The Knowledge-Based Software Assistant: Beyond CASE

NASA Technical Reports Server (NTRS)

Carozzoni, Joseph A.

1993-01-01

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

Learning Machine, Vietnamese Based Human-Computer Interface.

ERIC Educational Resources Information Center

Northwest Regional Educational Lab., Portland, OR.

The sixth session of IT@EDU98 consisted of seven papers on the topic of the learning machine--Vietnamese based human-computer interface, and was chaired by Phan Viet Hoang (Informatics College, Singapore). "Knowledge Based Approach for English Vietnamese Machine Translation" (Hoang Kiem, Dinh Dien) presents the knowledge base approach,…

Computational neuroanatomy: ontology-based representation of neural components and connectivity.

PubMed

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-02-05

A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

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

ERIC Educational Resources Information Center

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…

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

ERIC Educational Resources Information Center

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…

Adaptive Knowledge Management of Project-Based Learning

ERIC Educational Resources Information Center

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

ERIC Educational Resources Information Center

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…

Charting Collective Knowledge: Supporting Self-Regulated Learning in the Workplace

ERIC Educational Resources Information Center

Littlejohn, Allison; Milligan, Colin; Margaryan, Anoush

2012-01-01

Purpose: This study aims to outline an approach to improving the effectiveness of work-based learning through knowledge creation and enhancing self-regulated learning. The paper presents a case example of a novel approach to learning through knowledge creation in the workplace. This case example is based on empirical data collected through a study…

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

ERIC Educational Resources Information Center

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…

Using the Knowledge Transfer Partnership Approach in Undergraduate Education and Practice-Based Training to Encourage Employer Engagement

ERIC Educational Resources Information Center

Harris, Margaret; Chisholm, Colin; Burns, George

2013-01-01

Purpose: The purpose of this paper is to provide a conceptual viewpoint which proposes the use of the post graduate Knowledge Transfer Partnership (KTP) approach to learning in undergraduate education and practice-based training. Design/methodology/approach: This is an examination of the KTP approach and how this could be used effectively in…

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

PubMed

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.

Three Metacognitive Approaches to Training Pre-Service Teachers in Different Learning Phases of Technological Pedagogical Content Knowledge

ERIC Educational Resources Information Center

Kramarski, Bracha; Michalsky, Tova

2009-01-01

Our study investigated 3 metacognitive approaches provided during different phases of learning technological pedagogical content knowledge (TPCK) in a Web-based learning environment. These metacognitive approaches were based on self-question prompts (Kramarski & Mevarech, 2003) which appeared in pop-up screens and fostered the Self-Regulated…

Conceptual information processing: A robust approach to KBS-DBMS integration

NASA Technical Reports Server (NTRS)

Lazzara, Allen V.; Tepfenhart, William; White, Richard C.; Liuzzi, Raymond

1987-01-01

Integrating the respective functionality and architectural features of knowledge base and data base management systems is a topic of considerable interest. Several aspects of this topic and associated issues are addressed. The significance of integration and the problems associated with accomplishing that integration are discussed. The shortcomings of current approaches to integration and the need to fuse the capabilities of both knowledge base and data base management systems motivates the investigation of information processing paradigms. One such paradigm is concept based processing, i.e., processing based on concepts and conceptual relations. An approach to robust knowledge and data base system integration is discussed by addressing progress made in the development of an experimental model for conceptual information processing.

PSYCHE: An Object-Oriented Approach to Simulating Medical Education

PubMed Central

Mullen, Jamie A.

1990-01-01

Traditional approaches to computer-assisted instruction (CAI) do not provide realistic simulations of medical education, in part because they do not utilize heterogeneous knowledge bases for their source of domain knowledge. PSYCHE, a CAI program designed to teach hypothetico-deductive psychiatric decision-making to medical students, uses an object-oriented implementation of an intelligent tutoring system (ITS) to model the student, domain expert, and tutor. It models the transactions between the participants in complex transaction chains, and uses heterogeneous knowledge bases to represent both domain and procedural knowledge in clinical medicine. This object-oriented approach is a flexible and dynamic approach to modeling, and represents a potentially valuable tool for the investigation of medical education and decision-making.

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

PubMed Central

Barriga, Rosa Maria

1988-01-01

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

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

PubMed

Mrabet, Yassine; Kilicoglu, Halil; Roberts, Kirk; Demner-Fushman, Dina

2016-01-01

Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases. In the first step of our method, we recognize named entities in consumer health questions using an unsupervised method that relies on a biomedical knowledge base, UMLS, and an open-domain knowledge base, DBpedia. In the next step, we cast topic recognition as a binary classification problem of deciding whether a named entity is the question topic or not. We evaluated our approach on a dataset from the National Library of Medicine (NLM), introduced in this paper, and another from the Genetic and Rare Disease Information Center (GARD). The combination of knowledge bases outperformed the results obtained by individual knowledge bases by up to 16.5% F1 and achieved state-of-the-art performance. Our results demonstrate that combining open-domain knowledge bases with biomedical knowledge bases can lead to a substantial improvement in understanding user-generated health content.

Automated knowledge base development from CAD/CAE databases

NASA Technical Reports Server (NTRS)

Wright, R. Glenn; Blanchard, Mary

1988-01-01

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

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

ERIC Educational Resources Information Center

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…

Knowledge-Based Runway Assignment for Arrival Aircraft in the Terminal Area

DOT National Transportation Integrated Search

1997-01-01

A knowledge-based system for scheduling arrival traffic in the terminal area, : referred to as the Final Approach Spacing Tool (FAST), has been implemented and : operationally tested at the Dallas/Fort Worth Terminal Radar Approach Control : (TRACON)...

Computational neuroanatomy: ontology-based representation of neural components and connectivity

PubMed Central

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-01-01

Background A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. Results We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Conclusion Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future. PMID:19208191

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2014-01-01

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

Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Baichuan; Choudhury, Sutanay; Al-Hasan, Mohammad

2016-02-01

Estimating the confidence for a link is a critical task for Knowledge Graph construction. Link prediction, or predicting the likelihood of a link in a knowledge graph based on prior state is a key research direction within this area. We propose a Latent Feature Embedding based link recommendation model for prediction task and utilize Bayesian Personalized Ranking based optimization technique for learning models for each predicate. Experimental results on large-scale knowledge bases such as YAGO2 show that our approach achieves substantially higher performance than several state-of-art approaches. Furthermore, we also study the performance of the link prediction algorithm in termsmore » of topological properties of the Knowledge Graph and present a linear regression model to reason about its expected level of accuracy.« less

Relating GTE and Knowledge-Based Courseware Engineering: Some Epistemological Issues.

ERIC Educational Resources Information Center

De Diana, Italo P. F.; Ladhani, Al-Noor

1998-01-01

Discusses GTE (Generic Tutoring Environment) and knowledge-based courseware engineering from an epistemological point of view and suggests some combination of the two approaches. Topics include intelligent tutoring; courseware authoring; application versus acquisition of knowledge; and domain knowledge. (LRW)

Sustaining Knowledge Building as a Principle-Based Innovation at an Elementary School

ERIC Educational Resources Information Center

Zhang, Jianwei; Hong, Huang-Yao; Scardamalia, Marlene; Teo, Chew Lee; Morley, Elizabeth A.

2011-01-01

This study explores Knowledge Building as a principle-based innovation at an elementary school and makes a case for a principle- versus procedure-based approach to educational innovation, supported by new knowledge media. Thirty-nine Knowledge Building initiatives, each focused on a curriculum theme and facilitated by nine teachers over eight…

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

NASA Astrophysics Data System (ADS)

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.

A knowledge engineering framework towards clinical support for adverse drug event prevention: the PSIP approach.

PubMed

Koutkias, Vassilis; Stalidis, George; Chouvarda, Ioanna; Lazou, Katerina; Kilintzis, Vassilis; Maglaveras, Nicos

2009-01-01

Adverse Drug Events (ADEs) are currently considered as a major public health issue, endangering patients' safety and causing significant healthcare costs. Several research efforts are currently concentrating on the reduction of preventable ADEs by employing Information Technology (IT) solutions, which aim to provide healthcare professionals and patients with relevant knowledge and decision support tools. In this context, we present a knowledge engineering approach towards the construction of a Knowledge-based System (KBS) regarded as the core part of a CDSS (Clinical Decision Support System) for ADE prevention, all developed in the context of the EU-funded research project PSIP (Patient Safety through Intelligent Procedures in Medication). In the current paper, we present the knowledge sources considered in PSIP and the implications they pose to knowledge engineering, the methodological approach followed, as well as the components defining the knowledge engineering framework based on relevant state-of-the-art technologies and representation formalisms.

Enhancing Learning Outcomes with an Interactive Knowledge-Based Learning Environment Providing Narrative Feedback

ERIC Educational Resources Information Center

Stranieri, Andrew; Yearwood, John

2008-01-01

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

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

ERIC Educational Resources Information Center

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…

A Knowledge Based Approach to VLSI CAD

DTIC Science & Technology

1983-09-01

Avail-and/or Dist ISpecial L| OI. SEICURITY CLASIIrCATION OP THIS IPA.lErllm S Daene." A KNOwLEDE BASED APPROACH TO VLSI CAD’ Louis L Steinberg and...major issues lies in building up and managing the knowledge base of oesign expertise. We expect that, as with many recent expert systems, in order to

A Computer-Based Approach for Deriving and Measuring Individual and Team Knowledge Structure from Essay Questions

ERIC Educational Resources Information Center

Clariana, Roy B.; Wallace, Patricia

2007-01-01

This proof-of-concept investigation describes a computer-based approach for deriving the knowledge structure of individuals and of groups from their written essays, and considers the convergent criterion-related validity of the computer-based scores relative to human rater essay scores and multiple-choice test scores. After completing a…

Some requirements and suggestions for a methodology to develop knowledge based systems.

PubMed

Green, D W; Colbert, M; Long, J

1989-11-01

This paper describes an approach to the creation of a methodology for the development of knowledge based systems. It specifies some requirements and suggests how these requirements might be met. General requirements can be satisfied using a systems approach. More specific ones can be met by viewing an organization as a network of consultations for coordinating expertise. The nature of consultations is described and the form of a possible cognitive model using a blackboard architecture is outlined. The value of the approach is illustrated in terms of certain knowledge elicitation methods.

Distributed, cooperating knowledge-based systems

NASA Technical Reports Server (NTRS)

Truszkowski, Walt

1991-01-01

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

Knowledge Resources - A Knowledge Management Approach for Digital Ecosystems

NASA Astrophysics Data System (ADS)

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.

Engineering Knowledge for Assistive Living

NASA Astrophysics Data System (ADS)

Chen, Liming; Nugent, Chris

This paper introduces a knowledge based approach to assistive living in smart homes. It proposes a system architecture that makes use of knowledge in the lifecycle of assistive living. The paper describes ontology based knowledge engineering practices and discusses mechanisms for exploiting knowledge for activity recognition and assistance. It presents system implementation and experiments, and discusses initial results.

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

PubMed

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.

Knowledge-intensive software design systems: Can too much knowledge be a burden?

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1992-01-01

While acknowledging the considerable benefits of domain-specific, knowledge-intensive approaches to automated software engineering, it is prudent to carefully examine the costs of such approaches, as well. In adding domain knowledge to a system, a developer makes a commitment to understanding, representing, maintaining, and communicating that knowledge. This substantial overhead is not generally associated with domain-independent approaches. In this paper, I examine the downside of incorporating additional knowledge, and illustrate with examples based on our experience in building the SIGMA system. I also offer some guidelines for developers building domain-specific systems.

Knowledge-intensive software design systems: Can too much knowledge be a burden?

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1992-01-01

While acknowledging the considerable benefits of domain-specific, knowledge-intensive approaches to automated software engineering, it is prudent to carefully examine the costs of such approaches, as well. In adding domain knowledge to a system, a developer makes a commitment to understanding, representing, maintaining, and communicating that knowledge. This substantial overhead is not generally associated with domain-independent approaches. In this paper, I examine the downside of incorporating additional knowledge, and illustrate with examples based on our experiences building the SIGMA system. I also offer some guidelines for developers building domain-specific systems.

An approach to combining heuristic and qualitative reasoning in an expert system

NASA Technical Reports Server (NTRS)

Jiang, Wei-Si; Han, Chia Yung; Tsai, Lian Cheng; Wee, William G.

1988-01-01

An approach to combining the heuristic reasoning from shallow knowledge and the qualitative reasoning from deep knowledge is described. The shallow knowledge is represented in production rules and under the direct control of the inference engine. The deep knowledge is represented in frames, which may be put in a relational DataBase Management System. This approach takes advantage of both reasoning schemes and results in improved efficiency as well as expanded problem solving ability.

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

Discusses knowledge-based decision-support systems that use artificial intelligence approaches. Addresses the issue of how to create an effective case-based reasoning system for complex and evolving domains, focusing on automated methods for system optimization and domain knowledge evolution that can supplement knowledge acquired from domain…

COM3/369: Knowledge-based Information Systems: A new approach for the representation and retrieval of medical information

PubMed Central

Mann, G; Birkmann, C; Schmidt, T; Schaeffler, V

1999-01-01

Introduction Present solutions for the representation and retrieval of medical information from online sources are not very satisfying. Either the retrieval process lacks of precision and completeness the representation does not support the update and maintenance of the represented information. Most efforts are currently put into improving the combination of search engines and HTML based documents. However, due to the current shortcomings of methods for natural language understanding there are clear limitations to this approach. Furthermore, this approach does not solve the maintenance problem. At least medical information exceeding a certain complexity seems to afford approaches that rely on structured knowledge representation and corresponding retrieval mechanisms. Methods Knowledge-based information systems are based on the following fundamental ideas. The representation of information is based on ontologies that define the structure of the domain's concepts and their relations. Views on domain models are defined and represented as retrieval schemata. Retrieval schemata can be interpreted as canonical query types focussing on specific aspects of the provided information (e.g. diagnosis or therapy centred views). Based on these retrieval schemata it can be decided which parts of the information in the domain model must be represented explicitly and formalised to support the retrieval process. As representation language propositional logic is used. All other information can be represented in a structured but informal way using text, images etc. Layout schemata are used to assign layout information to retrieved domain concepts. Depending on the target environment HTML or XML can be used. Results Based on this approach two knowledge-based information systems have been developed. The 'Ophthalmologic Knowledge-based Information System for Diabetic Retinopathy' (OKIS-DR) provides information on diagnoses, findings, examinations, guidelines, and reference images related to diabetic retinopathy. OKIS-DR uses combinations of findings to specify the information that must be retrieved. The second system focuses on nutrition related allergies and intolerances. Information on allergies and intolerances of a patient are used to retrieve general information on the specified combination of allergies and intolerances. As a special feature the system generates tables showing food types and products that are tolerated or not tolerated by patients. Evaluation by external experts and user groups showed that the described approach of knowledge-based information systems increases the precision and completeness of knowledge retrieval. Due to the structured and non-redundant representation of information the maintenance and update of the information can be simplified. Both systems are available as WWW based online knowledge bases and CD-ROMs (cf. http://mta.gsf.de topic: products).

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

NASA Technical Reports Server (NTRS)

Rahimian, Eric N.; Graves, Sara J.

1988-01-01

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

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

NASA Technical Reports Server (NTRS)

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.

Multi-viewpoint clustering analysis

NASA Technical Reports Server (NTRS)

Mehrotra, Mala; Wild, Chris

1993-01-01

In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems.

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

ERIC Educational Resources Information Center

Vickers, Joan N.; Gaines, Brian R.

1988-01-01

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

A knowledge engineering approach to recognizing and extracting sequences of nucleic acids from scientific literature.

PubMed

García-Remesal, Miguel; Maojo, Victor; Crespo, José

2010-01-01

In this paper we present a knowledge engineering approach to automatically recognize and extract genetic sequences from scientific articles. To carry out this task, we use a preliminary recognizer based on a finite state machine to extract all candidate DNA/RNA sequences. The latter are then fed into a knowledge-based system that automatically discards false positives and refines noisy and incorrectly merged sequences. We created the knowledge base by manually analyzing different manuscripts containing genetic sequences. Our approach was evaluated using a test set of 211 full-text articles in PDF format containing 3134 genetic sequences. For such set, we achieved 87.76% precision and 97.70% recall respectively. This method can facilitate different research tasks. These include text mining, information extraction, and information retrieval research dealing with large collections of documents containing genetic sequences.

A formal approach to validation and verification for knowledge-based control systems

NASA Technical Reports Server (NTRS)

Castore, Glen

1987-01-01

As control systems become more complex in response to desires for greater system flexibility, performance and reliability, the promise is held out that artificial intelligence might provide the means for building such systems. An obstacle to the use of symbolic processing constructs in this domain is the need for verification and validation (V and V) of the systems. Techniques currently in use do not seem appropriate for knowledge-based software. An outline of a formal approach to V and V for knowledge-based control systems is presented.

Enhancing Users' Participation in Business Process Modeling through Ontology-Based Training

NASA Astrophysics Data System (ADS)

Macris, A.; Malamateniou, F.; Vassilacopoulos, G.

Successful business process design requires active participation of users who are familiar with organizational activities and business process modelling concepts. Hence, there is a need to provide users with reusable, flexible, agile and adaptable training material in order to enable them instil their knowledge and expertise in business process design and automation activities. Knowledge reusability is of paramount importance in designing training material on process modelling since it enables users participate actively in process design/redesign activities stimulated by the changing business environment. This paper presents a prototype approach for the design and use of training material that provides significant advantages to both the designer (knowledge - content reusability and semantic web enabling) and the user (semantic search, knowledge navigation and knowledge dissemination). The approach is based on externalizing domain knowledge in the form of ontology-based knowledge networks (i.e. training scenarios serving specific training needs) so that it is made reusable.

Knowledge acquisition and representation using fuzzy evidential reasoning and dynamic adaptive fuzzy Petri nets.

PubMed

Liu, Hu-Chen; Liu, Long; Lin, Qing-Lian; Liu, Nan

2013-06-01

The two most important issues of expert systems are the acquisition of domain experts' professional knowledge and the representation and reasoning of the knowledge rules that have been identified. First, during expert knowledge acquisition processes, the domain expert panel often demonstrates different experience and knowledge from one another and produces different types of knowledge information such as complete and incomplete, precise and imprecise, and known and unknown because of its cross-functional and multidisciplinary nature. Second, as a promising tool for knowledge representation and reasoning, fuzzy Petri nets (FPNs) still suffer a couple of deficiencies. The parameters in current FPN models could not accurately represent the increasingly complex knowledge-based systems, and the rules in most existing knowledge inference frameworks could not be dynamically adjustable according to propositions' variation as human cognition and thinking. In this paper, we present a knowledge acquisition and representation approach using the fuzzy evidential reasoning approach and dynamic adaptive FPNs to solve the problems mentioned above. As is illustrated by the numerical example, the proposed approach can well capture experts' diversity experience, enhance the knowledge representation power, and reason the rule-based knowledge more intelligently.

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

PubMed

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%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

A proven knowledge-based approach to prioritizing process information

NASA Technical Reports Server (NTRS)

Corsberg, Daniel R.

1991-01-01

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

PLAN-IT: Knowledge-Based Mission Sequencing

NASA Astrophysics Data System (ADS)

Biefeld, Eric W.

1987-02-01

Mission sequencing consumes a large amount of time and manpower during a space exploration effort. Plan-It is a knowledge-based approach to assist in mission sequencing. Plan-It uses a combined frame and blackboard architecture. This paper reports on the approach implemented by Plan-It and the current applications of Plan-It for sequencing at NASA.

Strategies and Resources for Contextualising the Curriculum Based on the Funds of Knowledge Approach: A Literature Review

ERIC Educational Resources Information Center

Llopart, Mariona; Esteban-Guitart, Moisès

2017-01-01

This article aims to describe and illustrate how the curriculum can be contextualised through different educational experiences based on the funds of knowledge approach. Educational contextualisation is understood to be the linking of curricular content (literacy, science, mathematics, social sciences) with students' lives, including prior…

Guided Work-Based Learning: Sharing Practical Teaching Knowledge with Student Teachers

ERIC Educational Resources Information Center

van Velzen, Corinne; Volman, Monique; Brekelmans, Mieke; White, Simone

2012-01-01

Building quality work-based learning opportunities for student teachers is a challenge for schools in school-university partnerships. This study focused on the guidance of student teachers by means of a mentoring approach aimed at sharing practical knowledge, with student teachers' learning needs as an emphasis. The approach was built on…

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

A knowledge-driven approach to cluster validity assessment.

PubMed

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.

Knowledge-based diagnosis for aerospace systems

NASA Technical Reports Server (NTRS)

Atkinson, David J.

1988-01-01

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

A knowledge-based machine vision system for space station automation

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Does an outcome-based approach to continuing medical education improve physicians' competences in rational prescribing?

PubMed

Esmaily, Hamideh M; Savage, Carl; Vahidi, Rezagoli; Amini, Abolghasem; Dastgiri, Saeed; Hult, Hakan; Dahlgren, Lars Owe; Wahlstrom, Rolf

2009-11-01

Continuing medical education (CME) is compulsory in Iran, and traditionally it is lecture-based, which is mostly not successful. Outcome-based education has been proposed for CME programs. To evaluate the effectiveness of an outcome-based educational intervention with a new approach based on outcomes and aligned teaching methods, on knowledge and skills of general physicians (GPs) working in primary care compared with a concurrent CME program in the field of "Rational prescribing". The method used was cluster randomized controlled design. All GPs working in six cities in one province in Iran were invited to participate. The cities were matched and randomly divided into an intervention arm for education on rational prescribing with an outcome-based approach, and a control arm for a traditional program on the same topic. Knowledge and skills were assessed using a pre- and post-test, including case scenarios. In total, 112 GPs participated. There were significant improvements in knowledge and prescribing skills after the training in the intervention arm as well as in comparison with the changes in the control arm. The overall intervention effect was 26 percentage units. The introduction of an outcome-based approach in CME appears to be effective when creating programs to improve GPs' knowledge and skills.

Using knowledge brokering to promote evidence-based policy-making: The need for support structures.

PubMed Central

van Kammen, Jessika; de Savigny, Don; Sewankambo, Nelson

2006-01-01

Knowledge brokering is a promising strategy to close the "know-do gap" and foster greater use of research findings and evidence in policy-making. It focuses on organizing the interactive process between the producers and users of knowledge so that they can co-produce feasible and research-informed policy options. We describe a recent successful experience with this novel approach in the Netherlands and discuss the requirements for effective institutionalization of knowledge brokering. We also discuss the potential of this approach to assist health policy development in low-income countries based on the experience of developing the Regional East-African Health (REACH)-Policy Initiative. We believe that intermediary organizations, such as regional networks, dedicated institutional mechanisms and funding agencies, can play key roles in supporting knowledge brokering. We recommend the need to support and learn from the brokerage approach to strengthen the relationship between the research and policy communities and hence move towards a stronger culture of evidence-based policy and policy-relevant research. PMID:16917647

How Structure Shapes Dynamics: Knowledge Development in Wikipedia - A Network Multilevel Modeling Approach

PubMed Central

Halatchliyski, Iassen; Cress, Ulrike

2014-01-01

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. PMID:25365319

Knowledge-based nonuniform sampling in multidimensional NMR.

PubMed

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

2011-07-01

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

Knowledge Sharing in an American Multinational Company Based in Malaysia

ERIC Educational Resources Information Center

Ling, Chen Wai; Sandhu, Manjit S.; Jain, Kamal Kishore

2009-01-01

Purpose: This paper seeks to examine the views of executives working in an American based multinational company (MNC) about knowledge sharing, barriers to knowledge sharing, and strategies to promote knowledge sharing. Design/methodology/approach: This study was carried out in phases. In the first phase, a topology of organizational mechanisms for…

Restoring Consistency In Subjective Information For Groundwater Driven Health Risk Assessment

NASA Astrophysics Data System (ADS)

Ozbek, M. M.; Pinder, G. F.

2004-12-01

In an earlier work (Ozbek and Pinder, 2003), we constructed a fuzzy rule-based knowledge base that uses subjective expert opinion to calculate risk-based design constraints (i.e., dose and pattern of exposure) to sustain the groundwater-driven individual health risk at a desired level. Ideally, our system must be capable to produce for any individual a meaningful risk result or for any given risk a meaningful design constraint, in the sense that the result is neither the empty set nor the whole domain of the variable of interest. Otherwise we consider our system as inconsistent. We present a method based on fuzzy similarity relations to restore consistency in our implicative fuzzy rule based system used for the risk-based groundwater remediation design problem. Both a global and a local approach are considered. Even though straightforward and computationally less demanding, the global approach can affect pieces of knowledge negatively by inducing unwarranted imprecision into the knowledge base. On the other hand, the local approach, given a family of parameterized similarity relations, determines a parameter for each inference such that consistent results are computed which may not be feasible in real time applications of our knowledge base. Several scenarios are considered for comparing the two approaches that suggest that for specific applications one or several approaches ranging from a completely global to a completely local one will be more suitable than others while calculating the design constraints.

Towards Semantic e-Science for Traditional Chinese Medicine

PubMed Central

Chen, Huajun; Mao, Yuxin; Zheng, Xiaoqing; Cui, Meng; Feng, Yi; Deng, Shuiguang; Yin, Aining; Zhou, Chunying; Tang, Jinming; Jiang, Xiaohong; Wu, Zhaohui

2007-01-01

Background Recent advances in Web and information technologies with the increasing decentralization of organizational structures have resulted in massive amounts of information resources and domain-specific services in Traditional Chinese Medicine. The massive volume and diversity of information and services available have made it difficult to achieve seamless and interoperable e-Science for knowledge-intensive disciplines like TCM. Therefore, information integration and service coordination are two major challenges in e-Science for TCM. We still lack sophisticated approaches to integrate scientific data and services for TCM e-Science. Results We present a comprehensive approach to build dynamic and extendable e-Science applications for knowledge-intensive disciplines like TCM based on semantic and knowledge-based techniques. The semantic e-Science infrastructure for TCM supports large-scale database integration and service coordination in a virtual organization. We use domain ontologies to integrate TCM database resources and services in a semantic cyberspace and deliver a semantically superior experience including browsing, searching, querying and knowledge discovering to users. We have developed a collection of semantic-based toolkits to facilitate TCM scientists and researchers in information sharing and collaborative research. Conclusion Semantic and knowledge-based techniques are suitable to knowledge-intensive disciplines like TCM. It's possible to build on-demand e-Science system for TCM based on existing semantic and knowledge-based techniques. The presented approach in the paper integrates heterogeneous distributed TCM databases and services, and provides scientists with semantically superior experience to support collaborative research in TCM discipline. PMID:17493289

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

PubMed Central

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-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. PMID:24088728

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

PubMed

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.

From Cultural Knowledge to Intercultural Communicative Competence: Changing Perspectives on the Role of Culture in Foreign Language Teaching

ERIC Educational Resources Information Center

Piatkowska, Katarzyna

2015-01-01

Approaches to the concept of culture and teaching cultural competence in a foreign language classroom have been changing over the last decades. The paper summarises, compares, contrasts and evaluates four major approaches to teaching cultural competence in foreign language teaching, that is, knowledge-based approach, contrastive approach,…

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

NASA Technical Reports Server (NTRS)

Dvorak, Jiri J.

1994-01-01

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

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

ERIC Educational Resources Information Center

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…

Major accident prevention through applying safety knowledge management approach.

PubMed

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.

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

PubMed

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.

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Improving the learning of clinical reasoning through computer-based cognitive representation

PubMed Central

Wu, Bian; Wang, Minhong; Johnson, Janice M.; Grotzer, Tina A.

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction. PMID:25518871

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

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

ERIC Educational Resources Information Center

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…

Critical Analysis of Textbooks: Knowledge-Generating Logics and the Emerging Image of "Global Economic Contexts"

ERIC Educational Resources Information Center

Thoma, Michael

2017-01-01

This paper presents an approach to the critical analysis of textbook knowledge, which, working from a discourse theory perspective (based on the work of Foucault), refers to the performative nature of language. The critical potential of the approach derives from an analysis of knowledge-generating logics, which produce particular images of reality…

Potential and Impact Factors of the Knowledge and Information Awareness Approach for Fostering Net-Based Collaborative Problem-Solving: An Overview

ERIC Educational Resources Information Center

Engelmann, Tanja

2014-01-01

For effective communication and collaboration in learning situations, it is important to know what the collaboration partners know. However, the acquisition of this knowledge is difficult, especially in collaborating groups with spatially distributed members. One solution is the "Knowledge and Information Awareness" approach developed by…

Don’t Like RDF Reification? Making Statements about Statements Using Singleton Property

PubMed Central

Nguyen, Vinh; Bodenreider, Olivier; Sheth, Amit

2015-01-01

Statements about RDF statements, or meta triples, provide additional information about individual triples, such as the source, the occurring time or place, or the certainty. Integrating such meta triples into semantic knowledge bases would enable the querying and reasoning mechanisms to be aware of provenance, time, location, or certainty of triples. However, an efficient RDF representation for such meta knowledge of triples remains challenging. The existing standard reification approach allows such meta knowledge of RDF triples to be expressed using RDF by two steps. The first step is representing the triple by a Statement instance which has subject, predicate, and object indicated separately in three different triples. The second step is creating assertions about that instance as if it is a statement. While reification is simple and intuitive, this approach does not have formal semantics and is not commonly used in practice as described in the RDF Primer. In this paper, we propose a novel approach called Singleton Property for representing statements about statements and provide a formal semantics for it. We explain how this singleton property approach fits well with the existing syntax and formal semantics of RDF, and the syntax of SPARQL query language. We also demonstrate the use of singleton property in the representation and querying of meta knowledge in two examples of Semantic Web knowledge bases: YAGO2 and BKR. Our experiments on the BKR show that the singleton property approach gives a decent performance in terms of number of triples, query length and query execution time compared to existing approaches. This approach, which is also simple and intuitive, can be easily adopted for representing and querying statements about statements in other knowledge bases. PMID:25750938

Partnering with Youth to Map Their Neighborhood Environments: A Multi-Layered GIS Approach

PubMed Central

Topmiller, Michael; Jacquez, Farrah; Vissman, Aaron T.; Raleigh, Kevin; Miller-Francis, Jenni

2014-01-01

Mapping approaches offer great potential for community-based participatory researchers interested in displaying youth perceptions and advocating for change. We describe a multi-layered approach for gaining local knowledge of neighborhood environments that engages youth as co-researchers and active knowledge producers. By integrating geographic information systems (GIS) with environmental audits, an interactive focus group, and sketch mapping, the approach provides a place-based understanding of physical activity resources from the situated experience of youth. Youth report safety and a lack of recreational resources as inhibiting physical activity. Maps reflecting youth perceptions aid policy-makers in making place-based improvements for youth neighborhood environments. PMID:25423245

What Do We Know and How Well Do We Know It? Identifying Practice-Based Insights in Education

ERIC Educational Resources Information Center

Miller, Barbara; Pasley, Joan

2012-01-01

Knowledge derived from practice forms a significant portion of the knowledge base in the education field, yet is not accessible using existing empirical research methods. This paper describes a systematic, rigorous, grounded approach to collecting and analysing practice-based knowledge using the authors' research in teacher leadership as an…

A Holistic School-Based Nutrition Program Fails to Improve Teachers' Nutrition-Related Knowledge, Attitudes and Behaviour in Rural China

ERIC Educational Resources Information Center

Wang, Dongxu; Stewart, Donald; Chang, Chun

2016-01-01

Purpose: The purpose of this paper is to examine the effectiveness of a holistic school-based nutrition programme using the health-promoting school (HPS) approach, on teachers' knowledge, attitudes and behaviour in relation to nutrition in rural China. Design/methodology/approach: A cluster-randomised intervention trial design was employed. Two…

Enhancing the Teaching-Learning Process: A Knowledge Management Approach

ERIC Educational Resources Information Center

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…

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing.

PubMed

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.

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2001-01-01

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

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2000-12-01

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

Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning.

PubMed

Wu, Bian; Wang, Minhong; Grotzer, Tina A; Liu, Jun; Johnson, Janice M

2016-08-22

Practical experience with clinical cases has played an important role in supporting the learning of clinical reasoning. However, learning through practical experience involves complex processes difficult to be captured by students. This study aimed to examine the effects of a computer-based cognitive-mapping approach that helps students to externalize the reasoning process and the knowledge underlying the reasoning process when they work with clinical cases. A comparison between the cognitive-mapping approach and the verbal-text approach was made by analyzing their effects on learning outcomes. Fifty-two third-year or higher students from two medical schools participated in the study. Students in the experimental group used the computer-base cognitive-mapping approach, while the control group used the verbal-text approach, to make sense of their thinking and actions when they worked with four simulated cases over 4 weeks. For each case, students in both groups reported their reasoning process (involving data capture, hypotheses formulation, and reasoning with justifications) and the underlying knowledge (involving identified concepts and the relationships between the concepts) using the given approach. The learning products (cognitive maps or verbal text) revealed that students in the cognitive-mapping group outperformed those in the verbal-text group in the reasoning process, but not in making sense of the knowledge underlying the reasoning process. No significant differences were found in a knowledge posttest between the two groups. The computer-based cognitive-mapping approach has shown a promising advantage over the verbal-text approach in improving students' reasoning performance. Further studies are needed to examine the effects of the cognitive-mapping approach in improving the construction of subject-matter knowledge on the basis of practical experience.

A collaborative filtering-based approach to biomedical knowledge discovery.

PubMed

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

Knowledge-rich temporal relation identification and classification in clinical notes

PubMed Central

D’Souza, Jennifer; Ng, Vincent

2014-01-01

Motivation: We examine the task of temporal relation classification for the clinical domain. Our approach to this task departs from existing ones in that it is (i) ‘knowledge-rich’, employing sophisticated knowledge derived from discourse relations as well as both domain-independent and domain-dependent semantic relations, and (ii) ‘hybrid’, combining the strengths of rule-based and learning-based approaches. Evaluation results on the i2b2 Clinical Temporal Relations Challenge corpus show that our approach yields a 17–24% and 8–14% relative reduction in error over a state-of-the-art learning-based baseline system when gold-standard and automatically identified temporal relations are used, respectively. Database URL: http://www.hlt.utdallas.edu/~jld082000/temporal-relations/ PMID:25414383

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

A Logical Framework for Service Migration Based Survivability

DTIC Science & Technology

2016-06-24

platforms; Service Migration Strategy Fuzzy Inference System Knowledge Base Fuzzy rules representing domain expert knowledge about implications of...service migration strategy. Our approach uses expert knowledge as linguistic reasoning rules and takes service programs damage assessment, service...programs complexity, and available network capability as input. The fuzzy inference system includes four components as shown in Figure 5: (1) a knowledge

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

NASA Technical Reports Server (NTRS)

LaBel, Kenneth A.

2004-01-01

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

Validation and detection of vessel landmarks by using anatomical knowledge

NASA Astrophysics Data System (ADS)

Beck, Thomas; Bernhardt, Dominik; Biermann, Christina; Dillmann, Rüdiger

2010-03-01

The detection of anatomical landmarks is an important prerequisite to analyze medical images fully automatically. Several machine learning approaches have been proposed to parse 3D CT datasets and to determine the location of landmarks with associated uncertainty. However, it is a challenging task to incorporate high-level anatomical knowledge to improve these classification results. We propose a new approach to validate candidates for vessel bifurcation landmarks which is also applied to systematically search missed and to validate ambiguous landmarks. A knowledge base is trained providing human-readable geometric information of the vascular system, mainly vessel lengths, radii and curvature information, for validation of landmarks and to guide the search process. To analyze the bifurcation area surrounding a vessel landmark of interest, a new approach is proposed which is based on Fast Marching and incorporates anatomical information from the knowledge base. Using the proposed algorithms, an anatomical knowledge base has been generated based on 90 manually annotated CT images containing different parts of the body. To evaluate the landmark validation a set of 50 carotid datasets has been tested in combination with a state of the art landmark detector with excellent results. Beside the carotid bifurcation the algorithm is designed to handle a wide range of vascular landmarks, e.g. celiac, superior mesenteric, renal, aortic, iliac and femoral bifurcation.

Facilitating Emergent Literacy Skills: A Literature-Based, Multiple Intelligence Approach

ERIC Educational Resources Information Center

Brand, Susan Trostle

2006-01-01

Educators have continually sought to achieve a balance between a phonics-based, code-emphasis program and a more holistic, meaning-based approach to emergent literacy instruction. This article describes an integrated phonics and literature-based approach to developing children's emergent literacy skills. These skills included alphabet knowledge,…

Linking science and decision making to promote an ecology for the city: practices and opportunities

Treesearch

Morgan Grove; Daniel L. Childers; Michael Galvin; Sarah J. Hines; Tischa Munoz-Erickson; Erika S. Svendsen

2016-01-01

To promote urban sustainability and resilience, there is an increasing demand for actionable science that links science and decision making based on social–ecological knowledge. Approaches, frameworks, and practices for such actionable science are needed and have only begun to emerge. We propose that approaches based on the co- design and co- production of knowledge...

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

ERIC Educational Resources Information Center

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…

Work-Centered Approach to Insurgency Campaign Analysis

DTIC Science & Technology

2007-06-01

a constructivist or sensemaking philosophy by defining data, information , situation awareness , and situation understanding in the following manner...present paper explores a new approach to understanding transnational insurgency movements –an approach based on a fundamental analysis of the knowledge ...country or region. By focusing at the fundamental level of knowledge creation, the resulting framework allows an understanding of insurgency

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Effectiveness of e-learning in continuing medical education for occupational physicians.

PubMed

Hugenholtz, Nathalie I R; de Croon, Einar M; Smits, Paul B; van Dijk, Frank J H; Nieuwenhuijsen, Karen

2008-08-01

Within a clinical context e-learning is comparable to traditional approaches of continuing medical education (CME). However, the occupational health context differs and until now the effect of postgraduate e-learning among occupational physicians (OPs) has not been evaluated. To evaluate the effect of e-learning on knowledge on mental health issues as compared to lecture-based learning in a CME programme for OPs. Within the context of a postgraduate meeting for 74 OPs, a randomized controlled trial was conducted. Test assessments of knowledge were made before and immediately after an educational session with either e-learning or lecture-based learning. In both groups, a significant gain in knowledge on mental health care was found (P < 0.05). However, there was no significant difference between the two educational approaches. The effect of e-learning on OPs' mental health care knowledge is comparable to a lecture-based approach. Therefore, e-learning can be beneficial for the CME of OPs.

Model compilation: An approach to automated model derivation

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Baudin, Catherine; Iwasaki, Yumi; Nayak, Pandurang; Tanaka, Kazuo

1990-01-01

An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

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

Measuring Knowledge Elaboration Based on a Computer-Assisted Knowledge Map Analytical Approach to Collaborative Learning

ERIC Educational Resources Information Center

Zheng, Lanqin; Huang, Ronghuai; Hwang, Gwo-Jen; Yang, Kaicheng

2015-01-01

The purpose of this study is to quantitatively measure the level of knowledge elaboration and explore the relationships between prior knowledge of a group, group performance, and knowledge elaboration in collaborative learning. Two experiments were conducted to investigate the level of knowledge elaboration. The collaborative learning objective in…

An application of object-oriented knowledge representation to engineering expert systems

NASA Technical Reports Server (NTRS)

Logie, D. S.; Kamil, H.; Umaretiya, J. R.

1990-01-01

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

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

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

An architecture for rule based system explanation

NASA Technical Reports Server (NTRS)

Fennel, T. R.; Johannes, James D.

1990-01-01

A system architecture is presented which incorporate both graphics and text into explanations provided by rule based expert systems. This architecture facilitates explanation of the knowledge base content, the control strategies employed by the system, and the conclusions made by the system. The suggested approach combines hypermedia and inference engine capabilities. Advantages include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. User models are suggested to control the type, amount, and order of information presented.

Knowledge Cultures and the Shaping of Work-Based Learning: The Case of Computer Engineering

ERIC Educational Resources Information Center

Nerland, Monika

2008-01-01

This paper examines how the knowledge culture of computer engineering--that is, the ways in which knowledge is produced, distributed, accumulated and collectively approached within this profession--serve to construct work-based learning in specific ways. Typically, the epistemic infrastructures take the form of information structures with a global…

Measuring and Visualizing Group Knowledge Elaboration in Online Collaborative Discussions

ERIC Educational Resources Information Center

Zheng, Yafeng; Xu, Chang; Li, Yanyan; Su, You

2018-01-01

Knowledge elaboration plays a critical role in promoting knowledge acquisition and facilitating the retention of target knowledge in online collaborative discussions. Adopting a key-term-based automated analysis approach, we proposed an indicator framework to measure the level of knowledge elaboration in terms of coverage, activation, and…

Developing Evidence for Public Health Policy and Practice: The Implementation of a Knowledge Translation Approach in a Staged, Multi-Methods Study in England, 2007-09

ERIC Educational Resources Information Center

South, Jane; Cattan, Mima

2014-01-01

Effective knowledge translation processes are critical for the development of evidence-based public health policy and practice. This paper reports on the design and implementation of an innovative approach to knowledge translation within a mixed methods study on lay involvement in public health programme delivery. The study design drew on…

Knowledge-Based Object Detection in Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

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.

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Exploring arts-based knowledge translation: sharing research findings through performing the patterns, rehearsing the results, staging the synthesis.

PubMed

Rieger, Kendra; Schultz, Annette S H

2014-04-01

Cultivation of knowledge translation (KT) strategies that actively engage health professionals in critical reflection of their practice and research-based evidence are imperative to address the research-practice gap. While research-based evidence is exponentially growing, our ability to facilitate uptake by nurses and other health professionals has not kept pace. Innovative approaches that extend epistemological bias beyond a singular standpoint of postpositivism, such as the utilization of arts-based methods, expand the possibility to address the complexities of context, engage audience members, promote dissemination within communities of practice, and foster new audiences interested in research findings. In this paper, we address the importance of adopting a social constructivist epistemological stance to facilitate knowledge translation to diverse audiences, explore various arts-based knowledge translation (ABKT) strategies, and open a dialogue concerning evaluative tenets of ABKT. ABKT utilizes various art forms to disseminate research knowledge to diverse audiences and promote evidence-informed practice. ABKT initiatives translate knowledge not based upon a linear model, which views knowledge as an objective entity, but rather operate from the premise that knowledge is socially situated, which demands acknowledging and engaging the learner within their context. Theatre, dance, photography, and poetry are art forms that are commonly used to communicate research findings to diverse audiences. Given the emerging interest and importance of utilizing this KT strategy situated within a social constructivist epistemology, potential challenges and plausible evaluative criteria specific to ABKT are presented. ABKT is an emerging KT strategy that is grounded in social constructivist epistemological tenets, and holds potential for meaningfully sharing new research knowledge with diverse audiences. ABKT is an innovative and synergistic approach to traditional dissemination strategies. This creative KT approach is emerging as potent transformational learning tools that are congruent with the relational nature of nursing practice. ABKT facilitates learning about new research findings in an engaging and critical reflective manner that promotes learning within communities of practice. © 2014 Sigma Theta Tau International.

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

NASA Technical Reports Server (NTRS)

Vogel, Alison Andrews

1989-01-01

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

Refining Automatically Extracted Knowledge Bases Using Crowdsourcing

PubMed Central

Xian, Xuefeng; 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. PMID:28588611

Pursuing common agendas: a collaborative model for knowledge translation between research and practice in clinical settings.

PubMed

Baumbusch, Jennifer L; Kirkham, Sheryl Reimer; Khan, Koushambhi Basu; McDonald, Heather; Semeniuk, Pat; Tan, Elsie; Anderson, Joan M

2008-04-01

There is an emerging discourse of knowledge translation that advocates a shift away from unidirectional research utilization and evidence-based practice models toward more interactive models of knowledge transfer. In this paper, we describe how our participatory approach to knowledge translation developed during an ongoing program of research concerning equitable care for diverse populations. At the core of our approach is a collaborative relationship between researchers and practitioners, which underpins the knowledge translation cycle, and occurs simultaneously with data collection/analysis/synthesis. We discuss lessons learned including: the complexities of translating knowledge within the political landscape of healthcare delivery, the need to negotiate the agendas of researchers and practitioners in a collaborative approach, and the kinds of resources needed to support this process.

Teaching Thinking and Problem Solving.

ERIC Educational Resources Information Center

Bransford, John; And Others

1986-01-01

This article focuses on two approaches to teaching reasoning and problem solving. One emphasizes the role of domain-specific knowledge; the other emphasizes general strategic and metacognitive knowledge. Many instructional programs are based on the latter approach. The article concludes that these programs can be strengthened by focusing on domain…

Semantics driven approach for knowledge acquisition from EMRs.

PubMed

Perera, Sujan; Henson, Cory; Thirunarayan, Krishnaprasad; Sheth, Amit; Nair, Suhas

2014-03-01

Semantic computing technologies have matured to be applicable to many critical domains such as national security, life sciences, and health care. However, the key to their success is the availability of a rich domain knowledge base. The creation and refinement of domain knowledge bases pose difficult challenges. The existing knowledge bases in the health care domain are rich in taxonomic relationships, but they lack nontaxonomic (domain) relationships. In this paper, we describe a semiautomatic technique for enriching existing domain knowledge bases with causal relationships gleaned from Electronic Medical Records (EMR) data. We determine missing causal relationships between domain concepts by validating domain knowledge against EMR data sources and leveraging semantic-based techniques to derive plausible relationships that can rectify knowledge gaps. Our evaluation demonstrates that semantic techniques can be employed to improve the efficiency of knowledge acquisition.

Knowledge Integration in Global R&D Networks

NASA Astrophysics Data System (ADS)

Erkelens, Rose; van den Hooff, Bart; Vlaar, Paul; Huysman, Marleen

This paper reports a qualitative study conducted at multinational organizations' R&D departments about their process of knowledge integration. Taking into account the knowledge based view (KBV) of the firm and the practice-based view of knowledge, and building on the literatures concerning specialization and integration of knowledge in organizations, we explore which factors may have a significant influence on the integration process of knowledge between R&D units. The findings indicated (1) the contribution of relevant factors influencing knowledge integration processes and (2) a thoughtful balance between engineering and emergent approaches to be helpful in understanding and overcoming knowledge integration issues.

Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.

PubMed

Radhakrishnan, Srinivasan; Erbis, Serkan; Isaacs, Jacqueline A; Kamarthi, Sagar

2017-01-01

Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map.

Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature

PubMed Central

Isaacs, Jacqueline A.

2017-01-01

Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map. PMID:28328983

Shared knowledge or shared affordances? Insights from an ecological dynamics approach to team coordination in sports.

PubMed

Silva, Pedro; Garganta, Júlio; Araújo, Duarte; Davids, Keith; Aguiar, Paulo

2013-09-01

Previous research has proposed that team coordination is based on shared knowledge of the performance context, responsible for linking teammates' mental representations for collective, internalized action solutions. However, this representational approach raises many questions including: how do individual schemata of team members become reformulated together? How much time does it take for this collective cognitive process to occur? How do different cues perceived by different individuals sustain a general shared mental representation? This representational approach is challenged by an ecological dynamics perspective of shared knowledge in team coordination. We argue that the traditional shared knowledge assumption is predicated on 'knowledge about' the environment, which can be used to share knowledge and influence intentions of others prior to competition. Rather, during competitive performance, the control of action by perceiving surrounding informational constraints is expressed in 'knowledge of' the environment. This crucial distinction emphasizes perception of shared affordances (for others and of others) as the main communication channel between team members during team coordination tasks. From this perspective, the emergence of coordinated behaviours in sports teams is based on the formation of interpersonal synergies between players resulting from collective actions predicated on shared affordances.

An Investigation of Knowledge-Building Activities in an Online Community of Practice at Subaru of America

ERIC Educational Resources Information Center

Land, Susan M.; Draper, Darryl C.; Ma, Ziyan; Hsieh, Hsiu-Wei; Smith, Brian K.; Jordan, Robert

2009-01-01

Current approaches to workplace learning emphasize designing communities of practice that are intended to support both formal and informal knowledge acquisition. This article presents the design and research of a knowledge-based community of practice for Subaru, based on principles outlined by Scardamalia (2002) and Zhang, Scardamalia, Lamon,…

Epistemological Beliefs and Knowledge Sharing in Work Teams: A New Model and Research Questions

ERIC Educational Resources Information Center

Weinberg, Frankie J.

2015-01-01

Purpose: The purpose of this paper is to present a knowledge-sharing model that explains individual members' motivation to share knowledge (knowledge donation and knowledge collection). Design/methodology/approach: The model is based on social-constructivist theories of epistemological beliefs, learning and distributed cognition, and is organized…

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

PubMed

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

PubMed Central

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. PMID:29623057

Cooperative knowledge evolution: a construction-integration approach to knowledge discovery in medicine.

PubMed

Schmalhofer, F J; Tschaitschian, B

1998-11-01

In this paper, we perform a cognitive analysis of knowledge discovery processes. As a result of this analysis, the construction-integration theory is proposed as a general framework for developing cooperative knowledge evolution systems. We thus suggest that for the acquisition of new domain knowledge in medicine, one should first construct pluralistic views on a given topic which may contain inconsistencies as well as redundancies. Only thereafter does this knowledge become consolidated into a situation-specific circumscription and the early inconsistencies become eliminated. As a proof for the viability of such knowledge acquisition processes in medicine, we present the IDEAS system, which can be used for the intelligent documentation of adverse events in clinical studies. This system provides a better documentation of the side-effects of medical drugs. Thereby, knowledge evolution occurs by achieving consistent explanations in increasingly larger contexts (i.e., more cases and more pharmaceutical substrates). Finally, it is shown how prototypes, model-based approaches and cooperative knowledge evolution systems can be distinguished as different classes of knowledge-based systems.

Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

NASA Astrophysics Data System (ADS)

Elag, M.; Goodall, J. L.

2013-12-01

Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL service is provided for semantic-based querying of the ontology.

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

How Knowledge Organizations Work: The Case of Detectives

ERIC Educational Resources Information Center

Gottschalk, Petter; Holgersson, Stefan; Karlsen, Jan Terje

2009-01-01

Purpose: The purpose of this paper is to conceptualize detectives in police investigations as knowledge workers. Design/methodology/approach: The paper is based on a literature review covering knowledge organizations, police organizations, police investigations, and detectives as knowledge workers. Findings: The paper finds that the changing role…

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

This paper presents an expert knowledge-based approach to landslide susceptibility mapping in an effort to overcome the deficiencies of data-driven approaches. The proposed approach consists of three generic steps: (1) extraction of knowledge on the relationship between landslide susceptibility and predisposing factors from domain experts, (2) characterization of predisposing factors using GIS techniques, and (3) prediction of landslide susceptibility under fuzzy logic. The approach was tested in two study areas in China - the Kaixian study area (about 250 km2) and the Three Gorges study area (about 4600 km2). The Kaixian study area was used to develop the approach and to evaluate its validity. The Three Gorges study area was used to test both the portability and the applicability of the developed approach for mapping landslide susceptibility over large study areas. Performance was evaluated by examining if the mean of the computed susceptibility values at landslide sites was statistically different from that of the entire study area. A z-score test was used to examine the statistical significance of the difference. The computed z for the Kaixian area was 3.70 and the corresponding p-value was less than 0.001. This suggests that the computed landslide susceptibility values are good indicators of landslide occurrences. In the Three Gorges study area, the computed z was 10.75 and the corresponding p-value was less than 0.001. In addition, we divided the susceptibility value into four levels: low (0.0-0.25), moderate (0.25-0.5), high (0.5-0.75) and very high (0.75-1.0). No landslides were found for areas of low susceptibility. Landslide density was about three times higher in areas of very high susceptibility than that in the moderate susceptibility areas, and more than twice as high as that in the high susceptibility areas. The results from the Three Gorge study area suggest that the extracted expert knowledge can be extrapolated to another study area and the developed approach can be used in large-scale projects. Results from these case studies suggest that the expert knowledge-based approach is effective in mapping landslide susceptibility and that its performance is maintained when it is moved to a new area from the model development area without changes to the knowledge base.

Translational Scholarship and a Palliative Approach: Enlisting the Knowledge-As-Action Framework.

PubMed

Reimer-Kirkham, Sheryl; Doane, Gweneth Hartrick; Antifeau, Elisabeth; Pesut, Barbara; Porterfield, Pat; Roberts, Della; Stajduhar, Kelli; Wikjord, Nicole

2015-01-01

Based on a retheorized epistemology for knowledge translation (KT) that problematizes the "know-do gap" and conceptualizes the knower, knowledge, and action as inseparable, this paper describes the application of the Knowledge-As-Action Framework. When applied as a heuristic device to support an inquiry process, the framework with the metaphor of a kite facilitates a responsiveness to the complexities that characterize KT. Examples from a KT demonstration project on the integration of a palliative approach at 3 clinical sites illustrate the interrelatedness of 6 dimensions-the local context, processes, people, knowledge, fluctuating realities, and values.

Optimal phase estimation with arbitrary a priori knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demkowicz-Dobrzanski, Rafal

2011-06-15

The optimal-phase estimation strategy is derived when partial a priori knowledge on the estimated phase is available. The solution is found with the help of the most famous result from the entanglement theory: the positive partial transpose criterion. The structure of the optimal measurements, estimators, and the optimal probe states is analyzed. This Rapid Communication provides a unified framework bridging the gap in the literature on the subject which until now dealt almost exclusively with two extreme cases: almost perfect knowledge (local approach based on Fisher information) and no a priori knowledge (global approach based on covariant measurements). Special attentionmore » is paid to a natural a priori probability distribution arising from a diffusion process.« less

Hypoxia-based strategies for regenerative dentistry-Views from the different dental fields.

PubMed

Müller, Anna Sonja; Janjić, Klara; Lilaj, Bledar; Edelmayer, Michael; Agis, Hermann

2017-09-01

The understanding of the cell biological processes underlying development and regeneration of oral tissues leads to novel regenerative approaches. Over the past years, knowledge on key roles of the hypoxia-based response has become more profound. Based on these findings, novel regenerative approaches for dentistry are emerging, which target cellular oxygen sensors. These approaches include hypoxia pre-conditioning and pharmacologically simulated hypoxia. The increase in studies on hypoxia and hypoxia-based strategies in regenerative dentistry highlights the growing attention to hypoxia's role in regeneration and its underlying biology, as well as its application in a therapeutic setting. In this narrative review, we present the current knowledge on the role of hypoxia in oral tissues and review the proposed hypoxia-based approaches in different fields of dentistry, including endodontics, orthodontics, periodontics, and oral surgery. Copyright © 2017 Elsevier Ltd. All rights reserved.

The KATE shell: An implementation of model-based control, monitor and diagnosis

NASA Technical Reports Server (NTRS)

Cornell, Matthew

1987-01-01

The conventional control and monitor software currently used by the Space Center for Space Shuttle processing has many limitations such as high maintenance costs, limited diagnostic capabilities and simulation support. These limitations have caused the development of a knowledge based (or model based) shell to generically control and monitor electro-mechanical systems. The knowledge base describes the system's structure and function and is used by a software shell to do real time constraints checking, low level control of components, diagnosis of detected faults, sensor validation, automatic generation of schematic diagrams and automatic recovery from failures. This approach is more versatile and more powerful than the conventional hard coded approach and offers many advantages over it, although, for systems which require high speed reaction times or aren't well understood, knowledge based control and monitor systems may not be appropriate.

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

PubMed

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.

Documenting Art Therapy Clinical Knowledge Using Interviews

ERIC Educational Resources Information Center

Regev, Dafna

2017-01-01

Practicing art therapists have vast stores of knowledge and experience, but in most cases, their work is not documented, and their clinical knowledge does not enter the academic discourse. This article proposes a systematic approach to the collection of practice knowledge about art therapy based on conducting interviews with art therapists who…

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

PubMed

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 approaches, they create opportunities to challenge assumptions about for whom, how, and what is defined as knowledge, and to develop and integrate research findings into health systems. When used appropriately, CBPR and IKT both have the potential to contribute to and advance implementation science about the conduct of collaborative health systems research.

Improving Professional Practice through Practice-Based Research: VaKE (Values "and" Knowledge Education) in University-Based Teacher Education

ERIC Educational Resources Information Center

Weinberger, Alfred; Patry, Jean-Luc; Weyringer, Sieglinde

2016-01-01

Evidence suggests that in the professional education of teachers the moral goals are currently a neglected topic in favor of the subject matter and knowledge. The constructivist instructional approach VaKE (Values "and" Knowledge Education) addresses this problem by combining the moral and epistemic goals through the discussion of moral…

Knowledge Acquisition of Generic Queries for Information Retrieval

PubMed Central

Seol, Yoon-Ho; Johnson, Stephen B.; Cimino, James J.

2002-01-01

Several studies have identified clinical questions posed by health care professionals to understand the nature of information needs during clinical practice. To support access to digital information sources, it is necessary to integrate the information needs with a computer system. We have developed a conceptual guidance approach in information retrieval, based on a knowledge base that contains the patterns of information needs. The knowledge base uses a formal representation of clinical questions based on the UMLS knowledge sources, called the Generic Query model. To improve the coverage of the knowledge base, we investigated a method for extracting plausible clinical questions from the medical literature. This poster presents the Generic Query model, shows how it is used to represent the patterns of clinical questions, and describes the framework used to extract knowledge from the medical literature.

Combining Knowledge and Data Driven Insights for Identifying Risk Factors using Electronic Health Records

PubMed Central

Sun, Jimeng; Hu, Jianying; Luo, Dijun; Markatou, Marianthi; Wang, Fei; Edabollahi, Shahram; Steinhubl, Steven E.; Daar, Zahra; Stewart, Walter F.

2012-01-01

Background: The ability to identify the risk factors related to an adverse condition, e.g., heart failures (HF) diagnosis, is very important for improving care quality and reducing cost. Existing approaches for risk factor identification are either knowledge driven (from guidelines or literatures) or data driven (from observational data). No existing method provides a model to effectively combine expert knowledge with data driven insight for risk factor identification. Methods: We present a systematic approach to enhance known knowledge-based risk factors with additional potential risk factors derived from data. The core of our approach is a sparse regression model with regularization terms that correspond to both knowledge and data driven risk factors. Results: The approach is validated using a large dataset containing 4,644 heart failure cases and 45,981 controls. The outpatient electronic health records (EHRs) for these patients include diagnosis, medication, lab results from 2003–2010. We demonstrate that the proposed method can identify complementary risk factors that are not in the existing known factors and can better predict the onset of HF. We quantitatively compare different sets of risk factors in the context of predicting onset of HF using the performance metric, the Area Under the ROC Curve (AUC). The combined risk factors between knowledge and data significantly outperform knowledge-based risk factors alone. Furthermore, those additional risk factors are confirmed to be clinically meaningful by a cardiologist. Conclusion: We present a systematic framework for combining knowledge and data driven insights for risk factor identification. We demonstrate the power of this framework in the context of predicting onset of HF, where our approach can successfully identify intuitive and predictive risk factors beyond a set of known HF risk factors. PMID:23304365

Translating knowledge into practice: An exploratory study of dementia-specific training for community-based service providers.

PubMed

O'Sullivan, Grace; Hocking, Clare; McPherson, Kathryn

2017-08-01

Objective To develop, deliver, and evaluate dementia-specific training designed to inform service delivery by enhancing the knowledge of community-based service providers. Methods This exploratory qualitative study used an interdisciplinary, interuniversity team approach to develop and deliver dementia-specific training. Participants included management, care staff, and clients from three organizations funded to provide services in the community. Data on the acceptability, applicability, and perceived outcomes of the training were gathered through focus group discussions and individual interviews. Transcripts were analyzed to generate open codes which were clustered into themes and sub-themes addressing the content, delivery, and value of the training. Findings Staff valued up-to-date knowledge and "real stories" grounded in practice. Clients welcomed the strengths-based approach. Contractual obligations impact on the application of knowledge in practice. Implications The capacity to implement new knowledge may be limited by the legislative policies which frame service provision, to the detriment of service users.

Evidence-Based Administration for Decision Making in the Framework of Knowledge Strategic Management

ERIC Educational Resources Information Center

Del Junco, Julio Garcia; Zaballa, Rafael De Reyna; de Perea, Juan Garcia Alvarez

2010-01-01

Purpose: This paper seeks to present a model based on evidence-based administration (EBA), which aims to facilitate the creation, transformation and diffusion of knowledge in learning organizations. Design/methodology/approach: A theoretical framework is proposed based on EBA and the case method. Accordingly, an empirical study was carried out in…

A Theory of the Measurement of Knowledge Content, Access, and Learning.

ERIC Educational Resources Information Center

Pirolli, Peter; Wilson, Mark

1998-01-01

An approach to the measurement of knowledge content, knowledge access, and knowledge learning is developed. First a theoretical view of cognition is described, and then a class of measurement models, based on Rasch modeling, is presented. Knowledge access and content are viewed as determining the observable actions selected by an agent to achieve…

[Sustainable Implementation of Evidence-Based Programmes in Health Promotion: A Theoretical Framework and Concept of Interactive Knowledge to Action].

PubMed

Rütten, A; Wolff, A; Streber, A

2016-03-01

This article discusses 2 current issues in the field of public health research: (i) transfer of scientific knowledge into practice and (ii) sustainable implementation of good practice projects. It also supports integration of scientific and practice-based evidence production. Furthermore, it supports utilisation of interactive models that transcend deductive approaches to the process of knowledge transfer. Existing theoretical approaches, pilot studies and thoughtful conceptual considerations are incorporated into a framework showing the interplay of science, politics and prevention practice, which fosters a more sustainable implementation of health promotion programmes. The framework depicts 4 key processes of interaction between science and prevention practice: interactive knowledge to action, capacity building, programme adaptation and adaptation of the implementation context. Ensuring sustainability of health promotion programmes requires a concentrated process of integrating scientific and practice-based evidence production in the context of implementation. Central to the integration process is the approach of interactive knowledge to action, which especially benefits from capacity building processes that facilitate participation and systematic interaction between relevant stakeholders. Intense cooperation also induces a dynamic interaction between multiple actors and components such as health promotion programmes, target groups, relevant organisations and social, cultural and political contexts. The reciprocal adaptation of programmes and key components of the implementation context can foster effectiveness and sustainability of programmes. Sustainable implementation of evidence-based health promotion programmes requires alternatives to recent deductive models of knowledge transfer. Interactive approaches prove to be promising alternatives. Simultaneously, they change the responsibilities of science, policy and public health practice. Existing boundaries within disciplines and sectors are overcome by arranging transdisciplinary teams as well as by developing common agendas and procedures. Such approaches also require adaptations of the structure of research projects such as extending the length of funding. © Georg Thieme Verlag KG Stuttgart · New York.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendell, Mark J.

This report briefly summarizes, based on recent review articles and selected more recent research reports, current scientific knowledge on two topics: assessing unhealthy levels of indoor D/M in homes and remediating home dampness-related problems to protect health. Based on a comparison of current scientific knowledge to that required to support effective, evidence-based, health-protective policies on home D/M, gaps in knowledge are highlighted, prior questions and research questions specified, and necessary research activities and approaches recommended.

Co-production of knowledge: An Inuit Indigenous Knowledge perspective

NASA Astrophysics Data System (ADS)

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 Monitoring and Scientific Methods for Sustained Arctic Observations. http://www.arcticobservingsummit.org/sites/arcticobservingsummit.org/files/Daniel_Laing_Kielsen%20Holm_et_al-AOS2016-Theme-6-IK-CBM-Synthesis-updated-2016-04.pdf

Applying IT Governance Concepts and Elements to Knowledge Governance: An Initial Approach

NASA Astrophysics Data System (ADS)

Rouyet, Juan Ignacio; Joyanes, Luis

As the era of knowledge-based economy is emerging, the importance of knowledge governance is gradually increasing. The question of how the governance mechanisms influence on the knowledge transactions is becoming increasingly relevant. However, the theoretical approaches have yet to solve outstanding issues, such as how the the micro-level governance mechanisms influence the knowledge processes or what kind of organizational hazard could decrease the benefits form the knowledge processes. Furthermore, the deployment of empirical studies to address the issues mentioned is arguably needed. This paper proposes a knowledge governance framework to assist effectively in the implementation of governance mechanisms for knowledge management processes. Additionally, it shows how this may be implented in a knowledge-intensive firm and proposes specific structures and governance mechanisms.

Evolutionary Local Search of Fuzzy Rules through a novel Neuro-Fuzzy encoding method.

PubMed

Carrascal, A; Manrique, D; Ríos, J; Rossi, C

2003-01-01

This paper proposes a new approach for constructing fuzzy knowledge bases using evolutionary methods. We have designed a genetic algorithm that automatically builds neuro-fuzzy architectures based on a new indirect encoding method. The neuro-fuzzy architecture represents the fuzzy knowledge base that solves a given problem; the search for this architecture takes advantage of a local search procedure that improves the chromosomes at each generation. Experiments conducted both on artificially generated and real world problems confirm the effectiveness of the proposed approach.

Behavior determinants among cardiac rehabilitation patients receiving educational interventions: an application of the health action process approach.

PubMed

Ghisi, Gabriela Lima de Melo; Grace, Sherry L; Thomas, Scott; Oh, Paul

2015-05-01

To (1) test the effect of a health action process approach (HAPA) theory-based education program in cardiac rehabilitation (CR) compared to traditional education on patient knowledge and HAPA constructs; and, (2) investigate the theoretical correlates of exercise behavior among CR patients receiving theory-based education. CR patients were exposed to an existing or HAPA-based 6 month education curriculum in this quasi-experimental study. Participants completed a survey assessing exercise behavior, HAPA constructs, and knowledge pre and post-program. 306 patients consented to participate, of which 146 (47.7%) were exposed to the theory-based educational curriculum. There was a significant improvement in patients' overall knowledge pre- to post-CR, as well as in some HAPA constructs and exercise behavior, regardless of curriculum (p < 0.05). Path analysis revealed that knowledge was significantly related to intention formation, and intentions to engage in exercise were not directly related to behavior, which required action planning. The theoretically-informed education curriculum was not associated with greater knowledge or exercise behavior as expected. Education in CR improves knowledge, and theoretical constructs related to exercise behavior. Educational curricula should be designed to not only increase patients' knowledge, but also enhance intentions, self-efficacy, and action planning. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Knowledge-based zonal grid generation for computational fluid dynamics

NASA Technical Reports Server (NTRS)

Andrews, Alison E.

1988-01-01

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

Health professionals' decision-making in wound management: a grounded theory.

PubMed

Gillespie, Brigid M; Chaboyer, Wendy; St John, Winsome; Morley, Nicola; Nieuwenhoven, Paul

2015-06-01

To develop a conceptual understanding of the decision-making processes used by healthcare professionals in wound care practice. With the global move towards using an evidence-base in standardizing wound care practices and the need to reduce hospital wound care costs, it is important to understand health professionals' decision-making in this important yet under-researched area. A grounded theory approach was used to explore clinical decision-making of healthcare professionals in wound care practice. Interviews were conducted with 20 multi-disciplinary participants from nursing, surgery, infection control and wound care who worked at a metropolitan hospital in Australia. Data were collected during 2012-2013. Constant comparative analysis underpinned by Strauss and Corbin's framework was used to identify clinical decision-making processes. The core category was 'balancing practice-based knowledge with evidence-based knowledge'. Participants' clinical practice and actions embedded the following processes: 'utilizing the best available information', 'using a consistent approach in wound assessment' and 'using a multidisciplinary approach'. The substantive theory explains how practice and evidence knowledge was balanced and the variation in use of intuitive practice-based knowledge versus evidence-based knowledge. Participants considered patients' needs and preferences, costs, outcomes, technologies, others' expertise and established practices. Participants' decision-making tended to be more heavily weighted towards intuitive practice-based processes. These findings offer a better understanding of the processes used by health professionals' in their decision-making in wound care. Such an understanding may inform the development of evidence-based interventions that lead to better patient outcomes. © 2014 John Wiley & Sons Ltd.

Knowledge-based support for the participatory design and implementation of shift systems.

PubMed

Gissel, A; Knauth, P

1998-01-01

This study developed a knowledge-based software system to support the participatory design and implementation of shift systems as a joint planning process including shift workers, the workers' committee, and management. The system was developed using a model-based approach. During the 1st phase, group discussions were repeatedly conducted with 2 experts. Thereafter a structure model of the process was generated and subsequently refined by the experts in additional semistructured interviews. Next, a factual knowledge base of 1713 relevant studies was collected on the effects of shift work. Finally, a prototype of the knowledge-based system was tested on 12 case studies. During the first 2 phases of the system, important basic information about the tasks to be carried out is provided for the user. During the 3rd phase this approach uses the problem-solving method of case-based reasoning to determine a shift rota which has already proved successful in other applications. It can then be modified in the 4th phase according to the shift workers' preferences. The last 2 phases support the final testing and evaluation of the system. The application of this system has shown that it is possible to obtain shift rotas suitable to actual problems and representative of good ergonomic solutions. A knowledge-based approach seems to provide valuable support for the complex task of designing and implementing a new shift system. The separation of the task into several phases, the provision of information at all stages, and the integration of all parties concerned seem to be essential factors for the success of the application.

Exploring Teacher Knowledge and Actions Supporting Technology-Enhanced Teaching in Elementary Schools: Two Approaches by Pre-Service Teachers

ERIC Educational Resources Information Center

Figg, Candace; Jamani, Kamini Jaipal

2011-01-01

Two approaches to teaching with technology to highlight practice-based teacher knowledge and actions for teaching technologically enhanced lessons are presented. Participants were two elementary pre-service teachers teaching during practicum. Qualitative data sources included verbatim transcripts of participant interviews, field notes of planning…

Forum: Learning Outcomes in Communication. The LOCs and the Shift to Student-Centered Learning

ERIC Educational Resources Information Center

Brown, Timothy J.; Castor, Theresa; Byrnes-Loinette, Kerry; Bowman, Jonathan; McBride, Chad

2016-01-01

Traditional teaching is based upon a "teacher"-centered rather than a "student"-centered approach (Bain, 2004). A teacher-centered approach underscores the long held philosophy that instructors are the gatekeepers of knowledge whose job is to convey their knowledge through a lecture, with students as passive receivers during…

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

DTIC Science & Technology

1988-01-19

approach for the analysis of aerial images. In this approach image analysis is performed ast three levels of abstraction, namely iconic or low-level... image analysis , symbolic or medium-level image analysis , and semantic or high-level image analysis . Domain dependent knowledge about prototypical urban

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

ERIC Educational Resources Information Center

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…

Knowledge Management and the Competitive Strategy of the Firm

ERIC Educational Resources Information Center

Halawi, Leila A.; McCarthy, Richard V.; Aronson, Jay E.

2006-01-01

Purpose: Knowledge management (KM) has emerged as a strategy to improve organizational competitiveness. Our purpose is to identify the relationship between KM and the firm's competitive advantage. Design/methodology/approach: We review the existing literature on KM and strategy formulation. We utilize the resource-based view approach as a lens for…

"Slow Science": Building Scientific Concepts in Physics in High School

ERIC Educational Resources Information Center

Bigozzi, Lucia; Tarchi, Christian; Falsini, Paola; Fiorentini, Carlo

2014-01-01

In this study, a progressive-learning approach to physics, based on knowledge-building pedagogy, was compared to a content-centered approach in which explanations, experiments, and discussions are centered on the transmission of knowledge. Forty-six students attending the first year of high school participated in this study over a whole school…

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Personal profile of medical students selected through a knowledge-based exam only: are we missing suitable students?

PubMed Central

Abbiati, Milena; Baroffio, Anne; Gerbase, Margaret W.

2016-01-01

Introduction A consistent body of literature highlights the importance of a broader approach to select medical school candidates both assessing cognitive capacity and individual characteristics. However, selection in a great number of medical schools worldwide is still based on knowledge exams, a procedure that might neglect students with needed personal characteristics for future medical practice. We investigated whether the personal profile of students selected through a knowledge-based exam differed from those not selected. Methods Students applying for medical school (N=311) completed questionnaires assessing motivations for becoming a doctor, learning approaches, personality traits, empathy, and coping styles. Selection was based on the results of MCQ tests. Principal component analysis was used to draw a profile of the students. Differences between selected and non-selected students were examined by Multivariate ANOVAs, and their impact on selection by logistic regression analysis. Results Students demonstrating a profile of diligence with higher conscientiousness, deep learning approach, and task-focused coping were more frequently selected (p=0.01). Other personal characteristics such as motivation, sociability, and empathy did not significantly differ, comparing selected and non-selected students. Conclusion Selection through a knowledge-based exam privileged diligent students. It did neither advantage nor preclude candidates with a more humane profile. PMID:27079886

Bridging Disciplinary Boundaries

ERIC Educational Resources Information Center

Mei, Linda

2009-01-01

Interdisciplinary education promotes the unity of knowledge by bridging the cultural divide between the social constructs of disciplines and encourages the development of knowledge to enhance society. As an inquiry-based and relevant approach that expands and advances knowledge, interdisciplinary education facilitates creativity and flexibility,…

Operator assistant systems - An experimental approach using a telerobotics application

NASA Technical Reports Server (NTRS)

Boy, Guy A.; Mathe, Nathalie

1993-01-01

This article presents a knowledge-based system methodology for developing operator assistant (OA) systems in dynamic and interactive environments. This is a problem both of training and design, which is the subject of this article. Design includes both design of the system to be controlled and design of procedures for operating this system. A specific knowledge representation is proposed for representing the corresponding system and operational knowledge. This representation is based on the situation recognition and analytical reasoning paradigm. It tries to make explicit common factors involved in both human and machine intelligence, including perception and reasoning. An OA system based on this representation has been developed for space telerobotics. Simulations have been carried out with astronauts and the resulting protocols have been analyzed. Results show the relevance of the approach and have been used for improving the knowledge representation and the OA architecture.

Knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation system.

PubMed

Boegl, Karl; Adlassnig, Klaus-Peter; Hayashi, Yoichi; Rothenfluh, Thomas E; Leitich, Harald

2004-01-01

This paper describes the fuzzy knowledge representation framework of the medical computer consultation system MedFrame/CADIAG-IV as well as the specific knowledge acquisition techniques that have been developed to support the definition of knowledge concepts and inference rules. As in its predecessor system CADIAG-II, fuzzy medical knowledge bases are used to model the uncertainty and the vagueness of medical concepts and fuzzy logic reasoning mechanisms provide the basic inference processes. The elicitation and acquisition of medical knowledge from domain experts has often been described as the most difficult and time-consuming task in knowledge-based system development in medicine. It comes as no surprise that this is even more so when unfamiliar representations like fuzzy membership functions are to be acquired. From previous projects we have learned that a user-centered approach is mandatory in complex and ill-defined knowledge domains such as internal medicine. This paper describes the knowledge acquisition framework that has been developed in order to make easier and more accessible the three main tasks of: (a) defining medical concepts; (b) providing appropriate interpretations for patient data; and (c) constructing inferential knowledge in a fuzzy knowledge representation framework. Special emphasis is laid on the motivations for some system design and data modeling decisions. The theoretical framework has been implemented in a software package, the Knowledge Base Builder Toolkit. The conception and the design of this system reflect the need for a user-centered, intuitive, and easy-to-handle tool. First results gained from pilot studies have shown that our approach can be successfully implemented in the context of a complex fuzzy theoretical framework. As a result, this critical aspect of knowledge-based system development can be accomplished more easily.

a Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

NASA Astrophysics Data System (ADS)

Park, Young-Tack; Kim, Jae-Hoon; Park, Hyun-Soo

1997-06-01

Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

Selection of Construction Methods: A Knowledge-Based Approach

PubMed Central

Skibniewski, Miroslaw

2013-01-01

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

Improving management of small natural features on private lands by negotiating the science-policy boundary for Maine vernal pools.

PubMed

Calhoun, Aram J K; Jansujwicz, Jessica S; Bell, Kathleen P; Hunter, Malcolm L

2014-07-29

Vernal pools are far more important for providing ecosystem services than one would predict based on their small size. However, prevailing resource-management strategies are not effectively conserving pools and other small natural features on private lands. Solutions are complicated by tensions between private property and societal rights, uncertainties over resource location and function, diverse stakeholders, and fragmented regulatory authority. The development and testing of new conservation approaches that link scientific knowledge, stakeholder decision-making, and conservation outcomes are important responses to this conservation dilemma. Drawing from a 15-y history of vernal pool conservation efforts in Maine, we describe the coevolution of pool conservation and research approaches, focusing on how research-based knowledge was produced and used in support of management decisions. As management shifted from reactive, top-down approaches to proactive and flexible approaches, research shifted from an ecology-focused program to an interdisciplinary program based on social-ecological systems. The most effective strategies for linking scientific knowledge with action changed as the decision-makers, knowledge needs, and context for vernal pool management advanced. Interactions among stakeholders increased the extent to which knowledge was coproduced and shifted the objective of stakeholder engagement from outreach to research collaboration and development of innovative conservation approaches. New conservation strategies were possible because of the flexible, solutions-oriented collaborations and trust between scientists and decision-makers (fostered over 15 y) and interdisciplinary, engaged research. Solutions to the dilemma of conserving small natural features on private lands, and analogous sustainability science challenges, will benefit from repeated negotiations of the science-policy boundary.

Towards transdisciplinarity in Arctic sustainability knowledge co-production: Socially-Oriented Observations as a participatory integrated activity

NASA Astrophysics Data System (ADS)

Vlasova, Tatiana; Volkov, Sergey

2016-09-01

The paper is an attempt to tie together main biogeophysical and social science projects under the auspice of interdisciplinary sustainability science development. Special attention is put to the necessity of the transdisciplinary knowledge co-production based on activities and problem-solutions approaches. It puts attention to the role of monitoring activities in sustainability interdisciplinary science and transdisciplinary knowledge evolution in the Arctic. Socially focused monitoring named Socially-Oriented Observations creating a transdisciplinary space is viewed as one of sources of learning and transformations towards sustainability making possible to shape rapid changes happening in the Arctic based on sustainability knowledge co-production. Continuous Socially-Oriented Observations integrating scientific, education and monitoring methods enables to define adaptation and transformation pathways in the Arctic - the most rapidly changing region of our planet. Socially-Oriented Observations are based on the existing and developing interdisciplinary scientific approaches emerged within natural science and social science projects, sustainable development and resilience concepts putting principle attention to building sustainable and resilient socio-ecological systems. It is argued that the Arctic sustainability science is a valuable component of the whole and broader system of the Arctic Sustainability knowledge co-produced with the help of transdisciplinary approaches integrating science, local/traditional knowledge, entrepreneurship, education, decision-making. Socially-Oriented Observations are designed to be a transdisciplinary interactive continuous participatory process empowering deliberate choices of people that can shape the changes and enable transformation towards sustainability. Approaches of Socially-Oriented Observations and methods of implementation that have been developed since the IPY 2007/2008 and being practiced in different regions of the Arctic are discussed.

Knowledge-guided golf course detection using a convolutional neural network fine-tuned on temporally augmented data

NASA Astrophysics Data System (ADS)

Chen, Jingbo; Wang, Chengyi; Yue, Anzhi; Chen, Jiansheng; He, Dongxu; Zhang, Xiuyan

2017-10-01

The tremendous success of deep learning models such as convolutional neural networks (CNNs) in computer vision provides a method for similar problems in the field of remote sensing. Although research on repurposing pretrained CNN to remote sensing tasks is emerging, the scarcity of labeled samples and the complexity of remote sensing imagery still pose challenges. We developed a knowledge-guided golf course detection approach using a CNN fine-tuned on temporally augmented data. The proposed approach is a combination of knowledge-driven region proposal, data-driven detection based on CNN, and knowledge-driven postprocessing. To confront data complexity, knowledge-derived cooccurrence, composition, and area-based rules are applied sequentially to propose candidate golf regions. To confront sample scarcity, we employed data augmentation in the temporal domain, which extracts samples from multitemporal images. The augmented samples were then used to fine-tune a pretrained CNN for golf detection. Finally, commission error was further suppressed by postprocessing. Experiments conducted on GF-1 imagery prove the effectiveness of the proposed approach.

A Personalized Recommendation-Based Mobile Learning Approach to Improving the Reading Performance of EFL Students

ERIC Educational Resources Information Center

Hsu, Ching-Kun; Hwang, Gwo-Jen; Chang, Chih-Kai

2013-01-01

In this paper, a personalized recommendation-based mobile language learning approach is proposed. A mobile learning system has been developed based on the approach by providing a reading material recommendation mechanism for guiding EFL (English as Foreign Language) students to read articles that match their preferences and knowledge levels, and a…

Fostering Upper Secondary Students' Ability to Engage in Practices of Scientific Investigation: a Comparative Analysis of an Explicit and an Implicit Instructional Approach

NASA Astrophysics Data System (ADS)

Vorholzer, Andreas; von Aufschnaiter, Claudia; Boone, William J.

2018-02-01

Inquiry-based teaching is considered as contributing to content-related, procedural, and epistemic learning goals of science education. In this study, a quasi-experimental research design was utilized to investigate to what extent embedding inquiry activities in an explicit and an implicit instructional approach fosters students' ability to engage in three practices of scientific investigation (POSI): (1) formulating questions and hypotheses, (2) planning investigations, (3) analyzing and interpreting data. Both approaches were implemented in a classroom-based intervention conducted in a German upper secondary school (N = 222). Students' procedural knowledge of the three POSI was assessed with a paper-pencil test prior and post to the intervention, their content knowledge and dispositional factors (e.g., cognitive abilities) were gathered once. Results show that not only explicit but also implicit instruction fosters students' knowledge of POSI. While overall explicit instruction was found to be more effective, the findings indicate that the effectiveness depends considerably on the practice addressed. Moreover, findings suggest that both approaches were equally beneficial for all students regardless of their prior content knowledge and their prior procedural knowledge of POSI. Potential conditions for the success of explicit and implicit approaches as well as implications for instruction on POSI in science classrooms and for future research are discussed.

The Role of Knowledge in Participatory and Pluralistic Approaches to ESE

ERIC Educational Resources Information Center

Rudsberg, Karin; Öhman, Johan

2015-01-01

The purpose of this article is to investigate "in situ" the functions that knowledge has when used by students in argumentative discussions. The study is based on Dewey's pragmatic perspective of knowledge, which means that knowledge gets its meaning in the activity at hand. The analyses are conducted using Transactional Argumentation…

Bridging the Gap in Knowledge Transfer between Academia and Practitioners

ERIC Educational Resources Information Center

Gera, Rajat

2012-01-01

Purpose: The paper intends to identify the causes or gaps in transfer of managerial knowledge between academia and practitioners and to develop a framework that overcomes the gaps through knowledge management, information technology and human resource practices. The paper aims to suggest a strategic approach based on the knowledge transfer cycle.…

An Interactive Medical Knowledge Assistant

NASA Astrophysics Data System (ADS)

Czejdo, Bogdan D.; Baszun, Mikolaj

This paper describes an interactive medical knowledge assistant that can help a doctor or a patient in making important health related decisions. The system is Web based and consists of several modules, including a medical knowledge base, a doctor interface module, patient interface module and a the main module of the medical knowledge assistant. The medical assistant is designed to help interpret the fuzzy data using rough sets approach. The patient interface includes sub-system for real time monitoring of patients' health parameters and sending them to the main module of the medical knowledge assistant.

Putting knowledge to work: a new approach.

PubMed

Evans, Karen; Guile, David; Harris, Judy; Allan, Helen

2010-04-01

Approaches to the longstanding challenges of 'integrating' subject-based and work-based knowledge have typically focused on questions of how learning can be 'transferred' from one setting to another, relating the assumed 'abstract' nature of theory to the assumed 'real' nature of practice. This is often seen as a single movement as encapsulated in the term 'from theory to practice'. The authors have developed a fresh approach that concentrates on different forms of knowledge and the ways in which these are contextualised and 're-contextualised' in movements between different sites of learning in colleges and workplaces. While the research has been carried out in a range of professional fields outside nursing, the arguments put forward by the authors are relevant to continuing debates within nursing around the theory-practice gap. The aim has been to explore how the subject-based and work-based aspects of a curriculum or learning programme can articulate with one another more effectively. The potential of the 're-contextualisation' approach for nurse education is outlined, with a view to further research. The original research was sponsored by the London Chamber of Commerce and Industry Commercial Education Trust and the Economic and Social Research Council Teaching and Learning Research Programme.

A data structure and algorithm for fault diagnosis

NASA Technical Reports Server (NTRS)

Bosworth, Edward L., Jr.

1987-01-01

Results of preliminary research on the design of a knowledge based fault diagnosis system for use with on-orbit spacecraft such as the Hubble Space Telescope are presented. A candidate data structure and associated search algorithm from which the knowledge based system can evolve is discussed. This algorithmic approach will then be examined in view of its inability to diagnose certain common faults. From that critique, a design for the corresponding knowledge based system will be given.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

What Are the Effects of Teaching Evidence-Based Health Care (EBHC)? Overview of Systematic Reviews

PubMed Central

Young, Taryn; Rohwer, Anke; Volmink, Jimmy; Clarke, Mike

2014-01-01

Background An evidence-based approach to health care is recognized internationally as a key competency for healthcare practitioners. This overview systematically evaluated and organized evidence from systematic reviews on teaching evidence-based health care (EBHC). Methods/Findings We searched for systematic reviews evaluating interventions for teaching EBHC to health professionals compared to no intervention or different strategies. Outcomes covered EBHC knowledge, skills, attitudes, practices and health outcomes. Comprehensive searches were conducted in April 2013. Two reviewers independently selected eligible reviews, extracted data and evaluated methodological quality. We included 16 systematic reviews, published between 1993 and 2013. There was considerable overlap across reviews. We found that 171 source studies included in the reviews related to 81 separate studies, of which 37 are in more than one review. Studies used various methodologies to evaluate educational interventions of varying content, format and duration in undergraduates, interns, residents and practicing health professionals. The evidence in the reviews showed that multifaceted, clinically integrated interventions, with assessment, led to improvements in knowledge, skills and attitudes. Interventions improved critical appraisal skills and integration of results into decisions, and improved knowledge, skills, attitudes and behaviour amongst practicing health professionals. Considering single interventions, EBHC knowledge and attitude were similar for lecture-based versus online teaching. Journal clubs appeared to increase clinical epidemiology and biostatistics knowledge and reading behavior, but not appraisal skills. EBHC courses improved appraisal skills and knowledge. Amongst practicing health professionals, interactive online courses with guided critical appraisal showed significant increase in knowledge and appraisal skills. A short workshop using problem-based approaches, compared to no intervention, increased knowledge but not appraisal skills. Conclusions EBHC teaching and learning strategies should focus on implementing multifaceted, clinically integrated approaches with assessment. Future rigorous research should evaluate minimum components for multifaceted interventions, assessment of medium to long-term outcomes, and implementation of these interventions. PMID:24489771

Process-Based Mission Assurance- Knowledge Management System

NASA Astrophysics Data System (ADS)

Kantzes, Zachary S.; Wander, Stephen; Otero, Suzanne; Vantine, William; Stuart, Richard

2005-12-01

The Process-Based Mission Assurance - Knowledge Management System (PBMA-KMS) implemented at the National Aeronautics and Space Administration (NASA) focuses on the practical application of the knowledge management (KM) theory and is based on a systems engineering management approach coupled to a continual improvement and risk management philosophy. Not to be confused with an Agency mandate, an intense focus has been placed on grassroots input to the future of the product. By providing emphasis to both Agency safety and mission success objectives and individual users' needs, the PBMA-KMS team has been able to be both reactive to Agency requirements and proactive to the needs of the community.PBMA-KMS is an excellent case study on how to use new approaches to facilitate and integrate safety into the culture of an organization. Principle discussion topics include: • Overarching themes,• Tactical approaches,• Highlights of key functionalities, and• Agency KM approach of managed Darwinism.PBMA-KMS can show how, by providing top-level guidance along with the necessary tools and support, the organization not only receives immediate value, but the long-ranging benefits of a more experienced, effective, and engaged workforce.

Automated Induction Of Rule-Based Neural Networks

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J.; Goodman, Rodney M.

1994-01-01

Prototype expert systems implemented in software and are functionally equivalent to neural networks set up automatically and placed into operation within minutes following information-theoretic approach to automated acquisition of knowledge from large example data bases. Approach based largely on use of ITRULE computer program.

Knowledge acquisition and learning process description in context of e-learning

NASA Astrophysics Data System (ADS)

Kiselev, B. G.; Yakutenko, V. A.; Yuriev, M. A.

2017-01-01

This paper investigates the problem of design of e-learning and MOOC systems. It describes instructional design-based approaches to e-learning systems design: IMS Learning Design, MISA and TELOS. To solve this problem we present Knowledge Field of Educational Environment with Competence boundary conditions - instructional engineering method for self-learning systems design. It is based on the simplified TELOS approach and enables a user to create their individual learning path by choosing prerequisite and target competencies. The paper provides the ontology model for the described instructional engineering method, real life use cases and the classification of the presented model. Ontology model consists of 13 classes and 15 properties. Some of them are inherited from Knowledge Field of Educational Environment and some are new and describe competence boundary conditions and knowledge validation objects. Ontology model uses logical constraints and is described using OWL 2 standard. To give TELOS users better understanding of our approach we list mapping between TELOS and KFEEC.

Enhancing Interprofessional Education With Team-Based Learning.

PubMed

Buhse, Marijean; Della Ratta, Carol

Interprofessional education (IPE) has gained momentum across health profession schools in simulation and clinical settings. Exploring interprofessional experiences in the classroom setting may further enhance collaborative skills while advancing clinical knowledge. The authors describe an innovative approach to IPE to teach chronic care concepts to graduate nursing, physician assistant, and public health students. Enhancing IPE with a team-based learning approach resulted in improved knowledge of chronic care management, student perceptions of mutual respect, and perceived development of communication and teamwork skills.

How much expert knowledge is it worth to put in conceptual hydrological models?

NASA Astrophysics Data System (ADS)

Antonetti, Manuel; Zappa, Massimiliano

2017-04-01

Both modellers and experimentalists agree on using expert knowledge to improve our conceptual hydrological simulations on ungauged basins. However, they use expert knowledge differently for both hydrologically mapping the landscape and parameterising a given hydrological model. Modellers use generally very simplified (e.g. topography-based) mapping approaches and put most of the knowledge for constraining the model by defining parameter and process relational rules. In contrast, experimentalists tend to invest all their detailed and qualitative knowledge about processes to obtain a spatial distribution of areas with different dominant runoff generation processes (DRPs) as realistic as possible, and for defining plausible narrow value ranges for each model parameter. Since, most of the times, the modelling goal is exclusively to simulate runoff at a specific site, even strongly simplified hydrological classifications can lead to satisfying results due to equifinality of hydrological models, overfitting problems and the numerous uncertainty sources affecting runoff simulations. Therefore, to test to which extent expert knowledge can improve simulation results under uncertainty, we applied a typical modellers' modelling framework relying on parameter and process constraints defined based on expert knowledge to several catchments on the Swiss Plateau. To map the spatial distribution of the DRPs, mapping approaches with increasing involvement of expert knowledge were used. Simulation results highlighted the potential added value of using all the expert knowledge available on a catchment. Also, combinations of event types and landscapes, where even a simplified mapping approach can lead to satisfying results, were identified. Finally, the uncertainty originated by the different mapping approaches was compared with the one linked to meteorological input data and catchment initial conditions.

Making Pedagogy Tangible: Developing Skills and Knowledge Using a Team Teaching and Blended Learning Approach

ERIC Educational Resources Information Center

Crawford, Renée; Jenkins, Louise E.

2018-01-01

In an era of accountability government and industry bodies are mandating that teacher education programs provide evidence of their impact. This paper provides an example of evidence-based practice, exploring how a team teaching and blended learning approach influenced the development of pre-service teachers (PSTs) competency skills and knowledge.…

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

ERIC Educational Resources Information Center

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…

Intercultural Communication Competence through Experiential Learning: The Importance of Student-Initiated Strategies and Dialogic Encounters

ERIC Educational Resources Information Center

Taylor, Josephine Ann

2007-01-01

Approaches to intercultural communication competence (ICC) generally argue the need for objective knowledge about another culture as well as knowledge about and the ability to achieve appropriate behaviors of that target culture. Most of these approaches continue to base themselves on a conception of culture as comprehensive but static.…

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

ERIC Educational Resources Information Center

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…

Ambulatory Morning Report: A Case-Based Method of Teaching EBM Through Experiential Learning.

PubMed

Luciano, Gina L; Visintainer, Paul F; Kleppel, Reva; Rothberg, Michael B

2016-02-01

Evidence-based medicine (EBM) skills are important to daily practice, but residents generally feel unskilled incorporating EBM into practice. The Kolb experiential learning theory, as applied to curricular planning, offers a unique methodology to help learners build an EBM skill set based on clinical experiences. We sought to blend the learner-centered, case-based merits of the morning report with an experientially based EBM curriculum. We describe and evaluate a patient-centered ambulatory morning report combining the User's Guides to the Medical Literature approach to EBM and experiential learning theory in the internal medicine department at Baystate Medical Center. The Kolb experiential learning theory postulates that experience transforms knowledge; within that premise we designed a curriculum to build EBM skills incorporating residents' patient encounters. By developing structured clinical questions based on recent clinical problems, residents activate prior knowledge. Residents acquire new knowledge through selection and evaluation of an article that addresses the structured clinical questions. Residents then apply and use new knowledge in future patient encounters. To assess the curriculum, we designed an 18-question EBM test, which addressed applied knowledge and EBM skills based on the User's Guides approach. Of the 66 residents who could participate in the curriculum, 61 (92%) completed the test. There was a modest improvement in EBM knowledge, primarily during the first year of training. Our experiential curriculum teaches EBM skills essential to clinical practice. The curriculum differs from traditional EBM curricula in that ours blends experiential learning with an EBM skill set; learners use new knowledge in real time.

Design of CIAO, a research program to support the development of an integrated approach to prevent overweight and obesity in the Netherlands.

PubMed

van Koperen, Marije Tm; van der Kleij, Rianne Mjj; Renders, Carry Cm; Crone, Matty Mr; Hendriks, Anna-Marie Am; Jansen, Maria M; van de Gaar, Vivian Vm; Raat, Hein Jh; Ruiter, Emilie Elm; Molleman, Gerard Grm; Schuit, Jantine Aj; Seidell, Jacob Jc

2014-01-01

The aim of this paper is to describe the research aims, concepts and methods of the research Consortium Integrated Approach of Overweight (CIAO). CIAO is a concerted action of five Academic Collaborative Centres, local collaborations between academic institutions, regional public health services, local authorities and other relevant sectors in the Netherlands. Prior research revealed lacunas in knowledge of and skills related to five elements of the integrated approach of overweight prevention in children (based upon the French EPODE approach), namely political support, parental education, implementation, social marketing and evaluation. CIAO aims to gain theoretical and practical insight of these elements through five sub-studies and to develop, based on these data, a framework for monitoring and evaluation. For this research program, mixed methods are used in all the five sub-studies. First, problem specification through literature research and consultation of stakeholders, experts, health promotion specialists, parents and policy makers will be carried out. Based on this information, models, theoretical frameworks and practical instruments will be developed, tested and evaluated in the communities that implement the integrated approach to prevent overweight in children. Knowledge obtained from these studies and insights from experts and stakeholders will be combined to create an evaluation framework to evaluate the integrated approach at central, local and individual levels that will be applicable to daily practice. This innovative research program stimulates sub-studies to collaborate with local stakeholders and to share and integrate their knowledge, methodology and results. Therefore, the output of this program (both knowledge and practical tools) will be matched and form building blocks of a blueprint for a local evidence- and practice-based integrated approach towards prevention of overweight in children. The output will then support various communities to further optimize the implementation and subsequently the effects of this approach.

Problem-Based Learning and Civic Engagement in Undergraduate Education

ERIC Educational Resources Information Center

Keegan, Louise C.; Losardo, Angela; McCullough, Kim C.

2017-01-01

Problem-based learning and civic engagement are complementary constructivist andragogical approaches that emphasize active learning by guiding students to develop their own understanding and knowledge of a topic through experience and reflection. By providing examples of clinical cases and community-based experiences, these approaches can enhance…

Knowledge 'Translation' as social learning: negotiating the uptake of research-based knowledge in practice.

PubMed

Salter, K L; Kothari, A

2016-02-29

Knowledge translation and evidence-based practice have relied on research derived from clinical trials, which are considered to be methodologically rigorous. The result is practice recommendations based on a narrow view of evidence. We discuss how, within a practice environment, in fact individuals adopt and apply new evidence derived from multiple sources through ongoing, iterative learning cycles. The discussion is presented in four sections. After elaborating on the multiple forms of evidence used in practice, in section 2 we argue that the practitioner derives contextualized knowledge through reflective practice. Then, in section 3, the focus shifts from the individual to the team with consideration of social learning and theories of practice. In section 4 we discuss the implications of integrative and negotiated knowledge exchange and generation within the practice environment. Namely, how can we promote the use of research within a team-based, contextualized knowledge environment? We suggest support for: 1) collaborative learning environments for active learning and reflection, 2) engaged scholarship approaches so that practice can inform research in a collaborative manner and 3) leveraging authoritative opinion leaders for their clinical expertise during the shared negotiation of knowledge and research. Our approach also points to implications for studying evidence-informed practice: the identification of practice change (as an outcome) ought to be supplemented with understandings of how and when social negotiation processes occur to achieve integrated knowledge. This article discusses practice knowledge as dependent on the practice context and on social learning processes, and suggests how research knowledge uptake might be supported from this vantage point.

Knowledge-based nursing diagnosis

NASA Astrophysics Data System (ADS)

Roy, Claudette; Hay, D. Robert

1991-03-01

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

A structural informatics approach to mine kinase knowledge bases.

PubMed

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.

Community health professionals' dementia knowledge, attitudes and care approach: a cross-sectional survey in Changsha, China.

PubMed

Wang, Yao; Xiao, Lily Dongxia; Luo, Yang; Xiao, Shui-Yuan; Whitehead, Craig; Davies, Owen

2018-05-25

Community health professionals play a significant role in dementia care. However, little is known about community health professionals' capacity in dementia care, especially in low and middle-income countries. The aim of the present study was to assess community health professionals' dementia knowledge, attitudes and care approach in China, a country with the largest population of people with dementia in the world and where community based dementia care services are much needed. A cross-sectional survey was conducted. 450 health professionals were recruited into the study using random sampling from community health service centres in Changsha, China. Their knowledge, attitudes and care approach were assessed utilising the Chinese version of the Alzheimer's Disease Knowledge Scale, Dementia Care Attitude Scale and Approach to Advanced Dementia Care Questionnaire respectively. A total of 390 participants returned the questionnaire (response rate 87%). Age, education, professional group and care experience were associated with knowledge scores, and overall dementia knowledge was poor. Attitudes were generally positive and influenced by age, professional group, gender and care experience. The experience of caring for people with dementia was positively associated with a person-centred care approach, although the participants tended not to use a person-centred care approach. A statistically significant association was found between knowledge and attitudes (r = 0.379, P < 0.001), and between attitudes and care approach (r = 0.143, P < 0.001). However, dementia knowledge has no relationship with a person-centred approach. Community health professionals showed generally positive attitudes towards people with dementia. However, they demonstrated poor dementia knowledge and tended not to use a person-centred care approach. The results suggest that a multifaceted approach consisting of educational interventions for community health professionals, and policy and resource development to meet the demand for community dementia care services, is urgently needed in China.

Discovering Knowledge from Noisy Databases Using Genetic Programming.

ERIC Educational Resources Information Center

Wong, Man Leung; Leung, Kwong Sak; Cheng, Jack C. Y.

2000-01-01

Presents a framework that combines Genetic Programming and Inductive Logic Programming, two approaches in data mining, to induce knowledge from noisy databases. The framework is based on a formalism of logic grammars and is implemented as a data mining system called LOGENPRO (Logic Grammar-based Genetic Programming System). (Contains 34…

Applying Case-Based Reasoning in Knowledge Management to Support Organizational Performance

ERIC Educational Resources Information Center

Wang, Feng-Kwei

2006-01-01

Research and practice in human performance technology (HPT) has recently accelerated the search for innovative approaches to supplement or replace traditional training interventions for improving organizational performance. This article examines a knowledge management framework built upon the theories and techniques of case-based reasoning (CBR)…

Competence-Based Knowledge Structures for Personalised Learning

ERIC Educational Resources Information Center

Heller, Jurgen; Steiner, Christina; Hockemeyer, Cord; Albert, Dietrich

2006-01-01

Competence-based extensions of Knowledge Space Theory are suggested as a formal framework for implementing key features of personalised learning in technology-enhanced learning. The approach links learning objects and assessment problems to the relevant skills that are taught or required. Various ways to derive these skills from domain ontologies…

Leveraging Event Reporting Through Knowledge Support: A Knowledge-Based Approach to Promoting Patient Fall Prevention.

PubMed

Yao, Bin; Kang, Hong; Miao, Qi; Zhou, Sicheng; Liang, Chen; Gong, Yang

2017-01-01

Patient falls are a common safety event type that impairs the healthcare quality. Strategies including solution tools and reporting systems for preventing patient falls have been developed and implemented in the U.S. However, the current strategies do not include timely knowledge support, which is in great need in bridging the gap between reporting and learning. In this study, we constructed a knowledge base of fall events by combining expert-reviewed fall prevention solutions and then integrating them into a reporting system. The knowledge base enables timely and tailored knowledge support and thus will serve as a prevailing fall prevention tool. This effort holds promise in making knowledge acquisition and management a routine process for enhancing the reporting and understanding of patient safety events.

Providing Knowledge Recommendations: An Approach for Informal Electronic Mentoring

ERIC Educational Resources Information Center

Colomo-Palacios, Ricardo; Casado-Lumbreras, Cristina; Soto-Acosta, Pedro; Misra, Sanjay

2014-01-01

The use of Web 2.0 technologies for knowledge management is invading the corporate sphere. The Web 2.0 is the most adopted knowledge transfer tool within knowledge intensive firms and is starting to be used for mentoring. This paper presents IM-TAG, a Web 2.0 tool, based on semantic technologies, for informal mentoring. The tool offers…

Educational Administration and the Management of Knowledge: 1980 Revisited

ERIC Educational Resources Information Center

Bates, Richard

2013-01-01

This paper revisits the thesis of a 1980 paper that suggested a new approach to educational administration based upon the New Sociology of Education. In particular it updates answers to the six key questions asked by that paper: what counts as knowledge; how is what counts as knowledge organised; how is what counts as knowledge transmitted; how is…

An expert system prototype for aiding in the development of software functional requirements for NASA Goddard's command management system: A case study and lessons learned

NASA Technical Reports Server (NTRS)

Liebowitz, Jay

1986-01-01

At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.

Assessing Metacognitive Knowledge in Web-Based Call: A Neural Network Approach

ERIC Educational Resources Information Center

Yeh, Siou-Wen; Lo, Jia-Jiunn

2005-01-01

The assessment of learners' metacognitive knowledge level is crucial when developing computer-assisted language learning systems. Currently, many systems assess learners' metacognitive knowledge level with pre-instructional questionnaires or metacognitive interviews. However, learners with limited language proficiency may be at a disadvantage in…

New approach to generating insights for aging research based on literature mining and knowledge integration

PubMed Central

Kwon, Yeondae; Natori, Yukikazu

2017-01-01

The proportion of the elderly population in most countries worldwide is increasing dramatically. Therefore, social interest in the fields of health, longevity, and anti-aging has been increasing as well. However, the basic research results obtained from a reductionist approach in biology and a bioinformatic approach in genome science have limited usefulness for generating insights on future health, longevity, and anti-aging-related research on a case by case basis. We propose a new approach that uses our literature mining technique and bioinformatics, which lead to a better perspective on research trends by providing an expanded knowledge base to work from. We demonstrate that our approach provides useful information that deepens insights on future trends which differs from data obtained conventionally, and this methodology is already paving the way for a new field in aging-related research based on literature mining. One compelling example of this is how our new approach can be a useful tool in drug repositioning. PMID:28817730

A web-based knowledge management system integrating Western and Traditional Chinese Medicine for relational medical diagnosis.

PubMed

Herrera-Hernandez, Maria C; Lai-Yuen, Susana K; Piegl, Les A; Zhang, Xiao

2016-10-26

This article presents the design of a web-based knowledge management system as a training and research tool for the exploration of key relationships between Western and Traditional Chinese Medicine, in order to facilitate relational medical diagnosis integrating these mainstream healing modalities. The main goal of this system is to facilitate decision-making processes, while developing skills and creating new medical knowledge. Traditional Chinese Medicine can be considered as an ancient relational knowledge-based approach, focusing on balancing interrelated human functions to reach a healthy state. Western Medicine focuses on specialties and body systems and has achieved advanced methods to evaluate the impact of a health disorder on the body functions. Identifying key relationships between Traditional Chinese and Western Medicine opens new approaches for health care practices and can increase the understanding of human medical conditions. Our knowledge management system was designed from initial datasets of symptoms, known diagnosis and treatments, collected from both medicines. The datasets were subjected to process-oriented analysis, hierarchical knowledge representation and relational database interconnection. Web technology was implemented to develop a user-friendly interface, for easy navigation, training and research. Our system was prototyped with a case study on chronic prostatitis. This trial presented the system's capability for users to learn the correlation approach, connecting knowledge in Western and Traditional Chinese Medicine by querying the database, mapping validated medical information, accessing complementary information from official sites, and creating new knowledge as part of the learning process. By addressing the challenging tasks of data acquisition and modeling, organization, storage and transfer, the proposed web-based knowledge management system is presented as a tool for users in medical training and research to explore, learn and update relational information for the practice of integrated medical diagnosis. This proposal in education has the potential to enable further creation of medical knowledge from both Traditional Chinese and Western Medicine for improved care providing. The presented system positively improves the information visualization, learning process and knowledge sharing, for training and development of new skills for diagnosis and treatment, and a better understanding of medical diseases. © IMechE 2016.

Improving management of small natural features on private lands by negotiating the science–policy boundary for Maine vernal pools

PubMed Central

Calhoun, Aram J. K.; Jansujwicz, Jessica S.; Bell, Kathleen P.; Hunter, Malcolm L.

2014-01-01

Vernal pools are far more important for providing ecosystem services than one would predict based on their small size. However, prevailing resource-management strategies are not effectively conserving pools and other small natural features on private lands. Solutions are complicated by tensions between private property and societal rights, uncertainties over resource location and function, diverse stakeholders, and fragmented regulatory authority. The development and testing of new conservation approaches that link scientific knowledge, stakeholder decision-making, and conservation outcomes are important responses to this conservation dilemma. Drawing from a 15-y history of vernal pool conservation efforts in Maine, we describe the coevolution of pool conservation and research approaches, focusing on how research-based knowledge was produced and used in support of management decisions. As management shifted from reactive, top-down approaches to proactive and flexible approaches, research shifted from an ecology-focused program to an interdisciplinary program based on social–ecological systems. The most effective strategies for linking scientific knowledge with action changed as the decision-makers, knowledge needs, and context for vernal pool management advanced. Interactions among stakeholders increased the extent to which knowledge was coproduced and shifted the objective of stakeholder engagement from outreach to research collaboration and development of innovative conservation approaches. New conservation strategies were possible because of the flexible, solutions-oriented collaborations and trust between scientists and decision-makers (fostered over 15 y) and interdisciplinary, engaged research. Solutions to the dilemma of conserving small natural features on private lands, and analogous sustainability science challenges, will benefit from repeated negotiations of the science–policy boundary. PMID:25002496

Semantic relatedness for evaluation of course equivalencies

NASA Astrophysics Data System (ADS)

Yang, Beibei

Semantic relatedness, or its inverse, semantic distance, measures the degree of closeness between two pieces of text determined by their meaning. Related work typically measures semantics based on a sparse knowledge base such as WordNet or Cyc that requires intensive manual efforts to build and maintain. Other work is based on a corpus such as the Brown corpus, or more recently, Wikipedia. This dissertation proposes two approaches to applying semantic relatedness to the problem of suggesting transfer course equivalencies. Two course descriptions are given as input to feed the proposed algorithms, which output a value that can be used to help determine if the courses are equivalent. The first proposed approach uses traditional knowledge sources such as WordNet and corpora for courses from multiple fields of study. The second approach uses Wikipedia, the openly-editable encyclopedia, and it focuses on courses from a technical field such as Computer Science. This work shows that it is promising to adapt semantic relatedness to the education field for matching equivalencies between transfer courses. A semantic relatedness measure using traditional knowledge sources such as WordNet performs relatively well on non-technical courses. However, due to the "knowledge acquisition bottleneck," such a resource is not ideal for technical courses, which use an extensive and growing set of technical terms. To address the problem, this work proposes a Wikipedia-based approach which is later shown to be more correlated to human judgment compared to previous work.

Knowledge-based fragment binding prediction.

PubMed

Tang, Grace W; Altman, Russ B

2014-04-01

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.

Knowledge-based Fragment Binding Prediction

PubMed Central

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

A Loud Silence: Working with Research-Based Theatre and A/R/Tography

ERIC Educational Resources Information Center

Lea, Graham W.; Belliveau, George; Wager, Amanda; Beck, Jaime L.

2011-01-01

Arts-based approaches to research have emerged as an integral component of current scholarship in the social sciences, education, health research, and humanities. Integrating arts-based methods and methodologies with research generates possibilities for fresh approaches for creating, translating, and exchanging knowledge (Barone & Eisner, 1997;…

Novel approaches to effects-based monitoring: 21st century tools for bio-effects prediction and surveillance

EPA Science Inventory

Effects-based monitoring (EBM) has been employed as a complement to chemical monitoring to help address knowledge gaps between chemical occurrence and biological effects. We have piloted several pathway-based approaches to EBM, that utilize modern bioinformatic and high throughpu...

Advanced Software Development Workstation Project

NASA Technical Reports Server (NTRS)

Lee, Daniel

1989-01-01

The Advanced Software Development Workstation Project, funded by Johnson Space Center, is investigating knowledge-based techniques for software reuse in NASA software development projects. Two prototypes have been demonstrated and a third is now in development. The approach is to build a foundation that provides passive reuse support, add a layer that uses domain-independent programming knowledge, add a layer that supports the acquisition of domain-specific programming knowledge to provide active support, and enhance maintainability and modifiability through an object-oriented approach. The development of new application software would use specification-by-reformulation, based on a cognitive theory of retrieval from very long-term memory in humans, and using an Ada code library and an object base. Current tasks include enhancements to the knowledge representation of Ada packages and abstract data types, extensions to support Ada package instantiation knowledge acquisition, integration with Ada compilers and relational databases, enhancements to the graphical user interface, and demonstration of the system with a NASA contractor-developed trajectory simulation package. Future work will focus on investigating issues involving scale-up and integration.

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

PubMed Central

2014-01-01

Background 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. Results 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. Conclusion 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. PMID:24959206

Interactive Cumulative Burden Assessment: Engaging Stakeholders in an Adaptive, Participatory and Transdisciplinary Approach

PubMed Central

Shrestha, Rehana; van Maarseveen, Martin

2018-01-01

Cumulative burden assessment (CuBA) has the potential to inform planning and decision-making on health disparities related to multiple environmental burdens. However, scholars have raised concerns about the social complexity to be dealt with while conducting CuBA, suggesting that it should be addressed in an adaptive, participatory and transdisciplinary (APT) approach. APT calls for deliberation among stakeholders by engaging them in a process of social learning and knowledge co-production. We propose an interactive stakeholder-based approach that facilitates a science-based stakeholder dialogue as an interface for combining different knowledge domains and engendering social learning in CuBA processes. Our approach allows participants to interact with each other using a flexible and auditable CuBA model implemented within a shared workspace. In two workshops we explored the usefulness and practicality of the approach. Results show that stakeholders were enabled to deliberate on cumulative burdens collaboratively, to learn about the technical uncertainties and social challenges associated with CuBA, and to co-produce knowledge in a realm of both technical and societal challenges. The paper identifies potential benefits relevant for responding to social complexity in the CuBA and further recommends exploration of how our approach can enable or constraint social learning and knowledge co-production in CuBA processes under various institutional, social and political contexts. PMID:29401676

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

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

PubMed Central

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 healthcare settings. PMID:23514237

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

PubMed

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.

A Symbolic Approach Using Feature Construction Capable of Acquiring Information/Knowledge for Building Expert Systems.

ERIC Educational Resources Information Center

Major, Raymond L.

1998-01-01

Presents a technique for developing a knowledge-base of information to use in an expert system. Proposed approach employs a popular machine-learning algorithm along with a method for forming a finite number of features or conjuncts of at most n primitive attributes. Illustrates this procedure by examining qualitative information represented in a…

Knowledge Ecology for Conceptual Growth: Teachers as Active Agents in Developing a Pluriliteracies Approach to Teaching for Learning (PTL)

ERIC Educational Resources Information Center

Coyle, Do; Halbach, Ana; Meyer, Oliver; Schuck, Kevin

2018-01-01

This article explores how a group of educators and researchers enacted an inclusive process of conceptual growth involving teachers and teacher educators as active agents, knowledge builders and meaning-makers in the development of a Pluriliteracies approach to Teaching for Learning (PTL). The evolution of a working model based on five emergent…

Unsupervised Medical Entity Recognition and Linking in Chinese Online Medical Text

PubMed Central

Gan, Liang; Cheng, Mian; Wu, Quanyuan

2018-01-01

Online medical text is full of references to medical entities (MEs), which are valuable in many applications, including medical knowledge-based (KB) construction, decision support systems, and the treatment of diseases. However, the diverse and ambiguous nature of the surface forms gives rise to a great difficulty for ME identification. Many existing solutions have focused on supervised approaches, which are often task-dependent. In other words, applying them to different kinds of corpora or identifying new entity categories requires major effort in data annotation and feature definition. In this paper, we propose unMERL, an unsupervised framework for recognizing and linking medical entities mentioned in Chinese online medical text. For ME recognition, unMERL first exploits a knowledge-driven approach to extract candidate entities from free text. Then, the categories of the candidate entities are determined using a distributed semantic-based approach. For ME linking, we propose a collaborative inference approach which takes full advantage of heterogenous entity knowledge and unstructured information in KB. Experimental results on real corpora demonstrate significant benefits compared to recent approaches with respect to both ME recognition and linking. PMID:29849994

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Navigating complexity through knowledge coproduction: Mainstreaming ecosystem services into disaster risk reduction.

PubMed

Reyers, Belinda; Nel, Jeanne L; O'Farrell, Patrick J; Sitas, Nadia; Nel, Deon C

2015-06-16

Achieving the policy and practice shifts needed to secure ecosystem services is hampered by the inherent complexities of ecosystem services and their management. Methods for the participatory production and exchange of knowledge offer an avenue to navigate this complexity together with the beneficiaries and managers of ecosystem services. We develop and apply a knowledge coproduction approach based on social-ecological systems research and assess its utility in generating shared knowledge and action for ecosystem services. The approach was piloted in South Africa across four case studies aimed at reducing the risk of disasters associated with floods, wildfires, storm waves, and droughts. Different configurations of stakeholders (knowledge brokers, assessment teams, implementers, and bridging agents) were involved in collaboratively designing each study, generating and exchanging knowledge, and planning for implementation. The approach proved useful in the development of shared knowledge on the sizable contribution of ecosystem services to disaster risk reduction. This knowledge was used by stakeholders to design and implement several actions to enhance ecosystem services, including new investments in ecosystem restoration, institutional changes in the private and public sector, and innovative partnerships of science, practice, and policy. By bringing together multiple disciplines, sectors, and stakeholders to jointly produce the knowledge needed to understand and manage a complex system, knowledge coproduction approaches offer an effective avenue for the improved integration of ecosystem services into decision making.

Navigating complexity through knowledge coproduction: Mainstreaming ecosystem services into disaster risk reduction

PubMed Central

Reyers, Belinda; Nel, Jeanne L.; O’Farrell, Patrick J.; Sitas, Nadia; Nel, Deon C.

2015-01-01

Achieving the policy and practice shifts needed to secure ecosystem services is hampered by the inherent complexities of ecosystem services and their management. Methods for the participatory production and exchange of knowledge offer an avenue to navigate this complexity together with the beneficiaries and managers of ecosystem services. We develop and apply a knowledge coproduction approach based on social–ecological systems research and assess its utility in generating shared knowledge and action for ecosystem services. The approach was piloted in South Africa across four case studies aimed at reducing the risk of disasters associated with floods, wildfires, storm waves, and droughts. Different configurations of stakeholders (knowledge brokers, assessment teams, implementers, and bridging agents) were involved in collaboratively designing each study, generating and exchanging knowledge, and planning for implementation. The approach proved useful in the development of shared knowledge on the sizable contribution of ecosystem services to disaster risk reduction. This knowledge was used by stakeholders to design and implement several actions to enhance ecosystem services, including new investments in ecosystem restoration, institutional changes in the private and public sector, and innovative partnerships of science, practice, and policy. By bringing together multiple disciplines, sectors, and stakeholders to jointly produce the knowledge needed to understand and manage a complex system, knowledge coproduction approaches offer an effective avenue for the improved integration of ecosystem services into decision making. PMID:26082541

Information Sharing and Knowledge Sharing as Communicative Activities

ERIC Educational Resources Information Center

Savolainen, Reijo

2017-01-01

Introduction: This paper elaborates the picture of information sharing and knowledge sharing as forms of communicative activity. Method: A conceptual analysis was made to find out how researchers have approached information sharing and knowledge sharing from the perspectives of transmission and ritual. The findings are based on the analysis of one…

Conceptualising Online Knowledge Sharing: What Teachers' Perceptions Can Tell Us

ERIC Educational Resources Information Center

Hood, Nina

2017-01-01

This study questions the current dependence on theories of social learning and communities of practice in research on teachers' online learning and online knowledge-sharing behaviour. It employs the interpretative approach to examine how teachers conceptualise their engagement with two USA-based online knowledge-sharing platforms within the…

A Qualitative Approach to Assessing Technological Pedagogical Content Knowledge

ERIC Educational Resources Information Center

Groth, Randall; Spickler, Donald; Bergner, Jennifer; Bardzell, Michael

2009-01-01

Because technological pedagogical content knowledge is becoming an increasingly important construct in the field of teacher education, there is a need for assessment mechanisms that capture teachers' development of this portion of the knowledge base for teaching. The paper describes a proposal drawing on qualitative data produced during lesson…

Technological Pedagogical Content Knowledge Development: Integrating Technology with a Research Teaching Perspective

ERIC Educational Resources Information Center

Guerra, Cecilia; Moreira, Antonio; Vieira, Rui

2017-01-01

Technological Pedagogical Content Knowledge (TPCK) represents the teachers' professional knowledge needed to integrate technology in education. Following a design-based approach this study describes the strategies for designing and assessing an in-service science teacher education course. Data was obtained through interviews, questionnaires, using…

A Knowledge-Modeling Approach to Integrate Multiple Clinical Practice Guidelines to Provide Evidence-Based Clinical Decision Support for Managing Comorbid Conditions.

PubMed

Abidi, Samina

2017-10-26

Clinical management of comorbidities is a challenge, especially in a clinical decision support setting, as it requires the safe and efficient reconciliation of multiple disease-specific clinical procedures to formulate a comorbid therapeutic plan that is both effective and safe for the patient. In this paper we pursue the integration of multiple disease-specific Clinical Practice Guidelines (CPG) in order to manage co-morbidities within a computerized Clinical Decision Support System (CDSS). We present a CPG integration framework-termed as COMET (Comorbidity Ontological Modeling & ExecuTion) that manifests a knowledge management approach to model, computerize and integrate multiple CPG to yield a comorbid CPG knowledge model that upon execution can provide evidence-based recommendations for handling comorbid patients. COMET exploits semantic web technologies to achieve (a) CPG knowledge synthesis to translate a paper-based CPG to disease-specific clinical pathways (CP) that include specialized co-morbidity management procedures based on input from domain experts; (b) CPG knowledge modeling to computerize the disease-specific CP using a Comorbidity CPG ontology; (c) CPG knowledge integration by aligning multiple ontologically-modeled CP to develop a unified comorbid CPG knowledge model; and (e) CPG knowledge execution using reasoning engines to derive CPG-mediated recommendations for managing patients with comorbidities. We present a web-accessible COMET CDSS that provides family physicians with CPG-mediated comorbidity decision support to manage Atrial Fibrillation and Chronic Heart Failure. We present our qualitative and quantitative analysis of the knowledge content and usability of COMET CDSS.

Semi-automated knowledge discovery: identifying and profiling human trafficking

NASA Astrophysics Data System (ADS)

Poelmans, Jonas; Elzinga, Paul; Ignatov, Dmitry I.; Kuznetsov, Sergei O.

2012-11-01

We propose an iterative and human-centred knowledge discovery methodology based on formal concept analysis. The proposed approach recognizes the important role of the domain expert in mining real-world enterprise applications and makes use of specific domain knowledge, including human intelligence and domain-specific constraints. Our approach was empirically validated at the Amsterdam-Amstelland police to identify suspects and victims of human trafficking in 266,157 suspicious activity reports. Based on guidelines of the Attorney Generals of the Netherlands, we first defined multiple early warning indicators that were used to index the police reports. Using concept lattices, we revealed numerous unknown human trafficking and loverboy suspects. In-depth investigation by the police resulted in a confirmation of their involvement in illegal activities resulting in actual arrestments been made. Our human-centred approach was embedded into operational policing practice and is now successfully used on a daily basis to cope with the vastly growing amount of unstructured information.

Cybernetics: A Possible Solution for the "Knowledge Gap" between "External" and "Internal" in Evaluation Processes

ERIC Educational Resources Information Center

Levin-Rozalis, Miri

2010-01-01

This paper addresses the issue of the knowledge gap between evaluators and the entity being evaluated: the dilemma of the knowledge of professional evaluators vs. the in-depth knowledge of the evaluated subjects. In order to optimize evaluative outcomes, the author suggests an approach based on ideas borrowed from the science of cybernetics as a…

Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

ERIC Educational Resources Information Center

Seeley, Karen M.

2004-01-01

This article examines the challenges specific to short-term intercultural treatments and recently developed approaches to intercultural treatments based on notions of cultural knowledge and cultural competence. The article introduces alternative approaches to short-term intercultural treatments based on ethnographic inquiry adapted for clinical…

Thematic Organizers as a Tool for Teaching from a Wholetheme Perspective.

ERIC Educational Resources Information Center

Iran-Nejad, Asghar

Learning in the wholetheme approach is defined as reorganizing one's own intuitive knowledge base, as opposed to storing facts. This presentation discusses several thematic organizers to illustrate their role as a teaching tool in helping learners reorganize their own intuitive knowledge base. Intimately tied to the brain's ground-figure processes…

ConMap: Investigating New Computer-Based Approaches to Assessing Conceptual Knowledge Structure in Physics.

ERIC Educational Resources Information Center

Beatty, Ian D.

There is a growing consensus among educational researchers that traditional problem-based assessments are not effective tools for diagnosing a student's knowledge state and for guiding pedagogical intervention, and that new tools grounded in the results of cognitive science research are needed. The ConMap ("Conceptual Mapping") project, described…

An Operational Approach for Building Learning Environments Supporting Cognitive Flexibility

ERIC Educational Resources Information Center

Chieu, Vu Minh

2007-01-01

Constructivism is a learning theory that states that people learn by actively constructing their own knowledge, based on prior knowledge. A significant number of ICT-based constructivist learning systems have been proposed in recent years. According to our analysis, those systems exhibit only a few constructivist principles, and a critical problem…

Measuring Teachers' Learning from a Problem-Based Learning Approach to Professional Development in Science Education

ERIC Educational Resources Information Center

Weizman, Ayelet; Covitt, Beth A.; Koehler, Matthew J.; Lundeberg, Mary A.; Oslund, Joy A.; Low, Mark R.; Eberhardt, Janet; Urban-Lurain, Mark

2008-01-01

In this study we measured changes in science teachers' conceptual science understanding (content knowledge) and pedagogical content knowledge (PCK) while participating in a problem-based learning (PBL) model of professional development. Teachers participated in a two-week long workshop followed by nine monthly meetings during one academic year…

Knowledge-based segmentation and feature analysis of hand and wrist radiographs

NASA Astrophysics Data System (ADS)

Efford, Nicholas D.

1993-07-01

The segmentation of hand and wrist radiographs for applications such as skeletal maturity assessment is best achieved by model-driven approaches incorporating anatomical knowledge. The reasons for this are discussed, and a particular frame-based or 'blackboard' strategy for the simultaneous segmentation of the hand and estimation of bone age via the TW2 method is described. The new approach is structured for optimum robustness and computational efficiency: features of interest are detected and analyzes in order of their size and prominence in the image, the largest and most distinctive being dealt with first, and the evidence generated by feature analysis is used to update a model of hand anatomy and hence guide later stages of the segmentation. Closed bone boundaries are formed by a hybrid technique combining knowledge-based, one-dimensional edge detection with model-assisted heuristic tree searching.

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Locally-Based Kernal PLS Smoothing to Non-Parametric Regression Curve Fitting

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Wheeler, Kevin; Korsmeyer, David (Technical Monitor)

2002-01-01

We present a novel smoothing approach to non-parametric regression curve fitting. This is based on kernel partial least squares (PLS) regression in reproducing kernel Hilbert space. It is our concern to apply the methodology for smoothing experimental data where some level of knowledge about the approximate shape, local inhomogeneities or points where the desired function changes its curvature is known a priori or can be derived based on the observed noisy data. We propose locally-based kernel PLS regression that extends the previous kernel PLS methodology by incorporating this knowledge. We compare our approach with existing smoothing splines, hybrid adaptive splines and wavelet shrinkage techniques on two generated data sets.

Motion Recognition and Modifying Motion Generation for Imitation Robot Based on Motion Knowledge Formation

NASA Astrophysics Data System (ADS)

Okuzawa, Yuki; Kato, Shohei; Kanoh, Masayoshi; Itoh, Hidenori

A knowledge-based approach to imitation learning of motion generation for humanoid robots and an imitative motion generation system based on motion knowledge learning and modification are described. The system has three parts: recognizing, learning, and modifying parts. The first part recognizes an instructed motion distinguishing it from the motion knowledge database by the continuous hidden markov model. When the motion is recognized as being unfamiliar, the second part learns it using locally weighted regression and acquires a knowledge of the motion. When a robot recognizes the instructed motion as familiar or judges that its acquired knowledge is applicable to the motion generation, the third part imitates the instructed motion by modifying a learned motion. This paper reports some performance results: the motion imitation of several radio gymnastics motions.

Just-in-Time Teaching, Just-in-Need Learning: Designing towards Optimized Pedagogical Outcomes

ERIC Educational Resources Information Center

Killi, Steinar; Morrison, Andrew

2015-01-01

Teaching methods are constantly being changed, new ones are developed and old methods have undergone a renaissance. Two main approaches to teaching prevail: a) lecture-based and project-based and b) an argumentative approach to known knowledge or learning by exploration. Today, there is a balance between these two approaches, and they are more…

A 5E Learning Cycle Approach-Based, Multimedia-Supplemented Instructional Unit for Structured Query Language

ERIC Educational Resources Information Center

Piyayodilokchai, Hongsiri; Panjaburee, Patcharin; Laosinchai, Parames; Ketpichainarong, Watcharee; Ruenwongsa, Pintip

2013-01-01

With the benefit of multimedia and the learning cycle approach in promoting effective active learning, this paper proposed a learning cycle approach-based, multimedia-supplemented instructional unit for Structured Query Language (SQL) for second-year undergraduate students with the aim of enhancing their basic knowledge of SQL and ability to apply…

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.

2013-01-01

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges thatmore » have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.« less

Public health situation awareness: toward a semantic approach

NASA Astrophysics Data System (ADS)

Mirhaji, Parsa; Richesson, Rachel L.; Turley, James P.; Zhang, Jiajie; Smith, Jack W.

2004-04-01

We propose a knowledge-based public health situation awareness system. The basis for this system is an explicit representation of public health situation awareness concepts and their interrelationships. This representation is based upon the users" (public health decision makers) cognitive model of the world, and optimized towards the efficacy of performance and relevance to the public health situation awareness processes and tasks. In our approach, explicit domain knowledge is the foundation for interpretation of public health data, as apposed to conventional systems where the statistical methods are the essence of the processes. Objectives: To develop a prototype knowledge-based system for public health situation awareness and to demonstrate the utility of knowledge intensive approaches in integration of heterogeneous information, eliminating the effects of incomplete and poor quality surveillance data, uncertainty in syndrome and aberration detection and visualization of complex information structures in public health surveillance settings, particularly in the context of bioterrorism (BT) preparedness. The system employs the Resource Definition Framework (RDF) and additional layers of more expressive languages to explicate the knowledge of domain experts into machine interpretable and computable problem-solving modules that can then guide users and computer systems in sifting through the most "relevant" data for syndrome and outbreak detection and investigation of root cause of the event. The Center for Biosecurity and Public Health Informatics Research is developing a prototype knowledge-based system around influenza, which has complex natural disease patterns, many public health implications, and is a potential agent for bioterrorism. The preliminary data from this effort may demonstrate superior performance in information integration, syndrome and aberration detection, information access through information visualization, and cross-domain investigation of the root causes of public health events.

Exploring the Impact of Prior Knowledge and Appropriate Feedback on Students' Perceived Cognitive Load and Learning Outcomes: Animation-Based Earthquakes Instruction

ERIC Educational Resources Information Center

Yeh, Ting-Kuang; Tseng, Kuan-Yun; Cho, Chung-Wen; Barufaldi, James P.; Lin, Mei-Shin; Chang, Chun-Yen

2012-01-01

The aim of this study was to develop an animation-based curriculum and to evaluate the effectiveness of animation-based instruction; the report involved the assessment of prior knowledge and the appropriate feedback approach, for the purpose of reducing perceived cognitive load and improving learning. The curriculum was comprised of five subunits…

A Research Agenda on Assessing and Remediating Home Dampness and Mold to Reduce Dampness-Related Health Effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendell, Mark J.

2015-06-01

This report briefly summarizes, based on recent review articles and selected more recent research reports, current scientific knowledge on two topics: assessing unhealthy levels of indoor D/M in homes and remediating home dampness-related problems to protect health. Based on a comparison of current scientific knowledge to that required to support effective, evidence-based, health-protective policies on home D/M, gaps in knowledge are highlighted, prior questions and research questions specified, and necessary research activities and approaches recommended.

Conceptual model of knowledge base system

NASA Astrophysics Data System (ADS)

Naykhanova, L. V.; Naykhanova, I. V.

2018-05-01

In the article, the conceptual model of the knowledge based system by the type of the production system is provided. The production system is intended for automation of problems, which solution is rigidly conditioned by the legislation. A core component of the system is a knowledge base. The knowledge base consists of a facts set, a rules set, the cognitive map and ontology. The cognitive map is developed for implementation of a control strategy, ontology - the explanation mechanism. Knowledge representation about recognition of a situation in the form of rules allows describing knowledge of the pension legislation. This approach provides the flexibility, originality and scalability of the system. In the case of changing legislation, it is necessary to change the rules set. This means that the change of the legislation would not be a big problem. The main advantage of the system is that there is an opportunity to be adapted easily to changes of the legislation.

The Knowledge Work of Professional Associations: Approaches to Standardisation and Forms of Legitimisation

ERIC Educational Resources Information Center

Nerland, Monika; Karseth, Berit

2015-01-01

This paper examines how professional associations engage themselves in efforts to develop, regulate and secure knowledge in their respective domains, with special emphasis on standardisation. The general emphasis on science in society brings renewed attention to the knowledge base of professionals, and positions professional bodies as key…

Transnational Corporations and Strategic Challenges: An Analysis of Knowledge Flows and Competitive Advantage

ERIC Educational Resources Information Center

de Pablos, Patricia Ordonez

2006-01-01

Purpose: The purpose of this paper is to analyse knowledge transfers in transnational corporations. Design/methodology/approach: The paper develops a conceptual framework for the analysis of knowledge flow transfers in transnationals. Based on this theoretical framework, the paper propose's research hypotheses and builds a causal model that links…

Transforming Environmental Knowledge into Behavior: The Mediating Role of Environmental Emotions

ERIC Educational Resources Information Center

Carmi, Nurit; Arnon, Sara; Orion, Nir

2015-01-01

The present study was based on the premise that environmental knowledge can drive environmental behavior only if it arouses environmental emotions. Using a structural equations modeling approach, we tested the direct, as well as the indirect (mediated) effects of knowledge on behavior and assessed the mediating role of environmental emotions. We…

Instructional Design as Knowledge Management: A Knowledge-in-Practice Approach to Choosing Instructional Methods

ERIC Educational Resources Information Center

McIver, Derrick; Fitzsimmons, Stacey; Flanagan, David

2016-01-01

Decisions about instructional methods are becoming more complex, with options ranging from problem sets to experiential service-learning projects. However, instructors not trained in instructional design may make these important decisions based on convenience, comfort, or trends. Instead, this article draws on the knowledge management literature…

"Shut up and Squat!" Learning Body Knowledge within the Gym

ERIC Educational Resources Information Center

Andreasson, Jesper

2014-01-01

The aim of this article is to describe and analyse learning processes among bodybuilders in bodybuilding environments, focusing on the ways activities form the basis for incorporation of both physical and cultural knowledge. Emanating from an ethnographic study, the arguments are based on a constructionist approach to knowledge. The result…

Integrating Neuroscience Knowledge into Social Work Education: A Case-Based Approach

ERIC Educational Resources Information Center

Egan, Marcia; Neely-Barnes, Susan L.; Combs-Orme, Terri

2011-01-01

New knowledge from the rapidly growing field of neuroscience has important implications for our understanding of human behavior in the social environment, yet little of this knowledge has made its way into social work education. This article presents a model for integrating neuroscience into instruction on human development, the bio psychosocial…

The evolution and provision of expert knowledge and its effective utilisation

NASA Astrophysics Data System (ADS)

Sammonds, Peter

2017-04-01

The specific aims of increasing Resilience to Natural Hazards in China programme are (i) to improve hazard forecasting, risk mitigation and preparedness based upon reliable knowledge of the fundamental processes involved and underpinned by basic science and, (ii) to improve the uptake of and responses to scientific advice, by developing risk-based approaches to natural hazards in collaboration with the communities at risk. One of the programme's principal goals is to integrate natural and social science research to increase the benefits for those affected by natural hazards. To that end a co-productive approach to research is expected, involving a framework for sharing knowledge and values between natural and social scientists and consultation with policy makers, civil society and other stakeholders. This paper explore knowledge relationships and reflective learning across disciplines. There is commonly a disjunction between the evolution and provision of expert knowledge and its effective utilisation. Building on experience as Strategic Advisor to the Increasing Resilience to Natural Hazards programme, this paper addresses the research needs to assess how scientific knowledge and risk reduction strategies can be most effectively developed and communicated.

An approach to knowledge engineering to support knowledge-based simulation of payload ground processing at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

Mcmanus, Shawn; Mcdaniel, Michael

1989-01-01

Planning for processing payloads was always difficult and time-consuming. With the advent of Space Station Freedom and its capability to support a myriad of complex payloads, the planning to support this ground processing maze involves thousands of man-hours of often tedious data manipulation. To provide the capability to analyze various processing schedules, an object oriented knowledge-based simulation environment called the Advanced Generic Accomodations Planning Environment (AGAPE) is being developed. Having nearly completed the baseline system, the emphasis in this paper is directed toward rule definition and its relation to model development and simulation. The focus is specifically on the methodologies implemented during knowledge acquisition, analysis, and representation within the AGAPE rule structure. A model is provided to illustrate the concepts presented. The approach demonstrates a framework for AGAPE rule development to assist expert system development.

Using Multiple Lenses to Examine the Development of Beginning Biology Teachers' Pedagogical Content Knowledge for Teaching Natural Selection Simulations

NASA Astrophysics Data System (ADS)

Sickel, Aaron J.; Friedrichsen, Patricia

2018-02-01

Pedagogical content knowledge (PCK) has become a useful construct to examine science teacher learning. Yet, researchers conceptualize PCK development in different ways. The purpose of this longitudinal study was to use three analytic lenses to understand the development of three beginning biology teachers' PCK for teaching natural selection simulations. We observed three early-career biology teachers as they taught natural selection in their respective school contexts over two consecutive years. Data consisted of six interviews with each participant. Using the PCK model developed by Magnusson et al. (1999), we examined topic-specific PCK development utilizing three different lenses: (1) expansion of knowledge within an individual knowledge base, (2) integration of knowledge across knowledge bases, and (3) knowledge that explicitly addressed core concepts of natural selection. We found commonalities across the participants, yet each lens was also useful to understand the influence of different factors (e.g., orientation, subject matter preparation, and the idiosyncratic nature of teacher knowledge) on PCK development. This multi-angle approach provides implications for considering the quality of beginning science teachers' knowledge and future research on PCK development. We conclude with an argument that explicitly communicating lenses used to understand PCK development will help the research community compare analytic approaches and better understand the nature of science teacher learning.

Knowledge Acquisition, Validation, and Maintenance in a Planning System for Automated Image Processing

NASA Technical Reports Server (NTRS)

Chien, Steve A.

1996-01-01

A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintainting the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems. This paper describes a planning application of automated imaging processing and our overall approach to knowledge acquisition for this application.

Progress and challenges in the application of artificial intelligence to computational fluid dynamics

NASA Technical Reports Server (NTRS)

Andrews, Alison E.

1987-01-01

An approach to analyzing CFD knowledge-based systems is proposed which is based, in part, on the concept of knowledge-level analysis. Consideration is given to the expert cooling fan design system, the PAN AIR knowledge system, grid adaptation, and expert zonal grid generation. These AI/CFD systems demonstrate that current AI technology can be successfully applied to well-formulated problems that are solved by means of classification or selection of preenumerated solutions.

Knowledge-Based Vision Techniques for the Autonomous Land Vehicle Program

DTIC Science & Technology

1991-10-01

Knowledge System The CKS is an object-oriented knowledge database that was originally designed to serve as the central information manager for a...34 Representation Space: An Approach to the Integra- tion of Visual Information ," Proc. of DARPA Image Understanding Workshop, Palo Alto, CA, pp. 263-272, May 1989...Strat, " Information Management in a Sensor-Based Au- tonomous System," Proc. DARPA Image Understanding Workshop, University of Southern CA, Vol.1, pp

Engineering youth service system infrastructure: Hawaii's continued efforts at large-scale implementation through knowledge management strategies.

PubMed

Nakamura, Brad J; Mueller, Charles W; Higa-McMillan, Charmaine; Okamura, Kelsie H; Chang, Jaime P; Slavin, Lesley; Shimabukuro, Scott

2014-01-01

Hawaii's Child and Adolescent Mental Health Division provides a unique illustration of a youth public mental health system with a long and successful history of large-scale quality improvement initiatives. Many advances are linked to flexibly organizing and applying knowledge gained from the scientific literature and move beyond installing a limited number of brand-named treatment approaches that might be directly relevant only to a small handful of system youth. This article takes a knowledge-to-action perspective and outlines five knowledge management strategies currently under way in Hawaii. Each strategy represents one component of a larger coordinated effort at engineering a service system focused on delivering both brand-named treatment approaches and complimentary strategies informed by the evidence base. The five knowledge management examples are (a) a set of modular-based professional training activities for currently practicing therapists, (b) an outreach initiative for supporting youth evidence-based practices training at Hawaii's mental health-related professional programs, (c) an effort to increase consumer knowledge of and demand for youth evidence-based practices, (d) a practice and progress agency performance feedback system, and (e) a sampling of system-level research studies focused on understanding treatment as usual. We end by outlining a small set of lessons learned and a longer term vision for embedding these efforts into the system's infrastructure.

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

PubMed Central

Xu, Rong; Li, Li; Wang, QuanQiu

2013-01-01

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

Object-based classification of global undersea topography and geomorphological features from the SRTM30_PLUS data

NASA Astrophysics Data System (ADS)

Dekavalla, Maria; Argialas, Demetre

2017-07-01

The analysis of undersea topography and geomorphological features provides necessary information to related disciplines and many applications. The development of an automated knowledge-based classification approach of undersea topography and geomorphological features is challenging due to their multi-scale nature. The aim of the study is to develop and evaluate an automated knowledge-based OBIA approach to: i) decompose the global undersea topography to multi-scale regions of distinct morphometric properties, and ii) assign the derived regions to characteristic geomorphological features. First, the global undersea topography was decomposed through the SRTM30_PLUS bathymetry data to the so-called morphometric objects of discrete morphometric properties and spatial scales defined by data-driven methods (local variance graphs and nested means) and multi-scale analysis. The derived morphometric objects were combined with additional relative topographic position information computed with a self-adaptive pattern recognition method (geomorphons), and auxiliary data and were assigned to characteristic undersea geomorphological feature classes through a knowledge base, developed from standard definitions. The decomposition of the SRTM30_PLUS data to morphometric objects was considered successful for the requirements of maximizing intra-object and inter-object heterogeneity, based on the near zero values of the Moran's I and the low values of the weighted variance index. The knowledge-based classification approach was tested for its transferability in six case studies of various tectonic settings and achieved the efficient extraction of 11 undersea geomorphological feature classes. The classification results for the six case studies were compared with the digital global seafloor geomorphic features map (GSFM). The 11 undersea feature classes and their producer's accuracies in respect to the GSFM relevant areas were Basin (95%), Continental Shelf (94.9%), Trough (88.4%), Plateau (78.9%), Continental Slope (76.4%), Trench (71.2%), Abyssal Hill (62.9%), Abyssal Plain (62.4%), Ridge (49.8%), Seamount (48.8%) and Continental Rise (25.4%). The knowledge-based OBIA classification approach was considered transferable since the percentages of spatial and thematic agreement between the most of the classified undersea feature classes and the GSFM exhibited low deviations across the six case studies.

Problem-Based Learning--Buginese Cultural Knowledge Model--Case Study: Teaching Mathematics at Junior High School

ERIC Educational Resources Information Center

Cheriani, Cheriani; Mahmud, Alimuddin; Tahmir, Suradi; Manda, Darman; Dirawan, Gufran Darma

2015-01-01

This study aims to determine the differences in learning output by using Problem Based Model combines with the "Buginese" Local Cultural Knowledge (PBL-Culture). It is also explores the students activities in learning mathematics subject by using PBL-Culture Models. This research is using Mixed Methods approach that combined quantitative…

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

ERIC Educational Resources Information Center

Gann, Linda

2013-01-01

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

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

ERIC Educational Resources Information Center

Gleeson, Jim

2012-01-01

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

Learning to Do Concept-Based Pragmatics Instruction: Teacher Development and L2 Pedagogical Content Knowledge

ERIC Educational Resources Information Center

van Compernolle, Rémi A.; Henery, Ashlie

2015-01-01

This article explores the development of pedagogical content knowledge in relation to one teacher's experience in learning to engage in a Vygotskian approach to teaching second language (L2) pragmatics known as "concept-based pragmatics instruction" (CBPI). The teacher, Mrs. Hanks, was a PhD candidate in second language acquisition at…

Redesigning Problem-Based Learning in the Knowledge Creation Paradigm for School Science Learning

ERIC Educational Resources Information Center

Yeo, Jennifer; Tan, Seng Chee

2014-01-01

The introduction of problem-based learning into K-12 science classrooms faces the challenge of achieving the dual goal of learning science content and developing problem-solving skills. To overcome this content-process tension in science classrooms, we employed the knowledge-creation approach as a boundary object between the two seemingly…

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

PubMed

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.

Meaningful Learning in the Cooperative Classroom

ERIC Educational Resources Information Center

Sharan, Yael

2015-01-01

Meaningful learning is based on more than what teachers transmit; it promotes the construction of knowledge out of learners' experience, feelings and exchanges with other learners. This educational view is based on the constructivist approach to learning and the co-operative learning approach. Researchers and practitioners in various…

A Knowledge Navigation Method for the Domain of Customers' Services of Mobile Communication Corporations in China

NASA Astrophysics Data System (ADS)

Wu, Jiangning; Wang, Xiaohuan

Rapidly increasing amount of mobile phone users and types of services leads to a great accumulation of complaining information. How to use this information to enhance the quality of customers' services is a big issue at present. To handle this kind of problem, the paper presents an approach to construct a domain knowledge map for navigating the explicit and tacit knowledge in two ways: building the Topic Map-based explicit knowledge navigation model, which includes domain TM construction, a semantic topic expansion algorithm and VSM-based similarity calculation; building Social Network Analysis-based tacit knowledge navigation model, which includes a multi-relational expert navigation algorithm and the criterions to evaluate the performance of expert networks. In doing so, both the customer managers and operators in call centers can find the appropriate knowledge and experts quickly and exactly. The experimental results show that the above method is very powerful for knowledge navigation.

Effective domain-dependent reuse in medical knowledge bases.

PubMed

Dojat, M; Pachet, F

1995-12-01

Knowledge reuse is now a critical issue for most developers of medical knowledge-based systems. As a rule, reuse is addressed from an ambitious, knowledge-engineering perspective that focuses on reusable general purpose knowledge modules, concepts, and methods. However, such a general goal fails to take into account the specific aspects of medical practice. From the point of view of the knowledge engineer, whose goal is to capture the specific features and intricacies of a given domain, this approach addresses the wrong level of generality. In this paper, we adopt a more pragmatic viewpoint, introducing the less ambitious goal of "domain-dependent limited reuse" and suggesting effective means of achieving it in practice. In a knowledge representation framework combining objects and production rules, we propose three mechanisms emerging from the combination of object-oriented programming and rule-based programming. We show these mechanisms contribute to achieve limited reuse and to introduce useful limited variations in medical expertise.

Impact of a brief addiction medicine training experience on knowledge self-assessment among medical learners.

PubMed

Klimas, Jan; Ahamad, Keith; Fairgrieve, Christoper; McLean, Mark; Mead, Annabel; Nolan, Seonaid; Wood, Evan

2017-01-01

Implementation of evidence-based approaches to the treatment of various substance use disorders is needed to tackle the existing epidemic of substance use and related harms. Most clinicians, however, lack knowledge and practical experience with these approaches. Given this deficit, the authors examined the impact of an inpatient elective in addiction medicine amongst medical trainees on addiction-related knowledge and medical management. Trainees who completed an elective with a hospital-based Addiction Medicine Consult Team (AMCT) in Vancouver, Canada, from May 2015 to May 2016, completed a 9-item self-evaluation scale before and immediately after the elective. A total of 48 participants completed both pre and post AMCT elective surveys. On average, participants were 28 years old (interquartile range [IQR] = 27-29) and contributed 20 days (IQR = 13-27) of clinical service. Knowledge of addiction medicine increased significantly post elective (mean difference [MD] = 8.63, standard deviation [SD] = 18.44; P = .002). The most and the least improved areas of knowledge were relapse prevention and substance use screening, respectively. Completion of a clinical elective with a hospital-based AMCT appears to improve medical trainees' addiction-related knowledge. Further evaluation and expansion of addiction medicine education is warranted to develop the next generation of skilled addiction care providers.

37: COMPARISON OF TWO METHODS: TBL-BASED AND LECTURE-BASED LEARNING IN NURSING CARE OF PATIENTS WITH DIABETES IN NURSING STUDENTS

PubMed Central

Khodaveisi, Masoud; Qaderian, Khosro; Oshvandi, Khodayar; Soltanian, Ali Reza; Vardanjani, Mehdi molavi

2017-01-01

Background and aims learning plays an important role in developing nursing skills and right care-taking. The Present study aims to evaluate two learning methods based on team –based learning and lecture-based learning in learning care-taking of patients with diabetes in nursing students. Method In this quasi-experimental study, 64 students in term 4 in nursing college of Bukan and Miandoab were included in the study based on knowledge and performance questionnaire including 15 questions based on knowledge and 5 questions based on performance on care-taking in patients with diabetes were used as data collection tool whose reliability was confirmed by cronbach alpha (r=0.83) by the researcher. To compare the mean score of knowledge and performance in each group in pre-test step and post-test step, pair –t test and to compare mean of scores in two groups of control and intervention, the independent t- test was used. Results There was not significant statistical difference between two groups in pre terms of knowledge and performance score (p=0.784). There was significant difference between the mean of knowledge scores and diabetes performance in the post-test in the team-based learning group and lecture-based learning group (p=0.001). There was significant difference between the mean score of knowledge of diabetes care in pre-test and post-test in base learning groups (p=0.001). Conclusion In both methods team-based and lecture-based learning approaches resulted in improvement in learning in students, but the rate of learning in the team-based learning approach is greater compared to that of lecture-based learning and it is recommended that this method be used as a higher education method in the education of students.

Approach to building knowledge bases in information-measuring systems diagnostics of acute leukemias

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.; Pronichev, A. N.; Polyakov, E. V.; Dmitrieva, V. V.

2018-01-01

The paper describes an approach for the formation of the reference base of peripheral blood cells and bone marrow in information-measuring systems of acute leukemia diagnostics. The proposed approach has allowed to create a system, that is enable peer evaluation of blood cells needed for the training of recognition systems when carrying out microscopic studies.

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

NASA Technical Reports Server (NTRS)

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.

The importance of knowledge-based technology.

PubMed

Cipriano, Pamela F

2012-01-01

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

A four stage approach for ontology-based health information system design.

PubMed

Kuziemsky, Craig E; Lau, Francis

2010-11-01

To describe and illustrate a four stage methodological approach to capture user knowledge in a biomedical domain area, use that knowledge to design an ontology, and then implement and evaluate the ontology as a health information system (HIS). A hybrid participatory design-grounded theory (GT-PD) method was used to obtain data and code them for ontology development. Prototyping was used to implement the ontology as a computer-based tool. Usability testing evaluated the computer-based tool. An empirically derived domain ontology and set of three problem-solving approaches were developed as a formalized model of the concepts and categories from the GT coding. The ontology and problem-solving approaches were used to design and implement a HIS that tested favorably in usability testing. The four stage approach illustrated in this paper is useful for designing and implementing an ontology as the basis for a HIS. The approach extends existing ontology development methodologies by providing an empirical basis for theory incorporated into ontology design. Copyright © 2010 Elsevier B.V. All rights reserved.

Towards a standardised representation of a knowledge base for adverse drug event prevention.

PubMed

Koutkias, Vassilis; Lazou, Katerina; de Clercq, Paul; Maglaveras, Nicos

2011-01-01

Knowledge representation is an important part of knowledge engineering activities that is crucial for enabling knowledge sharing and reuse. In this regard, standardised formalisms and technologies play a significant role. Especially for the medical domain, where knowledge may be tacit, not articulated and highly diverse, the development and adoption of standardised knowledge representations is highly challenging and of outmost importance to achieve knowledge interoperability. To this end, this paper presents a research effort towards the standardised representation of a Knowledge Base (KB) encapsulating rule-based signals and procedures for Adverse Drug Event (ADE) prevention. The KB constitutes an integral part of Clinical Decision Support Systems (CDSSs) to be used at the point of care. The paper highlights the requirements at the domain of discourse with respect to knowledge representation, according to which GELLO (an HL7 and ANSI standard) has been adopted. Results of our prototype implementation are presented along with the advantages and the limitations introduced by the employed approach.

The Galileo PPS expert monitoring and diagnostic prototype

NASA Technical Reports Server (NTRS)

Bahrami, Khosrow

1989-01-01

The Galileo PPS Expert Monitoring Module (EMM) is a prototype system implemented on the SUN workstation that will demonstrate a knowledge-based approach to monitoring and diagnosis for the Galileo spacecraft Power/Pyro subsystems. The prototype will simulate an analysis module functioning within the SFOC Engineering Analysis Subsystem Environment (EASE). This document describes the implementation of a prototype EMM for the Galileo spacecraft Power Pyro Subsystem. Section 2 of this document provides an overview of the issues in monitoring and diagnosis and comparison between traditional and knowledge-based solutions to this problem. Section 3 describes various tradeoffs which must be considered when designing a knowledge-based approach to monitoring and diagnosis, and section 4 discusses how these issues were resolved in constructing the prototype. Section 5 presents conclusions and recommendations for constructing a full-scale demonstration of the EMM. A Glossary provides definitions of terms used in this text.

Real-time visual tracking of less textured three-dimensional objects on mobile platforms

NASA Astrophysics Data System (ADS)

Seo, Byung-Kuk; Park, Jungsik; Park, Hanhoon; Park, Jong-Il

2012-12-01

Natural feature-based approaches are still challenging for mobile applications (e.g., mobile augmented reality), because they are feasible only in limited environments such as highly textured and planar scenes/objects, and they need powerful mobile hardware for fast and reliable tracking. In many cases where conventional approaches are not effective, three-dimensional (3-D) knowledge of target scenes would be beneficial. We present a well-established framework for real-time visual tracking of less textured 3-D objects on mobile platforms. Our framework is based on model-based tracking that efficiently exploits partially known 3-D scene knowledge such as object models and a background's distinctive geometric or photometric knowledge. Moreover, we elaborate on implementation in order to make it suitable for real-time vision processing on mobile hardware. The performance of the framework is tested and evaluated on recent commercially available smartphones, and its feasibility is shown by real-time demonstrations.

A knowledge-based, concept-oriented view generation system for clinical data.

PubMed

Zeng, Q; Cimino, J J

2001-04-01

Information overload is a well-known problem for clinicians who must review large amounts of data in patient records. Concept-oriented views, which organize patient data around clinical concepts such as diagnostic strategies and therapeutic goals, may offer a solution to the problem of information overload. However, although concept-oriented views are desirable, they are difficult to create and maintain. We have developed a general-purpose, knowledge-based approach to the generation of concept-oriented views and have developed a system to test our approach. The system creates concept-oriented views through automated identification of relevant patient data. The knowledge in the system is represented by both a semantic network and rules. The key relevant data identification function is accomplished by a rule-based traversal of the semantic network. This paper focuses on the design and implementation of the system; an evaluation of the system is reported separately.

Utilizing Expert Knowledge in Estimating Future STS Costs

NASA Technical Reports Server (NTRS)

Fortner, David B.; Ruiz-Torres, Alex J.

2004-01-01

A method of estimating the costs of future space transportation systems (STSs) involves classical activity-based cost (ABC) modeling combined with systematic utilization of the knowledge and opinions of experts to extend the process-flow knowledge of existing systems to systems that involve new materials and/or new architectures. The expert knowledge is particularly helpful in filling gaps that arise in computational models of processes because of inconsistencies in historical cost data. Heretofore, the costs of planned STSs have been estimated following a "top-down" approach that tends to force the architectures of new systems to incorporate process flows like those of the space shuttles. In this ABC-based method, one makes assumptions about the processes, but otherwise follows a "bottoms up" approach that does not force the new system architecture to incorporate a space-shuttle-like process flow. Prototype software has been developed to implement this method. Through further development of software, it should be possible to extend the method beyond the space program to almost any setting in which there is a need to estimate the costs of a new system and to extend the applicable knowledge base in order to make the estimate.

An analysis of the epistemic orientation of first- and third-year students in a physiotherapy program.

PubMed

Rancourt, R; Ballantine, C

1990-01-01

Previous research has demonstrated that practitioners within the same profession share a common approach to knowledge acquisition and transmission. A search for the identification of this common approach to knowledge in physiotherapy was undertaken using the Epistemic Orientation Model. The research reported was premised on the assumption that students admitted to physiotherapy programs in Canada possess an epistemic orientation that is similar to the epistemological structure of the knowledge base considered important to the program. Using a standardized instrument known as the Knowledge Accessing Modes Inventory (KAMI) to measure epistemic orientation, data were collected from a sample (N = 59) of first- and third-year students registered in a physiotherapy program in a central Canadian university. The data indicated that a high degree of association exists between the epistemological structure subsumed in the knowledge base deemed essential to gain admission to the program and the dominant rational epistemic mode of the practitioners-to-be. Based on the results, the article examines the usefulness of the epistemic orientation concept on activities within the profession. Implications for professional development are noted and avenues for further research are suggested.

Development of an expert system prototype for determining software functional requirements for command management activities at NASA Goddard

NASA Technical Reports Server (NTRS)

Liebowitz, J.

1986-01-01

The development of an expert system prototype for software functional requirement determination for NASA Goddard's Command Management System, as part of its process of transforming general requests into specific near-earth satellite commands, is described. The present knowledge base was formulated through interactions with domain experts, and was then linked to the existing Knowledge Engineering Systems (KES) expert system application generator. Steps in the knowledge-base development include problem-oriented attribute hierarchy development, knowledge management approach determination, and knowledge base encoding. The KES Parser and Inspector, in addition to backcasting and analogical mapping, were used to validate the expert system-derived requirements for one of the major functions of a spacecraft, the solar Maximum Mission. Knowledge refinement, evaluation, and implementation procedures of the expert system were then accomplished.

Investigating Approaches to Achieve Modularity Benefits in the Acquisition Ecosystem

DTIC Science & Technology

2017-06-09

actions and that of others, and how the assessments are affected by their actions. • Case study approach based on best practices, tacit knowledge... case study -derived exemplars, and items requiring further research on identifying additional enablers and useful knowledge constructs. All of these... case studies that document the effective use of modularity in system design for some or all of innovation, competition, cost, technology and

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salomons, G; Kelly, D

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 thatmore » 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.« less

Gaussian Processes for Data-Efficient Learning in Robotics and Control.

PubMed

Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward

2015-02-01

Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.

On Interactive Teaching Model of Translation Course Based on Wechat

ERIC Educational Resources Information Center

Lin, Wang

2017-01-01

Constructivism is a theory related to knowledge and learning, focusing on learners' subjective initiative, based on which the interactive approach has been proved to play a crucial role in language learning. Accordingly, the interactive approach can also be applied to translation teaching since translation itself is a bilingual transformational…

22 CFR 126.5 - Canadian exemptions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... assistance from a U.S. exporter. This transaction is based strictly on a “hand-off” approach because the... the U.S. exporter. This transaction is based strictly on a “hands-off” approach since the foreign... systemic study directed toward greater knowledge or understanding of the fundamental aspects of phenomena...

Structurally Based Therapeutic Evaluation: A Therapeutic and Practical Approach to Teaching Medicinal Chemistry.

ERIC Educational Resources Information Center

Alsharif, Naser Z.; And Others

1997-01-01

Explains structurally based therapeutic evaluation of drugs, which uses seven therapeutic criteria in translating chemical and structural knowledge into therapeutic decision making in pharmaceutical care. In a Creighton University (Nebraska) medicinal chemistry course, students apply the approach to solve patient-related therapeutic problems in…

E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

NASA Astrophysics Data System (ADS)

Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.

Model-based diagnostics for Space Station Freedom

NASA Technical Reports Server (NTRS)

Fesq, Lorraine M.; Stephan, Amy; Martin, Eric R.; Lerutte, Marcel G.

1991-01-01

An innovative approach to fault management was recently demonstrated for the NASA LeRC Space Station Freedom (SSF) power system testbed. This project capitalized on research in model-based reasoning, which uses knowledge of a system's behavior to monitor its health. The fault management system (FMS) can isolate failures online, or in a post analysis mode, and requires no knowledge of failure symptoms to perform its diagnostics. An in-house tool called MARPLE was used to develop and run the FMS. MARPLE's capabilities are similar to those available from commercial expert system shells, although MARPLE is designed to build model-based as opposed to rule-based systems. These capabilities include functions for capturing behavioral knowledge, a reasoning engine that implements a model-based technique known as constraint suspension, and a tool for quickly generating new user interfaces. The prototype produced by applying MARPLE to SSF not only demonstrated that model-based reasoning is a valuable diagnostic approach, but it also suggested several new applications of MARPLE, including an integration and testing aid, and a complement to state estimation.

Can Prior Knowledge Hurt Text Comprehension? An Answer Borrowed from Plato, Aristotle, and Descartes.

ERIC Educational Resources Information Center

Friedman, Lawrence B.

Taking a philosophical approach based on what Plato, Aristotle, and Descartes said about knowledge, this paper addresses some of the murkiness in the conceptual space surrounding the issue of whether prior knowledge does or does not facilitate text comprehension. Specifically, the paper first develops a non-exhaustive typology of cases in which…

An Investigation of Technological Pedagogical Content Knowledge, Self-Confidence, and Perception of Pre-Service Middle School Mathematics Teachers towards Instructional Technologies

ERIC Educational Resources Information Center

Karatas, Ilhan; Tunc, Mutlu Piskin; Yilmaz, Nurbanu; Karaci, Gulzade

2017-01-01

Technology provides new methods and approaches for educational activities. Therefore, teachers should improve their ability and knowledge to integrate technology into instruction. The use of technology-based learning environment which is effectively used to improve the technological pedagogical content knowledge of pre-service teachers has a…

A Fuzzy-Based Prior Knowledge Diagnostic Model with Multiple Attribute Evaluation

ERIC Educational Resources Information Center

Lin, Yi-Chun; Huang, Yueh-Min

2013-01-01

Prior knowledge is a very important part of teaching and learning, as it affects how instructors and students interact with the learning materials. In general, tests are used to assess students' prior knowledge. Nevertheless, conventional testing approaches usually assign only an overall score to each student, and this may mean that students are…

Informative Top-k Retrieval for Advanced Skill Management

NASA Astrophysics Data System (ADS)

Colucci, Simona; di Noia, Tommaso; Ragone, Azzurra; Ruta, Michele; Straccia, Umberto; Tinelli, Eufemia

The paper presents a knowledge-based framework for skills and talent management based on an advanced matchmaking between profiles of candidates and available job positions. Interestingly, informative content of top-k retrieval is enriched through semantic capabilities. The proposed approach allows to: (1) express a requested profile in terms of both hard constraints and soft ones; (2) provide a ranking function based also on qualitative attributes of a profile; (3) explain the resulting outcomes (given a job request, a motivation for the obtained score of each selected profile is provided). Top-k retrieval allows to select most promising candidates according to an ontology formalizing the domain knowledge. Such a knowledge is further exploited to provide a semantic-based explanation of missing or conflicting features in retrieved profiles. They also indicate additional profile characteristics emerging by the retrieval procedure for a further request refinement. A concrete case study followed by an exhaustive experimental campaign is reported to prove the approach effectiveness.

Practical and generalizable architecture for an intelligent tutoring system

NASA Astrophysics Data System (ADS)

Kaplan, Randy M.; Trenholm, Harriet

1993-03-01

In this paper we describe an intelligent tutoring system (ITS) called HYDRIVE (hydraulics interactive video experience). This system is built using several novel approaches to intelligent tutoring. The underlying rationale for HYDRIVE is based on the results of a cognitive task analysis. The reasoning component of the system makes extensive use of a hierarchical knowledge representation. Reasoning within the system is accomplished using a logic-based approach and is linked to a highly interactive interface using multimedia. The knowledge representation contains information that drives the multimedia elements of the system, and the reasoning components select the appropriate information to assess student knowledge or guide the student at any particular moment. As this system will be deployed throughout the Air Force maintenance function, the implementation platform is the IBM PC.

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

NASA Astrophysics Data System (ADS)

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 approaches to the maintenance of a large controlled medical terminology.

PubMed Central

Cimino, J J; Clayton, P D; Hripcsak, G; Johnson, S B

1994-01-01

OBJECTIVE: Develop a knowledge-based representation for a controlled terminology of clinical information to facilitate creation, maintenance, and use of the terminology. DESIGN: The Medical Entities Dictionary (MED) is a semantic network, based on the Unified Medical Language System (UMLS), with a directed acyclic graph to represent multiple hierarchies. Terms from four hospital systems (laboratory, electrocardiography, medical records coding, and pharmacy) were added as nodes in the network. Additional knowledge about terms, added as semantic links, was used to assist in integration, harmonization, and automated classification of disparate terminologies. RESULTS: The MED contains 32,767 terms and is in active clinical use. Automated classification was successfully applied to terms for laboratory specimens, laboratory tests, and medications. One benefit of the approach has been the automated inclusion of medications into multiple pharmacologic and allergenic classes that were not present in the pharmacy system. Another benefit has been the reduction of maintenance efforts by 90%. CONCLUSION: The MED is a hybrid of terminology and knowledge. It provides domain coverage, synonymy, consistency of views, explicit relationships, and multiple classification while preventing redundancy, ambiguity (homonymy) and misclassification. PMID:7719786

A Study of Building a Resource-Based Learning Environment with the Inquiry Learning Approach: Knowledge of Family Trees

ERIC Educational Resources Information Center

Kong, Siu Cheung; So, Wing Mui Winnie

2008-01-01

This study aims to provide teachers with ways and means to facilitate learners to develop nomenclature knowledge of family trees through the establishment of resource-based learning environments (RBLEs). It discusses the design of an RBLE in the classroom by selecting an appropriate context with the assistance of computer-mediated learning…

Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods

PubMed Central

Chasin, Rachel; Rumshisky, Anna; Uzuner, Ozlem; Szolovits, Peter

2014-01-01

Objective To evaluate state-of-the-art unsupervised methods on the word sense disambiguation (WSD) task in the clinical domain. In particular, to compare graph-based approaches relying on a clinical knowledge base with bottom-up topic-modeling-based approaches. We investigate several enhancements to the topic-modeling techniques that use domain-specific knowledge sources. Materials and methods The graph-based methods use variations of PageRank and distance-based similarity metrics, operating over the Unified Medical Language System (UMLS). Topic-modeling methods use unlabeled data from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC II) database to derive models for each ambiguous word. We investigate the impact of using different linguistic features for topic models, including UMLS-based and syntactic features. We use a sense-tagged clinical dataset from the Mayo Clinic for evaluation. Results The topic-modeling methods achieve 66.9% accuracy on a subset of the Mayo Clinic's data, while the graph-based methods only reach the 40–50% range, with a most-frequent-sense baseline of 56.5%. Features derived from the UMLS semantic type and concept hierarchies do not produce a gain over bag-of-words features in the topic models, but identifying phrases from UMLS and using syntax does help. Discussion Although topic models outperform graph-based methods, semantic features derived from the UMLS prove too noisy to improve performance beyond bag-of-words. Conclusions Topic modeling for WSD provides superior results in the clinical domain; however, integration of knowledge remains to be effectively exploited. PMID:24441986

The Genome-based Knowledge Management in Cycles model: a complex adaptive systems framework for implementation of genomic applications.

PubMed

Arar, Nedal; Knight, Sara J; Modell, Stephen M; Issa, Amalia M

2011-03-01

The main mission of the Genomic Applications in Practice and Prevention Network™ is to advance collaborative efforts involving partners from across the public health sector to realize the promise of genomics in healthcare and disease prevention. We introduce a new framework that supports the Genomic Applications in Practice and Prevention Network mission and leverages the characteristics of the complex adaptive systems approach. We call this framework the Genome-based Knowledge Management in Cycles model (G-KNOMIC). G-KNOMIC proposes that the collaborative work of multidisciplinary teams utilizing genome-based applications will enhance translating evidence-based genomic findings by creating ongoing knowledge management cycles. Each cycle consists of knowledge synthesis, knowledge evaluation, knowledge implementation and knowledge utilization. Our framework acknowledges that all the elements in the knowledge translation process are interconnected and continuously changing. It also recognizes the importance of feedback loops, and the ability of teams to self-organize within a dynamic system. We demonstrate how this framework can be used to improve the adoption of genomic technologies into practice using two case studies of genomic uptake.

Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology

PubMed Central

Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S

2017-01-01

Background There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. Objective This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. Methods We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. Results A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Conclusions Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. PMID:29021130

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

PubMed

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

2013-01-01

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

Using Data Crawlers and Semantic Web to Build Financial XBRL Data Generators: The SONAR Extension Approach

PubMed Central

Rodríguez-García, Miguel Ángel; Rodríguez-González, Alejandro; Valencia-García, Rafael; Gómez-Berbís, Juan Miguel

2014-01-01

Precise, reliable and real-time financial information is critical for added-value financial services after the economic turmoil from which markets are still struggling to recover. Since the Web has become the most significant data source, intelligent crawlers based on Semantic Technologies have become trailblazers in the search of knowledge combining natural language processing and ontology engineering techniques. In this paper, we present the SONAR extension approach, which will leverage the potential of knowledge representation by extracting, managing, and turning scarce and disperse financial information into well-classified, structured, and widely used XBRL format-oriented knowledge, strongly supported by a proof-of-concept implementation and a thorough evaluation of the benefits of the approach. PMID:24587726

Using data crawlers and semantic Web to build financial XBRL data generators: the SONAR extension approach.

PubMed

Rodríguez-García, Miguel Ángel; Rodríguez-González, Alejandro; Colomo-Palacios, Ricardo; Valencia-García, Rafael; Gómez-Berbís, Juan Miguel; García-Sánchez, Francisco

2014-01-01

Precise, reliable and real-time financial information is critical for added-value financial services after the economic turmoil from which markets are still struggling to recover. Since the Web has become the most significant data source, intelligent crawlers based on Semantic Technologies have become trailblazers in the search of knowledge combining natural language processing and ontology engineering techniques. In this paper, we present the SONAR extension approach, which will leverage the potential of knowledge representation by extracting, managing, and turning scarce and disperse financial information into well-classified, structured, and widely used XBRL format-oriented knowledge, strongly supported by a proof-of-concept implementation and a thorough evaluation of the benefits of the approach.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Generic screen representations for future-proof systems, is it possible? There is more to a GUI than meets the eye.

PubMed

van der Linden, Helma; Austin, Tony; Talmon, Jan

2009-09-01

Future-proof EHR systems must be capable of interpreting information structures for medical concepts that were not available at the build-time of the system. The two-model approach of CEN 13606/openEHR using archetypes achieves this by separating generic clinical knowledge from domain-related knowledge. The presentation of this information can either itself be generic, or require design time awareness of the domain knowledge being employed. To develop a Graphical User Interface (GUI) that would be capable of displaying previously unencountered clinical data structures in a meaningful way. Through "reasoning by analogy" we defined an approach for the representation and implementation of "presentational knowledge". A proof-of-concept implementation was built to validate its implementability and to test for unanticipated issues. A two-model approach to specifying and generating a screen representation for archetype-based information, inspired by the two-model approach of archetypes, was developed. There is a separation between software-related display knowledge and domain-related display knowledge and the toolkit is designed with the reuse of components in mind. The approach leads to a flexible GUI that can adapt not only to information structures that had not been predefined within the receiving system, but also to novel ways of displaying the information. We also found that, ideally, the openEHR Archetype Definition Language should receive minor adjustments to allow for generic binding.

Knowledge-driven computational modeling in Alzheimer's disease research: Current state and future trends.

PubMed

Geerts, Hugo; Hofmann-Apitius, Martin; Anastasio, Thomas J

2017-11-01

Neurodegenerative diseases such as Alzheimer's disease (AD) follow a slowly progressing dysfunctional trajectory, with a large presymptomatic component and many comorbidities. Using preclinical models and large-scale omics studies ranging from genetics to imaging, a large number of processes that might be involved in AD pathology at different stages and levels have been identified. The sheer number of putative hypotheses makes it almost impossible to estimate their contribution to the clinical outcome and to develop a comprehensive view on the pathological processes driving the clinical phenotype. Traditionally, bioinformatics approaches have provided correlations and associations between processes and phenotypes. Focusing on causality, a new breed of advanced and more quantitative modeling approaches that use formalized domain expertise offer new opportunities to integrate these different modalities and outline possible paths toward new therapeutic interventions. This article reviews three different computational approaches and their possible complementarities. Process algebras, implemented using declarative programming languages such as Maude, facilitate simulation and analysis of complicated biological processes on a comprehensive but coarse-grained level. A model-driven Integration of Data and Knowledge, based on the OpenBEL platform and using reverse causative reasoning and network jump analysis, can generate mechanistic knowledge and a new, mechanism-based taxonomy of disease. Finally, Quantitative Systems Pharmacology is based on formalized implementation of domain expertise in a more fine-grained, mechanism-driven, quantitative, and predictive humanized computer model. We propose a strategy to combine the strengths of these individual approaches for developing powerful modeling methodologies that can provide actionable knowledge for rational development of preventive and therapeutic interventions. Development of these computational approaches is likely to be required for further progress in understanding and treating AD. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Using Topdown Conceptual Analysis To Accelerate The Learning Of New Domains For Knowledge Engineers & Domain Experts

NASA Astrophysics Data System (ADS)

Xuan, Albert L.; Shinghal, Rajjan

1989-03-01

As the need for knowledge-based systems increases, an increasing number of domain experts are becoming interested in taking more active part in the building of knowledge-based systems. However, such a domain expert often must deal with a large number of unfamiliar terms concepts, facts, procedures and principles based on different approaches and schools of thought. He (for brevity, we shall use masculine pronouns for both genders) may need the help of a knowledge engineer (KE) in building the knowledge-based system but may encounter a number of problems. For instance, much of the early interaction between him and the knowl edge engineer may be spent in educating each other about their seperate kinds of expertise. Since the knowledge engineer will usually be ignorant of the knowledge domain while the domain expert (DE) will have little knowledge about knowledge-based systems, a great deal of time will be wasted on these issues ad the DE and the KE train each other to the point where a fruitful interaction can occur. In some situations, it may not even be possible for the DE to find a suitable KE to work with because he has no time to train the latter in his domain. This will engender the need for the DE to be more knowledgeable about knowledge-based systems and for the KE to find methods and techniques which will allow them to learn new domains as fast as they can. In any event, it is likely that the process of building knowledge-based systems will be smooth, er and more efficient if the domain expert is knowledgeable about the methods and techniques of knowledge-based systems building.

Comparing perceived and test-based knowledge of cancer risk and prevention among Hispanic and African Americans: an example of community participatory research.

PubMed

Jones, Loretta; Bazargan, Mohsen; Lucas-Wright, Anna; Vadgama, Jaydutt V; Vargas, Roberto; Smith, James; Otoukesh, Salman; Maxwell, Annette E

2013-01-01

Most theoretical formulations acknowledge that knowledge and awareness of cancer screening and prevention recommendations significantly influence health behaviors. This study compares perceived knowledge of cancer prevention and screening with test-based knowledge in a community sample. We also examine demographic variables and self-reported cancer screening and prevention behaviors as correlates of both knowledge scores, and consider whether cancer related knowledge can be accurately assessed using just a few, simple questions in a short and easy-to-complete survey. We used a community-partnered participatory research approach to develop our study aims and a survey. The study sample was composed of 180 predominantly African American and Hispanic community individuals who participated in a full-day cancer prevention and screening promotion conference in South Los Angeles, California, on July 2011. Participants completed a self-administered survey in English or Spanish at the beginning of the conference. Our data indicate that perceived and test-based knowledge scores are only moderately correlated. Perceived knowledge score shows a stronger association with demographic characteristics and other cancer related variables than the test-based score. Thirteen out of twenty variables that are examined in our study showed a statistically significant correlation with the perceived knowledge score, however, only four variables demonstrated a statistically significant correlation with the test-based knowledge score. Perceived knowledge of cancer prevention and screening was assessed with fewer items than test-based knowledge. Thus, using this assessment could potentially reduce respondent burden. However, our data demonstrate that perceived and test-based knowledge are separate constructs.

Symbolic Knowledge Processing for the Acquisition of Expert Behavior: A Study in Medicine.

DTIC Science & Technology

1984-05-01

information . It provides a model for this type of study, suggesting a different approach to the problem of learning and efficiency of knowledge -based...flow of information 2.2. Scope and description of the subsystems Three subsystems perform distinct operations using the preceding knowledge sources...which actually yields a new knowledge rCpresentation Ahere new external information is encoded in the combination and ordering of elements of the

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

ERIC Educational Resources Information Center

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…

Epistemic Beliefs of Middle and High School Students in a Problem-Based, Scientific Inquiry Unit: An Exploratory, Mixed Methods Study

ERIC Educational Resources Information Center

Gu, Jiangyue

2016-01-01

Epistemic beliefs are individuals' beliefs about the nature of knowledge, how knowledge is constructed, and how knowledge can be justified. This study employed a mixed-methods approach to examine: (a) middle and high school students' self-reported epistemic beliefs (quantitative) and epistemic beliefs revealed from practice (qualitative) during a…

Discovering and Articulating What Is Not yet Known: Using Action Learning and Grounded Theory as a Knowledge Management Strategy

ERIC Educational Resources Information Center

Pauleen, David J.; Corbitt, Brian; Yoong, Pak

2007-01-01

Purpose: To provide a conceptual model for the discovery and articulation of emergent organizational knowledge, particularly knowledge that develops when people work with new technologies. Design/methodology/approach: The model is based on two widely accepted research methods--action learning and grounded theory--and is illustrated using a case…

Student's Uncertainty Modeling through a Multimodal Sensor-Based Approach

ERIC Educational Resources Information Center

Jraidi, Imene; Frasson, Claude

2013-01-01

Detecting the student internal state during learning is a key construct in educational environment and particularly in Intelligent Tutoring Systems (ITS). Students' uncertainty is of primary interest as it is deeply rooted in the process of knowledge construction. In this paper we propose a new sensor-based multimodal approach to model…

Designing Social Media for Informal Learning and Knowledge Maturing in the Digital Workplace

ERIC Educational Resources Information Center

Ravenscroft, A.; Schmidt, A.; Cook, J.; Bradley, C.

2012-01-01

This paper presents an original approach to designing social media that support informal learning in the digital workplace. It adapts design-based research to take into account the embeddedness of interactions within digitally mediated work-based contexts. The approach is demonstrated through the design, implementation, and evaluation of software…

Effects of Problem Based Economics on High School Economics Instruction

ERIC Educational Resources Information Center

Finkelstein, Neal; Hanson, Thomas

2011-01-01

The primary purpose of this study is to assess student-level impacts of a problem-based instructional approach to high school economics. The curriculum approach examined here was designed to increase class participation and content knowledge for high school students who are learning economics. This study tests the effectiveness of Problem Based…

Direct Problem-Based Learning (DPBL): A Framework for Integrating Direct Instruction and Problem-Based Learning Approach

ERIC Educational Resources Information Center

Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

2018-01-01

Direct instruction approach has been widely used in higher education. Many studies revealed that direct instruction improved students' knowledge. The characteristics of direct instruction include the subject delivered through face-to-face interaction with the lecturers and materials that sequenced deliberately and taught explicitly. However,…

Constructing Knowledge with an Agent-Based Instructional Program: A Comparison of Cooperative and Individual Meaning Making

ERIC Educational Resources Information Center

Moreno, Roxana

2009-01-01

Participants in the present study were 87 college students who learned about botany using an agent-based instructional program with three different learning approaches: individual, jigsaw, or cooperative learning. Results showed no differences among learning approaches on retention. Students in jigsaw groups reported higher cognitive load during…

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

NASA Technical Reports Server (NTRS)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

[Basic assessment of needs for training in evidence-based medicine in Slovakia].

PubMed

Bacharova, L; Hlavacka, S; Rusnakova, V

2001-01-01

The health care reform in Slovakia produces a desire for greater responsibility for and control of strategic decisions and to be better able to evaluate international knowledge and experience in the specific national social and professional contexts. Evidence based medicine (EBM) provides an increasingly organised and accessible database of international knowledge in health and health care, capable of informing decisions at the macro and micro levels. The aim of this pilot study was to assess education, training and other capacity building needs in EBM and evidence based health care. This study was primarily qualitative and based on a triangular approach, which included: (1) The analysis of the situation in pre- and postgraduate education in Slovakia aiming to the estimation of needs in EBM and critical appraisal skills training; (2) The analysis of questionnaires distributed in a sample of 50 medical doctors and university educated public health workers undergoing a postgraduate training; (3) The discussion in focused groups. The findings and analysis uncovered a gap in knowledge and experience of EBM approaches, particularly of searching for evidence, utilising information technology, of undertaking critical appraisals of the validity and quality of external evidence and of knowledge of English. On the other hand the findings revealed a high access to information including the Internet access at the workplace, an increasing awareness of the need for up-date information, a demand for training and potential opportunities for action. The effective implementation introduction of EBM approach would require changes in broader political, cultural and behavioural contexts, including changes in pre- and postgraduate systems of professional and managerial education, changes in professional and managerial attitudes and changes in emphasis in skills and capacity building and improvements in knowledge management systems at the national level.

Knowledge Creation in Nursing Education

PubMed Central

Hassanian, Zahra Marzieh; Ahanchian, Mohammad Reza; Ahmadi, Suleiman; Gholizadeh, Rezvan Hossein; Karimi-Moonaghi, Hossein

2015-01-01

In today’s society, knowledge is recognized as a valuable social asset and the educational system is in search of a new strategy that allows them to construct their knowledge and experience. The purpose of this study was to explore the process of knowledge creation in nursing education. In the present study, the grounded theory approach was used. This method provides a comprehensive approach to collecting, organizing, and analyzing data. Data were obtained through 17 semi-structured interviews with nursing faculties and nursing students. Purposeful and theoretical sampling was conducted. Based on the method of Strauss and Corbin, the data were analyzed using fragmented, deep, and constant-comparative methods. The main categories included striving for growth and reduction of ambiguity, use of knowledge resources, dynamism of mind and social factors, converting knowledge, and creating knowledge. Knowledge was converted through mind processes, individual and group reflection, praxis and research, and resulted in the creation of nursing knowledge. Discrete nursing knowledge is gained through disconformity research in order to gain more individual advantages. The consequence of this analysis was gaining new knowledge. Knowledge management must be included in the mission and strategic planning of nursing education, and it should be planned through operational planning in order to create applicable knowledge. PMID:25716383

Computational functional genomics-based approaches in analgesic drug discovery and repurposing.

PubMed

Lippmann, Catharina; Kringel, Dario; Ultsch, Alfred; Lötsch, Jörn

2018-06-01

Persistent pain is a major healthcare problem affecting a fifth of adults worldwide with still limited treatment options. The search for new analgesics increasingly includes the novel research area of functional genomics, which combines data derived from various processes related to DNA sequence, gene expression or protein function and uses advanced methods of data mining and knowledge discovery with the goal of understanding the relationship between the genome and the phenotype. Its use in drug discovery and repurposing for analgesic indications has so far been performed using knowledge discovery in gene function and drug target-related databases; next-generation sequencing; and functional proteomics-based approaches. Here, we discuss recent efforts in functional genomics-based approaches to analgesic drug discovery and repurposing and highlight the potential of computational functional genomics in this field including a demonstration of the workflow using a novel R library 'dbtORA'.

A prototype knowledge-based simulation support system

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

1987-04-01

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

Guide for applied public health workforce research: an evidence-based approach to workforce development.

PubMed

Thacker, Stephen B

2009-11-01

Essential to achievement of the public health mission is a knowledgeable, competent, and prepared workforce; yet, there is little application of science and technical knowledge to ensuring the effectiveness of that workforce, be it governmental or private. In this article, I review the evidence for effective workforce development and argue for an increased emphasis on an evidence-based approach to ensuring an effective workforce by encouraging the generation of the evidence base that is required. To achieve this, I propose the appointment of an independent Task Force on Public Health Workforce Practice to oversee the development of a Guide for Public Health Workforce Research and Practice (Workforce Guide), a process that will generate and bring together the workforce evidence base for use by public health practitioners.

Knowing the ABCs: A Comparative Effectiveness Study of Two Methods of Diabetes Education

PubMed Central

Naik, Aanand D.; Teal, Cayla R.; Rodriguez, Elisa; Haidet, Paul

2011-01-01

Objective To test an active-learning, empowerment approach to teaching patients about the “diabetes ABCs” (hemoglobin A1C, systolic blood pressure, and low density lipoprotein cholesterol). Methods 84 (97%) diabetic patients who participated in a randomized effectiveness trial of two clinic-based group educational methods and completed a post-intervention assessment. The empowerment arm participated in a group session that incorporated two educational innovations (a conceptual metaphor to foster understanding, and team-based learning methods to foster active learning). The traditional diabetes education arm received a didactic group session focused on self-management and educational materials about the diabetes ABCs. Participants in both arms received individual review of their current ABC values. Results A questionnaire evaluated knowledge, understanding, and recall of the diabetes ABCs was administered three months after enrollment in the study. At three months, participants in the empowerment group demonstrated greater understanding of the diabetes ABCs (P<.0001), greater knowledge of their own values (P<.0001), and greater knowledge of guideline-derived target goals for the ABCs compared with participants in the traditional arm (P<.0001). Conclusion An active-learning, empowerment-based approach applied to diabetes education can lead to greater understanding and knowledge retention. Practice Implications An empowerment approach to education can facilitate informed, activated patients and increase performance of self-management behaviors. PMID:21300516

A Transactional Approach to Children's Learning in a Knowledge-Based Society.

ERIC Educational Resources Information Center

Seng, Seok-Hoon

The 21st century promises to make very different demands on our children and schools in a knowledge-based society. A slow but dynamic shift has been occurring in the Singapore educational system toward a learning nation and thinking school ethos. In the midst of this change, children will need to acquire a new set of skills. They will need to be…

Integration of language and sensor information

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.; Weijers, Bertus

2003-04-01

The talk describes the development of basic technologies of intelligent systems fusing data from multiple domains and leading to automated computational techniques for understanding data contents. Understanding involves inferring appropriate decisions and recommending proper actions, which in turn requires fusion of data and knowledge about objects, situations, and actions. Data might include sensory data, verbal reports, intelligence intercepts, or public records, whereas knowledge ought to encompass the whole range of objects, situations, people and their behavior, and knowledge of languages. In the past, a fundamental difficulty in combining knowledge with data was the combinatorial complexity of computations, too many combinations of data and knowledge pieces had to be evaluated. Recent progress in understanding of natural intelligent systems, including the human mind, leads to the development of neurophysiologically motivated architectures for solving these challenging problems, in particular the role of emotional neural signals in overcoming combinatorial complexity of old logic-based approaches. Whereas past approaches based on logic tended to identify logic with language and thinking, recent studies in cognitive linguistics have led to appreciation of more complicated nature of linguistic models. Little is known about the details of the brain mechanisms integrating language and thinking. Understanding and fusion of linguistic information with sensory data represent a novel challenging aspect of the development of integrated fusion systems. The presentation will describe a non-combinatorial approach to this problem and outline techniques that can be used for fusing diverse and uncertain knowledge with sensory and linguistic data.

Forms of Knowledge and Curriculum Coherence

ERIC Educational Resources Information Center

Muller, Johan

2009-01-01

This paper examines what is entailed by taking a socio-epistemic or "knowledge-based" approach to considerations of curriculum and qualifications. The paper begins by examining the roots of disciplinary difference in the medieval universities and their treatment in contemporary scholarly work; discusses implications for curriculum and…

Identifying novel drug indications through automated reasoning.

PubMed

Tari, Luis; Vo, Nguyen; Liang, Shanshan; Patel, Jagruti; Baral, Chitta; Cai, James

2012-01-01

With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process. In this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications. To evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.

Incorporating Semantics into Data Driven Workflows for Content Based Analysis

NASA Astrophysics Data System (ADS)

Argüello, M.; Fernandez-Prieto, M. J.

Finding meaningful associations between text elements and knowledge structures within clinical narratives in a highly verbal domain, such as psychiatry, is a challenging goal. The research presented here uses a small corpus of case histories and brings into play pre-existing knowledge, and therefore, complements other approaches that use large corpus (millions of words) and no pre-existing knowledge. The paper describes a variety of experiments for content-based analysis: Linguistic Analysis using NLP-oriented approaches, Sentiment Analysis, and Semantically Meaningful Analysis. Although it is not standard practice, the paper advocates providing automatic support to annotate the functionality as well as the data for each experiment by performing semantic annotation that uses OWL and OWL-S. Lessons learnt can be transmitted to legacy clinical databases facing the conversion of clinical narratives according to prominent Electronic Health Records standards.

A Semantic Lexicon-Based Approach for Sense Disambiguation and Its WWW Application

NASA Astrophysics Data System (ADS)

di Lecce, Vincenzo; Calabrese, Marco; Soldo, Domenico

This work proposes a basic framework for resolving sense disambiguation through the use of Semantic Lexicon, a machine readable dictionary managing both word senses and lexico-semantic relations. More specifically, polysemous ambiguity characterizing Web documents is discussed. The adopted Semantic Lexicon is WordNet, a lexical knowledge-base of English words widely adopted in many research studies referring to knowledge discovery. The proposed approach extends recent works on knowledge discovery by focusing on the sense disambiguation aspect. By exploiting the structure of WordNet database, lexico-semantic features are used to resolve the inherent sense ambiguity of written text with particular reference to HTML resources. The obtained results may be extended to generic hypertextual repositories as well. Experiments show that polysemy reduction can be used to hint about the meaning of specific senses in given contexts.

Inference of Gene Regulatory Networks Incorporating Multi-Source Biological Knowledge via a State Space Model with L1 Regularization

PubMed Central

Hasegawa, Takanori; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru; Imoto, Seiya

2014-01-01

Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in the field of systems biology. Currently, there are two main approaches in GRN analysis using time-course observation data, namely an ordinary differential equation (ODE)-based approach and a statistical model-based approach. The ODE-based approach can generate complex dynamics of GRNs according to biologically validated nonlinear models. However, it cannot be applied to ten or more genes to simultaneously estimate system dynamics and regulatory relationships due to the computational difficulties. The statistical model-based approach uses highly abstract models to simply describe biological systems and to infer relationships among several hundreds of genes from the data. However, the high abstraction generates false regulations that are not permitted biologically. Thus, when dealing with several tens of genes of which the relationships are partially known, a method that can infer regulatory relationships based on a model with low abstraction and that can emulate the dynamics of ODE-based models while incorporating prior knowledge is urgently required. To accomplish this, we propose a method for inference of GRNs using a state space representation of a vector auto-regressive (VAR) model with L1 regularization. This method can estimate the dynamic behavior of genes based on linear time-series modeling constructed from an ODE-based model and can infer the regulatory structure among several tens of genes maximizing prediction ability for the observational data. Furthermore, the method is capable of incorporating various types of existing biological knowledge, e.g., drug kinetics and literature-recorded pathways. The effectiveness of the proposed method is shown through a comparison of simulation studies with several previous methods. For an application example, we evaluated mRNA expression profiles over time upon corticosteroid stimulation in rats, thus incorporating corticosteroid kinetics/dynamics, literature-recorded pathways and transcription factor (TF) information. PMID:25162401

Knowledge Based Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle.

DTIC Science & Technology

1988-04-13

Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle Mark S. Fox, Nizwer Husain, Malcolm...McRoberts and Y.V.Reddy CMU-RI-TR-88-5 Intelligent Systems Laboratory The Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania D T T 13...years of research in the application of Artificial Intelligence to Simulation. Our focus has been in two areas: the use of Al knowledge representation

Semi-automated extraction of landslides in Taiwan based on SPOT imagery and DEMs

NASA Astrophysics Data System (ADS)

Eisank, Clemens; Hölbling, Daniel; Friedl, Barbara; Chen, Yi-Chin; Chang, Kang-Tsung

2014-05-01

The vast availability and improved quality of optical satellite data and digital elevation models (DEMs), as well as the need for complete and up-to-date landslide inventories at various spatial scales have fostered the development of semi-automated landslide recognition systems. Among the tested approaches for designing such systems, object-based image analysis (OBIA) stepped out to be a highly promising methodology. OBIA offers a flexible, spatially enabled framework for effective landslide mapping. Most object-based landslide mapping systems, however, have been tailored to specific, mainly small-scale study areas or even to single landslides only. Even though reported mapping accuracies tend to be higher than for pixel-based approaches, accuracy values are still relatively low and depend on the particular study. There is still room to improve the applicability and objectivity of object-based landslide mapping systems. The presented study aims at developing a knowledge-based landslide mapping system implemented in an OBIA environment, i.e. Trimble eCognition. In comparison to previous knowledge-based approaches, the classification of segmentation-derived multi-scale image objects relies on digital landslide signatures. These signatures hold the common operational knowledge on digital landslide mapping, as reported by 25 Taiwanese landslide experts during personal semi-structured interviews. Specifically, the signatures include information on commonly used data layers, spectral and spatial features, and feature thresholds. The signatures guide the selection and implementation of mapping rules that were finally encoded in Cognition Network Language (CNL). Multi-scale image segmentation is optimized by using the improved Estimation of Scale Parameter (ESP) tool. The approach described above is developed and tested for mapping landslides in a sub-region of the Baichi catchment in Northern Taiwan based on SPOT imagery and a high-resolution DEM. An object-based accuracy assessment is conducted by quantitatively comparing extracted landslide objects with landslide polygons that were visually interpreted by local experts. The applicability and transferability of the mapping system are evaluated by comparing initial accuracies with those achieved for the following two tests: first, usage of a SPOT image from the same year, but for a different area within the Baichi catchment; second, usage of SPOT images from multiple years for the same region. The integration of the common knowledge via digital landslide signatures is new in object-based landslide studies. In combination with strategies to optimize image segmentation this may lead to a more objective, transferable and stable knowledge-based system for the mapping of landslides from optical satellite data and DEMs.

MedSynDiKATe--design considerations for an ontology-based medical text understanding system.

PubMed Central

Hahn, U.; Romacker, M.; Schulz, S.

2000-01-01

MedSynDiKATe is a natural language processor for automatically acquiring knowledge from medical finding reports. The content of these documents is transferred to formal representation structures which constitute a corresponding text knowledge base. The general system architecture we present integrates requirements from the analysis of single sentences, as well as those of referentially linked sentences forming cohesive texts. The strong demands MedSynDiKATe poses to the availability of expressive knowledge sources are accounted for by two alternative approaches to (semi)automatic ontology engineering. PMID:11079899

Relatedness-based Multi-Entity Summarization

PubMed Central

Gunaratna, Kalpa; Yazdavar, Amir Hossein; Thirunarayan, Krishnaprasad; Sheth, Amit; Cheng, Gong

2017-01-01

Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail), and intelligent personal assistants (e.g., Google Now, Amazon Echo, and Apple’s Siri). In this paper, we present an approach that can summarize facts about a collection of entities by analyzing their relatedness in preference to summarizing each entity in isolation. Specifically, we generate informative entity summaries by selecting: (i) inter-entity facts that are similar and (ii) intra-entity facts that are important and diverse. We employ a constrained knapsack problem solving approach to efficiently compute entity summaries. We perform both qualitative and quantitative experiments and demonstrate that our approach yields promising results compared to two other stand-alone state-of-the-art entity summarization approaches. PMID:29051696

Improving drivers' knowledge of road rules using digital games.

PubMed

Li, Qing; Tay, Richard

2014-04-01

Although a proficient knowledge of the road rules is important to safe driving, many drivers do not retain the knowledge acquired after they have obtained their licenses. Hence, more innovative and appealing methods are needed to improve drivers' knowledge of the road rules. This study examines the effect of game based learning on drivers' knowledge acquisition and retention. We find that playing an entertaining game that is designed to impart knowledge of the road rules not only improves players' knowledge but also helps them retain such knowledge. Hence, learning by gaming appears to be a promising learning approach for driver education. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Impact of Team-Based Learning on Nervous System Examination Knowledge of Nursing Students.

PubMed

Hemmati Maslakpak, Masomeh; Parizad, Naser; Zareie, Farzad

2015-12-01

Team-based learning is one of the active learning approaches in which independent learning is combined with small group discussion in the class. This study aimed to determine the impact of team-based learning in nervous system examination knowledge of nursing students. This quasi-experimental study was conducted on 3(rd) grade nursing students, including 5th semester (intervention group) and 6(th) semester (control group). The traditional lecture method and the team-based learning method were used for educating the examination of the nervous system for intervention and control groups, respectively. The data were collected by a test covering 40-questions (multiple choice, matching, gap-filling and descriptive questions) before and after intervention in both groups. Individual Readiness Assurance Test (RAT) and Group Readiness Assurance Test (GRAT) used to collect data in the intervention group. In the end, the collected data were analyzed by SPSS ver. 13 using descriptive and inferential statistical tests. In team-based learning group, mean and standard deviation was 13.39 (4.52) before the intervention, which had been increased to 31.07 (3.20) after the intervention and this increase was statistically significant. Also, there was a statistically significant difference between the scores of RAT and GRAT in team-based learning group. Using team-based learning approach resulted in much better improvement and stability in the nervous system examination knowledge of nursing students compared to traditional lecture method; therefore, this method could be efficiently used as an effective educational approach in nursing education.

Comparing Health Education Approaches in Textbooks of Sixteen Countries

ERIC Educational Resources Information Center

Carvalho, Graca S.; Dantas, Catarina; Rauma, Anna-Liisa; Luzi, Daniela; Ruggieri, Roberta; Bogner, Franz; Geier, Christine; Caussidier, Claude; Berger, Dominique; Clement, Pierre

2008-01-01

Classically, health education has provided mainly factual knowledge about diseases and their prevention. This educational approach is within the so called Biomedical Model (BM). It is based on pathologic (Pa), curative (Cu) and preventive (Pr) conceptions of health. In contrast, the Health Promotion (HP) approach of health education intends to…

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

PubMed

Maier, Dieter; Kalus, Wenzel; Wolff, Martin; Kalko, Susana G; Roca, Josep; Marin de Mas, Igor; Turan, Nil; Cascante, Marta; Falciani, Francesco; Hernandez, Miguel; Villà-Freixa, Jordi; Losko, Sascha

2011-03-05

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. 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. 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 retrieval of sub-networks including protein-protein interaction, pathway, gene--disease and gene--compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

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

PubMed Central

2011-01-01

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 retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development. PMID:21375767

Argumentation Based Joint Learning: A Novel Ensemble Learning Approach

PubMed Central

Xu, Junyi; Yao, Li; Li, Le

2015-01-01

Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification. PMID:25966359

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

PubMed

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.

Attachment Theory and Neuroscience for Care Managers.

PubMed

Blakely, Thomas J; Dziadosz, Gregory M

2016-09-01

This article describes a model for care managers that is based on attachment theory supplemented by knowledge from neuroscience. Together, attachment theory and basic knowledge from neuroscience provide for both an organizing conceptual framework and a scientific, measureable approach to assessment and planning interventions in a care plan.

Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology.

PubMed

Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S; Venkatasubramanian, Venkat

2017-10-11

There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. ©Zhizun Zhang, Mila C Gonzalez, Stephen S Morse, Venkat Venkatasubramanian. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.10.2017.

Toward translational incremental similarity-based reasoning in breast cancer grading

NASA Astrophysics Data System (ADS)

Tutac, Adina E.; Racoceanu, Daniel; Leow, Wee-Keng; Müller, Henning; Putti, Thomas; Cretu, Vladimir

2009-02-01

One of the fundamental issues in bridging the gap between the proliferation of Content-Based Image Retrieval (CBIR) systems in the scientific literature and the deficiency of their usage in medical community is based on the characteristic of CBIR to access information by images or/and text only. Yet, the way physicians are reasoning about patients leads intuitively to a case representation. Hence, a proper solution to overcome this gap is to consider a CBIR approach inspired by Case-Based Reasoning (CBR), which naturally introduces medical knowledge structured by cases. Moreover, in a CBR system, the knowledge is incrementally added and learned. The purpose of this study is to initiate a translational solution from CBIR algorithms to clinical practice, using a CBIR/CBR hybrid approach. Therefore, we advance the idea of a translational incremental similarity-based reasoning (TISBR), using combined CBIR and CBR characteristics: incremental learning of medical knowledge, medical case-based structure of the knowledge (CBR), image usage to retrieve similar cases (CBIR), similarity concept (central for both paradigms). For this purpose, three major axes are explored: the indexing, the cases retrieval and the search refinement, applied to Breast Cancer Grading (BCG), a powerful breast cancer prognosis exam. The effectiveness of this strategy is currently evaluated over cases provided by the Pathology Department of Singapore National University Hospital, for the indexing. With its current accuracy, TISBR launches interesting perspectives for complex reasoning in future medical research, opening the way to a better knowledge traceability and a better acceptance rate of computer-aided diagnosis assistance among practitioners.

Discursive archaeology: constituting knowledge of militant nurses in trade associations.

PubMed

Almeida, Deybson Borba de; Silva, Gilberto Tadeu Reis da; Freitas, Genival Fernandes de; Padilha, Maria Itayra; Almeida, Igor Ferreira Borba de

2018-05-01

To analyze the constituting knowledge of militant nurses in trade associations. Historical research, based on the oral history method, with a qualitative approach carried out with 11 nurses who are/were militants for professional issues since the 1980s in the state of Bahia. The data collected through semi-structured interviews were organized in the software n-vivo 10 and analyzed based on dialectical hermeneutics. We identified pedagogical, administrative, public health, sociological, and trade union background knowledge as constituent of militant individuals. Final considerations: The constituting knowledge of militant nurses are inscribed in the Social Sciences, distanced from biomedical knowledge and power, pointing at ways for structuring nursing curricula. We identified the Brazilian Association of Nursing as a space for political formation.

Knowledge bases built on web languages from the point of view of predicate logics

NASA Astrophysics Data System (ADS)

Vajgl, Marek; Lukasová, Alena; Žáček, Martin

2017-06-01

The article undergoes evaluation of formal systems created on the base of web (ontology/concept) languages by simplifying the usual approach of knowledge representation within the FOPL, but sharing its expressiveness, semantic correct-ness, completeness and decidability. Evaluation of two of them - that one based on description logic and that one built on RDF model principles - identifies some of the lacks of those formal systems and presents, if possible, corrections of them. Possibilities to build an inference system capable to obtain new further knowledge over given knowledge bases including those describing domains by giant linked domain databases has been taken into account. Moreover, the directions towards simplifying FOPL language discussed here has been evaluated from the point of view of a possibility to become a web language for fulfilling an idea of semantic web.

Two Different Approaches to Automated Mark Up of Emotions in Text

NASA Astrophysics Data System (ADS)

Francisco, Virginia; Hervás, Raqucl; Gervás, Pablo

This paper presents two different approaches to automated marking up of texts with emotional labels. For the first approach a corpus of example texts previously annotated by human evaluators is mined for an initial assignment of emotional features to words. This results in a List of Emotional Words (LEW) which becomes a useful resource for later automated mark up. The mark up algorithm in this first approach mirrors closely the steps taken during feature extraction, employing for the actual assignment of emotional features a combination of the LEW resource and WordNet for knowledge-based expansion of words not occurring in LEW. The algorithm for automated mark up is tested against new text samples to test its coverage. The second approach mark up texts during their generation. We have a knowledge base which contains the necessary information for marking up the text. This information is related to actions and characters. The algorithm in this case employ the information of the knowledge database and decides the correct emotion for every sentence. The algorithm for automated mark up is tested against four different texts. The results of the two approaches are compared and discussed with respect to three main issues: relative adequacy of each one of the representations used, correctness and coverage of the proposed algorithms, and additional techniques and solutions that may be employed to improve the results.

Effects of the Team Competition-Based Ubiquitous Gaming Approach on Students' Interactive Patterns, Collective Efficacy and Awareness of Collaboration and Communication

ERIC Educational Resources Information Center

Chen, Chih-Hung; Hwang, Gwo-Jen

2017-01-01

Previous research has illustrated the importance of acquiring knowledge from authentic contexts; however, without full engagement, students' learning performance might not be as good as expected. In this study, a Team Competition-based Ubiquitous Gaming approach was proposed for improving students' learning effectiveness in authentic learning…

An Investigation of Primary School Teachers' PCK towards Science Subjects Using an Inquiry-Based Approach

ERIC Educational Resources Information Center

Alkis Küçükaydin, Mensure; Uluçinar Sagir, Safak

2016-01-01

In this study, the pedagogical content knowledge (PCK) of four experienced primary school teachers was investigated within the "Let's Solve the Riddle of Our Body Unit". The PCK investigation adopted a learning approach based on inquiry, content representation and pedagogical and professional-experience repertoires (PaP-eRs), and…

The Impact of a Scaffolded Assessment Intervention on Students' Academic Achievement in Web-Based Peer Assessment Activities

ERIC Educational Resources Information Center

Lee, Chien-I; Yang, Ya-Fei; Mai, Shin-Yi

2016-01-01

Web-based peer assessment has been considered an important process for learning. However, students may not offer constructive feedback due to lack of expertise knowledge. Therefore, this study proposed a scaffolded assessment approach accordingly. To evaluate the effectiveness of the proposed approach, the quasi-experimental design was employed to…

Exploring Graduate Entrepreneurship. A Collaborative, Co-Learning Based Approach for Students, Entrepreneurs and Educators

ERIC Educational Resources Information Center

Hannon, Paul D.; Collins, Lorna A.; Smith, Alison J.

2005-01-01

There is a strong interest in knowledge-based economies in increasing the levels of graduate entrepreneurship. The role of higher education in this context is crucial in enhancing the motivation and capability of graduates to engage in entrepreneurial activity. However, traditional pedagogical approaches in business and management as applied to…

Impact of Guided-Inquiry-Based Instruction with a Writing and Reflection Emphasis on Chemistry Students' Critical Thinking Abilities

ERIC Educational Resources Information Center

Gupta, Tanya; Burke, K. A.; Mehta, Akash; Greenbowe, Thomas J.

2015-01-01

The Science Writing Heuristic (SWH) laboratory instruction approach has been used successfully over a decade to engage students in laboratory activities. SWH-based instruction emphasizes knowledge construction through individual writing and reflection, and collaborative learning as a group. In the SWH approach, writing is a core component of…

Exploring Teacher Use of an Online Forum to Develop Game-Based Learning Literacy

ERIC Educational Resources Information Center

Barany, Amanda; Shah, Mamta; Foster, Aroutis

2017-01-01

Game-based learning researchers have emphasized the importance of teachers' game literacy and knowledge of pedagogical approaches involved in successfully adopting an instructional approach (Bell and Gresalfi, 2017). In this paper, we describe findings from an online resource that teachers used to generate a repository of games for use both during…

A Concept-Based Approach to Teaching Speech Acts in the EFL Classroom

ERIC Educational Resources Information Center

Nicholas, Allan

2015-01-01

While concept-based instruction (CBI), grounded in sociocultural theory, has been the subject of increased attention in recent years, it is still a relatively unknown methodology in language teaching contexts. In this approach, the emphasis is on helping learners develop a deep, conceptual understanding of a skill or knowledge area, so that this…

Efficacy of Blended Preservice Training for Resource Parents

PubMed Central

White, Lee; Delaney, Richard; Pacifici, Caesar; Nelson, Carol; Whitkin, Josh; Lovejoy, Maureen; Smalley, Betsy Keefer

2017-01-01

To evaluate a new way of meeting the growing demand for training prospective resource parents, our study compared the efficacy of a blended online and in-person approach with a traditional classroom-only approach. Findings based on a sample of 111 resource parent prospects showed significantly greater gains in knowledge from pre- to posttest for the blended approach over the classroom-only approach. The blended approach also produced dramatically lower dropout rates during preservice training. Both groups made significant gains in parenting awareness from pre to post, but those gains were greater for the classroom-only approach. Post hoc analyses examined this finding more closely. Satisfaction with training was comparably high for both groups. Gains in knowledge and awareness were sustained at a 3-month follow-up assessment. PMID:28626240

Exploring relation types for literature-based discovery.

PubMed

Preiss, Judita; Stevenson, Mark; Gaizauskas, Robert

2015-09-01

Literature-based discovery (LBD) aims to identify "hidden knowledge" in the medical literature by: (1) analyzing documents to identify pairs of explicitly related concepts (terms), then (2) hypothesizing novel relations between pairs of unrelated concepts that are implicitly related via a shared concept to which both are explicitly related. Many LBD approaches use simple techniques to identify semantically weak relations between concepts, for example, document co-occurrence. These generate huge numbers of hypotheses, difficult for humans to assess. More complex techniques rely on linguistic analysis, for example, shallow parsing, to identify semantically stronger relations. Such approaches generate fewer hypotheses, but may miss hidden knowledge. The authors investigate this trade-off in detail, comparing techniques for identifying related concepts to discover which are most suitable for LBD. A generic LBD system that can utilize a range of relation types was developed. Experiments were carried out comparing a number of techniques for identifying relations. Two approaches were used for evaluation: replication of existing discoveries and the "time slicing" approach.(1) RESULTS: Previous LBD discoveries could be replicated using relations based either on document co-occurrence or linguistic analysis. Using relations based on linguistic analysis generated many fewer hypotheses, but a significantly greater proportion of them were candidates for hidden knowledge. The use of linguistic analysis-based relations improves accuracy of LBD without overly damaging coverage. LBD systems often generate huge numbers of hypotheses, which are infeasible to manually review. Improving their accuracy has the potential to make these systems significantly more usable. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Galactic Structure: A Constructivist Approach to Teaching Astronomy.

ERIC Educational Resources Information Center

Domenech, Antonio; Casasus, Elena

1991-01-01

An astrophysics course based on the constructivist approach to science teaching is described. The study of galactic structure is given as an example. Direct experiences and observations, representative-symbolic language, organized knowledge, and formal strategies are emphasized. (KR)

Using the knowledge-to-action framework to guide the timing of dialysis initiation.

PubMed

Sood, Manish M; Manns, Braden; Nesrallah, Gihad

2014-05-01

The optimal time at which to initiate chronic dialysis remains unknown. Using a contemporary knowledge translation approach (the knowledge-to-action framework), a pan-Canadian collaboration (CANN-NET) set out to study the scope of the problem, then develop and disseminate evidence-based guidelines addressing the timing of dialysis initiation. The purpose of this review is to summarize the key findings and describe the planned Canadian knowledge translation strategy for improving knowledge and practices pertaining to the timing dialysis initiation. New research has provided considerable insights regarding the initiation of dialysis. A Canadian cohort study identified significant variation in the estimated glomerular filtration rate level at dialysis initiation, and a survey of providers identified related knowledge gaps that might be amenable to knowledge translation interventions. A recent knowledge synthesis/guideline concluded that early dialysis initiation is costly, and provides no measureable clinical benefits. A systematic knowledge translation intervention including a multifaceted approach may aid in reducing variation in practice and improving the quality of care. Utilizing the knowledge-to-action framework, we identified practice variation and key barriers to the optimal timing for dialysis initiation that may be amenable to knowledge translation strategies.

Is it time to drop the 'knowledge translation' metaphor? A critical literature review.

PubMed

Greenhalgh, Trisha; Wieringa, Sietse

2011-12-01

The literature on 'knowledge translation' presents challenges for the reviewer because different terms have been used to describe the generation, sharing and application of knowledge and different research approaches embrace different philosophical positions on what knowledge is. We present a narrative review of this literature which deliberately sought to highlight rather than resolve tensions between these different framings. Our findings suggest that while 'translation' is a widely used metaphor in medicine, it constrains how we conceptualise and study the link between knowledge and practice. The 'translation' metaphor has, arguably, led to particular difficulties in the fields of 'evidence-based management' and 'evidence-based policymaking' - where it seems that knowledge obstinately refuses to be driven unproblematically into practice. Many non-medical disciplines such as philosophy, sociology and organization science conceptualise knowledge very differently, as being (for example) 'created', 'constructed', 'embodied', 'performed' and 'collectively negotiated' - and also as being value-laden and tending to serve the vested interests of dominant élites. We propose that applying this wider range of metaphors and models would allow us to research the link between knowledge and practice in more creative and critical ways. We conclude that research should move beyond a narrow focus on the 'know-do gap' to cover a richer agenda, including: (a) the situation-specific practical wisdom (phronesis) that underpins clinical judgement; (b) the tacit knowledge that is built and shared among practitioners ('mindlines'); (c) the complex links between power and knowledge; and (d) approaches to facilitating macro-level knowledge partnerships between researchers, practitioners, policymakers and commercial interests.

The Second Prototype of the Development of a Technological Pedagogical Content Knowledge Based Instructional Design Model: An Implementation Study in a Technology Integration Course

ERIC Educational Resources Information Center

Lee, Chia-Jung; Kim, ChanMin

2014-01-01

This study presents a refined technological pedagogical content knowledge (also known as TPACK) based instructional design model, which was revised using findings from the implementation study of a prior model. The refined model was applied in a technology integration course with 38 preservice teachers. A case study approach was used in this…

Flipped Instruction in English Language Teacher Education: A Design-­Based Study in a Complex, Open-­Ended Learning Environment

ERIC Educational Resources Information Center

Egbert, Joy; Herman, David; Lee, HyunGyung

2015-01-01

Reports of flipped classrooms across areas in the field of ESL are rare, and those that address the complexities of ESL teacher education, particularly the methods course in which procedural knowledge is privileged over declarative knowledge, are even rarer. This paper uses a design-­-based research (DBR) approach to explore the flip of an ESL…

Knowledge and Attitudes of Ugandan Preservice Science and Mathematics Teachers toward Global and Ugandan Science--and Technology-Based Problems and/or Threats

ERIC Educational Resources Information Center

Robinson, Michael; Tibanyendera, Basil; Seltzer-Kelly, Debbie

2007-01-01

This article reports the effects of a science, technology, and society (STS) teaching approach on the knowledge and attitudes of preservice science and mathematics teachers in Uganda toward global science and technology-based problems and/or threats. The responses of a baseline or control group (N = 50) and an experimental group (N = 50) to five…

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

PubMed

Thiele, Ines; Hyduke, Daniel R; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan M T; Hsiung, Chao A; De Keersmaecker, Sigrid C J; Liao, Yu-Chieh; Marchal, Kathleen; Mo, Monica L; Özdemir, Emre; Raghunathan, Anu; Reed, Jennifer L; Shin, Sook-il; Sigurbjörnsdóttir, Sara; Steinmann, Jonas; Sudarsan, Suresh; Swainston, Neil; Thijs, Inge M; Zengler, Karsten; Palsson, Bernhard O; Adkins, Joshua N; Bumann, Dirk

2011-01-18

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thiele, Ines; Hyduke, Daniel R.; Steeb, Benjamin

2011-01-01

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of thismore » reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Finally, taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.« less

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

NASA Astrophysics Data System (ADS)

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 throughout the program. More specifically, analysis of the teachers' discourse during the second version revealed that the program led to significant changes in teachers' knowledge about their students' knowledge and in teachers' views about the following: 1. the advantages of the KIRs' innovative teaching tool, 2. the "evidence" as a useful resource for evaluating the contribution of the KIRs to students' learning, and more generally, as a powerful tool for investigating students' learning, and for improving practice, and 3. several "learner-centered" pedagogical aspects: the importance and legitimacy of learning from peers, the need to listen carefully to students' ideas and reflections, and the need to investigate students' knowledge using a variety of methods, and to plan the teaching accordingly. Our analysis of the students' worksheets verified the teachers' findings about their students' initial state of knowledge and the improvement of this knowledge as a result of advancing through the KIR phases. When we extended the sample and examined worksheets of additional classes, we found similar findings. We also found that the students were aware of the improvement in their knowledge and attributed this improvement to their working with the KIRs. Two major recommendations emerge from this study: 1. We recommend that KIRs be routinely incorporated into physics teaching. The results show that the KIRs contribute to teachers' practice and to students' learning and support the teachers in becoming more learner-centered in their teaching. 2. We recommend incorporating an evidence-based approach in long-term programs aimed at bringing about a significant change in the teachers' practice. In order to engage the teachers with the evidence endeavor, it is recommended to introduce them an innovative teaching tool that is considered by them important and to evoke their curiosity to find out empirically about the influence of the tool on their students' learning. It is also recommended to engage the teachers in ongoing interactions about their experience in implementing the innovative tools in their classes through an online platform by which special, simple online tools are enacted. The present study has several limitations that suggest directions for further study, some of which can be based on the present set of data, but others require additional study. These directions include a detailed study of individual teachers' professional development, studies of ways to up-scale the evidence-based approach and use it effectively in less intensive courses, an extensive study of how students study with the improved versions of the KIRs that resulted from this study, and further investigation into how the new computerized tools can be utilized in professional development courses. (Abstract shortened by UMI.)

Systems of evidence-based healthcare and personalised health information: some international and national trends.

PubMed

Gordon, C; Gray, J A; Toth, B; Veloso, M

2000-01-01

In Europe, North America and elsewhere, growing interest has focussed on evidence-based healthcare systems, incorporating the deployment of practice guidelines, as a field of application for health telematics. The clinical benefit and technical feasibility of common European approaches to this task has recently been demonstrated. In Europe it is likely that, building on recent progress in electronic health record architecture (EHRA) standards, a sufficient state of maturity can be reached to justify initiation within CEN TC251 of a prestandards process on guideline content formats during the current 5th Framework of EC RT&D activity. There is now a similar impetus to agree standards for this field in North America. Thanks to fruitful EC-USA contacts during the 4th Framework programme, there is now a chance, given well-planned coordination, to establish a global consensus optimally suited to serve the world-wide delivery and application of evidence-based medicine. This review notes three factors which may accelerate progress to convergence: (1) revolutionary changes in the knowledge basis of professional/patient/public healthcare partnerships, involving the key role of the Web as a health knowledge resource for citizens, and a rapidly growing market for personalised health information and advice; (2) the emergence at national levels of digital warehouses of clinical guidelines and EBM knowledge resources, agencies which are capable of brokering common mark-up and interchange media definitions between knowledge providers, industry and healthcare organizations; (3) the closing gap in knowledge management technology, with the advent of XML and RDF, between approaches and services based respectively on text mark-up and knowledge-base paradigms. A current project in the UK National Health Service (the National electronic Library of Health) is cited as an example of a national initiative designed to harness these trends.

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

PubMed

Orgiazzi, Alberto; Panagos, Panos; Yigini, Yusuf; Dunbar, Martha B; Gardi, Ciro; Montanarella, Luca; Ballabio, Cristiano

2016-03-01

Because of the increasing pressures exerted on soil, below-ground life is under threat. Knowledge-based rankings of potential threats to different components of soil biodiversity were developed in order to assess the spatial distribution of threats on a European scale. A list of 13 potential threats to soil biodiversity was proposed to experts with different backgrounds in order to assess the potential for three major components of soil biodiversity: soil microorganisms, fauna, and biological functions. This approach allowed us to obtain knowledge-based rankings of threats. These classifications formed the basis for the development of indices through an additive aggregation model that, along with ad-hoc proxies for each pressure, allowed us to preliminarily assess the spatial patterns of potential threats. Intensive exploitation was identified as the highest pressure. In contrast, the use of genetically modified organisms in agriculture was considered as the threat with least potential. The potential impact of climate change showed the highest uncertainty. Fourteen out of the 27 considered countries have more than 40% of their soils with moderate-high to high potential risk for all three components of soil biodiversity. Arable soils are the most exposed to pressures. Soils within the boreal biogeographic region showed the lowest risk potential. The majority of soils at risk are outside the boundaries of protected areas. First maps of risks to three components of soil biodiversity based on the current scientific knowledge were developed. Despite the intrinsic limits of knowledge-based assessments, a remarkable potential risk to soil biodiversity was observed. Guidelines to preliminarily identify and circumscribe soils potentially at risk are provided. This approach may be used in future research to assess threat at both local and global scale and identify areas of possible risk and, subsequently, design appropriate strategies for monitoring and protection of soil biota. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

The effect of the PROSPER partnership model on cultivating local stakeholder knowledge of evidence-based programs: a five-year longitudinal study of 28 communities.

PubMed

Crowley, D Max; Greenberg, Mark T; Feinberg, Mark E; Spoth, Richard L; Redmond, Cleve R

2012-02-01

A substantial challenge in improving public health is how to facilitate the local adoption of evidence-based interventions (EBIs). To do so, an important step is to build local stakeholders' knowledge and decision-making skills regarding the adoption and implementation of EBIs. One EBI delivery system, called PROSPER (PROmoting School-community-university Partnerships to Enhance Resilience), has effectively mobilized community prevention efforts, implemented prevention programming with quality, and consequently decreased youth substance abuse. While these results are encouraging, another objective is to increase local stakeholder knowledge of best practices for adoption, implementation and evaluation of EBIs. Using a mixed methods approach, we assessed local stakeholder knowledge of these best practices over 5 years, in 28 intervention and control communities. Results indicated that the PROSPER partnership model led to significant increases in expert knowledge regarding the selection, implementation, and evaluation of evidence-based interventions. Findings illustrate the limited programming knowledge possessed by members of local prevention efforts, the difficulty of complete knowledge transfer, and highlight one method for cultivating that knowledge.

Learning Resources Organization Using Ontological Framework

NASA Astrophysics Data System (ADS)

Gavrilova, Tatiana; Gorovoy, Vladimir; Petrashen, Elena

The paper describes the ontological approach to the knowledge structuring for the e-learning portal design as it turns out to be efficient and relevant to current domain conditions. It is primarily based on the visual ontology-based description of the content of the learning materials and this helps to provide productive and personalized access to these materials. The experience of ontology developing for Knowledge Engineering coursetersburg State University is discussed and “OntolingeWiki” tool for creating ontology-based e-learning portals is described.

Search Path Mapping: A Versatile Approach for Visualizing Problem-Solving Behavior.

ERIC Educational Resources Information Center

Stevens, Ronald H.

1991-01-01

Computer-based problem-solving examinations in immunology generate graphic representations of students' search paths, allowing evaluation of how organized and focused their knowledge is, how well their organization relates to critical concepts in immunology, where major misconceptions exist, and whether proper knowledge links exist between content…

Using Food Science Concepts to Enact Science-Indigenous Knowledge Systems Classroom Based Discourses

ERIC Educational Resources Information Center

Kwofie, Samuel; Ogunniyi, Meshach

2011-01-01

According to the World Bank and United Nations Educational, Scientific and Cultural Organization (UNESCO), Indigenous knowledge systems (IKS) could serve as leverage for augmenting policy formulation regarding health, environment and education. By exploring the appropriate pedagogic approaches, the potential exist for integrating IKS into the…

A Semi-Automatic Approach to Construct Vietnamese Ontology from Online Text

ERIC Educational Resources Information Center

Nguyen, Bao-An; Yang, Don-Lin

2012-01-01

An ontology is an effective formal representation of knowledge used commonly in artificial intelligence, semantic web, software engineering, and information retrieval. In open and distance learning, ontologies are used as knowledge bases for e-learning supplements, educational recommenders, and question answering systems that support students with…

Web-Mediated Knowledge Synthesis for Educators

ERIC Educational Resources Information Center

DeSchryver, Michael

2015-01-01

Ubiquitous and instant access to information on the Web is challenging what constitutes 21st century literacies. This article explores the notion of Web-mediated knowledge synthesis, an approach to integrating Web-based learning that may result in generative synthesis of ideas. This article describes the skills and strategies that may support…

Indigenous Knowledge Construction and Experiential Learning of Taiwanese Aborigines

ERIC Educational Resources Information Center

Lee, Ying

2009-01-01

Indigenous peoples in Taiwan belong to the Austronesian racial group. Confined to their oral language tradition, knowledge about Taiwan aborigines based on written documents reflected the positionality of dominant ethnic groups. This qualitative study employed participatory research approach to explore the process of producing their own knowledge…

Stealing Knowledge in a Landscape of Learning: Conceptualizations of Jazz Education

ERIC Educational Resources Information Center

Bjerstedt, Sven

2016-01-01

Theoretical approaches to learning in practice-based jazz improvisation contexts include situated learning and ecological perspectives. This article focuses on how interest-driven, self-sustaining jazz learning activities can be matched against the concepts of stolen knowledge (Brown & Duguid, 1996) and landscape of learning (Bjerstedt, 2014).…

Self-Knowledge, Capacity and Sensitivity: Prerequisites to Authentic Leadership by School Principals

ERIC Educational Resources Information Center

Begley, Paul T.

2006-01-01

Purpose: The article proposes three prerequisites to authentic leadership by school principals: self-knowledge, a capacity for moral reasoning, and sensitivity to the orientations of others. Design/methodology/approach: A conceptual framework, based on research on the valuation processes of school principals and their strategic responses to…

Curriculum Guide for Health Occupations Education. Revised and Expanded.

ERIC Educational Resources Information Center

Oyler, Charles; Swinney, Peggy

Designed to emphasize the acquisition of job skills, job-practical knowledge, job-theoretical knowledge, and associative needs, this curriculum guide for health occupations education utilizes principles of competency-based education and is reflective of a training model approach to health occupations education. The first of three major parts…

Organizational Commitment, Knowledge Management Interventions, and Learning Organization Capacity

ERIC Educational Resources Information Center

Massingham, Peter; Diment, Kieren

2009-01-01

Purpose: The purpose of this paper is to examine the relationship between organizational commitment and knowledge management initiatives in developing learning organization capacity (LOC). Design/methodology/approach: This is an empirical study based on a single case study, using partial least squares (PLS) analysis. Findings: The strategic…

A Study of Holocaust Survivors: Implications for Curriculum

ERIC Educational Resources Information Center

Greene, Roberta R.

2010-01-01

This article presents an approach to human behavior curriculum that requires students to achieve the purpose outlined in the Council on Social Work Education's 2008 Educational Policy and Accreditation Standards to "distinguish, appraise, and integrate multiple sources of knowledge, including research-based knowledge." It emphasizes and allows for…

Computer integrated documentation

NASA Technical Reports Server (NTRS)

Boy, Guy

1991-01-01

The main technical issues of the Computer Integrated Documentation (CID) project are presented. The problem of automation of documents management and maintenance is analyzed both from an artificial intelligence viewpoint and from a human factors viewpoint. Possible technologies for CID are reviewed: conventional approaches to indexing and information retrieval; hypertext; and knowledge based systems. A particular effort was made to provide an appropriate representation for contextual knowledge. This representation is used to generate context on hypertext links. Thus, indexing in CID is context sensitive. The implementation of the current version of CID is described. It includes a hypertext data base, a knowledge based management and maintenance system, and a user interface. A series is also presented of theoretical considerations as navigation in hyperspace, acquisition of indexing knowledge, generation and maintenance of a large documentation, and relation to other work.

Capturing Knowledge In Order To Optimize The Cutting Process For Polyethylene Pipes Using Knowledge Models

NASA Astrophysics Data System (ADS)

Rotaru, Ionela Magdalena

2015-09-01

Knowledge management is a powerful instrument. Areas where knowledge - based modelling can be applied are different from business, industry, government to education area. Companies engage in efforts to restructure the database held based on knowledge management principles as they recognize in it a guarantee of models characterized by the fact that they consist only from relevant and sustainable knowledge that can bring value to the companies. The proposed paper presents a theoretical model of what it means optimizing polyethylene pipes, thus bringing to attention two important engineering fields, the one of the metal cutting process and gas industry, who meet in order to optimize the butt fusion welding process - the polyethylene cutting part - of the polyethylene pipes. All approach is shaped on the principles of knowledge management. The study was made in collaboration with companies operating in the field.

Identifying Liver Cancer and Its Relations with Diseases, Drugs, and Genes: A Literature-Based Approach

PubMed Central

Song, Min

2016-01-01

In biomedicine, scientific literature is a valuable source for knowledge discovery. Mining knowledge from textual data has become an ever important task as the volume of scientific literature is growing unprecedentedly. In this paper, we propose a framework for examining a certain disease based on existing information provided by scientific literature. Disease-related entities that include diseases, drugs, and genes are systematically extracted and analyzed using a three-level network-based approach. A paper-entity network and an entity co-occurrence network (macro-level) are explored and used to construct six entity specific networks (meso-level). Important diseases, drugs, and genes as well as salient entity relations (micro-level) are identified from these networks. Results obtained from the literature-based literature mining can serve to assist clinical applications. PMID:27195695

Literature-Based Instruction: Reshaping the Curriculum.

ERIC Educational Resources Information Center

Raphael, Taffy E., Ed.; Au, Kathryn H., Ed.

Making a case for the value of literature-based instruction, this book presents an overview of the extensive knowledge base supporting literature-based approaches to literacy instruction. It notes that literature-based instruction goes beyond simply changing the kinds of texts children read--also required in literature-based instruction are an…

Distributed Knowledge Base Systems for Diagnosis and Information Retrieval.

DTIC Science & Technology

1985-09-01

thinks of the idiagnostic task, while it may be generic in the sense that the task may be quite similar across domains, it is not a unitary task...solving in our approach,’, outgrowth of ou group’s experience with MDX, a meaning that a special kind of organization and Q medical diagnostic program...5.4. Determining the Findings of a Knowledge U). It is important that the meaning of the Group knowledge group’s result be clear. In this knowledge

Nurses experience of using scientific knowledge in clinical practice: a grounded theory study.

PubMed

Renolen, Åste; Hjälmhult, Esther

2015-12-01

Guidelines recommend the use of evidence-based practice in nursing. Nurses are expected to give patients care and treatment based on the best knowledge available. They may have knowledge and positive attitudes, but this does not mean that they are basing their work on evidence-based practice. Knowledge is still lacking about what is needed to successfully implement evidence-based practice. The aim of this study was to gain more knowledge about what nurses perceive as the most important challenge in implementing evidence-based practice and to explain how they act to face and overcome this challenge. We used classical grounded theory methodology and collected data through four focus groups and one individual interview in different geographical locations in one large hospital trust in Norway. Fourteen registered clinical practice nurses participated. We analysed the data in accordance with grounded theory, using the constant comparative method. Contextual balancing of knowledge emerged as the core category and explains how the nurses dealt with their main concern, how to determine what types of knowledge they could trust. The nurses' main strategies were an inquiring approach, examining knowledge and maintaining control while taking care of patients. They combined their own experienced-based knowledge and the guidelines of evidence-based practice with a sense of control in the actual situation. The grounded theory contextual balancing of knowledge may help us to understand how nurses detect what types of knowledge they can trust in clinical practice. The nurses needed to rely on what they did, and they seemed to rely on their own experience rather than on research. © 2015 Nordic College of Caring Science.

Integrated knowledge translation: digging deeper, moving forward.

PubMed

Kothari, Anita; Wathen, C Nadine

2017-06-01

Integrated knowledge translation has risen in popularity as a solution to the underuse of research in policy and practice settings. It engages knowledge users-policymakers, practitioners, patients/consumers or their advocates, and members of the wider public-in mutually beneficial research that can involve the joint development of research questions, data collection, analysis and dissemination of findings. Knowledge that is co-produced has a better chance of being implemented. The purpose of this paper is to update developments in the field of integrated knowledge translation through a deeper analysis of the approach in practice-oriented and policy-oriented health research. We present collaborative models that fall outside the scope of integrated knowledge translation, but then explore consensus-based approaches and networks as alternate sites of knowledge co-production. We discuss the need to advance the field through the development, or use, of data collection and interpretation tools that creatively engage knowledge users in the research process. Most importantly, conceptually relevant outcomes need to be identified, including ones that focus on team transformation through the co-production of knowledge. We explore some of these challenges and benefits in detail to help researchers understand what integrated knowledge translation means, and whether the approach's potential added value is worth the investment of time, energy and other resources. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat.

PubMed

Valluru, Ravi; Reynolds, Matthew P; Salse, Jerome

2014-07-01

Transferring the knowledge bases between related species may assist in enlarging the yield potential of crop plants. Being cereals, rice and wheat share a high level of gene conservation; however, they differ at metabolic levels as a part of the environmental adaptation resulting in different yield capacities. This review focuses on the current understanding of genetic and molecular regulation of yield-associated traits in both crop species, highlights the similarities and differences and presents the putative knowledge gaps. We focus on the traits associated with phenology, photosynthesis, and assimilate partitioning and lodging resistance; the most important drivers of yield potential. Currently, there are large knowledge gaps in the genetic and molecular control of such major biological processes that can be filled in a translational biology approach in transferring genomics and genetics informations between rice and wheat.

Safeguards Knowledge Management & Retention at U.S. National Laboratories.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haddal, Risa; Jones, Rebecca; Bersell, Bridget

In 2017, four U.S. National Laboratories collaborated on behalf of DOE/NNSA to explore the safeguards knowledge retention problem, identify possible approaches, and develop a strategy to address it. The one-year effort consisted of four primary tasks. First, the project sought to identify critical safeguards information at risk of loss. Second, a survey and workshop were conducted to assess nine U.S. National Laboratories' efforts to determine current safeguards knowledge retention practices and challenges, and identify best practices. Third, specific tools were developed to identify and predict critical safeguards knowledge gaps and how best to recruit in order to fill those gaps.more » Finally, based on findings from the first three tasks and research on other organizational approaches to address similar issues, a strategy was developed on potential knowledge retention methods, customized HR policies, and best practices that could be implemented across the National Laboratory Complex.« less

Knowledge for the good of the individual and society: linking philosophy, disciplinary goals, theory, and practice.

PubMed

McCurry, Mary K; Revell, Susan M Hunter; Roy, Sr Callista

2010-01-01

Nursing as a profession has a social mandate to contribute to the good of society through knowledge-based practice. Knowledge is built upon theories, and theories, together with their philosophical bases and disciplinary goals, are the guiding frameworks for practice. This article explores a philosophical perspective of nursing's social mandate, the disciplinary goals for the good of the individual and society, and one approach for translating knowledge into practice through the use of a middle-range theory. It is anticipated that the integration of the philosophical perspective and model into nursing practice will strengthen the philosophy, disciplinary goal, theory, and practice links and expand knowledge within the discipline. With the focus on humanization, we propose that nursing knowledge for social good will embrace a synthesis of the individual and the common good. This approach converges vital and agency needs described by Hamilton and the primacy of maintaining the heritage of the good within the human species as outlined by Maritain. Further, by embedding knowledge development in a changing social and health care context, nursing focuses on the goals of clinical reasoning and action. McCubbin and Patterson's Double ABCX Model of Family Adaptation was used as an example of a theory that can guide practice at the community and global level. Using the theory-practice link as a foundation, the Double ABCX model provides practising nurses with one approach to meet the needs of individuals and society. The integration of theory into nursing practice provides a guide to achieve nursing's disciplinary goals of promoting health and preventing illness across the globe. When nursing goals are directed at the synthesis of the good of the individual and society, nursing's social and moral mandate may be achieved.

The smooth (tractor) operator: insights of knowledge engineering.

PubMed

Cullen, Ralph H; Smarr, Cory-Ann; Serrano-Baquero, Daniel; McBride, Sara E; Beer, Jenay M; Rogers, Wendy A

2012-11-01

The design of and training for complex systems requires in-depth understanding of task demands imposed on users. In this project, we used the knowledge engineering approach (Bowles et al., 2004) to assess the task of mowing in a citrus grove. Knowledge engineering is divided into four phases: (1) Establish goals. We defined specific goals based on the stakeholders involved. The main goal was to identify operator demands to support improvement of the system. (2) Create a working model of the system. We reviewed product literature, analyzed the system, and conducted expert interviews. (3) Extract knowledge. We interviewed tractor operators to understand their knowledge base. (4) Structure knowledge. We analyzed and organized operator knowledge to inform project goals. We categorized the information and developed diagrams to display the knowledge effectively. This project illustrates the benefits of knowledge engineering as a qualitative research method to inform technology design and training. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Towards a Semantic E-Learning Theory by Using a Modelling Approach

ERIC Educational Resources Information Center

Yli-Luoma, Pertti V. J.; Naeve, Ambjorn

2006-01-01

In the present study, a semantic perspective on e-learning theory is advanced and a modelling approach is used. This modelling approach towards the new learning theory is based on the four SECI phases of knowledge conversion: Socialisation, Externalisation, Combination and Internalisation, introduced by Nonaka in 1994, and involving two levels of…

Creativity in the Language Classroom: Towards a "Vichian" Approach in Second Language Teaching.

ERIC Educational Resources Information Center

Danesi, Marcel; D'Alfonso, Aldo

1989-01-01

Describes a "Vichian" approach (involving linguistic imagination and creativity) to the exploration of basic pedagogical matters in classroom language teaching. The approach is based on principles involving: (1) concrete language knowledge; (2) development from the concrete to the abstract; (3) the role of metaphor in verbal creativity;…

Automatic Generation of Tests from Domain and Multimedia Ontologies

ERIC Educational Resources Information Center

Papasalouros, Andreas; Kotis, Konstantinos; Kanaris, Konstantinos

2011-01-01

The aim of this article is to present an approach for generating tests in an automatic way. Although other methods have been already reported in the literature, the proposed approach is based on ontologies, representing both domain and multimedia knowledge. The article also reports on a prototype implementation of this approach, which…

Three Studies of Service-Learning as an Approach to Movement Integration in Elementary Classrooms

ERIC Educational Resources Information Center

Michael, Robert D., Jr.

2017-01-01

This dissertation consists of three studies that examine service-learning (SL) as an approach to incorporating movement integration (MI) in elementary classrooms as part of a comprehensive school physical activity program (CSPAP). All three studies attempt to advance the knowledge base about using partnership approaches to supporting school based…

A Catalyst-for-Change Approach to Evaluation Capacity Building

ERIC Educational Resources Information Center

Garcia-Iriarte, Edurne; Suarez-Balcazar, Yolanda; Taylor-Ritzler, Tina; Luna, Maria

2011-01-01

Evaluation capacity building (ECB) has become a popular approach for helping community-based organizations (CBOs) to meet their funders' demands for accountability. This case study reports the ECB process with one staff member using a catalyst-for-change approach. The authors analyzed the role of the catalyst in diffusing evaluation knowledge and…

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

NASA Technical Reports Server (NTRS)

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.

Learning About Semi Conductors for Teaching—the Role Played by Content Knowledge in Pedagogical Content Knowledge (PCK) Development

NASA Astrophysics Data System (ADS)

Rollnick, Marissa

2017-08-01

This study focuses on how teachers learn to teach a new topic and the role played by their developing content knowledge as they teach. The paper is based on seven high school science teachers' studies on the teaching of semiconductors, at the time a new topic in the curriculum. Analysis of artefacts such as teacher concept maps, video recordings of lessons, journals and other classroom-based evidence shows how the extent and type of teachers' content knowledge informed their choice of teaching approaches and how their learning of content took place alongside the development of teaching strategies. The development of content knowledge was combined with increased understanding of how to teach the topic in almost all cases. Evidence of development of teachers' PCK was found in their increased ability to design teaching strategies, and their use of representations and suitable assessment tasks for their lessons. Some specific common teaching strategies were identified across the teachers. These strategies could add to the canon of teachers' topic - specific professional knowledge for semiconductors. The study provides increased understanding of how teachers simultaneously master content and its teaching and how mediated self-reflection is a fruitful approach for assisting teachers to learn to teach a new topic.

Active Learning in Engineering Education: a (re)introduction

NASA Astrophysics Data System (ADS)

Lima, Rui M.; Andersson, Pernille Hammar; Saalman, Elisabeth

2017-01-01

The informal network 'Active Learning in Engineering Education' (ALE) has been promoting Active Learning since 2001. ALE creates opportunity for practitioners and researchers of engineering education to collaboratively learn how to foster learning of engineering students. The activities in ALE are centred on the vision that learners construct their knowledge based on meaningful activities and knowledge. In 2014, the steering committee of the ALE network reinforced the need to discuss the meaning of Active Learning and that was the base for this proposal for a special issue. More than 40 submissions were reviewed by the European Journal of Engineering Education community and this theme issue ended up with eight contributions, which are different both in their research and Active Learning approaches. These different Active Learning approaches are aligned with the different approaches that can be increasingly found in indexed journals.

From the EBM pyramid to the Greek temple: a new conceptual approach to Guidelines as implementation tools in mental health.

PubMed

Salvador-Carulla, L; Lukersmith, S; Sullivan, W

2017-04-01

Guideline methods to develop recommendations dedicate most effort around organising discovery and corroboration knowledge following the evidence-based medicine (EBM) framework. Guidelines typically use a single dimension of information, and generally discard contextual evidence and formal expert knowledge and consumer's experiences in the process. In recognition of the limitations of guidelines in complex cases, complex interventions and systems research, there has been significant effort to develop new tools, guides, resources and structures to use alongside EBM methods of guideline development. In addition to these advances, a new framework based on the philosophy of science is required. Guidelines should be defined as implementation decision support tools for improving the decision-making process in real-world practice and not only as a procedure to optimise the knowledge base of scientific discovery and corroboration. A shift from the model of the EBM pyramid of corroboration of evidence to the use of broader multi-domain perspective graphically depicted as 'Greek temple' could be considered. This model takes into account the different stages of scientific knowledge (discovery, corroboration and implementation), the sources of knowledge relevant to guideline development (experimental, observational, contextual, expert-based and experiential); their underlying inference mechanisms (deduction, induction, abduction, means-end inferences) and a more precise definition of evidence and related terms. The applicability of this broader approach is presented for the development of the Canadian Consensus Guidelines for the Primary Care of People with Developmental Disabilities.

Differences among Major Taxa in the Extent of Ecological Knowledge across Four Major Ecosystems

PubMed Central

Fisher, Rebecca; Knowlton, Nancy; Brainard, Russell E.; Caley, M. Julian

2011-01-01

Existing knowledge shapes our understanding of ecosystems and is critical for ecosystem-based management of the world's natural resources. Typically this knowledge is biased among taxa, with some taxa far better studied than others, but the extent of this bias is poorly known. In conjunction with the publically available World Registry of Marine Species database (WoRMS) and one of the world's premier electronic scientific literature databases (Web of Science®), a text mining approach is used to examine the distribution of existing ecological knowledge among taxa in coral reef, mangrove, seagrass and kelp bed ecosystems. We found that for each of these ecosystems, most research has been limited to a few groups of organisms. While this bias clearly reflects the perceived importance of some taxa as commercially or ecologically valuable, the relative lack of research of other taxonomic groups highlights the problem that some key taxa and associated ecosystem processes they affect may be poorly understood or completely ignored. The approach outlined here could be applied to any type of ecosystem for analyzing previous research effort and identifying knowledge gaps in order to improve ecosystem-based conservation and management. PMID:22073172

Are Dewey's Ideas Alive and Well in New Zealand Undergraduate Education? Kiwi Case Studies of Inquiry-Based Learning

ERIC Educational Resources Information Center

O'Steen, Billy

2008-01-01

Inquiry-based learning (IBL) is an approach that could be used by undergraduate educators that appears to meet the suggestions by Dewey to integrate students' interests and experiences with content knowledge. The IBL approach has been described as "a range of strategies used to promote learning through students' active, and increasingly…

Prior knowledge-based approach for associating ...

EPA Pesticide Factsheets

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

A standard based approach for biomedical knowledge representation.

PubMed

Farkash, Ariel; Neuvirth, Hani; Goldschmidt, Yaara; Conti, Costanza; Rizzi, Federica; Bianchi, Stefano; Salvi, Erika; Cusi, Daniele; Shabo, Amnon

2011-01-01

The new generation of health information standards, where the syntax and semantics of the content is explicitly formalized, allows for interoperability in healthcare scenarios and analysis in clinical research settings. Studies involving clinical and genomic data include accumulating knowledge as relationships between genotypic and phenotypic information as well as associations within the genomic and clinical worlds. Some involve analysis results targeted at a specific disease; others are of a predictive nature specific to a patient and may be used by decision support applications. Representing knowledge is as important as representing data since data is more useful when coupled with relevant knowledge. Any further analysis and cross-research collaboration would benefit from persisting knowledge and data in a unified way. This paper describes a methodology used in Hypergenes, an EC FP7 project targeting Essential Hypertension, which captures data and knowledge using standards such as HL7 CDA and Clinical Genomics, aligned with the CEN EHR 13606 specification. We demonstrate the benefits of such an approach for clinical research as well as in healthcare oriented scenarios.

Definition of sampling units begets conclusions in ecology: the case of habitats for plant communities.

PubMed

Mörsdorf, Martin A; Ravolainen, Virve T; Støvern, Leif Einar; Yoccoz, Nigel G; Jónsdóttir, Ingibjörg Svala; Bråthen, Kari Anne

2015-01-01

In ecology, expert knowledge on habitat characteristics is often used to define sampling units such as study sites. Ecologists are especially prone to such approaches when prior sampling frames are not accessible. Here we ask to what extent can different approaches to the definition of sampling units influence the conclusions that are drawn from an ecological study? We do this by comparing a formal versus a subjective definition of sampling units within a study design which is based on well-articulated objectives and proper methodology. Both approaches are applied to tundra plant communities in mesic and snowbed habitats. For the formal approach, sampling units were first defined for each habitat in concave terrain of suitable slope using GIS. In the field, these units were only accepted as the targeted habitats if additional criteria for vegetation cover were fulfilled. For the subjective approach, sampling units were defined visually in the field, based on typical plant communities of mesic and snowbed habitats. For each approach, we collected information about plant community characteristics within a total of 11 mesic and seven snowbed units distributed between two herding districts of contrasting reindeer density. Results from the two approaches differed significantly in several plant community characteristics in both mesic and snowbed habitats. Furthermore, differences between the two approaches were not consistent because their magnitude and direction differed both between the two habitats and the two reindeer herding districts. Consequently, we could draw different conclusions on how plant diversity and relative abundance of functional groups are differentiated between the two habitats depending on the approach used. We therefore challenge ecologists to formalize the expert knowledge applied to define sampling units through a set of well-articulated rules, rather than applying it subjectively. We see this as instrumental for progress in ecology as only rules based on expert knowledge are transparent and lead to results reproducible by other ecologists.

Fostering Wisdom-Based Action through Web 2.0 Communities of Practice: An Example of the Early Childhood Family Support Community of Practice

ERIC Educational Resources Information Center

Turnbull, Ann P.; Summers, Jean Ann; Gotto, George; Stowe, Matt; Beauchamp, Donna; Klein, Samara; Kyzar, Kathleen; Turnbull, Rud; Zuna, Nina

2009-01-01

This article discusses a new approach to knowledge translation using Web 2.0 technologies in an online Community of Practice (CoP). The purpose of the CoP is to promote wisdom-based action, a process that encourages people to engage with knowledge, match it to their own values, vision, and contexts, make a well-informed decision, and act on that…

An architecture for automated fault diagnosis. [Space Station Module/Power Management And Distribution

NASA Technical Reports Server (NTRS)

Ashworth, Barry R.

1989-01-01

A description is given of the SSM/PMAD power system automation testbed, which was developed using a systems engineering approach. The architecture includes a knowledge-based system and has been successfully used in power system management and fault diagnosis. Architectural issues which effect overall system activities and performance are examined. The knowledge-based system is discussed along with its associated automation implications, and interfaces throughout the system are presented.

Model-based software design

NASA Technical Reports Server (NTRS)

Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui; Yenne, Britt; Vansickle, Larry; Ballantyne, Michael

1992-01-01

Domain-specific knowledge is required to create specifications, generate code, and understand existing systems. Our approach to automating software design is based on instantiating an application domain model with industry-specific knowledge and then using that model to achieve the operational goals of specification elicitation and verification, reverse engineering, and code generation. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model.

Team-based learning for midwifery education.

PubMed

Moore-Davis, Tonia L; Schorn, Mavis N; Collins, Michelle R; Phillippi, Julia; Holley, Sharon

2015-01-01

Many US health care and education stakeholder groups, recognizing the need to prepare learners for collaborative practice in complex care environments, have called for innovative approaches in health care education. Team-based learning is an educational method that relies on in-depth student preparation prior to class, individual and team knowledge assessment, and use of small-group learning to apply knowledge to complex scenarios. Although team-based learning has been studied as an approach to health care education, its application to midwifery education is not well described. A master's-level, nurse-midwifery, didactic antepartum course was revised to a team-based learning format. Student grades, course evaluations, and aggregate American Midwifery Certification Board examination pass rates for 3 student cohorts participating in the team-based course were compared with 3 student cohorts receiving traditional, lecture-based instruction. Students had mixed responses to the team-based learning format. Student evaluations improved when faculty added recorded lectures as part of student preclass preparation. Statistical comparisons were limited by variations across cohorts; however, student grades and certification examination pass rates did not change substantially after the course revision. Although initial course revision was time-consuming for faculty, subsequent iterations of the course required less effort. Team-based learning provides students with more opportunity to interact during on-site classes and may spur application of knowledge into practice. However, it is difficult to assess the effect of the team-based learning approach with current measures. Further research is needed to determine the effects of team-based learning on communication and collaboration skills, as well as long-term performance in clinical practice. This article is part of a special series of articles that address midwifery innovations in clinical practice, education, interprofessional collaboration, health policy, and global health. © 2015 by the American College of Nurse-Midwives.

Nursing and the new biology: towards a realist, anti-reductionist approach to nursing knowledge.

PubMed

Nairn, Stuart

2014-10-01

As a system of knowledge, nursing has utilized a range of subjects and reconstituted them to reflect the thinking and practice of health care. Often drawn to a holistic model, nursing finds it difficult to resist the reductionist tendencies in biological and medical thinking. In this paper I will propose a relational approach to knowledge that is able to address this issue. The paper argues that biology is not characterized by one stable theory but is often a contentious topic and employs philosophically diverse models in its scientific research. Biology need not be seen as a reductionist science, but reductionism is nonetheless an important current within biological thinking. These reductionist currents can undermine nursing knowledge in four main ways. Firstly, that the conclusions drawn from reductionism go far beyond their data based on an approach that prioritizes biological explanations and eliminates others. Secondly, that the methods employed by biologists are sometimes weak, and the limitations are insufficiently acknowledged. Thirdly, that the assumptions that drive the research agenda are problematic, and finally that uncritical application of these ideas can be potentially disastrous for nursing practice. These issues are explored through an examination of the problems reductionism poses for the issue of gender, mental health, and altruism. I then propose an approach based on critical realism that adopts an anti-reductionist philosophy that utilizes the conceptual tools of emergence and a relational ontology. © 2014 John Wiley & Sons Ltd.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

Comparing the effect of group-based and compact disk-based training on midwives' knowledge and attitude toward domestic violence in women of reproductive age.

PubMed

Vakily, Masoomeh; Noroozi, Mahnaz; Yamani, Nikoo

2017-01-01

Training the health personnel about domestic violence would cause them to investigate and evaluate this issue more than before. Considering the new educational approaches for transferring knowledge, the goal of this research was to compare the effect of group-based and compact disk (CD)-based training on midwives' knowledge and attitude toward domestic violence. In this clinical experiment, seventy midwives working at health centers and hospitals of Isfahan were randomly allocated into two classes of group-based and CD-based trainings and were trained in the fields of recognition, prevention, and management of domestic violence. Data were collected by questionnaires which were completed by the midwives for evaluation of their knowledge and attitude. The mean score of midwives' knowledge and attitude toward domestic violence had a meaningful increase after the training (16.1, 46.9) compared to the score of before the training (12.1, 39.1) in both of the classes (group-based training: 17.7, 45.4) (CD-based training: 11.7, 38.6). No meaningful difference was observed between the two groups regarding midwives' attitude toward domestic violence after the intervention; however, regarding their knowledge level, the difference was statistically meaningful ( P = 0.001), and this knowledge increase was more in the CD-based training group. In spite of the effectiveness of both of the training methods in promoting midwives' knowledge and attitude about domestic violence, training with CD was more effective in increasing their knowledge; as a result, considering the benefits of CD-based training such as cost-effectiveness and possibility of use at any time, it is advised to be used in training programs for the health personnel.

Comparing the effect of group-based and compact disk-based training on midwives’ knowledge and attitude toward domestic violence in women of reproductive age

PubMed Central

Vakily, Masoomeh; Noroozi, Mahnaz; Yamani, Nikoo

2017-01-01

BACKGROUND: Training the health personnel about domestic violence would cause them to investigate and evaluate this issue more than before. Considering the new educational approaches for transferring knowledge, the goal of this research was to compare the effect of group-based and compact disk (CD)-based training on midwives’ knowledge and attitude toward domestic violence. METHODS: In this clinical experiment, seventy midwives working at health centers and hospitals of Isfahan were randomly allocated into two classes of group-based and CD-based trainings and were trained in the fields of recognition, prevention, and management of domestic violence. Data were collected by questionnaires which were completed by the midwives for evaluation of their knowledge and attitude. RESULTS: The mean score of midwives’ knowledge and attitude toward domestic violence had a meaningful increase after the training (16.1, 46.9) compared to the score of before the training (12.1, 39.1) in both of the classes (group-based training: 17.7, 45.4) (CD-based training: 11.7, 38.6). No meaningful difference was observed between the two groups regarding midwives’ attitude toward domestic violence after the intervention; however, regarding their knowledge level, the difference was statistically meaningful (P = 0.001), and this knowledge increase was more in the CD-based training group. CONCLUSIONS: In spite of the effectiveness of both of the training methods in promoting midwives’ knowledge and attitude about domestic violence, training with CD was more effective in increasing their knowledge; as a result, considering the benefits of CD-based training such as cost-effectiveness and possibility of use at any time, it is advised to be used in training programs for the health personnel. PMID:28852660

Unveiling health attitudes and creating good-for-you foods: the genomics metaphor, consumer innovative web-based technologies.

PubMed

Moskowitz, H R; German, J B; Saguy, I S

2005-01-01

This article presents an integrated analysis of three emerging knowledge bases in the nutrition and consumer products industries, and how they may effect the food industry. These knowledge bases produce new vistas for corporate product development, especially with respect to those foods that are positioned as 'good for you.' Couched within the current thinking of state-of-the-art knowledge and information, this article highlights how today's thinking about accelerated product development can be introduced into the food and health industries to complement these three research areas. The 3 knowledge bases are: the genomics revolution, which has opened new insights into understanding the interactions of personal needs of individual consumers with nutritionally relevant components of the foods; the investigation of food choice by scientific studies; the development of large scale databases (mega-studies) about the consumer mind. These knowledge bases, combined with new methods to understand the consumer through research, make possible a more focused development. The confluence of trends outlined in this article provides the corporation with the beginnings of a new path to a knowledge-based, principles-grounded product-development system. The approaches hold the potential to create foods based upon people's nutritional requirements combined with their individual preferences. Integrating these emerging knowledge areas with new consumer research techniques may well reshape how the food industry develops new products to satisfy consumer needs and wants.

Algorithm Optimally Orders Forward-Chaining Inference Rules

NASA Technical Reports Server (NTRS)

James, Mark

2008-01-01

People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.

Beginning to manage drug discovery and development knowledge.

PubMed

Sumner-Smith, M

2001-05-01

Knowledge management approaches and technologies are beginning to be implemented by the pharmaceutical industry in support of new drug discovery and development processes aimed at greater efficiencies and effectiveness. This trend coincides with moves to reduce paper, coordinate larger teams with more diverse skills that are distributed around the globe, and to comply with regulatory requirements for electronic submissions and the associated maintenance of electronic records. Concurrently, the available technologies have implemented web-based architectures with a greater range of collaborative tools and personalization through portal approaches. However, successful application of knowledge management methods depends on effective cultural change management, as well as proper architectural design to match the organizational and work processes within a company.

Exploring KM Features of High-Performance Companies

NASA Astrophysics Data System (ADS)

Wu, Wei-Wen

2007-12-01

For reacting to an increasingly rival business environment, many companies emphasize the importance of knowledge management (KM). It is a favorable way to explore and learn KM features of high-performance companies. However, finding out the critical KM features of high-performance companies is a qualitative analysis problem. To handle this kind of problem, the rough set approach is suitable because it is based on data-mining techniques to discover knowledge without rigorous statistical assumptions. Thus, this paper explored KM features of high-performance companies by using the rough set approach. The results show that high-performance companies stress the importance on both tacit and explicit knowledge, and consider that incentives and evaluations are the essentials to implementing KM.

Introduction to the special issue: parsimony and redundancy in models of language.

PubMed

Wiechmann, Daniel; Kerz, Elma; Snider, Neal; Jaeger, T Florian

2013-09-01

One of the most fundamental goals in linguistic theory is to understand the nature of linguistic knowledge, that is, the representations and mechanisms that figure in a cognitively plausible model of human language-processing. The past 50 years have witnessed the development and refinement of various theories about what kind of 'stuff' human knowledge of language consists of, and technological advances now permit the development of increasingly sophisticated computational models implementing key assumptions of different theories from both rationalist and empiricist perspectives. The present special issue does not aim to present or discuss the arguments for and against the two epistemological stances or discuss evidence that supports either of them (cf. Bod, Hay, & Jannedy, 2003; Christiansen & Chater, 2008; Hauser, Chomsky, & Fitch, 2002; Oaksford & Chater, 2007; O'Donnell, Hauser, & Fitch, 2005). Rather, the research presented in this issue, which we label usage-based here, conceives of linguistic knowledge as being induced from experience. According to the strongest of such accounts, the acquisition and processing of language can be explained with reference to general cognitive mechanisms alone (rather than with reference to innate language-specific mechanisms). Defined in these terms, usage-based approaches encompass approaches referred to as experience-based, performance-based and/or emergentist approaches (Amrnon & Snider, 2010; Bannard, Lieven, & Tomasello, 2009; Bannard & Matthews, 2008; Chater & Manning, 2006; Clark & Lappin, 2010; Gerken, Wilson, & Lewis, 2005; Gomez, 2002;

Lessons learned about art-based approaches for disseminating knowledge.

PubMed

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.

A Clinical Approach to the Diagnosis of Acid-Base Disorders

PubMed Central

Bear, Robert A.

1986-01-01

The ability to diagnose and manage acid-base disorders rapidly and effectively is essential to the care of critically ill patients. This article presents an approach to the diagnosis of pure and mixed acid-base disorders, metabolic or respiratory. The approach taken is based on using the law of mass-action equation as it applies to the bicarbonate buffer system (Henderson equation), using sub-classifications for diagnostic purposes of causes of metabolic acidosis and metabolic alkalosis, and using a knowledge of the well-defined and predictable compensatory responses that attempt to limit the change in pH in each of the primary acid-base disorders. PMID:21267134

Scaling the Fractal Plain: Towards a General View of Knowledge Management

ERIC Educational Resources Information Center

Griffiths, David; Evans, Peter

2011-01-01

Purpose: The purpose of the paper is to explore coherence across key disciplines of knowledge management (KM) for a general model as a way to address performance dissatisfaction in the field. Design/methodology/approach: Research employed an evidence-based meta-analysis (287 aspects of literature), triangulated through an exploratory survey (91…

Schools in the Making: Mapping Digital Spaces of Evidence

ERIC Educational Resources Information Center

Decuypere, Mathias; Ceulemans, Carlijne; Simons, Maarten

2014-01-01

In this article, the focus is on educational governing in the making. Drawing on conceptual underpinnings of socio-technical approaches, this implies an interest both on the way in which a sound knowledge base for policy measures is created, as on the distribution of that knowledge through publically available instruments. Governing by evidence…

Living Educational Theory Research as Transformational Continuing Professional Development

ERIC Educational Resources Information Center

Whitehead, Jack; Huxtable, Marie

2013-01-01

Continuing professional development (CPD) living educational theory offers an approach to CPD that enables educators to enhance their own professional practice and enable them to offer as gifts the knowledge, expertise and talents they develop to extend the knowledge base of the profession. In this paper we briefly introduce living theory research…

Marrying Content and Process in Computer Science Education

ERIC Educational Resources Information Center

Zendler, A.; Spannagel, C.; Klaudt, D.

2011-01-01

Constructivist approaches to computer science education emphasize that as well as knowledge, thinking skills and processes are involved in active knowledge construction. K-12 computer science curricula must not be based on fashions and trends, but on contents and processes that are observable in various domains of computer science, that can be…

Japan's Learning Communities in Hewlett-Packard Consulting and Integration: Challenging One-Size Fits All Solutions

ERIC Educational Resources Information Center

Kohlbacher, Florian; Mukai, Kazuo

2007-01-01

Purpose: This paper aims to explain and analyze community-based corporate knowledge sharing and organizational learning, the actual use of communities in Hewlett Packard (HP) Consulting and Integration (CI) and their role in leveraging and exploiting existing and creating new knowledge. Design/methodology/approach: The paper presents an…

Epistemic Metacognition in Context: Evaluating and Learning Online Information

ERIC Educational Resources Information Center

Mason, Lucia; Boldrin, Angela; Ariasi, Nicola

2010-01-01

This study examined epistemic metacognition as a reflective activity about knowledge and knowing in the context of online information searching on the Web, and whether it was related to prior knowledge on the topic, study approach, and domain-specific beliefs about science. In addition, we investigated whether Internet-based learning was…

Developing Content Knowledge in Struggling Readers: Differential Effects of Strategy Instruction for Younger and Older Elementary Students

ERIC Educational Resources Information Center

Elleman, Amy M.; Olinghouse, Natalie G.; Gilbert, Jennifer K.; Spencer, Jane Lawrence; Compton, Donald L.

2017-01-01

This study compared the effects of 2 strategy-based comprehension treatments intended to promote vocabulary and content knowledge for elementary students at risk for developing reading difficulties (N = 105) with a traditional content approach. The study examined the effectiveness of strategy versus nonstrategy instruction on reading…

Verbal Knowledge, Working Memory, and Processing Speed as Predictors of Verbal Learning in Older Adults

ERIC Educational Resources Information Center

Rast, Philippe

2011-01-01

The present study aimed at modeling individual differences in a verbal learning task by means of a latent structured growth curve approach based on an exponential function that yielded 3 parameters: initial recall, learning rate, and asymptotic performance. Three cognitive variables--speed of information processing, verbal knowledge, working…

Promoting Access: The Role of Organization and Awareness Factors. Elementary Subjects Center Series No. 1.

ERIC Educational Resources Information Center

Prawat, Richard S.

This review presents a framework that accommodates static and dynamic approaches to comprehension of students' transfer of knowledge and skill. The review focuses on three sets of variables considered fundamental to students' ability to access intellectual resources in potentially relevant situations: knowledge bases, strategies, and dispositions.…

Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Continuing education at the cutting edge: promoting transformative knowledge translation.

PubMed

McWilliam, Carol L

2007-01-01

As the evidence-based practice movement gains momentum, continuing education practitioners increasingly confront the challenge of developing and conducting opportunities for achieving research uptake. Recent thinking invites new approaches to continuing education for health professionals, with due consideration of what knowledge merits uptake by practitioners, who should play what role in the knowledge transfer process, and what educational approach should be used. This article presents an innovative theory-based strategy that encompasses this new perspective. Through a facilitated experience of perspective transformation, clinicians are engaged in an on-the-job process of developing a deeply felt interest in research findings relevant to everyday practice, as well as ownership of that knowledge and its application. The strategy becomes a sustainable, integrated part of clinical practice, fitting naturally within its dynamic, unique environment, context, and climate and overcoming the barrier of time. Clinician experience of a top-down push toward prescribed practice change is avoided. With an expanded role encompassing facilitation of active learning partnerships for practice change, the continuing educator fosters a learning organization culture across the institution. The resultant role changes and leadership and accountability issues are elaborated.

Free-Energy-Based Protein Design: Re-Engineering Cellular Retinoic Acid Binding Protein II Assisted by the Moveable-Type Approach.

PubMed

Zhong, Haizhen A; Santos, Elizabeth M; Vasileiou, Chrysoula; Zheng, Zheng; Geiger, James H; Borhan, Babak; Merz, Kenneth M

2018-03-14

How to fine-tune the binding free energy of a small-molecule to a receptor site by altering the amino acid residue composition is a key question in protein engineering. Indeed, the ultimate solution to this problem, to chemical accuracy (±1 kcal/mol), will result in profound and wide-ranging applications in protein design. Numerous tools have been developed to address this question using knowledge-based models to more computationally intensive molecular dynamics simulations-based free energy calculations, but while some success has been achieved there remains room for improvement in terms of overall accuracy and in the speed of the methodology. Here we report a fast, knowledge-based movable-type (MT)-based approach to estimate the absolute and relative free energy of binding as influenced by mutations in a small-molecule binding site in a protein. We retrospectively validate our approach using mutagenesis data for retinoic acid binding to the Cellular Retinoic Acid Binding Protein II (CRABPII) system and then make prospective predictions that are borne out experimentally. The overall performance of our approach is supported by its success in identifying mutants that show high or even sub-nano-molar binding affinities of retinoic acid to the CRABPII system.

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

PubMed

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.

A review of covariate selection for non-experimental comparative effectiveness research.

PubMed

Sauer, Brian C; Brookhart, M Alan; Roy, Jason; VanderWeele, Tyler

2013-11-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for a common cause pathway between treatment and outcome can remove confounding, whereas adjustment for other structural types may increase bias. For this reason, variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely known. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher's knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. Copyright © 2013 John Wiley & Sons, Ltd.

A Review of Covariate Selection for Nonexperimental Comparative Effectiveness Research

PubMed Central

Sauer, Brian C.; Brookhart, Alan; Roy, Jason; Vanderweele, Tyler

2014-01-01

This paper addresses strategies for selecting variables for adjustment in non-experimental comparative effectiveness research (CER), and uses causal graphs to illustrate the causal network that relates treatment to outcome. Variables in the causal network take on multiple structural forms. Adjustment for on a common cause pathway between treatment and outcome can remove confounding, while adjustment for other structural types may increase bias. For this reason variable selection would ideally be based on an understanding of the causal network; however, the true causal network is rarely know. Therefore, we describe more practical variable selection approaches based on background knowledge when the causal structure is only partially known. These approaches include adjustment for all observed pretreatment variables thought to have some connection to the outcome, all known risk factors for the outcome, and all direct causes of the treatment or the outcome. Empirical approaches, such as forward and backward selection and automatic high-dimensional proxy adjustment, are also discussed. As there is a continuum between knowing and not knowing the causal, structural relations of variables, we recommend addressing variable selection in a practical way that involves a combination of background knowledge and empirical selection and that uses the high-dimensional approaches. This empirical approach can be used to select from a set of a priori variables based on the researcher’s knowledge to be included in the final analysis or to identify additional variables for consideration. This more limited use of empirically-derived variables may reduce confounding while simultaneously reducing the risk of including variables that may increase bias. PMID:24006330

Formalization of treatment guidelines using Fuzzy Cognitive Maps and semantic web tools.

PubMed

Papageorgiou, Elpiniki I; Roo, Jos De; Huszka, Csaba; Colaert, Dirk

2012-02-01

Therapy decision making and support in medicine deals with uncertainty and needs to take into account the patient's clinical parameters, the context of illness and the medical knowledge of the physician and guidelines to recommend a treatment therapy. This research study is focused on the formalization of medical knowledge using a cognitive process, called Fuzzy Cognitive Maps (FCMs) and semantic web approach. The FCM technique is capable of dealing with situations including uncertain descriptions using similar procedure such as human reasoning does. Thus, it was selected for the case of modeling and knowledge integration of clinical practice guidelines. The semantic web tools were established to implement the FCM approach. The knowledge base was constructed from the clinical guidelines as the form of if-then fuzzy rules. These fuzzy rules were transferred to FCM modeling technique and, through the semantic web tools, the whole formalization was accomplished. The problem of urinary tract infection (UTI) in adult community was examined for the proposed approach. Forty-seven clinical concepts and eight therapy concepts were identified for the antibiotic treatment therapy problem of UTIs. A preliminary pilot-evaluation study with 55 patient cases showed interesting findings; 91% of the antibiotic treatments proposed by the implemented approach were in fully agreement with the guidelines and physicians' opinions. The results have shown that the suggested approach formalizes medical knowledge efficiently and gives a front-end decision on antibiotics' suggestion for cystitis. Concluding, modeling medical knowledge/therapeutic guidelines using cognitive methods and web semantic tools is both reliable and useful. Copyright © 2011 Elsevier Inc. All rights reserved.

Is it time to drop the ‘knowledge translation’ metaphor? A critical literature review

PubMed Central

Greenhalgh, Trisha; Wieringa, Sietse

2011-01-01

The literature on ‘knowledge translation’ presents challenges for the reviewer because different terms have been used to describe the generation, sharing and application of knowledge and different research approaches embrace different philosophical positions on what knowledge is. We present a narrative review of this literature which deliberately sought to highlight rather than resolve tensions between these different framings. Our findings suggest that while ‘translation’ is a widely used metaphor in medicine, it constrains how we conceptualise and study the link between knowledge and practice. The ‘translation’ metaphor has, arguably, led to particular difficulties in the fields of ‘evidence-based management’ and ‘evidence-based policymaking’ – where it seems that knowledge obstinately refuses to be driven unproblematically into practice. Many non-medical disciplines such as philosophy, sociology and organization science conceptualise knowledge very differently, as being (for example) ‘created’, ‘constructed’, ‘embodied’, ‘performed’ and ‘collectively negotiated’ – and also as being value-laden and tending to serve the vested interests of dominant élites. We propose that applying this wider range of metaphors and models would allow us to research the link between knowledge and practice in more creative and critical ways. We conclude that research should move beyond a narrow focus on the ‘know–do gap’ to cover a richer agenda, including: (a) the situation-specific practical wisdom (phronesis) that underpins clinical judgement; (b) the tacit knowledge that is built and shared among practitioners (‘mindlines’); (c) the complex links between power and knowledge; and (d) approaches to facilitating macro-level knowledge partnerships between researchers, practitioners, policymakers and commercial interests. PMID:22179293

Empowering Teaching for Participatory Citizenship: Evaluating the Impact of Alternative Civic Education Pedagogies on Civic Attitudes, Knowledge and Skills of Eight-Grade Students in Mexico

ERIC Educational Resources Information Center

Reimers, Fernando M.; Ortega, Maria Elena; Cardenas, Mariali; Estrada, Armando; Garza, Emanuel

2014-01-01

In spite of the fact that public schools were established to prepare students for citizenship, the alignment of teaching practice with this goal is poor. In part, this is because the knowledge base about the efficacy of curricular and pedagogical approaches in supporting specific civic outcomes is limited, as is our knowledge about the extent to…

Scotland's Knowledge Network: translating knowledge into action to improve quality of care.

PubMed

Wales, A; Graham, S; Rooney, K; Crawford, A

2012-11-01

The Knowledge Network (www.knowledge.scot.nhs.uk) is Scotland's online knowledge service for health and social care. It is designed to support practitioners to apply knowledge in frontline delivery of care, helping to translate knowledge into better health-care outcomes through safe, effective, person-centred care. The Knowledge Network helps to combine the worlds of evidence-based practice and quality improvement by providing access to knowledge about the effectiveness of clinical interventions ('know-what') and knowledge about how to implement this knowledge to support individual patients in working health-care environments ('know-how'). An 'evidence and guidance' search enables clinicians to quickly access quality-assured evidence and best practice, while point of care and mobile solutions provide knowledge in actionable formats to embed in clinical workflow. This research-based knowledge is complemented by social networking services and improvement tools which support the capture and exchange of knowledge from experience, facilitating practice change and systems improvement. In these cases, the Knowledge Network supports key components of the knowledge-to-action cycle--acquiring, creating, sharing and disseminating knowledge to improve performance and innovate. It provides a vehicle for implementing the recommendations of the national Knowledge into Action review, which outlines a new national approach to embedding knowledge in frontline practice and systems improvement.

The Effects of Prior-knowledge and Online Learning Approaches on Students' Inquiry and Argumentation Abilities

NASA Astrophysics Data System (ADS)

Yang, Wen-Tsung; Lin, Yu-Ren; She, Hsiao-Ching; Huang, Kai-Yi

2015-07-01

This study investigated the effects of students' prior science knowledge and online learning approaches (social and individual) on their learning with regard to three topics: science concepts, inquiry, and argumentation. Two science teachers and 118 students from 4 eighth-grade science classes were invited to participate in this research. Students in each class were divided into three groups according to their level of prior science knowledge; they then took either our social- or individual-based online science learning program. The results show that students in the social online argumentation group performed better in argumentation and online argumentation learning. Qualitative analysis indicated that the students' social interactions benefited the co-construction of sound arguments and the accurate understanding of science concepts. In constructing arguments, students in the individual online argumentation group were limited to knowledge recall and self-reflection. High prior-knowledge students significantly outperformed low prior-knowledge students in all three aspects of science learning. However, the difference in inquiry and argumentation performance between low and high prior-knowledge students decreased with the progression of online learning topics.

Emergency management in health: key issues and challenges in the UK.

PubMed

Lee, Andrew C K; Phillips, Wendy; Challen, Kirsty; Goodacre, Steve

2012-10-19

Emergency planning in the UK has grown considerably in recent years, galvanised by the threat of terrorism. However, deficiencies in NHS emergency planning were identified and the evidence-base that underpins it is questionable. Inconsistencies in terminologies and concepts also exist. Different models of emergency management exist internationally but the optimal system is unknown. This study examines the evidence-base and evidence requirements for emergency planning in the UK health context. The study involved semi-structured interviews with key stakeholders and opinion leaders. Purposive sampling was used to obtain a breadth of views from various agencies involved in emergency planning and response. Interviews were then analysed using a grounded approach using standard framework analysis techniques. We conducted 17 key informant interviews. Interviewees identified greater gaps in operational than technical aspects of emergency planning. Social and behavioural knowledge gaps were highlighted with regards to how individuals and organisations deal with risk and behave in emergencies. Evidence-based approaches to public engagement and for developing community resilience to disasters are lacking. Other gaps included how knowledge was developed and used. Conflicting views with regards to the optimal configuration and operation of the emergency management system were voiced. Four thematic categories for future research emerged:(i) Knowledge-base for emergency management: Further exploration is needed of how knowledge is acquired, valued, disseminated, adopted and retained.(ii) Social and behavioural issues: Greater understanding of how individuals approach risk and behave in emergencies is required.(iii) Organisational issues in emergencies: Several conflicting organisational issues were identified; value of planning versus plans, flexible versus standardized procedures, top-down versus bottom-up engagement, generic versus specific planning, and reactive versus proactive approaches to emergencies.(iv) Emergency management system: More study is required of system-wide issues relating to system configuration and operation, public engagement, and how emergency planning is assessed.

Knowledge Management in healthcare libraries: the current picture.

PubMed

Hopkins, Emily

2017-06-01

Knowledge management has seen something of a resurgence in attention amongst health librarians recently. Of course it has never ceased to exist, but now many library staff are becoming more involved in organisational knowledge management, and positioning themselves as key players in the sphere. No single model of knowledge management is proliferating, but approaches that best fit the organisation's size, structure and culture, and a blending of evidence based practice and knowledge sharing. Whatever it is called and whatever models are used, it's clear that for librarians and information professionals, the importance of putting knowledge and evidence into practice, sharing knowledge well and capturing it effectively, are still what we will continue to do. © 2017 Health Libraries Group.

Space power system automation approaches at the George C. Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Weeks, D. J.

1987-01-01

This paper discusses the automation approaches employed in various electrical power system breadboards at the Marshall Space Flight Center. Of particular interest is the application of knowledge-based systems to fault management and dynamic payload scheduling. A description of each major breadboard and the automation approach taken for each is given.

Engaging Students in a Simulated Collaborative Action Research Project: An Evaluation of a Participatory Approach to Learning

ERIC Educational Resources Information Center

Congdon, Graham John; Congdon, Shirley

2011-01-01

This article reports an action research project designed to develop and implement a new participatory learning and teaching approach to enable postgraduate healthcare students to develop skills and knowledge in preparation for undertaking an action research study within their practice setting. The learning and teaching approach was based upon the…

From bioethics to a sociology of bio-knowledge.

PubMed

Petersen, Alan

2013-12-01

Growing recognition of bioethics' shortcomings, associated in large part with its heavy reliance on abstract principles, or so-called principlism, has led many scholars to propose that the field should be reformed or reconceptualised. Principlism is seen to de-contextualise the process of ethical decision-making, thus restricting bioethics' contributions to debate and policy on new and emergent biotechnologies. This article examines some major critiques of bioethics and argues for an alternative normative approach; namely, a sociology of bio-knowledge focussing on human rights. The article discusses the need for such an approach, including the challenges posed by the recent rise of 'the bio-economy'. It explores some potential alternative bases for a normative sociology of bio-knowledge, before presenting the elements of the proposed human rights-focused approach. This approach, it is argued, will benefit from the insights and concepts offered by various fields of critical scholarship, particularly the emergent sociology of human rights, science and technology studies, Foucaultian scholarship, and feminist bioethics. Copyright © 2013 Elsevier Ltd. All rights reserved.

More than Anecdotes: Fishers' Ecological Knowledge Can Fill Gaps for Ecosystem Modeling.

PubMed

Bevilacqua, Ana Helena V; Carvalho, Adriana R; Angelini, Ronaldo; Christensen, Villy

2016-01-01

Ecosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers' knowledge could fill this gap, improving participation in and the management of fisheries. The same fishing area was modeled using two approaches: based on fishers' knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers' knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. The ecosystem attributes produced from the fishers' knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. This study provides evidence that fishers' knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries.

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

NASA Technical Reports Server (NTRS)

Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

1989-01-01

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

A bioinformatics approach for precision medicine off-label drug drug selection among triple negative breast cancer patients

PubMed Central

Cheng, Lijun; Schneider, Bryan P

2016-01-01

Background Cancer has been extensively characterized on the basis of genomics. The integration of genetic information about cancers with data on how the cancers respond to target based therapy to help to optimum cancer treatment. Objective The increasing usage of sequencing technology in cancer research and clinical practice has enormously advanced our understanding of cancer mechanisms. The cancer precision medicine is becoming a reality. Although off-label drug usage is a common practice in treating cancer, it suffers from the lack of knowledge base for proper cancer drug selections. This eminent need has become even more apparent considering the upcoming genomics data. Methods In this paper, a personalized medicine knowledge base is constructed by integrating various cancer drugs, drug-target database, and knowledge sources for the proper cancer drugs and their target selections. Based on the knowledge base, a bioinformatics approach for cancer drugs selection in precision medicine is developed. It integrates personal molecular profile data, including copy number variation, mutation, and gene expression. Results By analyzing the 85 triple negative breast cancer (TNBC) patient data in the Cancer Genome Altar, we have shown that 71.7% of the TNBC patients have FDA approved drug targets, and 51.7% of the patients have more than one drug target. Sixty-five drug targets are identified as TNBC treatment targets and 85 candidate drugs are recommended. Many existing TNBC candidate targets, such as Poly (ADP-Ribose) Polymerase 1 (PARP1), Cell division protein kinase 6 (CDK6), epidermal growth factor receptor, etc., were identified. On the other hand, we found some additional targets that are not yet fully investigated in the TNBC, such as Gamma-Glutamyl Hydrolase (GGH), Thymidylate Synthetase (TYMS), Protein Tyrosine Kinase 6 (PTK6), Topoisomerase (DNA) I, Mitochondrial (TOP1MT), Smoothened, Frizzled Class Receptor (SMO), etc. Our additional analysis of target and drug selection strategy is also fully supported by the drug screening data on TNBC cell lines in the Cancer Cell Line Encyclopedia. Conclusions The proposed bioinformatics approach lays a foundation for cancer precision medicine. It supplies much needed knowledge base for the off-label cancer drug usage in clinics. PMID:27107440

Perspectives to performance of environment and health assessments and models--from outputs to outcomes?

PubMed

Pohjola, Mikko V; Pohjola, Pasi; Tainio, Marko; Tuomisto, Jouni T

2013-06-26

The calls for knowledge-based policy and policy-relevant research invoke a need to evaluate and manage environment and health assessments and models according to their societal outcomes. This review explores how well the existing approaches to assessment and model performance serve this need. The perspectives to assessment and model performance in the scientific literature can be called: (1) quality assurance/control, (2) uncertainty analysis, (3) technical assessment of models, (4) effectiveness and (5) other perspectives, according to what is primarily seen to constitute the goodness of assessments and models. The categorization is not strict and methods, tools and frameworks in different perspectives may overlap. However, altogether it seems that most approaches to assessment and model performance are relatively narrow in their scope. The focus in most approaches is on the outputs and making of assessments and models. Practical application of the outputs and the consequential outcomes are often left unaddressed. It appears that more comprehensive approaches that combine the essential characteristics of different perspectives are needed. This necessitates a better account of the mechanisms of collective knowledge creation and the relations between knowledge and practical action. Some new approaches to assessment, modeling and their evaluation and management span the chain from knowledge creation to societal outcomes, but the complexity of evaluating societal outcomes remains a challenge.

An Integrative Bioinformatics Approach for Knowledge Discovery

NASA Astrophysics Data System (ADS)

Peña-Castillo, Lourdes; Phan, Sieu; Famili, Fazel

The vast amount of data being generated by large scale omics projects and the computational approaches developed to deal with this data have the potential to accelerate the advancement of our understanding of the molecular basis of genetic diseases. This better understanding may have profound clinical implications and transform the medical practice; for instance, therapeutic management could be prescribed based on the patient’s genetic profile instead of being based on aggregate data. Current efforts have established the feasibility and utility of integrating and analysing heterogeneous genomic data to identify molecular associations to pathogenesis. However, since these initiatives are data-centric, they either restrict the research community to specific data sets or to a certain application domain, or force researchers to develop their own analysis tools. To fully exploit the potential of omics technologies, robust computational approaches need to be developed and made available to the community. This research addresses such challenge and proposes an integrative approach to facilitate knowledge discovery from diverse datasets and contribute to the advancement of genomic medicine.

Developing "My Asthma Diary": a process exemplar of a patient-driven arts-based knowledge translation tool.

PubMed

Archibald, Mandy M; Hartling, Lisa; Ali, Samina; Caine, Vera; Scott, Shannon D

2018-06-05

Although it is well established that family-centered education is critical to managing childhood asthma, the information needs of parents of children with asthma are not being met through current educational approaches. Patient-driven educational materials that leverage the power of the storytelling and the arts show promise in communicating health information and assisting in illness self-management. However, such arts-based knowledge translation approaches are in their infancy, and little is known about how to develop such tools for parents. This paper reports on the development of "My Asthma Diary" - an innovative knowledge translation tool based on rigorous research evidence and tailored to parents' asthma-related information needs. We used a multi-stage process to develop four eBook prototypes of "My Asthma Diary." We conducted formative research on parents' information needs and identified high quality research evidence on childhood asthma, and used these data to inform the development of the asthma eBooks. We established interdisciplinary consulting teams with health researchers, practitioners, and artists to help iteratively create the knowledge translation tools. We describe the iterative, transdisciplinary process of developing asthma eBooks which incorporates: (I) parents' preferences and information needs on childhood asthma, (II) quality evidence on childhood asthma and its management, and (III) the engaging and informative powers of storytelling and visual art as methods to communicate complex health information to parents. We identified four dominant methodological and procedural challenges encountered during this process: (I) working within an inter-disciplinary team, (II) quantity and ordering of information, (III) creating a composite narrative, and (IV) balancing actual and ideal management scenarios. We describe a replicable and rigorous multi-staged approach to developing a patient-driven, creative knowledge translation tool, which can be adapted for use with different populations and contexts. We identified specific procedural and methodological challenges that others conducting comparable work should consider, particularly as creative, patient-driven knowledge translation strategies continue to emerge across health disciplines.

A knowledge-based system for prototypical reasoning

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Interdisciplinary collaboration in gerontology and geriatrics in Latin America: conceptual approaches and health care teams.

PubMed

Gomez, Fernando; Curcio, Carmen Lucia

2013-01-01

The underlying rationale to support interdisciplinary collaboration in geriatrics and gerontology is based on the complexity of elderly care. The most important characteristic about interdisciplinary health care teams for older people in Latin America is their subjective-basis framework. In other regions, teams are organized according to a theoretical knowledge basis with well-justified priorities, functions, and long-term goals, in Latin America teams are arranged according to subjective interests on solving their problems. Three distinct approaches of interdisciplinary collaboration in gerontology are proposed. The first approach is grounded in the scientific rationalism of European origin. Denominated "logical-rational approach," its core is to identify the significance of knowledge. The second approach is grounded in pragmatism and is more associated with a North American tradition. The core of this approach consists in enhancing the skills and competences of each participant; denominated "logical-instrumental approach." The third approach denominated "logical-subjective approach" has a Latin America origin. Its core consists in taking into account the internal and emotional dimensions of the team. These conceptual frameworks based in geographical contexts will permit establishing the differences and shared characteristics of interdisciplinary collaboration in geriatrics and gerontology to look for operational answers to solve the "complex problems" of older adults.

Decision making under uncertainty: a quasimetric approach.

PubMed

N'Guyen, Steve; Moulin-Frier, Clément; Droulez, Jacques

2013-01-01

We propose a new approach for solving a class of discrete decision making problems under uncertainty with positive cost. This issue concerns multiple and diverse fields such as engineering, economics, artificial intelligence, cognitive science and many others. Basically, an agent has to choose a single or series of actions from a set of options, without knowing for sure their consequences. Schematically, two main approaches have been followed: either the agent learns which option is the correct one to choose in a given situation by trial and error, or the agent already has some knowledge on the possible consequences of his decisions; this knowledge being generally expressed as a conditional probability distribution. In the latter case, several optimal or suboptimal methods have been proposed to exploit this uncertain knowledge in various contexts. In this work, we propose following a different approach, based on the geometric intuition of distance. More precisely, we define a goal independent quasimetric structure on the state space, taking into account both cost function and transition probability. We then compare precision and computation time with classical approaches.

An adaptive signal-processing approach to online adaptive tutoring.

PubMed

Bergeron, Bryan; Cline, Andrew

2011-01-01

Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

Effectiveness of an Evidence-Based Quality Improvement Approach to Cultural Competence Training: The Veterans Affairs' "Caring for Women Veterans" Program.

PubMed

Fox, Annie B; Hamilton, Alison B; Frayne, Susan M; Wiltsey-Stirman, Shannon; Bean-Mayberry, Bevanne; Carney, Diane; Di Leone, Brooke A L; Gierisch, Jennifer M; Goldstein, Karen M; Romodan, Yasmin; Sadler, Anne G; Yano, Elizabeth M; Yee, Ellen F; Vogt, Dawne

2016-01-01

Although providing culturally sensitive health care is vitally important, there is little consensus regarding the most effective strategy for implementing cultural competence trainings in the health care setting. Evidence-based quality improvement (EBQI), which involves adapting evidence-based practices to meet local needs, may improve uptake and effectiveness of a variety of health care innovations. Yet, to our knowledge, EBQI has not yet been applied to cultural competence training. To evaluate whether EBQI could enhance the impact of an evidence-based training intended to improve veterans affairs health care staff gender sensitivity and knowledge (Caring for Women Veterans; CWV), we compared the reach and effectiveness of EBQI delivery versus standard web-based implementation strategies of CWV and assessed barriers and facilitators to EBQI implementation. Workgroups at four diverse veterans affairs health care sites were randomized to either an EBQI or standard web-based implementation condition (SI). All EBQI sites selected a group-based implementation strategy. Employees (N = 84) completed pretraining and posttraining assessments of gender sensitivity and knowledge, and focus groups/interviews were conducted with leadership and staff before and after implementation. Reach of CWV was greater in the EBQI condition versus the SI condition. Whereas both gender sensitivity and knowledge improved in the EBQI condition, only gender sensitivity improved in the SI condition. Qualitative analyses revealed that the EBQI approach was well received, although a number of barriers were identified. Findings suggest that EBQI can enhance the uptake and effectiveness of employee trainings. However, the decision to pursue EBQI must be informed by a consideration of available resources.

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

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

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

PubMed

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.

A vector space model approach to identify genetically related diseases.

PubMed

Sarkar, Indra Neil

2012-01-01

The relationship between diseases and their causative genes can be complex, especially in the case of polygenic diseases. Further exacerbating the challenges in their study is that many genes may be causally related to multiple diseases. This study explored the relationship between diseases through the adaptation of an approach pioneered in the context of information retrieval: vector space models. A vector space model approach was developed that bridges gene disease knowledge inferred across three knowledge bases: Online Mendelian Inheritance in Man, GenBank, and Medline. The approach was then used to identify potentially related diseases for two target diseases: Alzheimer disease and Prader-Willi Syndrome. In the case of both Alzheimer Disease and Prader-Willi Syndrome, a set of plausible diseases were identified that may warrant further exploration. This study furthers seminal work by Swanson, et al. that demonstrated the potential for mining literature for putative correlations. Using a vector space modeling approach, information from both biomedical literature and genomic resources (like GenBank) can be combined towards identification of putative correlations of interest. To this end, the relevance of the predicted diseases of interest in this study using the vector space modeling approach were validated based on supporting literature. The results of this study suggest that a vector space model approach may be a useful means to identify potential relationships between complex diseases, and thereby enable the coordination of gene-based findings across multiple complex diseases.

Approach Towards an Evidence-Oriented Knowledge and Data Acquisition for the Optimization of Interdisciplinary Care in Dentistry and General Medicine.

PubMed

Seitz, Max W; Haux, Christian; Knaup, Petra; Schubert, Ingrid; Listl, Stefan

2018-01-01

Associations between dental and chronic-systemic diseases were observed frequently in medical research, however the findings of this research have so far found little relevance in everyday clinical treatment. Major problems are the assessment of evidence for correlations between such diseases and how to integrate current medical knowledge into the intersectoral care of dentists and general practitioners. On the example of dental and chronic-systemic diseases, the Dent@Prevent project develops an interdisciplinary decision support system (DSS), which provides the specialists with information relevant for the treatment of such cases. To provide the physicians with relevant medical knowledge, a mixed-methods approach is developed to acquire the knowledge in an evidence-oriented way. This procedure includes a literature review, routine data analyses, focus groups of dentists and general practitioners as well as the identification and integration of applicable guidelines and Patient Reported Measures (PRMs) into the treatment process. The developed mixed methods approach for an evidence-oriented knowledge acquisition indicates to be applicable and supportable for interdisciplinary projects. It can raise the systematic quality of the knowledge-acquisition process and can be applicable for an evidence-based system development. Further research is necessary to assess the impact on patient care and to evaluate possible applicability in other interdisciplinary areas.

Oral Health Knowledge, Attitude, and Approaches of Pre-Primary and Primary School Teachers in Mumbai, India.

PubMed

Mota, Ankita; Oswal, Kunal C; Sajnani, Dipti A; Sajnani, Anand K

2016-01-01

Background. School teachers have an internationally recognized potential role in school-based dental education and considerable importance has therefore been attributed to their dental knowledge. The objectives of this study were to determine the oral health related knowledge, attitudes, and approaches of pre-primary and primary school teachers in the city of Mumbai. Methods. The descriptive cross-sectional study was conducted in the suburban regions of Mumbai using a self-administered questionnaire and involved 511 teachers. Results. Teachers demonstrated inappropriate or incomplete knowledge regarding children's oral health. Only 53.2% knew that an individual has two sets of dentition. Moreover, only 45.4% of the teachers knew that a primary dentition consists of 20 teeth. Only 56.9% of the teachers asked their children to clean their mouth after snacking during school hours. 45.0% of the teachers were unaware of fluoridated tooth pastes whilst 78.9% of them were unaware of school water fluoridation programmes. Also, 54.8% of the teachers never discussed the oral health of children with their parents during parents meet. Conclusions. The studied school teachers demonstrated incomplete oral health knowledge, inappropriate oral practices, and unfavourable approaches to children's oral health. There is a definite and immediate need for organized training of school teachers on basic oral health knowledge.

A framework to explore the knowledge structure of multidisciplinary research fields.

PubMed

Uddin, Shahadat; Khan, Arif; Baur, Louise A

2015-01-01

Understanding emerging areas of a multidisciplinary research field is crucial for researchers, policymakers and other stakeholders. For them a knowledge structure based on longitudinal bibliographic data can be an effective instrument. But with the vast amount of available online information it is often hard to understand the knowledge structure for data. In this paper, we present a novel approach for retrieving online bibliographic data and propose a framework for exploring knowledge structure. We also present several longitudinal analyses to interpret and visualize the last 20 years of published obesity research data.

Combinatorial and high-throughput screening of materials libraries: review of state of the art.

PubMed

Potyrailo, Radislav; Rajan, Krishna; Stoewe, Klaus; Takeuchi, Ichiro; Chisholm, Bret; Lam, Hubert

2011-11-14

Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimization of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characterization approaches, advances in data analysis/mining, and new materials developments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and functional materials, polymer-based industrial coatings, sensing materials, and biomaterials.

Development of Scientific Approach Based on Discovery Learning Module

NASA Astrophysics Data System (ADS)

Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

2018-04-01

Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on discovery learning and scientific approach in electrolyte and non-electrolyte solution and Acid Based for the 10th and 11th grade of senior high school students were valid, practice, and effective.

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

PubMed

Singh, Maneesha; Singh, Sameer; Partridge, Derek

2004-12-01

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

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

Does integrating research into the prosthetics and orthotics undergraduate curriculum enhance students' clinical practice? An interview study on students' perception.

PubMed

Al Qaroot, Bashar S; Sobuh, Mohammad

2016-06-01

Problem-based learning (where rather than feeding students the knowledge, they look for it themselves) has long been thought of as an ideal approach in teaching because it would encourage students to acquire knowledge from an undetermined medium of wrong and right answers. However, the effect of such approach in the learning experience of prosthetics and orthotics students has never been investigated. This study explores the implications of integrating problem-based learning into teaching on the students' learning experience via implementing a research-informed clinical practice module into the curriculum of last year prosthetics and orthotics undergraduate students at the University of Jordan (Amman, Jordan). Qualitative research pilot study. Grounded theory approach was used based on the data collected from interviewing a focus group of four students. Students have identified a number of arguments from their experience in the research-informed clinical practice where, generally speaking, students described research-informed clinical practice as a very good method of education. Integrating problem-based learning into teaching has many positive implications. In particular, students pointed out that their learning experience and clinical practice have much improved after the research-informed clinical practice. Findings from this investigation demonstrate that embedding problem-based learning into prosthetics and orthotics students' curriculum has the potential to enhance students' learning experience, particularly students' evidence-based practice. This may lead to graduates who are more knowledgeable and thus who can offer the optimal patient care (i.e. clinical practice). © The International Society for Prosthetics and Orthotics 2014.

Using distant supervised learning to identify protein subcellular localizations from full-text scientific articles.

PubMed

Zheng, Wu; Blake, Catherine

2015-10-01

Databases of curated biomedical knowledge, such as the protein-locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to curate knowledge bases with automated approaches that leverage the increased availability of full-text scientific articles. This paper describes experiments that use distant supervised learning to identify protein subcellular localizations, which are important to understand protein function and to identify candidate drug targets. Experiments consider Swiss-Prot, the manually annotated subset of the UniProtKB protein knowledge base, and 43,000 full-text articles from the Journal of Biological Chemistry that contain just under 11.5 million sentences. The system achieves 0.81 precision and 0.49 recall at sentence level and an accuracy of 57% on held-out instances in a test set. Moreover, the approach identifies 8210 instances that are not in the UniProtKB knowledge base. Manual inspection of the 50 most likely relations showed that 41 (82%) were valid. These results have immediate benefit to researchers interested in protein function, and suggest that distant supervision should be explored to complement other manual data curation efforts. Copyright © 2015 Elsevier Inc. All rights reserved.

A theoretical framework for measuring knowledge in screening decision aid trials.

PubMed

Smith, Sian K; Barratt, Alexandra; Trevena, Lyndal; Simpson, Judy M; Jansen, Jesse; McCaffery, Kirsten J

2012-11-01

To describe a theoretical framework for assessing knowledge about the possible outcomes of participating in bowel cancer screening for the faecal occult blood test. The content of the knowledge measure was based on the UK General Medical Council's screening guidelines and a theory-based approach to assessing gist knowledge (Fuzzy Trace Theory). It comprised conceptual and numeric questions to assess knowledge of the underlying construct (e.g. false positive concept) and the approximate numbers affected (e.g. likelihood of a false positive). The measure was used in a randomised controlled trial involving 530 adults with low education, to compare the impact of a bowel screening decision aid with a screening information booklet developed for the Australian Government National Bowel Cancer Screening Program. The numeric knowledge scale was particularly responsive to the effects of the decision aid; at follow-up decision aid participants' numeric knowledge was significantly greater than the controls (P<0.001). This contrasts with the conceptual knowledge scale which improved significantly in both groups from baseline to follow-up (P<0.001). Our theory-based knowledge measure was responsive to change in conceptual knowledge and to the effect on numeric knowledge of a decision aid. This theoretical framework has the potential to guide the development of knowledge measures in other screening settings. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Irrelevance Reasoning in Knowledge Based Systems

NASA Technical Reports Server (NTRS)

Levy, A. Y.

1993-01-01

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

Adopting Problem-Based Learning Model for AN Electrical Engineering Curriculum

NASA Astrophysics Data System (ADS)

Khan, Mohamed Khan Aftab Ahmed; Sinnadurai, Rajendran; Amudha, M.; Elamvazuthi, I.; Vasant, P.

2010-06-01

The shortage of highly qualified academicians in a knowledge-based economy and potential benefits of Problem-Based Learning (PBL) approach has necessitated the adoption of PBL in many areas of education. This paper discusses a PBL experience for an electrical engineering undergraduate course. Some preliminary experiences of implementing them are described and discussed. It was found that PBL approach seem to be an efficient strategy not only for undergraduate engineering education but also for instilling lifelong learning.

Approaching Etuaptmumk--introducing a consensus-based mixed method for health services research.

PubMed

Chatwood, Susan; Paulette, Francois; Baker, Ross; Eriksen, Astrid; Hansen, Ketil Lenert; Eriksen, Heidi; Hiratsuka, Vanessa; Lavoie, Josée; Lou, Wendy; Mauro, Ian; Orbinski, James; Pabrum, Nathalie; Retallack, Hanna; Brown, Adalsteinn

2015-01-01

With the recognized need for health systems' improvements in the circumpolar and indigenous context, there has been a call to expand the research agenda across all sectors influencing wellness and to recognize academic and indigenous knowledge through the research process. Despite being recognized as a distinct body of knowledge in international forums and across indigenous groups, examples of methods and theories based on indigenous knowledge are not well documented in academic texts or peer-reviewed literature on health systems. This paper describes the use of a consensus-based, mixed method with indigenous knowledge by an experienced group of researchers and indigenous knowledge holders who collaborated on a study that explored indigenous values underlying health systems stewardship. The method is built on the principles of Etuaptmumk or two-eyed seeing, which aim to respond to and resolve the inherent conflicts between indigenous ways of knowing and the scientific inquiry that informs the evidence base in health care. Mixed methods' frameworks appear to provide a framing suitable for research questions that require data from indigenous knowledge sources and western knowledge. The nominal consensus method, as a western paradigm, was found to be responsive to embedding of indigenous knowledge and allowed space to express multiple perspectives and reach consensus on the question at hand. Further utilization and critical evaluation of this mixed methodology with indigenous knowledge are required.

Approaching Etuaptmumk – introducing a consensus-based mixed method for health services research

PubMed Central

Chatwood, Susan; Paulette, Francois; Baker, Ross; Eriksen, Astrid; Hansen, Ketil Lenert; Eriksen, Heidi; Hiratsuka, Vanessa; Lavoie, Josée; Lou, Wendy; Mauro, Ian; Orbinski, James; Pabrum, Nathalie; Retallack, Hanna; Brown, Adalsteinn

2015-01-01

With the recognized need for health systems’ improvements in the circumpolar and indigenous context, there has been a call to expand the research agenda across all sectors influencing wellness and to recognize academic and indigenous knowledge through the research process. Despite being recognized as a distinct body of knowledge in international forums and across indigenous groups, examples of methods and theories based on indigenous knowledge are not well documented in academic texts or peer-reviewed literature on health systems. This paper describes the use of a consensus-based, mixed method with indigenous knowledge by an experienced group of researchers and indigenous knowledge holders who collaborated on a study that explored indigenous values underlying health systems stewardship. The method is built on the principles of Etuaptmumk or two-eyed seeing, which aim to respond to and resolve the inherent conflicts between indigenous ways of knowing and the scientific inquiry that informs the evidence base in health care. Mixed methods’ frameworks appear to provide a framing suitable for research questions that require data from indigenous knowledge sources and western knowledge. The nominal consensus method, as a western paradigm, was found to be responsive to embedding of indigenous knowledge and allowed space to express multiple perspectives and reach consensus on the question at hand. Further utilization and critical evaluation of this mixed methodology with indigenous knowledge are required. PMID:26004427

Knowledge discovery about quality of life changes of spinal cord injury patients: clustering based on rules by states.

PubMed

Gibert, Karina; García-Rudolph, Alejandro; Curcoll, Lluïsa; Soler, Dolors; Pla, Laura; Tormos, José María

2009-01-01

In this paper, an integral Knowledge Discovery Methodology, named Clustering based on rules by States, which incorporates artificial intelligence (AI) and statistical methods as well as interpretation-oriented tools, is used for extracting knowledge patterns about the evolution over time of the Quality of Life (QoL) of patients with Spinal Cord Injury. The methodology incorporates the interaction with experts as a crucial element with the clustering methodology to guarantee usefulness of the results. Four typical patterns are discovered by taking into account prior expert knowledge. Several hypotheses are elaborated about the reasons for psychological distress or decreases in QoL of patients over time. The knowledge discovery from data (KDD) approach turns out, once again, to be a suitable formal framework for handling multidimensional complexity of the health domains.

Towards an Obesity-Cancer Knowledge Base: Biomedical Entity Identification and Relation Detection

PubMed Central

Lossio-Ventura, Juan Antonio; Hogan, William; Modave, François; Hicks, Amanda; Hanna, Josh; Guo, Yi; He, Zhe; Bian, Jiang

2017-01-01

Obesity is associated with increased risks of various types of cancer, as well as a wide range of other chronic diseases. On the other hand, access to health information activates patient participation, and improve their health outcomes. However, existing online information on obesity and its relationship to cancer is heterogeneous ranging from pre-clinical models and case studies to mere hypothesis-based scientific arguments. A formal knowledge representation (i.e., a semantic knowledge base) would help better organizing and delivering quality health information related to obesity and cancer that consumers need. Nevertheless, current ontologies describing obesity, cancer and related entities are not designed to guide automatic knowledge base construction from heterogeneous information sources. Thus, in this paper, we present methods for named-entity recognition (NER) to extract biomedical entities from scholarly articles and for detecting if two biomedical entities are related, with the long term goal of building a obesity-cancer knowledge base. We leverage both linguistic and statistical approaches in the NER task, which supersedes the state-of-the-art results. Further, based on statistical features extracted from the sentences, our method for relation detection obtains an accuracy of 99.3% and a f-measure of 0.993. PMID:28503356

Ensuring long-term utility of the AOP framework and knowledge for multiple stakeholders

EPA Science Inventory

1.Introduction There is a need to increase the development and implementation of predictive approaches to support chemical safety assessment. These predictive approaches feature generation of data from tools such as computational models, pathway-based in vitro assays, and short-t...

Biological Nature of Knowledge in the Learning Organisation

ERIC Educational Resources Information Center

Hall, William P.

2005-01-01

Purpose: To develop a biological approach to the analysis of learning organisations based on complexity theory, autopoiesis, and evolutionary epistemology. Design/methodology/approach: This paper synthesises ideas from disciplines ranging from physics, epistemology and philosophy of science to military affairs, to sketch a scientific framework in…