Science.gov

Sample records for 7-mer knowledge-based potential

  1. A relational data-knowledge base system and its potential in developing a distributed data-knowledge system

    NASA Technical Reports Server (NTRS)

    Rahimian, Eric N.; Graves, Sara J.

    1988-01-01

    A new approach used in constructing a rational data knowledge base system is described. The relational database is well suited for distribution due to its property of allowing data fragmentation and fragmentation transparency. An example is formulated of a simple relational data knowledge base which may be generalized for use in developing a relational distributed data knowledge base system. The efficiency and ease of application of such a data knowledge base management system is briefly discussed. Also discussed are the potentials of the developed model for sharing the data knowledge base as well as the possible areas of difficulty in implementing the relational data knowledge base management system.

  2. 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).

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. Cooperative Knowledge Bases.

    DTIC Science & Technology

    1988-02-01

    intellegent knowledge bases. The present state of our system for concurrent evaluation of a knowledge base of logic clauses using static allocation...de Kleer, J., An assumption-based TMS, Artificial Intelligence, Vol. 28, No. 2, 1986. [Doyle 79) Doyle, J. A truth maintenance system, Artificial

  9. A knowledge base for the discovery of function, diagnostic potential and drug effects on cellular and extracellular miRNAs

    PubMed Central

    2014-01-01

    Background MicroRNAs (miRNAs) are small noncoding RNAs that play an important role in the regulation of various biological processes through their interaction with cellular mRNAs. A significant amount of miRNAs has been found in extracellular human body fluids (e.g. plasma and serum) and some circulating miRNAs in the blood have been successfully revealed as biomarkers for diseases including cardiovascular diseases and cancer. Released miRNAs do not necessarily reflect the abundance of miRNAs in the cell of origin. It is claimed that release of miRNAs from cells into blood and ductal fluids is selective and that the selection of released miRNAs may correlate with malignancy. Moreover, miRNAs play a significant role in pharmacogenomics by down-regulating genes that are important for drug function. In particular, the use of drugs should be taken into consideration while analyzing plasma miRNA levels as drug treatment. This may impair their employment as biomarkers. Description We enriched our manually curated extracellular/circulating microRNAs database, miRandola, by providing (i) a systematic comparison of expression profiles of cellular and extracellular miRNAs, (ii) a miRNA targets enrichment analysis procedure, (iii) information on drugs and their effect on miRNA expression, obtained by applying a natural language processing algorithm to abstracts obtained from PubMed. Conclusions This allows users to improve the knowledge about the function, diagnostic potential, and the drug effects on cellular and circulating miRNAs. PMID:25077952

  10. Creating a knowledge-based economy in the United Arab Emirates: realising the unfulfilled potential of women in the science, technology and engineering fields

    NASA Astrophysics Data System (ADS)

    Ghazal Aswad, Noor; Vidican, Georgeta; Samulewicz, Diana

    2011-12-01

    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 their attitudes towards science, technology and engineering (STE). The findings point to the importance of adapting mainstream policies to the local context and the need to better understand the effect of culture and society on the individual and the economy. There is a need to increase interest in STE by raising awareness of what the fields entail, potential careers and their suitability with existing cultural beliefs. Also suggested is the need to overcome negative stereotypes of engineering, implement initiatives for further family involvement at the higher education level, as well as the need to ensure a greater availability of STE university programmes across the UAE.

  11. Conformational temperature-dependent behavior of a histone H2AX: a coarse-grained Monte Carlo approach via knowledge-based interaction potentials.

    PubMed

    Fritsche, Miriam; Pandey, Ras B; Farmer, Barry L; Heermann, Dieter W

    2012-01-01

    Histone proteins are not only important due to their vital role in cellular processes such as DNA compaction, replication and repair but also show intriguing structural properties that might be exploited for bioengineering purposes such as the development of nano-materials. Based on their biological and technological implications, it is interesting to investigate the structural properties of proteins as a function of temperature. In this work, we study the spatial response dynamics of the histone H2AX, consisting of 143 residues, by a coarse-grained bond fluctuating model for a broad range of normalized temperatures. A knowledge-based interaction matrix is used as input for the residue-residue Lennard-Jones potential.We find a variety of equilibrium structures including global globular configurations at low normalized temperature (T* = 0.014), combination of segmental globules and elongated chains (T* = 0.016,0.017), predominantly elongated chains (T* = 0.019,0.020), as well as universal SAW conformations at high normalized temperature (T* ≥ 0.023). The radius of gyration of the protein exhibits a non-monotonic temperature dependence with a maximum at a characteristic temperature (T(c)* = 0.019) where a crossover occurs from a positive (stretching at T* ≤ T(c)*) to negative (contraction at T* ≥ T(c)*) thermal response on increasing T*.

  12. Thermal response of proteins (histone H2AX, H3.1) by a coarse-grained Monte Carlo simulation with a knowledge-based phenomenological potential

    NASA Astrophysics Data System (ADS)

    Fritsche, Miriam; Heermann, Dieter; Pandey, Ras; Farmer, Barry

    2012-02-01

    Using a coarse-grained bond fluctuating model, we investigate structure and dynamics of two histones, H2AX (143 residues) and H3.1 (136 residues) as a function of temperature (T). A knowledged based contact matrix is used as an input for a phenomenological residue-residue interaction in a generalized Lennard-Jones potential. Metropolis algorithm is used to execute stochastic movement of each residue. A number of local and global physical quantities are analyzed. Despite unique energy and mobility profiles of its residues in a specific sequence, the histone H3.1 appears to undergo a structural transformation from a random coil to a globular conformation on reducing the temperature. The radius of gyration of the histone H2AX, in contrast, exhibits a non-monotonic dependence on temperature with a maximum at a characteristic temperature (Tc) where crossover occurs from a positive (stretching below Tc) to negative (contraction above Tc) thermal response on increasing T. Multi-scale structures of the proteins are examined by a detailed analysis of their structure functions.

  13. 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…

  14. Mobile robot knowledge base

    NASA Astrophysics Data System (ADS)

    Heath Pastore, Tracy; Barnes, Mitchell; Hallman, Rory

    2005-05-01

    Robot technology is developing at a rapid rate for both commercial and Department of Defense (DOD) applications. As a result, the task of managing both technology and experience information is growing. In the not-to-distant past, tracking development efforts of robot platforms, subsystems and components was not too difficult, expensive, or time consuming. To do the same today is a significant undertaking. The Mobile Robot Knowledge Base (MRKB) provides the robotics community with a web-accessible, centralized resource for sharing information, experience, and technology to more efficiently and effectively meet the needs of the robot system user. The resource includes searchable information on robot components, subsystems, mission payloads, platforms, and DOD robotics programs. In addition, the MRKB website provides a forum for technology and information transfer within the DOD robotics community and an interface for the Robotic Systems Pool (RSP). The RSP manages a collection of small teleoperated and semi-autonomous robotic platforms, available for loan to DOD and other qualified entities. The objective is to put robots in the hands of users and use the test data and fielding experience to improve robot systems.

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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.

  20. Population Education: A Knowledge Base.

    ERIC Educational Resources Information Center

    Jacobson, Willard J.

    To aid junior high and high school educators and curriculum planners as they develop population education programs, the book provides an overview of the population education knowledge base. In addition, it suggests learning activities, discussion questions, and background information which can be integrated into courses dealing with population,…

  1. Epistemology of knowledge based simulation

    SciTech Connect

    Reddy, R.

    1987-04-01

    Combining artificial intelligence concepts, with traditional simulation methodologies yields a powerful design support tool known as knowledge based simulation. This approach turns a descriptive simulation tool into a prescriptive tool, one which recommends specific goals. Much work in the area of general goal processing and explanation of recommendations remains to be done.

  2. Automated knowledge-base refinement

    NASA Technical Reports Server (NTRS)

    Mooney, Raymond J.

    1994-01-01

    Over the last several years, we have developed several systems for automatically refining incomplete and incorrect knowledge bases. These systems are given an imperfect rule base and a set of training examples and minimally modify the knowledge base to make it consistent with the examples. One of our most recent systems, FORTE, revises first-order Horn-clause knowledge bases. This system can be viewed as automatically debugging Prolog programs based on examples of correct and incorrect I/O pairs. In fact, we have already used the system to debug simple Prolog programs written by students in a programming language course. FORTE has also been used to automatically induce and revise qualitative models of several continuous dynamic devices from qualitative behavior traces. For example, it has been used to induce and revise a qualitative model of a portion of the Reaction Control System (RCS) of the NASA Space Shuttle. By fitting a correct model of this portion of the RCS to simulated qualitative data from a faulty system, FORTE was also able to correctly diagnose simple faults in this system.

  3. 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.

  4. Knowledge based jet engine diagnostics

    NASA Technical Reports Server (NTRS)

    Jellison, Timothy G.; Dehoff, Ronald L.

    1987-01-01

    A fielded expert system automates equipment fault isolation and recommends corrective maintenance action for Air Force jet engines. The knowledge based diagnostics tool was developed as an expert system interface to the Comprehensive Engine Management System, Increment IV (CEMS IV), the standard Air Force base level maintenance decision support system. XMAM (trademark), the Expert Maintenance Tool, automates procedures for troubleshooting equipment faults, provides a facility for interactive user training, and fits within a diagnostics information feedback loop to improve the troubleshooting and equipment maintenance processes. The application of expert diagnostics to the Air Force A-10A aircraft TF-34 engine equipped with the Turbine Engine Monitoring System (TEMS) is presented.

  5. 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.

  6. Knowledge Base Editor (SharpKBE)

    NASA Technical Reports Server (NTRS)

    Tikidjian, Raffi; James, Mark; Mackey, Ryan

    2007-01-01

    The SharpKBE software provides a graphical user interface environment for domain experts to build and manage knowledge base systems. Knowledge bases can be exported/translated to various target languages automatically, including customizable target languages.

  7. Foundation: Transforming data bases into knowledge bases

    NASA Technical Reports Server (NTRS)

    Purves, R. B.; Carnes, James R.; Cutts, Dannie E.

    1987-01-01

    One approach to transforming information stored in relational data bases into knowledge based representations and back again is described. This system, called Foundation, allows knowledge bases to take advantage of vast amounts of pre-existing data. A benefit of this approach is inspection, and even population, of data bases through an intelligent knowledge-based front-end.

  8. A Discussion of Knowledge Based Design

    NASA Technical Reports Server (NTRS)

    Wood, Richard M.; Bauer, Steven X. S.

    1999-01-01

    A discussion of knowledge and Knowledge- Based design as related to the design of aircraft is presented. The paper discusses the perceived problem with existing design studies and introduces the concepts of design and knowledge for a Knowledge- Based design system. A review of several Knowledge-Based design activities is provided. A Virtual Reality, Knowledge-Based system is proposed and reviewed. The feasibility of Virtual Reality to improve the efficiency and effectiveness of aerodynamic and multidisciplinary design, evaluation, and analysis of aircraft through the coupling of virtual reality technology and a Knowledge-Based design system is also reviewed. The final section of the paper discusses future directions for design and the role of Knowledge-Based design.

  9. Socially Relevant Knowledge Based Telemedicine

    DTIC Science & Technology

    2012-10-01

    provide, they have potential to change behavior and/or attitude at different situations and different circumstances. Fogg mentions that there are many...appropriate way to persuade users to perform various activities. Fogg [8] defines persuasive technologies as “interactive computing systems designed to...2009, pp 54-63. [8] Fogg , B. J., Persuasive Technology: Using computers to change what we think and do, 2003, Morgan Kaufman. [9] Pedersen, P

  10. 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.

  11. 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)

  12. Methodology for testing and validating knowledge bases

    NASA Technical Reports Server (NTRS)

    Krishnamurthy, C.; Padalkar, S.; Sztipanovits, J.; Purves, B. R.

    1987-01-01

    A test and validation toolset developed for artificial intelligence programs is described. The basic premises of this method are: (1) knowledge bases have a strongly declarative character and represent mostly structural information about different domains, (2) the conditions for integrity, consistency, and correctness can be transformed into structural properties of knowledge bases, and (3) structural information and structural properties can be uniformly represented by graphs and checked by graph algorithms. The interactive test and validation environment have been implemented on a SUN workstation.

  13. Knowledge based programming environments: A perspective

    NASA Technical Reports Server (NTRS)

    Amin, Ashok T.

    1988-01-01

    Programming environments is an area of recent origin and refers to an integrated set of tools, such as program library, text editor, compiler, and debugger, in support of program development. Understanding of programs and programming has lead to automated techniques for program development. Knowledge based programming system using program transformations offer significant impact on future program development methodologies. A review of recent developments in the area of knowledge based programming environments, from the perspective of software engineering, is presented.

  14. Knowledge Based Systems and Metacognition in Radar

    NASA Astrophysics Data System (ADS)

    Capraro, Gerard T.; Wicks, Michael C.

    An airborne ground looking radar sensor's performance may be enhanced by selecting algorithms adaptively as the environment changes. A short description of an airborne intelligent radar system (AIRS) is presented with a description of the knowledge based filter and detection portions. A second level of artificial intelligence (AI) processing is presented that monitors, tests, and learns how to improve and control the first level. This approach is based upon metacognition, a way forward for developing knowledge based systems.

  15. 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.

  16. Irrelevance Reasoning in Knowledge Based Systems

    NASA Technical Reports Server (NTRS)

    Levy, A. Y.

    1993-01-01

    This dissertation considers the problem of reasoning about irrelevance of knowledge in a principled and efficient manner. Specifically, it is concerned with two key problems: (1) developing algorithms for automatically deciding what parts of a knowledge base are irrelevant to a query and (2) the utility of relevance reasoning. The dissertation describes a novel tool, the query-tree, for reasoning about irrelevance. Based on the query-tree, we develop several algorithms for deciding what formulas are irrelevant to a query. Our general framework sheds new light on the problem of detecting independence of queries from updates. We present new results that significantly extend previous work in this area. The framework also provides a setting in which to investigate the connection between the notion of irrelevance and the creation of abstractions. We propose a new approach to research on reasoning with abstractions, in which we investigate the properties of an abstraction by considering the irrelevance claims on which it is based. We demonstrate the potential of the approach for the cases of abstraction of predicates and projection of predicate arguments. Finally, we describe an application of relevance reasoning to the domain of modeling physical devices.

  17. 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.

  18. 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.

  19. Knowledge-based flow field zoning

    NASA Technical Reports Server (NTRS)

    Andrews, Alison E.

    1988-01-01

    Automation flow field zoning in two dimensions is an important step towards easing the three-dimensional grid generation bottleneck in computational fluid dynamics. A knowledge based approach works well, but certain aspects of flow field zoning make the use of such an approach challenging. A knowledge based flow field zoner, called EZGrid, was implemented and tested on representative two-dimensional aerodynamic configurations. Results are shown which illustrate the way in which EZGrid incorporates the effects of physics, shape description, position, and user bias in a flow field zoning.

  20. 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.

  1. 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…

  2. 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)

  3. The adverse outcome pathway knowledge base

    EPA Science Inventory

    The rapid advancement of the Adverse Outcome Pathway (AOP) framework has been paralleled by the development of tools to store, analyse, and explore AOPs. The AOP Knowledge Base (AOP-KB) project has brought three independently developed platforms (Effectopedia, AOP-Wiki, and AOP-X...

  4. Improving the Knowledge Base in Teacher Education.

    ERIC Educational Resources Information Center

    Rockler, Michael J.

    Education in the United States for most of the last 50 years has built its knowledge base on a single dominating foundation--behavioral psychology. This paper analyzes the history of behaviorism. Syntheses are presented of the theories of Ivan P. Pavlov, J. B. Watson, and B. F. Skinner, all of whom contributed to the body of works on behaviorism.…

  5. Constructing Knowledge Bases: A Promising Instructional Tool.

    ERIC Educational Resources Information Center

    Trollip, Stanley R.; Lippert, Renate C.

    1987-01-01

    Argues that construction of knowledge bases is an instructional tool that encourages students' critical thinking in problem solving situations through metacognitive experiences. A study is described in which college students created expert systems to test the effectiveness of this method of instruction, and benefits for students and teachers are…

  6. Knowledge-based machine indexing from natural language text: Knowledge base design, development, and maintenance

    NASA Technical Reports Server (NTRS)

    Genuardi, Michael T.

    1993-01-01

    One strategy for machine-aided indexing (MAI) is to provide a concept-level analysis of the textual elements of documents or document abstracts. In such systems, natural-language phrases are analyzed in order to identify and classify concepts related to a particular subject domain. The overall performance of these MAI systems is largely dependent on the quality and comprehensiveness of their knowledge bases. These knowledge bases function to (1) define the relations between a controlled indexing vocabulary and natural language expressions; (2) provide a simple mechanism for disambiguation and the determination of relevancy; and (3) allow the extension of concept-hierarchical structure to all elements of the knowledge file. After a brief description of the NASA Machine-Aided Indexing system, concerns related to the development and maintenance of MAI knowledge bases are discussed. Particular emphasis is given to statistically-based text analysis tools designed to aid the knowledge base developer. One such tool, the Knowledge Base Building (KBB) program, presents the domain expert with a well-filtered list of synonyms and conceptually-related phrases for each thesaurus concept. Another tool, the Knowledge Base Maintenance (KBM) program, functions to identify areas of the knowledge base affected by changes in the conceptual domain (for example, the addition of a new thesaurus term). An alternate use of the KBM as an aid in thesaurus construction is also discussed.

  7. NRV web knowledge base on low-energy nuclear physics

    NASA Astrophysics Data System (ADS)

    Karpov, V.; Denikin, A. S.; Alekseev, A. P.; Zagrebaev, V. I.; Rachkov, V. A.; Naumenko, M. A.; Saiko, V. V.

    2016-09-01

    Principles underlying the organization and operation of the NRV web knowledge base on low-energy nuclear physics (http://nrv.jinr.ru) are described. This base includes a vast body of digitized experimental data on the properties of nuclei and on cross sections for nuclear reactions that is combined with a wide set of interconnected computer programs for simulating complex nuclear dynamics, which work directly in the browser of a remote user. Also, the current situation in the realms of application of network information technologies in nuclear physics is surveyed. The potential of the NRV knowledge base is illustrated in detail by applying it to the example of an analysis of the fusion of nuclei that is followed by the decay of the excited compound nucleus formed.

  8. 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.

  9. Bridging the gap: simulations meet knowledge bases

    NASA Astrophysics Data System (ADS)

    King, Gary W.; Morrison, Clayton T.; Westbrook, David L.; Cohen, Paul R.

    2003-09-01

    Tapir and Krill are declarative languages for specifying actions and agents, respectively, that can be executed in simulation. As such, they bridge the gap between strictly declarative knowledge bases and strictly executable code. Tapir and Krill components can be combined to produce models of activity which can answer questions about mechanisms and processes using conventional inference methods and simulation. Tapir was used in DARPA's Rapid Knowledge Formation (RKF) project to construct models of military tactics from the Army Field Manual FM3-90. These were then used to build Courses of Actions (COAs) which could be critiqued by declarative reasoning or via Monte Carlo simulation. Tapir and Krill can be read and written by non-knowledge engineers making it an excellent vehicle for Subject Matter Experts to build and critique knowledge bases.

  10. Clips as a knowledge based language

    NASA Technical Reports Server (NTRS)

    Harrington, James B.

    1987-01-01

    CLIPS is a language for writing expert systems applications on a personal or small computer. Here, the CLIPS programming language is described and compared to three other artificial intelligence (AI) languages (LISP, Prolog, and OPS5) with regard to the processing they provide for the implementation of a knowledge based system (KBS). A discussion is given on how CLIPS would be used in a control system.

  11. Satellite Contamination and Materials Outgassing Knowledge base

    NASA Technical Reports Server (NTRS)

    Minor, Jody L.; Kauffman, William J. (Technical Monitor)

    2001-01-01

    Satellite contamination continues to be a design problem that engineers must take into account when developing new satellites. To help with this issue, NASA's Space Environments and Effects (SEE) Program funded the development of the Satellite Contamination and Materials Outgassing Knowledge base. This engineering tool brings together in one location information about the outgassing properties of aerospace materials based upon ground-testing data, the effects of outgassing that has been observed during flight and measurements of the contamination environment by on-orbit instruments. The knowledge base contains information using the ASTM Standard E- 1559 and also consolidates data from missions using quartz-crystal microbalances (QCM's). The data contained in the knowledge base was shared with NASA by government agencies and industry in the US and international space agencies as well. The term 'knowledgebase' was used because so much information and capability was brought together in one comprehensive engineering design tool. It is the SEE Program's intent to continually add additional material contamination data as it becomes available - creating a dynamic tool whose value to the user is ever increasing. The SEE Program firmly believes that NASA, and ultimately the entire contamination user community, will greatly benefit from this new engineering tool and highly encourages the community to not only use the tool but add data to it as well.

  12. Presentation planning using an integrated knowledge base

    NASA Technical Reports Server (NTRS)

    Arens, Yigal; Miller, Lawrence; Sondheimer, Norman

    1988-01-01

    A description is given of user interface research aimed at bringing together multiple input and output modes in a way that handles mixed mode input (commands, menus, forms, natural language), interacts with a diverse collection of underlying software utilities in a uniform way, and presents the results through a combination of output modes including natural language text, maps, charts and graphs. The system, Integrated Interfaces, derives much of its ability to interact uniformly with the user and the underlying services and to build its presentations, from the information present in a central knowledge base. This knowledge base integrates models of the application domain (Navy ships in the Pacific region, in the current demonstration version); the structure of visual displays and their graphical features; the underlying services (data bases and expert systems); and interface functions. The emphasis is on a presentation planner that uses the knowledge base to produce multi-modal output. There has been a flurry of recent work in user interface management systems. (Several recent examples are listed in the references). Existing work is characterized by an attempt to relieve the software designer of the burden of handcrafting an interface for each application. The work has generally focused on intelligently handling input. This paper deals with the other end of the pipeline - presentations.

  13. 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).

  14. 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.

  15. Automated Fictional Ideation via Knowledge Base Manipulation.

    PubMed

    Llano, Maria Teresa; Colton, Simon; Hepworth, Rose; Gow, Jeremy

    The invention of fictional ideas (ideation) is often a central process in the creative production of artefacts such as poems, music and paintings, but has barely been studied in the computational creativity community. We present here a general approach to automated fictional ideation that works by manipulating facts specified in knowledge bases. More specifically, we specify a number of constructions which, by altering and combining facts from a knowledge base, result in the generation of fictions. Moreover, we present an instantiation of these constructions through the use of ConceptNet, a database of common sense knowledge. In order to evaluate the success of these constructions, we present a curation analysis that calculates the proportion of ideas which pass a typicality judgement. We further evaluate the output of this approach through a crowd-sourcing experiment in which participants were asked to rank ideas. We found a positive correlation between the participant's rankings and a chaining inference technique that automatically assesses the value of the fictions generated through our approach. We believe that these results show that this approach constitutes a firm basis for automated fictional ideation with evaluative capacity.

  16. 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.

  17. Modeling Guru: Knowledge Base for NASA Modelers

    NASA Astrophysics Data System (ADS)

    Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

    2009-05-01

    Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the

  18. 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.

  19. NASDA knowledge-based network planning system

    NASA Technical Reports Server (NTRS)

    Yamaya, K.; Fujiwara, M.; Kosugi, S.; Yambe, M.; Ohmori, M.

    1993-01-01

    One of the SODS (space operation and data system) sub-systems, NP (network planning) was the first expert system used by NASDA (national space development agency of Japan) for tracking and control of satellite. The major responsibilities of the NP system are: first, the allocation of network and satellite control resources and, second, the generation of the network operation plan data (NOP) used in automated control of the stations and control center facilities. Up to now, the first task of network resource scheduling was done by network operators. NP system automatically generates schedules using its knowledge base, which contains information on satellite orbits, station availability, which computer is dedicated to which satellite, and how many stations must be available for a particular satellite pass or a certain time period. The NP system is introduced.

  20. 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.

  1. 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.

  2. 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

  3. An Ebola virus-centered knowledge base.

    PubMed

    Kamdar, Maulik R; Dumontier, Michel

    2015-01-01

    Ebola virus (EBOV), of the family Filoviridae viruses, is a NIAID category A, lethal human pathogen. It is responsible for causing Ebola virus disease (EVD) that is a severe hemorrhagic fever and has a cumulative death rate of 41% in the ongoing epidemic in West Africa. There is an ever-increasing need to consolidate and make available all the knowledge that we possess on EBOV, even if it is conflicting or incomplete. This would enable biomedical researchers to understand the molecular mechanisms underlying this disease and help develop tools for efficient diagnosis and effective treatment. In this article, we present our approach for the development of an Ebola virus-centered Knowledge Base (Ebola-KB) using Linked Data and Semantic Web Technologies. We retrieve and aggregate knowledge from several open data sources, web services and biomedical ontologies. This knowledge is transformed to RDF, linked to the Bio2RDF datasets and made available through a SPARQL 1.1 Endpoint. Ebola-KB can also be explored using an interactive Dashboard visualizing the different perspectives of this integrated knowledge. We showcase how different competency questions, asked by domain users researching the druggability of EBOV, can be formulated as SPARQL Queries or answered using the Ebola-KB Dashboard.

  4. An Ebola virus-centered knowledge base

    PubMed Central

    Kamdar, Maulik R.; Dumontier, Michel

    2015-01-01

    Ebola virus (EBOV), of the family Filoviridae viruses, is a NIAID category A, lethal human pathogen. It is responsible for causing Ebola virus disease (EVD) that is a severe hemorrhagic fever and has a cumulative death rate of 41% in the ongoing epidemic in West Africa. There is an ever-increasing need to consolidate and make available all the knowledge that we possess on EBOV, even if it is conflicting or incomplete. This would enable biomedical researchers to understand the molecular mechanisms underlying this disease and help develop tools for efficient diagnosis and effective treatment. In this article, we present our approach for the development of an Ebola virus-centered Knowledge Base (Ebola-KB) using Linked Data and Semantic Web Technologies. We retrieve and aggregate knowledge from several open data sources, web services and biomedical ontologies. This knowledge is transformed to RDF, linked to the Bio2RDF datasets and made available through a SPARQL 1.1 Endpoint. Ebola-KB can also be explored using an interactive Dashboard visualizing the different perspectives of this integrated knowledge. We showcase how different competency questions, asked by domain users researching the druggability of EBOV, can be formulated as SPARQL Queries or answered using the Ebola-KB Dashboard. Database URL: http://ebola.semanticscience.org. PMID:26055098

  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. DeepDive: Declarative Knowledge Base Construction

    PubMed Central

    De Sa, Christopher; Ratner, Alex; Ré, Christopher; Shin, Jaeho; Wang, Feiran; Wu, Sen; Zhang, Ce

    2016-01-01

    The dark data extraction or knowledge base construction (KBC) problem is to populate a SQL database with information from unstructured data sources including emails, webpages, and pdf reports. KBC is a long-standing problem in industry and research that encompasses problems of data extraction, cleaning, and integration. We describe DeepDive, a system that combines database and machine learning ideas to help develop KBC systems. The key idea in DeepDive is that statistical inference and machine learning are key tools to attack classical data problems in extraction, cleaning, and integration in a unified and more effective manner. DeepDive programs are declarative in that one cannot write probabilistic inference algorithms; instead, one interacts by defining features or rules about the domain. A key reason for this design choice is to enable domain experts to build their own KBC systems. We present the applications, abstractions, and techniques of DeepDive employed to accelerate construction of KBC systems. PMID:28344371

  7. A Collaborative Environment for Knowledge Base Development

    NASA Astrophysics Data System (ADS)

    Li, W.; Yang, C.; Raskin, R.; Nebert, D. D.; Wu, H.

    2009-12-01

    Knowledge Base (KB) is an essential component for capturing, structuring and defining the meanings of domain knowledge. It’s important in enabling the sharing and interoperability of scientific data and services in a smart manner. It’s also the foundation for most the research in semantic field, such as semantic reasoning and ranking. In collaborating with ESIP, GMU is developing an online interface and supporting infrastructure to allow semantic registration of datasets and other web resources. The semantic description of data, services, and scientific content will be collected and transformed to the KB. As a case study, the harvest of web map services from by Nordic mapping agencies to build a virtual Arctic spatial data infrastructure will be used as the domain example. To automate the process, a controlled vocabulary of certain subjects, such as solid water, is created to filter from existing data and service repositories to obtain a collection of closely related document. Then latent semantic indexing is utilized to analyze semantic relationship among concepts that appears in service document. At last, semantic structure in plain text will be mapped and automatically populated to the specific presentation of knowledge in the KB.

  8. [Artificial intelligence--the knowledge base applied to nephrology].

    PubMed

    Sancipriano, G P

    2005-01-01

    The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

  9. Weather, knowledge base and life-style

    NASA Astrophysics Data System (ADS)

    Bohle, Martin

    2015-04-01

    Why to main-stream curiosity for earth-science topics, thus to appraise these topics as of public interest? Namely, to influence practices how humankind's activities intersect the geosphere. How to main-stream that curiosity for earth-science topics? Namely, by weaving diverse concerns into common threads drawing on a wide range of perspectives: be it beauty or particularity of ordinary or special phenomena, evaluating hazards for or from mundane environments, or connecting the scholarly investigation with concerns of citizens at large; applying for threading traditional or modern media, arts or story-telling. Three examples: First "weather"; weather is a topic of primordial interest for most people: weather impacts on humans lives, be it for settlement, for food, for mobility, for hunting, for fishing, or for battle. It is the single earth-science topic that went "prime-time" since in the early 1950-ties the broadcasting of weather forecasts started and meteorologists present their work to the public, daily. Second "knowledge base"; earth-sciences are a relevant for modern societies' economy and value setting: earth-sciences provide insights into the evolution of live-bearing planets, the functioning of Earth's systems and the impact of humankind's activities on biogeochemical systems on Earth. These insights bear on production of goods, living conditions and individual well-being. Third "life-style"; citizen's urban culture prejudice their experiential connections: earth-sciences related phenomena are witnessed rarely, even most weather phenomena. In the past, traditional rural communities mediated their rich experiences through earth-centric story-telling. In course of the global urbanisation process this culture has given place to society-centric story-telling. Only recently anthropogenic global change triggered discussions on geoengineering, hazard mitigation, demographics, which interwoven with arts, linguistics and cultural histories offer a rich narrative

  10. 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.

  11. Advanced software development workstation. Knowledge base design: Design of knowledge base for flight planning application

    NASA Technical Reports Server (NTRS)

    Izygon, Michel E.

    1992-01-01

    The development process of the knowledge base for the generation of Test Libraries for Mission Operations Computer (MOC) Command Support focused on a series of information gathering interviews. These knowledge capture sessions are supporting the development of a prototype for evaluating the capabilities of INTUIT on such an application. the prototype includes functions related to POCC (Payload Operation Control Center) processing. It prompts the end-users for input through a series of panels and then generates the Meds associated with the initialization and the update of hazardous command tables for a POCC Processing TLIB.

  12. Automated knowledge base development from CAD/CAE databases

    NASA Technical Reports Server (NTRS)

    Wright, R. Glenn; Blanchard, Mary

    1988-01-01

    Knowledge base development requires a substantial investment in time, money, and resources in order to capture the knowledge and information necessary for anything other than trivial applications. This paper addresses a means to integrate the design and knowledge base development process through automated knowledge base development from CAD/CAE databases and files. Benefits of this approach include the development of a more efficient means of knowledge engineering, resulting in the timely creation of large knowledge based systems that are inherently free of error.

  13. System Engineering for the NNSA Knowledge Base

    NASA Astrophysics Data System (ADS)

    Young, C.; Ballard, S.; Hipp, J.

    2006-05-01

    To improve ground-based nuclear explosion monitoring capability, GNEM R&E (Ground-based Nuclear Explosion Monitoring Research & Engineering) researchers at the national laboratories have collected an extensive set of raw data products. These raw data are used to develop higher level products (e.g. 2D and 3D travel time models) to better characterize the Earth at regional scales. The processed products and selected portions of the raw data are stored in an archiving and access system known as the NNSA (National Nuclear Security Administration) Knowledge Base (KB), which is engineered to meet the requirements of operational monitoring authorities. At its core, the KB is a data archive, and the effectiveness of the KB is ultimately determined by the quality of the data content, but access to that content is completely controlled by the information system in which that content is embedded. Developing this system has been the task of Sandia National Laboratories (SNL), and in this paper we discuss some of the significant challenges we have faced and the solutions we have engineered. One of the biggest system challenges with raw data has been integrating database content from the various sources to yield an overall KB product that is comprehensive, thorough and validated, yet minimizes the amount of disk storage required. Researchers at different facilities often use the same data to develop their products, and this redundancy must be removed in the delivered KB, ideally without requiring any additional effort on the part of the researchers. Further, related data content must be grouped together for KB user convenience. Initially SNL used whatever tools were already available for these tasks, and did the other tasks manually. The ever-growing volume of KB data to be merged, as well as a need for more control of merging utilities, led SNL to develop our own java software package, consisting of a low- level database utility library upon which we have built several

  14. 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.

  15. A knowledge base for Vitis vinifera functional analysis

    PubMed Central

    2015-01-01

    Background Vitis vinifera (Grapevine) is the most important fruit species in the modern world. Wine and table grapes sales contribute significantly to the economy of major wine producing countries. The most relevant goals in wine production concern quality and safety. In order to significantly improve the achievement of these objectives and to gain biological knowledge about cultivars, a genomic approach is the most reliable strategy. The recent grapevine genome sequencing offers the opportunity to study the potential roles of genes and microRNAs in fruit maturation and other physiological and pathological processes. Although several systems allowing the analysis of plant genomes have been reported, none of them has been designed specifically for the functional analysis of grapevine genomes of cultivars under environmental stress in connection with microRNA data. Description Here we introduce a novel knowledge base, called BIOWINE, designed for the functional analysis of Vitis vinifera genomes of cultivars present in Sicily. The system allows the analysis of RNA-seq experiments of two different cultivars, namely Nero d'Avola and Nerello Mascalese. Samples were taken under different climatic conditions of phenological phases, diseases, and geographic locations. The BIOWINE web interface is equipped with data analysis modules for grapevine genomes. In particular users may analyze the current genome assembly together with the RNA-seq data through a customized version of GBrowse. The web interface allows users to perform gene set enrichment by exploiting third-party databases. Conclusions BIOWINE is a knowledge base implementing a set of bioinformatics tools for the analysis of grapevine genomes. The system aims to increase our understanding of the grapevine varieties and species of Sicilian products focusing on adaptability to different climatic conditions, phenological phases, diseases, and geographic locations. PMID:26050794

  16. 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…

  17. Prior knowledge-based approach for associating ...

    EPA Pesticide Factsheets

    Evaluating the potential human health and/or ecological risks associated with exposures to complex chemical mixtures in the ambient environment is one of the central challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and bio-effects data to evaluate risks associated with chemicals present in the environment. We used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near two wastewater treatment plants. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data was also mapped to the assembly models to statistically evaluate the likelihood of a chemical contributing to the observed biological responses. The prior knowledge approach was able reasonably hypothesize the biological impacts at one site but not the other. Chemicals most likely contributing to the observed biological responses were identified at each location. Despite limitations to the approach, knowledge assembly models have strong potential for associating chemical occurrence with potential biological effects and providing a foundation for hypothesis generation to guide research and/or monitoring efforts relat

  18. Space shuttle main engine anomaly data and inductive knowledge based systems: Automated corporate expertise

    NASA Technical Reports Server (NTRS)

    Modesitt, Kenneth L.

    1987-01-01

    Progress is reported on the development of SCOTTY, an expert knowledge-based system to automate the analysis procedure following test firings of the Space Shuttle Main Engine (SSME). The integration of a large-scale relational data base system, a computer graphics interface for experts and end-user engineers, potential extension of the system to flight engines, application of the system for training of newly-hired engineers, technology transfer to other engines, and the essential qualities of good software engineering practices for building expert knowledge-based systems are among the topics discussed.

  19. Hospital Bioethics: A Beginning Knowledge Base for the Neonatal Social Worker.

    ERIC Educational Resources Information Center

    Silverman, Ed

    1992-01-01

    Notes that life-saving advances in medicine have created difficult ethical and legal dilemmas for health care professionals. Presents beginning knowledge base for bioethical practice, especially in hospital neonatal units. Outlines key elements of bioethical decision making and examines potential social work role from clinical and organizational…

  20. 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

  1. 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.

  2. The process for integrating the NNSA knowledge base.

    SciTech Connect

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

    2009-03-01

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

  3. XML-Based SHINE Knowledge Base Interchange Language

    NASA Technical Reports Server (NTRS)

    James, Mark; Mackey, Ryan; Tikidjian, Raffi

    2008-01-01

    The SHINE Knowledge Base Interchange Language software has been designed to more efficiently send new knowledge bases to spacecraft that have been embedded with the Spacecraft Health Inference Engine (SHINE) tool. The intention of the behavioral model is to capture most of the information generally associated with a spacecraft functional model, while specifically addressing the needs of execution within SHINE and Livingstone. As such, it has some constructs that are based on one or the other.

  4. Data/knowledge Base Processing Using Optical Associative Architectures

    NASA Astrophysics Data System (ADS)

    Akyokus, Selim

    Optical storage, communication, and processing technologies will have a great impact on the future data/knowledge base processing systems. The use of optics in data/knowledge base processing requires new design methods, architectures, and algorithms to apply the optical technology successfully. In this dissertation, three optical associative architectures are proposed. The basic data element in the proposed systems is a 2-D data page. Pages of database relations are stored in a page-oriented optical mass memory, retrieved, and processed in parallel. The first architecture uses a 1-D optical content addressable memory (OCAM) as the main functional unit. A 1-D OCAM is basically an optical vector-matrix multiplier which works as a CAM due to the spatial coding used for bit matching and masking. A 1-D OCAM can compare a search argument with a data page in parallel. The second architecture uses a 2-D OCAM as a main functional unit. A 2-D OCAM is an optical matrix-matrix multiplier which enables the comparison of a page of search arguments with a data page in parallel and in a single step. This architecture allows the execution of multiple selection and join operations very fast. The third architecture uses an optical perfect shuffle network for data routing and a processing array for performing parallel logic operations. A processing array based on symbolic substitution logic is introduced, and the use of a smart SLM as processing array is discussed. The symbolic substitution rules and algorithms for the implementation of search and bitonic sort operations are given for the proposed system. The implementation of relational database operations: selection, projection, update, deletion, sorting, duplication removal, aggregation functions, join, and set operations are described for the proposed systems, timing equations are developed for each operation, and their performances are analyzed. The proposed architectures take advantage of one-to-one mapping among the physical

  5. 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.

  6. 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.

  7. Evaluation of database technologies for the CTBT Knowledge Base prototype

    SciTech Connect

    Keyser, R.; Shepard-Dombroski, E.; Baur, D.; Hipp, J.; Moore, S.; Young, C.; Chael, E.

    1996-11-01

    This document examines a number of different software technologies in the rapidly changing field of database management systems, evaluates these systems in light of the expected needs of the Comprehensive Test Ban Treaty (CTBT) Knowledge Base, and makes some recommendations for the initial prototypes of the Knowledge Base. The Knowledge Base requirements are examined and then used as criteria for evaluation of the database management options. A mock-up of the data expected in the Knowledge Base is used as a basis for examining how four different database technologies deal with the problems of storing and retrieving the data. Based on these requirement and the results of the evaluation, the recommendation is that the Illustra database be considered for the initial prototype of the Knowledge Base. Illustra offers a unique blend of performance, flexibility, and features that will aid in the implementation of the prototype. At the same time, Illustra provides a high level of compatibility with the hardware and software environments present at the US NDC (National Data Center) and the PIDC (Prototype International Data Center).

  8. A Natural Language Interface Concordant with a Knowledge Base.

    PubMed

    Han, Yong-Jin; Park, Seong-Bae; Park, Se-Young

    2016-01-01

    The discordance between expressions interpretable by a natural language interface (NLI) system and those answerable by a knowledge base is a critical problem in the field of NLIs. In order to solve this discordance problem, this paper proposes a method to translate natural language questions into formal queries that can be generated from a graph-based knowledge base. The proposed method considers a subgraph of a knowledge base as a formal query. Thus, all formal queries corresponding to a concept or a predicate in the knowledge base can be generated prior to query time and all possible natural language expressions corresponding to each formal query can also be collected in advance. A natural language expression has a one-to-one mapping with a formal query. Hence, a natural language question is translated into a formal query by matching the question with the most appropriate natural language expression. If the confidence of this matching is not sufficiently high the proposed method rejects the question and does not answer it. Multipredicate queries are processed by regarding them as a set of collected expressions. The experimental results show that the proposed method thoroughly handles answerable questions from the knowledge base and rejects unanswerable ones effectively.

  9. Case-Based Tutoring from a Medical Knowledge Base

    PubMed Central

    Chin, Homer L.

    1988-01-01

    The past decade has seen the emergence of programs that make use of large knowledge bases to assist physicians in diagnosis within the general field of internal medicine. One such program, Internist-I, contains knowledge about over 600 diseases, covering a significant proportion of internal medicine. This paper describes the process of converting a subset of this knowledge base--in the area of cardiovascular diseases--into a probabilistic format, and the use of this resulting knowledge base to teach medical diagnostic knowledge. The system (called KBSimulator--for Knowledge-Based patient Simulator) generates simulated patient cases and uses these cases as a focal point from which to teach medical knowledge. It interacts with the student in a mixed-initiative fashion, presenting patients for the student to diagnose, and allowing the student to obtain further information on his/her own initiative in the context of that patient case. The system scores the student, and uses these scores to form a rudimentary model of the student. This resulting model of the student is then used to direct the generation of subsequent patient cases. This project demonstrates the feasibility of building an intelligent, flexible instructional system that uses a knowledge base constructed primarily for medical diagnosis.

  10. The browser prototype for the CTBT knowledge base

    SciTech Connect

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

    1997-07-02

    As part of the United States Department of Energy`s (DOE) Comprehensive Test Ban Treaty (CTBT) research and development effort, a Knowledge Base is being developed. This Knowledge Base will store the regional geophysical research results as well as geographic contexual information and make this information available to the Automated Data Processing (ADP routines) as well as human analysts involved in CTBT monitoring. This paper focuses on the initial development of a browser prototype to be used to interactively examine the contents of the CTBT Knowledge Base. The browser prototype is intended to be a research tool to experiment with different ways to display and integrate the datasets. An initial prototype version has been developed using Environmental Systems Research Incorporated`s (ESRI) ARC/INFO Geographic Information System (GIS) product. The conceptual requirements, design, initial implementation, current status, and future work plans are discussed. 4 refs., 2 figs.

  11. 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.

  12. 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.

  13. Creating a knowledge base of biological research papers

    SciTech Connect

    Hafner, C.D.; Baclawski, K.; Futrelle, R.P.; Fridman, N.

    1994-12-31

    Intelligent text-oriented tools for representing and searching the biological research literature are being developed, which combine object-oriented databases with artificial intelligence techniques to create a richly structured knowledge base of Materials and Methods sections of biological research papers. A knowledge model of experimental processes, biological and chemical substances, and analytical techniques is described, based on the representation techniques of taxonomic semantic nets and knowledge frames. Two approaches to populating the knowledge base with the contents of biological research papers are described: natural language processing and an interactive knowledge definition tool.

  14. 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

  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. Arranging ISO 13606 archetypes into a knowledge base.

    PubMed

    Kopanitsa, Georgy

    2014-01-01

    To enable the efficient reuse of standard based medical data we propose to develop a higher level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analyzed for their ability to be applied in the implementation of a higher level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

  17. Knowledge based systems: From process control to policy analysis

    SciTech Connect

    Marinuzzi, J.G.

    1993-06-01

    Los Alamos has been pursuing the use of Knowledge Based Systems for many years. These systems are currently being used to support projects that range across many production and operations areas. By investing time and money in people and equipment, Los Alamos has developed one of the strongest knowledge based systems capabilities within the DOE. Staff of Los Alamos` Mechanical & Electronic Engineering Division are using these knowledge systems to increase capability, productivity and competitiveness in areas of manufacturing quality control, robotics, process control, plant design and management decision support. This paper describes some of these projects and associated technical program approaches, accomplishments, benefits and future goals.

  18. Knowledge based systems: From process control to policy analysis

    SciTech Connect

    Marinuzzi, J.G.

    1993-01-01

    Los Alamos has been pursuing the use of Knowledge Based Systems for many years. These systems are currently being used to support projects that range across many production and operations areas. By investing time and money in people and equipment, Los Alamos has developed one of the strongest knowledge based systems capabilities within the DOE. Staff of Los Alamos' Mechanical Electronic Engineering Division are using these knowledge systems to increase capability, productivity and competitiveness in areas of manufacturing quality control, robotics, process control, plant design and management decision support. This paper describes some of these projects and associated technical program approaches, accomplishments, benefits and future goals.

  19. Ada as an implementation language for knowledge based systems

    NASA Technical Reports Server (NTRS)

    Rochowiak, Daniel

    1990-01-01

    Debates about the selection of programming languages often produce cultural collisions that are not easily resolved. This is especially true in the case of Ada and knowledge based programming. The construction of programming tools provides a desirable alternative for resolving the conflict.

  20. Planning and Implementing a High Performance Knowledge Base.

    ERIC Educational Resources Information Center

    Cortez, Edwin M.

    1999-01-01

    Discusses the conceptual framework for developing a rapid-prototype high-performance knowledge base for the four mission agencies of the United States Department of Agriculture and their university partners. Describes the background of the project and methods used for establishing the requirements; examines issues and problems surrounding semantic…

  1. 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.

  2. 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.

  3. 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.

  4. Toffler's Powershift: Creating New Knowledge Bases in Higher Education.

    ERIC Educational Resources Information Center

    Powers, Patrick James

    This paper examines the creation of new knowledge bases in higher education in light of the ideas of Alvin Toffler, whose trilogy "Future Shock" (1970), "The Third Wave" (1980), and "Powershift" (1990) focus on the processes, directions, and control of change, respectively. It discusses the increasingly important role…

  5. 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…

  6. 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…

  7. SCU at TREC 2014 Knowledge Base Acceleration Track

    DTIC Science & Technology

    2014-11-01

    SCU at TREC 2014 Knowledge Base Acceleration Track Hung Nguyen, Yi Fang Department of Computer Engineering Santa Clara University 500 El Camino ...University,Department of Computer Engineering,500 El Camino Real,Santa Clara,CA,95053 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING

  8. Desperately seeking data: knowledge base-database links.

    PubMed Central

    Hripcsak, G.; Johnson, S. B.; Clayton, P. D.

    1993-01-01

    Linking a knowledge-based system (KBS) to a clinical database is a difficult task, but critical if such systems are to achieve widespread use. The Columbia-Presbyterian Medical Center's clinical event monitor provides alerts, interpretations, research screening, and quality assurance functions for the center. Its knowledge base consists of Arden Syntax Medical Logic Modules (MLMs). The knowledge base was analyzed in order to quantify the use and impact of KBS-database links. The MLM data slot, which contains the definition of these links, had almost as many statements (5.8 vs. 8.8, ns with p = 0.15) and more tokens (122 vs. 76, p = 0.037) than the logic slot, which contains the actual medical knowledge. The data slot underwent about twice as many modifications over time as the logic slot (3.0 vs. 1.6 modifications/version, p = 0.010). Database queries and updates accounted for 97.2% of the MLM's total elapsed execution time. Thus, KBS-database links consume substantial resources in an MLM knowledge base, in terms of coding, maintenance, and performance. PMID:8130552

  9. 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…

  10. Development of a Knowledge Base for Incorporating Technology into Courses

    ERIC Educational Resources Information Center

    Rath, Logan

    2013-01-01

    This article discusses a project resulting from the request of a group of faculty at The College at Brockport to create a website for best practices in teaching and technology. The project evolved into a knowledge base powered by WordPress. Installation and configuration of WordPress resulted in the creation of custom taxonomies and post types,…

  11. 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.

  12. 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,…

  13. Common Sense about Uncommon Knowledge: The Knowledge Bases for Diversity.

    ERIC Educational Resources Information Center

    Smith, G. Pritchy

    This book explains knowledge bases for teaching diverse student populations. An introduction displays one first-year teacher's experiences with diverse students in a high school classroom in San Angelo, Texas in 1961. The 15 chapters are: (1) "Toward Defining Culturally Responsible and Responsive Teacher Education"; (2) "Knowledge…

  14. 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…

  15. Designing a Knowledge Base for Automatic Book Classification.

    ERIC Educational Resources Information Center

    Kim, Jeong-Hyen; Lee, Kyung-Ho

    2002-01-01

    Reports on the design of a knowledge base for an automatic classification in the library science field by using the facet classification principles of colon classification. Discusses inputting titles or key words into the computer to create class numbers through automatic subject recognition and processing title key words. (Author/LRW)

  16. Tools for Assembling and Managing Scalable Knowledge Bases

    DTIC Science & Technology

    2003-02-01

    1 1.1 Knowledge Translation .......................................................................................................................... 1...areas of the knowledge base and ontology construction process and are outlined in more detail below. 1.1 Knowledge Translation As mentioned above...during KB merging operations. 2.2 The Translation Problem Figure 2: The knowledge translation problem. The general problem we set out to solve is

  17. Grey Documentation as a Knowledge Base in Social Work.

    ERIC Educational Resources Information Center

    Berman, Yitzhak

    1994-01-01

    Defines grey documentation as documents issued informally and not available through normal channels and discusses the role that grey documentation can play in the social work knowledge base. Topics addressed include grey documentation and science; social work and the empirical approach in knowledge development; and dissemination of grey…

  18. 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.

  19. Intelligent Tools for Planning Knowledge base Development and Verification

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

  20. Towards an Intelligent Planning Knowledge Base Development Environment

    NASA Technical Reports Server (NTRS)

    Chien, S.

    1994-01-01

    ract describes work in developing knowledge base editing and debugging tools for the Multimission VICAR Planner (MVP) system. MVP uses artificial intelligence planning techniques to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing requests made to the JPL Multimission Image Processing Laboratory.

  1. Knowledge Based Engineering for Spatial Database Management and Use

    NASA Technical Reports Server (NTRS)

    Peuquet, D. (Principal Investigator)

    1984-01-01

    The use of artificial intelligence techniques that are applicable to Geographic Information Systems (GIS) are examined. Questions involving the performance and modification to the database structure, the definition of spectra in quadtree structures and their use in search heuristics, extension of the knowledge base, and learning algorithm concepts are investigated.

  2. 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)

  3. 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…

  4. 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.

  5. 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.

  6. Reducing a Knowledge-Base Search Space When Data Are Missing

    NASA Technical Reports Server (NTRS)

    James, Mark

    2007-01-01

    This software addresses the problem of how to efficiently execute a knowledge base in the presence of missing data. Computationally, this is an exponentially expensive operation that without heuristics generates a search space of 1 + 2n possible scenarios, where n is the number of rules in the knowledge base. Even for a knowledge base of the most modest size, say 16 rules, it would produce 65,537 possible scenarios. The purpose of this software is to reduce the complexity of this operation to a more manageable size. The problem that this system solves is to develop an automated approach that can reason in the presence of missing data. This is a meta-reasoning capability that repeatedly calls a diagnostic engine/model to provide prognoses and prognosis tracking. In the big picture, the scenario generator takes as its input the current state of a system, including probabilistic information from Data Forecasting. Using model-based reasoning techniques, it returns an ordered list of fault scenarios that could be generated from the current state, i.e., the plausible future failure modes of the system as it presently stands. The scenario generator models a Potential Fault Scenario (PFS) as a black box, the input of which is a set of states tagged with priorities and the output of which is one or more potential fault scenarios tagged by a confidence factor. The results from the system are used by a model-based diagnostician to predict the future health of the monitored system.

  7. 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.

  8. An Empirical Analysis of Knowledge Based Hypertext Navigation

    PubMed Central

    Snell, J.R.; Boyle, C.

    1990-01-01

    Our purpose is to investigate the effectiveness of knowledge-based navigation in a dermatology hypertext network. The chosen domain is a set of dermatology class notes implemented in Hypercard and SINS. The study measured time, number of moves, and success rates for subjects to find solutions to ten questions. The subjects were required to navigate within a dermatology hypertext network in order to find the solutions to a question. Our results indicate that knowledge-based navigation can assist the user in finding information of interest in a fewer number of node visits (moves) than with traditional button-based browsing or keyword searching. The time necessary to find an item of interest was lower for traditional-based methods. There was no difference in success rates for the two test groups.

  9. 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.

  10. 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.

  11. 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.

  12. A Study of Knowledge-Based Systems for Photo Interpretation.

    DTIC Science & Technology

    1980-06-01

    OIL (15] CAI Electronics SOPHIE (10] Medicine GUIDON [14] Learning Chemistry Meta-DENDRAL (i] Agriculture INDUCE [19] Mathematics AM [40] Intelligent...16 6. Computer-Aided Instruction: GUIDON Three types of traditional computer-aided instruction (CAI) are often distinguished: frame-oriented drill-and...systems have an obvious contribution to make to CAI. The GUIDON system developed by Clancey at Stanford exploits the MYCIN knowledge base about

  13. A knowledge based model of electric utility operations. Final report

    SciTech Connect

    1993-08-11

    This report consists of an appendix to provide a documentation and help capability for an analyst using the developed expert system of electric utility operations running in CLIPS. This capability is provided through a separate package running under the WINDOWS Operating System and keyed to provide displays of text, graphics and mixed text and graphics that explain and elaborate on the specific decisions being made within the knowledge based expert system.

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. Using the DOE Knowledge Base for Special Event Analysis

    SciTech Connect

    Armstrong, H.M.; Harris, J.M.; Young, C.J.

    1998-10-20

    The DOE Knowledge Base is a library of detailed information whose purpose is to support the United States National Data Center (USNDC) in its mission to monitor compliance with the Comprehensive Test Ban Treaty (CTBT). One of the important tasks which the USNDC must accomplish is to periodically perform detailed analysis of events of high interest, so-called "Special Events", to provide the national authority with information needed to make policy decisions. In this paper we investigate some possible uses of the Knowledge Base for Special Event Analysis (SEA), and make recommendations for improving Knowledge Base support for SEA. To analyze an event in detail, there are two basic types of data which must be used sensor-derived data (wave- forms, arrivals, events, etc.) and regiohalized contextual data (known sources, geological characteristics, etc.). Cur- rently there is no single package which can provide full access to both types of data, so for our study we use a separate package for each MatSeis, the Sandia Labs-developed MATLAB-based seismic analysis package, for wave- form data analysis, and ArcView, an ESRI product, for contextual data analysis. Both packages are well-suited to pro- totyping because they provide a rich set of currently available functionality and yet are also flexible and easily extensible, . Using these tools and Phase I Knowledge Base data sets, we show how the Knowledge Base can improve both the speed and the quality of SEA. Empirically-derived interpolated correction information can be accessed to improve both location estimates and associated error estimates. This information can in turn be used to identi~ any known nearby sources (e.g. mines, volcanos), which may then trigger specialized processing of the sensor data. Based on the location estimate, preferred magnitude formulas and discriminants can be retrieved, and any known blockages can be identified to prevent miscalculations. Relevant historic events can be identilled either by

  19. Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature

    PubMed Central

    Xu, Rong; Li, Li; Wang, QuanQiu

    2013-01-01

    Motivation: Systems approaches to studying phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repurposing. Currently, systematic study of disease phenotypic relationships on a phenome-wide scale is limited because large-scale machine-understandable disease–phenotype relationship knowledge bases are often unavailable. Here, we present an automatic approach to extract disease–manifestation (D-M) pairs (one specific type of disease–phenotype relationship) from the wide body of published biomedical literature. Data and Methods: Our method leverages external knowledge and limits the amount of human effort required. For the text corpus, we used 119 085 682 MEDLINE sentences (21 354 075 citations). First, we used D-M pairs from existing biomedical ontologies as prior knowledge to automatically discover D-M–specific syntactic patterns. We then extracted additional pairs from MEDLINE using the learned patterns. Finally, we analysed correlations between disease manifestations and disease-associated genes and drugs to demonstrate the potential of this newly created knowledge base in disease gene discovery and drug repurposing. Results: In total, we extracted 121 359 unique D-M pairs with a high precision of 0.924. Among the extracted pairs, 120 419 (99.2%) have not been captured in existing structured knowledge sources. We have shown that disease manifestations correlate positively with both disease-associated genes and drug treatments. Conclusions: The main contribution of our study is the creation of a large-scale and accurate D-M phenotype relationship knowledge base. This unique knowledge base, when combined with existing phenotypic, genetic and proteomic datasets, can have profound implications in our deeper understanding of disease etiology and in rapid drug repurposing. Availability: http://nlp.case.edu/public/data/DMPatternUMLS/ Contact: rxx@case.edu PMID:23828786

  20. 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.

  1. 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.

  2. SAFOD Brittle Microstructure and Mechanics Knowledge Base (BM2KB)

    NASA Astrophysics Data System (ADS)

    Babaie, Hassan A.; Broda Cindi, M.; Hadizadeh, Jafar; Kumar, Anuj

    2013-07-01

    Scientific drilling near Parkfield, California has established the San Andreas Fault Observatory at Depth (SAFOD), which provides the solid earth community with short range geophysical and fault zone material data. The BM2KB ontology was developed in order to formalize the knowledge about brittle microstructures in the fault rocks sampled from the SAFOD cores. A knowledge base, instantiated from this domain ontology, stores and presents the observed microstructural and analytical data with respect to implications for brittle deformation and mechanics of faulting. These data can be searched on the knowledge base‧s Web interface by selecting a set of terms (classes, properties) from different drop-down lists that are dynamically populated from the ontology. In addition to this general search, a query can also be conducted to view data contributed by a specific investigator. A search by sample is done using the EarthScope SAFOD Core Viewer that allows a user to locate samples on high resolution images of core sections belonging to different runs and holes. The class hierarchy of the BM2KB ontology was initially designed using the Unified Modeling Language (UML), which was used as a visual guide to develop the ontology in OWL applying the Protégé ontology editor. Various Semantic Web technologies such as the RDF, RDFS, and OWL ontology languages, SPARQL query language, and Pellet reasoning engine, were used to develop the ontology. An interactive Web application interface was developed through Jena, a java based framework, with AJAX technology, jsp pages, and java servlets, and deployed via an Apache tomcat server. The interface allows the registered user to submit data related to their research on a sample of the SAFOD core. The submitted data, after initial review by the knowledge base administrator, are added to the extensible knowledge base and become available in subsequent queries to all types of users. The interface facilitates inference capabilities in the

  3. Building a knowledge based economy in Russia using guided entrepreneurship

    NASA Astrophysics Data System (ADS)

    Reznik, Boris N.; Daniels, Marc; Ichim, Thomas E.; Reznik, David L.

    2005-06-01

    Despite advanced scientific and technological (S&T) expertise, the Russian economy is presently based upon manufacturing and raw material exports. Currently, governmental incentives are attempting to leverage the existing scientific infrastructure through the concept of building a Knowledge Based Economy. However, socio-economic changes do not occur solely by decree, but by alteration of approach to the market. Here we describe the "Guided Entrepreneurship" plan, a series of steps needed for generation of an army of entrepreneurs, which initiate a chain reaction of S&T-driven growth. The situation in Russia is placed in the framework of other areas where Guided Entrepreneurship has been successful.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Utilizing knowledge-base semantics in graph-based algorithms

    SciTech Connect

    Darwiche, A.

    1996-12-31

    Graph-based algorithms convert a knowledge base with a graph structure into one with a tree structure (a join-tree) and then apply tree-inference on the result. Nodes in the join-tree are cliques of variables and tree-inference is exponential in w*, the size of the maximal clique in the join-tree. A central property of join-trees that validates tree-inference is the running-intersection property: the intersection of any two cliques must belong to every clique on the path between them. We present two key results in connection to graph-based algorithms. First, we show that the running-intersection property, although sufficient, is not necessary for validating tree-inference. We present a weaker property for this purpose, called running-interaction, that depends on non-structural (semantical) properties of a knowledge base. We also present a linear algorithm that may reduce w* of a join-tree, possibly destroying its running-intersection property, while maintaining its running-interaction property and, hence, its validity for tree-inference. Second, we develop a simple algorithm for generating trees satisfying the running-interaction property. The algorithm bypasses triangulation (the standard technique for constructing join-trees) and does not construct a join-tree first. We show that the proposed algorithm may in some cases generate trees that are more efficient than those generated by modifying a join-tree.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Apprenticeship learning techniques for knowledge-based systems

    SciTech Connect

    Wilkins, D.C.

    1987-01-01

    This thesis describes apprenticeship learning techniques for automation of the transfer of expertise. Apprenticeship learning is a form of learning by watching, in which learning occurs as a byproduct of building explanations of human problem-solving actions. As apprenticeship is the most-powerful method that human experts use to refine and debug their expertise in knowledge-intensive domains such as medicine; this motivates giving such capabilities to an expert system. The major accomplishment in this thesis is showing how an explicit representation of the strategy knowledge to solve a general problem class, such as diagnosis, can provide a basis for learning the knowledge that is specific to a particular domain, such as medicine. The Odysseus learning program provides the first demonstration of using the same technique to transfer of expertise to and from an expert system knowledge base. Another major focus of this thesis is limitations of apprenticeship learning. It is shown that extant techniques for reasoning under uncertainty for expert systems lead to a sociopathic knowledge base.

  15. 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.

  16. Intelligent Physiologic Modeling: An Application of Knowledge Based Systems Technology to Medical Education

    PubMed Central

    Kunstaetter, Robert

    1986-01-01

    This presentation describes the design and implementation of a knowledge based physiologic modeling system (KBPMS) and a preliminary evaluation of its use as a learning resource within the context of an experimental medical curriculum -- the Harvard New Pathway. KBPMS possesses combined numeric and qualitative simulation capabilities and can provide explanations of its knowledge and behaviour. It has been implemented on a microcomputer with a user interface incorporating interactive graphics. The preliminary evaluation of KBPMS is based on anecdotal data which suggests that the system might have pedagogic potential. Much work remains to be done in enhancing and further evaluating KBPMS.

  17. A prototype natural language interface to a large complex knowledge base, the Foundational Model of Anatomy.

    PubMed

    Distelhorst, Gregory; Srivastava, Vishrut; Rosse, Cornelius; Brinkley, James F

    2003-01-01

    We describe a constrained natural language interface to a large knowledge base, the Foundational Model of Anatomy (FMA). The interface, called GAPP, handles simple or nested questions that can be parsed to the form, subject-relation-object, where subject or object is unknown. With the aid of domain-specific dictionaries the parsed sentence is converted to queries in the StruQL graph-searching query language, then sent to a server we developed, called OQAFMA, that queries the FMA and returns output as XML. Preliminary evaluation shows that GAPP has the potential to be used in the evaluation of the FMA by domain experts in anatomy.

  18. VIALACTEA knowledge base homogenizing access to Milky Way data

    NASA Astrophysics Data System (ADS)

    Molinaro, Marco; Butora, Robert; Bandieramonte, Marilena; Becciani, Ugo; Brescia, Massimo; Cavuoti, Stefano; Costa, Alessandro; Di Giorgio, Anna M.; Elia, Davide; Hajnal, Akos; Gabor, Hermann; Kacsuk, Peter; Liu, Scige J.; Molinari, Sergio; Riccio, Giuseppe; Schisano, Eugenio; Sciacca, Eva; Smareglia, Riccardo; Vitello, Fabio

    2016-08-01

    The VIALACTEA project has a work package dedicated to "Tools and Infrastructure" and, inside it, a task for the "Database and Virtual Observatory Infrastructure". This task aims at providing an infrastructure to store all the resources needed by the, more purposely, scientific work packages of the project itself. This infrastructure includes a combination of: storage facilities, relational databases and web services on top of them, and has taken, as a whole, the name of VIALACTEA Knowledge Base (VLKB). This contribution illustrates the current status of this VLKB. It details the set of data resources put together; describes the database that allows data discovery through VO inspired metadata maintenance; illustrates the discovery, cutout and access services built on top of the former two for the users to exploit the data content.

  19. A model for a knowledge-based system's life cycle

    NASA Technical Reports Server (NTRS)

    Kiss, Peter A.

    1990-01-01

    The American Institute of Aeronautics and Astronautics has initiated a Committee on Standards for Artificial Intelligence. Presented here are the initial efforts of one of the working groups of that committee. The purpose here is to present a candidate model for the development life cycle of Knowledge Based Systems (KBS). The intent is for the model to be used by the Aerospace Community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are detailed as are and the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

  20. 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.

  1. 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.

  2. The 2004 knowledge base parametric grid data software suite.

    SciTech Connect

    Wilkening, Lisa K.; Simons, Randall W.; Ballard, Sandy; Jensen, Lee A.; Chang, Marcus C.; Hipp, James Richard

    2004-08-01

    One of the most important types of data in the National Nuclear Security Administration (NNSA) Ground-Based Nuclear Explosion Monitoring Research and Engineering (GNEM R&E) Knowledge Base (KB) is parametric grid (PG) data. PG data can be used to improve signal detection, signal association, and event discrimination, but so far their greatest use has been for improving event location by providing ground-truth-based corrections to travel-time base models. In this presentation we discuss the latest versions of the complete suite of Knowledge Base PG tools developed by NNSA to create, access, manage, and view PG data. The primary PG population tool is the Knowledge Base calibration integration tool (KBCIT). KBCIT is an interactive computer application to produce interpolated calibration-based information that can be used to improve monitoring performance by improving precision of model predictions and by providing proper characterizations of uncertainty. It is used to analyze raw data and produce kriged correction surfaces that can be included in the Knowledge Base. KBCIT not only produces the surfaces but also records all steps in the analysis for later review and possible revision. New features in KBCIT include a new variogram autofit algorithm; the storage of database identifiers with a surface; the ability to merge surfaces; and improved surface-smoothing algorithms. The Parametric Grid Library (PGL) provides the interface to access the data and models stored in a PGL file database. The PGL represents the core software library used by all the GNEM R&E tools that read or write PGL data (e.g., KBCIT and LocOO). The library provides data representations and software models to support accurate and efficient seismic phase association and event location. Recent improvements include conversion of the flat-file database (FDB) to an Oracle database representation; automatic access of station/phase tagged models from the FDB during location; modification of the core

  3. 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.

  4. 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.

  5. 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.

  6. TMS for Instantiating a Knowledge Base With Incomplete Data

    NASA Technical Reports Server (NTRS)

    James, Mark

    2007-01-01

    A computer program that belongs to the class known among software experts as output truth-maintenance-systems (output TMSs) has been devised as one of a number of software tools for reducing the size of the knowledge base that must be searched during execution of artificial- intelligence software of the rule-based inference-engine type in a case in which data are missing. This program determines whether the consequences of activation of two or more rules can be combined without causing a logical inconsistency. For example, in a case involving hypothetical scenarios that could lead to turning a given device on or off, the program determines whether a scenario involving a given combination of rules could lead to turning the device both on and off at the same time, in which case that combination of rules would not be included in the scenario.

  7. 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.

  8. 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.

  9. 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.

  10. A knowledge base architecture for distributed knowledge agents

    NASA Technical Reports Server (NTRS)

    Riedesel, Joel; Walls, Bryan

    1990-01-01

    A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

  11. 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.

  12. 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

  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. Strategy Regulation: The Role of Intelligence, Metacognitive Attributions, and Knowledge Base.

    ERIC Educational Resources Information Center

    Alexander, Joyce M.; Schwanenflugel, Paula J.

    1994-01-01

    Studied influence of intelligence, metacognitive attributions, and knowledge base coherence in the regulation of the category-sorting strategy in first and second graders. Knowledge base was a powerful predictor of strategic-looking behavior; metacognitive attribution was most influential in low knowledge base conditions; and intelligence had…

  15. 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.

  16. 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

    As the new control system of the Mercator Telescope is being finalized, we can review some technologies and design methodologies that are advantageous, despite their relative uncommonness in astronomical instrumentation. Particular for the Mercator Telescope is that it is controlled by a single high-end soft-PLC (Programmable Logic Controller). Using off-the-shelf components only, our distributed embedded system controls all subsystems of the telescope such as the pneumatic primary mirror support, the hydrostatic bearing, the telescope axes, the dome, the safety system, and so on. We show how real-time application logic can be written conveniently in typical PLC languages (IEC 61131-3) and in C++ (to implement the pointing kernel) using the commercial TwinCAT 3 programming environment. This software processes the inputs and outputs of the distributed system in real-time via an observatory-wide EtherCAT network, which is synchronized with high precision to an IEEE 1588 (PTP, Precision Time Protocol) time reference clock. Taking full advantage of the ability of soft-PLCs to run both real-time and non real-time software, the same device also hosts the most important user interfaces (HMIs or Human Machine Interfaces) and communication servers (OPC UA for process data, FTP for XML configuration data, and VNC for remote control). To manage the complexity of the system and to streamline the development process, we show how most of the software, electronics and systems engineering aspects of the control system have been modeled as a set of scripts written in a Domain Specific Language (DSL). When executed, these scripts populate a Knowledge Base (KB) which can be queried to retrieve specific information. By feeding the results of those queries to a template system, we were able to generate very detailed "browsable" web-based documentation about the system, but also PLC software code, Python client code, model verification reports, etc. The aim of this paper is to

  17. EHR based Genetic Testing Knowledge Base (iGTKB) Development

    PubMed Central

    2015-01-01

    Background The gap between a large growing number of genetic tests and a suboptimal clinical workflow of incorporating these tests into regular clinical practice poses barriers to effective reliance on advanced genetic technologies to improve quality of healthcare. A promising solution to fill this gap is to develop an intelligent genetic test recommendation system that not only can provide a comprehensive view of genetic tests as education resources, but also can recommend the most appropriate genetic tests to patients based on clinical evidence. In this study, we developed an EHR based Genetic Testing Knowledge Base for Individualized Medicine (iGTKB). Methods We extracted genetic testing information and patient medical records from EHR systems at Mayo Clinic. Clinical features have been semi-automatically annotated from the clinical notes by applying a Natural Language Processing (NLP) tool, MedTagger suite. To prioritize clinical features for each genetic test, we compared odds ratio across four population groups. Genetic tests, genetic disorders and clinical features with their odds ratios have been applied to establish iGTKB, which is to be integrated into the Genetic Testing Ontology (GTO). Results Overall, there are five genetic tests operated with sample size greater than 100 in 2013 at Mayo Clinic. A total of 1,450 patients who was tested by one of the five genetic tests have been selected. We assembled 243 clinical features from the Human Phenotype Ontology (HPO) for these five genetic tests. There are 60 clinical features with at least one mention in clinical notes of patients taking the test. Twenty-eight clinical features with high odds ratio (greater than 1) have been selected as dominant features and deposited into iGTKB with their associated information about genetic tests and genetic disorders. Conclusions In this study, we developed an EHR based genetic testing knowledge base, iGTKB. iGTKB will be integrated into the GTO by providing relevant

  18. Dynamic reasoning in a knowledge-based system

    NASA Technical Reports Server (NTRS)

    Rao, Anand S.; Foo, Norman Y.

    1988-01-01

    Any space based system, whether it is a robot arm assembling parts in space or an onboard system monitoring the space station, has to react to changes which cannot be foreseen. As a result, apart from having domain-specific knowledge as in current expert systems, a space based AI system should also have general principles of change. This paper presents a modal logic which can not only represent change but also reason with it. Three primitive operations, expansion, contraction and revision are introduced and axioms which specify how the knowledge base should change when the external world changes are also specified. Accordingly the notion of dynamic reasoning is introduced, which unlike the existing forms of reasoning, provide general principles of change. Dynamic reasoning is based on two main principles, namely minimize change and maximize coherence. A possible-world semantics which incorporates the above two principles is also discussed. The paper concludes by discussing how the dynamic reasoning system can be used to specify actions and hence form an integral part of an autonomous reasoning and planning system.

  19. Prospector II: Towards a knowledge base for mineral deposits

    USGS Publications Warehouse

    McCammon, R.B.

    1994-01-01

    What began in the mid-seventies as a research effort in designing an expert system to aid geologists in exploring for hidden mineral deposits has in the late eighties become a full-sized knowledge-based system to aid geologists in conducting regional mineral resource assessments. Prospector II, the successor to Prospector, is interactive-graphics oriented, flexible in its representation of mineral deposit models, and suited to regional mineral resource assessment. In Prospector II, the geologist enters the findings for an area, selects the deposit models or examples of mineral deposits for consideration, and the program compares the findings with the models or the examples selected, noting the similarities, differences, and missing information. The models or the examples selected are ranked according to scores that are based on the comparisons with the findings. Findings can be reassessed and the process repeated if necessary. The results provide the geologist with a rationale for identifying those mineral deposit types that the geology of an area permits. In future, Prospector II can assist in the creation of new models used in regional mineral resource assessment and in striving toward an ultimate classification of mineral deposits. ?? 1994 International Association for Mathematical Geology.

  20. 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

  1. Incremental Knowledge Base Construction Using DeepDive

    PubMed Central

    Shin, Jaeho; Wu, Sen; Wang, Feiran; De Sa, Christopher; Zhang, Ce; Ré, Christopher

    2016-01-01

    Populating a database with unstructured information is a long-standing problem in industry and research that encompasses problems of extraction, cleaning, and integration. Recent names used for this problem include dealing with dark data and knowledge base construction (KBC). In this work, we describe DeepDive, a system that combines database and machine learning ideas to help develop KBC systems, and we present techniques to make the KBC process more efficient. We observe that the KBC process is iterative, and we develop techniques to incrementally produce inference results for KBC systems. We propose two methods for incremental inference, based respectively on sampling and variational techniques. We also study the tradeoff space of these methods and develop a simple rule-based optimizer. DeepDive includes all of these contributions, and we evaluate Deep-Dive on five KBC systems, showing that it can speed up KBC inference tasks by up to two orders of magnitude with negligible impact on quality. PMID:27144081

  2. Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes.

    PubMed

    Zhou, Du; Yuan, Xi; Gao, Haoxiang; Wang, Ailing; Liu, Jun; El Fakir, Omer; Politis, Denis J; Wang, Liliang; Lin, Jianguo

    2016-12-13

    The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions.

  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. Knowledge-based topographic feature extraction in medical images

    NASA Astrophysics Data System (ADS)

    Qian, JianZhong; Khair, Mohammad M.

    1995-08-01

    Diagnostic medical imaging often contains variations of patient anatomies, camera mispositioning, or other imperfect imaging condiitons. These variations contribute to uncertainty about shapes and boundaries of objects in images. As the results sometimes image features, such as traditional edges, may not be identified reliably and completely. We describe a knowledge based system that is able to reason about such uncertainties and use partial and locally ambiguous information to infer about shapes and lcoation of objects in an image. The system uses directional topographic features (DTFS), such as ridges and valleys, labeled from the underlying intensity surface to correlate to the intrinsic anatomical information. By using domain specific knowledge, the reasoning system can deduce significant anatomical landmarks based upon these DTFS, and can cope with uncertainties and fill in missing information. A succession of levels of representation for visual information and an active process of uncertain reasoning about this visual information are employed to realiably achieve the goal of image analysis. These landmarks can then be used in localization of anatomy of interest, image registration, or other clinical processing. The successful application of this system to a large set of planar cardiac images of nuclear medicine studies has demonstrated its efficiency and accuracy.

  5. The AI Bus architecture for distributed knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Schultz, Roger D.; Stobie, Iain

    1991-01-01

    The AI Bus architecture is layered, distributed object oriented framework developed to support the requirements of advanced technology programs for an order of magnitude improvement in software costs. The consequent need for highly autonomous computer systems, adaptable to new technology advances over a long lifespan, led to the design of an open architecture and toolbox for building large scale, robust, production quality systems. The AI Bus accommodates a mix of knowledge based and conventional components, running on heterogeneous, distributed real world and testbed environment. The concepts and design is described of the AI Bus architecture and its current implementation status as a Unix C++ library or reusable objects. Each high level semiautonomous agent process consists of a number of knowledge sources together with interagent communication mechanisms based on shared blackboards and message passing acquaintances. Standard interfaces and protocols are followed for combining and validating subsystems. Dynamic probes or demons provide an event driven means for providing active objects with shared access to resources, and each other, while not violating their security.

  6. 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.

  7. A knowledge based system for scientific data visualization

    NASA Technical Reports Server (NTRS)

    Senay, Hikmet; Ignatius, Eve

    1992-01-01

    A knowledge-based system, called visualization tool assistant (VISTA), which was developed to assist scientists in the design of scientific data visualization techniques, is described. The system derives its knowledge from several sources which provide information about data characteristics, visualization primitives, and effective visual perception. The design methodology employed by the system is based on a sequence of transformations which decomposes a data set into a set of data partitions, maps this set of partitions to visualization primitives, and combines these primitives into a composite visualization technique design. Although the primary function of the system is to generate an effective visualization technique design for a given data set by using principles of visual perception the system also allows users to interactively modify the design, and renders the resulting image using a variety of rendering algorithms. The current version of the system primarily supports visualization techniques having applicability in earth and space sciences, although it may easily be extended to include other techniques useful in other disciplines such as computational fluid dynamics, finite-element analysis and medical imaging.

  8. 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.

  9. 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.

  10. Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

    PubMed Central

    Zhou, Du; Yuan, Xi; Gao, Haoxiang; Wang, Ailing; Liu, Jun; El Fakir, Omer; Politis, Denis J.; Wang, Liliang; Lin, Jianguo

    2016-01-01

    The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions. PMID:28060298

  11. 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.

  12. 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.

  13. 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.

  14. Towards a Food Safety Knowledge Base Applicable in Crisis Situations and Beyond

    PubMed Central

    Falenski, Alexander; Weiser, Armin A.; Thöns, Christian; Appel, Bernd; Käsbohrer, Annemarie; Filter, Matthias

    2015-01-01

    In case of contamination in the food chain, fast action is required in order to reduce the numbers of affected people. In such situations, being able to predict the fate of agents in foods would help risk assessors and decision makers in assessing the potential effects of a specific contamination event and thus enable them to deduce the appropriate mitigation measures. One efficient strategy supporting this is using model based simulations. However, application in crisis situations requires ready-to-use and easy-to-adapt models to be available from the so-called food safety knowledge bases. Here, we illustrate this concept and its benefits by applying the modular open source software tools PMM-Lab and FoodProcess-Lab. As a fictitious sample scenario, an intentional ricin contamination at a beef salami production facility was modelled. Predictive models describing the inactivation of ricin were reviewed, relevant models were implemented with PMM-Lab, and simulations on residual toxin amounts in the final product were performed with FoodProcess-Lab. Due to the generic and modular modelling concept implemented in these tools, they can be applied to simulate virtually any food safety contamination scenario. Apart from the application in crisis situations, the food safety knowledge base concept will also be useful in food quality and safety investigations. PMID:26247028

  15. Towards a Food Safety Knowledge Base Applicable in Crisis Situations and Beyond.

    PubMed

    Falenski, Alexander; Weiser, Armin A; Thöns, Christian; Appel, Bernd; Käsbohrer, Annemarie; Filter, Matthias

    2015-01-01

    In case of contamination in the food chain, fast action is required in order to reduce the numbers of affected people. In such situations, being able to predict the fate of agents in foods would help risk assessors and decision makers in assessing the potential effects of a specific contamination event and thus enable them to deduce the appropriate mitigation measures. One efficient strategy supporting this is using model based simulations. However, application in crisis situations requires ready-to-use and easy-to-adapt models to be available from the so-called food safety knowledge bases. Here, we illustrate this concept and its benefits by applying the modular open source software tools PMM-Lab and FoodProcess-Lab. As a fictitious sample scenario, an intentional ricin contamination at a beef salami production facility was modelled. Predictive models describing the inactivation of ricin were reviewed, relevant models were implemented with PMM-Lab, and simulations on residual toxin amounts in the final product were performed with FoodProcess-Lab. Due to the generic and modular modelling concept implemented in these tools, they can be applied to simulate virtually any food safety contamination scenario. Apart from the application in crisis situations, the food safety knowledge base concept will also be useful in food quality and safety investigations.

  16. Development of a Prototype Model-Form Uncertainty Knowledge Base

    NASA Technical Reports Server (NTRS)

    Green, Lawrence L.

    2016-01-01

    Uncertainties are generally classified as either aleatory or epistemic. Aleatory uncertainties are those attributed to random variation, either naturally or through manufacturing processes. Epistemic uncertainties are generally attributed to a lack of knowledge. One type of epistemic uncertainty is called model-form uncertainty. The term model-form means that among the choices to be made during a design process within an analysis, there are different forms of the analysis process, which each give different results for the same configuration at the same flight conditions. Examples of model-form uncertainties include the grid density, grid type, and solver type used within a computational fluid dynamics code, or the choice of the number and type of model elements within a structures analysis. The objectives of this work are to identify and quantify a representative set of model-form uncertainties and to make this information available to designers through an interactive knowledge base (KB). The KB can then be used during probabilistic design sessions, so as to enable the possible reduction of uncertainties in the design process through resource investment. An extensive literature search has been conducted to identify and quantify typical model-form uncertainties present within aerospace design. An initial attempt has been made to assemble the results of this literature search into a searchable KB, usable in real time during probabilistic design sessions. A concept of operations and the basic structure of a model-form uncertainty KB are described. Key operations within the KB are illustrated. Current limitations in the KB, and possible workarounds are explained.

  17. Knowledge-based modelling of historical surfaces using lidar data

    NASA Astrophysics Data System (ADS)

    Höfler, Veit; Wessollek, Christine; Karrasch, Pierre

    2016-10-01

    Currently in archaeological studies digital elevation models are mainly used especially in terms of shaded reliefs for the prospection of archaeological sites. Hesse (2010) provides a supporting software tool for the determination of local relief models during the prospection using LiDAR scans. Furthermore the search for relicts from WW2 is also in the focus of his research. In James et al. (2006) the determined contour lines were used to reconstruct locations of archaeological artefacts such as buildings. This study is much more and presents an innovative workflow of determining historical high resolution terrain surfaces using recent high resolution terrain models and sedimentological expert knowledge. Based on archaeological field studies (Franconian Saale near Bad Neustadt in Germany) the sedimentological analyses shows that archaeological interesting horizon and geomorphological expert knowledge in combination with particle size analyses (Koehn, DIN ISO 11277) are useful components for reconstructing surfaces of the early Middle Ages. Furthermore the paper traces how it is possible to use additional information (extracted from a recent digital terrain model) to support the process of determination historical surfaces. Conceptual this research is based on methodology of geomorphometry and geo-statistics. The basic idea is that the working procedure is based on the different input data. One aims at tracking the quantitative data and the other aims at processing the qualitative data. Thus, the first quantitative data were available for further processing, which were later processed with the qualitative data to convert them to historical heights. In the final stage of the workflow all gathered information are stored in a large data matrix for spatial interpolation using the geostatistical method of Kriging. Besides the historical surface, the algorithm also provides a first estimation of accuracy of the modelling. The presented workflow is characterized by a high

  18. 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/.

  19. 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.

  20. Knowledge based systems: A preliminary survey of selected issues and techniques

    NASA Technical Reports Server (NTRS)

    Dominick, Wayne D. (Editor); Kavi, Srinu

    1984-01-01

    It is only recently that research in Artificial Intelligence (AI) is accomplishing practical results. Most of these results can be attributed to the design and use of expert systems (or Knowledge-Based Systems, KBS) - problem-solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. But many computer systems designed to see images, hear sounds, and recognize speech are still in a fairly early stage of development. In this report, a preliminary survey of recent work in the KBS is reported, explaining KBS concepts and issues and techniques used to construct them. Application considerations to construct the KBS and potential KBS research areas are identified. A case study (MYCIN) of a KBS is also provided.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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…

  7. The Knowledge Base as an Extension of Distance Learning Reference Service

    ERIC Educational Resources Information Center

    Casey, Anne Marie

    2012-01-01

    This study explores knowledge bases as extension of reference services for distance learners. Through a survey and follow-up interviews with distance learning librarians, this paper discusses their interest in creating and maintaining a knowledge base as a resource for reference services to distance learners. It also investigates their perceptions…

  8. An Expert System Developed from a Hard Data Knowledge Base: Example of a Laboratory Based Anemia Consultant

    PubMed Central

    Fattu, James M.; Blomberg, David J.; Patrick, Edward A.; Guth, Jo Ladley

    1985-01-01

    An expert system derived from a hard data knowledge base has been developed for the laboratory diagnosis of anemias. Five hundred sixty patient records were reviewed and analyzed in a knowledge base system, the CONSULT LEARNING SYSTEM (CLS). Probabilities obtained from the CLS were used to train the expert system, CONSULT-I. This paper is a preliminary report of the development of an expert system from hard data (patient records), the modification of this training by expert hematologists, and performance evaluation. CONSULT-I is a system of artificial intelligence and statistical pattern recognition for developing expert classification systems. Multiple presentations of categories may be stored in its knowledge base. In this study, only two presentations were stored: (1) hard data alone obtained from the 560 patient records, and (2) the hard data presentation edited by experts using rules of Insignificance and Can't. The utility of extending a low cost screening test (CBC with smear evaluation) by means of an expert system is appealing for potential cost reduction in health care. The expert system allows for immediate use of the multi-dimensional knowledge stored in 30 features about the CBC, and provides Actions oriented toward more immediate diagnosis.

  9. Impact of knowledge-based software engineering on aerospace systems

    NASA Technical Reports Server (NTRS)

    Peyton, Liem; Gersh, Mark A.; Swietek, Gregg

    1991-01-01

    The emergence of knowledge engineering as a software technology will dramatically alter the use of software by expanding application areas across a wide spectrum of industries. The engineering and management of large aerospace software systems could benefit from a knowledge engineering approach. An understanding of this technology can potentially make significant improvements to the current practice of software engineering, and provide new insights into future development and support practices.

  10. Development of a standardized knowledge base to generate individualized medication plans automatically with drug administration recommendations

    PubMed Central

    Send, Alexander F J; Al-Ayyash, Adel; Schecher, Sabrina; Rudofsky, Gottfried; Klein, Ulrike; Schaier, Matthias; Pruszydlo, Markus G; Witticke, Diana; Lohmann, Kristina; Kaltschmidt, Jens; Haefeli, Walter E; Seidling, Hanna M

    2013-01-01

    Aims We aimed to develop a generic knowledge base with drug administration recommendations which allows the generation of a dynamic and comprehensive medication plan and to evaluate its comprehensibility and potential benefit in a qualitative pilot study with patients and physicians. Methods Based on a literature search and previously published medication plans, a prototype was developed and iteratively refined through qualitative evaluation (interviews with patients and focus group discussions with physicians). To develop the recommendations for safe administration of specific drugs we screened the summary of product characteristics (SmPC) of different exemplary brands, allocated the generated advice to groups with brands potentially requiring the same advice, and reviewed these allocations regarding applicability and appropriateness of the recommendations. Results For the recommendations, 411 SmPCs of 140 different active ingredients including all available galenic formulations, routes of administrations except infusions, and administration devices were screened. Finally, 515 distinct administration recommendations were included in the database. In 926 different generic groups, 29 879 allocations of brands to general advice, food advice, indications, step-by-step instructions, or combinations thereof were made. Thereby, 27 216 of the preselected allocations (91.1%) were confirmed as appropriate. In total, one third of the German drug market was labelled with information. Conclusions Generic grouping of brands according to their active ingredient and other drug characteristics and allocation of standardized administration recommendations is feasible for a large drug market and can be integrated in a medication plan. PMID:24007451

  11. 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.

  12. 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.

  13. Automated knowledge acquisition for second generation knowledge base systems: A conceptual analysis and taxonomy

    SciTech Connect

    Williams, K.E.; Kotnour, T.

    1991-12-31

    In this paper, we present a conceptual analysis of knowledge-base development methodologies. The purpose of this research is to help overcome the high cost and lack of efficiency in developing knowledge base representations for artificial intelligence applications. To accomplish this purpose, we analyzed the available methodologies and developed a knowledge-base development methodology taxonomy. We review manual, machine-aided, and machine-learning methodologies. A set of developed characteristics allows description and comparison among the methodologies. We present the results of this conceptual analysis of methodologies and recommendations for development of more efficient and effective tools.

  14. Automated knowledge acquisition for second generation knowledge base systems: A conceptual analysis and taxonomy

    SciTech Connect

    Williams, K.E.; Kotnour, T.

    1991-01-01

    In this paper, we present a conceptual analysis of knowledge-base development methodologies. The purpose of this research is to help overcome the high cost and lack of efficiency in developing knowledge base representations for artificial intelligence applications. To accomplish this purpose, we analyzed the available methodologies and developed a knowledge-base development methodology taxonomy. We review manual, machine-aided, and machine-learning methodologies. A set of developed characteristics allows description and comparison among the methodologies. We present the results of this conceptual analysis of methodologies and recommendations for development of more efficient and effective tools.

  15. A JAVA implementation of a medical knowledge base for decision support.

    PubMed

    Ambrosiadou, V; Goulis, D; Shankararaman, V; Shamtani, G

    1999-01-01

    Distributed decision support is a challenging issue requiring the implementation of advanced computer science techniques together with tools of development which offer ease of communication and efficiency of searching and control performance. This paper presents a JAVA implementation of a knowledge base model called ARISTOTELES which may be used in order to support the development of the medical knowledge base by clinicians in diverse specialised areas of interest. The advantages that are evident by the application of such a cognitive model are ease of knowledge acquisition, modular construction of the knowledge base and greater acceptance from clinicians.

  16. 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.

  17. Coordination between control and knowledge based systems for autonomous vehicle guidance

    SciTech Connect

    Harmon, S.Y.

    1983-01-01

    A technique for coordination between control and knowledge based components of an autonomous mobile robot guidance system is discussed. This technique models the interaction process as multiple message passing tasks. A protocol with which to structure the messages has been developed. This protocol builds upon an available transport layer. The synchronization between tasks for real time control and slower knowledge based tasks is achieved by having the knowledge based tasks always work in anticipation of events to come. The implementation of this technique in the form of an autonomous mobile ground robot is used for illustration. Various elements of this robot's hardware and software architecture are discussed.

  18. 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.

  19. 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

  20. An application of knowledge-based systems to satellite control

    NASA Astrophysics Data System (ADS)

    Skiffington, B.; Carrig, J.; Kornell, J.

    This paper describes an expert system prototype which approaches some issues of satellite command and control. The task of the prototype system is to assist a spacecraft controller in maneuvering a geosynchronous satellite for the purpose of maintaining an accurate spacecraft pointing angle, i.e., station keeping. From an expert system's point of view, two features of the system are notable. First, a tool for automated knowledge acquisition was employed. Because the domain experts were in Maryland while the AI experts were in California, a means to automate knowledge acquisition was required. Second, the system involves a blend of simulation and expert systems technology distributed between a DEC VAX computer and a LISP machine (a special purpose AI computer). This kind of distribution is a plausible model for potential real-world installations.

  1. A Knowledge-Based Representation Scheme for Environmental Science Models

    NASA Technical Reports Server (NTRS)

    Keller, Richard M.; Dungan, Jennifer L.; Lum, Henry, Jr. (Technical Monitor)

    1994-01-01

    One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.

  2. 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.

  3. 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 NASA-Ames and the Royal Aerospace Establishment on Knowledge Based Systems (KBS) was established. This joint activity is concerned with tools and techniques for the implementation and validation of real-time KBS. The proposed next stage of the research is described, in which some of the problems of implementing and validating a Knowledge Based Autopilot (KBAP) for a generic high performance aircraft will be studied.

  4. BJUT at TREC 2015 Microblog Track: Real Time Filtering Using Knowledge Base

    DTIC Science & Technology

    2015-11-20

    conference on Knowledge discovery and data mining, pages 133–142. ACM, 2002. ChengXiang Zhai and John Lafferty. Two-stage language models for information...BJUT at TREC 2015 Microblog Track: Real-Time Filtering Using Knowledge Base Luyang Liu1,2,3, Zhen Yang1,2,3,⇤ 1. College of Computer Science, Beijing...classic retrieval model combined with the external knowledge base, i.e., Wikipedia, for query expansion. Besides, we introduced the knowledge

  5. Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis

    DTIC Science & Technology

    1989-08-01

    Automatic Line Network Extraction from Aerial Imangery of Urban Areas Sthrough KnowledghBased Image Analysis N 04 Final Technical ReportI December...Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis Accesion For NTIS CRA&I DTIC TAB 0...paittern re’ognlition. blac’kboardl oriented symbollic processing, knowledge based image analysis , image understanding, aer’ial imsagery, urban area, 17

  6. A Different Approach to the Generation of Patient Management Problems from a Knowledge-Based System

    PubMed Central

    Barriga, Rosa Maria

    1988-01-01

    Several strategies are proposed to approach the generation of Patient Management Problems from a Knowledge Base and avoid inconsistencies in the results. These strategies are based on a different Knowledge Base structure and in the use of case introductions that describe the patient attributes which are not disease-dependent. This methodology has proven effective in a recent pilot test and it is on its way to implementation as part of an educational program at CWRU, School of Medicine.

  7. 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

  8. EENdb: a database and knowledge base of ZFNs and TALENs for endonuclease engineering.

    PubMed

    Xiao, An; Wu, Yingdan; Yang, Zhipeng; Hu, Yingying; Wang, Weiye; Zhang, Yutian; Kong, Lei; Gao, Ge; Zhu, Zuoyan; Lin, Shuo; Zhang, Bo

    2013-01-01

    We report here the construction of engineered endonuclease database (EENdb) (http://eendb.zfgenetics.org/), a searchable database and knowledge base for customizable engineered endonucleases (EENs), including zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs). EENs are artificial nucleases designed to target and cleave specific DNA sequences. EENs have been shown to be a very useful genetic tool for targeted genome modification and have shown great potentials in the applications in basic research, clinical therapies and agricultural utilities, and they are specifically essential for reverse genetics research in species where no other gene targeting techniques are available. EENdb contains over 700 records of all the reported ZFNs and TALENs and related information, such as their target sequences, the peptide components [zinc finger protein-/transcription activator-like effector (TALE)-binding domains, FokI variants and linker peptide/framework], the efficiency and specificity of their activities. The database also lists EEN engineering tools and resources as well as information about forms and types of EENs, EEN screening and construction methods, detection methods for targeting efficiency and many other utilities. The aim of EENdb is to represent a central hub for EEN information and an integrated solution for EEN engineering. These studies may help to extract in-depth properties and common rules regarding ZFN or TALEN efficiency through comparison of the known ZFNs or TALENs.

  9. 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

  10. 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.

  11. Planning and design of a knowledge based system for green manufacturing management

    NASA Astrophysics Data System (ADS)

    Kamal Mohd Nawawi, Mohd; Mohd Zuki Nik Mohamed, Nik; Shariff Adli Aminuddin, Adam

    2013-12-01

    This paper presents a conceptual design approach to the development of a hybrid Knowledge Based (KB) system for Green Manufacturing Management (GMM) at the planning and design stages. The research concentrates on the GMM by using a hybrid KB system, which is a blend of KB system and Gauging Absences of Pre-requisites (GAP). The hybrid KB/GAP system identifies all potentials elements of green manufacturing management issues throughout the development of this system. The KB system used in the planning and design stages analyses the gap between the existing and the benchmark organizations for an effective implementation through the GAP analysis technique. The proposed KBGMM model at the design stage explores two components, namely Competitive Priority and Lean Environment modules. Through the simulated results, the KBGMM System has identified, for each modules and sub-module, the problem categories in a prioritized manner. The System finalized all the Bad Points (BP) that need to be improved to achieve benchmark implementation of GMM at the design stage. The System provides valuable decision making information for the planning and design a GMM in term of business organization.

  12. Proceedings of the 25th Seismic Research Review -- Nuclear Explosion Monitoring: Building the Knowledge Base

    SciTech Connect

    Chavez, Francesca C.; Mendius, E. Louise

    2003-09-23

    These proceedings contain papers prepared for the 25th Seismic Research Review -- Nuclear Explosion Monitoring: Building the Knowledge Base, held 23-25 September, 2003 in Tucson, Arizona. These papers represent the combined research related to ground-based nuclear explosion monitoring funded by the National Nuclear Security Administration (NNSA), Defense Threat Reduction Agency (DTRA), Air Force Research Laboratory (AFRL), US Army Space and Missile Defense Command, and other invited sponsors. The scientific objectives of the research are to improve the United States capability to detect, locate, and identify nuclear explosions. The purpose of the meeting is to provide the sponsoring agencies, as well as potential users, an opportunity to review research accomplished during the preceding year and to discuss areas of investigation for the coming year. For the researchers, it provides a forum for the exchange of scientific information toward achieving program goals, and an opportunity to discuss results and future plans. Paper topics include: seismic regionalization and calibration; detection and location of sources; wave propagation from source to receiver; the nature of seismic sources, including mining practices; hydroacoustic, infrasound, and radionuclide methods; on-site inspection; and data processing.

  13. 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.

  14. 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/.

  15. Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 6. Part A. Computer Architectures for Very Large Knowledge Bases

    DTIC Science & Technology

    1988-06-01

    that efficiently manage very large knowledge bases (VLKB) in a real time environment. There is a current need for expert systems with large and very...large knowledge bases. With these systems comes the problem of the efficient management of the knowledge base. Database management system technology can...approaches. The context cf our knowledge base management research is that of logic programming. That is, the inferencing mechanism is written in a logic

  16. 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...Presidential Helicopter Acquisition: Program Established Knowledge-Based Business Case and Entered System Development with Plans for Managing...progress by establishing a knowledge- based business case for entry into system development that included an approved cost, schedule and performance

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. A Knowledge-Based Weighting Framework to Boost the Power of Genome-Wide Association Studies

    PubMed Central

    Li, Miao-Xin; Sham, Pak C.; Cherny, Stacey S.; Song, You-Qiang

    2010-01-01

    Background We are moving to second-wave analysis of genome-wide association studies (GWAS), characterized by comprehensive bioinformatical and statistical evaluation of genetic associations. Existing biological knowledge is very valuable for GWAS, which may help improve their detection power particularly for disease susceptibility loci of moderate effect size. However, a challenging question is how to utilize available resources that are very heterogeneous to quantitatively evaluate the statistic significances. Methodology/Principal Findings We present a novel knowledge-based weighting framework to boost power of the GWAS and insightfully strengthen their explorative performance for follow-up replication and deep sequencing. Built upon diverse integrated biological knowledge, this framework directly models both the prior functional information and the association significances emerging from GWAS to optimally highlight single nucleotide polymorphisms (SNPs) for subsequent replication. In the theoretical calculation and computer simulation, it shows great potential to achieve extra over 15% power to identify an association signal of moderate strength or to use hundreds of whole-genome subjects fewer to approach similar power. In a case study on late-onset Alzheimer disease (LOAD) for a proof of principle, it highlighted some genes, which showed positive association with LOAD in previous independent studies, and two important LOAD related pathways. These genes and pathways could be originally ignored due to involved SNPs only having moderate association significance. Conclusions/Significance With user-friendly implementation in an open-source Java package, this powerful framework will provide an important complementary solution to identify more true susceptibility loci with modest or even small effect size in current GWAS for complex diseases. PMID:21217833

  4. Investigating Pathways from the Earth Science Knowledge Base to Candidate Solutions

    NASA Astrophysics Data System (ADS)

    Anderson, D. J.; Johnson, E.; Mita, D.; Dabbiru, L.; Katragadda, S.; Lewis, D.; O'Hara, C.

    2007-12-01

    A principle objective of the NASA Applied Sciences Program is to support the transition of scientific research results into decisions which benefit society. One of the Solutions Network activities supporting this goal is the generation of Candidate Solutions derived from NASA Earth Science research results that have the potential to enhance future operational systems for societal benefit. In short, the program seeks to fill gaps between Earth Science results and operational needs. The Earth Science Knowledge Base (ESKB) is being developed to provide connectivity and deliver content for the research information needs of the NASA Applied Science Program and related scientific communities of practice. Data has been collected which will permit users to identify and analyze the current network of interactions between organizations within the community of practice, harvest research results fixed to those interactions, examine the individual components of that research, and assist in developing strategies for furthering research. The ESKB will include information about organizations that conduct NASA-funded Earth Science research, NASA research solicitations, principal investigators, research publications and other project reports, publication authors, inter-agency agreements like memoranda-of-understanding, and NASA assets, models, decision support tools, and data products employed in the course of or developed as a part of the research. The generation of candidate solutions is the first step in developing rigorously tested applications for operational use from the normal yet chaotic process of natural discovery. While the process of 'idea generation' cannot be mechanized, the ESKB serves to provide a resource for testing theories about advancing research streams into the operational realm. Formulation Reports are the documents which outline a Candidate Solution. The reports outline the essential elements, most of which are detailed in the ESKB, which must be analyzed

  5. Arranging ISO 13606 archetypes into a knowledge base using UML connectors.

    PubMed

    Kopanitsa, Georgy

    2014-01-01

    To enable the efficient reuse of standard based medical data we propose to develop a higher-level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analysed for their ability to be applied in the implementation of a higher-level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  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. Deception Detection in Expert Source Information Through Bayesian Knowledge-Bases

    DTIC Science & Technology

    2008-02-04

    intelligence and have implemented deception detection algorithms using probabilistic,intelligent, multi - agent systems . We have also conducted numerous...Bayesian Knowledge Bases," Data and Knowledge Engineering 64, 218-241, 2008. Yuan, Xiuqing, "Deception Detection in Multi - Agent System and War

  12. Development of the Regulatory Commission and Knowledge Base System and Investigation of Possible Augmentation Technologies

    DTIC Science & Technology

    1988-07-01

    1987. Gary Zuckerman, personal communication, Software A& E , Marketing Representative, March, 1987. 7 Zuckerman, personal communication. * 18"KES for...Today’s Knowledge Based Systems," (Software A&E, 1986). 𔃽Ricki Kleist, personal communication, Software A& E , Marketing Representative, March, 1987. 20

  13. The Influence of the Knowledge Base on the Development of Mnemonic Strategies.

    ERIC Educational Resources Information Center

    Ornstein, Peter A.; Naus, Mary J.

    A dominant theme in cognitive psychology is that prior knowledge in long-term memory has a strong influence on an individual's cognitive processing. Citing numerous memory studies with children, knowledge base effects are presented as part of a broader picture of memory development. Using the sort/recall procedure (asking subjects to group sets of…

  14. 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…

  15. The Relationship between Agriculture Knowledge Bases for Teaching and Sources of Knowledge

    ERIC Educational Resources Information Center

    Rice, Amber H.; Kitchel, Tracy

    2015-01-01

    The purpose of this study was to describe the agriculture knowledge bases for teaching of agriculture teachers and to see if a relationship existed between years of teaching experience, sources of knowledge, and development of pedagogical content knowledge (PCK), using quantitative methods. A model of PCK from mathematics was utilized as a…

  16. Northeast Artificial Intelligence Consortium Annual Report 1987. Volume 8. Knowledge Base Maintenance Using Logic Programming Methodologies

    DTIC Science & Technology

    1989-03-01

    small toy example, the code above demonstrates the ease with which knowledge base implementers can directly define notions of consistency and maintance ...It seems apparent that (2) could be replaced or supplemented by maintance of other sorts of relationships between theories, in particular, the sorts

  17. The Educational Media and Technology Profession: An Agenda for Research and Assessment of the Knowledge Base.

    ERIC Educational Resources Information Center

    Molenda, Michael; Olive, J. Fred III

    This report is the first effort to stake out the territory to be included in research on the profession of educational media and technology (em/t), and explore the existing knowledge base within that territory. It comprises a set of questions, the answers to which cast a light on who is in the profession, where it is going, and what useful…

  18. 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…

  19. Elaborating the Grounding of the Knowledge Base on Language and Learning for Preservice Literacy Teachers

    ERIC Educational Resources Information Center

    Piazza, Carolyn L.; Wallat, Cynthia

    2006-01-01

    This purpose of this article is to present a qualitative inquiry into the genesis of sociolinguistics and the contributions of eight sociolinguistic pioneers. This inquiry, based on an historical interpretation of events, reformulates the concept of validation as the social construction of a scientific knowledge base, and explicates three themes…

  20. 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.

  1. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    NASA Technical Reports Server (NTRS)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  2. 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.

  3. Building a Knowledge Base for Teacher Education: An Experience in K-8 Mathematics Teacher Preparation

    ERIC Educational Resources Information Center

    Hiebert, James; Morris, Anne K.

    2009-01-01

    Consistent with the theme of this issue, we describe the details of one continuing effort to build knowledge for teacher education. We argue that building a useful knowledge base requires attention to the processes used to generate, record, and vet knowledge. By using 4 features of knowledge-building systems we identified in the introductory…

  4. 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.

  5. Effects of the Knowledge Base on Children's Rehearsal and Organizational Strategies.

    ERIC Educational Resources Information Center

    Ornstein, Peter A.; Naus, Mary J.

    In addition to the important role of memory strategies in mediating age changes in recall performance, it is clear that the permanent memory system (or information available in the knowledge base) exerts a significant influence on the acquisition and retention of information. Age changes in memory performance will be fully understood only through…

  6. Sensitivity analysis of land unit suitability for conservation using a knowledge-based system.

    PubMed

    Humphries, Hope C; Bourgeron, Patrick S; Reynolds, Keith M

    2010-08-01

    The availability of spatially continuous data layers can have a strong impact on selection of land units for conservation purposes. The suitability of ecological conditions for sustaining the targets of conservation is an important consideration in evaluating candidate conservation sites. We constructed two fuzzy logic-based knowledge bases to determine the conservation suitability of land units in the interior Columbia River basin using NetWeaver software in the Ecosystem Management Decision Support application framework. Our objective was to assess the sensitivity of suitability ratings, derived from evaluating the knowledge bases, to fuzzy logic function parameters and to the removal of data layers (land use condition, road density, disturbance regime change index, vegetation change index, land unit size, cover type size, and cover type change index). The amount and geographic distribution of suitable land polygons was most strongly altered by the removal of land use condition, road density, and land polygon size. Removal of land use condition changed suitability primarily on private or intensively-used public land. Removal of either road density or land polygon size most strongly affected suitability on higher-elevation US Forest Service land containing small-area biophysical environments. Data layers with the greatest influence differed in rank between the two knowledge bases. Our results reinforce the importance of including both biophysical and socio-economic attributes to determine the suitability of land units for conservation. The sensitivity tests provided information about knowledge base structuring and parameterization as well as prioritization for future data needs.

  7. 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…

  8. Sociopathic Knowledge Bases: Correct Knowledge Can Be Harmful Even Given Unlimited Computation

    DTIC Science & Technology

    1989-08-01

    SYMBOL 7a. NAME OF MONITORING ORGANIZATION *University of Illinois f (If applicable) Artificial Intelligence (Code 1133) ______________________ 1...Mathews Ave Dist Urbana, IL 61801 A August 1989 Submitted for Publication: Artificial Intelligence Journal Sociopathic Knowledge Bases: Correct...Introduction Reasoning under uncertainty has been widely investigated in artificial intelligence . Prob- abilistic approaches are of particular relevance

  9. Students' Refinement of Knowledge during the Development of Knowledge Bases for Expert Systems.

    ERIC Educational Resources Information Center

    Lippert, Renate; Finley, Fred

    The refinement of the cognitive knowledge base was studied through exploration of the transition from novice to expert and the use of an instructional strategy called novice knowledge engineering. Six college freshmen, who were enrolled in an honors physics course, used an expert system to create questions, decisions, rules, and explanations…

  10. Testing of a Natural Language Retrieval System for a Full Text Knowledge Base.

    ERIC Educational Resources Information Center

    Bernstein, Lionel M.; Williamson, Robert E.

    1984-01-01

    The Hepatitis Knowledge Base (text of prototype information system) was used for modifying and testing "A Navigator of Natural Language Organized (Textual) Data" (ANNOD), a retrieval system which combines probabilistic, linguistic, and empirical means to rank individual paragraphs of full text for similarity to natural language queries…

  11. Application of knowledge-based vision to closed-loop control of the injection molding process

    NASA Astrophysics Data System (ADS)

    Marsh, Robert; Stamp, R. J.; Hill, T. M.

    1997-10-01

    An investigation is under way to develop a control system for an industrial process which uses a vision systems as a sensor. The research is aimed at the improvement of product quality in commercial injection molding system. A significant enhancement has been achieved in the level of application of visually based inspection techniques to component quality. The aim of the research has been the investigation, and employment, of inspection methods that use knowledge based machine vision. The application of such techniques in this context is comprehensive, extending from object oriented analysis, design and programming of the inspection program, to the application of rule based reasoning, to image interpretation, vision system diagnostics, component diagnostics and molding machine control. In this way, knowledge handling methods are exploited wherever they prove to be beneficial. The vision knowledge base contains information on the procedures required to achieve successful identification of component surface defects. A collection of image processing and pattern recognition algorithms are applied selectively. Once inspection of the component has been performed, defects are related to process variables which affect the quality of the component, and another knowledge base is used to effect a control action at the molding machine. Feedback from other machine sensor is also used to direct the control procedure. Results from the knowledge based vision inspection system are encouraging. They indicate that rapid and effective fault detection and analysis is feasible, as is the verification of system integrity.

  12. CONCEPTUAL FRAMEWORK FOR THE CHEMICAL EFFECTS IN BIOLOGICAL SYSTEMS (CEBS) TOXICOGENOMICS KNOWLEDGE BASE

    EPA Science Inventory

    Conceptual Framework for the Chemical Effects in Biological Systems (CEBS) T oxicogenomics Knowledge Base

    Abstract
    Toxicogenomics studies how the genome is involved in responses to environmental stressors or toxicants. It combines genetics, genome-scale mRNA expressio...

  13. Preparing Oral Examinations of Mathematical Domains with the Help of a Knowledge-Based Dialogue System.

    ERIC Educational Resources Information Center

    Schmidt, Peter

    A conception of discussing mathematical material in the domain of calculus is outlined. Applications include that university students work at their knowledge and prepare for their oral examinations by utilizing the dialog system. The conception is based upon three pillars. One central pillar is a knowledge base containing the collections of…

  14. 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.

  15. Longitudinal Assessment of Progress in Reasoning Capacity and Relation with Self-Estimation of Knowledge Base

    ERIC Educational Resources Information Center

    Collard, Anne; Mélot, France; Bourguignon, Jean-Pierre

    2015-01-01

    The aim of the study was to investigate progress in reasoning capacity and knowledge base appraisal in a longitudinal analysis of data from summative evaluation throughout a medical problem-based learning curriculum. The scores in multidisciplinary discussion of a clinical case and multiple choice questionnaires (MCQs) were studied longitudinally…

  16. 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…

  17. Proposing a Knowledge Base for Teaching Academic Content to English Language Learners: Disciplinary Linguistic Knowledge

    ERIC Educational Resources Information Center

    Turkan, Sultan; De Oliveira, Luciana C.; Lee, Okhee; Phelps, Geoffrey

    2014-01-01

    Background/Context: The current research on teacher knowledge and teacher accountability falls short on information about what teacher knowledge base could guide preparation and accountability of the mainstream teachers for meeting the academic needs of ELLs. Most recently, research on specialized knowledge for teaching has offered ways to…

  18. 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…

  19. English Language Teacher Educators' Pedagogical Knowledge Base: The Macro and Micro Categories

    ERIC Educational Resources Information Center

    Moradkhani, Shahab; Akbari, Ramin; Samar, Reza Ghafar; Kiany, Gholam Reza

    2013-01-01

    The aim of this study was to determine the major categories of English language teacher educators' pedagogical knowledge base. To this end, semi-structured interviews were conducted with 5 teachers, teacher educators, and university professors (15 participants in total). The results of data analysis indicated that teacher educators' pedagogical…

  20. 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.

  1. Developing a Knowledge Base for Educational Leadership and Management in East Asia

    ERIC Educational Resources Information Center

    Hallinger, Philip

    2011-01-01

    The role of school leadership in educational reform has reached the status of a truism, and led to major changes in school leader recruitment, selection, training and appraisal. While similar policy trends are evident in East Asia, the empirical knowledge base underlying these measures is distorted and lacking in validation. This paper begins by…

  2. Developing the Knowledge Base for Supervisor Induction and Professional Growth: Validating the Model.

    ERIC Educational Resources Information Center

    Friedman, Malcolm; Watkins, Regina M.

    Prior to implementation of a supervisory staff development program, it is necessary to review current literature in the field of educational administration in order to define specific elements (domains) of the supervisory knowledge base. A qualitative research study involving a review of relevant literature yielded 13 primary domains or categories…

  3. The Knowledge Base of Non-Native English-Speaking Teachers: Perspectives of Teachers and Administrators

    ERIC Educational Resources Information Center

    Zhang, Fengjuan; Zhan, Ju

    2014-01-01

    This study explores the knowledge base of non-native English-speaking teachers (NNESTs) working in the Canadian English as a second language (ESL) context. By examining NNESTs' experiences in seeking employment and teaching ESL in Canada, and investigating ESL program administrators' perceptions and hiring practices in relation to NNESTs, it…

  4. 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…

  5. Static and Completion Analysis for Planning Knowledge Base Development and Verification

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

  6. Knowledge Bases for Effective Teaching: Beginning Teachers' Development as Teachers of Primary Geography

    ERIC Educational Resources Information Center

    Martin, Fran

    2008-01-01

    This paper reports the findings of a research project into beginning teacher development conducted in the United Kingdom. A model for beginning teacher development in the field of primary geography is proposed which looks at the relative knowledge bases needed for effective geography teaching. The model is used to aid analysis of data gathered…

  7. Clear as Glass: A Combined List of Print and Electronic Journals in the Knowledge Base

    ERIC Educational Resources Information Center

    Lowe, M. Sara

    2008-01-01

    The non-standard practice at Cowles Library at Drake University has been to display electronic journals and some print journals in the Knowledge Base while simultaneously listing print journals and some electronic journals in the online public access catalog (OPAC). The result was a system that made it difficult for patrons to determine our…

  8. The Feasibility and Effectiveness of a Pilot Resident-Organized and -Led Knowledge Base Review

    ERIC Educational Resources Information Center

    Vautrot, Victor J.; Festin, Fe E.; Bauer, Mark S.

    2010-01-01

    Objective: The Accreditation Council for Graduate Medical Education (ACGME) requires a sufficient medical knowledge base as one of the six core competencies in residency training. The authors judged that an annual "short-course" review of medical knowledge would be a useful adjunct to standard seminar and rotation teaching, and that a…

  9. 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.

  10. The Impact of the Shifting Knowledge Base, from Development to Achievement, on Early Childhood Education Programs

    ERIC Educational Resources Information Center

    Tyler, Kathleen P.

    2012-01-01

    Interest in child development as a knowledge base for early childhood education programs flourished in the 1970s as a result of the theories and philosophies of Jean Piaget and other cognitive developmentalists. During subsequent decades in America, reform movements emphasizing accountability and achievement became a political and social…

  11. Appropriating Professionalism: Restructuring the Official Knowledge Base of England's "Modernised" Teaching Profession

    ERIC Educational Resources Information Center

    Beck, John

    2009-01-01

    The present paper examines efforts by government and government agencies in England to prescribe and control the knowledge base of a teaching profession that has, under successive New Labour administrations since 1997, been subjected to "modernisation". A theoretical framework drawn from aspects of the work of Basil Bernstein, and of Rob…

  12. 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.

  13. The nature of students' science knowledge base: Using assessment to paint a picture

    NASA Astrophysics Data System (ADS)

    Gotwals, Amelia Wenk

    Goals in inquiry-based science include not only that students understand content knowledge, but also that students be able to utilize this knowledge in complex problem solving situations to work with tasks that involve skills such as interpreting data and formulating scientific explanations. In addition, advancements in the measurement sciences allow for sophisticated and complex ways to score and interpret student responses on assessment tasks. However, while many studies have shown the benefits of scientific inquiry in the classroom and others have described new types of psychometric models available for scoring analysis, few have combined the two to develop a better understanding of how students "know" science. I describe an assessment system used to create items that systematically measure and disentangle three focal aspects of sixth grade students' science knowledge base associated with the BioKIDS: Kids' Inquiry of Diverse Species curriculum. Then, using students' verbal and written responses to the assessment, I analyzed the validity of the assessment tasks and examined the nature of students' science knowledge base when working in science problem solving situations. Overall, the results suggest that the tasks created using the assessment system provided students with opportunities to demonstrate the knowledge and skills about which they were designed, thus indicating that utilizing this assessment system could enable assessment designers to create tasks that allow them to gather information about multiple key aspects of students' science knowledge base. Specifically, tasks can generate information about students' content knowledge, explanation ability and interpreting data ability. In addition, utilizing psychometric models, the results suggest that students have a multidimensional science knowledge base. However, after students have participated in an inquiry-based curricular program, these dimensions are highly related to one another. Despite the

  14. 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

  15. Generic supervisor: A knowledge-based tool for control of space station on-board systems

    NASA Technical Reports Server (NTRS)

    Carnes, J. R.; Nelson, R.

    1988-01-01

    The concept of a generic module for management of onboard systems grew out of the structured analysis effort for the Space Station software. Hierarchical specification of subsystems software revealed that nontrivial supervisory elements are required at all levels. The number of supervisors (and subsequent software) required to implement the hierarchical control over onboard functions comprise a large portion of the Space Station software. Thus, a generic knowledge based supervisory module significantly reduces the amount of software developed. This module, the Generic Supervisor, depends on its knowledge of control to provide direction for subordinates and feedback to superiors within a specific subsystem area. The Generic Supervisor provides an adaptable and maintainable control system. A portion of the Space Station Environmental Control and Life Support System (ECLSS) was implemented as a hierarchy of supervisors. This prototype implementation demonstrates the feasibility of a generic knowledge based supervisor, and its facility to meet complex mission requirements.

  16. Knowledge bases, clinical decision support systems, and rapid learning in oncology.

    PubMed

    Yu, Peter Paul

    2015-03-01

    One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care.

  17. 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.

  18. 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.

  19. CKB - the compound knowledge base: a text based chemical search system.

    PubMed

    Walker, Matthew J; Hull, Richard D; Singh, Suresh B

    2002-01-01

    The Compound Knowledge Base (CKB) was developed as a means of locating structures and additional relevant information from a given known structural identifier. Any of Chemical Abstracts Service Registry Number, company code (code number the producing company refers to the chemical entity internally), generic name (trivial or class name), or trade name (name under which the compound is marketed) can be provided as a query. CKB will provide the remaining available information as well as the corresponding structure for any matching compound in the database. The interface to the Compound Knowledge Base is Internet/World Wide Web-based, using Netscape Navigator and the ChemDraw Pro Plugin, which allows Merck scientists quick and easy access to the database from their desktop. The design and implementation of the database and the search interface are herein detailed.

  20. 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.

  1. 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.

  2. Optimization of compartments arrangement of submarine pressure hull with knowledge based system

    NASA Astrophysics Data System (ADS)

    Chung, Bo-Young; Kim, Soo-Young; Shin, Sung-Chul; Koo, Youn-Hoe; Kraus, Andreas

    2011-12-01

    This study aims to optimize an arrangement of ship compartments with knowledge-based systems. Though great attention has been shown to the optimization of hull forms in recent years, the study on arrangement design optimization has received relatively little attention. A ship is both an engineering system and a kind of assembly of many spaces. This means that, to design an arrangement of ship compartments, it is necessary to treat not only geometric data but also knowledge on topological relations between spaces and components of a ship. In this regard, we select a suitable knowledge representation scheme for describing ship compartments and their relations, and then develop a knowledge-based system using expert system shell. This new approach is applied to create design variations for optimization on an arrangement of a pressure hull of a submerged vehicle. Finally, we explicate how our approach improves the design process.

  3. 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.

  4. SAFOD Brittle Microstructure and Mechanics Knowledge Base (SAFOD BM2KB)

    NASA Astrophysics Data System (ADS)

    Babaie, H. A.; Hadizadeh, J.; di Toro, G.; Mair, K.; Kumar, A.

    2008-12-01

    We have developed a knowledge base to store and present the data collected by a group of investigators studying the microstructures and mechanics of brittle faulting using core samples from the SAFOD (San Andreas Fault Observatory at Depth) project. The investigations are carried out with a variety of analytical and experimental methods primarily to better understand the physics of strain localization in fault gouge. The knowledge base instantiates an specially-designed brittle rock deformation ontology developed at Georgia State University. The inference rules embedded in the semantic web languages, such as OWL, RDF, and RDFS, which are used in our ontology, allow the Pellet reasoner used in this application to derive additional truths about the ontology and knowledge of this domain. Access to the knowledge base is via a public website, which is designed to provide the knowledge acquired by all the investigators involved in the project. The stored data will be products of studies such as: experiments (e.g., high-velocity friction experiment), analyses (e.g., microstructural, chemical, mass transfer, mineralogical, surface, image, texture), microscopy (optical, HRSEM, FESEM, HRTEM]), tomography, porosity measurement, microprobe, and cathodoluminesence. Data about laboratories, experimental conditions, methods, assumptions, equipments, and mechanical properties and lithology of the studied samples will also be presented on the website per investigation. The ontology was modeled applying the UML (Unified Modeling Language) in Rational Rose, and implemented in OWL-DL (Ontology Web Language) using the Protégé ontology editor. The UML model was converted to OWL-DL by first mapping it to Ecore (.ecore) and Generator model (.genmodel) with the help of the EMF (Eclipse Modeling Framework) plugin in Eclipse. The Ecore model was then mapped to a .uml file, which later was converted into an .owl file and subsequently imported into the Protégé ontology editing environment

  5. 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.

  6. 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.

  7. Virtual Center for Renal Support: Definition of a Novel Knowledge-Based Telemedicine System

    DTIC Science & Technology

    2007-11-02

    second part, the formal definition of the novel Virtual Center for Renal Support (VCRS) is done. Design of VCRS relies on a model- based system...supervision of therapies. Keywords – Remote healthcare, telemedicine, ESRD, peritoneal dialysis, hemodialysis , ESRD costs, knowledge-based assistance...patients was 25.689 (745 pmp) [3], but 40% of prevalent ESRD patients had a functioning graft, 55% were in hemodialysis therapy and the rest were

  8. Knowledge Based Systems (KBS) Verification, Validation, Evaluation, and Testing (VVE&T) Bibliography: Topical Categorization

    DTIC Science & Technology

    2003-03-01

    Different?," Jour. of Experimental & Theoretical Artificial Intelligence, Special Issue on Al for Systems Validation and Verification, 12(4), 2000, pp...Hamilton, D., " Experiences in Improving the State of Practice in Verification and Validation of Knowledge-Based Systems," Workshop Notes of the AAAI...Unsuspected Power of the Standard Turing Test," Jour. of Experimental & Theoretical Artificial Intelligence., 12, 2000, pp3 3 1-3 4 0 . [30] Gaschnig

  9. 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.

  10. Knowledge Based Synthesis of Efficient Structures for Concurrent Computation Using Fat-Trees and Pipelining.

    DTIC Science & Technology

    1986-12-31

    based on the proof is feasible. KES.U.86.11 AFO -Th, 87-0 791 Kestrel Institute Knowledge Based Synthesis of Efficient Structures for Concurrent...manner similar to an assembly line. The proof is a constructive one; a synthesis method based on the proof is feasible. 2 Chapter 2 Introduction This...These techniques are based on the use of closures as a device to schedule commu- nication, resulting from divide and conquer, between halves of a tree

  11. Orbital transfer vehicle launch operations study: Automated technology knowledge base, volume 4

    NASA Technical Reports Server (NTRS)

    1986-01-01

    A simplified retrieval strategy for compiling automation-related bibliographies from NASA/RECON is presented. Two subsets of NASA Thesaurus subject terms were extracted: a primary list, which is used to obtain an initial set of citations; and a secondary list, which is used to limit or further specify a large initial set of citations. These subject term lists are presented in Appendix A as the Automated Technology Knowledge Base (ATKB) Thesaurus.

  12. Generic Tasks for Knowledge-Based Problem Solving: Extension and New Directions

    DTIC Science & Technology

    1991-02-01

    will be described. The major results arise from projects that are continuations of the following areas of research: theory building for task...knowledge-based system to a model representing the "complete" domain theory . One approach for representing this knowiedge is to define a functional I...Appendix: A ii implementation not-. In Computational Models of Discovery and Theory Formation, 1990. ~161 P.R. Myers. J.F. Davis, and D. Herman. A task

  13. Towards Transdisciplinary Science and Technology as Emerging Systems Thinking for Knowledge based Information Society

    NASA Astrophysics Data System (ADS)

    Funabashi, Motohisa

    This paper presents an emerging direction of systems thinking, transdisiciplinary science and technology, that is expected to respond to critical issues such as environmental sustainability in our knowledge based information society. Firstly today's systems analysis to global warming is presented for reviewing current systems approaches, then some hypothetical requisites for the further advancements are investigated with historical consideration on systems thinking. Finally present efforts for developing transdisciplinary science and technology are presented to meet the societal requirements.

  14. Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

    NASA Technical Reports Server (NTRS)

    Lara-Rosano, Felipe

    1992-01-01

    In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.

  15. 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.

  16. 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.

  17. Integration of an OWL-DL knowledge base with an EHR prototype and providing customized information.

    PubMed

    Jing, Xia; Kay, Stephen; Marley, Tom; Hardiker, Nicholas R

    2014-09-01

    When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledge is often an important contribution to their ability to make more informed decisions. In this paper we describe a method by which an external, formal representation of clinical and molecular genetic knowledge can be integrated into an EHR such that customized knowledge can be delivered to clinicians in a context-appropriate manner.Web Ontology Language-Description Logic (OWL-DL) is a formal knowledge representation language that is widely used for creating, organizing and managing biomedical knowledge through the use of explicit definitions, consistent structure and a computer-processable format, particularly in biomedical fields. In this paper we describe: 1) integration of an OWL-DL knowledge base with a standards-based EHR prototype, 2) presentation of customized information from the knowledge base via the EHR interface, and 3) lessons learned via the process. The integration was achieved through a combination of manual and automatic methods. Our method has advantages for scaling up to and maintaining knowledge bases of any size, with the goal of assisting clinicians and other EHR users in making better informed health care decisions.

  18. A preliminary taxonomy and a standard knowledge base for mental-health system indicators in Spain

    PubMed Central

    2010-01-01

    Background There are many sources of information for mental health indicators but we lack a comprehensive classification and hierarchy to improve their use in mental health planning. This study aims at developing a preliminary taxonomy and its related knowledge base of mental health indicators usable in Spain. Methods A qualitative method with two experts panels was used to develop a framing document, a preliminary taxonomy with a conceptual map of health indicators, and a knowledge base consisting of key documents, glossary and database of indicators with an evaluation of their relevance for Spain. Results A total of 661 indicators were identified and organised hierarchically in 4 domains (Context, Resources, Use and Results), 12 subdomains and 56 types. Among these the expert panels identified 200 indicators of relevance for the Spanish system. Conclusions The classification and hierarchical ordering of the mental health indicators, the evaluation according to their level of relevance and their incorporation into a knowledge base are crucial for the development of a basic list of indicators for use in mental health planning. PMID:21122091

  19. Detecting knowledge base inconsistencies using automated generation of text and examples

    SciTech Connect

    Mittal, V.O.; Moore, J.D.

    1996-12-31

    Verifying the fidelity of domain representation in large knowledge bases (KBs) is a difficult problem: domain experts are typically not experts in knowledge representation languages, and as knowledge bases grow more complex, visual inspection of the various terms and their abstract definitions, their interrelationships and the limiting, boundary cases becomes much harder. This paper presents an approach to help verify and refine abstract term definitions in knowledge bases. It assumes that it is easier for a domain expert to determine the correctness of individual concrete examples than it is to verify and correct all the ramifications of an abstract, intentional specification. To this end, our approach presents the user with an interface in which abstract terms in the KB are described using examples and natural language generated from the underlying domain representation. Problems in the KB are therefore manifested as problems in the generated description. The user can then highlight specific examples or parts of the explanation that seem problematic. The system reasons about the underlying domain model by using the discourse plan generated for the description. This paper briefly describes the working of the system and illustrates three possible types of problem manifestations using an example of a specification of floating-point numbers in Lisp.

  20. Scaling up explanation generation: Large-scale knowledge bases and empirical studies

    SciTech Connect

    Lester, J.C.; Porter, B.W.

    1996-12-31

    To explain complex phenomena, an explanation system must be able to select information from a formal representation of domain knowledge, organize the selected information into multisentential discourse plans, and realize the discourse plans in text. Although recent years have witnessed significant progress in the development of sophisticated computational mechanisms for explanation, empirical results have been limited. This paper reports on a seven year effort to empirically study explanation generation from semantically rich, large-scale knowledge bases. We first describe Knight, a robust explanation system that constructs multi-sentential and multi-paragraph explanations from the Biology Knowledge Base, a large-scale knowledge base in the domain of botanical anatomy, physiology, and development. We then introduce the Two Panel evaluation methodology and describe how Knight`s performance was assessed with this methodology in the most extensive empirical evaluation conducted on an explanation system. In this evaluation, Knight scored within {open_quotes}half a grade{close_quote} of domain experts, and its performance exceeded that of one of the domain experts.

  1. Integrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation Extraction.

    PubMed

    Zhang, Yaoyun; Soysal, Ergin; Moon, Sungrim; Wang, Jingqi; Tao, Cui; Xu, Hua

    2015-01-01

    A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications. This paper describes our initial step towards establishing a comprehensive knowledge base of disease and lab tests relations utilizing three public on-line resources. LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase. Disease and lab test concepts are identified using MetaMap and relations between diseases and lab tests are determined based on source-specific rules. Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%. Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book. Moreover, we found additional disease-lab test relations from on-line resources, indicating they are complementary to existing reference books for building a comprehensive disease and lab test relation knowledge base.

  2. 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.

  3. 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.

  4. Knowledge base and sensor bus messaging service architecture for critical tsunami warning and decision-support

    NASA Astrophysics Data System (ADS)

    Sabeur, Z. A.; Wächter, J.; Middleton, S. E.; Zlatev, Z.; Häner, R.; Hammitzsch, M.; Loewe, P.

    2012-04-01

    The intelligent management of large volumes of environmental monitoring data for early tsunami warning requires the deployment of robust and scalable service oriented infrastructure that is supported by an agile knowledge-base for critical decision-support In the TRIDEC project (TRIDEC 2010-2013), a sensor observation service bus of the TRIDEC system is being developed for the advancement of complex tsunami event processing and management. Further, a dedicated TRIDEC system knowledge-base is being implemented to enable on-demand access to semantically rich OGC SWE compliant hydrodynamic observations and operationally oriented meta-information to multiple subscribers. TRIDEC decision support requires a scalable and agile real-time processing architecture which enables fast response to evolving subscribers requirements as the tsunami crisis develops. This is also achieved with the support of intelligent processing services which specialise in multi-level fusion methods with relevance feedback and deep learning. The TRIDEC knowledge base development work coupled with that of the generic sensor bus platform shall be presented to demonstrate advanced decision-support with situation awareness in context of tsunami early warning and crisis management.

  5. Virk: an active learning-based system for bootstrapping knowledge base development in the neurosciences.

    PubMed

    Ambert, Kyle H; Cohen, Aaron M; Burns, Gully A P C; Boudreau, Eilis; Sonmez, Kemal

    2013-01-01

    The frequency and volume of newly-published scientific literature is quickly making manual maintenance of publicly-available databases of primary data unrealistic and costly. Although machine learning (ML) can be useful for developing automated approaches to identifying scientific publications containing relevant information for a database, developing such tools necessitates manually annotating an unrealistic number of documents. One approach to this problem, active learning (AL), builds classification models by iteratively identifying documents that provide the most information to a classifier. Although this approach has been shown to be effective for related problems, in the context of scientific databases curation, it falls short. We present Virk, an AL system that, while being trained, simultaneously learns a classification model and identifies documents having information of interest for a knowledge base. Our approach uses a support vector machine (SVM) classifier with input features derived from neuroscience-related publications from the primary literature. Using our approach, we were able to increase the size of the Neuron Registry, a knowledge base of neuron-related information, by a factor of 90%, a knowledge base of neuron-related information, in 3 months. Using standard biocuration methods, it would have taken between 1 and 2 years to make the same number of contributions to the Neuron Registry. Here, we describe the system pipeline in detail, and evaluate its performance against other approaches to sampling in AL.

  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. 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.

  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. Integrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation Extraction

    PubMed Central

    Zhang, Yaoyun; Soysal, Ergin; Moon, Sungrim; Wang, Jingqi; Tao, Cui; Xu, Hua

    2015-01-01

    A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications. This paper describes our initial step towards establishing a comprehensive knowledge base of disease and lab tests relations utilizing three public on-line resources. LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase. Disease and lab test concepts are identified using MetaMap and relations between diseases and lab tests are determined based on source-specific rules. Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%. Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book. Moreover, we found additional disease-lab test relations from on-line resources, indicating they are complementary to existing reference books for building a comprehensive disease and lab test relation knowledge base. PMID:26306271

  10. 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.

  11. 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

  12. 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.

  13. 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.)

  14. 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.

  15. The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research

    PubMed Central

    2014-01-01

    Background Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. Results The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. Conclusions The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http

  16. 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.

  17. 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.

  18. 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.

  19. Knowledge based ranking algorithm for comparative assessment of post-closure care needs of closed landfills.

    PubMed

    Sizirici, Banu; Tansel, Berrin; Kumar, Vivek

    2011-06-01

    Post-closure care (PCC) activities at landfills include cap maintenance; water quality monitoring; maintenance and monitoring of the gas collection/control system, leachate collection system, groundwater monitoring wells, and surface water management system; and general site maintenance. The objective of this study was to develop an integrated data and knowledge based decision making tool for preliminary estimation of PCC needs at closed landfills. To develop the decision making tool, 11 categories of parameters were identified as critical areas which could affect future PCC needs. Each category was further analyzed by detailed questions which could be answered with limited data and knowledge about the site, its history, location, and site specific characteristics. Depending on the existing knowledge base, a score was assigned to each question (on a scale 1-10, as 1 being the best and 10 being the worst). Each category was also assigned a weight based on its relative importance on the site conditions and PCC needs. The overall landfill score was obtained from the total weighted sum attained. Based on the overall score, landfill conditions could be categorized as critical, acceptable, or good. Critical condition indicates that the landfill may be a threat to the human health and the environment and necessary steps should be taken. Acceptable condition indicates that the landfill is currently stable and the monitoring should be continued. Good condition indicates that the landfill is stable and the monitoring activities can be reduced in the future. The knowledge base algorithm was applied to two case study landfills for preliminary assessment of PCC performance.

  20. Knowledge based ranking algorithm for comparative assessment of post-closure care needs of closed landfills

    SciTech Connect

    Sizirici, Banu; Tansel, Berrin; Kumar, Vivek

    2011-06-15

    Post-closure care (PCC) activities at landfills include cap maintenance; water quality monitoring; maintenance and monitoring of the gas collection/control system, leachate collection system, groundwater monitoring wells, and surface water management system; and general site maintenance. The objective of this study was to develop an integrated data and knowledge based decision making tool for preliminary estimation of PCC needs at closed landfills. To develop the decision making tool, 11 categories of parameters were identified as critical areas which could affect future PCC needs. Each category was further analyzed by detailed questions which could be answered with limited data and knowledge about the site, its history, location, and site specific characteristics. Depending on the existing knowledge base, a score was assigned to each question (on a scale 1-10, as 1 being the best and 10 being the worst). Each category was also assigned a weight based on its relative importance on the site conditions and PCC needs. The overall landfill score was obtained from the total weighted sum attained. Based on the overall score, landfill conditions could be categorized as critical, acceptable, or good. Critical condition indicates that the landfill may be a threat to the human health and the environment and necessary steps should be taken. Acceptable condition indicates that the landfill is currently stable and the monitoring should be continued. Good condition indicates that the landfill is stable and the monitoring activities can be reduced in the future. The knowledge base algorithm was applied to two case study landfills for preliminary assessment of PCC performance.

  1. 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.

  2. 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.

  3. 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.

  4. Investigation of candidate data structures and search algorithms to support a knowledge based fault diagnosis system

    NASA Technical Reports Server (NTRS)

    Bosworth, Edward L., Jr.

    1987-01-01

    The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

  5. HSTDEK: Developing a methodology for construction of large-scale, multi-use knowledge bases

    NASA Technical Reports Server (NTRS)

    Freeman, Michael S.

    1987-01-01

    The primary research objectives of the Hubble Space Telescope Design/Engineering Knowledgebase (HSTDEK) are to develop a methodology for constructing and maintaining large scale knowledge bases which can be used to support multiple applications. To insure the validity of its results, this research is being persued in the context of a real world system, the Hubble Space Telescope. The HSTDEK objectives are described in detail. The history and motivation of the project are briefly described. The technical challenges faced by the project are outlined.

  6. 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).

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Knowledge based translation and problem solving in an intelligent individualized instruction system

    NASA Technical Reports Server (NTRS)

    Jung, Namho; Biegel, John E.

    1994-01-01

    An Intelligent Individualized Instruction I(sup 3) system is being built to provide computerized instruction. We present the roles of a translator and a problem solver in an intelligent computer system. The modular design of the system provides for easier development and allows for future expansion and maintenance. CLIPS modules and classes are utilized for the purpose of the modular design and inter module communications. CLIPS facts and rules are used to represent the system components and the knowledge base. CLIPS provides an inferencing mechanism to allow the I(sup 3) system to solve problems presented to it in English.

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

    DOEpatents

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

    2011-04-26

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

  14. 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

  15. Participatory approach to the development of a knowledge base for problem-solving in diabetes self-management

    PubMed Central

    Cole-Lewis, Heather J.; Smaldone, Arlene M.; Davidson, Patricia R.; Kukafka, Rita; Tobin, Jonathan N.; Cassells, Andrea; Mynatt, Elizabeth D.; Hripcsak, George; Mamykina, Lena

    2015-01-01

    Objective To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. Materials and methods The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. Results The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. Discussion The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. Conclusion The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions. PMID:26547253

  16. 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.

  17. New developments of a knowledge based system (VEG) for inferring vegetation characteristics

    NASA Technical Reports Server (NTRS)

    Kimes, D. S.; Harrison, P. A.; Harrison, P. R.

    1992-01-01

    An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

  18. Syn-Lethality: An Integrative Knowledge Base of Synthetic Lethality towards Discovery of Selective Anticancer Therapies

    PubMed Central

    Li, Xue-juan; Mishra, Shital K.; Wu, Min; Zhang, Fan

    2014-01-01

    Synthetic lethality (SL) is a novel strategy for anticancer therapies, whereby mutations of two genes will kill a cell but mutation of a single gene will not. Therefore, a cancer-specific mutation combined with a drug-induced mutation, if they have SL interactions, will selectively kill cancer cells. While numerous SL interactions have been identified in yeast, only a few have been known in human. There is a pressing need to systematically discover and understand SL interactions specific to human cancer. In this paper, we present Syn-Lethality, the first integrative knowledge base of SL that is dedicated to human cancer. It integrates experimentally discovered and verified human SL gene pairs into a network, associated with annotations of gene function, pathway, and molecular mechanisms. It also includes yeast SL genes from high-throughput screenings which are mapped to orthologous human genes. Such an integrative knowledge base, organized as a relational database with user interface for searching and network visualization, will greatly expedite the discovery of novel anticancer drug targets based on synthetic lethality interactions. The database can be downloaded as a stand-alone Java application. PMID:24864230

  19. 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.

  20. Developing an ontological explosion knowledge base for business continuity planning purposes.

    PubMed

    Mohammadfam, Iraj; Kalatpour, Omid; Golmohammadi, Rostam; Khotanlou, Hasan

    2013-01-01

    Industrial accidents are among the most known challenges to business continuity. Many organisations have lost their reputation following devastating accidents. To manage the risks of such accidents, it is necessary to accumulate sufficient knowledge regarding their roots, causes and preventive techniques. The required knowledge might be obtained through various approaches, including databases. Unfortunately, many databases are hampered by (among other things) static data presentations, a lack of semantic features, and the inability to present accident knowledge as discrete domains. This paper proposes the use of Protégé software to develop a knowledge base for the domain of explosion accidents. Such a structure has a higher capability to improve information retrieval compared with common accident databases. To accomplish this goal, a knowledge management process model was followed. The ontological explosion knowledge base (EKB) was built for further applications, including process accident knowledge retrieval and risk management. The paper will show how the EKB has a semantic feature that enables users to overcome some of the search constraints of existing accident databases.

  1. A spectral-knowledge-based approach for urban land-cover discrimination

    NASA Technical Reports Server (NTRS)

    Wharton, Stephen W.

    1987-01-01

    A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was developed that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.

  2. 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.

  3. 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.

  4. 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.

  5. The Digital Anatomist Distributed Framework and Its Applications to Knowledge-based Medical Imaging

    PubMed Central

    Brinkley, James F.; Rosse, Cornelius

    1997-01-01

    Abstract The domain of medical imaging is anatomy. Therefore, anatomic knowledge should be a rational basis for organizing and analyzing images. The goals of the Digital Anatomist Program at the University of Washington include the development of an anatomically based software framework for organizing, analyzing, visualizing and utilizing biomedical information. The framework is based on representations for both spatial and symbolic anatomic knowledge, and is being implemented in a distributed architecture in which multiple client programs on the Internet are used to update and access an expanding set of anatomical information resources. The development of this framework is driven by several practical applications, including symbolic anatomic reasoning, knowledge based image segmentation, anatomy information retrieval, and functional brain mapping. Since each of these areas involves many difficult image processing issues, our research strategy is an evolutionary one, in which applications are developed somewhat independently, and partial solutions are integrated in a piecemeal fashion, using the network as the substrate. This approach assumes that networks of interacting components can synergistically work together to solve problems larger than either could solve on its own. Each of the individual projects is described, along with evaluations that show that the individual components are solving the problems they were designed for, and are beginning to interact with each other in a synergistic manner. We argue that this synergy will increase, not only within our own group, but also among groups as the Internet matures, and that an anatomic knowledge base will be a useful means for fostering these interactions. PMID:9147337

  6. An American knowledge base in England - Alternate implementations of an expert system flight status monitor

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

    A joint activity between the Dryden Flight Research Facility of the NASA Ames Research Center (Ames-Dryden) and the Royal Aerospace Establishment (RAE) on knowledge-based systems has been agreed. Under the agreement, a flight status monitor knowledge base developed at Ames-Dryden has been implemented using the real-time AI (artificial intelligence) toolkit MUSE, which was developed in the UK. Here, the background to the cooperation is described and the details of the flight status monitor and a prototype MUSE implementation are presented. It is noted that the capabilities of the expert-system flight status monitor to monitor data downlinked from the flight test aircraft and to generate information on the state and health of the system for the test engineers provides increased safety during flight testing of new systems. Furthermore, the expert-system flight status monitor provides the systems engineers with ready access to the large amount of information required to describe a complex aircraft system.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Knowledge-based system V and V in the Space Station Freedom program

    NASA Technical Reports Server (NTRS)

    Kelley, Keith; Hamilton, David; Culbert, Chris

    1992-01-01

    Knowledge Based Systems (KBS's) are expected to be heavily used in the Space Station Freedom Program (SSFP). Although SSFP Verification and Validation (V&V) requirements are based on the latest state-of-the-practice in software engineering technology, they may be insufficient for Knowledge Based Systems (KBS's); it is widely stated that there are differences in both approach and execution between KBS V&V and conventional software V&V. In order to better understand this issue, we have surveyed and/or interviewed developers from sixty expert system projects in order to understand the differences and difficulties in KBS V&V. We have used this survey results to analyze the SSFP V&V requirements for conventional software in order to determine which specific requirements are inappropriate for KBS V&V and why they are inappropriate. Further work will result in a set of recommendations that can be used either as guidelines for applying conventional software V&V requirements to KBS's or as modifications to extend the existing SSFP conventional software V&V requirements to include KBS requirements. The results of this work are significant to many projects, in addition to SSFP, which will involve KBS's.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  13. Knowledge-base for the new human reliability analysis method, A Technique for Human Error Analysis (ATHEANA)

    SciTech Connect

    Cooper, S.E.; Wreathall, J.; Thompson, C.M., Drouin, M.; Bley, D.C.

    1996-10-01

    This paper describes the knowledge base for the application of the new human reliability analysis (HRA) method, a ``A Technique for Human Error Analysis`` (ATHEANA). Since application of ATHEANA requires the identification of previously unmodeled human failure events, especially errors of commission, and associated error-forcing contexts (i.e., combinations of plant conditions and performance shaping factors), this knowledge base is an essential aid for the HRA analyst.

  14. Use of Knowledge Base Systems (EMDS) in Strategic and Tactical Forest Planning

    NASA Astrophysics Data System (ADS)

    Jensen, M. E.; Reynolds, K.; Stockmann, K.

    2008-12-01

    The USDA Forest Service 2008 Planning Rule requires Forest plans to provide a strategic vision for maintaining the sustainability of ecological, economic, and social systems across USFS lands through the identification of desired conditions and objectives. In this paper we show how knowledge-based systems can be efficiently used to evaluate disparate natural resource information to assess desired conditions and related objectives in Forest planning. We use the Ecosystem Management Decision Support (EMDS) system (http://www.institute.redlands.edu/emds/), which facilitates development of both logic-based models for evaluating ecosystem sustainability (desired conditions) and decision models to identify priority areas for integrated landscape restoration (objectives). The study area for our analysis spans 1,057 subwatersheds within western Montana and northern Idaho. Results of our study suggest that knowledge-based systems such as EMDS are well suited to both strategic and tactical planning and that the following points merit consideration in future National Forest (and other land management) planning efforts: 1) Logic models provide a consistent, transparent, and reproducible method for evaluating broad propositions about ecosystem sustainability such as: are watershed integrity, ecosystem and species diversity, social opportunities, and economic integrity in good shape across a planning area? The ability to evaluate such propositions in a formal logic framework also allows users the opportunity to evaluate statistical changes in outcomes over time, which could be very useful for regional and national reporting purposes and for addressing litigation; 2) The use of logic and decision models in strategic and tactical Forest planning provides a repository for expert knowledge (corporate memory) that is critical to the evaluation and management of ecosystem sustainability over time. This is especially true for the USFS and other federal resource agencies, which are

  15. Functional connectivity decreases in autism in emotion, self, and face circuits identified by Knowledge-based Enrichment Analysis.

    PubMed

    Cheng, Wei; Rolls, Edmund T; Zhang, Jie; Sheng, Wenbo; Ma, Liang; Wan, Lin; Luo, Qiang; Feng, Jianfeng

    2017-03-01

    A powerful new method is described called Knowledge based functional connectivity Enrichment Analysis (KEA) for interpreting resting state functional connectivity, using circuits that are functionally identified using search terms with the Neurosynth database. The method derives its power by focusing on neural circuits, sets of brain regions that share a common biological function, instead of trying to interpret single functional connectivity links. This provides a novel way of investigating how task- or function-related networks have resting state functional connectivity differences in different psychiatric states, provides a new way to bridge the gap between task and resting-state functional networks, and potentially helps to identify brain networks that might be treated. The method was applied to interpreting functional connectivity differences in autism. Functional connectivity decreases at the network circuit level in 394 patients with autism compared with 473 controls were found in networks involving the orbitofrontal cortex, anterior cingulate cortex, middle temporal gyrus cortex, and the precuneus, in networks that are implicated in the sense of self, face processing, and theory of mind. The decreases were correlated with symptom severity.

  16. ELECTRICA: ELEctronic knowledge base for Clinical care, Teaching and Research In Child Abuse.

    PubMed

    Offiah, Amaka; Hume, Jessica; Bamsey, Ian; Jenkinson, Howard; Lings, Brian

    2011-11-01

    Child abuse is a highly significant public health issue with 4-16% of children being physically abused. The diagnosis is sensitive and challenging, with many radiologists dissatisfied with current levels of training and support. The literature shows a lack of prospective scientific research in this complex field. An ELEctronic knowledge base for Clinical care, Teaching and Research In Child Abuse (ELECTRICA) should solve many current problems. ELECTRICA will be populated with clinical information, radiographs and radiographic findings in children younger than 3 years of age presenting with injury (accidental or suspected abuse), to form a unique resource. This web-based tool will unify the investigative protocol in suspected abuse and support training and allow multicentre national and international collaborative research and provide robust evidence to support the legal process.

  17. Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts.

    PubMed

    Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam; Zurek, Tomasz

    2015-01-01

    Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains.

  18. Fast QRS Detection with an Optimized Knowledge-Based Method: Evaluation on 11 Standard ECG Databases

    PubMed Central

    Elgendi, Mohamed

    2013-01-01

    The current state-of-the-art in automatic QRS detection methods show high robustness and almost negligible error rates. In return, the methods are usually based on machine-learning approaches that require sufficient computational resources. However, simple-fast methods can also achieve high detection rates. There is a need to develop numerically efficient algorithms to accommodate the new trend towards battery-driven ECG devices and to analyze long-term recorded signals in a time-efficient manner. A typical QRS detection method has been reduced to a basic approach consisting of two moving averages that are calibrated by a knowledge base using only two parameters. In contrast to high-accuracy methods, the proposed method can be easily implemented in a digital filter design. PMID:24066054

  19. Development the conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation

    NASA Astrophysics Data System (ADS)

    Milana; Khan, M. K.; Munive, J. E.

    2014-07-01

    The importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. A knowledge-based approach to arterial stiffness estimation using the digital volume pulse.

    PubMed

    Jang, Dae-Geun; Farooq, Umar; Park, Seung-Hun; Goh, Choong-Won; Hahn, Minsoo

    2012-08-01

    We have developed a knowledge based approach for arterial stiffness estimation. The proposed new approach reliably estimates arterial stiffness based on the analysis of age and heart rate normalized reflected wave arrival time. The proposed new approach reduces cost, space, technical expertise, specialized equipment, complexity, and increases the usability compared to recently researched noninvasive arterial stiffness estimators. The proposed method consists of two main stages: pulse feature extraction and linear regression analysis. The new approach extracts the pulse features and establishes a linear prediction equation. On evaluating proposed methodology with pulse wave velocity (PWV) based arterial stiffness estimators, the proposed methodology offered the error rate of 8.36% for men and 9.52% for women, respectively. With such low error rates and increased benefits, the proposed approach could be usefully applied as low cost and effective solution for ubiquitous and home healthcare environments.

  5. 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.

  6. Multi-frame knowledge based text enhancement for mobile phone captured videos

    NASA Astrophysics Data System (ADS)

    Ozarslan, Suleyman; Eren, P. Erhan

    2014-02-01

    In this study, we explore automated text recognition and enhancement using mobile phone captured videos of store receipts. We propose a method which includes Optical Character Resolution (OCR) enhanced by our proposed Row Based Multiple Frame Integration (RB-MFI), and Knowledge Based Correction (KBC) algorithms. In this method, first, the trained OCR engine is used for recognition; then, the RB-MFI algorithm is applied to the output of the OCR. The RB-MFI algorithm determines and combines the most accurate rows of the text outputs extracted by using OCR from multiple frames of the video. After RB-MFI, KBC algorithm is applied to these rows to correct erroneous characters. Results of the experiments show that the proposed video-based approach which includes the RB-MFI and the KBC algorithm increases the word character recognition rate to 95%, and the character recognition rate to 98%.

  7. 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.

  8. Knowledge-based load leveling and task allocation in human-machine systems

    NASA Technical Reports Server (NTRS)

    Chignell, M. H.; Hancock, P. A.

    1986-01-01

    Conventional human-machine systems use task allocation policies which are based on the premise of a flexible human operator. This individual is most often required to compensate for and augment the capabilities of the machine. The development of artificial intelligence and improved technologies have allowed for a wider range of task allocation strategies. In response to these issues a Knowledge Based Adaptive Mechanism (KBAM) is proposed for assigning tasks to human and machine in real time, using a load leveling policy. This mechanism employs an online workload assessment and compensation system which is responsive to variations in load through an intelligent interface. This interface consists of a loading strategy reasoner which has access to information about the current status of the human-machine system as well as a database of admissible human/machine loading strategies. Difficulties standing in the way of successful implementation of the load leveling strategy are examined.

  9. Enriching semantic knowledge bases for opinion mining in big data applications.

    PubMed

    Weichselbraun, A; Gindl, S; Scharl, A

    2014-10-01

    This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a domain-specific training corpus, and (iii) ground this contextual information to structured background knowledge sources such as ConceptNet and WordNet. A quantitative evaluation shows a significant improvement when using an enriched version of SenticNet for polarity classification. Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the strengths and weaknesses of the concept grounding, and on the quality of the enrichment process.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. A knowledge-based approach to identification and adaptation in dynamical systems control

    NASA Technical Reports Server (NTRS)

    Glass, B. J.; Wong, C. M.

    1988-01-01

    Artificial intelligence techniques are applied to the problems of model form and parameter identification of large-scale dynamic systems. The object-oriented knowledge representation is discussed in the context of causal modeling and qualitative reasoning. Structured sets of rules are used for implementing qualitative component simulations, for catching qualitative discrepancies and quantitative bound violations, and for making reconfiguration and control decisions that affect the physical system. These decisions are executed by backward-chaining through a knowledge base of control action tasks. This approach was implemented for two examples: a triple quadrupole mass spectrometer and a two-phase thermal testbed. Results of tests with both of these systems demonstrate that the software replicates some or most of the functionality of a human operator, thereby reducing the need for a human-in-the-loop in the lower levels of control of these complex systems.

  15. 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.

  16. A fuzzy knowledge-based decision support system for groundwater pollution risk evaluation.

    PubMed

    Uricchio, Vito F; Giordano, Raffaele; Lopez, Nicola

    2004-11-01

    In this paper we propose a decision support system that can provide information on the environmental impact of anthropic activities by examining their effects on groundwater quality. We use the combined value of both intrinsic vulnerability of a specific local aquifer, obtained by implementing a parametric managerial model (SINTACS), and a degree of hazard value, which takes into account specific human activities. Incomplete information is notoriously common in environmental planning. To overcome this deficiency we apply an algorithmic and a qualitative approach, based on expert judgment incorporated into the system's knowledge base. The decision support system takes into account the uncertainty of the environmental domain by using fuzzy logic and evaluates the reliability of the results according to information availability.

  17. 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

  18. 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.

  19. ADEpedia: a scalable and standardized knowledge base of Adverse Drug Events using semantic web technology.

    PubMed

    Jiang, Guoqian; Solbrig, Harold R; Chute, Christopher G

    2011-01-01

    A source of semantically coded Adverse Drug Event (ADE) data can be useful for identifying common phenotypes related to ADEs. We proposed a comprehensive framework for building a standardized ADE knowledge base (called ADEpedia) through combining ontology-based approach with semantic web technology. The framework comprises four primary modules: 1) an XML2RDF transformation module; 2) a data normalization module based on NCBO Open Biomedical Annotator; 3) a RDF store based persistence module; and 4) a front-end module based on a Semantic Wiki for the review and curation. A prototype is successfully implemented to demonstrate the capability of the system to integrate multiple drug data and ontology resources and open web services for the ADE data standardization. A preliminary evaluation is performed to demonstrate the usefulness of the system, including the performance of the NCBO annotator. In conclusion, the semantic web technology provides a highly scalable framework for ADE data source integration and standard query service.

  20. 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.

  1. Framing a Knowledge Base for a Legal Expert System Dealing with Indeterminate Concepts

    PubMed Central

    Araszkiewicz, Michał; Łopatkiewicz, Agata; Zienkiewicz, Adam; Zurek, Tomasz

    2015-01-01

    Despite decades of development of formal tools for modelling legal knowledge and reasoning, the creation of a fully fledged legal decision support system remains challenging. Among those challenges, such system requires an enormous amount of commonsense knowledge to derive legal expertise. This paper describes the development of a negotiation decision support system (the Parenting Plan Support System or PPSS) to support parents in drafting an agreement (the parenting plan) for the exercise of parental custody of minor children after a divorce is granted. The main objective here is to discuss problems of framing an intuitively appealing and computationally efficient knowledge base that can adequately represent the indeterminate legal concept of the well-being of the child in the context of continental legal culture and of Polish law in particular. In addition to commonsense reasoning, interpretation of such a concept demands both legal expertise and significant professional knowledge from other domains. PMID:26495435

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. ADAPT: A knowledge-based synthesis tool for digital signal processing system design

    SciTech Connect

    Cooley, E.S.

    1988-01-01

    A computer aided synthesis tool for expansion, compression, and filtration of digital images is described. ADAPT, the Autonomous Digital Array Programming Tool, uses an extensive design knowledge base to synthesize a digital signal processing (DSP) system. Input to ADAPT can be either a behavioral description in English, or a block level specification via Petri Nets. The output from ADAPT comprises code to implement the DSP system on an array of processors. ADAPT is constructed using C, Prolog, and X Windows on a SUN 3/280 workstation. ADAPT knowledge encompasses DSP component information and the design algorithms and heuristics of a competent DSP designer. The knowledge is used to form queries for design capture, to generate design constraints from the user's responses, and to examine the design constraints. These constraints direct the search for possible DSP components and target architectures. Constraints are also used for partitioning the target systems into less complex subsystems. The subsystems correspond to architectural building blocks of the DSP design. These subsystems inherit design constraints and DSP characteristics from their parent blocks. Thus, a DSP subsystem or parent block, as designed by ADAPT, must meet the user's design constraints. Design solutions are sought by searching the Components section of the design knowledge base. Component behavior which matches or is similar to that required by the DSP subsystems is sought. Each match, which corresponds to a design alternative, is evaluated in terms of its behavior. When a design is sufficiently close to the behavior required by the user, detailed mathematical simulations may be performed to accurately determine exact behavior.

  7. WE-F-BRB-00: New Developments in Knowledge-Based Treatment Planning and Automation

    SciTech Connect

    2015-06-15

    Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

  8. 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.

  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. Data Collection and Integration in Support of the NNSA Knowledge Base

    NASA Astrophysics Data System (ADS)

    Stead, R. J.; Young, C.

    2006-05-01

    The goal of the NNSA Ground-based Nuclear Explosion Research and Engineering program (GNEM R&E)is to develop, demonstrate, and deliver advanced technologies and systems to operational monitoring agencies to support ground-based detection, location, and identification of nuclear explosions. A major component of this is Earth information. This Earth information is embedded in a custom-designed data storage and access system known as the NNSA knowledge base (KB). The GNEM research conducted at the national laboratories to populate the KB requires collection and integration of a remarkably large and diverse collection of geophysical data to develop the types of products needed to improve monitoring capability. The size and diversity of these data present substantial technical challenges to achieve complete, correct, consistent, useful, and accessible information. The bulk of these data are seismic, but there are also hydroacoustic data and a growing volume of infrasound data. The primary categories of data are bulletins (event locations and the supporting detection information), waveforms, and ground-truth event information (GT). These data are processed by the labs to produce the higher-level engineering products (e.g. travel time correction surfaces) that are needed for operational monitoring, but the basic data must also be included in the KB to fully test and verify the operational products. Without the supporting data and metadata capturing the processing details, the operational engineering products cannot be validated and thus will not be used for operations. Over the past several years the NNSA labs have integrated and delivered several versions of the Knowledge Base and in the process we have developed and refined a substantial foundation of software, structures, and procedures to assure high-quality integration of diverse data sets. Software advances include generalized database interfaces (such as dbtoolbox) and generalized QA/QC software. Structural

  11. Strategic Plan for Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

    SciTech Connect

    Rich Johnson; Kimberlyn C. Mousseau; Hyung Lee

    2011-09-01

    NE-KAMS knowledge base will assist computational analysts, physics model developers, experimentalists, nuclear reactor designers, and federal regulators by: (1) Establishing accepted standards, requirements and best practices for V&V and UQ of computational models and simulations, (2) Establishing accepted standards and procedures for qualifying and classifying experimental and numerical benchmark data, (3) Providing readily accessible databases for nuclear energy related experimental and numerical benchmark data that can be used in V&V assessments and computational methods development, (4) Providing a searchable knowledge base of information, documents and data on V&V and UQ, and (5) Providing web-enabled applications, tools and utilities for V&V and UQ activities, data assessment and processing, and information and data searches. From its inception, NE-KAMS will directly support nuclear energy research, development and demonstration programs within the U.S. Department of Energy (DOE), including the Consortium for Advanced Simulation of Light Water Reactors (CASL), the Nuclear Energy Advanced Modeling and Simulation (NEAMS), the Light Water Reactor Sustainability (LWRS), the Small Modular Reactors (SMR), and the Next Generation Nuclear Power Plant (NGNP) programs. These programs all involve computational modeling and simulation (M&S) of nuclear reactor systems, components and processes, and it is envisioned that NE-KAMS will help to coordinate and facilitate collaboration and sharing of resources and expertise for V&V and UQ across these programs. In addition, from the outset, NE-KAMS will support the use of computational M&S in the nuclear industry by developing guidelines and recommended practices aimed at quantifying the uncertainty and assessing the applicability of existing analysis models and methods. The NE-KAMS effort will initially focus on supporting the use of computational fluid dynamics (CFD) and thermal hydraulics (T/H) analysis for M&S of nuclear

  12. A knowledge-based design framework for airplane conceptual and preliminary design

    NASA Astrophysics Data System (ADS)

    Anemaat, Wilhelmus A. J.

    The goal of work described herein is to develop the second generation of Advanced Aircraft Analysis (AAA) into an object-oriented structure which can be used in different environments. One such environment is the third generation of AAA with its own user interface, the other environment with the same AAA methods (i.e. the knowledge) is the AAA-AML program. AAA-AML automates the initial airplane design process using current AAA methods in combination with AMRaven methodologies for dependency tracking and knowledge management, using the TechnoSoft Adaptive Modeling Language (AML). This will lead to the following benefits: (1) Reduced design time: computer aided design methods can reduce design and development time and replace tedious hand calculations. (2) Better product through improved design: more alternative designs can be evaluated in the same time span, which can lead to improved quality. (3) Reduced design cost: due to less training and less calculation errors substantial savings in design time and related cost can be obtained. (4) Improved Efficiency: the design engineer can avoid technically correct but irrelevant calculations on incomplete or out of sync information, particularly if the process enables robust geometry earlier. Although numerous advancements in knowledge based design have been developed for detailed design, currently no such integrated knowledge based conceptual and preliminary airplane design system exists. The third generation AAA methods are tested over a ten year period on many different airplane designs. Using AAA methods will demonstrate significant time savings. The AAA-AML system will be exercised and tested using 27 existing airplanes ranging from single engine propeller, business jets, airliners, UAV's to fighters. Data for the varied sizing methods will be compared with AAA results, to validate these methods. One new design, a Light Sport Aircraft (LSA), will be developed as an exercise to use the tool for designing a new airplane

  13. Knowledge based functions for routine use at a German university hospital setting: the issue of fine tuning.

    PubMed Central

    Bürkle, T.; Prokosch, H. U.; Hussak, G.; Dudeck, J.

    1997-01-01

    In this paper we present the introduction of knowledge based functions into clinical routine at Giessen University Hospital. For this purpose a therapy planning module at the medical intensive care unit has been extensively redesigned in order to support the structured documentation of drug prescriptions. After introduction of this new HIS component in January 1996 research has been initiated to establish a basic drug therapy knowledge base. The main components of a knowledge based system have been fully incorporated into the hospital information system WING and are in routine use since December 1996. During a pre-production phase warnings of reminder functions were logged and reviewed by an interdisciplinary team in order to adapt the system to the actual clinical environment. The paper describes experiences during this fine tuning and adaptation process which was necessary to bring a small set of knowledge modules into clinical routine. PMID:9357589

  14. 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.

  15. On the optimal design of molecular sensing interfaces with lipid bilayer assemblies - A knowledge based approach

    NASA Astrophysics Data System (ADS)

    Siontorou, Christina G.

    2012-12-01

    Biosensors are analytic devices that incorporate a biochemical recognition system (biological, biologicalderived or biomimic: enzyme, antibody, DNA, receptor, etc.) in close contact with a physicochemical transducer (electrochemical, optical, piezoelectric, conductimetric, etc.) that converts the biochemical information, produced by the specific biological recognition reaction (analyte-biomolecule binding), into a chemical or physical output signal, related to the concentration of the analyte in the measuring sample. The biosensing concept is based on natural chemoreception mechanisms, which are feasible over/within/by means of a biological membrane, i.e., a structured lipid bilayer, incorporating or attached to proteinaceous moieties that regulate molecular recognition events which trigger ion flux changes (facilitated or passive) through the bilayer. The creation of functional structures that are similar to natural signal transduction systems, correlating and interrelating compatibly and successfully the physicochemical transducer with the lipid film that is self-assembled on its surface while embedding the reconstituted biological recognition system, and at the same time manage to satisfy the basic conditions for measuring device development (simplicity, easy handling, ease of fabrication) is far from trivial. The aim of the present work is to present a methodological framework for designing such molecular sensing interfaces, functioning within a knowledge-based system built on an ontological platform for supplying sub-systems options, compatibilities, and optimization parameters.

  16. Knowledge management: An abstraction of knowledge base and database management systems

    NASA Technical Reports Server (NTRS)

    Riedesel, Joel D.

    1990-01-01

    Artificial intelligence application requirements demand powerful representation capabilities as well as efficiency for real-time domains. Many tools exist, the most prevalent being expert systems tools such as ART, KEE, OPS5, and CLIPS. Other tools just emerging from the research environment are truth maintenance systems for representing non-monotonic knowledge, constraint systems, object oriented programming, and qualitative reasoning. Unfortunately, as many knowledge engineers have experienced, simply applying a tool to an application requires a large amount of effort to bend the application to fit. Much work goes into supporting work to make the tool integrate effectively. A Knowledge Management Design System (KNOMAD), is described which is a collection of tools built in layers. The layered architecture provides two major benefits; the ability to flexibly apply only those tools that are necessary for an application, and the ability to keep overhead, and thus inefficiency, to a minimum. KNOMAD is designed to manage many knowledge bases in a distributed environment providing maximum flexibility and expressivity to the knowledge engineer while also providing support for efficiency.

  17. 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.

  18. Design consideration in constructing high performance embedded Knowledge-Based Systems (KBS)

    NASA Technical Reports Server (NTRS)

    Dalton, Shelly D.; Daley, Philip C.

    1988-01-01

    As the hardware trends for artificial intelligence (AI) involve more and more complexity, the process of optimizing the computer system design for a particular problem will also increase in complexity. Space applications of knowledge based systems (KBS) will often require an ability to perform both numerically intensive vector computations and real time symbolic computations. Although parallel machines can theoretically achieve the speeds necessary for most of these problems, if the application itself is not highly parallel, the machine's power cannot be utilized. A scheme is presented which will provide the computer systems engineer with a tool for analyzing machines with various configurations of array, symbolic, scaler, and multiprocessors. High speed networks and interconnections make customized, distributed, intelligent systems feasible for the application of AI in space. The method presented can be used to optimize such AI system configurations and to make comparisons between existing computer systems. It is an open question whether or not, for a given mission requirement, a suitable computer system design can be constructed for any amount of money.

  19. The ins and outs of eukaryotic viruses: Knowledge base and ontology of a viral infection

    PubMed Central

    Hulo, Chantal; Masson, Patrick; de Castro, Edouard; Auchincloss, Andrea H.; Foulger, Rebecca; Poux, Sylvain; Lomax, Jane; Bougueleret, Lydie; Xenarios, Ioannis

    2017-01-01

    Viruses are genetically diverse, infect a wide range of tissues and host cells and follow unique processes for replicating themselves. All these processes were investigated and indexed in ViralZone knowledge base. To facilitate standardizing data, a simple ontology of viral life-cycle terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address unique viral replication cycle processes, and existing terminology was modified and adapted. The virus life-cycle is classically described by schematic pictures. Using this ontology, it can be represented by a combination of successive terms: “entry”, “latency”, “transcription”, “replication” and “exit”. Each of these parts is broken down into discrete steps. For example Zika virus “entry” is broken down in successive steps: “Attachment”, “Apoptotic mimicry”, “Viral endocytosis/ macropinocytosis”, “Fusion with host endosomal membrane”, “Viral factory”. To demonstrate the utility of a standard ontology for virus biology, this work was completed by annotating virus data in the ViralZone, UniProtKB and Gene Ontology databases. PMID:28207819

  20. 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.

  1. Adversarial intent modeling using embedded simulation and temporal Bayesian knowledge bases

    NASA Astrophysics Data System (ADS)

    Pioch, Nicholas J.; Melhuish, James; Seidel, Andy; Santos, Eugene, Jr.; Li, Deqing; Gorniak, Mark

    2009-05-01

    To foster shared battlespace awareness among air strategy planners, BAE Systems has developed Commander's Model Integration and Simulation Toolkit (CMIST), an Integrated Development Environment for authoring, integration, validation, and debugging of models relating multiple domains, including political, military, social, economic and information. CMIST provides a unified graphical user interface for such systems of systems modeling, spanning several disparate modeling paradigms. Here, we briefly review the CMIST architecture and then compare modeling results using two approaches to intent modeling. The first uses reactive agents with simplified behavior models that apply rule-based triggers to initiate actions based solely on observations of the external world at the current time in the simulation. The second method models proactive agents running an embedded CMIST simulation representing their projection of how events may unfold in the future in order to take early preventative action. Finally, we discuss a recent extension to CMIST that incorporates Temporal Bayesian Knowledge Bases for more sophisticated models of adversarial intent that are capable of inferring goals and future actions given evidence of current actions at particular times.

  2. Prior-knowledge-based spectral mixture analysis for impervious surface mapping

    SciTech Connect

    Zhang, Jinshui; He, Chunyang; Zhou, Yuyu; Zhu, Shuang; Shuai, Guanyuan

    2014-01-03

    In this study, we developed a prior-knowledge-based spectral mixture analysis (PKSMA) to map impervious surfaces by using endmembers derived separately for high- and low-density urban regions. First, an urban area was categorized into high- and low-density urban areas, using a multi-step classification method. Next, in high-density urban areas that were assumed to have only vegetation and impervious surfaces (ISs), the Vegetation-Impervious model (V-I) was used in a spectral mixture analysis (SMA) with three endmembers: vegetation, high albedo, and low albedo. In low-density urban areas, the Vegetation-Impervious-Soil model (V-I-S) was used in an SMA analysis with four endmembers: high albedo, low albedo, soil, and vegetation. The fraction of IS with high and low albedo in each pixel was combined to produce the final IS map. The root mean-square error (RMSE) of the IS map produced using PKSMA was about 11.0%, compared to 14.52% using four-endmember SMA. Particularly in high-density urban areas, PKSMA (RMSE = 6.47%) showed better performance than four-endmember (15.91%). The results indicate that PKSMA can improve IS mapping compared to traditional SMA by using appropriately selected endmembers and is particularly strong in high-density urban areas.

  3. 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.

  4. 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.

  5. Sedentary Behavior and Health: Broadening the Knowledge Base and Strengthening the Science.

    PubMed

    Hadgraft, Nyssa; Owen, Neville

    2017-04-07

    We provide an overview of a recently published, edited book in a rapidly emerging field of research, policy, and practice for physical activity: Sedentary Behavior and Health. In this commentary, we highlight the broad perspectives provided in the 27 chapters of Sedentary Behavior and Health and suggest a research strategy to move the field forward-not only with scientific rigor, but also with breadth of scholarship. The book's chapters provide an overview of the background to and contexts for sedentary behavior and health. They then highlight the importance of understanding health consequences and underlying mechanisms; introduce key measurement technology and analytic strategies; consider sedentary behavior in subpopulations; describe conceptual models and theories to guide sedentary behavior interventions; and explain what is known about interventions in different settings. Considering the breadth of perspectives brought to bear on the field and the plethora of opportunities for research, policy, and practice, we suggest 3 elements of an interdisciplinary research strategy drawing upon the primary knowledge bases of physical activity and health: through the experimental methods of exercise science, through the observational tools of epidemiology, and through the conceptual approaches and methods of behavioral science. A better understanding of the health consequences of sedentary behavior and how they may be influenced can be encompassed by 3 key questions: What changes are needed to most effectively influence sedentary behaviors? What elements of sedentary behavior should be changed to improve health outcomes? What are the feasibility of and the benefits from changing sedentary behavior?

  6. 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.

  7. 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.

  8. VenomKB, a new knowledge base for facilitating the validation of putative venom therapies

    PubMed Central

    Romano, Joseph D.; Tatonetti, Nicholas P.

    2015-01-01

    Animal venoms have been used for therapeutic purposes since the dawn of recorded history. Only a small fraction, however, have been tested for pharmaceutical utility. Modern computational methods enable the systematic exploration of novel therapeutic uses for venom compounds. Unfortunately, there is currently no comprehensive resource describing the clinical effects of venoms to support this computational analysis. We present VenomKB, a new publicly accessible knowledge base and website that aims to act as a repository for emerging and putative venom therapies. Presently, it consists of three database tables: (1) Manually curated records of putative venom therapies supported by scientific literature, (2) automatically parsed MEDLINE articles describing compounds that may be venom derived, and their effects on the human body, and (3) automatically retrieved records from the new Semantic Medline resource that describe the effects of venom compounds on mammalian anatomy. Data from VenomKB may be selectively retrieved in a variety of popular data formats, are open-source, and will be continually updated as venom therapies become better understood. PMID:26601758

  9. 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.

  10. Advanced piloted aircraft flight control system design methodology. Volume 1: Knowledge base

    NASA Technical Reports Server (NTRS)

    Mcruer, Duane T.; Myers, Thomas T.

    1988-01-01

    The development of a comprehensive and electric methodology for conceptual and preliminary design of flight control systems is presented and illustrated. The methodology is focused on the design stages starting with the layout of system requirements and ending when some viable competing system architectures (feedback control structures) are defined. The approach is centered on the human pilot and the aircraft as both the sources of, and the keys to the solution of, many flight control problems. The methodology relies heavily on computational procedures which are highly interactive with the design engineer. To maximize effectiveness, these techniques, as selected and modified to be used together in the methodology, form a cadre of computational tools specifically tailored for integrated flight control system preliminary design purposes. While theory and associated computational means are an important aspect of the design methodology, the lore, knowledge and experience elements, which guide and govern applications are critical features. This material is presented as summary tables, outlines, recipes, empirical data, lists, etc., which encapsulate a great deal of expert knowledge. Much of this is presented in topical knowledge summaries which are attached as Supplements. The composite of the supplements and the main body elements constitutes a first cut at a a Mark 1 Knowledge Base for manned-aircraft flight control.

  11. The Developmental Brain Disorders Database (DBDB): a curated neurogenetics knowledge base with clinical and research applications.

    PubMed

    Mirzaa, Ghayda M; Millen, Kathleen J; Barkovich, A James; Dobyns, William B; Paciorkowski, Alex R

    2014-06-01

    The number of single genes associated with neurodevelopmental disorders has increased dramatically over the past decade. The identification of causative genes for these disorders is important to clinical outcome as it allows for accurate assessment of prognosis, genetic counseling, delineation of natural history, inclusion in clinical trials, and in some cases determines therapy. Clinicians face the challenge of correctly identifying neurodevelopmental phenotypes, recognizing syndromes, and prioritizing the best candidate genes for testing. However, there is no central repository of definitions for many phenotypes, leading to errors of diagnosis. Additionally, there is no system of levels of evidence linking genes to phenotypes, making it difficult for clinicians to know which genes are most strongly associated with a given condition. We have developed the Developmental Brain Disorders Database (DBDB: https://www.dbdb.urmc.rochester.edu/home), a publicly available, online-curated repository of genes, phenotypes, and syndromes associated with neurodevelopmental disorders. DBDB contains the first referenced ontology of developmental brain phenotypes, and uses a novel system of levels of evidence for gene-phenotype associations. It is intended to assist clinicians in arriving at the correct diagnosis, select the most appropriate genetic test for that phenotype, and improve the care of patients with developmental brain disorders. For researchers interested in the discovery of novel genes for developmental brain disorders, DBDB provides a well-curated source of important genes against which research sequencing results can be compared. Finally, DBDB allows novel observations about the landscape of the neurogenetics knowledge base.

  12. Soybean Knowledge Base (SoyKB): a Web Resource for Soybean Translational Genomics

    SciTech Connect

    Joshi, Trupti; Patil, Kapil; Fitzpatrick, Michael R.; Franklin, Levi D.; Yao, Qiuming; Cook, Jeffrey R.; Wang, Zhem; Libault, Marc; Brechenmacher, Laurent; Valliyodan, Babu; Wu, Xiaolei; Cheng, Jianlin; Stacey, Gary; Nguyen, Henry T.; Xu, Dong

    2012-01-17

    Background: Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for soybean translational genomics. SoyKB is designed to handle the management and integration of soybean genomics, transcriptomics, proteomics and metabolomics data along with annotation of gene function and biological pathway. It contains information on four entities, namely genes, microRNAs, metabolites and single nucleotide polymorphisms (SNPs). Methods: SoyKB has many useful tools such as Affymetrix probe ID search, gene family search, multiple gene/ metabolite search supporting co-expression analysis, and protein 3D structure viewer as well as download and upload capacity for experimental data and annotations. It has four tiers of registration, which control different levels of access to public and private data. It allows users of certain levels to share their expertise by adding comments to the data. It has a user-friendly web interface together with genome browser and pathway viewer, which display data in an intuitive manner to the soybean researchers, producers and consumers. Conclusions: SoyKB addresses the increasing need of the soybean research community to have a one-stop-shop functional and translational omics web resource for information retrieval and analysis in a user-friendly way. SoyKB can be publicly accessed at http://soykb.org/.

  13. Knowledge based optimum feature selection for lung nodule diagnosis on thin section thoracic CT

    NASA Astrophysics Data System (ADS)

    Samala, Ravi K.; Moreno, Wilfrido A.; Song, Danshong; You, Yuncheng; Qian, Wei

    2009-02-01

    An approach for optimum selection of lung nodule image characteristics in the feature domain is presented. This was applied to the classification module in the CAD system with data that was extracted from 42 ROI's of the 38 cases with an effective diameter of 3 to 8.5mm. 11 fundamental features were computed on the basis of dimensionality and image characteristics. The relation between the represented features of the 4 radiologists and the computed features was mapped using non-parametric correlation coefficients, multiple regression analysis and principle component analysis (PCA). Malignant and benign modules were classified based on the artificial neural network (ANN) to confirm the hypothesis from the mapping analysis. From the computed features and the radiologist's annotations, correlation coefficients between 0.2693 and 0.5178 were obtained. A combination of analyses namely regression, PCA, correlation and ANN were used to select optimum features. This resulted in F-test values of 0.821 and 0.643 for malignant and benign nodules respectively. The study of the relationship between the features and the weightage towards each of the representative classes resulted in optimum feature input for a CAD system. A composite analysis derived from correlation, PCA, multiple regression and the classification algorithm, collectively termed as the knowledge base, was used arrive at an "optimum" set of lung nodule features.

  14. 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.

  15. Fuzzy Linguistic Knowledge Based Behavior Extraction for Building Energy Management Systems

    SciTech Connect

    Dumidu Wijayasekara; Milos Manic

    2013-08-01

    Significant portion of world energy production is consumed by building Heating, Ventilation and Air Conditioning (HVAC) units. Thus along with occupant comfort, energy efficiency is also an important factor in HVAC control. Modern buildings use advanced Multiple Input Multiple Output (MIMO) control schemes to realize these goals. However, since the performance of HVAC units is dependent on many criteria including uncertainties in weather, number of occupants, and thermal state, the performance of current state of the art systems are sub-optimal. Furthermore, because of the large number of sensors in buildings, and the high frequency of data collection, large amount of information is available. Therefore, important behavior of buildings that compromise energy efficiency or occupant comfort is difficult to identify. This paper presents an easy to use and understandable framework for identifying such behavior. The presented framework uses human understandable knowledge-base to extract important behavior of buildings and present it to users via a graphical user interface. The presented framework was tested on a building in the Pacific Northwest and was shown to be able to identify important behavior that relates to energy efficiency and occupant comfort.

  16. 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.

  17. 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.

  18. Medication-indication knowledge bases: a systematic review and critical appraisal

    PubMed Central

    Tran, Tran H; Chase, Herbert S; Friedman, Carol

    2015-01-01

    Objective Medication-indication information is a key part of the information needed for providing decision support for and promoting appropriate use of medications. However, this information is not readily available to end users, and a lot of the resources only contain this information in unstructured form (free text). A number of public knowledge bases (KBs) containing structured medication-indication information have been developed over the years, but a direct comparison of these resources has not yet been conducted. Material and Methods We conducted a systematic review of the literature to identify all medication-indication KBs and critically appraised these resources in terms of their scope as well as their support for complex indication information. Results We identified 7 KBs containing medication-indication data. They notably differed from each other in terms of their scope, coverage for on- or off-label indications, source of information, and choice of terminologies for representing the knowledge. The majority of KBs had issues with granularity of the indications as well as with representing duration of therapy, primary choice of treatment, and comedications or comorbidities. Discussion and Conclusion This is the first study directly comparing public KBs of medication indications. We identified several gaps in the existing resources, which can motivate future research. PMID:26335981

  19. 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.

  20. 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).

  1. RegenBase: a knowledge base of spinal cord injury biology for translational research

    PubMed Central

    Callahan, Alison; Abeyruwan, Saminda W.; Al-Ali, Hassan; Sakurai, Kunie; Ferguson, Adam R.; Popovich, Phillip G.; Shah, Nigam H.; Visser, Ubbo; Bixby, John L.; Lemmon, Vance P.

    2016-01-01

    Spinal cord injury (SCI) research is a data-rich field that aims to identify the biological mechanisms resulting in loss of function and mobility after SCI, as well as develop therapies that promote recovery after injury. SCI experimental methods, data and domain knowledge are locked in the largely unstructured text of scientific publications, making large scale integration with existing bioinformatics resources and subsequent analysis infeasible. The lack of standard reporting for experiment variables and results also makes experiment replicability a significant challenge. To address these challenges, we have developed RegenBase, a knowledge base of SCI biology. RegenBase integrates curated literature-sourced facts and experimental details, raw assay data profiling the effect of compounds on enzyme activity and cell growth, and structured SCI domain knowledge in the form of the first ontology for SCI, using Semantic Web representation languages and frameworks. RegenBase uses consistent identifier schemes and data representations that enable automated linking among RegenBase statements and also to other biological databases and electronic resources. By querying RegenBase, we have identified novel biological hypotheses linking the effects of perturbagens to observed behavioral outcomes after SCI. RegenBase is publicly available for browsing, querying and download. Database URL: http://regenbase.org PMID:27055827

  2. Advancing User Supports with a Structured How-To Knowledge Base for Earth Science Data

    NASA Technical Reports Server (NTRS)

    Shen, Suhung; Acker, James G.; Lynnes, Christopher S.; Beaty, Tammy; Lighty, Luther; Kempler, Steven J.

    2016-01-01

    It is a challenge to access and process fast growing Earth science data from satellites and numerical models, which may be archived in very different data format and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and/or formats. A type of structured online document, data recipe, were created in beginning 2013 by Goddard Earth Science Data and Information Services Center (GES DISC). A data recipe is the How-To document created by using the fixed template, containing step-by-step instructions with screenshots and examples of accessing and working with real data. The recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant to some recipes. In 2014, the NASA Earth Science Data System Working Group (ESDSWG) for data recipes was established, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group started with inventory and analysis of existing EOSDIS-wide online help documents, and provided recommendations and guidelines and for writing and grouping data recipes. This presentation will overview activities of creating How-To documents at GES DISC and ESDSWG. We encourage feedback and contribution from users for improving the data How-To knowledge base.

  3. NRPS-PKS: a knowledge-based resource for analysis of NRPS/PKS megasynthases.

    PubMed

    Ansari, Mohd Zeeshan; Yadav, Gitanjali; Gokhale, Rajesh S; Mohanty, Debasisa

    2004-07-01

    NRPS-PKS is web-based software for analysing large multi-enzymatic, multi-domain megasynthases that are involved in the biosynthesis of pharmaceutically important natural products such as cyclosporin, rifamycin and erythromycin. NRPS-PKS has been developed based on a comprehensive analysis of the sequence and structural features of several experimentally characterized biosynthetic gene clusters. The results of these analyses have been organized as four integrated searchable databases for elucidating domain organization and substrate specificity of nonribosomal peptide synthetases and three types of polyketide synthases. These databases work as the backend of NRPS-PKS and provide the knowledge base for predicting domain organization and substrate specificity of uncharacterized NRPS/PKS clusters. Benchmarking on a large set of biosynthetic gene clusters has demonstrated that, apart from correct identification of NRPS and PKS domains, NRPS-PKS can also predict specificities of adenylation and acyltransferase domains with reasonably high accuracy. These features of NRPS-PKS make it a valuable resource for identification of natural products biosynthesized by NRPS/PKS gene clusters found in newly sequenced genomes. The training and test sets of gene clusters included in NRPS-PKS correlate information on 307 open reading frames, 2223 functional protein domains, 68 starter/extender precursors and their specific recognition motifs, and also the chemical structure of 101 natural products from four different families. NRPS-PKS is a unique resource which provides a user-friendly interface for correlating chemical structures of natural products with the domains and modules in the corresponding nonribosomal peptide synthetases or polyketide synthases. It also provides guidelines for domain/module swapping as well as site-directed mutagenesis experiments to engineer biosynthesis of novel natural products. NRPS-PKS can be accessed at http://www.nii.res.in/nrps-pks.html.

  4. Knowledge based word-concept model estimation and refinement for biomedical text mining.

    PubMed

    Jimeno Yepes, Antonio; Berlanga, Rafael

    2015-02-01

    Text mining of scientific literature has been essential for setting up large public biomedical databases, which are being widely used by the research community. In the biomedical domain, the existence of a large number of terminological resources and knowledge bases (KB) has enabled a myriad of machine learning methods for different text mining related tasks. Unfortunately, KBs have not been devised for text mining tasks but for human interpretation, thus performance of KB-based methods is usually lower when compared to supervised machine learning methods. The disadvantage of supervised methods though is they require labeled training data and therefore not useful for large scale biomedical text mining systems. KB-based methods do not have this limitation. In this paper, we describe a novel method to generate word-concept probabilities from a KB, which can serve as a basis for several text mining tasks. This method not only takes into account the underlying patterns within the descriptions contained in the KB but also those in texts available from large unlabeled corpora such as MEDLINE. The parameters of the model have been estimated without training data. Patterns from MEDLINE have been built using MetaMap for entity recognition and related using co-occurrences. The word-concept probabilities were evaluated on the task of word sense disambiguation (WSD). The results showed that our method obtained a higher degree of accuracy than other state-of-the-art approaches when evaluated on the MSH WSD data set. We also evaluated our method on the task of document ranking using MEDLINE citations. These results also showed an increase in performance over existing baseline retrieval approaches.

  5. 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

  6. Establishing an Accepted Skill Set and Knowledge Base for Directors of University and College Intensive English Programs

    ERIC Educational Resources Information Center

    Forbes, Megan Julie

    2012-01-01

    The purpose of this study was to establish an accepted skill set, knowledge base, and overview of personal qualities necessary to be a director of a university or college based, non-proprietary intensive English program (UIEP). This research serves as a means of moving towards meeting three critical needs in the field. This research should inform…

  7. 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,…

  8. Evolving Expert Knowledge Bases: Applications of Crowdsourcing and Serious Gaming to Advance Knowledge Development for Intelligent Tutoring Systems

    ERIC Educational Resources Information Center

    Floryan, Mark

    2013-01-01

    This dissertation presents a novel effort to develop ITS technologies that adapt by observing student behavior. In particular, we define an evolving expert knowledge base (EEKB) that structures a domain's information as a set of nodes and the relationships that exist between those nodes. The structure of this model is not the particularly novel…

  9. Making Sense of Images of Fact and Fiction: A Critical Review of the Knowledge Base for School Leadership in Vietnam

    ERIC Educational Resources Information Center

    Hallinger, Philip; Walker, Allan; Trung, Gian Tu

    2015-01-01

    Purpose: The purpose of this paper is to review both international and domestic (i.e. Vietnamese language) journal articles and graduate theses and dissertations on educational leadership in Vietnam. The review addresses two specific goals: first, to describe and critically assess the nature of the formal knowledge base on principal leadership in…

  10. 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…

  11. Challenges in Mentoring Software Development Projects in the High School: Analysis According to Shulman's Teacher Knowledge Base Model

    ERIC Educational Resources Information Center

    Meerbaum-Salant, Orni; Hazzan, Orit

    2009-01-01

    This paper focuses on challenges in mentoring software development projects in the high school and analyzes difficulties encountered by Computer Science teachers in the mentoring process according to Shulman's Teacher Knowledge Base Model. The main difficulties that emerged from the data analysis belong to the following knowledge sources of…

  12. 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…

  13. Dynamic Interaction: A Measurement Development and Empirical Evaluation of Knowledge Based Systems and Web 2.0 Decision Support Mashups

    ERIC Educational Resources Information Center

    Beemer, Brandon Alan

    2010-01-01

    The research presented in this dissertation focuses on the organizational and consumer need for knowledge based support in unstructured domains, by developing a measurement scale for dynamic interaction. Addressing this need is approached and evaluated from two different perspectives. The first approach is the development of Knowledge Based…

  14. 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.

  15. The Professional Knowledge Base and Practice of Irish Post-Primary Teachers: What Is the Research Evidence Telling Us?

    ERIC Educational Resources Information Center

    Gleeson, Jim

    2012-01-01

    Drawing on relevant research findings, this paper considers the professional knowledge base and practice of Irish post-primary teachers. Important aspects of the Irish context are discussed, including the official neglect of educational research, the prevailing top-down approach to curriculum reform and low levels of investment in teacher…

  16. The Case for a Knowledge Based DoD Software Enterprise: An Exploratory Study Using System Dynamics

    DTIC Science & Technology

    2007-09-01

    September 2007 3 . REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE: The Case for a Knowledge Based DoD Software Enterprise...CLASSIFICATION OF ABSTRACT Unclassified 20. LIMITATION OF ABSTRACT UU NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89) Prescribed by ANSI...8 3 . Integration ..........................................................................................11 4

  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. 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…

  19. The Start-Up, Evolution and Impact of a Research Group in a University Developing Its Knowledge Base

    ERIC Educational Resources Information Center

    Horta, Hugo; Martins, Rui

    2014-01-01

    This article focuses on the understudied role of research groups contributing to develop the knowledge base of developing universities in regions lagging behind in human, financial and scientific resources. We analyse the evolution of a research group that, in less than 10 years, achieved worldwide recognition in the field of microelectronics,…

  20. 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…

  1. Bridging islands of information to establish an integrated knowledge base of drugs and health outcomes of interest.

    PubMed

    Boyce, Richard D; Ryan, Patrick B; Norén, G Niklas; Schuemie, Martijn J; Reich, Christian; Duke, Jon; Tatonetti, Nicholas P; Trifirò, Gianluca; Harpaz, Rave; Overhage, J Marc; Hartzema, Abraham G; Khayter, Mark; Voss, Erica A; Lambert, Christophe G; Huser, Vojtech; Dumontier, Michel

    2014-08-01

    The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to establish an open-source community effort to develop a global knowledge base, one that brings together and standardizes all available information for all drugs and all health outcomes of interest (HOIs) from all electronic sources pertinent to drug safety. To make this vision a reality, we have established a workgroup within the Observational Health Data Sciences and Informatics (OHDSI, http://ohdsi.org) collaborative. The workgroup's mission is to develop an open-source standardized knowledge base for the effects of medical products and an efficient procedure for maintaining and expanding it. The knowledge base will make it simpler for practitioners to access, retrieve, and synthesize evidence so that they can reach a rigorous and accurate assessment of causal relationships between a given drug and HOI. Development of the knowledge base will proceed with the measureable goal of supporting an efficient and thorough evidence-based assessment of the effects of 1,000 active ingredients across 100 HOIs. This non-trivial task will result in a high-quality and generally applicable drug safety knowledge base. It will also yield a reference standard of drug-HOI pairs that will enable more advanced methodological research that empirically evaluates the performance of drug safety analysis methods.

  2. Knowledge-based interpretation of toxoplasmosis serology test results including fuzzy temporal concepts--the ToxoNet system.

    PubMed

    Kopecky, D; Hayde, M; Prusa, A R; Adlassnig, K P

    2001-01-01

    Transplacental transmission of Toxoplasma gondii from an infected, pregnant woman to the unborn that occurs with a probability of about 60 percent [1] results in fetal damage to a degree depending on the gestational age. The computer system ToxoNet processes the results of serological antibody tests having been performed during pregnancy by means of a knowledge base containing medical knowledge on the interpretation of Toxoplasmosis serology tests. By applying this knowledge ToxoNet generates interpretive reports consisting of a diagnostic interpretation and recommendations for therapy and further testing. For that purpose it matches the results of all serological investigations of maternal blood with the content of the knowledge base returning complete textual interpretations for all given findings. The interpretation algorithm derives the stage of maternal infection from these that is used to infer the degree of fetal threat. To consider varying immune responses of particular patients, certain time intervals have to be kept between two subsequent tests in order to guarantee a correct interpretation of the test results. These time intervals are modelled as fuzzy sets, since they allow the formal description of the temporal uncertainties. ToxoNet comprises the knowledge base, an interpretation system, and a program for the creation and modification of the knowledge base. It is available from the World Wide Web by starting a standard browser like the Internet Explorer or the Netscape Navigator. Thus ToxoNet supports the physician in Toxoplasmosis diagnostics and in addition allows to adopt the way of making decisions to the characteristics of the particular laboratory by modifying the underlying knowledge base.

  3. Multi-Case Knowledge-Based IMRT Treatment Planning in Head and Neck Cancer

    NASA Astrophysics Data System (ADS)

    Grzetic, Shelby Mariah

    Head and neck cancer (HNC) IMRT treatment planning is a challenging process that relies heavily on the planner's experience. Previously, we used the single, best match from a library of manually planned cases to semi-automatically generate IMRT plans for a new patient. The current multi-case Knowledge Based Radiation Therapy (MC-KBRT) study utilized different matching cases for each of six individual organs-at-risk (OARs), then combined those six cases to create the new treatment plan. From a database of 103 patient plans created by experienced planners, MC-KBRT plans were created for 40 (17 unilateral and 23 bilateral) HNC "query" patients. For each case, 2D beam's-eye-view images were used to find similar geometric "match" patients separately for each of 6 OARs. Dose distributions for each OAR from the 6 matching cases were combined and then warped to suit the query case's geometry. The dose-volume constraints were used to create the new query treatment plan without the need for human decision-making throughout the IMRT optimization. The optimized MC-KBRT plans were compared against the clinically approved plans and Version 1 (previous KBRT using only one matching case with dose warping) using the dose metrics: mean, median, and maximum (brainstem and cord+5mm) doses. Compared to Version 1, MC-KBRT had no significant reduction of the dose to any of the OARs in either unilateral or bilateral cases. Compared to the manually planned unilateral cases, there was significant reduction of the oral cavity mean/median dose (>2Gy) at the expense of the contralateral parotid. Compared to the manually planned bilateral cases, reduction of dose was significant in the ipsilateral parotid, larynx, and oral cavity (>3Gy mean/median) while maintaining PTV coverage. MC-KBRT planning in head and neck cancer generates IMRT plans with better dose sparing than manually created plans. MC-KBRT using multiple case matches does not show significant dose reduction compared to using a

  4. Strategic Plan for Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

    SciTech Connect

    Kimberlyn C. Mousseau

    2011-10-01

    The Nuclear Energy Computational Fluid Dynamics Advanced Modeling and Simulation (NE-CAMS) system is being developed at the Idaho National Laboratory (INL) in collaboration with Bettis Laboratory, Sandia National Laboratory (SNL), Argonne National Laboratory (ANL), Utah State University (USU), and other interested parties with the objective of developing and implementing a comprehensive and readily accessible data and information management system for computational fluid dynamics (CFD) verification and validation (V&V) in support of nuclear energy systems design and safety analysis. The two key objectives of the NE-CAMS effort are to identify, collect, assess, store and maintain high resolution and high quality experimental data and related expert knowledge (metadata) for use in CFD V&V assessments specific to the nuclear energy field and to establish a working relationship with the U.S. Nuclear Regulatory Commission (NRC) to develop a CFD V&V database, including benchmark cases, that addresses and supports the associated NRC regulations and policies on the use of CFD analysis. In particular, the NE-CAMS system will support the Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, which aims to develop and deploy advanced modeling and simulation methods and computational tools for reliable numerical simulation of nuclear reactor systems for design and safety analysis. Primary NE-CAMS Elements There are four primary elements of the NE-CAMS knowledge base designed to support computer modeling and simulation in the nuclear energy arena as listed below. Element 1. The database will contain experimental data that can be used for CFD validation that is relevant to nuclear reactor and plant processes, particularly those important to the nuclear industry and the NRC. Element 2. Qualification standards for data evaluation and classification will be incorporated and applied such that validation data sets will result in well

  5. Data Recipes: Toward Creating How-To Knowledge Base for Earth Science Data

    NASA Technical Reports Server (NTRS)

    Shen, Suhung; Lynnes, Chris; Acker, James G.; Beaty, Tammy

    2015-01-01

    overview of the data recipe activites at GES DISC and ESDSWG. We are seeking requirements and input from a broader data user community to establish a strong knowledge base for Earth science data research and application implementations.

  6. 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

  7. 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

  8. 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

  9. Mapping the knowledge base for maritime health: 2. a framework for analysis.

    PubMed

    Carter, Tim

    2011-01-01

    The knowledge base for maritime health has a number of constant features that have become apparent over the last 150 years. These can be used to structure an analysis of the current state of knowledge and to identify where there is sound evidence about the nature and scale of risks and about the effectiveness of intervention to reduce harm. It can also show where there are deficiencies in knowledge and point to the ways in which these could be remedied. Past events, as discussed in the first article, also indicate the dynamics of the political, economic and human interactions that are central to improving knowledge and to its application to improve the health of seafarers. The sources of useful knowledge about seafarer's health range from single case reports of an unusual disease to long-term studies of common chronic disease incidence. The most accessible events to record are clinically apparent illness, injury, or cause of death, but active investigative studies may look at risks in the environment, personal risk factors, or pre-clinical phases of disease. Comparisons between subsets of a population are needed to look rigorously at health risks or at the effectiveness of intervention. This is best done if information on the at risk population can be used as the basis for deriving the incidence or prevalence of illness and if the populations compared are as similar as possible in every way, except that being studied. Sometimes large studies in onshore populations can provide information that it is not feasible to collect on seafarers. Information on seafarers' health can be collected in several settings: at sea, on arrival in port, during leave periods, or after retirement. For acute illness and for injury a single setting can provide the basis for estimating risks, but for chronic conditions cases arising in several settings have to be included and the at risk population calculated to enable the incidence to be studied. Knowledge about the health of seafarers can

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Expert validation of the knowledge base for E-CAD - a pre-hospital dispatch triage decision support system.

    PubMed

    Mirza, Muzna; Saini, Devashish; Brown, Todd B; Orthner, Helmuth F; Mazza, Giovanni; Battles, Marcie M

    2007-10-11

    The knowledge base (KB) for E-CAD (Enhanced Computer-Aided Dispatch), a triage decision support system for Emergency Medical Dispatch (EMD) of medical resources in trauma cases, is being evaluated. We aim to achieve expert consensus for validation and refinement of the E-CAD KB using the modified Delphi technique. Evidence-based, expert-validated and refined KB will provide improved EMD practice guidelines and may facilitate acceptance of the E-CAD by state-wide professionals.

  18. 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

  19. 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.

  20. 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…

  1. 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…

  2. A Capstone Wiki Knowledge Base: A Case Study of an Online Tool Designed to Promote Life-Long Learning through Engineering Literature Research

    ERIC Educational Resources Information Center

    Clarke, James B.; Coyle, James R.

    2011-01-01

    This article reports the results of a case study in which an experimental wiki knowledge base was designed, developed, and tested by the Brill Science Library at Miami University for an undergraduate engineering senior capstone project. The wiki knowledge base was created to determine if the science library could enhance the engineering literature…

  3. A System for Discovering Bioengineered Threats by Knowledge Base Driven Mining of Toxin Data

    DTIC Science & Technology

    2004-08-01

    describe in detail the TKB system that we have developed that can be used to identify homologs of toxins. The TKB contains molecular, biological and...information on known as well as potential biological toxins. A detailed description of the new system follows. This section describes our work...the information in a format that is independent of any particular platform and must be globally accessible. 3. Project Details This section describes

  4. 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.

  5. User`s guide for the KBERT 1.0 code: For the knowledge-based estimation of hazards of radioactive material releases from DOE nuclear facilities

    SciTech Connect

    Browitt, D.S.; Washington, K.E.; Powers, D.A.

    1995-07-01

    The possibility of worker exposure to radioactive materials during accidents at nuclear facilities is a principal concern of the DOE. The KBERT software has been developed at Sandia National Laboratories under DOE support to address this issue by assisting in the estimation of risks posed by accidents at chemical and nuclear facilities. KBERT is an acronym for Knowledge-Based system for Estimating hazards of Radioactive material release Transients. The current prototype version of KBERT focuses on calculation of doses and consequences to in-facility workers due to accidental releases of radioactivity. This report gives detailed instructions on how a user who is familiar with the design, layout and potential hazards of a facility can use KBERT to assess the risks to workers in that facility. KBERT is a tool that allows a user to simulate possible accidents and observe the predicted consequences. Potential applications of KBERT include the evaluation of the efficacy of evacuation practices, worker shielding, personal protection equipment and the containment of hazardous materials.

  6. Assessment of herbal medicinal products: Challenges, and opportunities to increase the knowledge base for safety assessment

    SciTech Connect

    Jordan, Scott A.; Cunningham, David G.; Marles, Robin J.

    2010-03-01

    Although herbal medicinal products (HMP) have been perceived by the public as relatively low risk, there has been more recognition of the potential risks associated with this type of product as the use of HMPs increases. Potential harm can occur via inherent toxicity of herbs, as well as from contamination, adulteration, plant misidentification, and interactions with other herbal products or pharmaceutical drugs. Regulatory safety assessment for HMPs relies on both the assessment of cases of adverse reactions and the review of published toxicity information. However, the conduct of such an integrated investigation has many challenges in terms of the quantity and quality of information. Adverse reactions are under-reported, product quality may be less than ideal, herbs have a complex composition and there is lack of information on the toxicity of medicinal herbs or their constituents. Nevertheless, opportunities exist to capitalise on newer information to increase the current body of scientific evidence. Novel sources of information are reviewed, such as the use of poison control data to augment adverse reaction information from national pharmacovigilance databases, and the use of more recent toxicological assessment techniques such as predictive toxicology and omics. The integration of all available information can reduce the uncertainty in decision making with respect to herbal medicinal products. The example of Aristolochia and aristolochic acids is used to highlight the challenges related to safety assessment, and the opportunities that exist to more accurately elucidate the toxicity of herbal medicines.

  7. Towards the knowledge-based design of universal influenza epitope ensemble vaccines

    PubMed Central

    Sheikh, Qamar M.; Gatherer, Derek; Reche, Pedro A; Flower, Darren R.

    2016-01-01

    Motivation: Influenza A viral heterogeneity remains a significant threat due to unpredictable antigenic drift in seasonal influenza and antigenic shifts caused by the emergence of novel subtypes. Annual review of multivalent influenza vaccines targets strains of influenza A and B likely to be predominant in future influenza seasons. This does not induce broad, cross protective immunity against emergent subtypes. Better strategies are needed to prevent future pandemics. Cross-protection can be achieved by activating CD8+ and CD4+ T cells against highly conserved regions of the influenza genome. We combine available experimental data with informatics-based immunological predictions to help design vaccines potentially able to induce cross-protective T-cells against multiple influenza subtypes. Results: To exemplify our approach we designed two epitope ensemble vaccines comprising highly conserved and experimentally verified immunogenic influenza A epitopes as putative non-seasonal influenza vaccines; one specifically targets the US population and the other is a universal vaccine. The USA-specific vaccine comprised 6 CD8+ T cell epitopes (GILGFVFTL, FMYSDFHFI, GMDPRMCSL, SVKEKDMTK, FYIQMCTEL, DTVNRTHQY) and 3 CD4+ epitopes (KGILGFVFTLTVPSE, EYIMKGVYINTALLN, ILGFVFTLTVPSERG). The universal vaccine comprised 8 CD8+ epitopes: (FMYSDFHFI, GILGFVFTL, ILRGSVAHK, FYIQMCTEL, ILKGKFQTA, YYLEKANKI, VSDGGPNLY, YSHGTGTGY) and the same 3 CD4+ epitopes. Our USA-specific vaccine has a population protection coverage (portion of the population potentially responsive to one or more component epitopes of the vaccine, PPC) of over 96 and 95% coverage of observed influenza subtypes. The universal vaccine has a PPC value of over 97 and 88% coverage of observed subtypes. Availability and Implementation: http://imed.med.ucm.es/Tools/episopt.html. Contact: d.r.flower@aston.ac.uk PMID:27402904

  8. 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

  9. The Integration Process for Incorporating Nuclear Explosion Monitoring Research Results into the National Nuclear Security Administration Knowledge Base

    SciTech Connect

    GALLEGOS, DAVID P.; CARR, DORTHE B.; HERRINGTON, PRESTON B.; HARRIS, JAMES M.; EDWARDS, C.L.; TAYLOR, STEVEN R.; WOGMAN, NED A.; ANDERSON, DALE N.; CASEY, LESLIE A.

    2002-09-01

    The process of developing the National Nuclear Security Administration (NNSA) Knowledge Base (KB) must result in high-quality Information Products in order to support activities for monitoring nuclear explosions consistent with United States treaty and testing moratoria monitoring missions. The validation, verification, and management of the Information Products is critical to successful scientific integration, and hence, will enable high-quality deliveries to be made to the United States National Data Center (USNDC) at the Air Force Technical Applications Center (AFTAC). As an Information Product passes through the steps necessary to become part of a delivery to AFTAC, domain experts (including technical KB Working Groups that comprise NNSA and DOE laboratory staff and the customer) will provide coordination and validation, where validation is the determination of relevance and scientific quality. Verification is the check for completeness and correctness, and will be performed by both the Knowledge Base Integrator and the Scientific Integrator with support from the Contributor providing two levels of testing to assure content integrity and performance. The Information Products and their contained data sets will be systematically tracked through the integration portion of their life cycle. The integration process, based on lessons learned during its initial implementations, is presented in this report.

  10. 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.

  11. Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic web technologies.

    PubMed

    Jiang, Guoqian; Wang, Liwei; Liu, Hongfang; Solbrig, Harold R; Chute, Christopher G

    2013-01-01

    A semantically coded knowledge base of adverse drug events (ADEs) with severity information is critical for clinical decision support systems and translational research applications. However it remains challenging to measure and identify the severity information of ADEs. The objective of the study is to develop and evaluate a semantic web based approach for building a knowledge base of severe ADEs based on the FDA Adverse Event Reporting System (AERS) reporting data. We utilized a normalized AERS reporting dataset and extracted putative drug-ADE pairs and their associated outcome codes in the domain of cardiac disorders. We validated the drug-ADE associations using ADE datasets from SIDe Effect Resource (SIDER) and the UMLS. We leveraged the Common Terminology Criteria for Adverse Event (CTCAE) grading system and classified the ADEs into the CTCAE in the Web Ontology Language (OWL). We identified and validated 2,444 unique Drug-ADE pairs in the domain of cardiac disorders, of which 760 pairs are in Grade 5, 775 pairs in Grade 4 and 2,196 pairs in Grade 3.

  12. Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

    NASA Astrophysics Data System (ADS)

    Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

    2005-02-01

    An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

  13. PromAn: an integrated knowledge-based web server dedicated to promoter analysis

    PubMed Central

    Lardenois, Aurélie; Chalmel, Frédéric; Bianchetti, Laurent; Sahel, José-Alain; Léveillard, Thierry; Poch, Olivier

    2006-01-01

    PromAn is a modular web-based tool dedicated to promoter analysis that integrates distinct complementary databases, methods and programs. PromAn provides automatic analysis of a genomic region with minimal prior knowledge of the genomic sequence. Prediction programs and experimental databases are combined to locate the transcription start site (TSS) and the promoter region within a large genomic input sequence. Transcription factor binding sites (TFBSs) can be predicted using several public databases and user-defined motifs. Also, a phylogenetic footprinting strategy, combining multiple alignment of large genomic sequences and assignment of various scores reflecting the evolutionary selection pressure, allows for evaluation and ranking of TFBS predictions. PromAn results can be displayed in an interactive graphical user interface, PromAnGUI. It integrates all of this information to highlight active promoter regions, to identify among the huge number of TFBS predictions those which are the most likely to be potentially functional and to facilitate user refined analysis. Such an integrative approach is essential in the face of a growing number of tools dedicated to promoter analysis in order to propose hypotheses to direct further experimental validations. PromAn is publicly available at . PMID:16845074

  14. A knowledge-based weighting approach to ligand-based virtual screening.

    PubMed

    Stiefl, Nikolaus; Zaliani, Andrea

    2006-01-01

    On the basis of the recently introduced reduced graph concept of ErG (extending reduced graphs), a straightforward weighting approach to include additional (e.g., structural or SAR) knowledge into similarity searching procedures for virtual screening (wErG) is proposed. This simple procedure is exemplified with three data sets, for which interaction patterns available from X-ray structures of native or peptidomimetic ligands with their target protein are used to significantly improve retrieval rates of known actives from the MDL Drug Report database. The results are compared to those of other virtual screening techniques such as Daylight fingerprints, FTrees, UNITY, and various FlexX docking protocols. Here, it is shown that wErG exhibits a very good and stable performance independent of the target structure. On the basis of this (and the fact that ErG retrieves structurally more dissimilar compounds due to its potential to perform scaffold-hopping), the combination of wErG and FlexX is successfully explored. Overall, wErG is not only an easily applicable weighting procedure that efficiently identifies actives in large data sets but it is also straightforward to understand for both medicinal and computational chemists and can, therefore, be driven by several aspects of project-related knowledge (e.g., X-ray, NMR, SAR, and site-directed mutagenesis) in a very early stage of the hit identification process.

  15. The Knowledge Base for Achieving the Sustainable Development Goal Targets on Water Supply, Sanitation and Hygiene

    PubMed Central

    Hutton, Guy; Chase, Claire

    2016-01-01

    Safe drinking water, sanitation, and hygiene (WASH) are fundamental to an improved standard of living. Globally, 91% of households used improved drinking water sources in 2015, while for improved sanitation it is 68%. Wealth disparities are stark, with rural populations, slum dwellers and marginalized groups lagging significantly behind. Service coverage is significantly lower when considering the new water and sanitation targets under the sustainable development goals (SDGs) which aspire to a higher standard of ‘safely managed’ water and sanitation. Lack of access to WASH can have an economic impact as much as 7% of Gross Domestic Product, not including the social and environmental consequences. Research points to significant health and socio-economic consequences of poor nutritional status, child growth and school performance caused by inadequate WASH. Groundwater over-extraction and pollution of surface water bodies have serious impacts on water resource availability and biodiversity, while climate change exacerbates the health risks of water insecurity. A significant literature documents the beneficial impacts of WASH interventions, and a growing number of impact evaluation studies assess how interventions are optimally financed, implemented and sustained. Many innovations in behavior change and service delivery offer potential for scaling up services to meet the SDGs. PMID:27240389

  16. Use of knowledge-based assistant in marketing of bulk fertilizer storage plants

    NASA Astrophysics Data System (ADS)

    Franklin, Reynold; Burns, Daniel T.; Pyle, Daniel W.

    2001-10-01

    Bulk fertilizer storage companies have undergone dramatic changes including expansions and unification with various companies. This has resulted in the need for large, state- of-the-art fertilizer storage plants. Various factors such as proper layout of the facility, dry fertilizer storage, liquid fertilizer storage, bulk material handling equipment, automation of equipment automation etc. play a vital role in the development of storage plants. Planning for such a facility requires vast amounts of time and collaboration between the planning engineers, building contractor, equipment manufacturer, equipment automates, and other suppliers. Specializing exclusively in development of fertilizer storage plants, Stueve Construction Co. has long felt the need to develop a tool, which will aid in the proposal study and cost analysis of the various entities. This paper describes the feasibility study of developing an expert system incorporation the expertise of the various agents playing a pivotal role in the development of a bulk fertilizer storage plants. Apart from its use in developing a proposal study, its potential use as a marketing tool for the various agencies are also discussed.

  17. The Knowledge Base for Achieving the Sustainable Development Goal Targets on Water Supply, Sanitation and Hygiene.

    PubMed

    Hutton, Guy; Chase, Claire

    2016-05-27

    Safe drinking water, sanitation, and hygiene (WASH) are fundamental to an improved standard of living. Globally, 91% of households used improved drinking water sources in 2015, while for improved sanitation it is 68%. Wealth disparities are stark, with rural populations, slum dwellers and marginalized groups lagging significantly behind. Service coverage is significantly lower when considering the new water and sanitation targets under the sustainable development goals (SDGs) which aspire to a higher standard of 'safely managed' water and sanitation. Lack of access to WASH can have an economic impact as much as 7% of Gross Domestic Product, not including the social and environmental consequences. Research points to significant health and socio-economic consequences of poor nutritional status, child growth and school performance caused by inadequate WASH. Groundwater over-extraction and pollution of surface water bodies have serious impacts on water resource availability and biodiversity, while climate change exacerbates the health risks of water insecurity. A significant literature documents the beneficial impacts of WASH interventions, and a growing number of impact evaluation studies assess how interventions are optimally financed, implemented and sustained. Many innovations in behavior change and service delivery offer potential for scaling up services to meet the SDGs.

  18. Detecting Spatial Patterns of Natural Hazards from the Wikipedia Knowledge Base

    NASA Astrophysics Data System (ADS)

    Fan, J.; Stewart, K.

    2015-07-01

    The Wikipedia database is a data source of immense richness and variety. Included in this database are thousands of geotagged articles, including, for example, almost real-time updates on current and historic natural hazards. This includes usercontributed information about the location of natural hazards, the extent of the disasters, and many details relating to response, impact, and recovery. In this research, a computational framework is proposed to detect spatial patterns of natural hazards from the Wikipedia database by combining topic modeling methods with spatial analysis techniques. The computation is performed on the Neon Cluster, a high performance-computing cluster at the University of Iowa. This work uses wildfires as the exemplar hazard, but this framework is easily generalizable to other types of hazards, such as hurricanes or flooding. Latent Dirichlet Allocation (LDA) modeling is first employed to train the entire English Wikipedia dump, transforming the database dump into a 500-dimension topic model. Over 230,000 geo-tagged articles are then extracted from the Wikipedia database, spatially covering the contiguous United States. The geo-tagged articles are converted into an LDA topic space based on the topic model, with each article being represented as a weighted multidimension topic vector. By treating each article's topic vector as an observed point in geographic space, a probability surface is calculated for each of the topics. In this work, Wikipedia articles about wildfires are extracted from the Wikipedia database, forming a wildfire corpus and creating a basis for the topic vector analysis. The spatial distribution of wildfire outbreaks in the US is estimated by calculating the weighted sum of the topic probability surfaces using a map algebra approach, and mapped using GIS. To provide an evaluation of the approach, the estimation is compared to wildfire hazard potential maps created by the USDA Forest service.

  19. Knowledge-based decision support for Space Station assembly sequence planning

    NASA Technical Reports Server (NTRS)

    1991-01-01

    A complete Personal Analysis Assistant (PAA) for Space Station Freedom (SSF) assembly sequence planning consists of three software components: the system infrastructure, intra-flight value added, and inter-flight value added. The system infrastructure is the substrate on which software elements providing inter-flight and intra-flight value-added functionality are built. It provides the capability for building representations of assembly sequence plans and specification of constraints and analysis options. Intra-flight value-added provides functionality that will, given the manifest for each flight, define cargo elements, place them in the National Space Transportation System (NSTS) cargo bay, compute performance measure values, and identify violated constraints. Inter-flight value-added provides functionality that will, given major milestone dates and capability requirements, determine the number and dates of required flights and develop a manifest for each flight. The current project is Phase 1 of a projected two phase program and delivers the system infrastructure. Intra- and inter-flight value-added were to be developed in Phase 2, which has not been funded. Based on experience derived from hundreds of projects conducted over the past seven years, ISX developed an Intelligent Systems Engineering (ISE) methodology that combines the methods of systems engineering and knowledge engineering to meet the special systems development requirements posed by intelligent systems, systems that blend artificial intelligence and other advanced technologies with more conventional computing technologies. The ISE methodology defines a phased program process that begins with an application assessment designed to provide a preliminary determination of the relative technical risks and payoffs associated with a potential application, and then moves through requirements analysis, system design, and development.

  20. Meta-Modeling: A Knowledge-Based Approach to Facilitating Model Construction and Reuse

    NASA Technical Reports Server (NTRS)

    Keller, Richard M.; Dungan, Jennifer L.

    1997-01-01

    In this paper, we introduce a new modeling approach called meta-modeling and illustrate its practical applicability to the construction of physically-based ecosystem process models. As a critical adjunct to modeling codes meta-modeling requires explicit specification of certain background information related to the construction and conceptual underpinnings of a model. This information formalizes the heretofore tacit relationship between the mathematical modeling code and the underlying real-world phenomena being investigated, and gives insight into the process by which the model was constructed. We show how the explicit availability of such information can make models more understandable and reusable and less subject to misinterpretation. In particular, background information enables potential users to better interpret an implemented ecosystem model without direct assistance from the model author. Additionally, we show how the discipline involved in specifying background information leads to improved management of model complexity and fewer implementation errors. We illustrate the meta-modeling approach in the context of the Scientists' Intelligent Graphical Modeling Assistant (SIGMA) a new model construction environment. As the user constructs a model using SIGMA the system adds appropriate background information that ties the executable model to the underlying physical phenomena under investigation. Not only does this information improve the understandability of the final model it also serves to reduce the overall time and programming expertise necessary to initially build and subsequently modify models. Furthermore, SIGMA's use of background knowledge helps eliminate coding errors resulting from scientific and dimensional inconsistencies that are otherwise difficult to avoid when building complex models. As a. demonstration of SIGMA's utility, the system was used to reimplement and extend a well-known forest ecosystem dynamics model: Forest-BGC.