A collaborative filtering-based approach to biomedical knowledge discovery.

Science.gov (United States)

Lever, Jake; Gakkhar, Sitanshu; Gottlieb, Michael; Rashnavadi, Tahereh; Lin, Santina; Siu, Celia; Smith, Maia; Jones, Martin R; Krzywinski, Martin; Jones, Steven J M; Wren, Jonathan

2018-02-15

The increase in publication rates makes it challenging for an individual researcher to stay abreast of all relevant research in order to find novel research hypotheses. Literature-based discovery methods make use of knowledge graphs built using text mining and can infer future associations between biomedical concepts that will likely occur in new publications. These predictions are a valuable resource for researchers to explore a research topic. Current methods for prediction are based on the local structure of the knowledge graph. A method that uses global knowledge from across the knowledge graph needs to be developed in order to make knowledge discovery a frequently used tool by researchers. We propose an approach based on the singular value decomposition (SVD) that is able to combine data from across the knowledge graph through a reduced representation. Using cooccurrence data extracted from published literature, we show that SVD performs better than the leading methods for scoring discoveries. We also show the diminishing predictive power of knowledge discovery as we compare our predictions with real associations that appear further into the future. Finally, we examine the strengths and weaknesses of the SVD approach against another well-performing system using several predicted associations. All code and results files for this analysis can be accessed at https://github.com/jakelever/knowledgediscovery. sjones@bcgsc.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A decision support system based on hybrid knowledge approach for nuclear power plant operation

International Nuclear Information System (INIS)

Yang, J.O.; Chang, S.H.

1991-01-01

This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. Frames and rules are adopted to represent the various knowledge types. Rule-based deduction and abduction are used for shallow and deep knowledge based reasoning respectively. The event-based operational guidelines are provided to the operator according to the diagnosed results

Knowledge-based biomedical word sense disambiguation: comparison of approaches

Directory of Open Access Journals (Sweden)

Aronson Alan R

2010-11-01

Full Text Available Abstract Background Word sense disambiguation (WSD algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature. Statistical learning approaches have produced good results, but the size of the UMLS makes the production of training data infeasible to cover all the domain. Methods We present research on existing WSD approaches based on knowledge bases, which complement the studies performed on statistical learning. We compare four approaches which rely on the UMLS Metathesaurus as the source of knowledge. The first approach compares the overlap of the context of the ambiguous word to the candidate senses based on a representation built out of the definitions, synonyms and related terms. The second approach collects training data for each of the candidate senses to perform WSD based on queries built using monosemous synonyms and related terms. These queries are used to retrieve MEDLINE citations. Then, a machine learning approach is trained on this corpus. The third approach is a graph-based method which exploits the structure of the Metathesaurus network of relations to perform unsupervised WSD. This approach ranks nodes in the graph according to their relative structural importance. The last approach uses the semantic types assigned to the concepts in the Metathesaurus to perform WSD. The context of the ambiguous word and semantic types of the candidate concepts are mapped to Journal Descriptors. These mappings are compared to decide among the candidate concepts. Results are provided estimating accuracy of the different methods on the WSD test collection available from the NLM. Conclusions We have found that the last approach achieves better results compared to the other methods. The graph-based approach, using the structure of the Metathesaurus network to estimate the relevance of the Metathesaurus concepts, does not perform well

An approach to build a knowledge base for reactor diagnostic system using statistical method

International Nuclear Information System (INIS)

Yokobayashi, Masao; Matsumoto, Kiyoshi; Kohsaka, Atsuo

1988-01-01

In the development of a rule-based expert system, one of the key issues is how to acquire knowledge and to build a knowledge base. When the knowledge base of DISKET was built, which is an expert system for nuclear reactor accident diagnosis developed in Japan Atomic Energy Research Institute, several problems have been experienced. To write rules is a time-consuming task, and it was difficult to keep the objectivity and consistency of rules as the number of rules increased. Certainty factors must be determined often according to engineering judgement, i.e. empirically or intuitively. A systematic approach was attempted to cope with these difficulties and to build efficiently an objective knowledge base. The approach described in this paper is based on the concept that a prototype knowledge base, colloquially speaking an initial guess, should first be generated in a systematic way, then it is modified or improved by human experts for practical use. Factor analysis was used as the systematic way. DISKET system, the procedure of building a knowledge base, and the verification of the approach are reported. (Kako, I.)

Influencing factors for condition-based maintenance in railway tracks using knowledge-based approach

NARCIS (Netherlands)

Jamshidi, A.; Hajizadeh, S.; Naeimi, M.; Nunez Vicencio, Alfredo; Li, Z.

2017-01-01

In this paper, we present a condition-based maintenance decision method using
knowledge-based approach for rail surface defects. A railway track may contain a considerable number of surface defects which influence track maintenance decisions. The proposed method is based on two sets of

Knowledge management of eco-industrial park for efficient energy utilization through ontology-based approach

International Nuclear Information System (INIS)

Zhang, Chuan; Romagnoli, Alessandro; Zhou, Li; Kraft, Markus

2017-01-01

Highlights: •An intelligent energy management system for Eco-Industrial Park (EIP) is proposed. •An explicit domain ontology for EIP energy management is designed. •Ontology-based approach can increase knowledge interoperability within EIP. •Ontology-based approach can allow self-optimization without human intervention in EIP. •The proposed system harbours huge potential in the future scenario of Internet of Things. -- Abstract: An ontology-based approach for Eco-Industrial Park (EIP) knowledge management is proposed in this paper. The designed ontology in this study is formalized conceptualization of EIP. Based on such an ontological representation, a Knowledge-Based System (KBS) for EIP energy management named J-Park Simulator (JPS) is developed. By applying JPS to the solution of EIP waste heat utilization problem, the results of this study show that ontology is a powerful tool for knowledge management of complex systems such as EIP. The ontology-based approach can increase knowledge interoperability between different companies in EIP. The ontology-based approach can also allow intelligent decision making by using disparate data from remote databases, which implies the possibility of self-optimization without human intervention scenario of Internet of Things (IoT). It is shown through this study that KBS can bridge the communication gaps between different companies in EIP, sequentially more potential Industrial Symbiosis (IS) links can be established to improve the overall energy efficiency of the whole EIP.

Case-based approaches for knowledge application and organisational learning

DEFF Research Database (Denmark)

Wang, Chengbo; Johansen, John; Luxhøj, James T.

2005-01-01

In dealing with the strategic issues within a manufacturing system, it is necessary to facilitate formulating the composing elements of a set of strategic manufacturing practices and activity patterns that will support an enterprise to reinforce and increase its competitive advantage....... These practices and activity patterns are based on learning and applying the knowledge internal and external to an organisation. To ensure their smooth formulation process, there are two important techniques designed – an expert adaptation approach and an expert evaluation approach. These two approaches provide...

An Analysis of Knowledge Sharing Approaches for Emerging-technology-based Strategic Alliances in Electronic Industry

Institute of Scientific and Technical Information of China (English)

LIU Ju; LI Yong-jian

2006-01-01

Emerging technologies are now initiating new industries and transforming old ones with tremendous power. They are different games compared with established technologies with distinctive characteristics of knowledge management in knowledge-based and technological-innovation-based competition. How to obtain knowledge advantage and enhance competences by knowledge sharing for emerging-technology-based strategic alliances (ETBSA) is what we concern in this paper. On the basis of our previous work on emerging technologies'distinctive attributes, we counter the wide spread presumption that the primary purpose of strategic alliances is knowledge acquiring by means of learning. We offers new insight into the knowledge sharing approaches of ETBSAs - the knowledge integrating approach by which each member firm integrates its partner's complementary knowledge base into the products and services and maintains its own knowledge specialization at the same time. So that ETBSAs should plan and practice their knowledge sharing strategies from the angle of knowledge integrating rather than knowledge acquiring. A four-dimensional framework is developed to analyze the advantages and disadvantages of these two knowledge sharing approaches. Some cases in electronic industry are introduced to illustrate our point of view.

A Task-Based Approach to Organization: Knowledge, Communication and Structure

OpenAIRE

Luis Garicano; Yanhui Wu

2010-01-01

We bridge a gap between organizational economics and strategy research by developing a task-based approach to analyze organizational knowledge, process and structure, and deriving testable implications for the relation between production and organizational structure. We argue that organization emerges to integrate disperse knowledge and to coordinate talent in production and is designed to complement the limitations of human ability. The complexity of the tasks undertaken determines the optim...

From Provenance Standards and Tools to Queries and Actionable Provenance

Science.gov (United States)

Ludaescher, B.

2017-12-01

The W3C PROV standard provides a minimal core for sharing retrospective provenance information for scientific workflows and scripts. PROV extensions such as DataONE's ProvONE model are necessary for linking runtime observables in retrospective provenance records with conceptual-level prospective provenance information, i.e., workflow (or dataflow) graphs. Runtime provenance recorders, such as DataONE's RunManager for R, or noWorkflow for Python capture retrospective provenance automatically. YesWorkflow (YW) is a toolkit that allows researchers to declare high-level prospective provenance models of scripts via simple inline comments (YW-annotations), revealing the computational modules and dataflow dependencies in the script. By combining and linking both forms of provenance, important queries and use cases can be supported that neither provenance model can afford on its own. We present existing and emerging provenance tools developed for the DataONE and SKOPE (Synthesizing Knowledge of Past Environments) projects. We show how the different tools can be used individually and in combination to model, capture, share, query, and visualize provenance information. We also present challenges and opportunities for making provenance information more immediately actionable for the researchers who create it in the first place. We argue that such a shift towards "provenance-for-self" is necessary to accelerate the creation, sharing, and use of provenance in support of transparent, reproducible computational and data science.

Identification of provenance rocks based on EPMA analyses of heavy minerals

Science.gov (United States)

Shimizu, M.; Sano, N.; Ueki, T.; Yonaga, Y.; Yasue, K. I.; Masakazu, N.

2017-12-01

Information on mountain building is significant in the field of geological disposal of high-level radioactive waste, because this affects long-term stability in groundwater flow system. Provenance analysis is one of effective approaches for understanding building process of mountains. Chemical compositions of heavy minerals, as well as their chronological data, can be an index for identification of provenance rocks. The accurate identification requires the measurement of as many grains as possible. In order to achieve an efficient provenance analysis, we developed a method for quick identification of heavy minerals using an Electron Probe Micro Analyzer (EPMA). In this method, heavy mineral grains extracted from a sample were aligned on a glass slide and mounted in a resin. Concentration of 28 elements was measured for 300-500 grains per sample using EPMA. To measure as many grains as possible, we prioritized swiftness of measurement over precision, configuring measurement time of about 3.5 minutes for each grain. Identification of heavy minerals was based on their chemical composition. We developed a Microsoft® Excel® spread sheet input criteria of mineral identification using a typical range of chemical compositions for each mineral. The grains of 110 wt.% total were rejected. The criteria of mineral identification were revised through the comparison between mineral identification by optical microscopy and chemical compositions of grains classified as "unknown minerals". Provenance rocks can be identified based on abundance ratio of identified minerals. If no significant difference of the abundance ratio was found among source rocks, chemical composition of specific minerals was used as another index. This method was applied to the sediments of some regions in Japan where provenance rocks had lithological variations but similar formation ages. Consequently, the provenance rocks were identified based on chemical compositions of heavy minerals resistant to

Foundation: Transforming data bases into knowledge bases

Science.gov (United States)

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.

Intelligent assembly time analysis, using a digital knowledge based approach

NARCIS (Netherlands)

Jin, Y.; Curran, R.; Butterfield, J.; Burke, R.; Welch, B.

2009-01-01

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for

Fuzzy knowledge bases integration based on ontology

OpenAIRE

Ternovoy, Maksym; Shtogrina, Olena

2012-01-01

the paper describes the approach for fuzzy knowledge bases integration with the usage of ontology. This approach is based on metadata-base usage for integration of different knowledge bases with common ontology. The design process of metadata-base is described.

An Algebraic Approach to Knowledge Bases Informational Equivalence

OpenAIRE

Plotkin, B.; Plotkin, T.

2003-01-01

In this paper we study the notion of knowledge from the positions of universal algebra and algebraic logic. We consider first order knowledge which is based on first order logic. We define categories of knowledge and knowledge bases. These notions are defined for the fixed subject of knowledge. The key notion of informational equivalence of two knowledge bases is introduced. We use the idea of equivalence of categories in this definition. We prove that for finite models there is a clear way t...

Lessons learned about art-based approaches for disseminating knowledge.

Science.gov (United States)

Bruce, Anne; Makaroff, Kara L Schick; Sheilds, Laurene; Beuthin, Rosanne; Molzahn, Anita; Shermak, Sheryl

2013-01-01

To present a case example of using an arts-based approach and the development of an art exhibit to disseminate research findings from a narrative research study. Once a study has been completed, the final step of dissemination of findings is crucial. In this paper, we explore the benefits of bringing nursing research into public spaces using an arts-based approach. Findings from a qualitative narrative study exploring experiences of living with life-threatening illnesses. Semi-structured in-depth interviews were conducted with 32 participants living with cancer, chronic renal disease, or HIV/AIDS. Participants were invited to share a symbol representing their experience of living with life-threatening illness and the meaning it held for them. The exhibit conveyed experiences of how people story and re-story their lives when living with chronic kidney disease, cancer or HIV. Photographic images of symbolic representations of study participants' experiences and poetic narratives from their stories were exhibited in a public art gallery. The theoretical underpinning of arts-based approaches and the lessons learned in creating an art exhibit from research findings are explored. Creative art forms for research and disseminating knowledge offer new ways of understanding and knowing that are under-used in nursing. Arts-based approaches make visible patients' experiences that are often left unarticulated or hidden. Creative dissemination approaches such as art exhibits can promote insight and new ways of knowing that communicate nursing research to both public and professional audiences.

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

Science.gov (United States)

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

2016-01-01

To develop an expandable knowledge base of reusable knowledge related to self-management of diabetes that can be used as a foundation for patient-centric decision support tools. The structure and components of the knowledge base were created in participatory design with academic diabetes educators using knowledge acquisition methods. The knowledge base was validated using scenario-based approach with practicing diabetes educators and individuals with diabetes recruited from Community Health Centers (CHCs) serving economically disadvantaged communities and ethnic minorities in New York. The knowledge base includes eight glycemic control problems, over 150 behaviors known to contribute to these problems coupled with contextual explanations, and over 200 specific action-oriented self-management goals for correcting problematic behaviors, with corresponding motivational messages. The validation of the knowledge base suggested high level of completeness and accuracy, and identified improvements in cultural appropriateness. These were addressed in new iterations of the knowledge base. The resulting knowledge base is theoretically grounded, incorporates practical and evidence-based knowledge used by diabetes educators in practice settings, and allows for personally meaningful choices by individuals with diabetes. Participatory design approach helped researchers to capture implicit knowledge of practicing diabetes educators and make it explicit and reusable. The knowledge base proposed here is an important step towards development of new generation patient-centric decision support tools for facilitating chronic disease self-management. While this knowledge base specifically targets diabetes, its overall structure and composition can be generalized to other chronic conditions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A Knowledge-based Recommendation Framework using SVN Numbers

Directory of Open Access Journals (Sweden)

Roddy Cabezas Padilla

2017-06-01

Full Text Available Current knowledge based recommender systems, despite proven useful and having a high impact, persist with some shortcomings. Among its limitations are the lack of more flexible models and the inclusion of indeterminacy of the factors involved for computing a global similarity.

An Adaptive Approach to Managing Knowledge Development in a Project-Based Learning Environment

Science.gov (United States)

Tilchin, Oleg; Kittany, Mohamed

2016-01-01

In this paper we propose an adaptive approach to managing the development of students' knowledge in the comprehensive project-based learning (PBL) environment. Subject study is realized by two-stage PBL. It shapes adaptive knowledge management (KM) process and promotes the correct balance between personalized and collaborative learning. The…

A structural informatics approach to mine kinase knowledge bases.

Science.gov (United States)

Brooijmans, Natasja; Mobilio, Dominick; Walker, Gary; Nilakantan, Ramaswamy; Denny, Rajiah A; Feyfant, Eric; Diller, David; Bikker, Jack; Humblet, Christine

2010-03-01

In this paper, we describe a combination of structural informatics approaches developed to mine data extracted from existing structure knowledge bases (Protein Data Bank and the GVK database) with a focus on kinase ATP-binding site data. In contrast to existing systems that retrieve and analyze protein structures, our techniques are centered on a database of ligand-bound geometries in relation to residues lining the binding site and transparent access to ligand-based SAR data. We illustrate the systems in the context of the Abelson kinase and related inhibitor structures. 2009 Elsevier Ltd. All rights reserved.

Knowledge Resources - A Knowledge Management Approach for Digital Ecosystems

Science.gov (United States)

Kurz, Thomas; Eder, Raimund; Heistracher, Thomas

The paper at hand presents an innovative approach for the conception and implementation of knowledge management in Digital Ecosystems. Based on a reflection of Digital Ecosystem research of the past years, an architecture is outlined which utilizes Knowledge Resources as the central and simplest entities of knowledge transfer. After the discussion of the related conception, the result of a first prototypical implementation is described that helps the transformation of implicit knowledge to explicit knowledge for wide use.

Benefiting from Customer and Competitor Knowledge: A Market-Based Approach to Organizational Learning

Science.gov (United States)

Hoe, Siu Loon

2008-01-01

Purpose: The purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market-based approach to organizational learning. Design/methodology/approach: The extant organizational learning…

An Ensemble Approach to Knowledge-Based Intensity-Modulated Radiation Therapy Planning

Directory of Open Access Journals (Sweden)

Jiahan Zhang

2018-03-01

Full Text Available Knowledge-based planning (KBP utilizes experienced planners’ knowledge embedded in prior plans to estimate optimal achievable dose volume histogram (DVH of new cases. In the regression-based KBP framework, previously planned patients’ anatomical features and DVHs are extracted, and prior knowledge is summarized as the regression coefficients that transform features to organ-at-risk DVH predictions. In our study, we find that in different settings, different regression methods work better. To improve the robustness of KBP models, we propose an ensemble method that combines the strengths of various linear regression models, including stepwise, lasso, elastic net, and ridge regression. In the ensemble approach, we first obtain individual model prediction metadata using in-training-set leave-one-out cross validation. A constrained optimization is subsequently performed to decide individual model weights. The metadata is also used to filter out impactful training set outliers. We evaluate our method on a fresh set of retrospectively retrieved anonymized prostate intensity-modulated radiation therapy (IMRT cases and head and neck IMRT cases. The proposed approach is more robust against small training set size, wrongly labeled cases, and dosimetric inferior plans, compared with other individual models. In summary, we believe the improved robustness makes the proposed method more suitable for clinical settings than individual models.

Distributional and Knowledge-Based Approaches for Computing Portuguese Word Similarity

Directory of Open Access Journals (Sweden)

Hugo Gonçalo Oliveira

2018-02-01

Full Text Available Identifying similar and related words is not only key in natural language understanding but also a suitable task for assessing the quality of computational resources that organise words and meanings of a language, compiled by different means. This paper, which aims to be a reference for those interested in computing word similarity in Portuguese, presents several approaches for this task and is motivated by the recent availability of state-of-the-art distributional models of Portuguese words, which add to several lexical knowledge bases (LKBs for this language, available for a longer time. The previous resources were exploited to answer word similarity tests, which also became recently available for Portuguese. We conclude that there are several valid approaches for this task, but not one that outperforms all the others in every single test. Distributional models seem to capture relatedness better, while LKBs are better suited for computing genuine similarity, but, in general, better results are obtained when knowledge from different sources is combined.

An Integrated Open Approach to Capturing Systematic Knowledge for Manufacturing Process Innovation Based on Collective Intelligence

Directory of Open Access Journals (Sweden)

Gangfeng Wang

2018-02-01

Full Text Available Process innovation plays a vital role in the manufacture realization of increasingly complex new products, especially in the context of sustainable development and cleaner production. Knowledge-based innovation design can inspire designers’ creative thinking; however, the existing scattered knowledge has not yet been properly captured and organized according to Computer-Aided Process Innovation (CAPI. Therefore, this paper proposes an integrated approach to tackle this non-trivial issue. By analyzing the design process of CAPI and technical features of open innovation, a novel holistic paradigm of process innovation knowledge capture based on collective intelligence (PIKC-CI is constructed from the perspective of the knowledge life cycle. Then, a multi-source innovation knowledge fusion algorithm based on semantic elements reconfiguration is applied to form new public knowledge. To ensure the credibility and orderliness of innovation knowledge refinement, a collaborative editing strategy based on knowledge lock and knowledge–social trust degree is explored. Finally, a knowledge management system MPI-OKCS integrating the proposed techniques is implemented into the pre-built CAPI general platform, and a welding process innovation example is provided to illustrate the feasibility of the proposed approach. It is expected that our work would lay the foundation for the future knowledge-inspired CAPI and smart process planning.

Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach

NARCIS (Netherlands)

Miao, Yongwu; Sloep, Peter; Koper, Rob

2009-01-01

Miao, Y., Sloep, P. B., & Koper, R. (2009). Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach. Presented at the 'Open workshop of TENCompetence - Rethinking Learning and Employment at a Time of Economic Uncertainty-event'. November, 19, 2009,

Active Provenance in Data-intensive Research

Science.gov (United States)

Spinuso, Alessandro; Mihajlovski, Andrej; Filgueira, Rosa; Atkinson, Malcolm

2017-04-01

Scientific communities are building platforms where the usage of data-intensive workflows is crucial to conduct their research campaigns. However managing and effectively support the understanding of the 'live' processes, fostering computational steering, sharing and re-use of data and methods, present several bottlenecks. These are often caused by the poor level of documentation on the methods and the data and how users interact with it. This work wants to explore how in such systems, flexibility in the management of the provenance and its adaptation to the different users and application contexts can lead to new opportunities for its exploitation, improving productivity. In particular, this work illustrates a conceptual and technical framework enabling tunable and actionable provenance in data-intensive workflow systems in support of reproducible science. It introduces the concept of Agile data-intensive systems to define the characteristic of our target platform. It shows a novel approach to the integration of provenance mechanisms, offering flexibility in the scale and in the precision of the provenance data collected, ensuring its relevance to the domain of the data-intensive task, fostering its rapid exploitation. The contributions address aspects of the scale of the provenance records, their usability and active role in the research life-cycle. We will discuss the use of dynamically generated provenance types as the approach for the integration of provenance mechanisms into a data-intensive workflow system. Enabling provenance can be transparent to the workflow user and developer, as well as fully controllable and customisable, depending from their expertise and the application's reproducibility, monitoring and validation requirements. The API that allows the realisation and adoption of a provenance type is presented, especially for what concerns the support of provenance profiling, contextualisation and precision. An actionable approach to provenance

INTEGRATING CASE-BASED REASONING, KNOWLEDGE-BASED APPROACH AND TSP ALGORITHM FOR MINIMUM TOUR FINDING

Directory of Open Access Journals (Sweden)

Hossein Erfani

2009-07-01

Full Text Available Imagine you have traveled to an unfamiliar city. Before you start your daily tour around the city, you need to know a good route. In Network Theory (NT, this is the traveling salesman problem (TSP. A dynamic programming algorithm is often used for solving this problem. However, when the road network of the city is very complicated and dense, which is usually the case, it will take too long for the algorithm to find the shortest path. Furthermore, in reality, things are not as simple as those stated in AT. For instance, the cost of travel for the same part of the city at different times may not be the same. In this project, we have integrated TSP algorithm with AI knowledge-based approach and case-based reasoning in solving the problem. With this integration, knowledge about the geographical information and past cases are used to help TSP algorithm in finding a solution. This approach dramatically reduces the computation time required for minimum tour finding.

Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach

NARCIS (Netherlands)

Miao, Yongwu; Sloep, Peter; Koper, Rob

2009-01-01

Miao, Y., Sloep, P. B., & Koper, R. (2010). Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach. In D. Griffiths & R. Koper (Eds.), Rethinking Learning and Employment at a Time of Economic Uncertainty. Proceedings of the 6th TENCompetence Open

A user-orientated approach to provenance capture and representation for in silico experiments, explored within the atmospheric chemistry community.

Science.gov (United States)

Martin, Chris J; Haji, Mohammed H; Jimack, Peter K; Pilling, Michael J; Dew, Peter M

2009-07-13

We present a novel user-orientated approach to provenance capture and representation for in silico experiments, contrasted against the more systems-orientated approaches that have been typical within the e-Science domain. In our approach, we seek to capture the scientist's reasoning in the form of annotations as an experiment evolves, while using the scientist's terminology in the representation of process provenance. Our user-orientated approach is applied in a case study within the atmospheric chemistry domain: we consider the design, development and evaluation of an electronic laboratory notebook, a provenance capture and storage tool, for iterative model development.

Business Process Management – A Traditional Approach Versus a Knowledge Based Approach

Directory of Open Access Journals (Sweden)

Roberto Paiano

2015-12-01

Full Text Available The enterprise management represents a heterogeneous aggregate of both resources and assets that need to be coordinated and orchestrated in order to reach the goals related to the business mission. Influences and forces that may influence this process, and also for that they should be considered, are not concentrated in the business environment, but they are related to the entireoperational context of a company. For this reason, business processes must be the most versatile and flexible with respect to the changes that occur within the whole operational context of a company.Considering the supportive role that information systems play in favour of Business Process Management - BPM, it is also essential to implement a constant, continuous and quick mechanism for the information system alignment with respect to the evolution followed by business processes.In particular, such mechanism must intervene on BPM systems in order to keep them aligned and compliant with respect to both the context changes and the regulations. In order to facilitate this alignment mechanism, companies are already referring to the support offered by specific solutions, such as knowledge bases. In this context, a possible solution might be the approach we propose, which is based on a specific framework called Process Management System. Our methodology implements a knowledge base support for business experts, which is not limited to the BPM operating phases, but includes also the engineering and prototyping activities of the corresponding information system. This paper aims to compare and evaluate a traditional BPM approach with respect to theapproach we propose. In effect, such analysis aims to emphasize the lack of traditional methodology especially with respect to the alignment between business processes and information systems, along with their compliance with context domain and regulations.

Knowledge Engineering Approach to the Geotectonic Discourse

Science.gov (United States)

Pshenichny, Cyril

2014-05-01

The intellectual challenge of geotectonics is, and always was, much harder than that of most of the sciences: geotectonics has to say much when there is objectively not too much to say. As the target of study (the genesis of regional and planetary geological structures) is vast and multidisciplinary and is more or less generic for many geological disciplines, its more or less complete description is practically inachievable. Hence, the normal pathway of natural-scientific research - first acquire data, then draw conclusion - unlikely can be the case here. Geotectonics does quite the opposite; its approach is purely abductive: first to suggest a conceptualization (hypothesis) based on some external grounds (either general planetary/cosmic/philosophic/religious considerations, or based on experience gained from research of other structures/regions/planets) and then to acquire data that either support or refute it. In fact, geotectonics defines the context for data acquisition, and hence, the paradigm for the entire body of geology. Being an obvious necessity for a descriptive science, this nevertheless creates a number of threats: • Like any people, scientists like simplicity and unity, and therefore a single geotectonic hypothesis may seem preferable once based on the data available at the moment and oppress other views which may acquire evidence in the future; • As impartial data acquisition is rather a myth than reality even in most of the natural sciences, in a study like geology this process becomes strongly biased by the reigning hypothesis and controlled to supply only supportive evidence; • It becomes collectively agreed that any, or great many, domains of geological knowledge are determined by a geotectonic concept, which is, in turn, offered by a reigning hypothesis (sometimes reclassified as theory) - e.g., exploration geologists must involve the global geotectonic terminology in their technical reports on assessment of mineral or hydrocarbon

Tracing where and who provenance in Linked Data: A calculus

OpenAIRE

Dezani-Ciancaglini, Mariangiola; Horne, Ross; Sassone, Vladimiro

2012-01-01

Linked Data provides some sensible guidelines for publishing and consuming data on the Web. Data published on the Web has no inherent truth, yet its quality can often be assessed based on its provenance. This work introduces a new approach to provenance for Linked Data. The simplest notion of provenance-viz., a named graph indicating where the data is now-is extended with a richer provenance format. The format reflects the behaviour of processes interacting with Linked Data, tracing where the...

A PROCESS-BASED APPROACH TO KNOWLEDGE MANAGEMENT

OpenAIRE

Kovačić, Andrej; Bosilj Vukšić, Vesna; Lončar, Anita

2006-01-01

This paper analyses the relationship between business process modelling, knowledge management and information systems development projects. The paper’s main objective is to present business rules as the encoded knowledge of corporate business practices. Further, it introduces a rule-based business activity meta-model as a repository in which business knowledge can be captured and traced from their origin in the business environment through to their implementation in information systems. The c...

An approach to build knowledge base for reactor accident diagnostic system using statistical method

International Nuclear Information System (INIS)

Kohsaka, Atsuo; Yokobayashi, Masao; Matsumoto, Kiyoshi; Fujii, Minoru

1988-01-01

In the development of a rule based expert system, one of key issues is how to build a knowledge base (KB). A systematic approach has been attempted for building an objective KB efficiently. The approach is based on the concept that a prototype KB should first be generated in a systematic way and then it is to be modified and/or improved by expert for practical use. The statistical method, Factor Analysis, was applied to build a prototype KB for the JAERI expert system DISKET using source information obtained from a PWR simulator. The prototype KB was obtained and the inference with this KB was performed against several types of transients. In each diagnosis, the transient type was well identified. From this study, it is concluded that the statistical method used is useful for building a prototype knowledge base. (author)

A knowledge-based approach to the design of integrated renewable energy systems

Energy Technology Data Exchange (ETDEWEB)

Ramakumar, R.; Abouzahr, I. (Oklahoma State Univ., Stillwater, OK (United States). Engineering Energy Lab.); Ashenayi, K. (Dept. of Electrical Engineering, Univ. of Tulsa, Tulsa, OK (United States))

1992-12-01

Integrated Renewable Energy Systems (IRES) utilize two or more renewable energy resources and end-use technologies to supply a variety of energy needs, often in a stand-alone mode. A knowledge-based design approach that minimizes the total capital cost at a pre-selected reliability level is presented. The reliability level is quantified by the loss of power supply probability (LPSP). The procedure includes some resource-need matching based on economics, the quality of energy needed, and the characteristics of the resource. A detailed example is presented in this paper and discussed to illustrate the usefullness of the design approach.

Knowledge management as an approach to strengthen safety culture in nuclear organizations

International Nuclear Information System (INIS)

Karseka, T.S.; Yanev, Y.L.

2013-01-01

In the last 10 years knowledge management (KM) in nuclear organizations has emerged as a powerful strategy to deal with important and frequently critical issues of attrition, generation change and knowledge transfer. Applying KM practices in operating organizations, in technical support organizations and regulatory bodies has proven to be efficient and necessary for maintaining competence and skills for achieving high level of safety and operational performance. The IAEA defines KM as an integrated, systematic approach to identifying, acquiring, transforming, developing, disseminating, using, sharing, and preserving knowledge, relevant to achieving specified objectives. KM focuses on people and organizational culture to stimulate and nurture the sharing and use of knowledge; on processes or methods to find, create, capture and share knowledge; and on technology to store and assimilate knowledge and to make it readily accessible in a manner which will allow people to work together even if they are not located together. A main objective of this paper is to describe constructive actions which can sponsor knowledge sharing and solidarity in safety conscious attitude among all employees. All principles and approaches refer primarily to Nuclear Power Plant (NPP) operating organizations but are also applicable to other institutions involved into nuclear sector. (orig.)

Knowledge management as an approach to strengthen safety culture in nuclear organizations

Energy Technology Data Exchange (ETDEWEB)

Karseka, T.S.; Yanev, Y.L. [International Atomic Energy Agency, Vienna (Austria). Nuclear Energy Dept.

2013-04-15

In the last 10 years knowledge management (KM) in nuclear organizations has emerged as a powerful strategy to deal with important and frequently critical issues of attrition, generation change and knowledge transfer. Applying KM practices in operating organizations, in technical support organizations and regulatory bodies has proven to be efficient and necessary for maintaining competence and skills for achieving high level of safety and operational performance. The IAEA defines KM as an integrated, systematic approach to identifying, acquiring, transforming, developing, disseminating, using, sharing, and preserving knowledge, relevant to achieving specified objectives. KM focuses on people and organizational culture to stimulate and nurture the sharing and use of knowledge; on processes or methods to find, create, capture and share knowledge; and on technology to store and assimilate knowledge and to make it readily accessible in a manner which will allow people to work together even if they are not located together. A main objective of this paper is to describe constructive actions which can sponsor knowledge sharing and solidarity in safety conscious attitude among all employees. All principles and approaches refer primarily to Nuclear Power Plant (NPP) operating organizations but are also applicable to other institutions involved into nuclear sector. (orig.)

Knowledge based expert system approach to instrumentation selection (INSEL

Directory of Open Access Journals (Sweden)

S. Barai

2004-08-01

Full Text Available The selection of appropriate instrumentation for any structural measurement of civil engineering structure is a complex task. Recent developments in Artificial Intelligence (AI can help in an organized use of experiential knowledge available on instrumentation for laboratory and in-situ measurement. Usually, the instrumentation decision is based on the experience and judgment of experimentalists. The heuristic knowledge available for different types of measurement is domain dependent and the information is scattered in varied knowledge sources. The knowledge engineering techniques can help in capturing the experiential knowledge. This paper demonstrates a prototype knowledge based system for INstrument SELection (INSEL assistant where the experiential knowledge for various structural domains can be captured and utilized for making instrumentation decision. In particular, this Knowledge Based Expert System (KBES encodes the heuristics on measurement and demonstrates the instrument selection process with reference to steel bridges. INSEL runs on a microcomputer and uses an INSIGHT 2+ environment.

SU-E-P-43: A Knowledge Based Approach to Guidelines for Software Safety

International Nuclear Information System (INIS)

Salomons, G; Kelly, D

2015-01-01

Purpose: In the fall of 2012, a survey was distributed to medical physicists across Canada. The survey asked the respondents to comment on various aspects of software development and use in their clinic. The survey revealed that most centers employ locally produced (in-house) software of some kind. The respondents also indicated an interest in having software guidelines, but cautioned that the realities of cancer clinics include variations, that preclude a simple solution. Traditional guidelines typically involve periodically repeating a set of prescribed tests with defined tolerance limits. However, applying a similar formula to software is problematic since it assumes that the users have a perfect knowledge of how and when to apply the software and that if the software operates correctly under one set of conditions it will operate correctly under all conditions Methods: In the approach presented here the personnel involved with the software are included as an integral part of the system. Activities performed to improve the safety of the software are done with both software and people in mind. A learning oriented approach is taken, following the premise that the best approach to safety is increasing the understanding of those associated with the use or development of the software. Results: The software guidance document is organized by areas of knowledge related to use and development of software. The categories include: knowledge of the underlying algorithm and its limitations; knowledge of the operation of the software, such as input values, parameters, error messages, and interpretation of output; and knowledge of the environment for the software including both data and users. Conclusion: We propose a new approach to developing guidelines which is based on acquiring knowledge-rather than performing tests. The ultimate goal is to provide robust software guidelines which will be practical and effective

SU-E-P-43: A Knowledge Based Approach to Guidelines for Software Safety

Energy Technology Data Exchange (ETDEWEB)

Salomons, G [Cancer Center of Southeastern Ontario & Queen’s University, Kingston, ON (Canada); Kelly, D [Royal Military College of Canada, Kingston, ON, CA (Canada)

2015-06-15

Purpose: In the fall of 2012, a survey was distributed to medical physicists across Canada. The survey asked the respondents to comment on various aspects of software development and use in their clinic. The survey revealed that most centers employ locally produced (in-house) software of some kind. The respondents also indicated an interest in having software guidelines, but cautioned that the realities of cancer clinics include variations, that preclude a simple solution. Traditional guidelines typically involve periodically repeating a set of prescribed tests with defined tolerance limits. However, applying a similar formula to software is problematic since it assumes that the users have a perfect knowledge of how and when to apply the software and that if the software operates correctly under one set of conditions it will operate correctly under all conditions Methods: In the approach presented here the personnel involved with the software are included as an integral part of the system. Activities performed to improve the safety of the software are done with both software and people in mind. A learning oriented approach is taken, following the premise that the best approach to safety is increasing the understanding of those associated with the use or development of the software. Results: The software guidance document is organized by areas of knowledge related to use and development of software. The categories include: knowledge of the underlying algorithm and its limitations; knowledge of the operation of the software, such as input values, parameters, error messages, and interpretation of output; and knowledge of the environment for the software including both data and users. Conclusion: We propose a new approach to developing guidelines which is based on acquiring knowledge-rather than performing tests. The ultimate goal is to provide robust software guidelines which will be practical and effective.

Distributed, cooperating knowledge-based systems

Science.gov (United States)

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.

The knowledge base of journalism

DEFF Research Database (Denmark)

Svith, Flemming

In this paper I propose the knowledge base as a fruitful way to apprehend journalism. With the claim that the majority of practice is anchored in knowledge – understood as 9 categories of rationales, forms and levels – this knowledge base appears as a contextual look at journalists’ knowledge......, and place. As an analytical framework, the knowledge base is limited to understand the practice of newspaper journalists, but, conversely, the knowledge base encompasses more general beginnings through the inclusion of overall structural relationships in the media and journalism and general theories...... on practice and knowledge. As the result of an abductive reasoning is a theory proposal, there is a need for more deductive approaches to test the validity of this knowledge base claim. It is thus relevant to investigate which rationales are included in the knowledge base of journalism, as the dimension does...

In defense of types in knowledge-based CAAD

DEFF Research Database (Denmark)

Galle, Per

1997-01-01

There are two basic approaches to representation of design knowledge in knowledge-based CAAD systems, the type-based approach which has a long tradition, and the more recent typeless approach. Proponents of the latter have offered a number of arguments against the type-based approach which...

The Knowledge Governance Approach

DEFF Research Database (Denmark)

Foss, Nicolai J.

with diverse capabilities of handling these transactions. Various open research issues that a knowledge governance approach may illuminate are sketched. Although knowledge governance draws clear inspiration from organizational economics and `rational' organization theory, it recognizes that knowledge......An attempt is made to characterize a `knowledge governance approach' as a distinctive, emerging field that cuts across the fields of knowledge management, organisation studies, strategy and human resource management. Knowledge governance is taken up with how the deployment of administrative...

Using ePortfolio-Based Learning Approach to Facilitate Knowledge Sharing and Creation among College Students

Science.gov (United States)

Chang, Chi-Cheng; Chou, Pao-Nan; Liang, Chaoyan

2018-01-01

The purpose of the present study was to examine the effects of the ePortfolio-based learning approach (ePBLA) on knowledge sharing and creation with 92 college students majoring in electrical engineering as the participants. Multivariate analysis of covariance (MANCOVA) with a covariance of pretest on knowledge sharing and creation was conducted…

A knowledge-based approach to the evaluation of fault trees

International Nuclear Information System (INIS)

Hwang, Yann-Jong; Chow, Louis R.; Huang, Henry C.

1996-01-01

A list of critical components is useful for determining the potential problems of a complex system. However, to find this list through evaluating the fault trees is expensive and time consuming. This paper intends to propose an integrated software program which consists of a fault tree constructor, a knowledge base, and an efficient algorithm for evaluating minimal cut sets of a large fault tree. The proposed algorithm uses the approaches of top-down heuristic searching and the probability-based truncation. That makes the evaluation of fault trees obviously efficient and provides critical components for solving the potential problems in complex systems. Finally, some practical fault trees are included to illustrate the results

Intelligent Flowcharting Developmental Approach to Legal Knowledge Based System

Directory of Open Access Journals (Sweden)

Nitin Balaji Bilgi

2011-10-01

Full Text Available The basic aim of this research, described in this paper is to develop a hybrid legal expert system/ knowledge based system, with specific reference to the transfer of property act, within the Indian legal system which is often in demand. In this paper the authors discuss an traditional approach to combining two types of reasoning methodologies, Rule Based Reasoning (RBR and Case Based Reasoning (CBR. In RBR module we have interpreted and implemented rules that occur in legal statutes of the Transfer of property act. In the CBR module we have an implementation to find the related cases. The VisiRule software made available by Logic Programming Associates is used in the development of RBR part this expert system. The authors have used java Net Beans for development of CBR. VisiRule is a decision charting tool, in which the rules are defined by a combination of graphical shapes and pieces of text, and produces rules.

Bridging the provenance gap: opportunities and challenges tracking in and ex silico provenance in sUAS workflows

Science.gov (United States)

Thomer, A.

2017-12-01

Data provenance - the record of the varied processes that went into the creation of a dataset, as well as the relationships between resulting data objects - is necessary to support the reusability, reproducibility and reliability of earth science data. In sUAS-based research, capturing provenance can be particularly challenging because of the breadth and distributed nature of the many platforms used to collect, process and analyze data. In any given project, multiple drones, controllers, computers, software systems, sensors, cameras, imaging processing algorithms and data processing workflows are used over sometimes long periods of time. These platforms and processing result in dozens - if not hundreds - of data products in varying stages of readiness-for-analysis and sharing. Provenance tracking mechanisms are needed to make the relationships between these many data products explicit, and therefore more reusable and shareable. In this talk, I discuss opportunities and challenges in tracking provenance in sUAS-based research, and identify gaps in current workflow-capture technologies. I draw on prior work conducted as part of the IMLS-funded Site-Based Data Curation project in which we developed methods of documenting in and ex silico (that is, computational and non-computation) workflows, and demonstrate this approaches applicability to research with sUASes. I conclude with a discussion of ontologies and other semantic technologies that have potential application in sUAS research.

THE DESIGN OF KNOWLEDGE BASE FOR SURFACE RELATIONS BASED PART RECOGNITION APPROACH

Directory of Open Access Journals (Sweden)

Adem ÇİÇEK

2007-01-01

Full Text Available In this study, a new knowledge base for an expert system used in part recognition algorithm has been designed. Parts are recognized by the computer program by comparing face adjacency relations and attributes belonging to each part represented in the rules in the knowledge base developed with face adjacency relations and attributes generated from STEP file of the part. Besides, rule writing process has been quite simplified by generating the rules represented in the knowledge base with an automatic rule writing module developed within the system. With the knowledge base and automatic rule writing module used in the part recognition system, simple, intermediate and complex parts can be recognized by a part recognition program.

Risk based knowledge assessments: towards a toolbox for managing key knowledge assets

International Nuclear Information System (INIS)

Bright, Clive

2008-01-01

Full text: It is now well acknowledged that considerable Knowledge Management (KM) issues are faced by national and international nuclear communities. Much of these problems relate to issues of an ageing workforce and the significantly reduced influx of new generation of nuclear engineers and scientists. The management discipline of KM contains a broad spectrum of methods and techniques. However, the effective implementation of a KM strategy requires the selection and deployment of appropriate and targeted approaches that are pertinent to the particular issues of the technical or business area within an organisation. A clear strategy is contingent upon an assessment of what are the knowledge areas and what are the key (knowledge) risk areas. In particular the following issues have to be addressed: 'what knowledge exists?', 'what is the nature and format of that knowledge?' and 'what knowledge is key to our continued, safe, and effective operation?'. Answers to such questions will enable an organisation to prioritise KM effort and employ subsequent KM approaches that are appropriate. Subsequent approaches ranging from the utilisation of information technologies, such as databases; knowledge retention methods; and the setting up of Community of Practices to share knowledge and experience. This paper considers a risk assessment based approach to KM. In so doing the paper extends work previously reported on an approach to conducting knowledge audits by considering the integration of that approach with approaches to (knowledge) risk assessment. The paper also provides a brief review of the various KM approaches that can act to reduce the level of risk faced by an organisation. The paper concludes by reflecting upon the role, value of deploying such a risk based approach. (author)

Is Student Knowledge of Anatomy Affected by a Problem-Based Learning Approach? A Review

Science.gov (United States)

Williams, Jonathan M.

2014-01-01

A fundamental understanding of anatomy is critical for students on many health science courses. It has been suggested that a problem-based approach to learning anatomy may result in deficits in foundation knowledge. The aim of this review is to compare traditional didactic methods with problem-based learning methods for obtaining anatomy…

Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

Science.gov (United States)

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

2013-01-01

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

Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

Directory of Open Access Journals (Sweden)

Sandra Page

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

Restful Implementation of Catalogue Service for Geospatial Data Provenance

Science.gov (United States)

Jiang, L. C.; Yue, P.; Lu, X. C.

2013-10-01

Provenance, also known as lineage, is important in understanding the derivation history of data products. Geospatial data provenance helps data consumers to evaluate the quality and reliability of geospatial data. In a service-oriented environment, where data are often consumed or produced by distributed services, provenance could be managed by following the same service-oriented paradigm. The Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) is used for the registration and query of geospatial data provenance by extending ebXML Registry Information Model (ebRIM). Recent advance of the REpresentational State Transfer (REST) paradigm has shown great promise for the easy integration of distributed resources. RESTful Web Service aims to provide a standard way for Web clients to communicate with servers based on REST principles. The existing approach for provenance catalogue service could be improved by adopting the RESTful design. This paper presents the design and implementation of a catalogue service for geospatial data provenance following RESTful architecture style. A middleware named REST Converter is added on the top of the legacy catalogue service to support a RESTful style interface. The REST Converter is composed of a resource request dispatcher and six resource handlers. A prototype service is developed to demonstrate the applicability of the approach.

Analytical Features: A Knowledge-Based Approach to Audio Feature Generation

Directory of Open Access Journals (Sweden)

Pachet François

2009-01-01

Full Text Available We present a feature generation system designed to create audio features for supervised classification tasks. The main contribution to feature generation studies is the notion of analytical features (AFs, a construct designed to support the representation of knowledge about audio signal processing. We describe the most important aspects of AFs, in particular their dimensional type system, on which are based pattern-based random generators, heuristics, and rewriting rules. We show how AFs generalize or improve previous approaches used in feature generation. We report on several projects using AFs for difficult audio classification tasks, demonstrating their advantage over standard audio features. More generally, we propose analytical features as a paradigm to bring raw signals into the world of symbolic computation.

Integrating scientific and local knowledge to inform risk-based management approaches for climate adaptation

Directory of Open Access Journals (Sweden)

Nathan P. Kettle

2014-01-01

Full Text Available Risk-based management approaches to climate adaptation depend on the assessment of potential threats, and their causes, vulnerabilities, and impacts. The refinement of these approaches relies heavily on detailed local knowledge of places and priorities, such as infrastructure, governance structures, and socio-economic conditions, as well as scientific understanding of climate projections and trends. Developing processes that integrate local and scientific knowledge will enhance the value of risk-based management approaches, facilitate group learning and planning processes, and support the capacity of communities to prepare for change. This study uses the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS process, a form of analytic-deliberative dialogue, and the conceptual frameworks of hazard management and climate vulnerability, to integrate scientific and local knowledge. We worked with local government staff in an urbanized barrier island community (Sullivan’s Island, South Carolina to consider climate risks, impacts, and adaptation challenges associated with sea level rise and wastewater and stormwater management. The findings discuss how the process increases understanding of town officials’ views of risks and climate change impacts to barrier islands, the management actions being considered to address of the multiple impacts of concern, and the local tradeoffs and challenges in adaptation planning. We also comment on group learning and specific adaptation tasks, strategies, and needs identified.

A knowledge based approach to matching human neurodegenerative disease and animal models

Directory of Open Access Journals (Sweden)

Maryann E Martone

2013-05-01

Full Text Available Neurodegenerative diseases present a wide and complex range of biological and clinical features. Animal models are key to translational research, yet typically only exhibit a subset of disease features rather than being precise replicas of the disease. Consequently, connecting animal to human conditions using direct data-mining strategies has proven challenging, particularly for diseases of the nervous system, with its complicated anatomy and physiology. To address this challenge we have explored the use of ontologies to create formal descriptions of structural phenotypes across scales that are machine processable and amenable to logical inference. As proof of concept, we built a Neurodegenerative Disease Phenotype Ontology and an associated Phenotype Knowledge Base using an entity-quality model that incorporates descriptions for both human disease phenotypes and those of animal models. Entities are drawn from community ontologies made available through the Neuroscience Information Framework and qualities are drawn from the Phenotype and Trait Ontology. We generated ~1200 structured phenotype statements describing structural alterations at the subcellular, cellular and gross anatomical levels observed in 11 human neurodegenerative conditions and associated animal models. PhenoSim, an open source tool for comparing phenotypes, was used to issue a series of competency questions to compare individual phenotypes among organisms and to determine which animal models recapitulate phenotypic aspects of the human disease in aggregate. Overall, the system was able to use relationships within the ontology to bridge phenotypes across scales, returning non-trivial matches based on common subsumers that were meaningful to a neuroscientist with an advanced knowledge of neuroanatomy. The system can be used both to compare individual phenotypes and also phenotypes in aggregate. This proof of concept suggests that expressing complex phenotypes using formal

Validation Of Critical Knowledge-Based Systems

Science.gov (United States)

Duke, Eugene L.

1992-01-01

Report discusses approach to verification and validation of knowledge-based systems. Also known as "expert systems". Concerned mainly with development of methodologies for verification of knowledge-based systems critical to flight-research systems; e.g., fault-tolerant control systems for advanced aircraft. Subject matter also has relevance to knowledge-based systems controlling medical life-support equipment or commuter railroad systems.

Knowledge base verification based on enhanced colored petri net

Energy Technology Data Exchange (ETDEWEB)

Kim, Jong Hyun; Seong, Poong Hyun [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1998-12-31

Verification is a process aimed at demonstrating whether a system meets it`s specified requirements. As expert systems are used in various applications, the knowledge base verification of systems takes an important position. The conventional Petri net approach that has been studied recently in order to verify the knowledge base is found that it is inadequate to verify the knowledge base of large and complex system, such as alarm processing system of nuclear power plant. Thus, we propose an improved method that models the knowledge base as enhanced colored Petri net. In this study, we analyze the reachability and the error characteristics of the knowledge base and apply the method to verification of simple knowledge base. 8 refs., 4 figs. (Author)

Knowledge base verification based on enhanced colored petri net

Energy Technology Data Exchange (ETDEWEB)

Kim, Jong Hyun; Seong, Poong Hyun [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

1997-12-31

Verification is a process aimed at demonstrating whether a system meets it`s specified requirements. As expert systems are used in various applications, the knowledge base verification of systems takes an important position. The conventional Petri net approach that has been studied recently in order to verify the knowledge base is found that it is inadequate to verify the knowledge base of large and complex system, such as alarm processing system of nuclear power plant. Thus, we propose an improved method that models the knowledge base as enhanced colored Petri net. In this study, we analyze the reachability and the error characteristics of the knowledge base and apply the method to verification of simple knowledge base. 8 refs., 4 figs. (Author)

Lean approach in knowledge work

Directory of Open Access Journals (Sweden)

Hanna Kropsu-Vehkapera

2018-05-01

Full Text Available Purpose: Knowledge work productivity is a key area of improvement for many organisations. Lean approach is a sustainable way to achieve operational excellence and can be applied in many areas. The purpose of this novel study is to examine the potential of using lean approach for improving knowledge work practices. Design/methodology/approach: A systematic literature review has been carried out to study how lean approach is realised in knowledge work. The research is conceptual in nature and draws upon earlier research findings. Findings: This study shows that lean studies’ in knowledge work is an emerging research area. This study documents the methods and practices implemented in knowledge work to date, and presents a knowledge work continuum, which is an essential framework for effective lean approach deployment and to frame future research focus in knowledge work productivity. Research limitations/implications: This study structures the concept of knowledge work and outlines a concrete concept derived from earlier literature. The study summarises the literature on lean in knowledge work and highlights, which methods are used. More research is needed to understand how lean can be implemented in complex knowledge work environment and not only on the repetitive knowledge work. The limitations of this research are due to the limited availability of previous research. Practical implications: To analyse the nature of knowledge work, we implicate the areas where lean methods especially apply to improving knowledge work productivity. When applying lean in knowledge work context the focus should be using the people better and improving information flow. Originality/value: This study focuses on adapting lean methods into a knowledge work context and summarises earlier research done in this field. The study discusses the potential to improve knowledge work productivity by implementing lean methods and presents a unique knowledge work continuum to

Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach

OpenAIRE

Miao, Yongwu; Sloep, Peter; Koper, Rob

2009-01-01

Miao, Y., Sloep, P. B., & Koper, R. (2010). Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach. In D. Griffiths & R. Koper (Eds.), Rethinking Learning and Employment at a Time of Economic Uncertainty. Proceedings of the 6th TENCompetence Open workshop (pp. 22-33). November, 19-20, 2009, Manchester, UK. Bolton, UK: Institute for Educational Cybernetics, The University of Bolton. For the complete book please see http://hdl.handle.net/1820/3191

An approach to build a knowledge base for reactor accident diagnostic expert system

International Nuclear Information System (INIS)

Yoshida, K.; Fujii, M.; Fujiki, K.; Yokobayashi, M.; Kohsaka, A.; Aoyagi, T.; Hirota, Y.

1987-01-01

In the development of a rule based expert system, one of the key issues is how to acquire knowledge and to build knowledge base (KB). On building the KB of DISKET, which is an expert system for nuclear reactor accident diagnosis developed in JAERI, several problems have been experienced as follows. To write rules is a time consuming task, and it is difficult to keep the objectivity and consistency of rules as the number of rules increase. Further, certainty factors (CFs) must be often determined according to engineering judgment, i.e., empirically or intuitively. A systematic approach was attempted to handle these difficulties and to build an objective KB efficiently. The approach described in this paper is based on the concept that a prototype KB, colloquially speaking an initial guess, should first be generated in a systematic way and then is to be modified and/or improved by human experts for practical use. Statistical methods, principally Factor Analysis, were used as the systematic way to build a prototype KB for the DISKET using a PWR plant simulator data. The source information is a number of data obtained from the simulation of transients, such as the status of components and annunciator etc., and major process parameters like pressures, temperatures and so on

Biomechanical differences in the stem straightening process among Pinus pinaster provenances. A new approach for early selection of stem straightness.

Science.gov (United States)

Sierra-de-Grado, Rosario; Pando, Valentín; Martínez-Zurimendi, Pablo; Peñalvo, Alejandro; Báscones, Esther; Moulia, Bruno

2008-06-01

Stem straightness is an important selection trait in Pinus pinaster Ait. breeding programs. Despite the stability of stem straightness rankings in provenance trials, the efficiency of breeding programs based on a quantitative index of stem straightness remains low. An alternative approach is to analyze biomechanical processes that underlie stem form. The rationale for this selection method is that genetic differences in the biomechanical processes that maintain stem straightness in young plants will continue to control stem form throughout the life of the tree. We analyzed the components contributing most to genetic differences among provenances in stem straightening processes by kinetic analysis and with a biomechanical model defining the interactions between the variables involved (Fournier's model). This framework was tested on three P. pinaster provenances differing in adult stem straightness and growth. One-year-old plants were tilted at 45 degrees, and individual stem positions and sizes were recorded weekly for 5 months. We measured the radial extension of reaction wood and the anatomical features of wood cells in serial stem cross sections. The integral effect of reaction wood on stem leaning was computed with Fournier's model. Responses driven by both primary and secondary growth were involved in the stem straightening process, but secondary-growth-driven responses accounted for most differences among provenances. Plants from the straight-stemmed provenance showed a greater capacity for stem straightening than plants from the sinuous provenances mainly because of (1) more efficient reaction wood (higher maturation strains) and (2) more pronounced secondary-growth-driven autotropic decurving. These two process-based traits are thus good candidates for early selection of stem straightness, but additional tests on a greater number of genotypes over a longer period are required.

A selective review of knowledge-based approaches to database design

Directory of Open Access Journals (Sweden)

Shahrul Azman Noah

1995-01-01

Full Text Available The inclusion of real world knowledge or specialised knowledge has not been addressed by the majority of the systems reviewed. ODA has real world knowledge provided by using a thesaurus-type structure to represent generic models. Only NITDT includes the specialised knowledge in its knowledge base. NITDT classified its knowledge into application specific, domain specific and general knowledge. However the literature does not discuss in detail how this knowledge is applied during the design session. One of the key factors that distinguish computer-based expert systems from human experts is that the latter apply not only their specialised expertise to a problem but also their general knowledge of the world. NITDT is the only system reviewed here that holds any form of internal domain specific knowledge, which can be easily augmented, enriched and updated, as required. This knowledge allows the designer to be an active participant along with the user in the design process and significantly eases the user task. The inclusion of real world knowledge and specialised knowledge is an area that must be further addressed before intelligent tools are able to offer a realistic level of assistance to the human designers.

Condensed and Updated Version of the Systematic Approach Meteorological Knowledge Base Western North Pacific

OpenAIRE

Carr, Lester E., III; Elsberry, Russell L.; Boothe, Mark A.

1997-01-01

The views expressed in this report are those of the authors and do not reflect the official policy or position of the Department of Defense. The meteorological knowledge base for the Systematic and Integrated Approach to Tropical Cydone Track Forecasting proposed by Carr and Elsberry has evolved as additional research has been completed. This Systematic Approach has been applied in the eastern and central North Pacific, and in the Southern Hemisphere, a number of conceptual models have bee...

Constructing and Refining Knowledge Bases: A Collaborative Apprenticeship Multistrategy Learning Approach

National Research Council Canada - National Science Library

Tecuci, Gheorghe

2000-01-01

This research has developed a theory, methodology and learning agent shell for development of knowledge bases and knowledge-based agents, by domain experts, with limited assistance from knowledge engineers...

Approaching Knowledge Management through the Lens of the Knowledge Life Cycle: A Case Study Investigation

Science.gov (United States)

Fowlin, Julaine M.; Cennamo, Katherine S.

2017-01-01

More organizational leaders are recognizing that their greatest competitive advantage is the knowledge base of their employees and for organizations to thrive knowledge management (KM) systems need to be in place that encourage the natural interplay and flow of tacit and explicit knowledge. Approaching KM through the lens of the knowledge life…

Participatory knowledge-management design: A semiotic approach

DEFF Research Database (Denmark)

Valtolina, Stefano; Barricelli, Barbara Rita; Dittrich, Yvonne

2012-01-01

vocabularies, notations, and suitable visual structures for navigating among interface elements. To this end, the paper describes how our semiotic approach supports processes for representing, storing, accessing, and transferring knowledge through which the information architecture of an interactive system can......The aim of this paper is to present a design strategy for collaborative knowledge-management systems based on a semiotic approach. The contents and structure of experts' knowledge is highly dependent on professional or individual practice. Knowledge-management systems that support cooperation...... a semiotic perspective to computer application and human–computer interaction. From a semiotic perspective, the computer application is both a message from the designer to the user about the structure of the problem domain, as well as about interaction with it, and a structured channel for the user...

Problems and Projects Based Approach For Analog Electronic Circuits' Course

Directory of Open Access Journals (Sweden)

Vahé Nerguizian

2009-04-01

Full Text Available New educational methods and approaches are recently introduced and implemented at several North American and European universities using Problems and Projects Based Approach (PPBA. The PPBA employs a teaching technique based mostly on competences/skills rather than only on knowledge. This method has been implemented and proven by several pedagogical instructors and authors at several educational institutions. This approach is used at different disciplines such as medicine, biology, engineering and many others. It has the advantage to improve the student's skills and the knowledge retention rate, and reflects the 21st century industrial/company needs and demands. Before implementing this approach to a course, a good resources preparation and planning is needed upfront by the responsible or instructor of the course to achieve the course and students related objectives. This paper presents the preparation, the generated documentation and the implementation of a pilot project utilizing PPBA education for a second year undergraduate electronic course over a complete semester, and for two different class groups (morning and evening groups. The outcome of this project (achieved goals, observed difficulties and lessons learned is presented based on different tools such as students 'in class' communication and feedback, different course evaluation forms and the professor/instructor feedback. Resources, challenges, difficulties and recommendations are also assessed and presented. The impact, the effect and the results (during and at the end of the academic fall session of the PPBA on students and instructor are discussed, validated, managed and communicated to help other instructor in taking appropriate approach decisions with respect to this new educational approach compared to the classical one.

Community-based knowledge translation: unexplored opportunities

Directory of Open Access Journals (Sweden)

Armstrong Rebecca

2011-06-01

Full Text Available Abstract Background Knowledge translation is an interactive process of knowledge exchange between health researchers and knowledge users. Given that the health system is broad in scope, it is important to reflect on how definitions and applications of knowledge translation might differ by setting and focus. Community-based organizations and their practitioners share common characteristics related to their setting, the evidence used in this setting, and anticipated outcomes that are not, in our experience, satisfactorily reflected in current knowledge translation approaches, frameworks, or tools. Discussion Community-based organizations face a distinctive set of challenges and concerns related to engaging in the knowledge translation process, suggesting a unique perspective on knowledge translation in these settings. Specifically, community-based organizations tend to value the process of working in collaboration with multi-sector stakeholders in order to achieve an outcome. A feature of such community-based collaborations is the way in which 'evidence' is conceptualized or defined by these partners, which may in turn influence the degree to which generalizable research evidence in particular is relevant and useful when balanced against more contextually-informed knowledge, such as tacit knowledge. Related to the issues of evidence and context is the desire for local information. For knowledge translation researchers, developing processes to assist community-based organizations to adapt research findings to local circumstances may be the most helpful way to advance decision making in this area. A final characteristic shared by community-based organizations is involvement in advocacy activities, a function that has been virtually ignored in traditional knowledge translation approaches. Summary This commentary is intended to stimulate further discussion in the area of community-based knowledge translation. Knowledge translation, and exchange

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing

OpenAIRE

Li, Chunhua; Zhao, Pengpeng; Sheng, Victor S.; Xian, Xuefeng; Wu, Jian; Cui, Zhiming

2017-01-01

Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality i...

Network-based approaches to climate knowledge discovery

Science.gov (United States)

Budich, Reinhard; Nyberg, Per; Weigel, Tobias

2011-11-01

Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

Knowledge-based diagnosis for aerospace systems

Science.gov (United States)

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.

Adaptive Knowledge Management of Project-Based Learning

Science.gov (United States)

Tilchin, Oleg; Kittany, Mohamed

2016-01-01

The goal of an approach to Adaptive Knowledge Management (AKM) of project-based learning (PBL) is to intensify subject study through guiding, inducing, and facilitating development knowledge, accountability skills, and collaborative skills of students. Knowledge development is attained by knowledge acquisition, knowledge sharing, and knowledge…

Knowledge Representation in Patient Safety Reporting: An Ontological Approach

OpenAIRE

Liang Chen; Yang Gong

2016-01-01

Purpose: The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. Design/methodology/approach: We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our desig...

Process fault diagnosis using knowledge-based systems

International Nuclear Information System (INIS)

Sudduth, A.L.

1991-01-01

Advancing technology in process plants has led to increased need for computer based process diagnostic systems to assist the operator. One approach to this problem is to use an embedded knowledge based system to interpret measurement signals. Knowledge based systems using only symptom based rules are inadequate for real time diagnosis of dynamic systems; therefore a model based approach is necessary. Though several forms of model based reasoning have been proposed, the use of qualitative causal models incorporating first principles knowledge of process behavior structure, and function appear to have the most promise as a robust modeling methodology. In this paper the structure of a diagnostic system is described which uses model based reasoning and conventional numerical methods to perform process diagnosis. This system is being applied to emergency diesel generator system in nuclear stations

Provenance tracking in the ViroLab Virtual Laboratory

NARCIS (Netherlands)

Baliś, B.; Bubak, M.; Wach, J.

2008-01-01

Provenance describes the process which led to the creation of a piece of data. Tracking provenance of experiment results is essential in modern environments which support conducting of in silico experiments. We present a provenance tracking approach developed as part of the virtual laboratory of the

Automated knowledge base development from CAD/CAE databases

Science.gov (United States)

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.

Major accident prevention through applying safety knowledge management approach.

Science.gov (United States)

Kalatpour, Omid

2016-01-01

Many scattered resources of knowledge are available to use for chemical accident prevention purposes. The common approach to management process safety, including using databases and referring to the available knowledge has some drawbacks. The main goal of this article was to devise a new emerged knowledge base (KB) for the chemical accident prevention domain. The scattered sources of safety knowledge were identified and scanned. Then, the collected knowledge was formalized through a computerized program. The Protégé software was used to formalize and represent the stored safety knowledge. The domain knowledge retrieved as well as data and information. This optimized approach improved safety and health knowledge management (KM) process and resolved some typical problems in the KM process. Upgrading the traditional resources of safety databases into the KBs can improve the interaction between the users and knowledge repository.

Current trends on knowledge-based systems

CERN Document Server

Valencia-García, Rafael

2017-01-01

This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others. Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used...

A Knowledge Model Sharing Based Approach to Privacy-Preserving Data Mining

OpenAIRE

Hongwei Tian; Weining Zhang; Shouhuai Xu; Patrick Sharkey

2012-01-01

Privacy-preserving data mining (PPDM) is an important problem and is currently studied in three approaches: the cryptographic approach, the data publishing, and the model publishing. However, each of these approaches has some problems. The cryptographic approach does not protect privacy of learned knowledge models and may have performance and scalability issues. The data publishing, although is popular, may suffer from too much utility loss for certain types of data mining applications. The m...

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

Science.gov (United States)

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. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

1988-01-01

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

Provenance-Based Debugging and Drill-Down in Data-Oriented Workflows

KAUST Repository

Ikeda, Robert

2012-04-01

Panda (for Provenance and Data) is a system that supports the creation and execution of data-oriented workflows, with automatic provenance generation and built-in provenance tracing operations. Workflows in Panda are arbitrary a cyclic graphs containing both relational (SQL) processing nodes and opaque processing nodes programmed in Python. For both types of nodes, Panda generates logical provenance - provenance information stored at the processing-node level - and uses the generated provenance to support record-level backward tracing and forward tracing operations. In our demonstration we use Panda to integrate, process, and analyze actual education data from multiple sources. We specifically demonstrate how Panda\\'s provenance generation and tracing capabilities can be very useful for workflow debugging, and for drilling down on specific results of interest. © 2012 IEEE.

Dynamic Data Citation through Provenance - new approach for reproducible science in Geoscience Australia.

Science.gov (United States)

Bastrakova, I.; Car, N.

2017-12-01

Geoscience Australia (GA) is recognised and respected as the National Repository and steward of multiple nationally significance data collections that provides geoscience information, services and capability to the Australian Government, industry and stakeholders. Internally, this brings a challenge of managing large volume (11 PB) of diverse and highly complex data distributed through a significant number of catalogues, applications, portals, virtual laboratories, and direct downloads from multiple locations. Externally, GA is facing constant changer in the Government regulations (e.g. open data and archival laws), growing stakeholder demands for high quality and near real-time delivery of data and products, and rapid technological advances enabling dynamic data access. Traditional approach to citing static data and products cannot satisfy increasing demands for the results from scientific workflows, or items within the workflows to be open, discoverable, thrusted and reproducible. Thus, citation of data, products, codes and applications through the implementation of provenance records is being implemented. This approach involves capturing the provenance of many GA processes according to a standardised data model and storing it, as well as metadata for the elements it references, in a searchable set of systems. This provides GA with ability to cite workflows unambiguously as well as each item within each workflow, including inputs and outputs and many other registered components. Dynamic objects can therefore be referenced flexibly in relation to their generation process - a dataset's metadata indicates where to obtain its provenance from - meaning the relevant facts of its dynamism need not be crammed into a single citation object with a single set of attributes. This allows for simple citations, similar to traditional static document citations such as references in journals, to be used for complex dynamic data and other objects such as software code.

Empowering Provenance in Data Integration

Science.gov (United States)

Kondylakis, Haridimos; Doerr, Martin; Plexousakis, Dimitris

The provenance of data has recently been recognized as central to the trust one places in data. This paper presents a novel framework in order to empower provenance in a mediator based data integration system. We use a simple mapping language for mapping schema constructs, between an ontology and relational sources, capable to carry provenance information. This language extends the traditional data exchange setting by translating our mapping specifications into source-to-target tuple generating dependencies (s-t tgds). Then we define formally the provenance information we want to retrieve i.e. annotation, source and tuple provenance. We provide three algorithms to retrieve provenance information using information stored on the mappings and the sources. We show the feasibility of our solution and the advantages of our framework.

Provenance metadata gathering and cataloguing of EFIT++ code execution

Energy Technology Data Exchange (ETDEWEB)

Lupelli, I., E-mail: ivan.lupelli@ccfe.ac.uk [CCFE, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Muir, D.G.; Appel, L.; Akers, R.; Carr, M. [CCFE, Culham Science Centre, Abingdon, Oxon OX14 3DB (United Kingdom); Abreu, P. [Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa (Portugal)

2015-10-15

Highlights: • An approach for automatic gathering of provenance metadata has been presented. • A provenance metadata catalogue has been created. • The overhead in the code runtime is less than 10%. • The metadata/data size ratio is about ∼20%. • A visualization interface based on Gephi, has been presented. - Abstract: Journal publications, as the final product of research activity, are the result of an extensive complex modeling and data analysis effort. It is of paramount importance, therefore, to capture the origins and derivation of the published data in order to achieve high levels of scientific reproducibility, transparency, internal and external data reuse and dissemination. The consequence of the modern research paradigm is that high performance computing and data management systems, together with metadata cataloguing, have become crucial elements within the nuclear fusion scientific data lifecycle. This paper describes an approach to the task of automatically gathering and cataloguing provenance metadata, currently under development and testing at Culham Center for Fusion Energy. The approach is being applied to a machine-agnostic code that calculates the axisymmetric equilibrium force balance in tokamaks, EFIT++, as a proof of principle test. The proposed approach avoids any code instrumentation or modification. It is based on the observation and monitoring of input preparation, workflow and code execution, system calls, log file data collection and interaction with the version control system. Pre-processing, post-processing, and data export and storage are monitored during the code runtime. Input data signals are captured using a data distribution platform called IDAM. The final objective of the catalogue is to create a complete description of the modeling activity, including user comments, and the relationship between data output, the main experimental database and the execution environment. For an intershot or post-pulse analysis (∼1000

Provenance metadata gathering and cataloguing of EFIT++ code execution

International Nuclear Information System (INIS)

Lupelli, I.; Muir, D.G.; Appel, L.; Akers, R.; Carr, M.; Abreu, P.

2015-01-01

Highlights: • An approach for automatic gathering of provenance metadata has been presented. • A provenance metadata catalogue has been created. • The overhead in the code runtime is less than 10%. • The metadata/data size ratio is about ∼20%. • A visualization interface based on Gephi, has been presented. - Abstract: Journal publications, as the final product of research activity, are the result of an extensive complex modeling and data analysis effort. It is of paramount importance, therefore, to capture the origins and derivation of the published data in order to achieve high levels of scientific reproducibility, transparency, internal and external data reuse and dissemination. The consequence of the modern research paradigm is that high performance computing and data management systems, together with metadata cataloguing, have become crucial elements within the nuclear fusion scientific data lifecycle. This paper describes an approach to the task of automatically gathering and cataloguing provenance metadata, currently under development and testing at Culham Center for Fusion Energy. The approach is being applied to a machine-agnostic code that calculates the axisymmetric equilibrium force balance in tokamaks, EFIT++, as a proof of principle test. The proposed approach avoids any code instrumentation or modification. It is based on the observation and monitoring of input preparation, workflow and code execution, system calls, log file data collection and interaction with the version control system. Pre-processing, post-processing, and data export and storage are monitored during the code runtime. Input data signals are captured using a data distribution platform called IDAM. The final objective of the catalogue is to create a complete description of the modeling activity, including user comments, and the relationship between data output, the main experimental database and the execution environment. For an intershot or post-pulse analysis (∼1000

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

Science.gov (United States)

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15

Citation and Recognition of contributions using Semantic Provenance Knowledge Captured in the OPeNDAP Software Framework

Science.gov (United States)

West, P.; Michaelis, J.; Lebot, T.; McGuinness, D. L.; Fox, P. A.

2014-12-01

Providing proper citation and attribution for published data, derived data products, and the software tools used to generate them, has always been an important aspect of scientific research. However, It is often the case that this type of detailed citation and attribution is lacking. This is in part because it often requires manual markup since dynamic generation of this type of provenance information is not typically done by the tools used to access, manipulate, transform, and visualize data. In addition, the tools themselves lack the information needed to be properly cited themselves. The OPeNDAP Hyrax Software Framework is a tool that provides access to and the ability to constrain, manipulate, and transform, different types of data from different data formats, into a common format, the DAP (Data Access Protocol), in order to derive new data products. A user, or another software client, specifies an HTTP URL in order to access a particular piece of data, and appropriately transform it to suit a specific purpose of use. The resulting data products, however, do not contain any information about what data was used to create it, or the software process used to generate it, let alone information that would allow the proper citing and attribution to down stream researchers and tool developers. We will present our approach to provenance capture in Hyrax including a mechanism that can be used to report back to the hosting site any derived products, such as publications and reports, using the W3C PROV recommendation pingback service. We will demonstrate our utilization of Semantic Web and Web standards, the development of an information model that extends the PROV model for provenance capture, and the development of the pingback service. We will present our findings, as well as our practices for providing provenance information, visualization of the provenance information, and the development of pingback services, to better enable scientists and tool developers to be

Knowledge-light adaptation approaches in case-based reasoning for radiotherapy treatment planning.

Science.gov (United States)

Petrovic, Sanja; Khussainova, Gulmira; Jagannathan, Rupa

2016-03-01

Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which can be difficult to acquire and often is not readily available. In this study, we investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation. We developed two adaptation approaches: adaptation based on machine-learning tools and adaptation-guided retrieval. They were used to adapt the beam number and beam angles suggested in the retrieved case. Two machine-learning tools, neural networks and naive Bayes classifier, were used in the adaptation to learn how the difference in attribute values between the retrieved and new cases affects the output of these two cases. The adaptation-guided retrieval takes into consideration not only the similarity between the new and retrieved cases, but also how to adapt the retrieved case. The research was carried out in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. All experiments were performed using real-world brain cancer

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing.

Science.gov (United States)

Li, Chunhua; Zhao, Pengpeng; Sheng, Victor S; Xian, Xuefeng; Wu, Jian; Cui, Zhiming

2017-01-01

Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality improvement for a knowledge base. To address this problem, we first introduce a concept of semantic constraints that can be used to detect potential errors and do inference among candidate facts. Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing and prune unnecessary questions. Our experiments show that our method improves the quality of knowledge bases significantly and outperforms state-of-the-art automatic methods under a reasonable crowdsourcing cost.

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing

Directory of Open Access Journals (Sweden)

Chunhua Li

2017-01-01

Full Text Available Machine-constructed knowledge bases often contain noisy and inaccurate facts. There exists significant work in developing automated algorithms for knowledge base refinement. Automated approaches improve the quality of knowledge bases but are far from perfect. In this paper, we leverage crowdsourcing to improve the quality of automatically extracted knowledge bases. As human labelling is costly, an important research challenge is how we can use limited human resources to maximize the quality improvement for a knowledge base. To address this problem, we first introduce a concept of semantic constraints that can be used to detect potential errors and do inference among candidate facts. Then, based on semantic constraints, we propose rank-based and graph-based algorithms for crowdsourced knowledge refining, which judiciously select the most beneficial candidate facts to conduct crowdsourcing and prune unnecessary questions. Our experiments show that our method improves the quality of knowledge bases significantly and outperforms state-of-the-art automatic methods under a reasonable crowdsourcing cost.

Maximizing the knowledge base: Knowledge Base+ and the Global Open Knowledgebase

Directory of Open Access Journals (Sweden)

Liam Earney

2013-11-01

Full Text Available The motivation for the two projects discussed in this article is the simple premise that the current inaccuracies of data in the library supply chain are detrimental to the user experience, limit the ability of institutions to effectively manage their collections and that resolving them is increasingly unsustainable at the institutional level. Two projects, Knowledge Base+ (KB+ in the UK and Global Open Knowledgebase (GOKb in the USA, are working in cooperation with a range of other partners, and adopting a communitycentric approach to address these issues and broaden the scope and utility of knowledge bases more generally. The belief is that only through collaboration at a wide range of levels and on a number of fronts can these challenges be overcome.

A knowledge-based approach for C-factor mapping in Spain using Landsat TM and GIS

DEFF Research Database (Denmark)

Veihe (former Folly), Anita; Bronsveld, M.C.; Clavaux, M

1996-01-01

The cover and management factor (C) in the Universal Soil Loss Equation (USLE), is one of the most important parameters for assessing erosion. In this study it is shown how a knowledge-based approach can be used to optimize C-factor mapping in the Mediterranean region being characterized...... to the limitations of the USLE...

Provenance-Based Debugging and Drill-Down in Data-Oriented Workflows

KAUST Repository

Ikeda, Robert; Cho, Junsang; Fang, Charlie; Salihoglu, Semih; Torikai, Satoshi; Widom, Jennifer

2012-01-01

Panda (for Provenance and Data) is a system that supports the creation and execution of data-oriented workflows, with automatic provenance generation and built-in provenance tracing operations. Workflows in Panda are arbitrary a cyclic graphs

(CBTP) on knowledge, problem-solving and learning approach

African Journals Online (AJOL)

In the first instance attention is paid to the effect of a computer-based teaching programme (CBTP) on the knowledge, problem-solving skills and learning approach of student ... In the practice group (oncology wards) no statistically significant change in the learning approach of respondents was found after using the CBTP.

GrandBase: generating actionable knowledge from Big Data

Directory of Open Access Journals (Sweden)

Xiu Susie Fang

2017-08-01

Full Text Available Purpose – This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB, called GrandBase. Design/methodology/approach – In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase. In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed. Findings – Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed. Originality/value – To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem. Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

A Knowledge-driven Approach to Composite Activity Recognition in Smart Environments

OpenAIRE

Chen, Liming; Wang, H.; Sterritt, Roy; Okeyo, George

2012-01-01

Knowledge-driven activity recognition has recently attracted increasing attention but mainly focused on simple activities. This paper extends previous work to introduce a knowledge-driven approach to recognition of composite activities such as interleaved and concurrent activities. The approach combines ontological and temporal knowledge modelling formalisms for composite activity modelling. It exploits ontological reasoning for simple activity recognition and rule-based temporal inference to...

The analysis phase in development of knowledge-based systems

International Nuclear Information System (INIS)

Brooking, A.G.

1986-01-01

Over the past twenty years computer scientists have realized that, in order to produce reliable software that is easily modifiable, a proven methodology is required. Unlike conventional systems there is little knowledge of the life cycle of these knowledge-based systems. However, if the life cycle of conventional systems, it is not unreasonable to assume that analysis will come first. With respect to the analysis task there is an enormous difference in types of analysis. Conventional systems analysis is predominately concerned with what happens within the system. Typically, procedures will be noted in the way they relate to each other, the way data moves and changes within the system. There is often an example, on paper or machine, that can be observed

A knowledge-driven approach to cluster validity assessment.

Science.gov (United States)

Bolshakova, Nadia; Azuaje, Francisco; Cunningham, Pádraig

2005-05-15

This paper presents an approach to assessing cluster validity based on similarity knowledge extracted from the Gene Ontology. The program is freely available for non-profit use on request from the authors.

Tracing Technological Development Trajectories: A Genetic Knowledge Persistence-Based Main Path Approach.

Directory of Open Access Journals (Sweden)

Hyunseok Park

Full Text Available The aim of this paper is to propose a new method to identify main paths in a technological domain using patent citations. Previous approaches for using main path analysis have greatly improved our understanding of actual technological trajectories but nonetheless have some limitations. They have high potential to miss some dominant patents from the identified main paths; nonetheless, the high network complexity of their main paths makes qualitative tracing of trajectories problematic. The proposed method searches backward and forward paths from the high-persistence patents which are identified based on a standard genetic knowledge persistence algorithm. We tested the new method by applying it to the desalination and the solar photovoltaic domains and compared the results to output from the same domains using a prior method. The empirical results show that the proposed method can dramatically reduce network complexity without missing any dominantly important patents. The main paths identified by our approach for two test cases are almost 10x less complex than the main paths identified by the existing approach. The proposed approach identifies all dominantly important patents on the main paths, but the main paths identified by the existing approach miss about 20% of dominantly important patents.

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

Science.gov (United States)

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.

Land Degradation Monitoring in the Ordos Plateau of China Using an Expert Knowledge and BP-ANN-Based Approach

Directory of Open Access Journals (Sweden)

Yaojie Yue

2016-11-01

Full Text Available Land degradation monitoring is of vital importance to provide scientific information for promoting sustainable land utilization. This paper presents an expert knowledge and BP-ANN-based approach to detect and monitor land degradation in an effort to overcome the deficiencies of image classification and vegetation index-based approaches. The proposed approach consists of three generic steps: (1 extraction of knowledge on the relationship between land degradation degree and predisposing factors, which are NDVI and albedo, from domain experts; (2 establishment of a land degradation detecting model based on the BP-ANN algorithm; and (3 land degradation dynamic analysis. A comprehensive analysis was conducted on the development of land degradation in the Ordos Plateau of China in 1990, 2000 and 2010. The results indicate that the proposed approach is reliable for monitoring land degradation, with an overall accuracy of 91.2%. From 1990–2010, a reverse trend of land degradation is observed in Ordos Plateau. Regions with relatively high land degradation dynamic were mostly located in the northeast of Ordos Plateau. Additionally, most of the regions have transferred from a hot spot of land degradation to a less changed area. It is suggested that land utilization optimization plays a key role for effective land degradation control. However, it should be highlighted that the goals of such strategies should aim at the main negative factors causing land degradation, and the land use type and its quantity must meet the demand of population and be reconciled with natural conditions. Results from this case study suggest that the expert knowledge and BP-ANN-based approach is effective in mapping land degradation.

Model-based Abstraction of Data Provenance

NARCIS (Netherlands)

Probst, Christian W.; Hansen, René Rydhof

Identifying provenance of data provides insights to the origin of data and intermediate results, and has recently gained increased interest due to data-centric applications. In this work we extend a data-centric system view with actors handling the data and policies restricting actions. This

Knowledge-based Fragment Binding Prediction

Science.gov (United States)

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Transition to knowledge-based economy in Saudi Arabia

NARCIS (Netherlands)

Nour, S.

2014-01-01

This paper discusses the progress in transition to knowledge-based economy in Saudi Arabia. As for the methodology, this paper uses updated secondary data obtained from different sources. It uses both descriptive and comparative approaches and uses the OECD definition of knowledge-based economy and

Characterization of GM events by insert knowledge adapted re-sequencing approaches.

Science.gov (United States)

Yang, Litao; Wang, Congmao; Holst-Jensen, Arne; Morisset, Dany; Lin, Yongjun; Zhang, Dabing

2013-10-03

Detection methods and data from molecular characterization of genetically modified (GM) events are needed by stakeholders of public risk assessors and regulators. Generally, the molecular characteristics of GM events are incomprehensively revealed by current approaches and biased towards detecting transformation vector derived sequences. GM events are classified based on available knowledge of the sequences of vectors and inserts (insert knowledge). Herein we present three insert knowledge-adapted approaches for characterization GM events (TT51-1 and T1c-19 rice as examples) based on paired-end re-sequencing with the advantages of comprehensiveness, accuracy, and automation. The comprehensive molecular characteristics of two rice events were revealed with additional unintended insertions comparing with the results from PCR and Southern blotting. Comprehensive transgene characterization of TT51-1 and T1c-19 is shown to be independent of a priori knowledge of the insert and vector sequences employing the developed approaches. This provides an opportunity to identify and characterize also unknown GM events.

A knowledge-based approach to improving and homogenizing intensity modulated radiation therapy planning quality among treatment centers: an example application to prostate cancer planning.

Science.gov (United States)

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

2013-09-01

Intensity modulated radiation therapy (IMRT) treatment planning can have wide variation among different treatment centers. We propose a system to leverage the IMRT planning experience of larger institutions to automatically create high-quality plans for outside clinics. We explore feasibility by generating plans for patient datasets from an outside institution by adapting plans from our institution. A knowledge database was created from 132 IMRT treatment plans for prostate cancer at our institution. The outside institution, a community hospital, provided the datasets for 55 prostate cancer cases, including their original treatment plans. For each "query" case from the outside institution, a similar "match" case was identified in the knowledge database, and the match case's plan parameters were then adapted and optimized to the query case by use of a semiautomated approach that required no expert planning knowledge. The plans generated with this knowledge-based approach were compared with the original treatment plans at several dose cutpoints. Compared with the original plan, the knowledge-based plan had a significantly more homogeneous dose to the planning target volume and a significantly lower maximum dose. The volumes of the rectum, bladder, and femoral heads above all cutpoints were nominally lower for the knowledge-based plan; the reductions were significantly lower for the rectum. In 40% of cases, the knowledge-based plan had overall superior (lower) dose-volume histograms for rectum and bladder; in 54% of cases, the comparison was equivocal; in 6% of cases, the knowledge-based plan was inferior for both bladder and rectum. Knowledge-based planning was superior or equivalent to the original plan in 95% of cases. The knowledge-based approach shows promise for homogenizing plan quality by transferring planning expertise from more experienced to less experienced institutions. Copyright © 2013 Elsevier Inc. All rights reserved.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support

OpenAIRE

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Background Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians? experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mech...

Persistent identifiers for web service requests relying on a provenance ontology design pattern

Science.gov (United States)

Car, Nicholas; Wang, Jingbo; Wyborn, Lesley; Si, Wei

2016-04-01

Delivering provenance information for datasets produced from static inputs is relatively straightforward: we represent the processing actions and data flow using provenance ontologies and link to stored copies of the inputs stored in repositories. If appropriate detail is given, the provenance information can then describe what actions have occurred (transparency) and enable reproducibility. When web service-generated data is used by a process to create a dataset instead of a static inputs, we need to use sophisticated provenance representations of the web service request as we can no longer just link to data stored in a repository. A graph-based provenance representation, such as the W3C's PROV standard, can be used to model the web service request as a single conceptual dataset and also as a small workflow with a number of components within the same provenance report. This dual representation does more than just allow simplified or detailed views of a dataset's production to be used where appropriate. It also allow persistent identifiers to be assigned to instances of a web service requests, thus enabling one form of dynamic data citation, and for those identifiers to resolve to whatever level of detail implementers think appropriate in order for that web service request to be reproduced. In this presentation we detail our reasoning in representing web service requests as small workflows. In outline, this stems from the idea that web service requests are perdurant things and in order to most easily persist knowledge of them for provenance, we should represent them as a nexus of relationships between endurant things, such as datasets and knowledge of particular system types, as these endurant things are far easier to persist. We also describe the ontology design pattern that we use to represent workflows in general and how we apply it to different types of web service requests. We give examples of specific web service requests instances that were made by systems

Enhancing the Teaching-Learning Process: A Knowledge Management Approach

Science.gov (United States)

Bhusry, Mamta; Ranjan, Jayanthi

2012-01-01

Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…

Aggregation by Provenance Types: A Technique for Summarising Provenance Graphs

Directory of Open Access Journals (Sweden)

Luc Moreau

2015-04-01

Full Text Available As users become confronted with a deluge of provenance data, dedicated techniques are required to make sense of this kind of information. We present Aggregation by Provenance Types, a provenance graph analysis that is capable of generating provenance graph summaries. It proceeds by converting provenance paths up to some length k to attributes, referred to as provenance types, and by grouping nodes that have the same provenance types. The summary also includes numeric values representing the frequency of nodes and edges in the original graph. A quantitative evaluation and a complexity analysis show that this technique is tractable; with small values of k, it can produce useful summaries and can help detect outliers. We illustrate how the generated summaries can further be used for conformance checking and visualization.

An Ontology-Based Approach for Knowledge Lifecycle Management within Aircraft Lifecycle Phases

NARCIS (Netherlands)

Verhagen, W.J.C.

2013-01-01

In the aerospace domain, manufacturers and operators constantly seek to improve their products and processes. Increasingly, knowledge-based applications are developed to support or automate knowledge-intensive engineering tasks, saving time and money. However, engineering knowledge changes over

Issues involved in a knowledge-based approach to procedure synthesis

International Nuclear Information System (INIS)

Hajek, B.K.; Khartabil, L.F.; Miller, D.W.

1992-01-01

Many knowledge-based systems (KBSs) have been built to assist human operators in managing nuclear power plant operating functions, such as monitoring, fault diagnosis, alarm filtering, and procedure management. For procedure management, KBSs have been built to display and track existing written procedures or to dynamically follow procedure execution by monitoring plant data and action execution and suggesting recovery steps. More recent works build KBSs able to synthesize procedures. This paper addresses and examines the main issues related to the implementation of on-line procedure synthesis using KBSs. A KBS for procedure synthesis can provide a more robust and effective procedural plan during accidents. Currently existing procedures for abnormal plant conditions, written as precompiled step sets based on the event and symptom approaches, are inherently not robust because anticipation of all potential plant states and associated plant responses is not possible. Thus, their failure recovery capability is limited to the precompiled set. Procedure synthesis has the potential to overcome these two problems because it does not require such precompilation of large sets of plant states and associated recovery procedures. Other benefits obtained from a complete procedure synthesis system are providing (a) a methodology for off-line procedure verification and (b) a methodology for the eventual automation of plant operations

Knowledge-Centric Technical Support Organization (TSO) Using Process Oriented Knowledge Management Approach

International Nuclear Information System (INIS)

Mohamad Safuan Sulaiman; Siti Nurbahyah Hamdan; Mohd Dzul Aiman Aslan

2014-01-01

In the United States of America, Process Oriented Knowledge Management (POKM) Model has been successfully implemented in most of Nuclear Power Plants. This approach has been introduced in Nuclear Knowledge Management program by the IAEA since 2011. Malaysia has involved in the IAEA Coordinated Research Project (CRP) focusing the approach started in 2011. The main objective for Malaysian participation of this project is to support readiness in terms of nuclear technical knowledge by Technical Support Organization (TSO) for Nuclear Power Program. This project has focused on several nuclear technical areas which consist of Public Information (PI), Radiological Impact Assessment (RIA), Nuclear Reactor Technology (NRT), Plant and Prototype Development (PDC) and nuclear knowledge management. This paper articulates the detail POKM approach and project experience in implementing the approach at organizational level. (author)

Knowledge Governance in Project-Based Organizations

DEFF Research Database (Denmark)

Pemsel, Sofia; Wiewiora, Anna; Müller, Ralf

This paper conceptualizes knowledge governance (KG) in project-based organizations (PBOs) and its methodological approaches for empirical investigation. Three key contributions towards a multi-faceted view of KG and an understanding of KG in PBOs are advanced. These contributions include a defini......This paper conceptualizes knowledge governance (KG) in project-based organizations (PBOs) and its methodological approaches for empirical investigation. Three key contributions towards a multi-faceted view of KG and an understanding of KG in PBOs are advanced. These contributions include...... a definition of KG in PBOs, a conceptual framework to investigate KG and a methodological framework for empirical inquiry into KG in PBO settings. Our definition highlights the contingent nature of KG processes in relation to their organizational context. The conceptual framework addresses macro- and micro...

Using Blockchain and smart contracts for secure data provenance management

OpenAIRE

Ramachandran, Aravind; Kantarcioglu, Dr. Murat

2017-01-01

Blockchain technology has evolved from being an immutable ledger of transactions for cryptocurrencies to a programmable interactive the environment for building distributed reliable applications. Although, blockchain technology has been used to address various challenges, to our knowledge none of the previous work focused on using blockchain to develop a secure and immutable scientific data provenance management framework that automatically verifies the provenance records. In this work, we le...

Knowledge based management of technical specifications

International Nuclear Information System (INIS)

Fiedler, U.; Schalm, S.; Pranckeviciute, K.

1992-01-01

TechSPEX is a knowledge based advisory system for checking the status of a nuclear plant on compliance with the safety limits and the limiting conditions of operation. These prescripts for safe reactor operation exist as textual information. For the purpose of its operational use an explicit representation formalism is introduced. On this basis, various approaches of text retrieval are realized, condition based surveillance and control is supported too. Knowledge editing and verification modules ease the adaption to changing requirements. TechSPEX has been implemented in PROLOG. (author). 6 refs, 3 figs

An approach to enrich online medical Problem-Based Learning with tacit healthcare knowledge.

Science.gov (United States)

Cheah, Yu-N; Rashid, Faridah Abdul; Abidi, Syed Sibte Raza

2003-01-01

Existing Problem-Based Learning (PBL) problems, though suitable in their own right for teaching purposes, are limited in their potential to evolve by themselves and to create new knowledge. Presently, they are based on textbook examples of past cases and/or cases that have been transcribed by a clinician. In this paper, we present (a) a tacit healthcare knowledge representation formalism called Healthcare Scenarios, (b) the relevance of healthcare scenarios in PBL in healthcare and medicine, (c) a novel PBL-Scenario-based tacit knowledge explication strategy and (d) an online PBL Problem Composer and Presenter (PBL-Online) to facilitate the acquisition and utilisation of expert-quality tacit healthcare knowledge to enrich online PBL. We employ a confluence of healthcare knowledge management tools and Internet technologies to bring tacit healthcare knowledge-enriched PBL to a global and yet more accessible level.

An Ontology-Based Knowledge Modelling for a Sustainability Assessment Domain

Directory of Open Access Journals (Sweden)

Agnieszka Konys

2018-01-01

Full Text Available Sustainability assessment has received more and more attention from researchers and it offers a large number of opportunities to measure and evaluate the level of its accomplishment. However, proper selection of a particular sustainability assessment approach, reflecting problem properties and the evaluator’s preferences, is a complex and important issue. Due to an existing number of different approaches dedicated to assessing, supporting, or measuring the level of sustainability and their structure oriented on the particular domain usage, problems with accurate matching frequently occur. On the other hand, the efficiency of sustainability assessment depends on the available knowledge of the ongoing capabilities. Additionally, actual research trends confirm that knowledge engineering gives a method to handle domain knowledge practically and effectively. Unfortunately, literature studies confirm that there is a lack of knowledge systematization in the sustainability assessment domain, however. The practical application of knowledge-based mechanisms may cover this gap. In this paper, we provide formal, practical and technological guidance to a knowledge management-based approach to sustainability assessment. We propose ontology as a form of knowledge conceptualization and using knowledge engineering, we make gathered knowledge publicly available and reusable, especially in terms of interoperability of collected knowledge.

An Object-Oriented Approach to Knowledge Representation in a Biomedical Domain

NARCIS (Netherlands)

Ensing, M.; Paton, R.; Speel, P.H.W.M.; Speel, P.H.W.M.; Rada, R.

1994-01-01

An object-oriented approach has been applied to the different stages involved in developing a knowledge base about insulin metabolism. At an early stage the separation of terminological and assertional knowledge was made. The terminological component was developed by medical experts and represented

Knowledge collaborative incentive based on inter-organizational cooperative innovation of project-based supply chain

Directory of Open Access Journals (Sweden)

Guangdong Wu

2013-09-01

Full Text Available Purpose: Within project-based supply chain inter-organizational cooperative innovation, the achievement of project value-adding reflects by factors such as project-based organizational effect level, the relationship between project cooperative innovation objectives etc. The purpose is to provide a reliable reference for the contractor reasonably allocate the effect level and resources between the knowledge input and innovation stage and realize the knowledge collaboration for project-based supply chain. Design/methodology/approach: Based on the assumption of equal cooperation between project-based organizations, from the view of maximizing project value-adding and the relationship of effect cost between knowledge input and innovation stage in consideration, the knowledge collaborative incentive model for project-based supply chain inter-organizational cooperative innovation was established, and solved through the first-order and second-order approach, then the digital simulation and example analysis were presented. Findings: The results show that, the project management enterprise resorted to adjust project knowledge collaboration incentive intensity and implemented knowledge input-innovation coordinative incentive strategy, not only could achieve project value-adding maximization, but also could realize net earnings Pareto improvement between project management enterprise and contractor. Research limitations/implications: To simplify the knowledge flow among project-based organizations, the knowledge flow in the model hypothesis is presented as knowledge input and knowledge innovation stage, thus it may affect the final analysis results. Originality/value: In construction project practice, knowledge is become more and more important to achieve project value-adding. The research can provide a theoretical guideline for the project-based organizations, such as the contractor, the owner, especially how to utilize their core knowledge.

Next Generation Cloud-based Science Data Systems and Their Implications on Data and Software Stewardship, Preservation, and Provenance

Science.gov (United States)

Hua, H.; Manipon, G.; Starch, M.

2017-12-01

NASA's upcoming missions are expected to be generating data volumes at least an order of magnitude larger than current missions. A significant increase in data processing, data rates, data volumes, and long-term data archive capabilities are needed. Consequently, new challenges are emerging that impact traditional data and software management approaches. At large-scales, next generation science data systems are exploring the move onto cloud computing paradigms to support these increased needs. New implications such as costs, data movement, collocation of data systems & archives, and moving processing closer to the data, may result in changes to the stewardship, preservation, and provenance of science data and software. With more science data systems being on-boarding onto cloud computing facilities, we can expect more Earth science data records to be both generated and kept in the cloud. But at large scales, the cost of processing and storing global data may impact architectural and system designs. Data systems will trade the cost of keeping data in the cloud with the data life-cycle approaches of moving "colder" data back to traditional on-premise facilities. How will this impact data citation and processing software stewardship? What are the impacts of cloud-based on-demand processing and its affect on reproducibility and provenance. Similarly, with more science processing software being moved onto cloud, virtual machines, and container based approaches, more opportunities arise for improved stewardship and preservation. But will the science community trust data reprocessed years or decades later? We will also explore emerging questions of the stewardship of the science data system software that is generating the science data records both during and after the life of mission.

Knowledge base mechanisms

Energy Technology Data Exchange (ETDEWEB)

Suwa, M; Furukawa, K; Makinouchi, A; Mizoguchi, T; Mizoguchi, F; Yamasaki, H

1982-01-01

One of the principal goals of the Fifth Generation Computer System Project for the coming decade is to develop a methodology for building knowledge information processing systems which will provide people with intelligent agents. The key notion of the fifth generation computer system is knowledge used for problem solving. In this paper the authors describe the plan of Randd on knowledge base mechanisms. A knowledge representation system is to be designed to support knowledge acquisition for the knowledge information processing systems. The system will include a knowledge representation language, a knowledge base editor and a debugger. It is also expected to perform as a kind of meta-inference system. In order to develop the large scale knowledge base systems, a knowledge base mechanism based on the relational model is to be studied in the earlier stage of the project. Distributed problem solving is also one of the main issues of the project. 19 references.

Utilizing Provenance in Reusable Research Objects

Directory of Open Access Journals (Sweden)

Zhihao Yuan

2018-03-01

Full Text Available Science is conducted collaboratively, often requiring the sharing of knowledge about computational experiments. When experiments include only datasets, they can be shared using Uniform Resource Identifiers (URIs or Digital Object Identifiers (DOIs. An experiment, however, seldom includes only datasets, but more often includes software, its past execution, provenance, and associated documentation. The Research Object has recently emerged as a comprehensive and systematic method for aggregation and identification of diverse elements of computational experiments. While a necessary method, mere aggregation is not sufficient for the sharing of computational experiments. Other users must be able to easily recompute on these shared research objects. Computational provenance is often the key to enable such reuse. In this paper, we show how reusable research objects can utilize provenance to correctly repeat a previous reference execution, to construct a subset of a research object for partial reuse, and to reuse existing contents of a research object for modified reuse. We describe two methods to summarize provenance that aid in understanding the contents and past executions of a research object. The first method obtains a process-view by collapsing low-level system information, and the second method obtains a summary graph by grouping related nodes and edges with the goal to obtain a graph view similar to application workflow. Through detailed experiments, we show the efficacy and efficiency of our algorithms.

Formal Support for Development of Knowledge-Based Systems

NARCIS (Netherlands)

Fensel, Dieter; Van Harmelen, Frank; Reif, Wolfgang; Ten Teije, Annette

1998-01-01

This article provides an approach for developing reliable knowledge-based systems. Its main contributions are: Specification is done at an architectural level that abstracts from a specific implementation formalism. The model of expertise of CommonKADS distinguishs different types of knowledge and

Models, methods and software for distributed knowledge acquisition for the automated construction of integrated expert systems knowledge bases

International Nuclear Information System (INIS)

Dejneko, A.O.

2011-01-01

Based on an analysis of existing models, methods and means of acquiring knowledge, a base method of automated knowledge acquisition has been chosen. On the base of this method, a new approach to integrate information acquired from knowledge sources of different typologies has been proposed, and the concept of a distributed knowledge acquisition with the aim of computerized formation of the most complete and consistent models of problem areas has been introduced. An original algorithm for distributed knowledge acquisition from databases, based on the construction of binary decision trees has been developed [ru

Comparison of clinical knowledge bases for summarization of electronic health records.

Science.gov (United States)

McCoy, Allison B; Sittig, Dean F; Wright, Adam

2013-01-01

Automated summarization tools that create condition-specific displays may improve clinician efficiency. These tools require new kinds of knowledge that is difficult to obtain. We compared five problem-medication pair knowledge bases generated using four previously described knowledge base development approaches. The number of pairs in the resulting mapped knowledge bases varied widely due to differing mapping techniques from the source terminologies, ranging from 2,873 to 63,977,738 pairs. The number of overlapping pairs across knowledge bases was low, with one knowledge base having half of the pairs overlapping with another knowledge base, and most having less than a third overlapping. Further research is necessary to better evaluate the knowledge bases independently in additional settings, and to identify methods to integrate the knowledge bases.

Extending eScience Provenance with User-Submitted Semantic Annotations

Science.gov (United States)

Michaelis, J.; Zednik, S.; West, P.; Fox, P. A.; McGuinness, D. L.

2010-12-01

eScience based systems generate provenance of their data products, related to such things as: data processing, data collection conditions, expert evaluation, and data product quality. Recent advances in web-based technology offer users the possibility of making annotations to both data products and steps in accompanying provenance traces, thereby expanding the utility of such provenance for others. These contributing users may have varying backgrounds, ranging from system experts to outside domain experts to citizen scientists. Furthermore, such users may wish to make varying types of annotations - ranging from documenting the purpose of a provenance step to raising concerns about the quality of data dependencies. Semantic Web technologies allow for such kinds of rich annotations to be made to provenance through the use of ontology vocabularies for (i) organizing provenance, and (ii) organizing user/annotation classifications. Furthermore, through Linked Data practices, Semantic linkages may be made from provenance steps to external data of interest. A desire for Semantically-annotated provenance has been motivated by data management issues in the Mauna Loa Solar Observatory’s (MLSO) Advanced Coronal Observing System (ACOS). In ACOS, photomoeter-based readings are taken of solar activity and subsequently processed into final data products consumable by end users. At intermediate stages of ACOS processing, factors such as evaluations by human experts and weather conditions are logged, which could impact data product quality. If such factors are linked via user-submitted annotations to provenance, it could be significantly beneficial for other users. Likewise, the background of a user could impact the credibility of their annotations. For example, an annotation made by a citizen scientist describing the purpose of a provenance step may not be as reliable as a similar annotation made by an ACOS project member. For this work, we have developed a software package that

A knowledge-based approach to estimating the magnitude and spatial patterns of potential threats to soil biodiversity.

Science.gov (United States)

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

Influence of the Migration Process on the Learning Performances of Fuzzy Knowledge Bases

DEFF Research Database (Denmark)

Akrout, Khaled; Baron, Luc; Balazinski, Marek

2007-01-01

This paper presents the influence of the process of migration between populations in GENO-FLOU, which is an environment of learning of fuzzy knowledge bases by genetic algorithms. Initially the algorithm did not use the process of migration. For the learning, the algorithm uses a hybrid coding......, binary for the base of rules and real for the data base. This hybrid coding used with a set of specialized operators of reproduction proven to be an effective environment of learning. Simulations were made in this environment by adding a process of migration. While varying the number of populations...

Characterization of GM events by insert knowledge adapted re-sequencing approaches

OpenAIRE

Yang, Litao; Wang, Congmao; Holst-Jensen, Arne; Morisset, Dany; Lin, Yongjun; Zhang, Dabing

2013-01-01

Detection methods and data from molecular characterization of genetically modified (GM) events are needed by stakeholders of public risk assessors and regulators. Generally, the molecular characteristics of GM events are incomprehensively revealed by current approaches and biased towards detecting transformation vector derived sequences. GM events are classified based on available knowledge of the sequences of vectors and inserts (insert knowledge). Herein we present three insert knowledge-ad...

Fault detection and reliability, knowledge based and other approaches

International Nuclear Information System (INIS)

Singh, M.G.; Hindi, K.S.; Tzafestas, S.G.

1987-01-01

These proceedings are split up into four major parts in order to reflect the most significant aspects of reliability and fault detection as viewed at present. The first part deals with knowledge-based systems and comprises eleven contributions from leading experts in the field. The emphasis here is primarily on the use of artificial intelligence, expert systems and other knowledge-based systems for fault detection and reliability. The second part is devoted to fault detection of technological systems and comprises thirteen contributions dealing with applications of fault detection techniques to various technological systems such as gas networks, electric power systems, nuclear reactors and assembly cells. The third part of the proceedings, which consists of seven contributions, treats robust, fault tolerant and intelligent controllers and covers methodological issues as well as several applications ranging from nuclear power plants to industrial robots to steel grinding. The fourth part treats fault tolerant digital techniques and comprises five contributions. Two papers, one on reactor noise analysis, the other on reactor control system design, are indexed separately. (author)

Competency-based teacher training: A systematic revision of a proven programme in medical didactics.

Science.gov (United States)

Griewatz, Jan; Simon, Melanie; Lammerding-Koeppel, Maria

2017-01-01

Objectives: Competency-based medical education (CBME) requires factual knowledge to be practically applied together with skills and attitudes. With the National Competence-Based Learning Objectives for Undergraduate Medical Education (NKLM) representing a strong official demand for competence-orientation, it is generally important to explicitly outline its characteristics and review its realisation in teacher trainings. Further requirements are given by the core competencies for medical teachers (KLM). As an example the MQ programme ("Medizindidaktische Qualifikation") in Baden-Wuerttemberg, a long established and well-accepted training, has been critically revised on this basis, concerning its suitability for the demands of CBME, its needs for adjustment and the efforts to be undertaken for its implementation. Methods: In a systematic quality management process the MQ curriculum and its organisational framing were analysed and further developed in a step-wise comprehensive approach, using the six-step cycle by Kern. The procedures included a thorough needs assessment (e.g. literature research, programme mapping), strategic decisions on structure and content, piloting and evaluation. During the process essential elements of project and change management were considered. Results: The experiences of the MQ example revealed helpful information for key factors to be considered in the pending change process any training provider will be confronted with. Guiding questions were developed related to the process phases. Our analyses showed persistent key points of proven value as stable foundation for change, as well as components needing special consideration to foster competence-oriented aims and transfer into practice: reflection, feedback, application-oriented methods and transparent competence development. These aspects have to be consciously perceived and experienced by participants. Taking this into account, we re-designed the course evidence-based. Besides

Modeling and knowledge acquisition processes using case-based inference

Directory of Open Access Journals (Sweden)

Ameneh Khadivar

2017-03-01

Full Text Available The method of acquisition and presentation of the organizational Process Knowledge has considered by many KM researches. In this research a model for process knowledge acquisition and presentation has been presented by using the approach of Case Base Reasoning. The validation of the presented model was evaluated by conducting an expert panel. Then a software has been developed based on the presented model and implemented in Eghtesad Novin Bank of Iran. In this company, based on the stages of the presented model, first the knowledge intensive processes has been identified, then the Process Knowledge was stored in a knowledge base in the format of problem/solution/consequent .The retrieval of the knowledge was done based on the similarity of the nearest neighbor algorithm. For validating of the implemented system, results of the system has compared by the results of the decision making of the expert of the process.

Knowledge Reduction Based on Divide and Conquer Method in Rough Set Theory

Directory of Open Access Journals (Sweden)

Feng Hu

2012-01-01

Full Text Available The divide and conquer method is a typical granular computing method using multiple levels of abstraction and granulations. So far, although some achievements based on divided and conquer method in the rough set theory have been acquired, the systematic methods for knowledge reduction based on divide and conquer method are still absent. In this paper, the knowledge reduction approaches based on divide and conquer method, under equivalence relation and under tolerance relation, are presented, respectively. After that, a systematic approach, named as the abstract process for knowledge reduction based on divide and conquer method in rough set theory, is proposed. Based on the presented approach, two algorithms for knowledge reduction, including an algorithm for attribute reduction and an algorithm for attribute value reduction, are presented. Some experimental evaluations are done to test the methods on uci data sets and KDDCUP99 data sets. The experimental results illustrate that the proposed approaches are efficient to process large data sets with good recognition rate, compared with KNN, SVM, C4.5, Naive Bayes, and CART.

A System Theoretical Inspired Approach to Knowledge Construction

DEFF Research Database (Denmark)

Mathiasen, Helle

2008-01-01

student's knowledge construction, in the light of operative constructivism, inspired by the German sociologist N. Luhmann's system theoretical approach to epistemology. Taking observations as operations based on distinction and indication (selection) contingency becomes a fundamental condition in learning......  Abstract The aim of this paper is to discuss the relation between teaching and learning. The point of departure is that teaching environments (communication forums) is a potential facilitator for learning processes and knowledge construction. The paper present a theoretical frame work, to discuss...... processes, and a condition which teaching must address as far as teaching strives to stimulate non-random learning outcomes. Thus learning outcomes understood as the individual learner's knowledge construction cannot be directly predicted from events and characteristics in the environment. This has...

Integrating prediction, provenance, and optimization into high energy workflows

Energy Technology Data Exchange (ETDEWEB)

Schram, M.; Bansal, V.; Friese, R. D.; Tallent, N. R.; Yin, J.; Barker, K. J.; Stephan, E.; Halappanavar, M.; Kerbyson, D. J.

2017-10-01

We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

Identification of Managerial Competencies in Knowledge-based Organizations

Directory of Open Access Journals (Sweden)

Königová Martina

2012-03-01

Full Text Available Managerial competencies identification and development are important tools of human resources management that is aimed at achieving strategic organizational goals. Due to current dynamic development and changes, more and more attention is being paid to the personality of managers and their competencies, since they are viewed as important sources of achieving a competitive advantage. The objective of this article is to identify managerial competencies in the process of filling vacant working positions in knowledge-based organizations in the Czech Republic. The objective was determined with reference to the Czech Science Foundation GACR research project which focuses on the identification of managerial competencies in knowledge-based organizations in the Czech Republic. This identification within the frame of the research project is primarily designed and subsequently realised on the basis of content analysis of media communications such as advertisements - a means through which knowledge- based organizations search for suitable candidates for vacant managerial positions. The first part of the article deals with theoretical approaches to knowledge-based organizations and issues on competencies. The second part evaluates the outcomes of the survey carried out, and also summarizes the basic steps of the application of competencies. The final part summarizes the benefits and difficulties of applying the competency-based approach as a tool of efficient management of organizations for the purpose of achieving a competitive advantage.

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

Science.gov (United States)

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

2015-01-01

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. 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. 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. 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%. 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.

Community-based participatory research and integrated knowledge translation: advancing the co-creation of knowledge.

Science.gov (United States)

Jull, Janet; Giles, Audrey; Graham, Ian D

2017-12-19

Better use of research evidence (one form of "knowledge") in health systems requires partnerships between researchers and those who contend with the real-world needs and constraints of health systems. Community-based participatory research (CBPR) and integrated knowledge translation (IKT) are research approaches that emphasize the importance of creating partnerships between researchers and the people for whom the research is ultimately meant to be of use ("knowledge users"). There exist poor understandings of the ways in which these approaches converge and diverge. Better understanding of the similarities and differences between CBPR and IKT will enable researchers to use these approaches appropriately and to leverage best practices and knowledge from each. The co-creation of knowledge conveys promise of significant social impacts, and further understandings of how to engage and involve knowledge users in research are needed. We examine the histories and traditions of CBPR and IKT, as well as their points of convergence and divergence. We critically evaluate the ways in which both have the potential to contribute to the development and integration of knowledge in health systems. As distinct research traditions, the underlying drivers and rationale for CBPR and IKT have similarities and differences across the areas of motivation, social location, and ethics; nevertheless, the practices of CBPR and IKT converge upon a common aim: the co-creation of knowledge that is the result of knowledge user and researcher expertise. We argue that while CBPR and IKT both have the potential to contribute evidence to implementation science and practices for collaborative research, clarity for the purpose of the research-social change or application-is a critical feature in the selection of an appropriate collaborative approach to build knowledge. CBPR and IKT bring distinct strengths to a common aim: to foster democratic processes in the co-creation of knowledge. As research

KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS

Directory of Open Access Journals (Sweden)

F. Boochs

2012-07-01

Full Text Available Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL, used for formulating the knowledge base and the Semantic Web Rule Language (SWRL with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’ knowledge of the scene and algorithmic processing.

Knowledge-Based Object Detection in Laser Scanning Point Clouds

Science.gov (United States)

Boochs, F.; Karmacharya, A.; Marbs, A.

2012-07-01

Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

Role of Knowledge Based Communities in Knowledge Process

Directory of Open Access Journals (Sweden)

Sebastian Ion CEPTUREANU

2015-12-01

Full Text Available In the new economy, knowledge is an essential component of economic and social systems. The organizational focus has to be on building knowledge-based management, development of human resource and building intellectual capital capabilities. Knowledge-based management is defined, at company level, by economic processes that emphasize creation, selling, buying, learning, storing, developing, sharing and protection of knowledge as a decisive condition for profit and long-term sustainability of the company. Hence, knowledge is, concurently, according to a majoritiy of specialists, raw material, capital, product and an essential input. Knowledge-based communities are one of the main constituent elements of a framework for knowledge based management. These are peer networks consisting of practitioners within an organization, supporting each other to perform better through the exchange and sharing of knowledge. Some large companies have contributed or supported the establishment of numerous communities of practice, some of which may have several thousand members. They operate in different ways, are of different sizes, have different areas of interest and addresses knowledge at different levels of its maturity. This article examines the role of knowledge-based communities from the perspective of knowledge based management, given that the arrangements for organizational learning, creating, sharing, use of knowledge within organizations become more heterogeneous and take forms more difficult to predict by managers and specialists.

Can free open access resources strengthen knowledge-based emerging public health priorities, policies and programs in Africa?

Science.gov (United States)

Tambo, Ernest; Madjou, Ghislaine; Khayeka-Wandabwa, Christopher; Tekwu, Emmanuel N; Olalubi, Oluwasogo A; Midzi, Nicolas; Bengyella, Louis; Adedeji, Ahmed A; Ngogang, Jeanne Y

2016-01-01

Tackling emerging epidemics and infectious diseases burden in Africa requires increasing unrestricted open access and free use or reuse of regional and global policies reforms as well as timely communication capabilities and strategies. Promoting, scaling up data and information sharing between African researchers and international partners are of vital importance in accelerating open access at no cost. Free Open Access (FOA) health data and information acceptability, uptake tactics and sustainable mechanisms are urgently needed. These are critical in establishing real time and effective knowledge or evidence-based translation, proven and validated approaches, strategies and tools to strengthen and revamp health systems.  As such, early and timely access to needed emerging public health information is meant to be instrumental and valuable for policy-makers, implementers, care providers, researchers, health-related institutions and stakeholders including populations when guiding health financing, and planning contextual programs.

Automated Extraction of Cranial Landmarks from Computed Tomography Data using a Combined Method of Knowledge and Pattern Based Approaches

Directory of Open Access Journals (Sweden)

Roshan N. RAJAPAKSE

2016-03-01

Full Text Available Accurate identification of anatomical structures from medical imaging data is a significant and critical function in the medical domain. Past studies in this context have mainly utilized two main approaches, the knowledge and learning methodologies based methods. Further, most of previous reported studies have focused on identification of landmarks from lateral X-ray Computed Tomography (CT data, particularly in the field of orthodontics. However, this study focused on extracting cranial landmarks from large sets of cross sectional CT slices using a combined method of the two aforementioned approaches. The proposed method of this study is centered mainly on template data sets, which were created using the actual contour patterns extracted from CT cases for each of the landmarks in consideration. Firstly, these templates were used to devise rules which are a characteristic of the knowledge based method. Secondly, the same template sets were employed to perform template matching related to the learning methodologies approach. The proposed method was tested on two landmarks, the Dorsum sellae and the Pterygoid plate, using CT cases of 5 subjects. The results indicate that, out of the 10 tests, the output images were within the expected range (desired accuracy in 7 instances and acceptable range (near accuracy for 2 instances, thus verifying the effectiveness of the combined template sets centric approach proposed in this study.

Mathematical Knowledge for Teaching, Standards-Based Mathematics Teaching Practices, and Student Achievement in the Context of the "Responsive Classroom Approach"

Science.gov (United States)

Ottmar, Erin R.; Rimm-Kaufman, Sara E.; Larsen, Ross A.; Berry, Robert Q.

2015-01-01

This study investigates the effectiveness of the Responsive Classroom (RC) approach, a social and emotional learning intervention, on changing the relations between mathematics teacher and classroom inputs (mathematical knowledge for teaching [MKT] and standards-based mathematics teaching practices) and student mathematics achievement. Work was…

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Retrospective analysis of 104 histologically proven adult brainstem gliomas: clinical symptoms, therapeutic approaches and prognostic factors

International Nuclear Information System (INIS)

Reithmeier, Thomas; Kuzeawu, Aanyo; Hentschel, Bettina; Loeffler, Markus; Trippel, Michael; Nikkhah, Guido

2014-01-01

Adult brainstem gliomas are rare primary brain tumors (<2% of gliomas). The goal of this study was to analyze clinical, prognostic and therapeutic factors in a large series of histologically proven brainstem gliomas. Between 1997 and 2007, 104 patients with a histologically proven brainstem glioma were retrospectively analyzed. Data about clinical course of disease, neuropathological findings and therapeutic approaches were analyzed. The median age at diagnosis was 41 years (range 18-89 years), median KPS before any operative procedure was 80 (range 20-100) and median survival for the whole cohort was 18.8 months. Histopathological examinations revealed 16 grade I, 31 grade II, 42 grade III and 14 grade IV gliomas. Grading was not possible in 1 patient. Therapeutic concepts differed according to the histopathology of the disease. Median overall survival for grade II tumors was 26.4 months, for grade III tumors 12.9 months and for grade IV tumors 9.8 months. On multivariate analysis the relative risk to die increased with a KPS ≤ 70 by factor 6.7, with grade III/IV gliomas by the factor 1.8 and for age ≥ 40 by the factor 1.7. External beam radiation reduced the risk to die by factor 0.4. Adult brainstem gliomas present with a wide variety of neurological symptoms and postoperative radiation remains the cornerstone of therapy with no proven benefit of adding chemotherapy. Low KPS, age ≥ 40 and higher tumor grade have a negative impact on overall survival

An Inference-Based Framework to Manage Data Provenance in Geoscience Applications

NARCIS (Netherlands)

Huq, M.R.; Apers, Peter M.G.; Wombacher, Andreas

2013-01-01

Data provenance allows scientists to validate their model as well as to investigate the origin of an unexpected value. Furthermore, it can be used as a replication recipe for output data products. However, capturing provenance requires enormous effort by scientists in terms of time and training.

Virk: An Active Learning-based System for Bootstrapping Knowledge Base Development in the Neurosciences

Directory of Open Access Journals (Sweden)

Kyle H. Ambert

2013-12-01

Full Text Available 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 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, 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 active learning 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 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 1-2 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 active learning.

Irrelevance Reasoning in Knowledge Based Systems

Science.gov (United States)

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.

Knowledge-Oriented Physics-Based Motion Planning for Grasping Under Uncertainty

OpenAIRE

Ud Din, Muhayy; Akbari, Aliakbar; Rosell Gratacòs, Jan

2017-01-01

Grasping an object in unstructured and uncertain environments is a challenging task, particularly when a collision-free trajectory does not exits. High-level knowledge and reasoning processes, as well as the allowing of interaction between objects, can enhance the planning efficiency in such environments. In this direction, this study proposes a knowledge-oriented physics-based motion planning approach for a hand-arm system that uses a high-level knowledge-based reasoning to partition the wor...

Data provenance assurance in the cloud using blockchain

Science.gov (United States)

Shetty, Sachin; Red, Val; Kamhoua, Charles; Kwiat, Kevin; Njilla, Laurent

2017-05-01

Ever increasing adoption of cloud technology scales up the activities like creation, exchange, and alteration of cloud data objects, which create challenges to track malicious activities and security violations. Addressing this issue requires implementation of data provenance framework so that each data object in the federated cloud environment can be tracked and recorded but cannot be modified. The blockchain technology gives a promising decentralized platform to build tamper-proof systems. Its incorruptible distributed ledger/blockchain complements the need of maintaining cloud data provenance. In this paper, we present a cloud based data provenance framework using block chain which traces data record operations and generates provenance data. We anchor provenance data records into block chain transactions, which provide validation on provenance data and preserve user privacy at the same time. Once the provenance data is uploaded to the global block chain network, it is extremely challenging to tamper the provenance data. Besides, the provenance data uses hashed user identifiers prior to uploading so the blockchain nodes cannot link the operations to a particular user. The framework ensures that the privacy is preserved. We implemented the architecture on ownCloud, uploaded records to blockchain network, stored records in a provenance database and developed a prototype in form of a web service.

Knowledge Representation in Patient Safety Reporting: An Ontological Approach

Directory of Open Access Journals (Sweden)

Liang Chen

2016-10-01

Full Text Available Purpose: The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. Design/methodology/approach: We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our design, implementation, and evaluation of the ontology at its initial stage. Findings: We describe the design and initial outcomes of the ontology implementation. The evaluation results demonstrate the clinical validity of the ontology by a self-developed survey measurement. Research limitations: The proposed ontology was developed and evaluated using a small number of information sources. Presently, US data are used, but they are not essential for the ultimate structure of the ontology. Practical implications: The goal of improving patient safety can be aided through investigating patient safety reports and providing actionable knowledge to clinical practitioners. As such, constructing a domain specific ontology for patient safety reports serves as a cornerstone in information collection and text mining methods. Originality/value: The use of ontologies provides abstracted representation of semantic information and enables a wealth of applications in a reporting system. Therefore, constructing such a knowledge base is recognized as a high priority in health care.

Using fuzzy rule-based knowledge model for optimum plating conditions search

Science.gov (United States)

Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.

2018-03-01

The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.

Approaches of Knowledge Management System for the Decommissioning of Nuclear Facilities

International Nuclear Information System (INIS)

Iguchi, Y.; Yanagihara, S.; Kato, Y.; Tezuka, M.; Koda, Y.

2016-01-01

Full text: The decommissioning of a nuclear facility is a long term project, handling information beginning with design, construction and operation. Moreover, the decommissioning project is likely to be extended because of the lack of the waste disposal site. In this situation, as the transfer of knowledge to the next generation is a crucial issue, approaches of knowledge management (KM) are necessary. For this purpose, the total system of decommissioning knowledge management system (KMS) is proposed. In this system, we should arrange, organize and systematize the data and information of the plant design, maintenance history, trouble events, waste management records etc. The collected data, information and records should be organized by computer support systems. It becomes a base of the explicit knowledge. Moreover, measures of extracting tacit knowledge from retiring employees are necessary. The experience of the retirees should be documented as much as possible through effective questionnaire or interview process. In this way, various KM approaches become an integrated KMS as a whole. The system should be used for daily accumulation of knowledge thorough the planning, implementation and evaluation of decommissioning activities and it will contribute to the transfer of knowledge. (author

Knowledge-Based Control Systems via Internet Part I. Applications in Biotechnology

Directory of Open Access Journals (Sweden)

Georgi Georgiev

2005-04-01

Full Text Available An extensive approach towards the dissemination of expert knowledge and coordination efforts to distributed points and seamless integration of control strategies applied to distributed yet identical systems is crucial to enhance overall efficiency and operational costs. Application of Knowledge-Based Control System via Internet will be very efficient especially in biotechnology, because many industrial bioprocesses, based on the same technological principles, are distributed in the whole world. Brewing industry oriented practical solutions illustrate this approach.

A knowledge translation project on community-centred approaches in public health.

Science.gov (United States)

Stansfield, J; South, J

2018-03-01

This article examines the development and impact of a national knowledge translation project aimed at improving access to evidence and learning on community-centred approaches for health and wellbeing. Structural changes in the English health system meant that knowledge on community engagement was becoming lost and a fragmented evidence base was seen to impact negatively on policy and practice. A partnership started between Public Health England, NHS England and Leeds Beckett University in 2014 to address these issues. Following a literature review and stakeholder consultation, evidence was published in a national guide to community-centred approaches. This was followed by a programme of work to translate the evidence into national strategy and local practice.The article outlines the key features of the knowledge translation framework developed. Results include positive impacts on local practice and national policy, for example adoption within National Institute for Health and Care Evidence (NICE) guidance and Local Authority public health plans and utilization as a tool for local audit of practice and commissioning. The framework was successful in its non-linear approach to knowledge translation across a range of inter-connected activity, built on national leadership, knowledge brokerage, coalition building and a strong collaboration between research institute and government agency.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

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Minoo Aminian

2014-01-01

Full Text Available 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.

Development of a tool for knowledge base verification of expert system based on Design/CPN

International Nuclear Information System (INIS)

Kim, Jong Hyun

1998-02-01

Verification is a necessary work in developing a reliable expert system. Verification is a process aimed at demonstrating whether a system meets it's specified requirements. As expert systems are used in various applications, the knowledge base verification of systems takes an important position. The conventional Petri net approach that has been studied recently in order to verify the knowledge base is found that it is inadequate to verify the knowledge base of large and complex system, such as alarm processing system of nuclear power plant. Thus, we propose an improved method that models the knowledge base as enhanced colored Petri net. In this study, we analyze the reachability and the error characteristics of the knowledge base. Generally, verification process requires computational support by automated tools. For this reason, this study developed a tool for knowledge base verification based on Design/CPN, which is a tool for editing, modeling, and simulating Colored Petri net. This tool uses Enhanced Colored Petri net as a modeling method. By applying this tool to the knowledge base of nuclear power plant, it is noticed that it can successfully check most of the anomalies that can occur in a knowledge base

KNOWLEDGE SOCIETY, GENERAL FRAMEWORK FOR KNOWLEDGE BASED ECONOMY

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Dragos CRISTEA

2011-03-01

Full Text Available This paper tries to present the existent relation between knowledge society and knowledge based economy. We will identify the main pillars of knowledge society and present their importance for the development of knowledge societies. Further, we will present two perspectives over knowledge societies, respectively science and learning perspectives, that directly affects knowledge based economies. At the end, we will conclude by identifying some important questions that must be answered regarding this new social paradigm.

Knowledge-based utility

International Nuclear Information System (INIS)

Chwalowski, M.

1997-01-01

This presentation provides industry examples of successful marketing practices by companies facing deregulation and competition. The common thread through the examples is that long term survival of today's utility structure is dependent on the strategic role of knowledge. As opposed to regulated monopolies which usually own huge physical assets and have very little intelligence about their customers, unregulated enterprises tend to be knowledge-based, characterized by higher market value than book value. A knowledge-based enterprise gathers data, creates information and develops knowledge by leveraging it as a competitive weapon. It institutionalizes human knowledge as a corporate asset for use over and over again by the use of databases, computer networks, patents, billing, collection and customer services (BCCS), branded interfaces and management capabilities. Activities to become knowledge-based such as replacing inventory/fixed assets with information about material usage to reduce expenditure and achieve more efficient operations, and by focusing on integration and value-adding delivery capabilities, were reviewed

A diagnostic expert system for the nuclear power plant b ased on the hybrid knowledge approach

International Nuclear Information System (INIS)

Yang, J.O.; Chang, S.H.

1989-01-01

A diagnostic expert system, the hybrid knowledge based plant operation supporting system (HYPOSS), which has been developed to support operators' decisionmaking during the transients of the nuclear power plant, is described. HYPOSS adopts the hybrid knowledge approach, which combines both shallow and deep knowledge to take advantage of the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure. They are structural, functional, behavioral, and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions, respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem-solving behavior modeled in HYPOSS. The event-based operational guidelines are provided to the operator according to the diagnosed results. If the exact anomalies cannot be identified while some of the critical safety functions are challenged, the function-based operational guidelines are provided to the operator. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies show good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

A Provenance Tracking Model for Data Updates

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Gabriel Ciobanu

2012-08-01

Full Text Available For data-centric systems, provenance tracking is particularly important when the system is open and decentralised, such as the Web of Linked Data. In this paper, a concise but expressive calculus which models data updates is presented. The calculus is used to provide an operational semantics for a system where data and updates interact concurrently. The operational semantics of the calculus also tracks the provenance of data with respect to updates. This provides a new formal semantics extending provenance diagrams which takes into account the execution of processes in a concurrent setting. Moreover, a sound and complete model for the calculus based on ideals of series-parallel DAGs is provided. The notion of provenance introduced can be used as a subjective indicator of the quality of data in concurrent interacting systems.

Awareness of knowledge and practice regarding physical activity: A population-based prospective, observational study among students in Nanjing, China.

Directory of Open Access Journals (Sweden)

Fei Xu

Full Text Available Physical activity (PA promotion has proven effectiveness in preventing childhood obesity. Increasing children's health knowledge is the most frequently used approach in PA intervention programs targeting childhood obesity prevention. However, little is known about the specific association between the change in a child's knowledge awareness and their PA practice.A one-year follow-up study was conducted among primary and junior high school students in Nanjing, China. At baseline students' knowledge of healthy behavior, and their PA levels, were assessed. Students who were unaware of the association between PA and obesity were followed for one academic year. After nine-months their knowledge and PA levels were re-measured using the same validated questionnaire. Mixed effects regression models were used to estimate the relationship between awareness of knowledge about the link between PA and obesity and PA changes.Of the 1899 students who were unaware of the association between PA and obesity at baseline, 1859 (follow-up rate = 97.9% were successfully followed-up. After nine months 1318 (70.9% participants had become aware of PA-obesity association. Compared to their counterparts who remained unaware, students who became aware of the PA-obesity association were more likely to increase both the frequency (odds ratio (OR = 1.34, 95%CI = 1.09, 1.64 and duration (OR = 1.34, 95%CI = 1.09, 1.65 of PA, after adjusting for potentially confounding variables.Becoming aware of the known link between PA and obesity led to positive behavior modification regarding PA in this cohort of Chinese students. This is of particular importance that knowledge disimination and health education may be a useful approach for population-based physical activity promotion aiming at childhood obesity prevention in China.

Knowledge-based systems programming for knowledge intensive teaching

NARCIS (Netherlands)

Achten, H.H.; Dijkstra, J.; Oxman, R.M.; Colajanni, B.; Pellitteri, G.

1995-01-01

Typological design implies extensive knowledge of building types in order to design a building belonging to a building type. It facilitates the design process, which can be considered as a sequence of decisions. The paper gives an outline of a new approach in a course teaching typological knowledge

Knowledge-based systems programming for knowledge intensive teaching

NARCIS (Netherlands)

Achten, H.H.; Dijkstra, J.; Oxman, R.M.; Bax, M.F.T.

1994-01-01

Typological design implies extensive knowledge of building types in order to design a building belonging to a building type. It facilitates the design process, which can be considered as a sequence of decisions. The paper gives an outline of a new approach in a course teaching typological knowledge

The emerging knowledge governance approach : challenges and characteristics

OpenAIRE

Foss, Nicolai Juul

2006-01-01

The “knowledge governance approach” is characterized as a distinctive, emerging approach that cuts across the fields of knowledge management, organisation studies, strategy, and human resource management. Knowledge governance is taken up with how the deployment of governance mechanisms influences knowledge processes, such as sharing, retaining and creating knowledge. It insists on clear micro (behavioural) foundations, adopts an economizing perspective, and examines the links between knowledg...

Knowledge Management as an Approach to Learning and Instructing Sector University Students in Post-Soviet Professional Education

Science.gov (United States)

Volegzhanina, Irina S.; Chusovlyanova, Svetlana V.; Adolf, Vladimir A.; Bykadorova, Ekaterina S.; Belova, Elena N.

2017-01-01

The relevance of the study depends on addressing to the issue of knowledge management in learning and instructing students of post-Soviet sector universities. In this regard, the article is intended to reveal the nature of knowledge management approach compared to the knowledge-based one predominated in Soviet education. The flagship approach of…

Isotopic approach to the provenance study of artifacts

International Nuclear Information System (INIS)

Mabuchi, Hisao

1994-01-01

Isotopic abundance ratios, which are proved to be generally constant, are known to vary, for certain elements, from one place to another. Light elements, such as hydrogen, lithium, boron, carbon, nitrogen, oxygen and sulfur, show measurable variations of their isotope ratios due to isotopic fractionation which takes place during geochemical or biochemical processes. Isotope ratios of strontium and lead vary due to the decay of long-lived radioactive nuclides 87 Rb and 238 U- 235 U- 232 Th, respectively. Such isotopic anomalies can be applicable to provenance studies of archaeological objects. Thus, 13 C/ 12 C, 18 O/ 16 O, or 87 Sr/ 86 Sr were used to examine the authenticity of Greek marble statues. Also, lead isotope ratios have been used since mid-1960s extensively for provenance studies of glasses and bronzes of different civilizations. As an example, the author presents a series of his own works on lead isotope ratios applied to ancient Japanese bronzes, which are summarized as follows. 1) It was generally observed that lead isotope ratios reflect difference in culture to which bronzes belong. 2) Mirrors in the Western Han period (206 B.C. - A.D.8) are clearly distinguished by lead isotope ratios from those made after the mid-Eastern Han period (ca.A.D.150 - 300). 3) Korean mirrors and weapons excavated from the Yayoi sites contain lead of easily recognizable Mississippi Valley type. 4) Bronze objects made in Japan (imitative Han style mirrors, Dotaku, imitative weapons, arrowheads etc.) in the Yayoi and Kofun periods are classified by lead isotope ratios in the following order: the Korean mirror type to the Western Han mirror type in the Yayoi period and the mid- to post- Han mirror type in the Kofun period. 5) Indigenous Japanese lead seems to have been used after the mid-7th century. (J.P.N.)

Federated provenance of oceanographic research cruises: from metadata to data

Science.gov (United States)

Thomas, Rob; Leadbetter, Adam; Shepherd, Adam

2016-04-01

The World Wide Web Consortium's Provenance Data Model and associated Semantic Web ontology (PROV-O) have created much interest in the Earth and Space Science Informatics community (Ma et al., 2014). Indeed, PROV-O has recently been posited as an upper ontology for the alignment of various data models (Cox, 2015). Similarly, PROV-O has been used as the building blocks of a data release lifecycle ontology (Leadbetter & Buck, 2015). In this presentation we show that the alignment between different local data descriptions of an oceanographic research cruise can be achieved through alignment with PROV-O and that descriptions of the funding bodies, organisations and researchers involved in a cruise and its associated data release lifecycle can be modelled within a PROV-O based environment. We show that, at a first-order, this approach is scalable by presenting results from three endpoints (the Biological and Chemical Oceanography Data Management Office at Woods Hole Oceanographic Institution, USA; the British Oceanographic Data Centre at the National Oceanography Centre, UK; and the Marine Institute, Ireland). Current advances in ontology engineering, provide pathways to resolving reasoning issues from varying perspectives on implementing PROV-O. This includes the use of the Information Object design pattern where such edge cases as research cruise scheduling efforts are considered. PROV-O describes only things which have happened, but the Information Object design pattern allows for the description of planned research cruises through its statement that the local data description is not the the entity itself (in this case the planned research cruise) and therefore the local data description itself can be described using the PROV-O model. In particular, we present the use of the data lifecycle ontology to show the connection between research cruise activities and their associated datasets, and the publication of those data sets online with Digital Object Identifiers and

A collaborative knowledge management framework for supply chains: A UML-based model approach

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Jorge Esteban Hernández

2008-12-01

Full Text Available In the most general cases, collaborative activities imply a distributed decision-making process which involves several supply chain nodes. In this paper, by means of a literature review, and by also considering the deficiencies of existing proposals, a collaborative knowledge management UML-based framework supported is proposed. In addition, this proposal synthesizes existing knowledge, and it not only fulfils, but enriches, each component with the modeller’s own knowledge.

A Design Thinking Approach to Teaching Knowledge Management

Science.gov (United States)

Wang, Shouhong; Wang, Hai

2008-01-01

Pedagogies for knowledge management courses are still undeveloped. This Teaching Tip introduces a design thinking approach to teaching knowledge management. An induction model used to guide students' real-life projects for knowledge management is presented. (Contains 1 figure.)

A knowledge-based system for prototypical reasoning

Science.gov (United States)

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.

Painterly rendered portraits from photographs using a knowledge-based approach

Science.gov (United States)

DiPaola, Steve

2007-02-01

Portrait artists using oils, acrylics or pastels use a specific but open human vision methodology to create a painterly portrait of a live sitter. When they must use a photograph as source, artists augment their process, since photographs have: different focusing - everything is in focus or focused in vertical planes; value clumping - the camera darkens the shadows and lightens the bright areas; as well as color and perspective distortion. In general, artistic methodology attempts the following: from the photograph, the painting must 'simplify, compose and leave out what's irrelevant, emphasizing what's important'. While seemingly a qualitative goal, artists use known techniques such as relying on source tone over color to indirect into a semantic color temperature model, use brush and tonal "sharpness" to create a center of interest, lost and found edges to move the viewers gaze through the image towards the center of interest as well as other techniques to filter and emphasize. Our work attempts to create a knowledge domain of the portrait painter process and incorporate this knowledge into a multi-space parameterized system that can create an array of NPR painterly rendering output by analyzing the photographic-based input which informs the semantic knowledge rules.

Software Development for Auto-Generation of Interlocking Knowledge base using Artificial Intelligence Approach

Energy Technology Data Exchange (ETDEWEB)

Ko, Yun Seok [Nanseoul University (Korea); Kim, JOng Sun [Kwangwoon University (Korea)

1999-06-01

This paper proposes IIKBAG (Intelligent Interlocking Knowledge Base Generator) which can build automatically the interlocking knowledge base utilized as the real-time interlocking strategy of the electronic interlocking system in order to enhance it's reliability and expansion. The IIKBAG consists of the inference engine and the knowledge base. The former has an auto-learning function which searches all the train routes for the given station model based on heuristic search technique while dynamically searching the model, and then generates automatically the interlocking patterns obtained from the interlocking relations of signal facilities on the routes. The latter is designed as the structure which the real-time expert system embedded on IS (Interlocking System) can use directly in order to enhances the reliability and accuracy. The IIKBAG is implemented in C computer language for the purpose of the build and interface of the station structure database. And, a typical station model is simulated to prove the validity of the proposed IIKBAG. (author). 13 refs., 5 figs., 2 tabs.

Individual, social, and cultural approaches to knowledge sharing

Directory of Open Access Journals (Sweden)

Widen, Gunilla

2017-09-01

Full Text Available Workplace knowledge sharing is a complex process and there are a large number of studies in the area. In this article three theoretical approaches in library and information science are used to discuss knowledge sharing in the workplace. The approaches are information behavior, social capital, and information culture, and they bring important insights that need to be considered from a holistic management point of view when it comes to knowledge sharing. The individual's relation to different levels of context is important, meaning both in relation to work roles, work tasks, situations, organizational structures, and culture. The frameworks also shed light on where and how knowledge sharing activities are present in the organization. From a knowledge management point of view, it is important to acknowledge that when knowledge is valued, there is also an awareness of the knowledge sharing activities. Also, in addition to more traditional views of context, the frameworks bring forward different views on context, such as time and space as contextual factors.

Supporting the Knowledge-to-Action Process: A Systems-Thinking Approach

Science.gov (United States)

Cherney, Adrian; Head, Brian

2011-01-01

The processes for moving research-based knowledge to the domains of action in social policy and professional practice are complex. Several disciplinary research traditions have illuminated several key aspects of these processes. A more holistic approach, drawing on systems thinking, has also been outlined and advocated by recent contributors to…

Implementing knowledge into practice for improved neonatal survival; a cluster-randomised, community-based trial in Quang Ninh province, Vietnam

Directory of Open Access Journals (Sweden)

Huy Tran Q

2011-09-01

Full Text Available Abstract Background Globally, almost 4 million newborns die during the first 4 weeks of life every year. By increased use of evidence-based knowledge in the healthcare system a large proportion of these neonatal deaths could be prevented. But there is a severe lack of knowledge on effective methods for successful implementation of evidence into practice, particularly in low- and middle-income countries. Recent studies have demonstrated promising results with increased survival among both mothers and newborns using community-based approaches. In Vietnam evidence-based guidelines on reproductive health were launched in 2003 and revised in 2009. The overall objective of the current project is to evaluate if a facilitation intervention on the community level, with a problem-solving approach involving local representatives if the healthcare system and the community, results in improvements of neonatal health and survival. Methods/Design The study, which has been given the acronym NeoKIP (Neonatal Health - Knowledge Into Practice, took place in 8 districts composed by 90 communes in a province in northern Vietnam, where neonatal mortality rate was 24/1000 in 2005. A cluster randomised design was used, allocating clusters, as defined as a commune and its correponding Commune Health Center (CHC to either intervention or control arm. The facilitation intervention targeted staff at healthcare centres and key persons in the communes. The facilitator role was performed by lay women (Women's Union representatives using quality improvement techniques to initiate and sustain improvement processes targeting identified problem areas. The intervention has been running over 3 years and data were collected on the facilitation process, healthcare staff knowledge in neonatal care and their behaviour in clinical practice, and reproductive and perinatal health indicators. Primary outcome is neonatal mortality. Discussion The intervention is participatory and dynamic

Managing knowledge business intelligence: A cognitive analytic approach

Science.gov (United States)

Surbakti, Herison; Ta'a, Azman

2017-10-01

The purpose of this paper is to identify and analyze integration of Knowledge Management (KM) and Business Intelligence (BI) in order to achieve competitive edge in context of intellectual capital. Methodology includes review of literatures and analyzes the interviews data from managers in corporate sector and models established by different authors. BI technologies have strong association with process of KM for attaining competitive advantage. KM have strong influence from human and social factors and turn them to the most valuable assets with efficient system run under BI tactics and technologies. However, the term of predictive analytics is based on the field of BI. Extracting tacit knowledge is a big challenge to be used as a new source for BI to use in analyzing. The advanced approach of the analytic methods that address the diversity of data corpus - structured and unstructured - required a cognitive approach to provide estimative results and to yield actionable descriptive, predictive and prescriptive results. This is a big challenge nowadays, and this paper aims to elaborate detail in this initial work.

PAV ontology: provenance, authoring and versioning.

Science.gov (United States)

Ciccarese, Paolo; Soiland-Reyes, Stian; Belhajjame, Khalid; Gray, Alasdair Jg; Goble, Carole; Clark, Tim

2013-11-22

approaches, namely Provenance Vocabulary (PRV), DC Terms and BIBFRAME. We identify similarities and analyze differences between those vocabularies and PAV, outlining strengths and weaknesses of our proposed model. We specify SKOS mappings that align PAV with DC Terms. We conclude the paper with general remarks on the applicability of PAV.

Interaction Patterns in Web-based Knowledge Communities: Two-Mode Network Approach

NARCIS (Netherlands)

Vollenbroek, Wouter Bernardus; de Vries, Sjoerd A.; Fred, Ana; Dietz, Jan; Aveiro, David; Liu, Kecheng; Bernardino, Jorge; Filipe, Joaquim

2016-01-01

The importance of web-based knowledge communities (WKCs) in the 'network society' is growing. This trend is seen in many disciplines, like education, government, finance and other profit- and non-profit organisations. There is a need for understanding the development of these online communities in

Protocol for a systematic review of the use of narrative storytelling and visual-arts-based approaches as knowledge translation tools in healthcare

Science.gov (United States)

2013-01-01

Background The arts are powerful, accessible forms of communication that have the potential to impart knowledge by attracting interest and developing meaningful connections. Knowledge translation aims to reduce the ‘evidence-practice’ gap by developing, implementing and evaluating strategies designed to enhance awareness and promote behavior change congruent with research evidence. Increasingly, innovative approaches such as narrative storytelling and other arts-based interventions are being investigated to bridge the growing gap between practice and research. This study is the first to systematically identify and synthesize current research on narrative storytelling and visual art to translate and disseminate health research. Methods A health research librarian will develop and implement search strategies designed to identify relevant evidence. Studies will be included if they are primary research employing narrative storytelling and/or visual art as a knowledge translation strategy in healthcare. Two reviewers will independently perform study selection, quality assessment, and data extraction using standard forms. Disagreements will be resolved through discussion or third party adjudication. Data will be grouped and analyzed by research design, type of knowledge translation strategy (that is, a narrative or visual-arts-based approach), and target audience. An overall synthesis across all studies will be conducted. Discussion The findings from this research project will describe the ‘state of the science’ regarding the use of narrative storytelling and visual art as knowledge translation strategies. This systematic review will provide critical information for: (1) researchers conducting knowledge translation intervention studies; (2) nursing, medicine, and allied healthcare professionals; (3) healthcare consumers, including patients and families; and (4) decision makers and knowledge users who are charged to increase use of the latest research in

Protocol for a systematic review of the use of narrative storytelling and visual-arts-based approaches as knowledge translation tools in healthcare.

Science.gov (United States)

Scott, Shannon D; Brett-MacLean, Pamela; Archibald, Mandy; Hartling, Lisa

2013-03-20

The arts are powerful, accessible forms of communication that have the potential to impart knowledge by attracting interest and developing meaningful connections. Knowledge translation aims to reduce the 'evidence-practice' gap by developing, implementing and evaluating strategies designed to enhance awareness and promote behavior change congruent with research evidence. Increasingly, innovative approaches such as narrative storytelling and other arts-based interventions are being investigated to bridge the growing gap between practice and research. This study is the first to systematically identify and synthesize current research on narrative storytelling and visual art to translate and disseminate health research. A health research librarian will develop and implement search strategies designed to identify relevant evidence. Studies will be included if they are primary research employing narrative storytelling and/or visual art as a knowledge translation strategy in healthcare. Two reviewers will independently perform study selection, quality assessment, and data extraction using standard forms. Disagreements will be resolved through discussion or third party adjudication. Data will be grouped and analyzed by research design, type of knowledge translation strategy (that is, a narrative or visual-arts-based approach), and target audience. An overall synthesis across all studies will be conducted. The findings from this research project will describe the 'state of the science' regarding the use of narrative storytelling and visual art as knowledge translation strategies. This systematic review will provide critical information for: (1) researchers conducting knowledge translation intervention studies; (2) nursing, medicine, and allied healthcare professionals; (3) healthcare consumers, including patients and families; and (4) decision makers and knowledge users who are charged to increase use of the latest research in healthcare settings.

How structure shapes dynamics: knowledge development in Wikipedia--a network multilevel modeling approach.

Directory of Open Access Journals (Sweden)

Iassen Halatchliyski

Full Text Available Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base.

Self organising hypothesis networks: a new approach for representing and structuring SAR knowledge.

Science.gov (United States)

Hanser, Thierry; Barber, Chris; Rosser, Edward; Vessey, Jonathan D; Webb, Samuel J; Werner, Stéphane

2014-01-01

Combining different sources of knowledge to build improved structure activity relationship models is not easy owing to the variety of knowledge formats and the absence of a common framework to interoperate between learning techniques. Most of the current approaches address this problem by using consensus models that operate at the prediction level. We explore the possibility to directly combine these sources at the knowledge level, with the aim to harvest potentially increased synergy at an earlier stage. Our goal is to design a general methodology to facilitate knowledge discovery and produce accurate and interpretable models. To combine models at the knowledge level, we propose to decouple the learning phase from the knowledge application phase using a pivot representation (lingua franca) based on the concept of hypothesis. A hypothesis is a simple and interpretable knowledge unit. Regardless of its origin, knowledge is broken down into a collection of hypotheses. These hypotheses are subsequently organised into hierarchical network. This unification permits to combine different sources of knowledge into a common formalised framework. The approach allows us to create a synergistic system between different forms of knowledge and new algorithms can be applied to leverage this unified model. This first article focuses on the general principle of the Self Organising Hypothesis Network (SOHN) approach in the context of binary classification problems along with an illustrative application to the prediction of mutagenicity. It is possible to represent knowledge in the unified form of a hypothesis network allowing interpretable predictions with performances comparable to mainstream machine learning techniques. This new approach offers the potential to combine knowledge from different sources into a common framework in which high level reasoning and meta-learning can be applied; these latter perspectives will be explored in future work.

Knowledge Acquisition Using Linguistic-Based Knowledge Analysis

Science.gov (United States)

Daniel L. Schmoldt

1998-01-01

Most knowledge-based system developmentefforts include acquiring knowledge from one or more sources. difficulties associated with this knowledge acquisition task are readily acknowledged by most researchers. While a variety of knowledge acquisition methods have been reported, little has been done to organize those different methods and to suggest how to apply them...

ProvenCare-Psoriasis: A disease management model to optimize care.

Science.gov (United States)

Gionfriddo, Michael R; Pulk, Rebecca A; Sahni, Dev R; Vijayanagar, Sonal G; Chronowski, Joseph J; Jones, Laney K; Evans, Michael A; Feldman, Steven R; Pride, Howard

2018-03-15

There are a variety of evidence-based treatments available for psoriasis. The transition of this evidence into practice is challenging. In this article, we describe the design of our disease management approach for Psoriasis (ProvenCare®) and present preliminary evidence of the effect of its implementation. In designing our approach, we identified three barriers to optimal care: 1) lack of a standardized and discrete disease activity measure within the electronic health record, 2) lack of a system-wide, standardized approach to care, and 3) non-uniform financial access to appropriate non-pharmacologic treatments. We implemented several solutions, which collectively form our approach. We standardized the documentation of clinical data such as body surface area (BSA), created a disease management algorithm for psoriasis, and aligned incentives to facilitate the implementation of the algorithm. This approach provides more coordinated, cost effective care for psoriasis, while being acceptable to key stakeholders. Future work will examine the effect of the implementation of our approach on important clinical and patient outcomes.

Nonlinear Knowledge in Kernel-Based Multiple Criteria Programming Classifier

Science.gov (United States)

Zhang, Dongling; Tian, Yingjie; Shi, Yong

Kernel-based Multiple Criteria Linear Programming (KMCLP) model is used as classification methods, which can learn from training examples. Whereas, in traditional machine learning area, data sets are classified only by prior knowledge. Some works combine the above two classification principle to overcome the defaults of each approach. In this paper, we propose a model to incorporate the nonlinear knowledge into KMCLP in order to solve the problem when input consists of not only training example, but also nonlinear prior knowledge. In dealing with real world case breast cancer diagnosis, the model shows its better performance than the model solely based on training data.

SEIS-PROV: Practical Provenance for Seismological Data

Science.gov (United States)

Krischer, L.; Smith, J. A.; Tromp, J.

2015-12-01

It is widely recognized that reproducibility is crucial to advance science, but at the same time it is very hard to actually achieve. This results in it being recognized but also mostly ignored by a large fraction of the community. A key ingredient towards full reproducibility is to capture and describe the history of data, an issue known as provenance. We present SEIS-PROV, a practical format and data model to store provenance information for seismological data. In a seismological context, provenance can be seen as information about the processes that generated and modified a particular piece of data. For synthetic waveforms the provenance information describes which solver and settings therein were used to generate it. When looking at processed seismograms, the provenance conveys information about the different time series analysis steps that led to it. Additional uses include the description of derived data types, such as cross-correlations and adjoint sources, enabling their proper storage and exchange. SEIS-PROV is based on W3C PROV (http://www.w3.org/TR/prov-overview/), a standard for generic provenance information. It then applies an additional set of constraints to make it suitable for seismology. We present a definition of the SEIS-PROV format, a way to check if any given file is a valid SEIS-PROV document, and two sample implementations: One in SPECFEM3D GLOBE (https://geodynamics.org/cig/software/specfem3d_globe/) to store the provenance information of synthetic seismograms and another one as part of the ObsPy (http://obspy.org) framework enabling automatic tracking of provenance information during a series of analysis and transformation stages. This, along with tools to visualize and interpret provenance graphs, offers a description of data history that can be readily tracked, stored, and exchanged.

Variational segmentation problems using prior knowledge in imaging and vision

DEFF Research Database (Denmark)

Fundana, Ketut

This dissertation addresses variational formulation of segmentation problems using prior knowledge. Variational models are among the most successful approaches for solving many Computer Vision and Image Processing problems. The models aim at finding the solution to a given energy functional defined......, prior knowledge is needed to obtain the desired solution. The introduction of shape priors in particular, has proven to be an effective way to segment objects of interests. Firstly, we propose a prior-based variational segmentation model to segment objects of interest in image sequences, that can deal....... Many objects have high variability in shape and orientation. This often leads to unsatisfactory results, when using a segmentation model with single shape template. One way to solve this is by using more sophisticated shape models. We propose to incorporate shape priors from a shape sub...

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

International Nuclear Information System (INIS)

Morman, J.A.; Reifman, J.; Vitela, J.E.; Wei, T.Y.C.; Applequist, C.A.; Hippely, P.; Kuk, W.; Tsoukalas, L.H.

1998-01-01

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

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

International Nuclear Information System (INIS)

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

1997-01-01

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

One knowledge base or many knowledge pools?

DEFF Research Database (Denmark)

Lundvall, Bengt-Åke

It is increasingly realized that knowledge is the most important resource and that learning is the most important process in the economy. Sometimes this is expressed by coining the current era as characterised by a ‘knowledge based economy'. But this concept might be misleading by indicating...... that there is one common knowledge base on which economic activities can be built. In this paper we argue that it is more appropriate to see the economy as connecting to different ‘pools of knowledge'. The argument is built upon a conceptual framework where we make distinctions between private/public, local....../global, individual/collective and tacit/codified knowledge. The purpose is both ‘academic' and practical. Our analysis demonstrates the limits of a narrowly economic perspective on knowledge and we show that these distinctions have important implications both for innovation policy and for management of innovation....

Visualisation methods for large provenance collections in data-intensive collaborative platforms

Science.gov (United States)

Spinuso, Alessandro; Fligueira, Rosa; Atkinson, Malcolm; Gemuend, Andre

2016-04-01

This work investigates improving the methods of visually representing provenance information in the context of modern data-driven scientific research. It explores scenarios where data-intensive workflows systems are serving communities of researchers within collaborative environments, supporting the sharing of data and methods, and offering a variety of computation facilities, including HPC, HTC and Cloud. It focuses on the exploration of big-data visualization techniques aiming at producing comprehensive and interactive views on top of large and heterogeneous provenance data. The same approach is applicable to control-flow and data-flow workflows or to combinations of the two. This flexibility is achieved using the W3C-PROV recommendation as a reference model, especially its workflow oriented profiles such as D-PROV (Messier et al. 2013). Our implementation is based on the provenance records produced by the dispel4py data-intensive processing library (Filgueira et al. 2015). dispel4py is an open-source Python framework for describing abstract stream-based workflows for distributed data-intensive applications, developed during the VERCE project. dispel4py enables scientists to develop their scientific methods and applications on their laptop and then run them at scale on a wide range of e-Infrastructures (Cloud, Cluster, etc.) without making changes. Users can therefore focus on designing their workflows at an abstract level, describing actions, input and output streams, and how they are connected. The dispel4py system then maps these descriptions to the enactment platforms, such as MPI, Storm, multiprocessing. It provides a mechanism which allows users to determine the provenance information to be collected and to analyze it at runtime. For this work we consider alternative visualisation methods for provenance data, from infinite lists and localised interactive graphs, to radial-views. The latter technique has been positively explored in many fields, from text

ProvenCare perinatal: a model for delivering evidence/ guideline-based care for perinatal populations.

Science.gov (United States)

Berry, Scott A; Laam, Leslie A; Wary, Andrea A; Mateer, Harry O; Cassagnol, Hans P; McKinley, Karen E; Nolan, Ruth A

2011-05-01

Geisinger Health System (GHS) has applied its ProvenCare model to demonstrate that a large integrated health care delivery system, enabled by an electronic health record (EHR), could reengineer a complicated clinical process, reduce unwarranted variation, and provide evidence-based care for patients with a specified clinical condition. In 2007 GHS began to apply the model to a more complicated, longer-term condition of "wellness"--perinatal care. ADAPTING PROVENCARE TO PERINATAL CARE: The ProvenCare Perinatal initiative was more complex than the five previous ProvenCare endeavors in terms of breadth, scope, and duration. Each of the 22 sites created a process flow map to depict the current, real-time process at each location. The local practice site providers-physicians and mid-level practitioners-reached consensus on 103 unique best practice measures (BPMs), which would be tracked for every patient. These maps were then used to create a single standardized pathway that included the BPMs but also preserved some unique care offerings that reflected the needs of the local context. A nine-phase methodology, expanded from the previous six-phase model, was implemented on schedule. Pre- to postimplementation improvement occurred for all seven BPMs or BPM bundles that were considered the most clinically relevant, with five statistically significant. In addition, the rate of primary cesarean sections decreased by 32%, and birth trauma remained unchanged as the number of vaginal births increased. Preliminary experience suggests that integrating evidence/guideline-based best practices into work flows in inpatient and outpatient settings can achieve improvements in daily patient care processes and outcomes.

A Provenance-Based Infrastructure to Support the Life Cycle of Executable Papers

DEFF Research Database (Denmark)

2011-01-01

As publishers establish a greater online presence as well as infrastructure to support the distribution of more varied information, the idea of an executable paper that enables greater interaction has developed. An executable paper provides more information for computational experiments and results...... than the text, tables, and figures of standard papers. Executable papers can bundle computational content that allow readers and reviewers to interact, validate, and explore experiments. By including such content, authors facilitate future discoveries by lowering the barrier to reproducing...... and extending results. We present an infrastructure for creating, disseminating, and maintaining executable papers. Our approach is rooted in provenance, the documentation of exactly how data, experiments, and results were generated. We seek to improve the experience for everyone involved in the life cycle...

Knowledge representation and knowledge base design for operator advisor system

International Nuclear Information System (INIS)

Hangos, K.M.; Sziano, T.; Tapolcai, L.

1990-01-01

The problems of knowledge representation, knowledge base handling and design has been described for an Operator Advisor System in the Paks Nuclear Power Plant. The Operator Advisor System is to be implemented as a part of the 5th and 6th unit. The knowledge of the Operator Advisor system is described by a few elementary knowledge items (diagnostic event functions, fault graph, action trees), weighted directed graphs have been found as their common structure. List-type and relational representation of these graphs have been used for the on-line and off-line part of the knowledge base respectively. A uniform data base design and handling has been proposed which consists of a design system, a knowledge base editor and a knowledge base compiler

Knowledge-Based Reinforcement Learning for Data Mining

Science.gov (United States)

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

A history-tracing XML-based provenance framework for workflows

NARCIS (Netherlands)

Gerhards, M; Belloum, A.; Berretz, F.; Sander, V.; Skorupa, S.

2010-01-01

The importance of validating and reproducing the outcome of computational processes is fundamental to many application domains. Assuring the provenance of workflows will likely become even more important with respect to the incorporation of human tasks to standard workflows by emerging standards

ProvenCare: Geisinger's Model for Care Transformation through Innovative Clinical Initiatives and Value Creation.

Science.gov (United States)

2009-04-01

Geisinger's system of care can be seen as a microcosm of the national delivery of healthcare, with implications for decision makers in other health plans. In this interview, Dr Ronald A. Paulus focuses on Geisinger's unique approach to patient care. In its core, this approach represents a system of quality and value initiatives based on 3 major programs-Proven Health Navigation (medical home); the ProvenCare model; and transitions of care. The goal of such an approach is to optimize disease management by using a rational reimbursement paradigm for appropriate interventions, providing innovative incentives, and engaging patients in their own care as part of any intervention. Dr Paulus explains the reasons why, unlike Geisinger, other stakeholders, including payers, providers, patients, and employers, have no intrinsic reasons to be concerned with quality and value initiatives. In addition, he says, an electronic infrastructure that could be modified as management paradigms evolve is a necessary tool to ensure the healthcare delivery system's ability to adapt to new clinical realities quickly to ensure the continuation of delivering best value for all stakeholders.

Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy.

Science.gov (United States)

Katić, Darko; Schuck, Jürgen; Wekerle, Anna-Laura; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

2016-06-01

Computer assistance is increasingly common in surgery. However, the amount of information is bound to overload processing abilities of surgeons. We propose methods to recognize the current phase of a surgery for context-aware information filtering. The purpose is to select the most suitable subset of information for surgical situations which require special assistance. We combine formal knowledge, represented by an ontology, and experience-based knowledge, represented by training samples, to recognize phases. For this purpose, we have developed two different methods. Firstly, we use formal knowledge about possible phase transitions to create a composition of random forests. Secondly, we propose a method based on cultural optimization to infer formal rules from experience to recognize phases. The proposed methods are compared with a purely formal knowledge-based approach using rules and a purely experience-based one using regular random forests. The comparative evaluation on laparoscopic pancreas resections and adrenalectomies employs a consistent set of quality criteria on clean and noisy input. The rule-based approaches proved best with noisefree data. The random forest-based ones were more robust in the presence of noise. Formal and experience-based knowledge can be successfully combined for robust phase recognition.

Course Ontology-Based User's Knowledge Requirement Acquisition from Behaviors within E-Learning Systems

Science.gov (United States)

Zeng, Qingtian; Zhao, Zhongying; Liang, Yongquan

2009-01-01

User's knowledge requirement acquisition and analysis are very important for a personalized or user-adaptive learning system. Two approaches to capture user's knowledge requirement about course content within an e-learning system are proposed and implemented in this paper. The first approach is based on the historical data accumulated by an…

Reconstructing Sessions from Data Discovery and Access Logs to Build a Semantic Knowledge Base for Improving Data Discovery

Directory of Open Access Journals (Sweden)

Yongyao Jiang

2016-04-01

Full Text Available Big geospatial data are archived and made available through online web discovery and access. However, finding the right data for scientific research and application development is still a challenge. This paper aims to improve the data discovery by mining the user knowledge from log files. Specifically, user web session reconstruction is focused upon in this paper as a critical step for extracting usage patterns. However, reconstructing user sessions from raw web logs has always been difficult, as a session identifier tends to be missing in most data portals. To address this problem, we propose two session identification methods, including time-clustering-based and time-referrer-based methods. We also present the workflow of session reconstruction and discuss the approach of selecting appropriate thresholds for relevant steps in the workflow. The proposed session identification methods and workflow are proven to be able to extract data access patterns for further pattern analyses of user behavior and improvement of data discovery for more relevancy data ranking, suggestion, and navigation.

An approach to development of ontological knowledge base in the field of scientific and research activity in Russia

Science.gov (United States)

Murtazina, M. Sh; Avdeenko, T. V.

2018-05-01

The state of art and the progress in application of semantic technologies in the field of scientific and research activity have been analyzed. Even elementary empirical comparison has shown that the semantic search engines are superior in all respects to conventional search technologies. However, semantic information technologies are insufficiently used in the field of scientific and research activity in Russia. In present paper an approach to construction of ontological model of knowledge base is proposed. The ontological model is based on the upper-level ontology and the RDF mechanism for linking several domain ontologies. The ontological model is implemented in the Protégé environment.

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

Science.gov (United States)

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.

An Adaptable System to Support Provenance Management for the Public Policy-Making Process in Smart Cities

Directory of Open Access Journals (Sweden)

Barkha Javed

2018-01-01

Full Text Available Government policies aim to address public issues and problems and therefore play a pivotal role in people’s lives. The creation of public policies, however, is complex given the perspective of large and diverse stakeholders’ involvement, considerable human participation, lengthy processes, complex task specification and the non-deterministic nature of the process. The inherent complexities of the policy process impart challenges for designing a computing system that assists in supporting and automating the business process pertaining to policy setup, which also raises concerns for setting up a tracking service in the policy-making environment. A tracking service informs how decisions have been taken during policy creation and can provide useful and intrinsic information regarding the policy process. At present, there exists no computing system that assists in tracking the complete process that has been employed for policy creation. To design such a system, it is important to consider the policy environment challenges; for this a novel network and goal based approach has been framed and is covered in detail in this paper. Furthermore, smart governance objectives that include stakeholders’ participation and citizens’ involvement have been considered. Thus, the proposed approach has been devised by considering smart governance principles and the knowledge environment of policy making where tasks are largely dependent on policy makers’ decisions and on individual policy objectives. Our approach reckons the human dimension for deciding and defining autonomous process activities at run time. Furthermore, with the network-based approach, so-called provenance data tracking is employed which enables the capture of policy process.

Data Mining and Knowledge Discovery via Logic-Based Methods

CERN Document Server

Triantaphyllou, Evangelos

2010-01-01

There are many approaches to data mining and knowledge discovery (DM&KD), including neural networks, closest neighbor methods, and various statistical methods. This monograph, however, focuses on the development and use of a novel approach, based on mathematical logic, that the author and his research associates have worked on over the last 20 years. The methods presented in the book deal with key DM&KD issues in an intuitive manner and in a natural sequence. Compared to other DM&KD methods, those based on mathematical logic offer a direct and often intuitive approach for extracting easily int

Integration of evidence-based knowledge management in microsystems: a tele-ICU experience.

Science.gov (United States)

Rincon, Teresa A

2012-01-01

The Institute of Medicine's proposed 6 aims to improve health care are timely, safe, effective, efficient, equitable, and patient-centered care. Unfortunately, it also asserts that improvements in these 6 dimensions cannot be achieved within the existing framework of care systems. These systems are based on unrealistic expectations on human cognition and vigilance, and demonstrate a lack of dependence on computerized systems to support care processes and put information at the point of use. Knowledge-based care and evidence-based clinical decision-making need to replace the unscientific care that is being delivered in health care. Building care practices on evidence within an information technology platform is needed to support sound clinical decision-making and to influence organizational adoption of evidence-based practice in health care. Despite medical advances and evidence-based recommendations for treatment of severe sepsis, it remains a significant cause of mortality and morbidity in the world. It is a complex disease state that has proven difficult to define, diagnose, and treat. Supporting bedside teams with real-time knowledge and expertise to target early identification of severe sepsis and compliance to Surviving Sepsis Campaign, evidence-based practice bundles are important to improving outcomes. Using a centralized, remote team of expert nurses and an open-source software application to advance clinical decision-making and execution of the severe sepsis bundle will be examined.

Knowledge-based Telecom Industry

OpenAIRE

Vinje, Villeman; Nordkvelde, Marius

2011-01-01

BI Norwegian School of Management is conducting a national research project entitled “A knowledge-based Norway”. Thirteen major knowledge-based industries in Norway are being analyzed under the auspices of the project. This study assesses the underlying properties of a global knowledge hub to examine the extent to which the Norwegian telecom industry – which encompasses all telecom firms located in Norway regardless of ownership – constitutes a global knowledge hub. It commences with a ge...

Logical provenance in data-oriented workflows?

KAUST Repository

Ikeda, R.

2013-04-01

We consider the problem of defining, generating, and tracing provenance in data-oriented workflows, in which input data sets are processed by a graph of transformations to produce output results. We first give a new general definition of provenance for general transformations, introducing the notions of correctness, precision, and minimality. We then determine when properties such as correctness and minimality carry over from the individual transformations\\' provenance to the workflow provenance. We describe a simple logical-provenance specification language consisting of attribute mappings and filters. We provide an algorithm for provenance tracing in workflows where logical provenance for each transformation is specified using our language. We consider logical provenance in the relational setting, observing that for a class of Select-Project-Join (SPJ) transformations, logical provenance specifications encode minimal provenance. We have built a prototype system supporting the features and algorithms presented in the paper, and we report a few preliminary experimental results. © 2013 IEEE.

Special Section: The third provenance challenge on using the open provenance model for interoperability

NARCIS (Netherlands)

Simmhan, Y; Groth, P.T.; Moreau, L

2011-01-01

The third provenance challenge was organized to evaluate the efficacy of the Open Provenance Model (OPM) in representing and sharing provenance with the goal of improving the specification. A data loading scientific workflow that ingests data files into a relational database for the Pan-STARRS sky

LabelFlow Framework for Annotating Workflow Provenance

Directory of Open Access Journals (Sweden)

Pinar Alper

2018-02-01

Full Text Available Scientists routinely analyse and share data for others to use. Successful data (reuse relies on having metadata describing the context of analysis of data. In many disciplines the creation of contextual metadata is referred to as reporting. One method of implementing analyses is with workflows. A stand-out feature of workflows is their ability to record provenance from executions. Provenance is useful when analyses are executed with changing parameters (changing contexts and results need to be traced to respective parameters. In this paper we investigate whether provenance can be exploited to support reporting. Specifically; we outline a case-study based on a real-world workflow and set of reporting queries. We observe that provenance, as collected from workflow executions, is of limited use for reporting, as it supports queries partially. We identify that this is due to the generic nature of provenance, its lack of domain-specific contextual metadata. We observe that the required information is available in implicit form, embedded in data. We describe LabelFlow, a framework comprised of four Labelling Operators for decorating provenance with domain-specific Labels. LabelFlow can be instantiated for a domain by plugging it with domain-specific metadata extractors. We provide a tool that takes as input a workflow, and produces as output a Labelling Pipeline for that workflow, comprised of Labelling Operators. We revisit the case-study and show how Labels provide a more complete implementation of reporting queries.

Citation analysis: A social and dynamic approach to knowledge organization

DEFF Research Database (Denmark)

Hjørland, Birger

2013-01-01

Knowledge organization (KO) and bibliometrics have traditionally been seen as separate subfields of library and information science, but bibliometric techniques make it possible to identify candidate terms for thesauri and to organize knowledge by relating scientific papers and authors to each...... be considered superior for all purposes. The main difference between traditional knowledge organization systems (KOSs) and maps based on citation analysis is that the first group represents intellectual KOSs, whereas the second represents social KOSs. For this reason bibliometric maps cannot be expected ever...... other and thereby indicating kinds of relatedness and semantic distance. It is therefore important to view bibliometric techniques as a family of approaches to KO in order to illustrate their relative strengths and weaknesses. The subfield of bibliometrics concerned with citation analysis forms...

The management of nuclear knowledge and expertise for sustainable development

International Nuclear Information System (INIS)

Stumpf, W.

2004-01-01

Knowledge is the key resource of most organisations in today's world. To manage it effectively requires the concept of organisational knowledge rather than simply knowledge that is centered in individuals. This needs to be addressed through the concept of an 'organisational core competency' that has proven itself within many organisations. Hard knowledge can be captured easily but not the nebulous 'tacit learning' that is embodied in the life-long experience of employees. Some of the more recent methods to capture the tacit learning within organisations are explored. Since the middle 1990s, the International Atomic Energy Agency has redirected its technical co-operation (TC) programme towards a focused 'needs driven' approach away from the former 'technologically driven' approach. From a 'before' and 'after' comparison, it is concluded that the new strategy is better placed to manage the preservation of the nuclear knowledge and to ensure the sustainability of these projects. (author)

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

Science.gov (United States)

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.

Sphinx: merging knowledge-based and ab initio approaches to improve protein loop prediction.

Science.gov (United States)

Marks, Claire; Nowak, Jaroslaw; Klostermann, Stefan; Georges, Guy; Dunbar, James; Shi, Jiye; Kelm, Sebastian; Deane, Charlotte M

2017-05-01

Loops are often vital for protein function, however, their irregular structures make them difficult to model accurately. Current loop modelling algorithms can mostly be divided into two categories: knowledge-based, where databases of fragments are searched to find suitable conformations and ab initio, where conformations are generated computationally. Existing knowledge-based methods only use fragments that are the same length as the target, even though loops of slightly different lengths may adopt similar conformations. Here, we present a novel method, Sphinx, which combines ab initio techniques with the potential extra structural information contained within loops of a different length to improve structure prediction. We show that Sphinx is able to generate high-accuracy predictions and decoy sets enriched with near-native loop conformations, performing better than the ab initio algorithm on which it is based. In addition, it is able to provide predictions for every target, unlike some knowledge-based methods. Sphinx can be used successfully for the difficult problem of antibody H3 prediction, outperforming RosettaAntibody, one of the leading H3-specific ab initio methods, both in accuracy and speed. Sphinx is available at http://opig.stats.ox.ac.uk/webapps/sphinx. deane@stats.ox.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Approaches to Maintaining and Building Organisational Knowledge

International Nuclear Information System (INIS)

Juurmaa, Tellervo

2014-01-01

Conclusions: • Involvement of people is one of the most important enablers of successful KM; • KM focuses on organisational knowledge that is needed for achieving business goals; • Working culture and KM activities embedded in the ways of working are essential for management of organisational knowledge; • Formal KM approach is needed as well, and one of its objectives is to support informal KM activities; • For a successful management of organisational knowledge, KM related functions need to be identified and understood as one entity

Evaluation of Community Health Education Workshops among Chinese Older Adults in Chicago: A Community-Based Participatory Research Approach

Science.gov (United States)

Dong, Xinqi; Li, Yawen; Chen, Ruijia; Chang, E-Shien; Simon, Melissa

2013-01-01

Background: Health education is one of the proven ways to improve knowledge and change health attitudes and behaviors. This study is intended to assess the effectiveness of five health workshops in a Chinese community, focusing on depression, elder abuse, nutrition, breast cancer and stroke. Methods: A community-based participatory research…

Analysis of a Knowledge-Management-Based Process of Transferring Project Management Skills

Science.gov (United States)

Ioi, Toshihiro; Ono, Masakazu; Ishii, Kota; Kato, Kazuhiko

2012-01-01

Purpose: The purpose of this paper is to propose a method for the transfer of knowledge and skills in project management (PM) based on techniques in knowledge management (KM). Design/methodology/approach: The literature contains studies on methods to extract experiential knowledge in PM, but few studies exist that focus on methods to convert…

S-ProvFlow: provenance model and tools for scalable and adaptive analysis pipelines in geoscience.

Science.gov (United States)

Spinuso, A.; Mihajlovski, A.; Atkinson, M.; Filgueira, R.; Klampanos, I.; Sanchez, S.

2017-12-01

The reproducibility of scientific findings is essential to improve the quality and application of modern data-driven research. Delivering such reproducibility is challenging in the context of systems handling large data-streams with sophisticated computational methods. Similarly, the SKA (Square Kilometer Array) will collect an unprecedented volume of radio-wave signals that will have to be reduced and transformed into derived products, with impact on space-weather research. This highlights the importance of having cross-disciplines mechanisms at the producer's side that rely on usable lineage data to support validation and traceability of the new artifacts. To be informative, provenance has to describe each methods' abstractions and their implementation as mappings onto distributed platforms and their concurrent execution, capturing relevant internal dependencies at runtime. Producers and intelligent toolsets should be able to exploit the produced provenance, steering real-time monitoring activities and inferring adaptations of methods at runtime.We present a model of provenance (S-PROV) that extends W3C PROV and ProvONE, broadening coverage of provenance to aspects related to distribution, scale-up and steering of stateful streaming operators in analytic pipelines. This is supported by a technical framework for tuneable and actionable lineage, ensuring its relevance to the users' interests, fostering its rapid exploitation to facilitate research practices. By applying concepts such as provenance typing and profiling, users define rules to capture common provenance patterns and activate selective controls based on domain-metadata. The traces are recorded in a document-store with index optimisation and a web API serves advanced interactive tools (S-ProvFlow, https://github.com/KNMI/s-provenance). These allow different classes of consumers to rapidly explore the provenance data. The system, which contributes to the SKA-Link initiative, within technology and

Systematic reviews and knowledge translation.

Science.gov (United States)

Tugwell, Peter; Robinson, Vivian; Grimshaw, Jeremy; Santesso, Nancy

2006-08-01

Proven effective interventions exist that would enable all countries to meet the Millennium Development Goals. However, uptake and use of these interventions in the poorest populations is at least 50% less than in the richest populations within each country. Also, we have recently shown that community effectiveness of interventions is lower for the poorest populations due to a "staircase" effect of lower coverage/access, worse diagnostic accuracy, less provider compliance and less consumer adherence. We propose an evidence-based framework for equity-oriented knowledge translation to enhance community effectiveness and health equity. This framework is represented as a cascade of steps to assess and prioritize barriers and thus choose effective knowledge translation interventions that are tailored for relevant audiences (public, patient, practitioner, policy-maker, press and private sector), as well as the evaluation, monitoring and sharing of these strategies. We have used two examples of effective interventions (insecticide-treated bednets to prevent malaria and childhood immunization) to illustrate how this framework can provide a systematic method for decision-makers to ensure the application of evidence-based knowledge in disadvantaged populations. Future work to empirically validate and evaluate the usefulness of this framework is needed. We invite researchers and implementers to use the cascade for equity-oriented knowledge translation as a guide when planning implementation strategies for proven effective interventions. We also encourage policy-makers and health-care managers to use this framework when deciding how effective interventions can be implemented in their own settings.

A knowledge base architecture for distributed knowledge agents

Science.gov (United States)

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.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

Science.gov (United States)

Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally

2017-10-02

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

Science.gov (United States)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

Knowledge types: a practical approach to guide knowledge engineering in domains of building design

DEFF Research Database (Denmark)

Andersen, Tom

1996-01-01

The article discuss different viiws on classifying knowledge. It provides a guidance to knowledge acquistion based on a specific classification scheme.......The article discuss different viiws on classifying knowledge. It provides a guidance to knowledge acquistion based on a specific classification scheme....

An Ebola virus-centered knowledge base

Science.gov (United States)

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

An Ebola virus-centered knowledge base.

Science.gov (United States)

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. © The Author(s) 2015. Published by Oxford University Press.

Logically automorphically equivalent knowledge bases

OpenAIRE

Aladova, Elena; Plotkin, Tatjana

2017-01-01

Knowledge bases theory provide an important example of the field where applications of universal algebra and algebraic logic look very natural, and their interaction with practical problems arising in computer science might be very productive. In this paper we study the equivalence problem for knowledge bases. Our interest is to find out how the informational equivalence is related to the logical description of knowledge. Studying various equivalences of knowledge bases allows us to compare d...

Querying Provenance Information: Basic Notions and an Example from Paleoclimate Reconstruction

Science.gov (United States)

Stodden, V.; Ludaescher, B.; Bocinsky, K.; Kintigh, K.; Kohler, T.; McPhillips, T.; Rush, J.

2016-12-01

Computational models are used to reconstruct and explain past environments and to predict likely future environments. For example, Bocinsky and Kohler have performed a 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest. The resulting academic publications not only contain traditional method descriptions, figures, etc. but also links to code and data for basic transparency and reproducibility. Examples include ResearchCompendia.org and the new project "Merging Science and Cyberinfrastructure Pathways: The Whole Tale." Provenance information provides a further critical element to understand a published study and to possibly extend or challenge the findings of the original authors. We present different notions and uses of provenance information using a computational archaeology example, e.g., the common use of "provenance for others" (for transparency and reproducibility), but also the more elusive but equally important use of "provenance for self". To this end, we distinguish prospective provenance (a.k.a. workflow) from retrospective provenance (a.k.a. data lineage) and show how combinations of both forms of provenance can be used to answer different kinds of important questions about a workflow and its execution. Since many workflows are developed using scripting or special purpose languages such as Python and R, we employ an approach and toolkit called YesWorkflow that brings provenance modeling, capture, and querying into the realm of scripting. YesWorkflow employs the basic W3C PROV standard, as well as the ProvONE extension for sharing and exchanging retrospective and prospective provenance information, respectively. Finally, we argue that the utility of provenance information should be maximized by developing different kinds provenance questions and queries during the early phases of computational workflow design and implementation.

Knowledge brokering for healthy aging: a scoping review of potential approaches.

Science.gov (United States)

Van Eerd, Dwayne; Newman, Kristine; DeForge, Ryan; Urquhart, Robin; Cornelissen, Evelyn; Dainty, Katie N

2016-10-19

Developing a healthcare delivery system that is more responsive to the future challenges of an aging population is a priority in Canada. The World Health Organization acknowledges the need for knowledge translation frameworks in aging and health. Knowledge brokering (KB) is a specific knowledge translation approach that includes making connections between people to facilitate the use of evidence. Knowledge gaps exist about KB roles, approaches, and guiding frameworks. The objective of the scoping review is to identify and describe KB approaches and the underlying conceptual frameworks (models, theories) used to guide the approaches that could support healthy aging. Literature searches were done in PubMed, EMBASE, PsycINFO, EBM reviews (Cochrane Database of systematic reviews), CINAHL, and SCOPUS, as well as Google and Google Scholar using terms related to knowledge brokering. Titles, abstracts, and full reports were reviewed independently by two reviewers who came to consensus on all screening criteria. Documents were included if they described a KB approach and details about the underlying conceptual basis. Data about KB approach, target stakeholders, KB outcomes, and context were extracted independently by two reviewers. Searches identified 248 unique references. Screening for inclusion revealed 19 documents that described 15 accounts of knowledge brokering and details about conceptual guidance and could be applied in healthy aging contexts. Eight KB elements were detected in the approaches though not all approaches incorporated all elements. The underlying conceptual guidance for KB approaches varied. Specific KB frameworks were referenced or developed for nine KB approaches while the remaining six cited more general KT frameworks (or multiple frameworks) as guidance. The KB approaches that we found varied greatly depending on the context and stakeholders involved. Three of the approaches were explicitly employed in the context of health aging. Common elements

Dacfood: a knowledge-based system for decision support in case of radiological contamination of foodstuffs

International Nuclear Information System (INIS)

Diaz, A.; Despres, A.; Soulatges, D.

1991-01-01

In case of radiological contamination of foodstuffs, the introduction of a countermeasure has to be justified by balancing its advantages and drawbacks, as recommended by ICRP. Also, to provide authorities with information about the decision context, it has been decided to develop a Decision Support System (DSS). A knowledge-based approach is used for the DSS. Indeed, it allows: . better modelling thanks to, for instance, object oriented programming and rules, . ability to introduce more knowledge thanks to an easier consistency and validity control of the knowledge base, . handling of uncertainties (incomplete, uncertain or evolving knowledge). The present state of the system is presented. DACFOOD is a decision aiding system for contamined foodstuffs, based on a knowledge-based approach. A demonstration model has been developed in a post-Chernobyl CEC research program. It evaluates the sanitary situation, the alternative actions through costs and sanitary effects, and gives information on the decisional background

File Level Provenance Tracking in CMS

CERN Document Server

Jones, C D; Paterno, M; Sexton-Kennedy, L; Tanenbaum, W; Riley, D S

2009-01-01

The CMS off-line framework stores provenance information within CMS's standard ROOT event data files. The provenance information is used to track how each data product was constructed, including what other data products were read to do the construction. We will present how the framework gathers the provenance information, the efforts necessary to minimise the space used to store the provenance in the file and the tools that will be available to use the provenance.

A Model of an Expanded-Frame Hypermedia Knowledge-Base for Instruction.

Science.gov (United States)

Lacy, Mark J.; Wood, R. Kent

1993-01-01

Argues that current computer-based instruction does not exploit the instructional possibilities of computers. Critiques current models of computer-based instruction: behaviorist as too linear and constructivist as too unstructured. Offers a design model of Expanded-frame Hypermedia Knowledge-bases as an instructional approach allowing hypermedia…

A Structured Review and Classification of Demolding Issues and Proven Solutions

DEFF Research Database (Denmark)

Delaney, K. D.; Bissacco, G.; Kennedy, D.

2012-01-01

The demolding of replicated parts can result in damage to both the replication tooling and finished parts and is a particular problem for the replication of smaller parts which can be quite fragile. Various techniques have been proposed in the literature to solve such problems by reducing....... Such a rationalization of existing knowledge will enable replication tool developers to systematically select and apply proven solutions to solve, and ultimately prevent, demolding problems....... the overall demolding force. This paper presents the challenge of demolding replicated parts and reviews the proven solutions from the literature which have been developed. A summary chart of these solutions is presented which may be used to implement plans to solve demolding problems with replicated parts...

Form-based Approaches vs. Task-Based Approaches

Directory of Open Access Journals (Sweden)

Zahra Talebi

2015-07-01

Full Text Available This study aimed at investigating whether task-based approaches bear any superiority to that of more traditional ones evident in presentation-practice- and production phase .to fulfill the purpose of the study, the participants within the age range of 11-19, took part in the study. Following a pretest, treatment, and a posttest, the obtained data was analyzed using analysis of covariance (ANCOVA to examine the effects of the variables. The results of the analysis showed that participants in the PPP group did significantly better in the grammar recognition of the posttest than that of the task group. However, their counterparts in the task group gained better scores in the writing section of the test .this research study provided evidence in support of task proponents' claim in the merit of task-based activity in raising learners' implicit knowledge claiming to play the primary role in spontaneous speech.

Integrative pathway knowledge bases as a tool for systems molecular medicine.

Science.gov (United States)

Liang, Mingyu

2007-08-20

There exists a sense of urgency to begin to generate a cohesive assembly of biomedical knowledge as the pace of knowledge accumulation accelerates. The urgency is in part driven by the emergence of systems molecular medicine that emphasizes the combination of systems analysis and molecular dissection in the future of medical practice and research. A potentially powerful approach is to build integrative pathway knowledge bases that link organ systems function with molecules.

Provenance management in Swift with implementation details.

Energy Technology Data Exchange (ETDEWEB)

Gadelha, L. M. R; Clifford, B.; Mattoso, M.; Wilde, M.; Foster, I. (Mathematics and Computer Science); ( CLS-CI); (Federal Univ. of Rio de Janeiro); (National Lab. for Scientific Computing, Brazil); (Univ. of Chicago)

2011-04-01

The Swift parallel scripting language allows for the specification, execution and analysis of large-scale computations in parallel and distributed environments. It incorporates a data model for recording and querying provenance information. In this article we describe these capabilities and evaluate interoperability with other systems through the use of the Open Provenance Model. We describe Swift's provenance data model and compare it to the Open Provenance Model. We also describe and evaluate activities performed within the Third Provenance Challenge, which consisted of implementing a specific scientific workflow, capturing and recording provenance information of its execution, performing provenance queries, and exchanging provenance information with other systems. Finally, we propose improvements to both the Open Provenance Model and Swift's provenance system.

Network-based Approaches in Pharmacology.

Science.gov (United States)

Boezio, Baptiste; Audouze, Karine; Ducrot, Pierre; Taboureau, Olivier

2017-10-01

In drug discovery, network-based approaches are expected to spotlight our understanding of drug action across multiple layers of information. On one hand, network pharmacology considers the drug response in the context of a cellular or phenotypic network. On the other hand, a chemical-based network is a promising alternative for characterizing the chemical space. Both can provide complementary support for the development of rational drug design and better knowledge of the mechanisms underlying the multiple actions of drugs. Recent progress in both concepts is discussed here. In addition, a network-based approach using drug-target-therapy data is introduced as an example. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

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.

ADVANCED APPROACH TO PRODUCTION WORKFLOW COMPOSITION ON ENGINEERING KNOWLEDGE PORTALS

OpenAIRE

Novogrudska, Rina; Kot, Tatyana; Globa, Larisa; Schill, Alexander

2016-01-01

Background. In the environment of engineering knowledge portals great amount of partial workflows is concentrated. Such workflows are composed into general workflow aiming to perform real complex production task. Characteristics of partial workflows and general workflow structure are not studied enough, that affects the impossibility of general production workflowdynamic composition.Objective. Creating an approach to the general production workflow dynamic composition based on the partial wor...

An Ontology-Based Conceptual Model For Accumulating And Reusing Knowledge In A DMAIC Process

Science.gov (United States)

Nguyen, ThanhDat; Kifor, Claudiu Vasile

2015-09-01

DMAIC (Define, Measure, Analyze, Improve, and Control) is an important process used to enhance quality of processes basing on knowledge. However, it is difficult to access DMAIC knowledge. Conventional approaches meet a problem arising from structuring and reusing DMAIC knowledge. The main reason is that DMAIC knowledge is not represented and organized systematically. In this article, we overcome the problem basing on a conceptual model that is a combination of DMAIC process, knowledge management, and Ontology engineering. The main idea of our model is to utilizing Ontologies to represent knowledge generated by each of DMAIC phases. We build five different knowledge bases for storing all knowledge of DMAIC phases with the support of necessary tools and appropriate techniques in Information Technology area. Consequently, these knowledge bases provide knowledge available to experts, managers, and web users during or after DMAIC execution in order to share and reuse existing knowledge.

Knowledge-based fault diagnosis system for refuse collection vehicle

International Nuclear Information System (INIS)

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

2015-01-01

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

Knowledge-based fault diagnosis system for refuse collection vehicle

Energy Technology Data Exchange (ETDEWEB)

Tan, CheeFai; Juffrizal, K.; Khalil, S. N.; Nidzamuddin, M. Y. [Centre of Advanced Research on Energy, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka (Malaysia)

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.

Proven Weight Loss Methods

Science.gov (United States)

Fact Sheet Proven Weight Loss Methods What can weight loss do for you? Losing weight can improve your health in a number of ways. It can lower ... at www.hormone.org/Spanish . Proven Weight Loss Methods Fact Sheet www.hormone.org

Nuclear Knowledge Management: the IAEA Approach

International Nuclear Information System (INIS)

Sbaffoni, M.; De Grosbois, J.

2015-01-01

Knowledge in an organization is residing in people, processes and technology. Adequate awareness of their knowledge assets and of the risk of losing them is vital for safe and secure operations of nuclear installations. Senior managers understand this important linkage, and in the last years there is an increasing tendency in nuclear organizations to implement knowledge management strategies to ensure that the adequate and necessary knowledge is available at the right time, in the right place. Specific and advanced levels of knowledge are clearly required to achieve and maintain technical expertise, and experience must be developed and be available throughout the nuclear technology lifecycle. If a nuclear organization does not possess or have access to the required technical knowledge, a full understanding of the potential consequences of decisions and actions may not be possible, and safety, security and safeguards might be compromised. Effective decision making during design, licencing, procurement, construction, commissioning, operation, maintenance, refurbishment, and decommissioning of nuclear facilities needs to be risk-informed and knowledge-driven. Nuclear technology is complex and brings with it inherent and unique risks that must be managed to acceptably low levels. Nuclear managers have a responsibility not only to establish adequate technical knowledge and experience in their nuclear organizations but also to maintain it. The consequences of failing to manage the organizations key knowledge assets can result in serious degradations or accidents. The IAEA Nuclear Knowledge Management (NKM) sub-programme was established more than 10 years ago to support Nuclear Organizations, at Member States request, in the implementation and dissemination of the NKM methodology, through the development of guidance and tools, and by providing knowledge management services and assistance. The paper will briefly present IAEA understanding of and approach to knowledge

Ontology development for provenance tracing in National Climate Assessment of the US Global Change Research Program

Science.gov (United States)

Fu, Linyun; Ma, Xiaogang; Zheng, Jin; Goldstein, Justin; Duggan, Brian; West, Patrick; Aulenbach, Steve; Tilmes, Curt; Fox, Peter

2014-05-01

This poster will show how we used a case-driven iterative methodology to develop an ontology to represent the content structure and the associated provenance information in a National Climate Assessment (NCA) report of the US Global Change Research Program (USGCRP). We applied the W3C PROV-O ontology to implement a formal representation of provenance. We argue that the use case-driven, iterative development process and the application of a formal provenance ontology help efficiently incorporate domain knowledge from earth and environmental scientists in a well-structured model interoperable in the context of the Web of Data.

Knowledge-based system for automatic MBR control.

Science.gov (United States)

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

2010-01-01

of the knowledge-based DSS and details the knowledge-based control module. Preliminary results of the application of the control module to regulate the air flow rate of an MBR working with variable flux demonstrates the usefulness of this approach.

Using Motivational Interviewing with School-Age Bullies: A New Use for a Proven, Evidence-Based Intervention

Science.gov (United States)

Juhnke, Brenna A.; Juhnke, Gerald A.; Curtis, Russell C.; Thompson, E. Heather; Coll, Kenneth M.; Yu, Fangzhou; Moyer, Michael S.; Mullett, Alison

2013-01-01

Motivational interviewing is a proven, evidence-based intervention. It has been successfully utilized as a potent intervention with students presenting a broad range of concerns from substance abuse to obesity. To date, however, no articles exist within the general counseling literature or the "Journal of School Counseling" specifically…

Managing visitor sites in Svalbard: from a precautionary approach towards knowledge-based management

Directory of Open Access Journals (Sweden)

Kirstin Fangel

2012-05-01

Full Text Available Increased tourism in the Arctic calls for more knowledge to meet management challenges. This paper reviews existing knowledge of the effects of human use on vegetation, fauna and cultural heritage in Svalbard, and it addresses the need for site-specific knowledge for improved management. This paper draws upon scientific studies, knowledge held by management authorities and local people, the Governor's database on visitors and visited sites and our own data from landing sites we visited. There is a certain level of basic knowledge available, allowing us to roughly grade the vulnerability of sites. However, there is a thorough lack of site-specific data related to the management of single locations or groups of similar locations. Future research needs to address specific on-site challenges in the management of visitor sites. Relevant management models and measures are discussed. We contend that a shift away from a blanket application of the precautionary principle and towards a more integrated, site-specific and evidence-based management plan will contribute to more trusted and reliable, and thereby acceptable among stakeholders, decisions in the management of growing tourism activity in Svalbard.

Knowledge-based computer systems for radiotherapy planning.

Science.gov (United States)

Kalet, I J; Paluszynski, W

1990-08-01

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

Knowledge based maintenance

Energy Technology Data Exchange (ETDEWEB)

Sturm, A [Hamburgische Electacitaets-Werke AG Hamburg (Germany)

1998-12-31

The establishment of maintenance strategies is of crucial significance for the reliability of a plant and the economic efficiency of maintenance measures. Knowledge about the condition of components and plants from the technical and business management point of view therefore becomes one of the fundamental questions and the key to efficient management and maintenance. A new way to determine the maintenance strategy can be called: Knowledge Based Maintenance. A simple method for determining strategies while taking the technical condition of the components of the production process into account to the greatest possible degree which can be shown. A software with an algorithm for Knowledge Based Maintenance leads the user during complex work to the determination of maintenance strategies for this complex plant components. (orig.)

Knowledge based maintenance

Energy Technology Data Exchange (ETDEWEB)

Sturm, A. [Hamburgische Electacitaets-Werke AG Hamburg (Germany)

1997-12-31

The establishment of maintenance strategies is of crucial significance for the reliability of a plant and the economic efficiency of maintenance measures. Knowledge about the condition of components and plants from the technical and business management point of view therefore becomes one of the fundamental questions and the key to efficient management and maintenance. A new way to determine the maintenance strategy can be called: Knowledge Based Maintenance. A simple method for determining strategies while taking the technical condition of the components of the production process into account to the greatest possible degree which can be shown. A software with an algorithm for Knowledge Based Maintenance leads the user during complex work to the determination of maintenance strategies for this complex plant components. (orig.)

A structured approach to introduce knowledge management practice in a national nuclear research institution in Malaysia

International Nuclear Information System (INIS)

Daud, A.H.

2004-01-01

In 2002, the Government of Malaysia has launched the Knowledge Management Master Plan with the aim to transform Malaysian from a production-based economy to a knowledge-based economy. In June 2003, the 2nd National Science and Technology policy was launched. The policy puts in place programmes, institutions and partnerships to enhance Malaysian economic position. Several initiatives developed emphasize on the important roles of national nuclear research institutions in the knowledge based economy. The Malaysian Institute for Nuclear Technology Research (MINT) as a national nuclear research institution is thus expected to make significant contributions to the knowledge economy. To a certain extent MINT has been successful in knowledge acquisition and exploitation from more advanced countries as well as in knowledge generation and in the knowledge application and diffusion to the socio-economic sectors. This paper describes a structured approach to introduce the knowledge management practices or initiatives in MINT. It also describes some of the challenges foreseen in adopting the practices. (author)

Uncertainty, Pluralism, and the Knowledge-Based Theory of the Firm

DEFF Research Database (Denmark)

Reihlen, Markus; Ringberg, Torsten

2013-01-01

-cultural conventions and other social processes. Although comprehensive in scope, we argue that a knowledge-based theory of the firm needs to integrate a cognitivist approach that includes the synergetic production of tacit and explicit knowledge, the role of reflective thinking in resolving strategic uncertainties......, and the interaction between the individual and the social. This socio-cognitive theory of the firm posits that sustained competitive advantage of a firm is founded on the ability to align knowledge internally within the firm as well as externally with its stakeholders through the individual sense-making of feedback...

Analysing Discourse. An Approach From the Sociology of Knowledge

Directory of Open Access Journals (Sweden)

Reiner Keller

2005-09-01

Full Text Available The contribution outlines a research pro­gramme which I have coined the "sociology of knowledge approach to discourse" (Wissens­sozio­logische Diskursanalyse. This approach to dis­course integrates important insights of FOU­CAULT's theory of discourse into the interpretative paradigm in the social sciences, especially the "German" approach of hermeneutic sociology of knowledge (Hermeneutische Wissenssoziologie. Accordingly, in this approach discourses are con­sidered as "structured and structuring structures" which shape social practices of enunciation. Un­like some Foucauldian approaches, this form of discourse analysis recognises the importance of socially constituted actors in the social production and circulation of knowledge. Furthermore, it com­bines research questions related to the concept of "discourse" with the methodical toolbox of qual­itative social research. Going beyond ques­tions of language in use, "the sociology of knowl­edge ap­proach to discourse" (Wissenssozio­logi­sche Dis­kurs­analyse addresses sociological inter­ests, the analyses of social relations and politics of knowl­edge as well as the discursive construction of re­al­ity as an empirical ("material" process. For empiri­cal research on discourse the approach proposes the use of analytical concepts from the sociology of knowledge tradition, such as inter­pretative schemes or frames (Deutungsmuster, "clas­sifi­ca­tions", "phenomenal structure" (Phäno­men­struktur, "narrative structure", "dispositif" etc., and the use of the methodological strategies of "grounded theory". URN: urn:nbn:de:0114-fqs0503327

Knowledge of Chlamydia trachomatis among men and women approached to participate in community-based screening, Scotland, UK

Directory of Open Access Journals (Sweden)

Hart Graham J

2010-12-01

Full Text Available Abstract Background Poor awareness and knowledge of Chlamydia trachomatis could be a barrier to uptake of screening. This study aimed to determine the level of awareness and knowledge of chlamydia among young people who were being approached in a variety of community settings and offered opportunistic screening. Methods Men and women aged 16-24 years were approached in education, health and fitness, and workplace settings and invited to complete a self-administered questionnaire then provide a urine sample for chlamydia testing. Follow-up semi-structured interviews with 24 respondents were carried out after test results were received. Results 363 questionnaires were completed (43.5% from men. Whilst awareness of chlamydia was high, knowledge decreased as questions became increasingly focussed so that around half of respondents were unaware of the asymptomatic nature of chlamydia infections. Men's knowledge of symptoms was consistently lower than women's, with most men failing to identify unusual discharge as a symptom in men (men 58.3%, female 45.8%, p = 0.019; fewer men knew unusual discharge was a symptom among women (men 65.3% female 21.4%, p Conclusions Despite scientific gains in understanding chlamydia infection, public understanding remains limited. Greater efforts are required to translate scientific evidence to the public. An improvement in knowledge may maximise gains from interventions to improve detection.

Knowledge of Chlamydia trachomatis among men and women approached to participate in community-based screening, Scotland, UK.

Science.gov (United States)

Lorimer, Karen; Hart, Graham J

2010-12-30

Poor awareness and knowledge of Chlamydia trachomatis could be a barrier to uptake of screening. This study aimed to determine the level of awareness and knowledge of chlamydia among young people who were being approached in a variety of community settings and offered opportunistic screening. Men and women aged 16-24 years were approached in education, health and fitness, and workplace settings and invited to complete a self-administered questionnaire then provide a urine sample for chlamydia testing. Follow-up semi-structured interviews with 24 respondents were carried out after test results were received. 363 questionnaires were completed (43.5% from men). Whilst awareness of chlamydia was high, knowledge decreased as questions became increasingly focussed so that around half of respondents were unaware of the asymptomatic nature of chlamydia infections. Men's knowledge of symptoms was consistently lower than women's, with most men failing to identify unusual discharge as a symptom in men (men 58.3%, female 45.8%, p = 0.019); fewer men knew unusual discharge was a symptom among women (men 65.3% female 21.4%, p participation in the study. Despite scientific gains in understanding chlamydia infection, public understanding remains limited. Greater efforts are required to translate scientific evidence to the public. An improvement in knowledge may maximise gains from interventions to improve detection.

Scientific Reproducibility in Biomedical Research: Provenance Metadata Ontology for Semantic Annotation of Study Description.

Science.gov (United States)

Sahoo, Satya S; Valdez, Joshua; Rueschman, Michael

2016-01-01

Scientific reproducibility is key to scientific progress as it allows the research community to build on validated results, protect patients from potentially harmful trial drugs derived from incorrect results, and reduce wastage of valuable resources. The National Institutes of Health (NIH) recently published a systematic guideline titled "Rigor and Reproducibility " for supporting reproducible research studies, which has also been accepted by several scientific journals. These journals will require published articles to conform to these new guidelines. Provenance metadata describes the history or origin of data and it has been long used in computer science to capture metadata information for ensuring data quality and supporting scientific reproducibility. In this paper, we describe the development of Provenance for Clinical and healthcare Research (ProvCaRe) framework together with a provenance ontology to support scientific reproducibility by formally modeling a core set of data elements representing details of research study. We extend the PROV Ontology (PROV-O), which has been recommended as the provenance representation model by World Wide Web Consortium (W3C), to represent both: (a) data provenance, and (b) process provenance. We use 124 study variables from 6 clinical research studies from the National Sleep Research Resource (NSRR) to evaluate the coverage of the provenance ontology. NSRR is the largest repository of NIH-funded sleep datasets with 50,000 studies from 36,000 participants. The provenance ontology reuses ontology concepts from existing biomedical ontologies, for example the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), to model the provenance information of research studies. The ProvCaRe framework is being developed as part of the Big Data to Knowledge (BD2K) data provenance project.

Knowledge Base of Mathematics Teacher Educators: A Goals-Knowledge-Practice Approach

Science.gov (United States)

Veselovsky, Aleksandra

2017-01-01

Critical analysis of the literature reveals that many questions about the knowledge and practice of mathematics teacher educators (MTEs) remain in need of further research: how do they know what to teach; how do they learn how to teach teachers; how do they prepare to teach their courses; how does the research on teacher education inform their…

Autonomous Cryogenic Load Operations: Knowledge-Based Autonomous Test Engineer

Science.gov (United States)

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.

Problem based learning: enhancing constructivist activities and engagement by fostering online knowledge sharing

OpenAIRE

Malik, Manish

2009-01-01

PBL was first introduced in medical education as a pure constructivist activity. This was popularly known as the McMaster approach [1]. Later, as can be seen in the literature [2], [4]-[10], there were several different implementations of PBL. There is no single definition of what is classed as a PBL activity. Similarly, there is no one approach reported to be the only successful approach. Sharing of knowledge and discussions based on this knowledge are the hall mark of any successful PBL bas...

Developing an intranet towards knowledge sharing: A practitioner-based inquiry

Directory of Open Access Journals (Sweden)

U. R. Averweg

2008-11-01

Full Text Available The intranet is a common feature in many organizations. With the increasing use of a technology infrastructure in organizations, there is a continued challenge for employees in an organization to contribute their knowledge willingly and to make use of knowledge sharing with other employees. Intranets are well-suited for use as a strategic tool in knowledge sharing due to their ability to support the distribution, connectivity and publishing of data and information. Intranets should be seen as integral to an organization’s knowledge management strategy and should be tailored to suit and enhance an organization’s knowledge-sharing activities. The question arises: To what extent does an organization’s existing intranet facilitate knowledge sharing? From a practitioner-based inquiry perspective, this question was explored by the selection of a large organization – eThekwini Municipality, Durban, South Africa – as the field of application. Derived from a mixed methodology approach, the results of a survey are presented. It is suggested that encouragement be given for more practitioner-based inquiry research.

Systematic approach for the design of pumpable cement-based grouts for immobilization of hazardous wastes

International Nuclear Information System (INIS)

Sams, T.L.; Gilliam, T.M.

1987-01-01

Cement-based grouts have been proven to be an economical and environmentally acceptable means of waste disposal. Costs can be reduced if the grout is pumped to the disposal site. This paper presents a systematic approach to guide the development of pumpable grouts. 20 refs., 2 figs

Machine intelligence and knowledge bases

Energy Technology Data Exchange (ETDEWEB)

Furukawa, K

1981-09-01

The basic functions necessary in machine intelligence are a knowledge base and a logic programming language such as PROLOG using deductive reasoning. Recently inductive reasoning based on meta knowledge and default reasoning have been developed. The creative thought model of Lenit is reviewed and the concept of knowledge engineering is introduced. 17 references.

New frontiers in information and production systems modelling and analysis incentive mechanisms, competence management, knowledge-based production

CERN Document Server

Novikov, Dmitry; Bakhtadze, Natalia; Zaikin, Oleg

2016-01-01

This book demonstrates how to apply modern approaches to complex system control in practical applications involving knowledge-based systems. The dimensions of knowledge-based systems are extended by incorporating new perspectives from control theory, multimodal systems and simulation methods.  The book is divided into three parts: theory, production system and information system applications. One of its main focuses is on an agent-based approach to complex system analysis. Moreover, specialised forms of knowledge-based systems (like e-learning, social network, and production systems) are introduced with a new formal approach to knowledge system modelling.   The book, which offers a valuable resource for researchers engaged in complex system analysis, is the result of a unique cooperation between scientists from applied computer science (mainly from Poland) and leading system control theory researchers from the Russian Academy of Sciences’ Trapeznikov Institute of Control Sciences.

Facilitating Fine Grained Data Provenance using Temporal Data Model

NARCIS (Netherlands)

Huq, M.R.; Wombacher, Andreas; Apers, Peter M.G.

2010-01-01

E-science applications use fine grained data provenance to maintain the reproducibility of scientific results, i.e., for each processed data tuple, the source data used to process the tuple as well as the used approach is documented. Since most of the e-science applications perform on-line

Transferring Codified Knowledge: Socio-Technical versus Top-Down Approaches

Science.gov (United States)

Guzman, Gustavo; Trivelato, Luiz F.

2008-01-01

Purpose: This paper aims to analyse and evaluate the transfer process of codified knowledge (CK) performed under two different approaches: the "socio-technical" and the "top-down". It is argued that the socio-technical approach supports the transfer of CK better than the top-down approach. Design/methodology/approach: Case study methodology was…

Explicit Knowledge-based Reasoning for Visual Question Answering

OpenAIRE

Wang, Peng; Wu, Qi; Shen, Chunhua; Hengel, Anton van den; Dick, Anthony

2015-01-01

We describe a method for visual question answering which is capable of reasoning about contents of an image on the basis of information extracted from a large-scale knowledge base. The method not only answers natural language questions using concepts not contained in the image, but can provide an explanation of the reasoning by which it developed its answer. The method is capable of answering far more complex questions than the predominant long short-term memory-based approach, and outperform...

Identification and Ranking of Critical Success Factors of Knowledge Management Using Fuzzy Quality Function Deployment Approach: A Case Study

Directory of Open Access Journals (Sweden)

Ali Mohaghar

2014-02-01

Based on the information accessible for the researchers, this is one of the first works which evaluates the key factors of successful knowledge management through fuzzy quality function deployment approach. It is expected that the proposed method would represent appropriate tools for enterprises which have decided to implement knowledge management because it prioritizes the critical success factors based on the knowledge management outcomes.

Automatic segmentation of coronary vessels from digital subtracted angiograms: a knowledge-based approach

International Nuclear Information System (INIS)

Stansfield, S.A.

1986-01-01

This paper presents a rule-based expert system for identifying and isolating coronary vessels in digital angiograms. The system is written in OPS5 and LISP and uses low level processors written in C. The system embodies both stages of the vision hierarchy: The low level image processing stage works concurrently with edges (or lines) and regions to segment the input image. Its knowledge is that of segmentation, grouping, and shape analysis. The high level stage then uses its knowledge of cardiac anatomy and physiology to interpret the result and to eliminate those structures not desired in the output. (Auth.)

Approach of simultaneous localization and mapping based on local maps for robot

Institute of Scientific and Technical Information of China (English)

CHEN Bai-fan; CAI Zi-xing; HU De-wen

2006-01-01

An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps.A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.

Water use efficiency studies of Acacia senegal (L.) Willd provenances in Sudan

International Nuclear Information System (INIS)

Mustafa, A.F.; Elamin, K.H.; Salih, A.A.

1996-01-01

An experiment was conducted in 1989 to screen Acacia senegal L. Willd provenances collected from within the natural gum belt for high water use efficiency. Thirteen provenances were tested for water use efficiency and consequently 6 out of them were selected for further screening. The selection was based on their performance in the preliminary screening. Both the preliminary and the detailed study revealed that provenances 7, 3 and 11 combine high dry matter production with high water use efficiency. Water use efficiency and dry matter production appears to be negatively correlated with root length density and root/shoot ratios. Provenances 7 which exhibited the highest water use efficiency and dry matter yield had the lowest root/shoot ratio and also a low root length density. Based on these studies provenance 7 can be considered a suitable candidate for introduction into gum-belt of Sudan through for rehabilitation of this region. (author). 5 refs, 1 fig., 3 tabs

Water use efficiency studies of Acacia senegal (L.) Willd provenances in Sudan

Energy Technology Data Exchange (ETDEWEB)

Mustafa, A F; Elamin, K H [Forestry Research Section, Wad Medani (Sudan); Salih, A A [Soil Science Section, Wad Medani (Sudan)

1996-07-01

An experiment was conducted in 1989 to screen Acacia senegal L. Willd provenances collected from within the natural gum belt for high water use efficiency. Thirteen provenances were tested for water use efficiency and consequently 6 out of them were selected for further screening. The selection was based on their performance in the preliminary screening. Both the preliminary and the detailed study revealed that provenances 7, 3 and 11 combine high dry matter production with high water use efficiency. Water use efficiency and dry matter production appears to be negatively correlated with root length density and root/shoot ratios. Provenances 7 which exhibited the highest water use efficiency and dry matter yield had the lowest root/shoot ratio and also a low root length density. Based on these studies provenance 7 can be considered a suitable candidate for introduction into gum-belt of Sudan through for rehabilitation of this region. (author). 5 refs, 1 fig., 3 tabs.

School-Based Intervention for Nutrition Promotion in Mi Yun County, Beijing, China: Does a Health-Promoting School Approach Improve Parents' Knowledge, Attitudes and Behaviour?

Science.gov (United States)

Wang, Dongxu; Stewart, Donald; Chang, Chun

2016-01-01

Purpose: The purpose of this paper is to assess whether the school-based nutrition programme using the health-promoting school (HPS) framework was effective to improve parents' knowledge, attitudes and behaviour (KAB) in relation to nutrition in rural Mi Yun County, Beijing. Design/methodology/approach: A cluster-randomised intervention trial…

Knowledge Based Economy Assessment

OpenAIRE

Madalina Cristina Tocan

2012-01-01

The importance of knowledge-based economy (KBE) in the XXI century is evident. In the article the reflection of knowledge on economy is analyzed. The main point is targeted to the analysis of characteristics of knowledge expression in economy and to the construction of structure of KBE expression. This allows understanding the mechanism of functioning of knowledge economy. The authors highlight the possibility to assess the penetration level of KBE which could manifest itself trough the exist...

Ecosystem-based management in the Wadden Sea: Principles for the governance of knowledge

Science.gov (United States)

Giebels, Diana; van Buuren, Arwin; Edelenbos, Jurian

2013-09-01

The governance of the Wadden Sea has to contend with a complex interplay of social and ecological systems. Social systems tend to be characterized by pluralism of - often conflicting - norms and values, and ecological systems are characterized by high complexity and natural and human-induced variability, leading to unpredictable and nonlinear behavior. This highly volatile situation challenges traditional forms of management as well as traditional ways of organizing knowledge for decision-making processes. Ecosystem-based management approaches have been developed to find more effective, holistic, and evidence-based strategies to deal with the challenges of complex socio-ecological systems. They also require another way of dealing with (scientific) knowledge, the way it is produced and applied. In this paper, from the perspective of ecosystem-based management, we define the specific principles that apply to the way knowledge is mobilized and applied within decision-making processes. We illuminate these principles by examining three empirical cases of ecosystem-based management within, or related to, the Wadden Sea area. Finally, we reflect upon our findings and elaborate on the extent to which our theoretical framework is capable of describing and assessing the interaction between knowledge and decision making within ecosystem-based management approaches.

Taxonomy-Based Approaches to Quality Assurance of Ontologies

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Michael Halper

2017-01-01

Full Text Available Ontologies are important components of health information management systems. As such, the quality of their content is of paramount importance. It has been proven to be practical to develop quality assurance (QA methodologies based on automated identification of sets of concepts expected to have higher likelihood of errors. Four kinds of such sets (called QA-sets organized around the themes of complex and uncommonly modeled concepts are introduced. A survey of different methodologies based on these QA-sets and the results of applying them to various ontologies are presented. Overall, following these approaches leads to higher QA yields and better utilization of QA personnel. The formulation of additional QA-set methodologies will further enhance the suite of available ontology QA tools.

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

Science.gov (United States)

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.

A Knowledge Engineering Approach to Developing Educational Computer Games for Improving Students' Differentiating Knowledge

Science.gov (United States)

Hwang, Gwo-Jen; Sung, Han-Yu; Hung, Chun-Ming; Yang, Li-Hsueh; Huang, Iwen

2013-01-01

Educational computer games have been recognized as being a promising approach for motivating students to learn. Nevertheless, previous studies have shown that without proper learning strategies or supportive models, the learning achievement of students might not be as good as expected. In this study, a knowledge engineering approach is proposed…

Knowledge Base Editor (SharpKBE)

Science.gov (United States)

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.

An Approach towards Promoting Iranian Caregivers’ Knowledge on Early Childhood Development

Directory of Open Access Journals (Sweden)

Firoozeh Sajedi

2018-03-01

Full Text Available Background: According to the World Health Organization (WHO, parents need to be informed about Early Childhood Development (ECD. Different methods of parents’ education include group-based, face-to-face, book, booklet, web-based, technology-based, and mobile learning using laptops, tablets, and cell phones. Paying attention to caregivers' attitudes is the first step to their education. The objectives of this study were to determine parental education requirements and the best approach towards promoting caregivers` knowledge about ECD, from the perspective of the Iranian main child caregivers. Materials and Methods: A qualitative approach with directional content analysis method was used. Participants were selected through purposive sampling. Thirty-one child-caregivers participated in 5 individual interviews and 5 focus group discussions (FGDs. Participants were parents and grandparents that had less than the 36-month child (grandchild, and kindergarten staffs. Four criteria namely: validity, transferability, reliability and verifiability were used to validate data. Results: According to the perspective of participants, two main themes were requirements for parent education (educators, educational content, time, place, and approach to educate child caregivers (mobile learning, group and face-to-face education, electronic learning, media, physical resources, totally 98 sub-themes. Finally the best approach to educate child caregivers was a multi-model approach includes group or face-to-face education with mobile learning. Conclusion: Participants suggested a multi-model approach based on traditional and modern technological methods, especially mobile learning (smartphone. They believed that the educational approach should be flexible and selectable, so caregivers can choose an appropriate individual method.

Provenance Representation in the Global Change Information System (GCIS)

Science.gov (United States)

Tilmes, Curt

2012-01-01

Global climate change is a topic that has become very controversial despite strong support within the scientific community. It is common for agencies releasing information about climate change to be served with Freedom of Information Act (FOIA) requests for everything that led to that conclusion. Capturing and presenting the provenance, linking to the research papers, data sets, models, analyses, observation instruments and satellites, etc. supporting key findings has the potential to mitigate skepticism in this domain. The U.S. Global Change Research Program (USGCRP) is now coordinating the production of a National Climate Assessment (NCA) that presents our best understanding of global change. We are now developing a Global Change Information System (GCIS) that will present the content of that report and its provenance, including the scientific support for the findings of the assessment. We are using an approach that will present this information both through a human accessible web site as well as a machine readable interface for automated mining of the provenance graph. We plan to use the developing W3C PROV Data Model and Ontology for this system.

Fagus sylvatica L. provenances maintain different leaf metabolic profiles and functional response

Science.gov (United States)

Aranda, Ismael; Sánchez-Gómez, David; de Miguel, Marina; Mancha, Jose Antonio; Guevara, María Angeles; Cadahía, Estrella; Fernández de Simón, María Brígida

2017-07-01

Most temperate forest tree species will suffer important environmental changes as result of the climate change. Adaptiveness to local conditions could change at different sites in the future. In this context, the study of intra-specific variability is important to clarify the singularity of different local populations. Phenotypic differentiation between three beech provenances covering a wide latitudinal range (Spain/ES, Germany/DE and Sweden/SE), was studied in a greenhouse experiment. Non-target leaf metabolite profiles and ecophysiological response was analyzed in well-watered and water stressed seedlings. There was a provenance-specific pattern in the relative concentrations of some leaf metabolites regardless watering treatment. The DE and SE from the center and north of the distribution area of the species showed a clear differentiation from the ES provenance in the relative concentration of some metabolites. Thus the ES provenance from the south maintained larger relative concentration of some organic and amino acids (e.g. fumaric and succinic acids or valine and isoleucine), and in some secondary metabolites (e.g. kaempferol, caffeic and ferulic acids). The ecophysiological response to mild water stress was similar among the three provenances as a consequence of the moderate water stress applied to seedlings, although leaf N isotope composition (δ15N) and leaf C:N ratio were higher and lower respectively in DE than in the other two provenances. This would suggest potential differences in the capacity to uptake and post-process nitrogen according to provenance. An important focus of the study was to address for the first time inter-provenance leaf metabolic diversity in beech from a non-targeted metabolic profiling approach that allowed differentiation of the three studied provenances.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

Directory of Open Access Journals (Sweden)

Falciani Francesco

2011-03-01

Full Text Available Abstract Background To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the

A knowledge based method for nuclear plant loading pattern determination

International Nuclear Information System (INIS)

Dauboin, P.

1990-01-01

This paper deals with the design of a knowledge based system for solving an industrial problem which occurs in nuclear fuel management. The problem lies in determining satisfactory loading patterns for nuclear plants. Its primary feature consists in the huge search space involved. Conventional resolution processes are formally defined and analyzed: there is no general algorithm which guarantees to always provide a reasonable solution in each situation. We propose a new approach to solve this constrained search problem using domain-specific knowledge and general constraint-based heuristics. During a preprocessing step, a problem dependent search algorithm is designed. This procedure is then automatically implemented in FORTRAN. The generated routines have proved to be very efficient finding solutions which could not have been provided using logic programming. A prototype expert system has already been applied to actual reload pattern searches. While combining efficiency and flexibility, this knowledge based system enables human experts to rapidly match new constraints and requirements

Reusing Design Knowledge Based on Design Cases and Knowledge Map

Science.gov (United States)

Yang, Cheng; Liu, Zheng; Wang, Haobai; Shen, Jiaoqi

2013-01-01

Design knowledge was reused for innovative design work to support designers with product design knowledge and help designers who lack rich experiences to improve their design capacity and efficiency. First, based on the ontological model of product design knowledge constructed by taxonomy, implicit and explicit knowledge was extracted from some…

Automated knowledge-base refinement

Science.gov (United States)

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.

Blended Risk Approach in Applying PSA Models to Risk-Based Regulations

International Nuclear Information System (INIS)

Dimitrijevic, V. B.; Chapman, J. R.

1996-01-01

In this paper, the authors will discuss a modern approach in applying PSA models in risk-based regulation. The Blended Risk Approach is a combination of traditional and probabilistic processes. It is receiving increased attention in different industries in the U. S. and abroad. The use of the deterministic regulations and standards provides a proven and well understood basis on which to assess and communicate the impact of change to plant design and operation. Incorporation of traditional values into risk evaluation is working very well in the blended approach. This approach is very application specific. It includes multiple risk attributes, qualitative risk analysis, and basic deterministic principles. In blending deterministic and probabilistic principles, this approach ensures that the objectives of the traditional defense-in-depth concept are not compromised and the design basis of the plant is explicitly considered. (author)

Place-Based Education for Environmental Behavior: A 'Funds of Knowledge' and Social Capital Approach

Science.gov (United States)

Cruz, Austin R.; Selby, Samantha T.; Durham, William H.

2018-01-01

In this paper we suggest that a new theoretical framework is needed within environmental education in the discussion of rural, underserved communities in Latin America. We argue that a community-resources approach, comprised of funds of knowledge and social capital, should be incorporated into contemporary research on place- and community-based…

XML-Based SHINE Knowledge Base Interchange Language

Science.gov (United States)

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.

Case-based reasoning: The marriage of knowledge base and data base

Science.gov (United States)

Pulaski, Kirt; Casadaban, Cyprian

1988-01-01

The coupling of data and knowledge has a synergistic effect when building an intelligent data base. The goal is to integrate the data and knowledge almost to the point of indistinguishability, permitting them to be used interchangeably. Examples given in this paper suggest that Case-Based Reasoning is a more integrated way to link data and knowledge than pure rule-based reasoning.

Integration of object-oriented knowledge representation with the CLIPS rule based system

Science.gov (United States)

Logie, David S.; Kamil, Hasan

1990-01-01

The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

An approach to knowledge dynamic maintenance for emotional agents

OpenAIRE

Fulladoza Dalibón, Santiago E.; Martínez, Diego C.; Simari, Guillermo Ricardo

2014-01-01

In this work we present an approach to emotional reasoning for believable agents, by introducing a mechanism to progressively build a map of knowledge for reasoning. We present the notion of inference graph for progressive reasoning in an emotional context. In this model, knowledge is partially highlighted and noticed by the agent.

A knowledge-based system framework for real-time monitoring applications

International Nuclear Information System (INIS)

Heaberlin, J.O.; Robinson, A.H.

1989-01-01

A real-time environment presents a challenge for knowledge-based systems for process monitoring with on-line data acquisition in nuclear power plants. These applications are typically data intensive. This, coupled with the dynamic nature of events on which problematic decisions are based, requires the development of techniques fundamentally different from those generally employed. Traditional approaches involve knowledge management techniques developed for static data, the majority of which is elicited directly from the user in a consultation environment. Inference mechanisms are generally noninterruptible, requiring all appropriate rules to be fired before new data can be accommodated. As a result, traditional knowledge-based applications in real-time environments have inherent problems in dealing with the time dependence of both the data and the solution process. For example, potential problems include obtaining a correct solution too late to be of use or focusing computing resources on problems that no longer exist. A knowledge-based system framework, the real-time framework (RTF), has been developed that can accommodate the time dependencies and resource trade-offs required for real-time process monitoring applications. This framework provides real-time functionality by using generalized problem-solving goals and control strategies that are modifiable during system operation and capable of accommodating feedback for redirection of activities

Augmentation of Explicit Spatial Configurations by Knowledge-Based Inference on Geometric Fields

Directory of Open Access Journals (Sweden)

Dan Tappan

2009-04-01

Full Text Available A spatial configuration of a rudimentary, static, realworld scene with known objects (animals and properties (positions and orientations contains a wealth of syntactic and semantic spatial information that can contribute to a computational understanding far beyond what its quantitative details alone convey. This work presents an approach that (1 quantitatively represents what a configuration explicitly states, (2 integrates this information with implicit, commonsense background knowledge of its objects and properties, (3 infers additional, contextually appropriate, commonsense spatial information from and about their interrelationships, and (4 augments the original representation with this combined information. A semantic network represents explicit, quantitative information in a configuration. An inheritance-based knowledge base of relevant concepts supplies implicit, qualitative background knowledge to support semantic interpretation. Together, these structures provide a simple, nondeductive, constraint-based, geometric logical formalism to infer substantial implicit knowledge for intrinsic and deictic frames of spatial reference.

A knowledge-based system for optimization of fuel reload configurations

International Nuclear Information System (INIS)

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

1989-01-01

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

Play as mediator for knowledge-creation in Problem Based Learning

DEFF Research Database (Denmark)

Thorsted, Ann Charlotte; Bing, Rie Grønbeck; Kristensen, Michael

2015-01-01

the students find that this experience enhanced a different learning form, from the one they knew from their earlier PBL processes? What was it the playful approach to PBL as a learning method had mediated? The article leads on to a distinction and a model encircling three different knowledge forms based...

The Knowledge Sharing Based on PLIB Ontology and XML for Collaborative Product Commerce

Science.gov (United States)

Ma, Jun; Luo, Guofu; Li, Hao; Xiao, Yanqiu

Collaborative Product Commerce (CPC) has become a brand-new commerce mode for manufacture. In order to promote information communication with each other more efficiently in CPC, a knowledge-sharing framework based on PLIB (ISO 13584) ontology and XML was presented, and its implementation method was studied. At first, according to the methodology of PLIB (ISO 13584), a common ontology—PLIB ontology was put forward which provide a coherent conceptual meaning within the context of CPC domain. Meanwhile, for the sake of knowledge intercommunion via internet, the PLIB ontology formalization description by EXPRESS mode was converted into XML Schema, and two mapping methods were presented: direct mapping approach and meta-levels mapping approach, while the latter was adopted. Based on above work, a parts resource knowledge-sharing framework (CPC-KSF) was put forward and realized, which has been applied in the process of automotive component manufacturing collaborative product commerce.

Exchanging Description Logic Knowledge Bases

NARCIS (Netherlands)

Arenas, M.; Botoeva, E.; Calvanese, D.; Ryzhikov, V.; Sherkhonov, E.

2012-01-01

In this paper, we study the problem of exchanging knowledge between a source and a target knowledge base (KB), connected through mappings. Differently from the traditional database exchange setting, which considers only the exchange of data, we are interested in exchanging implicit knowledge. As

A knowledge integration approach to flood vulnerability

Science.gov (United States)

Mazzorana, Bruno; Fuchs, Sven

2014-05-01

Understanding, qualifying and quantifying vulnerability is an essential need for implementing effective and efficient flood risk mitigation strategies; in particular if possible synergies between different mitigation alternatives, such as active and passive measures, should be achieved. In order to combine different risk management options it is necessary to take an interdisciplinary approach to vulnerability reduction, and as a result the affected society may be willing to accept a certain degree of self-responsibility. However, due to differing mono-disciplinary approaches and regional foci undertaken until now, different aspects of vulnerability to natural hazards in general and to floods in particular remain uncovered and as a result the developed management options remain sub-optimal. Taking an even more fundamental viewpoint, the empirical vulnerability functions used in risk assessment specifically fail to capture physical principles of the damage-generating mechanisms to the build environment. The aim of this paper is to partially close this gap by discussing a balanced knowledge integration approach which can be used to resolve the multidisciplinary disorder in flood vulnerability research. Modelling techniques such as mathematical-physical modelling of the flood hazard impact to and response from the building envelope affected, and formative scenario analyses of possible consequences in terms of damage and loss are used in synergy to provide an enhanced understanding of vulnerability and to render the derived knowledge into interdisciplinary mitigation strategies. The outlined formal procedure allows for a convincing knowledge alignment of quantified, but partial, information about vulnerability as a result of the application of physical and engineering notions and valuable, but often underspecified, qualitative argumentation strings emerging from the adopted socio-economic viewpoint.

Querying Natural Logic Knowledge Bases

DEFF Research Database (Denmark)

Andreasen, Troels; Bulskov, Henrik; Jensen, Per Anker

2017-01-01

This paper describes the principles of a system applying natural logic as a knowledge base language. Natural logics are regimented fragments of natural language employing high level inference rules. We advocate the use of natural logic for knowledge bases dealing with querying of classes...... in ontologies and class-relationships such as are common in life-science descriptions. The paper adopts a version of natural logic with recursive restrictive clauses such as relative clauses and adnominal prepositional phrases. It includes passive as well as active voice sentences. We outline a prototype...... for partial translation of natural language into natural logic, featuring further querying and conceptual path finding in natural logic knowledge bases....

Diverging Drought Resistance of Scots Pine Provenances Revealed by Infrared Thermography

Directory of Open Access Journals (Sweden)

Hannes Seidel

2016-08-01

Full Text Available With recent climate changes, Scots pine (Pinus sylvestris L. forests have been affected by die-off events. Assisted migration of adapted provenances mitigates drought impacts and promotes forest regeneration. Although suitable provenances are difficult to identify by traditional ecophysiological techniques, which are time consuming and invasive, plant water status can be easily assessed by infrared thermography. Thus, we examined the stress responses of 2-year-old potted Scots pine seedlings from six provenances (Bulgaria, France, Germany, Italy, Poland, and Spain based on two thermal indices (crop water stress index and stomatal conductance index. Both indices were derived from infrared images during a six-week drought/control treatment in a greenhouse in the summer of 2013. The pines were monitored during the stress and subsequent recovery period. After controlling for fluctuating environmental conditions, soil moisture or treatment-specific water supply was the most important driver of drought stress. The stress magnitude and response to soil water deficit depended on provenance. Under moderate drought conditions, pines from western and eastern Mediterranean provenances (Bulgaria, France, and Spain expressed lower stress levels than those from both continental provenances (Germany and Poland. In pines from the Spanish and Bulgarian provenances, the stress level differences were significantly lower than in continental pines. Moreover, pines from continental provenances were less resilient (showed less recovery after the stress period than Mediterranean pines. Under extreme drought, all provenances were equally stressed with almost no significant differences in their thermal indices. Provenance-specific differences in drought resistance, which are associated with factors such as summer precipitation at the origin of Scots pine seedlings, may offer promising tracks of adaptation to future drought risks.

A rights-based approach to science literacy using local languages: Contextualising inquiry-based learning in Africa

Science.gov (United States)

Babaci-Wilhite, Zehlia

2017-06-01

This article addresses the importance of teaching and learning science in local languages. The author argues that acknowledging local knowledge and using local languages in science education while emphasising inquiry-based learning improve teaching and learning science. She frames her arguments with the theory of inquiry, which draws on perspectives of both dominant and non-dominant cultures with a focus on science literacy as a human right. She first examines key assumptions about knowledge which inform mainstream educational research and practice. She then argues for an emphasis on contextualised learning as a right in education. This means accounting for contextualised knowledge and resisting the current trend towards de-contextualisation of curricula. This trend is reflected in Zanzibar's recent curriculum reform, in which English replaced Kiswahili as the language of instruction (LOI) in the last two years of primary school. The author's own research during the initial stage of the change (2010-2015) revealed that the effect has in fact proven to be counterproductive, with educational quality deteriorating further rather than improving. Arguing that language is essential to inquiry-based learning, she introduces a new didactic model which integrates alternative assumptions about the value of local knowledge and local languages in the teaching and learning of science subjects. In practical terms, the model is designed to address key science concepts through multiple modalities - "do it, say it, read it, write it" - a "hands-on" experiential combination which, she posits, may form a new platform for innovation based on a unique mix of local and global knowledge, and facilitate genuine science literacy. She provides examples from cutting-edge educational research and practice that illustrate this new model of teaching and learning science. This model has the potential to improve learning while supporting local languages and culture, giving local languages their

Artificial intelligence and tutoring systems computational and cognitive approaches to the communication of knowledge

CERN Document Server

Wenger, Etienne

2014-01-01

Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretic

Recording Process Documentation for Provenance

NARCIS (Netherlands)

Groth, P.T.; Moreau, L

2009-01-01

Scientific and business communities are adopting large-scale distributed systems as a means to solve a wide range of resource-intensive tasks. These communities also have requirements in terms of provenance. We define the provenance of a result produced by a distributed system as the process that

Decision-theoretic approaches to non-knowledge in economics

OpenAIRE

Svetlova, Ekaterina; van Elst, Henk

2014-01-01

We review two strands of conceptual approaches to the formal representation of a decision maker's non-knowledge at the initial stage of a static one-person, one-shot decision problem in economic theory. One focuses on representations of non-knowledge in terms of probability measures over sets of mutually exclusive and exhaustive consequence-relevant states of Nature, the other deals with unawareness of potentially important events by means of sets of states that are less complete than the ful...

Enhancing SAT Based Planning with Landmark Knowledge

NARCIS (Netherlands)

Elffers, J.; Konijnenberg, D.; Walraven, E.M.P.; Spaan, M.T.J.

2013-01-01

Several approaches exist to solve Artificial Intelligence planning problems, but little attention has been given to the combination of using landmark knowledge and satisfiability (SAT). Landmark knowledge has been exploited successfully in the heuristics of classical planning. Recently it was also

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

Science.gov (United States)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Authoritative knowledge, evidence-based medicine, and behavioral pediatrics.

Science.gov (United States)

Kennell, J H

1999-12-01

Evidence-based medicine is the conscientious and judicious use of current best knowledge in making decisions about the care of individual patients, often from well-designed, randomized, controlled trials. Authoritative medicine is the traditional approach to learning and practicing medicine, but no one authority has comprehensive scientific knowledge. Archie Cochrane proposed that every medical specialty should compile a list of all of the randomized, controlled trials within its field to be available for those who wish to know what treatments are effective. This was done first for obstetrics by a group collecting and critically analyzing all of the randomized trials and then indicating procedures every mother should have and those that no mother should have. Support during labor was used as an example. Similar groups are now active in almost all specialties, with information available on the Internet in the Cochrane Database of Systematic Reviews. Developmental-behavioral pediatrics should be part of this movement to evidence-based medicine.

Automatic Recognition of Chinese Personal Name Using Conditional Random Fields and Knowledge Base

Directory of Open Access Journals (Sweden)

Chuan Gu

2015-01-01

Full Text Available According to the features of Chinese personal name, we present an approach for Chinese personal name recognition based on conditional random fields (CRF and knowledge base in this paper. The method builds multiple features of CRF model by adopting Chinese character as processing unit, selects useful features based on selection algorithm of knowledge base and incremental feature template, and finally implements the automatic recognition of Chinese personal name from Chinese document. The experimental results on open real corpus demonstrated the effectiveness of our method and obtained high accuracy rate and high recall rate of recognition.

Managing nuclear knowledge: A SCK-CEN concern: Status of a practical knowledge management approach

International Nuclear Information System (INIS)

Ruyssen, M.L.; Moons, F.; Borgermans, P.

2004-01-01

Preserving and enhancing the institutional memory has become a strategic concern for SCK-CEN. Managing the Knowledge Capital is a long term journey, starting from a strategic commitment and integrating various operational projects. Since 2002, several pilot projects in different areas of expertise have been conducted to set up nuclear knowledge repositories and to sustain interactive research communities. Beyond the establishment of a corporate knowledge sharing culture, dedicated web-based portals based on both well established and emerging open source internet technologies ensure the long term persistence of data and the continuous capture of knowledge by providing on-line tools and related QA procedures. (author)

Nuclear Knowledge Innovations Assimilation: The Impact of Organizational Knowledge Frames and Triple Helix Dynamics of Knowledge Base

International Nuclear Information System (INIS)

Hossain, M. D.; Sultana, T.

2016-01-01

Full text: Previous research did not investigate the impact of the TH dynamics of knowledge innovations on the nuclear knowledge innovations adoption/assimilation in the organizational context. Hence, the recommendation of R&D policy reformulation seems too broad. These gaps are the prime motivators for the research. In the organizational context, we posit that TH dynamics of knowledge base innovation serves as complements to managers’ knowledge frames related to a technology innovation. We examine interactions between three knowledge frames—integration frame, opportunism frame, and policy knowledge frame, and two TH dynamics of knowledge innovations—bilateral TH dynamics of knowledge innovations and trilateral TH dynamics of knowledge innovations, and their relationship with the assimilation of nuclear knowledge innovations. We aim to research on the issues of the dynamics of knowledge base of innovations involving TH collaborations (university, industry and government) in Bangladesh as a new build nuclear project. As a result, we can find out the impact of TH collaborations on organizational nuclear knowledge innovations management as well as core institutional problems of the knowledge base of innovation systems in terms of R&D policy. Finally, findings identify lack in production of nuclear knowledge innovations and concrete recommendation of R&D policy reformulation. (author

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

Science.gov (United States)

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

2013-02-01

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

Knowledge base rule partitioning design for CLIPS

Science.gov (United States)

Mainardi, Joseph D.; Szatkowski, G. P.

1990-01-01

This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

Ontology-Based Knowledge Organization for the Radiograph Images Segmentation

Directory of Open Access Journals (Sweden)

MATEI, O.

2008-04-01

Full Text Available The quantity of thoracic radiographies in the medical field is ever growing. An automated system for segmenting the images would help doctors enormously. Some approaches are knowledge-based; therefore we propose here an ontology for this purpose. Thus it is machine oriented, rather than human-oriented. That is all the structures visible on a thoracic image are described from a technical point of view.

Integrated approach to knowledge acquisition and safety management of complex plants with emphasis on human factors

International Nuclear Information System (INIS)

Kosmowski, K.T.

1998-01-01

In this paper an integrated approach to the knowledge acquisition and safety management of complex industrial plants is proposed and outlined. The plant is considered within a man-technology-environment (MTE) system. The knowledge acquisition is aimed at the consequent reliability evaluation of human factor and probabilistic modeling of the plant. Properly structured initial knowledge is updated in life-time of the plant. The data and knowledge concerning the topology of safety related systems and their functions are created in a graphical CAD system and are object oriented. Safety oriented monitoring of the plant includes abnormal situations due to external and internal disturbances, failures of hard/software components and failures of human factor. The operation and safety related evidence is accumulated in special data bases. Data/knowledge bases are designed in such a way to support effectively the reliability and safety management of the plant. (author)

A Comparative Assessment of Knowledge Management Leadership Approaches within the Department of Defense

Science.gov (United States)

2007-03-01

A COMPARATIVE ASSESSMENT OF KNOWLEDGE MANAGEMENT LEADERSHIP APPROACHES WITHIN THE DEPARTMENT OF DEFENSE... MANAGEMENT LEADERSHIP APPROACHES WITHIN THE DEPARTMENT OF DEFENSE THESIS Presented to the Faculty Department of Systems and Engineering...KNOWLEDGE MANAGEMENT LEADERSHIP APPROACHES WITHIN THE DEPARTMENT OF DEFENSE Tommy V. S. Marshall II, BS Captain, USAF Approved

End user interface and knowledge base editing system of CSPAR: a knowledge-based consultation system for preventive maintenance in nuclear plants

International Nuclear Information System (INIS)

Sinohara, Yasusi; Terano, Takao; Nishiyama, Takuya

1988-01-01

Consultation System for Prevention of Abnormal-event Recurrence (CSPAR) is a knowledge-based system to analyze the same kind of events to a given fault reported on a nuclear power plant and to give users some informations for effective measures preventing them. This report discusses the interfaces of CSPAR for both end-users and knowledge-base editors. The interfaces are highly interactive and multi-window oriented. The features are as follows: (1) The end-user interfaces has Japanese language processing facility, which enables the users to consult CSPAR with various synonims and related terms for knowledge-base handling; (2) The knowledge-base editing system is used by knowledge-base editors for maintaining the knowledge on both plants' equipments and abnormal events sequences. It has facilities for easy maintenance of knowledge-bases, which includes a graphic oriented browser, a knowledge-base retriever, and a knowledge-base checker. (author)

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

Science.gov (United States)

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

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. 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. 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.

Knowledge of evidence-based dentistry among academic dental practitioners of Bhopal, India: a preliminary survey

Directory of Open Access Journals (Sweden)

Aishwarya Singh

2015-06-01

Full Text Available This study aimed to characterize the knowledge of evidence-based dentistry (EBD among dental faculty members in the city of Bhopal in central India. A cross-sectional questionnaire was administered at two dental colleges in Bhopal City. All dental faculty members who were present on the day of the study and who agreed to participate were included in the study. A total of 50 dental faculty members returned the questionnaire. Six Likert-type questions were asked, and the percentages of various responses were used for analysis. Sixteen faculty members (32.0% strongly agreed that EBD is a process of making decisions based on scientifically proven evidence. Fifteen faculty members (30.0% strongly disagreed or disagreed with the item stating that the best and quickest way to find evidence is by reading textbooks or asking experienced colleagues. Thirteen faculty members (26.0% strongly agreed that EBD allows dentists to improve their scientific knowledge and clinical skills. It is recommended that EBD be included in undergraduate and postgraduate curricula and in intensive continuing dental education programs that are conducted for dental faculty members.

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

Science.gov (United States)

1989-08-01

1757 I Sociopathic Knowledge Bases: Correct Knowledge Can Be Harmful Even Given Unlimited Computation DTIC5 by flELECTE 5David C. Wilkins and Yong...NUMBERSWOKNI PROGRAM RAT TSWOKUI 61153N RR04206 OC 443g-008 11 TITLE (Include Security Classification) Sociopathic Knowledge Bases: Correct Knowledge Can be...probabilistic rules are shown to be sociopathic and so this problem is very widespread. Sociopathicity has important consequences for rule induction

Theories of knowledge organization — theories of knowledge

DEFF Research Database (Denmark)

Hjørland, Birger

2013-01-01

more or less on specific epistemological ideals (e.g. empiricism, rationalism, historicism or pragmatism), the evaluation of classification includes the evaluation of the epistemological foundations of the research on which given classifications have been based. The field of knowledge organization...... itself is based on different approaches and traditions such as user-based and cognitive views, facet-analytical views, numeric taxonomic approaches, bibliometrics and domain-analytic approaches. These approaches and traditions are again connected to epistemological views, which have to be considered...

Management of knowledge across generations: preventing knowledge loss, enabling knowledge readiness

International Nuclear Information System (INIS)

Day, John A.

2012-01-01

J. Day argued that the preservation of records is a necessary, but not a sufficient condition to enable intelligent future decision making and management of nuclear waste. He distinguishes knowledge management from information management. Information without the potential to act on it is information for its own sake. He believes that knowledge will be a key factor for the generations that follow us. Records need knowledge, and knowledge needs records. A single representation of knowledge can be dangerous. Knowledge is multifaceted and complex, which necessitates a holistic approach. Throughout the presentation the concepts of 'knowledge readiness' and 'knowledge mothballing' (the process of knowing, forgetting and relearning) were proposed. Based on experiences at Sellafield the actions of knowledge audit mapping (including technical, societal and historical knowledge), knowledge loss risk assessing (although we would like to we cannot hold on to everything, and should thus take a risk approach, asking ourselves what is at stake if we delete certain parts of information), and knowledge retention for the long term management of a nuclear facility were presented. During the discussion, the link between knowledge and behaviour was raised. It was argued that the better informed people are, the less likely they are to make mistakes

Finding gene regulatory network candidates using the gene expression knowledge base.

Science.gov (United States)

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Integrating knowledge and control into hypermedia-based training environments: Experiments with HyperCLIPS

Science.gov (United States)

Hill, Randall W., Jr.

1990-01-01

The issues of knowledge representation and control in hypermedia-based training environments are discussed. The main objective is to integrate the flexible presentation capability of hypermedia with a knowledge-based approach to lesson discourse management. The instructional goals and their associated concepts are represented in a knowledge representation structure called a 'concept network'. Its functional usages are many: it is used to control the navigation through a presentation space, generate tests for student evaluation, and model the student. This architecture was implemented in HyperCLIPS, a hybrid system that creates a bridge between HyperCard, a popular hypertext-like system used for building user interfaces to data bases and other applications, and CLIPS, a highly portable government-owned expert system shell.

Health Care Leadership: Managing Knowledge Bases as Stakeholders.

Science.gov (United States)

Rotarius, Timothy

Communities are composed of many organizations. These organizations naturally form clusters based on common patterns of knowledge, skills, and abilities of the individual organizations. Each of these spontaneous clusters represents a distinct knowledge base. The health care knowledge base is shown to be the natural leader of any community. Using the Central Florida region's 5 knowledge bases as an example, each knowledge base is categorized as a distinct type of stakeholder, and then a specific stakeholder management strategy is discussed to facilitate managing both the cooperative potential and the threatening potential of each "knowledge base" stakeholder.

Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

Science.gov (United States)

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object

Passing Decisions in Football: Introducing an Empirical Approach to Estimating the Effects of Perceptual Information and Associative Knowledge.

Science.gov (United States)

Steiner, Silvan

2018-01-01

The importance of various information sources in decision-making in interactive team sports is debated. While some highlight the role of the perceptual information provided by the current game context, others point to the role of knowledge-based information that athletes have regarding their team environment. Recently, an integrative perspective considering the simultaneous involvement of both of these information sources in decision-making in interactive team sports has been presented. In a theoretical example concerning passing decisions, the simultaneous involvement of perceptual and knowledge-based information has been illustrated. However, no precast method of determining the contribution of these two information sources empirically has been provided. The aim of this article is to bridge this gap and present a statistical approach to estimating the effects of perceptual information and associative knowledge on passing decisions. To this end, a sample dataset of scenario-based passing decisions is analyzed. This article shows how the effects of perceivable team positionings and athletes' knowledge about their fellow team members on passing decisions can be estimated. Ways of transfering this approach to real-world situations and implications for future research using more representative designs are presented.

Passing Decisions in Football: Introducing an Empirical Approach to Estimating the Effects of Perceptual Information and Associative Knowledge

Directory of Open Access Journals (Sweden)

Silvan Steiner

2018-03-01

Full Text Available The importance of various information sources in decision-making in interactive team sports is debated. While some highlight the role of the perceptual information provided by the current game context, others point to the role of knowledge-based information that athletes have regarding their team environment. Recently, an integrative perspective considering the simultaneous involvement of both of these information sources in decision-making in interactive team sports has been presented. In a theoretical example concerning passing decisions, the simultaneous involvement of perceptual and knowledge-based information has been illustrated. However, no precast method of determining the contribution of these two information sources empirically has been provided. The aim of this article is to bridge this gap and present a statistical approach to estimating the effects of perceptual information and associative knowledge on passing decisions. To this end, a sample dataset of scenario-based passing decisions is analyzed. This article shows how the effects of perceivable team positionings and athletes' knowledge about their fellow team members on passing decisions can be estimated. Ways of transfering this approach to real-world situations and implications for future research using more representative designs are presented.

RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

Science.gov (United States)

Pan, Xiaoyong; Shen, Hong-Bin

2017-02-28

RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recognize the target RNAs and why they bind specific positions is still far from clear. Machine learning-based algorithms are widely acknowledged to be capable of speeding up this process. Although many automatic tools have been developed to predict the RNA-protein binding sites from the rapidly growing multi-resource data, e.g. sequence, structure, their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains. The other difficulty is how to interpret the prediction results. Existing approaches tend to terminate after outputting the potential discrete binding sites on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation. In viewing of these challenges, we propose a deep learning-based framework (iDeep) by using a novel hybrid convolutional neural network and deep belief network to predict the RBP interaction sites and motifs on RNAs. This new protocol is featured by transforming the original observed data into a high-level abstraction feature space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6

Wood constructions. Energy eficient, sustainable, practically proven; Holzbau Konstruktionen. Energieeffizient, nachhaltig, praxisgerecht

Energy Technology Data Exchange (ETDEWEB)

Lueckmann, Rudolf

2012-07-01

The book 'Wood constructions' provides standardized and practically proven designs, all necessary information on building physics, fire protection and additional specialized knowledge for energy efficient renovations and construction details in wood construction. The main topics of this book are: Fundamentals, timber-frame structures, wood preservation, thermal insulation, sound insulation, fire protection, energy-efficient timber buildings, timber construction systems, rehabilitation of timber structures, relevant regulations and standards.

Knowledge based Entrepreneurship

DEFF Research Database (Denmark)

Heebøll, John

This book is dedicated enterprising people with a technical or a scientific background who consider commercializing ideas and inventions within their field of expertise via a new business activity or a new company. It aims at distilling experiences from many successful and not so successful start......-up ventures from the Technical University of Denmark, 1988 – 2008 into practical, portable knowledge that can be used by future knowledge-based entrepreneurs to set up new companies efficiently or to stay away from it; to do what’s needed and avoid the pitfalls....

Automated Generation of OCL Constraints: NL based Approach vs Pattern Based Approach

Directory of Open Access Journals (Sweden)

IMRAN SARWAR BAJWA

2017-04-01

Full Text Available This paper presents an approach used for automated generations of software constraints. In this model, the SBVR (Semantics of Business Vocabulary and Rules based semi-formal representation is obtained from the syntactic and semantic analysis of a NL (Natural Language (such as English sentence. A SBVR representation is easy to translate to other formal languages as SBVR is based on higher-order logic like other formal languages such as OCL (Object Constraint Language. The proposed model endows with a systematic and powerful system of incorporating NL knowledge on the formal languages. A prototype is constructed in Java (an Eclipse plug-in as a proof of the concept. The performance was tested for a few sample texts taken from existing research thesis reports and books

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

Science.gov (United States)

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

Assessing the Dynamic Behavior of Online Q&A Knowledge Markets: A System Dynamics Approach

Science.gov (United States)

Jafari, Mostafa; Hesamamiri, Roozbeh; Sadjadi, Jafar; Bourouni, Atieh

2012-01-01

Purpose: The objective of this paper is to propose a holistic dynamic model for understanding the behavior of a complex and internet-based kind of knowledge market by considering both social and economic interactions. Design/methodology/approach: A system dynamics (SD) model is formulated in this study to investigate the dynamic characteristics of…

Cultural and Rhetorical Bases for communicating knowledge in web based communities

DEFF Research Database (Denmark)

Kampf, Constance; Kommers, Piet

2008-01-01

Cultural and Rhetorical Bases for communicating knowledge in web based communities How can we extend learner-centred theories for educational technology to include, for instance, the cultural and rhetorical backgrounds which influence participants in online communities as they engage in knowledge...... via web-based communities the intersection of culture and rhetoric in web-based communication rhetoric and discourse in the process of communicating knowledge via technology heuristics for knowledge communication from teaching in online forums connections between identity and knowledge communication...... This call for papers invites papers focused on theoretical frameworks or empirical research which highlights the cultural and/or rhetorical aspects of communicating knowledge in web based communities. We are looking for work that brings together methods and perspectives across disciplines...

Development of a component centered fault monitoring and diagnosis knowledge based system for space power system

Science.gov (United States)

Lee, S. C.; Lollar, Louis F.

1988-01-01

The overall approach currently being taken in the development of AMPERES (Autonomously Managed Power System Extendable Real-time Expert System), a knowledge-based expert system for fault monitoring and diagnosis of space power systems, is discussed. The system architecture, knowledge representation, and fault monitoring and diagnosis strategy are examined. A 'component-centered' approach developed in this project is described. Critical issues requiring further study are identified.

Knowledge management method for knowledge based BWR Core Operation Management System

Energy Technology Data Exchange (ETDEWEB)

Wada, Yutaka; Fukuzaki, Takaharu; Kobayashi, Yasuhiro

1989-03-01

A knowledge management method is proposed to support an except whose knowledge is stored in a knowledge base in the BWR Core Operation Management System. When the alterations in the operation plans are motivated by the expert after evaluating them, the method attempts to find the knowledge which must be modified and to give the expert guidances. In this way the resultant operation plans are improved by modifying values of referenced data. Using data dependency among data, which are defined and referred during inference, data to be modified are retrieved. In generating modification guidances, data reference and definition procedures are classified by syntactic analysis of knowledge. The modified data values are calculated with a sensitivity between the increment in the data to be modified and the resultant one in the performance of operation plans. The efficiency of the knowledge management by the proposed method, when applied to the knowledge based system including 500 pieces of knowledge for BWR control rod programming, is higher than that for interactive use of existing general purpose editors. (author).

Knowledge management method for knowledge based BWR Core Operation Management System

International Nuclear Information System (INIS)

Wada, Yutaka; Fukuzaki, Takaharu; Kobayashi, Yasuhiro

1989-01-01

A knowledge management method is proposed to support an except whose knowledge is stored in a knowledge base in the BWR Core Operation Management System. When the alterations in the operation plans are motivated by the expert after evaluating them, the method attempts to find the knowledge which must be modified and to give the expert guidances. In this way the resultant operation plans are improved by modifying values of referenced data. Using data dependency among data, which are defined and referred during inference, data to be modified are retrieved. In generating modification guidances, data reference and definition procedures are classified by syntactic analysis of knowledge. The modified data values are calculated with a sensitivity between the increment in the data to be modified and the resultant one in the performance of operation plans. The efficiency of the knowledge management by the proposed method, when applied to the knowledge based system including 500 pieces of knowledge for BWR control rod programming, is higher than that for interactive use of existing general purpose editors. (author)

Logical provenance in data-oriented workflows?

KAUST Repository

Ikeda, R.; Das Sarma, Akash; Widom, J.

2013-01-01

for general transformations, introducing the notions of correctness, precision, and minimality. We then determine when properties such as correctness and minimality carry over from the individual transformations' provenance to the workflow provenance. We

A Practical Approach to Constructing a Knowledge Graph for Cybersecurity

Directory of Open Access Journals (Sweden)

Yan Jia

2018-02-01

Full Text Available Cyberattack forms are complex and varied, and the detection and prediction of dynamic types of attack are always challenging tasks. Research on knowledge graphs is becoming increasingly mature in many fields. At present, it is very significant that certain scholars have combined the concept of the knowledge graph with cybersecurity in order to construct a cybersecurity knowledge base. This paper presents a cybersecurity knowledge base and deduction rules based on a quintuple model. Using machine learning, we extract entities and build ontology to obtain a cybersecurity knowledge base. New rules are then deduced by calculating formulas and using the path-ranking algorithm. The Stanford named entity recognizer (NER is also used to train an extractor to extract useful information. Experimental results show that the Stanford NER provides many features and the useGazettes parameter may be used to train a recognizer in the cybersecurity domain in preparation for future work. Keywords: Cybersecurity, Knowledge graph, Knowledge deduction

Intelligent Knowledge Recommendation Methods for R&D Knowledge Portals

Institute of Scientific and Technical Information of China (English)

KIM Jongwoo; LEE Hongjoo; PARK Sungjoo

2004-01-01

The personalization in knowledge portals and knowledge management systems is mainly performed based on users' explicitly specified categories and keywords. The explicit specification approach requires users' participation to start personalization services, and has limitation to adapt changes of users' preference. This paper suggests two implicit personalization approaches: automatic user category assignment method and automatic keyword profile generation method. The performances of the implicit personalization approaches are compared with traditional personalization approach using an Internet news site experiment. The result of the experiment shows that the suggested personalization approaches provide sufficient recommendation effectiveness with lessening users'unwanted involvement in personalization process.

Knowledge-based development in Singapore and Malaysia

OpenAIRE

Menkhoff, Thomas; Gerke, Solvay; Evers, Hans-Dieter; Chay, Yue Wah

2009-01-01

This paper addresses the question how knowledge is used to benefit the economic development of Singapore and Malaysia. Both countries have followed strict science policies to establish knowledge governance regimes for a knowledge-based economy. On the basis of empirical studies in both countries we show, how ethnic and religious diversity impact on the ability to develop an epistemic culture of knowledge sharing and ultimately an innovative knowledge-based economy.

Tracking and Establishing Provenance of Earth Science Datasets: A NASA-Based Example

Science.gov (United States)

Ramapriyan, Hampapuram K.; Goldstein, Justin C.; Hua, Hook; Wolfe, Robert E.

2016-01-01

Information quality is of paramount importance to science. Accurate, scientifically vetted and statistically meaningful and, ideally, reproducible information engenders scientific trust and research opportunities. Not surprisingly, federal bodies (e.g., NASA, NOAA, USGS) have very strictly affirmed the importance of information quality in their product requirements. So-called Highly Influential Scientific Assessments (HISA) such as The Third US National Climate Assessment (NCA3) published in 2014 undergo a very rigorous review process to ensure transparency and credibility. To support the transparency of such reports, the U.S. Global Change Research Program (USGCRP) has developed the Global Change Information System (GCIS). A recent activity was performed to trace the provenance as completely as possible for all NCA3 figures that were predominantly based on NASA data. This poster presents the mechanics of that project and the lessons learned from that activity.

Towards a National Innovation System in México Based on Knowledge

OpenAIRE

Helios Feria, Victor; Hidalgo Nuchera, Antonio

2008-01-01

In the last years, the research in diverse disciplines has increased the importance of innovation studies at the national level. In this sense, this paper proposes the development of National Innovation Systems (NIS) and its application to the economy in Mexico. Considering the characteristics and limitations of the study region, the mentioned proposal of NIS it is necessary to integrate the study of Knowledge-Based Economies (KBE) approach to study of the different approaches developed about...

Effect of web-based education on nursing students' urinary catheterization knowledge and skills.

Science.gov (United States)

Öztürk, Deniz; Dinç, Leyla

2014-05-01

Nursing is a practice-based discipline that requires the integration of theory and practice. Nurse educators must continuously revise educational curricula and incorporate information technology into the curriculum to provide students with the necessary knowledge and skills. The aim of this study was to assess the effect of web-based education on students' urinary catheterization knowledge and skills. A convenience sample of 111 first year nursing students enrolled at two universities in Ankara during the academic year of 2011-2012 participated in this quasi-experimental study. The experimental group (n=59) received a web-based and web-enhanced learning approach along with learning and practicing the required material twice as much as the control group, whereas the control group (n=52) received traditional classroom instruction. A knowledge test of 20 multiple-choice questions and a skills checklist were used to assess student performance. There was no difference between the experimental group and the control group in knowledge scores; however, students in the web-based group had higher scores for urinary catheterization skills. The highest scores in knowledge and skills were obtained by students who experienced web-based education as a supplement to tradition instruction. Web-based education had positive effects on the urinary catheterization skills of nursing students, and its positive effect increased for both knowledge and skills when it supplements classroom instruction. Based on these results, we suggest the use of web-based education as a supplement to traditional classroom instruction for nursing education. © 2013.

Towards an information extraction and knowledge formation framework based on Shannon entropy

Directory of Open Access Journals (Sweden)

Iliescu Dragoș

2017-01-01

Full Text Available Information quantity subject is approached in this paperwork, considering the specific domain of nonconforming product management as information source. This work represents a case study. Raw data were gathered from a heavy industrial works company, information extraction and knowledge formation being considered herein. Involved method for information quantity estimation is based on Shannon entropy formula. Information and entropy spectrum are decomposed and analysed for extraction of specific information and knowledge-that formation. The result of the entropy analysis point out the information needed to be acquired by the involved organisation, this being presented as a specific knowledge type.

A Road Map for Knowledge Management Systems Design Using Axiomatic Design Approach

Directory of Open Access Journals (Sweden)

Houshmand Mahmoud

2017-01-01

Full Text Available Successful design and implementation of knowledge management systems have been the main concern of many researchers. It has been reported that more than 50% of knowledge management systems have failed, therefore, it is required to seek for a new and comprehensive scientific approach to design and implement it. In the design and implementation of a knowledge management system, it is required to know ’what we want to achieve’ and ’how and by what processes we will achieve it’. A literature review conducted and axiomatic design theory selected for this purpose. For the first time, this paper develops a conceptual design of knowledge management systems by means of a hierarchical structure, composed of ’Functional Requirements’ (FRs, ’Design Parameters’ (DPs, and ’Process Variables’ (PVs. The intersection of several studies conducted in the field of knowledge management systems has been used to design the knowledge management model. It reveals that six essential bases of knowledge management are organizational culture, organizational structure, human resources, management and leadership, information technology, and the external environment of the organization; that are represented as top DPs in the structure of the model. These essential factors are decomposed to lower levels by means of zigzagging. The model implemented in Tehran Urban and Suburban Railway Operation Corporation (TUSROC and the results were very promising. The most important result of this study is a roadmap to design successful and efficient knowledge management systems.

Exploiting Expert Knowledge to Enhance Simulation-based Optimization of Environmental Remediation Systems

Science.gov (United States)

Reslink, C. F.; Matott, L. S.

2012-12-01

Designing cost-effective systems to safeguard national water supplies from contaminated sites is often aided by simulation-based optimization - where a flow or transport model is linked with an "off-the-shelf" global optimization search algorithm. However, achieving good performance from these types of optimizers within a reasonable computational budget has proven to be difficult. Therefore, this research seeks to boost optimization efficiency by augmenting search procedures with non-traditional information, such as site-specific knowledge and practitioner rules-of-thumb. An example application involving pump-and-treat optimization is presented in which a series of extraction wells are to be installed to intercept pollutants at a contaminated site in Billings, Montana. Selected heuristic algorithms (e.g. Genetic Algorithm) are interfaced with a rules engine that makes inline adjustments to the well locations of candidate pump-and-treat designs. If necessary, the rules engine modifies a given pump-and-treat design so that: (1) wells are placed within plume boundaries; and (2) well placement is biased toward areas where, if left untreated, the plume is predicted to spread most rapidly. Results suggest that incorporating this kind of expert knowledge can significantly increase the search efficiency of many popular global optimizers.

Patient Safety Based Knowledge Management SECI to Improve Nusrsing Students Competency

Directory of Open Access Journals (Sweden)

Joanggi Wiriatarina Harianto

2015-10-01

Full Text Available Introduction: Patient safety is an important component of health services quality,and  basic principles of patient care. Nursing students also have a great potential to make an action that could endanger the patient, because hospital is one of student practice area. The purpose of this study was to improve the nursing students competency in patient safety by using knowledge management SECI approached. Method: The study used exploratory survey, and quasy experiment. The samples were some of nursing students of STIKes Muhammadiyah Samarinda who were on internship programme that selected using simple random sampling technique, in total of 54 students. This research’s variables were the knowledge management SECI based-patient safety and nursing student’s competency. The data were collected by using questionnaires and observation. The data were analyze by using Partial Least Square (PLS. Result: The result showed that there were significant influence the implementation of a model patient safety based knowledge management seci on increased competence nursing students. Discussion: Improved student competency in patient safety using SECI knowledge management was carried out in four phases, that is Socialization, Externalization, Combination, and Internalization. The result was a new knowledge related to patient safety that able to improve the student’s competency.. Keywords: Patient safety, Knowledge management, SECI, competency

Provenance trials of larch in Siberia

Energy Technology Data Exchange (ETDEWEB)

Milyutin, L.I. [V.N. Sukachev Inst. of Forest SB RAS, Krasnoyarsk (Russian Federation)

1995-12-31

Some results of provenance trials of larch in Siberia are given. These provenance trials were established in the last thirty years by efforts of V.N. Sukaczev Inst. of Forest. Provenances and species of larch were tested in some field trials distributed over Siberia between Lat. N 52 deg and 66 deg, Long. E 88 deg and 113 deg: near Krasnoyarsk, in Republic Khakasia (an altitudes of 800 and 1200 metres), in the Lower Yenisei near Turukhansk, in the west and south regions of Krasnoyarsk territory, in the Upper Lena, near Chita. 2 refs

Archives and societal provenance Australian essays

CERN Document Server

Piggott, Michael

2012-01-01

Records and archival arrangements in Australia are globally relevant because Australia's indigenous people represent the oldest living culture in the world, and because modern Australia is an ex-colonial society now heavily multicultural in outlook. Archives and Societal Provenance explores this distinctiveness using the theoretical concept of societal provenance as propounded by Canadian archival scholars led by Dr Tom Nesmith. The book's seventeen essays blend new writing and re-workings of earlier work, comprising the fi rst text to apply a societal provenance perspective to a national sett

Provenance trials of larch in Siberia

Energy Technology Data Exchange (ETDEWEB)

Milyutin, L I [V.N. Sukachev Inst. of Forest SB RAS, Krasnoyarsk (Russian Federation)

1996-12-31

Some results of provenance trials of larch in Siberia are given. These provenance trials were established in the last thirty years by efforts of V.N. Sukaczev Inst. of Forest. Provenances and species of larch were tested in some field trials distributed over Siberia between Lat. N 52 deg and 66 deg, Long. E 88 deg and 113 deg: near Krasnoyarsk, in Republic Khakasia (an altitudes of 800 and 1200 metres), in the Lower Yenisei near Turukhansk, in the west and south regions of Krasnoyarsk territory, in the Upper Lena, near Chita. 2 refs

Supporting Knowledge Transfer through Decomposable Reasoning Artifacts

Energy Technology Data Exchange (ETDEWEB)

Pike, William A.; May, Richard A.; Turner, Alan E.

2007-01-03

Technology to support knowledge transfer and cooperative inquiry must offer its users the ability to effectively interpret knowledge structures produced by collaborators. Communicating the reasoning processes that underlie a finding is one method for enhancing interpretation, and can result in more effective evaluation and application of shared knowledge. In knowledge management tools, interpretation is aided by creating knowledge artifacts that can expose their provenance to scrutiny and that can be transformed into diverse representations that suit their consumers’ perspectives and preferences. We outline the information management needs of inquiring communities characterized by hypothesis generation tasks, and propose a model for communication, based in theories of hermeneutics, semiotics, and abduction, in which knowledge structures can be decomposed into the lower-level reasoning artifacts that produced them. We then present a proof-of-concept implementation for an environment to support the capture and communication of analytic products, with emphasis on the domain of intelligence analysis.

Interorganizational Knowledge Division Decision Model Based on Cooperative Innovation of Supply Chain System

Directory of Open Access Journals (Sweden)

Wei Zhang

2014-01-01

Full Text Available Within interorganizational cooperative innovation of construction supply chain system, the achievement of project value-adding could be reflected by several factors, such as project-based organizational effect level, and the relationship between project cooperative innovation objectives. In this paper, based on the assumption of equal cooperation between project-based organizations, we selected the knowledge cooperation between the owner and contractor in construction supply chain system as research object. From the perspective of maximizing project value-adding and the relationship of effort cost between knowledge input and innovation stage in consideration, we established the knowledge collaborative incentive model for interorganizational cooperative innovation of construction supply chain system and proposed the first-order and second-order approaches. Then we conducted the digital simulation and example analysis, its results showed that if the owner has the capability to achieve project value-adding in knowledge cooperation, he would adopt a part commissioned way. Otherwise, a fully commissioned way would be better.

An "Evidence-Based" Professional Development Program for Physics Teachers Focusing on Knowledge Integration

Science.gov (United States)

Berger, Hana

This dissertation is concerned with the design and study of an evidence-based approach to the professional development of high-school physics teachers responding to the need to develop effective continuing professional development programs (CPD) in domains that require genuine changes in teachers' views, knowledge, and practice. The goals of the thesis were to design an evidence-based model for the CPD program, to implement it with teachers, and to study its influence on teachers' knowledge, views, and practice, as well as its impact on students' learning. The program was developed in three consecutive versions: a pilot, first, and second versions. Based on the pilot version (that was not part of this study), we developed the first version of the program in which we studied difficulties in employing the evidence-based and blended-learning approaches. According to our findings, we modified the strategies for enacting these approaches in the second version of the program. The influence of the program on the teachers and students was studied during the enactment of the second version of the program. The model implemented in the second version of the program was characterized by four main design principles: 1. The KI and evidence aspects are acquired simultaneously in an integrated manner. 2. The guidance of the teachers follows the principles of cognitive apprenticeship both in the evidence and the KI aspects. 3. The teachers experience the innovative activities as learners. 4. The program promotes continuity of teachers' learning through a structured "blended learning" approach. The results of our study show that this version of the program achieved its goals; throughout the program the teachers progressed in their knowledge, views, and practice concerning the knowledge integration, and in the evidence and learner-centered aspects. The results also indicated that students improved their knowledge of physics and knowledge integration skills that were developed

Learning about knowledge: A complex network approach

International Nuclear Information System (INIS)

Fontoura Costa, Luciano da

2006-01-01

An approach to modeling knowledge acquisition in terms of walks along complex networks is described. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks--i.e., networks composed of successive interconnected layers--are related to compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks--i.e., unreachable nodes--the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barabasi-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaus of knowledge stagnation in the case of the preferential movement strategy in the presence of conditional edges

Co-production of knowledge: An Inuit Indigenous Knowledge perspective

Science.gov (United States)

Daniel, R.; Behe, C.

2017-12-01

A "co-production of knowledge" approach brings together different knowledge systems while building equitable and collaborative partnerships from `different ways of knowing.' Inuit Indigenous Knowledge is a systematic way of thinking applied to phenomena across biological, physical, cultural and spiritual systems; rooted with a holistic understanding of ecosystems (ICC Alaska 2016). A holistic image of Arctic environmental change is attained by bringing Indigenous Knowledge (IK) holders and scientists together through a co-production of knowledge framework. Experts from IK and science should be involved together from the inception of a project. IK should be respected as its own knowledge system and should not be translated into science. A co-production of knowledge approach is important in developing adaptation policies and practices, for sustainability and to address biodiversity conservation (Daniel et al. 2016). Co-production of knowledge is increasingly being recognized by the scientific community at-large. However, in many instances the concept is being incorrectly applied. This talk will build on the important components of co-production of knowledge from an Inuit perspective and specifically IK. In this presentation we will differentiate the co-production of knowledge from a multi-disciplinary approach or multi-evidence based decision-making. We underscore the role and value of different knowledge systems with different methodologies and the need for collaborative approaches in identifying research questions. We will also provide examples from our experiences with Indigenous communities and scientists in the Arctic. References: Inuit Circumpolar Council of Alaska. 2016. Alaskan Inuit Food Security Conceptual Framework: How to Assess the Arctic From An Inuit Perspective, 201pp. Daniel, R., C. Behe, J. Raymond-Yakoubian, E. Krummel, and S. Gearhead. Arctic Observing Summit White Paper Synthesis, Theme 6: Interfacing Indigenous Knowledge, Community-based

Consultancy on 'IAEA initiative to establish a fast reactor knowledge base'. Working material

International Nuclear Information System (INIS)

2005-01-01

At the outset of the meeting, Member States interest in establishing Fast Reactor Knowledge Base was acknowledged by the participants. While the broader objective of the initiative was to develop a Knowledge Base into which the existing Knowledge Preservation Systems will fit, the specific objectives of the meeting were: Make recommendations on FRKP methodology and guidance, Review the proposed structure of the Agency's FRKP Initiative, Make recommendations on the role of the Agency and the Member States implementing the Agency's FRKP Initiative, Develop an approach for the implementation of the structure of the Agency's RFKP Initiative. The meeting concluded covering many aspects of the initiative namely systematic method of data capturing, structuring and functions of FRKP System etc. and placed a strong emphasis on the continues role of IAEA's support and coordination in the data retrieval and knowledge preservation efforts