience on our fab. The output of the System allows a fast detection and reaction to yield issues, mainly to those that are still on the initial or baseline stages.

  14. Knowledge-based approach to de novo design using reaction vectors.

    PubMed

    Patel, Hina; Bodkin, Michael J; Chen, Beining; Gillet, Valerie J

    2009-05-01

    A knowledge-based approach to the de novo design of synthetically feasible molecules is described. The method is based on reaction vectors which represent the structural changes that take place at the reaction center along with the environment in which the reaction occurs. The reaction vectors are derived automatically from a database of reactions which is not restricted by size or reaction complexity. A structure generation algorithm has been developed whereby reaction vectors can be applied to previously unseen starting materials in order to suggest novel syntheses. The approach has been implemented in KNIME and is validated by reproducing known synthetic routes. We then present applications of the method in different drug design scenarios including lead optimization and library enumeration. The method offers great potential for capturing and using the growing body of data on reactions that is becoming available through electronic laboratory notebooks.

  15. The neXtProt knowledgebase on human proteins: current status

    PubMed Central

    Gaudet, Pascale; Michel, Pierre-André; Zahn-Zabal, Monique; Cusin, Isabelle; Duek, Paula D.; Evalet, Olivier; Gateau, Alain; Gleizes, Anne; Pereira, Mario; Teixeira, Daniel; Zhang, Ying; Lane, Lydie; Bairoch, Amos

    2015-01-01

    neXtProt (http://www.nextprot.org) is a human protein-centric knowledgebase developed at the SIB Swiss Institute of Bioinformatics. Focused solely on human proteins, neXtProt aims to provide a state of the art resource for the representation of human biology by capturing a wide range of data, precise annotations, fully traceable data provenance and a web interface which enables researchers to find and view information in a comprehensive manner. Since the introductory neXtProt publication, significant advances have been made on three main aspects: the representation of proteomics data, an extended representation of human variants and the development of an advanced search capability built around semantic technologies. These changes are presented in the current neXtProt update. PMID:25593349

  16. Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method

    NASA Astrophysics Data System (ADS)

    Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi

    In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

  17. A Knowledge-based Evolution Algorithm approach to political districting problem

    NASA Astrophysics Data System (ADS)

    Chou, Chung-I.

    2011-01-01

    The political districting problem is to study how to partition a comparatively large zone into many minor electoral districts. In our previously works, we have mapped this political problem onto a q-state Potts model system by using statistical physics methods. The political constraints (such as contiguity, population equality, etc.) are transformed to an energy function with interactions between sites or external fields acting on the system. Several optimization algorithms such as simulated annealing method and genetic algorithm have been applied to this problem. In this report, we will show how to apply the Knowledge-based Evolution Algorithm (KEA) to the problem. Our test objects include two real cities (Taipei and Kaohsiung) and the simulated cities. The results showed the KEA can reach the same minimum which has been found by using other methods in each test case.

  18. Knowledge-Based Manufacturing and Structural Design for a High Speed Civil Transport

    NASA Technical Reports Server (NTRS)

    Marx, William J.; Mavris, Dimitri N.; Schrage, Daniel P.

    1994-01-01

    The aerospace industry is currently addressing the problem of integrating manufacturing and design. To address the difficulties associated with using many conventional procedural techniques and algorithms, one feasible way to integrate the two concepts is with the development of an appropriate Knowledge-Based System (KBS). The authors present their reasons for selecting a KBS to integrate design and manufacturing. A methodology for an aircraft producibility assessment is proposed, utilizing a KBS for manufacturing process selection, that addresses both procedural and heuristic aspects of designing and manufacturing of a High Speed Civil Transport (HSCT) wing. A cost model is discussed that would allow system level trades utilizing information describing the material characteristics as well as the manufacturing process selections. Statements of future work conclude the paper.

  19. GARN: Sampling RNA 3D Structure Space with Game Theory and Knowledge-Based Scoring Strategies.

    PubMed

    Boudard, Mélanie; Bernauer, Julie; Barth, Dominique; Cohen, Johanne; Denise, Alain

    2015-01-01

    Cellular processes involve large numbers of RNA molecules. The functions of these RNA molecules and their binding to molecular machines are highly dependent on their 3D structures. One of the key challenges in RNA structure prediction and modeling is predicting the spatial arrangement of the various structural elements of RNA. As RNA folding is generally hierarchical, methods involving coarse-grained models hold great promise for this purpose. We present here a novel coarse-grained method for sampling, based on game theory and knowledge-based potentials. This strategy, GARN (Game Algorithm for RNa sampling), is often much faster than previously described techniques and generates large sets of solutions closely resembling the native structure. GARN is thus a suitable starting point for the molecular modeling of large RNAs, particularly those with experimental constraints. GARN is available from: http://garn.lri.fr/.

  20. KIPSE1: A Knowledge-based Interactive Problem Solving Environment for data estimation and pattern classification

    NASA Technical Reports Server (NTRS)

    Han, Chia Yung; Wan, Liqun; Wee, William G.

    1990-01-01

    A knowledge-based interactive problem solving environment called KIPSE1 is presented. The KIPSE1 is a system built on a commercial expert system shell, the KEE system. This environment gives user capability to carry out exploratory data analysis and pattern classification tasks. A good solution often consists of a sequence of steps with a set of methods used at each step. In KIPSE1, solution is represented in the form of a decision tree and each node of the solution tree represents a partial solution to the problem. Many methodologies are provided at each node to the user such that the user can interactively select the method and data sets to test and subsequently examine the results. Otherwise, users are allowed to make decisions at various stages of problem solving to subdivide the problem into smaller subproblems such that a large problem can be handled and a better solution can be found.

  1. A knowledge-based expert system for managing underground coal mines in the US

    SciTech Connect

    Grayson, R.L.; Yuan, S.; Dean, J.M.; Reddy, N.P. )

    1990-07-01

    Research by the U.S. Bureau of Mines (BOM) on the reasons why some mines are more productive than others has revealed the importance of good mine management practices. The Mine Management Support System is being developed, under the cosponsorship of the BOM and the West Virginia Energy and Water Research Center, as a knowledge-based expert system for better management of underground coal mines. Concentrating on capturing the complex body of knowledge needed to enhance efficient management of a mine, it will encompass information and preferred rules on work scheduling, work practices, regulations impinging on the accomplishment of work, responses to operating problems, and the labor-management work agreement. In this paper different components of the mine system, modeled using an object-oriented layering technique, will be displayed graphically to aid in coordinating work plans, and to present locations of equipment, supplies, and proposed subsystem components.

  2. Using fuzzy logic to integrate neural networks and knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Yen, John

    1991-01-01

    Outlined here is a novel hybrid architecture that uses fuzzy logic to integrate neural networks and knowledge-based systems. The author's approach offers important synergistic benefits to neural nets, approximate reasoning, and symbolic processing. Fuzzy inference rules extend symbolic systems with approximate reasoning capabilities, which are used for integrating and interpreting the outputs of neural networks. The symbolic system captures meta-level information about neural networks and defines its interaction with neural networks through a set of control tasks. Fuzzy action rules provide a robust mechanism for recognizing the situations in which neural networks require certain control actions. The neural nets, on the other hand, offer flexible classification and adaptive learning capabilities, which are crucial for dynamic and noisy environments. By combining neural nets and symbolic systems at their system levels through the use of fuzzy logic, the author's approach alleviates current difficulties in reconciling differences between low-level data processing mechanisms of neural nets and artificial intelligence systems.

  3. Postponing aging and prolonging life expectancy with the knowledge-based economy.

    PubMed

    Kristjuhan, Ulo

    2012-04-01

    People are interested in the aging phenomenon and hope that scientists are doing as much as they can to solve the mysteries of aging. However, this is not the case. A lot of knowledge is produced for local interests in curing specific disorders; aging is studied much less. Today's economy is undergoing a transition to a knowledge-based economy. Knowledge of aging should be integrated into the economies of contemporary societies. Aging research and intervention can ensure better health, primarily among middle-aged and older people, and prolong life. There are many reasons why postponing aging and rejuvenation research is not as widespread as it should be. Developed countries should create economic stimuli for such studies and intervention.

  4. Optimization of knowledge-based systems and expert system building tools

    NASA Technical Reports Server (NTRS)

    Yasuda, Phyllis; Mckellar, Donald

    1993-01-01

    The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

  5. Analysis of knowledge-based expert systems as tools for construction design

    NASA Astrophysics Data System (ADS)

    Cole, Arthur N.

    1991-03-01

    Because construction costs are continuously rising, Congress mandated that those within the respective branches of military service who are responsible for planning and executing construction programs develop policies and procedures that ensure that the individual projects are designed, bid, and constructed as rapidly as possible. This requires an approach that demands maximum efficiency from the design process. Reviews are necessary to ensure that designs meet all requirements, but the reviews themselves must be conducted in the least amount of time so as to preclude delays. Design tools that increases efficiency are knowledge-based expert systems which are interactive computer programs that incorporate judgement, experience, rules of thumb, and other expertise, so as to provide knowledgeable advice about a specific domain. They mimic the thought process employed by a human expert in solving a problem.

  6. Structural topology design of container ship based on knowledge-based engineering and level set method

    NASA Astrophysics Data System (ADS)

    Cui, Jin-ju; Wang, De-yu; Shi, Qi-qi

    2015-06-01

    Knowledge-Based Engineering (KBE) is introduced into the ship structural design in this paper. From the implementation of KBE, the design solutions for both Rules Design Method (RDM) and Interpolation Design Method (IDM) are generated. The corresponding Finite Element (FE) models are generated. Topological design of the longitudinal structures is studied where the Gaussian Process (GP) is employed to build the surrogate model for FE analysis. Multi-objective optimization methods inspired by Pareto Front are used to reduce the design tank weight and outer surface area simultaneously. Additionally, an enhanced Level Set Method (LSM) which employs implicit algorithm is applied to the topological design of typical bracket plate which is used extensively in ship structures. Two different sets of boundary conditions are considered. The proposed methods show satisfactory efficiency and accuracy.

  7. Geomorphological feature extraction from a digital elevation model through fuzzy knowledge-based classification

    NASA Astrophysics Data System (ADS)

    Argialas, Demetre P.; Tzotsos, Angelos

    2003-03-01

    The objective of this research was the investigation of advanced image analysis methods for geomorphological mapping. Methods employed included multiresolution segmentation of the Digital Elevation Model (DEM) GTOPO30 and fuzzy knowledge based classification of the segmented DEM into three geomorphological classes: mountain ranges, piedmonts and basins. The study area was a segment of the Basin and Range Physiographic Province in Nevada, USA. The implementation was made in eCognition. In particular, the segmentation of GTOPO30 resulted into primitive objects. The knowledge-based classification of the primitive objects based on their elevation and shape parameters, resulted in the extraction of the geomorphological features. The resulted boundaries in comparison to those by previous studies were found satisfactory. It is concluded that geomorphological feature extraction can be carried out through fuzzy knowledge based classification as implemented in eCognition.

  8. A development environment for knowledge-based medical applications on the World-Wide Web.

    PubMed

    Riva, A; Bellazzi, R; Lanzola, G; Stefanelli, M

    1998-11-01

    The World-Wide Web (WWW) is increasingly being used as a platform to develop distributed applications, particularly in contexts, such as medical ones, where high usability and availability are required. In this paper we propose a methodology for the development of knowledge-based medical applications on the web, based on the use of an explicit domain ontology to automatically generate parts of the system. We describe a development environment, centred on the LISPWEB Common Lisp HTTP server, that supports this methodology, and we show how it facilitates the creation of complex web-based applications, by overcoming the limitations that normally affect the adequacy of the web for this purpose. Finally, we present an outline of a system for the management of diabetic patients built using the LISPWEB environment.

  9. Collaborative development of knowledge-based support systems: a case study.

    PubMed

    Lindgren, Helena; Winnberg, Patrik J; Yan, Chunli

    2012-01-01

    We investigate a user-driven collaborative knowledge engineering and interaction design process. The outcome is a knowledge-based support application tailored to physicians in the local dementia care community. The activity is organized as a part of a collaborative effort between different organizations to develop their local clinical practice. Six local practitioners used the generic decision-support prototype system DMSS-R developed for the dementia domain during a period and participated in evaluations and re-design. Additional two local domain experts and a domain expert external to the local community modeled the content and design of DMSS-R by using the modeling system ACKTUS. Obstacles and success factors occurring when enabling the end-users to design their own tools are detected and interpreted using a proposed framework for improving care through the use of clinical guidelines. The results are discussed.

  10. Knowledge-Based Analysis And Understanding Of 3D Medical Images

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.; Juvvadi, Sridhar

    1988-06-01

    The anatomical three-dimensional (3D) medical imaging modalities, such as X-ray CT and MRI, have been well recognized in the diagnostic radiology for several years while the nuclear medicine modalities, such as PET, have just started making a strong impact through functional imaging. Though PET images provide the functional information about the human organs, they are hard to interpret because of the lack of anatomical information. Our objective is to develop a knowledge-based biomedical image analysis system which can interpret the anatomical images (such as CT). The anatomical information thus obtained can then be used in analyzing PET images of the same patient. This will not only help in interpreting PET images but it will also provide a means of studying the correlation between the anatomical and functional imaging. This paper presents the preliminary results of the knowledge based biomedical image analysis system for interpreting CT images of the chest.

  11. Knowledge-based potentials in bioinformatics: From a physicist’s viewpoint

    NASA Astrophysics Data System (ADS)

    Zheng, Wei-Mou

    2015-12-01

    Biological raw data are growing exponentially, providing a large amount of information on what life is. It is believed that potential functions and the rules governing protein behaviors can be revealed from analysis on known native structures of proteins. Many knowledge-based potentials for proteins have been proposed. Contrary to most existing review articles which mainly describe technical details and applications of various potential models, the main foci for the discussion here are ideas and concepts involving the construction of potentials, including the relation between free energy and energy, the additivity of potentials of mean force and some key issues in potential construction. Sequence analysis is briefly viewed from an energetic viewpoint. Project supported in part by the National Natural Science Foundation of China (Grant Nos. 11175224 and 11121403).

  12. The neXtProt knowledgebase on human proteins: 2017 update

    PubMed Central

    Gaudet, Pascale; Michel, Pierre-André; Zahn-Zabal, Monique; Britan, Aurore; Cusin, Isabelle; Domagalski, Marcin; Duek, Paula D.; Gateau, Alain; Gleizes, Anne; Hinard, Valérie; Rech de Laval, Valentine; Lin, JinJin; Nikitin, Frederic; Schaeffer, Mathieu; Teixeira, Daniel; Lane, Lydie; Bairoch, Amos

    2017-01-01

    The neXtProt human protein knowledgebase (https://www.nextprot.org) continues to add new content and tools, with a focus on proteomics and genetic variation data. neXtProt now has proteomics data for over 85% of the human proteins, as well as new tools tailored to the proteomics community. Moreover, the neXtProt release 2016-08-25 includes over 8000 phenotypic observations for over 4000 variations in a number of genes involved in hereditary cancers and channelopathies. These changes are presented in the current neXtProt update. All of the neXtProt data are available via our user interface and FTP site. We also provide an API access and a SPARQL endpoint for more technical applications. PMID:27899619

  13. Knowledge-based automatic recognition technology of radome from infrared images

    NASA Astrophysics Data System (ADS)

    Wang, Xiao-jian; Ma, Ling; Fang, Xiao; Chen, Lei; Lu, Hong-bin

    2009-07-01

    In this paper, a kind of knowledge-based automatic target recognition (ATR) technology of radome from infrared image is studied. The circular imaging of radome is used as the characteristic distinguished from background to realize target recognition. For the characteristic of low contrast of infrared image, brightness transformation is used to preliminarily enhance the contrast of the original image. In the light of the fact that target background outline statistically takes on vertical and horizontal directivity, a kind of revised Sobel operator with direction of 45°and 135°is adopted to detect edge feature so that background noise is effectively suppressed. To reduce the error ratio of target recognition from single frame image, the method to inspect the relativity of target recognition results of successive frames is adopted. The performance of the algorithm is tested using actually taken infrared radome images, and the right recognition ratio is around 90%, which turns out that this technology is feasible.

  14. Building organisational cyber resilience: A strategic knowledge-based view of cyber security management.

    PubMed

    Ferdinand, Jason

    The concept of cyber resilience has emerged in recent years in response to the recognition that cyber security is more than just risk management. Cyber resilience is the goal of organisations, institutions and governments across the world and yet the emerging literature is somewhat fragmented due to the lack of a common approach to the subject. This limits the possibility of effective collaboration across public, private and governmental actors in their efforts to build and maintain cyber resilience. In response to this limitation, and to calls for a more strategically focused approach, this paper offers a knowledge-based view of cyber security management that explains how an organisation can build, assess, and maintain cyber resilience.

  15. Knowledge-based assistance for science visualization and analysis using large distributed databases

    NASA Technical Reports Server (NTRS)

    Handley, Thomas H., Jr.; Jacobson, Allan S.; Doyle, Richard J.; Collins, Donald J.

    1993-01-01

    Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scalable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded with this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on concept called the DataHub. With the DataHub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (address, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

  16. Knowledge-based assistance for science visualization and analysis using large distributed databases

    NASA Technical Reports Server (NTRS)

    Handley, Thomas H., Jr.; Jacobson, Allan S.; Doyle, Richard J.; Collins, Donald J.

    1992-01-01

    Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scaleable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on the concept called the Data Hub. With the Data Hub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (access, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

  17. Comparative development of knowledge-based bioeconomy in the European Union and Turkey.

    PubMed

    Celikkanat Ozan, Didem; Baran, Yusuf

    2014-09-01

    Biotechnology, defined as the technological application that uses biological systems and living organisms, or their derivatives, to create or modify diverse products or processes, is widely used for healthcare, agricultural and environmental applications. The continuity in industrial applications of biotechnology enables the rise and development of the bioeconomy concept. Bioeconomy, including all applications of biotechnology, is defined as translation of knowledge received from life sciences into new, sustainable, environment friendly and competitive products. With the advanced research and eco-efficient processes in the scope of bioeconomy, more healthy and sustainable life is promised. Knowledge-based bioeconomy with its economic, social and environmental potential has already been brought to the research agendas of European Union (EU) countries. The aim of this study is to summarize the development of knowledge-based bioeconomy in EU countries and to evaluate Turkey's current situation compared to them. EU-funded biotechnology research projects under FP6 and FP7 and nationally-funded biotechnology projects under The Scientific and Technological Research Council of Turkey (TUBITAK) Academic Research Funding Program Directorate (ARDEB) and Technology and Innovation Funding Programs Directorate (TEYDEB) were examined. In the context of this study, the main research areas and subfields which have been funded, the budget spent and the number of projects funded since 2003 both nationally and EU-wide and the gaps and overlapping topics were analyzed. In consideration of the results, detailed suggestions for Turkey have been proposed. The research results are expected to be used as a roadmap for coordinating the stakeholders of bioeconomy and integrating Turkish Research Areas into European Research Areas.

  18. Knowledge-based assistance for science visualization and analysis using large distributed databases

    NASA Technical Reports Server (NTRS)

    Handley, Thomas H., Jr.; Jacobson, Allan S.; Doyle, Richard J.; Collins, Donald J.

    1992-01-01

    Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scaleable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on the concept called the Data Hub. With the Data Hub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (access, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

  19. Knowledge-based assistance for science visualization and analysis using large distributed databases

    NASA Technical Reports Server (NTRS)

    Handley, Thomas H., Jr.; Jacobson, Allan S.; Doyle, Richard J.; Collins, Donald J.

    1993-01-01

    Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scalable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded with this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on concept called the DataHub. With the DataHub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (address, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

  20. A knowledge-based imaging informatics approach to managing patients treated with proton beam therapy

    NASA Astrophysics Data System (ADS)

    Liu, B. J.; Huang, H. K.; Law, M.; Le, Anh; Documet, Jorge; Gertych, Arek

    2007-03-01

    Last year we presented work on an imaging informatics approach towards developing quantitative knowledge and tools based on standardized DICOM-RT objects for Image-Guided Radiation Therapy. In this paper, we have extended this methodology to perform knowledge-based medical imaging informatics research on specific clinical scenarios where brain tumor patients are treated with Proton Beam Therapy (PT). PT utilizes energized charged particles, protons, to deliver dose to the target region. Protons are energized to specific velocities which determine where they will deposit maximum energy within the body to destroy cancerous cells. Treatment Planning is similar in workflow to traditional Radiation Therapy methods such as Intensity-Modulated Radiation Therapy (IMRT) which utilizes a priori knowledge to drive the treatment plan in an inverse manner. In March 2006, two new RT Objects were drafted in a DICOM-RT Supplement 102 specifically for Ion Therapy which includes Proton Therapy. The standardization of DICOM-RT-ION objects and the development of a knowledge base as well as decision-support tools that can be add-on features to the ePR DICOM-RT system were researched. We have developed a methodology to perform knowledge-based medical imaging informatics research on specific clinical scenarios. This methodology can be used to extend to Proton Therapy and the development of future clinical decision-making scenarios during the course of the patient's treatment that utilize "inverse treatment planning". In this paper, we present the initial steps toward extending this methodology for PT and lay the foundation for development of future decision-support tools tailored to cancer patients treated with PT. By integrating decision-support knowledge and tools designed to assist in the decision-making process, a new and improved "knowledge-enhanced treatment planning" approach can be realized.

  1. A framework for the knowledge-based interpretation of laboratory data in intensive care units using deductive database technology.

    PubMed Central

    Schwaiger, J.; Haller, M.; Finsterer, U.

    1992-01-01

    In co-operation with the Institute of Anaesthesiology of the Ludwig-Maximilians-University in Munich a computer-based system for the analysis and interpretation of renal function, fluid and electrolyte metabolism of critical care patients has been developed. This paper focuses on the requirements and implementation aspects of the knowledge-based interpretation for this particular system. Objective of the proposed approach is, to transform an enormous--and constantly increasing--amount of raw data available in modern intensive care units (ICUs) into relevant, patient-oriented information, which is easy to understand by the medical staff. The essential features of a knowledge-based system at an ICU are outlined. A system is described where these features are realized using deductive database technology as a specification paradigm and extended relational databases as an implementation platform. The integration into the hospital information system is highlighted. PMID:1482854

  2. Integrating a modern knowledge-based system architecture with a legacy VA database: the ATHENA and EON projects at Stanford.

    PubMed

    Advani, A; Tu, S; O'Connor, M; Coleman, R; Goldstein, M K; Musen, M

    1999-01-01

    We present a methodology and database mediator tool for integrating modern knowledge-based systems, such as the Stanford EON architecture for automated guideline-based decision-support, with legacy databases, such as the Veterans Health Information Systems & Technology Architecture (VISTA) systems, which are used nation-wide. Specifically, we discuss designs for database integration in ATHENA, a system for hypertension care based on EON, at the VA Palo Alto Health Care System. We describe a new database mediator that affords the EON system both physical and logical data independence from the legacy VA database. We found that to achieve our design goals, the mediator requires two separate mapping levels and must itself involve a knowledge-based component.

  3. A framework for the knowledge-based interpretation of laboratory data in intensive care units using deductive database technology.

    PubMed

    Schwaiger, J; Haller, M; Finsterer, U

    1992-01-01

    In co-operation with the Institute of Anaesthesiology of the Ludwig-Maximilians-University in Munich a computer-based system for the analysis and interpretation of renal function, fluid and electrolyte metabolism of critical care patients has been developed. This paper focuses on the requirements and implementation aspects of the knowledge-based interpretation for this particular system. Objective of the proposed approach is, to transform an enormous--and constantly increasing--amount of raw data available in modern intensive care units (ICUs) into relevant, patient-oriented information, which is easy to understand by the medical staff. The essential features of a knowledge-based system at an ICU are outlined. A system is described where these features are realized using deductive database technology as a specification paradigm and extended relational databases as an implementation platform. The integration into the hospital information system is highlighted.

  4. The role of textual semantic constraints in knowledge-based inference generation during reading comprehension: A computational approach.

    PubMed

    Yeari, Menahem; van den Broek, Paul

    2015-01-01

    The present research adopted a computational approach to explore the extent to which the semantic content of texts constrains the activation of knowledge-based inferences. Specifically, we examined whether textual semantic constraints (TSC) can explain (1) the activation of predictive inferences, (2) the activation of bridging inferences and (3) the higher prevalence of the activation of bridging inferences compared to predictive inferences. To examine these hypotheses, we computed the strength of semantic associations between texts and probe items as presented to human readers in previous behavioural studies, using the Latent Semantic Analysis (LSA) algorithm. We tested whether stronger semantic associations are observed for inferred items compared to control items. Our results show that in 15 out of 17 planned comparisons, the computed strength of semantic associations successfully simulated the activation of inferences. These findings suggest that TSC play a central role in the activation of knowledge-based inferences.

  5. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer

    PubMed Central

    Griffith, Malachi; Spies, Nicholas C; Krysiak, Kilannin; McMichael, Joshua F; Coffman, Adam C; Danos, Arpad M; Ainscough, Benjamin J; Ramirez, Cody A; Rieke, Damian T; Kujan, Lynzey; Barnell, Erica K; Wagner, Alex H; Skidmore, Zachary L; Wollam, Amber; Liu, Connor J; Jones, Martin R; Bilski, Rachel L; Lesurf, Robert; Feng, Yan-Yang; Shah, Nakul M; Bonakdar, Melika; Trani, Lee; Matlock, Matthew; Ramu, Avinash; Campbell, Katie M; Spies, Gregory C; Graubert, Aaron P; Gangavarapu, Karthik; Eldred, James M; Larson, David E; Walker, Jason R; Good, Benjamin M; Wu, Chunlei; Su, Andrew I; Dienstmann, Rodrigo; Margolin, Adam A; Tamborero, David; Lopez-Bigas, Nuria; Jones, Steven J M; Bose, Ron; Spencer, David H; Wartman, Lukas D; Wilson, Richard K; Mardis, Elaine R; Griffith, Obi L

    2017-01-01

    CIViC is an expert-crowdsourced knowledgebase for Clinical Interpretation of Variants in Cancer describing the therapeutic, prognostic, diagnostic and predisposing relevance of inherited and somatic variants of all types. CIViC is committed to open-source code, open-access content, public application programming interfaces (APIs) and provenance of supporting evidence to allow for the transparent creation of current and accurate variant interpretations for use in cancer precision medicine. PMID:28138153

  6. Knowledge-based personalized search engine for the Web-based Human Musculoskeletal System Resources (HMSR) in biomechanics.

    PubMed

    Dao, Tien Tuan; Hoang, Tuan Nha; Ta, Xuan Hien; Tho, Marie Christine Ho Ba

    2013-02-01

    Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical processes, pathological knowledge and practical expertise. In this present work, an advanced knowledge-based personalized search engine was developed. Our search engine was based on a client-server multi-layer multi-agent architecture and the principle of semantic web services to acquire dynamically accurate and reliable HMSR information by a semantic processing and visualization approach. A security-enhanced mechanism was applied to protect the medical information. A multi-agent crawler was implemented to develop a content-based database of HMSR information. A new semantic-based PageRank score with related mathematical formulas were also defined and implemented. As the results, semantic web service descriptions were presented in OWL, WSDL and OWL-S formats. Operational scenarios with related web-based interfaces for personal computers and mobile devices were presented and analyzed. Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized search engine. In fact, our knowledge-based personalized search engine allows different users such as orthopedic patient and experts or healthcare system managers or medical students to access remotely into useful, accurate, reliable and good-quality HMSR information for their learning and medical purposes. Copyright © 2012 Elsevier Inc. All rights reserved.

  7. Analysis of Defects in Trouser Manufacturing: Development of a Knowledge-Based Framework. Volume 1. Final Technical Report

    DTIC Science & Technology

    1992-02-28

    apparel manufacturing. Two knowledge-based software systems--FDAS (Fabric Defects Analysis System) and SDAS (Sewing Defects Analysis System) -- have been...sewing, finishing and packing departments of an apparel plant producing denim trousers. Based on the visual description of the defect in the fabric...type, orientation and mode of repetition of the defect), FDAS identifies the defect and suggest possible causes and remedies. Apparel Quality Control

  8. GENESIS, a knowledge-based genetic engineering simulation system for representation of genetic data and experiment planning.

    PubMed Central

    Friedland, P; Kedes, L; Brutlag, D; Iwasaki, Y; Bach, R

    1982-01-01

    We have built a knowledge-based genetic engineering simulation system-- GENESIS-- capable of representing both domain-specific and general knowledge. Information is stored within a hierarchically-organized framework composed of structures called units. A series of sophisticated editors enables no-computer specialist molecular geneticists to construct a knowledge base through direct interaction with the computer. Three types of knowledge specific to the domain of molecular genetics, MAPS, sequences and RULES are discussed in detail with examples. PMID:6950365

  9. Evaluation of a Knowledge-Based Planning Solution for Head and Neck Cancer

    SciTech Connect

    Tol, Jim P. Delaney, Alexander R.; Dahele, Max; Slotman, Ben J.; Verbakel, Wilko F.A.R.

    2015-03-01

    Purpose: Automated and knowledge-based planning techniques aim to reduce variations in plan quality. RapidPlan uses a library consisting of different patient plans to make a model that can predict achievable dose-volume histograms (DVHs) for new patients and uses those models for setting optimization objectives. We benchmarked RapidPlan versus clinical plans for 2 patient groups, using 3 different libraries. Methods and Materials: Volumetric modulated arc therapy plans of 60 recent head and neck cancer patients that included sparing of the salivary glands, swallowing muscles, and oral cavity were evenly divided between 2 models, Model{sub 30A} and Model{sub 30B}, and were combined in a third model, Model{sub 60}. Knowledge-based plans were created for 2 evaluation groups: evaluation group 1 (EG1), consisting of 15 recent patients, and evaluation group 2 (EG2), consisting of 15 older patients in whom only the salivary glands were spared. RapidPlan results were compared with clinical plans (CP) for boost and/or elective planning target volume homogeneity index, using HI{sub B}/HI{sub E} = 100 × (D2% − D98%)/D50%, and mean dose to composite salivary glands, swallowing muscles, and oral cavity (D{sub sal}, D{sub swal}, and D{sub oc}, respectively). Results: For EG1, RapidPlan improved HI{sub B} and HI{sub E} values compared with CP by 1.0% to 1.3% and 1.0% to 0.6%, respectively. Comparable D{sub sal} and D{sub swal} values were seen in Model{sub 30A}, Model{sub 30B}, and Model{sub 60}, decreasing by an average of 0.1, 1.0, and 0.8 Gy and 4.8, 3.7, and 4.4 Gy, respectively. However, differences were noted between individual organs at risk (OARs), with Model{sub 30B} increasing D{sub oc} by 0.1, 3.2, and 2.8 Gy compared with CP, Model{sub 30A}, and Model{sub 60}. Plan quality was less consistent when the patient was flagged as an outlier. For EG2, RapidPlan decreased D{sub sal} by 4.1 to 4.9 Gy on average, whereas HI{sub B} and HI{sub E} decreased by 1.1% to

  10. On-the-spot lung cancer differential diagnosis by label-free, molecular vibrational imaging and knowledge-based classification.

    PubMed

    Gao, Liang; Li, Fuhai; Thrall, Michael J; Yang, Yaliang; Xing, Jiong; Hammoudi, Ahmad A; Zhao, Hong; Massoud, Yehia; Cagle, Philip T; Fan, Yubo; Wong, Kelvin K; Wang, Zhiyong; Wong, Stephen T C

    2011-09-01

    We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.

  11. On-the-spot lung cancer differential diagnosis by label-free, molecular vibrational imaging and knowledge-based classification

    NASA Astrophysics Data System (ADS)

    Gao, Liang; Li, Fuhai; Thrall, Michael J.; Yang, Yaliang; Xing, Jiong; Hammoudi, Ahmad A.; Zhao, Hong; Massoud, Yehia; Cagle, Philip T.; Fan, Yubo; Wong, Kelvin K.; Wang, Zhiyong; Wong, Stephen T. C.

    2011-09-01

    We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.

  12. An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

    PubMed Central

    Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

    2012-01-01

    This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions. PMID:23112650

  13. Shewanella knowledgebase: integration of the experimental data and computational predictions suggests a biological role for transcription of intergenic regions

    SciTech Connect

    Karpinets, Tatiana V; Romine, Margaret; Schmoyer, Denise D; Kora, Guruprasad H; Syed, Mustafa H; Leuze, Michael Rex; Serres, Margrethe H.; Park, Byung; Uberbacher, Edward C

    2010-01-01

    Shewanellae are facultative gamma-proteobacteria whose remarkable respiratory versatility has resulted in interest in their utility for bioremediation of heavy metals and radionuclides and for energy generation in microbial fuel cells. Extensive experimental efforts over the last several years and the availability of 21 sequenced Shewanella genomes made it possible to collect and integrate a wealth of information on the genus into one public resource providing new avenues for making biological discoveries and for developing a system level understanding of the cellular processes. The Shewanella knowledgebase was established in 2005 to provide a framework for integrated genome-based studies on Shewanella ecophysiology. The present version of the knowledgebase provides access to a diverse set of experimental and genomic data along with tools for curation of genome annotations and visualization and integration of genomic data with experimental data. As a demonstration of the utility of this resource, we examined a single microarray data set from Shewanella oneidensis MR-1 for new insights into regulatory processes. The integrated analysis of the data predicted a new type of bacterial transcriptional regulation involving co-transcription of the intergenic region with the downstream gene and suggested a biological role for co-transcription that likely prevents the binding of a regulator of the upstream gene to the regulator binding site located in the intergenic region. Database URL: http://shewanella-knowledgebase.org:8080/Shewanella/ or http://spruce.ornl.gov:8080/Shewanella/

  14. Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy

    SciTech Connect

    Shiraishi, Satomi; Moore, Kevin L.

    2016-01-15

    Purpose: To demonstrate knowledge-based 3D dose prediction for external beam radiotherapy. Methods: Using previously treated plans as training data, an artificial neural network (ANN) was trained to predict a dose matrix based on patient-specific geometric and planning parameters, such as the closest distance (r) to planning target volume (PTV) and organ-at-risks (OARs). Twenty-three prostate and 43 stereotactic radiosurgery/radiotherapy (SRS/SRT) cases with at least one nearby OAR were studied. All were planned with volumetric-modulated arc therapy to prescription doses of 81 Gy for prostate and 12–30 Gy for SRS. Using these clinically approved plans, ANNs were trained to predict dose matrix and the predictive accuracy was evaluated using the dose difference between the clinical plan and prediction, δD = D{sub clin} − D{sub pred}. The mean (〈δD{sub r}〉), standard deviation (σ{sub δD{sub r}}), and their interquartile range (IQR) for the training plans were evaluated at a 2–3 mm interval from the PTV boundary (r{sub PTV}) to assess prediction bias and precision. Initially, unfiltered models which were trained using all plans in the cohorts were created for each treatment site. The models predict approximately the average quality of OAR sparing. Emphasizing a subset of plans that exhibited superior to the average OAR sparing during training, refined models were created to predict high-quality rectum sparing for prostate and brainstem sparing for SRS. Using the refined model, potentially suboptimal plans were identified where the model predicted further sparing of the OARs was achievable. Replans were performed to test if the OAR sparing could be improved as predicted by the model. Results: The refined models demonstrated highly accurate dose distribution prediction. For prostate cases, the average prediction bias for all voxels irrespective of organ delineation ranged from −1% to 0% with maximum IQR of 3% over r{sub PTV} ∈ [ − 6, 30] mm. The

  15. Design of Composite Structures Using Knowledge-Based and Case Based Reasoning

    NASA Technical Reports Server (NTRS)

    Lambright, Jonathan Paul

    1996-01-01

    A method of using knowledge based and case based reasoning to assist designers during conceptual design tasks of composite structures was proposed. The cooperative use of heuristics, procedural knowledge, and previous similar design cases suggests a potential reduction in design cycle time and ultimately product lead time. The hypothesis of this work is that the design process of composite structures can be improved by using Case-Based Reasoning (CBR) and Knowledge-Based (KB) reasoning in the early design stages. The technique of using knowledge-based and case-based reasoning facilitates the gathering of disparate information into one location that is easily and readily available. The method suggests that the inclusion of downstream life-cycle issues into the conceptual design phase reduces potential of defective, and sub-optimal composite structures. Three industry experts were interviewed extensively. The experts provided design rules, previous design cases, and test problems. A Knowledge Based Reasoning system was developed using the CLIPS (C Language Interpretive Procedural System) environment and a Case Based Reasoning System was developed using the Design Memory Utility For Sharing Experiences (MUSE) xviii environment. A Design Characteristic State (DCS) was used to document the design specifications, constraints, and problem areas using attribute-value pair relationships. The DCS provided consistent design information between the knowledge base and case base. Results indicated that the use of knowledge based and case based reasoning provided a robust design environment for composite structures. The knowledge base provided design guidance from well defined rules and procedural knowledge. The case base provided suggestions on design and manufacturing techniques based on previous similar designs and warnings of potential problems and pitfalls. The case base complemented the knowledge base and extended the problem solving capability beyond the existence of

  16. Design of Composite Structures Using Knowledge-Based and Case Based Reasoning

    NASA Technical Reports Server (NTRS)

    Lambright, Jonathan Paul

    1996-01-01

    A method of using knowledge based and case based reasoning to assist designers during conceptual design tasks of composite structures was proposed. The cooperative use of heuristics, procedural knowledge, and previous similar design cases suggests a potential reduction in design cycle time and ultimately product lead time. The hypothesis of this work is that the design process of composite structures can be improved by using Case-Based Reasoning (CBR) and Knowledge-Based (KB) reasoning in the early design stages. The technique of using knowledge-based and case-based reasoning facilitates the gathering of disparate information into one location that is easily and readily available. The method suggests that the inclusion of downstream life-cycle issues into the conceptual design phase reduces potential of defective, and sub-optimal composite structures. Three industry experts were interviewed extensively. The experts provided design rules, previous design cases, and test problems. A Knowledge Based Reasoning system was developed using the CLIPS (C Language Interpretive Procedural System) environment and a Case Based Reasoning System was developed using the Design Memory Utility For Sharing Experiences (MUSE) xviii environment. A Design Characteristic State (DCS) was used to document the design specifications, constraints, and problem areas using attribute-value pair relationships. The DCS provided consistent design information between the knowledge base and case base. Results indicated that the use of knowledge based and case based reasoning provided a robust design environment for composite structures. The knowledge base provided design guidance from well defined rules and procedural knowledge. The case base provided suggestions on design and manufacturing techniques based on previous similar designs and warnings of potential problems and pitfalls. The case base complemented the knowledge base and extended the problem solving capability beyond the existence of

  17. A Knowledge-Based Approach to Improving and Homogenizing Intensity Modulated Radiation Therapy Planning Quality Among Treatment Centers: An Example Application to Prostate Cancer Planning

    SciTech Connect

    Good, David; Lo, Joseph; Lee, W. Robert; Wu, Q. Jackie; Yin, Fang-Fang; Das, Shiva K.

    2013-09-01

    Purpose: Intensity modulated radiation therapy (IMRT) treatment planning can have wide variation among different treatment centers. We propose a system to leverage the IMRT planning experience of larger institutions to automatically create high-quality plans for outside clinics. We explore feasibility by generating plans for patient datasets from an outside institution by adapting plans from our institution. Methods and Materials: A knowledge database was created from 132 IMRT treatment plans for prostate cancer at our institution. The outside institution, a community hospital, provided the datasets for 55 prostate cancer cases, including their original treatment plans. For each “query” case from the outside institution, a similar “match” case was identified in the knowledge database, and the match case’s plan parameters were then adapted and optimized to the query case by use of a semiautomated approach that required no expert planning knowledge. The plans generated with this knowledge-based approach were compared with the original treatment plans at several dose cutpoints. Results: Compared with the original plan, the knowledge-based plan had a significantly more homogeneous dose to the planning target volume and a significantly lower maximum dose. The volumes of the rectum, bladder, and femoral heads above all cutpoints were nominally lower for the knowledge-based plan; the reductions were significantly lower for the rectum. In 40% of cases, the knowledge-based plan had overall superior (lower) dose–volume histograms for rectum and bladder; in 54% of cases, the comparison was equivocal; in 6% of cases, the knowledge-based plan was inferior for both bladder and rectum. Conclusions: Knowledge-based planning was superior or equivalent to the original plan in 95% of cases. The knowledge-based approach shows promise for homogenizing plan quality by transferring planning expertise from more experienced to less experienced institutions.

  18. Improving Loop Modeling of the Antibody Complementarity-Determining Region 3 Using Knowledge-Based Restraints

    PubMed Central

    Finn, Jessica A.; Koehler Leman, Julia; Cisneros, Alberto; Crowe, James E.; Meiler, Jens

    2016-01-01

    Structural restrictions are present even in the most sequence diverse portions of antibodies, the complementary determining region (CDR) loops. Previous studies identified robust rules that define canonical structures for five of the six CDR loops, however the heavy chain CDR 3 (HCDR3) defies standard classification attempts. The HCDR3 loop can be subdivided into two domains referred to as the “torso” and the “head” domains and two major families of canonical torso structures have been identified; the more prevalent “bulged” and less frequent “non-bulged” torsos. In the present study, we found that Rosetta loop modeling of 28 benchmark bulged HCDR3 loops is improved with knowledge-based structural restraints developed from available antibody crystal structures in the PDB. These restraints restrict the sampling space Rosetta searches in the torso domain, limiting the φ and ψ angles of these residues to conformations that have been experimentally observed. The application of these restraints in Rosetta result in more native-like structure sampling and improved score-based differentiation of native-like HCDR3 models, significantly improving our ability to model antibody HCDR3 loops. PMID:27182833

  19. HIVed, a knowledgebase for differentially expressed human genes and proteins during HIV infection, replication and latency

    PubMed Central

    Li, Chen; Ramarathinam, Sri H.; Revote, Jerico; Khoury, Georges; Song, Jiangning; Purcell, Anthony W.

    2017-01-01

    Measuring the altered gene expression level and identifying differentially expressed genes/proteins during HIV infection, replication and latency is fundamental for broadening our understanding of the mechanisms of HIV infection and T-cell dysfunction. Such studies are crucial for developing effective strategies for virus eradication from the body. Inspired by the availability and enrichment of gene expression data during HIV infection, replication and latency, in this study, we proposed a novel compendium termed HIVed (HIV expression database; http://hivlatency.erc.monash.edu/) that harbours comprehensive functional annotations of proteins, whose genes have been shown to be dysregulated during HIV infection, replication and latency using different experimental designs and measurements. We manually curated a variety of third-party databases for structural and functional annotations of the protein entries in HIVed. With the goal of benefiting HIV related research, we collected a number of biological annotations for all the entries in HIVed besides their expression profile, including basic protein information, Gene Ontology terms, secondary structure, HIV-1 interaction and pathway information. We hope this comprehensive protein-centric knowledgebase can bridge the gap between the understanding of differentially expressed genes and the functions of their protein products, facilitating the generation of novel hypotheses and treatment strategies to fight against the HIV pandemic. PMID:28358052

  20. The Application of Integrated Knowledge-based Systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

    NASA Technical Reports Server (NTRS)

    Loftin, Karin C.; Ly, Bebe; Webster, Laurie; Verlander, James; Taylor, Gerald R.; Riley, Gary; Culbert, Chris; Holden, Tina; Rudisill, Marianne

    1993-01-01

    One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through the Biomedical Risk Assessment Intelligent Network (BRAIN), an integrated network of both human and computer elements. The BRAIN will function as an advisor to flight surgeons by assessing the risk of in-flight biomedical problems and recommending appropriate countermeasures. This paper describes the joint effort among various NASA elements to develop BRAIN and an Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of the following: (1) knowledge acquisition; (2) integration of IDRA components; (3) use of expert systems to automate the biomedical prediction process; (4) development of a user-friendly interface; and (5) integration of the IDRA prototype and Exercise Countermeasures Intelligent System (ExerCISys). Because the C Language, CLIPS (the C Language Integrated Production System), and the X-Window System were portable and easily integrated, they were chosen as the tools for the initial IDRA prototype. The feasibility was tested by developing an IDRA prototype that predicts the individual risk of influenza. The application of knowledge-based systems to risk assessment is of great market value to the medical technology industry.

  1. The fault monitoring and diagnosis knowledge-based system for space power systems: AMPERES, phase 1

    NASA Technical Reports Server (NTRS)

    Lee, S. C.

    1989-01-01

    The objective is to develop a real time fault monitoring and diagnosis knowledge-based system (KBS) for space power systems which can save costly operational manpower and can achieve more reliable space power system operation. The proposed KBS was developed using the Autonomously Managed Power System (AMPS) test facility currently installed at NASA Marshall Space Flight Center (MSFC), but the basic approach taken for this project could be applicable for other space power systems. The proposed KBS is entitled Autonomously Managed Power-System Extendible Real-time Expert System (AMPERES). In Phase 1 the emphasis was put on the design of the overall KBS, the identification of the basic research required, the initial performance of the research, and the development of a prototype KBS. In Phase 2, emphasis is put on the completion of the research initiated in Phase 1, and the enhancement of the prototype KBS developed in Phase 1. This enhancement is intended to achieve a working real time KBS incorporated with the NASA space power system test facilities. Three major research areas were identified and progress was made in each area. These areas are real time data acquisition and its supporting data structure; sensor value validations; development of inference scheme for effective fault monitoring and diagnosis, and its supporting knowledge representation scheme.

  2. Human Disease Insight: An integrated knowledge-based platform for disease-gene-drug information.

    PubMed

    Tasleem, Munazzah; Ishrat, Romana; Islam, Asimul; Ahmad, Faizan; Hassan, Md Imtaiyaz

    2016-01-01

    The scope of the Human Disease Insight (HDI) database is not limited to researchers or physicians as it also provides basic information to non-professionals and creates disease awareness, thereby reducing the chances of patient suffering due to ignorance. HDI is a knowledge-based resource providing information on human diseases to both scientists and the general public. Here, our mission is to provide a comprehensive human disease database containing most of the available useful information, with extensive cross-referencing. HDI is a knowledge management system that acts as a central hub to access information about human diseases and associated drugs and genes. In addition, HDI contains well-classified bioinformatics tools with helpful descriptions. These integrated bioinformatics tools enable researchers to annotate disease-specific genes and perform protein analysis, search for biomarkers and identify potential vaccine candidates. Eventually, these tools will facilitate the analysis of disease-associated data. The HDI provides two types of search capabilities and includes provisions for downloading, uploading and searching disease/gene/drug-related information. The logistical design of the HDI allows for regular updating. The database is designed to work best with Mozilla Firefox and Google Chrome and is freely accessible at http://humandiseaseinsight.com.

  3. Development of a Knowledgebase to Integrate, Analyze, Distribute, and Visualize Microbial Community Systems Biology Data

    SciTech Connect

    Banfield, Jillian

    2015-01-15

    We have developed a flexible knowledgebase system, ggKbase, (http://gg.berkeley.edu), to enable effective data analysis and knowledge generation from samples from which metagenomic and other ‘omics’ data are obtained. Within ggKbase, data can be interpreted, integrated and linked to other databases and services. Sequence information from complex metagenomic samples can be quickly and effectively resolved into genomes and biologically meaningful investigations of an organism’s metabolic potential can then be conducted. Critical features make analyses efficient, allowing analysis of hundreds of genomes at a time. The system is being used to support research in multiple DOE-relevant systems, including the LBNL SFA subsurface science biogeochemical cycling research at Rifle, Colorado. ggKbase is supporting the research of a rapidly growing group of users. It has enabled studies of carbon cycling in acid mine drainage ecosystems, biologically-mediated transformations in deep subsurface biomes sampled from mines and the north slope of Alaska, to study the human microbiome and for laboratory bioreactor-based remediation investigations.

  4. Knowledge-based discovery for designing CRISPR-CAS systems against invading mobilomes in thermophiles.

    PubMed

    Chellapandi, P; Ranjani, J

    2015-09-01

    Clustered regularly interspaced short palindromic repeats (CRISPRs) are direct features of the prokaryotic genomes involved in resistance to their bacterial viruses and phages. Herein, we have identified CRISPR loci together with CRISPR-associated sequences (CAS) genes to reveal their immunity against genome invaders in the thermophilic archaea and bacteria. Genomic survey of this study implied that genomic distribution of CRISPR-CAS systems was varied from strain to strain, which was determined by the degree of invading mobiloms. Direct repeats found to be equal in some extent in many thermopiles, but their spacers were differed in each strain. Phylogenetic analyses of CAS superfamily revealed that genes cmr, csh, csx11, HD domain, devR were belonged to the subtypes of cas gene family. The members in cas gene family of thermophiles were functionally diverged within closely related genomes and may contribute to develop several defense strategies. Nevertheless, genome dynamics, geological variation and host defense mechanism were contributed to share their molecular functions across the thermophiles. A thermophilic archaean, Thermococcus gammotolerans and thermophilic bacteria, Petrotoga mobilis and Thermotoga lettingae have shown superoperons-like appearance to cluster cas genes, which were typically evolved for their defense pathways. A cmr operon was identified with a specific promoter in a thermophilic archaean, Caldivirga maquilingensis. Overall, we concluded that knowledge-based genomic survey and phylogeny-based functional assignment have suggested for designing a reliable genetic regulatory circuit naturally from CRISPR-CAS systems, acquired defense pathways, to thermophiles in future synthetic biology.

  5. Data mining and intelligent queries in a knowledge-based multimedia medical database system

    NASA Astrophysics Data System (ADS)

    Zhang, Shuhua; Coleman, John D.

    2000-04-01

    Multimedia medical databases have accumulated large quantities of data and information about patients and their medical conditions. Patterns and relationships within this data could provide new knowledge for making better medical decisions. Unfortunately, few technologies have been developed and applied to discover and use this hidden knowledge. We are currently developing a next generation knowledge-based multimedia medical database, named MedBase, with advanced behaviors for data analysis and data fusion. As part of this R&D effort, a knowledge-rich data model is constructed to incorporate data mining techniques/tools to assist the building of medical knowledge bases, and to facilitate intelligent answering of users' investigative and knowledge queries in the database. Techniques such as data generalization, classification, clustering, semantic structures, and concept hierarchies, are used to acquire and represent both symbolic and spatial knowledge implicit in the database. With the availability of semantic structures, concept hierarchies and generalized knowledge, queries may be posed and answered at multiple levels of abstraction. In this article we provide a general description of the approaches and efforts undertaken so far in the MedBase project.

  6. Knowledge-based and data-driven models in arrhythmia fuzzy classification.

    PubMed

    Silipo, R; Vergassola, R; Zong, W; Berthold, M R

    2001-01-01

    Fuzzy rules automatically derived from a set of training examples quite often produce better classification results than fuzzy rules translated from medical knowledge. This study aims to investigate the difference in domain representation between a knowledge-based and a data-driven fuzzy system applied to an electrocardiography classification problem. For a three-class electrocardiographic arrhythmia classification task a set of fifteen fuzzy rules is derived from medical expertise on the basis of twelve electrocardiographic measures. A second set of fuzzy rules is automatically constructed on thirty-nine MIT-BIH database's records. The performances of the two classifiers on thirteen different records are comparable and up to a certain extent complementary. The two fuzzy models are then analyzed, by using the concept of information gain to estimate the impact of each ECG measure on each fuzzy decision process. Both systems rely on the beat prematurity degree and the QRS complex width and neglect the P wave existence and the ST segment features. The PR interval is not well characterized across the fuzzy medical rules while it plays an important role in the data-driven fuzzy system. The T wave area shows a higher information gain in the knowledge based decision process, and is not very much exploited by the data-driven system. The main difference between a human designed and a data driven ECG arrhythmia classifier is found about the PR interval and the T wave.

  7. Computing gene expression data with a knowledge-based gene clustering approach.

    PubMed

    Rosa, Bruce A; Oh, Sookyung; Montgomery, Beronda L; Chen, Jin; Qin, Wensheng

    2010-01-01

    Computational analysis methods for gene expression data gathered in microarray experiments can be used to identify the functions of previously unstudied genes. While obtaining the expression data is not a difficult task, interpreting and extracting the information from the datasets is challenging. In this study, a knowledge-based approach which identifies and saves important functional genes before filtering based on variability and fold change differences was utilized to study light regulation. Two clustering methods were used to cluster the filtered datasets, and clusters containing a key light regulatory gene were located. The common genes to both of these clusters were identified, and the genes in the common cluster were ranked based on their coexpression to the key gene. This process was repeated for 11 key genes in 3 treatment combinations. The initial filtering method reduced the dataset size from 22,814 probes to an average of 1134 genes, and the resulting common cluster lists contained an average of only 14 genes. These common cluster lists scored higher gene enrichment scores than two individual clustering methods. In addition, the filtering method increased the proportion of light responsive genes in the dataset from 1.8% to 15.2%, and the cluster lists increased this proportion to 18.4%. The relatively short length of these common cluster lists compared to gene groups generated through typical clustering methods or coexpression networks narrows the search for novel functional genes while increasing the likelihood that they are biologically relevant.

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

    SciTech Connect

    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.

  9. HIVed, a knowledgebase for differentially expressed human genes and proteins during HIV infection, replication and latency.

    PubMed

    Li, Chen; Ramarathinam, Sri H; Revote, Jerico; Khoury, Georges; Song, Jiangning; Purcell, Anthony W

    2017-03-30

    Measuring the altered gene expression level and identifying differentially expressed genes/proteins during HIV infection, replication and latency is fundamental for broadening our understanding of the mechanisms of HIV infection and T-cell dysfunction. Such studies are crucial for developing effective strategies for virus eradication from the body. Inspired by the availability and enrichment of gene expression data during HIV infection, replication and latency, in this study, we proposed a novel compendium termed HIVed (HIV expression database; http://hivlatency.erc.monash.edu/) that harbours comprehensive functional annotations of proteins, whose genes have been shown to be dysregulated during HIV infection, replication and latency using different experimental designs and measurements. We manually curated a variety of third-party databases for structural and functional annotations of the protein entries in HIVed. With the goal of benefiting HIV related research, we collected a number of biological annotations for all the entries in HIVed besides their expression profile, including basic protein information, Gene Ontology terms, secondary structure, HIV-1 interaction and pathway information. We hope this comprehensive protein-centric knowledgebase can bridge the gap between the understanding of differentially expressed genes and the functions of their protein products, facilitating the generation of novel hypotheses and treatment strategies to fight against the HIV pandemic.

  10. Capturing district nursing through a knowledge-based electronic caseload analysis tool (eCAT).

    PubMed

    Kane, Kay

    2014-03-01

    The Electronic Caseload Analysis Tool (eCAT) is a knowledge-based software tool to assist the caseload analysis process. The tool provides a wide range of graphical reports, along with an integrated clinical advisor, to assist district nurses, team leaders, operational and strategic managers with caseload analysis by describing, comparing and benchmarking district nursing practice in the context of population need, staff resources, and service structure. District nurses and clinical lead nurses in Northern Ireland developed the tool, along with academic colleagues from the University of Ulster, working in partnership with a leading software company. The aim was to use the eCAT tool to identify the nursing need of local populations, along with the variances in district nursing practice, and match the workforce accordingly. This article reviews the literature, describes the eCAT solution and discusses the impact of eCAT on nursing practice, staff allocation, service delivery and workforce planning, using fictitious exemplars and a post-implementation evaluation from the trusts.

  11. Research on Knowledge-Based Optimization Method of Indoor Location Based on Low Energy Bluetooth

    NASA Astrophysics Data System (ADS)

    Li, C.; Li, G.; Deng, Y.; Wang, T.; Kang, Z.

    2017-09-01

    With the rapid development of LBS (Location-based Service), the demand for commercialization of indoor location has been increasing, but its technology is not perfect. Currently, the accuracy of indoor location, the complexity of the algorithm, and the cost of positioning are hard to be simultaneously considered and it is still restricting the determination and application of mainstream positioning technology. Therefore, this paper proposes a method of knowledge-based optimization of indoor location based on low energy Bluetooth. The main steps include: 1) The establishment and application of a priori and posterior knowledge base. 2) Primary selection of signal source. 3) Elimination of positioning gross error. 4) Accumulation of positioning knowledge. The experimental results show that the proposed algorithm can eliminate the signal source of outliers and improve the accuracy of single point positioning in the simulation data. The proposed scheme is a dynamic knowledge accumulation rather than a single positioning process. The scheme adopts cheap equipment and provides a new idea for the theory and method of indoor positioning. Moreover, the performance of the high accuracy positioning results in the simulation data shows that the scheme has a certain application value in the commercial promotion.

  12. Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force field.

    PubMed

    Xu, Dong; Zhang, Yang

    2012-07-01

    Ab initio protein folding is one of the major unsolved problems in computational biology owing to the difficulties in force field design and conformational search. We developed a novel program, QUARK, for template-free protein structure prediction. Query sequences are first broken into fragments of 1-20 residues where multiple fragment structures are retrieved at each position from unrelated experimental structures. Full-length structure models are then assembled from fragments using replica-exchange Monte Carlo simulations, which are guided by a composite knowledge-based force field. A number of novel energy terms and Monte Carlo movements are introduced and the particular contributions to enhancing the efficiency of both force field and search engine are analyzed in detail. QUARK prediction procedure is depicted and tested on the structure modeling of 145 nonhomologous proteins. Although no global templates are used and all fragments from experimental structures with template modeling score >0.5 are excluded, QUARK can successfully construct 3D models of correct folds in one-third cases of short proteins up to 100 residues. In the ninth community-wide Critical Assessment of protein Structure Prediction experiment, QUARK server outperformed the second and third best servers by 18 and 47% based on the cumulative Z-score of global distance test-total scores in the FM category. Although ab initio protein folding remains a significant challenge, these data demonstrate new progress toward the solution of the most important problem in the field.

  13. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

    PubMed Central

    2010-01-01

    Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

  14. Biotechnology as the engine for the Knowledge-Based Bio-Economy.

    PubMed

    Aguilar, Alfredo; Bochereau, Laurent; Matthiessen, Line

    2010-01-01

    The European Commission has defined the Knowledge-Based Bio-Economy (KBBE) as the process of transforming life science knowledge into new, sustainable, eco-efficient and competitive products. The term "Bio-Economy" encompasses all industries and economic sectors that produce, manage and otherwise exploit biological resources and related services. Over the last decades biotechnologies have led to innovations in many agricultural, industrial, medical sectors and societal activities. Biotechnology will continue to be a major contributor to the Bio-Economy, playing an essential role in support of economic growth, employment, energy supply and a new generation of bio-products, and to maintain the standard of living. The paper reviews some of the main biotechnology-related research activities at European level. Beyond the 7th Framework Program for Research and Technological Development (FP7), several initiatives have been launched to better integrate FP7 with European national research activities, promote public-private partnerships and create better market and regulatory environments for stimulating innovation.

  15. Human Resource Development for Knowledge-based Society and Challenges of Nagoya University

    NASA Astrophysics Data System (ADS)

    Miyata, Takashi

    Innovation in the previous century resulted in development of useful products ranging from automobiles and aircraft to cellular phones. However, the innovation and development of science and technology have changed the society and brought about negative issues. The issues emerged in the previous century remain in the excessive forms in the 21st century. The 21st century is seeing the rise of knowledge-based society, and paradigm shift is now going on. Human resources of university for creation of innovation are being called on to contribute to solving issues. Young people who pass through a doctor program must play a role as an innovator who can promote the paradigm shift. However, the higher education system of the universities in Japan is now required to be changed to dissolve the mismatch on the doctor program with industries, government and students. The discussion in the Business-University Forum of Japan for innovation of education system and a few challenges of the Nagoya University are introduced in this paper.

  16. Initial Validation of a Knowledge-Based Measure of Social Information Processing and Anger Management

    PubMed Central

    Cassano, Michael; MacEvoy, Julie Paquette; Costigan, Tracy

    2010-01-01

    Over the past fifteen years many schools have utilized aggression prevention programs. Despite these apparent advances, many programs are not examined systematically to determine the areas in which they are most effective. One reason for this is that many programs, especially those in urban under-resourced areas, do not utilize outcome measures that are sensitive to the needs of ethnic minority students. The current study illustrates how a new knowledge-based measure of social information processing and anger management techniques was designed through a partnership-based process to ensure that it would be sensitive to the needs of urban, predominately African American youngsters, while also having broad potential applicability for use as an outcome assessment tool for aggression prevention programs focusing upon social information processing. The new measure was found to have strong psychometric properties within a sample of urban predominately African American youth, as item analyses suggested that almost all items discriminate well between more and less knowledgeable individuals, that the test-retest reliability of the measure is strong, and that the measure appears to be sensitive to treatment changes over time. In addition, the overall score of this new measure is moderately associated with attributions of hostility on two measures (negative correlations) and demonstrates a low to moderate negative association with peer and teacher report measures of overt and relational aggression. More research is needed to determine the measure's utility outside of the urban school context. PMID:20449645

  17. SIGMA: A Knowledge-Based Simulation Tool Applied to Ecosystem Modeling

    NASA Technical Reports Server (NTRS)

    Dungan, Jennifer L.; Keller, Richard; Lawless, James G. (Technical Monitor)

    1994-01-01

    The need for better technology to facilitate building, sharing and reusing models is generally recognized within the ecosystem modeling community. The Scientists' Intelligent Graphical Modelling Assistant (SIGMA) creates an environment for model building, sharing and reuse which provides an alternative to more conventional approaches which too often yield poorly documented, awkwardly structured model code. The SIGMA interface presents the user a list of model quantities which can be selected for computation. Equations to calculate the model quantities may be chosen from an existing library of ecosystem modeling equations, or built using a specialized equation editor. Inputs for dim equations may be supplied by data or by calculation from other equations. Each variable and equation is expressed using ecological terminology and scientific units, and is documented with explanatory descriptions and optional literature citations. Automatic scientific unit conversion is supported and only physically-consistent equations are accepted by the system. The system uses knowledge-based semantic conditions to decide which equations in its library make sense to apply in a given situation, and supplies these to the user for selection. "Me equations and variables are graphically represented as a flow diagram which provides a complete summary of the model. Forest-BGC, a stand-level model that simulates photosynthesis and evapo-transpiration for conifer canopies, was originally implemented in Fortran and subsequenty re-implemented using SIGMA. The SIGMA version reproduces daily results and also provides a knowledge base which greatly facilitates inspection, modification and extension of Forest-BGC.

  18. Knowledge-based image understanding and classification system for medical image databases

    NASA Astrophysics Data System (ADS)

    Luo, Hui; Gaborski, Roger S.; Acharya, Raj S.

    2002-05-01

    With the advent of Computer Radiographs(CR) and Digital Radiographs(DR), image understanding and classification in medical image databases have attracted considerable attention. In this paper, we propose a knowledge-based image understanding and classification system for medical image databases. An object-oriented knowledge model has been introduced and the idea that content features of medical images must hierarchically match to the related knowledge model is used. As a result of finding the best match model, the input image can be classified. The implementation of the system includes three stages. The first stage focuses on the match of the coarse pattern of the model class and has three steps: image preprocessing, feature extraction, and neural network classification. Once the coarse shape classification is done, a small set of plausible model candidates are then employed for a detailed match in the second stage. Its match outputs imply the result models might be contained in the processed images. Finally, an evaluation strategy is used to further confirm the results. The performance of the system has been tested on different types of digital radiographs, including pelvis, ankle, elbow and etc. The experimental results suggest that the system prototype is applicable and robust, and the accuracy of the system is near 70% in our image databases.

  19. A knowledge-based, two-step procedure for extracting channel networks from noisy dem data

    NASA Astrophysics Data System (ADS)

    Smith, Terence R.; Zhan, Cixiang; Gao, Peng

    We present a new procedure for extracting channel networks from noisy DEM data. The procedure is a knowledge-based, two-step procedure employing both local and nonlocal information. In particular, we employ a model of an ideal drainage network as a source of constraints that must be satisfied by the output of the procedure. We embed these constraints as part of the network extraction procedure. In a first step, the procedure employs the facet model of Haralick to extract valley information from digital images. The constraints employed at this stage relate to conditions indicating reliable valley pixels. In a second step, the procedure applies knowledge of drainage networks to integrate reliable valley points discovered into a network of single-pixel width lines. This network satisfies the constraints imposed by viewing a drainage network as a binary tree in which the channel segments have a one-pixel width. The procedure performs well on DEM data in the example investigated. The overall worst-case performance of the procedure is O( N) log N), but the most computationally intensive step in the procedure is parallelized easily. Hence the procedure is a good candidate for automation.

  20. ESPRE: a knowledge-based system to support platelet transfusion decisions.

    PubMed

    Sielaff, B H; Connelly, D P; Scott, E P

    1989-05-01

    ESPRE is a knowledge-based system which aids in the review of requests for platelet transfusions in the hospital blood bank. It is a microcomputer-based decision support system written in LISP and utilizes a hybrid frame and rule architecture. By automatically obtaining most of the required patient data directly from the hospital's main laboratory computers via a direct link, very little keyboard entry is required. Assessment of time trends computed from the data constitutes an important aspect of this system. To aid the blood bank personnel in deciding on the appropriateness of the requested transfusion, the system provides an explanatory report which includes a list of patient-specific data, a list of the conditions for which a transfusion would be appropriate for the particular patient (given the clinical condition), and the conclusions drawn by the system. In an early clinical evaluation of ESPRE, out of a random sample of 75 platelet transfusion requests, there were only three disagreements between ESPRE and blood bank personnel.

  1. A Knowledge-Based and Model-Driven Requirements Engineering Approach to Conceptual Satellite Design

    NASA Astrophysics Data System (ADS)

    Dos Santos, Walter A.; Leonor, Bruno B. F.; Stephany, Stephan

    Satellite systems are becoming even more complex, making technical issues a significant cost driver. The increasing complexity of these systems makes requirements engineering activities both more important and difficult. Additionally, today's competitive pressures and other market forces drive manufacturing companies to improve the efficiency with which they design and manufacture space products and systems. This imposes a heavy burden on systems-of-systems engineering skills and particularly on requirements engineering which is an important phase in a system's life cycle. When this is poorly performed, various problems may occur, such as failures, cost overruns and delays. One solution is to underpin the preliminary conceptual satellite design with computer-based information reuse and integration to deal with the interdisciplinary nature of this problem domain. This can be attained by taking a model-driven engineering approach (MDE), in which models are the main artifacts during system development. MDE is an emergent approach that tries to address system complexity by the intense use of models. This work outlines the use of SysML (Systems Modeling Language) and a novel knowledge-based software tool, named SatBudgets, to deal with these and other challenges confronted during the conceptual phase of a university satellite system, called ITASAT, currently being developed by INPE and some Brazilian universities.

  2. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders.

    PubMed

    Hamosh, Ada; Scott, Alan F; Amberger, Joanna S; Bocchini, Carol A; McKusick, Victor A

    2005-01-01

    Online Mendelian Inheritance in Man (OMIM) is a comprehensive, authoritative and timely knowledgebase of human genes and genetic disorders compiled to support human genetics research and education and the practice of clinical genetics. Started by Dr Victor A. McKusick as the definitive reference Mendelian Inheritance in Man, OMIM (http://www.ncbi.nlm.nih.gov/omim/) is now distributed electronically by the National Center for Biotechnology Information, where it is integrated with the Entrez suite of databases. Derived from the biomedical literature, OMIM is written and edited at Johns Hopkins University with input from scientists and physicians around the world. Each OMIM entry has a full-text summary of a genetically determined phenotype and/or gene and has numerous links to other genetic databases such as DNA and protein sequence, PubMed references, general and locus-specific mutation databases, HUGO nomenclature, MapViewer, GeneTests, patient support groups and many others. OMIM is an easy and straightforward portal to the burgeoning information in human genetics.

  3. A methodology for evaluating potential KBS (Knowledge-Based Systems) applications

    SciTech Connect

    Melton, R.B.; DeVaney, D.M.; Whiting, M.A.; Laufmann, S.C.

    1989-06-01

    It is often difficult to assess how well Knowledge-Based Systems (KBS) techniques and paradigms may be applied to automating various tasks. This report describes the approach and organization of an assessment procedure that involves two levels of analysis. Level One can be performed by individuals with little technical expertise relative to KBS development, while Level Two is intended to be used by experienced KBS developers. The two levels review four groups of issues: goals, appropriateness, resources, and non-technical considerations. Those criteria are identified which are important at each step in the assessment. A qualitative methodology for scoring the task relative to the assessment criteria is provided to alloy analysts to make better informed decisions with regard to the potential effectiveness of applying KBS technology. In addition to this documentation, the assessment methodology has been implemented for personal computers use using the HYPERCARD{trademark} software on a Macintosh{trademark} computer. This interactive mode facilities small group analysis of potential KBS applications and permits a non-sequential appraisal with provisions for automated note-keeping and question scoring. The results provide a useful tool for assessing the feasibility of using KBS techniques in performing tasks in support of treaty verification or IC functions. 13 refs., 3 figs.

  4. A knowledge-based search engine to navigate the information thicket of nanotoxicology.

    PubMed

    Sauer, Ursula G; Kneuer, Carsten; Tentschert, Jutta; Wächter, Thomas; Schroeder, Michael; Butzke, Daniel; Luch, Andreas; Liebsch, Manfred; Grune, Barbara; Götz, Mario E

    2011-02-01

    The risk assessment of nano-sized materials (NM) currently suffers from great uncertainties regarding their putative toxicity for humans and the environment. An extensive amount of the respective original research literature has to be evaluated before a targeted and hypothesis-driven Environmental and Health Safety research can be stipulated. Furthermore, to comply with the European animal protection legislation in vitro testing has to be preferred whenever possible. Against this background, there is the need for tools that enable producers of NM and risk assessors for a fast and comprehensive data retrieval, thereby linking the 3Rs principle to the hazard identification of NM. Here we report on the development of a knowledge-based search engine that is tailored to the particular needs of risk assessors in the area of NM. Comprehensive retrieval of data from studies utilising in vitro as well as in vivo methods relying on the PubMed database is presented exemplarily with a titanium dioxide case study. A fast, relevant and reliable information retrieval is of paramount importance for the scientific community dedicated to develop safe NM in various product areas, and for risk assessors obliged to identify data gaps, to define additional data requirements for approval of NM and to create strategies for integrated testing using alternative methods. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. Knowledge-based deformable surface model with application to segmentation of brain structures in MRI

    NASA Astrophysics Data System (ADS)

    Ghanei, Amir; Soltanian-Zadeh, Hamid; Elisevich, Kost; Fessler, Jeffrey A.

    2001-07-01

    We have developed a knowledge-based deformable surface for segmentation of medical images. This work has been done in the context of segmentation of hippocampus from brain MRI, due to its challenge and clinical importance. The model has a polyhedral discrete structure and is initialized automatically by analyzing brain MRI sliced by slice, and finding few landmark features at each slice using an expert system. The expert system decides on the presence of the hippocampus and its general location in each slice. The landmarks found are connected together by a triangulation method, to generate a closed initial surface. The surface deforms under defined internal and external force terms thereafter, to generate an accurate and reproducible boundary for the hippocampus. The anterior and posterior (AP) limits of the hippocampus is estimated by automatic analysis of the location of brain stem, and some of the features extracted in the initialization process. These data are combined together with a priori knowledge using Bayes method to estimate a probability density function (pdf) for the length of the structure in sagittal direction. The hippocampus AP limits are found by optimizing this pdf. The model is tested on real clinical data and the results show very good model performance.

  6. Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks.

    PubMed

    Davis, Allan Peter; Murphy, Cynthia G; Saraceni-Richards, Cynthia A; Rosenstein, Michael C; Wiegers, Thomas C; Mattingly, Carolyn J

    2009-01-01

    The Comparative Toxicogenomics Database (CTD) is a curated database that promotes understanding about the effects of environmental chemicals on human health. Biocurators at CTD manually curate chemical-gene interactions, chemical-disease relationships and gene-disease relationships from the literature. This strategy allows data to be integrated to construct chemical-gene-disease networks. CTD is unique in numerous respects: curation focuses on environmental chemicals; interactions are manually curated; interactions are constructed using controlled vocabularies and hierarchies; additional gene attributes (such as Gene Ontology, taxonomy and KEGG pathways) are integrated; data can be viewed from the perspective of a chemical, gene or disease; results and batch queries can be downloaded and saved; and most importantly, CTD acts as both a knowledgebase (by reporting data) and a discovery tool (by generating novel inferences). Over 116,000 interactions between 3900 chemicals and 13,300 genes have been curated from 270 species, and 5900 gene-disease and 2500 chemical-disease direct relationships have been captured. By integrating these data, 350,000 gene-disease relationships and 77,000 chemical-disease relationships can be inferred. This wealth of chemical-gene-disease information yields testable hypotheses for understanding the effects of environmental chemicals on human health. CTD is freely available at http://ctd.mdibl.org.

  7. Structural semantic interconnections: a knowledge-based approach to word sense disambiguation.

    PubMed

    Navigli, Roberto; Velardi, Paola

    2005-07-01

    Word Sense Disambiguation (WSD) is traditionally considered an Al-hard problem. A break-through in this field would have a significant impact on many relevant Web-based applications, such as Web information retrieval, improved access to Web services, information extraction, etc. Early approaches to WSD, based on knowledge representation techniques, have been replaced in the past few years by more robust machine learning and statistical techniques. The results of recent comparative evaluations of WSD systems, however, show that these methods have inherent limitations. On the other hand, the increasing availability of large-scale, rich lexical knowledge resources seems to provide new challenges to knowledge-based approaches. In this paper, we present a method, called structural semantic interconnections (SSI), which creates structural specifications of the possible senses for each word in a context and selects the best hypothesis according to a grammar G, describing relations between sense specifications. Sense specifications are created from several available lexical resources that we integrated in part manually, in part with the help of automatic procedures. The SSI algorithm has been applied to different semantic disambiguation problems, like automatic ontology population, disambiguation of sentences in generic texts, disambiguation of words in glossary definitions. Evaluation experiments have been performed on specific knowledge domains (e.g., tourism, computer networks, enterprise interoperability), as well as on standard disambiguation test sets.

  8. Self-revealing software: a method for producing understandable knowledge-based systems

    SciTech Connect

    Paul, J.

    1988-01-01

    System self-explanation is critical for the construction, utility, acceptance, and maintenance of complex, knowledge-based software. This dissertation presents a new methodology and implementation techniques that enable software systems to explain their knowledge and reasoning, i.e., to become self-revealing. These systems are capable of self-analysis-they introspect about their own knowledge and behavior. This internal awareness coupled with intelligent communication ability provide the critical resources necessary for more understandable, self-explaining systems. The theory addresses the spectrum of explanation goals and is applicable to complex and unstructured domains and to general control structures. The method, called REVEAL, represents the culmination of research and experimentation with new explanation techniques conducted as part of the development of a legal expert system, SAL (System for Asbestos Litigation). SAL adheres to the design philosophy of REVEAL and uses many of the associated techniques. Throughout the dissertation, the theoretical concepts are demonstrated by examples of their implementation in SAL.

  9. Knowledge-based factor analysis of multidimensional nuclear medicine image sequences

    NASA Astrophysics Data System (ADS)

    Yap, Jeffrey T.; Chen, Chin-Tu; Cooper, Malcolm; Treffert, Jon D.

    1994-05-01

    We have developed a knowledge-based approach to analyzing dynamic nuclear medicine data sets using factor analysis. Prior knowledge is used as constraints to produce factor images and their associated time functions which are physically and physiologically realistic. These methods have been applied to both planar and tomographic image sequences acquired using various single-photon emitting and positron emitting radiotracers. Computer-simulated data, non-human primate studies, and human clinical studies have been used to develop and evaluate the methodology. The organ systems studied include the kidneys, heart, brain, liver, and bone. The factors generated represent various isolated aspects of physiologic function, such as tissue perfusion and clearance. In some clinical studies, the factors have indicated the potential to isolate diseased tissue from normally functioning tissue. In addition, the factor analysis of data acquired using newly developed radioligands has shown the ability to differentiate the specific binding of the radioligand to the targeted receptors from the non-specific binding. This suggests the potential use of factor analysis in the development and evaluation of radiolabeled compounds as well as in the investigation of specific receptor systems and their role in diagnosing disease.

  10. Knowledge-based automated technique for measuring total lung volume from CT

    NASA Astrophysics Data System (ADS)

    Brown, Matthew S.; McNitt-Gray, Michael F.; Mankovich, Nicholas J.; Goldin, Jonathan G.; Aberle, Denise R.

    1996-04-01

    A robust, automated technique has been developed for estimating total lung volumes from chest computed tomography (CT) images. The technique includes a method for segmenting major chest anatomy. A knowledge-based approach automates the calculation of separate volumes of the whole thorax, lungs, and central tracheo-bronchial tree from volumetric CT data sets. A simple, explicit 3D model describes properties such as shape, topology and X-ray attenuation, of the relevant anatomy, which constrain the segmentation of these anatomic structures. Total lung volume is estimated as the sum of the right and left lungs and excludes the central airways. The method requires no operator intervention. In preliminary testing, the system was applied to image data from two healthy subjects and four patients with emphysema who underwent both helical CT and pulmonary function tests. To obtain single breath-hold scans, the healthy subjects were scanned with a collimation of 5 mm and a pitch of 1.5, while the emphysema patients were scanned with collimation of 10 mm at a pitch of 2.0. CT data were reconstructed as contiguous image sets. Automatically calculated volumes were consistent with body plethysmography results (< 10% difference).

  11. DBD-Hunter: a knowledge-based method for the prediction of DNA-protein interactions.

    PubMed

    Gao, Mu; Skolnick, Jeffrey

    2008-07-01

    The structures of DNA-protein complexes have illuminated the diversity of DNA-protein binding mechanisms shown by different protein families. This lack of generality could pose a great challenge for predicting DNA-protein interactions. To address this issue, we have developed a knowledge-based method, DNA-binding Domain Hunter (DBD-Hunter), for identifying DNA-binding proteins and associated binding sites. The method combines structural comparison and the evaluation of a statistical potential, which we derive to describe interactions between DNA base pairs and protein residues. We demonstrate that DBD-Hunter is an accurate method for predicting DNA-binding function of proteins, and that DNA-binding protein residues can be reliably inferred from the corresponding templates if identified. In benchmark tests on approximately 4000 proteins, our method achieved an accuracy of 98% and a precision of 84%, which significantly outperforms three previous methods. We further validate the method on DNA-binding protein structures determined in DNA-free (apo) state. We show that the accuracy of our method is only slightly affected on apo-structures compared to the performance on holo-structures cocrystallized with DNA. Finally, we apply the method to approximately 1700 structural genomics targets and predict that 37 targets with previously unknown function are likely to be DNA-binding proteins. DBD-Hunter is freely available at http://cssb.biology.gatech.edu/skolnick/webservice/DBD-Hunter/.

  12. Ada and knowledge-based systems: A prototype combining the best of both worlds

    NASA Technical Reports Server (NTRS)

    Brauer, David C.

    1986-01-01

    A software architecture is described which facilitates the construction of distributed expert systems using Ada and selected knowledge based systems. This architecture was utilized in the development of a Knowledge-based Maintenance Expert System (KNOMES) prototype for the Space Station Mobile Service Center (MSC). The KNOMES prototype monitors a simulated data stream from MSC sensors and built-in test equipment. It detects anomalies in the data and performs diagnosis to determine the cause. The software architecture which supports the KNOMES prototype allows for the monitoring and diagnosis tasks to be performed concurrently. The basic concept of this software architecture is named ACTOR (Ada Cognitive Task ORganization Scheme). An individual ACTOR is a modular software unit which contains both standard data processing and artificial intelligence components. A generic ACTOR module contains Ada packages for communicating with other ACTORs and accessing various data sources. The knowledge based component of an ACTOR determines the role it will play in a system. In this prototype, an ACTOR will monitor the MSC data stream.

  13. VIP: A knowledge-based design aid for the engineering of space systems

    NASA Technical Reports Server (NTRS)

    Lewis, Steven M.; Bellman, Kirstie L.

    1990-01-01

    The Vehicles Implementation Project (VIP), a knowledge-based design aid for the engineering of space systems is described. VIP combines qualitative knowledge in the form of rules, quantitative knowledge in the form of equations, and other mathematical modeling tools. The system allows users rapidly to develop and experiment with models of spacecraft system designs. As information becomes available to the system, appropriate equations are solved symbolically and the results are displayed. Users may browse through the system, observing dependencies and the effects of altering specific parameters. The system can also suggest approaches to the derivation of specific parameter values. In addition to providing a tool for the development of specific designs, VIP aims at increasing the user's understanding of the design process. Users may rapidly examine the sensitivity of a given parameter to others in the system and perform tradeoffs or optimizations of specific parameters. A second major goal of VIP is to integrate the existing corporate knowledge base of models and rules into a central, symbolic form.

  14. ISPE: A knowledge-based system for fluidization studies. 1990 Annual report

    SciTech Connect

    Reddy, S.

    1991-01-01

    Chemical engineers use mathematical simulators to design, model, optimize and refine various engineering plants/processes. This procedure requires the following steps: (1) preparation of an input data file according to the format required by the target simulator; (2) excecuting the simulation; and (3) analyzing the results of the simulation to determine if all ``specified goals`` are satisfied. If the goals are not met, the input data file must be modified and the simulation repeated. This multistep process is continued until satisfactory results are obtained. This research was undertaken to develop a knowledge based system, IPSE (Intelligent Process Simulation Environment), that can enhance the productivity of chemical engineers/modelers by serving as an intelligent assistant to perform a variety tasks related to process simulation. ASPEN, a widely used simulator by the US Department of Energy (DOE) at Morgantown Energy Technology Center (METC) was selected as the target process simulator in the project. IPSE, written in the C language, was developed using a number of knowledge-based programming paradigms: object-oriented knowledge representation that uses inheritance and methods, rulebased inferencing (includes processing and propagation of probabilistic information) and data-driven programming using demons. It was implemented using the knowledge based environment LASER. The relationship of IPSE with the user, ASPEN, LASER and the C language is shown in Figure 1.

  15. Sensorimotor representation and knowledge-based reasoning for spatial exploration and localisation.

    PubMed

    Zetzsche, C; Wolter, J; Schill, K

    2008-12-01

    We investigate a hybrid system for autonomous exploration and navigation, and implement it in a virtual mobile agent, which operates in virtual spatial environments. The system is based on several distinguishing properties. The representation is not map-like, but based on sensorimotor features, i.e. on combinations of sensory features and motor actions. The system has a hybrid architecture, which integrates a bottom-up processing of sensorimotor features with a top-down, knowledge-based reasoning strategy. This strategy selects the optimal motor action in each step according to the principle of maximum information gain. Two sensorimotor levels with different behavioural granularity are implemented, a macro-level, which controls the movements of the agent in space, and a micro-level, which controls its eye movements. At each level, the same type of hybrid architecture and the same principle of information gain are used for sensorimotor control. The localisation performance of the system is tested with large sets of virtual rooms containing different mixtures of unique and non-unique objects. The results demonstrate that the system efficiently performs those exploratory motor actions that yield a maximum amount of information about the current environment. Localisation is typically achieved within a few steps. Furthermore, the computational complexity of the underlying computations is limited, and the system is robust with respect to minor variations in the spatial environments.

  16. Diagnosis by integrating model-based reasoning with knowledge-based reasoning

    NASA Technical Reports Server (NTRS)

    Bylander, Tom

    1988-01-01

    Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

  17. Knowledge-based prediction of plan quality metrics in intracranial stereotactic radiosurgery.

    PubMed

    Shiraishi, Satomi; Tan, Jun; Olsen, Lindsey A; Moore, Kevin L

    2015-02-01

    The objective of this work was to develop a comprehensive knowledge-based methodology for predicting achievable dose-volume histograms (DVHs) and highly precise DVH-based quality metrics (QMs) in stereotactic radiosurgery/radiotherapy (SRS/SRT) plans. Accurate QM estimation can identify suboptimal treatment plans and provide target optimization objectives to standardize and improve treatment planning. Correlating observed dose as it relates to the geometric relationship of organs-at-risk (OARs) to planning target volumes (PTVs) yields mathematical models to predict achievable DVHs. In SRS, DVH-based QMs such as brain V10Gy (volume receiving 10 Gy or more), gradient measure (GM), and conformity index (CI) are used to evaluate plan quality. This study encompasses 223 linear accelerator-based SRS/SRT treatment plans (SRS plans) using volumetric-modulated arc therapy (VMAT), representing 95% of the institution's VMAT radiosurgery load from the past four and a half years. Unfiltered models that use all available plans for the model training were built for each category with a stratification scheme based on target and OAR characteristics determined emergently through initial modeling process. Model predictive accuracy is measured by the mean and standard deviation of the difference between clinical and predicted QMs, δQM = QMclin - QMpred, and a coefficient of determination, R(2). For categories with a large number of plans, refined models are constructed by automatic elimination of suspected suboptimal plans from the training set. Using the refined model as a presumed achievable standard, potentially suboptimal plans are identified. Predictions of QM improvement are validated via standardized replanning of 20 suspected suboptimal plans based on dosimetric predictions. The significance of the QM improvement is evaluated using the Wilcoxon signed rank test. The most accurate predictions are obtained when plans are stratified based on proximity to OARs and their PTV

  18. Multidimensional segmentation of coronary intravascular ultrasound images using knowledge-based methods

    NASA Astrophysics Data System (ADS)

    Olszewski, Mark E.; Wahle, Andreas; Vigmostad, Sarah C.; Sonka, Milan

    2005-04-01

    In vivo studies of the relationships that exist among vascular geometry, plaque morphology, and hemodynamics have recently been made possible through the development of a system that accurately reconstructs coronary arteries imaged by x-ray angiography and intravascular ultrasound (IVUS) in three dimensions. Currently, the bottleneck of the system is the segmentation of the IVUS images. It is well known that IVUS images contain numerous artifacts from various sources. Previous attempts to create automated IVUS segmentation systems have suffered from either a cost function that does not include enough information, or from a non-optimal segmentation algorithm. The approach presented in this paper seeks to strengthen both of those weaknesses -- first by building a robust, knowledge-based cost function, and then by using a fully optimal, three-dimensional segmentation algorithm. The cost function contains three categories of information: a compendium of learned border patterns, information theoretic and statistical properties related to the imaging physics, and local image features. By combining these criteria in an optimal way, weaknesses associated with cost functions that only try to optimize a single criterion are minimized. This cost function is then used as the input to a fully optimal, three-dimensional, graph search-based segmentation algorithm. The resulting system has been validated against a set of manually traced IVUS image sets. Results did not show any bias, with a mean unsigned luminal border positioning error of 0.180 +/- 0.027 mm and an adventitial border positioning error of 0.200 +/- 0.069 mm.

  19. TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes.

    PubMed

    Zhao, Min; Kim, Pora; Mitra, Ramkrishna; Zhao, Junfei; Zhao, Zhongming

    2016-01-04

    Tumor suppressor genes (TSGs) are a major type of gatekeeper genes in the cell growth. A knowledgebase with the systematic collection and curation of TSGs in multiple cancer types is critically important for further studying their biological functions as well as for developing therapeutic strategies. Since its development in 2012, the Tumor Suppressor Gene database (TSGene), has become a popular resource in the cancer research community. Here, we reported the TSGene version 2.0, which has substantial updates of contents (e.g. up-to-date literature and pan-cancer genomic data collection and curation), data types (noncoding RNAs and protein-coding genes) and content accessibility. Specifically, the current TSGene 2.0 contains 1217 human TSGs (1018 protein-coding and 199 non-coding genes) curated from over 9000 articles. Additionally, TSGene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Cancer Genome Atlas. A new web interface is available at http://bioinfo.mc.vanderbilt.edu/TSGene/. Systematic analyses of 199 non-coding TSGs provide numerous cancer-specific non-coding mutational events for further screening and clinical use. Intriguingly, we identified 49 protein-coding TSGs that were consistently down-regulated in 11 cancer types. In summary, TSGene 2.0, which is the only available database for TSGs, provides the most updated TSGs and their features in pan-cancer. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  20. Temporal and spatial analysis in knowledge-based physics problem-solving

    NASA Astrophysics Data System (ADS)

    Lee, Xiang-Seng

    Physics problems as stated in textbooks are typically informal and incomplete, and not amenable to the direct application of the general laws of physics. A theory of analysis for automatically solving such problems is presented. In particular, the theory provides a detailed methodology for constructing a formal problem representation, called physical representation, upon which physics laws may be appropriately selected and instantiated. With the equations generated by these laws, the solutions to these problems are obtained through strictly mathematical manipulations. This theory provides a well-structured domain language, in which it is relatively easy to state mechanical knowledge and mechanics problems. In the language the notion of basic physical phenomenon for representing the knowledge of physical situations and events is introduced. This notion serves as both the building block for the physical representation and as a vehicle for accessing the appropriate physical laws. Both basic physical phenomena and more traditional temporal entities, instants, and intervals may be used as time references. This dual-system representation facilitates bi-level abstractions of time necessary to avoid discontinuities introduced by short impulsive phenomena, e.g., collisions, and corresponds well with human-like temporal reasoning. The language also includes an ontology of space, using multiple abstractions to account for its inherent complexity, and representation schemes for physical laws and equations. The other key ingredient of the theory is a repertoire of ordered knowledge sources, formulated to specify the derivation procedures of a physical representation. The domain language, in which these knowledge sources are written, has a structure which is useful as a theoretical basis for determining their ordering and inference step sizes. This practice has proven crucial for building knowledge-based systems that are easy to debug and modify. The theory was implemented and

  1. A knowledge-based imaging informatics approach for managing proton beam therapy of cancer patients.

    PubMed

    Liu, Brent J

    2007-08-01

    The need for a unified patient-oriented information system to handle complex proton therapy (PT) imaging and informatics data during the course of patient treatment is becoming steadily apparent due to the ever increasing demands for better diagnostic treatment planning and more accurate information. Currently, this information is scattered throughout each of the different treatment and information systems in the oncology department. Furthermore, the lack of organization with standardized methods makes it difficult and time-consuming to navigate through the maze of data, resulting in challenges during patient treatment planning. We present a methodology to develop this electronic patient record (ePR) system based on DICOM standards and perform knowledge-based medical imaging informatics research on specific clinical scenarios where patients are treated with PT. Treatment planning is similar in workflow to traditional radiation therapy (RT) methods such as intensity-modulated radiation therapy (IMRT), which utilizes a priori knowledge to drive the treatment plan in an inverse manner. In March 2006, two new RT objects were drafted in a DICOM-RT Supplement 102 specifically for ion therapy, which includes PT. The standardization of DICOM-RT-ION objects and the development of a knowledge base as well as decision-support tools that can be add-on features to the ePR DICOM-RT system were researched. This methodology can be used to extend to PT and the development of future clinical decision-making scenarios during the course of the patient's treatment that utilize "inverse treatment planning." We present the initial steps of this imaging and informatics methodology for PT and lay the foundation for development of future decision-support tools tailored to cancer patients treated with PT. By integrating decision-support knowledge and tools designed to assist in the decision-making process, a new and improved "knowledge-enhanced treatment planning" approach can be realized.

  2. Combining elements of information fusion and knowledge-based systems to support situation analysis

    NASA Astrophysics Data System (ADS)

    Roy, Jean

    2006-04-01

    Situation awareness has emerged as an important concept in military and public security environments. Situation analysis is defined as a process, the examination of a situation, its elements, and their relations, to provide and maintain a product, i.e., a state of situation awareness for the decision maker(s). It is well established that information fusion, defined as the process of utilizing one or more information sources over time to assemble a representation of aspects of interest in an environment, is a key enabler to meeting the demanding requirements of situation analysis. However, although information fusion is important, developing and adopting a knowledge-centric view of situation analysis should provide a more holistic perspective of this process. This is based on the notion that awareness ultimately has to do with having knowledge of something. Moreover, not all of the situation elements and relationships of interest are directly observable. Those aspects of interest that cannot be observed must be inferred, i.e., derived as a conclusion from facts or premises, or by reasoning from evidence. This paper discusses aspects of knowledge, and how it can be acquired from experts, formally represented and stored in knowledge bases to be exploited by computer programs, and validated. Knowledge engineering is reviewed, with emphasis given to cognitive and ontological engineering. Facets of reasoning are discussed, along with inferencing methods that can be used in computer applications. Finally, combining elements of information fusion and knowledge-based systems, an overall approach and framework for the building of situation analysis support systems is presented.

  3. Chemogenomics knowledgebased polypharmacology analyses of drug abuse related G-protein coupled receptors and their ligands

    PubMed Central

    Xie, Xiang-Qun; Wang, Lirong; Liu, Haibin; Ouyang, Qin; Fang, Cheng; Su, Weiwei

    2013-01-01

    Drug abuse (DA) and addiction is a complex illness, broadly viewed as a neurobiological impairment with genetic and environmental factors that influence its development and manifestation. Abused substances can disrupt the activity of neurons by interacting with many proteins, particularly G-protein coupled receptors (GPCRs). A few medicines that target the central nervous system (CNS) can also modulate DA related proteins, such as GPCRs, which can act in conjunction with the controlled psychoactive substance(s) and increase side effects. To fully explore the molecular interaction networks that underlie DA and to effectively modulate the GPCRs in these networks with small molecules for DA treatment, we built a drug-abuse domain specific chemogenomics knowledgebase (DA-KB) to centralize the reported chemogenomics research information related to DA and CNS disorders in an effort to benefit researchers across a broad range of disciplines. We then focus on the analysis of GPCRs as many of them are closely related with DA. Their distribution in human tissues was also analyzed for the study of side effects caused by abused drugs. We further implement our computational algorithms/tools to explore DA targets, DA mechanisms and pathways involved in polydrug addiction and to explore polypharmacological effects of the GPCR ligands. Finally, the polypharmacology effects of GPCRs-targeted medicines for DA treatment were investigated and such effects can be exploited for the development of drugs with polypharmacophore for DA intervention. The chemogenomics database and the analysis tools will help us better understand the mechanism of drugs abuse and facilitate to design new medications for system pharmacotherapy of DA. PMID:24567719

  4. Ab Initio Protein Structure Assembly Using Continuous Structure Fragments and Optimized Knowledge-based Force Field

    PubMed Central

    Xu, Dong; Zhang, Yang

    2012-01-01

    Ab initio protein folding is one of the major unsolved problems in computational biology due to the difficulties in force field design and conformational search. We developed a novel program, QUARK, for template-free protein structure prediction. Query sequences are first broken into fragments of 1–20 residues where multiple fragment structures are retrieved at each position from unrelated experimental structures. Full-length structure models are then assembled from fragments using replica-exchange Monte Carlo simulations, which are guided by a composite knowledge-based force field. A number of novel energy terms and Monte Carlo movements are introduced and the particular contributions to enhancing the efficiency of both force field and search engine are analyzed in detail. QUARK prediction procedure is depicted and tested on the structure modeling of 145 non-homologous proteins. Although no global templates are used and all fragments from experimental structures with template modeling score (TM-score) >0.5 are excluded, QUARK can successfully construct 3D models of correct folds in 1/3 cases of short proteins up to 100 residues. In the ninth community-wide Critical Assessment of protein Structure Prediction (CASP9) experiment, QUARK server outperformed the second and third best servers by 18% and 47% based on the cumulative Z-score of global distance test-total (GDT-TS) scores in the free modeling (FM) category. Although ab initio protein folding remains a significant challenge, these data demonstrate new progress towards the solution of the most important problem in the field. PMID:22411565

  5. Transferability of Empirical Potentials and the Knowledgebase of Interatomic Models (KIM)

    NASA Astrophysics Data System (ADS)

    Karls, Daniel S.

    Empirical potentials have proven to be an indispensable tool in understanding complex material behavior at the atomic scale due to their unrivaled computational efficiency. However, as they are currently used in the materials community, the realization of their full utility is stifled by a number of implementational difficulties. An emerging project specifically aimed to address these problems is the Knowledgebase of Interatomic Models (KIM). The primary purpose of KIM is to serve as an open-source, publically accessible repository of standardized implementations of empirical potentials (Models), simulation codes which use them to compute material properties (Tests), and first-principles/experimental data corresponding to these properties (Reference Data). Aside from eliminating the redundant expenditure of scientific resources and the irreproducibility of results computed using empirical potentials, a unique benefit offered by KIM is the ability to gain a further understanding of a Model's transferability, i.e. its ability to make accurate predictions for material properties which it was not fitted to reproduce. In the present work, we begin by surveying the various classes of mathematical representations of atomic environments which are used to define empirical potentials. We then proceed to offer a broad characterization of empirical potentials in the context of machine learning which reveals three distinct categories with which any potential may be associated. Combining one of the aforementioned representations of atomic environments with a suitable regression technique, we define the Regression Algorithm for Transferability Estimation (RATE), which permits a quantitative estimation of the transferability of an arbitrary potential. Finally, we demonstrate the application of RATE to a specific training set consisting of bulk structures, clusters, surfaces, and nanostructures of silicon. A specific analysis of the underlying quantities inferred by RATE which are

  6. Consistent Refinement of Submitted Models at CASP using a Knowledge-based Potential

    PubMed Central

    Chopra, Gaurav; Kalisman, Nir; Levitt, Michael

    2010-01-01

    Protein structure refinement is an important but unsolved problem; it must be solved if we are to predict biological function that is very sensitive to structural details. Specifically, Critical Assessment of Techniques for Protein Structure Prediction (CASP) shows that the accuracy of predictions in the comparative modeling category is often worse than that of the template on which the homology model is based. Here we describe a refinement protocol that is able to consistently refine submitted predictions for all categories at CASP7. The protocol uses direct energy minimization of the knowledge-based potential of mean force that is based on the interaction statistics of 167 atom types (Summa and Levitt, Proc Natl Acad Sci USA 2007; 104:3177–3182). Our protocol is thus computationally very efficient; it only takes a few minutes of CPU time to run typical protein models (300 residues). We observe an average structural improvement of 1% in GDT_TS, for predictions that have low and medium homology to known PDB structures (Global Distance Test score or GDT_TS between 50 and 80%). We also observe a marked improvement in the stereochemistry of the models. The level of improvement varies amongst the various participants at CASP, but we see large improvements (>10% increase in GDT_TS) even for models predicted by the best performing groups at CASP7. In addition, our protocol consistently improved the best predicted models in the refinement category at CASP7 and CASP8. These improvements in structure and stereochemistry prove the usefulness of our computationally inexpensive, powerful and automatic refinement protocol. PMID:20589633

  7. MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases

    PubMed Central

    2012-01-01

    Background Increasingly, metabolite and reaction information is organized in the form of genome-scale metabolic reconstructions that describe the reaction stoichiometry, directionality, and gene to protein to reaction associations. A key bottleneck in the pace of reconstruction of new, high-quality metabolic models is the inability to directly make use of metabolite/reaction information from biological databases or other models due to incompatibilities in content representation (i.e., metabolites with multiple names across databases and models), stoichiometric errors such as elemental or charge imbalances, and incomplete atomistic detail (e.g., use of generic R-group or non-explicit specification of stereo-specificity). Description MetRxn is a knowledgebase that includes standardized metabolite and reaction descriptions by integrating information from BRENDA, KEGG, MetaCyc, Reactome.org and 44 metabolic models into a single unified data set. All metabolite entries have matched synonyms, resolved protonation states, and are linked to unique structures. All reaction entries are elementally and charge balanced. This is accomplished through the use of a workflow of lexicographic, phonetic, and structural comparison algorithms. MetRxn allows for the download of standardized versions of existing genome-scale metabolic models and the use of metabolic information for the rapid reconstruction of new ones. Conclusions The standardization in description allows for the direct comparison of the metabolite and reaction content between metabolic models and databases and the exhaustive prospecting of pathways for biotechnological production. This ever-growing dataset currently consists of over 76,000 metabolites participating in more than 72,000 reactions (including unresolved entries). MetRxn is hosted on a web-based platform that uses relational database models (MySQL). PMID:22233419

  8. Knowledge-Based Methods To Train and Optimize Virtual Screening Ensembles

    PubMed Central

    2016-01-01

    Ensemble docking can be a successful virtual screening technique that addresses the innate conformational heterogeneity of macromolecular drug targets. Yet, lacking a method to identify a subset of conformational states that effectively segregates active and inactive small molecules, ensemble docking may result in the recommendation of a large number of false positives. Here, three knowledge-based methods that construct structural ensembles for virtual screening are presented. Each method selects ensembles by optimizing an objective function calculated using the receiver operating characteristic (ROC) curve: either the area under the ROC curve (AUC) or a ROC enrichment factor (EF). As the number of receptor conformations, N, becomes large, the methods differ in their asymptotic scaling. Given a set of small molecules with known activities and a collection of target conformations, the most resource intense method is guaranteed to find the optimal ensemble but scales as O(2N). A recursive approximation to the optimal solution scales as O(N2), and a more severe approximation leads to a faster method that scales linearly, O(N). The techniques are generally applicable to any system, and we demonstrate their effectiveness on the androgen nuclear hormone receptor (AR), cyclin-dependent kinase 2 (CDK2), and the peroxisome proliferator-activated receptor δ (PPAR-δ) drug targets. Conformations that consisted of a crystal structure and molecular dynamics simulation cluster centroids were used to form AR and CDK2 ensembles. Multiple available crystal structures were used to form PPAR-δ ensembles. For each target, we show that the three methods perform similarly to one another on both the training and test sets. PMID:27097522

  9. LCG Persistency Framework (CORAL, COOL, POOL): Status and Outlook

    SciTech Connect

    Valassi, A.; Clemencic, M.; Dykstra, D.; Frank, M.; Front, D.; Govi, G.; Kalkhof, A.; Loth, A.; Nowak, M.; Pokorski, W.; Salnikov, A.; Schmidt, S.A.; Trentadue, R.; Wache, M.; Xie, Z.; /Princeton U.

    2012-04-19

    The Persistency Framework consists of three software packages (CORAL, COOL and POOL) addressing the data access requirements of the LHC experiments in different areas. It is the result of the collaboration between the CERN IT Department and the three experiments (ATLAS, CMS and LHCb) that use this software to access their data. POOL is a hybrid technology store for C++ objects, metadata catalogs and collections. CORAL is a relational database abstraction layer with an SQL-free API. COOL provides specific software tools and components for the handling of conditions data. This paper reports on the status and outlook of the project and reviews in detail the usage of each package in the three experiments.

  10. D0 data processing within EDG/LCG

    SciTech Connect

    Harenberg, Torsten; Bos, Kors; Byrom, Rob; Fisher, Steve; Groep, David; van Leeuwen, Willem; Mattig, Peter; Templon, Jeff; /NIKHEF, Amsterdam

    2004-12-01

    In September 2003, the D0 experiment at TEvatron has launched a reprocessing effort. In total 519,212,822 of the experiment's events have been reprocessed to use the new perceptions of the detector's behavior. Out of these events 97,619,114 have been reprocessed at remote sites. For the first time, the European DataGRID has been used to re-process a part of these events as an evaluation of the EDG application testbed. They used EDG's own R-GMA database for monitoring and bookkeeping and constructed four tables: (1) submission table--records the submission of jobs to the Resource Broker; (2) job start table--holds the time the job started on a Worker Node together with process ID and many more; (3) job end table--information is published immediately before the job stops; and (4) command table--a command list table for debugging purposes. As D0 has its own data management system called ''SAM'', some sort of channel between SAM and the EDG data management system is required. The approach used is shown to the left, were a certain storage area, physically present on a back-end server machine, is visible both from a SAM-enabled machine (''SAM station'') and from EDG machines at the same site. This has bene achieved at NIKHEF. The D0 software has been adapted to run in the EDG framework. Only a few changes has to be made. Missing libraries were included and some extra packages were shipped (pyxml and Python 2.1). However, arounding wrapper scripts were written to handle the in- and output and put/get it from/to EDG's Data Management System (DMS).

  11. A knowledge-based approach to estimating the magnitude and spatial patterns of potential threats to soil biodiversity.

    PubMed

    Orgiazzi, Alberto; Panagos, Panos; Yigini, Yusuf; Dunbar, Martha B; Gardi, Ciro; Montanarella, Luca; Ballabio, Cristiano

    2016-03-01

    Because of the increasing pressures exerted on soil, below-ground life is under threat. Knowledge-based rankings of potential threats to different components of soil biodiversity were developed in order to assess the spatial distribution of threats on a European scale. A list of 13 potential threats to soil biodiversity was proposed to experts with different backgrounds in order to assess the potential for three major components of soil biodiversity: soil microorganisms, fauna, and biological functions. This approach allowed us to obtain knowledge-based rankings of threats. These classifications formed the basis for the development of indices through an additive aggregation model that, along with ad-hoc proxies for each pressure, allowed us to preliminarily assess the spatial patterns of potential threats. Intensive exploitation was identified as the highest pressure. In contrast, the use of genetically modified organisms in agriculture was considered as the threat with least potential. The potential impact of climate change showed the highest uncertainty. Fourteen out of the 27 considered countries have more than 40% of their soils with moderate-high to high potential risk for all three components of soil biodiversity. Arable soils are the most exposed to pressures. Soils within the boreal biogeographic region showed the lowest risk potential. The majority of soils at risk are outside the boundaries of protected areas. First maps of risks to three components of soil biodiversity based on the current scientific knowledge were developed. Despite the intrinsic limits of knowledge-based assessments, a remarkable potential risk to soil biodiversity was observed. Guidelines to preliminarily identify and circumscribe soils potentially at risk are provided. This approach may be used in future research to assess threat at both local and global scale and identify areas of possible risk and, subsequently, design appropriate strategies for monitoring and protection of soil

  12. Development of Design-a-Trial, a knowledge-based critiquing system for authors of clinical trial protocols.

    PubMed

    Wyatt, J C; Altman, D G; Heathfield, H A; Pantin, C F

    1994-06-01

    Many published clinical trials are poorly designed, suggesting that the protocol was incomplete, disorganised or contained errors. This fact, doctors' limited statistical skills and the shortage of medical statisticians, prompted us to develop a knowledge-based aid, Design-a-Trial, for authors of clinical trial protocols. This interviews a physician, prompts them with suitable design options, comments on the statistical rigour and feasibility of their proposed design and generates a 6-page draft protocol document. This paper outlines the process used to develop Design-a-Trial, presents preliminary evaluation results, and discusses lessons we learned which may apply to the developed of other medical decision-aids.

  13. A Hybrid Knowledge-Based and Empirical Scoring Function for Protein-Ligand Interaction: SMoG2016.

    PubMed

    Debroise, Théau; Shakhnovich, Eugene I; Chéron, Nicolas

    2017-03-27

    We present the third generation of our scoring function for the prediction of protein-ligand binding free energy. This function is now a hybrid between a knowledge-based potential and an empirical function. We constructed a diversified set of ∼1000 complexes from the PDBBinding-CN database for the training of the function, and we show that this number of complexes generates enough data to build the potential. The occurrence of 420 different types of atomic pairwise interactions is computed in up to five different ranges of distances to derive the knowledge-based part. All of the parameters were optimized, and we were able to considerably improve the accuracy of the scoring function with a Pearson correlation coefficient against experimental binding free energies of up to 0.57, which ranks our new scoring function as one of the best currently available and the second-best in terms of standard deviation (SD = 1.68 kcal/mol). The function was then further improved by inclusion of different terms taking into account repulsion and loss of entropy upon binding, and we show that it is capable of recovering native binding poses up to 80% of the time. All of the programs, tools, and protein sets are released in the Supporting Information or as open-source programs.

  14. Development of the knowledge-based and empirical combined scoring algorithm (KECSA) to score protein-ligand interactions.

    PubMed

    Zheng, Zheng; Merz, Kenneth M

    2013-05-24

    We describe a novel knowledge-based protein-ligand scoring function that employs a new definition for the reference state, allowing us to relate a statistical potential to a Lennard-Jones (LJ) potential. In this way, the LJ potential parameters were generated from protein-ligand complex structural data contained in the Protein Databank (PDB). Forty-nine (49) types of atomic pairwise interactions were derived using this method, which we call the knowledge-based and empirical combined scoring algorithm (KECSA). Two validation benchmarks were introduced to test the performance of KECSA. The first validation benchmark included two test sets that address the training set and enthalpy/entropy of KECSA. The second validation benchmark suite included two large-scale and five small-scale test sets, to compare the reproducibility of KECSA, with respect to two empirical score functions previously developed in our laboratory (LISA and LISA+), as well as to other well-known scoring methods. Validation results illustrate that KECSA shows improved performance in all test sets when compared with other scoring methods, especially in its ability to minimize the root mean square error (RMSE). LISA and LISA+ displayed similar performance using the correlation coefficient and Kendall τ as the metric of quality for some of the small test sets. Further pathways for improvement are discussed for which would allow KECSA to be more sensitive to subtle changes in ligand structure.

  15. A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.

    PubMed

    Thiele, Ines; Hyduke, Daniel R; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan M T; Hsiung, Chao A; De Keersmaecker, Sigrid C J; Liao, Yu-Chieh; Marchal, Kathleen; Mo, Monica L; Özdemir, Emre; Raghunathan, Anu; Reed, Jennifer L; Shin, Sook-il; Sigurbjörnsdóttir, Sara; Steinmann, Jonas; Sudarsan, Suresh; Swainston, Neil; Thijs, Inge M; Zengler, Karsten; Palsson, Bernhard O; Adkins, Joshua N; Bumann, Dirk

    2011-01-18

    Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

  16. Development of an intelligent interface for adding spatial objects to a knowledge-based geographic information system

    NASA Technical Reports Server (NTRS)

    Campbell, William J.; Goettsche, Craig

    1989-01-01

    Earth Scientists lack adequate tools for quantifying complex relationships between existing data layers and studying and modeling the dynamic interactions of these data layers. There is a need for an earth systems tool to manipulate multi-layered, heterogeneous data sets that are spatially indexed, such as sensor imagery and maps, easily and intelligently in a single system. The system can access and manipulate data from multiple sensor sources, maps, and from a learned object hierarchy using an advanced knowledge-based geographical information system. A prototype Knowledge-Based Geographic Information System (KBGIS) was recently constructed. Many of the system internals are well developed, but the system lacks an adequate user interface. A methodology is described for developing an intelligent user interface and extending KBGIS to interconnect with existing NASA systems, such as imagery from the Land Analysis System (LAS), atmospheric data in Common Data Format (CDF), and visualization of complex data with the National Space Science Data Center Graphics System. This would allow NASA to quickly explore the utility of such a system, given the ability to transfer data in and out of KBGIS easily. The use and maintenance of the object hierarchies as polymorphic data types brings, to data management, a while new set of problems and issues, few of which have been explored above the prototype level.

  17. Personal profile of medical students selected through a knowledge-based exam only: are we missing suitable students?

    PubMed Central

    Abbiati, Milena; Baroffio, Anne; Gerbase, Margaret W.

    2016-01-01

    Introduction A consistent body of literature highlights the importance of a broader approach to select medical school candidates both assessing cognitive capacity and individual characteristics. However, selection in a great number of medical schools worldwide is still based on knowledge exams, a procedure that might neglect students with needed personal characteristics for future medical practice. We investigated whether the personal profile of students selected through a knowledge-based exam differed from those not selected. Methods Students applying for medical school (N=311) completed questionnaires assessing motivations for becoming a doctor, learning approaches, personality traits, empathy, and coping styles. Selection was based on the results of MCQ tests. Principal component analysis was used to draw a profile of the students. Differences between selected and non-selected students were examined by Multivariate ANOVAs, and their impact on selection by logistic regression analysis. Results Students demonstrating a profile of diligence with higher conscientiousness, deep learning approach, and task-focused coping were more frequently selected (p=0.01). Other personal characteristics such as motivation, sociability, and empathy did not significantly differ, comparing selected and non-selected students. Conclusion Selection through a knowledge-based exam privileged diligent students. It did neither advantage nor preclude candidates with a more humane profile. PMID:27079886

  18. Automatic glioma characterization from dynamic susceptibility contrast imaging: brain tumor segmentation using knowledge-based fuzzy clustering.

    PubMed

    Emblem, Kyrre E; Nedregaard, Baard; Hald, John K; Nome, Terje; Due-Tonnessen, Paulina; Bjornerud, Atle

    2009-07-01

    To assess whether glioma volumes from knowledge-based fuzzy c-means (FCM) clustering of multiple MR image classes can provide similar diagnostic efficacy values as manually defined tumor volumes when characterizing gliomas from dynamic susceptibility contrast (DSC) imaging. Fifty patients with newly diagnosed gliomas were imaged using DSC MR imaging at 1.5 Tesla. To compare our results with manual tumor definitions, glioma volumes were also defined independently by four neuroradiologists. Using a histogram analysis method, diagnostic efficacy values for glioma grade and expected patient survival were assessed. The areas under the receiver operator characteristics curves were similar when using manual and automated tumor volumes to grade gliomas (P = 0.576-0.970). When identifying a high-risk patient group (expected survival <2 years) and a low-risk patient group (expected survival >2 years), a higher log-rank value from Kaplan-Meier survival analysis was observed when using automatic tumor volumes (14.403; P < 0.001) compared with the manual volumes (10.650-12.761; P = 0.001-0.002). Our results suggest that knowledge-based FCM clustering of multiple MR image classes provides a completely automatic, user-independent approach to selecting the target region for presurgical glioma characterization. (c) 2009 Wiley-Liss, Inc.

  19. A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

    SciTech Connect

    Thiele, Ines; Hyduke, Daniel R.; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K.; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan MT; Hsiung, Chao A.; De Keersmaecker, Sigrid CJ; Liao, Yu-Chieh; Marchal, Kathleen; Mo, Monica L.; Özdemir, Emre; Raghunathan, Anu; Reed, Jennifer L.; Shin, Sook-Il; Sigurbjörnsdóttir, Sara; Steinmann, Jonas; Sudarsan, Suresh; Swainston, Neil; Thijs, Inge M.; Zengler, Karsten; Palsson, Bernhard O.; Adkins, Joshua N.; Bumann, Dirk

    2011-01-01

    Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Finally, taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

  20. Ontology-Driven Knowledge-Based Health-Care System, An Emerging Area - Challenges And Opportunities - Indian Scenario

    NASA Astrophysics Data System (ADS)

    Sunitha, A.; Babu, G. Suresh

    2014-11-01

    Recent studies in the decision making efforts in the area of public healthcare systems have been tremendously inspired and influenced by the entry of ontology. Ontology driven systems results in the effective implementation of healthcare strategies for the policy makers. The central source of knowledge is the ontology containing all the relevant domain concepts such as locations, diseases, environments and their domain sensitive inter-relationships which is the prime objective, concern and the motivation behind this paper. The paper further focuses on the development of a semantic knowledge-base for public healthcare system. This paper describes the approach and methodologies in bringing out a novel conceptual theme in establishing a firm linkage between three different ontologies related to diseases, places and environments in one integrated platform. This platform correlates the real-time mechanisms prevailing within the semantic knowledgebase and establishing their inter-relationships for the first time in India. This is hoped to formulate a strong foundation for establishing a much awaited basic need for a meaningful healthcare decision making system in the country. Introduction through a wide range of best practices facilitate the adoption of this approach for better appreciation, understanding and long term outcomes in the area. The methods and approach illustrated in the paper relate to health mapping methods, reusability of health applications, and interoperability issues based on mapping of the data attributes with ontology concepts in generating semantic integrated data driving an inference engine for user-interfaced semantic queries.

  1. The effect of a knowledge-based ergonomic intervention amongst administrators at Aga Khan University Hospital, Nairobi.

    PubMed

    Wanyonyi, Nancy; Frantz, Jose; Saidi, Hassan

    2015-01-01

    Low back pain (LBP) and neck pain are part of the common work-related musculoskeletal disorders with a large impact on the affected person. Despite having a multifactorial aetiology, ergonomic factors play a major role thus necessitating workers' education. To determine the prevalence of ergonomic-related LBP and neck pain, and describe the effect of a knowledge-based ergonomic intervention amongst administrators in Aga Khan University Hospital, Nairobi. This study applied a mixed method design utilizing a survey and two focus group discussions (FGD). A self-administered questionnaire was distributed to 208 participants through systematic sampling. A one hour knowledge-based ergonomic session founded on the survey results was thereafter administered to interested participants, followed by two FGDs a month later with purposive selection of eight participants to explore their experience of the ergonomic intervention. Quantitative data was captured and analyzed using SPSS by means of descriptive and inferential statistics, whereas thematic content analysis was used for qualitative data. Most participants were knowledgeable about ergonomic-related LBP and neck pain with a twelve month prevalence of 75.5% and 67.8% respectively. Continual ergonomic education is necessary for adherence to health-related behaviours that will preventwork-related LBP and neck pain.

  2. Development of the Knowledge-based & Empirical Combined Scoring Algorithm (KECSA) to Score Protein-Ligand Interactions

    PubMed Central

    Zheng, Zheng

    2013-01-01

    We describe a novel knowledge-based protein-ligand scoring function that employs a new definition for the reference state, allowing us to relate a statistical potential to a Lennard-Jones (LJ) potential. In this way, the LJ potential parameters were generated from protein-ligand complex structural data contained in the PDB. Forty-nine types of atomic pairwise interactions were derived using this method, which we call the knowledge-based and empirical combined scoring algorithm (KECSA). Two validation benchmarks were introduced to test the performance of KECSA. The first validation benchmark included two test sets that address the training-set and enthalpy/entropy of KECSA The second validation benchmark suite included two large-scale and five small-scale test sets to compare the reproducibility of KECSA with respect to two empirical score functions previously developed in our laboratory (LISA and LISA+), as well as to other well-known scoring methods. Validation results illustrate that KECSA shows improved performance in all test sets when compared with other scoring methods especially in its ability to minimize the RMSE. LISA and LISA+ displayed similar performance using the correlation coefficient and Kendall τ as the metric of quality for some of the small test sets. Further pathways for improvement are discussed which would KECSA more sensitive to subtle changes in ligand structure. PMID:23560465

  3. A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

    PubMed Central

    2011-01-01

    Background Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Results Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Conclusion Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation. PMID:21244678

  4. MO-FG-303-03: Demonstration of Universal Knowledge-Based 3D Dose Prediction

    SciTech Connect

    Shiraishi, S; Moore, K L

    2015-06-15

    Purpose: To demonstrate a knowledge-based 3D dose prediction methodology that can accurately predict achievable radiotherapy distributions. Methods: Using previously treated plans as input, an artificial neural network (ANN) was trained to predict 3D dose distributions based on 14 patient-specific anatomical parameters including the distance (r) to planning target volume (PTV) boundary, organ-at-risk (OAR) boundary distances, and angular position ( θ,φ). 23 prostate and 49 stereotactic radiosurgery (SRS) cases with ≥1 nearby OARs were studied. All were planned with volumetric-modulated arc therapy (VMAT) to prescription doses of 81Gy for prostate and 12–30Gy for SRS. Site-specific ANNs were trained using all prostate 23 plans and using a 24 randomly-selected subset for the SRS model. The remaining 25 SRS plans were used to validate the model. To quantify predictive accuracy, the dose difference between the clinical plan and prediction were calculated on a voxel-by-voxel basis δD(r,θ,φ)=Dclin(r,θ,φ)-Dpred(r, θ,φ). Grouping voxels by boundary distance, the mean <δ Dr>=(1/N)Σ -θ,φ D(r,θ,φ) and inter-quartile range (IQR) quantified the accuracy of this method for deriving DVH estimations. The standard deviation (σ) of δ D quantified the 3D dose prediction error on a voxel-by-voxel basis. Results: The ANNs were highly accurate in predictive ability for both prostate and SRS plans. For prostate, <δDr> ranged from −0.8% to +0.6% (max IQR=3.8%) over r=0–32mm, while 3D dose prediction accuracy averaged from σ=5–8% across the same range. For SRS, from r=0–34mm the training set <δDr> ranged from −3.7% to +1.5% (max IQR=4.4%) while the validation set <δDr> ranged from −2.2% to +5.8% (max IQR=5.3%). 3D dose prediction accuracy averaged σ=2.5% for the training set and σ=4.0% over the same interval. Conclusion: The study demonstrates this technique’s ability to predict achievable 3D dose distributions for VMAT SRS and prostate. Future

  5. Architecture for Knowledge-Based and Federated Search of Online Clinical Evidence

    PubMed Central

    Walther, Martin; Nguyen, Ken; Lovell, Nigel H

    2005-01-01

    Background It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. Objectives The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. Methods A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. Results Clinicians performed 1662 searches over the trial. The average search duration was 4.9 ± 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. Conclusions The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite

  6. Architecture for knowledge-based and federated search of online clinical evidence.

    PubMed

    Coiera, Enrico; Walther, Martin; Nguyen, Ken; Lovell, Nigel H

    2005-10-24

    It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. Clinicians performed 1662 searches over the trial. The average search duration was 4.9 +/- 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the

  7. Knowledge-based prediction of plan quality metrics in intracranial stereotactic radiosurgery

    SciTech Connect

    Shiraishi, Satomi; Moore, Kevin L.; Tan, Jun; Olsen, Lindsey A.

    2015-02-15

    Purpose: The objective of this work was to develop a comprehensive knowledge-based methodology for predicting achievable dose–volume histograms (DVHs) and highly precise DVH-based quality metrics (QMs) in stereotactic radiosurgery/radiotherapy (SRS/SRT) plans. Accurate QM estimation can identify suboptimal treatment plans and provide target optimization objectives to standardize and improve treatment planning. Methods: Correlating observed dose as it relates to the geometric relationship of organs-at-risk (OARs) to planning target volumes (PTVs) yields mathematical models to predict achievable DVHs. In SRS, DVH-based QMs such as brain V{sub 10Gy} (volume receiving 10 Gy or more), gradient measure (GM), and conformity index (CI) are used to evaluate plan quality. This study encompasses 223 linear accelerator-based SRS/SRT treatment plans (SRS plans) using volumetric-modulated arc therapy (VMAT), representing 95% of the institution’s VMAT radiosurgery load from the past four and a half years. Unfiltered models that use all available plans for the model training were built for each category with a stratification scheme based on target and OAR characteristics determined emergently through initial modeling process. Model predictive accuracy is measured by the mean and standard deviation of the difference between clinical and predicted QMs, δQM = QM{sub clin} − QM{sub pred}, and a coefficient of determination, R{sup 2}. For categories with a large number of plans, refined models are constructed by automatic elimination of suspected suboptimal plans from the training set. Using the refined model as a presumed achievable standard, potentially suboptimal plans are identified. Predictions of QM improvement are validated via standardized replanning of 20 suspected suboptimal plans based on dosimetric predictions. The significance of the QM improvement is evaluated using the Wilcoxon signed rank test. Results: The most accurate predictions are obtained when plans are

  8. Considering Human Capital Theory in Assessment and Training: Mapping the Gap between Current Skills and the Needs of a Knowledge-Based Economy in Northeast Iowa

    ERIC Educational Resources Information Center

    Mihm-Herold, Wendy

    2010-01-01

    In light of the current economic downturn, thousands of Iowans are unemployed and this is the ideal time to build the skills of the workforce to compete in the knowledge-based economy so businesses and entrepreneurs can compete in a global economy. A tool for assessing the skills and knowledge of dislocated workers and students as well as…

  9. Creating a Knowledge-Based Economy in the United Arab Emirates: Realising the Unfulfilled Potential of Women in the Science, Technology and Engineering Fields

    ERIC Educational Resources Information Center

    Aswad, Noor Ghazal; Vidican, Georgeta; Samulewicz, Diana

    2011-01-01

    As the United Arab Emirates (UAE) moves towards a knowledge-based economy, maximising the participation of the national workforce, especially women, in the transformation process is crucial. Using survey methods and semi-structured interviews, this paper examines the factors that influence women's decisions regarding their degree programme and…

  10. New Learning Models for the New Knowledge-Based Economy: Professional and Local-Personal Networks as a Source of Knowledge Development in the Multimedia Sector.

    ERIC Educational Resources Information Center

    Tremblay, Diane-Gabrielle

    The role of professional and local-personal networks as a source of knowledge development in the new knowledge-based economy was examined in a 15-month study that focuses on people working in the multimedia industry in Montreal, Quebec. The study focused on the modes of exchange and learning, collaborative work, and management and development of…

  11. Creating a Knowledge-Based Economy in the United Arab Emirates: Realising the Unfulfilled Potential of Women in the Science, Technology and Engineering Fields

    ERIC Educational Resources Information Center

    Aswad, Noor Ghazal; Vidican, Georgeta; Samulewicz, Diana

    2011-01-01

    As the United Arab Emirates (UAE) moves towards a knowledge-based economy, maximising the participation of the national workforce, especially women, in the transformation process is crucial. Using survey methods and semi-structured interviews, this paper examines the factors that influence women's decisions regarding their degree programme and…

  12. An Emerging Knowledge-Based Economy in China? Indicators from OECD Databases. OECD Science, Technology and Industry Working Papers, 2004/4

    ERIC Educational Resources Information Center

    Criscuolo, Chiara; Martin, Ralf

    2004-01-01

    The main objective of this Working Paper is to show a set of indicators on the knowledge-based economy for China, mainly compiled from databases within EAS, although data from databases maintained by other parts of the OECD are included as well. These indicators are put in context by comparison with data for the United States, Japan and the EU (or…

  13. An Emerging Knowledge-Based Economy in China? Indicators from OECD Databases. OECD Science, Technology and Industry Working Papers, 2004/4

    ERIC Educational Resources Information Center

    Criscuolo, Chiara; Martin, Ralf

    2004-01-01

    The main objective of this Working Paper is to show a set of indicators on the knowledge-based economy for China, mainly compiled from databases within EAS, although data from databases maintained by other parts of the OECD are included as well. These indicators are put in context by comparison with data for the United States, Japan and the EU (or…

  14. Reflexive Professionalism as a Second Generation of Evidence-Based Practice: Some Considerations on the Special Issue "What Works? Modernizing the Knowledge-Base of Social Work"

    ERIC Educational Resources Information Center

    Otto, Hans-Uwe; Polutta, Andreas; Ziegler, Holger

    2009-01-01

    This article refers sympathetically to the thoughtful debates and positions in the "Research on Social Work Practice" ("RSWP"; Special Issue, July, 2008 issue) on "What Works? Modernizing the Knowledge-Base of Social Work." It highlights the need for empirical efficacy and effectiveness research in social work and…

  15. Considering Human Capital Theory in Assessment and Training: Mapping the Gap between Current Skills and the Needs of a Knowledge-Based Economy in Northeast Iowa

    ERIC Educational Resources Information Center

    Mihm-Herold, Wendy

    2010-01-01

    In light of the current economic downturn, thousands of Iowans are unemployed and this is the ideal time to build the skills of the workforce to compete in the knowledge-based economy so businesses and entrepreneurs can compete in a global economy. A tool for assessing the skills and knowledge of dislocated workers and students as well as…

  16. Photon Optimizer (PO) prevails over Progressive Resolution Optimizer (PRO) for VMAT planning with or without knowledge-based solution.

    PubMed

    Jiang, Fan; Wu, Hao; Yue, Haizhen; Jia, Fei; Zhang, Yibao

    2017-03-01

    The enhanced dosimetric performance of knowledge-based volumetric modulated arc therapy (VMAT) planning might be jointly contributed by the patient-specific optimization objectives, as estimated by the RapidPlan model, and by the potentially improved Photon Optimizer (PO) algorithm than the previous Progressive Resolution Optimizer (PRO) engine. As PO is mandatory for RapidPlan estimation but optional for conventional manual planning, appreciating the two optimizers may provide practical guidelines for the algorithm selection because knowledge-based planning may not replace the current method completely in a short run. Using a previously validated dose-volume histogram (DVH) estimation model which can produce clinically acceptable plans automatically for rectal cancer patients without interactive manual adjustment, this study reoptimized 30 historically approved plans (referred as clinical plans that were created manually with PRO) with RapidPlan solution (PO plans). Then the PRO algorithm was utilized to optimize the plans again using the same dose-volume constraints as PO plans, where the line objectives were converted as a series of point objectives automatically (PRO plans). On the basis of comparable target dose coverage, the combined applications of new objectives and PO algorithm have significantly reduced the organs-at-risk (OAR) exposure by 23.49-32.72% than the clinical plans. These discrepancies have been largely preserved after substituting PRO for PO, indicating the dosimetric improvements were mostly attributable to the refined objectives. Therefore, Eclipse users of earlier versions may instantly benefit from adopting the model-generated objectives from other RapidPlan-equipped centers, even with PRO algorithm. However, the additional contribution made by the PO relative to PRO accounted for 1.54-3.74%, suggesting PO should be selected with priority whenever available, with or without RapidPlan solution as a purchasable package. Significantly

  17. An intelligent, knowledge-based multiple criteria decision making advisor for systems design

    NASA Astrophysics Data System (ADS)

    Li, Yongchang

    of an appropriate decision making method. Furthermore, some DMs may be exclusively using one or two specific methods which they are familiar with or trust and not realizing that they may be inappropriate to handle certain classes of the problems, thus yielding erroneous results. These issues reveal that in order to ensure a good decision a suitable decision method should be chosen before the decision making process proceeds. The first part of this dissertation proposes an MCDM process supported by an intelligent, knowledge-based advisor system referred to as Multi-Criteria Interactive Decision-Making Advisor and Synthesis process (MIDAS), which is able to facilitate the selection of the most appropriate decision making method and which provides insight to the user for fulfilling different preferences. The second part of this dissertation presents an autonomous decision making advisor which is capable of dealing with ever-evolving real time information and making autonomous decisions under uncertain conditions. The advisor encompasses a Markov Decision Process (MDP) formulation which takes uncertainty into account when determines the best action for each system state. (Abstract shortened by UMI.)

  18. Intelligent personal navigator supported by knowledge-based systems for estimating dead reckoning navigation parameters

    NASA Astrophysics Data System (ADS)

    Moafipoor, Shahram

    Personal navigators (PN) have been studied for about a decade in different fields and applications, such as safety and rescue operations, security and emergency services, and police and military applications. The common goal of all these applications is to provide precise and reliable position, velocity, and heading information of each individual in various environments. In the PN system developed in this dissertation, the underlying assumption is that the system does not require pre-existing infrastructure to enable pedestrian navigation. To facilitate this capability, a multisensor system concept, based on the Global Positioning System (GPS), inertial navigation, barometer, magnetometer, and a human pedometry model has been developed. An important aspect of this design is to use the human body as navigation sensor to facilitate Dead Reckoning (DR) navigation in GPS-challenged environments. The system is designed predominantly for outdoor environments, where occasional loss of GPS lock may happen; however, testing and performance demonstration have been extended to indoor environments. DR navigation is based on a relative-measurement approach, with the key idea of integrating the incremental motion information in the form of step direction (SD) and step length (SL) over time. The foundation of the intelligent navigation system concept proposed here rests in exploiting the human locomotion pattern, as well as change of locomotion in varying environments. In this context, the term intelligent navigation represents the transition from the conventional point-to-point DR to dynamic navigation using the knowledge about the mechanism of the moving person. This approach increasingly relies on integrating knowledge-based systems (KBS) and artificial intelligence (AI) methodologies, including artificial neural networks (ANN) and fuzzy logic (FL). In addition, a general framework of the quality control for the real-time validation of the DR processing is proposed, based on a

  19. Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

    PubMed Central

    Eck, Brendan L.; Fahmi, Rachid; Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun; Miao, Jun; Wilson, David L.

    2015-01-01

    Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, PC. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and

  20. Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

    SciTech Connect

    Eck, Brendan L.; Fahmi, Rachid; Miao, Jun; Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun; Wilson, David L.

    2015-10-15

    Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit

  1. Outlier identification in radiation therapy knowledge-based planning: A study of pelvic cases.

    PubMed

    Sheng, Yang; Ge, Yaorong; Yuan, Lulin; Li, Taoran; Yin, Fang-Fang; Wu, Qingrong Jackie

    2017-09-04

    The purpose of this study was to apply statistical metrics to identify outliers and to investigate the impact of outliers on knowledge-based planning in radiation therapy of pelvic cases. We also aimed to develop a systematic workflow for identifying and analyzing geometric and dosimetric outliers. Four groups (G1-G4) of pelvic plans were sampled in this study. These include the following three groups of clinical IMRT cases: G1 (37 prostate cases), G2 (37 prostate plus lymph node cases) and G3 (37 prostate bed cases). Cases in G4 were planned in accordance with dynamic-arc radiation therapy procedure and include 10 prostate cases in addition to those from G1. The workflow was separated into two parts: 1. identifying geometric outliers, assessing outlier impact, and outlier cleaning; 2. identifying dosimetric outliers, assessing outlier impact, and outlier cleaning. G2 and G3 were used to analyze the effects of geometric outliers (first experiment outlined below) while G1 and G4 were used to analyze the effects of dosimetric outliers (second experiment outlined below). A baseline model was trained by regarding all G2 cases as inliers. G3 cases were then individually added to the baseline model as geometric outliers. The impact on the model was assessed by comparing leverages of inliers (G2) and outliers (G3). A receiver-operating-characteristic (ROC) analysis was performed to determine the optimal threshold. The experiment was repeated by training the baseline model with all G3 cases as inliers and perturbing the model with G2 cases as outliers. A separate baseline model was trained with 32 G1 cases. Each G4 case (dosimetric outlier) was subsequently added to perturb the model. Predictions of dose-volume histograms (DVHs) were made using these perturbed models for the remaining 5 G1 cases. A Weighted Sum of Absolute Residuals (WSAR) was used to evaluate the impact of the dosimetric outliers. The leverage of inliers and outliers was significantly different. The

  2. Ontology Language to Support Description of Experiment Control System Semantics, Collaborative Knowledge-Base Design and Ontology Reuse

    SciTech Connect

    Vardan Gyurjyan, D Abbott, G Heyes, E Jastrzembski, B Moffit, C Timmer, E Wolin

    2009-10-01

    In this paper we discuss the control domain specific ontology that is built on top of the domain-neutral Resource Definition Framework (RDF). Specifically, we will discuss the relevant set of ontology concepts along with the relationships among them in order to describe experiment control components and generic event-based state machines. Control Oriented Ontology Language (COOL) is a meta-data modeling language that provides generic means for representation of physics experiment control processes and components, and their relationships, rules and axioms. It provides a semantic reference frame that is useful for automating the communication of information for configuration, deployment and operation. COOL has been successfully used to develop a complete and dynamic knowledge-base for experiment control systems, developed using the AFECS framework.

  3. STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

    NASA Technical Reports Server (NTRS)

    Rogers, James L.; Feyock, Stefan; Sobieszczanski-Sobieski, Jaroslaw

    1988-01-01

    The purpose of this research effort is to investigate the benefits that might be derived from applying artificial intelligence tools in the area of conceptual design. Therefore, the emphasis is on the artificial intelligence aspects of conceptual design rather than structural and optimization aspects. A prototype knowledge-based system, called STRUTEX, was developed to initially configure a structure to support point loads in two dimensions. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user by integrating a knowledge base interface and inference engine, a data base interface, and graphics while keeping the knowledge base and data base files separate. The system writes a file which can be input into a structural synthesis system, which combines structural analysis and optimization.

  4. STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

    NASA Technical Reports Server (NTRS)

    Robers, James L.; Sobieszczanski-Sobieski, Jaroslaw

    1989-01-01

    Only recently have engineers begun making use of Artificial Intelligence (AI) tools in the area of conceptual design. To continue filling this void in the design process, a prototype knowledge-based system, called STRUTEX has been developed to initially configure a structure to support point loads in two dimensions. This prototype was developed for testing the application of AI tools to conceptual design as opposed to being a testbed for new methods for improving structural analysis and optimization. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user. How the system is constructed to interact with the user is described. Of special interest is the information flow between the knowledge base and the data base under control of the algorithmic main program. Examples of computed and refined structures are presented during the explanation of the system.

  5. Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

    PubMed Central

    De, Asok

    2014-01-01

    In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

  6. Knowledge-based Characterization of Similarity Relationships in the Human Protein-Tyrosine Phosphatase Family for Rational Inhibitor Design

    PubMed Central

    Vidović, Dušica; Schürer, Stephan C.

    2009-01-01

    Tyrosine phosphorylation, controlled by the coordinated action of protein-tyrosine kinases (PTKs) and protein-tyrosine phosphatases (PTPs), is a fundamental regulatory mechanism of numerous physiological processes. PTPs are implicated in a number of human diseases and their potential as prospective drug targets is increasingly being recognized. Despite their biological importance, until now no comprehensive overview has been reported describing how all members of the human PTP family are related. Here we review the entire human PTP family and present a systematic knowledge-based characterization of global and local similarity relationships, which are relevant for the development of small molecule inhibitors. We use parallel homology modeling to expand the current PTP structure space and analyze the human PTPs based on local three-dimensional catalytic sites and domain sequences. Furthermore, we demonstrate the importance of binding site similarities in understanding cross-reactivity and inhibitor selectivity in the design of small molecule inhibitors. PMID:19810703

  7. The pan-genome: towards a knowledge-based discovery of novel targets for vaccines and antibacterials.

    PubMed

    Muzzi, Alessandro; Masignani, Vega; Rappuoli, Rino

    2007-06-01

    During the past decade, sequencing of the entire genome of pathogenic bacteria has become a widely used practice in microbiology research. More recently, sequence data from multiple isolates of a single pathogen have provided new insights into the microevolution of a species as well as helping researchers to decipher its virulence mechanisms. The comparison of multiple strains of a single species has resulted in the definition of the species pan-genome, as a measure of the total gene repertoire that can pertain to a given microorganism. This concept can be exploited not only to study the diversity of a species, but also, as we discuss here, to provide the opportunity to use a knowledge-based approach for the development of novel vaccine candidates and new-generation targets for antimicrobials.

  8. An approach to knowledge engineering to support knowledge-based simulation of payload ground processing at the Kennedy Space Center

    NASA Technical Reports Server (NTRS)

    Mcmanus, Shawn; Mcdaniel, Michael

    1989-01-01

    Planning for processing payloads was always difficult and time-consuming. With the advent of Space Station Freedom and its capability to support a myriad of complex payloads, the planning to support this ground processing maze involves thousands of man-hours of often tedious data manipulation. To provide the capability to analyze various processing schedules, an object oriented knowledge-based simulation environment called the Advanced Generic Accomodations Planning Environment (AGAPE) is being developed. Having nearly completed the baseline system, the emphasis in this paper is directed toward rule definition and its relation to model development and simulation. The focus is specifically on the methodologies implemented during knowledge acquisition, analysis, and representation within the AGAPE rule structure. A model is provided to illustrate the concepts presented. The approach demonstrates a framework for AGAPE rule development to assist expert system development.

  9. An iterative knowledge-based scoring function to predict protein-ligand interactions: II. Validation of the scoring function.

    PubMed

    Huang, Sheng-You; Zou, Xiaoqin

    2006-11-30

    We have developed an iterative knowledge-based scoring function (ITScore) to describe protein-ligand interactions. Here, we assess ITScore through extensive tests on native structure identification, binding affinity prediction, and virtual database screening. Specifically, ITScore was first applied to a test set of 100 protein-ligand complexes constructed by Wang et al. (J Med Chem 2003, 46, 2287), and compared with 14 other scoring functions. The results show that ITScore yielded a high success rate of 82% on identifying native-like binding modes under the criterion of rmsd < or = 2 A for each top-ranked ligand conformation. The success rate increased to 98% if the top five conformations were considered for each ligand. In the case of binding affinity prediction, ITScore also obtained a good correlation for this test set (R = 0.65). Next, ITScore was used to predict binding affinities of a second diverse test set of 77 protein-ligand complexes prepared by Muegge and Martin (J Med Chem 1999, 42, 791), and compared with four other widely used knowledge-based scoring functions. ITScore yielded a high correlation of R2 = 0.65 (or R = 0.81) in the affinity prediction. Finally, enrichment tests were performed with ITScore against four target proteins using the compound databases constructed by Jacobsson et al. (J Med Chem 2003, 46, 5781). The results were compared with those of eight other scoring functions. ITScore yielded high enrichments in all four database screening tests. ITScore can be easily combined with the existing docking programs for the use of structure-based drug design.

  10. SU-F-BRA-13: Knowledge-Based Treatment Planning for Prostate LDR Brachytherapy Based On Principle Component Analysis

    SciTech Connect

    Roper, J; Bradshaw, B; Godette, K; Schreibmann, E; Chanyavanich, V

    2015-06-15

    Purpose: To create a knowledge-based algorithm for prostate LDR brachytherapy treatment planning that standardizes plan quality using seed arrangements tailored to individual physician preferences while being fast enough for real-time planning. Methods: A dataset of 130 prior cases was compiled for a physician with an active prostate seed implant practice. Ten cases were randomly selected to test the algorithm. Contours from the 120 library cases were registered to a common reference frame. Contour variations were characterized on a point by point basis using principle component analysis (PCA). A test case was converted to PCA vectors using the same process and then compared with each library case using a Mahalanobis distance to evaluate similarity. Rank order PCA scores were used to select the best-matched library case. The seed arrangement was extracted from the best-matched case and used as a starting point for planning the test case. Computational time was recorded. Any subsequent modifications were recorded that required input from a treatment planner to achieve an acceptable plan. Results: The computational time required to register contours from a test case and evaluate PCA similarity across the library was approximately 10s. Five of the ten test cases did not require any seed additions, deletions, or moves to obtain an acceptable plan. The remaining five test cases required on average 4.2 seed modifications. The time to complete manual plan modifications was less than 30s in all cases. Conclusion: A knowledge-based treatment planning algorithm was developed for prostate LDR brachytherapy based on principle component analysis. Initial results suggest that this approach can be used to quickly create treatment plans that require few if any modifications by the treatment planner. In general, test case plans have seed arrangements which are very similar to prior cases, and thus are inherently tailored to physician preferences.

  11. Experiences in improving the state of the practice in verification and validation of knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Culbert, Chris; French, Scott W.; Hamilton, David

    1994-01-01

    Knowledge-based systems (KBS's) are in general use in a wide variety of domains, both commercial and government. As reliance on these types of systems grows, the need to assess their quality and validity reaches critical importance. As with any software, the reliability of a KBS can be directly attributed to the application of disciplined programming and testing practices throughout the development life-cycle. However, there are some essential differences between conventional software and KBSs, both in construction and use. The identification of these differences affect the verification and validation (V&V) process and the development of techniques to handle them. The recognition of these differences is the basis of considerable on-going research in this field. For the past three years IBM (Federal Systems Company - Houston) and the Software Technology Branch (STB) of NASA/Johnson Space Center have been working to improve the 'state of the practice' in V&V of Knowledge-based systems. This work was motivated by the need to maintain NASA's ability to produce high quality software while taking advantage of new KBS technology. To date, the primary accomplishment has been the development and teaching of a four-day workshop on KBS V&V. With the hope of improving the impact of these workshops, we also worked directly with NASA KBS projects to employ concepts taught in the workshop. This paper describes two projects that were part of this effort. In addition to describing each project, this paper describes problems encountered and solutions proposed in each case, with particular emphasis on implications for transferring KBS V&V technology beyond the NASA domain.

  12. Getting libraries involved in industry-university-government collaboration : Libraries should support inauguration of business and lead SME into a knowledge-based society : What Toshiaki Takeuchi does as Business Library Association's President

    NASA Astrophysics Data System (ADS)

    Morita, Utako

    Getting libraries involved in industry-university-government collaboration : Libraries should support inauguration of business and lead SME into a knowledge-based society : What Toshiaki Takeuchi does as Business Library Association's President

  13. Heuristic knowledge-based planning for single-isocenter stereotactic radiosurgery to multiple brain metastases.

    PubMed

    Ziemer, Benjamin P; Sanghvi, Parag; Hattangadi-Gluth, Jona; Moore, Kevin L

    2017-07-21

    Single-isocenter, volumetric-modulated arc therapy (VMAT) stereotactic radiosurgery (SRS) for multiple brain metastases (multimets) can deliver highly conformal dose distributions and reduce overall patient treatment time compared to other techniques. However, treatment planning for multimet cases is highly complex due to variability in numbers and sizes of brain metastases, as well as their relative proximity to organs-at-risk (OARs). The purpose of this study was to automate the VMAT planning of multimet cases through a knowledge-based planning (KBP) approach that adapts single-target SRS dose predictions to multiple target predictions. Using a previously published artificial neural network (ANN) KBP system trained on single-target, linac-based SRS plans, 3D dose distribution predictions for multimet patients were obtained by treating each brain lesion as a solitary target and subsequently combining individual dose predictions into a single distribution. Spatial dose distributions di(r→) for each of the i = 1…N lesions were merged using the combination function d(r→)=∑iNdin(r→)1/n. The optimal value of n was determined by minimizing root-mean squared (RMS) difference between clinical multimet plans and predicted dose per unit length along the line profile joining each lesion in the clinical cohort. The gradient measure GM=[3/4π]1/3V50%1/3-V100%1/3 is the primary quality metric for SRS plan evaluation at our institution and served as the main comparative metric between clinical plans and the KBP results. A total of 41 previously treated multimet plans, with target numbers ranging from N = 2-10, were used to validate the ANN predictions and subsequent KBP auto-planning routine. Fully deliverable KBP plans were developed by converting predicted dose distribution into patient-specific optimization objectives for the clinical treatment planning system (TPS). Plan parity was maintained through identical arc configuration and target normalization. Overall

  14. Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

    NASA Technical Reports Server (NTRS)

    Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

    1993-01-01

    The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

  15. Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

    NASA Technical Reports Server (NTRS)

    Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

    1993-01-01

    The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

  16. Using Quality Management Methods in Knowledge-Based Organizations. An Approach to the Application of the Taguchi Method to the Process of Pressing Tappets into Anchors

    NASA Astrophysics Data System (ADS)

    Ţîţu, M. A.; Pop, A. B.; Ţîţu, Ș

    2017-06-01

    This paper presents a study on the modelling and optimization of certain variables by using the Taguchi Method with a view to modelling and optimizing the process of pressing tappets into anchors, process conducted in an organization that promotes knowledge-based management. The paper promotes practical concepts of the Taguchi Method and describes the way in which the objective functions are obtained and used during the modelling and optimization of the process of pressing tappets into the anchors.

  17. XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

    PubMed

    Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

    2008-03-01

    High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

  18. Predicting DNA-binding locations and orientation on proteins using knowledge-based learning of geometric properties.

    PubMed

    Wang, Chien-Chih; Chen, Chien-Yu

    2011-10-14

    DNA-binding proteins perform their functions through specific or non-specific sequence recognition. Although many sequence- or structure-based approaches have been proposed to identify DNA-binding residues on proteins or protein-binding sites on DNA sequences with satisfied performance, it remains a challenging task to unveil the exact mechanism of protein-DNA interactions without crystal complex structures. Without information from complexes, the linkages between DNA-binding proteins and their binding sites on DNA are still missing. While it is still difficult to acquire co-crystallized structures in an efficient way, this study proposes a knowledge-based learning method to effectively predict DNA orientation and base locations around the protein's DNA-binding sites when given a protein structure. First, the functionally important residues of a query protein are predicted by a sequential pattern mining tool. After that, surface residues falling in the predicted functional regions are determined based on the given structure. These residues are then clustered based on their spatial coordinates and the resultant clusters are ranked by a proposed DNA-binding propensity function. Clusters with high DNA-binding propensities are treated as DNA-binding units (DBUs) and each DBU is analyzed by principal component analysis (PCA) to predict potential orientation of DNA grooves. More specifically, the proposed method is developed to predict the direction of the tangent line to the helix curve of the DNA groove where a DBU is going to bind. This paper proposes a knowledge-based learning procedure to determine the spatial location of the DNA groove with respect to the query protein structure by considering geometric propensity between protein side chains and DNA bases. The 11 test cases used in this study reveal that the location and orientation of the DNA groove around a selected DBU can be predicted with satisfied errors. This study presents a method to predict the location

  19. A knowledge-based taxonomy of critical factors for adopting electronic health record systems by physicians: a systematic literature review

    PubMed Central

    2010-01-01

    Background The health care sector is an area of social and economic interest in several countries; therefore, there have been lots of efforts in the use of electronic health records. Nevertheless, there is evidence suggesting that these systems have not been adopted as it was expected, and although there are some proposals to support their adoption, the proposed support is not by means of information and communication technology which can provide automatic tools of support. The aim of this study is to identify the critical adoption factors for electronic health records by physicians and to use them as a guide to support their adoption process automatically. Methods This paper presents, based on the PRISMA statement, a systematic literature review in electronic databases with adoption studies of electronic health records published in English. Software applications that manage and process the data in the electronic health record have been considered, i.e.: computerized physician prescription, electronic medical records, and electronic capture of clinical data. Our review was conducted with the purpose of obtaining a taxonomy of the physicians main barriers for adopting electronic health records, that can be addressed by means of information and communication technology; in particular with the information technology roles of the knowledge management processes. Which take us to the question that we want to address in this work: "What are the critical adoption factors of electronic health records that can be supported by information and communication technology?". Reports from eight databases covering electronic health records adoption studies in the medical domain, in particular those focused on physicians, were analyzed. Results The review identifies two main issues: 1) a knowledge-based classification of critical factors for adopting electronic health records by physicians; and 2) the definition of a base for the design of a conceptual framework for supporting the

  20. Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking

    PubMed Central

    Sasse, Alexander; de Vries, Sjoerd J.; Schindler, Christina E. M.; de Beauchêne, Isaure Chauvot

    2017-01-01

    Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scoring step is one of the bottlenecks in the performance of many state-of-the-art protocols. The performance of scoring functions depends on the quality of the generated structures and its coupling to the sampling algorithm. A tool kit, GRADSCOPT (GRid Accelerated Directly SCoring OPTimizing), was designed to allow rapid development and optimization of different knowledge-based scoring potentials for specific objectives in protein-protein docking. Different atomistic and coarse-grained potentials can be created by a grid-accelerated directly scoring dependent Monte-Carlo annealing or by a linear regression optimization. We demonstrate that the scoring functions generated by our approach are similar to or even outperform state-of-the-art scoring functions for predicting near-native solutions. Of additional importance, we find that potentials specifically trained to identify the native bound complex perform rather poorly on identifying acceptable or medium quality (near-native) solutions. In contrast, atomistic long-range contact potentials can increase the average fraction of near-native poses by up to a factor 2.5 in the best scored 1% decoys (compared to existing scoring), emphasizing the need of specific docking potentials for different steps in the docking protocol. PMID:28118389

  1. PCOSKB: A KnowledgeBase on genes, diseases, ontology terms and biochemical pathways associated with PolyCystic Ovary Syndrome.

    PubMed

    Joseph, Shaini; Barai, Ram Shankar; Bhujbalrao, Rasika; Idicula-Thomas, Susan

    2016-01-04

    Polycystic ovary syndrome (PCOS) is one of the major causes of female subfertility worldwide and ≈ 7-10% of women in reproductive age are affected by it. The affected individuals exhibit varying types and levels of comorbid conditions, along with the classical PCOS symptoms. Extensive studies on PCOS across diverse ethnic populations have resulted in a plethora of information on dysregulated genes, gene polymorphisms and diseases linked to PCOS. However, efforts have not been taken to collate and link these data. Our group, for the first time, has compiled PCOS-related information available through scientific literature; cross-linked it with molecular, biochemical and clinical databases and presented it as a user-friendly, web-based online knowledgebase for the benefit of the scientific and clinical community. Manually curated information on associated genes, single nucleotide polymorphisms, diseases, gene ontology terms and pathways along with supporting reference literature has been collated and included in PCOSKB (http://pcoskb.bicnirrh.res.in). © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. APL: An angle probability list to improve knowledge-based metaheuristics for the three-dimensional protein structure prediction.

    PubMed

    Borguesan, Bruno; Barbachan e Silva, Mariel; Grisci, Bruno; Inostroza-Ponta, Mario; Dorn, Márcio

    2015-12-01

    Tertiary protein structure prediction is one of the most challenging problems in structural bioinformatics. Despite the advances in algorithm development and computational strategies, predicting the folded structure of a protein only from its amino acid sequence remains as an unsolved problem. We present a new computational approach to predict the native-like three-dimensional structure of proteins. Conformational preferences of amino acid residues and secondary structure information were obtained from protein templates stored in the Protein Data Bank and represented as an Angle Probability List. Two knowledge-based prediction methods based on Genetic Algorithms and Particle Swarm Optimization were developed using this information. The proposed method has been tested with twenty-six case studies selected to validate our approach with different classes of proteins and folding patterns. Stereochemical and structural analysis were performed for each predicted three-dimensional structure. Results achieved suggest that the Angle Probability List can improve the effectiveness of metaheuristics used to predicted the three-dimensional structure of protein molecules by reducing its conformational search space. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Structure for a knowledge-based system to estimate Soviet tactics in the air-land battle. Master's thesis

    SciTech Connect

    Fletcher, A.M.

    1988-03-01

    The purpose of this thesis was to build a prototype decision aid that can use knowledge about Soviet military doctrine and tactics to infer when, where, and how the Soviet Army plans to attack NATO defenses given intelligence data about Soviet (Red) military units, terrain data, and the positions of the NATO (Blue) defenses. Issues are raised that must be resolved before such a decision aid, which is part of the Rapid Application of Air Power concept, can become operational. First examined is the need to shorten the C2 decision cycle in order for the ATOC staff to keep pace with the tempo of modern warfare. The Rapid Application of Air Power is a concept that includes automating various steps in the decision cycle to allow air power to be applied proactively to stop Soviet forces before they obtain critical objectives. A structure is presented for automating the second step in the decision cycle, assessing and clarifying the situation, through a knowledge-based decision aid for interpreting intelligence data from the perspective of Soviet (Red) doctrine and estimating future Red tactical objectives and maneuvers.

  4. Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis.

    PubMed

    Aniba, Mohamed Radhouene; Siguenza, Sophie; Friedrich, Anne; Plewniak, Frédéric; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

    2009-01-01

    The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented.

  5. MorphoCol: An ontology-based knowledgebase for the characterisation of clinically significant bacterial colony morphologies.

    PubMed

    Sousa, Ana Margarida; Pereira, Maria Olívia; Lourenço, Anália

    2015-06-01

    One of the major concerns of the biomedical community is the increasing prevalence of antimicrobial resistant microorganisms. Recent findings show that the diversification of colony morphology may be indicative of the expression of virulence factors and increased resistance to antibiotic therapeutics. To transform these findings, and upcoming results, into a valuable clinical decision making tool, colony morphology characterisation should be standardised. Notably, it is important to establish the minimum experimental information necessary to contextualise the environment that originated the colony morphology, and describe the main morphological features associated unambiguously. This paper presents MorphoCol, a new ontology-based tool for the standardised, consistent and machine-interpretable description of the morphology of colonies formed by human pathogenic bacteria. The Colony Morphology Ontology (CMO) is the first controlled vocabulary addressing the specificities of the morphology of clinically significant bacteria, whereas the MorphoCol publicly Web-accessible knowledgebase is an end-user means to search and compare CMO annotated colony morphotypes. Its ultimate aim is to help correlate the morphological alterations manifested by colony-forming bacteria during infection with their response to the antimicrobial treatments administered. MorphoCol is the first tool to address bacterial colony morphotyping systematically and deliver a free of charge resource to the community. Hopefully, it may introduce interesting features of analysis on pathogenic behaviour and play a significant role in clinical decision making. http://morphocol.org. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. PCOSKB: A KnowledgeBase on genes, diseases, ontology terms and biochemical pathways associated with PolyCystic Ovary Syndrome

    PubMed Central

    Joseph, Shaini; Barai, Ram Shankar; Bhujbalrao, Rasika; Idicula-Thomas, Susan

    2016-01-01

    Polycystic ovary syndrome (PCOS) is one of the major causes of female subfertility worldwide and ≈7–10% of women in reproductive age are affected by it. The affected individuals exhibit varying types and levels of comorbid conditions, along with the classical PCOS symptoms. Extensive studies on PCOS across diverse ethnic populations have resulted in a plethora of information on dysregulated genes, gene polymorphisms and diseases linked to PCOS. However, efforts have not been taken to collate and link these data. Our group, for the first time, has compiled PCOS-related information available through scientific literature; cross-linked it with molecular, biochemical and clinical databases and presented it as a user-friendly, web-based online knowledgebase for the benefit of the scientific and clinical community. Manually curated information on associated genes, single nucleotide polymorphisms, diseases, gene ontology terms and pathways along with supporting reference literature has been collated and included in PCOSKB (http://pcoskb.bicnirrh.res.in). PMID:26578565

  7. Development of a knowledge-base for automatic monitoring of renal function of intensive care patients over time.

    PubMed

    Heindl, B; Pollwein, B; Schleutermann, S; Haller, M; Finsterer, U

    2000-05-01

    Renal dysfunction is a major problem in the management of critically ill patients. Monitoring of renal parameters over time is a prerequisite for detection of any significant deterioration of kidney function. Thus, we developed a knowledge-base for the dynamic monitoring of renal function of critically ill patients. A database with renal parameters of 750 intensive care patients was analyzed for distribution of parameters within predefined intervals of the creatinine clearance. Additionally, a subgroup of 11 patients with (quite) normal renal function over 11 days was selected and the daily variability of renal parameters was analyzed. An interdisciplinary expert team selected a set of nine clinically relevant renal parameters and formulated, on the basis of the data analysis and the parameter set, eight definitions of renal function, which represent four levels of renal performance. These definitions were arranged into an hierarchical structure, considering only clinically relevant changes of renal function. A change from one functional state to another inside of 2 days indicates a relevant alteration of renal function. Monitoring of time courses can additionally be performed by statistical analysis of the daily variability of parameters and comparison with their 'normal' variability. Moreover, rules were established for the plausibility check of results and interpretations of single parameters and parameter sets formulated.

  8. Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

    PubMed

    Bae, H; Seo, H Y; Kim, S; Kim, Y

    2006-01-01

    Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.

  9. 3D-liquid chromatography as a complex mixture characterization tool for knowledge-based downstream process development.

    PubMed

    Hanke, Alexander T; Tsintavi, Eleni; Ramirez Vazquez, Maria Del Pilar; van der Wielen, Luuk A M; Verhaert, Peter D E M; Eppink, Michel H M; van de Sandt, Emile J A X; Ottens, Marcel

    2016-09-01

    Knowledge-based development of chromatographic separation processes requires efficient techniques to determine the physicochemical properties of the product and the impurities to be removed. These characterization techniques are usually divided into approaches that determine molecular properties, such as charge, hydrophobicity and size, or molecular interactions with auxiliary materials, commonly in the form of adsorption isotherms. In this study we demonstrate the application of a three-dimensional liquid chromatography approach to a clarified cell homogenate containing a therapeutic enzyme. Each separation dimension determines a molecular property relevant to the chromatographic behavior of each component. Matching of the peaks across the different separation dimensions and against a high-resolution reference chromatogram allows to assign the determined parameters to pseudo-components, allowing to determine the most promising technique for the removal of each impurity. More detailed process design using mechanistic models requires isotherm parameters. For this purpose, the second dimension consists of multiple linear gradient separations on columns in a high-throughput screening compatible format, that allow regression of isotherm parameters with an average standard error of 8%. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1283-1291, 2016. © 2016 American Institute of Chemical Engineers.

  10. Data acquisition for a real time fault monitoring and diagnosis knowledge-based system for space power system

    NASA Technical Reports Server (NTRS)

    Wilhite, Larry D.; Lee, S. C.; Lollar, Louis F.

    1989-01-01

    The design and implementation of the real-time data acquisition and processing system employed in the AMPERES project is described, including effective data structures for efficient storage and flexible manipulation of the data by the knowledge-based system (KBS), the interprocess communication mechanism required between the data acquisition system and the KBS, and the appropriate data acquisition protocols for collecting data from the sensors. Sensor data are categorized as critical or noncritical data on the basis of the inherent frequencies of the signals and the diagnostic requirements reflected in their values. The critical data set contains 30 analog values and 42 digital values and is collected every 10 ms. The noncritical data set contains 240 analog values and is collected every second. The collected critical and noncritical data are stored in separate circular buffers. Buffers are created in shared memory to enable other processes, i.e., the fault monitoring and diagnosis process and the user interface process, to freely access the data sets.

  11. Object recognition in brain CT-scans: Knowledge-based fusion of data from multiple feature extractors

    SciTech Connect

    Li, H.; Deklerck, R.; Cuyper, B. De; Nyssen, E.; Cornelis, J.; Hermanus, A.

    1995-06-01

    This paper describes a knowledge-based image interpretation system for the segmentation and labeling of a series of 2-D brain X-ray CT-scans, parallel to the orbito-metal plane. The system combines the image primitive information produced by different low level vision techniques in order to improve the reliability of the segmentation and the image interpretation. It is implemented in a blackboard environment that is holding various types of prior information and which controls the interpretation process. The scoring model is applied for the fusion of information derived from three types of image primitives (points, edges, and regions). A model, containing both analogical and propositional knowledge on the brain objects, is used to direct the interpretation process. The linguistic variables, introduced to describe the propositional features of the brain model, are defined by fuzzy membership functions. Constraint functions are applied to evaluate the plausibility of the mapping between image primitives and brain model data objects. Procedural knowledge has been integrated into different knowledge sources. Experimental results illustrate the reliability and robustness of the system against small variations in slice orientation and interpatient variability in the images.

  12. Knowledge-based expert systems and a proof-of-concept case study for multiple sequence alignment construction and analysis

    PubMed Central

    Aniba, Mohamed Radhouene; Siguenza, Sophie; Friedrich, Anne; Plewniak, Frédéric; Poch, Olivier; Marchler-Bauer, Aron

    2009-01-01

    The traditional approach to bioinformatics analyses relies on independent task-specific services and applications, using different input and output formats, often idiosyncratic, and frequently not designed to inter-operate. In general, such analyses were performed by experts who manually verified the results obtained at each step in the process. Today, the amount of bioinformatics information continuously being produced means that handling the various applications used to study this information presents a major data management and analysis challenge to researchers. It is now impossible to manually analyse all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. We review the recent use of integrated expert systems aimed at providing more efficient knowledge extraction for bioinformatics research. A general methodology for building knowledge-based expert systems is described, focusing on the unstructured information management architecture, UIMA, which provides facilities for both data and process management. A case study involving a multiple alignment expert system prototype called AlexSys is also presented. PMID:18971242

  13. Usefulness of a Low Tube Voltage: Knowledge-Based Iterative Model Reconstruction Algorithm for Computed Tomography Venography.

    PubMed

    Iyama, Yuji; Nakaura, Takeshi; Iyama, Ayumi; Kidoh, Masafumi; Oda, Seitaro; Tokuyasu, Shinichi; Yamashita, Yasuyuki

    The objective of this study was to evaluate the use of 80-kVp scans with knowledge-based iterative model reconstruction (IMR) for computed tomography venography (CTV). This prospective study received institutional review board approval; a previous informed consent was obtained from all participants. We enrolled 30 patients with suspected deep venous thrombosis or pulmonary embolism who were to undergo 80-kVp CTV studies. The images were reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR), and IMR. The venous attenuation, image noise, and contrast-to-noise ratio at the iliac, femoral, and popliteal veins were compared on FBP, HIR, and IMR images. We performed qualitative image analysis (image noise, image contrast, image sharpness, streak artifacts, and overall image quality) of the 3 reconstruction methods and measured their reconstruction times. There was no significant difference in venous attenuation among the 3 reconstruction methods (P > 0.05). On IMR images, the image noise was lowest at all 3 venous locations, and the contrast-to-noise ratio was highest. Qualitative evaluation scores were also highest for IMR images. The reconstruction time for FBP, HIR, and IMR imaging was 25.4 ± 1.9 seconds, 43.3 ± 3.3 seconds, and 78.7 ± 6.0 seconds, respectively. At clinically acceptable reconstruction times, 80-kVp CTV using the IMR technique yielded better qualitative and quantitative image quality than HIR and FBP.

  14. A knowledge-based scoring function for protein-RNA interactions derived from a statistical mechanics-based iterative method.

    PubMed

    Huang, Sheng-You; Zou, Xiaoqin

    2014-04-01

    Protein-RNA interactions play important roles in many biological processes. Given the high cost and technique difficulties in experimental methods, computationally predicting the binding complexes from individual protein and RNA structures is pressingly needed, in which a reliable scoring function is one of the critical components. Here, we have developed a knowledge-based scoring function, referred to as ITScore-PR, for protein-RNA binding mode prediction by using a statistical mechanics-based iterative method. The pairwise distance-dependent atomic interaction potentials of ITScore-PR were derived from experimentally determined protein-RNA complex structures. For validation, we have compared ITScore-PR with 10 other scoring methods on four diverse test sets. For bound docking, ITScore-PR achieved a success rate of up to 86% if the top prediction was considered and up to 94% if the top 10 predictions were considered, respectively. For truly unbound docking, the respective success rates of ITScore-PR were up to 24 and 46%. ITScore-PR can be used stand-alone or easily implemented in other docking programs for protein-RNA recognition.

  15. Integrating knowledge-based multi-criteria evaluation techniques with GIS for landfill site selection: A case study using AHP

    NASA Astrophysics Data System (ADS)

    Fagbohun, B. J.; Aladejana, O. O.

    2016-09-01

    A major challenge in most growing urban areas of developing countries, without a pre-existing land use plan is the sustainable and efficient management of solid wastes. Siting a landfill is a complicated task because of several environmental regulations. This challenge gives birth to the need to develop efficient strategies for the selection of proper waste disposal sites in accordance with all existing environmental regulations. This paper presents a knowledge-based multi-criteria decision analysis using GIS for the selection of suitable landfill site in Ado-Ekiti, Nigeria. In order to identify suitable sites for landfill, seven factors - land use/cover, geology, river, soil, slope, lineament and roads - were taken into consideration. Each factor was classified and ranked based on prior knowledge about the area and existing guidelines. Weights for each factor were determined through pair-wise comparison using Saaty's 9 point scale and AHP. The integration of factors according to their weights using weighted index overlay analysis revealed that 39.23 km2 within the area was suitable to site a landfill. The resulting suitable area was classified as high suitability covering 6.47 km2 (16.49%), moderate suitability 25.48 km2 (64.95%) and low suitability 7.28 km2 (18.56%) based on their overall weights.

  16. A knowledge-based iterative model reconstruction algorithm: can super-low-dose cardiac CT be applicable in clinical settings?

    PubMed

    Oda, Seitaro; Utsunomiya, Daisuke; Funama, Yoshinori; Katahira, Kazuhiro; Honda, Keiichi; Tokuyasu, Shinichi; Vembar, Mani; Yuki, Hideaki; Noda, Katsuo; Oshima, Shuichi; Yamashita, Yasuyuki

    2014-01-01

    To investigate whether "full" iterative reconstruction, a knowledge-based iterative model reconstruction (IMR), enables radiation dose reduction by 80% at cardiac computed tomography (CT). A total of 23 patients (15 men, eight women; mean age 64.3 ± 13.4 years) who underwent retrospectively electrocardiography-gated cardiac CT with dose modulation were evaluated. We compared full-dose (FD; 730 mAs) images reconstructed with filtered back projection (FBP) technique and the low-dose (LD; 146 mAs) images reconstructed with FBP and IMR techniques. Objective and subjective image quality parameters were compared among the three different CT images. There was no significant difference in the CT attenuation among the three reconstructions. The mean image noise of LD-IMR (18.3 ± 10.6 Hounsfield units [HU]) was significantly lowest among the three reconstructions (41.9 ± 15.3 HU for FD-FBP and 109.9 ± 42.6 HU for LD-FBP; P < .01). The contrast-to-noise ratio of LD-IMR was better than that of FD-FBP and LD-FBP (P < .01). Visual evaluation score was also highest for LD-IMR. The IMR can provide improved image quality at super-low-dose cardiac CT with 20% of the standard tube current. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  17. Development of a Knowledge-based Application Utilizing Ontologies for the Continuing Site-specific JJ1017 Master Maintenance.

    PubMed

    Kobayashi, Tatsuaki; Tsuji, Shintaro; Yagahara, Ayako; Tanikawa, Takumi; Umeda, Tokuo

    2015-07-01

    The purpose of this study was to develop the JJ1017 Knowledge-based Application (JKA) to support the continuing maintenance of a site-specific JJ1017 master defined by the JJ1017 guideline as a standard radiologic procedure master for medical information systems that are being adopted by some medical facilities in Japan. The method consisted of the following three steps: (1) construction of the JJ1017 Ontology (JJOnt) as a knowledge base using the Hozo (an environment for building/using ontologies); (2) development of modules (operation, I/O, graph modules) that are required to continue the maintenance of a site-specific JJ1017 master; and (3) unit testing of the JKA that consists of the JJOnt and the modules. As a result, the number of classes included in the JJOnt was 21,697. Within the radiologic procedure classes included in the above, the ratio of a JJ1017 master code for an external beam radiotherapy was the highest (51%). In unit testing of the JKA, we checked the main operations (e.g., keyword search of a JJ1017 master code/code meaning, editing the description of classes, etc.). The JJOnt is a knowledge base for implementing features that medical technologists find necessary in medical information systems. To enable medical technologists to exchange/retrieve semantically accurate information while using medical information systems in the future, we expect the JKA to support the maintenance and improvement of the site-specific JJ1017 master.

  18. Data acquisition for a real time fault monitoring and diagnosis knowledge-based system for space power system

    NASA Technical Reports Server (NTRS)

    Wilhite, Larry D.; Lee, S. C.; Lollar, Louis F.

    1989-01-01

    The design and implementation of the real-time data acquisition and processing system employed in the AMPERES project is described, including effective data structures for efficient storage and flexible manipulation of the data by the knowledge-based system (KBS), the interprocess communication mechanism required between the data acquisition system and the KBS, and the appropriate data acquisition protocols for collecting data from the sensors. Sensor data are categorized as critical or noncritical data on the basis of the inherent frequencies of the signals and the diagnostic requirements reflected in their values. The critical data set contains 30 analog values and 42 digital values and is collected every 10 ms. The noncritical data set contains 240 analog values and is collected every second. The collected critical and noncritical data are stored in separate circular buffers. Buffers are created in shared memory to enable other processes, i.e., the fault monitoring and diagnosis process and the user interface process, to freely access the data sets.

  19. Cross-institutional knowledge-based planning (KBP) implementation and its performance comparison to Auto-Planning Engine (APE).

    PubMed

    Wu, Binbin; Kusters, Martijn; Kunze-Busch, Martina; Dijkema, Tim; McNutt, Todd; Sanguineti, Giuseppe; Bzdusek, Karl; Dritschilo, Anatoly; Pang, Dalong

    2017-04-01

    To investigate (1) whether a plan library established at one institution can be applied for another institution's knowledge-based planning (KBP); (2) the performance of cross-institutional KBP compared to Auto-Planning Engine (APE). Radboud University Medical Center (RUMC) provided 35 oropharyngeal cancer patients (68Gy to PTV(68) and 50.3Gy to PTV(50.3)) with clinically-delivered and comparative APE plans. The Johns Hopkins University (JHU) contributed a three-dose-level plan library consisting of 179 clinically-delivered plans. MedStar Georgetown University Hospital (MGUH) contributed a KBP approach employing overlap-volume histogram (OVH-KBP), where the JHU library was used for guiding RUMC patients' KBP. Since clinical protocols adopted at RUMC and JHU are different and both approaches require protocol-specific planning parameters as initial input, 10 randomly selected patients from RUMC were set aside for deriving them. The finalized parameters were applied to the remaining 25 patients for OVH-KBP and APE plan generation. A Wilcoxon rank-sum test was used for statistical comparison. PTV(68) and PTV(50.3)'s V95 in OVH-KBP and APE were similar (p>0.36). Cord's D0.1 cc in OVH-KBP was reduced by 5.1Gy (p=0.0001); doses to other organs were similar (p>0.2). APE and OVH-KBP's plan quality is comparable. Institutional-protocol differences can be addressed to allow cross-institutional library sharing. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Knowledge-Based Personal Health System to empower outpatients of diabetes mellitus by means of P4 Medicine.

    PubMed

    Bresó, Adrián; Sáez, Carlos; Vicente, Javier; Larrinaga, Félix; Robles, Montserrat; García-Gómez, Juan Miguel

    2015-01-01

    Diabetes Mellitus (DM) affects hundreds of millions of people worldwide and it imposes a large economic burden on healthcare systems. We present a web patient empowering system (PHSP4) that ensures continuous monitoring and assessment of the health state of patients with DM (type I and II). PHSP4 is a Knowledge-Based Personal Health System (PHS) which follows the trend of P4 Medicine (Personalized, Predictive, Preventive, and Participative). It provides messages to outpatients and clinicians about the achievement of objectives, follow-up, and treatments adjusted to the patient condition. Additionally, it calculates a four-component risk vector of the associated pathologies with DM: Nephropathy, Diabetic retinopathy, Diabetic foot, and Cardiovascular event. The core of the system is a Rule-Based System which Knowledge Base is composed by a set of rules implementing the recommendations of the American Diabetes Association (ADA) (American Diabetes Association: http://www.diabetes.org/ ) clinical guideline. The PHSP4 is designed to be standardized and to facilitate its interoperability by means of terminologies (SNOMED-CT [The International Health Terminology Standards Development Organization: http://www.ihtsdo.org/snomed-ct/ ] and UCUM [The Unified Code for Units of Measure: http://unitsofmeasure.org/ ]), standardized clinical documents (HL7 CDA R2 [Health Level Seven International: http://www.hl7.org/index.cfm ]) for managing Electronic Health Record (EHR). We have evaluated the functionality of the system and its users' acceptance of the system using simulated and real data, and a questionnaire based in the Technology Acceptance Model methodology (TAM). Finally results show the reliability of the system and the high acceptance of clinicians.

  1. Assessing side-chain perturbations of the protein backbone: a knowledge-based classification of residue Ramachandran space.

    PubMed

    Dahl, David B; Bohannan, Zach; Mo, Qianxing; Vannucci, Marina; Tsai, Jerry

    2008-05-02

    Grouping the 20 residues is a classic strategy to discover ordered patterns and insights about the fundamental nature of proteins, their structure, and how they fold. Usually, this categorization is based on the biophysical and/or structural properties of a residue's side-chain group. We extend this approach to understand the effects of side chains on backbone conformation and to perform a knowledge-based classification of amino acids by comparing their backbone phi, psi distributions in different types of secondary structure. At this finer, more specific resolution, torsion angle data are often sparse and discontinuous (especially for nonhelical classes) even though a comprehensive set of protein structures is used. To ensure the precision of Ramachandran plot comparisons, we applied a rigorous Bayesian density estimation method that produces continuous estimates of the backbone phi, psi distributions. Based on this statistical modeling, a robust hierarchical clustering was performed using a divergence score to measure the similarity between plots. There were seven general groups based on the clusters from the complete Ramachandran data: nonpolar/beta-branched (Ile and Val), AsX (Asn and Asp), long (Met, Gln, Arg, Glu, Lys, and Leu), aromatic (Phe, Tyr, His, and Cys), small (Ala and Ser), bulky (Thr and Trp), and, lastly, the singletons of Gly and Pro. At the level of secondary structure (helix, sheet, turn, and coil), these groups remain somewhat consistent, although there are a few significant variations. Besides the expected uniqueness of the Gly and Pro distributions, the nonpolar/beta-branched and AsX clusters were very consistent across all types of secondary structure. Effectively, this consistency across the secondary structure classes implies that side-chain steric effects strongly influence a residue's backbone torsion angle conformation. These results help to explain the plasticity of amino acid substitutions on protein structure and should help in

  2. Materials Characterization at Utah State University: Facilities and Knowledge-base of Electronic Properties of Materials Applicable to Spacecraft Charging

    NASA Technical Reports Server (NTRS)

    Dennison, J. R.; Thomson, C. D.; Kite, J.; Zavyalov, V.; Corbridge, Jodie

    2004-01-01

    In an effort to improve the reliability and versatility of spacecraft charging models designed to assist spacecraft designers in accommodating and mitigating the harmful effects of charging on spacecraft, the NASA Space Environments and Effects (SEE) Program has funded development of facilities at Utah State University for the measurement of the electronic properties of both conducting and insulating spacecraft materials. We present here an overview of our instrumentation and capabilities, which are particularly well suited to study electron emission as related to spacecraft charging. These measurements include electron-induced secondary and backscattered yields, spectra, and angular resolved measurements as a function of incident energy, species and angle, plus investigations of ion-induced electron yields, photoelectron yields, sample charging and dielectric breakdown. Extensive surface science characterization capabilities are also available to fully characterize the samples in situ. Our measurements for a wide array of conducting and insulating spacecraft materials have been incorporated into the SEE Charge Collector Knowledge-base as a Database of Electronic Properties of Materials Applicable to Spacecraft Charging. This Database provides an extensive compilation of electronic properties, together with parameterization of these properties in a format that can be easily used with existing spacecraft charging engineering tools and with next generation plasma, charging, and radiation models. Tabulated properties in the Database include: electron-induced secondary electron yield, backscattered yield and emitted electron spectra; He, Ar and Xe ion-induced electron yields and emitted electron spectra; photoyield and solar emittance spectra; and materials characterization including reflectivity, dielectric constant, resistivity, arcing, optical microscopy images, scanning electron micrographs, scanning tunneling microscopy images, and Auger electron spectra. Further

  3. MitProNet: A Knowledgebase and Analysis Platform of Proteome, Interactome and Diseases for Mammalian Mitochondria

    PubMed Central

    Mao, Song; Chai, Xiaoqiang; Hu, Yuling; Hou, Xugang; Tang, Yiheng; Bi, Cheng; Li, Xiao

    2014-01-01

    Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated

  4. Knowledge-based treatment planning: An inter-technique and inter-system feasibility study for prostate cancer.

    PubMed

    Cagni, Elisabetta; Botti, Andrea; Micera, Renato; Galeandro, Maria; Sghedoni, Roberto; Orlandi, Matteo; Iotti, Cinzia; Cozzi, Luca; Iori, Mauro

    2017-04-01

    Helical Tomotherapy (HT) plans were used to create two RapidPlan knowledge-based (KB) models to generate plans with different techniques and to guide the optimization in a different treatment planning system for prostate plans. Feasibility and performance of these models were evaluated. two sets of 35 low risk (LR) and 30 intermediate risk (IR) prostate cancer cases who underwent HT treatments were selected to train RapidPlan models. The KB predicted constraints were used to perform new 20KB plans using RapidArc technique (KB-RA) (inter-technique validation), and to optimise 20 new HT (KB-HT) plans in the Tomoplan (inter-system validation). For each validation modality, KB plans were benchmarked with the manual plans created by an expert planner (EP). RapidPlan was successfully configured using HT plans. The KB-RA plans fulfilled the clinical dose-volume requirements in 100% and 92% of cases for planning target volumes (PTVs) and organs at risk (OARs), respectively. For KB-HT plans these percentages were found to be a bit lower: 90% for PTVs and 86% for OARs. In comparison to EP plans, the KB-RA plans produced higher bladder doses for both LR and IR, and higher rectum doses for LR. KB-HT and EP plans produced similar results. RapidPlan can be trained to create models by using plans of a different treatment modality. These models were suitable for generating clinically acceptable plans for inter-technique and inter-system applications. The use of KB models based on plans of consolidated technique could be useful with a new treatment modality. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  5. AlzPlatform: An Alzheimer’s Disease Domain-Specific Chemogenomics Knowledgebase for Polypharmacology and Target Identification Research

    PubMed Central

    2015-01-01

    Alzheimer’s disease (AD) is one of the most complicated progressive neurodegeneration diseases that involve many genes, proteins, and their complex interactions. No effective medicines or treatments are available yet to stop or reverse the progression of the disease due to its polygenic nature. To facilitate discovery of new AD drugs and better understand the AD neurosignaling pathways involved, we have constructed an Alzheimer’s disease domain-specific chemogenomics knowledgebase, AlzPlatform (www.cbligand.org/AD/) with cloud computing and sourcing functions. AlzPlatform is implemented with powerful computational algorithms, including our established TargetHunter, HTDocking, and BBB Predictor for target identification and polypharmacology analysis for AD research. The platform has assembled various AD-related chemogenomics data records, including 928 genes and 320 proteins related to AD, 194 AD drugs approved or in clinical trials, and 405 188 chemicals associated with 1 023 137 records of reported bioactivities from 38 284 corresponding bioassays and 10 050 references. Furthermore, we have demonstrated the application of the AlzPlatform in three case studies for identification of multitargets and polypharmacology analysis of FDA-approved drugs and also for screening and prediction of new AD active small chemical molecules and potential novel AD drug targets by our established TargetHunter and/or HTDocking programs. The predictions were confirmed by reported bioactivity data and our in vitro experimental validation. Overall, AlzPlatform will enrich our knowledge for AD target identification, drug discovery, and polypharmacology analyses and, also, facilitate the chemogenomics data sharing and information exchange/communications in aid of new anti-AD drug discovery and development. PMID:24597646

  6. Structural variation of alpha-synuclein with temperature by a coarse-grained approach with knowledge-based interactions

    NASA Astrophysics Data System (ADS)

    Mirau, Peter; Farmer, B. L.; Pandey, R. B.

    2015-09-01

    Despite enormous efforts, our understanding the structure and dynamics of α-synuclein (ASN), a disordered protein (that plays a key role in neurodegenerative disease) is far from complete. In order to better understand sequence-structure-property relationships in α-SYNUCLEIN we have developed a coarse-grained model using knowledge-based residue-residue interactions and used it to study the structure of free ASN as a function of temperature (T) with a large-scale Monte Carlo simulation. Snapshots of the simulation and contour contact maps show changes in structure formation due to self-assembly as a function of temperature. Variations in the residue mobility profiles reveal clear distinction among three segments along the protein sequence. The N-terminal (1-60) and C-terminal (96-140) regions contain the least mobile residues, which are separated by the higher mobility non-amyloid component (NAC) (61-95). Our analysis of the intra-protein contact profile shows a higher frequency of residue aggregation (clumping) in the N-terminal region relative to that in the C-terminal region, with little or no aggregation in the NAC region. The radius of gyration (Rg) of ASN decays monotonically with decreasing the temperature, consistent with the finding of Allison et al. (JACS, 2009). Our analysis of the structure function provides an insight into the mass (N) distribution of ASN, and the dimensionality (D) of the structure as a function of temperature. We find that the globular structure with D ≈ 3 at low T, a random coil, D ≈ 2 at high T and in between (2 ≤ D ≤ 3) at the intermediate temperatures. The magnitudes of D are in agreement with experimental estimates (J. Biological Chem 2002).

  7. Development and evaluation of VIE-PNN, a knowledge-based system for calculating the parenteral nutrition of newborn infants.

    PubMed

    Horn, Werner; Popow, Christian; Miksch, Silvia; Kirchner, Lieselotte; Seyfang, Andreas

    2002-03-01

    Calculating the daily changing composition of parenteral nutrition for small newborn infants is troublesome and time consuming routine work in neonatal intensive care. The task needs expertise and experience and is prone to inherent calculation errors. We designed VIE-PNN (Vienna Expert System for Parenteral Nutrition of Neonates), a knowledge-based system (KBS) in order to reduce daily routine work and calculation errors. VIE-PNN was redesigned several times because the clinicians accepted the system only when it saved time. The most recent version of VIE-PNN uses an Hypertext Markup Language (HTML)-based client-server architecture and is integrated into the intranet of the local patient data management system. Since more than 3 years all parenteral nutrition plans are calculated using VIE-PNN. Evaluating the system's performance and the users contentedness, we compared 50 nutrition plans calculated in parallel using VIE-PNN or a hand-held calculator, retrospectively analyzed more than 5000 nutrition plans stored in VIE-PNNs database and evaluated a user questionnaire. Nutrition plans were calculated in a mean time of 2.4 versus 7.1min using VIE-PNN or the hand-held calculator. Errors and omissions in the nutrition plans were detected in 22% versus 56% and errors in the VIE-PNN's plans occurring only with interactively changed values. Reviews of stored plans show that a mean of 4 out of 16 parameters were interactively changed. VIE-PNN was well accepted. Most important reasons for the successful operation of VIE-PNN in the daily routine work were time savings and robustness of the system.

  8. Towards knowledge-based systems in clinical practice: development of an integrated clinical information and knowledge management support system.

    PubMed

    Kalogeropoulos, Dimitris A; Carson, Ewart R; Collinson, Paul O

    2003-09-01

    Given that clinicians presented with identical clinical information will act in different ways, there is a need to introduce into routine clinical practice methods and tools to support the scientific homogeneity and accountability of healthcare decisions and actions. The benefits expected from such action include an overall reduction in cost, improved quality of care, patient and public opinion satisfaction. Computer-based medical data processing has yielded methods and tools for managing the task away from the hospital management level and closer to the desired disease and patient management level. To this end, advanced applications of information and disease process modelling technologies have already demonstrated an ability to significantly augment clinical decision making as a by-product. The wide-spread acceptance of evidence-based medicine as the basis of cost-conscious and concurrently quality-wise accountable clinical practice suffices as evidence supporting this claim. Electronic libraries are one-step towards an online status of this key health-care delivery quality control environment. Nonetheless, to date, the underlying information and knowledge management technologies have failed to be integrated into any form of pragmatic or marketable online and real-time clinical decision making tool. One of the main obstacles that needs to be overcome is the development of systems that treat both information and knowledge as clinical objects with same modelling requirements. This paper describes the development of such a system in the form of an intelligent clinical information management system: a system which at the most fundamental level of clinical decision support facilitates both the organised acquisition of clinical information and knowledge and provides a test-bed for the development and evaluation of knowledge-based decision support functions.

  9. Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

    NASA Astrophysics Data System (ADS)

    Elag, M.; Goodall, J. L.

    2013-12-01

    Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL

  10. Can knowledge-based N management produce more staple grain with lower greenhouse gas emission and reactive nitrogen pollution? A meta-analysis.

    PubMed

    Xia, Longlong; Lam, Shu Kee; Chen, Deli; Wang, Jinyang; Tang, Quan; Yan, Xiaoyuan

    2017-05-01

    Knowledge-based nitrogen (N) management, which is designed for a better synchronization of crop N demand with N supply, is critical for global food security and environmental sustainability. Yet, a comprehensive assessment on how these N management practices affect food production, greenhouse gas emission (GHG), and N pollution in China is lacking. We compiled the results of 376 studies (1166 observations) to evaluate the overall effects of seven knowledge-based N management practices on crop productivity, nitrous oxide (N2 O) emission, and major reactive N (Nr) losses (ammonia, NH3 ; N leaching and runoff), for staple grain (rice, wheat, and corn) production in China. These practices included the application of controlled-release N fertilizer, nitrification inhibitor (NI) and urease inhibitor (UI), higher splitting frequency of fertilizer N application, lower basal N fertilizer (BF) proportion, deep placement of N fertilizer, and optimal N rate based on soil N test. Our results showed that, compared to traditional N management, these knowledge-based N practices significantly increased grain yields by 1.3-10.0%, which is attributed to the higher aboveground N uptake (5.1-12.1%) and N use efficiency in grain (8.0-48.2%). Moreover, these N management practices overall reduced GHG emission and Nr losses, by 5.4-39.8% for N2 O emission, 30.7-61.5% for NH3 emission (except for the NI application), 13.6-37.3% for N leaching, and 15.5-45.0% for N runoff. The use of NI increased NH3 emission by 27.5% (9.0-56.0%), which deserves extra-attention. The cost and benefit analysis indicated that the yield profit of these N management practices exceeded the corresponding input cost, which resulted in a significant increase of the net economic benefit by 2.9-12.6%. These results suggest that knowledge-based N management practice can be considered an effective way to ensure food security and improve environmental sustainability, while increasing economic return. © 2016 John Wiley

  11. Development and evaluation of a clinical model for lung cancer patients using stereotactic body radiotherapy (SBRT) within a knowledge-based algorithm for treatment planning.

    PubMed

    Snyder, Karen Chin; Kim, Jinkoo; Reding, Anne; Fraser, Corey; Gordon, James; Ajlouni, Munther; Movsas, Benjamin; Chetty, Indrin J

    2016-11-08

    The purpose of this study was to describe the development of a clinical model for lung cancer patients treated with stereotactic body radiotherapy (SBRT) within a knowledge-based algorithm for treatment planning, and to evaluate the model performance and applicability to different planning techniques, tumor locations, and beam arrangements. 105 SBRT plans for lung cancer patients previously treated at our institution were included in the development of the knowledge-based model (KBM). The KBM was trained with a combination of IMRT, VMAT, and 3D CRT techniques. Model performance was validated with 25 cases, for both IMRT and VMAT. The full KBM encompassed lesions located centrally vs. peripherally (43:62), upper vs. lower (62:43), and anterior vs. posterior (60:45). Four separate sub-KBMs were created based on tumor location. Results were compared with the full KBM to evaluate its robustness. Beam templates were used in conjunction with the optimizer to evaluate the model's ability to handle suboptimal beam placements. Dose differences to organs-at-risk (OAR) were evaluated between the plans gener-ated by each KBM. Knowledge-based plans (KBPs) were comparable to clinical plans with respect to target conformity and OAR doses. The KBPs resulted in a lower maximum spinal cord dose by 1.0 ± 1.6 Gy compared to clinical plans, p = 0.007. Sub-KBMs split according to tumor location did not produce significantly better DVH estimates compared to the full KBM. For central lesions, compared to the full KBM, the peripheral sub-KBM resulted in lower dose to 0.035 cc and 5 cc of the esophagus, both by 0.4Gy ± 0.8Gy, p = 0.025. For all lesions, compared to the full KBM, the posterior sub-KBM resulted in higher dose to 0.035 cc, 0.35 cc, and 1.2 cc of the spinal cord by 0.2 ± 0.4Gy, p = 0.01. Plans using template beam arrangements met target and OAR criteria, with an increase noted in maximum heart dose (1.2 ± 2.2Gy, p = 0.01) and GI (0.2 ± 0.4, p = 0.01) for the nine

  12. Sbexpert users guide (version 1.0): A knowledge-based decision-support system for spruce beetle management. Forest Service general technical report

    SciTech Connect

    Reynolds, K.M.; Holsten, E.H.; Werner, R.A.

    1995-03-01

    SBexpert version 1.0 is a knowledge-based decision-support system for management of spruce beetle developed for use in Microsoft Windows. The users guide provides detailed instructions on the use of all SBexpert features. SBexpert has four main subprograms; introduction, analysis, textbook, and literature. The introduction is the first of the five subtopics in the SBexpert help system. The analysis topic is an advisory system for spruce beetle management that provides recommendation for reducing spruce beetle hazard and risk to spruce stands and is the main analytical topic in SBexpert. The textbook and literature topics provide complementary decision support for analysis.

  13. Discovery of novel inhibitors of Aurora kinases with indazole scaffold: In silico fragment-based and knowledge-based drug design.

    PubMed

    Chang, Chun-Feng; Lin, Wen-Hsing; Ke, Yi-Yu; Lin, Yih-Shyan; Wang, Wen-Chieh; Chen, Chun-Hwa; Kuo, Po-Chu; Hsu, John T A; Uang, Biing-Jiun; Hsieh, Hsing-Pang

    2016-11-29

    Aurora kinases have emerged as important anticancer targets so that there are several inhibitors have advanced into clinical study. Herein, we identified novel indazole derivatives as potent Aurora kinases inhibitors by utilizing in silico fragment-based approach and knowledge-based drug design. After intensive hit-to-lead optimization, compounds 17 (dual Aurora A and B), 21 (Aurora B selective) and 30 (Aurora A selective) possessed indazole privileged scaffold with different substituents, which provide sub-type kinase selectivity. Computational modeling helps in understanding that the isoform selectivity could be targeted specific residue in the Aurora kinase binding pocket in particular targeting residues Arg220, Thr217 or Glu177.

  14. UniProtKB/Swiss-Prot, the Manually Annotated Section of the UniProt KnowledgeBase: How to Use the Entry View.

    PubMed

    Boutet, Emmanuel; Lieberherr, Damien; Tognolli, Michael; Schneider, Michel; Bansal, Parit; Bridge, Alan J; Poux, Sylvain; Bougueleret, Lydie; Xenarios, Ioannis

    2016-01-01

    The Universal Protein Resource (UniProt, http://www.uniprot.org ) consortium is an initiative of the SIB Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) to provide the scientific community with a central resource for protein sequences and functional information. The UniProt consortium maintains the UniProt KnowledgeBase (UniProtKB), updated every 4 weeks, and several supplementary databases including the UniProt Reference Clusters (UniRef) and the UniProt Archive (UniParc).The Swiss-Prot section of the UniProt KnowledgeBase (UniProtKB/Swiss-Prot) contains publicly available expertly manually annotated protein sequences obtained from a broad spectrum of organisms. Plant protein entries are produced in the frame of the Plant Proteome Annotation Program (PPAP), with an emphasis on characterized proteins of Arabidopsis thaliana and Oryza sativa. High level annotations provided by UniProtKB/Swiss-Prot are widely used to predict annotation of newly available proteins through automatic pipelines.The purpose of this chapter is to present a guided tour of a UniProtKB/Swiss-Prot entry. We will also present some of the tools and databases that are linked to each entry.

  15. TH-A-9A-08: Knowledge-Based Quality Control of Clinical Stereotactic Radiosurgery Treatment Plans

    SciTech Connect

    Shiraishi, S; Moore, K L; Tan, J; Olsen, L

    2014-06-15

    Purpose: To develop a quality control tool to reduce stereotactic radiosurgery (SRS) planning variability using models that predict achievable plan quality metrics (QMs) based on individual patient anatomy. Methods: Using a knowledge-based methodology that quantitatively correlates anatomical geometric features to resultant organ-at-risk (OAR) dosimetry, we developed models for predicting achievable OAR dose-volume histograms (DVHs) by training with a cohort of previously treated SRS patients. The DVH-based QMs used in this work are the gradient measure, GM=(3/4pi)^1/3*[V50%^1/3−V100%^1/3], and V10Gy of normal brain. As GM quantifies the total rate of dose fall-off around the planning target volume (PTV), all voxels inside the patient's body contour were treated as OAR for DVH prediction. 35 previously treated SRS plans from our institution were collected; all were planned with non-coplanar volumetric-modulated arc therapy to prescription doses of 12–25 Gy. Of the 35-patient cohort, 15 were used for model training and 20 for model validation. Accuracies of the predictions were quantified by the mean and the standard deviation of the difference between clinical and predicted QMs, δQM=QM-clin−QM-pred. Results: Best agreement between predicted and clinical QMs was obtained when models were built separately for V-PTV<2.5cc and V-PTV>2.5cc. Eight patients trained the V-PTV<2.5cc model and seven patients trained the V-PTV>2.5cc models, respectively. The mean and the standard deviation of δGM were 0.3±0.4mm for the training sets and −0.1±0.6mm for the validation sets, demonstrating highly accurate GM predictions. V10Gy predictions were also highly accurate, with δV10Gy=0.8±0.7cc for the training sets and δV10Gy=0.7±1.4cc for the validation sets. Conclusion: The accuracy of the models in predicting two key SRS quality metrics highlights the potential of this technique for quality control for SRS treatments. Future investigations will seek to determine

  16. A knowledge-based method for reducing attenuation artefacts caused by cardiac appliances in myocardial PET/CT.

    PubMed

    Hamill, James J; Brunken, Richard C; Bybel, Bohdan; DiFilippo, Frank P; Faul, David D

    2006-06-07

    Attenuation artefacts due to implanted cardiac defibrillator leads have previously been shown to adversely impact cardiac PET/CT imaging. In this study, the severity of the problem is characterized, and an image-based method is described which reduces the resulting artefact in PET. Automatic implantable cardioverter defibrillator (AICD) leads cause a moving-metal artefact in the CT sections from which the PET attenuation correction factors (ACFs) are derived. Fluoroscopic cine images were measured to demonstrate that the defibrillator's highly attenuating distal shocking coil moves rhythmically across distances on the order of 1 cm. Rhythmic motion of this magnitude was created in a phantom with a moving defibrillator lead. A CT study of the phantom showed that the artefact contained regions of incorrect, very high CT values and adjacent regions of incorrect, very low CT values. The study also showed that motion made the artefact more severe. A knowledge-based metal artefact reduction method (MAR) is described that reduces the magnitude of the error in the CT images, without use of the corrupted sinograms. The method modifies the corrupted image through a sequence of artefact detection procedures, morphological operations, adjustments of CT values and three-dimensional filtering. The method treats bone the same as metal. The artefact reduction method is shown to run in a few seconds, and is validated by applying it to a series of phantom studies in which reconstructed PET tracer distribution values are wrong by as much as 60% in regions near the CT artefact when MAR is not applied, but the errors are reduced to about 10% of expected values when MAR is applied. MAR changes PET image values by a few per cent in regions not close to the artefact. The changes can be larger in the vicinity of bone. In patient studies, the PET reconstruction without MAR sometimes results in anomalously high values in the infero-septal wall. Clinical performance of MAR is assessed by two

  17. The use of knowledge-based Genetic Algorithm for starting time optimisation in a lot-bucket MRP

    NASA Astrophysics Data System (ADS)

    Ridwan, Muhammad; Purnomo, Andi

    2016-01-01

    In production planning, Material Requirement Planning (MRP) is usually developed based on time-bucket system, a period in the MRP is representing the time and usually weekly. MRP has been successfully implemented in Make To Stock (MTS) manufacturing, where production activity must be started before customer demand is received. However, to be implemented successfully in Make To Order (MTO) manufacturing, a modification is required on the conventional MRP in order to make it in line with the real situation. In MTO manufacturing, delivery schedule to the customers is defined strictly and must be fulfilled in order to increase customer satisfaction. On the other hand, company prefers to keep constant number of workers, hence production lot size should be constant as well. Since a bucket in conventional MRP system is representing time and usually weekly, hence, strict delivery schedule could not be accommodated. Fortunately, there is a modified time-bucket MRP system, called as lot-bucket MRP system that proposed by Casimir in 1999. In the lot-bucket MRP system, a bucket is representing a lot, and the lot size is preferably constant. The time to finish every lot could be varying depends on due date of lot. Starting time of a lot must be determined so that every lot has reasonable production time. So far there is no formal method to determine optimum starting time in the lot-bucket MRP system. Trial and error process usually used for it but some time, it causes several lots have very short production time and the lot-bucket MRP would be infeasible to be executed. This paper presents the use of Genetic Algorithm (GA) for optimisation of starting time in a lot-bucket MRP system. Even though GA is well known as powerful searching algorithm, however, improvement is still required in order to increase possibility of GA in finding optimum solution in shorter time. A knowledge-based system has been embedded in the proposed GA as the improvement effort, and it is proven that the

  18. A knowledge-based method for reducing attenuation artefacts caused by cardiac appliances in myocardial PET/CT

    NASA Astrophysics Data System (ADS)

    Hamill, James J.; Brunken, Richard C.; Bybel, Bohdan; Di Filippo, Frank P.; Faul, David D.

    2006-06-01

    Attenuation artefacts due to implanted cardiac defibrillator leads have previously been shown to adversely impact cardiac PET/CT imaging. In this study, the severity of the problem is characterized, and an image-based method is described which reduces the resulting artefact in PET. Automatic implantable cardioverter defibrillator (AICD) leads cause a moving-metal artefact in the CT sections from which the PET attenuation correction factors (ACFs) are derived. Fluoroscopic cine images were measured to demonstrate that the defibrillator's highly attenuating distal shocking coil moves rhythmically across distances on the order of 1 cm. Rhythmic motion of this magnitude was created in a phantom with a moving defibrillator lead. A CT study of the phantom showed that the artefact contained regions of incorrect, very high CT values and adjacent regions of incorrect, very low CT values. The study also showed that motion made the artefact more severe. A knowledge-based metal artefact reduction method (MAR) is described that reduces the magnitude of the error in the CT images, without use of the corrupted sinograms. The method modifies the corrupted image through a sequence of artefact detection procedures, morphological operations, adjustments of CT values and three-dimensional filtering. The method treats bone the same as metal. The artefact reduction method is shown to run in a few seconds, and is validated by applying it to a series of phantom studies in which reconstructed PET tracer distribution values are wrong by as much as 60% in regions near the CT artefact when MAR is not applied, but the errors are reduced to about 10% of expected values when MAR is applied. MAR changes PET image values by a few per cent in regions not close to the artefact. The changes can be larger in the vicinity of bone. In patient studies, the PET reconstruction without MAR sometimes results in anomalously high values in the infero-septal wall. Clinical performance of MAR is assessed by two

  19. A dosimetric evaluation of knowledge-based VMAT planning with simultaneous integrated boosting for rectal cancer patients.

    PubMed

    Wu, Hao; Jiang, Fan; Yue, Haizhen; Li, Sha; Zhang, Yibao

    2016-11-08

    RapidPlan, a commercial knowledge-based optimizer, has been tested on head and neck, lung, esophageal, breast, liver, and prostate cancer patients. To appraise its performance on VMAT planning with simultaneous integrated boosting (SIB) for rectal cancer, this study configured a DVH (dose-volume histogram) estimation model consisting 80 best-effort manual cases of this type. Using the model-generated objectives, the MLC (multileaf collimator) sequences of other 70 clinically approved plans were reoptimized, while the remaining parameters, such as field geometry and photon energy, were maintained. Dosimetric outcomes were assessed by comparing homogeneity index (HI), conformal index (CI), hot spots (volumes receiving over 107% of the prescribed dose, V107%), mean dose and dose to the 50% volume of femoral head (Dmean_FH and D50%_FH), and urinary bladder (Dmean_UB and D50%_UB), and the mean DVH plotting. Paired samples t-test or Wilcoxon signed-rank test suggested that comparable CI were achieved by RapidPlan (0.99± 0.04 for PTVboost, and 1.03 ± 0.02 for PTV) and original plans (1.00 ± 0.05 for PTVboost and 1.03 ± 0.02 for PTV), respectively (p > 0.05). Slightly improved HI of planning target volume (PTVboost) and PTV were observed in the RapidPlan cases (0.05 ± 0.01 for PTVboost, and 0.26 ± 0.01 for PTV) than the original plans (0.06 ± 0.01 for PTVboost and 0.26 ± 0.01 for PTV), p < 0.05. More cases with positive V107% were found in the original (18 plans) than the RapidPlan group (none). RapidPlan significantly reduced the D50%_FH (by 1.53 Gy / 9.86% from 15.52 ± 2.17 to 13.99± 1.16 Gy), Dmean_FH (by 1.29 Gy / 7.78% from 16.59± 2.07 to 15.30 ± 0.70 G), D50%_UB (by 4.93 Gy / 17.50% from 28.17 ± 3.07 to 23.24± 2.13 Gy), and Dmean_UB (by 3.94Gy / 13.43% from 29.34 ± 2.34 to 25.40 ± 1.36 Gy), respectively. The more concentrated distribution of RapidPlan data points indicated an enhanced consis-tency of plan quality.

  20. Two-dimensional knowledge-based volumetric reconstruction of the right ventricle documents short-term improvement in pulmonary hypertension.

    PubMed

    Schwaiger, Johannes P; Knight, Daniel S; Kaier, Thomas; Gallimore, Adele; Denton, Christopher P; Schreiber, Benjamin E; Handler, Clive; Coghlan, John G

    2017-06-01

    Data are scarce about short-term right ventricular changes in pulmonary hypertension. Two-dimensional knowledge-based reconstruction of the right ventricle with 2D echocardiography (2DKBR) has been shown to be a valid alternative to Cardiac MRI. In this longitudinal study 25 pulmonary hypertension patients underwent 2DKBR of the right ventricle, assessment of NT-proBNP levels and functional class at baseline and after a mean follow-up of 6.1 months. Patients were followed up clinically for a further mean of 8.2 months. The majority of patients had connective tissue disease (CTD) associated pulmonary arterial hypertension (n=15) or chronic thromboembolic pulmonary hypertension (CTEPH; n=6). A total of 15 patients underwent an intervention, either new targeted therapy, escalation of targeted therapy or pulmonary endarterectomy. A total of 10 clinically stable patients were routinely followed up without any change in therapy. There were significant improvements in the right ventricular end-diastolic volume index (111±29 mL/m² vs 100±36 mL/m²; P=.038), end-systolic volume index (72±23 mL/m² vs 61±25 mL/m²; P=.001), and ejection fraction (35±10% vs 40±9%; P=.030). Changes in NT-proBNP levels correlated strongest with changes in end-systolic volume index (r=-.77; P=<.0001). Four patients experienced clinical worsening during extended follow-up, dilatation of the right ventricle was associated with clinical worsening. In a CTD and CTEPH dominated patient population significant reverse remodeling and improvement of ejection fraction occurred despite a short follow-up and was paralleled by significant changes in NT-proBNP levels. Further right ventricular dilatation was associated with worse clinical outcome. 2DKBR is a feasible substitute for Cardiac MRI to follow-up right ventricular indices in pulmonary hypertension. © 2017, Wiley Periodicals, Inc.