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Sample records for 7-mer knowledge-based potential

  1. Effective knowledge-based potentials.

    PubMed

    Ferrada, Evandro; Melo, Francisco

    2009-07-01

    Empirical or knowledge-based potentials have many applications in structural biology such as the prediction of protein structure, protein-protein, and protein-ligand interactions and in the evaluation of stability for mutant proteins, the assessment of errors in experimentally solved structures, and the design of new proteins. Here, we describe a simple procedure to derive and use pairwise distance-dependent potentials that rely on the definition of effective atomic interactions, which attempt to capture interactions that are more likely to be physically relevant. Based on a difficult benchmark test composed of proteins with different secondary structure composition and representing many different folds, we show that the use of effective atomic interactions significantly improves the performance of potentials at discriminating between native and near-native conformations. We also found that, in agreement with previous reports, the potentials derived from the observed effective atomic interactions in native protein structures contain a larger amount of mutual information. A detailed analysis of the effective energy functions shows that atom connectivity effects, which mostly arise when deriving the potential by the incorporation of those indirect atomic interactions occurring beyond the first atomic shell, are clearly filtered out. The shape of the energy functions for direct atomic interactions representing hydrogen bonding and disulfide and salt bridges formation is almost unaffected when effective interactions are taken into account. On the contrary, the shape of the energy functions for indirect atom interactions (i.e., those describing the interaction between two atoms bound to a direct interacting pair) is clearly different when effective interactions are considered. Effective energy functions for indirect interacting atom pairs are not influenced by the shape or the energy minimum observed for the corresponding direct interacting atom pair. Our results

  2. 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.

  3. Novel nonlinear knowledge-based mean force potentials based on machine learning.

    PubMed

    Dong, Qiwen; Zhou, Shuigeng

    2011-01-01

    The prediction of 3D structures of proteins from amino acid sequences is one of the most challenging problems in molecular biology. An essential task for solving this problem with coarse-grained models is to deduce effective interaction potentials. The development and evaluation of new energy functions is critical to accurately modeling the properties of biological macromolecules. Knowledge-based mean force potentials are derived from statistical analysis of proteins of known structures. Current knowledge-based potentials are almost in the form of weighted linear sum of interaction pairs. In this study, a class of novel nonlinear knowledge-based mean force potentials is presented. The potential parameters are obtained by nonlinear classifiers, instead of relative frequencies of interaction pairs against a reference state or linear classifiers. The support vector machine is used to derive the potential parameters on data sets that contain both native structures and decoy structures. Five knowledge-based mean force Boltzmann-based or linear potentials are introduced and their corresponding nonlinear potentials are implemented. They are the DIH potential (single-body residue-level Boltzmann-based potential), the DFIRE-SCM potential (two-body residue-level Boltzmann-based potential), the FS potential (two-body atom-level Boltzmann-based potential), the HR potential (two-body residue-level linear potential), and the T32S3 potential (two-body atom-level linear potential). Experiments are performed on well-established decoy sets, including the LKF data set, the CASP7 data set, and the Decoys “R”Us data set. The evaluation metrics include the energy Z score and the ability of each potential to discriminate native structures from a set of decoy structures. Experimental results show that all nonlinear potentials significantly outperform the corresponding Boltzmann-based or linear potentials, and the proposed discriminative framework is effective in developing knowledge-based

  4. 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).

  5. 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.

  6. On the Importance of the Distance Measures Used to Train and Test Knowledge-Based Potentials for Proteins

    PubMed Central

    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. PMID:25411785

  7. 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

  8. 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

  9. Protection of rat liver against hepatic ischemia-reperfusion injury by a novel selenocysteine-containing 7-mer peptide

    PubMed Central

    Jiang, Qianqian; Pan, Yu; Cheng, Yupeng; Li, Huiling; Li, Hui

    2016-01-01

    Hepatic ischemia-reperfusion (I-R) injury causes acute organ damage or dysfunction, and remains a problem for liver transplantation. In the I-R phase, the generation of reactive oxygen species aggravates the injury. In the current study, a novel selenocysteine-containing 7-mer peptide (H-Arg-Sec-Gly-Arg-Asn-Ala-Gln-OH) was constructed to imitate the active site of an antioxidant enzyme, glutathione peroxidase (GPX). The 7-mer peptide which has a lower molecular weight, and improved water-solubility, higher stability and improved cell membrane permeability compared with other GPX mimics. Its GPX activity reached 13 U/µmol, which was 13 times that of ebselen (a representative GPX mimic). The effect of this GPX mimic on I-R injury of the liver was assessed in rats. The 7-mer peptide significantly inhibited the increase in serum hepatic amino-transferases, tissue malondialdehyde, nitric oxide contents, myeloperoxidase activity and decrease of GPX activity compared with I-R tissue. Following treatment with the 7-mer peptide, the expression of B-cell CLL/lymphoma-2 (Bcl-2) was significantly upregulated at the mRNA and protein level compared with the I-R group, as determined by reverse transcription-polymerase chain reaction and immunohistochemistry, respectively. By contrast, Bcl-2 associated X protein (Bax) was downregulated by the 7-mer peptide compared the I-R group. Histological and ultrastructural changes of the rat liver tissue were also compared among the experimental groups. The results of the current study suggest that the 7-mer peptide protected the liver against hepatic I-R injury via suppression of oxygen-derived free radicals and regulation of Bcl-2 and Bax expression, which are involved in the apoptosis of liver cells. The findings of the present study will further the investigation of the 7-mer peptide as an effective therapeutic agent in hepatic I-R injury. PMID:27431272

  10. Classification and comparison of ligand-binding sites derived from grid-mapped knowledge-based potentials.

    PubMed

    Hoppe, Christian; Steinbeck, Christoph; Wohlfahrt, Gerd

    2006-03-01

    We describe the application of knowledge-based potentials implemented in the MOE program to compare the ligand-binding sites of several proteins. The binding probabilities for a polar and a hydrophobic probe are calculated on a grid to allow easy comparison of binding sites of superimposed related proteins. The method is fast and simple enough to simultaneously use structural information of multiple proteins of a target family. The method can be used to rapidly cluster proteins into subfamilies according to the similarity of hydrophobic and polar fields of their ligand-binding sites. Regions of the binding site which are common within a protein family can be identified and analysed for the design of family-targeted libraries or those which differ for improvement of ligand selectivity. The field-based hierarchical clustering is demonstrated for three protein families: the ligand-binding domains of nuclear receptors, the ATP-binding sites of protein kinases and the substrate binding sites of proteases. More detailed comparisons are presented for serine proteases of the chymotrypsin family, for the peroxisome proliferator-activated receptor subfamily of nuclear receptors and for progesterone and androgen receptor. The results are in good accordance with structure-based analysis and highlight important differences of the binding sites, which have been also described in the literature.

  11. 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

  12. 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.

  13. Knowledge based programming at KSC

    NASA Technical Reports Server (NTRS)

    Tulley, J. H., Jr.; Delaune, C. I.

    1986-01-01

    Various KSC knowledge-based systems projects are discussed. The objectives of the knowledge-based automatic test equipment and Shuttle connector analysis network projects are described. It is observed that knowledge-based programs must handle factual and expert knowledge; the characteristics of these two types of knowledge are examined. Applications for the knowledge-based programming technique are considered.

  14. 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.

  15. 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…

  16. 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.

  17. Protection of rat liver against hepatic ischemia-reperfusion injury by a novel selenocysteine-containing 7-mer peptide.

    PubMed

    Jiang, Qianqian; Pan, Yu; Cheng, Yupeng; Li, Huiling; Li, Hui

    2016-09-01

    Hepatic ischemia-reperfusion (I-R) injury causes acute organ damage or dysfunction, and remains a problem for liver transplantation. In the I-R phase, the generation of reactive oxygen species aggravates the injury. In the current study, a novel selenocysteine-containing 7‑mer peptide (H-Arg-Sec-Gly-Arg-Asn-Ala-Gln-OH) was constructed to imitate the active site of an antioxidant enzyme, glutathione peroxidase (GPX). The 7‑mer peptide which has a lower molecular weight, and improved water‑solubility, higher stability and improved cell membrane permeability compared with other GPX mimics. Its GPX activity reached 13 U/µmol, which was 13 times that of ebselen (a representative GPX mimic). The effect of this GPX mimic on I‑R injury of the liver was assessed in rats. The 7‑mer peptide significantly inhibited the increase in serum hepatic amino‑transferases, tissue malondialdehyde, nitric oxide contents, myeloperoxidase activity and decrease of GPX activity compared with I‑R tissue. Following treatment with the 7‑mer peptide, the expression of B‑cell CLL/lymphoma‑2 (Bcl‑2) was significantly upregulated at the mRNA and protein level compared with the I‑R group, as determined by reverse transcription‑polymerase chain reaction and immunohistochemistry, respectively. By contrast, Bcl‑2 associated X protein (Bax) was downregulated by the 7‑mer peptide compared the I‑R group. Histological and ultrastructural changes of the rat liver tissue were also compared among the experimental groups. The results of the current study suggest that the 7‑mer peptide protected the liver against hepatic I‑R injury via suppression of oxygen‑derived free radicals and regulation of Bcl‑2 and Bax expression, which are involved in the apoptosis of liver cells. The findings of the present study will further the investigation of the 7-mer peptide as an effective therapeutic agent in hepatic I-R injury. PMID:27431272

  18. 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.

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

    PubMed

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

    2015-08-28

    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.

  20. 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

  1. 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.

  2. Expert and Knowledge Based Systems.

    ERIC Educational Resources Information Center

    Demaid, Adrian; Edwards, Lyndon

    1987-01-01

    Discusses the nature and current state of knowledge-based systems and expert systems. Describes an expert system from the viewpoints of a computer programmer and an applications expert. Addresses concerns related to materials selection and forecasts future developments in the teaching of materials engineering. (ML)

  3. 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,…

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Knowledge-Based Network Operations

    NASA Astrophysics Data System (ADS)

    Wu, Chuan-lin; Hung, Chaw-Kwei; Stedry, Steven P.; McClure, James P.; Yeh, Show-Way

    1988-03-01

    An expert system is being implemented for enhancing operability of the Ground Communication Facility (GCF) of Jet Propulsion Laboratory's (JPL) Deep Space Network (DSN). The DSN is a tracking network for all of JPL's spacecraft plus a subset of spacecrafts launched by other NASA centers. A GCF upgrade task is set to replace the current GCF aging system with new, modern equipments which are capable of using knowledge-based monitor and control approach. The expert system, implemented in terms of KEE and SUN workstation, is used for performing network fault management, configuration management, and performance management in real-time. Monitor data are collected from each processor and DSCC's in every five seconds. In addition to serving as input parameters of the expert system, extracted management information is used to update a management information database. For the monitor and control purpose, software of each processor is divided into layers following the OSI standard. Each layer is modeled as a finite state machine. A System Management Application Process (SMAP) is implemented at application layer, which coordinates layer managers of the same processor and communicates with peer SMAPs of other processors. The expert system will be tuned by augmenting the production rules as the operation is going on, and its performance will be measured.

  11. 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.

  12. Decision Support and Knowledge-Based Systems.

    ERIC Educational Resources Information Center

    Konsynski, Benn R.; And Others

    1988-01-01

    A series of articles addresses issues concerning decision support and knowledge based systems. Topics covered include knowledge-based systems for information centers; object oriented systems; strategic information systems case studies; user perception; manipulation of certainty factors by individuals and expert systems; spreadsheet program use;…

  13. A knowledge base browser using hypermedia

    NASA Technical Reports Server (NTRS)

    Pocklington, Tony; Wang, Lui

    1990-01-01

    A hypermedia system is being developed to browse CLIPS (C Language Integrated Production System) knowledge bases. This system will be used to help train flight controllers for the Mission Control Center. Browsing this knowledge base will be accomplished either by having navigating through the various collection nodes that have already been defined, or through the query languages.

  14. 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.

  15. Updating knowledge bases with disjunctive information

    SciTech Connect

    Zhang, Yan; Foo, Norman Y.

    1996-12-31

    It is well known that the minimal change principle was widely used in knowledge base updates. However, recent research has shown that conventional minimal change methods, eg. the PMA, are generally problematic for updating knowledge bases with disjunctive information. In this paper, we propose two different approaches to deal with this problem - one is called the minimal change with exceptions (MCE), the other is called the minimal change with maximal disjunctive inclusions (MCD). The first method is syntax-based, while the second is model-theoretic. We show that these two approaches are equivalent for propositional knowledge base updates, and the second method is also appropriate for first order knowledge base updates. We then prove that our new update approaches still satisfy the standard Katsuno and Mendelzon`s update postulates.

  16. 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)

  17. 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.

  18. 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.

  19. Knowledge-based generalization of metabolic models.

    PubMed

    Zhukova, Anna; Sherman, David James

    2014-07-01

    Genome-scale metabolic model reconstruction is a complicated process beginning with (semi-)automatic inference of the reactions participating in the organism's metabolism, followed by many iterations of network analysis and improvement. Despite advances in automatic model inference and analysis tools, reconstruction may still miss some reactions or add erroneous ones. Consequently, a human expert's analysis of the model will continue to play an important role in all the iterations of the reconstruction process. This analysis is hampered by the size of the genome-scale models (typically thousands of reactions), which makes it hard for a human to understand them. To aid human experts in curating and analyzing metabolic models, we have developed a method for knowledge-based generalization that provides a higher-level view of a metabolic model, masking its inessential details while presenting its essential structure. The method groups biochemical species in the model into semantically equivalent classes based on the ChEBI ontology, identifies reactions that become equivalent with respect to the generalized species, and factors those reactions into generalized reactions. Generalization allows curators to quickly identify divergences from the expected structure of the model, such as alternative paths or missing reactions, that are the priority targets for further curation. We have applied our method to genome-scale yeast metabolic models and shown that it improves understanding by helping to identify both specificities and potential errors. PMID:24766276

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. The Knowledge-Based Technology Applications Center (KBTAC) seminar series. Volume 1, Introduction to knowledge-based systems

    SciTech Connect

    Meyer, W.; Scherer, J.; DeLuke, R.; Wood, R.M.

    1992-12-01

    Knowledge-based systems are a means of capturing and productively and efficiently using utility accumulated knowledge and expertise. The first step in this process is to identify what types of problems and applications can benefit from the use of expert systems. Once potential applications have been identified, it is necessary to involve management in supporting the use and developing of the expert system. To do that, management must be made aware of the costs of benefits associated with the development, routine use and maintenance of these systems. To truly understand how knowledge-based systems differ from conventional programming the manager and potential user needs to become familiar with the concept of symbolic reasoning or programming where knowledge is manipulated, not just data as in conventional programming. Knowledge-based systems use all the information manipulation that is found in conventional programming but adds to that knowledge-based programming. How does a program use knowledge? That is accomplished in a knowledge-based system by the inferencing process. Rules allow reasoning to flow backward from a conclusion or a result to circumstances or a causes. Alternatively, certain data or information can lead to a conclusion or a result. The reader will be lead through this process of symbolic reasoning or programming including the presentation of several examples. The software available to develop expert systems is discussed as is the hardware on which that software is operable. Costs and other features of the hardware are presented in detail. Finally, the many different ways in which KBTAC can assist in developing expert systems is discussed. This assistance ranges from phone calls to assistance at KBTAC`s site or at your utility.

  7. Viewing Knowledge Bases as Qualitative Models.

    ERIC Educational Resources Information Center

    Clancey, William J.

    The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The…

  8. 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...

  9. Ethics, Inclusiveness, and the UCEA Knowledge Base.

    ERIC Educational Resources Information Center

    Strike, Kenneth A.

    1995-01-01

    Accepts most of Bull and McCarthy's rejection of the ethical boundary thesis in this same "EAQ" issue. Reinterprets their argument, using a three-part model of administrative knowledge. Any project for constructing an educational administration knowledge base is suspect, since little "pure" empirical and instrumental knowledge will be confirmed by…

  10. 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.…

  11. The Knowledge Bases of the Expert Teacher.

    ERIC Educational Resources Information Center

    Turner-Bisset, Rosie

    1999-01-01

    Presents a model for knowledge bases for teaching that will act as a mental map for understanding the complexity of teachers' professional knowledge. Describes the sources and evolution of the model, explains how the model functions in practice, and provides an illustration using an example of teaching in history. (CMK)

  12. The Knowledge Base for Teaching. ERIC Digest.

    ERIC Educational Resources Information Center

    Strom, Sharon

    This digest examines the knowledge base for teaching, noting that many critical decisions about educational structure, policy, and assessment rely on it. The professionalization of teaching depends on showing that teaching requires mastery of a specialized body of knowledge that is applied ethically. Serious deliberation is needed in the…

  13. 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.

  14. 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.

  15. 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.

  16. Knowledge-based programming support tool

    SciTech Connect

    Harandi, M.T.

    1983-01-01

    This paper presents an overview of a knowledge based programming support tool. Although the system would not synthesize programs automatically, it has the capability of aiding programmers in various phases of program production such as design, coding, debugging and testing. The underlying design principles of this system are similar to those governing the implementation of knowledge-based expertise in other domains of human mental skill. The system is composed of several major units, each an expert system for a sub-domain of program development process. It implements various elements of programming expertise as an interactive system equipped with provisions by which the domain specialist could easily and effectively transfer to the system the knowledge it needs for its decision making. 19 references.

  17. Knowledge-based system for computer security

    SciTech Connect

    Hunteman, W.J.

    1988-01-01

    The rapid expansion of computer security information and technology has provided little support for the security officer to identify and implement the safeguards needed to secure a computing system. The Department of Energy Center for Computer Security is developing a knowledge-based computer security system to provide expert knowledge to the security officer. The system is policy-based and incorporates a comprehensive list of system attack scenarios and safeguards that implement the required policy while defending against the attacks. 10 figs.

  18. 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.

  19. 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.

  20. 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.

  1. Empirical Analysis and Refinement of Expert System Knowledge Bases

    PubMed Central

    Weiss, Sholom M.; Politakis, Peter; Ginsberg, Allen

    1986-01-01

    Recent progress in knowledge base refinement for expert systems is reviewed. Knowledge base refinement is characterized by the constrained modification of rule-components in an existing knowledge base. The goals are to localize specific weaknesses in a knowledge base and to improve an expert system's performance. Systems that automate some aspects of knowledge base refinement can have a significant impact on the related problems of knowledge base acquisition, maintenance, verification, and learning from experience. The SEEK empiricial analysis and refinement system is reviewed and its successor system, SEEK2, is introduced. Important areas for future research in knowledge base refinement are described.

  2. 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.

  3. PharmGKB: The Pharmacogenomics Knowledge Base

    PubMed Central

    Thorn, Caroline F.; Klein, Teri E.; Altman, Russ B.

    2014-01-01

    The Pharmacogenomics Knowledge Base, PharmGKB, is an interactive tool for researchers investigating how genetic variation affects drug response. The PharmGKB Web site, http://www.pharmgkb.org, displays genotype, molecular, and clinical knowledge integrated into pathway representations and Very Important Pharmacogene (VIP) summaries with links to additional external resources. Users can search and browse the knowledgebase by genes, variants, drugs, diseases, and pathways. Registration is free to the entire research community, but subject to agreement to use for research purposes only and not to redistribute. Registered users can access and download data to aid in the design of future pharmacogenetics and pharmacogenomics studies. PMID:23824865

  4. Tools for constructing knowledge-based systems

    SciTech Connect

    Cross, G.R.

    1986-03-01

    The original expert systems for the most part were handcrafted directly, using various dialects of the LISP programming language. The inference and knowledge representation components of these systems can be separated from the domain-specific portion of the expert system and can be used again for an entirely different task. Some of these tools, generically called shells, are discussed. Although these shells provide help in building knowledge-based systems, considerable skill in artificial intelligence programming is still necessary to create an expert system that accomplishes a nontrivial task.

  5. 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).

  6. A knowledge based software engineering environment testbed

    NASA Technical Reports Server (NTRS)

    Gill, C.; Reedy, A.; Baker, L.

    1985-01-01

    The Carnegie Group Incorporated and Boeing Computer Services Company are developing a testbed which will provide a framework for integrating conventional software engineering tools with Artifical Intelligence (AI) tools to promote automation and productivity. The emphasis is on the transfer of AI technology to the software development process. Experiments relate to AI issues such as scaling up, inference, and knowledge representation. In its first year, the project has created a model of software development by representing software activities; developed a module representation formalism to specify the behavior and structure of software objects; integrated the model with the formalism to identify shared representation and inheritance mechanisms; demonstrated object programming by writing procedures and applying them to software objects; used data-directed and goal-directed reasoning to, respectively, infer the cause of bugs and evaluate the appropriateness of a configuration; and demonstrated knowledge-based graphics. Future plans include introduction of knowledge-based systems for rapid prototyping or rescheduling; natural language interfaces; blackboard architecture; and distributed processing

  7. Knowledge-based expert system configurator

    SciTech Connect

    Wakefield, K.A.; Gould, S.S.

    1990-01-01

    The term knowledge-based expert system'' usually brings to mind a rather extensive list of commercially available expert system shells with the associated complexity of implementing the given inferencing strategies to drive a rule base of knowledge for solving particular classes of problems. A significant amount of learning time is required to understand all of the intricacies of the systems in order to effectively utilize their salient features while working around the canned'' constraints. The amount of effort required to prototype the first attempt'' is therefore substantial and can quickly lead to the unfortunate effect of reticence toward applying expert systems. This paper describes an alternative approach to use of specialized shells in developing or prototyping first-attempting knowledge-based expert systems using Lotus 123, a commonly used spreadsheet software package. The advantages of using this approach are discussed. The working example presented makes use of the forward-chaining capabilities available to determine automatically the hardware jumper and switch configuration for a distributed process control system. Hardware configuration control documentation is generated for use by field engineers and maintenance technicians. 4 refs., 4 figs.

  8. 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.

  9. Compilation for critically constrained knowledge bases

    SciTech Connect

    Schrag, R.

    1996-12-31

    We show that many {open_quotes}critically constrained{close_quotes} Random 3SAT knowledge bases (KBs) can be compiled into disjunctive normal form easily by using a variant of the {open_quotes}Davis-Putnam{close_quotes} proof procedure. From these compiled KBs we can answer all queries about entailment of conjunctive normal formulas, also easily - compared to a {open_quotes}brute-force{close_quotes} approach to approximate knowledge compilation into unit clauses for the same KBs. We exploit this fact to develop an aggressive hybrid approach which attempts to compile a KB exactly until a given resource limit is reached, then falls back to approximate compilation into unit clauses. The resulting approach handles all of the critically constrained Random 3SAT KBs with average savings of an order of magnitude over the brute-force approach.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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. PMID:26055098

  15. A Knowledge-Based Imagery Exploitation System

    NASA Astrophysics Data System (ADS)

    Smyrniotis, Chuck; Payton, Paul M.; Barrett, Eamon B.

    1989-03-01

    Automation of major portions of the imagery exploitation process is becoming a necessity for meeting current and future imagery exploitation needs. In this paper we describe a prototype Automated Exploitation System (AES) which addresses requirements for monitoring objects of interest and situation assessment in large geographic areas. The purpose of AES is to aid the image analyst in performing routine, commonplace tasks more effectively. AES consists of four main subsystems: Cue Extractor (CE), Knowledge-Based Exploitation (KBE), Interactive Work-Station (IWS), and a database subsystem. The CE processes raw image data, and identifies objects and target cues based on pixel- and object-model data. Cues and image registration coefficients are passed to KBE for screening and verification, situation assessment and planning. KBE combines the cues with ground-truth and doctrinal knowledge in screening the cues to determine their importance. KBE generates reports on image analysis which passes on to the IWS from which an image analyst can monitor, observe, and evaluate system functionality as well as respond to critical items identified by KBE. The database subsystem stores and shares reference imagery, collateral information and digital terrain data to support both automated and interactive processing. This partitioning of functions to subsystems facilitates hierarchical application of knowledge in image interpretation. The AES current prototype helps in identification, capture, representation, and refinement of knowledge. The KBE subsystem, which is the primary focus of the present paper, runs on a Symbolics 3675 computer and its software is written in the ART expert system and LISP language.

  16. Knowledge-based system verification and validation

    NASA Technical Reports Server (NTRS)

    Johnson, Sally C.

    1990-01-01

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

  17. 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

  18. 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.

  19. 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.

  20. 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

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

    NASA Astrophysics Data System (ADS)

    Saveland, James M.

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

  2. 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

  3. 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.

  4. 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…

  5. 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 that knowledge bases, the…

  6. Applying Knowledge-Based Techniques to Software Development.

    ERIC Educational Resources Information Center

    Harandi, Mehdi T.

    1986-01-01

    Reviews overall structure and design principles of a knowledge-based programming support tool, the Knowledge-Based Programming Assistant, which is being developed at University of Illinois Urbana-Champaign. The system's major units (program design program coding, and intelligent debugging) and additional functions are described. (MBR)

  7. Verification of knowledge bases based on containment checking

    SciTech Connect

    Levy. A.Y.; Rousset, M.C.

    1996-12-31

    Building complex knowledge based applications requires encoding large amounts of domain knowledge. After acquiring knowledge from domain experts, much of the effort in building a knowledge base goes into verifying that the knowledge is encoded correctly. We consider the problem of verifying hybrid knowledge bases that contain both Horn rules and a terminology in a description logic. Our approach to the verification problem is based on showing a close relationship to the problem of query containment. Our first contribution, based on this relationship, is presenting a thorough analysis of the decidability and complexity of the verification problem, for knowledge bases containing recursive rules and the interpreted predicates =, {le}, < and {ne}. Second, we show that important new classes of constraints on correct inputs and outputs can be expressed in a hybrid setting, in which a description logic class hierarchy is also considered, and we present the first complete algorithm for verifying such hybrid knowledge bases.

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

    SciTech Connect

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

    1997-08-01

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

  9. 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…

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Embedded knowledge-based system for automatic target recognition

    NASA Astrophysics Data System (ADS)

    Aboutalib, A. O.

    1990-10-01

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

  16. 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. PMID:26904105

  17. 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).

  18. 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.

  19. A Natural Language Interface Concordant with a Knowledge Base

    PubMed Central

    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. PMID:26904105

  20. Knowledge-based environment for hierarchical modeling and simulation

    SciTech Connect

    Kim, Taggon.

    1988-01-01

    This dissertation develops a knowledge-based environment for hierarchical modeling and simulation of discrete-event systems as the major part of a longer, ongoing research project in artificial intelligence and distributed simulation. In developing the environment, a knowledge representation framework for modeling and simulation, which unifies structural and behavioral knowledge of simulation models, is proposed by incorporating knowledge-representation schemes in artificial intelligence within simulation models. The knowledge base created using the framework is composed of a structural knowledge base called entity structure base and a behavioral knowledge base called model base. The DEVS-Scheme, a realization of DEVS (Discrete Event System Specifiation) formalism in a LISP-based, object-oriented environment, is extended to facilitate the specification of behavioral knowledge of models, especially for kernel models that are suited to model massively parallel computer architectures. The ESP Scheme, a realization of entity structure formalism in a frame-theoretic representation, is extended to represent structural knowledge of models and to manage it in the structural knowledge base.

  1. 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.

  2. Building a knowledge base to support a digital library.

    PubMed

    Mendonça, E A; Cimino, J J

    2001-01-01

    As part of an effort to develop a knowledge base to support searching online medical literature according to individual needs, we have studied the possibility of using the co-occurrence of MeSH terms in MEDLINE citations associated with the search strategies optimal for evidence based medicine to automated construction of a knowledge base. This study evaluates the relevance of the relationships between the semantic relationship pairs generated by the process, and the clinical validity of the semantic types involved in the process. From the semantic pairs proposed by our method, a group of clinicians judge sixty percent to be relevant. The remaining forty percent included semantic types considered unimportant by clinicians. The knowledge extraction method showed reasonable results. We believe it can be appropriate for the task of retrieving information from the medical record in order to guide users during a searching and retrieval process. Future directions include the validation of the knowledge, based on an evaluation of system performance.

  3. 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

  4. 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. PMID:25160140

  5. 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.

  6. Developing a Knowledge Base and Taxonomy in Instructional Technology.

    ERIC Educational Resources Information Center

    Caffarella, Edward P.; Fly, Kenneth

    The purpose of this study was to test the feasibility of using a model adapted from the instructional design and technology (ID&T) taxonomy model proposed by the Association for Educational Communications and Technology (AECT) Definitions and Terminology Committee to build an ID&T knowledge base. The model was tested by mapping a random sample of…

  7. 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.

  8. 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.

  9. 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.

  10. 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…

  11. Cataloging and Expert Systems: AACR2 as a Knowledge Base.

    ERIC Educational Resources Information Center

    Hjerppe, Roland; Olander, Birgitta

    1989-01-01

    Describes a project that developed two expert systems for library cataloging using the second edition of the Anglo American Cataloging Rules (AACR2) as a knowledge base. The discussion covers cataloging as interpretation, the structure of AACR2, and the feasibility of using expert systems for cataloging in traditional library settings. (26…

  12. 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…

  13. 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…

  14. 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.

  15. 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…

  16. 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,…

  17. Integrating knowledge based functionality in commercial hospital information systems.

    PubMed

    Müller, M L; Ganslandt, T; Eich, H P; Lang, K; Ohmann, C; Prokosch, H U

    2000-01-01

    Successful integration of knowledge-based functions in the electronic patient record depends on direct and context-sensitive accessibility and availability to clinicians and must suit their workflow. In this paper we describe an exemplary integration of an existing standalone scoring system for acute abdominal pain into two different commercial hospital information systems using Java/Corba technolgy.

  18. 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…

  19. 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 and…

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

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

    PubMed

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

    2015-08-26

    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.

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

    NASA Astrophysics Data System (ADS)

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

    1989-03-01

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

  7. 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.

  8. 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.

  9. MetaShare: Enabling Knowledge-Based Data Management

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  10. Current and future trends in metagenomics : Development of knowledge bases

    NASA Astrophysics Data System (ADS)

    Mori, Hiroshi; Yamada, Takuji; Kurokawa, Ken

    Microbes are essential for every part of life on Earth. Numerous microbes inhabit the biosphere, many of which are uncharacterized or uncultivable. They form a complex microbial community that deeply affects against surrounding environments. Metagenome analysis provides a radically new way of examining such complex microbial community without isolation or cultivation of individual bacterial community members. In this article, we present a brief discussion about a metagenomics and the development of knowledge bases, and also discuss about the future trends in metagenomics.

  11. 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.

  12. 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.

  13. 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

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

    NASA Astrophysics Data System (ADS)

    Moreno, Arnaldo

    2008-02-01

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

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

    SciTech Connect

    Moreno, Arnaldo

    2008-02-15

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

  16. Knowledge-based computer-aided detection of masses on digitized mammograms: a preliminary assessment.

    PubMed

    Chang, Y H; Hardesty, L A; Hakim, C M; Chang, T S; Zheng, B; Good, W F; Gur, D

    2001-04-01

    The purpose of this work was to develop and evaluate a computer-aided detection (CAD) scheme for the improvement of mass identification on digitized mammograms using a knowledge-based approach. Three hundred pathologically verified masses and 300 negative, but suspicious, regions, as initially identified by a rule-based CAD scheme, were randomly selected from a large clinical database for development purposes. In addition, 500 different positive and 500 negative regions were used to test the scheme. This suspicious region pruning scheme includes a learning process to establish a knowledge base that is then used to determine whether a previously identified suspicious region is likely to depict a true mass. This is accomplished by quantitatively characterizing the set of known masses, measuring "similarity" between a suspicious region and a "known" mass, then deriving a composite "likelihood" measure based on all "known" masses to determine the state of the suspicious region. To assess the performance of this method, receiver-operating characteristic (ROC) analyses were employed. Using a leave-one-out validation method with the development set of 600 regions, the knowledge-based CAD scheme achieved an area under the ROC curve of 0.83. Fifty-one percent of the previously identified false-positive regions were eliminated, while maintaining 90% sensitivity. During testing of the 1,000 independent regions, an area under the ROC curve as high as 0.80 was achieved. Knowledge-based approaches can yield a significant reduction in false-positive detections while maintaining reasonable sensitivity. This approach has the potential of improving the performance of other rule-based CAD schemes.

  17. Manned spaceflight activity planning with knowledge-based systems

    NASA Technical Reports Server (NTRS)

    Mogilensky, J.; Dalton, R. E.; Scarl, E. A.

    1983-01-01

    An on-board expert system, capable of assisting with crew-activity planning and platform-status monitoring, could provide unprecedented autonomy to the crew of a permanently manned space station. To demonstrate this concept's feasibility, an existing knowledge-based system is adapted to support Space Shuttle crew-activity timeline planning. Proposed timeline changes are to be checked for compliance with crew capabilities and mission operating guidelines, so that a nonexpert can be guided through a successful plan modification. Early lessons that have been learned about the scope of the adaptation needed to achieve this objective are presented.

  18. 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

  19. 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.

  20. Database and knowledge base integration in decision support systems.

    PubMed Central

    Johansson, B.; Shahsavar, N.; Ahlfeldt, H.; Wigertz, O.

    1996-01-01

    Since decision support systems (DSS) in medicine often are linked to clinical databases it is important to find methods that facilitate the work for DSS developers to implement database queries in the knowledge base (KB). This paper presents a method for linking clinical databases to a KB with Arden Syntax modules. The method is based on a query meta database including templates for SQL queries. During knowledge module authoring the medical expert only refers to a code in the query meta database. Our method uses standard tools so it can be implemented on different platforms and linked to different clinical databases. PMID:8947666

  1. A prototype knowledge-based simulation support system

    SciTech Connect

    Hill, T.R.; Roberts, S.D.

    1987-04-01

    As a preliminary step toward the goal of an intelligent automated system for simulation modeling support, we explore the feasibility of the overall concept by generating and testing a prototypical framework. A prototype knowledge-based computer system was developed to support a senior level course in industrial engineering so that the overall feasibility of an expert simulation support system could be studied in a controlled and observable setting. The system behavior mimics the diagnostic (intelligent) process performed by the course instructor and teaching assistants, finding logical errors in INSIGHT simulation models and recommending appropriate corrective measures. The system was programmed in a non-procedural language (PROLOG) and designed to run interactively with students working on course homework and projects. The knowledge-based structure supports intelligent behavior, providing its users with access to an evolving accumulation of expert diagnostic knowledge. The non-procedural approach facilitates the maintenance of the system and helps merge the roles of expert and knowledge engineer by allowing new knowledge to be easily incorporated without regard to the existing flow of control. The background, features and design of the system are describe and preliminary results are reported. Initial success is judged to demonstrate the utility of the reported approach and support the ultimate goal of an intelligent modeling system which can support simulation modelers outside the classroom environment. Finally, future extensions are suggested.

  2. 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.

  3. Knowledge-based system for the design of heat exchangers

    NASA Astrophysics Data System (ADS)

    Cochran, W. J.; Hainley, Don; Khartabil, Loay

    1993-03-01

    A knowledge based system has been developed to assist engineers in the design of compact heat exchangers. The main objectives of this project were to: (1) automate aspects of heat exchanger design; (2) produce multiple successful designs quickly; and (3) optimize these designs based on specific constraints or criteria. Productivity improvements from use of this system have been as much as two orders of magnitude. The design of heat exchangers is a time-consuming, iterative process. For a given set of requirements a design engineer uses his knowledge and experience to pick an initial design point and then calculates (with a large Fortran program) the performance for that design. If performance data do not meet requirements, various design parameters are modified and performance is calculated again. An expert system now embodies design expertise (rules for design decisions) allowing automation of this iterative process and substantial time savings for engineers. In addition, optimizing successful designs is now practical, whereas in the past it was generally infeasible due to the amount of labor involved. A configuration system was also developed that serves as a `front- end' for the design system. The configuration system matches design requirements to existing products and offers suggestions for initial design points. Both were developed with the KAPPA knowledge based system shell. The two KAPPA programs and the Fortran program for numerical calculations are integrated within a Windows 3.1 environment on a 486 PC.

  4. Big Data Analytics in Immunology: A Knowledge-Based Approach

    PubMed Central

    Zhang, Guang Lan

    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. PMID:25045677

  5. Knowledge based cluster ensemble for cancer discovery from biomolecular data.

    PubMed

    Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying

    2011-06-01

    The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.

  6. 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.

  7. 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.

  8. 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

  9. Mindtagger: A Demonstration of Data Labeling in Knowledge Base Construction

    PubMed Central

    Shin, Jaeho; Ré, Christopher; Cafarella, Michael

    2016-01-01

    End-to-end knowledge base construction systems using statistical inference are enabling more people to automatically extract high-quality domain-specific information from unstructured data. As a result of deploying DeepDive framework across several domains, we found new challenges in debugging and improving such end-to-end systems to construct high-quality knowledge bases. DeepDive has an iterative development cycle in which users improve the data. To help our users, we needed to develop principles for analyzing the system's error as well as provide tooling for inspecting and labeling various data products of the system. We created guidelines for error analysis modeled after our colleagues' best practices, in which data labeling plays a critical role in every step of the analysis. To enable more productive and systematic data labeling, we created Mindtagger, a versatile tool that can be configured to support a wide range of tasks. In this demonstration, we show in detail what data labeling tasks are modeled in our error analysis guidelines and how each of them is performed using Mindtagger. PMID:27144082

  10. 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. PMID:25045677

  11. 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.

  12. Knowledge-based imaging-sensor fusion system

    NASA Technical Reports Server (NTRS)

    Westrom, George

    1989-01-01

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

  13. 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.

  14. 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.

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

    PubMed

    Lau, F; Vincent, D D

    1995-01-01

    There is a growing interest in using care maps in ICU. So far, the emphasis has been on developing the critical path, problem/outcome, and variance reporting for specific diagnoses. This paper presents a conceptual knowledge-based care protocol system design for the ICU. It is based on the manual care map currently in use for managing myocardial infarction in the ICU of the Sturgeon General Hospital in Alberta. The proposed design uses expert rules, object schemas, case-based reasoning, and quantitative models as sources of its knowledge. Also being developed is a decision model with explicit linkages for outcome-process-measure from the care map. The resulting system is intended as a bedside charting and decision-support tool for caregivers. Proposed usage includes charting by acknowledgment, generation of alerts, and critiques on variances/events recorded, recommendations for planned interventions, and comparison with historical cases. Currently, a prototype is being developed on a PC-based network with Visual Basic, Level-Expert Object, and xBase. A clinical trial is also planned to evaluate whether this knowledge-based care protocol can reduce the length of stay of patients with myocardial infarction in the ICU. PMID:8591604

  16. Spinning fantasy: themes, structure, and the knowledge base.

    PubMed

    Lucariello, J

    1987-04-01

    The influence of the child's knowledge base, in terms of event schemas, on symbolic play behavior was investigated. The pretend play behavior of 10 mother-child (2-0 to 2-4) dyads was observed in 2 play contexts. Play was examined for thematic content and the following structural components: self-other relations, substitute/imaginary objects, action integration, and planfulness. The highest levels of symbolic play behavior emerged in pretense episodes whose thematic content was event based. Additionally, thematic content affected the respective roles of mother and child in the construction of pretense. In pretense activity based on themes with which the child was familiar (e.g., routine events), the child, as well as the mother, participated in advanced levels of symbolic play activity, coconstructing pretense. In pretense based on themes unfamiliar to the child, the mother was almost exclusively responsible for the pretense. Thus, the development of child symbolic play appears to be related to the knowledge base in that its emergence is domain-specific--limited to themes for which the child has knowledge--before being more widely manifested. PMID:2435465

  17. Portable Knowledge-Based Diagnostic And Maintenance Systems

    NASA Astrophysics Data System (ADS)

    Darvish, John; Olson, Noreen S.

    1989-03-01

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

  18. A knowledge-based approach to software development

    SciTech Connect

    White, D.A.

    1995-09-01

    Traditional software development consists of many knowledge intensive and intellectual activities related to understanding a problem to be solved and designing a solution to that problem. These activities are informal, subjective, and undocumented and are the same for original development and subsequent support. Since 1982, the USAF Rome Laboratory has been developing the Knowledge-Based Software Assistant (KBSA), a revolutionary new paradigm for software development that will achieve orders of magnitude improvement in productivity and quality. KBSA does not pursue the improvement of traditional technologies or methodologies such as new programming languages and management procedures to fulfill this objective, but has instead adopted a revolutionary new approach. KBSA is a knowledge-based, computer-mediated paradigm for the evolutionary definition, specification, development, and long-term support of software. The computer becomes an `intelligent partner` and `corporate memory` in this paradigm, formally capturing the appropriate knowledge and actively using this knowledge to provide assistance and automation. The productivity of developers will dramatically improve because of the increased assistance, automation and re-utilization of domain and programming knowledge. The quality of software, both correctness and satisfying requirements, will also improve because the development process is formal and easier to use.

  19. Automatic generation of a metamodel from an existing knowledge base to assist the development of a new analogous knowledge base.

    PubMed

    Bouaud, J; Séroussi, B

    2002-01-01

    Knowledge acquisition is a key step in the development of knowledge-based systems and methods have been proposed to help elicitating a domain-specific task model from a generic task model. We explored how an existing validated knowledge base (KB) represented by a decision tree could be automatically processed to infer a higher level domain-specific task model. On-codoc is a guideline-based decision support system applied to breast cancer therapy. Assuming task identity and ontological proximity between breast and lung cancer domains, the generalization of the breast can-cer KB should allow to build a metamodel to serve as a guide for the elaboration of a new specific KB on lung cancer. Two types of parametrized generalization methods based on tree structure simplification and ontological abstraction were used. We defined a similarity distance and a generalization coefficient to select the best metamodel identified as the closest to the original decision tree of the most generalized metamodels. PMID:12463788

  20. Knowledge-based navigation of complex information spaces

    SciTech Connect

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

    1996-12-31

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

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

    NASA Technical Reports Server (NTRS)

    Ricks, Wendell R.

    1990-01-01

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

  2. 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.

  3. ProbOnto: ontology and knowledge base of probability distributions

    PubMed Central

    Swat, Maciej J.; Grenon, Pierre; Wimalaratne, Sarala

    2016-01-01

    Motivation: Probability distributions play a central role in mathematical and statistical modelling. The encoding, annotation and exchange of such models could be greatly simplified by a resource providing a common reference for the definition of probability distributions. Although some resources exist, no suitably detailed and complex ontology exists nor any database allowing programmatic access. Results: ProbOnto, is an ontology-based knowledge base of probability distributions, featuring more than 80 uni- and multivariate distributions with their defining functions, characteristics, relationships and re-parameterization formulas. It can be used for model annotation and facilitates the encoding of distribution-based models, related functions and quantities. Availability and Implementation: http://probonto.org Contact: mjswat@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153608

  4. 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.

  5. Knowledge-based generalization of metabolic networks: a practical study.

    PubMed

    Zhukova, Anna; Sherman, David J

    2014-04-01

    The complex process of genome-scale metabolic network reconstruction involves semi-automatic reaction inference, analysis, and refinement through curation by human experts. Unfortunately, decisions by experts are hampered by the complexity of the network, which can mask errors in the inferred network. In order to aid an expert in making sense out of the thousands of reactions in the organism's metabolism, we developed a method for knowledge-based generalization that provides a higher-level view of the network, highlighting the particularities and essential structure, while hiding the details. In this study, we show the application of this generalization method to 1,286 metabolic networks of organisms in Path2Models that describe fatty acid metabolism. We compare the generalised networks and show that we successfully highlight the aspects that are important for their curation and comparison. PMID:24712528

  6. Structure of the knowledge base for an expert labeling system

    NASA Technical Reports Server (NTRS)

    Rajaram, N. S.

    1981-01-01

    One of the principal objectives of the NASA AgRISTARS program is the inventory of global crop resources using remotely sensed data gathered by Land Satellites (LANDSAT). A central problem in any such crop inventory procedure is the interpretation of LANDSAT images and identification of parts of each image which are covered by a particular crop of interest. This task of labeling is largely a manual one done by trained human analysts and consequently presents obstacles to the development of totally automated crop inventory systems. However, development in knowledge engineering as well as widespread availability of inexpensive hardware and software for artificial intelligence work offers possibilities for developing expert systems for labeling of crops. Such a knowledge based approach to labeling is presented.

  7. 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.

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

    NASA Technical Reports Server (NTRS)

    Henson, Troy; Rone, Kyle

    1988-01-01

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

  9. 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.

  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. Knowledge-based generalization of metabolic networks: a practical study.

    PubMed

    Zhukova, Anna; Sherman, David J

    2014-04-01

    The complex process of genome-scale metabolic network reconstruction involves semi-automatic reaction inference, analysis, and refinement through curation by human experts. Unfortunately, decisions by experts are hampered by the complexity of the network, which can mask errors in the inferred network. In order to aid an expert in making sense out of the thousands of reactions in the organism's metabolism, we developed a method for knowledge-based generalization that provides a higher-level view of the network, highlighting the particularities and essential structure, while hiding the details. In this study, we show the application of this generalization method to 1,286 metabolic networks of organisms in Path2Models that describe fatty acid metabolism. We compare the generalised networks and show that we successfully highlight the aspects that are important for their curation and comparison.

  12. Knowledge-based decision support for patient monitoring in cardioanesthesia.

    PubMed

    Schecke, T; Langen, M; Popp, H J; Rau, G; Käsmacher, H; Kalff, G

    1992-01-01

    An approach to generating 'intelligent alarms' is presented that aggregates many information items, i.e. measured vital signs, recent medications, etc., into state variables that more directly reflect the patient's physiological state. Based on these state variables the described decision support system AES-2 also provides therapy recommendations. The assessment of the state variables and the generation of therapeutic advice follow a knowledge-based approach. Aspects of uncertainty, e.g. a gradual transition between 'normal' and 'below normal', are considered applying a fuzzy set approach. Special emphasis is laid on the ergonomic design of the user interface, which is based on color graphics and finger touch input on the screen. Certain simulation techniques considerably support the design process of AES-2 as is demonstrated with a typical example from cardioanesthesia. PMID:1402299

  13. 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.

  14. 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.

  15. The Knowledge Base Interface for Parametric Grid Information

    SciTech Connect

    Hipp, James R.; Simons, Randall W.; Young, Chris J.

    1999-08-03

    The parametric grid capability of the Knowledge Base (KBase) provides an efficient robust way to store and access interpolatable information that is needed to monitor the Comprehensive Nuclear Test Ban Treaty. To meet both the accuracy and performance requirements of operational monitoring systems, we use an approach which combines the error estimation of kriging with the speed and robustness of Natural Neighbor Interpolation. The method involves three basic steps: data preparation, data storage, and data access. In past presentations we have discussed in detail the first step. In this paper we focus on the latter two, describing in detail the type of information which must be stored and the interface used to retrieve parametric grid data from the Knowledge Base. Once data have been properly prepared, the information (tessellation and associated value surfaces) needed to support the interface functionality, can be entered into the KBase. The primary types of parametric grid data that must be stored include (1) generic header information; (2) base model, station, and phase names and associated ID's used to construct surface identifiers; (3) surface accounting information; (4) tessellation accounting information; (5) mesh data for each tessellation; (6) correction data defined for each surface at each node of the surfaces owning tessellation (7) mesh refinement calculation set-up and flag information; and (8) kriging calculation set-up and flag information. The eight data components not only represent the results of the data preparation process but also include all required input information for several population tools that would enable the complete regeneration of the data results if that should be necessary.

  16. 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

  17. 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 production, consumption and economic…

  18. 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.

  19. LLNL Middle East, North Africa and Western Eurasia Knowledge Base

    SciTech Connect

    O'Boyle, J; Ruppert, S D; Hauk, T F; Dodge, D A; Ryall, F; Firpo, M A

    2001-07-12

    The Lawrence Livermore National Laboratory (LLNL) Ground-Based Nuclear Event Monitoring (GNEM) program has made significant progress populating a comprehensive Seismic Research Knowledge Base (SRKB) and deriving calibration parameters for the Middle East, North Africa and Western Eurasia (ME/NA/WE) regions. The LLNL SRKB provides not only a coherent framework in which to store and organize very large volumes of collected seismic waveforms, associated event parameter information, and spatial contextual data, but also provides an efficient data processing/research environment for deriving location and discrimination correction surfaces. The SRKB is a flexible and extensible framework consisting of a relational database (RDB), Geographical Information System (GIS), and associated product/data visualization and data management tools. This SRKB framework is designed to accommodate large volumes of data (almost 3 million waveforms from 57,000 events) in diverse formats from many sources (both LLNL derived research and integrated contractor products), in addition to maintaining detailed quality control and metadata. We have developed expanded look-up tables for critical station parameter information (including location and response) and an integrated and reconciled event catalog data set (including specification of preferred origin solutions and associated phase arrivals) for the PDE, CMT, ISC, REB and selected regional catalogs. Using the SRKB framework, we are combining traveltime observations, event characterization studies, and regional tectonic models to assemble a library of ground truth information and phenomenology (e.g. travel-time and amplitude) correction surfaces required for support of the ME/NA/WE regionalization program. We also use the SRKB to integrate data and research products from a variety of sources, such as contractors and universities, to merge and maintain quality control of the data sets. Corrections and parameters distilled from the LLNL SRKB

  20. A clinical trial of a knowledge-based medical record.

    PubMed

    Safran, C; Rind, D M; Davis, R B; Sands, D Z; Caraballo, E; Rippel, K; Wang, Q; Rury, C; Makadon, H J; Cotton, D J

    1995-01-01

    To meet the needs of primary care physicians caring for patients with HIV infection, we developed a knowledge-based medical record to allow the on-line patient record to play an active role in the care process. These programs integrate the on-line patient record, rule-based decision support, and full-text information retrieval into a clinical workstation for the practicing clinician. To determine whether use of a knowledge-based medical record was associated with more rapid and complete adherence to practice guidelines and improved quality of care, we performed a controlled clinical trial among physicians and nurse practitioners caring for 349 patients infected with the human immuno-deficiency virus (HIV); 191 patients were treated by 65 physicians and nurse practitioners assigned to the intervention group, and 158 patients were treated by 61 physicians and nurse practitioners assigned to the control group. During the 18-month study period, the computer generated 303 alerts in the intervention group and 388 in the control group. The median response time of clinicians to these alerts was 11 days in the intervention group and 52 days in the control group (PJJ0.0001, log-rank test). During the study, the computer generated 432 primary care reminders for the intervention group and 360 reminders for the control group. The median response time of clinicians to these alerts was 114 days in the intervention group and more than 500 days in the control group (PJJ0.0001, log-rank test). Of the 191 patients in the intervention group, 67 (35%) had one or more hospitalizations, compared with 70 (44%) of the 158 patients in the control group (PJ=J0.04, Wilcoxon test stratified for initial CD4 count). There was no difference in survival between the intervention and control groups (P = 0.18, log-rank test). We conclude that our clinical workstation significantly changed physicians' behavior in terms of their response to alerts regarding primary care interventions and that these

  1. 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

  2. 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.

  3. PmiRKB: a plant microRNA knowledge base

    PubMed Central

    Meng, Yijun; Gou, Lingfeng; Chen, Dijun; Mao, Chuanzao; Jin, Yongfeng; Wu, Ping; Chen, Ming

    2011-01-01

    MicroRNAs (miRNAs), one type of small RNAs (sRNAs) in plants, play an essential role in gene regulation. Several miRNA databases were established; however, successively generated new datasets need to be collected, organized and analyzed. To this end, we have constructed a plant miRNA knowledge base (PmiRKB) that provides four major functional modules. In the ‘SNP’ module, single nucleotide polymorphism (SNP) data of seven Arabidopsis (Arabidopsis thaliana) accessions and 21 rice (Oryza sativa) subspecies were collected to inspect the SNPs within pre-miRNAs (precursor microRNAs) and miRNA—target RNA duplexes. Depending on their locations, SNPs can affect the secondary structures of pre-miRNAs, or interactions between miRNAs and their targets. A second module, ‘Pri-miR’, can be used to investigate the tissue-specific, transcriptional contexts of pre- and pri-miRNAs (primary microRNAs), based on massively parallel signature sequencing data. The third module, ‘MiR–Tar’, was designed to validate thousands of miRNA—target pairs by using parallel analysis of RNA end (PARE) data. Correspondingly, the fourth module, ‘Self-reg’, also used PARE data to investigate the metabolism of miRNA precursors, including precursor processing and miRNA- or miRNA*-mediated self-regulation effects on their host precursors. PmiRKB can be freely accessed at http://bis.zju.edu.cn/pmirkb/. PMID:20719744

  4. A Generalized Knowledge-Based Discriminatory Function for Biomolecular Interactions

    PubMed Central

    Bernard, Brady; Samudrala, Ram

    2010-01-01

    Several novel and established knowledge-based discriminatory function formulations and reference state derivations have been evaluated to identify parameter sets capable of distinguishing native and near-native biomolecular interactions from incorrect ones. We developed the r·m·r function, a novel atomic level radial distribution function with mean reference state that averages over all pairwise atom types from a reduced atom type composition, using experimentally determined intermolecular complexes in the Cambridge Structural Database (CSD) and the Protein Data Bank (PDB) as the information sources. We demonstrate that r·m·r had the best discriminatory accuracy and power for protein-small molecule and protein-DNA interactions, regardless of whether the native complex was included or excluded from the test set. The superior performance of the r·m·r discriminatory function compared to seventeen alternative functions evaluated on publicly available test sets for protein-small molecule and protein-DNA interactions indicated that the function was not over optimized through back testing on a single class of biomolecular interactions. The initial success of the reduced composition and superior performance with the CSD as the distribution set over the PDB implies that further improvements and generality of the function are possible by deriving probabilities from subsets of the CSD, using structures that consist of only the atom types to be considered for given biomolecular interactions. The method is available as a web server module at http://protinfo.compbio.washington.edu. PMID:19127590

  5. Knowledge based system for Satellite data product selection

    NASA Astrophysics Data System (ADS)

    Goyal, R.; Jayasudha, T.; Pandey, P.; Rama Devi, D.; Rebecca, A.; Manju Sarma, M.; Lakshmi, B.

    2014-11-01

    In recent years, the use of satellite data for geospatial applications has multiplied and contributed significantly towards development of the society. Satellite data requirements, in terms of spatial and spectral resolution, periodicity of data, level of correction and other parameters, vary for different applications. For major applications, remote sensing data alone may not suffice and may require additional data like field data. An application user, even though being versatile in his application, may not know which satellite data is best suited for his application, how to use the data and what information can be derived from the data. Remote sensing domain experts have the proficiency of using appropriate data for remote sensing applications. Entrenching domain expertise into the system and building a knowledge base system for satellite data product selection is vital. Non specialist data users need a user-friendly software which guides them to the most suitable satellite data product on the basis of their application. Such tool will aid the usage for apt remote sensed data for various sectors of application users. Additionally, the consumers will be less concerned about the technical particulars of the platforms that provide satellite data, instead focusing on the content and values in the data product, meeting the timelines and ease of access. Embedding knowledge is a popular and effective means of increasing the power of using a system. This paper describes a system, driven by the built-in knowledge of domain experts, for satellite data products selection for geospatial applications.

  6. How Quality Improvement Practice Evidence Can Advance the Knowledge Base.

    PubMed

    OʼRourke, Hannah M; Fraser, Kimberly D

    2016-01-01

    Recommendations for the evaluation of quality improvement interventions have been made in order to improve the evidence base of whether, to what extent, and why quality improvement interventions affect chosen outcomes. The purpose of this article is to articulate why these recommendations are appropriate to improve the rigor of quality improvement intervention evaluation as a research endeavor, but inappropriate for the purposes of everyday quality improvement practice. To support our claim, we describe the differences between quality improvement interventions that occur for the purpose of practice as compared to research. We then carefully consider how feasibility, ethics, and the aims of evaluation each impact how quality improvement interventions that occur in practice, as opposed to research, can or should be evaluated. Recommendations that fit the evaluative goals of practice-based quality improvement interventions are needed to support fair appraisal of the distinct evidence they produce. We describe a current debate on the nature of evidence to assist in reenvisioning how quality improvement evidence generated from practice might complement that generated from research, and contribute in a value-added way to the knowledge base. PMID:27584696

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. Knowledge base navigator facilitating regional analysis inter-tool communication.

    SciTech Connect

    Hampton, Jeffery Wade; Chael, Eric Paul; Hart, Darren M.; Merchant, Bion John; Chown, Matthew N.

    2004-08-01

    To make use of some portions of the National Nuclear Security Administration (NNSA) Knowledge Base (KB) for which no current operational monitoring applications were available, Sandia National Laboratories have developed a set of prototype regional analysis tools (MatSeis, EventID Tool, CodaMag Tool, PhaseMatch Tool, Dendro Tool, Infra Tool, etc.), and we continue to maintain and improve these. Individually, these tools have proven effective in addressing specific monitoring tasks, but collectively their number and variety tend to overwhelm KB users, so we developed another application - the KB Navigator - to launch the tools and facilitate their use for real monitoring tasks. The KB Navigator is a flexible, extensible java application that includes a browser for KB data content, as well as support to launch any of the regional analysis tools. In this paper, we will discuss the latest versions of KB Navigator and the regional analysis tools, with special emphasis on the new overarching inter-tool communication methodology that we have developed to make the KB Navigator and the tools function together seamlessly. We use a peer-to-peer communication model, which allows any tool to communicate with any other. The messages themselves are passed as serialized XML, and the conversion from Java to XML (and vice versa) is done using Java Architecture for XML Binding (JAXB).

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. A knowledge based expert system for condition monitoring

    SciTech Connect

    Selkirk, C.G.; Roberge, P.R.; Fisher, G.F.; Yeung, K.K.

    1994-12-31

    Condition monitoring (CM) is the focus of many maintenance philosophies around the world today. In the Canadian Forces (CF), CM has played an important role in the maintenance of aircraft systems since the introduction of spectrometric oil analysis (SOAP) over twenty years ago. Other techniques in use in the CF today include vibration analysis (VA), ferrography, and filter debris analysis (FDA). To improve the usefulness and utility gained from these CM techniques, work is currently underway to incorporate expert systems into them. An expert system for FDA is being developed which will aid filter debris analysts in identifying wear debris and wear level trends, and which will provide the analyst with reference examples in an attempt to standardize results. Once completed, this knowledge based expert system will provide a blueprint from which other CM expert systems can be created. Amalgamating these specific systems into a broad based global system will provide the CM analyst with a tool that will be able to correlate data and results from each of the techniques, thereby increasing the utility of each individual method of analysis. This paper will introduce FDA and then outline the development of the FDA expert system and future applications.

  20. 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.

  1. A knowledge-based modeling for plantar pressure image reconstruction.

    PubMed

    Ostadabbas, Sarah; Nourani, Mehrdad; Saeed, Adnan; Yousefi, Rasoul; Pompeo, Matthew

    2014-10-01

    It is known that prolonged pressure on the plantar area is one of the main factors in developing foot ulcers. With current technology, electronic pressure monitoring systems can be placed as an insole into regular shoes to continuously monitor the plantar area and provide evidence on ulcer formation process as well as insight for proper orthotic footwear design. The reliability of these systems heavily depends on the spatial resolution of their sensor platforms. However, due to the cost and energy constraints, practical wireless in-shoe pressure monitoring systems have a limited number of sensors, i.e., typically K < 10. In this paper, we present a knowledge-based regression model (SCPM) to reconstruct a spatially continuous plantar pressure image from a small number of pressure sensors. This model makes use of high-resolution pressure data collected clinically to train a per-subject regression function. SCPM is shown to outperform all other tested interpolation methods for K < 60 sensors, with less than one-third of the error for K = 10 sensors. SCPM bridges the gap between the technological capability and medical need and can play an important role in the adoption of sensing insole for a wide range of medical applications.

  2. Ontology-based knowledge base model construction-OntoKBCF.

    PubMed

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

    2007-01-01

    Semantic web technologies are used in the construction of a bio-health knowledge base model, which, when coupled with an Electronic Health Record (EHR), is to be used by clinicians. Specifically, this ontology provides the basis for a domain knowledge resource that attempts to bridge biological and clinical information. The prototype is focused on a Cystic Fibrosis exemplar, and the content of the model includes: Cochrane reviews; a time-oriented description; gene therapy; and the most common cystic fibrosis gene mutations. The facts within the model range from nucleo-base mutation and amino acid change to clinical phenotype. The knowledge is represented by layers from the micro level to the macro level. Here, emphasis is placed upon the details between levels (i.e., the vertical axis) and these are made available to bridge the knowledge from different levels. The description of gender, age, mutation and clinical manifestations are clues for matching points within an EHR system. OWL is the ontology representation language used and the output from Protégé-OWL is a XML-based file format, which facilitates further application and communication.

  3. 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.

  4. 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

  5. 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. PMID:26247028

  6. 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.

  7. 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

  8. TEXSYS. [a knowledge based system for the Space Station Freedom thermal control system test-bed

    NASA Technical Reports Server (NTRS)

    Bull, John

    1990-01-01

    The Systems Autonomy Demonstration Project has recently completed a major test and evaluation of TEXSYS, a knowledge-based system (KBS) which demonstrates real-time control and FDIR for the Space Station Freedom thermal control system test-bed. TEXSYS is the largest KBS ever developed by NASA and offers a unique opportunity for the study of technical issues associated with the use of advanced KBS concepts including: model-based reasoning and diagnosis, quantitative and qualitative reasoning, integrated use of model-based and rule-based representations, temporal reasoning, and scale-up performance issues. TEXSYS represents a major achievement in advanced automation that has the potential to significantly influence Space Station Freedom's design for the thermal control system. An overview of the Systems Autonomy Demonstration Project, the thermal control system test-bed, the TEXSYS architecture, preliminary test results, and thermal domain expert feedback are presented.

  9. 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.

  10. 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/.

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

    PubMed Central

    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/. PMID:26313379

  12. 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.

  13. Development of a Knowledge Base for Enduser Consultation of AAL-Systems.

    PubMed

    Röll, Natalie; Stork, Wilhelm; Rosales, Bruno; Stephan, René; Knaup, Petra

    2016-01-01

    Manufacturer information, user experiences and product availability of assistive living technologies are usually not known to citizens or consultation centers. The different knowledge levels concerning the availability of technology shows the need for building up a knowledge base. The aim of this contribution is the definition of requirements in the development of knowledge bases for AAL consultations. The major requirements, such as a maintainable and easy to use structure were implemented into a web based knowledge base, which went productive in ~3700 consulting interviews of municipal technology information centers. Within this field phase the implementation of the requirements for a knowledge base in the field of AAL consulting was evaluated and further developed.

  14. 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.

  15. 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…

  16. 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…

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

    PubMed

    Curtis, A C

    1984-10-01

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

  18. 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.

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

    PubMed

    Curtis, A C

    1984-10-01

    Major components of knowledge-based systems are summarized, along with the programming language features generally useful in their implementation. LISP and MUMPS are briefly described and compared as vehicles for building knowledge-based systems. The paper concludes with suggestions for extensions to MUMPS that might increase its usefulness in artificial intelligence applications without affecting the essential nature of the language. PMID:6549025

  20. Knowledge base and neural network approach for protein secondary structure prediction.

    PubMed

    Patel, Maulika S; Mazumdar, Himanshu S

    2014-11-21

    Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods.

  1. Structure of a protein (H2AX): a comparative study with knowledge-based interactions

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

    The structural and conformational properties of the histone protein H2AX (with143 residues) is studied by a coarse-grained model as a function of temperature (T). Three knowledge-based phenomenological interactions (MJ, BT, and BFKV) are used as input to a generalized Lennard-Jones potential for residue-residue interactions. Large-scale Monte Carlo simulations are performed to identify similarity and differences in the equilibrium structures with these potentials. Multi-scale structures of the protein are examined by a detailed analysis of their structure functions. We find that the radius of gyration (Rg) of H2AX depends non-monotonically on temperature with a maximum at a characteristic value Tc, a common feature to each interaction. The characteristic temperature and the range of non-monotonic thermal response and decay pattern are, however, sensitive to interactions. A comparison of the structural properties emerging from three potentials will be presented in this talk. This work is supported by Air Force Research Laboratory.

  2. Validation of a Crowdsourcing Methodology for Developing a Knowledge Base of Related Problem-Medication Pairs

    PubMed Central

    Wright, A.; Krousel-Wood, M.; Thomas, E. J.; McCoy, J. A.; Sittig, D. F.

    2015-01-01

    Summary Background Clinical knowledge bases of problem-medication pairs are necessary for many informatics solutions that improve patient safety, such as clinical summarization. However, developing these knowledge bases can be challenging. Objective We sought to validate a previously developed crowdsourcing approach for generating a knowledge base of problem-medication pairs in a large, non-university health care system with a widely used, commercially available electronic health record. Methods We first retrieved medications and problems entered in the electronic health record by clinicians during routine care during a six month study period. Following the previously published approach, we calculated the link frequency and link ratio for each pair then identified a threshold cutoff for estimated problem-medication pair appropriateness through clinician review; problem-medication pairs meeting the threshold were included in the resulting knowledge base. We selected 50 medications and their gold standard indications to compare the resulting knowledge base to the pilot knowledge base developed previously and determine its recall and precision. Results The resulting knowledge base contained 26,912 pairs, had a recall of 62.3% and a precision of 87.5%, and outperformed the pilot knowledge base containing 11,167 pairs from the previous study, which had a recall of 46.9% and a precision of 83.3%. Conclusions We validated the crowdsourcing approach for generating a knowledge base of problem-medication pairs in a large non-university health care system with a widely used, commercially available electronic health record, indicating that the approach may be generalizable across healthcare settings and clinical systems. Further research is necessary to better evaluate the knowledge, to compare crowdsourcing with other approaches, and to evaluate if incorporating the knowledge into electronic health records improves patient outcomes. PMID:26171079

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Controllable Solid Propulsion Combustion and Acoustic Knowledge Base Improvements

    NASA Technical Reports Server (NTRS)

    McCauley, Rachel; Fischbach, Sean; Fredrick, Robert

    2012-01-01

    Controllable solid propulsion systems have distinctive combustion and acoustic environments that require enhanced testing and analysis techniques to progress this new technology from development to production. In a hot gas valve actuating system, the movement of the pintle through the hot gas exhibits complex acoustic disturbances and flow characteristics that can amplify induced pressure loads that can damage or detonate the rocket motor. The geometry of a controllable solid propulsion gas chamber can set up unique unsteady flow which can feed acoustic oscillations patterns that require characterization. Research in this area aids in the understanding of how best to design, test, and analyze future controllable solid rocket motors using the lessons learned from past government programs as well as university research and testing. This survey paper will give the reader a better understanding of the potentially amplifying affects propagated by a controllable solid rocket motor system and the knowledge of the tools current available to address these acoustic disturbances in a preliminary design. Finally the paper will supply lessons learned from past experiences which will allow the reader to come away with understanding of what steps need to be taken when developing a controllable solid rocket propulsion system. The focus of this survey will be on testing and analysis work published by solid rocket programs and from combustion and acoustic books, conference papers, journal articles, and additionally from subject matter experts dealing currently with controllable solid rocket acoustic analysis.

  9. KBSIM: a system for interactive knowledge-based simulation.

    PubMed

    Hakman, M; Groth, T

    1991-01-01

    The KBSIM system integrates quantitative simulation with symbolic reasoning techniques, under the control of a user interface management system, using a relational database management system for data storage and interprocess communication. The system stores and processes knowledge from three distinct knowledge domains, viz. (i) knowledge about the processes of the system under investigation, expressed in terms of a Continuous System Simulation Language (CSSL); (ii) heuristic knowledge on how to reach the goals of the simulation experiment, expressed in terms of a Rule Description Language (RDL); and (iii) knowledge about the requirements of the intended users, expressed in terms of a User Interface Description Language (UIDL). The user works in an interactive environment controlling the simulation course with use of a mouse and a large screen containing a set of 'live' charts and forms. The user is assisted by an embedded 'expert system' module continuously watching both the system's behavior and the user's action, and producing alerts, alarms, comments and advice. The system was developed on a Hewlett-Packard 9000/350 workstation under the HP-Unix and HP-Windows operating systems, using the MIMER database management system, and Fortran, Prolog/Lisp and C as implementation languages. The KBSIM system has great potentials for supporting problem solving, design of working procedures and teaching related to management of highly dynamic systems. PMID:2060297

  10. 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.

  11. Development of a Knowledge Base for Enduser Consultation of AAL-Systems.

    PubMed

    Röll, Natalie; Stork, Wilhelm; Rosales, Bruno; Stephan, René; Knaup, Petra

    2016-01-01

    Manufacturer information, user experiences and product availability of assistive living technologies are usually not known to citizens or consultation centers. The different knowledge levels concerning the availability of technology shows the need for building up a knowledge base. The aim of this contribution is the definition of requirements in the development of knowledge bases for AAL consultations. The major requirements, such as a maintainable and easy to use structure were implemented into a web based knowledge base, which went productive in ~3700 consulting interviews of municipal technology information centers. Within this field phase the implementation of the requirements for a knowledge base in the field of AAL consulting was evaluated and further developed. PMID:27577407

  12. Towards a knowledge-based system to assist the Brazilian data-collecting system operation

    NASA Technical Reports Server (NTRS)

    Rodrigues, Valter; Simoni, P. O.; Oliveira, P. P. B.; Oliveira, C. A.; Nogueira, C. A. M.

    1988-01-01

    A study is reported which was carried out to show how a knowledge-based approach would lead to a flexible tool to assist the operation task in a satellite-based environmental data collection system. Some characteristics of a hypothesized system comprised of a satellite and a network of Interrogable Data Collecting Platforms (IDCPs) are pointed out. The Knowledge-Based Planning Assistant System (KBPAS) and some aspects about how knowledge is organized in the IDCP's domain are briefly described.

  13. 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.

  14. 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.

  15. 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.

  16. 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. PMID:26631432

  17. tcTKB: an integrated cardiovascular toxicity knowledge base for targeted cancer drugs

    PubMed Central

    Xu, Rong; Wang, QuanQiu

    2015-01-01

    Targeted cancer drugs are often associated with unexpectedly high cardiovascular (CV) adverse events. Systematic approaches to studying CV events associated with targeted anticancer drugs have high potential for elucidating the complex pathways underlying targeted anti-cancer drugs. In this study, we built tcTKB, a comprehensive CV toxicity knowledge base for targeted cancer drugs, by extracting drug-CV pairs from five large-scale and complementary data sources. The data sources include FDA drug labels (44,979 labels), the FDA Adverse Event Reporting System (FAERS) (4,285,097 records), the Canada Vigilance Adverse Reaction Online Database (CVAROD) (1,107,752 records), published biomedical literature (21,354,075 records), and published full-text articles from the Journal of Oncology (JCO) (13,855 articles). tcTKB contains 14,351 drug-CV pairs for 45 targeted anticancer drugs and 1,842 CV events. We demonstrate that CV events positively correlate with drug target genes and drug metabolism genes, demonstrating that tcTKB in combination with other data resources, could facilitate our understanding of targeted anticancer drugs and their associated CV toxicities. PMID:26958275

  18. Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus.

    PubMed

    Wheeler, Diek W; White, Charise M; Rees, Christopher L; Komendantov, Alexander O; Hamilton, David J; Ascoli, Giorgio A

    2015-09-24

    Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron properties are often reported with incompletely defined and notoriously inconsistent terminology, creating a formidable challenge for data integration. Our extensive literature mining and data reconciliation identified 122 neuron types based on neurotransmitter, axonal and dendritic patterns, synaptic specificity, electrophysiology, and molecular biomarkers. All ∼3700 annotated properties are individually supported by specific evidence (∼14,000 pieces) in peer-reviewed publications. Systematic analysis of this unprecedented amount of machine-readable information reveals novel correlations among neuron types and properties, the potential connectivity of the full hippocampal circuitry, and outstanding knowledge gaps. User-friendly browsing and online querying of Hippocampome.org may aid design and interpretation of both experiments and simulations. This powerful, simple, and extensible neuron classification endeavor is unique in its detail, utility, and completeness.

  19. 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.

  20. 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.

  1. 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.

  2. Knowledge-based model of hydrogen-bonding propensity in organic crystals.

    PubMed

    Galek, Peter T A; Fábián, László; Motherwell, W D Samuel; Allen, Frank H; Feeder, Neil

    2007-10-01

    A new method is presented to predict which donors and acceptors form hydrogen bonds in a crystal structure, based on the statistical analysis of hydrogen bonds in the Cambridge Structural Database (CSD). The method is named the logit hydrogen-bonding propensity (LHP) model. The approach has a potential application in identifying both likely and unusual hydrogen bonding, which can help to rationalize stable and metastable crystalline forms, of relevance to drug development in the pharmaceutical industry. Whilst polymorph prediction techniques are widely used, the LHP model is knowledge-based and is not restricted by the computational issues of polymorph prediction, and as such may form a valuable precursor to polymorph screening. Model construction applies logistic regression, using training data obtained with a new survey method based on the CSD system. The survey categorizes the hydrogen bonds and extracts model parameter values using descriptive structural and chemical properties from three-dimensional organic crystal structures. LHP predictions from a fitted model are made using two-dimensional observables alone. In the initial cases analysed, the model is highly accurate, achieving approximately 90% correct classification of both observed hydrogen bonds and non-interacting donor-acceptor pairs. Extensive statistical validation shows the LHP model to be robust across a range of small-molecule organic crystal structures. PMID:17873446

  3. Hippocampome.org: a knowledge base of neuron types in the rodent hippocampus

    PubMed Central

    Wheeler, Diek W; White, Charise M; Rees, Christopher L; Komendantov, Alexander O; Hamilton, David J; Ascoli, Giorgio A

    2015-01-01

    Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron properties are often reported with incompletely defined and notoriously inconsistent terminology, creating a formidable challenge for data integration. Our extensive literature mining and data reconciliation identified 122 neuron types based on neurotransmitter, axonal and dendritic patterns, synaptic specificity, electrophysiology, and molecular biomarkers. All ∼3700 annotated properties are individually supported by specific evidence (∼14,000 pieces) in peer-reviewed publications. Systematic analysis of this unprecedented amount of machine-readable information reveals novel correlations among neuron types and properties, the potential connectivity of the full hippocampal circuitry, and outstanding knowledge gaps. User-friendly browsing and online querying of Hippocampome.org may aid design and interpretation of both experiments and simulations. This powerful, simple, and extensible neuron classification endeavor is unique in its detail, utility, and completeness. DOI: http://dx.doi.org/10.7554/eLife.09960.001 PMID:26402459

  4. 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

  5. Text-mining applied to autoimmune disease research: the Sjögren’s syndrome knowledge base

    PubMed Central

    2012-01-01

    Background Sjögren’s syndrome is a tissue-specific autoimmune disease that affects exocrine tissues, especially salivary glands and lacrimal glands. Despite a large body of evidence gathered over the past 60 years, significant gaps still exist in our understanding of Sjögren’s syndrome. The goal of this study was to develop a database that collects and organizes gene and protein expression data from the existing literature for comparative analysis with future gene expression and proteomic studies of Sjögren’s syndrome. Description To catalog the existing knowledge in the field, we used text mining to generate the Sjögren’s Syndrome Knowledge Base (SSKB) of published gene/protein data, which were extracted from PubMed using text mining of over 7,700 abstracts and listing approximately 500 potential genes/proteins. The raw data were manually evaluated to remove duplicates and false-positives and assign gene names. The data base was manually curated to 477 entries, including 377 potential functional genes, which were used for enrichment and pathway analysis using gene ontology and KEGG pathway analysis. Conclusions The Sjögren’s syndrome knowledge base ( http://sskb.umn.edu) can form the foundation for an informed search of existing knowledge in the field as new potential therapeutic targets are identified by conventional or high throughput experimental techniques. PMID:22759918

  6. Knowledge based system verification and validation as related to automation of space station subsystems: Rationale for a knowledge based system lifecycle

    NASA Technical Reports Server (NTRS)

    Richardson, Keith; Wong, Carla

    1988-01-01

    The role of verification and validation (V and V) in software has been to support and strengthen the software lifecycle and to ensure that the resultant code meets the standards of the requirements documents. Knowledge Based System (KBS) V and V should serve the same role, but the KBS lifecycle is ill-defined. The rationale of a simple form of the KBS lifecycle is presented, including accommodation to certain critical KBS differences from software development.

  7. Database decomposition of a knowledge-based CAD system in mammography: an ensemble approach to improve detection

    NASA Astrophysics Data System (ADS)

    Mazurowski, Maciej A.; Zurada, Jacek M.; Tourassi, Georgia D.

    2008-03-01

    Although ensemble techniques have been investigated in supervised machine learning, their potential with knowledge-based systems is unexplored. The purpose of this study is to investigate the ensemble approach with a knowledge-based (KB) CAD system for the detection of masses in screening mammograms. The system is designed to determine the presence of a mass in a query mammographic region of interest (ROI) based on its similarity with previously acquired examples of mass and normal cases. Similarity between images is assessed using normalized mutual information. Two different approaches of knowledge database decomposition were investigated to create the ensemble. The first approach was random division of the knowledge database into a pre-specified number of equal size, separate groups. The second approach was based on k-means clustering of the knowledge cases according to common texture features extracted from the ROIs. The ensemble components were fused using a linear classifier. Based on a database of 1820 ROIs (901 masses and 919 and the leave-one-out crossvalidation scheme, the ensemble techniques improved the performance of the original KB-CAD system (A z = 0.86+/-0.01). Specifically, random division resulted in ROC area index of A z = 0.90 +/- 0.01 while k-means clustering provided further improvement (A z = 0.91 +/- 0.01). Although marginally better, the improvement was statistically significant. The superiority of the k-means clustering scheme was robust regardless of the number of clusters. This study supports the idea of incorporation of ensemble techniques with knowledge-based systems in mammography.

  8. A protein relational database and protein family knowledge bases to facilitate structure-based design analyses.

    PubMed

    Mobilio, Dominick; Walker, Gary; Brooijmans, Natasja; Nilakantan, Ramaswamy; Denny, R Aldrin; Dejoannis, Jason; Feyfant, Eric; Kowticwar, Rupesh K; Mankala, Jyoti; Palli, Satish; Punyamantula, Sairam; Tatipally, Maneesh; John, Reji K; Humblet, Christine

    2010-08-01

    The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom-atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid-centroid and centroid-atom distances and angles have also been included permitting queries for pi-stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

  9. 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

  10. Constructing Clinical Decision Support Systems for Adverse Drug Event Prevention: A Knowledge-based Approach.

    PubMed

    Koutkias, Vassilis; Kilintzis, Vassilis; Stalidis, George; Lazou, Katerina; Collyda, Chrysa; Chazard, Emmanuel; McNair, Peter; Beuscart, Regis; Maglaveras, Nicos

    2010-11-13

    A knowledge-based approach is proposed that is employed for the construction of a framework suitable for the management and effective use of knowledge on Adverse Drug Event (ADE) prevention. The framework has as its core part a Knowledge Base (KB) comprised of rule-based knowledge sources, that is accompanied by the necessary inference and query mechanisms to provide healthcare professionals and patients with decision support services in clinical practice, in terms of alerts and recommendations on preventable ADEs. The relevant Knowledge Based System (KBS) is developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the foundations of the framework, its knowledge model and KB structure, as well as recent progress as regards the population of the KB, the implementation of the KBS, and results on the KBS verification in decision support operation.

  11. A situational approach to the design of a patient-oriented disease-specific knowledge base.

    PubMed Central

    Kim, Matthew I.; Ladenson, Paul; Johnson, Kevin B.

    2002-01-01

    We have developed a situational approach to the organization of disease-specific information that seeks to provide patients with targeted access to content in a knowledge base. Our approach focuses on dividing a defined knowledge base into sections corresponding to discrete clinical events associated with the evaluation and treatment of a specific disorder. Common reasons for subspecialty referral are used to generate situational statements that serve as entry points into the knowledge base. Each section includes defining questions generated using keywords associated with specific topics. Defining questions are linked to patient-focused answers. Evaluation of a thyroid cancer web site designed using this approach has identified high ratings for usability, relevance, and comprehension of retrieved information. This approach may be particularly useful in the development of resources for newly diagnosed patients. PMID:12463852

  12. 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.

  13. County level population estimation using knowledge-based image classification and regression models

    NASA Astrophysics Data System (ADS)

    Nepali, Anjeev

    This paper presents methods and results of county-level population estimation using Landsat Thematic Mapper (TM) images of Denton County and Collin County in Texas. Landsat TM images acquired in March 2000 were classified into residential and non-residential classes using maximum likelihood classification and knowledge-based classification methods. Accuracy assessment results from the classified image produced using knowledge-based classification and traditional supervised classification (maximum likelihood classification) methods suggest that knowledge-based classification is more effective than traditional supervised classification methods. Furthermore, using randomly selected samples of census block groups, ordinary least squares (OLS) and geographically weighted regression (GWR) models were created for total population estimation. The overall accuracy of the models is over 96% at the county level. The results also suggest that underestimation normally occurs in block groups with high population density, whereas overestimation occurs in block groups with low population density.

  14. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1987-01-01

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

  16. 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. PMID:24743069

  17. 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.

  18. Expansion of the Ligand Knowledge Base for Chelating P,P-Donor Ligands (LKB-PP).

    PubMed

    Jover, Jesús; Fey, Natalie; Harvey, Jeremy N; Lloyd-Jones, Guy C; Orpen, A Guy; Owen-Smith, Gareth J J; Murray, Paul; Hose, David R J; Osborne, Robert; Purdie, Mark

    2012-08-13

    We have expanded the ligand knowledge base for bidentate P,P- and P,N-donor ligands (LKB-PP, Organometallics2008, 31, 1372-1383) by 208 ligands and introduced an additional steric descriptor (nHe8). This expanded knowledge base now captures information on 334 bidentate ligands and has been processed with principal component analysis (PCA) of the descriptors to produce a detailed map of bidentate ligand space, which better captures ligand variation and has been used for the analysis of ligand properties. PMID:24882917

  19. yOWL: an ontology-driven knowledge base for yeast biologists.

    PubMed

    Villanueva-Rosales, Natalia; Dumontier, Michel

    2008-10-01

    Knowledge management is an ongoing challenge for the biological community such that large, diverse and continuously growing information requires more sophisticated methods to store, integrate and query their knowledge. The semantic web initiative provides a new knowledge engineering framework to represent, share and discover information. In this paper, we describe our efforts towards the development of an ontology-based knowledge base, including aspects from ontology design and population using "semantic" data mashup, to automated reasoning and semantic query answering. Based on yeast data obtained from the Saccharomyces Genome Database and UniProt, we discuss the challenges encountered during the building of the knowledge base and how they were overcome.

  20. 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.

  1. HIV-K: an integrative knowledge base for semantic integration of AIDS-related malignancy data and treatment outcomes.

    PubMed

    Tirado-Ramos, A; Saltz, Joel; Lechowicz, Mary Jo

    2010-01-01

    Technological innovations such as web services and collaborative Grid platforms like caGrid can create opportunities to converge the worlds of health care and clinical research, by facilitating access and integration of HIV-related malignancy clinical and outcomes data at more sophisticated, semantic levels. At the same time, large numbers of randomized clinical trial and outcomes data on AIDS-defining malignancies (ADM) and non-AIDS-defining malignancies (nADM) have been produced during the last few years. There is still much work to do, though, on obtaining clear conclusions from the integration of such information. This is a white paper on work in progress from Emory University's HIV/AIDS related malignancy data integrative knowledge base project (HIV-K). We are working to increase the understanding of available clinical trial data and outcomes of ADM such as lymphoma, as well as nADM such as anal cancer, Hodgkin lymphoma, or liver cancer. Our hypothesis is that, by creating prototypes of tools for semantics-enabled integrative knowledge bases for HIV/AIDS-related malignancy data, we will facilitate the identification of patterns and potential new overall evidence, as well as the linking of integrated data and results to registries of interest.

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

    ERIC Educational Resources Information Center

    Parkinson, B.; Hudson, P.

    2002-01-01

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

  3. 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…

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

    ERIC Educational Resources Information Center

    Vickers, Joan N.; Gaines, Brian R.

    1988-01-01

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

  5. Expanding the Socio-Cultural Knowledge Base of TESOL Teacher Education

    ERIC Educational Resources Information Center

    Dogancay-Aktuna, Seran

    2006-01-01

    This paper argues for the expansion of the knowledge base of TESOL teacher education to integrate greater awareness of the sociocultural and political context of teaching English to speakers of other languages. It is argued that the changing roles of teachers, insights gained from classroom research and recent developments in critical applied…

  6. Expert System Knowledge Base for a Computer Simulation of Judgments on Dossiers of School Teacher Performance.

    ERIC Educational Resources Information Center

    Peterson, Kenneth D.

    The expert system computer simulation detailed in this report is designed to investigate patterns of valuing in decision-making about dossiers of performance data used in teacher promotion evaluations. The knowledge base for the simulation consists of 111 questions organized into 117 rules. The questions and linked advice were derived from…

  7. Limitations of Levels, Learning Outcomes and Qualifications as Drivers Towards a More Knowledge-Based Society

    ERIC Educational Resources Information Center

    Brown, Alan

    2008-01-01

    National (and European) qualifications frameworks, the specification of learning outcomes and grand targets like the Lisbon goals of increasing the supply of graduates in Europe in order to achieve a more knowledge-based society are all predicated upon the idea of moving people through to higher and well-defined levels of skills, knowledge and…

  8. Transformational Learning and Human Resource Development: Advances toward a Knowledge Based Society through Humor

    ERIC Educational Resources Information Center

    Parke, Joanne

    2004-01-01

    A common thread within a growing globalism is the creation of an emerging knowledge-based workforce. This paper will discuss a message supported by adult education theory that is beginning to manifest itself in human resource development and the growing globalism that steeped in communication and information. Theoretical implications are reviewed…

  9. 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.

  10. Elements of Creative Social Science: Part I--Towards Greater Authority for the Knowledge Base.

    ERIC Educational Resources Information Center

    Lengyel, Peter

    1989-01-01

    Presents an argument defending the cognitive knowledge base in the social sciences. Contends that the findings related to the sociosphere are as important as those findings in the technosphere or biosphere. Suggests that the creation of a social science equivalency to research and development which would be called operationalizing and assembly.…

  11. Developing genomic knowledge bases and databases to support clinical management: current perspectives.

    PubMed

    Huser, Vojtech; Sincan, Murat; Cimino, James J

    2014-01-01

    Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.

  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. 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.

  14. A Knowledge Representation Language for Large Knowledge Bases and "Intelligent" Information Retrieval Systems.

    ERIC Educational Resources Information Center

    Zarri, Gian Piero

    1990-01-01

    Describes a conceptual Knowledge Representation Language (KRL) developed at the French National Center for Scientific Research, that is used for the construction and use of Large Knowledge Bases (LKBs) and/or Intelligent Information Retrieval Systems (IIRSs). Semantic factors are discussed, and the specialization hierarchies used are explained.…

  15. Will They Know Enough?: Pre-Service Primary Teachers' Knowledge Base for Teaching Integrated Social Sciences

    ERIC Educational Resources Information Center

    Tambyah, Mallihai

    2008-01-01

    A significant issue in primary teacher education is developing a knowledge base which prepares teachers to teach in a range of subject areas. In Australia, the problem in primary social science education is compounded by the integrated nature of the key learning area of Studies of Society and Environment (SOSE). Recent debates on teaching…

  16. 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…

  17. 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'…

  18. 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…

  19. Not "There" Yet: A Canadian Perspective on the Knowledge Base in Educational Administration.

    ERIC Educational Resources Information Center

    Young, Beth

    A feminist perspective on educational administration in Canada is provided in this paper, which reviews feminist critiques of educational administration research and offers a synthesis of contemporary Canadian feminist research. The main thesis is that the Canadian knowledge base has begun to incorporate the concepts of "Canadian" and "education";…

  20. 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 Moore and…

  1. 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…

  2. 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...

  3. Approximate Degrees of Similarity between a User's Knowledge and the Tutorial Systems' Knowledge Base

    ERIC Educational Resources Information Center

    Mogharreban, Namdar

    2004-01-01

    A typical tutorial system functions by means of interaction between four components: the expert knowledge base component, the inference engine component, the learner's knowledge component and the user interface component. In typical tutorial systems the interaction and the sequence of presentation as well as the mode of evaluation are…

  4. 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…

  5. 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.

  6. 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.

  7. Simultaneous Mapping of Interactions between Scientific and Technological Knowledge Bases: The Case of Space Communications.

    ERIC Educational Resources Information Center

    Hassan, E.

    2003-01-01

    Examines the knowledge structure of the field of space communications using bibliometric mapping techniques based on textual analysis. Presents a new approach with the aim of visualizing simultaneously the configuration of the scientific and technological knowledge bases at a worldwide level, and discusses results that show different…

  8. 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…

  9. 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…

  10. 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…

  11. 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 proposed by…

  12. The Unintended Consequences of a Standardized Knowledge Base in Advancing Educational Leadership Preparation

    ERIC Educational Resources Information Center

    English, Fenwick W.

    2006-01-01

    Background: The quest for a "knowledge base" in educational administration resulting in the construction of national standards for preparing school leaders has brought with it an unexpected downside. Purpose: It is argued that instead of raising the bar for preparing educational leaders, the standards have lowered them, first by embracing only a…

  13. 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.

  14. 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…

  15. 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…

  16. Promoting women's health: redefining the knowledge base and strategies for change.

    PubMed

    Ruzek, S; Hill, J

    1986-01-01

    Promoting women's health involves undertaking a critical gender-based analysis of women's health status and health needs and the knowledge bases which underlie health promotion action. The authors argue that professional and lay definitions of health problems often differ and that these differences stem from a differential emphasis on existing knowledge bases. Here the authors explore the focus of epidemiological, clinical, and experiential knowledge and suggest ways in which each does or does not address many key health issues which women themselves identify as important. Attention is also directed towards women's own suppressed and devalued knowledge as embodied in traditional folk practices and alternative care forms. Recommendations are made to improve existing knowledge bases by transforming some of the value orientations, priorities, methods and the social organization of research. The authors suggest that positive health promotion strategies must be based on an improved knowledge base and must incorporate three key concepts which women emphasize as central--self determination, women-centred values, and a gender-based political analysis. Strategies and methods to achieve these ends are suggested for health educators and policy-makers who wish to develop more positive approaches to promoting women's health. PMID:10286863

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

    ERIC Educational Resources Information Center

    Humphrey, Suzanne; Miller, Nancy E.

    1987-01-01

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

  18. 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 "learning…

  19. 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…

  20. 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…

  1. Towards a unified approach to the design of knowledge based agile manufacturing systems: Part 1 - methodology

    SciTech Connect

    Jones, A.H.; Uzam, M.

    1996-12-31

    To date there are no general techniques available to design Knowledge Based Discrete Event Control Systems. In this paper, a new technique is proposed which solves the problem. The generality of the technique means that the method can be applied to any complex (multi-component) Discrete Event Control problem and can easily accommodate diagnostics and reconfiguration. The technique involves firstly, defining the complex Discrete Event Control system as a colored Petri net controller and then converting colored Petri net controller into a colored Token Passing Logic Controller via Token Passing Logic (TPL) technique and finally, representing the colored Token Passing Logic Controller as rules within a control knowledge base for use within a concurrent inference engine. The technique is described by considering the fundamental structures inherent in colored Petri net control design and shows how to convert these structures into a knowledge base suitable for Discrete Event Control. Moreover, a context sensitive concurrent inference engine is also proposed to ensure the correct processing of the control knowledge base. An illustrative example of how this methodology can be applied to a complex discrete event control problem is described in Part II.

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

    PubMed

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

    1998-01-01

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

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

    PubMed

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

    1998-01-01

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

  4. A knowledge based search tool for performance measures in health care systems.

    PubMed

    Beyan, Oya D; Baykal, Nazife

    2012-02-01

    Performance measurement is vital for improving the health care systems. However, we are still far from having accepted performance measurement models. Researchers and developers are seeking comparable performance indicators. We developed an intelligent search tool to identify appropriate measures for specific requirements by matching diverse care settings. We reviewed the literature and analyzed 229 performance measurement studies published after 2000. These studies are evaluated with an original theoretical framework and stored in the database. A semantic network is designed for representing domain knowledge and supporting reasoning. We have applied knowledge based decision support techniques to cope with uncertainty problems. As a result we designed a tool which simplifies the performance indicator search process and provides most relevant indicators by employing knowledge based systems.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. PVDaCS - A prototype knowledge-based expert system for certification of spacecraft data

    NASA Technical Reports Server (NTRS)

    Wharton, Cathleen; Shiroma, Patricia J.; Simmons, Karen E.

    1989-01-01

    On-line data management techniques to certify spacecraft information are mandated by increasing telemetry rates. Knowledge-based expert systems offer the ability to certify data electronically without the need for time-consuming human interaction. Issues of automatic certification are explored by designing a knowledge-based expert system to certify data from a scientific instrument, the Orbiter Ultraviolet Spectrometer, on an operating NASA planetary spacecraft, Pioneer Venus. The resulting rule-based system, called PVDaCS (Pioneer Venus Data Certification System), is a functional prototype demonstrating the concepts of a larger system design. A key element of the system design is the representation of an expert's knowledge through the usage of well ordered sequences. PVDaCS produces a certification value derived from expert knowledge and an analysis of the instrument's operation. Results of system performance are presented.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    1990-03-01

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

  13. A knowledge-based system for optimization of fuel reload configurations

    SciTech Connect

    Galperin, A.; Kimhi, S.; Segev, M. )

    1989-05-01

    The authors discuss a knowledge-based production system developed for generating optimal fuel reload configurations. The system was based on a heuristic search method and implemented in Common Lisp programming language. The knowledge base embodied the reactor physics, reactor operations, and a general approach to fuel management strategy. The data base included a description of the physical system involved, i.e., the core geometry and fuel storage. The fifth cycle of the Three Mile Island Unit 1 pressurized water reactor was chosen as a test case. Application of the system to the test case revealed a self-learning process by which a relatively large number of near-optimal configurations were discovered. Several selected solutions were subjected to detailed analysis and demonstrated excellent performance. To summarize, applicability of the proposed heuristic search method in the domain of nuclear fuel management was proved unequivocally.

  14. 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.

  15. An RDF/OWL knowledge base for query answering and decision support in clinical pharmacogenetics.

    PubMed

    Samwald, Matthias; Freimuth, Robert; Luciano, Joanne S; Lin, Simon; Powers, Robert L; Marshall, M Scott; Adlassnig, Klaus-Peter; Dumontier, Michel; Boyce, Richard D

    2013-01-01

    Genetic testing for personalizing pharmacotherapy is bound to become an important part of clinical routine. To address associated issues with data management and quality, we are creating a semantic knowledge base for clinical pharmacogenetics. The knowledge base is made up of three components: an expressive ontology formalized in the Web Ontology Language (OWL 2 DL), a Resource Description Framework (RDF) model for capturing detailed results of manual annotation of pharmacogenomic information in drug product labels, and an RDF conversion of relevant biomedical datasets. Our work goes beyond the state of the art in that it makes both automated reasoning as well as query answering as simple as possible, and the reasoning capabilities go beyond the capabilities of previously described ontologies.

  16. Knowledge based system for runtime controlling of multiscale model of ion-exchange solvent extraction

    NASA Astrophysics Data System (ADS)

    Macioł, Piotr; Gotfryd, Leszek; Macioł, Andrzej

    2012-09-01

    The hereby paper concerns the issue of solution of runtime controlling of multiscale model of ion-exchange solvent extraction. It is based on cooperation of a framework applying Agile Multiscale Modeling Methodology (AM3), and the REBIT Knowledge Based System. Ion-exchange solvent extraction has been shortly introduced. Design assumptions of AM3 and theoretical basis of REBIT have been described. Designed workflows and rules for simple laminar/ turbulent flow and extraction processes have been shown.

  17. A knowledge-based decision support system in bioinformatics: an application to protein complex extraction

    PubMed Central

    2013-01-01

    Background We introduce a Knowledge-based Decision Support System (KDSS) in order to face the Protein Complex Extraction issue. Using a Knowledge Base (KB) coding the expertise about the proposed scenario, our KDSS is able to suggest both strategies and tools, according to the features of input dataset. Our system provides a navigable workflow for the current experiment and furthermore it offers support in the configuration and running of every processing component of that workflow. This last feature makes our system a crossover between classical DSS and Workflow Management Systems. Results We briefly present the KDSS' architecture and basic concepts used in the design of the knowledge base and the reasoning component. The system is then tested using a subset of Saccharomyces cerevisiae Protein-Protein interaction dataset. We used this subset because it has been well studied in literature by several research groups in the field of complex extraction: in this way we could easily compare the results obtained through our KDSS with theirs. Our system suggests both a preprocessing and a clustering strategy, and for each of them it proposes and eventually runs suited algorithms. Our system's final results are then composed of a workflow of tasks, that can be reused for other experiments, and the specific numerical results for that particular trial. Conclusions The proposed approach, using the KDSS' knowledge base, provides a novel workflow that gives the best results with regard to the other workflows produced by the system. This workflow and its numeric results have been compared with other approaches about PPI network analysis found in literature, offering similar results. PMID:23368995

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Travel-time correction surface generation for the DOE Knowledge Base

    SciTech Connect

    Hipp, J.; Young, C.; Keyser, R.

    1997-08-01

    The DOE Knowledge Base data storage and access model consists of three parts: raw data processing, intermediate surface generation, and final output surface interpolation. The paper concentrates on the second step, surface generation, specifically applied to travel-time correction data. The surface generation for the intermediate step is accomplished using a modified kriging solution that provides robust error estimates for each for each interpolated point and satisfies many important physical requirements including differing quality data points, user-definable range of influence for each point, blend to background values for both interpolated values and error estimates beyond the ranges, and the ability to account for the effects of geologic region boundaries. These requirements are outlined and discussed and are linked to requirements specified for the final output model in the DOE Knowledge Base. Future work will focus on testing the entire Knowledge Base model using the regional calibration data sets which are being gathered by researchers at Los Alamos and Lawrence Livermore National Laboratories.

  4. 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.

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

    SciTech Connect

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

    1990-11-01

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

  6. MHCWeb: converting a WWW database into a knowledge-based collaborative environment.

    PubMed Central

    Hon, L.; Abernethy, N. F.; Brusic, V.; Chai, J.; Altman, R. B.

    1998-01-01

    The World Wide Web (WWW) is useful for distributing scientific data. Most existing web data resources organize their information either in structured flat files or relational databases with basic retrieval capabilities. For databases with one or a few simple relations, these approaches are successful, but they can be cumbersome when there is a data model involving multiple relations between complex data. We believe that knowledge-based resources offer a solution in these cases. Knowledge bases have explicit declarations of the concepts in the domain, along with the relations between them. They are usually organized hierarchically, and provide a global data model with a controlled vocabulary. We have created the OWEB architecture for building online scientific data resources using knowledge bases. OWEB provides a shell for structuring data, providing secure and shared access, and creating computational modules for processing and displaying data. In this paper, we describe the translation of the online immunological database MHCPEP into an OWEB system called MHCWeb. This effort involved building a conceptual model for the data, creating a controlled terminology for the legal values for different types of data, and then translating the original data into the new structure. The OWEB environment allows for flexible access to the data by both users and computer programs. Images Figure 1 Figure 2 Figure 3 Figure 4 PMID:9929358

  7. 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. PMID:24997857

  8. 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.

  9. Can Croatia join Europe as competitive knowledge-based society by 2010?

    PubMed

    Petrovecki, Mladen; Paar, Vladimir; Primorac, Dragan

    2006-12-01

    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 valuable commodities 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 4 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. A knowledge-based design for assemble system for vehicle seat

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    Companies worldwide are striving to reduce the costs of their products to impact their bottom line profitability. When it comes to improving profits, there are in two choices: sell more or cut the cost of what is currently being sold. Given the depressed economy of the last several years, the "sell more" option, in many cases, has been taken off the table. As a result, cost cutting is often the most effective path. One of the industrial challenges is to search for the shorten product development and lower manufacturing cost especially in the early stage of designing the product. Knowledge-based system is used to assist the industry when the expert is not available and to keep the expertise within the company. The application of knowledge-based system will enable the standardization and accuracy of the assembly process. For this purpose, a knowledge-based design for assemble system is developed to assist the industry to plan the assembly process of the vehicle seat.

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

    PubMed

    Humphrey, S M; Miller, N E

    1987-05-01

    This article describes the Indexing Aid Project for conducting research in the areas of knowledge representation and indexing for information retrieval in order to develop interactive knowledge-based systems for computer-assisted indexing of the periodical medical literature. The system uses an experimental frame-based knowledge representation language, FrameKit, implemented in Franz Lisp. The initial prototype is designed to interact with trained MEDLINE indexers who will be prompted to enter subject terms as slot values in filling in document-specific frame data structures that are derived from the knowledge-base frames. In addition, the automatic application of rules associated with the knowledge-base frames produces a set of Medical Subject Heading (MeSH) keyword indices to the document. Important features of the system are representation of explicit relationships through slots which express the relations; slot values, restrictions, and rules made available by inheritance through "is-a" hierarchies; slot values denoted by functions that retrieve values from other slots; and restrictions on slot values displayable during data entry. PMID:10301519

  17. 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

  18. 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

  19. Points of Departure: Developing the Knowledge Base of ESL and FSL Teachers for K-12 Programs in Canada

    ERIC Educational Resources Information Center

    Faez, Farahnaz

    2011-01-01

    In this paper I examine similarities and differences between the required knowledge base of teachers of English as a second language (ESL) and French as a second language (FSL) for teaching in Kindergarten through Grade 12 programs in Canada. Drawing on knowledge base frameworks in language teacher education (Freeman and Johnson, 1998; Richards,…

  20. 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.

  1. 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.)

  2. 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

  3. 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.

  4. Parametric Grid Information in the DOE Knowledge Base: Data Preparation, Storage, and Access

    SciTech Connect

    HIPP,JAMES R.; MOORE,SUSAN G.; MYERS,STEPHEN C.; SCHULTZ,CRAIG A.; SHEPHERD,ELLEN; YOUNG,CHRISTOPHER J.

    1999-10-01

    The parametric grid capability of the Knowledge Base provides an efficient, robust way to store and access interpolatable information which is needed to monitor the Comprehensive Nuclear Test Ban Treaty. To meet both the accuracy and performance requirements of operational monitoring systems, we use a new approach which combines the error estimation of kriging with the speed and robustness of Natural Neighbor Interpolation (NNI). The method involves three basic steps: data preparation (DP), data storage (DS), and data access (DA). The goal of data preparation is to process a set of raw data points to produce a sufficient basis for accurate NNI of value and error estimates in the Data Access step. This basis includes a set of nodes and their connectedness, collectively known as a tessellation, and the corresponding values and errors that map to each node, which we call surfaces. In many cases, the raw data point distribution is not sufficiently dense to guarantee accurate error estimates from the NNI, so the original data set must be densified using a newly developed interpolation technique known as Modified Bayesian Kriging. Once appropriate kriging parameters have been determined by variogram analysis, the optimum basis for NNI is determined in a process they call mesh refinement, which involves iterative kriging, new node insertion, and Delauny triangle smoothing. The process terminates when an NNI basis has been calculated which will fir the kriged values within a specified tolerance. In the data storage step, the tessellations and surfaces are stored in the Knowledge Base, currently in a binary flatfile format but perhaps in the future in a spatially-indexed database. Finally, in the data access step, a client application makes a request for an interpolated value, which triggers a data fetch from the Knowledge Base through the libKBI interface, a walking triangle search for the containing triangle, and finally the NNI interpolation.

  5. Parametric Grid Information in the DOE Knowledge Base: Data Preparation, Storage and Access.

    SciTech Connect

    Hipp, J. R.; Young, C. J.; Moore, S. G.; Shepherd, E. R.; Schultz, C. A.; Myers, S. C.

    1999-10-01

    The parametric grid capability of the Knowledge Base provides an efficient, robust way to store and access interpolatable information which is needed to monitor the Comprehensive Nuclear Test Ban Treaty. To meet both the accuracy and performance requirements of operational monitoring systems, we use a new approach which combines the error estimation of kriging with the speed and robustness of Natural Neighbor Interpolation (NNI). The method involves three basic steps: data preparation (DP), data storage (DS), and data access (DA). The goal of data preparation is to process a set of raw data points to produce a sufficient basis for accurate NNI of value and error estimates in the Data Access step. This basis includes a set of nodes and their connectedness, collectively known as a tessellation, and the corresponding values and errors that map to each node, which we call surfaces. In many cases, the raw data point distribution is not sufficiently dense to guarantee accurate error estimates from the NNI, so the original data set must be densified using a newly developed interpolation technique known as Modified Bayesian Kriging. Once appropriate kriging parameters have been determined by variogram analysis, the optimum basis for NNI is determined in a process we call mesh refinement, which involves iterative kriging, new node insertion, and Delauny triangle smoothing. The process terminates when an NNI basis has been calculated which will fit the kriged values within a specified tolerance. In the data storage step, the tessellations and surfaces are stored in the Knowledge Base, currently in a binary flatfile format but perhaps in the future in a spatially-indexed database. Finally, in the data access step, a client application makes a request for an interpolated value, which triggers a data fetch from the Knowledge Base through the libKBI interface, a walking triangle search for the containing triangle, and finally the NNI interpolation.

  6. 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.

  7. 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.

  8. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

  10. Knowledge-based control of grasping in robot hands using heuristics from human motor skills

    SciTech Connect

    Bekey, G.A. . Computer Science Dept.); Liu, H. . Artificial Intelligence Systems Section); Tomovic, R. . Dept. of Electrical Engineering); Karplus, W.J. . Computer Science Dept.)

    1993-12-01

    The development of a grasp planner for multifingered robot hands is described. The planner is knowledge-based, selecting grasp postures by reasoning from symbolic information on target object geometry and the nature of the task. The ability of the planner to utilize task information is based on an attempt to mimic human grasping behavior. Several task attributes and a set of heuristics derived from observation of human motor skills are included in the system. The paper gives several examples of the reasoning of the system in selecting the appropriate grasp mode for spherical and cylindrical objects for different tasks.

  11. 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.

  12. 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.

  13. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1990-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  16. 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.

  17. 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).

  18. Improvements on transient characteristics of transverse flux homopolar linear machines using artificial knowledge-based strategy

    SciTech Connect

    Liu, C.T.; Kuo, J.L.

    1995-06-01

    This paper, which continues the preceding works will provide further detailed discussions about both parasitic hunting-effect alleviation of transverse flux homopolar linear induction machine (TFLIM), and improvement on closed-loop transient characteristics of transverse flux homopolar linear oscillating machine (TFLOM). Novel artificial knowledge-based compensators are proposed here to solve above problems for these time-varying and highly nonlinear machine systems. It will be shown that not only this approach is easy of practical implementation, but also the involved design tasks of such compensators are applicable for other linear machine control objectives. Illustrations and verifications will be supplied to confirm the graceful features of this intelligent strategy.

  19. Knowledge-Based Motion Control of AN Intelligent Mobile Autonomous System

    NASA Astrophysics Data System (ADS)

    Isik, Can

    An Intelligent Mobile Autonomous System (IMAS), which is equipped with vision and low level sensors to cope with unknown obstacles, is modeled as a hierarchy of path planning and motion control. This dissertation concentrates on the lower level of this hierarchy (Pilot) with a knowledge-based controller. The basis of a theory of knowledge-based controllers is established, using the example of the Pilot level motion control of IMAS. In this context, the knowledge-based controller with a linguistic world concept is shown to be adequate for the minimum time control of an autonomous mobile robot motion. The Pilot level motion control of IMAS is approached in the framework of production systems. The three major components of the knowledge-based control that are included here are the hierarchies of the database, the rule base and the rule evaluator. The database, which is the representation of the state of the world, is organized as a semantic network, using a concept of minimal admissible vocabulary. The hierarchy of rule base is derived from the analytical formulation of minimum-time control of IMAS motion. The procedure introduced for rule derivation, which is called analytical model verbalization, utilizes the concept of causalities to describe the system behavior. A realistic analytical system model is developed and the minimum-time motion control in an obstacle strewn environment is decomposed to a hierarchy of motion planning and control. The conditions for the validity of the hierarchical problem decomposition are established, and the consistency of operation is maintained by detecting the long term conflicting decisions of the levels of the hierarchy. The imprecision in the world description is modeled using the theory of fuzzy sets. The method developed for the choice of the rule that prescribes the minimum-time motion control among the redundant set of applicable rules is explained and the usage of fuzzy set operators is justified. Also included in the

  20. 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.

  1. 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.

  2. Knowledge based systems: A critical survey of major concepts, issues and techniques. Visuals

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

    This Working Paper Series entry represents a collection of presentation visuals associated with the companion report entitled, Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques, USL/DBMS NASA/RECON Working Paper Series report number DBMS.NASA/RECON-9. The objectives of the report are to: examine various techniques used to build the KBS; to examine at least one KBS in detail, i.e., a case study; to list and identify limitations and problems with the KBS; to suggest future areas of research; and to provide extensive reference materials.

  3. C-PHIS: a concept map-based knowledge base framework to develop personal health information systems.

    PubMed

    Karla, Pramukh R; Gurupur, Varadraj P

    2013-10-01

    In this paper we describe the development of a Personal Health Information System using a knowledge base developed using concept maps. Here we describe a solution for providing the critical need to develop an information capturing system that helps domain experts in developing a graphical representation of the aforementioned knowledge base which can then be converted to a machine-actable form of information. A prototype application has been developed using this information capturing system that clearly demonstrates the use of the knowledge base framework using concept maps to develop Personal Health Information System for lung cancer patients.

  4. 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.

  5. Syn-lethality: an integrative knowledge base of synthetic lethality towards discovery of selective anticancer therapies.

    PubMed

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

    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.

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

    NASA Astrophysics Data System (ADS)

    Williams, Chris; Murphy, Robin R.

    2006-05-01

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

  7. 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.

  8. 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.

  9. 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.

  10. Hybrid hill-climbing and knowledge-based methods for intelligent news filtering

    SciTech Connect

    Mock, K.J.

    1996-12-31

    As the size of the Internet increases, the amount of data available to users has dramatically risen, resulting in an information overload for users. This work involved the creation of an intelligent information news filtering system named INFOS (Intelligent News Filtering Organizational System) to reduce the user`s search burden by automatically eliminating Usenet news articles predicted to be irrelevant. These predictions are learned automatically by adapting an internal user model that is based upon features taken from articles and collaborative features derived from other users. The features are manipulated through keyword-based techniques and knowledge-based techniques to perform the actual filtering. Knowledge-based systems have the advantage of analyzing input text in detail, but at the cost of computational complexity and the difficulty of scaling up to large domains. In contrast, statistical and keyword approaches scale up readily but result in a shallower understanding of the input. A hybrid system integrating both approaches improves accuracy over keyword approaches, supports domain knowledge, and retains scalability. The system would be enhanced by more robust word disambiguation.

  11. 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.

  12. Three-dimensional reconstruction of pulmonary blood vessels by using anatomical knowledge base

    NASA Astrophysics Data System (ADS)

    Inaoka, Noriko; Suzuki, Hideo; Mori, Masaki; Takabatake, Hirotsugu; Suzuki, Akira

    1991-07-01

    This paper presents a knowledge-based method for automatic reconstruction and recognition of pulmonary blood vessels from chest x-ray CT images with 10-mm thickness. The system has four main stages: (1) automatic extraction and segmentation of blood vessel components from each 2-D image, (2) analysis of these components, (3) a search for points connecting blood vessel segments in different CT slices, using a knowledge base for 3-D reconstruction, and (4) object manipulation and display. The authors also describe a method of representing 3-D anatomical knowledge of the pulmonary blood vessel structure. The edges of blood vessels in chest x-ray images are unclear, in contrast to those in angiograms. Each CT slice has thickness, and blood vessels are slender, so a simple graphical display, which can be used for bone tissues from CT images, is not sufficient for pulmonary blood vessels. It is therefore necessary to use anatomical knowledge to track the blood vessel lines in 3-D spaces. Experimental results using actual images of a normal adult male has shown that utilizing anatomical information enables one to improve processing efficiency and precision, such as blood vessel extraction and searching for connecting points.

  13. 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.

  14. 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. PMID:24113639

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

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  16. 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

  17. SIGMA: A Knowledge-Based Simulation Tool Applied to Ecosystem Modeling

    NASA Technical Reports Server (NTRS)

    Dungan, Jennifer L.; Keller, Richard; Lawless, James G. (Technical Monitor)

    1994-01-01

    The need for better technology to facilitate building, sharing and reusing models is generally recognized within the ecosystem modeling community. The Scientists' Intelligent Graphical Modelling Assistant (SIGMA) creates an environment for model building, sharing and reuse which provides an alternative to more conventional approaches which too often yield poorly documented, awkwardly structured model code. The SIGMA interface presents the user a list of model quantities which can be selected for computation. Equations to calculate the model quantities may be chosen from an existing library of ecosystem modeling equations, or built using a specialized equation editor. Inputs for dim equations may be supplied by data or by calculation from other equations. Each variable and equation is expressed using ecological terminology and scientific units, and is documented with explanatory descriptions and optional literature citations. Automatic scientific unit conversion is supported and only physically-consistent equations are accepted by the system. The system uses knowledge-based semantic conditions to decide which equations in its library make sense to apply in a given situation, and supplies these to the user for selection. "Me equations and variables are graphically represented as a flow diagram which provides a complete summary of the model. Forest-BGC, a stand-level model that simulates photosynthesis and evapo-transpiration for conifer canopies, was originally implemented in Fortran and subsequenty re-implemented using SIGMA. The SIGMA version reproduces daily results and also provides a knowledge base which greatly facilitates inspection, modification and extension of Forest-BGC.

  18. 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

  19. The Digital Anatomist distributed framework and its applications to knowledge-based medical imaging.

    PubMed

    Brinkley, J F; Rosse, C

    1997-01-01

    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

  20. 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

  1. NSIDC Knowledge Base: Using Knowledge Networking Tools to Help Data Users to Help Themselves

    NASA Astrophysics Data System (ADS)

    McAllister, M.; Tressel, S.

    2012-12-01

    In the age of information, scientists and non-scientists alike expect answers to their questions to be available on LCD display with just a few clicks of a mouse. Over the past decade, NSIDC User Services has seen a sizable increase in total data users, with a growing percentage coming from non-science backgrounds. In order to meet the demands of so many curious minds and to better appeal to the diversifying user community, NSIDC User Services is in the process of utilizing professional helpdesk software to create NSIDC Knowledge Base: a multimedia platform for supporting data users. Ultimately, searchable, referenced articles on common user problems and FAQ's will appear beside video tutorials demonstrating how to use the data. Links to other data centers' user support departments will be offered when questions expand beyond the scope of NSIDC. NSIDC Knowledge Base aims to be a resource allowing users to help themselves as well as a gateway to finding resources at related data centers.

  2. Predicting Mycobacterium tuberculosis complex clades using knowledge-based Bayesian networks.

    PubMed

    Aminian, Minoo; Couvin, David; Shabbeer, Amina; Hadley, Kane; Vandenberg, Scott; Rastogi, Nalin; 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.

  3. An architecture for performance optimization in a collaborative knowledge-based approach for wireless sensor networks.

    PubMed

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

    2011-01-01

    Over the past few years, Intelligent Spaces (ISs) have received the attention of many Wireless Sensor Network researchers. Recently, several studies have been devoted to identify their common capacities and to set up ISs over these networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks for the purpose of implementing ISs. This work presents a distributed architecture proposal for collaborative Fuzzy Rule-Based Systems embedded in Wireless Sensor Networks, which has been designed to optimize the implementation of ISs. This architecture includes the following: (a) an optimized design for the inference engine; (b) a visual interface; (c) a module to reduce the redundancy and complexity of the knowledge bases; (d) a module to evaluate the accuracy of the new knowledge base; (e) a module to adapt the format of the rules to the structure used by the inference engine; and (f) a communications protocol. As a real-world application of this architecture and the proposed methodologies, we show an application to the problem of modeling two plagues of the olive tree: prays (olive moth, Prays oleae Bern.) and repilo (caused by the fungus Spilocaea oleagina). The results show that the architecture presented in this paper significantly decreases the consumption of resources (memory, CPU and battery) without a substantial decrease in the accuracy of the inferred values.

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

    NASA Astrophysics Data System (ADS)

    Cheng, Linfu; McKendrick, John D.

    1989-03-01

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

  5. Creation of a master table for checking indication and contraindication of medicine from a knowledge base linked with a thesaurus.

    PubMed

    Ji, Shanmei; Matsumura, Yasushi; Kuwata, Shigeki; Nakano, Hirohiko; Chen, Yufeng; Teratani, Tadamasa; Zhang, Qiyan; Mineno, Takahiro; Takeda, Hiroshi

    2004-12-01

    To develop a system for checking indication and contraindication of medicines in prescription order entry system, a master table consisting of the disease names corresponding to the medicines adopted in a hospital is needed. The creation of this table requires a considerable manpower. We developed a Web-based system for constructing a medicine/disease thesaurus and a knowledge base. By authority management of users, this system enables many specialists to create the thesaurus collaboratively without confusion. It supports the creation of a knowledge base using concept names by referring to the thesaurus, which is automatically converted to the check master table. When a disease name or medicine name was added to the thesaurus, the check table was automatically updated. We constructed a thesaurus and a knowledge base in the field of circulatory system disease. The knowledge base linked with the thesaurus proved to be efficient for making the check master table for indication/contraindication of medicines.

  6. 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...

  7. 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

  8. An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic

    NASA Astrophysics Data System (ADS)

    Zhu, A.-Xing; Wang, Rongxun; Qiao, Jianping; Qin, Cheng-Zhi; Chen, Yongbo; Liu, Jing; Du, Fei; Lin, Yang; Zhu, Tongxin

    2014-06-01

    This paper presents an expert knowledge-based approach to landslide susceptibility mapping in an effort to overcome the deficiencies of data-driven approaches. The proposed approach consists of three generic steps: (1) extraction of knowledge on the relationship between landslide susceptibility and predisposing factors from domain experts, (2) characterization of predisposing factors using GIS techniques, and (3) prediction of landslide susceptibility under fuzzy logic. The approach was tested in two study areas in China - the Kaixian study area (about 250 km2) and the Three Gorges study area (about 4600 km2). The Kaixian study area was used to develop the approach and to evaluate its validity. The Three Gorges study area was used to test both the portability and the applicability of the developed approach for mapping landslide susceptibility over large study areas. Performance was evaluated by examining if the mean of the computed susceptibility values at landslide sites was statistically different from that of the entire study area. A z-score test was used to examine the statistical significance of the difference. The computed z for the Kaixian area was 3.70 and the corresponding p-value was less than 0.001. This suggests that the computed landslide susceptibility values are good indicators of landslide occurrences. In the Three Gorges study area, the computed z was 10.75 and the corresponding p-value was less than 0.001. In addition, we divided the susceptibility value into four levels: low (0.0-0.25), moderate (0.25-0.5), high (0.5-0.75) and very high (0.75-1.0). No landslides were found for areas of low susceptibility. Landslide density was about three times higher in areas of very high susceptibility than that in the moderate susceptibility areas, and more than twice as high as that in the high susceptibility areas. The results from the Three Gorge study area suggest that the extracted expert knowledge can be extrapolated to another study area and the

  9. Enabling the use of hereditary information from pedigree tools in medical knowledge-based systems.

    PubMed

    Gay, Pablo; López, Beatriz; Plà, Albert; Saperas, Jordi; Pous, Carles

    2013-08-01

    The use of family information is a key issue to deal with inheritance illnesses. This kind of information use to come in the form of pedigree files, which contain structured information as tree or graphs, which explains the family relationships. Knowledge-based systems should incorporate the information gathered by pedigree tools to assess medical decision making. In this paper, we propose a method to achieve such a goal, which consists on the definition of new indicators, and methods and rules to compute them from family trees. The method is illustrated with several case studies. We provide information about its implementation and integration on a case-based reasoning tool. The method has been experimentally tested with breast cancer diagnosis data. The results show the feasibility of our methodology.

  10. 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.

  11. 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.

  12. Mathematics/Arithmetic Knowledge-Based Way of Thinking and Its Maintenance Needed for Engineers

    NASA Astrophysics Data System (ADS)

    Harada, Shoji

    Examining curriculum among universities revealed that no significant difference in math class or related subjects can be seen. However, amount and depth of those studies, in general, differed depending on content of curriculum and the level of achievement at entrance to individual university. Universalization of higher education shows that students have many problems in learning higher level of traditional math and that the memory of math they learned quickly fades away after passing in exam. It means that further development of higher math knowledgebased engineer after graduation from universities. Under these circumstances, the present author, as one of fun of math, propose how to maintain way of thinking generated by math knowledge. What necessary for engineer is to pay attention to common books, dealing with elementary mathematics or arithmetic- related matters. This surely leads engineer to nourish math/arithmetic knowledge-based way of thinking.

  13. 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.

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

    PubMed

    Ferdinand, Jason

    The concept of cyber resilience has emerged in recent years in response to the recognition that cyber security is more than just risk management. Cyber resilience is the goal of organisations, institutions and governments across the world and yet the emerging literature is somewhat fragmented due to the lack of a common approach to the subject. This limits the possibility of effective collaboration across public, private and governmental actors in their efforts to build and maintain cyber resilience. In response to this limitation, and to calls for a more strategically focused approach, this paper offers a knowledge-based view of cyber security management that explains how an organisation can build, assess, and maintain cyber resilience. PMID:26642176

  15. 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

  16. 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.

  17. Analyzing Knowledge Base Content Development and Review: Recommendations for a Robust Knowledge Management Infrastructure

    PubMed Central

    Wilkinson, Steven G.; Rocha, Roberto A.; Rhodes, Julie

    2002-01-01

    Change is a necessary function of good medicine and quality health care and will undoubtedly be vital for the future. As advances in medicine continue, so will change, requiring the need for maintenance of existing knowledge as well as the need for integrating new knowledge. In order to understand the current process at Intermountain Health Care and to see how we might improve this process, we retrospectively studied the changes made to a knowledge base during the year 2001. The findings discovered have implications that are guiding our efforts in designing a knowledge management infrastructure. Additionally, we propose to integrate recommendations from other researchers into the design that will not only assist in the development and maintenance of knowledge, but will also support change tracking and version control.

  18. Application of knowledge-based network management techniques for packet radio networks

    NASA Astrophysics Data System (ADS)

    Doyle, R. J.; Sastry, A. R. K.

    The authors developed a preliminary version of a knowledge-based model for network management and reconfiguration using blackboard techniques and have applied it to packet radio networks. The analysis is concerned with developing procedures for evaluation of candidate recovery/reconfiguration methodologies and techniques for fault isolation and related monitoring functions. As an initial step, the generic blackboard was chosen as the artificial intelligence environment to develop the management tools and interlink it to a packet radio network simulator that was used as a testbed network to be controlled and monitored. The details of the interaction of the management environment and the packet radio simulator as implemented in the model so far, and present numerical results obtained through the execution of some preliminary rules are described.

  19. 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.

  20. Knowledge-base for interpretation of cerebrospinal fluid data patterns. Essentials in neurology and psychiatry.

    PubMed

    Reiber, Hansotto

    2016-06-01

    The physiological and biophysical knowledge base for interpretations of cerebrospinal fluid (CSF) data and reference ranges are essential for the clinical pathologist and neurochemist. With the popular description of the CSF flow dependent barrier function, the dynamics and concentration gradients of blood-derived, brain-derived and leptomeningeal proteins in CSF or the specificity-independent functions of B-lymphocytes in brain also the neurologist, psychiatrist, neurosurgeon as well as the neuropharmacologist may find essentials for diagnosis, research or development of therapies. This review may help to replace the outdated ideas like "leakage" models of the barriers, linear immunoglobulin Index Interpretations or CSF electrophoresis. Calculations, Interpretations and analytical pitfalls are described for albumin quotients, quantitation of immunoglobulin synthesis in Reibergrams, oligoclonal IgG, IgM analysis, the polyspecific ( MRZ- ) antibody reaction, the statistical treatment of CSF data and general quality assessment in the CSF laboratory. The diagnostic relevance is documented in an accompaning review. PMID:27332077

  1. 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.

  2. 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.

  3. 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.

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

    NASA Technical Reports Server (NTRS)

    Yasuda, Phyllis; Mckellar, Donald

    1993-01-01

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

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

    PubMed Central

    Weichselbraun, A.; Gindl, S.; Scharl, A.

    2014-01-01

    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. PMID:25431524

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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. PMID:26495435

  11. 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%.

  12. 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.

  13. 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

  14. 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.

  15. Design of knowledge-based image retrieval system: implications from radiologists' cognitive processes

    NASA Astrophysics Data System (ADS)

    Liu Sheng, Olivia R.; Wei, Chih-Ping; Ozeki, Takeshi; Ovitt, Theron W.; Ishida, Jiro

    1992-07-01

    In a radiological examination reading, radiologists usually compare a newly generated examination with previous examinations of the same patient. For this reason, the retrieval of old images is a critical design requirement of totally digital radiology using Picture Archiving and Communication Systems (PACS). To achieve the required performance in a PACS with a hierarchical and possibly distributed image archival system, pre-fetching of images from slower or remote storage devices to the local buffers of workstations is proposed. Image Retrieval Expert System (IRES) is a knowledge-based image retrieval system which will predict and then pre-fetch relevant old images. Previous work on IRES design focused on the knowledge acquisition phase and the development of an efficient modeling methodology and architecture. The goal of this paper is to evaluate the effectiveness of the current IRES design and to identify appropriate directions for exploring other design features and alternatives by means of a cognitive study and an associated survey study.

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

    NASA Astrophysics Data System (ADS)

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

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

  17. Programming constructs for real-time distributed knowledge-based systems

    SciTech Connect

    Cromarty, A.S.

    1988-01-01

    This study presents a set of mechanisms for use in the construction of distributed knowledge-based systems that must meet such practical performance constraints. These mechanisms are made manifest in the form of programming-language constructs designed to support the development of DKBS's that implement a multiplicity of alternative policies and abstract architectures. The proposed constructs are studied, using two techniques: implementation in an experimental testbed environment and performance measurement in controlled experiments that assess the time cost of interagent communications among loosely-coupled LISP processes. The author's empirical data on interagent communications should prove valuable to DKBS implementors who must meet real-time constraints using contemporary hardware and software technology. It is concluded that it is possible to construct interagent communications cost models that are useful and have a high degree of predictive value. Experimental results indicate that the cost of message-based interagent communications between symbolic processing agents is very high.

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

    PubMed

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

    1998-11-01

    The World-Wide Web (WWW) is increasingly being used as a platform to develop distributed applications, particularly in contexts, such as medical ones, where high usability and availability are required. In this paper we propose a methodology for the development of knowledge-based medical applications on the web, based on the use of an explicit domain ontology to automatically generate parts of the system. We describe a development environment, centred on the LISPWEB Common Lisp HTTP server, that supports this methodology, and we show how it facilitates the creation of complex web-based applications, by overcoming the limitations that normally affect the adequacy of the web for this purpose. Finally, we present an outline of a system for the management of diabetic patients built using the LISPWEB environment. PMID:9821518

  19. Building an organized knowledge base: Concept mapping and achievement in secondary school physics

    NASA Astrophysics Data System (ADS)

    Pankratius, William J.

    Direct teaching of problem-solving methods to high school physics students met with little success. Expert problem solving depended upon an organized knowledge base. Concept mapping was found to be a key to organizing an effective knowledge base. The investigation of the effect of the degree of concept mapping on achievement was the purpose of this study. Six intact high school physics classes, taught by this investigator, took part in the study. Two classes were control groups and received standard instruction. Four classes received six weeks of concept-mapping instruction prior to the unit under study. Two of these four classes were the low-level treatment group and were required to submit concept maps at the conclusion of the instruction. The other two classes were the high-level treatment group and were required to submit concept maps at the beginning and at the conclusion of the unit under study. One class from each treatment group took a pretest prior to instruction. An analysis of the posttest results revealed no pretest sensitization. A one-way analysis of covariance indicated a significant main effect for the treatment level at the p < 0.05 level. A pair of single-df comparisons of the adjusted treatment means resulted in significant differences (p < 0.05) between the control group and the average of the treatment means as well as between the two experimental groups. It can be concluded that for this sample (upper-middle-class high school physics students) mapping concepts prior to, during, and subsequent to instruction led to greater achievement as measured by posttest scores.

  20. 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.

  1. 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.

  2. Knowledge-based medical image analysis and representation for integrating content definition with the radiological report.

    PubMed

    Kulikowski, C A; Gong, L; Mezrich, R S

    1995-03-01

    Technology breakthroughs in high-speed, high-capacity, and high performance desk-top computers and workstations make the possibility of integrating multimedia medical data to better support clinical decision making, computer-aided education, and research not only attractive, but feasible. To systematically evaluate results from increasingly automated image segmentation it is necessary to correlate them with the expert judgments of radiologists and other clinical specialists interpreting the images. These are contained in increasingly computerized radiological reports and other related clinical records. But to make automated comparison feasible it is necessary to first ensure compatibility of the knowledge content of images with the descriptions contained in these records. Enough common vocabulary, language, and knowledge representation components must be represented on the computer, followed by automated extraction of image-content descriptions from the text, which can then be matched to the results of automated image segmentation. A knowledge-based approach to image segmentation is essential to obtain the structured image descriptions needed for matching against the expert's descriptions. We have developed a new approach to medical image analysis which helps generate such descriptions: a knowledge-based object-centered hierarchical planning method for automatically composing the image analysis processes. The problem-solving steps of specialists are represented at the knowledge level in terms of goals, tasks, and domain objects and concepts separately from the implementation level for specific representations of different image types, and generic analysis methods. This system can serve as a major functional component in incrementally building and updating a structured and integrated hybrid information system of patient data.(ABSTRACT TRUNCATED AT 250 WORDS)

  3. 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

  4. 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.

  5. The need and potential for building a integrated knowledge-base of the Earth-Human system

    NASA Astrophysics Data System (ADS)

    Jacobs, Clifford

    2011-03-01

    The pursuit of scientific understanding is increasingly based on interdisciplinary research. To understand more deeply the planet and its interactions requires a progressively more holistic approach, exploring knowledge coming from all scientific and engineering disciplines including but not limited to, biology, chemistry, computer sciences, geosciences, material sciences, mathematics, physics, cyberinfrastucture, and social sciences. Nowhere is such an approach more critical than in the study of global climate change in which one of the major challenges is the development of next-generation Earth System Models that include coupled and interactive representations of ecosystems, agricultural working lands and forests, urban environments, biogeochemistry, atmospheric chemistry, ocean and atmospheric currents, the water cycle, land ice, and human activities.

  6. 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

  7. 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

  8. A germline knowledge based computational approach for determining antibody complementarity determining regions.

    PubMed

    Zhao, Shanrong; Lu, Jin

    2010-01-01

    Determination of framework regions (FRs) and complementarity determining regions (CDRs) in an antibody is essential for understanding the underlying biology as well as antibody engineering and optimization. However, there are no computational algorithms available to delimit an antibody sequence or a library of sequences into FRs and CDRs in a coherent and automatic fashion. Based upon the mapping relationships among mature antibody sequences and their corresponding germline gene segments, a novel computational algorithm has been developed for automatic determination of CDRs. Even though a human can make more than 10(12) different antibody molecules in its preimmune repertoire to fight off invading pathogens, these antibodies are generated from rearrangements of a very limited number of germline variable (V) gene, diversity (D) gene and joining (J) gene segments followed by somatic hypermutation. The framework regions FR1, FR2 and FR3 in mature antibodies are encoded by germline V gene segments, while FR4 is encoded by J gene segments. Since there are only a limited number of germline gene segments, these genes can be pre-delimited to generate a knowledge base of FRs and CDRs. Then for a given antibody sequence, the algorithm scans each pre-delimited gene in knowledge base, finds the best matching V and J segments, and accordingly, identifies the FRs and CDRs. The described algorithm is stringently tested using nearly 25,000 human antibody sequences from NCBI, and it is proven to be very robust. Over 99.7% of antibody sequences can be delimited computationally. Of those delimited sequences, only 0.28% of them have somatic insertions and deletions in FRs, and their corresponding delimited results need manual checking. Another feature of the algorithm is that it is CDR definition independent, and can be easily extended to other CDR definitions besides the most widely used Kabat, Chothia and IMGT definitions. In addition to delimitation of antibody sequences into FRs

  9. Northeast Artificial Intelligence Consortium (NAIC). Volume 11. Knowledge-base maintenance. Final report, Sep 84-Dec 89

    SciTech Connect

    Bowen, K.

    1990-12-01

    The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and the Office of Scientific Research. Its purpose was to conduct pertinent research in artificial intelligence and to perform activities ancillary to this research. This report describes progress during the existence of the NAIC on the technical research tasks undertaken at the member universities. The topics covered in general are: versatile expert system for equipment maintenance, distributed AI for communications system control, automatic photointerpretation, time-oriented problem solving, speech understanding systems, knowledge based maintenance, hardware architectures for very large systems, knowledge based reasoning and planning, and a knowledge acquisition, assistance, and explanation system. The specific topic for this volume is the use of logic programming methodologies for knowledge base maintenance.

  10. 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.

  11. 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.

  12. Applications of the automatic change detection for disaster monitoring by the knowledge-based framework

    NASA Astrophysics Data System (ADS)

    Tadono, T.; Hashimoto, S.; Onosato, M.; Hori, M.

    2012-11-01

    Change detection is a fundamental approach in utilization of satellite remote sensing image, especially in multi-temporal analysis that involves for example extracting damaged areas by a natural disaster. Recently, the amount of data obtained by Earth observation satellites has increased significantly owing to the increasing number and types of observing sensors, the enhancement of their spatial resolution, and improvements in their data processing systems. In applications for disaster monitoring, in particular, fast and accurate analysis of broad geographical areas is required to facilitate efficient rescue efforts. It is expected that robust automatic image interpretation is necessary. Several algorithms have been proposed in the field of automatic change detection in past, however they are still lack of robustness for multi purposes, an instrument independency, and accuracy better than a manual interpretation. We are trying to develop a framework for automatic image interpretation using ontology-based knowledge representation. This framework permits the description, accumulation, and use of knowledge drawn from image interpretation. Local relationships among certain concepts defined in the ontology are described as knowledge modules and are collected in the knowledge base. The knowledge representation uses a Bayesian network as a tool to describe various types of knowledge in a uniform manner. Knowledge modules are synthesized and used for target-specified inference. The results applied to two types of disasters by the framework without any modification and tuning are shown in this paper.

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

    PubMed

    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

  14. 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.

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

    PubMed

    Chellapandi, P; Ranjani, J

    2015-09-01

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

  17. 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.

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

    SciTech Connect

    Tung, S.I.

    1986-01-01

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

  19. Weaning Patients From Mechanical Ventilation: A Knowledge-Based System Approach

    PubMed Central

    Tong, David A.

    1990-01-01

    The WEANing PROtocol (WEANPRO) knowledge-based system assists respiratory therapists and nurses in weaning post-operative cardiovascular patients from mechanical ventilation in the intensive care unit. The knowledge contained in WEANPRO is represented by rules and is implemented in M.1® by Teknowledge, Inc. WEANPRO will run on any IBM® compatible microcomputer. WEANPRO's performance in weaning patients in the intensive care unit was evaluated three ways: (1) a statistical comparison between the mean number of arterial blood gases required to wean patients to a T-piece with and without the use of WEANPRO, (2) a critique of the suggestions offered by the system by clinicians not involved in the system development, and (3) an inspection of the user's acceptance of WEANPRO in the intensive care unit. The results of the evaluations revealed that using WEANPRO significantly decreases the number of arterial blood gas analyses needed to wean patients from total dependance on mechanical ventilation to independent breathing using a T-piece. In doing so, WEANPRO's suggestions are accurate and its use is accepted by the clinicians. Currently, WEANPRO is being used in the intensive care unit at the East Unit of Baptist Memorial Hospital in Memphis, Tennessee.

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

    PubMed

    Finn, Jessica A; Koehler Leman, Julia; Willis, Jordan R; Cisneros, Alberto; Crowe, James E; Meiler, Jens

    2016-01-01

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

  1. Lynx: a knowledge base and an analytical workbench for integrative medicine.

    PubMed

    Sulakhe, Dinanath; Xie, Bingqing; Taylor, Andrew; D'Souza, Mark; Balasubramanian, Sandhya; Hashemifar, Somaye; White, Steven; Dave, Utpal J; Agam, Gady; Xu, Jinbo; Wang, Sheng; Gilliam, T Conrad; Maltsev, Natalia

    2016-01-01

    Lynx (http://lynx.ci.uchicago.edu) is a web-based database and a knowledge extraction engine. It supports annotation and analysis of high-throughput experimental data and generation of weighted hypotheses regarding genes and molecular mechanisms contributing to human phenotypes or conditions of interest. Since the last release, the Lynx knowledge base (LynxKB) has been periodically updated with the latest versions of the existing databases and supplemented with additional information from public databases. These additions have enriched the data annotations provided by Lynx and improved the performance of Lynx analytical tools. Moreover, the Lynx analytical workbench has been supplemented with new tools for reconstruction of co-expression networks and feature-and-network-based prioritization of genetic factors and molecular mechanisms. These developments facilitate the extraction of meaningful knowledge from experimental data and LynxKB. The Service Oriented Architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces.

  2. A Knowledge-Based and Model-Driven Requirements Engineering Approach to Conceptual Satellite Design

    NASA Astrophysics Data System (ADS)

    Dos Santos, Walter A.; Leonor, Bruno B. F.; Stephany, Stephan

    Satellite systems are becoming even more complex, making technical issues a significant cost driver. The increasing complexity of these systems makes requirements engineering activities both more important and difficult. Additionally, today's competitive pressures and other market forces drive manufacturing companies to improve the efficiency with which they design and manufacture space products and systems. This imposes a heavy burden on systems-of-systems engineering skills and particularly on requirements engineering which is an important phase in a system's life cycle. When this is poorly performed, various problems may occur, such as failures, cost overruns and delays. One solution is to underpin the preliminary conceptual satellite design with computer-based information reuse and integration to deal with the interdisciplinary nature of this problem domain. This can be attained by taking a model-driven engineering approach (MDE), in which models are the main artifacts during system development. MDE is an emergent approach that tries to address system complexity by the intense use of models. This work outlines the use of SysML (Systems Modeling Language) and a novel knowledge-based software tool, named SatBudgets, to deal with these and other challenges confronted during the conceptual phase of a university satellite system, called ITASAT, currently being developed by INPE and some Brazilian universities.

  3. 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.

  4. A Knowledge-Based System For The Delineation Of The Coronary Arteries

    NASA Astrophysics Data System (ADS)

    Smets, Carl; Suetens, Paul; Oosterlinck, Andre J.; van de Werf, Frans

    1989-05-01

    In this article we will present work in progress concerning a knowledge-based system for the labeling of the coronary arteries on single projections. The approach is based on a gradual refinement of the interpretation results, starting from the detection of blood vessel center lines, the extraction of bar-like primitives and the connection into blood vessel segments. In this paper we will focus on the final stage which is the labeling of the delineated blood vessel segments. In contrast with most existing approaches which are mainly based on a sequential labeling of the vessels starting from the most important segment, our system uses a constraint satisfaction technique. Mainly, because most anatomical knowledge can be easily formalized as constraints on local attributes such as position, greyvalue, thickness and orientation and as constraints on relations between blood vessel segments such as "left of" or "in same direction". Anatomical models are developed for the Left Coronary Artery in standard RAO and LAO views. In general, only 1-2 interpretations are left, which is an encouraging result if you take into account that for some projections there is a considerable overlap between vessel segments.

  5. 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.

  6. 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.

  7. 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

  8. Integrating movement in academic classrooms: understanding, applying and advancing the knowledge base.

    PubMed

    Webster, C A; Russ, L; Vazou, S; Goh, T L; Erwin, H

    2015-08-01

    In the context of comprehensive and coordinated approaches to school health, academic classrooms have gained attention as a promising setting for increasing physical activity and reducing sedentary time among children. The aims of this paper are to review the rationale and knowledge base related to movement integration in academic classrooms, consider the practical applications of current knowledge to interventions and teacher education, and suggest directions for future research. Specifically, this paper (i) situates movement integration amid policy and research related to children's health and the school as a health-promoting environment; (ii) highlights the benefits of movement integration; (iii) summarizes movement integration programs and interventions; (iv) examines factors associated with classroom teachers' movement integration; (v) offers strategies for translating research to practice and (vi) forwards recommendations for future inquiry related to the effectiveness and sustainability of efforts to integrate movement into classroom routines. This paper provides a comprehensive resource for developing state-of-the-art initiatives to maximize children's movement in academic classrooms as a key strategy for important goals in both education and public health.

  9. 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/.

  10. Human Resource Development for Knowledge-based Society and Challenges of Nagoya University

    NASA Astrophysics Data System (ADS)

    Miyata, Takashi

    Innovation in the previous century resulted in development of useful products ranging from automobiles and aircraft to cellular phones. However, the innovation and development of science and technology have changed the society and brought about negative issues. The issues emerged in the previous century remain in the excessive forms in the 21st century. The 21st century is seeing the rise of knowledge-based society, and paradigm shift is now going on. Human resources of university for creation of innovation are being called on to contribute to solving issues. Young people who pass through a doctor program must play a role as an innovator who can promote the paradigm shift. However, the higher education system of the universities in Japan is now required to be changed to dissolve the mismatch on the doctor program with industries, government and students. The discussion in the Business-University Forum of Japan for innovation of education system and a few challenges of the Nagoya University are introduced in this paper.

  11. XROUTE: A knowledge-based routing system using neural networks and genetic algorithms

    SciTech Connect

    Kadaba, N.

    1990-01-01

    This dissertation is concerned with applying alternative methods of artificial intelligence (AI) in conjunction with mathematical methods to Vehicle Routing Problems. The combination of good mathematical models, knowledge-based systems, artificial neural networks, and adaptive genetic algorithms (GA) - which are shown to be synergistic - produces near-optimal results, which none of the individual methods can produce on its own. A significant problem associated with application of the Back Propagation learning paradigm for pattern classification with neural networks is the lack of high accuracy in generalization when the domain is large. In this work, a multiple neural network system is employed, using two self-organizing neural networks that work as feature extractors, producing information that is used to train a generalization neural network. The technique was successfully applied to the selection of control rules for a Traveling Salesman Problem heuristic, thus making it adaptive to the input problem instance. XROUTE provides an interactive visualization system, using state-of-the-art vehicle routing models and AI tools, yet allows an interactive environment for human expertise to be utilized in powerful ways. XROUTE provides an experimental, exploratory framework that allows many variations, and alternatives to problems with different characteristics. XROUTE is dynamic, expandable, and adaptive, and typically outperforms alternative methods in computer-aided vehicle routing.

  12. Lynx: a knowledge base and an analytical workbench for integrative medicine.

    PubMed

    Sulakhe, Dinanath; Xie, Bingqing; Taylor, Andrew; D'Souza, Mark; Balasubramanian, Sandhya; Hashemifar, Somaye; White, Steven; Dave, Utpal J; Agam, Gady; Xu, Jinbo; Wang, Sheng; Gilliam, T Conrad; Maltsev, Natalia

    2016-01-01

    Lynx (http://lynx.ci.uchicago.edu) is a web-based database and a knowledge extraction engine. It supports annotation and analysis of high-throughput experimental data and generation of weighted hypotheses regarding genes and molecular mechanisms contributing to human phenotypes or conditions of interest. Since the last release, the Lynx knowledge base (LynxKB) has been periodically updated with the latest versions of the existing databases and supplemented with additional information from public databases. These additions have enriched the data annotations provided by Lynx and improved the performance of Lynx analytical tools. Moreover, the Lynx analytical workbench has been supplemented with new tools for reconstruction of co-expression networks and feature-and-network-based prioritization of genetic factors and molecular mechanisms. These developments facilitate the extraction of meaningful knowledge from experimental data and LynxKB. The Service Oriented Architecture provides public access to LynxKB and its analytical tools via user-friendly web services and interfaces. PMID:26590263

  13. 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.

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

    PubMed

    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

  15. 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.

  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. 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.

  18. 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

  19. BioBIKE: a Web-based, programmable, integrated biological knowledge base.

    PubMed

    Elhai, Jeff; Taton, Arnaud; Massar, J P; Myers, John K; Travers, Mike; Casey, Johnny; Slupesky, Mark; Shrager, Jeff

    2009-07-01

    BioBIKE (biobike.csbc.vcu.edu) is a web-based environment enabling biologists with little programming expertise to combine tools, data, and knowledge in novel and possibly complex ways, as demanded by the biological problem at hand. BioBIKE is composed of three integrated components: a biological knowledge base, a graphical programming interface and an extensible set of tools. Each of the five current BioBIKE instances provides all available information (genomic, metabolic, experimental) appropriate to a given research community. The BioBIKE programming language and graphical programming interface employ familiar operations to help users combine functions and information to conduct biologically meaningful analyses. Many commonly used tools, such as Blast and PHYLIP, are built-in, allowing users to access them within the same interface and to pass results from one to another. Users may also invent their own tools, packaging complex expressions under a single name, which is immediately made accessible through the graphical interface. BioBIKE represents a partial solution to the difficult question of how to enable those with no background in computer programming to work directly and creatively with mass biological information. BioBIKE is distributed under the MIT Open Source license. A description of the underlying language and other technical matters is available at www.Biobike.org. PMID:19433511

  20. Socio-cultural and Knowledge-Based Barriers to Tuberculosis Diagnosis for Women in Bhopal, India

    PubMed Central

    McArthur, Evonne; Bali, Surya; Khan, Azim A.

    2016-01-01

    Background: In India, only one woman is diagnosed with tuberculosis (TB) for every 2.4 men. Previous studies have indicated gender disparities in care-seeking behavior and TB diagnosis; however, little is known about the specific barriers women face. Objectives: This study aimed to characterize socio-cultural and knowledge-based barriers that affected TB diagnosis for women in Bhopal, India. Materials and Methods: In-depth interviews were conducted with 13 affected women and 6 health-care workers. The Bhopal Diagnostic Microscopy Laboratory Register (n = 121) and the Bhopal district report (n = 261) were examined for diagnostic and care-seeking trends. Results: Women, especially younger women, faced socio-cultural barriers and stigma, causing many to hide their symptoms. Older women had little awareness about TB. Women often sought treatment from private practitioners, resulting in delayed diagnosis. Conclusions: Understanding these diagnostic and help-seeking behaviors barriers for women is critical for development of a gender-sensitive TB control program. PMID:26917876

  1. SPECTRA: An Integrated Knowledge Base for Comparing Tissue and Tumor-Specific PPI Networks in Human.

    PubMed

    Micale, Giovanni; Ferro, Alfredo; Pulvirenti, Alfredo; Giugno, Rosalba

    2015-01-01

    Protein-protein interaction (PPI) networks available in public repositories usually represent relationships between proteins within the cell. They ignore the specific set of tissues or tumors where the interactions take place. Indeed, proteins can form tissue-selective complexes, while they remain inactive in other tissues. For these reasons, a great attention has been recently paid to tissue-specific PPI networks, in which nodes are proteins of the global PPI network whose corresponding genes are preferentially expressed in specific tissues. In this paper, we present SPECTRA, a knowledge base to build and compare tissue or tumor-specific PPI networks. SPECTRA integrates gene expression and protein interaction data from the most authoritative online repositories. We also provide tools for visualizing and comparing such networks, in order to identify the expression and interaction changes of proteins across tissues, or between the normal and pathological states of the same tissue. SPECTRA is available as a web server at http://alpha.dmi.unict.it/spectra.

  2. 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.

  3. 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.

  4. ESPRE: a knowledge-based system to support platelet transfusion decisions.

    PubMed

    Sielaff, B H; Connelly, D P; Scott, E P

    1989-05-01

    ESPRE is a knowledge-based system which aids in the review of requests for platelet transfusions in the hospital blood bank. It is a microcomputer-based decision support system written in LISP and utilizes a hybrid frame and rule architecture. By automatically obtaining most of the required patient data directly from the hospital's main laboratory computers via a direct link, very little keyboard entry is required. Assessment of time trends computed from the data constitutes an important aspect of this system. To aid the blood bank personnel in deciding on the appropriateness of the requested transfusion, the system provides an explanatory report which includes a list of patient-specific data, a list of the conditions for which a transfusion would be appropriate for the particular patient (given the clinical condition), and the conclusions drawn by the system. In an early clinical evaluation of ESPRE, out of a random sample of 75 platelet transfusion requests, there were only three disagreements between ESPRE and blood bank personnel. PMID:2656504

  5. Structural semantic interconnections: a knowledge-based approach to word sense disambiguation.

    PubMed

    Navigli, Roberto; Velardi, Paola

    2005-07-01

    Word Sense Disambiguation (WSD) is traditionally considered an Al-hard problem. A break-through in this field would have a significant impact on many relevant Web-based applications, such as Web information retrieval, improved access to Web services, information extraction, etc. Early approaches to WSD, based on knowledge representation techniques, have been replaced in the past few years by more robust machine learning and statistical techniques. The results of recent comparative evaluations of WSD systems, however, show that these methods have inherent limitations. On the other hand, the increasing availability of large-scale, rich lexical knowledge resources seems to provide new challenges to knowledge-based approaches. In this paper, we present a method, called structural semantic interconnections (SSI), which creates structural specifications of the possible senses for each word in a context and selects the best hypothesis according to a grammar G, describing relations between sense specifications. Sense specifications are created from several available lexical resources that we integrated in part manually, in part with the help of automatic procedures. The SSI algorithm has been applied to different semantic disambiguation problems, like automatic ontology population, disambiguation of sentences in generic texts, disambiguation of words in glossary definitions. Evaluation experiments have been performed on specific knowledge domains (e.g., tourism, computer networks, enterprise interoperability), as well as on standard disambiguation test sets.

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

    PubMed

    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.

  7. Extending the evaluation of Genia Event task toward knowledge base construction and comparison to Gene Regulation Ontology task

    PubMed Central

    2015-01-01

    Background The third edition of the BioNLP Shared Task was held with the grand theme "knowledge base construction (KB)". The Genia Event (GE) task was re-designed and implemented in light of this theme. For its final report, the participating systems were evaluated from a perspective of annotation. To further explore the grand theme, we extended the evaluation from a perspective of KB construction. Also, the Gene Regulation Ontology (GRO) task was newly introduced in the third edition. The final evaluation of the participating systems resulted in relatively low performance. The reason was attributed to the large size and complex semantic representation of the ontology. To investigate potential benefits of resource exchange between the presumably similar tasks, we measured the overlap between the datasets of the two tasks, and tested whether the dataset for one task can be used to enhance performance on the other. Results We report an extended evaluation on all the participating systems in the GE task, incoporating a KB perspective. For the evaluation, the final submission of each participant was converted to RDF statements, and evaluated using 8 queries that were formulated in SPARQL. The results suggest that the evaluation may be concluded differently between the two different perspectives, annotation vs. KB. We also provide a comparison of the GE and GRO tasks by converting their datasets into each other's format. More than 90% of the GE data could be converted into the GRO task format, while only half of the GRO data could be mapped to the GE task format. The imbalance in conversion indicates that the GRO is a comprehensive extension of the GE task ontology. We further used the converted GRO data as additional training data for the GE task, which helped improve GE task participant system performance. However, the converted GE data did not help GRO task participants, due to overfitting and the ontology gap. PMID:26202680

  8. Prediction of conformational epitopes with the use of a knowledge-based energy function and geometrically related neighboring residue characteristics

    PubMed Central

    2013-01-01

    Background A conformational epitope (CE) in an antigentic protein is composed of amino acid residues that are spatially near each other on the antigen's surface but are separated in sequence; CEs bind their complementary paratopes in B-cell receptors and/or antibodies. CE predication is used during vaccine design and in immuno-biological experiments. Here, we develop a novel system, CE-KEG, which predicts CEs based on knowledge-based energy and geometrical neighboring residue contents. The workflow applied grid-based mathematical morphological algorithms to efficiently detect the surface atoms of the antigens. After extracting surface residues, we ranked CE candidate residues first according to their local average energy distributions. Then, the frequencies at which geometrically related neighboring residue combinations in the potential CEs occurred were incorporated into our workflow, and the weighted combinations of the average energies and neighboring residue frequencies were used to assess the sensitivity, accuracy, and efficiency of our prediction workflow. Results We prepared a database containing 247 antigen structures and a second database containing the 163 non-redundant antigen structures in the first database to test our workflow. Our predictive workflow performed better than did algorithms found in the literature in terms of accuracy and efficiency. For the non-redundant dataset tested, our workflow achieved an average of 47.8% sensitivity, 84.3% specificity, and 80.7% accuracy according to a 10-fold cross-validation mechanism, and the performance was evaluated under providing top three predicted CE candidates for each antigen. Conclusions Our method combines an energy profile for surface residues with the frequency that each geometrically related amino acid residue pair occurs to identify possible CEs in antigens. This combination of these features facilitates improved identification for immuno-biological studies and synthetic vaccine design. CE-KEG is

  9. Minitrack on data and knowledge base issues in genomics at the 27th Hawaii International Conference on system sciences

    SciTech Connect

    1995-05-01

    This report is a summary of the proceedings from the Minitrack on Data and Knowledge Base Issues in Genomics at the 27th Hawaii International Conference on System Science, January 4 - 7, 1994. The minitrack was organized by Dong-Guk Shin (University of Connecticut) and Francois Rechenmann (INRIA, France). Support was jointly provided by the NSF, NIH and DOE. The minitrack included, after rigorous review, ten full papers and four extended abstracts in the following five different research subareas of genome informatics: data modeling and management, sequence analysis, graphical user interface, interoperation in a heterogenous computing environment, and system integration in a knowledge-based approach.

  10. Workflow analysis and evidence-based medicine: towards integration of knowledge-based functions in hospital information systems.

    PubMed Central

    Mueller, M. L.; Ganslandt, T.; Frankewitsch, T.; Krieglstein, C. F.; Senninger, N.; Prokosch, H. U.

    1999-01-01

    The large extent and complexity of scientific evidence described in the concept of evidence-based medicine often overwhelms clinicians who want to apply best external evidence. Hospital Information Systems usually do not provide knowledge-based functions to support context-sensitive linking to external information sources. Knowledge-based components need specific data, which must be entered manually and should be well adapted to clinical environment to be accepted by clinicians. This paper describes a workflow-based approach to understand and visualize clinical reality as a preliminary to designing software applications, and possible starting points for further software development. PMID:10566375

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

    NASA Technical Reports Server (NTRS)

    Ricks, Wendell R.

    1991-01-01

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

  12. Mapping the knowledge base for maritime health: 4 safety and performance at sea.

    PubMed

    Carter, Tim

    2011-01-01

    There is very little recent investigative work on the contribution of health related impairment and disability to either accident risks or to reduced performance at sea, the only exception being studies on fatigue and parallel data on sleep related incidents. Incidents where health related impairment, other than fatigue, has contributed are very rarely found in reports of maritime accident investigations. This may either indicate the irrelevance of these forms of impairment to accidents or alternatively point to the effectiveness of existing control measures. The main approach to risk reduction is by the application of fitness criteria to seafarers during medical examinations. Where there is a knowledge base it is either, as in the case of vision, a very old one that relates to patterns of visual task that differ markedly from those in modern shipping or, as with hearing, is based on untested assumptions about the levels of impairment that will prevent effective communications at sea. There are practical limitations to the assessment of cognitive functions as these encompass such a wide range of impairments from those associated with fatigue, medication, or substance abuse to those relating to age or to the risks of sudden incapacitation from a pre-existing illness. Physical capability can be assessed but only in limited ways in the course of a medical examination. In the absence of clear evidence of accident risks associated with health-related impairments or disabilities it is unlikely that there will be pressure to update criteria that appear to be providing satisfactory protection. As capability is related to the tasks performed, investigations need to integrate information on ergonomic and organizational aspects with that on health and impairment. Criteria that may select seafarers with health- -related impairment need to be reviewed wherever the task demands in modern shipping have changed, in order to relax or modify them where indicated in order to reduce

  13. Designing and Developing a NASA Research Projects Knowledge Base and Implementing Knowledge Management and Discovery Techniques

    NASA Astrophysics Data System (ADS)

    Dabiru, L.; O'Hara, C. G.; Shaw, D.; Katragadda, S.; Anderson, D.; Kim, S.; Shrestha, B.; Aanstoos, J.; Frisbie, T.; Policelli, F.; Keblawi, N.

    2006-12-01

    The Research Project Knowledge Base (RPKB) is currently being designed and will be implemented in a manner that is fully compatible and interoperable with enterprise architecture tools developed to support NASA's Applied Sciences Program. Through user needs assessment, collaboration with Stennis Space Center, Goddard Space Flight Center, and NASA's DEVELOP Staff personnel insight to information needs for the RPKB were gathered from across NASA scientific communities of practice. To enable efficient, consistent, standard, structured, and managed data entry and research results compilation a prototype RPKB has been designed and fully integrated with the existing NASA Earth Science Systems Components database. The RPKB will compile research project and keyword information of relevance to the six major science focus areas, 12 national applications, and the Global Change Master Directory (GCMD). The RPKB will include information about projects awarded from NASA research solicitations, project investigator information, research publications, NASA data products employed, and model or decision support tools used or developed as well as new data product information. The RPKB will be developed in a multi-tier architecture that will include a SQL Server relational database backend, middleware, and front end client interfaces for data entry. The purpose of this project is to intelligently harvest the results of research sponsored by the NASA Applied Sciences Program and related research program results. We present various approaches for a wide spectrum of knowledge discovery of research results, publications, projects, etc. from the NASA Systems Components database and global information systems and show how this is implemented in SQL Server database. The application of knowledge discovery is useful for intelligent query answering and multiple-layered database construction. Using advanced EA tools such as the Earth Science Architecture Tool (ESAT), RPKB will enable NASA and

  14. MeRy-B, a metabolomic database and knowledge base for exploring plant primary metabolism.

    PubMed

    Deborde, Catherine; Jacob, Daniel

    2014-01-01

    Plant primary metabolites are organic compounds that are common to all or most plant species and are essential for plant growth, development, and reproduction. They are intermediates and products of metabolism involved in photosynthesis and other biosynthetic processes. Primary metabolites belong to different compound families, mainly carbohydrates, organic acids, amino acids, nucleotides, fatty acids, steroids, or lipids. Until recently, unlike the Human Metabolome Database ( http://www.hmdb.ca ) dedicated to human metabolism, there was no centralized database or repository dedicated exclusively to the plant kingdom that contained information on metabolites and their concentrations in a detailed experimental context. MeRy-B is the first platform for plant (1)H-NMR metabolomic profiles (MeRy-B, http://bit.ly/meryb ), designed to provide a knowledge base of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata. MeRy-B contains lists of plant metabolites, mostly primary metabolites and unknown compounds, with information about experimental conditions, the factors studied, and metabolite concentrations for 19 different plant species (Arabidopsis, broccoli, daphne, grape, maize, barrel clover, melon, Ostreococcus tauri, palm date, palm tree, peach, pine tree, eucalyptus, plantain rice, strawberry, sugar beet, tomato, vanilla), compiled from more than 2,300 annotated NMR profiles for various organs or tissues deposited by 30 different private or public contributors in September 2013. Currently, about half of the data deposited in MeRy-B is publicly available. In this chapter, readers will be shown how to (1) navigate through and retrieve data of publicly available projects on MeRy-B website; (2) visualize lists of experimentally identified metabolites and their concentrations in all plant species present in MeRy-B; (3) get primary metabolite list for a particular plant species in MeRy-B; and for a

  15. Ab Initio Protein Structure Assembly Using Continuous Structure Fragments and Optimized Knowledge-based Force Field

    PubMed Central

    Xu, Dong; Zhang, Yang

    2012-01-01

    Ab initio protein folding is one of the major unsolved problems in computational biology due to the difficulties in force field design and conformational search. We developed a novel program, QUARK, for template-free protein structure prediction. Query sequences are first broken into fragments of 1–20 residues where multiple fragment structures are retrieved at each position from unrelated experimental structures. Full-length structure models are then assembled from fragments using replica-exchange Monte Carlo simulations, which are guided by a composite knowledge-based force field. A number of novel energy terms and Monte Carlo movements are introduced and the particular contributions to enhancing the efficiency of both force field and search engine are analyzed in detail. QUARK prediction procedure is depicted and tested on the structure modeling of 145 non-homologous proteins. Although no global templates are used and all fragments from experimental structures with template modeling score (TM-score) >0.5 are excluded, QUARK can successfully construct 3D models of correct folds in 1/3 cases of short proteins up to 100 residues. In the ninth community-wide Critical Assessment of protein Structure Prediction (CASP9) experiment, QUARK server outperformed the second and third best servers by 18% and 47% based on the cumulative Z-score of global distance test-total (GDT-TS) scores in the free modeling (FM) category. Although ab initio protein folding remains a significant challenge, these data demonstrate new progress towards the solution of the most important problem in the field. PMID:22411565

  16. 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.

  17. 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

  18. It Ain't the Heat, It's the Humanity: Evidence and Implications of a Knowledge-Based Consensus on Man-Made Global Warming

    NASA Astrophysics Data System (ADS)

    Jacobs, P.; Cook, J.; Nuccitelli, D. A.

    2013-12-01

    One of the most worrisome misconceptions among the general public about climate change is a belief that scientists disagree not only about the cause of the present climate change, but also whether or not the planet is currently warming. Recent surveys have demonstrated that an overwhelming consensus exists, both within the scientific literature and among scientists with climate expertise, that the planet is warming and humans are driving this climatic change. This disconnect, or 'consensus gap', between scientific agreement and public belief has significant consequences for public understanding of the reality and cause of climate change, as well as support for potential solutions. Ensuring that the consensus message is not simply broadcast but is also accepted as legitimate by the public appears to be a primary education and communications opportunity. While the existence of a consensus is not itself evidence of a position's truth, according to Miller (2013) scientific consensus can be taken as evidence that a position is true if it is 'knowledge-based', satisfying the conditions of social calibration, apparent consilience of evidence, and social diversity. We demonstrate that the scientific consensus on anthropogenic climate change is knowledge-based, satisfying Miller's criteria. In so doing, we hope to increase confidence in its use as an education and communications tool, and assure the public of its validity. We show the consensus is socially calibrated, based on common evidential standards, ontological schemes, and shared formalism. We establish that consilience of evidence points overwhelmingly to the reality of anthropogenic climate change by examining the evidence from several perspectives. We identify unique fingerprints expected as a result of increased greenhouse forcing, eliminate potential natural drivers of climate change as the cause of the present change, and demonstrate the consistency of the observed climate response with known changes in natural

  19. 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…

  20. Secondary Mathematics Teachers' Beliefs, Attitudes, Knowledge Base, and Practices in Meeting the Needs of English Language Learners

    ERIC Educational Resources Information Center

    Gann, Linda

    2013-01-01

    The research centered on secondary mathematics teachers' beliefs, attitudes, knowledge base, and practices in meeting the academic and language needs of English language learners. Using socio-cultural theory and social practice theory to frame the study, the research design employed a mixed methods approach incorporating self-reported…

  1. 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…

  2. 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…

  3. School Administration: The New Knowledge Base. The Fifth Yearbook of the National Council of Professors of Educational Administration.

    ERIC Educational Resources Information Center

    Wildman, Louis, Ed.

    This "Yearbook" is a compilation of 34 articles that represent "state-of-the-art" thought in educational administration as of 1997. The yearbook is organized in accordance with a knowledge-base outline that was developed through repeated surveys of professors of educational administration and practicing administrators. The articles cover the…

  4. 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…

  5. Integrated Database And Knowledge Base For Genomic Prospective Cohort Study In Tohoku Medical Megabank Toward Personalized Prevention And Medicine.

    PubMed

    Ogishima, Soichi; Takai, Takako; Shimokawa, Kazuro; Nagaie, Satoshi; Tanaka, Hiroshi; Nakaya, Jun

    2015-01-01

    The Tohoku Medical Megabank project is a national project to revitalization of the disaster area in the Tohoku region by the Great East Japan Earthquake, and have conducted large-scale prospective genome-cohort study. Along with prospective genome-cohort study, we have developed integrated database and knowledge base which will be key database for realizing personalized prevention and medicine.

  6. 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…

  7. A Knowledge-Based Expert System Which Assists Non-Profit Organizations in Fund-Raising Software Selections.

    ERIC Educational Resources Information Center

    Hoppe, Patricia Anne

    Outcomes of a project designed to develop the knowledge base necessary for creating an expert system that would help nonprofit organizations select fund-raising software are presented in this paper. When the system is completed, its components will ask the user for information that will assist in determining the organization's administrative needs…

  8. 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…

  9. 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…

  10. The Teacher Educator's Handbook: Building a Knowledge Base for the Preparation of Teachers. The Jossey-Bass Education Series.

    ERIC Educational Resources Information Center

    Murray, Frank B., Ed.

    In this book, leading scholars address a range of issues, ideas, and research findings in the field of teacher education, examining specific disciplines, social foundations, and program structures, as well as school reform and diversity. Part One: The Need for a Knowledge Base contains five chapters: "Beyond Natural Teaching: The Case for…

  11. 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…

  12. 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,…

  13. 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, over the past…

  14. 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…

  15. 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 related to…

  16. 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

  17. Introducing the Forensic Research/Reference on Genetics knowledge base, FROG-kb

    PubMed Central

    2012-01-01

    Background Online tools and databases based on multi-allelic short tandem repeat polymorphisms (STRPs) are actively used in forensic teaching, research, and investigations. The Fst value of each CODIS marker tends to be low across the populations of the world and most populations typically have all the common STRP alleles present diminishing the ability of these systems to discriminate ethnicity. Recently, considerable research is being conducted on single nucleotide polymorphisms (SNPs) to be considered for human identification and description. However, online tools and databases that can be used for forensic research and investigation are limited. Methods The back end DBMS (Database Management System) for FROG-kb is Oracle version 10. The front end is implemented with specific code using technologies such as Java, Java Servlet, JSP, JQuery, and GoogleCharts. Results We present an open access web application, FROG-kb (Forensic Research/Reference on Genetics-knowledge base, http://frog.med.yale.edu), that is useful for teaching and research relevant to forensics and can serve as a tool facilitating forensic practice. The underlying data for FROG-kb are provided by the already extensively used and referenced ALlele FREquency Database, ALFRED (http://alfred.med.yale.edu). In addition to displaying data in an organized manner, computational tools that use the underlying allele frequencies with user-provided data are implemented in FROG-kb. These tools are organized by the different published SNP/marker panels available. This web tool currently has implemented general functions possible for two types of SNP panels, individual identification and ancestry inference, and a prediction function specific to a phenotype informative panel for eye color. Conclusion The current online version of FROG-kb already provides new and useful functionality. We expect FROG-kb to grow and expand in capabilities and welcome input from the forensic community in identifying datasets and

  18. Knowledge-based annotation of small molecule binding sites in proteins

    PubMed Central

    2010-01-01

    developed to predict binding sites with high accuracy in terms of their biological validity. It also provides a common platform for function prediction, knowledge-based docking and for small molecule virtual screening. The method can be applied even for a query sequence without structure. The method is available at http://www.ncbi.nlm.nih.gov/Structure/ibis/ibis.cgi. PMID:20594344

  19. 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

  20. Intent and error recognition as part of a knowledge-based cockpit assistant

    NASA Astrophysics Data System (ADS)

    Strohal, Michael; Onken, Reiner

    1998-03-01

    With the Crew Assistant Military Aircraft (CAMA) a knowledge- based cockpit assistant system for future military transport aircraft is developed and tested to enhance situation awareness. Human-centered automation was the central principal for the development of CAMA, an approach to achieve advanced man-machine interaction, mainly by enhancing situation awareness. The CAMA-module Pilot Intent and Error Recognition (PIER) evaluates the pilot's activities and mission events in order to interpret and understand the pilot's actions in the context of the flight situation. Expected crew actions based on the flight plan are compared with the actual behavior shown by the crew. If discrepancies are detected the PIER module tries to figure out, whether the deviation was caused erroneously or by a sensible intent. By monitoring pilot actions as well as the mission context, the system is able to compare the pilot's action with a set of behavioral hypotheses. In case of an intentional deviation from the flight plan, the module checks, whether the behavior matches to the given set of behavior patterns of the pilot. Intent recognition can increase man-machine synergy by anticipating a need for assistance pertinent to the pilot's intent without having a pilot request. The interpretation of all possible situations with respect to intent recognition in terms of a reasoning process is based on a set of decision rules. To cope with the need of inferencing under uncertainty a fuzzy-logic approach is used. A weakness of the fuzzy-logic approach lies in the possibly ill-defined boundaries of the fuzzy sets. Self-Organizing Maps (SOM) as introduced and elaborated on by T. Kohonen are applied to improve the fuzzy set data and rule base complying with observed pilot behavior. Hierarchical cluster analysis is used to locate clusters of similar patterns in the maps. As introduced by Pedrycz, every feature is evaluated using fuzzy sets for each designated cluster. This approach allows to