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.

Investigating TPACK: Knowledge Growth in Teaching with Technology

ERIC Educational Resources Information Center

Niess, Margaret L.

2011-01-01

Technological pedagogical and content knowledge (TPACK) presents a dynamic framework for describing teachers' knowledge required for designing, implementing, and evaluating curriculum and instruction with technology. TPACK strategic thinking includes knowing when, where, and how to use domain-specific knowledge and strategies for guiding students'…

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.

Conceptual Knowledge Acquisition in Biomedicine: A Methodological Review

PubMed Central

Payne, Philip R.O.; Mendonça, Eneida A.; Johnson, Stephen B.; Starren, Justin B.

2007-01-01

The use of conceptual knowledge collections or structures within the biomedical domain is pervasive, spanning a variety of applications including controlled terminologies, semantic networks, ontologies, and database schemas. A number of theoretical constructs and practical methods or techniques support the development and evaluation of conceptual knowledge collections. This review will provide an overview of the current state of knowledge concerning conceptual knowledge acquisition, drawing from multiple contributing academic disciplines such as biomedicine, computer science, cognitive science, education, linguistics, semiotics, and psychology. In addition, multiple taxonomic approaches to the description and selection of conceptual knowledge acquisition and evaluation techniques will be proposed in order to partially address the apparent fragmentation of the current literature concerning this domain. PMID:17482521

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.

Canadian residents' perceived manager training needs.

PubMed

Stergiopoulos, Vicky; Lieff, Susan; Razack, Saleem; Lee, A Curtis; Maniate, Jerry M; Hyde, Stacey; Taber, Sarah; Frank, Jason R

2010-01-01

Despite widespread endorsement for administrative training during residency, teaching and learning in this area remains intermittent and limited in most programmes. To inform the development of a Manager Train-the-Trainer program for faculty, the Royal College of Physicians and Surgeons of Canada undertook a survey of perceived Manager training needs among postgraduate trainees. A representative sample of Canadian specialty residents received a web-based questionnaire in 2009 assessing their perceived deficiencies in 13 Manager knowledge and 11 Manager skill domains, as determined by gap scores (GSs). GSs were defined as the difference between residents' perceived current and desired level of knowledge or skill in selected Manager domains. Residents' educational preferences for furthering their Manager knowledge and skills were also elicited. Among the 549 residents who were emailed the survey, 199 (36.2%) responded. Residents reported significant gaps in most knowledge and skills domains examined. Residents' preferred educational methods for learning Manager knowledge and skills included workshops, web-based formats and interactive small groups. The results of this national survey, highlighting significant perceived gaps in multiple Manager knowledge and skills domains, may inform the development of Manager curricula and faculty development activities to address deficiencies in training in this important area.

A Review of Similarities between Domain-Specific Determinants of Four Health Behaviors among Adolescents

ERIC Educational Resources Information Center

Peters, Louk W. H.; Wiefferink, Carin H.; Hoekstra, Femke; Buijs, Goof J.; ten Dam, Geert T. M.; Paulussen, Theo G. W. M.

2009-01-01

Schools are overloaded with health promotion programs that, altogether, focus on a broad array of behavioral domains, including substance abuse, sexuality and nutrition. Although the specific content of programs varies according to the domain focus, programs usually address similar concepts: knowledge, attitudinal beliefs, social influences and…

Domain-Specific Knowledge and Why Teaching Generic Skills Does Not Work

ERIC Educational Resources Information Center

Tricot, André; Sweller, John

2014-01-01

Domain-general cognitive knowledge has frequently been used to explain skill when domain-specific knowledge held in long-term memory may provide a better explanation. An emphasis on domain-general knowledge may be misplaced if domain-specific knowledge is the primary factor driving acquired intellectual skills. We trace the long history of…

Developmental Change in the Influence of Domain-General Abilities and Domain-Specific Knowledge on Mathematics Achievement: An Eight-Year Longitudinal Study

PubMed Central

Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo

2016-01-01

The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects and domain-specific effects were indexed by prior grade mathematics achievement and mathematical cognition measures of prior grade number knowledge, addition skills, and fraction knowledge. Use of functional data analysis enabled grade-by-grade estimation of overall domain-general and domain-specific effects on subsequent mathematics achievement, the relative importance of individual domain-general and domain-specific variables on this achievement, and linear and non-linear across-grade estimates of these effects. The overall importance of domain-general abilities for subsequent achievement was stable across grades, with working memory emerging as the most important domain-general ability in later grades. The importance of prior mathematical competencies on subsequent mathematics achievement increased across grades, with number knowledge and arithmetic skills critical in all grades and fraction knowledge in later grades. Overall, domain-general abilities were more important than domain-specific knowledge for mathematics learning in early grades but general abilities and domain-specific knowledge were equally important in later grades. PMID:28781382

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.

International trends in solid-state lighting : analyses of the article and patent literature.

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

Tsao, Jeffrey Yeenien; Huey, Mark C.; Boyack, Kevin W.

We present an analysis of the literature of solid-state lighting, based on a comprehensive dataset of 35,851 English-language articles and 12,420 U.S. patents published or issued during the years 1977-2004 in the foundational knowledge domain of electroluminescent materials and phenomena. The dataset was created using a complex, iteratively developed search string. The records in the dataset were then partitioned according to: whether they are articles or patents, their publication or issue date, their national or continental origin, whether the active electroluminescent material was inorganic or organic, and which of a number of emergent knowledge sub-domains they aggregate into on themore » basis of bibliographic coupling. From these partitionings, we performed a number of analyses, including: identification of knowledge sub-domains of historical and recent importance, and trends over time of the contributions of various nations and continents to the knowledge domain and its sub-domains. Among the key results: (1) The knowledge domain as a whole has been growing quickly: the average growth rates of the inorganic and organic knowledge sub-domains have been 8%/yr and 25%/yr, respectively, compared to average growth rates less than 5%/yr for English-language articles and U.S. patents in other knowledge domains. The growth rate of the organic knowledge sub-domain is so high that its historical dominance by the inorganic knowledge sub-domain will, at current trajectories, be reversed in the coming decade. (2) Amongst nations, the U.S. is the largest contributor to the overall knowledge domain, but Japan is on a trajectory to become the largest contributor within the coming half-decade. Amongst continents, Asia became the largest contributor during the past half-decade, overwhelmingly so for the organic knowledge sub-domain. (3) The relative contributions to the article and patent datasets differ for the major continents: North America contributing relatively more patents, Europe contributing relatively more articles, and Asia contributing in a more balanced fashion. (4) For the article dataset, the nations that contribute most in quantity also contribute most in breadth, while the nations that contribute less in quantity concentrate their contributions in particular knowledge sub-domains. For the patent dataset, North America and Europe tend to contribute improvements in end-use applications (e.g., in sensing, phototherapy and communications), while Asia tends to contribute improvements at the materials and chip levels. (5) The knowledge sub-domains that emerge from aggregations based on bibliographic coupling are roughly organized, for articles, by the degree of localization of electrons and holes in the material or phenomenon of interest, and for patents, according to both their emphasis on chips, systems or applications, and their emphasis on organic or inorganic materials. (6) The six 'hottest' topics in the article dataset are: spintronics, AlGaN UV LEDs, nanowires, nanophosphors, polyfluorenes and electrophosphorescence. The nine 'hottest' topics in the patent dataset are: OLED encapsulation, active-matrix displays, multicolor OLEDs, thermal transfer for OLED fabrication, ink-jet printed OLEDs, phosphor-converted LEDs, ornamental LED packages, photocuring and phototherapy, and LED retrofitting lamps. A significant caution in interpreting these results is that they are based on English-language articles and U.S. patents, and hence will tend to over-represent the strength of English-speaking nations (particularly the U.S.), and under-represent the strength of non-English-speaking nations (particularly China).« less

Knowledge Representation Standards and Interchange Formats for Causal Graphs

NASA Technical Reports Server (NTRS)

Throop, David R.; Malin, Jane T.; Fleming, Land

2005-01-01

In many domains, automated reasoning tools must represent graphs of causally linked events. These include fault-tree analysis, probabilistic risk assessment (PRA), planning, procedures, medical reasoning about disease progression, and functional architectures. Each of these fields has its own requirements for the representation of causation, events, actors and conditions. The representations include ontologies of function and cause, data dictionaries for causal dependency, failure and hazard, and interchange formats between some existing tools. In none of the domains has a generally accepted interchange format emerged. The paper makes progress towards interoperability across the wide range of causal analysis methodologies. We survey existing practice and emerging interchange formats in each of these fields. Setting forth a set of terms and concepts that are broadly shared across the domains, we examine the several ways in which current practice represents them. Some phenomena are difficult to represent or to analyze in several domains. These include mode transitions, reachability analysis, positive and negative feedback loops, conditions correlated but not causally linked and bimodal probability distributions. We work through examples and contrast the differing methods for addressing them. We detail recent work in knowledge interchange formats for causal trees in aerospace analysis applications in early design, safety and reliability. Several examples are discussed, with a particular focus on reachability analysis and mode transitions. We generalize the aerospace analysis work across the several other domains. We also recommend features and capabilities for the next generation of causal knowledge representation standards.

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

NASA Technical Reports Server (NTRS)

Keller, Richard M. (Editor); Barstow, David; Lowry, Michael R.; Tong, Christopher H.

1992-01-01

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface.

Changing Conception of Sources of Memory Development. 1985/23.

ERIC Educational Resources Information Center

Chi, Michelene T. H.

1985-01-01

Explanations for memory development have tended to focus on acquistion of general strategies and metaknowledge. Recently, emphasis has been given to the knowledge base as a whole, including general world-knowledge and domain-specific knowledge and procedures. Evidence is presented from the memory development literature showing why strategies and…

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.

Text Processing of Domain-Related Information for Individuals with High and Low Domain Knowledge.

ERIC Educational Resources Information Center

Spilich, George J.; And Others

1979-01-01

The way in which previously acquired knowledge affects the processing on new domain-related information was investigated. Text processing was studied in two groups differing in knowledge of the domain of baseball. A knowledge structure for the domain was constructed, and text propositions were classified. (SW)

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

Effects of Domain Knowledge, Working Memory Capacity, and Age on Cognitive Performance: An Investigation of the Knowledge-Is-Power Hypothesis

ERIC Educational Resources Information Center

Hambrick, David Z.; Engle, Randall W.

2002-01-01

Domain knowledge facilitates performance in many cognitive tasks. However, very little is known about the interplay between domain knowledge and factors that are believed to reflect general, and relatively stable, characteristics of the individual. The primary goal of this study was to investigate the interplay between domain knowledge and one…

Effects of domain knowledge, working memory capacity, and age on cognitive performance: an investigation of the knowledge-is-power hypothesis.

PubMed

Hambrick, David Z; Engle, Randall W

2002-06-01

Domain knowledge facilitates performance in many cognitive tasks. However, very little is known about the interplay between domain knowledge and factors that are believed to reflect general, and relatively stable, characteristics of the individual. The primary goal of this study was to investigate the interplay between domain knowledge and one such factor: working memory capacity. Adults from wide ranges of working memory capacity, age, and knowledge about the game of baseball listened to, and then answered questions about, simulated radio broadcasts of baseball games. There was a strong facilitative effect of preexisting knowledge of baseball on memory performance, particularly for information judged to be directly relevant to the baseball games. However, there was a positive effect of working memory capacity on memory performance as well, and there was no indication that domain knowledge attenuated this effect. That is, working memory capacity contributed to memory performance even at high levels of domain knowledge. Similarly, there was no evidence that domain knowledge attenuated age-related differences (favoring young adults) in memory performance. We discuss implications of the results for understanding proficiency in cognitive domains from an individual-differences perspective. Copyright 2001 Elsevier Science (USA).

The Attraction Effect in Decision Making: Superior Performance by Older Adults

PubMed Central

Kim, Sunghan; Hasher, Lynn

2006-01-01

Previous work showed that older adults’ choice performance can be wiser than that of younger adults (Tentori, Osherson, Hasher, & May, 2001). We contrasted two possible interpretations: a general expertise/wisdom view that suggests that older adults are generally more skilled at making decisions than younger adults and a domain-specific expertise view that suggests that older adults are more skilled decision makers only in domains in which they have greater knowledge. These hypotheses were contrasted using attraction effect tasks in two different domains: earning extra credit in a course and grocery shopping, domains presumed to be of different levels of knowledge to younger and older adults. Older adults showed consistent choice for both domains; younger adults showed consistent choice only for the extra credit problem. Several explanations of these findings are considered, including Damasio’s somatic marker theory and age differences in reliance on heuristic versus analytic styles. PMID:15881294

A concept ideation framework for medical device design.

PubMed

Hagedorn, Thomas J; Grosse, Ian R; Krishnamurty, Sundar

2015-06-01

Medical device design is a challenging process, often requiring collaboration between medical and engineering domain experts. This collaboration can be best institutionalized through systematic knowledge transfer between the two domains coupled with effective knowledge management throughout the design innovation process. Toward this goal, we present the development of a semantic framework for medical device design that unifies a large medical ontology with detailed engineering functional models along with the repository of design innovation information contained in the US Patent Database. As part of our development, existing medical, engineering, and patent document ontologies were modified and interlinked to create a comprehensive medical device innovation and design tool with appropriate properties and semantic relations to facilitate knowledge capture, enrich existing knowledge, and enable effective knowledge reuse for different scenarios. The result is a Concept Ideation Framework for Medical Device Design (CIFMeDD). Key features of the resulting framework include function-based searching and automated inter-domain reasoning to uniquely enable identification of functionally similar procedures, tools, and inventions from multiple domains based on simple semantic searches. The significance and usefulness of the resulting framework for aiding in conceptual design and innovation in the medical realm are explored via two case studies examining medical device design problems. Copyright © 2015 Elsevier Inc. All rights reserved.

The KASE approach to domain-specific software systems

NASA Technical Reports Server (NTRS)

Bhansali, Sanjay; Nii, H. Penny

1992-01-01

Designing software systems, like all design activities, is a knowledge-intensive task. Several studies have found that the predominant cause of failures among system designers is lack of knowledge: knowledge about the application domain, knowledge about design schemes, knowledge about design processes, etc. The goal of domain-specific software design systems is to explicitly represent knowledge relevant to a class of applications and use it to partially or completely automate various aspects of the designing systems within that domain. The hope is that this would reduce the intellectual burden on the human designers and lead to more efficient software development. In this paper, we present a domain-specific system built on top of KASE, a knowledge-assisted software engineering environment being developed at the Stanford Knowledge Systems Laboratory. We introduce the main ideas underlying the construction of domain specific systems within KASE, illustrate the application of the idea in the synthesis of a system for tracking aircraft from radar signals, and discuss some of the issues in constructing domain-specific systems.

Domain knowledge patterns in pedagogical diagnostics

NASA Astrophysics Data System (ADS)

Miarka, Rostislav

2017-07-01

This paper shows a proposal of representation of knowledge patterns in RDF(S) language. Knowledge patterns are used for reuse of knowledge. They can be divided into two groups - Top-level knowledge patterns and Domain knowledge patterns. Pedagogical diagnostics is aimed at testing of knowledge of students at primary and secondary school. An example of domain knowledge pattern from pedagogical diagnostics is part of this paper.

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.

Science, education and industry information resources complementarity as a basis for design of knowledge management systems

NASA Astrophysics Data System (ADS)

Maksimov, N. V.; Tikhomirov, G. V.; Golitsyna, O. L.

2017-01-01

The main problems and circumstances that influence the processes of creating effective knowledge management systems were described. These problems particularly include high species diversity of instruments for knowledge representation, lack of adequate lingware, including formal representation of semantic relationships. For semantic data descriptions development a conceptual model of the subject area and a conceptual-lexical system should be designed on proposals of ISO-15926 standard. It is proposed to conduct an information integration of educational and production processes on the basis of information systems technologies. Integrated knowledge management system information environment combines both traditional information resources and specific information resources of subject domain including task context and implicit/tacit knowledge.

Outcome and Impact Evaluation of a Transgender Health Course for Health Profession Students.

PubMed

Braun, Hannan M; Garcia-Grossman, Ilana R; Quiñones-Rivera, Andrea; Deutsch, Madeline B

2017-02-01

Being transgender is associated with numerous health disparities, and transgender individuals face mistreatment and discrimination in healthcare settings. At the same time, healthcare professionals report inadequate preparation to care for transgender people, and patients often have to teach their own medical providers about transgender care. Our study aimed to evaluate the impact of an elective course for health profession students in transgender health that was implemented to address these gaps in provider knowledge. Students participated in a 10-session, lunch-hour elective course during the spring of 2015. To evaluate impact, course participants completed pre-, immediately post-, and 3-month postcourse questionnaires, including a previously validated nine-item transphobia scale, to determine the course's effect on knowledge, attitudes, and beliefs about transgender health. Forty-six students completed the pre- and immediately postelective questionnaire (74% response rate). Compared with pre-elective surveys, immediately postelective scores demonstrated increased knowledge in most domains and reduced transphobia. Specific knowledge domains with improvements included terminology, best practices for collecting gender identity, awareness of the DSM-V gender dysphoria diagnosis, medications used for gender affirmation, and relevant federal policies. A previously validated transphobia scale was found to have good reliability in the current sample. This elective course led to positive short-term changes in measures of multiple knowledge domains and reduced measures of transphobia among health profession students. Further study is needed to assess the long-term impact. Our methods and findings, including the demonstration of reliability of a previously validated nine-item transphobia scale, serve as formative data for the future development of theory-based transgender medicine curricula and measures.

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.

Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

PubMed

Sheikhtaheri, Abbas; Sadoughi, Farahnaz; Hashemi Dehaghi, Zahra

2014-09-01

Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

Knowledge Representation and Ontologies

NASA Astrophysics Data System (ADS)

Grimm, Stephan

Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

A Multidisciplinary Model for Development of Intelligent Computer-Assisted Instruction.

ERIC Educational Resources Information Center

Park, Ok-choon; Seidel, Robert J.

1989-01-01

Proposes a schematic multidisciplinary model to help developers of intelligent computer-assisted instruction (ICAI) identify the types of required expertise and integrate them into a system. Highlights include domain types and expertise; knowledge acquisition; task analysis; knowledge representation; student modeling; diagnosis of learning needs;…

Knowledge Discovery in Chess Using an Aesthetics Approach

ERIC Educational Resources Information Center

Iqbal, Azlan

2012-01-01

Computational aesthetics is a relatively new subfield of artificial intelligence (AI). It includes research that enables computers to "recognize" (and evaluate) beauty in various domains such as visual art, music, and games. Aside from the benefit this gives to humans in terms of creating and appreciating art in these domains, there are perhaps…

Dispositional Predictors of Problem Solving in the Field of Office Work

ERIC Educational Resources Information Center

Rausch, Andreas

2017-01-01

It was investigated how domain-specific knowledge, fluid intelligence, vocational interest and work-related self-efficacy predicted domain-specific problem-solving performance in the field of office work. The participants included 100 German VET (vocational education and training) students nearing the end of a 3-year apprenticeship program as an…

Human trafficking education for nurse practitioners: Integration into standard curriculum.

PubMed

Lutz, Rebecca M

2018-02-01

Human trafficking is a crime resulting in serious negative health outcomes for the victims. To provide optimal care, thus improving health outcomes, healthcare providers must be able to identify victims as they seek care for acute and chronic physical illness, communicable diseases, sexually transmitted infections, and mental health disorders (Lederer and Wetzel, 2014; Oram et al., 2012). Unfortunately, healthcare providers lack appropriate knowledge of clues that would lead to victim identification. This may result in a failure to identify victims (Beck et al., 2015; Ross et al., 2015; Konstantopoulos et al., 2013; Chisolm-Straker et al., 2012). Increasing the number of healthcare providers able to identify, treat, and refer victims of trafficking for further care is imperative. The study evaluated the knowledge level of student nurse practitioners enrolled in an adult, family, or pediatric clinical course. Knowledge domains included the definitions, laws, prevalence, identification, treatment, and community and social service resources. The study was designed as a non-probability sampling of adult, family, and pediatric nurse practitioner students (n=73). Participants included students enrolled in the Adult & Older Adult I or the Primary Care of the Child & Adolescent I course at a large public university. The study was designed as a one hour educational intervention intended for presentation in a lecture-style format. The educational intervention included a PowerPoint lecture and embedded videos. The pre-survey, designed as a paper survey, contained a demographic section followed by six survey questions covering the six domains of interest. Following the intervention, participants completed the post-survey prior to leaving the classroom. Pre-survey results pinpointed knowledge gaps across all six domains under investigation. Post-survey results revealed an increase in knowledge across all six domains of interest. The educational intervention increased knowledge of human trafficking among students enrolled in a nurse practitioner program. Informed nurse practitioners have the ability to identify, treat, and refer victims of trafficking. As an integral part of the health care team, nurse practitioners should receive trafficking education as part of the standard course curricula. Copyright © 2017 Elsevier Ltd. All rights reserved.

Patient understanding of emergency department discharge instructions: where are knowledge deficits greatest?

PubMed

Engel, Kirsten G; Buckley, Barbara A; Forth, Victoria E; McCarthy, Danielle M; Ellison, Emily P; Schmidt, Michael J; Adams, James G

2012-09-01

Many patients are discharged from the emergency department (ED) with an incomplete understanding of the information needed to safely care for themselves at home. Patients have demonstrated particular difficulty in understanding post-ED care instructions (including medications, home care, and follow-up). The objective of this study was to further characterize these deficits and identify gaps in knowledge that may place the patient at risk for complications or poor outcomes. This was a prospective cohort, phone interview-based study of 159 adult English-speaking patients within 24 to 36 hours of ED discharge. Patient knowledge was assessed for five diagnoses (ankle sprain, back pain, head injury, kidney stone, and laceration) across the following five domains: diagnosis, medications, home care, follow-up, and return instructions. Knowledge was determined based on the concordance between direct patient recall and diagnosis-specific discharge instructions combined with chart review. Two authors scored each case independently and discussed discrepancies before providing a final score for each domain (no, minimal, partial, or complete comprehension). Descriptive statistics were used for the analyses. The study population was 50% female with a median age of 41 years (interquartile range [IQR] = 29 to 53 years). Knowledge deficits were demonstrated by the majority of patients in the domain of home care instructions (80%) and return instructions (79%). Less frequent deficits were found for the domains of follow-up (39%), medications (22%), and diagnosis (14%). Minimal or no understanding in at least one domain was demonstrated by greater than two-thirds of patients and was found in 40% of cases for home care and 51% for return instructions. These deficits occurred less frequently for domains of follow-up (18%), diagnosis (3%), and medications (3%). Patients demonstrate the most frequent knowledge deficits for home care and return instructions, raising significant concerns for adherence and outcomes. © 2012 by the Society for Academic Emergency Medicine.

Measuring Student Knowledge of Landscapes and Their Formation Timespans

ERIC Educational Resources Information Center

Jolley, Alison; Jones, Francis; Harris, Sara

2013-01-01

Geologic time is a crucial component of any geoscientist's training. Essential knowledge of geologic time includes rates of geologic processes and the associated time it takes for geologic features to form, yet measuring conceptual thinking abilities in these domains is challenging. We describe development and initial application of the Landscape…

Standard precautions and infection control, medical students' knowledge and behavior at a Saudi university: the need for change.

PubMed

Amin, Tarek Tawfik; Al Noaim, Khalid Ibrahim; Bu Saad, Mohammed Ahmed; Al Malhm, Turki Ahmed; Al Mulhim, Abdullah Abdulaziz; Al Awas, Marwah Abdulaziz

2013-04-21

No previous studies have reported the knowledge of Saudi medical students about Standard Precautions (SPs) and infection control. The objectives of this study were to assess medical students' knowledge in clinical years at King Faisal University, Saudi Arabia about SPs' and to explore their attitudes toward the current curricular/training in providing them with effective knowledge and necessary skills with regard to SPs. This cross sectional study targeted students in clinical stage at College of Medicine, King Faisal University, Saudi Arabia. A pre-tested anonymous self administered data collection form was used. Inquires about students' characteristics, general concepts of infection control/SPs, hand hygiene, personal protective equipment, sharp injuries and disposal, and care of health providers were included. The main source of information for each domain was also inquired. The second part dedicated to explore the attitudes toward the curricular and teaching relevant to SPs. A total of 251 students were included. Knowledge scores in all domains were considerably low, 67 (26.7%) students scored ? 24 (out of 41points) which was considered as an acceptable level of knowledge, 22.2% in 4th year, 20.5% in 5th year and 36.8% in 6th year. Sharp injuries, personal protective equipment and health care of the providers showed the least knowledge scores. The main sources of knowledge were self learning, and informal bed side practices The majority of students' believed that the current teaching and training are insufficient in providing them with the necessary knowledge and skills regarding SPs. The overall knowledge scores for SPs were low especially in the domains of hand hygiene, sharp management, and personal protective equipment reflecting insufficient and ineffective instructions received by medical students through the current curriculum posing them vulnerable to health facilities related infections. Proper curricular reform and training are required to protect students and their patients.

Adult Age Differences in Knowledge-Driven Reading

ERIC Educational Resources Information Center

Miller, Lisa M. Soederberg; Stine-Morrow, Elizabeth A. L.; Kirkorian, Heather L.; Conroy, Michelle L.

2004-01-01

The authors investigated the effects of domain knowledge on online reading among younger and older adults. Individuals were randomly assigned to either a domain-relevant (i.e., high-knowledge) or domain-irrelevant (i.e., low-knowledge) training condition. Two days later, participants read target passages on a computer that drew on information…

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.

Effects of Working Memory Capacity and Domain Knowledge on Recall for Grocery Prices.

PubMed

Bermingham, Douglas; Gardner, Michael K; Woltz, Dan J

2016-01-01

Hambrick and Engle (2002) proposed 3 models of how domain knowledge and working memory capacity may work together to influence episodic memory: a "rich-get-richer" model, a "building blocks" model, and a "compensatory" model. Their results supported the rich-get-richer model, although later work by Hambrick and Oswald (2005) found support for a building blocks model. We investigated the effects of domain knowledge and working memory on recall of studied grocery prices. Working memory was measured with 3 simple span tasks. A contrast of realistic versus fictitious foods in the episodic memory task served as our manipulation of domain knowledge, because participants could not have domain knowledge of fictitious food prices. There was a strong effect for domain knowledge (realistic food-price pairs were easier to remember) and a moderate effect for working memory capacity (higher working memory capacity produced better recall). Furthermore, the interaction between domain knowledge and working memory produced a small but significant interaction in 1 measure of price recall. This supported the compensatory model and stands in contrast to previous research.

Benchmarking Ontologies: Bigger or Better?

PubMed Central

Yao, Lixia; Divoli, Anna; Mayzus, Ilya; Evans, James A.; Rzhetsky, Andrey

2011-01-01

A scientific ontology is a formal representation of knowledge within a domain, typically including central concepts, their properties, and relations. With the rise of computers and high-throughput data collection, ontologies have become essential to data mining and sharing across communities in the biomedical sciences. Powerful approaches exist for testing the internal consistency of an ontology, but not for assessing the fidelity of its domain representation. We introduce a family of metrics that describe the breadth and depth with which an ontology represents its knowledge domain. We then test these metrics using (1) four of the most common medical ontologies with respect to a corpus of medical documents and (2) seven of the most popular English thesauri with respect to three corpora that sample language from medicine, news, and novels. Here we show that our approach captures the quality of ontological representation and guides efforts to narrow the breach between ontology and collective discourse within a domain. Our results also demonstrate key features of medical ontologies, English thesauri, and discourse from different domains. Medical ontologies have a small intersection, as do English thesauri. Moreover, dialects characteristic of distinct domains vary strikingly as many of the same words are used quite differently in medicine, news, and novels. As ontologies are intended to mirror the state of knowledge, our methods to tighten the fit between ontology and domain will increase their relevance for new areas of biomedical science and improve the accuracy and power of inferences computed across them. PMID:21249231

Pedagogically-Driven Ontology Network for Conceptualizing the e-Learning Assessment Domain

ERIC Educational Resources Information Center

Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura

2015-01-01

The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…

The Development of a Corpus-Based Tool for Exploring Domain-Specific Collocational Knowledge in English

ERIC Educational Resources Information Center

Huang, Ping-Yu; Chen, Chien-Ming; Tsao, Nai-Lung; Wible, David

2015-01-01

Since it was published, Coxhead's (2000) Academic Word List (AWL) has been frequently used in English for academic purposes (EAP) classrooms, included in numerous teaching materials, and re-examined in light of various domain-specific corpora. Although well-received, the AWL has been criticized for ignoring some important facts that words still…

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.

Cost-Benefit Analysis of Confidentiality Policies for Advanced Knowledge Management Systems

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

May, D

Knowledge Discovery (KD) processes can create new information within a Knowledge Management (KM) system. In many domains, including government, this new information must be secured against unauthorized disclosure. Applying an appropriate confidentiality policy achieves this. However, it is not evident which confidentiality policy to apply, especially when the goals of sharing and disseminating knowledge have to be balanced with the requirements to secure knowledge. This work proposes to solve this problem by developing a cost-benefit analysis technique for examining the tradeoffs between securing and sharing discovered knowledge.

From scenarios to domain models: processes and representations

NASA Astrophysics Data System (ADS)

Haddock, Gail; Harbison, Karan

1994-03-01

The domain specific software architectures (DSSA) community has defined a philosophy for the development of complex systems. This philosophy improves productivity and efficiency by increasing the user's role in the definition of requirements, increasing the systems engineer's role in the reuse of components, and decreasing the software engineer's role to the development of new components and component modifications only. The scenario-based engineering process (SEP), the first instantiation of the DSSA philosophy, has been adopted by the next generation controller project. It is also the chosen methodology of the trauma care information management system project, and the surrogate semi-autonomous vehicle project. SEP uses scenarios from the user to create domain models and define the system's requirements. Domain knowledge is obtained from a variety of sources including experts, documents, and videos. This knowledge is analyzed using three techniques: scenario analysis, task analysis, and object-oriented analysis. Scenario analysis results in formal representations of selected scenarios. Task analysis of the scenario representations results in descriptions of tasks necessary for object-oriented analysis and also subtasks necessary for functional system analysis. Object-oriented analysis of task descriptions produces domain models and system requirements. This paper examines the representations that support the DSSA philosophy, including reference requirements, reference architectures, and domain models. The processes used to create and use the representations are explained through use of the scenario-based engineering process. Selected examples are taken from the next generation controller project.

Perspectives on knowledge in engineering design

NASA Technical Reports Server (NTRS)

Rasdorf, W. J.

1985-01-01

Various perspectives are given of the knowledge currently used in engineering design, specifically dealing with knowledge-based expert systems (KBES). Constructing an expert system often reveals inconsistencies in domain knowledge while formalizing it. The types of domain knowledge (facts, procedures, judgments, and control) differ from the classes of that knowledge (creative, innovative, and routine). The feasible tasks for expert systems can be determined based on these types and classes of knowledge. Interpretive tasks require reasoning about a task in light of the knowledge available, where generative tasks create potential solutions to be tested against constraints. Only after classifying the domain by type and level can the engineer select a knowledge-engineering tool for the domain being considered. The critical features to be weighed after classification are knowledge representation techniques, control strategies, interface requirements, compatibility with traditional systems, and economic considerations.

Semantic Data Integration and Knowledge Management to Represent Biological Network Associations.

PubMed

Losko, Sascha; Heumann, Klaus

2017-01-01

The vast quantities of information generated by academic and industrial research groups are reflected in a rapidly growing body of scientific literature and exponentially expanding resources of formalized data, including experimental data, originating from a multitude of "-omics" platforms, phenotype information, and clinical data. For bioinformatics, the challenge remains to structure this information so that scientists can identify relevant information, to integrate this information as specific "knowledge bases," and to formalize this knowledge across multiple scientific domains to facilitate hypothesis generation and validation. Here we report on progress made in building a generic knowledge management environment capable of representing and mining both explicit and implicit knowledge and, thus, generating new knowledge. Risk management in drug discovery and clinical research is used as a typical example to illustrate this approach. In this chapter we introduce techniques and concepts (such as ontologies, semantic objects, typed relationships, contexts, graphs, and information layers) that are used to represent complex biomedical networks. The BioXM™ Knowledge Management Environment is used as an example to demonstrate how a domain such as oncology is represented and how this representation is utilized for research.

Secular trends on traditional ecological knowledge: An analysis of different domains of knowledge among Tsimane' men.

PubMed

Reyes-García, Victoria; Luz, Ana C; Gueze, Maximilien; Paneque-Gálvez, Jaime; Macía, Manuel J; Orta-Martínez, Martí; Pino, Joan

2013-10-01

Empirical research provides contradictory evidence of the loss of traditional ecological knowledge across societies. Researchers have argued that culture, methodological differences, and site-specific conditions are responsible for such contradictory evidences. We advance and test a third explanation: the adaptive nature of traditional ecological knowledge systems. Specifically, we test whether different domains of traditional ecological knowledge experience different secular changes and analyze trends in the context of other changes in livelihoods. We use data collected among 651 Tsimane' men (Bolivian Amazon). Our findings indicate that different domains of knowledge follow different secular trends. Among the domains of knowledge analyzed, medicinal and wild edible knowledge appear as the most vulnerable; canoe building and firewood knowledge seem to remain constant across generations; whereas house building knowledge seems to experience a slight secular increase. Our analysis reflects on the adaptive nature of traditional ecological knowledge, highlighting how changes in this knowledge system respond to the particular needs of a society in a given point of time.

A knowledge representation approach using fuzzy cognitive maps for better navigation support in an adaptive learning system.

PubMed

Chrysafiadi, Konstantina; Virvou, Maria

2013-12-01

In this paper a knowledge representation approach of an adaptive and/or personalized tutoring system is presented. The domain knowledge should be represented in a more realistic way in order to allow the adaptive and/or personalized tutoring system to deliver the learning material to each individual learner dynamically taking into account her/his learning needs and her/his different learning pace. To succeed this, the domain knowledge representation has to depict the possible increase or decrease of the learner's knowledge. Considering that the domain concepts that constitute the learning material are not independent from each other, the knowledge representation approach has to allow the system to recognize either the domain concepts that are already partly or completely known for a learner, or the domain concepts that s/he has forgotten, taking into account the learner's knowledge level of the related concepts. In other words, the system should be informed about the knowledge dependencies that exist among the domain concepts of the learning material, as well as the strength on impact of each domain concept on others. Fuzzy Cognitive Maps (FCMs) seem to be an ideal way for representing graphically this kind of information. The suggested knowledge representation approach has been implemented in an e-learning adaptive system for teaching computer programming. The particular system was used by the students of a postgraduate program in the field of Informatics in the University of Piraeus and was compared with a corresponding system, in which the domain knowledge was represented using the most common used technique of network of concepts. The results of the evaluation were very encouraging.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks.

PubMed

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-08-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

PubMed Central

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-01-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features. PMID:26705504

The effect of an android-based application on the knowledge of the caregivers of children with cerebral palsy

PubMed Central

Ghazisaeedi, Marjan; Safari, Ameneh; Sheikhtaheri, Abbas; Dalvand, Hamid

2016-01-01

Background: Mobile health and e-learning may have a significant impact on training patients, physicians, students and caregivers. This study aimed to evaluate the effect of using an educational mobile application on the knowledge of the caregivers of children with cerebral palsy (CP). Methods: We used a previously developed mobile application. The knowledge of 17 caregivers of children with CP (including parents) about the daily care of their children was evaluated through a self-assessment and a test with multiple-choice and true-false questions. Next, the application, which included several educational modules for the daily care of the children with CP, was given to the caregivers to use continually for two months. After this period, the knowledge of the caregivers was evaluated by the same tools. Data analysis was performed by SPSS-16, using paired-sample t-test or Wilcoxon test. Results: The effect of the use of this educational application on the knowledge of caregivers in all childcare domains, except for eating, was reported to be significant (p<0.05). Furthermore, the results of the multiplechoice test revealed that this application increased the knowledge of caregivers in all domains except playing (p<0.05). Conclusion: Training through novel technologies such as Smartphone along with their applications can improve the knowledge of caregivers about the daily care of children with cerebral palsy. PMID:28491831

The effect of an android-based application on the knowledge of the caregivers of children with cerebral palsy.

PubMed

Ghazisaeedi, Marjan; Safari, Ameneh; Sheikhtaheri, Abbas; Dalvand, Hamid

2016-01-01

Background: Mobile health and e-learning may have a significant impact on training patients, physicians, students and caregivers. This study aimed to evaluate the effect of using an educational mobile application on the knowledge of the caregivers of children with cerebral palsy (CP). Methods: We used a previously developed mobile application. The knowledge of 17 caregivers of children with CP (including parents) about the daily care of their children was evaluated through a self-assessment and a test with multiple-choice and true-false questions. Next, the application, which included several educational modules for the daily care of the children with CP, was given to the caregivers to use continually for two months. After this period, the knowledge of the caregivers was evaluated by the same tools. Data analysis was performed by SPSS-16, using paired-sample t-test or Wilcoxon test. Results: The effect of the use of this educational application on the knowledge of caregivers in all childcare domains, except for eating, was reported to be significant (p<0.05). Furthermore, the results of the multiplechoice test revealed that this application increased the knowledge of caregivers in all domains except playing (p<0.05). Conclusion: Training through novel technologies such as Smartphone along with their applications can improve the knowledge of caregivers about the daily care of children with cerebral palsy.

M-and-C Domain Map Maker: an environment complimenting MDE with M-and-C knowledge and ensuring solution completeness

NASA Astrophysics Data System (ADS)

Patwari, Puneet; Choudhury, Subhrojyoti R.; Banerjee, Amar; Swaminathan, N.; Pandey, Shreya

2016-07-01

Model Driven Engineering (MDE) as a key driver to reduce development cost of M&C systems is beginning to find acceptance across scientific instruments such as Radio Telescopes and Nuclear Reactors. Such projects are adopting it to reduce time to integrate, test and simulate their individual controllers and increase reusability and traceability in the process. The creation and maintenance of models is still a significant challenge to realizing MDE benefits. Creating domain-specific modelling environments reduces the barriers, and we have been working along these lines, creating a domain-specific language and environment based on an M&C knowledge model. However, large projects involve several such domains, and there is still a need to interconnect the domain models, in order to ensure modelling completeness. This paper presents a knowledge-centric approach to doing that, by creating a generic system model that underlies the individual domain knowledge models. We present our vision for M&C Domain Map Maker, a set of processes and tools that enables explication of domain knowledge in terms of domain models with mutual consistency relationships to aid MDE.

Reuse: A knowledge-based approach

NASA Technical Reports Server (NTRS)

Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui

1992-01-01

This paper describes our research in automating the reuse process through the use of application domain models. Application domain models are explicit formal representations of the application knowledge necessary to understand, specify, and generate application programs. Furthermore, they provide a unified repository for the operational structure, rules, policies, and constraints of a specific application area. In our approach, domain models are expressed in terms of a transaction-based meta-modeling language. This paper has described in detail the creation and maintenance of hierarchical structures. These structures are created through a process that includes reverse engineering of data models with supplementary enhancement from application experts. Source code is also reverse engineered but is not a major source of domain model instantiation at this time. In the second phase of the software synthesis process, program specifications are interactively synthesized from an instantiated domain model. These specifications are currently integrated into a manual programming process but will eventually be used to derive executable code with mechanically assisted transformations. This research is performed within the context of programming-in-the-large types of systems. Although our goals are ambitious, we are implementing the synthesis system in an incremental manner through which we can realize tangible results. The client/server architecture is capable of supporting 16 simultaneous X/Motif users and tens of thousands of attributes and classes. Domain models have been partially synthesized from five different application areas. As additional domain models are synthesized and additional knowledge is gathered, we will inevitably add to and modify our representation. However, our current experience indicates that it will scale and expand to meet our modeling needs.

Building the Knowledge Base to Support the Automatic Animation Generation of Chinese Traditional Architecture

NASA Astrophysics Data System (ADS)

Wei, Gongjin; Bai, Weijing; Yin, Meifang; Zhang, Songmao

We present a practice of applying the Semantic Web technologies in the domain of Chinese traditional architecture. A knowledge base consisting of one ontology and four rule bases is built to support the automatic generation of animations that demonstrate the construction of various Chinese timber structures based on the user's input. Different Semantic Web formalisms are used, e.g., OWL DL, SWRL and Jess, to capture the domain knowledge, including the wooden components needed for a given building, construction sequence, and the 3D size and position of every piece of wood. Our experience in exploiting the current Semantic Web technologies in real-world application systems indicates their prominent advantages (such as the reasoning facilities and modeling tools) as well as the limitations (such as low efficiency).

GeoSegmenter: A statistically learned Chinese word segmenter for the geoscience domain

NASA Astrophysics Data System (ADS)

Huang, Lan; Du, Youfu; Chen, Gongyang

2015-03-01

Unlike English, the Chinese language has no space between words. Segmenting texts into words, known as the Chinese word segmentation (CWS) problem, thus becomes a fundamental issue for processing Chinese documents and the first step in many text mining applications, including information retrieval, machine translation and knowledge acquisition. However, for the geoscience subject domain, the CWS problem remains unsolved. Although a generic segmenter can be applied to process geoscience documents, they lack the domain specific knowledge and consequently their segmentation accuracy drops dramatically. This motivated us to develop a segmenter specifically for the geoscience subject domain: the GeoSegmenter. We first proposed a generic two-step framework for domain specific CWS. Following this framework, we built GeoSegmenter using conditional random fields, a principled statistical framework for sequence learning. Specifically, GeoSegmenter first identifies general terms by using a generic baseline segmenter. Then it recognises geoscience terms by learning and applying a model that can transform the initial segmentation into the goal segmentation. Empirical experimental results on geoscience documents and benchmark datasets showed that GeoSegmenter could effectively recognise both geoscience terms and general terms.

Developmental Change in the Influence of Domain-General Abilities and Domain-Specific Knowledge on Mathematics Achievement: An Eight-Year Longitudinal Study

ERIC Educational Resources Information Center

Geary, David C.; Nicholas, Alan; Li, Yaoran; Sun, Jianguo

2017-01-01

The contributions of domain-general abilities and domain-specific knowledge to subsequent mathematics achievement were longitudinally assessed (n = 167) through 8th grade. First grade intelligence and working memory and prior grade reading achievement indexed domain-general effects, and domain-specific effects were indexed by prior grade…

Introduction of Virtual Patient Software to Enhance Physician Assistant Student Knowledge in Palliative Medicine.

PubMed

Prazak, Kristine A

2017-01-01

The purpose of this project was to infuse palliative medicine and end-of-life care creatively into physician assistant (PA) education. Nine second-year PA students volunteered to participate in this quasi-experimental, pretest-posttest pilot study. Students initially completed an anonymous survey evaluating seven domains of knowledge in palliative medicine coupled with a self-assessment in competence. Virtual patient software was then used to simulate clinical encounters that addressed major palliative care domains. Upon completion of these cases, the same survey, with the addition of three questions about their own personal feelings, was administered. Overall response was positive in regard to improved knowledge and the virtual patient experience. After completion of the cases, students rated their self-assessed skills higher in all domains than prior to completing the cases. Factual knowledge scores showed a slight but not significant improvement, with an average pre-survey score of 4.56 and post-survey score of 4.67. Using virtual patient software can be a way of infusing palliative medicine and end-of-life care into PA education. These encounters can then be modified to include interprofessional encounters within the health professions.

Contextualized analysis of a needs assessment using the Theoretical Domains Framework: a case example in endocrinology

PubMed Central

2014-01-01

Background The Theoretical Domains Framework (TDF) is a set of 14 domains of behavior change that provide a framework for the critical issues and factors influencing optimal knowledge translation. Considering that a previous study has identified optimal knowledge translation techniques for each TDF domain, it was hypothesized that the TDF could be used to contextualize and interpret findings from a behavioral and educational needs assessment. To illustrate this hypothesis, findings and recommendations drawn from a 2012 national behavioral and educational needs assessment conducted with healthcare providers who treat and manage Growth and Growth Hormone Disorders, will be discussed using the TDF. Methods This needs assessment utilized a mixed-methods research approach that included a combination of: [a] data sources (Endocrinologists (n:120), Pediatric Endocrinologists (n:53), Pediatricians (n:52)), [b] data collection methods (focus groups, interviews, online survey), [c] analysis methodologies (qualitative - analyzed through thematic analysis, quantitative - analyzed using frequencies, cross-tabulations, and gap analysis). Triangulation was used to generate trustworthy findings on the clinical practice gaps of endocrinologists, pediatric endocrinologists, and general pediatricians in their provision of care to adult patients with adult growth hormone deficiency or acromegaly, or children/teenagers with pediatric growth disorders. The identified gaps were then broken into key underlying determinants, categorized according to the TDF domains, and linked to optimal behavioral change techniques. Results The needs assessment identified 13 gaps, each with one or more underlying determinant(s). Overall, these determinants were mapped to 9 of the 14 TDF domains. The Beliefs about Consequences domain was identified as a contributing determinant to 7 of the 13 challenges. Five of the gaps could be related to the Skills domain, while three were linked to the Knowledge domain. Conclusions The TDF categorization of the needs assessment findings allowed recommendation of appropriate behavior change techniques for each underlying determinant, and facilitated communication and understanding of the identified issues to a broader audience. This approach provides a means for health education researchers to categorize gaps and challenges identified through educational needs assessments, and facilitates the application of these findings by educators and knowledge translators, by linking the gaps to recommended behavioral change techniques. PMID:25060235

Contextualized analysis of a needs assessment using the Theoretical Domains Framework: a case example in endocrinology.

PubMed

Lazure, Patrice; Bartel, Robert C; Biller, Beverly M K; Molitch, Mark E; Rosenthal, Stephen M; Ross, Judith L; Bernsten, Brock D; Hayes, Sean M

2014-07-24

The Theoretical Domains Framework (TDF) is a set of 14 domains of behavior change that provide a framework for the critical issues and factors influencing optimal knowledge translation. Considering that a previous study has identified optimal knowledge translation techniques for each TDF domain, it was hypothesized that the TDF could be used to contextualize and interpret findings from a behavioral and educational needs assessment. To illustrate this hypothesis, findings and recommendations drawn from a 2012 national behavioral and educational needs assessment conducted with healthcare providers who treat and manage Growth and Growth Hormone Disorders, will be discussed using the TDF. This needs assessment utilized a mixed-methods research approach that included a combination of: [a] data sources (Endocrinologists (n:120), Pediatric Endocrinologists (n:53), Pediatricians (n:52)), [b] data collection methods (focus groups, interviews, online survey), [c] analysis methodologies (qualitative - analyzed through thematic analysis, quantitative - analyzed using frequencies, cross-tabulations, and gap analysis). Triangulation was used to generate trustworthy findings on the clinical practice gaps of endocrinologists, pediatric endocrinologists, and general pediatricians in their provision of care to adult patients with adult growth hormone deficiency or acromegaly, or children/teenagers with pediatric growth disorders. The identified gaps were then broken into key underlying determinants, categorized according to the TDF domains, and linked to optimal behavioral change techniques. The needs assessment identified 13 gaps, each with one or more underlying determinant(s). Overall, these determinants were mapped to 9 of the 14 TDF domains. The Beliefs about Consequences domain was identified as a contributing determinant to 7 of the 13 challenges. Five of the gaps could be related to the Skills domain, while three were linked to the Knowledge domain. The TDF categorization of the needs assessment findings allowed recommendation of appropriate behavior change techniques for each underlying determinant, and facilitated communication and understanding of the identified issues to a broader audience. This approach provides a means for health education researchers to categorize gaps and challenges identified through educational needs assessments, and facilitates the application of these findings by educators and knowledge translators, by linking the gaps to recommended behavioral change techniques.

Supplemental knowledge acquisition through external product interface for CLIPS

NASA Technical Reports Server (NTRS)

Saito, Tim; Ebaud, Stephen; Loftin, Bowen R.

1990-01-01

Traditionally, the acquisition of knowledge for expert systems consisted of the interview process with the domain or subject matter expert (SME), observation of domain environment, and information gathering and research which constituted a direct form of knowledge acquisition (KA). The knowledge engineer would be responsible for accumulating pertinent information and/or knowledge from the SME(s) for input into the appropriate expert system development tool. The direct KA process may (or may not) have included forms of data or documentation to incorporate from the SME's surroundings. The differentiation between direct KA and supplemental KA (indirect) would be the difference in the use of data. In acquiring supplemental knowledge, the knowledge engineer would access other types of evidence (manuals, documents, data files, spreadsheets, etc.) that would support the reasoning or premises of the SME. When an expert makes a decision in a particular task, one tool that may have been used to justify a recommendation, would have been a spreadsheet total or column figure. Locating specific decision points from that data within the SME's framework would constitute supplemental KA. Data used for a specific purpose in one system or environment would be used as supplemental knowledge for another, specifically a CLIPS project.

Comprehensively Assessing Cognitive and Behavioral Risks for HIV Infection among Middle-Aged and Older Adults

ERIC Educational Resources Information Center

Paniagua, Freddy A.; O'Boyle, Michael

2008-01-01

A comprehensive survey of HIV/AIDS with middle-aged and older adults should include six domains (e.g., factual knowledge regarding the acquisition and transmission of HIV, traditionally-accepted behavioral risks for HIV infection). A sample of 23 women (54.8%) and 19 men (45.2%), ranging in age from 51 to 85 were surveyed across such domains.…

Becoming sustainable: human determinants of change.

PubMed

Frank, Gerhard

2014-05-15

The author is a natural scientist and philosopher who has been involved in the global experience industry for more than 25 years. During this period of time he has developed a coherent, interdisciplinary body of knowledge that appears to be of essential interest as related to the transition towards a sustainable society: the Experience Science (Frank, 2011, 2012). Important scientific inputs come from underlying disciplines like cybernetics, system theory, psychology, and cognitive science. One of the key findings of the Experience Science is the innate structure of human experiencing. Any human experience includes 5 different experiential domains that influence and regulate each other: the emotional domain (feeling); the mental imagery domain (mental narrating); the sensorimotor domain (acting & perceiving); the linguistic domain (rational reasoning); the communicational domain (conversing). In the light of the Experience Science the dilemma of the current transition process towards a sustainable society becomes clearly visible. Any relevant attempt reduces the existing problems to more or less exclusively the linguistic, rational domain. Although ever evolving rational knowledge indeed is an indispensable prerequisite for a sustainable future this is not enough. Societal change towards a sustainable life-style can only happen if the whole experiential system gets a chance to reorganize itself. This leads to the following logical consequence. Any rational knowledge is embedded in a both emotional and narrative knowledge system that underlies and frames human reasoning. As long as human learning restricts itself to an exclusively rational attempt the underlying emotional and narrative program remains untouched. The learner hence continues orienting her attention into the direction determined by the underlying emotional and narrative paradigm. The paper delineates the experiential determinants of change and analyzes their specific, constitutive interrelations. From this a holistic choreography of change learning is outlined that pays tribute to the intrinsic transition principles represented by the human learner. © 2013.

Interrelationship of Knowledge, Interest, and Recall: Assessing a Model of Domain Learning.

ERIC Educational Resources Information Center

Alexander, Patricia A.; And Others

1995-01-01

Two experiments involving 125 college and graduate students examined the interrelationship of subject-matter knowledge, interest, and recall in the field of human immunology and biology and assessed cross-domain performance in physics. Patterns of knowledge, interest, and performance fit well with the premises of the Model of Domain Learning. (SLD)

Contribution of Content Knowledge and Learning Ability to the Learning of Facts.

ERIC Educational Resources Information Center

Kuhara-Kojima, Keiko; Hatano, Giyoo

1991-01-01

In 3 experiments, 1,598 Japanese college students were examined concerning the learning of facts in 2 content domains, baseball and music. Content knowledge facilitated fact learning only in the relevant domain; learning ability facilitated fact learning in both domains. Effects of content knowledge and learning ability were additive. (SLD)

Network Search: A New Way of Seeing the Education Knowledge Domain

ERIC Educational Resources Information Center

McFarland, Daniel; Klopfer, Eric

2010-01-01

Background: The educational knowledge domain may be understood as a system composed of multiple, co-evolving networks that reflect the form and content of a cultural field. This paper describes the educational knowledge domain as having a community structure (form) based in relations of production (authoring) and consumption (referencing), and a…

Domain Knowledge, Search Behaviour, and Search Effectiveness of Engineering and Science Students: An Exploratory Study

ERIC Educational Resources Information Center

Zhang, Xiangmin; Anghelescu, Hermina G. B.; Yuan, Xiaojun

2005-01-01

Introduction: This study sought to answer three questions: 1) Would the level of domain knowledge significantly affect the user's search behaviour? 2) Would the level of domain knowledge significantly affect search effectiveness, and 3) What would be the relationship between search behaviour and search effectiveness? Method: Participants were…

The Effects of Domain Knowledge and Instructional Manipulation on Creative Idea Generation

ERIC Educational Resources Information Center

Hao, Ning

2010-01-01

The experiment was designed to explore the effects of domain knowledge, instructional manipulation, and the interaction between them on creative idea generation. Three groups of participants who respectively possessed the domain knowledge of biology, sports, or neither were asked to finish two tasks: imagining an extraterrestrial animal and…

An automated knowledge-based textual summarization system for longitudinal, multivariate clinical data.

PubMed

Goldstein, Ayelet; Shahar, Yuval

2016-06-01

Design and implement an intelligent free-text summarization system: The system's input includes large numbers of longitudinal, multivariate, numeric and symbolic clinical raw data, collected over varying periods of time, and in different complex contexts, and a suitable medical knowledge base. The system then automatically generates a textual summary of the data. We aim to prove the feasibility of implementing such a system, and to demonstrate its potential benefits for clinicians and for enhancement of quality of care. We have designed a new, domain-independent, knowledge-based system, the CliniText system, for automated summarization in free text of longitudinal medical records of any duration, in any context. The system is composed of six components: (1) A temporal abstraction module generates all possible abstractions from the patient's raw data using a temporal-abstraction knowledge base; (2) The abductive reasoning module infers abstractions or events from the data, which were not explicitly included in the database; (3) The pruning module filters out raw or abstract data based on predefined heuristics; (4) The document structuring module organizes the remaining raw or abstract data, according to the desired format; (5) The microplanning module, groups the raw or abstract data and creates referring expressions; (6) The surface realization module, generates the text, and applies the grammar rules of the chosen language. We have performed an initial technical evaluation of the system in the cardiac intensive-care and diabetes domains. We also summarize the results of a more detailed evaluation study that we have performed in the intensive-care domain that assessed the completeness, correctness, and overall quality of the system's generated text, and its potential benefits to clinical decision making. We assessed these measures for 31 letters originally composed by clinicians, and for the same letters when generated by the CliniText system. We have successfully implemented all of the components of the CliniText system in software. We have also been able to create a comprehensive temporal-abstraction knowledge base to support its functionality, mostly in the intensive-care domain. The initial technical evaluation of the system in the cardiac intensive-care and diabetes domains has shown great promise, proving the feasibility of constructing and operating such systems. The detailed results of the evaluation in the intensive-care domain are out of scope of the current paper, and we refer the reader to a more detailed source. In all of the letters composed by clinicians, there were at least two important items per letter missed that were included by the CliniText system. The clinicians' letters got a significantly better grade in three out of four measured quality parameters, as judged by an expert; however, the variance in the quality was much higher in the clinicians' letters. In addition, three clinicians answered questions based on the discharge letter 40% faster, and answered four out of the five questions equally well or significantly better, when using the CliniText-generated letters, than when using the clinician-composed letters. Constructing a working system for automated summarization in free text of large numbers of varying periods of multivariate longitudinal clinical data is feasible. So is the construction of a large knowledge base, designed to support such a system, in a complex clinical domain, such as the intensive-care domain. The integration of the quality and functionality results suggests that the optimal discharge letter should exploit both human and machine, possibly by creating a machine-generated draft that will be polished by a human clinician. Copyright © 2016 Elsevier Inc. All rights reserved.

Domain and Specification Models for Software Engineering

NASA Technical Reports Server (NTRS)

Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui

1992-01-01

This paper discusses our approach to representing application domain knowledge for specific software engineering tasks. Application domain knowledge is embodied in a domain model. Domain models are used to assist in the creation of specification models. 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. One aspect of the system-hierarchical organization is described in detail.

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

Autonomously acquiring declarative and procedural knowledge for ICAT systems

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1993-01-01

The construction of Intelligent Computer Aided Training (ICAT) systems is critically dependent on the ability to define and encode knowledge. This knowledge engineering effort can be broadly divided into two categories: domain knowledge and expert or task knowledge. Domain knowledge refers to the physical environment or system with which the expert interacts. Expert knowledge consists of the set of procedures and heuristics employed by the expert in performing their task. Both these areas are a significant bottleneck in the acquisition of knowledge for ICAT systems. This paper presents a research project in the area of autonomous knowledge acquisition using a passive observation concept. The system observes an expert and then generalizes the observations into production rules representing the domain expert's knowledge.

Individual differences and their measurement: A review of 100 years of research.

PubMed

Sackett, Paul R; Lievens, Filip; Van Iddekinge, Chad H; Kuncel, Nathan R

2017-03-01

This article reviews 100 years of research on individual differences and their measurement, with a focus on research published in the Journal of Applied Psychology. We focus on 3 major individual differences domains: (a) knowledge, skill, and ability, including both the cognitive and physical domains; (b) personality, including integrity, emotional intelligence, stable motivational attributes (e.g., achievement motivation, core self-evaluations), and creativity; and (c) vocational interests. For each domain, we describe the evolution of the domain across the years and highlight major theoretical, empirical, and methodological developments, including relationships between individual differences and variables such as job performance, job satisfaction, and career development. We conclude by discussing future directions for individual differences research. Trends in the literature include a growing focus on substantive issues rather than on the measurement of individual differences, a differentiation between constructs and measurement methods, and the use of innovative ways of assessing individual differences, such as simulations, other-reports, and implicit measures. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Vivir Con Un Corazón Saludable: a Community-Based Educational Program Aimed at Increasing Cardiovascular Health Knowledge in High-Risk Hispanic Women.

PubMed

Romero, Daniela C; Sauris, Aileen; Rodriguez, Fátima; Delgado, Daniela; Reddy, Ankita; Foody, JoAnne M

2016-03-01

Hispanic women suffer from high rates of cardiometabolic risk factors and an increasingly disproportionate burden of cardiovascular disease (CVD). Particularly, Hispanic women with limited English proficiency suffer from low levels of CVD knowledge associated with adverse CVD health outcomes. Thirty-two predominantly Spanish-speaking Hispanic women completed, Vivir Con un Corazón Saludable (VCUCS), a culturally tailored Spanish language-based 6-week intensive community program targeting CVD health knowledge through weekly interactive health sessions. A 30-question CVD knowledge questionnaire was used to assess mean changes in CVD knowledge at baseline and postintervention across five major knowledge domains including CVD epidemiology, dietary knowledge, medical information, risk factors, and heart attack symptoms. Completion of the program was associated with a statistically significant (p < 0.001) increase in total mean CVD knowledge scores from 39 % (mean 11.7/30.0) to 66 % (mean 19.8/30.0) postintervention consistent with a 68 % increase in overall mean CVD scores. There was a statistically significant (p < 0.001) increase in mean knowledge scores across all five CVD domains. A culturally tailored Spanish language-based health program is effective in increasing CVD awareness among high CVD risk Hispanic women with low English proficiency and low baseline CVD knowledge.

Does Domain Knowledge Moderate Involvement of Working Memory Capacity in Higher-Level Cognition? A Test of Three Models

ERIC Educational Resources Information Center

Hambrick, D.Z.; Oswald, F.L.

2005-01-01

Research suggests that both working memory capacity and domain knowledge contribute to individual differences in higher-level cognition. This study evaluated three hypotheses concerning the interplay between these factors. The compensation hypothesis predicts that domain knowledge attenuates the influence of working memory capacity on higher-level…

College students' memory for vocabulary in their majors: evidence for a nonlinear relation between knowledge and memory.

PubMed

DeMarie, Darlene; Aloise-Young, Patricia A; Prideaux, Cheri L; Muransky-Doran, Jean; Gerda, Julie Hart

2004-09-01

The effect of domain knowledge on students' memory for vocabulary terms was investigated. Participants were 142 college students (94 education majors and 48 business majors). The measure of domain knowledge was the number of courses completed in the major. Students recalled three different lists (control, education, and business) of 20 words. Knowledge effects were estimated controlling for academic aptitude, academic achievement, and general memory ability. Domain-specific knowledge consistently predicted recall, above and beyond the effect of these control variables. Moreover, nonlinear models better represented the relation between knowledge and memory, with very similar functions predicting recall in both knowledge domains. Specifically, early in the majors more classes corresponded with increased memory performance, but a plateau period, when more classes did not result in higher recall, was evident for both majors. Longitudinal research is needed to explore at what point in learning novices' performance begins to resemble experts' performance.

Peer Review-Based Scripted Collaboration to Support Domain-Specific and Domain-General Knowledge Acquisition in Computer Science

ERIC Educational Resources Information Center

Demetriadis, Stavros; Egerter, Tina; Hanisch, Frank; Fischer, Frank

2011-01-01

This study investigates the effectiveness of using peer review in the context of scripted collaboration to foster both domain-specific and domain-general knowledge acquisition in the computer science domain. Using a one-factor design with a script and a control condition, students worked in small groups on a series of computer science problems…

Utilizing AI in Temporal, Spatial, and Resource Scheduling

NASA Technical Reports Server (NTRS)

Stottler, Richard; Kalton, Annaka; Bell, Aaron

2006-01-01

Aurora is a software system enabling the rapid, easy solution of complex scheduling problems involving spatial and temporal constraints among operations and scarce resources (such as equipment, workspace, and human experts). Although developed for use in the International Space Station Processing Facility, Aurora is flexible enough that it can be easily customized for application to other scheduling domains and adapted as the requirements change or become more precisely known over time. Aurora s scheduling module utilizes artificial-intelligence (AI) techniques to make scheduling decisions on the basis of domain knowledge, including knowledge of constraints and their relative importance, interdependencies among operations, and possibly frequent changes in governing schedule requirements. Unlike many other scheduling software systems, Aurora focuses on resource requirements and temporal scheduling in combination. For example, Aurora can accommodate a domain requirement to schedule two subsequent operations to locations adjacent to a shared resource. The graphical interface allows the user to quickly visualize the schedule and perform changes reflecting additional knowledge or alterations in the situation. For example, the user might drag the activity corresponding to the start of operations to reflect a late delivery.

Toward a general ontology for digital forensic disciplines.

PubMed

Karie, Nickson M; Venter, Hein S

2014-09-01

Ontologies are widely used in different disciplines as a technique for representing and reasoning about domain knowledge. However, despite the widespread ontology-related research activities and applications in different disciplines, the development of ontologies and ontology research activities is still wanting in digital forensics. This paper therefore presents the case for establishing an ontology for digital forensic disciplines. Such an ontology would enable better categorization of the digital forensic disciplines, as well as assist in the development of methodologies and specifications that can offer direction in different areas of digital forensics. This includes such areas as professional specialization, certifications, development of digital forensic tools, curricula, and educational materials. In addition, the ontology presented in this paper can be used, for example, to better organize the digital forensic domain knowledge and explicitly describe the discipline's semantics in a common way. Finally, this paper is meant to spark discussions and further research on an internationally agreed ontological distinction of the digital forensic disciplines. Digital forensic disciplines ontology is a novel approach toward organizing the digital forensic domain knowledge and constitutes the main contribution of this paper. © 2014 American Academy of Forensic Sciences.

A Proposal to Develop Interactive Classification Technology

NASA Technical Reports Server (NTRS)

deBessonet, Cary

1998-01-01

Research for the first year was oriented towards: 1) the design of an interactive classification tool (ICT); and 2) the development of an appropriate theory of inference for use in ICT technology. The general objective was to develop a theory of classification that could accommodate a diverse array of objects, including events and their constituent objects. Throughout this report, the term "object" is to be interpreted in a broad sense to cover any kind of object, including living beings, non-living physical things, events, even ideas and concepts. The idea was to produce a theory that could serve as the uniting fabric of a base technology capable of being implemented in a variety of automated systems. The decision was made to employ two technologies under development by the principal investigator, namely, SMS (Symbolic Manipulation System) and SL (Symbolic Language) [see debessonet, 1991, for detailed descriptions of SMS and SL]. The plan was to enhance and modify these technologies for use in an ICT environment. As a means of giving focus and direction to the proposed research, the investigators decided to design an interactive, classificatory tool for use in building accessible knowledge bases for selected domains. Accordingly, the proposed research was divisible into tasks that included: 1) the design of technology for classifying domain objects and for building knowledge bases from the results automatically; 2) the development of a scheme of inference capable of drawing upon previously processed classificatory schemes and knowledge bases; and 3) the design of a query/ search module for accessing the knowledge bases built by the inclusive system. The interactive tool for classifying domain objects was to be designed initially for textual corpora with a view to having the technology eventually be used in robots to build sentential knowledge bases that would be supported by inference engines specially designed for the natural or man-made environments in which the robots would be called upon to operate.

Mapping knowledge domains: Characterizing PNAS

PubMed Central

Boyack, Kevin W.

2004-01-01

A review of data mining and analysis techniques that can be used for the mapping of knowledge domains is given. Literature mapping techniques can be based on authors, documents, journals, words, and/or indicators. Most mapping questions are related to research assessment or to the structure and dynamics of disciplines or networks. Several mapping techniques are demonstrated on a data set comprising 20 years of papers published in PNAS. Data from a variety of sources are merged to provide unique indicators of the domain bounded by PNAS. By using funding source information and citation counts, it is shown that, on an aggregate basis, papers funded jointly by the U.S. Public Health Service (which includes the National Institutes of Health) and non-U.S. government sources outperform papers funded by other sources, including by the U.S. Public Health Service alone. Grant data from the National Institute on Aging show that, on average, papers from large grants are cited more than those from small grants, with performance increasing with grant amount. A map of the highest performing papers over the 20-year period was generated by using citation analysis. Changes and trends in the subjects of highest impact within the PNAS domain are described. Interactions between topics over the most recent 5-year period are also detailed. PMID:14963238

Development of Veteran-Centric Competency Domains for Psychiatric-Mental Health Nurse Practitioner Residents.

PubMed

York, Janet; Sternke, Lisa Marie; Myrick, Donald Hugh; Lauerer, Joy; Hair, Carole

2016-11-01

The mental health needs of military service members, Veterans, and their families are a designated national priority; however, there has been little emphasis on the inclusion of Veteran-centric domains in competency-based nursing education for psychiatric-mental health nurse practitioners (PMHNPs). The current article describes the identification and application of Veteran-centric domains in an innovative pilot residency program for PMHNPs, funded by the Veterans Health Administration Office of Academic Affiliations. Fourteen Veteran-centric competency domains were developed from literature review, including knowledge, attitudes, and skill behaviors. Adoption and application of these domains in curricular components included the resident competency evaluation, baseline assessment of military experience, and evidence-based practice seminars and training. Methods of competency domain evaluation are presented, along with gaps related to the evaluation of competency skills. The delivery of mental health services reflecting these domains is consistent with the VA core values and goal of developing a positive service culture. [Journal of Psychosocial Nursing and Mental Health Services, 54(11), 31-36.]. Copyright 2016, SLACK Incorporated.

The role of professional knowledge in case-based reasoning in practical ethics.

PubMed

Pinkus, Rosa Lynn; Gloeckner, Claire; Fortunato, Angela

2015-06-01

The use of case-based reasoning in teaching professional ethics has come of age. The fields of medicine, engineering, and business all have incorporated ethics case studies into leading textbooks and journal articles, as well as undergraduate and graduate professional ethics courses. The most recent guidelines from the National Institutes of Health recognize case studies and face-to-face discussion as best practices to be included in training programs for the Responsible Conduct of Research. While there is a general consensus that case studies play a central role in the teaching of professional ethics, there is still much to be learned regarding how professionals learn ethics using case-based reasoning. Cases take many forms, and there are a variety of ways to write them and use them in teaching. This paper reports the results of a study designed to investigate one of the issues in teaching case-based ethics: the role of one's professional knowledge in learning methods of moral reasoning. Using a novel assessment instrument, we compared case studies written and analyzed by three groups of students whom we classified as: (1) Experts in a research domain in bioengineering. (2) Novices in a research domain in bioengineering. (3) The non-research group--students using an engineering domain in which they were interested but had no in-depth knowledge. This study demonstrates that a student's level of understanding of a professional knowledge domain plays a significant role in learning moral reasoning skills.

Bidirectional Transfer between Metaphorical Related Domains in Implicit Learning of Form-Meaning Connections

PubMed Central

Yang, Zhiliang; Dienes, Zoltan

2013-01-01

People can implicitly learn a connection between linguistic forms and meanings, for example between specific determiners (e.g. this, that…) and the type of nouns to which they apply. Li et al (2013) recently found that transfer of form-meaning connections from a concrete domain (height) to an abstract domain (power) was achieved in a metaphor-consistent way without awareness, showing that unconscious knowledge can be abstract and flexibly deployed. The current study aims to determine whether people transfer knowledge of form-meaning connections not only from a concrete domain to an abstract one, but also vice versa, consistent with metaphor representation being bi-directional. With a similar paradigm as used by Li et al, participants learnt form- meaning connections of different domains (concrete vs. abstract) and then were tested on two kinds of generalizations (same and different domain generalization). As predicted, transfer of form-meaning connections occurred bidirectionally when structural knowledge was unconscious. Moreover, the present study also revealed that more transfer occurred between metaphorically related domains when judgment knowledge was conscious (intuition) rather than unconscious (guess). Conscious and unconscious judgment knowledge may have different functional properties. PMID:23844159

Interactive knowledge discovery with the doctor-in-the-loop: a practical example of cerebral aneurysms research.

PubMed

Girardi, Dominic; Küng, Josef; Kleiser, Raimund; Sonnberger, Michael; Csillag, Doris; Trenkler, Johannes; Holzinger, Andreas

2016-09-01

Established process models for knowledge discovery find the domain-expert in a customer-like and supervising role. In the field of biomedical research, it is necessary to move the domain-experts into the center of this process with far-reaching consequences for both their research output and the process itself. In this paper, we revise the established process models for knowledge discovery and propose a new process model for domain-expert-driven interactive knowledge discovery. Furthermore, we present a research infrastructure which is adapted to this new process model and demonstrate how the domain-expert can be deeply integrated even into the highly complex data-mining process and data-exploration tasks. We evaluated this approach in the medical domain for the case of cerebral aneurysms research.

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…

Domain-specific knowledge as the "dark matter" of adult intelligence: Gf/Gc, personality and interest correlates.

PubMed

Ackerman, P L

2000-03-01

An enduring controversy in intelligence theory and assessment, the argument that middle-aged adults are, on average, less intelligent than young adults, is addressed in this study. A sample of 228 educated adults between ages 21 and 62 years was given an array of tests that focused on a broad assessment of intelligence-as-knowledge, traditional estimates of fluid intelligence (Gf) and crystallized intelligence (Gc), personality, and interests. The results indicate that middle-aged adults are more knowledgeable in many domains, compared with younger adults. A coherent pattern of ability, personality, and interest relations is found. The results are consistent with a developmental perspective of intelligence that includes both traditional ability and non-ability determinants of intelligence during adulthood. A reassessment of the nature of intelligence in adulthood is provided, in the context of a lifelong learning and investment model, called PPIK, for intelligence-as-Process, Personality, Interests, and intelligence-as-Knowledge (Ackerman, 1996).

Embedding Open-domain Common-sense Knowledge from Text

PubMed Central

Goodwin, Travis; Harabagiu, Sanda

2017-01-01

Our ability to understand language often relies on common-sense knowledge – background information the speaker can assume is known by the reader. Similarly, our comprehension of the language used in complex domains relies on access to domain-specific knowledge. Capturing common-sense and domain-specific knowledge can be achieved by taking advantage of recent advances in open information extraction (IE) techniques and, more importantly, of knowledge embeddings, which are multi-dimensional representations of concepts and relations. Building a knowledge graph for representing common-sense knowledge in which concepts discerned from noun phrases are cast as vertices and lexicalized relations are cast as edges leads to learning the embeddings of common-sense knowledge accounting for semantic compositionality as well as implied knowledge. Common-sense knowledge is acquired from a vast collection of blogs and books as well as from WordNet. Similarly, medical knowledge is learned from two large sets of electronic health records. The evaluation results of these two forms of knowledge are promising: the same knowledge acquisition methodology based on learning knowledge embeddings works well both for common-sense knowledge and for medical knowledge Interestingly, the common-sense knowledge that we have acquired was evaluated as being less neutral than than the medical knowledge, as it often reflected the opinion of the knowledge utterer. In addition, the acquired medical knowledge was evaluated as more plausible than the common-sense knowledge, reflecting the complexity of acquiring common-sense knowledge due to the pragmatics and economicity of language. PMID:28649676

A flight expert system for on-board fault monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Ali, Moonis

1990-01-01

An architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing, and recovering from inflight faults is described. A prototype was implemented and an attempt was made to automate the knowledge acquisition process by employing a learning by being told methodology. The scope of acquired knowledge ranges from domain knowledge, including the information about objects and their relationships, to the procedural knowledge associated with the functionality of the mechanisms. AKAS (automatic knowledge acquisition system) is the constructed prototype for demonstration proof of concept, in which the expert directly interfaces with the knowledge acquisition system to ultimately construct the knowledge base for the particular application. The expert talks directly to the system using a natural language restricted only by the extent of the definitions in an analyzer dictionary, i.e., the interface understands a subset of concepts related to a given domain. In this case, the domain is the electrical system of the Boeing 737. Efforts were made to define and employ heuristics as well as algorithmic rules to conceptualize data produced by normal and faulty jet engine behavior examples. These rules were employed in developing the machine learning system (MLS). The input to MLS is examples which contain data of normal and faulty engine behavior and which are obtained from an engine simulation program. MLS first transforms the data into discrete selectors. Partial descriptions formed by those selectors are then generalized or specialized to generate concept descriptions about faults. The concepts are represented in the form of characteristic and discriminant descriptions, which are stored in the knowledge base and are employed to diagnose faults. MLS was successfully tested on jet engine examples.

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.

Realizing Relevance: The Influence of Domain-Specific Information on Generation of New Knowledge through Integration in 4- to 8-Year-Old Children

ERIC Educational Resources Information Center

Bauer, Patricia J.; Larkina, Marina

2017-01-01

In accumulating knowledge, direct modes of learning are complemented by productive processes, including self-generation based on integration of separate episodes. Effects of the number of potentially relevant episodes on integration were examined in 4- to 8-year-olds (N = 121; racially/ethnically heterogeneous sample, English speakers, from large…

Children's Comprehension of Object Relative Sentences: It's Extant Language Knowledge That Matters, Not Domain-General Working Memory

ERIC Educational Resources Information Center

Rusli, Yazmin Ahmad; Montgomery, James W.

2017-01-01

Purpose: The aim of this study was to determine whether extant language (lexical) knowledge or domain-general working memory is the better predictor of comprehension of object relative sentences for children with typical development. We hypothesized that extant language knowledge, not domain-general working memory, is the better predictor. Method:…

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

PubMed

Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A

1995-06-01

PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.

Representing Human Expertise by the OWL Web Ontology Language to Support Knowledge Engineering in Decision Support Systems.

PubMed

Ramzan, Asia; Wang, Hai; Buckingham, Christopher

2014-01-01

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Knowledge Distance, Cognitive-Search Processes, and Creativity

PubMed Central

Acar, Oguz Ali; van den Ende, Jan

2016-01-01

Prior research has provided conflicting arguments and evidence about whether people who are outsiders or insiders relative to a knowledge domain are more likely to demonstrate scientific creativity in that particular domain. We propose that the nature of the relationship between creativity and the distance of an individual’s expertise from a knowledge domain depends on his or her cognitive processes of problem solving (i.e., cognitive-search effort and cognitive-search variation). In an analysis of 230 solutions generated in a science contest platform, we found that distance was positively associated with creativity when problem solvers engaged in a focused search (i.e., low cognitive-search variation) and exerted a high level of cognitive effort. People whose expertise was close to a knowledge domain, however, were more likely to demonstrate creativity in that domain when they drew on a wide variety of different knowledge elements for recombination (i.e., high cognitive-search variation) and exerted substantial cognitive effort. PMID:27016241

Knowledge Distance, Cognitive-Search Processes, and Creativity: The Making of Winning Solutions in Science Contests.

PubMed

Acar, Oguz Ali; van den Ende, Jan

2016-05-01

Prior research has provided conflicting arguments and evidence about whether people who are outsiders or insiders relative to a knowledge domain are more likely to demonstrate scientific creativity in that particular domain. We propose that the nature of the relationship between creativity and the distance of an individual's expertise from a knowledge domain depends on his or her cognitive processes of problem solving (i.e., cognitive-search effort and cognitive-search variation). In an analysis of 230 solutions generated in a science contest platform, we found that distance was positively associated with creativity when problem solvers engaged in a focused search (i.e., low cognitive-search variation) and exerted a high level of cognitive effort. People whose expertise was close to a knowledge domain, however, were more likely to demonstrate creativity in that domain when they drew on a wide variety of different knowledge elements for recombination (i.e., high cognitive-search variation) and exerted substantial cognitive effort. © The Author(s) 2016.

HCV knowledge among a sample of HCV positive Aboriginal Australians residing in New South Wales.

PubMed

Wilson, Hannah; Brener, Loren; Jackson, L Clair; Saunders, Veronica; Johnson, Priscilla; Treloar, Carla

2017-06-01

Australian Aboriginal and Torres Strait Islanders are overrepresented in both the prevalence and incidence of the hepatitis C (HCV). HCV knowledge has been associated with a range of positive health behaviours. HCV knowledge has previously been investigated as a single construct; however examining different knowledge domains (i.e. transmission, risk of complications, testing and treatment) separately may be beneficial. This study investigated whether having greater HCV knowledge in different domains is associated with self-reported positive health behaviours. 203 Aboriginal people living with HCV completed a survey assessing HCV knowledge, testing and care, lifestyle changes since diagnosis and treatment intent. Respondents' knowledge was relatively high. Greater knowledge of risk of health complications was associated with undertaking more positive lifestyle changes since diagnosis. Respondents testing and treatment knowledge was significantly associated with incarceration, lifestyle changes since diagnosis and future treatment intentions. This study illustrates the importance of ensuring that knowledge is high across different HCV domains to optimise a range of positive health behaviours of Aboriginal people living with HCV. Future health promotion campaigns targeted at Aboriginal people living with HCV could benefit from broadening their focus from prevention to other domains such as testing and treatment.

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

Generic domain models in software engineering

NASA Technical Reports Server (NTRS)

Maiden, Neil

1992-01-01

This paper outlines three research directions related to domain-specific software development: (1) reuse of generic models for domain-specific software development; (2) empirical evidence to determine these generic models, namely elicitation of mental knowledge schema possessed by expert software developers; and (3) exploitation of generic domain models to assist modelling of specific applications. It focuses on knowledge acquisition for domain-specific software development, with emphasis on tool support for the most important phases of software development.

ASIST SIG/CR Classification Workshop 2000: Classification for User Support and Learning.

ERIC Educational Resources Information Center

Soergel, Dagobert

2001-01-01

Reports on papers presented at the 62nd Annual Meeting of ASIST (American Society for Information Science and Technology) for the Special Interest Group in Classification Research (SIG/CR). Topics include types of knowledge; developing user-oriented classifications, including domain analysis; classification in the user interface; and automatic…

Investigating Effects of Embedding Collaboration in an Intelligent Tutoring System for Elementary School Students

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent

2016-01-01

Intelligent Tutoring Systems (ITSs) are beneficial for individual students learning in several domains, including mathematics where they have been used to support both secondary and elementary students. Collaborative learning may be beneficial to include in ITSs, particularly for conceptual knowledge. There is little work on collaborative ITSs,…

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.

Segmentation of medical images using explicit anatomical knowledge

NASA Astrophysics Data System (ADS)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

Evaluation of knowledge regarding gestational diabetes mellitus and its association with glycaemic level: A Malaysian study.

PubMed

Hussain, Zahid; Yusoff, Zuraidah Mohd; Sulaiman, Syed Azhar Syed

2015-06-01

The aim of this study was to evaluate the knowledge about GDM and its corresponding relation with glycaemic level in GDM patients. A cross-sectional study was conducted in antenatal clinic of Hospital Pulau Pinang, Malaysia from June 2013 to December 2013 using Gestational Diabetes Mellitus Knowledge Questionnaire (GDMKQ) on the sample of 175 GDM patients. Three most recent fasting plasma glucose (FPG) values (mmol/l) were taken from patients profiles and mean was calculated. A total of 166 patients were included in final analysis. A total mean knowledge score of 166 patients was 10.01±3.63 and total mean FPG value was 5.50±1.13. Knowledge had a significant negative association with FPG (r=- 0.306, P<0.01). Among different knowledge domains, highest mean score was seen for diet/food values domain and lowest for management of GDM. Educational level seems to be the most significant predictor of GDM knowledge and glycaemic control. Highest mean knowledge score and lowest mean glycaemic levels were recorded for patients aged 25-29 years, Malay ethnicity, working women and family history of DM. Higher Knowledge about GDM is related to better glycaemic control. New educational strategies should be developed to improve the lower health literacy. Copyright © 2014 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

[Bibliometric analysis of current glaucoma research based on Pubmed database].

PubMed

Huang, Wen-bin; Wang, Wei; Zhou, Min-wen; Chen, Shi-da; Zhang, Xiu-lan

2013-11-01

To survey the distribution pattern and subject domain knowledge of worldwide glaucoma research based on literatures in Pubmed database. Literatures on glaucoma published in 2007 to 2011 were identified in Pubmed database. The analytic items of an article include published year, country, language author, and journal. After core mesh terms had been characterized by BICOMS, the co-occurrence matrix was built. Cluster analysis was finished by SPSS 20.0. Then visualized network was drawn using ucinet 6.0. Totally 6427 literatures were included, the number of annual articles changed slightly between 2007 and 2011. The United States, England, Germany, Australia, and France together accounted for 77.63% of articles. There were 52 high-frequency subjects and hot topics were clustered into the following 10 categories: (1) Pathology of optic disc and nerve fibers and OCT application, (2) METHODS: of visual field (VF) and visual function examination, (3) Glaucoma drug medications, (4) Pathology and physiology of primary open angle glaucoma (POAG) including VF and intraocular pressure (IOP), (5) Glaucoma surgery, (6) Gene research related to POAG, (7) Glaucoma disease pathology and animal models, (8) Ocular hypertension (OHT) induced complications and corneal changes, (9) Etiology of congenital glaucoma and complications, (10) Etiology and epidemiology of glaucoma. The visualized domain knowledge mapping was successfully built. The pathology of optic disc and nerve fibers, medications, and surgery were well developed. Study on IOP and visual field was in the core domain, which have an important link to etiology, diagnosis, and therapy. The researches on glaucomatous gene, disease pathology model, congenital glaucoma, etiology and epidemiology were not developed well, which are of great promotion space. The distribution pattern and subject domain knowledge of worldwide glaucoma research in the recent five years were shown by using bibliometric analysis.Western developed countries play a leading role in the field of glaucoma research, the international influence of related research in China needs to be strengthened.

The process-knowledge model of health literacy: evidence from a componential analysis of two commonly used measures.

PubMed

Chin, Jessie; Morrow, Daniel G; Stine-Morrow, Elizabeth A L; Conner-Garcia, Thembi; Graumlich, James F; Murray, Michael D

2011-01-01

We investigated the effects of domain-general processing capacity (fluid ability such as working memory), domain-general knowledge (crystallized ability such as vocabulary), and domain-specific health knowledge for two of the most commonly used measures of health literacy (S-TOFHLA and REALM). One hundred forty six community-dwelling older adults participated; 103 had been diagnosed with hypertension. The results showed that older adults who had higher levels of processing capacity or knowledge (domain-general or health) performed better on both of the health literacy measures. Processing capacity interacted with knowledge: Processing capacity had a lower level of association with health literacy for participants with more knowledge than for those with lower levels of knowledge, suggesting that knowledge may offset the effects of processing capacity limitations on health literacy. Furthermore, performance on the two health literacy measures appeared to reflect a different weighting for the three types of abilities. S-TOFHLA performance reflected processing capacity as well as general knowledge, whereas performance on the REALM depended more on general and health knowledge than on processing capacity. The findings support a process-knowledge model of health literacy among older adults, and have implications for selecting health literacy measures in various health care contexts.

Research Prototype: Automated Analysis of Scientific and Engineering Semantics

NASA Technical Reports Server (NTRS)

Stewart, Mark E. M.; Follen, Greg (Technical Monitor)

2001-01-01

Physical and mathematical formulae and concepts are fundamental elements of scientific and engineering software. These classical equations and methods are time tested, universally accepted, and relatively unambiguous. The existence of this classical ontology suggests an ideal problem for automated comprehension. This problem is further motivated by the pervasive use of scientific code and high code development costs. To investigate code comprehension in this classical knowledge domain, a research prototype has been developed. The prototype incorporates scientific domain knowledge to recognize code properties (including units, physical, and mathematical quantity). Also, the procedure implements programming language semantics to propagate these properties through the code. This prototype's ability to elucidate code and detect errors will be demonstrated with state of the art scientific codes.

The Development and Validation of the Osteoporosis Prevention and Awareness Tool (OPAAT) in Malaysia

PubMed Central

Wong, Kok Thong; Low, Bee Yean

2015-01-01

Objectives To develop and validate Osteoporosis Prevention and Awareness Tool (OPAAT) in Malaysia. Methods The OPAAT was modified from the Malaysian Osteoporosis Knowledge Tool and developed from an exploratory study on patients. Face and content validity was established by an expert panel. The OPAAT consists of 30 items, categorized into three domains. A higher score indicates higher knowledge level. English speaking non-osteoporotic postmenopausal women ≥50 years of age and pharmacists were included in the study. Results A total of 203 patients and 31 pharmacists were recruited. Factor analysis extracted three domains. Flesch reading ease was 59.2. The mean±SD accuracy rate was 0.60±0.22 (range: 0.26-0.94). The Cronbach’s α for each domain ranged from 0.286-0.748. All items were highly correlated (Spearman’s rho: 0.761-0.990, p<0.05), with no significant change in the overall test-retest scores, indicating that OPAAT has achieved stable reliability. Pharmacists had higher knowledge score than patients (80.9±8.7vs63.6±17.4, p<0.001), indicating that the OPAAT was able to discriminate between the knowledge levels of pharmacists and patients. Conclusion The OPAAT was found to be a valid and reliable instrument for assessing patient’s knowledge about osteoporosis and its prevention in Malaysia. The OPAAT can be used to identify individuals in need of osteoporosis educational intervention. PMID:25938494

Expertise in Problem Solving.

ERIC Educational Resources Information Center

Chi, Michelene T. H.; And Others

Based on the premise that the quality of domain-specific knowledge is the main determinant of expertise in that domain, an examination was made of the shift from considering general, domain-independent skills and procedures, in both cognitive psychology and artificial intelligence, to the study of the knowledge base. Empirical findings and…

A feature dictionary supporting a multi-domain medical knowledge base.

PubMed

Naeymi-Rad, F

1989-01-01

Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

U.S. Spacesuit Knowledge Capture Accomplishments in Fiscal Years 2012 and 2013

NASA Technical Reports Server (NTRS)

Chullen, Cinda; Oliva, Vladenka R.

2014-01-01

The NASA U.S. Spacesuit Knowledge Capture (KC) program has existed since the beginning of 2008. The program was designed to augment engineers and other technical team members with historical spacesuit information to add to their understanding of the spacesuit, its evolution, its limitations, and its capabilities. Over 40 seminars have captured spacesuit history and knowledge over the last six years of the program's existence. Subject matter experts have provided lectures and some were interviewed to help bring the spacesuit to life so that lessons learned will never be lost. As well, the program concentrated in reaching out to the public and industry by making the recorded events part of the public domain through the NASA technical library through YouTube media. The U.S. Spacesuit KC topics have included lessons learned from some of the most prominent spacesuit experts and spacesuit users including current and former astronauts. The events have enriched the spacesuit legacy knowledge from Gemini, Apollo, Skylab, Space Shuttle and International Space Station Programs. As well, expert engineers and scientists have shared their challenges and successes to be remembered. Based on evidence by the thousands of people who have viewed the recordings online, the last few years have been some of the most successful years of the KC program's life with numerous digital recordings and public releases. This paper reviews the events accomplished and archived over Fiscal Years 2012 and 2013 and highlights a few of the most memorable ones. This paper also communicates ways to access the events that are available internally on the NASA domain as well as those released on the public domain.

A systematic map of systematic reviews in pediatric dentistry--what do we really know?

PubMed

Mejàre, Ingegerd A; Klingberg, Gunilla; Mowafi, Frida K; Stecksén-Blicks, Christina; Twetman, Svante H A; Tranæus, Sofia H

2015-01-01

To identify, appraise and summarize existing knowledge and knowledge gaps in practice-relevant questions in pediatric dentistry. A systematic mapping of systematic reviews was undertaken for domains considered important in daily clinical practice. The literature search covered questions in the following domains: behavior management problems/dental anxiety; caries risk assessment and caries detection including radiographic technologies; prevention and non-operative treatment of caries in primary and young permanent teeth; operative treatment of caries in primary and young permanent teeth; prevention and treatment of periodontal disease; management of tooth developmental and mineralization disturbances; prevention and treatment of oral conditions in children with chronic diseases/developmental disturbances/obesity; diagnosis, prevention and treatment of dental erosion and tooth wear; treatment of traumatic injuries in primary and young permanent teeth and cost-effectiveness of these interventions. Abstracts and full text reviews were assessed independently by two reviewers and any differences were solved by consensus. AMSTAR was used to assess the risk of bias of each included systematic review. Reviews judged as having a low or moderate risk of bias were used to formulate existing knowledge and knowledge gaps. Out of 81 systematic reviews meeting the inclusion criteria, 38 were judged to have a low or moderate risk of bias. Half of them concerned caries prevention. The quality of evidence was high for a caries-preventive effect of daily use of fluoride toothpaste and moderate for fissure sealing with resin-based materials. For the rest the quality of evidence for the effects of interventions was low or very low. There is an urgent need for primary clinical research of good quality in most clinically-relevant domains in pediatric dentistry.

A Systematic Map of Systematic Reviews in Pediatric Dentistry—What Do We Really Know?

PubMed Central

Mejàre, Ingegerd A.; Klingberg, Gunilla; Mowafi, Frida K.; Stecksén-Blicks, Christina; Twetman, Svante H. A.; Tranæus, Sofia H.

2015-01-01

Objectives To identify, appraise and summarize existing knowledge and knowledge gaps in practice-relevant questions in pediatric dentistry. Methods A systematic mapping of systematic reviews was undertaken for domains considered important in daily clinical practice. The literature search covered questions in the following domains: behavior management problems/dental anxiety; caries risk assessment and caries detection including radiographic technologies; prevention and non-operative treatment of caries in primary and young permanent teeth; operative treatment of caries in primary and young permanent teeth; prevention and treatment of periodontal disease; management of tooth developmental and mineralization disturbances; prevention and treatment of oral conditions in children with chronic diseases/developmental disturbances/obesity; diagnosis, prevention and treatment of dental erosion and tooth wear; treatment of traumatic injuries in primary and young permanent teeth and cost-effectiveness of these interventions. Abstracts and full text reviews were assessed independently by two reviewers and any differences were solved by consensus. AMSTAR was used to assess the risk of bias of each included systematic review. Reviews judged as having a low or moderate risk of bias were used to formulate existing knowledge and knowledge gaps. Results Out of 81 systematic reviews meeting the inclusion criteria, 38 were judged to have a low or moderate risk of bias. Half of them concerned caries prevention. The quality of evidence was high for a caries-preventive effect of daily use of fluoride toothpaste and moderate for fissure sealing with resin-based materials. For the rest the quality of evidence for the effects of interventions was low or very low. Conclusion There is an urgent need for primary clinical research of good quality in most clinically-relevant domains in pediatric dentistry. PMID:25706629

Behaviors and Knowledge of HealthCorps New York City High School Students: Nutrition, Mental Health and Physical Activity

PubMed Central

Moonseong, Heo; Erica, Irvin; Natania, Ostrovsky; Carmen, Isasi; Shawn, Hayes; Judith, Wylie-Rosett

2015-01-01

BACKGROUND HealthCorps provides school wellness programming using curricula to promote changes in nutrition, mental health and physical activity behaviors. The research objective was to evaluate effects of implementing its curricula on nutrition, mental health and physical activity knowledge and behavior. METHODS Pre- and post-survey data were collected (N = 2255) during the 2012-13 academic year from 14 New York City public high schools. An 18-item knowledge questionnaire addressed 3 domains; 26 behavioral items were analyzed by factor analysis to identify 6 behavior domains, breakfast being a seventh one-item domain. We examined the effects stratified by sex, applying mixed-effects models to take into account clustering effects of schools and participants adjusted for age. RESULTS The HealthCorps program significantly increased all 3 knowledge domains (p < .05), and significantly changed several key behavioral domains. Boys significantly increased fruits/vegetables intake (p = .03). Girls increased acceptance of new fruits/vegetables (p = .03) and breakfast consumption (p = .04), and decreased sugar-sweetened beverages and energy dense food intake (p = .03). The associations between knowledge and behavior were stronger in boys than girls. CONCLUSION The HealthCorps program significantly increased participants’ knowledge on nutrition, mental health and physical activity. It also improved several key behavioral domains, which are targets of the 2010 Dietary Guidelines to address obesity in youth. PMID:26762819

Behaviors and Knowledge of HealthCorps New York City High School Students: Nutrition, Mental Health, and Physical Activity.

PubMed

Heo, Moonseong; Irvin, Erica; Ostrovsky, Natania; Isasi, Carmen; Blank, Arthur E; Lounsbury, David W; Fredericks, Lynn; Yom, Tiana; Ginsberg, Mindy; Hayes, Shawn; Wylie-Rosett, Judith

2016-02-01

HealthCorps provides school wellness programming using curricula to promote changes in nutrition, mental health, and physical activity behaviors. The research objective was to evaluate effects of implementing its curricula on nutrition, mental health, and physical activity knowledge and behavior. Pre- and postsurvey data were collected (N = 2255) during the 2012-2013 academic year from 14 New York City public high schools. An 18-item knowledge questionnaire addressed 3 domains; 26 behavioral items were analyzed by factor analysis to identify 6 behavior domains, breakfast being a seventh 1-item domain. We examined the effects stratified by sex, applying mixed-effects models to take into account clustering effects of schools and participants adjusted for age. The HealthCorps program significantly increased all 3 knowledge domains (p < .05), and significantly changed several key behavioral domains. Boys significantly increased fruits/vegetables intake (p = .03). Girls increased acceptance of new fruits/vegetables (p = .03) and breakfast consumption (p = .04), and decreased sugar-sweetened beverages and energy dense food intake (p = .03). The associations between knowledge and behavior were stronger in boys than girls. The HealthCorps program significantly increased participants' knowledge on nutrition, mental health, and physical activity. It also improved several key behavioral domains, which are targets of the 2010 Dietary Guidelines to address obesity in youth. © 2016, American School Health Association.

Children's Comprehension of Object Relative Sentences: It's Extant Language Knowledge That Matters, Not Domain-General Working Memory.

PubMed

Rusli, Yazmin Ahmad; Montgomery, James W

2017-10-17

The aim of this study was to determine whether extant language (lexical) knowledge or domain-general working memory is the better predictor of comprehension of object relative sentences for children with typical development. We hypothesized that extant language knowledge, not domain-general working memory, is the better predictor. Fifty-three children (ages 9-11 years) completed a word-level verbal working-memory task, indexing extant language (lexical) knowledge; an analog nonverbal working-memory task, representing domain-general working memory; and a hybrid sentence comprehension task incorporating elements of both agent selection and cross-modal picture-priming paradigms. Images of the agent and patient were displayed at the syntactic gap in the object relative sentences, and the children were asked to select the agent of the sentence. Results of general linear modeling revealed that extant language knowledge accounted for a unique 21.3% of variance in the children's object relative sentence comprehension over and above age (8.3%). Domain-general working memory accounted for a nonsignificant 1.6% of variance. We interpret the results to suggest that extant language knowledge and not domain-general working memory is a critically important contributor to children's object relative sentence comprehension. Results support a connectionist view of the association between working memory and object relative sentence comprehension. https://doi.org/10.23641/asha.5404573.

NED-IIS: An Intelligent Information System for Forest Ecosystem Management

Treesearch

W.D. Potter; S. Somasekar; R. Kommineni; H.M. Rauscher

1999-01-01

We view Intelligent Information System (IIS) as composed of a unified knowledge base, database, and model base. The model base includes decision support models, forecasting models, and cvsualization models for example. In addition, we feel that the model base should include domain specific porblems solving modules as well as decision support models. This, then,...

Application of a Multimedia Service and Resource Management Architecture for Fault Diagnosis

PubMed Central

Castro, Alfonso; Sedano, Andrés A.; García, Fco. Javier; Villoslada, Eduardo

2017-01-01

Nowadays, the complexity of global video products has substantially increased. They are composed of several associated services whose functionalities need to adapt across heterogeneous networks with different technologies and administrative domains. Each of these domains has different operational procedures; therefore, the comprehensive management of multi-domain services presents serious challenges. This paper discusses an approach to service management linking fault diagnosis system and Business Processes for Telefónica’s global video service. The main contribution of this paper is the proposal of an extended service management architecture based on Multi Agent Systems able to integrate the fault diagnosis with other different service management functionalities. This architecture includes a distributed set of agents able to coordinate their actions under the umbrella of a Shared Knowledge Plane, inferring and sharing their knowledge with semantic techniques and three types of automatic reasoning: heterogeneous, ontology-based and Bayesian reasoning. This proposal has been deployed and validated in a real scenario in the video service offered by Telefónica Latam. PMID:29283398

Application of a Multimedia Service and Resource Management Architecture for Fault Diagnosis.

PubMed

Castro, Alfonso; Sedano, Andrés A; García, Fco Javier; Villoslada, Eduardo; Villagrá, Víctor A

2017-12-28

Nowadays, the complexity of global video products has substantially increased. They are composed of several associated services whose functionalities need to adapt across heterogeneous networks with different technologies and administrative domains. Each of these domains has different operational procedures; therefore, the comprehensive management of multi-domain services presents serious challenges. This paper discusses an approach to service management linking fault diagnosis system and Business Processes for Telefónica's global video service. The main contribution of this paper is the proposal of an extended service management architecture based on Multi Agent Systems able to integrate the fault diagnosis with other different service management functionalities. This architecture includes a distributed set of agents able to coordinate their actions under the umbrella of a Shared Knowledge Plane, inferring and sharing their knowledge with semantic techniques and three types of automatic reasoning: heterogeneous, ontology-based and Bayesian reasoning. This proposal has been deployed and validated in a real scenario in the video service offered by Telefónica Latam.

Knowledge Interaction Design for Creative Knowledge Work

NASA Astrophysics Data System (ADS)

Nakakoji, Kumiyo; Yamamoto, Yasuhiro

This paper describes our approach for the development of application systems for creative knowledge work, particularly for early stages of information design tasks. Being a cognitive tool serving as a means of externalization, an application system affects how the user is engaged in the creative process through its visual interaction design. Knowledge interaction design described in this paper is a framework where a set of application systems for different information design domains are developed based on an interaction model, which is designed for a particular model of a thinking process. We have developed two sets of application systems using the knowledge interaction design framework: one includes systems for linear information design, such as writing, movie-editing, and video-analysis; the other includes systems for network information design, such as file-system navigation and hypertext authoring. Our experience shows that the resulting systems encourage users to follow a certain cognitive path through graceful user experience.

Thoughts on Expertise.

ERIC Educational Resources Information Center

Glaser, Robert

This paper briefly reviews research on tasks in knowledge-rich domains including developmental studies, work in artificial intelligence, studies of expert/novice problem solving, and information processing analysis of aptitude test tasks that have provided increased understanding of the nature of expertise. Particularly evident is the finding that…

Complexities of Teaching and Implications for Equity

ERIC Educational Resources Information Center

Lee, Carol D.

2011-01-01

Teacher knowledge involves a complex network of inter-related domains, including cognition; differences in learning strengths for primary and secondary school students; social and emotional development across the life course; motivation; language acquisition and socialization; curriculum design and assessment; and classroom management. In…

Helping Students Use Virtual Libraries Effectively.

ERIC Educational Resources Information Center

Fitzgerald, Mary Ann; Galloway, Chad

2001-01-01

Describes a study in which online behavior of high school and undergraduate students using GALILEO (Georgia Library Learning Online), a virtual library, were observed. Topics include cognitive demands; technology literacy; domain knowledge; search strategies; relevance; evaluation of information; information literacy standards; and suggestions to…

Predicting Children's Reading and Mathematics Achievement from Early Quantitative Knowledge and Domain-General Cognitive Abilities

PubMed Central

Chu, Felicia W.; vanMarle, Kristy; Geary, David C.

2016-01-01

One hundred children (44 boys) participated in a 3-year longitudinal study of the development of basic quantitative competencies and the relation between these competencies and later mathematics and reading achievement. The children's preliteracy knowledge, intelligence, executive functions, and parental educational background were also assessed. The quantitative tasks assessed a broad range of symbolic and nonsymbolic knowledge and were administered four times across 2 years of preschool. Mathematics achievement was assessed at the end of each of 2 years of preschool, and mathematics and word reading achievement were assessed at the end of kindergarten. Our goals were to determine how domain-general abilities contribute to growth in children's quantitative knowledge and to determine how domain-general and domain-specific abilities contribute to children's preschool mathematics achievement and kindergarten mathematics and reading achievement. We first identified four core quantitative competencies (e.g., knowledge of the cardinal value of number words) that predict later mathematics achievement. The domain-general abilities were then used to predict growth in these competencies across 2 years of preschool, and the combination of domain-general abilities, preliteracy skills, and core quantitative competencies were used to predict mathematics achievement across preschool and mathematics and word reading achievement at the end of kindergarten. Both intelligence and executive functions predicted growth in the four quantitative competencies, especially across the first year of preschool. A combination of domain-general and domain-specific competencies predicted preschoolers' mathematics achievement, with a trend for domain-specific skills to be more strongly related to achievement at the beginning of preschool than at the end of preschool. Preschool preliteracy skills, sensitivity to the relative quantities of collections of objects, and cardinal knowledge predicted reading and mathematics achievement at the end of kindergarten. Preliteracy skills were more strongly related to word reading, whereas sensitivity to relative quantity was more strongly related to mathematics achievement. The overall results indicate that a combination of domain-general and domain-specific abilities contribute to development of children's early mathematics and reading achievement. PMID:27252675

Predicting Children's Reading and Mathematics Achievement from Early Quantitative Knowledge and Domain-General Cognitive Abilities.

PubMed

Chu, Felicia W; vanMarle, Kristy; Geary, David C

2016-01-01

One hundred children (44 boys) participated in a 3-year longitudinal study of the development of basic quantitative competencies and the relation between these competencies and later mathematics and reading achievement. The children's preliteracy knowledge, intelligence, executive functions, and parental educational background were also assessed. The quantitative tasks assessed a broad range of symbolic and nonsymbolic knowledge and were administered four times across 2 years of preschool. Mathematics achievement was assessed at the end of each of 2 years of preschool, and mathematics and word reading achievement were assessed at the end of kindergarten. Our goals were to determine how domain-general abilities contribute to growth in children's quantitative knowledge and to determine how domain-general and domain-specific abilities contribute to children's preschool mathematics achievement and kindergarten mathematics and reading achievement. We first identified four core quantitative competencies (e.g., knowledge of the cardinal value of number words) that predict later mathematics achievement. The domain-general abilities were then used to predict growth in these competencies across 2 years of preschool, and the combination of domain-general abilities, preliteracy skills, and core quantitative competencies were used to predict mathematics achievement across preschool and mathematics and word reading achievement at the end of kindergarten. Both intelligence and executive functions predicted growth in the four quantitative competencies, especially across the first year of preschool. A combination of domain-general and domain-specific competencies predicted preschoolers' mathematics achievement, with a trend for domain-specific skills to be more strongly related to achievement at the beginning of preschool than at the end of preschool. Preschool preliteracy skills, sensitivity to the relative quantities of collections of objects, and cardinal knowledge predicted reading and mathematics achievement at the end of kindergarten. Preliteracy skills were more strongly related to word reading, whereas sensitivity to relative quantity was more strongly related to mathematics achievement. The overall results indicate that a combination of domain-general and domain-specific abilities contribute to development of children's early mathematics and reading achievement.

A Short Note on Rules and Higher Order Rules.

ERIC Educational Resources Information Center

Scandura, Joseph M.

This brief paper argues that structural analysis--an extended form of cognitive task analysis--demonstrates that both domain dependent and domain independent knowledge can be derived from specific content domains. It is noted that the major difference between the two is that lower order rules (specific knowledge) are derived directly from specific…

Examining the Domain-Specificity of Metacognition Using Academic Domains and Task-Specific Individual Differences

ERIC Educational Resources Information Center

Scott, Brianna M.; Berman, Ashleigh F.

2013-01-01

Metacognition refers to students' knowledge and regulation of cognition, as well as their accuracy in predicting their academic performance. This study addressed two major questions: 1) how do metacognitive knowledge, regulation and accuracy differ across domains?, and 2) how do students' individual differences relate to their reported…

The Influence of Domain Knowledge on the Functional Capacity of Working Memory

ERIC Educational Resources Information Center

Ricks, Travis Rex; Wiley, Jennifer

2009-01-01

Theories of expertise have proposed that superior cognitive performance is in part due to increases in the functional capacity of working memory during domain-related tasks. Consistent with this approach Fincher-Kiefer et al. (1988), found that domain knowledge increased scores on baseball-related reading span tasks. The present studies extended…

The study of co-citation analysis and knowledge structure on healthcare domain

NASA Astrophysics Data System (ADS)

Chu, Kuo-Chung; Liu, Wen-I.; Tsai, Ming-Yu

2012-11-01

With the prevalence of Internet and digital archives, the online e-journal database facilitates scholars to search literature in a research domain, or to cross-search an inter-disciplined field; the key literature can be efficiently traced out. This study intends to build a Web-based citation analysis system, which consists of four modules, they are: 1) literature search module; (2) statistics module; (3) articles analysis module; and (4) co-citation analysis module. The system focuses on PubMed Central dataset that has 170,000 records. In a research domain, a specific keyword searches in terms of authors, journals, and core issues. In addition, we use data mining techniques for co-citation analysis. The results assist researchers with in-depth understanding of the domain knowledge. Having an automated system for co-citation analysis, it helps to understand changes, trends, and knowledge structure of research domain. For the best of our knowledge, the proposed system differentiates from existing online electronic retrieval database analysis function. Perhaps, the proposed system is going to be a value-added database of healthcare domain, and hope to contribute the researchers.

The identification of knowledge content and function in manual labour.

PubMed

Shalin, Valerie; Verdile, Charles

2003-06-10

Calls for an alternative conceptualization of cognition for applied concerns retain the core commitment of the basic research community to abstract cognition detached from a physical environment. The present paper attempts to break out of the dominant, narrow view of cognition and cognitive domains, with a cognitive analysis of digging ditches for the utility industry. To illustrate knowledge-based cognition in manual labour excerpts are presented from the journal entries of a moderately experienced student working a summer job, organized with a representation that distinguishes between the goals and methods of work. The journal entries illustrate the functions of knowledge for interacting with a physical environment; knowledge enables the selection, execution and monitoring of work methods, the interpretation of perceptual information, the application of task completion criteria and the ability for explanation and generalization. To emphasize the generality of the functions of cognition in ditch digging, comparable functions are indicated in a domain rarely regarded as a form of manual labour: the practice of internal medicine. Discussion of the results includes the implications for cognitive theory as well as practical implications for productivity, training and task analysis.

Domain-Specific Knowledge and General Skills in Reading Comprehension.

ERIC Educational Resources Information Center

Kuhara-Kojima, Keiko; Hatano, Giyoo

A study examined whether the reading comprehension of students with rich domain-specific knowledge will be better than that of students without it and whether assessed general skills will be correlated significantly with reading comprehension performance for students without specific knowledge, but negligible for the students with much specific…

Structural and functional aspects of the nonribosomal peptide synthetase condensation domain superfamily: discovery, dissection and diversity.

PubMed

Bloudoff, Kristjan; Schmeing, T Martin

2017-11-01

Nonribosomal peptide synthetases (NRPSs) are incredible macromolecular machines that produce a wide range of biologically- and therapeutically-relevant molecules. During synthesis, peptide elongation is performed by the condensation (C) domain, as it catalyzes amide bond formation between the nascent peptide and the amino acid it adds to the chain. Since their discovery more than two decades ago, C domains have been subject to extensive biochemical, bioinformatic, mutagenic, and structural analyses. They are composed of two lobes, each with homology to chloramphenicol acetyltransferase, have two binding sites for their two peptidyl carrier protein-bound ligands, and have an active site with conserved motif HHxxxDG located between the two lobes. This review discusses some of the important insights into the structure, catalytic mechanism, specificity, and gatekeeping functions of C domains revealed since their discovery. In addition, C domains are the archetypal members of the C domain superfamily, which includes several other members that also function as NRPS domains. The other family members can replace the C domain in NRP synthesis, can work in concert with a C domain, or can fulfill diverse and novel functions. These domains include the epimerization (E) domain, the heterocyclization (Cy) domain, the ester-bond forming C domain, the fungal NRPS terminal C domain (C T ), the β-lactam ring forming C domain, and the X domain. We also discuss structural and function insight into C, E, Cy, C T and X domains, to present a holistic overview of historical and current knowledge of the C domain superfamily. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Current-events knowledge in adults: an investigation of age, intelligence, and nonability determinants.

PubMed

Beier, M E; Ackerman, P L

2001-12-01

This study expanded the scope of knowledge typically included in intellectual assessment to incorporate domains of current-events knowledge from the 1930s to the 1990s across the areas of art/humanities, politics/economics, popular culture, and nature/science/technology. Results indicated that age of participants was significantly and positively related to knowledge about current events. Moreover, fluid intelligence was a less effective predictor of knowledge levels than was crystallized intelligence. Personality (i.e. Openness to Experience) and self-concept were also positively related to current-events knowledge. The results are consistent with an investment theory of adult intellect, which views development as an ongoing outcome of the combined influences of intelligence-as-process, personality, and interests, leading to intelligence-as-knowledge (P. L. Ackerman, 1996b).

Memory and Comprehension for Health Information among Older Adults: Distinguishing the Effects of Domain-General and Domain-Specific Knowledge

PubMed Central

Chin, Jessie; Payne, Brennan; Gao, Xuefei; Conner-Garcia, Thembi; Graumlich, James F.; Murray, Michael D.; Morrow, Daniel G.; Stine-Morrow, Elizabeth A.L.

2014-01-01

While there is evidence that knowledge influences understanding of health information, less is known about the processing mechanisms underlying this effect and its impact on memory. We used the moving window paradigm to examine how older adults varying in domain-general crystallized ability (verbal ability) and health knowledge allocate attention to understand health and domain-general texts. Participants (n=107, aged 60 to 88 yrs) read and recalled single sentences about hypertension and about non-health topics. Mixed-effects modeling of word-by-word reading times suggested that domain-general crystallized ability increased conceptual integration regardless of text domain, while health knowledge selectively increased resource allocation to conceptual integration at clause boundaries in health texts. These patterns of attentional allocation were related to subsequent recall performance. Although older adults with lower levels of crystallized ability were less likely to engage in integrative processing, when they did, this strategy had a compensatory effect in improving recall. These findings suggest that semantic integration during reading is an important comprehension process that supports the construction of the memory representation and is engendered by knowledge. Implications of the findings for theories of text processing and memory as well as for designing patient education materials are discussed. PMID:24787361

Memory and comprehension for health information among older adults: distinguishing the effects of domain-general and domain-specific knowledge.

PubMed

Chin, Jessie; Payne, Brennan; Gao, Xuefei; Conner-Garcia, Thembi; Graumlich, James F; Murray, Michael D; Morrow, Daniel G; Stine-Morrow, Elizabeth A L

2015-01-01

While there is evidence that knowledge influences understanding of health information, less is known about the processing mechanisms underlying this effect and its impact on memory. We used the moving window paradigm to examine how older adults varying in domain-general crystallised ability (verbal ability) and health knowledge allocate attention to understand health and domain-general texts. Participants (n = 107, age: 60-88 years) read and recalled single sentences about hypertension and about non-health topics. Mixed-effects modelling of word-by-word reading times suggested that domain-general crystallised ability increased conceptual integration regardless of text domain, while health knowledge selectively increased resource allocation to conceptual integration at clause boundaries in health texts. These patterns of attentional allocation were related to subsequent recall performance. Although older adults with lower levels of crystallised ability were less likely to engage in integrative processing, when they did, this strategy had a compensatory effect in improving recall. These findings suggest that semantic integration during reading is an important comprehension process that supports the construction of the memory representation and is engendered by knowledge. Implications of the findings for theories of text processing and memory as well as for designing patient education materials are discussed.

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.

Sentiment classification technology based on Markov logic networks

NASA Astrophysics Data System (ADS)

He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

2016-07-01

With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

Requirements and Solutions for Personalized Health Systems.

PubMed

Blobel, Bernd; Ruotsalainen, Pekka; Lopez, Diego M; Oemig, Frank

2017-01-01

Organizational, methodological and technological paradigm changes enable a precise, personalized, predictive, preventive and participative approach to health and social services supported by multiple actors from different domains at diverse level of knowledge and skills. Interoperability has to advance beyond Information and Communication Technologies (ICT) concerns, including the real world business domains and their processes, but also the individual context of all actors involved. The paper introduces and compares personalized health definitions, summarizes requirements and principles for pHealth systems, and considers intelligent interoperability. It addresses knowledge representation and harmonization, decision intelligence, and usability as crucial issues in pHealth. On this basis, a system-theoretical, ontology-based, policy-driven reference architecture model for open and intelligent pHealth ecosystems and its transformation into an appropriate ICT design and implementation is proposed.

The Transition to High School: Current Knowledge, Future Directions

PubMed Central

2011-01-01

In the American educational system, school transitions are frequent and predictable, but they can disrupt student functioning across developmental domains. How students experience school transitions has been a focus of research for some time, but the high school transition has received less attention, and the limited research often focuses on a particular developmental domain (e.g., academics and socioemotional well-being) to the exclusion of a more integrated model. This review relies on life course theory to establish an organizational framework for interpreting and connecting the diffuse and sometimes disparate findings on the high school transition, including adolescent developmental trajectories and the influence of social ties, changing sociocultural contexts, and stratification systems. Conclusions identify aspects for future inquiry suggested by current knowledge and the tenets of the life course perspective. PMID:21966178

Toward Knowledge Systems for Sustainability Science

NASA Astrophysics Data System (ADS)

Zaks, D. P.; Jahn, M.

2011-12-01

Managing ecosystems for the outcomes of agricultural productivity and resilience will require fundamentally different knowledge management systems. In the industrial paradigm of the 20th century, land was considered an open, unconstrained system managed for maximum yield. While dramatic increases in yield occurred in some crops and locations, unintended but often foreseeable consequences emerged. While productivity remains a key objective, we must develop analytic systems that can identify better management options for the full range of monetized and non-monetized inputs, outputs and outcomes that are captured in the following framing question: How much valued service (e.g. food, materials, energy) can we draw from a landscape while maintaining adequate levels of other valued or necessary services (e.g. biodiversity, water, climate regulation, cultural services) including the long-term productivity of the land? This question is placed within our contemporary framing of valued services, but structured to illuminate the shifts required to achieve long-term sufficiency and planetary resilience. This framing also highlights the need for fundamentally new knowledge systems including information management infrastructures, which effectively support decision-making on landscapes. The purpose of this initiative by authors from diverse fields across government and academic science is to call attention to the need for a vision and investment in sustainability science for landscape management. Substantially enhanced capabilities are needed to compare and integrate information from diverse sources, collected over time that link choices made to meet our needs from landscapes to both short and long term consequences. To further the goal of an information infrastructure for sustainability science, three distinct but interlocking domains are best distinguished: 1) a domain of data, information and knowledge assets; 2) a domain that houses relevant models and tools in a curated space; and 3) a domain that includes decision support tools and systems tailored toward frame particular trade-offs, which may focus on inputs or outputs and may range in scale from local to global. An information infrastructure for sustainability science is best built be built and maintained as a modular, open source, open standard, open access, open content platform. We have defined the scope of this challenge, managing choices within agroecosystems, recognizing that any decision on a landscape involves multidimensional tradeoffs. An effort to address this challenge will need a cohesive, coherent and targeted approach toward an integrated knowledge management infrastructure for sustainability science applied to land management is essential to move more rapidly toward sustainable, productive, and resilient landscapes.

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.

Exploring the knowledge behind predictions in everyday cognition: an iterated learning study.

PubMed

Stephens, Rachel G; Dunn, John C; Rao, Li-Lin; Li, Shu

2015-10-01

Making accurate predictions about events is an important but difficult task. Recent work suggests that people are adept at this task, making predictions that reflect surprisingly accurate knowledge of the distributions of real quantities. Across three experiments, we used an iterated learning procedure to explore the basis of this knowledge: to what extent is domain experience critical to accurate predictions and how accurate are people when faced with unfamiliar domains? In Experiment 1, two groups of participants, one resident in Australia, the other in China, predicted the values of quantities familiar to both (movie run-times), unfamiliar to both (the lengths of Pharaoh reigns), and familiar to one but unfamiliar to the other (cake baking durations and the lengths of Beijing bus routes). While predictions from both groups were reasonably accurate overall, predictions were inaccurate in the selectively unfamiliar domains and, surprisingly, predictions by the China-resident group were also inaccurate for a highly familiar domain: local bus route lengths. Focusing on bus routes, two follow-up experiments with Australia-resident groups clarified the knowledge and strategies that people draw upon, plus important determinants of accurate predictions. For unfamiliar domains, people appear to rely on extrapolating from (not simply directly applying) related knowledge. However, we show that people's predictions are subject to two sources of error: in the estimation of quantities in a familiar domain and extension to plausible values in an unfamiliar domain. We propose that the key to successful predictions is not simply domain experience itself, but explicit experience of relevant quantities.

CARDS: A blueprint and environment for domain-specific software reuse

NASA Technical Reports Server (NTRS)

Wallnau, Kurt C.; Solderitsch, Anne Costa; Smotherman, Catherine

1992-01-01

CARDS (Central Archive for Reusable Defense Software) exploits advances in domain analysis and domain modeling to identify, specify, develop, archive, retrieve, understand, and reuse domain-specific software components. An important element of CARDS is to provide visibility into the domain model artifacts produced by, and services provided by, commercial computer-aided software engineering (CASE) technology. The use of commercial CASE technology is important to provide rich, robust support for the varied roles involved in a reuse process. We refer to this kind of use of knowledge representation systems as supporting 'knowledge-based integration.'

Using a Foundational Ontology for Reengineering a Software Enterprise Ontology

NASA Astrophysics Data System (ADS)

Perini Barcellos, Monalessa; de Almeida Falbo, Ricardo

The knowledge about software organizations is considerably relevant to software engineers. The use of a common vocabulary for representing the useful knowledge about software organizations involved in software projects is important for several reasons, such as to support knowledge reuse and to allow communication and interoperability between tools. Domain ontologies can be used to define a common vocabulary for sharing and reuse of knowledge about some domain. Foundational ontologies can be used for evaluating and re-designing domain ontologies, giving to these real-world semantics. This paper presents an evaluating of a Software Enterprise Ontology that was reengineered using the Unified Foundation Ontology (UFO) as basis.

ASIST 2001. Information in a Networked World: Harnessing the Flow. Part III: Poster Presentations.

ERIC Educational Resources Information Center

Proceedings of the ASIST Annual Meeting, 2001

2001-01-01

Topics of Poster Presentations include: electronic preprints; intranets; poster session abstracts; metadata; information retrieval; watermark images; video games; distributed information retrieval; subject domain knowledge; data mining; information theory; course development; historians' use of pictorial images; information retrieval software;…

Proceedings of the Workshop on Change of Representation and Problem Reformulation

NASA Technical Reports Server (NTRS)

Lowry, Michael R.

1992-01-01

The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.

Knowledge representation for commonality

NASA Technical Reports Server (NTRS)

Yeager, Dorian P.

1990-01-01

Domain-specific knowledge necessary for commonality analysis falls into two general classes: commonality constraints and costing information. Notations for encoding such knowledge should be powerful and flexible and should appeal to the domain expert. The notations employed by the Commonality Analysis Problem Solver (CAPS) analysis tool are described. Examples are given to illustrate the main concepts.

Memetic Algorithms, Domain Knowledge, and Financial Investing

ERIC Educational Resources Information Center

Du, Jie

2012-01-01

While the question of how to use human knowledge to guide evolutionary search is long-recognized, much remains to be done to answer this question adequately. This dissertation aims to further answer this question by exploring the role of domain knowledge in evolutionary computation as applied to real-world, complex problems, such as financial…

Global Mental Health: sharing and synthesizing knowledge for sustainable development.

PubMed

O'Donnell, K; O'Donnell, M Lewis

2016-01-01

Global mental health (GMH) is a growing domain with an increasing capacity to positively impact the world community's efforts for sustainable development and wellbeing. Sharing and synthesizing GMH and multi-sectoral knowledge, the focus of this paper, is an important way to support these global efforts. This paper consolidates some of the most recent and relevant 'context resources' [global multi-sector (GMS) materials, emphasizing world reports on major issues] and 'core resources' (GMH materials, including newsletters, texts, conferences, training, etc.). In addition to offering a guided index of materials, it presents an orientation framework (global integration) to help make important information as accessible and useful as possible. Mental health colleagues are encouraged to stay current in GMH and global issues, to engage in the emerging agendas for sustainable development and wellbeing, and to intentionally connect and contribute across sectors. Colleagues in all sectors are encouraged to do likewise, and to take advantage of the wealth of shared and synthesized knowledge in the GMH domain, such as the materials featured in this paper.

Adaptation of Educational Text to an Open Interactive Learning System: A Case Study for ReTuDiS

ERIC Educational Resources Information Center

Samarakou, M.; Fylladitakis, E. D.; Tsaganou, G.; Gelegenis, J.; Karolidis, D.; Prentakis, P.

2013-01-01

Theoretical education is mainly based on university text-books, which usually include texts not structured according to any theory of text comprehension. Structuring a text is a demanding process. Text should be organized and structured in order to include descriptions on micro and macro-level representation of the knowledge domain. Since this is…

How scientific experiments are designed: Problem solving in a knowledge-rich, error-rich environment

NASA Astrophysics Data System (ADS)

Baker, Lisa M.

While theory formation and the relation between theory and data has been investigated in many studies of scientific reasoning, researchers have focused less attention on reasoning about experimental design, even though the experimental design process makes up a large part of real-world scientists' reasoning. The goal of this thesis was to provide a cognitive account of the scientific experimental design process by analyzing experimental design as problem-solving behavior (Newell & Simon, 1972). Three specific issues were addressed: the effect of potential error on experimental design strategies, the role of prior knowledge in experimental design, and the effect of characteristics of the space of alternate hypotheses on alternate hypothesis testing. A two-pronged in vivo/in vitro research methodology was employed, in which transcripts of real-world scientific laboratory meetings were analyzed as well as undergraduate science and non-science majors' design of biology experiments in the psychology laboratory. It was found that scientists use a specific strategy to deal with the possibility of error in experimental findings: they include "known" control conditions in their experimental designs both to determine whether error is occurring and to identify sources of error. The known controls strategy had not been reported in earlier studies with science-like tasks, in which participants' responses to error had consisted of replicating experiments and discounting results. With respect to prior knowledge: scientists and undergraduate students drew on several types of knowledge when designing experiments, including theoretical knowledge, domain-specific knowledge of experimental techniques, and domain-general knowledge of experimental design strategies. Finally, undergraduate science students generated and tested alternates to their favored hypotheses when the space of alternate hypotheses was constrained and searchable. This result may help explain findings of confirmation bias in earlier studies using science-like tasks, in which characteristics of the alternate hypothesis space may have made it unfeasible for participants to generate and test alternate hypotheses. In general, scientists and science undergraduates were found to engage in a systematic experimental design process that responded to salient features of the problem environment, including the constant potential for experimental error, availability of alternate hypotheses, and access to both theoretical knowledge and knowledge of experimental techniques.

Why older workers work beyond the retirement age: a qualitative study.

PubMed

Sewdas, Ranu; de Wind, Astrid; van der Zwaan, Lennart G L; van der Borg, Wieke E; Steenbeek, Romy; van der Beek, Allard J; Boot, Cécile R L

2017-08-22

The aims of the present study were to: 1) gain insight into reasons for working beyond the statutory retirement age from older workers' perspectives, and 2) explore how the domains of the research framework Study on Transitions in Employment, Ability and Motivation (STREAM) can be applied to working beyond retirement age. A qualitative research design included individual interviews (n = 15) and three focus groups (n = 18 participants) conducted with older workers aged 65 years and older continuing in a paid job or self-employment. Interview participants were recruited from an existing STREAM cohort study. Focus group participants were recruited from companies and employment agencies. The data were subjected to thematic analysis. The most important motives for working beyond retirement age were maintaining daily routines and financial benefit. Good health and flexible work arrangements were mentioned as important preconditions. The themes emerging from the categorization of the motives and preconditions corresponded to the domains of health, work characteristics, skills and knowledge, and social and financial factors from the STREAM research framework. However, our analysis revealed one additional theme-purpose in life. This study offers important new insights into the various preconditions and motives that influence working beyond retirement age. In addition, the five domains of the STREAM research framework, including the additional domain of 'purpose in life', seem to be applicable to working beyond retirement age. This knowledge contributes to the development of work-related interventions that enhance older workers' motivation to prolong their working lives.

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

NASA Technical Reports Server (NTRS)

Gomaa, Hassan; Kerschberg, Larry; Sugumaran, Vijayan

1992-01-01

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

General and Domain-Specific Contributions to Creative Ideation and Creative Performance

PubMed Central

An, Donggun; Runco, Mark A.

2016-01-01

The general objective of this study was to reexamine two views of creativity, one positing that there is a general creative capacity or talent and the other that creativity is domain-specific. These two views were compared by (a) testing correlations among measures of domain-general and domain-specific creativity and (b) examining how the general and the specific measures was each related to indices of knowledge, motivation, and personality. Participants were 147 college students enrolled in a foreign language course. Data were collected on participants’ domain knowledge, motivation, and creative personality, as well as four measures representing “General or Domain-Specific Creative Ideation” or “Creative Performance and Activity”. Results indicated that the four measures of creativity were correlated with one another, except for “General Performance and Activity” and “Domain-Specific Ideation.” A canonical correlation indicated that knowledge, motivation, and personality were significantly correlated with the four creativity measures (Rc = .49, p < .01). Multiple regressions uncovered particular relationships consistent with the view that creativity has both general and domain-specific contributions. Limitations, such as the focus on one domain, and future directions are discussed. PMID:27872664

Disciplinary knowledge of K-3 teachers and their knowledge calibration in the domain of early literacy.

PubMed

Cunningham, Anne E; Perry, Kathryn E; Stanovich, Keith E; Stanovich, Paula J

2004-06-01

Recently, investigators have begun to pay increasing attention to the role of teachers' domain specific knowledge in the area of reading, and its implications for both classroom practice and student learning. The aims of the present study were to assess kindergarten to third-grade teachers' actual and perceived reading-related subject matter knowledge, and to investigate the extent to which teachers calibrate their reading related subject matter knowledge by examining relationships between actual and perceived knowledge. Results indicated that while teachers demonstrated limited knowledge of children's literature, phoneme awareness, and phonics, the majority of these same teachers evaluated their knowledge levels quite positively. Teachers demonstrated some ability to calibrate their own knowledge levels in the area of children's literature, yet they were poorly calibrated in the domains of phoneme awareness and phonics. These findings suggest that teachers tend to overestimate their reading related subject matter knowledge and are often unaware of what they know and do not know. Implications for the design of teacher education at both the preservice and inservice levels are discussed.

Childhood vaccination communication outcomes unpacked and organized in a taxonomy to facilitate core outcome establishment.

PubMed

Kaufman, Jessica; Ryan, Rebecca; Glenton, Claire; Lewin, Simon; Bosch-Capblanch, Xavier; Cartier, Yuri; Cliff, Julie; Oyo-Ita, Angela; Ames, Heather; Muloliwa, Artur Manuel; Oku, Afiong; Rada, Gabriel; Hill, Sophie

2017-04-01

We present a comprehensive taxonomy of outcomes for childhood vaccination communication interventions. Adding to our earlier map of trial outcomes, we aimed to (1) identify relevant outcomes not measured in trials, (2) identify outcomes from stakeholder focus groups, and (3) organize outcomes into a taxonomy. We identified additional outcomes from nonvaccination health communication literature and through parent and health care professional focus groups. We organized outcomes into the taxonomy through iterative discussion and informed by organizational principles established by leaders in core outcome research. The taxonomy includes three overarching core areas, divided into eight domains and then into outcomes. Core area one is psychosocial impact, including the domains "knowledge or understanding," "attitudes or beliefs," and "decision-making." Core area two is health impact, covering "vaccination status and behaviors" and "health status and well-being." Core area three is community, social, or health system impact, containing "intervention design and implementation," "community participation," and "resource use." To our knowledge, this taxonomy is the first attempt to conceptualize the range of potential outcomes for vaccination communication. It can be used by researchers selecting outcomes for complex communication interventions. We will also present the taxonomy to stakeholders to establish core outcome domains. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Purpose and Learning Benefits of Simulations: A Design and Development Perspective.

ERIC Educational Resources Information Center

Goosen, Kenneth R.; Jensen, Ron; Wells, Robert

2001-01-01

Considers the role of the simulation designer in the development of business enterprise simulations used in collegiate business education. Topics include the designer's knowledge domain; conflicting business administration theories in accounting, finance, economics, marketing, production, and income tax; and other designer issues. (LRW)

Concussion Management in Your Schools: A Call to Action

ERIC Educational Resources Information Center

Pierson, Eric E.; Canto, Angela I.

2015-01-01

School psychologists are key professionals in assessment, intervention, prevention, and consultation across academic, behavioral, and emotional domains. Often, this includes working with injured or ill students. Given the high prevalence of concussions among children and adolescents, knowledgeable school psychologists are needed to work with these…

Cognitive and Academic Profiles Associated with Math Disability Subtypes

ERIC Educational Resources Information Center

Kubas, Hanna A.; Schmid, Amy D.; Drefs, Michelle A.; Poole, Jennifer M.; Holland, Sara; Fiorello, Catherine A.

2014-01-01

Children with math disabilities (MD) represent a heterogeneous group and often display deficits in one or more cognitive domains. Math proficiency requires a number of different cognitive processes, including quantitative knowledge, working memory, processing speed, fluid reasoning, and executive functions. Assessment practices that do not address…

Training Peer-Feedback Skills on Geometric Construction Tasks: Role of Domain Knowledge and Peer-Feedback Levels

ERIC Educational Resources Information Center

Alqassab, Maryam; Strijbos, Jan-Willem; Ufer, Stefan

2018-01-01

Peer feedback is widely used to train assessment skills and to support collaborative learning of various learning tasks, but research on peer feedback in the domain of mathematics is limited. Although domain knowledge seems to be a prerequisite for peer-feedback provision, it only recently received attention in the peer-feedback literature. In…

Contributions of Domain-General Cognitive Resources and Different Forms of Arithmetic Development to Pre-Algebraic Knowledge

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Compton, Donald L.; Fuchs, Douglas; Powell, Sarah R.; Schumacher, Robin F.; Hamlett, Carol L.; Vernier, Emily; Namkung, Jessica M.; Vukovic, Rose K.

2012-01-01

The purpose of this study was to investigate the contributions of domain-general cognitive resources and different forms of arithmetic development to individual differences in pre-algebraic knowledge. Children (n = 279, mean age = 7.59 years) were assessed on 7 domain-general cognitive resources as well as arithmetic calculations and word problems…

Cognitive Demand Differences in Causal Inferences: Characters' Plans Are More Difficult to Comprehend than Physical Causation

ERIC Educational Resources Information Center

Shears, Connie; Miller, Vanessa; Ball, Megan; Hawkins, Amanda; Griggs, Janna; Varner, Andria

2007-01-01

Readers may draw knowledge-based inferences to connect sentences in text differently depending on the knowledge domain being accessed. Most prior research has focused on the direction of the causal explanation (predictive vs. backward) without regard to the knowledge domain drawn on to support comprehension. We suggest that less cognitive effort…

General Intelligence, Emotional Intelligence and Academic Knowledge as Predictors of Creativity Domains: A Study of Gifted Students

ERIC Educational Resources Information Center

Sahin, Feyzullah

2016-01-01

Creativity of the individual is dependent on numerous factors, such as knowledge, general intelligence and emotional intelligence. The general purpose of this study is to investigate the effect of general intelligence, emotional intelligence and academic knowledge on the emerging of domain-specific creativity. The study was conducted on 178…

The Knowledge Base and Memory Performance: A Comparison of Academically Successful and Unsuccessful Learners. Paper 5/1987.

ERIC Educational Resources Information Center

Schneider, Wolfgang; And Others

The expert-novice paradigm, which demonstrates the outstanding role of domain-specific knowledge in explaining differences in memory behavior and performance, was examined. Two studies are described which compared memory performance of groups equivalent with regard to domain-specific knowledge but differing in intellectual ability. The hypothesis…

Motor Knowledge Is One Dimension for Concept Organization: Further Evidence from a Chinese Semantic Dementia Case

ERIC Educational Resources Information Center

Lin, Nan; Guo, Qihao; Han, Zaizhu; Bi, Yanchao

2011-01-01

Neuropsychological and neuroimaging studies have indicated that motor knowledge is one potential dimension along which concepts are organized. Here we present further direct evidence for the effects of motor knowledge in accounting for categorical patterns across object domains (living vs. nonliving) and grammatical domains (nouns vs. verbs), as…

Designing Interaction as a Learning Process: Supporting Users' Domain Knowledge Development in Interaction

ERIC Educational Resources Information Center

Choi, Jung-Min

2010-01-01

The primary concern in current interaction design is focused on how to help users solve problems and achieve goals more easily and efficiently. While users' sufficient knowledge acquisition of operating a product or system is considered important, their acquisition of problem-solving knowledge in the task domain has largely been disregarded. As a…

Teaching Efficacy: Exploring Relationships between Mathematics and Science Self-Efficacy Beliefs, PCK and Domain Knowledge among Preservice Teachers from the United States

ERIC Educational Resources Information Center

Thomson, Margareta Maria; DiFrancesca, Daniell; Carrier, Sarah; Lee, Carrie

2017-01-01

This mixed-methods study investigated the relationships among preservice teachers' efficacy beliefs, pedagogical content knowledge (PCK) and their domain knowledge (DK) as related to mathematics and science teaching. Quantitative results revealed that participants' PCK was significantly correlated with their mathematics and science efficacy…

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.

Barriers to and enablers of diabetic retinopathy screening attendance: a systematic review of published and grey literature.

PubMed

Graham-Rowe, E; Lorencatto, F; Lawrenson, J G; Burr, J M; Grimshaw, J M; Ivers, N M; Presseau, J; Vale, L; Peto, T; Bunce, C; Francis, J J

2018-05-23

To identify and synthesize studies reporting modifiable barriers/enablers associated with retinopathy screening attendance in people with Type 1 or Type 2 diabetes, and to identify those most likely to influence attendance. We searched MEDLINE, EMBASE, PsycINFO, Cochrane Library and the 'grey literature' for quantitative and qualitative studies to February 2017. Data (i.e. participant quotations, interpretive summaries, survey results) reporting barriers/enablers were extracted and deductively coded into domains from the Theoretical Domains Framework; with domains representing categories of theoretical barriers/enablers proposed to mediate behaviour change. Inductive thematic analysis was conducted within domains to describe the role each domain plays in facilitating or hindering screening attendance. Domains that were more frequently coded and for which more themes were generated were judged more likely to influence attendance. Sixty-nine primary studies were included. We identified six theoretical domains ['environmental context and resources' (75% of included studies), 'social influences' (51%), 'knowledge' (50%), 'memory, attention, decision processes' (50%), 'beliefs about consequences' (38%) and 'emotions' (33%)] as the key mediators of diabetic retinopathy screening attendance. Examples of barriers populating these domains included inaccurate diabetic registers and confusion between routine eye care and retinopathy screening. Recommendations by healthcare professionals and community-level media coverage acted as enablers. Across a variety of contexts, we found common barriers to and enablers of retinopathy screening that could be targeted in interventions aiming to increase screening attendance. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

What helps or hinders midwives to implement physical activity guidelines for obese pregnant women? A questionnaire survey using the Theoretical Domains Framework.

PubMed

McParlin, Catherine; Bell, Ruth; Robson, Stephen C; Muirhead, Colin R; Araújo-Soares, Vera

2017-06-01

to investigate barriers and facilitators to physical activity (PA) guideline implementation for midwives when advising obese pregnant women. a cross-sectional, self-completion, anonymous questionnaire was designed using the Theoretical Domains Framework. this framework was developed to evaluate the implementation of guidelines by health care professionals. A total of 40 questions were included. These were informed by previous research on pregnant women's and midwives views, knowledge and attitudes to PA, and supported by national evidence based guidelines. Demographic information and free text comments were also collected. three diverse NHS Trusts in the North East of England. all midwives employed by two hospital Trusts and the community midwives from the third Trust (n=375) were invited to participate. mean domain scores were calculated. Factor and regression analysis were performed to describe which theoretical domains may be influencing practice. Free text comments were analysed thematically. 192 (53%) questionnaires were returned. Mean domain scores were highest for social professional role and knowledge, and lowest for skills, beliefs about capabilities and behaviour regulation. Regression analysis indicated that skills and memory/attention/decision domains had a statistically significant influence on midwives discussing PA with obese pregnant women and advising them accordingly. Midwives comments indicated that they felt it was part of their role to discuss PA with all pregnant women but felt they lacked the skills and resources to do so effectively. midwives seem to have the necessary knowledge about the need/importance of PA advice for obese women and believe it is part of their role, but perceive they lack necessary skills and resources, and do not plan or prioritise the discussion regarding PA with obese pregnant woman. designing interventions that improve skills, promote routine enquiry regarding PA and provide resources (eg. information, referral pathways) may help improve midwives' PA advice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Understanding the Problems of Learning Mathematics.

ERIC Educational Resources Information Center

Semilla-Dube, Lilia

1983-01-01

A model is being developed to categorize problems in teaching and learning mathematics. Categories include problems due to language difficulties, lack of prerequisite knowledge, and those related to the affective domain. This paper calls on individuals to share teaching and learning episodes; those submitted will then be compiled and categorized.…

Defining Integrated Student Supports for Linked Learning Pathways. Knowledge Brief

ERIC Educational Resources Information Center

John W. Gardner Center for Youth and Their Communities, 2016

2016-01-01

This document outlines how effectively integrated student supports build or scaffold student competencies in five broad domains of learning for college, career, and civic readiness. Relevant supports are not limited to "services" or "programs" but extend to enabling resources and social conditions, including, for example,…

Computer Proficiency for Online Learning: Factorial Invariance of Scores among Teachers

ERIC Educational Resources Information Center

Martin, Amy L.; Reeves, Todd D.; Smith, Thomas J.; Walker, David A.

2016-01-01

Online learning is variously employed in K-12 education, including for teacher professional development. However, the use of computer-based technologies for learning purposes assumes learner computer proficiency, making this construct an important domain of procedural knowledge in formal and informal online learning contexts. Addressing this…

Assessment Using Multi-Criteria Decision Approach for "Higher Order Skills" Learning Domains

ERIC Educational Resources Information Center

Ramakishnan, Sadhu Balasundaram; Ramadoss, Balakrishnan

2009-01-01

Over the past several decades, a wider range of assessment strategies has gained prominence in classrooms, including complex assessment items such as individual or group projects, student journals and other creative writing tasks, graphic/artistic representations of knowledge, clinical interviews, student presentations and performances, peer- and…

An Intelligent Simulator for Telerobotics Training

ERIC Educational Resources Information Center

Belghith, K.; Nkambou, R.; Kabanza, F.; Hartman, L.

2012-01-01

Roman Tutor is a tutoring system that uses sophisticated domain knowledge to monitor the progress of students and advise them while they are learning how to operate a space telerobotic system. It is intended to help train operators of the Space Station Remote Manipulator System (SSRMS) including astronauts, operators involved in ground-based…

Disentangling the Role of Domain-Specific Knowledge in Student Modeling

NASA Astrophysics Data System (ADS)

Ruppert, John; Duncan, Ravit Golan; Chinn, Clark A.

2017-08-01

This study explores the role of domain-specific knowledge in students' modeling practice and how this knowledge interacts with two domain-general modeling strategies: use of evidence and developing a causal mechanism. We analyzed models made by middle school students who had a year of intensive model-based instruction. These models were made to explain a familiar but unstudied biological phenomenon: late onset muscle pain. Students were provided with three pieces of evidence related to this phenomenon and asked to construct a model to account for this evidence. Findings indicate that domain-specific resources play a significant role in the extent to which the models accounted for provided evidence. On the other hand, familiarity with the situation appeared to contribute to the mechanistic character of models. Our results indicate that modeling strategies alone are insufficient for the development of a mechanistic model that accounts for provided evidence and that, while learners can develop a tentative model with a basic familiarity of the situation, scaffolding certain domain-specific knowledge is necessary to assist students with incorporating evidence in modeling tasks.

Using a Relational Database to Index Infectious Disease Information

PubMed Central

Brown, Jay A.

2010-01-01

Mapping medical knowledge into a relational database became possible with the availability of personal computers and user-friendly database software in the early 1990s. To create a database of medical knowledge, the domain expert works like a mapmaker to first outline the domain and then add the details, starting with the most prominent features. The resulting “intelligent database” can support the decisions of healthcare professionals. The intelligent database described in this article contains profiles of 275 infectious diseases. Users can query the database for all diseases matching one or more specific criteria (symptom, endemic region of the world, or epidemiological factor). Epidemiological factors include sources (patients, water, soil, or animals), routes of entry, and insect vectors. Medical and public health professionals could use such a database as a decision-support software tool. PMID:20623018

The Effect of Teacher Performance in Implementation of The 2013 Curriculum Toward Chemistry Learning Achievement

NASA Astrophysics Data System (ADS)

Dewi, L. P.; Djohar, A.

2018-04-01

This research is a study about implementation of the 2013 Curriculum on Chemistry subject. This study aims to determine the effect of teacher performance toward chemistry learning achievement. The research design involves the independent variable, namely the performance of Chemistry teacher, and the dependent variable that is Chemistry learning achievement which includes the achievement in knowledge and skill domain. The subject of this research are Chemistry teachers and High School students in Bandung City. The research data is obtained from questionnaire about teacher performance assessed by student and Chemistry learning achievement from the students’ report. Data were analyzed by using MANOVA test. The result of multivariate significance test shows that there is a significant effect of teacher performance toward Chemistry learning achievement in knowledge and skill domain with medium effect size.

PREDOSE: A Semantic Web Platform for Drug Abuse Epidemiology using Social Media

PubMed Central

Cameron, Delroy; Smith, Gary A.; Daniulaityte, Raminta; Sheth, Amit P.; Dave, Drashti; Chen, Lu; Anand, Gaurish; Carlson, Robert; Watkins, Kera Z.; Falck, Russel

2013-01-01

Objectives The role of social media in biomedical knowledge mining, including clinical, medical and healthcare informatics, prescription drug abuse epidemiology and drug pharmacology, has become increasingly significant in recent years. Social media offers opportunities for people to share opinions and experiences freely in online communities, which may contribute information beyond the knowledge of domain professionals. This paper describes the development of a novel Semantic Web platform called PREDOSE (PREscription Drug abuse Online Surveillance and Epidemiology), which is designed to facilitate the epidemiologic study of prescription (and related) drug abuse practices using social media. PREDOSE uses web forum posts and domain knowledge, modeled in a manually created Drug Abuse Ontology (DAO) (pronounced dow), to facilitate the extraction of semantic information from User Generated Content (UGC). A combination of lexical, pattern-based and semantics-based techniques is used together with the domain knowledge to extract fine-grained semantic information from UGC. In a previous study, PREDOSE was used to obtain the datasets from which new knowledge in drug abuse research was derived. Here, we report on various platform enhancements, including an updated DAO, new components for relationship and triple extraction, and tools for content analysis, trend detection and emerging patterns exploration, which enhance the capabilities of the PREDOSE platform. Given these enhancements, PREDOSE is now more equipped to impact drug abuse research by alleviating traditional labor-intensive content analysis tasks. Methods Using custom web crawlers that scrape UGC from publicly available web forums, PREDOSE first automates the collection of web-based social media content for subsequent semantic annotation. The annotation scheme is modeled in the DAO, and includes domain specific knowledge such as prescription (and related) drugs, methods of preparation, side effects, routes of administration, etc. The DAO is also used to help recognize three types of data, namely: 1) entities, 2) relationships and 3) triples. PREDOSE then uses a combination of lexical and semantic-based techniques to extract entities and relationships from the scraped content, and a top-down approach for triple extraction that uses patterns expressed in the DAO. In addition, PREDOSE uses publicly available lexicons to identify initial sentiment expressions in text, and then a probabilistic optimization algorithm (from related research) to extract the final sentiment expressions. Together, these techniques enable the capture of fine-grained semantic information from UGC, and querying, search, trend analysis and overall content analysis of social media related to prescription drug abuse. Moreover, extracted data are also made available to domain experts for the creation of training and test sets for use in evaluation and refinements in information extraction techniques. Results A recent evaluation of the information extraction techniques applied in the PREDOSE platform indicates 85% precision and 72% recall in entity identification, on a manually created gold standard dataset. In another study, PREDOSE achieved 36% precision in relationship identification and 33% precision in triple extraction, through manual evaluation by domain experts. Given the complexity of the relationship and triple extraction tasks and the abstruse nature of social media texts, we interpret these as favorable initial results. Extracted semantic information is currently in use in an online discovery support system, by prescription drug abuse researchers at the Center for Interventions, Treatment and Addictions Research (CITAR) at Wright State University. Conclusion A comprehensive platform for entity, relationship, triple and sentiment extraction from such abstruse texts has never been developed for drug abuse research. PREDOSE has already demonstrated the importance of mining social media by providing data from which new findings in drug abuse research were uncovered. Given the recent platform enhancements, including the refined DAO, components for relationship and triple extraction, and tools for content, trend and emerging pattern analysis, it is expected that PREDOSE will play a significant role in advancing drug abuse epidemiology in future. PMID:23892295

A middle man approach to knowledge acquisition in expert systems

NASA Technical Reports Server (NTRS)

Jordan, Janice A.; Lin, Min-Jin; Mayer, Richard J.; Sterle, Mark E.

1990-01-01

The Weed Control Advisor (WCA) is a robust expert system that has been successfully implemented on an IBM AT class microcomputer in CLIPS. The goal of the WCA was to demonstrate the feasibility of providing an economical, efficient, user friendly system through which Texas rice producers could obtain expert level knowledge regarding herbicide application for weed control. During the development phase of the WCA, an improved knowledge acquisition method which we call the Middle Man Approach (MMA) was applied to facilitate the communication process between the domain experts and the knowledge engineer. The MMA served to circumvent the problems associated with the more traditional forms of knowledge acquisition by placing the Middle Man, a semi-expert in the problem domain with some computer expertise, at the site of system development. The middle man was able to contribute to system development in two major ways. First, the Middle Man had experience working in rice production and could assume many of the responsibilities normally performed by the domain experts such as explaining the background of the problem domain and determining the important relations. Second, the Middle Man was familiar with computers and worked closely with the system developers to update the rules after the domain experts reviewed the prototype, contribute to the help menus and explanation portions of the expert system, conduct the testing that is required to insure that the expert system gives the expected results answer questions in a timely way, help the knowledge engineer structure the domain knowledge into a useable form, and provide insight into the end user's profile which helped in the development of the simple user friendly interface. The final results were not only that both time expended and costs were greatly reduced by using the MMA, but the quality of the system was improved. This papa will introduce the WCA system and then discuss traditional knowledge acquisition along with some of the problems often associated with it, the MMA methodology, and its application to the WCA development.

Towards a Conceptual Design of a Cross-Domain Integrative Information System for the Geosciences

NASA Astrophysics Data System (ADS)

Zaslavsky, I.; Richard, S. M.; Valentine, D. W.; Malik, T.; Gupta, A.

2013-12-01

As geoscientists increasingly focus on studying processes that span multiple research domains, there is an increased need for cross-domain interoperability solutions that can scale to the entire geosciences, bridging information and knowledge systems, models, software tools, as well as connecting researchers and organization. Creating a community-driven cyberinfrastructure (CI) to address the grand challenges of integrative Earth science research and education is the focus of EarthCube, a new research initiative of the U.S. National Science Foundation. We are approaching EarthCube design as a complex socio-technical system of systems, in which communication between various domain subsystems, people and organizations enables more comprehensive, data-intensive research designs and knowledge sharing. In particular, we focus on integrating 'traditional' layered CI components - including information sources, catalogs, vocabularies, services, analysis and modeling tools - with CI components supporting scholarly communication, self-organization and social networking (e.g. research profiles, Q&A systems, annotations), in a manner that follows and enhances existing patterns of data, information and knowledge exchange within and across geoscience domains. We describe an initial architecture design focused on enabling the CI to (a) provide an environment for scientifically sound information and software discovery and reuse; (b) evolve by factoring in the impact of maturing movements like linked data, 'big data', and social collaborations, as well as experience from work on large information systems in other domains; (c) handle the ever increasing volume, complexity and diversity of geoscience information; (d) incorporate new information and analytical requirements, tools, and techniques, and emerging types of earth observations and models; (e) accommodate different ideas and approaches to research and data stewardship; (f) be responsive to the existing and anticipated needs of researchers and organizations representing both established and emerging CI users; and (g) make best use of NSF's current investment in the geoscience CI. The presentation will focus on the challenges and methodology of EarthCube CI design, in particular on supporting social engagement and interaction between geoscientists and computer scientists as a core function of EarthCube architecture. This capability must include mechanisms to not only locate and integrate available geoscience resources, but also engage individuals and projects, research products and publications, and enable efficient communication across many EarthCube stakeholders leading to long-term institutional alignment and trusted collaborations.

A reusable knowledge acquisition shell: KASH

NASA Technical Reports Server (NTRS)

Westphal, Christopher; Williams, Stephen; Keech, Virginia

1991-01-01

KASH (Knowledge Acquisition SHell) is proposed to assist a knowledge engineer by providing a set of utilities for constructing knowledge acquisition sessions based on interviewing techniques. The information elicited from domain experts during the sessions is guided by a question dependency graph (QDG). The QDG defined by the knowledge engineer, consists of a series of control questions about the domain that are used to organize the knowledge of an expert. The content information supplies by the expert, in response to the questions, is represented in the form of a concept map. These maps can be constructed in a top-down or bottom-up manner by the QDG and used by KASH to generate the rules for a large class of expert system domains. Additionally, the concept maps can support the representation of temporal knowledge. The high degree of reusability encountered in the QDG and concept maps can vastly reduce the development times and costs associated with producing intelligent decision aids, training programs, and process control functions.

Does prior domain-specific content knowledge influence students' recall of arguments surrounding interdisciplinary topics?

PubMed

Schmidt, Hiemke K; Rothgangel, Martin; Grube, Dietmar

2017-12-01

Awareness of various arguments can help interactants present opinions, stress points, and build counterarguments during discussions. At school, some topics are taught in a way that students learn to accumulate knowledge and gather arguments, and later employ them during debates. Prior knowledge may facilitate recalling information on well structured, fact-based topics, but does it facilitate recalling arguments during discussions on complex, interdisciplinary topics? We assessed the prior knowledge in domains related to a bioethical topic of 277 students from Germany (approximately 15 years old), their interest in the topic, and their general knowledge. The students read a text with arguments for and against prenatal diagnostics and tried to recall the arguments one week later and again six weeks later. Prior knowledge in various domains related to the topic individually and separately helped students recall the arguments. These relationships were independent of students' interest in the topic and their general knowledge. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

The Cognitive Processes Used in Team Collaboration During Asynchronous, Distributed Decision Making

DTIC Science & Technology

2004-06-01

Transfer Conventions (IPtcp) IP: Solution Alternatives (IPsa) KB: Collaborative Knowledge (KBck) KB: Shared Understanding ( KBsu ) KB: Domain...Gill.” KBsu : Knowledge Building (shared understanding) = using facts to justify a solution. “I think Eddie did it because he was hard of hearing...KB: Collaborative Knowledge (KBck) KB: Shared Understanding ( KBsu ) KB: Domain Expertise (IPde) * * ** ** ** = significant Results 15

XML Based Markup Languages for Specific Domains

NASA Astrophysics Data System (ADS)

Varde, Aparna; Rundensteiner, Elke; Fahrenholz, Sally

A challenging area in web based support systems is the study of human activities in connection with the web, especially with reference to certain domains. This includes capturing human reasoning in information retrieval, facilitating the exchange of domain-specific knowledge through a common platform and developing tools for the analysis of data on the web from a domain expert's angle. Among the techniques and standards related to such work, we have XML, the eXtensible Markup Language. This serves as a medium of communication for storing and publishing textual, numeric and other forms of data seamlessly. XML tag sets are such that they preserve semantics and simplify the understanding of stored information by users. Often domain-specific markup languages are designed using XML, with a user-centric perspective. Standardization bodies and research communities may extend these to include additional semantics of areas within and related to the domain. This chapter outlines the issues to be considered in developing domain-specific markup languages: the motivation for development, the semantic considerations, the syntactic constraints and other relevant aspects, especially taking into account human factors. Illustrating examples are provided from domains such as Medicine, Finance and Materials Science. Particular emphasis in these examples is on the Materials Markup Language MatML and the semantics of one of its areas, namely, the Heat Treating of Materials. The focus of this chapter, however, is not the design of one particular language but rather the generic issues concerning the development of domain-specific markup languages.

Different personal propensities among scientists relate to deeper vs. broader knowledge contributions

PubMed Central

Bateman, Thomas S.; Hess, Andrew M.

2015-01-01

Scientific journal publications, and their contributions to knowledge, can be described by their depth (specialized, domain-specific knowledge extensions) and breadth (topical scope, including spanning multiple knowledge domains). Toward generating hypotheses about how scientists’ personal dispositions would uniquely predict deeper vs. broader contributions to the literature, we assumed that conducting broader studies is generally viewed as less attractive (e.g., riskier) than conducting deeper studies. Study 1 then supported our assumptions: the scientists surveyed considered a hypothetical broader study, compared with an otherwise-comparable deeper study, to be riskier, a less-significant opportunity, and of lower potential importance; they further reported being less likely to pursue it and, in a forced choice, most chose to work on the deeper study. In Study 2, questionnaire measures of medical researchers’ personal dispositions and 10 y of PubMed data indicating their publications’ topical coverage revealed how dispositions differentially predict depth vs. breadth. Competitiveness predicted depth positively, whereas conscientiousness predicted breadth negatively. Performance goal orientation predicted depth but not breadth, and learning goal orientation contrastingly predicted breadth but not depth. Openness to experience positively predicted both depth and breadth. Exploratory work behavior (the converse of applying and exploiting one’s current knowledge) predicted breadth positively and depth negatively. Thus, this research distinguishes depth and breadth of published knowledge contributions, and provides new insights into how scientists’ personal dispositions influence research processes and products. PMID:25733900

Different personal propensities among scientists relate to deeper vs. broader knowledge contributions.

PubMed

Bateman, Thomas S; Hess, Andrew M

2015-03-24

Scientific journal publications, and their contributions to knowledge, can be described by their depth (specialized, domain-specific knowledge extensions) and breadth (topical scope, including spanning multiple knowledge domains). Toward generating hypotheses about how scientists' personal dispositions would uniquely predict deeper vs. broader contributions to the literature, we assumed that conducting broader studies is generally viewed as less attractive (e.g., riskier) than conducting deeper studies. Study 1 then supported our assumptions: the scientists surveyed considered a hypothetical broader study, compared with an otherwise-comparable deeper study, to be riskier, a less-significant opportunity, and of lower potential importance; they further reported being less likely to pursue it and, in a forced choice, most chose to work on the deeper study. In Study 2, questionnaire measures of medical researchers' personal dispositions and 10 y of PubMed data indicating their publications' topical coverage revealed how dispositions differentially predict depth vs. breadth. Competitiveness predicted depth positively, whereas conscientiousness predicted breadth negatively. Performance goal orientation predicted depth but not breadth, and learning goal orientation contrastingly predicted breadth but not depth. Openness to experience positively predicted both depth and breadth. Exploratory work behavior (the converse of applying and exploiting one's current knowledge) predicted breadth positively and depth negatively. Thus, this research distinguishes depth and breadth of published knowledge contributions, and provides new insights into how scientists' personal dispositions influence research processes and products.

PSG-EXPERT. An expert system for the diagnosis of sleep disorders.

PubMed

Fred, A; Filipe, J; Partinen, M; Paiva, T

2000-01-01

This paper describes PSG-EXPERT, an expert system in the domain of sleep disorders exploring polysomnographic data. The developed software tool is addressed from two points of view: (1)--as an integrated environment for the development of diagnosis-oriented expert systems; (2)--as an auxiliary diagnosis tool in the particular domain of sleep disorders. Developed over a Windows platform, this software tool extends one of the most popular shells--CLIPS (C Language Integrated Production System) with the following features: backward chaining engine; graph-based explanation facilities; knowledge editor including a fuzzy fact editor and a rules editor, with facts-rules integrity checking; belief revision mechanism; built-in case generator and validation module. It therefore provides graphical support for knowledge acquisition, edition, explanation and validation. From an application domain point of view, PSG-Expert is an auxiliary diagnosis system for sleep disorders based on polysomnographic data, that aims at assisting the medical expert in his diagnosis task by providing automatic analysis of polysomnographic data, summarising the results of this analysis in terms of a report of major findings and possible diagnosis consistent with the polysomnographic data. Sleep disorders classification follows the International Classification of Sleep Disorders. Major features of the system include: browsing on patients data records; structured navigation on Sleep Disorders descriptions according to ASDA definitions; internet links to related pages; diagnosis consistent with polysomnographic data; graphical user-interface including graph-based explanatory facilities; uncertainty modelling and belief revision; production of reports; connection to remote databases.

Children’s Safety Initiative: A National Assessment of Pediatric Educational Needs amongEmergency Medical Services Providers

PubMed Central

Hansen, Matthew; Meckler, Garth; Dickinson, Caitlyn; Dickenson, Kathryn; Jui, Jonathan; Lambert, William; Guise, Jeanne-Marie

2014-01-01

Objective Emergency Medical Services (EMS) providers may have critical knowledge gaps in pediatric care due to lack of exposure and training. There is currently little evidence to guide educators to the knowledge gaps most likely to improve patient safety. The objective of this study was to identify educational needs of EMS providers related to pediatric care in various domains in order to inform development of curricula. Methods The Children’s Safety Initiative-EMS performed a three-phase Delphi survey on patient safety in pediatric emergencies among providers and content experts in pediatric emergency care including physicians, nurses and pre-hospital providers of all levels. Each round included questions related to educational needs of providers or the effect of training on patient safety events. We identified knowledge gaps in the following domains: case exposure, competency and knowledge, assessment and decision making, and critical thinking and proficiency. Individual knowledge gaps were ranked by portion of respondents who ranked them “highly likely” (likert-type score 7–10 out of 10) to contribute to safety events. Results There were 737 respondents who were included in analysis of the first phase of the survey. Paramedics were 50.8% of respondents; EMT-Basics/first responders were 22% and physicians 11.4%. The top educational priorities identified in the final round of the survey include: pediatric airway management, responder anxiety when working with children, and general pediatric skills among providers. The top three needs in decision-making include knowing when to alter plans mid-course, knowing when to perform and advanced airway, and assessing pain in children. The top 3 technical or procedural skills needs were pediatric advanced airway, neonatal resuscitation, and intravenous/intraosseos access. For neonates, specific educational needs identified included knowing appropriate vital signs and preventing hypothermia. Conclusions This is the first large-scale Delphi survey related to pediatric pre-hospital education. Our results provide foundational information related to the educational needs of pre-hospital providers. Medical directors and educators can use the results to shape future curricular development. PMID:25296191

Children's safety initiative: a national assessment of pediatric educational needs among emergency medical services providers.

PubMed

Hansen, Matthew; Meckler, Garth; Dickinson, Caitlyn; Dickenson, Kathryn; Jui, Jonathan; Lambert, William; Guise, Jeanne-Marie

2015-01-01

Emergency medical services (EMS) providers may have critical knowledge gaps in pediatric care due to lack of exposure and training. There is currently little evidence to guide educators to the knowledge gaps that most need to be addressed to improve patient safety. The objective of this study was to identify educational needs of EMS providers related to pediatric care in various domains in order to inform development of curricula. The Children's Safety Initiative-EMS performed a three-phase Delphi survey on patient safety in pediatric emergencies among providers and content experts in pediatric emergency care, including physicians, nurses, and prehospital providers of all levels. Each round included questions related to educational needs of providers or the effect of training on patient safety events. We identified knowledge gaps in the following domains: case exposure, competency and knowledge, assessment and decision making, and critical thinking and proficiency. Individual knowledge gaps were ranked by portion of respondents who ranked them "highly likely" (Likert-type score 7-10 out of 10) to contribute to safety events. There were 737 respondents who were included in analysis of the first phase of the survey. Paramedics were 50.8% of respondents, EMT-basics/first responders were 22%, and physicians 11.4%. The top educational priorities identified in the final round of the survey include pediatric airway management, responder anxiety when working with children, and general pediatric skills among providers. The top three needs in decision-making include knowing when to alter plans mid-course, knowing when to perform an advanced airway, and assessing pain in children. The top 3 technical or procedural skills needs were pediatric advanced airway, neonatal resuscitation, and intravenous/intraosseous access. For neonates, specific educational needs identified included knowing appropriate vital signs and preventing hypothermia. This is the first large-scale Delphi survey related to pediatric prehospital education. Our results provide foundational information related to the educational needs of prehospital providers. Medical directors and educators can use the results to shape future curricular development.

Models versus theories as a primary carrier of nursing knowledge: A philosophical argument.

PubMed

Bender, Miriam

2018-01-01

Theories and models are not equivalent. I argue that an orientation towards models as a primary carrier of nursing knowledge overcomes many ongoing challenges in philosophy of nursing science, including the theory-practice divide and the paradoxical pursuit of predictive theories in a discipline that is defined by process and a commitment to the non-reducibility of the health/care experience. Scientific models describe and explain the dynamics of specific phenomenon. This is distinct from theory, which is traditionally defined as propositions that explain and/or predict the world. The philosophical case has been made against theoretical universalism, showing that a theory can be true in its domain, but that no domain is universal. Subsequently, philosophers focused on scientific models argued that they do the work of defining the boundary conditions-the domain(s)-of a theory. Further analysis has shown the ways models can be constructed and function independent of theory, meaning models can comprise distinct, autonomous "carriers of scientific knowledge." Models are viewed as representations of the active dynamics, or mechanisms, of a phenomenon. Mechanisms are entities and activities organized such that they are productive of regular changes. Importantly, mechanisms are by definition not static: change may alter the mechanism and thereby alter or create entirely new phenomena. Orienting away from theory, and towards models, focuses scholarly activity on dynamics and change. This makes models arguably critical to nursing science, enabling the production of actionable knowledge about the dynamics of process and change in health/care. I briefly explore the implications for nursing-and health/care-knowledge and practice. © 2017 John Wiley & Sons Ltd.

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.

Factors associated with poor knowledge among adults on tuberculosis in Bangladesh: results from a nationwide survey.

PubMed

Hossain, Shahed; Zaman, Khalequ; Quaiyum, Abdul; Banu, Sayera; Husain, Ashaque; Islam, Akramul; Borgdorff, Martien; van Leth, Frank

2015-05-01

In 2012, Bangladesh continues to be one of the 22 high tuberculosis (TB) burden countries in the world. Although free diagnosis and management for TB is available throughout the country, case notification rate/100,000 population for new smear positive (NSP) cases under the national TB control programme (NTP) remained at around 70/100,000 population and have not changed much since 2006. Knowledge on TB disease, treatment and its management could be an important predictor for utilization of TB services and influence case detection under the NTP. Our objective is to describe knowledge of TB among newly diagnosed TB cases and community controls to assess factors associated with poor knowledge in order to identify programmatic implications for control measures. Embedded in TB prevalence survey 2007-2009, we included 240 TB cases from the TB registers and 240 persons ≥ 15 years of age randomly selected from the households where the survey was implemented. All participants were interviewed using a structured, pre-tested questionnaire to evaluate their TB knowledge. Regression analyses were done to assess associations with poor knowledge of TB. Our survey documented that overall there was fair knowledge in all domains investigated. However, based on the number of correct answers to the questionnaires, community controls showed significantly poorer knowledge than the TB cases in the domains of TB transmission (80% vs. 88%), mode of transmission (67% vs. 82%), knowing ≥ 1 suggestive symptoms including cough (78% vs. 89%), curability of TB (90% vs. 98%) and availability of free treatment (75% vs. 95%). Community controls were more likely to have poor knowledge of TB issues compared to the TB cases even after controlling for other factors such as education and occupation in a multivariate model (OR 3.46, 95% CI: 2.00-6.09). Knowledge on various aspects of TB and TB services varies significantly between TB cases and community controls in Bangladesh. The overall higher levels of knowledge in TB cases could identify them as peer educators in ongoing communication approaches to improve care seeking behavior of the TB suspects in the community and hence case detection.

Workplace nutrition knowledge questionnaire: psychometric validation and application.

PubMed

Guadagnin, Simone C; Nakano, Eduardo Y; Dutra, Eliane S; de Carvalho, Kênia M B; Ito, Marina K

2016-11-01

Workplace dietary intervention studies in low- and middle-income countries using psychometrically sound measures are scarce. This study aimed to validate a nutrition knowledge questionnaire (NQ) and its utility in evaluating the changes in knowledge among participants of a Nutrition Education Program (NEP) conducted at the workplace. A NQ was tested for construct validity, internal consistency and discriminant validity. It was applied in a NEP conducted at six workplaces, in order to evaluate the effect of an interactive or a lecture-based education programme on nutrition knowledge. Four knowledge domains comprising twenty-three items were extracted in the final version of the NQ. Internal consistency of each domain was significant, with Kuder-Richardson formula values>0·60. These four domains presented a good fit in the confirmatory factor analysis. In the discriminant validity test, both the Expert and Lay groups scored>0·52, but the Expert group scores were significantly higher than those of the Lay group in all domains. When the NQ was applied in the NEP, the overall questionnaire scores increased significantly because of the NEP intervention, in both groups (P<0·001). However, the increase in NQ scores was significantly higher in the interactive group than in the lecture group, in the overall score (P=0·008) and in the healthy eating domain (P=0·009). The validated NQ is a short and useful tool to assess gain in nutrition knowledge among participants of NEP at the workplace. According to the NQ, an interactive nutrition education had a higher impact on nutrition knowledge than a lecture programme.

A learning apprentice for software parts composition

NASA Technical Reports Server (NTRS)

Allen, Bradley P.; Holtzman, Peter L.

1987-01-01

An overview of the knowledge acquisition component of the Bauhaus, a prototype computer aided software engineering (CASE) workstation for the development of domain-specific automatic programming systems (D-SAPS) is given. D-SAPS use domain knowledge in the refinement of a description of an application program into a compilable implementation. The approach to the construction of D-SAPS was to automate the process of refining a description of a program, expressed in an object-oriented domain language, into a configuration of software parts that implement the behavior of the domain objects.

Knowledge acquisition for temporal abstraction.

PubMed

Stein, A; Musen, M A; Shahar, Y

1996-01-01

Temporal abstraction is the task of detecting relevant patterns in data over time. The knowledge-based temporal-abstraction method uses knowledge about a clinical domain's contexts, external events, and parameters to create meaningful interval-based abstractions from raw time-stamped clinical data. In this paper, we describe the acquisition and maintenance of domain-specific temporal-abstraction knowledge. Using the PROTEGE-II framework, we have designed a graphical tool for acquiring temporal knowledge directly from expert physicians, maintaining the knowledge in a sharable form, and converting the knowledge into a suitable format for use by an appropriate problem-solving method. In initial tests, the tool offered significant gains in our ability to rapidly acquire temporal knowledge and to use that knowledge to perform automated temporal reasoning.

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

Towards a Framework of Using Knowledge Tools for Teaching by Solving Problems in Technology-Enhanced Learning Environment

ERIC Educational Resources Information Center

Kostousov, Sergei; Kudryavtsev, Dmitry

2017-01-01

Problem solving is a critical competency for modern world and also an effective way of learning. Education should not only transfer domain-specific knowledge to students, but also prepare them to solve real-life problems--to apply knowledge from one or several domains within specific situation. Problem solving as teaching tool is known for a long…

An Analysis of Knowledge Structure, Diversity and Diagnostic Abilities among Pre-Service Science Teachers within the Domain of Oxidation and Reduction Chemistry

ERIC Educational Resources Information Center

Bischoff, Paul J.; Avery, Leanne; Golden, Constance Feldt; French, Paul

2010-01-01

The purpose of this study was to investigate the development of preservice science teachers' knowledge structures in the domain of oxidation and reduction chemistry. Knowledge structures were elicited through video-recorded semi-structured interviews before and after the unit of instruction, and analyzed using a visual flow map representation.…

Examining the Inseparability of Content Knowledge from LSP Reading Ability: An Approach Combining Bifactor-Multidimensional Item Response Theory and Structural Equation Modeling

ERIC Educational Resources Information Center

Cai, Yuyang; Kunnan, Antony John

2018-01-01

This study examined the separability of domain-general and domain-specific content knowledge from Language for Specific Purposes (LSP) reading ability. A pool of 1,491 nursing students in China participated by responding to a nursing English test and a nursing knowledge test. Primary data analysis involved four steps: (a) conducting a…

Studies on Experimental Ontology and Knowledge Service Development in Bio-Environmental Engineering

NASA Astrophysics Data System (ADS)

Zhang, Yunliang

2018-01-01

The existing domain-related ontology and information service patterns are analyzed, and the main problems faced by the experimental scheme knowledge service were clarified. The ontology framework model for knowledge service of Bio-environmental Engineering was proposed from the aspects of experimental materials, experimental conditions and experimental instruments, and this ontology will be combined with existing knowledge organization systems to organize scientific and technological literatures, data and experimental schemes. With the similarity and priority calculation, it can improve the related domain research.

A relational metric, its application to domain analysis, and an example analysis and model of a remote sensing domain

NASA Technical Reports Server (NTRS)

Mcgreevy, Michael W.

1995-01-01

An objective and quantitative method has been developed for deriving models of complex and specialized spheres of activity (domains) from domain-generated verbal data. The method was developed for analysis of interview transcripts, incident reports, and other text documents whose original source is people who are knowledgeable about, and participate in, the domain in question. To test the method, it is applied here to a report describing a remote sensing project within the scope of the Earth Observing System (EOS). The method has the potential to improve the designs of domain-related computer systems and software by quickly providing developers with explicit and objective models of the domain in a form which is useful for design. Results of the analysis include a network model of the domain, and an object-oriented relational analysis report which describes the nodes and relationships in the network model. Other products include a database of relationships in the domain, and an interactive concordance. The analysis method utilizes a newly developed relational metric, a proximity-weighted frequency of co-occurrence. The metric is applied to relations between the most frequently occurring terms (words or multiword entities) in the domain text, and the terms found within the contexts of these terms. Contextual scope is selectable. Because of the discriminating power of the metric, data reduction from the association matrix to the network is simple. In addition to their value for design. the models produced by the method are also useful for understanding the domains themselves. They can, for example, be interpreted as models of presence in the domain.

Requirements analysis, domain knowledge, and design

NASA Technical Reports Server (NTRS)

Potts, Colin

1988-01-01

Two improvements to current requirements analysis practices are suggested: domain modeling, and the systematic application of analysis heuristics. Domain modeling is the representation of relevant application knowledge prior to requirements specification. Artificial intelligence techniques may eventually be applicable for domain modeling. In the short term, however, restricted domain modeling techniques, such as that in JSD, will still be of practical benefit. Analysis heuristics are standard patterns of reasoning about the requirements. They usually generate questions of clarification or issues relating to completeness. Analysis heuristics can be represented and therefore systematically applied in an issue-based framework. This is illustrated by an issue-based analysis of JSD's domain modeling and functional specification heuristics. They are discussed in the context of the preliminary design of simple embedded systems.

Towards Knowledge Management for Smart Manufacturing.

PubMed

Feng, Shaw C; Bernstein, William Z; Hedberg, Thomas; Feeney, Allison Barnard

2017-09-01

The need for capturing knowledge in the digital form in design, process planning, production, and inspection has increasingly become an issue in manufacturing industries as the variety and complexity of product lifecycle applications increase. Both knowledge and data need to be well managed for quality assurance, lifecycle-impact assessment, and design improvement. Some technical barriers exist today that inhibit industry from fully utilizing design, planning, processing, and inspection knowledge. The primary barrier is a lack of a well-accepted mechanism that enables users to integrate data and knowledge. This paper prescribes knowledge management to address a lack of mechanisms for integrating, sharing, and updating domain-specific knowledge in smart manufacturing. Aspects of the knowledge constructs include conceptual design, detailed design, process planning, material property, production, and inspection. The main contribution of this paper is to provide a methodology on what knowledge manufacturing organizations access, update, and archive in the context of smart manufacturing. The case study in this paper provides some example knowledge objects to enable smart manufacturing.

Nutrition-sensitive agricultural interventions and gender dynamics: A qualitative study in Nepal.

PubMed

Kjeldsberg, Cecilie; Shrestha, Niva; Patel, Miti; Davis, Dale; Mundy, Gary; Cunningham, Kenda

2018-03-24

Undernutrition and low women's status persist as major development obstacles in South Asia and specifically, Nepal. Multi-sectoral approaches, including nutrition-sensitive agriculture, are potential avenues for further reductions in undernutrition. Although evidence is growing, many questions remain regarding how gender mediates the translation of agricultural production activities into nutritional benefit. In this study, we examined how gender influences the pathway from agricultural production to improved income and control of income, with a focus on five domains of empowerment: decision-making power, freedom of mobility, social support, workload and time, and self-efficacy. For this, we conducted a qualitative retrospective assessment (N = 10 FGDs) among 73 beneficiary women of a nutrition-sensitive agriculture programme implemented from 2008 to 2012 in two districts of Nepal-Baitadi and Kailali. We found that women reported increased decision-making power, new knowledge and skills, increased recognition by their family members of their new knowledge and contributions, and self-efficacy as farmers and sellers, whereas workload and time were the most consistent constraints noted. We also found that each empowerment domain operated differently at different stages of the pathway, sometimes representing barriers and at other times, opportunities and that the interconnectedness of the domains made them difficult to disentangle in practice. Finally, there were major contextual differences for some domains (e.g., freedom of mobility) between the two districts. Future policies and programmes need to include in-depth formative research to ensure that interventions address context-specific gender and social norms to maximise programmatic opportunities to achieve desired results. © 2018 John Wiley & Sons Ltd.

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression

PubMed Central

Jiang, Feng; Han, Ji-zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods. PMID:29623088

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression.

PubMed

Yu, Xu; Lin, Jun-Yu; Jiang, Feng; Du, Jun-Wei; Han, Ji-Zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

Integration into Big Data: First Steps to Support Reuse of Comprehensive Toxicity Model Modules (SOT)

EPA Science Inventory

Data surrounding the needs of human disease and toxicity modeling are largely siloed limiting the ability to extend and reuse modules across knowledge domains. Using an infrastructure that supports integration across knowledge domains (animal toxicology, high-throughput screening...

A multi-agent intelligent environment for medical knowledge.

PubMed

Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder

2003-03-01

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).

Origins of Knowledge: Insights from Precocial Species.

PubMed

Versace, Elisabetta; Vallortigara, Giorgio

2015-01-01

Behavioral responses are influenced by knowledge acquired during the lifetime of an individual and by predispositions transmitted across generations. Establishing the origin of knowledge and the role of the unlearned component is a challenging task, given that both learned and unlearned knowledge can orient perception, learning, and the encoding of environmental features since the first stages of life. Ethical and practical issues constrain the investigation of unlearned knowledge in altricial species, including human beings. On the contrary, precocial animals can be tested on a wide range of tasks and capabilities immediately after birth and in controlled rearing conditions. Insects and precocial avian species are very convenient models to dissect the knowledge systems that enable young individuals to cope with their environment in the absence of specific previous experience. We present the state of the art of research on the origins of knowledge that comes from different models and disciplines. Insects have been mainly used to investigate unlearned sensory preferences and prepared learning mechanisms. The relative simplicity of the neural system and fast life cycle of insects make them ideal models to investigate the neural circuitry and evolutionary dynamics of unlearned traits. Among avian species, chicks of the domestic fowl have been the focus of many studies, and showed to possess unlearned knowledge in the sensory, physical, spatial, numerical and social domains. Solid evidence shows the existence of unlearned knowledge in different domains in several species, from sensory and social preferences to the left-right representation of the mental number line. We show how non-mammalian models of cognition, and in particular precocial species, can shed light into the adaptive value and evolutionary history of unlearned knowledge.

Parental behavioral control in academic and non-academic domains: a three-year longitudinal study in the Chinese culture.

PubMed

Shek, Daniel T L; Lee, Tak Yan

2007-01-01

For over three consecutive years, 2559 Chinese adolescents (mean age = 12.65 years at Wave 1) responded to instruments assessing their perceived parental behavioral control based on measures of parental knowledge, expectation, monitoring, and discipline. The results show that compared with parental control in the academic domain, parental control in the non-academic domain (peer relations domain) was relatively weaker, using parental knowledge, parental expectation, parental monitoring, and parental discipline as indicators, and a decline in parental behavioral control occurred over time. Although domain (academic domain versus non-academic domain) X time (Time 1, Time 2 versus Time 3) interaction effects were found, the findings mirrored the main effects of domain and time. Parental education and economic sufficiency were linearly related to differences in parental behavioral control in the academic domain and non-academic domain. The present findings suggest that traditional Chinese cultural emphasis on academic excellence still prevails in the contemporary Chinese culture.

Beyond rules: The next generation of expert systems

NASA Technical Reports Server (NTRS)

Ferguson, Jay C.; Wagner, Robert E.

1987-01-01

The PARAGON Representation, Management, and Manipulation system is introduced. The concepts of knowledge representation, knowledge management, and knowledge manipulation are combined in a comprehensive system for solving real world problems requiring high levels of expertise in a real time environment. In most applications the complexity of the problem and the representation used to describe the domain knowledge tend to obscure the information from which solutions are derived. This inhibits the acquisition of domain knowledge verification/validation, places severe constraints on the ability to extend and maintain a knowledge base while making generic problem solving strategies difficult to develop. A unique hybrid system was developed to overcome these traditional limitations.

A Collaborative Knowledge Management Process for Implementing Healthcare Enterprise Information Systems

NASA Astrophysics Data System (ADS)

Cheng, Po-Hsun; Chen, Sao-Jie; Lai, Jin-Shin; Lai, Feipei

This paper illustrates a feasible health informatics domain knowledge management process which helps gather useful technology information and reduce many knowledge misunderstandings among engineers who have participated in the IBM mainframe rightsizing project at National Taiwan University (NTU) Hospital. We design an asynchronously sharing mechanism to facilitate the knowledge transfer and our health informatics domain knowledge management process can be used to publish and retrieve documents dynamically. It effectively creates an acceptable discussion environment and even lessens the traditional meeting burden among development engineers. An overall description on the current software development status is presented. Then, the knowledge management implementation of health information systems is proposed.

Knowledge applied to new domains: the unconscious succeeds where the conscious fails.

PubMed

Scott, Ryan B; Dienes, Zoltan

2010-03-01

A common view holds that consciousness is needed for knowledge acquired in one domain to be applied in a novel domain. We present evidence for the opposite; where the transfer of knowledge is achieved only in the absence of conscious awareness. Knowledge of artificial grammars was examined where training and testing occurred in different vocabularies or modalities. In all conditions grammaticality judgments attributed to random selection showed above-chance accuracy (60%), while those attributed to conscious decisions did not. Participants also rated each string's familiarity and performed a perceptual task assessing fluency. Familiarity was predicted by repetition structure and was thus related to grammaticality. Fluency, though increasing familiarity, was unrelated to grammaticality. While familiarity predicted all judgments only those attributed to random selection showed a significant additional contribution of grammaticality, deriving primarily from chunk novelty. In knowledge transfer, as in visual perception (Marcel, 1993), the unconscious may outperform the conscious.

Pay attention! The critical importance of assessing attention in older adults with dementia.

PubMed

Kolanowski, Ann M; Fick, Donna M; Yevchak, Andrea M; Hill, Nikki L; Mulhall, Paula M; McDowell, Jane A

2012-11-01

Attention is an important cognitive domain that is affected in Alzheimer's disease and other dementias. It influences performance in most other cognitive domains, as well as activities of daily living. Nurses are often unaware of the critical importance of assessing attention as part of the overall mental status examination. This article addresses an important gap in nurses' knowledge. The authors present a brief overview of attention as a critical cognitive domain in dementia; review instruments/methods for standardizing and enhancing the assessment of attention; and offer ways to help ensure that best practices in the assessment, recognition, and documentation of inattention are implemented in the clinical area. Clinical resources that practicing nurses may find helpful are included. Copyright 2012, SLACK Incorporated.

Choosing Appropriate Theories for Understanding Hospital Reporting of Adverse Drug Events, a Theoretical Domains Framework Approach.

PubMed

Shalviri, Gloria; Yazdizadeh, Bahareh; Mirbaha, Fariba; Gholami, Kheirollah; Majdzadeh, Reza

2018-01-01

Adverse drug events (ADEs) may cause serious injuries including death. Spontaneous reporting of ADEs plays a great role in detection and prevention of them; however, underreporting always exists. Although several interventions have been utilized to solve this problem, they are mainly based on experience and the rationale for choosing them has no theoretical base. The vast variety of behavioural theories makes it difficult to choose appropriate theory. Theoretical domains framework (TDF) is suggested as a solution. The objective of this study was to select the best theory for evaluating ADE reporting in hospitals based on TDF. We carried out three focus group discussions with hospital pharmacists and nurses, based on TDF questions. The analysis was performed through five steps including coding discussions transcript, extracting beliefs, selecting relevant domains, matching related constructs to the extracted beliefs, and determining the appropriate theories in each domain. The theory with the highest number of matched domains and constructs was selected as the theory of choice. A total of six domains were identified relevant to ADE reporting, including "Knowledge", "Skills", "Beliefs about consequences", "Motivation and goals", "Environmental context and resources" and "Social influences". We found theory of planned behavior as the comprehensive theory to study factors influencing ADE reporting in hospitals, since it was relevant theory in five out of six relevant domains and the common theory in 55 out of 75 identified beliefs. In conclusion, we suggest theory of planned behavior for further studies on designing appropriate interventions to increase ADE reporting in hospitals.

A Preliminary Survey of Professionalism Teaching Practices in Anatomy Education among Indian Medical Colleges

ERIC Educational Resources Information Center

Karunakaran, Ilavenil; Thirumalaikolundusubramanian, Ponniah; Nalinakumari, Sheela Das

2017-01-01

Professionalism and ethics have gained widespread recognition as competencies to be fulfilled, taught, and assessed within medical education. The role of the anatomy course in developed nations has evolved over time and now encompasses multiple domains, including knowledge, skills, and the inculcation of professionalism and ethics. The Medical…

Educating the Educator: Use of Pulse Oximetry in Athletic Training

ERIC Educational Resources Information Center

Berry, David C.; Seitz, S. Robert

2012-01-01

The 5th edition of the "Athletic Training Education Competencies" expanded the scope of knowledge and skill set of entry-level athletic trainers related to the domain of "Acute Care of Injuries and Illnesses." One of these major changes includes the introduction of adjunct airway techniques, such as oropharyngeal and nasopharyngeal airways and…

New knowledge-based genetic algorithm for excavator boom structural optimization

NASA Astrophysics Data System (ADS)

Hua, Haiyan; Lin, Shuwen

2014-03-01

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

Contributions of Domain-General Cognitive Resources and Different Forms of Arithmetic Development to Pre-Algebraic Knowledge

PubMed Central

Fuchs, Lynn S.; Compton, Donald L.; Fuchs, Douglas; Powell, Sarah R.; Schumacher, Robin F.; Hamlett, Carol L.; Vernier, Emily; Namkung, Jessica M.; Vukovic, Rose K.

2012-01-01

The purpose of this study was to investigate the contributions of domain-general cognitive resources and different forms of arithmetic development to individual differences in pre-algebraic knowledge. Children (n=279; mean age=7.59 yrs) were assessed on 7 domain-general cognitive resources as well as arithmetic calculations and word problems at start of 2nd grade and on calculations, word problems, and pre-algebraic knowledge at end of 3rd grade. Multilevel path analysis, controlling for instructional effects associated with the sequence of classrooms in which students were nested across grades 2–3, indicated arithmetic calculations and word problems are foundational to pre-algebraic knowledge. Also, results revealed direct contributions of nonverbal reasoning and oral language to pre-algebraic knowledge, beyond indirect effects that are mediated via arithmetic calculations and word problems. By contrast, attentive behavior, phonological processing, and processing speed contributed to pre-algebraic knowledge only indirectly via arithmetic calculations and word problems. PMID:22409764

Applying Knowledge Management to an Organization's Transformation

NASA Technical Reports Server (NTRS)

Potter, Shannon; Gill, Tracy; Fritsche, Ralph

2008-01-01

Although workers in the information age have more information at their fingertips than ever before, the ability to effectively capture and reuse actual knowledge is still a surmounting challenge for many organizations. As high tech organizations transform from providing complex products and services in an established domain to providing them in new domains, knowledge remains an increasingly valuable commodity. This paper explores the supply and demand elements of the "knowledge market" within the International Space Station and Spacecraft Processing Directorate (ISSSPD) of NASA's Kennedy Space Center (KSC). It examines how knowledge supply and knowledge demand determine the success of an organization's knowledge management (KM) activities, and how the elements of a KM infrastructure (tools, culture, and training), can be used to create and sustain knowledge supply and demand

A Rules-Based Service for Suggesting Visualizations to Analyze Earth Science Phenomena.

NASA Astrophysics Data System (ADS)

Prabhu, A.; Zednik, S.; Fox, P. A.; Ramachandran, R.; Maskey, M.; Shie, C. L.; Shen, S.

2016-12-01

Current Earth Science Information Systems lack support for new or interdisciplinary researchers, who may be unfamiliar with the domain vocabulary or the breadth of relevant data available. We need to evolve the current information systems, to reduce the time required for data preparation, processing and analysis. This can be done by effectively salvaging the "dark" resources in Earth Science. We assert that Earth science metadata assets are dark resources, information resources that organizations collect, process, and store for regular business or operational activities but fail to utilize for other purposes. In order to effectively use these dark resources, especially for data processing and visualization, we need a combination of domain, data product and processing knowledge, i.e. a knowledge base from which specific data operations can be performed. In this presentation, we describe a semantic, rules based approach to provide i.e. a service to visualize Earth Science phenomena, based on the data variables extracted using the "dark" metadata resources. We use Jena rules to make assertions about compatibility between a phenomena and various visualizations based on multiple factors. We created separate orthogonal rulesets to map each of these factors to the various phenomena. Some of the factors we have considered include measurements, spatial resolution and time intervals. This approach enables easy additions and deletions based on newly obtained domain knowledge or phenomena related information and thus improving the accuracy of the rules service overall.

DOLCE ROCKS: Integrating Foundational and Geoscience Ontologies--Preliminary Results for the Integration of Concepts from DOLCE, GeoSciML, and SWEET

NASA Astrophysics Data System (ADS)

Brodaric, B.; Probst, F.

2007-12-01

Ontologies are being developed bottom-up in many geoscience domains to aid semantic-enabled computing. The contents of these ontologies are typically partitioned along domain boundaries, such as geology, geophsyics, hydrology, or are developed for specific data sets or processing needs. At the same time, very general foundational ontologies are being independently developed top-down to help facilitate integration of knowledge across such domains, and to provide homogeneity to the organization of knowledge within the domains. In this work we investigate the suitability of integrating the DOLCE foundational ontology with concepts from two prominent geoscience knowledge representations, GeoSciML and SWEET, to investigate the alignment of the concepts found within the foundational and domain representations. The geoscience concepts are partially mapped to each other and to those in the foundational ontology, via the subclass and other relations, resulting in an integrated OWL-based ontology called DOLCE ROCKS. These preliminary results demonstrate variable alignment between the foundational and domain concepts, and also between the domain concepts. Further work is required to ascertain the impact of this integrated ontology approach on broader geoscience ontology design, on the unification of domain ontologies, as well as their use within semantic-enabled geoscience applications.

Implementation of a frame-based representation in CLIPS

NASA Technical Reports Server (NTRS)

Assal, Hisham; Myers, Leonard

1990-01-01

Knowledge representation is one of the major concerns in expert systems. The representation of domain-specific knowledge should agree with the nature of the domain entities and their use in the real world. For example, architectural applications deal with objects and entities such as spaces, walls, and windows. A natural way of representing these architectural entities is provided by frames. This research explores the potential of using the expert system shell CLIPS, developed by NASA, to implement a frame-based representation that can accommodate architectural knowledge. These frames are similar but quite different from the 'template' construct in version 4.3 of CLIPS. Templates support only the grouping of related information and the assignment of default values to template fields. In addition to these features frames provide other capabilities including definition of classes, inheritance between classes and subclasses, relation of objects of different classes with 'has-a', association of methods (demons) of different types (standard and user-defined) to fields (slots), and creation of new fields at run-time. This frame-based representation is implemented completely in CLIPS. No change to the source code is necessary.

System and method for integrating and accessing multiple data sources within a data warehouse architecture

DOEpatents

Musick, Charles R [Castro Valley, CA; Critchlow, Terence [Livermore, CA; Ganesh, Madhaven [San Jose, CA; Slezak, Tom [Livermore, CA; Fidelis, Krzysztof [Brentwood, CA

2006-12-19

A system and method is disclosed for integrating and accessing multiple data sources within a data warehouse architecture. The metadata formed by the present method provide a way to declaratively present domain specific knowledge, obtained by analyzing data sources, in a consistent and useable way. Four types of information are represented by the metadata: abstract concepts, databases, transformations and mappings. A mediator generator automatically generates data management computer code based on the metadata. The resulting code defines a translation library and a mediator class. The translation library provides a data representation for domain specific knowledge represented in a data warehouse, including "get" and "set" methods for attributes that call transformation methods and derive a value of an attribute if it is missing. The mediator class defines methods that take "distinguished" high-level objects as input and traverse their data structures and enter information into the data warehouse.

Analysis of the trauma section of the orthopaedic in-training examination.

PubMed

Taylor, Benjamin C; Fowler, T Ty

2011-07-07

The Orthopaedic In-Training Examination is a comprehensive test produced annually by the American Academy of Orthopaedic Surgeons, and was first administered in 1963. At the time of the examination's conception, its objectives were to: (1) measure the knowledge of orthopedic residents and provide objective comparisons; (2) help determine acceptable minimal standards for trainees; and (3) help provide an objective assessment of orthopedic education. We retrospectively reviewed all Orthopaedic In-Training Examinations from 2004 to 2008, with particular focus on the questions listed in the musculoskeletal trauma domain on each year's program director report. The musculoskeletal trauma domain, including topics, recommended answers, and references, was reviewed to provide an educational resource for residents and residency programs when studying or designing educational curricula. The information in this analysis may help in development of a core musculoskeletal trauma knowledge base or facilitate determination of appropriate journal club and didactic lecture content. Copyright 2011, SLACK Incorporated.

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

Capturing domain knowledge from multiple sources: the rare bone disorders use case.

PubMed

Groza, Tudor; Tudorache, Tania; Robinson, Peter N; Zankl, Andreas

2015-01-01

Lately, ontologies have become a fundamental building block in the process of formalising and storing complex biomedical information. The community-driven ontology curation process, however, ignores the possibility of multiple communities building, in parallel, conceptualisations of the same domain, and thus providing slightly different perspectives on the same knowledge. The individual nature of this effort leads to the need of a mechanism to enable us to create an overarching and comprehensive overview of the different perspectives on the domain knowledge. We introduce an approach that enables the loose integration of knowledge emerging from diverse sources under a single coherent interoperable resource. To accurately track the original knowledge statements, we record the provenance at very granular levels. We exemplify the approach in the rare bone disorders domain by proposing the Rare Bone Disorders Ontology (RBDO). Using RBDO, researchers are able to answer queries, such as: "What phenotypes describe a particular disorder and are common to all sources?" or to understand similarities between disorders based on divergent groupings (classifications) provided by the underlying sources. RBDO is available at http://purl.org/skeletome/rbdo. In order to support lightweight query and integration, the knowledge captured by RBDO has also been made available as a SPARQL Endpoint at http://bio-lark.org/se_skeldys.html.

Adapting Word Embeddings from Multiple Domains to Symptom Recognition from Psychiatric Notes

PubMed Central

Zhang, Yaoyun; Li, Hee-Jin; Wang, Jingqi; Cohen, Trevor; Roberts, Kirk; Xu, Hua

2018-01-01

Mental health is increasingly recognized an important topic in healthcare. Information concerning psychiatric symptoms is critical for the timely diagnosis of mental disorders, as well as for the personalization of interventions. However, the diversity and sparsity of psychiatric symptoms make it challenging for conventional natural language processing techniques to automatically extract such information from clinical text. To address this problem, this study takes the initiative to use and adapt word embeddings from four source domains – intensive care, biomedical literature, Wikipedia and Psychiatric Forum – to recognize symptoms in the target domain of psychiatry. We investigated four different approaches including 1) only using word embeddings of the source domain, 2) directly combining data of the source and target to generate word embeddings, 3) assigning different weights to word embeddings, and 4) retraining the word embedding model of the source domain using a corpus of the target domain. To the best of our knowledge, this is the first work of adapting multiple word embeddings of external domains to improve psychiatric symptom recognition in clinical text. Experimental results showed that the last two approaches outperformed the baseline methods, indicating the effectiveness of our new strategies to leverage embeddings from other domains. PMID:29888086

Evidence-Based Practice Knowledge, Attitude, Access and Confidence: A comparison of dental hygiene and dental students.

PubMed

Santiago, Victoria; Cardenas, Melissa; Charles, Anne Laure; Hernandez, Estefany; Oyoyo, Udochukwu; Kwon, So Ran

2018-04-01

Purpose: The purpose of this study was to evaluate whether current educational strategies at a dental institution in the United States made a difference in dental hygiene (DNHY) and dental students' (D3) learning outcomes in the four domains of evidence-based practice (EBP), knowledge, attitude, accessing evidence, and confidence (KACE), following a 12-week research design course. Methods: All participants DNHY (n=19) and D3 (n=96) enrolled in the research design course at Loma Linda University completed a paper KACE survey distributed on the first day of class. Students completed the KACE survey once more at the end of the 12-week course. Pre- and post-survey results were compared both within and between the DNHY and D3 student groups to identify the learning outcomes in the four domains of EBP; knowledge, attitude, accessing evidence, and confidence in EBP. Descriptive statistics were conducted to profile all variables in the study; the level of significance was set at α=0.05. Results: All DNHY students (n=19) completed the pre and post KACE surveys; of the D3 (n=96) students enrolled in the course 82% (n=79) competed the post-survey. Comparison of the survey results showed that both DNHY and D3 students demonstrated statistically significant increases in their level of knowledge and attitude (p < 0.05) towards EBP. In the attitude domain, DNHY students indicated more positive attitudes towards EBP (p < 0.001) than their D3 student cohorts. Neither group demonstrated significant changes in confidence in applying EBP (p > 0.05). Conclusion: DNHY and D3 students increased their knowledge and developed more positive attitudes towards EBP following a 12-week research design course. Study results identify improvement areas for EBP knowledge acquisition including determining levels of evidence, analysis of study results, and evaluating the appropriateness of research study designs through the use of validated EBP survey instrument. Copyright © 2018 The American Dental Hygienists’ Association.

Formalizing Knowledge in Multi-Scale Agent-Based Simulations

PubMed Central

Somogyi, Endre; Sluka, James P.; Glazier, James A.

2017-01-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

PubMed

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

Learning and Reasoning in Unknown Domains

NASA Astrophysics Data System (ADS)

Strannegård, Claes; Nizamani, Abdul Rahim; Juel, Jonas; Persson, Ulf

2016-12-01

In the story Alice in Wonderland, Alice fell down a rabbit hole and suddenly found herself in a strange world called Wonderland. Alice gradually developed knowledge about Wonderland by observing, learning, and reasoning. In this paper we present the system Alice In Wonderland that operates analogously. As a theoretical basis of the system, we define several basic concepts of logic in a generalized setting, including the notions of domain, proof, consistency, soundness, completeness, decidability, and compositionality. We also prove some basic theorems about those generalized notions. Then we model Wonderland as an arbitrary symbolic domain and Alice as a cognitive architecture that learns autonomously by observing random streams of facts from Wonderland. Alice is able to reason by means of computations that use bounded cognitive resources. Moreover, Alice develops her belief set by continuously forming, testing, and revising hypotheses. The system can learn a wide class of symbolic domains and challenge average human problem solvers in such domains as propositional logic and elementary arithmetic.

Domain-specific learning of grammatical structure in musical and phonological sequences.

PubMed

Bly, Benjamin Martin; Carrión, Ricardo E; Rasch, Björn

2009-01-01

Artificial grammar learning depends on acquisition of abstract structural representations rather than domain-specific representational constraints, or so many studies tell us. Using an artificial grammar task, we compared learning performance in two stimulus domains in which respondents have differing tacit prior knowledge. We found that despite grammatically identical sequence structures, learning was better for harmonically related chord sequences than for letter name sequences or harmonically unrelated chord sequences. We also found transfer effects within the musical and letter name tasks, but not across the domains. We conclude that knowledge acquired in implicit learning depends not only on abstract features of structured stimuli, but that the learning of regularities is in some respects domain-specific and strongly linked to particular features of the stimulus domain.

Incursions from the epicentre: Southern theory, social science, and the global HIV research domain.

PubMed

Hodes, Rebecca; Morrell, Robert

2018-03-01

Research about HIV constitutes a global domain of academic knowledge. The patterns that structure this domain reflect inequalities in the production and dissemination of knowledge, as well as broader inequalities in geopolitics. Conventional metrics for assessing the value and impact of academic research reveal that "Northern" research remains dominant, while "Southern" research remains peripheral. Southern theory provides a framework for greater critical engagement with knowledge produced by researchers within the global South. With a focus on HIV social science, we show that investigators working in and from Africa have produced and disseminated knowledge fundamental to the global domain of HIV research, and argue that their epistemological contribution may be understood within the framework of Southern theory. Through repurposing a bibliometrical measure of citation count, we constitute a new archive of highly cited social science research. With a focus on South Africa, we situate this archive within changing historical contexts, connecting research findings to developments in medicine, health sciences and politics. We focus on two key themes in the evolution of HIV knowledge: (1) the significance of context and locality - the "setting" of HIV research; and (2) sex, race and risk - changing ideas about the social determinants of HIV transmission.

A future Outlook: Web based Simulation of Hydrodynamic models

NASA Astrophysics Data System (ADS)

Islam, A. S.; Piasecki, M.

2003-12-01

Despite recent advances to present simulation results as 3D graphs or animation contours, the modeling user community still faces some shortcomings when trying to move around and analyze data. Typical problems include the lack of common platforms with standard vocabulary to exchange simulation results from different numerical models, insufficient descriptions about data (metadata), lack of robust search and retrieval tools for data, and difficulties to reuse simulation domain knowledge. This research demonstrates how to create a shared simulation domain in the WWW and run a number of models through multi-user interfaces. Firstly, meta-datasets have been developed to describe hydrodynamic model data based on geographic metadata standard (ISO 19115) that has been extended to satisfy the need of the hydrodynamic modeling community. The Extended Markup Language (XML) is used to publish this metadata by the Resource Description Framework (RDF). Specific domain ontology for Web Based Simulation (WBS) has been developed to explicitly define vocabulary for the knowledge based simulation system. Subsequently, this knowledge based system is converted into an object model using Meta Object Family (MOF). The knowledge based system acts as a Meta model for the object oriented system, which aids in reusing the domain knowledge. Specific simulation software has been developed based on the object oriented model. Finally, all model data is stored in an object relational database. Database back-ends help store, retrieve and query information efficiently. This research uses open source software and technology such as Java Servlet and JSP, Apache web server, Tomcat Servlet Engine, PostgresSQL databases, Protégé ontology editor, RDQL and RQL for querying RDF in semantic level, Jena Java API for RDF. Also, we use international standards such as the ISO 19115 metadata standard, and specifications such as XML, RDF, OWL, XMI, and UML. The final web based simulation product is deployed as Web Archive (WAR) files which is platform and OS independent and can be used by Windows, UNIX, or Linux. Keywords: Apache, ISO 19115, Java Servlet, Jena, JSP, Metadata, MOF, Linux, Ontology, OWL, PostgresSQL, Protégé, RDF, RDQL, RQL, Tomcat, UML, UNIX, Windows, WAR, XML

CHAMPION: Intelligent Hierarchical Reasoning Agents for Enhanced Decision Support

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

Hohimer, Ryan E.; Greitzer, Frank L.; Noonan, Christine F.

2011-11-15

We describe the design and development of an advanced reasoning framework employing semantic technologies, organized within a hierarchy of computational reasoning agents that interpret domain specific information. Designed based on an inspirational metaphor of the pattern recognition functions performed by the human neocortex, the CHAMPION reasoning framework represents a new computational modeling approach that derives invariant knowledge representations through memory-prediction belief propagation processes that are driven by formal ontological language specification and semantic technologies. The CHAMPION framework shows promise for enhancing complex decision making in diverse problem domains including cyber security, nonproliferation and energy consumption analysis.

Comprehension of University Texts: Effects of Domain-Knowledge and Summary

ERIC Educational Resources Information Center

Pascual, Gema; Goikoetxea, Edurne

2014-01-01

Our aim is to evaluate reading comprehension strategies based on empirical evidence and applicable to undergraduate students. Our hypotheses were that domain-knowledge or summary would have more influence on local, global, and inferential questions than rereading-question-answering instruction. Results of Experiment 1 were mixed in terms of…

Developing Domain Ontologies for Course Content

ERIC Educational Resources Information Center

Boyce, Sinead; Pahl, Claus

2007-01-01

Ontologies have the potential to play an important role in instructional design and the development of course content. They can be used to represent knowledge about content, supporting instructors in creating content or learners in accessing content in a knowledge-guided way. While ontologies exist for many subject domains, their quality and…

Elaborative-Interrogation and Prior-Knowledge Effects on Learning of Facts.

ERIC Educational Resources Information Center

Woloshyn, Vera E.; And Others

1992-01-01

The differences among elaborative-interrogation, reading-to-understand, and no-exposure control conditions with familiar domain material in contrast to unfamiliar domain material were studied for 50 Canadian and 50 west German undergraduates. Results provide evidence of effects of both elaborative interrogation and prior knowledge on learning.…

An Ontology for Learning Services on the Shop Floor

ERIC Educational Resources Information Center

Ullrich, Carsten

2016-01-01

An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as…

Descriptive Analysis of the Graphic Representations of Science Textbooks

ERIC Educational Resources Information Center

Khine, Myint Swe; Liu, Yang

2017-01-01

Textbooks are primary teaching aids, sources from which students obtain knowledge of science domain. Due to this fact, curriculum developers in the field emphasize the crucial role of analysing the contents of science textbooks in improving science education. Scientific domain knowledge relies on graphical representations for the manifestation of…

Mapping University Students' Epistemic Framing of Computational Physics Using Network Analysis

ERIC Educational Resources Information Center

Bodin, Madelen

2012-01-01

Solving physics problem in university physics education using a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modeling. These competences are in turn related to students' beliefs about the domains as well as about learning. These knowledge and beliefs components are…

Detailed Knowledge About HIV Epidemiology and Transmission Dynamics and Their Associations With Preventive and Risk Behaviors Among Gay, Bisexual, and Other Men Who Have Sex With Men in the United States

PubMed Central

Sullivan, Stephen P; Stephenson, Rob B

2017-01-01

Background Gay, bisexual, and other men who have sex with men (GBMSM) in the United States remain disproportionately affected by human immunodeficiency virus (HIV). Yet their testing frequency is suboptimal and condomless anal sex (CAS) is increasing. Behavioral theories posit that information about HIV is a pivotal construct in individual risk reduction. However, measurements of knowledge have traditionally focused on ever hearing about HIV and being aware of the most common routes of spread. Objective Using a national Web-based sample of sexually active GBMSM, we sought to (1) quantify levels of detailed knowledge about HIV epidemiology and transmission dynamics, (2) describe variations in detailed knowledge levels across demographic strata, and (3) evaluate potential associations of increasing levels of detailed knowledge with HIV testing in the past year and engaging in CAS with a male partner in the past 3 months. Methods GBMSM were recruited through a social networking website (Facebook) from August to September 2015 and asked 17 knowledge-based questions pertaining to the following 2 domains using a Web-based survey: HIV epidemiology (9 questions including statistics on incidence, prevalence, and distribution) and HIV transmission dynamics (8 questions including modes of spread and per-act transmission probabilities). Ordinal domain-specific indices of detailed knowledge were created for each respondent by summing their number of correct responses. Separate cumulative logit models were used to identify factors independently associated with each index, and multivariable logistic regression models were used to characterize associations with HIV testing history and recently engaging in CAS. Results Of the 1064 participants in our study, only half (49.62%, 528/1064) had been tested for HIV in the past year, and almost half (47.84%, 509/1064) had engaged in CAS with a male partner in the past 3 months. Majority scored 3 of 9 epidemiology questions correct (26.88%, 286/1064) and 5 of 8 transmission dynamics questions correct (25.00%, 266/1064). Participants younger than 35 years, of non-Hispanic non-white or Hispanic race and ethnicity, with lower educational levels, and who reported a sexual orientation other than homosexual or gay were significantly less knowledgeable about HIV transmission dynamics. Increasing levels of knowledge about this domain were independently associated with testing in the past year (adjusted odds ratio for each additional correct response: 1.10, 95% CI 1.01-1.20) but not with recent CAS. Increasing knowledge about HIV epidemiology was not associated with either outcome. Conclusions Increasing detailed knowledge about HIV epidemiology might not be as important as educating sexually active GBMSM regarding transmission dynamics. Researchers and practitioners designing prevention messages targeting GBMSM should bear in mind that not all knowledge is equal and that some aspects might have a greater positive impact than others. Future research to identify influential content and contemporary modes of delivery is needed. PMID:28264795

The palliative care knowledge questionnaire for PEACE: reliability and validity of an instrument to measure palliative care knowledge among physicians.

PubMed

Yamamoto, Ryo; Kizawa, Yoshiyuki; Nakazawa, Yoko; Morita, Tatsuya

2013-11-01

In Japan, a nationwide palliative care education program for primary palliative care (the Palliative care Emphasis program on symptom management and Assessment for Continuous medical Education: PEACE) was established in 2008. Effective delivery of such programs relies on adequate evaluations of program efficacy; however, such an instrument does not exist. This study aimed to develop and validate a measurement tool to quantify knowledge level of physicians about broader areas of palliative care, by which the effect of an education program could be measured. We conducted a cross-sectional, anonymous, self-administered questionnaire survey with a group of 801 conveniently sampled physicians in October 2010. To examine the test-retest reliability of items and domains, the questionnaire was reissued two weeks after the first survey was completed. This study used psychometric methods, including item response theory, intraclass correlation coefficients, and known-group validity. The response rate was 54% (n=434). We included 33 items across the following 9 domains: (1) philosophy of palliative care, (2) cancer pain, (3) side effects of opioids, (4) dyspnea, (5) nausea and vomiting, (6) psychological distress, (7) delirium, (8) communication regarding palliative care, and (9) community-based palliative care. For these items, the intraclass correlation was 0.84 and the Kuder-Richardson Formula 20 (KR-20) test of internal consistency was 0.87. There was a significant difference in the scores between palliative care specialists and other physicians. We successfully validated a newly developed palliative care knowledge questionnaire to evaluate PEACE effectiveness (PEACE-Q). The PEACE-Q could be useful for evaluating both palliative care knowledge among physicians and education programs in primary palliative care.

Investigating implicit knowledge in ontologies with application to the anatomical domain.

PubMed

Zhang, S; Bodenreider, O

2004-01-01

Knowledge in biomedical ontologies can be explicitly represented (often by means of semantic relations), but may also be implicit, i.e., embedded in the concept names and inferable from various combinations of semantic relations. This paper investigates implicit knowledge in two ontologies of anatomy: the Foundational Model of Anatomy and GALEN. The methods consist of extracting the knowledge explicitly represented, acquiring the implicit knowledge through augmentation and inference techniques, and identifying the origin of each semantic relation. The number of relations (12 million in FMA and 4.6 million in GALEN), broken down by source, is presented. Major findings include: each technique provides specific relations; and many relations can be generated by more than one technique. The application of these findings to ontology auditing, validation, and maintenance is discussed, as well as the application to ontology integration.

The correlation between ostomy knowledge and self-care ability with psychosocial adjustment in Chinese patients with a permanent colostomy: a descriptive study .

PubMed

Cheng, Fang; Meng, Ai-feng; Yang, Li-Fang; Zhang, Yi-nan

2013-07-01

A colostomy can have a negative impact on patient quality of life. Research suggests that psychosocial adaptation is positively associated with quality of life, but few reports address this adaptation and its related factors in patients with a permanent colostomy. A 4-month, descriptive study was conducted to assess the impact of ostomy knowledge and ability to self-care on the psychosocial adjustment of 54 Chinese outpatients (47 men, 14 participants 40 to 50 years old, 40 participants 50 to 70 years old) with a permanent colostomy to investigate the correlation between stoma knowledge, self-care ability, and psychosocial adjustment. Assessment instruments included a sociodemographic data questionnaire and a Chinese translation of the Ostomy Adjustment Inventory-23 that comprises 20 items in three domains (positive emotions, negative emotions, and social life). Participants rated statements on a scale from 0 (totally disagree) to 4 (totally agree); a score of 40 indicates a low level of psychosocial adjustment. Participants also completed the Stoma-related Knowledge Scale, comprising 14 5-point Likert scale questions where low scores indicate low knowledge, and they answered one question regarding self-care ability. Data were analyzed using statistical software for social science. The average stoma-related knowledge score suggested moderate levels of knowledge (45.112 ± 13.358). Twenty (20) participants managed all stoma care aspects independently, 30 required some assistance, and four (4) required care by someone else. The three domains of psychosocial adjustment scores (positive emotions, negative emotions, and social life) were 17.60 ± 4.093,12.92 ± 3.440, and 19.15 ± 6.316, respectively. Knowledge and the three domains of psychosocial adjustment were positively correlated with positive emotion (r = .610, P = 0.001), negative emotion (r = .696, P = 0.000), and social life adjustment (r = .617, P = 0.001). A significant difference in psychosocial adjustment scores was found between persons who did (57.37 ± 9.81) and those that did not (47.83 ± 8.18) independently care for their own stoma (P = 0.005). Persons with high levels of knowledge and independence had a high level of psychosocial adjustment. Providing knowledge and emphasizing/teaching self-care may help persons with a colostomy make the necessary daily and social life adaptations.

Multidisciplinary Analysis of Cyclophilin A Function in Human Breast Cancer

DTIC Science & Technology

2011-03-01

4 INTRODUCTION The growth and progression of human breast cancer is regulated by several cell surface receptors, including the...substantively to the biology of human breast cancer through its regulation of cell surface signaling, including that of the PRLr. We believe that the knowledge... dynamic structure of CypA in complex with PRLr and its proximal molecule Jak2. We have purified recombinant CypA, the intracellular domain (ICD) of

Developmental Foundations of Children's Fraction Magnitude Knowledge.

PubMed

Mou, Yi; Li, Yaoran; Hoard, Mary K; Nugent, Lara D; Chu, Felicia W; Rouder, Jeffrey N; Geary, David C

2016-01-01

The conceptual insight that fractions represent magnitudes is a critical yet daunting step in children's mathematical development, and the knowledge of fraction magnitudes influences children's later mathematics learning including algebra. In this study, longitudinal data were analyzed to identify the mathematical knowledge and domain-general competencies that predicted 8 th and 9 th graders' (n=122) knowledge of fraction magnitudes and its cross-grade gains. Performance on the fraction magnitude measures predicted 9 th grade algebra achievement. Understanding and fluently identifying the numerator-denominator relation in 7 th grade emerged as the key predictor of later fraction magnitudes knowledge in both 8 th and 9 th grades. Competence at using fraction procedures, knowledge of whole number magnitudes, and the central executive contributed to 9 th but not 8 th graders' fraction magnitude knowledge, and knowledge of whole number magnitude contributed to cross-grade gains. The key results suggest fluent processing of numerator-denominator relations presages students' understanding of fractions as magnitudes and that the integration of whole number and fraction magnitudes occurs gradually.

Essential nurse practitioner business knowledge: An interprofessional perspective.

PubMed

LaFevers, David; Ward-Smith, Peggy; Wright, Wendy

2015-04-01

To describe business practice knowledge from the perspectives of nurse practitioners (NPs) who are practicing clinicians, academic instructors, and clinic managers. Using the eight domains of business practice attitudes identified by the Medical Group Management Associations Body of Knowledge (MGMA), which are supported by the American Association of Colleges of Nursing (AACN), a study-specific survey was developed. Data, which describe the knowledge and attitudes with respect to business practices, were obtained from 370 participants. Regardless of their job classification, these participants described (1) quality management, (2) risk management, and (3) patient care systems as critical business practice knowledge. Consensus was also achieved when ranking the content for business practice knowledge: (1) patient care systems, (2) business operation, and (3) financial management. These data identify gaps in business practice knowledge and content that should be included in educational programs. Business practice knowledge is essential for a successful clinical practice and should be a professional practice skill for the NP. ©2015 American Association of Nurse Practitioners.

Learning to Predict Consequences as a Method of Knowledge Transfer in Reinforcement Learning.

PubMed

Chalmers, Eric; Contreras, Edgar Bermudez; Robertson, Brandon; Luczak, Artur; Gruber, Aaron

2017-04-17

The reinforcement learning (RL) paradigm allows agents to solve tasks through trial-and-error learning. To be capable of efficient, long-term learning, RL agents should be able to apply knowledge gained in the past to new tasks they may encounter in the future. The ability to predict actions' consequences may facilitate such knowledge transfer. We consider here domains where an RL agent has access to two kinds of information: agent-centric information with constant semantics across tasks, and environment-centric information, which is necessary to solve the task, but with semantics that differ between tasks. For example, in robot navigation, environment-centric information may include the robot's geographic location, while agent-centric information may include sensor readings of various nearby obstacles. We propose that these situations provide an opportunity for a very natural style of knowledge transfer, in which the agent learns to predict actions' environmental consequences using agent-centric information. These predictions contain important information about the affordances and dangers present in a novel environment, and can effectively transfer knowledge from agent-centric to environment-centric learning systems. Using several example problems including spatial navigation and network routing, we show that our knowledge transfer approach can allow faster and lower cost learning than existing alternatives.

S3QL: A distributed domain specific language for controlled semantic integration of life sciences data

PubMed Central

2011-01-01

Background The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control. We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data. Results Reflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases. Conclusions S3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms. PMID:21756325

S3QL: a distributed domain specific language for controlled semantic integration of life sciences data.

PubMed

Deus, Helena F; Correa, Miriã C; Stanislaus, Romesh; Miragaia, Maria; Maass, Wolfgang; de Lencastre, Hermínia; Fox, Ronan; Almeida, Jonas S

2011-07-14

The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control.We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data. Reflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases. S3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms.

The knowledge translation status in selected Eastern-Mediterranean universities and research institutes.

PubMed

Maleki, Katayoun; Hamadeh, Randah R; Gholami, Jaleh; Mandil, Ahmed; Hamid, Saima; Butt, Zahid Ahmad; Bin Saeed, Abdulaziz; El Kheir, Dalia Y M; Saleem, Mohammed; Maqsoud, Sahar; Safi, Najibullah; Abdul-Majeed, Ban A; Majdzadeh, Reza

2014-01-01

A serious worldwide effort to strengthen research based knowledge translation (KT) has begun in recent years and some countries, particularly developed ones, are trying to incorporate KT in their health and health research systems. Keeping in mind the recent economic depression and the need to perform more efficient research, we aimed to assess and compare the KT status of selected health research institutes in the Eastern Mediterranean Regions' countries, and to identify their strengths and weaknesses in the field. After finding the focal points that would steer the focus group discussions (FGDs) and help complete the 'Self Assessment Tool for Research Institutes' (SATORI) tool, each focal point held two FGDs in which researchers, research authorities and other individuals specified in detail further in the study were held. The scores obtained by each institute were evaluated quantitatively, and the transcriptions were analyzed qualitatively with OpenCode software. For ease of analysis the 50 items of the SATORI were classified into 7 main domains: 'priority setting', 'research quality and timeliness', 'researchers' KT capacities', 'facilities and pre-requisites of KT', 'processes and regulations supporting KT', 'interaction with research users', and 'promoting and evaluating the use of knowledge'. Based on the scoring system, the strongest domain was 'research quality and timeliness'. 'Priority setting' was the weakest domain of all. The remaining domains were more or less equal in strength and were not in a favorable state. The qualitative findings confirmed the quantitative findings. The main problem, it seems, is that a KT climate does not exist in the region. And despite the difference in the contexts, there are many similarities in the region's institutes included in this study. Collaborative efforts can play a role in creating this climate by steering countries towards KT and suggesting regional strategic directions according to their needs.

Combined constraints on the structure and physical properties of the East Antarctic lithosphere from geology and geophysics.

NASA Astrophysics Data System (ADS)

Reading, A. M.; Staal, T.; Halpin, J.; Whittaker, J. M.; Morse, P. E.

2017-12-01

The lithosphere of East Antarctica is one of the least explored regions of the planet, yet it is gaining in importance in global scientific research. Continental heat flux density and 3D glacial isostatic adjustment studies, for example, rely on a good knowledge of the deep structure in constraining model inputs.In this contribution, we use a multidisciplinary approach to constrain lithospheric domains. To seismic tomography models, we add constraints from magnetic studies and also new geological constraints. Geological knowledge exists around the periphery of East Antarctica and is reinforced in the knowledge of plate tectonic reconstructions. The subglacial geology of the Antarctic hinterland is largely unknown but the plate reconstructions allow the well-posed extrapolation of major terranes into the interior of the continent, guided by the seismic tomography and magnetic images. We find that the northern boundary of the lithospheric domain centred on the Gamburtsev Subglacial Mountains has a possible trend that runs south of the Lambert Glacier region, turning coastward through Wilkes Land. Other periphery-to-interior connections are less well constrained and the possibility of lithospheric domains that are entirely sub-glacial is high. We develop this framework to include a probabilistic method of handling alternate models and quantifiable uncertainties. We also show first results in using a Bayesian approach to predicting lithospheric boundaries from multivariate data.Within the newly constrained domains, we constrain heat flux (density) as the sum of basal heat flux and upper crustal heat flux. The basal heat flux is constrained by geophysical methods while the upper crustal heat flux is constrained by geology or predicted geology. In addition to heat flux constraints, we also consider the variations in friction experienced by moving ice sheets due to varying geology.

Adaptive Semantic and Social Web-based learning and assessment environment for the STEM

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

2014-05-01

We are building a cloud- and Semantic Web-based personalized, adaptive learning environment for the STEM fields that integrates and leverages Social Web technologies to allow instructors and authors of learning material to collaborate in semi-automatic development and update of their common domain and task ontologies and building their learning resources. The semi-automatic ontology learning and development minimize issues related to the design and maintenance of domain ontologies by knowledge engineers who do not have any knowledge of the domain. The social web component of the personal adaptive system will allow individual and group learners to interact with each other and discuss their own learning experience and understanding of course material, and resolve issues related to their class assignments. The adaptive system will be capable of representing key knowledge concepts in different ways and difficulty levels based on learners' differences, and lead to different understanding of the same STEM content by different learners. It will adapt specific pedagogical strategies to individual learners based on their characteristics, cognition, and preferences, allow authors to assemble remotely accessed learning material into courses, and provide facilities for instructors to assess (in real time) the perception of students of course material, monitor their progress in the learning process, and generate timely feedback based on their understanding or misconceptions. The system applies a set of ontologies that structure the learning process, with multiple user friendly Web interfaces. These include the learning ontology (models learning objects, educational resources, and learning goal); context ontology (supports adaptive strategy by detecting student situation), domain ontology (structures concepts and context), learner ontology (models student profile, preferences, and behavior), task ontologies, technological ontology (defines devices and places that surround the student), pedagogy ontology, and learner ontology (defines time constraint, comment, profile).

A knowledge engineering taxonomy for intelligent tutoring system development

NASA Technical Reports Server (NTRS)

Fink, Pamela K.; Herren, L. Tandy

1993-01-01

This paper describes a study addressing the issue of developing an appropriate mapping of knowledge acquisition methods to problem types for intelligent tutoring system development. Recent research has recognized that knowledge acquisition methodologies are not general across problem domains; the effectiveness of a method for obtaining knowledge depends on the characteristics of the domain and problem solving task. Southwest Research Institute developed a taxonomy of problem types by evaluating the characteristics that discriminate between problems and grouping problems that share critical characteristics. Along with the problem taxonomy, heuristics that guide the knowledge acquisition process based on the characteristics of the class are provided.

The Coherence Formation Model of Illustrated Text Comprehension: A Path Model of Attention to Multimedia Text

ERIC Educational Resources Information Center

Fitzhugh, Shannon Leigh

2012-01-01

The study reported here tests a model that includes several factors thought to contribute to the comprehension of static multimedia learning materials (i.e. background knowledge, working memory, attention to components as measured with eye movement measures). The model examines the effects of working memory capacity, domain specific (biology) and…

Analyzing the Use of Concept Maps in Computer Science: A Systematic Mapping Study

ERIC Educational Resources Information Center

dos Santos, Vinicius; de Souza, Érica F.; Felizardo, Katia R; Vijaykumar, Nandamudi L.

2017-01-01

Context: concept Maps (CMs) enable the creation of a schematic representation of a domain knowledge. For this reason, CMs have been applied in different research areas, including Computer Science. Objective: the objective of this paper is to present the results of a systematic mapping study conducted to collect and evaluate existing research on…

Why Arts Integration Improves Long-Term Retention of Content

ERIC Educational Resources Information Center

Rinne, Luke; Gregory, Emma; Yarmolinskaya, Julia; Hardiman, Mariale

2011-01-01

Advocates of the arts agree that the K-12 curriculum should include dedicated time for arts instruction. Some have argued further that knowledge and skills acquired through the arts transfer to nonarts domains. Others claim that evidence of this kind of transfer is limited and instead argue that the arts cultivate valuable dispositions that help…

In-Between Fatalism and Leverage: The Different Effects of Socioeconomic Variables on Students' Civic and Political Experiences and Literacy

ERIC Educational Resources Information Center

Malafaia, Carla; Neves, Tiago; Menezes, Isabel

2017-01-01

Purpose: This article explores the classical relationship between socioeconomic status and political domains, and the need to include different variables (contextual and individual) to measure the effect of economic and cultural capitals on youth participation and knowledge. Method: A multivariate analysis of covariance was performed on a sample…

Effects of Dialogic Learning on Value-Loaded Critical Thinking

ERIC Educational Resources Information Center

Frijters, Stan; ten Dam, Geert; Rijlaarsdam, Gert

2008-01-01

Education should endeavour to include the competences that students need to participate in a democratic society in a responsible and adequate way. The crucial question is how this can be realized in a curriculum aimed at domain-specific knowledge and skills and organized in school subjects. In this article we present a study on teaching…

Barriers and facilitators to hospital pharmacists' engagement in medication safety activities: a qualitative study using the theoretical domains framework.

PubMed

Mekonnen, Alemayehu B; McLachlan, Andrew J; Brien, Jo-Anne E; Mekonnen, Desalew; Abay, Zenahebezu

2018-01-01

Hospital pharmacists play a central role in medication safety activities. However, in Ethiopia, this role has been launched recently and little is known regarding the current status of this extended service. Using the Theoretical Domains Framework (TDF), we aimed to identify the barriers and facilitators to hospital pharmacists' engagement in medication safety activities across various public hospitals in the Amhara region of Ethiopia. Eight focus group discussions, using an interview guide that was drawn upon the TDF, were conducted with 44 hospital pharmacists to explore their beliefs regarding their involvement in clinical services. Group discussions were audio-recorded, transcribed verbatim, and analysed using directed content analysis based on the TDF. Relevant domains were identified by applying relevance criteria to each of the domains in the TDF. Content analysis revealed six domains that influence hospital pharmacists' engagement in medication safety activities. These domains included 'Knowledge', 'Skills', 'Environmental context and resources', 'Motivations and goals', 'Social influences' and 'Social/professional role'. Most hospital pharmacists believed knowledge gap was an issue, as was the lack of training and supportive skills although some expressed as they were competent enough for their skills in identifying medication related problems. Most participants were very much enthusiastic for their extended roles and were positive towards the future of the profession; however, competing priorities along with the lack of remuneration and awareness (of other health care professionals) regarding the profession's role were barriers to service delivery. There were also a number of resource constraints, such as staffing, infrastructure and government funding, and acceptance rate of pharmacist's recommendation that were likely to influence the clinical practice of pharmacists. Using the TDF , this study identified a wide range of barriers and facilitators to hospital pharmacists' engagement in medication safety activities in resource-limited settings. There existed considerable interrelationships between domains that were perceived to influence hospital pharmacists' behaviours, and this may assist in designing behaviour change interventions that target common behavioural domains.

"BioONT": Improving Knowledge Organization and Representation in the Domain of Biometric Authentication

ERIC Educational Resources Information Center

Buerle, Stephen

2017-01-01

This dissertation explores some of the fundamental challenges facing the information assurance community as it relates to knowledge categorization, organization and representation within the field of information security and more specifically within the domain of biometric authentication. A primary objective of this research is the development of…

Applying Cognitive Science to Education: Thinking and Learning in Scientific and Other Complex Domains

ERIC Educational Resources Information Center

Reif, Frederick

2008-01-01

Many students find it difficult to learn the kinds of knowledge and thinking required by college or high school courses in mathematics, science, or other complex domains. Thus they often emerge with significant misconceptions, fragmented knowledge, and inadequate problem-solving skills. Most instructors or textbook authors approach their teaching…

Constructing Domain-Specific Knowledge in Kindergarten: Relations among Knowledge, Intelligence, and Strategic Performance

ERIC Educational Resources Information Center

Alexander, Joyce M.; Johnson, Kathy E.; Leibham, Mary E.; DeBauge, Christiane

2005-01-01

Thirty kindergarten children from two classrooms participated in a 3-week curricular unit on dinosaurs designed to teach taxonomic relations and distinguishing features aligned with 15 dinosaur species. Both domain-specific learning and strategic performance on a Twenty Questions game were assessed twice throughout the curriculum, as well as…

Research in the Hard Sciences, and in Very Hard "Softer" Domains

ERIC Educational Resources Information Center

Phillips, D. C.

2014-01-01

The author of this commentary argues that physical scientists are attempting to advance knowledge in the so-called hard sciences, whereas education researchers are laboring to increase knowledge and understanding in an "extremely hard" but softer domain. Drawing on the work of Popper and Dewey, this commentary highlights the relative…

Making Connections in Math: Activating a Prior Knowledge Analogue Matters for Learning

ERIC Educational Resources Information Center

Sidney, Pooja G.; Alibali, Martha W.

2015-01-01

This study investigated analogical transfer of conceptual structure from a prior-knowledge domain to support learning in a new domain of mathematics: division by fractions. Before a procedural lesson on division by fractions, fifth and sixth graders practiced with a surface analogue (other operations on fractions) or a structural analogue (whole…

Self-Monitoring and Its Relationship to Medical Knowledge

ERIC Educational Resources Information Center

McConnell, Meghan M.; Regehr, Glenn; Wood, Timothy J.; Eva, Kevin W.

2012-01-01

In the domain of self-assessment, researchers have begun to draw distinctions between summative self-assessment activities (i.e., making an overall judgment of one's ability in a particular domain) and self-monitoring processes (i.e., an "in the moment" awareness of whether one has the necessary knowledge or skills to address a specific…

A Knowledge Engineering Approach to Develop Domain Ontology

ERIC Educational Resources Information Center

Yun, Hongyan; Xu, Jianliang; Xiong, Jing; Wei, Moji

2011-01-01

Ontologies are one of the most popular and widespread means of knowledge representation and reuse. A few research groups have proposed a series of methodologies for developing their own standard ontologies. However, because this ontological construction concerns special fields, there is no standard method to build domain ontology. In this paper,…

Influence of Domain Knowledge on Monitoring Performance across the Life Span

ERIC Educational Resources Information Center

Löffler, Elisabeth; von der Linden, Nicole; Schneider, Wolfgang

2016-01-01

Two studies were conducted to investigate effects of domain knowledge on metacognitive monitoring across the life span in materials of different complexity. Participants from 4 age groups (3rd-grade children, adolescents, younger and older adults) were compared using an expert-novice paradigm. In Study 1, soccer experts' and novices'…

Improved ant colony optimization for optimal crop and irrigation water allocation by incorporating domain knowledge

USDA-ARS?s Scientific Manuscript database

An improved ant colony optimization (ACO) formulation for the allocation of crops and water to different irrigation areas is developed. The formulation enables dynamic adjustment of decision variable options and makes use of visibility factors (VFs, the domain knowledge that can be used to identify ...

(Mis)Perceptions of Continuing Education: Insights from Knowledge Translation, Quality Improvement, and Patient Safety Leaders

ERIC Educational Resources Information Center

Kitto, Simon C.; Bell, Mary; Goldman, Joanne; Peller, Jennifer; Silver, Ivan; Sargeant, Joan; Reeves, Scott

2013-01-01

Introduction: Minimal attention has been given to the intersection and potential collaboration among the domains of continuing education (CE), knowledge translation (KT), quality improvement (QI), and patient safety (PS), despite their overlapping objectives. A study was undertaken to examine leaders' perspectives of these 4 domains and their…

Medical Group Structural Integration May Not Ensure That Care Is Integrated, From The Patient's Perspective.

PubMed

Kerrissey, Michaela J; Clark, Jonathan R; Friedberg, Mark W; Jiang, Wei; Fryer, Ashley K; Frean, Molly; Shortell, Stephen M; Ramsay, Patricia P; Casalino, Lawrence P; Singer, Sara J

2017-05-01

Structural integration is increasing among medical groups, but whether these changes yield care that is more integrated remains unclear. We explored the relationships between structural integration characteristics of 144 medical groups and perceptions of integrated care among their patients. Patients' perceptions were measured by a validated national survey of 3,067 Medicare beneficiaries with multiple chronic conditions across six domains that reflect knowledge and support of, and communication with, the patient. Medical groups' structural characteristics were taken from the National Study of Physician Organizations and included practice size, specialty mix, technological capabilities, and care management processes. Patients' survey responses were most favorable for the domain of test result communication and least favorable for the domain of provider support for medication and home health management. Medical groups' characteristics were not consistently associated with patients' perceptions of integrated care. However, compared to patients of primary care groups, patients of multispecialty groups had strong favorable perceptions of medical group staff knowledge of patients' medical histories. Opportunities exist to improve patient care, but structural integration of medical groups might not be sufficient for delivering care that patients perceive as integrated. Project HOPE—The People-to-People Health Foundation, Inc.

Drawing on Experience: How Domain Knowledge Is Reflected in Sketches of Scientific Structures and Processes

NASA Astrophysics Data System (ADS)

Jee, Benjamin D.; Gentner, Dedre; Uttal, David H.; Sageman, Bradley; Forbus, Kenneth; Manduca, Cathryn A.; Ormand, Carol J.; Shipley, Thomas F.; Tikoff, Basil

2014-12-01

Capturing the nature of students' mental representations and how they change with learning is a primary goal in science education research. This can be challenging in spatially intense domains, such as geoscience, architecture, and engineering. In this research, we test whether sketching can be used to gauge level of expertise in geoscience, using new technology designed to facilitate this process. We asked participants with differing levels of geoscience experience to copy two kinds of geoscience images—photographs of rock formations and causal diagrams. To permit studying the process of sketching as well as the structure and content of the sketches, we used the CogSketch system (Forbus et al. 2011, Topics in Cognitive Science 3:648-666) to record the time course of sketching and analyze the sketches themselves. Relative to novices, geoscience students included more geological structures and relational symbols in their sketches of geoscience materials and were more likely to construct their sketches in a sequence consistent with the order of causal events. These differences appear to stem from differences in domain knowledge, because they did not show up in participants' sketches of materials from other fields. The findings and methods of this research suggest new ways to promote and assess science learning, which are well suited to the visual-spatial demands of many domains.

Essential Nutrition and Food Systems Components for School Curricula: Views from Experts in Iran

PubMed Central

SADEGHOLVAD, Sanaz; YEATMAN, Heather; OMIDVAR, Nasrin; PARRISH, Anne-Maree; WORSLEY, Anthony

2017-01-01

Background: This study aimed to investigate food experts’ views on important nutrition and food systems knowledge issues for education purposes at schools in Iran. Methods: In 2012, semi-structured, face-to-face or telephone interviews were conducted with twenty-eight acknowledged Iranian experts in food and nutrition fields. Participants were selected from four major provinces in Iran (Tehran, Isfahan, Fars and Gilan). Open-ended interview questions were used to identify nutrition and food systems knowledge issues, which experts considered as important to be included in school education programs. Qualitative interviews were analyzed thematically using NVivo. Results: A framework of knowledge that would assist Iranian students and school-leavers to make informed decisions in food-related areas was developed, comprising five major clusters and several sub-clusters. Major knowledge clusters included nutrition basics; food production; every day food-related practices; prevalent nutritional health problems in Iran and improvement of students’ ethical attitudes in the food domain. Conclusion: These findings provide a guide to curriculum developers and policy makers to assess current education curricula in order to optimize students’ knowledge of nutrition and food systems. PMID:28845405

Botulinum neurotoxin structure, engineering, and novel cellular trafficking and targeting.

PubMed

Singh, B R

2006-04-01

Botulinum neurotoxins are multifaceted molecules, which are truly unique not only in their mode of action, but also their utility as a drug carrier either across the gut wall or to the nerve terminals. The molecule is divided in clear functional domains that can operate independently. This feature can be used to employ them as cargo carrier by linking other drugs or vaccines with the binding and translocation domains of BoNT. While the domain structures are largely independent of each other, the dynamic structure of these domains, especially that of the enzymatic domain (L chain), is quite different from the reported crystal structures for several BoNT serotypes and their enzymatic domain. This review discusses the comparative structures of BoNT in crystal and solution for their relevance to the molecular mechanism of BoNT action, especially in view of our recent discovery that the enzymatically active structure of the BoNT exists as a molten-globule and that of the endopeptidase domain as a novel PRIME conformation. Finally, a non-exhaustive discussion has been included to explain the long-lasting biological effects of certain serotypes of BoNT, based on the current knowledge of the structure-function of different serotypes of botulinum neurotoxins.

Ontology patterns for tabular representations of biomedical knowledge on neglected tropical diseases

PubMed Central

Santana, Filipe; Schober, Daniel; Medeiros, Zulma; Freitas, Fred; Schulz, Stefan

2011-01-01

Motivation: Ontology-like domain knowledge is frequently published in a tabular format embedded in scientific publications. We explore the re-use of such tabular content in the process of building NTDO, an ontology of neglected tropical diseases (NTDs), where the representation of the interdependencies between hosts, pathogens and vectors plays a crucial role. Results: As a proof of concept we analyzed a tabular compilation of knowledge about pathogens, vectors and geographic locations involved in the transmission of NTDs. After a thorough ontological analysis of the domain of interest, we formulated a comprehensive design pattern, rooted in the biomedical domain upper level ontology BioTop. This pattern was implemented in a VBA script which takes cell contents of an Excel spreadsheet and transforms them into OWL-DL. After minor manual post-processing, the correctness and completeness of the ontology was tested using pre-formulated competence questions as description logics (DL) queries. The expected results could be reproduced by the ontology. The proposed approach is recommended for optimizing the acquisition of ontological domain knowledge from tabular representations. Availability and implementation: Domain examples, source code and ontology are freely available on the web at http://www.cin.ufpe.br/~ntdo. Contact: fss3@cin.ufpe.br PMID:21685092

A metamodel for mobile forensics investigation domain

PubMed Central

Abd Razak, Shukor; Othman, Siti Hajar; Mohammed, Arafat; Saeed, Faisal

2017-01-01

With the rapid development of technology, mobile phones have become an essential tool in terms of crime fighting and criminal investigation. However, many mobile forensics investigators face difficulties with the investigation process in their domain. These difficulties are due to the heavy reliance of the forensics field on knowledge which, although a valuable resource, is scattered and widely dispersed. The wide dispersion of mobile forensics knowledge not only makes investigation difficult for new investigators, resulting in substantial waste of time, but also leads to ambiguity in the concepts and terminologies of the mobile forensics domain. This paper developed an approach for mobile forensics domain based on metamodeling. The developed approach contributes to identify common concepts of mobile forensics through a development of the Mobile Forensics Metamodel (MFM). In addion, it contributes to simplifying the investigation process and enables investigation teams to capture and reuse specialized forensic knowledge, thereby supporting the training and knowledge management activities. Furthermore, it reduces the difficulty and ambiguity in the mobile forensics domain. A validation process was performed to ensure the completeness and correctness of the MFM. The validation was conducted using two techniques for improvements and adjustments to the metamodel. The last version of the adjusted metamodel was named MFM 1.2. PMID:28445486

Bisphenol A (BPA) binding on full-length architectures of estrogen receptor.

PubMed

Liu, Yaquan; Qu, Kaili; Hai, Ying; Zhao, Chunyan

2018-08-01

Previous research has shown that the major toxicity mechanism for many environment chemicals is binding with estrogen receptor (ER) and blocking endogenous estrogen access, including bisphenol A (BPA). However, the molecular level understanding the global consequence of BPA binding on the full-length architectures of ER is largely unknown, which is a necessary stage to evaluate estrogen-like toxicity of BPA. In the present work, the consequence of BPA on full-length architectures of ER was firstly modeled based on molecular dynamics, focusing on the cross communication between multi-domains including ligand binding domain (LBD) and DNA binding domain (DBD). The study proved consequence of BPA upon full-length ER structure was dependent on long-range communications between multiple protein domains. The allosteric effects occurring in LBD units could alter dimerization formation through a crucial change in residue-residue connections, which resulted in relaxation of DBD. It indicated BPA could present consequence on the full-size receptor, not only on the separate domains, but also on the cross communication among LBD, DBD, and DNA molecules. It might provide detailed insight into the knowledge about the structural characteristics of ER and its role in gene regulation, which eventually helped us evaluate the estrogen-like toxicity upon BPA binding with full-length ER. © 2018 Wiley Periodicals, Inc.

Goal-Based Domain Modeling as a Basis for Cross-Disciplinary Systems Engineering

NASA Astrophysics Data System (ADS)

Jarke, Matthias; Nissen, Hans W.; Rose, Thomas; Schmitz, Dominik

Small and medium-sized enterprises (SMEs) are important drivers for innovation. In particular, project-driven SMEs that closely cooperate with their customers have specific needs in regard to information engineering of their development process. They need a fast requirements capture since this is most often included in the (unpaid) offer development phase. At the same time, they need to maintain and reuse the knowledge and experiences they have gathered in previous projects extensively as it is their core asset. The situation is complicated further if the application field crosses disciplinary boundaries. To bridge the gaps and perspectives, we focus on shared goals and dependencies captured in models at a conceptual level. Such a model-based approach also offers a smarter connection to subsequent development stages, including a high share of automated code generation. In the approach presented here, the agent- and goal-oriented formalism i * is therefore extended by domain models to facilitate information organization. This extension permits a domain model-based similarity search, and a model-based transformation towards subsequent development stages. Our approach also addresses the evolution of domain models reflecting the experiences from completed projects. The approach is illustrated with a case study on software-intensive control systems in an SME of the automotive domain.

Lexical leverage: Category knowledge boosts real-time novel word recognition in two-year- olds

PubMed Central

Borovsky, Arielle; Ellis, Erica M.; Evans, Julia L.; Elman, Jeffrey L.

2016-01-01

Recent research suggests that infants tend to add words to their vocabulary that are semantically related to other known words, though it is not clear why this pattern emerges. In this paper, we explore whether infants to leverage their existing vocabulary and semantic knowledge when interpreting novel label-object mappings in real-time. We initially identified categorical domains for which individual 24-month-old infants have relatively higher and lower levels of knowledge, irrespective of overall vocabulary size. Next, we taught infants novel words in these higher and lower knowledge domains and then asked if their subsequent real-time recognition of these items varied as a function of their category knowledge. While our participants successfully acquired the novel label -object mappings in our task, there were important differences in the way infants recognized these words in real time. Namely, infants showed more robust recognition of high (vs. low) domain knowledge words. These findings suggest that dense semantic structure facilitates early word learning and real-time novel word recognition. PMID:26452444

Neighbourhood ethnic diversity buffers school readiness impact in ESL children.

PubMed

Puchala, Chassidy; Vu, Lan T H; Muhajarine, Nazeem

2010-01-01

Contextual factors, as measured by neighbourhood characteristics, shape the experiences children have and affect their "school readiness", i.e., whether they are well or poorly prepared for the transition from home to kindergarten. This study assessed the independent effects of individual and neighbourhood factors on school readiness; specifically, it examined whether and to what degree neighbourhood factors modified children's language ability and thus their school readiness in a population of children in Saskatoon, Saskatchewan. The study included all children attending kindergarten in 2001, 2003 and 2005 in Saskatoon. School readiness and child characteristics were measured by the Early Development Instrument (EDI). The EDI measures child development at school commencement in five domains: physical health and well-being, social competence, emotional maturity, cognitive and language development, and communication skills and general knowledge. Data from the 2001 Census were used to characterize Saskatoon's neighbourhoods. Multilevel modeling examined the independent and buffering or exacerbating effects of individual and neighbourhood factors on the relation between English as a Second Language (ESL) status in children and EDI domain scores. ESL children had significantly lower scores on all EDI domains compared with non-ESL children. Certain factors (e.g., younger age, male, Aboriginal status, having special needs) were significantly related to lower readiness in terms of the emotional maturity, and communication skills and general knowledge domains. Importantly, children who lived in neighbourhoods that were highly transient (with a higher proportion of residents who had moved in the previous year) had lower EDI scores on both domains, and those in neighbourhoods with lower rates of employment had lower EDI scores on communication skills and general knowledge. Neighbourhood ethnic diversity mitigated the negative impact of ESL status on school readiness for both domains. ESL children from neighbourhoods with a high degree of ethnic diversity had higher EDI scores than ESL children from neighbourhoods with low ethnic diversity. The current study provided insight regarding the impact of contextual factors in addition to individual factors, such as ESL status, on school readiness outcomes. Future research should continue to examine contextual factors related to ESL status and early child developmental outcomes, particularly focusing on the mechanisms of influence.

The impact of domain knowledge on structured data collection and templated note design.

PubMed

Windle, T; McClay, J C; Windle, J R

2013-01-01

The objective of this case report is to evaluate the importance of specialized domain knowledge when designing and using structured templated notes in a clinical environment. To analyze the impact of specialization on structured note generation we compared notes generated for three scenarios: 1) We compared the templated history of present illness (HPI) for patients presenting with a dermatology concern to the dermatologist versus the emergency department. 2) We compared the evaluation of chest pain by ED physicians versus cardiologists. 3) Finally, we compared the data elements asked for in the evaluation of the gastrointestinal system between cardiologists and the liver transplant service (LTS). We used the SNOMED CT representation via BioPortal to evaluate specificity and grouping between data elements and specialized physician groups. We found few similarities in structured data elements designed by and for the specific physician groups. The distinctness represented both differences in granularity as well as fundamental differences in data elements requested. When compared to ED physicians, dermatologists had different and more granular elements while cardiologists requested much more granular data. Comparing cardiologists and LTS, there were differences in the data elements requested. This case study supports the importance of domain knowledge in EHR design and implementation. That different specialities should want and use different information is well supported by cognitive science literature. Despite this, it is rare for domain knowledge to be considered in EHR implementation. Physicians with correct domain knowledge should be involved in the design process of templated notes.

Applying data mining techniques to medical time series: an empirical case study in electroencephalography and stabilometry.

PubMed

Anguera, A; Barreiro, J M; Lara, J A; Lizcano, D

2016-01-01

One of the major challenges in the medical domain today is how to exploit the huge amount of data that this field generates. To do this, approaches are required that are capable of discovering knowledge that is useful for decision making in the medical field. Time series are data types that are common in the medical domain and require specialized analysis techniques and tools, especially if the information of interest to specialists is concentrated within particular time series regions, known as events. This research followed the steps specified by the so-called knowledge discovery in databases (KDD) process to discover knowledge from medical time series derived from stabilometric (396 series) and electroencephalographic (200) patient electronic health records (EHR). The view offered in the paper is based on the experience gathered as part of the VIIP project. Knowledge discovery in medical time series has a number of difficulties and implications that are highlighted by illustrating the application of several techniques that cover the entire KDD process through two case studies. This paper illustrates the application of different knowledge discovery techniques for the purposes of classification within the above domains. The accuracy of this application for the two classes considered in each case is 99.86% and 98.11% for epilepsy diagnosis in the electroencephalography (EEG) domain and 99.4% and 99.1% for early-age sports talent classification in the stabilometry domain. The KDD techniques achieve better results than other traditional neural network-based classification techniques.

Determining similarity of scientific entities in annotation datasets

PubMed Central

Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

2015-01-01

Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug–drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called ‘AnnSim’ that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1–1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ PMID:25725057

Determining similarity of scientific entities in annotation datasets.

PubMed

Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

2015-01-01

Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug-drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called 'AnnSim' that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1-1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ © The Author(s) 2015. Published by Oxford University Press.

U.S. Spacesuit Knowledge Capture Accomplishments in Fiscal Years 2012 and 2013

NASA Technical Reports Server (NTRS)

Chullen, Cinda; Oliva, Vladenka R.

2014-01-01

The NASA U.S. spacesuit knowledge capture (KC) program has been in operations since the beginning 2008. The program was designed to augment engineers and others with information about spacesuits in a historical way. A multitude of seminars have captured spacesuit history and knowledge over the last six years of the programs existence. Subject matter experts have provided lectures and were interviewed to help bring the spacesuit to life so that lessons learned will never be lost. As well, the program concentrated in reaching out to the public and industry by making the recorded events part of the public domain through the NASA technical library via You Tube media. The U.S. spacesuit KC topics have included lessons learned from some of the most prominent spacesuit experts and spacesuit users including current and former astronauts. The events have enriched the spacesuit legacy knowledge from Gemini, Apollo, Skylab, Space Shuttle and International Space Station Programs. As well, expert engineers and scientists have shared their challenges and successes to be remembered. The last few years have been some of the most successful years of the KC program program's life with numerous recordings and releases to the public. It is evidenced by the thousands that have view the recordings online. This paper reviews the events accomplished and archived over Fiscal Years 2012 and 2013 and highlights a few of the most memorable ones. This paper also communicates ways to access the events that are available internally to NASA as well as in the public domain.

A knowledge translation intervention designed using audit and feedback and the Theoretical Domains Framework for physical therapists working in inpatient rehabilitation: A case report.

PubMed

Romney, Wendy; Salbach, Nancy; Parrott, James Scott; Deutsch, Judith E

2018-04-16

Little is known about the process of engaging key stakeholders to select and design a knowledge translation (KT) intervention to increase the use of an outcome measure using audit and feedback. The purpose of this case report was to describe the development of a KT intervention designed with organizational support to increase physical therapists' (PTs) use of a selected outcome measure in an inpatient sub-acute rehabilitation hospital. Eleven PTs who worked at a sub-acute rehabilitation hospital participated. After determining organizational support, a mixed methods barrier assessment including a chart audit, questionnaire, and a focus group with audit and feedback was used to select an outcome measure and design a locally tailored intervention. The intervention was mapped using the Theoretical Domains Framework (TDF). One investigator acted as knowledge broker and co-designed the intervention with clinician and supervisor support. The 4-m walk test was selected through a group discussion facilitated by the knowledge broker. Support from the facility and input from the key stakeholders guided the design of a tailored KT intervention to increase use of gait speed. The intervention design included an interactive educational meeting, with documentation and environmental changes. Input from the clinicians on the educational meeting, documentation changes and placement of tracks, and support from the supervisor were used to design and locally adapt a KT intervention to change assessment practice among PTs in an inpatient sub-acute rehabilitation hospital. Implementation and evaluation of the intervention is underway.

A Novel Domain Assembly Routine for Creating Full-Length Models of Membrane Proteins from Known Domain Structures.

PubMed

Koehler Leman, Julia; Bonneau, Richard

2018-04-03

Membrane proteins composed of soluble and membrane domains are often studied one domain at a time. However, to understand the biological function of entire protein systems and their interactions with each other and drugs, knowledge of full-length structures or models is required. Although few computational methods exist that could potentially be used to model full-length constructs of membrane proteins, none of these methods are perfectly suited for the problem at hand. Existing methods require an interface or knowledge of the relative orientations of the domains or are not designed for domain assembly, and none of them are developed for membrane proteins. Here we describe the first domain assembly protocol specifically designed for membrane proteins that assembles intra- and extracellular soluble domains and the transmembrane domain into models of the full-length membrane protein. Our protocol does not require an interface between the domains and samples possible domain orientations based on backbone dihedrals in the flexible linker regions, created via fragment insertion, while keeping the transmembrane domain fixed in the membrane. For five examples tested, our method mp_domain_assembly, implemented in RosettaMP, samples domain orientations close to the known structure and is best used in conjunction with experimental data to reduce the conformational search space.

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

NASA Technical Reports Server (NTRS)

Genuardi, Michael T.

1993-01-01

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

Age Differences in the Effects of Domain Knowledge on Reading Efficiency

PubMed Central

Miller, Lisa M. Soederberg

2009-01-01

The present study investigated age differences in the effects of knowledge on the efficiency with which information is processed while reading. Individuals between 18 and 85 years of age, with varying levels of cooking knowledge, read and recalled a series of short passages within the domain of cooking. Reading efficiency was operationalized as time spent reading divided by the amount recalled for each passage. Results showed that reading efficiency increased with increasing levels of knowledge among older but not younger adults. Similarly, those with smaller working memory capacities showed increasing efficiency with increasing knowledge. These findings suggest that knowledge promotes a more efficient allocation policy which is particularly helpful in later life, perhaps due to age-related declines in working memory capacity. PMID:19290738

To ontologise or not to ontologise: An information model for a geospatial knowledge infrastructure

NASA Astrophysics Data System (ADS)

Stock, Kristin; Stojanovic, Tim; Reitsma, Femke; Ou, Yang; Bishr, Mohamed; Ortmann, Jens; Robertson, Anne

2012-08-01

A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created. This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge. The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.

The intellectual structure and substance of the knowledge utilization field: a longitudinal author co-citation analysis, 1945 to 2004.

PubMed

Estabrooks, Carole A; Derksen, Linda; Winther, Connie; Lavis, John N; Scott, Shannon D; Wallin, Lars; Profetto-McGrath, Joanne

2008-11-13

It has been argued that science and society are in the midst of a far-reaching renegotiation of the social contract between science and society, with society becoming a far more active partner in the creation of knowledge. On the one hand, new forms of knowledge production are emerging, and on the other, both science and society are experiencing a rapid acceleration in new forms of knowledge utilization. Concomitantly since the Second World War, the science underpinning the knowledge utilization field has had exponential growth. Few in-depth examinations of this field exist, and no comprehensive analyses have used bibliometric methods. Using bibliometric analysis, specifically first author co-citation analysis, our group undertook a domain analysis of the knowledge utilization field, tracing its historical development between 1945 and 2004. Our purposes were to map the historical development of knowledge utilization as a field, and to identify the changing intellectual structure of its scientific domains. We analyzed more than 5,000 articles using citation data drawn from the Web of Science. Search terms were combinations of knowledge, research, evidence, guidelines, ideas, science, innovation, technology, information theory and use, utilization, and uptake. We provide an overview of the intellectual structure and how it changed over six decades. The field does not become large enough to represent with a co-citation map until the mid-1960s. Our findings demonstrate vigorous growth from the mid-1960s through 2004, as well as the emergence of specialized domains reflecting distinct collectives of intellectual activity and thought. Until the mid-1980s, the major domains were focused on innovation diffusion, technology transfer, and knowledge utilization. Beginning slowly in the mid-1980s and then growing rapidly, a fourth scientific domain, evidence-based medicine, emerged. The field is dominated in all decades by one individual, Everett Rogers, and by one paradigm, innovation diffusion. We conclude that the received view that social science disciplines are in a state where no accepted set of principles or theories guide research (i.e., that they are pre-paradigmatic) could not be supported for this field. Second, we document the emergence of a new domain within the knowledge utilization field, evidence-based medicine. Third, we conclude that Everett Rogers was the dominant figure in the field and, until the emergence of evidence-based medicine, his representation of the general diffusion model was the dominant paradigm in the field.

The intellectual structure and substance of the knowledge utilization field: A longitudinal author co-citation analysis, 1945 to 2004

PubMed Central

Estabrooks, Carole A; Derksen, Linda; Winther, Connie; Lavis, John N; Scott, Shannon D; Wallin, Lars; Profetto-McGrath, Joanne

2008-01-01

Background It has been argued that science and society are in the midst of a far-reaching renegotiation of the social contract between science and society, with society becoming a far more active partner in the creation of knowledge. On the one hand, new forms of knowledge production are emerging, and on the other, both science and society are experiencing a rapid acceleration in new forms of knowledge utilization. Concomitantly since the Second World War, the science underpinning the knowledge utilization field has had exponential growth. Few in-depth examinations of this field exist, and no comprehensive analyses have used bibliometric methods. Methods Using bibliometric analysis, specifically first author co-citation analysis, our group undertook a domain analysis of the knowledge utilization field, tracing its historical development between 1945 and 2004. Our purposes were to map the historical development of knowledge utilization as a field, and to identify the changing intellectual structure of its scientific domains. We analyzed more than 5,000 articles using citation data drawn from the Web of Science®. Search terms were combinations of knowledge, research, evidence, guidelines, ideas, science, innovation, technology, information theory and use, utilization, and uptake. Results We provide an overview of the intellectual structure and how it changed over six decades. The field does not become large enough to represent with a co-citation map until the mid-1960s. Our findings demonstrate vigorous growth from the mid-1960s through 2004, as well as the emergence of specialized domains reflecting distinct collectives of intellectual activity and thought. Until the mid-1980s, the major domains were focused on innovation diffusion, technology transfer, and knowledge utilization. Beginning slowly in the mid-1980s and then growing rapidly, a fourth scientific domain, evidence-based medicine, emerged. The field is dominated in all decades by one individual, Everett Rogers, and by one paradigm, innovation diffusion. Conclusion We conclude that the received view that social science disciplines are in a state where no accepted set of principles or theories guide research (i.e., that they are pre-paradigmatic) could not be supported for this field. Second, we document the emergence of a new domain within the knowledge utilization field, evidence-based medicine. Third, we conclude that Everett Rogers was the dominant figure in the field and, until the emergence of evidence-based medicine, his representation of the general diffusion model was the dominant paradigm in the field. PMID:19014512

An information theory analysis of spatial decisions in cognitive development

PubMed Central

Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.

2015-01-01

Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of “cognitive entropy” were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured “chunking” of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

A Method for Populating the Knowledge Base of APTAS, a Domain-Oriented Application Composition System

DTIC Science & Technology

1993-12-01

proposed a domain analysis approach called Feature-Oriented Domain Analysis ( FODA ). The approach identifies prominent features (similarities) and...characteristics of software systems in the domain. Unlike the other domain analysis approaches we have summarized, the re- searchers described FODA in...Domain Analysis ( FODA ) Feasibility Study. Technical Report, Software Engineering Institute, Carnegie Mellon University, Novem- ber 1990. 19. Lee, Kenneth

How do physicians become medical experts? A test of three competing theories: distinct domains, independent influence and encapsulation models.

PubMed

Violato, Claudio; Gao, Hong; O'Brien, Mary Claire; Grier, David; Shen, E

2018-05-01

The distinction between basic sciences and clinical knowledge which has led to a theoretical debate on how medical expertise is developed has implications for medical school and lifelong medical education. This longitudinal, population based observational study was conducted to test the fit of three theories-knowledge encapsulation, independent influence, distinct domains-of the development of medical expertise employing structural equation modelling. Data were collected from 548 physicians (292 men-53.3%; 256 women-46.7%; mean age = 24.2 years on admission) who had graduated from medical school 2009-2014. They included (1) Admissions data of undergraduate grade point average and Medical College Admission Test sub-test scores, (2) Course performance data from years 1, 2, and 3 of medical school, and (3) Performance on the NBME exams (i.e., Step 1, Step 2 CK, and Step 3). Statistical fit indices (Goodness of Fit Index-GFI; standardized root mean squared residual-SRMR; root mean squared error of approximation-RSMEA) and comparative fit [Formula: see text] of three theories of cognitive development of medical expertise were used to assess model fit. There is support for the knowledge encapsulation three factor model of clinical competency (GFI = 0.973, SRMR = 0.043, RSMEA = 0.063) which had superior fit indices to both the independent influence and distinct domains theories ([Formula: see text] vs [Formula: see text] [[Formula: see text

Information Visualization: The State of the Art for Maritime Domain Awareness

DTIC Science & Technology

2006-08-01

les auteurs et aux évaluations de la qualité de certains documents, mots-clés et liens. La version sur papier de cette base de données se trouve à...interface design principles, psychological studies, and perception research • include a review of visualization theory including current visualization...builds on that a theory of how maps are understood (knowledge schemata and cognitive representations), and then analyses the use of symbols and

Structural Dynamics of the GW182 Silencing Domain Including its RNA Recognition motif (RRM) Revealed by Hydrogen-Deuterium Exchange Mass Spectrometry

NASA Astrophysics Data System (ADS)

Cieplak-Rotowska, Maja K.; Tarnowski, Krzysztof; Rubin, Marcin; Fabian, Marc R.; Sonenberg, Nahum; Dadlez, Michal; Niedzwiecka, Anna

2018-01-01

The human GW182 protein plays an essential role in micro(mi)RNA-dependent gene silencing. miRNA silencing is mediated, in part, by a GW182 C-terminal region called the silencing domain, which interacts with the poly(A) binding protein and the CCR4-NOT deadenylase complex to repress protein synthesis. Structural studies of this GW182 fragment are challenging due to its predicted intrinsically disordered character, except for its RRM domain. However, detailed insights into the properties of proteins containing disordered regions can be provided by hydrogen-deuterium exchange mass spectrometry (HDX/MS). In this work, we applied HDX/MS to define the structural state of the GW182 silencing domain. HDX/MS analysis revealed that this domain is clearly divided into a natively unstructured part, including the CCR4-NOT interacting motif 1, and a distinct RRM domain. The GW182 RRM has a very dynamic structure, since water molecules can penetrate the whole domain in 2 h. The finding of this high structural dynamics sheds new light on the RRM structure. Though this domain is one of the most frequently occurring canonical protein domains in eukaryotes, these results are - to our knowledge - the first HDX/MS characteristics of an RRM. The HDX/MS studies show also that the α2 helix of the RRM can display EX1 behavior after a freezing-thawing cycle. This means that the RRM structure is sensitive to environmental conditions and can change its conformation, which suggests that the state of the RRM containing proteins should be checked by HDX/MS in regard of the conformational uniformity. [Figure not available: see fulltext.

The Global Teaching Profession: How Treating Teachers as Knowledge Workers Improves the Esteem of the Teaching Profession

ERIC Educational Resources Information Center

Price, Heather E.; Weatherby, Kristen

2018-01-01

To better understand the status of the teaching profession, we present a conceptual framework outlining the 4 domains of knowledge-worker professionals: professional benchmarks, professional discretion, room for promotion, and workplace conditions and use the TALIS 2013 survey data to show that these domains exist globally and vary within…

Web-Based Undergraduate Chemistry Problem-Solving: The Interplay of Task Performance, Domain Knowledge and Web-Searching Strategies

ERIC Educational Resources Information Center

She, Hsiao-Ching; Cheng, Meng-Tzu; Li, Ta-Wei; Wang, Chia-Yu; Chiu, Hsin-Tien; Lee, Pei-Zon; Chou, Wen-Chi; Chuang, Ming-Hua

2012-01-01

This study investigates the effect of Web-based Chemistry Problem-Solving, with the attributes of Web-searching and problem-solving scaffolds, on undergraduate students' problem-solving task performance. In addition, the nature and extent of Web-searching strategies students used and its correlation with task performance and domain knowledge also…

The world of geography: Visualizing a knowledge domain with cartographic means

PubMed Central

Skupin, André

2004-01-01

From an informed critique of existing methods to the development of original tools, cartographic engagement can provide a unique perspective on knowledge domain visualization. Along with a discussion of some principles underlying a cartographically informed visualization methodology, results of experiments involving several thousand conference abstracts will be sketched and their plausibility reflected on. PMID:14764896

Relative Expertise in an Everyday Reasoning Task: Epistemic Understanding, Problem Representation, and Reasoning Competence

ERIC Educational Resources Information Center

Weinstock, Michael

2009-01-01

Experts in cognitive domains differ from non-experts in how they represent problems and knowledge, and in their epistemic understandings of tasks in their domain of expertise. This study investigates whether task-specific epistemic understanding also underlies the representation of knowledge on an everyday reasoning task on which the competent…

The Effect of Individual Differences on Searching the Web.

ERIC Educational Resources Information Center

Ihadjadene, Madjid; Chaudiron, Stephanne,; Martins, Daniel

2003-01-01

Reports results from a project that investigated the influence of two types of expertise--knowledge of the search domain and experience of the Web search engines--on students' use of a Web search engine. Results showed participants with good knowledge in the domain and participants with high experience of the Web had the best performances. (AEF)

Positioning Continuing Education: Boundaries and Intersections between the Domains Continuing Education, Knowledge Translation, Patient Safety and Quality Improvement

ERIC Educational Resources Information Center

Kitto, Simon; Bell, Mary; Peller, Jennifer; Sargeant, Joan; Etchells, Edward; Reeves, Scott; Silver, Ivan

2013-01-01

Public and professional concern about health care quality, safety and efficiency is growing. Continuing education, knowledge translation, patient safety and quality improvement have made concerted efforts to address these issues. However, a coordinated and integrated effort across these domains is lacking. This article explores and discusses the…

Sound credit scores and financial decisions despite cognitive aging.

PubMed

Li, Ye; Gao, Jie; Enkavi, A Zeynep; Zaval, Lisa; Weber, Elke U; Johnson, Eric J

2015-01-06

Age-related deterioration in cognitive ability may compromise the ability of older adults to make major financial decisions. We explore whether knowledge and expertise accumulated from past decisions can offset cognitive decline to maintain decision quality over the life span. Using a unique dataset that combines measures of cognitive ability (fluid intelligence) and of general and domain-specific knowledge (crystallized intelligence), credit report data, and other measures of decision quality, we show that domain-specific knowledge and expertise provide an alternative route for sound financial decisions. That is, cognitive aging does not spell doom for financial decision-making in domains where the decision maker has developed expertise. These results have important implications for public policy and for the design of effective interventions and decision aids.

Fast tracking the design of theory-based KT interventions through a consensus process.

PubMed

Bussières, André E; Al Zoubi, Fadi; Quon, Jeffrey A; Ahmed, Sara; Thomas, Aliki; Stuber, Kent; Sajko, Sandy; French, Simon

2015-02-11

Despite available evidence for optimal management of spinal pain, poor adherence to guidelines and wide variations in healthcare services persist. One of the objectives of the Canadian Chiropractic Guideline Initiative is to develop and evaluate targeted theory- and evidence-informed interventions to improve the management of non-specific neck pain by chiropractors. In order to systematically develop a knowledge translation (KT) intervention underpinned by the Theoretical Domains Framework (TDF), we explored the factors perceived to influence the use of multimodal care to manage non-specific neck pain, and mapped behaviour change techniques to key theoretical domains. Individual telephone interviews exploring beliefs about managing neck pain were conducted with a purposive sample of 13 chiropractors. The interview guide was based upon the TDF. Interviews were digitally recorded, transcribed verbatim and analysed by two independent assessors using thematic content analysis. A 15-member expert panel formally met to design a KT intervention. Nine TDF domains were identified as likely relevant. Key beliefs (and relevant domains of the TDF) included the following: influence of formal training, colleagues and patients on clinicians (Social Influences); availability of educational material (Environmental Context and Resources); and better clinical outcomes reinforcing the use of multimodal care (Reinforcement). Facilitating factors considered important included better communication (Skills); audits of patients' treatment-related outcomes (Behavioural Regulation); awareness and agreement with guidelines (Knowledge); and tailoring of multimodal care (Memory, Attention and Decision Processes). Clinicians conveyed conflicting beliefs about perceived threats to professional autonomy (Social/Professional Role and Identity) and speed of recovery from either applying or ignoring the practice recommendations (Beliefs about Consequences). The expert panel mapped behaviour change techniques to key theoretical domains and identified relevant KT strategies and modes of delivery to increase the use of multimodal care among chiropractors. A multifaceted KT educational intervention targeting chiropractors' management of neck pain was developed. The KT intervention consisted of an online education webinar series, clinical vignettes and a video underpinned by the Brief Action Planning model. The intervention was designed to reflect key theoretical domains, behaviour change techniques and intervention components. The effectiveness of the proposed intervention remains to be tested.

Declining Financial Capacity in Mild Cognitive Impairment: A Six-Year Longitudinal Study.

PubMed

Martin, Roy C; Gerstenecker, Adam; Triebel, Kristen L; Falola, Michael; McPherson, Tarrant; Cutter, Gary; Marson, Daniel C

2018-03-31

To investigate financial skill decline over a 6-year period in persons with mild cognitive impairment (MCI) presumed due to Alzheimer's disease (AD). Study participants were cognitively normal (CN) older adults (n = 82) and adults with MCI (n = 91) based on consensus conference diagnosis. Participants completed baseline and up to six annual follow-up assessments that included standardized financial skills measurement (Financial Capacity Instrument; FCI; nine FCI domain and two global scores). We examined FCI change over time using mixed-model repeated measures analysis adjusted for baseline age and follow-up duration. At baseline, the CN group performed better than the MCI group across both global and seven domain scores. Group × Time interaction effects (all p's <.02) were found for all global and domain scores. The largest interaction effects were observed for complex domains of Financial Conceptual Knowledge, Checkbook Management, Bank Statement Management, and Bill Payment (all p's <.0001). Annualized decline in the MCI group's global scores, calculated in relation to CN group performance, was 10-17% over the initial 3-year time span and 22-24% at 6 years. Decline in FCI domain scores ranged from 6% (Knowledge of Assets/Estate) to 22% (Investment Decision-Making) at 3 year follow-up, and from 15% (Basic Monetary Skills) to 37% (Financial Judgment) at 6 year follow-up. Over a 6-year period, persons with MCI demonstrated significant declines in multiple financial skills and in particular financial judgment. The findings highlight the importance of ongoing oversight by family members and clinicians of financial skills and activities in persons with MCI.

Using the theoretical domains framework to identify barriers and enablers to pediatric asthma management in primary care settings.

PubMed

Yamada, Janet; Potestio, Melissa L; Cave, Andrew J; Sharpe, Heather; Johnson, David W; Patey, Andrea M; Presseau, Justin; Grimshaw, Jeremy M

2017-12-20

This study aimed to apply a theory-based approach to identify barriers and enablers to implementing the Alberta Primary Care Asthma Pediatric Pathway (PCAPP) into clinical practice. Phase 1 included an assessment of assumptions underlying the intervention from the perspectives of the developers. Phase 2 determined the perceived barriers and enablers for: 1) primary care physicians' prescribing practices, 2) allied health care professionals' provision of asthma education to parents, and 3) children and parents' adherence to their treatment plans. Interviews were conducted with 35 individuals who reside in Alberta, Canada. Phase 1 included three developers. Phase 2 included 11 primary care physicians, 10 allied health care professionals, and 11 parents of children with asthma. Phase 2 interviews were based on the 14 domains of the Theoretical Domains Framework (TDF). Transcribed interviews were analyzed using a directed content analysis. Key assumptions by the developers about the intervention, and beliefs by others about the barriers and enablers of the targeted behaviors were identified. Eight TDF domains mapped onto the assumptions of the pathway as described by the intervention developers. Interviews with health care professionals and parents identified nine TDF domains that influenced the targeted behaviors: knowledge, skills, beliefs about capabilities, social/professional role and identity, beliefs about consequences, environmental context and resources, behavioral regulation, social influences, and emotions. Barriers and enablers perceived by health care professionals and parents that influenced asthma management will inform the optimization of the PCAPP prior to its evaluation.

Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

PubMed Central

Bau, Cho-Tsan; Huang, Chung-Yi

2014-01-01

Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353

Construction of a clinical decision support system for undergoing surgery based on domain ontology and rules reasoning.

PubMed

Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi

2014-05-01

To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé-Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia.

Knowledge-Based Reinforcement Learning for Data Mining

NASA Astrophysics Data System (ADS)

Kudenko, Daniel; Grzes, Marek

Data Mining is the process of extracting patterns from data. Two general avenues of research in the intersecting areas of agents and data mining can be distinguished. The first approach is concerned with mining an agent’s observation data in order to extract patterns, categorize environment states, and/or make predictions of future states. In this setting, data is normally available as a batch, and the agent’s actions and goals are often independent of the data mining task. The data collection is mainly considered as a side effect of the agent’s activities. Machine learning techniques applied in such situations fall into the class of supervised learning. In contrast, the second scenario occurs where an agent is actively performing the data mining, and is responsible for the data collection itself. For example, a mobile network agent is acquiring and processing data (where the acquisition may incur a certain cost), or a mobile sensor agent is moving in a (perhaps hostile) environment, collecting and processing sensor readings. In these settings, the tasks of the agent and the data mining are highly intertwined and interdependent (or even identical). Supervised learning is not a suitable technique for these cases. Reinforcement Learning (RL) enables an agent to learn from experience (in form of reward and punishment for explorative actions) and adapt to new situations, without a teacher. RL is an ideal learning technique for these data mining scenarios, because it fits the agent paradigm of continuous sensing and acting, and the RL agent is able to learn to make decisions on the sampling of the environment which provides the data. Nevertheless, RL still suffers from scalability problems, which have prevented its successful use in many complex real-world domains. The more complex the tasks, the longer it takes a reinforcement learning algorithm to converge to a good solution. For many real-world tasks, human expert knowledge is available. For example, human experts have developed heuristics that help them in planning and scheduling resources in their work place. However, this domain knowledge is often rough and incomplete. When the domain knowledge is used directly by an automated expert system, the solutions are often sub-optimal, due to the incompleteness of the knowledge, the uncertainty of environments, and the possibility to encounter unexpected situations. RL, on the other hand, can overcome the weaknesses of the heuristic domain knowledge and produce optimal solutions. In the talk we propose two techniques, which represent first steps in the area of knowledge-based RL (KBRL). The first technique [1] uses high-level STRIPS operator knowledge in reward shaping to focus the search for the optimal policy. Empirical results show that the plan-based reward shaping approach outperforms other RL techniques, including alternative manual and MDP-based reward shaping when it is used in its basic form. We showed that MDP-based reward shaping may fail and successful experiments with STRIPS-based shaping suggest modifications which can overcome encountered problems. The STRIPSbased method we propose allows expressing the same domain knowledge in a different way and the domain expert can choose whether to define an MDP or STRIPS planning task. We also evaluated the robustness of the proposed STRIPS-based technique to errors in the plan knowledge. In case that STRIPS knowledge is not available, we propose a second technique [2] that shapes the reward with hierarchical tile coding. Where the Q-function is represented with low-level tile coding, a V-function with coarser tile coding can be learned in parallel and used to approximate the potential for ground states. In the context of data mining, our KBRL approaches can also be used for any data collection task where the acquisition of data may incur considerable cost. In addition, observing the data collection agent in specific scenarios may lead to new insights into optimal data collection behaviour in the respective domains. In future work, we intend to demonstrate and evaluate our techniques on concrete real-world data mining applications.

In two minds: dual-process accounts of reasoning.

PubMed

Evans, Jonathan St B T

2003-10-01

Researchers in thinking and reasoning have proposed recently that there are two distinct cognitive systems underlying reasoning. System 1 is old in evolutionary terms and shared with other animals: it comprises a set of autonomous subsystems that include both innate input modules and domain-specific knowledge acquired by a domain-general learning mechanism. System 2 is evolutionarily recent and distinctively human: it permits abstract reasoning and hypothetical thinking, but is constrained by working memory capacity and correlated with measures of general intelligence. These theories essentially posit two minds in one brain with a range of experimental psychological evidence showing that the two systems compete for control of our inferences and actions.

Important ingredients for health adaptive information systems.

PubMed

Senathirajah, Yalini; Bakken, Suzanne

2011-01-01

Healthcare information systems frequently do not truly meet clinician needs, due to the complexity, variability, and rapid change in medical contexts. Recently the internet world has been transformed by approaches commonly termed 'Web 2.0'. This paper proposes a Web 2.0 model for a healthcare adaptive architecture. The vision includes creating modular, user-composable systems which aim to make all necessary information from multiple internal and external sources available via a platform, for the user to use, arrange, recombine, author, and share at will, using rich interfaces where advisable. Clinicians can create a set of 'widgets' and 'views' which can transform data, reflect their domain knowledge and cater to their needs, using simple drag and drop interfaces without the intervention of programmers. We have built an example system, MedWISE, embodying the user-facing parts of the model. This approach to HIS is expected to have several advantages, including greater suitability to user needs (reflecting clinician rather than programmer concepts and priorities), incorporation of multiple information sources, agile reconfiguration to meet emerging situations and new treatment deployment, capture of user domain expertise and tacit knowledge, efficiencies due to workflow and human-computer interaction improvements, and greater user acceptance.

Advancing interprofessional patient safety education for medical, nursing, and pharmacy learners during clinical rotations.

PubMed

Thom, Kerri A; Heil, Emily L; Croft, Lindsay D; Duffy, Alison; Morgan, Daniel J; Johantgen, Mary

2016-11-01

Clinical errors are common and can lead to adverse events and patient death. Health professionals must work within interprofessional teams to provide safe and effective care to patients, yet current curricula is lacking with regards to interprofessional education and patient safety. We describe the development and implementation of an interprofessional course aimed at medical, nursing, and pharmacy learners during their clinical training at a large academic medical centre. The course objectives were based on core competencies for interprofessional education and patient safety. The course was offered as recurring three 1-hour sessions, including case-based discussions and a mock root cause analysis. Forty-three students attended at least one session over a 7-month period. We performed a cross-sectional survey of participants to assess readiness for interprofessional learning and a before and after comparison of patient safety knowledge. All students reported a high level of readiness for interprofessional learning, indicating an interest in interprofessional opportunities. In general, understanding and knowledge of the four competency domains in patient safety was low before the course and 100% of students reported an increase in knowledge in these domains after participating in the course.

Risks and risk governance in unconventional shale gas development.

PubMed

Small, Mitchell J; Stern, Paul C; Bomberg, Elizabeth; Christopherson, Susan M; Goldstein, Bernard D; Israel, Andrei L; Jackson, Robert B; Krupnick, Alan; Mauter, Meagan S; Nash, Jennifer; North, D Warner; Olmstead, Sheila M; Prakash, Aseem; Rabe, Barry; Richardson, Nathan; Tierney, Susan; Webler, Thomas; Wong-Parodi, Gabrielle; Zielinska, Barbara

2014-01-01

A broad assessment is provided of the current state of knowledge regarding the risks associated with shale gas development and their governance. For the principal domains of risk, we identify observed and potential hazards and promising mitigation options to address them, characterizing current knowledge and research needs. Important unresolved research questions are identified for each area of risk; however, certain domains exhibit especially acute deficits of knowledge and attention, including integrated studies of public health, ecosystems, air quality, socioeconomic impacts on communities, and climate change. For these, current research and analysis are insufficient to either confirm or preclude important impacts. The rapidly evolving landscape of shale gas governance in the U.S. is also assessed, noting challenges and opportunities associated with the current decentralized (state-focused) system of regulation. We briefly review emerging approaches to shale gas governance in other nations, and consider new governance initiatives and options in the U.S. involving voluntary industry certification, comprehensive development plans, financial instruments, and possible future federal roles. In order to encompass the multiple relevant disciplines, address the complexities of the evolving shale gas system and reduce the many key uncertainties needed for improved management, a coordinated multiagency federal research effort will need to be implemented.

Positioning continuing education: boundaries and intersections between the domains continuing education, knowledge translation, patient safety and quality improvement.

PubMed

Kitto, Simon; Bell, Mary; Peller, Jennifer; Sargeant, Joan; Etchells, Edward; Reeves, Scott; Silver, Ivan

2013-03-01

Public and professional concern about health care quality, safety and efficiency is growing. Continuing education, knowledge translation, patient safety and quality improvement have made concerted efforts to address these issues. However, a coordinated and integrated effort across these domains is lacking. This article explores and discusses the similarities and differences amongst the four domains in relation to their missions, stakeholders, methods, and limitations. This paper highlights the potential for a more integrated and collaborative partnership to promote networking and information sharing amongst the four domains. This potential rests on the premise that an integrated approach may result in the development and implementation of more holistic and effective interdisciplinary interventions. In conclusion, an outline of current research that is informed by the preliminary findings in this paper is also briefly discussed. The research concerns a comprehensive mapping of the relationships between the domains to gain an understanding of potential dissonances between how the domains represent themselves, their work and the work of their 'partner' domains.

Passive acquisition of CLIPS rules

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1991-01-01

The automated acquisition of knowledge by machine has not lived up to expectations, and knowledge engineering remains a human intensive task. Part of the reason for the lack of success is the difference in the cognitive focus of the expert. The expert must shift his or her focus from the subject domain to that of the representation environment. In doing so this cognitive shift introduces opportunity for errors and omissions. Presented here is work that observes the expert interact with a simulation of the domain. The system logs changes in the simulation objects and the expert's actions in response to those changes. This is followed by the application of inductive reasoning to move the domain specific rules observed to general domain rules.

The locus of adult intelligence: knowledge, abilities, and nonability traits.

PubMed

Ackerman, P L; Rolfhus, E L

1999-06-01

Some intelligence theorists (e.g., R. B. Cattell, 1943; D. O. Hebb, 1942) have suggested that knowledge is one aspect of human intelligence that is well preserved or increases during adult development. Very little is known about knowledge structures across different domains or about how individual differences in knowledge relate to other traits. Twenty academic and technology-oriented tests were administered to 135 middle-aged adults. In comparison with younger college students, the middle-aged adults knew more about nearly all of the various knowledge domains. Knowledge was partly predicted by general intelligence, by crystallized abilities, and by personality, interest, and self-concept. Implications of this work are discussed in the context of a developmental theory that focuses on the acquisition and maintenance of intelligence-as-knowledge, as well as the role of knowledge for predicting the vocational and avocational task performance of adults.

Longitudinal analysis of domain-level breast cancer literacy among African-American women.

PubMed

Mabiso, Athur; Williams, Karen Patricia; Todem, David; Templin, Thomas N

2010-02-01

Functional breast cancer literacy was assessed among African-American women and measured at the domain level over time. We used the Kin Keeper(SM) Cancer Prevention Intervention to educate 161 African-American women on three domains of breast cancer literacy: (i) cancer awareness, (ii) knowledge of breast cancer screening modalities and (iii) cancer prevention and control. A breast cancer literacy assessment was administered pre- and post-educational intervention at two time points followed by another assessment 12 months after the second intervention. Generalized estimating equations were specified to predict the probability of correctly answering questions in each domain over time. Domain-level literacy differentials exist; at baseline, women had higher test scores in the breast cancer prevention and control domain than the cancer awareness domain (odds ratio = 1.67, 95% confidence interval 1.19-2.34). After Kin Keeper(SM) Cancer Prevention Intervention, African-American women consistently improved their breast cancer literacy in all domains over the five time stages (P < 0.001) though at different rates for each domain. Differences in domain-level breast cancer literacy highlight the importance of assessing literacy at the domain level. Interventions to improve African-American women's breast cancer literacy should focus on knowledge of breast cancer screening modalities and cancer awareness domains.

The experience of electroconvulsive therapy and its impact on associated stigma: A meta-analysis.

PubMed

Aoki, Yuta; Yamaguchi, Sosei; Ando, Shuntaro; Sasaki, Natsuki; Bernick, Peter J; Akiyama, Tsuyoshi

2016-12-01

Despite its efficacy and safety, electroconvulsive therapy (ECT) is underutilized, in part due to stigma associated with the treatment. The aim of this study was to test the hypothesis that experiencing ECT has an impact on associated stigma, as measured by patient and family knowledge of and attitudes toward ECT. A comprehensive literature search was conducted using MEDLINE, EMBASE and PsycINFO. Studies with cross-sectional and/or longitudinal designs were identified. Studies were further categorized into subcategories based on participant type (patients or patient family members) and outcome domain (knowledge or attitudes). Effect size (Cohen's d) was calculated for each study and then integrated into each subcategory (participant type by outcome domain) using a random effect model. Eight studies were identified as being eligible for analysis. Two studies were cross-sectional, five were longitudinal and one incorporated both designs. Analysis of the longitudinal studies indicated that experiencing ECT both increased knowledge of and improved attitudes toward ECT in patients; in family members of patients, analysis showed significant positive change in knowledge of ECT, but no significant change in attitudes toward ECT. Experience with ECT may have a positive impact on knowledge of and attitudes toward ECT. However, the quality of evidence of included studies was low; further research is required in order to clarify the relationship and to identify information of use to individuals considering ECT as a treatment option. © The Author(s) 2016.

Knowledge Discovery from Biomedical Ontologies in Cross Domains.

PubMed

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies.

Knowledge Discovery from Biomedical Ontologies in Cross Domains

PubMed Central

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies. PMID:27548262

A Step towards a Sharable Community Knowledge Base for WRF Settings -Developing a WRF Setting Methodology based on a case study in a Torrential Rainfall Event

NASA Astrophysics Data System (ADS)

CHU, Q.; Xu, Z.; Zhuo, L.; Han, D.

2016-12-01

Increased requirements for interactions between different disciplines and readily access to the numerical weather forecasting system featured with portability and extensibility have made useful contribution to the increases of downstream model users in WRF over recent years. For these users, a knowledge base classified by the representative events would be much helpful. This is because the determination of model settings is regarded as the most important steps in WRF. However, such a process is generally time-consuming, even if with a high computational platform. As such, we propose a sharable proper lookup table on WRF domain settings and corresponding procedures based on a representative torrential rainfall event in Beijing, China. It has been found that WRF's simulations' drift away from the input lateral boundary conditions can be significantly reduced with the adjustment of the domain settings. Among all the impact factors, the placement of nested domain can not only affect the moving speed and angle of the storm-center, but also the location and amount of heavy-rain-belt which can only be detected with adjusted spatial resolutions. Spin-up time is also considered in the model settings, which is demonstrated to have the most obvious influence on the accuracy of the simulations. This conclusion is made based on the large diversity of spatial distributions of precipitation, in terms of the amount of heavy rain varied from -30% to 58% among each experiment. After following all the procedures, the variations of domain settings have minimal effect on the modeling and show the best correlation (larger than 0.65) with fusion observations. So the model settings, including domain size covering the greater Beijing area, 1:5:5 downscaling ratio, 57 vertical levels with top of 50hpa and 60h spin-up time, are found suitable for predicting the similar convective torrential rainfall event in Beijing area. We hope that the procedure for building the community WRF knowledge base in this paper would be helpful to peer-researchers and operational communities by saving them from repeating each other's work. More importantly, the results by studying different events and locations could enrich this community knowledge base to benefit WRF users around the world in the future.

To include or not to include: Evaluations and reasoning about the failure to include peers with autism spectrum disorder in elementary students.

PubMed

Bottema-Beutel, Kristen; Turiel, Elliot; DeWitt, Mila N; Wolfberg, Pamela J

2017-01-01

Given the significant role that typically developing children play in the social lives of children with autism spectrum disorder, it is important to understand how they evaluate and reason about the inclusion/exclusion of children with autism spectrum disorder in social situations. The objective of this study is to determine elementary students' evaluations, reasoning patterns, and reasoning complexity regarding the failure to include children with autism spectrum disorder in social activities. Forty-four elementary-aged students participated in interviews, which included vignettes describing four contexts in which a child with autism spectrum disorder is not invited to a social event. Responses were analyzed according to social domain theory, an approach emphasizing that children identify and coordinate different domains of social knowledge, including the moral, personal, societal, and prudential. Results showed that regardless of grade and context, most children judge that failure to include on the basis of disability status is not acceptable. However, the complexity of children's reasoning (i.e. the extent to which they drew upon and coordinated multiple domains) was higher in older children. Mean complexity scores were also higher in a birthday party context as compared to a playdate context. We offer implications for future research and practice regarding the social inclusion of children with autism spectrum disorder. © The Author(s) 2016.

Searching Across the International Space Station Databases

NASA Technical Reports Server (NTRS)

Maluf, David A.; McDermott, William J.; Smith, Ernest E.; Bell, David G.; Gurram, Mohana

2007-01-01

Data access in the enterprise generally requires us to combine data from different sources and different formats. It is advantageous thus to focus on the intersection of the knowledge across sources and domains; keeping irrelevant knowledge around only serves to make the integration more unwieldy and more complicated than necessary. A context search over multiple domain is proposed in this paper to use context sensitive queries to support disciplined manipulation of domain knowledge resources. The objective of a context search is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The search supports formally the tasks of selecting, combining, extending, specializing, and modifying components from a diverse set of domains. This paper demonstrates a new paradigm in composition of information for enterprise applications. In particular, it discusses an approach to achieving data integration across multiple sources, in a manner that does not require heavy investment in database and middleware maintenance. This lean approach to integration leads to cost-effectiveness and scalability of data integration with an underlying schemaless object-relational database management system. This highly scalable, information on demand system framework, called NX-Search, which is an implementation of an information system built on NETMARK. NETMARK is a flexible, high-throughput open database integration framework for managing, storing, and searching unstructured or semi-structured arbitrary XML and HTML used widely at the National Aeronautics Space Administration (NASA) and industry.

Generation of surgical pathology report using a 5,000-word speech recognizer.

PubMed

Tischler, A S; Martin, M R

1989-10-01

Pressures to decrease both turnaround time and operating costs simultaneously have placed conflicting demands on traditional forms of medical transcription. The new technology of voice recognition extends the promise of enabling the pathologist or other medical professional to dictate a correct report and have it printed and/or transmitted to a database immediately. The usefulness of voice recognition systems depends on several factors, including ease of use, reliability, speed, and accuracy. These in turn depend on the general underlying design of the systems and inclusion in the systems of a specific knowledge base appropriate for each application. Development of a good knowledge base requires close collaboration between a domain expert and a knowledge engineer with expertise in voice recognition. The authors have recently completed a knowledge base for surgical pathology using the Kurzweil VoiceReport 5,000-word system.

Vulnerable Women’s Self-Care Needs in Knowledge, Attitude and Practice Concerning Sexually Transmitted Diseases

PubMed Central

Alimohammadi, Nasrollah; Baghersad, Zahra; Boroumandfar, Zahra

2016-01-01

Background: Vulnerable women are prone to sexually transmitted diseases (STD) due to their special conditions and poor knowledge about these diseases in the society. Therefore, the present study aimed to determine the vulnerable women’s self-care needs in knowledge, attitude and practice concerning STD. Methods: This is a cross-sectional-descriptive study conducted in 2014. The data collection was carried out using a self-administered structured questionnaire. 120 vulnerable women referring to centers affiliated to health and well-being center in Isfahan participated in this study. They were selected through proportional rationing sampling and filled out a researcher developed questionnaire containing information on personal characteristics, self-care knowledge, attitude, and practice needs toward the STD. The data were analyzed using statistical methods including Spearman & Pearson correlation co-efficient, independent t-test and ANOVA. All analyses were carried out using SPSS, 20. Results: Based on the results, most of the subjects mentioned that their priorities of self-care needs in domains of knowledge, attitude and practice were “familiarization with the types and contamination ways of sexually transmitted diseases” (57.9%); “diagnosis of STD only makes us anxious” (24.8), and “the method of washing the genital area before and after intercourse” 41.3%), respectively. There was a significant association among marital status, education, history of addiction, and self-care needs in domains of knowledge, attitude and practice (P<0.05). Conclusion: Results showed that vulnerable women not only knew their need about STD, but also paid attention to their attitude and practice needs toward STD. Therefore, educational programs should be designed and administrated by the experts, based on vulnerable women’s self-care needs concerning their knowledge, attitude and practice to prevent and control STD in vulnerable individuals. PMID:27382588

Tell Me a Story: How Children's Developing Domain Knowledge Affects Their Story Construction

ERIC Educational Resources Information Center

Sobel, David M.; Weisberg, Deena Skolnick

2014-01-01

Young children distinguish between the physical and biological domains of knowledge. The current study examines how this distinction is expressed in a story construction task. Three- and 4-year-olds were shown pairs of pictures, one that depicted a normal event and one that depicted an event that violated either physical or biological causal…

Knowledge at Work.

ERIC Educational Resources Information Center

Scribner, Sylvia

1985-01-01

Activity theory posits that culturally organized actions guide the acquisition and organization of knowledge. This theory was applied to the organization of knowledge within a large milk processing plant. The dairy was found to be organized by social knowledge, yet individuals creatively synthesized several domains of knowledge to organize their…

The Ecology of Technological Progress: How Symbiosis and Competition Affect the Growth of Technology Domains

ERIC Educational Resources Information Center

Carnabuci, Gianluca

2010-01-01

We show that the progress of technological knowledge is an inherently ecological process, wherein the growth rate of each technology domain depends on dynamics occurring in "other" technology domains. We identify two sources of ecological interdependence among technology domains. First, there are symbiotic interdependencies, implying…

Automated Extraction of Substance Use Information from Clinical Texts.

PubMed

Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

2015-01-01

Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

Measuring Quality in Ethics Consultation.

PubMed

Bliss, Sally E; Oppenlander, Jane; Dahlke, Jacob M; Meyer, Gordon J; Williford, Eva M; Macauley, Robert C

2016-01-01

For all of the emphasis on quality improvement-as well as the acknowledged overlap between assessment of the quality of healthcare services and clinical ethics-the quality of clinical ethics consultation has received scant attention, especially in terms of empirical measurement. Recognizing this need, the second edition of Core Competencies for Health Care Ethics Consultation1 identified four domains of ethics quality: (1) ethicality, (2) stakeholders' satisfaction, (3) resolution of the presenting conflict/dilemma, and (4) education that translates into knowledge. This study is the first, to our knowledge, to directly measure all of these domains. Here we describe the quality improvement process undertaken at a tertiary care academic medical center, as well as the tools developed to measure the quality of ethics consultation, which include post-consultation satisfaction surveys and weekly case conferences. The information gained through these tools helps to improve not only the process of ethics consultation, but also the measurement and assurance of quality. Copyright 2016 The Journal of Clinical Ethics. All rights reserved.

Executive control systems in the engineering design environment. M.S. Thesis

NASA Technical Reports Server (NTRS)

Hurst, P. W.

1985-01-01

An executive control system (ECS) is a software structure for unifying various applications codes into a comprehensive system. It provides a library of applications, a uniform access method through a cental user interface, and a data management facility. A survey of twenty-four executive control systems designed to unify various CAD/CAE applications for use in diverse engineering design environments within government and industry was conducted. The goals of this research were to establish system requirements to survey state-of-the-art architectural design approaches, and to provide an overview of the historical evolution of these systems. Foundations for design are presented and include environmental settings, system requirements, major architectural components, and a system classification scheme based on knowledge of the supported engineering domain(s). An overview of the design approaches used in developing the major architectural components of an ECS is presented with examples taken from the surveyed systems. Attention is drawn to four major areas of ECS development: interdisciplinary usage; standardization; knowledge utilization; and computer science technology transfer.

Physics education students’ cognitive and affective domains toward ecological phenomena

NASA Astrophysics Data System (ADS)

Napitupulu, N. D.; Munandar, A.; Redjeki, S.; Tjasyono, B.

2018-05-01

Environmental education is become prominent in dealing with natural phenomena that occur nowadays. Studying environmental physics will lead students to have conceptual understanding which are importent in enhancing attitudes toward ecological phenomena that link directry to cognitive and affective domains. This research focused on the the relationship of cognitive and affective domains toward ecological phenomena. Thirty-seven Physics Education students participated in this study and validated sources of data were collected to eksplore students’ conceptual understanding as cognitive domain and to investigate students’ attitudes as affective domain. The percentage of cognitive outcome and affective outcome are explore. The features of such approaches to environmental learning are discussion through analysis of contribution of cognitive to develop the attitude ecological as affective outcome. The result shows that cognitive domains do not contribute significantly to affective domain toward ecological henomena as an issue trend in Central Sulawesi although students had passed Environmental Physics instruction for two semester. In fact, inferior knowledge in a way actually contributes to the attitude domain caused by the prior knowledge that students have as ombo as a Kaili local wisdom.

Ontology-guided data preparation for discovering genotype-phenotype relationships.

PubMed

Coulet, Adrien; Smaïl-Tabbone, Malika; Benlian, Pascale; Napoli, Amedeo; Devignes, Marie-Dominique

2008-04-25

Complexity and amount of post-genomic data constitute two major factors limiting the application of Knowledge Discovery in Databases (KDD) methods in life sciences. Bio-ontologies may nowadays play key roles in knowledge discovery in life science providing semantics to data and to extracted units, by taking advantage of the progress of Semantic Web technologies concerning the understanding and availability of tools for knowledge representation, extraction, and reasoning. This paper presents a method that exploits bio-ontologies for guiding data selection within the preparation step of the KDD process. We propose three scenarios in which domain knowledge and ontology elements such as subsumption, properties, class descriptions, are taken into account for data selection, before the data mining step. Each of these scenarios is illustrated within a case-study relative to the search of genotype-phenotype relationships in a familial hypercholesterolemia dataset. The guiding of data selection based on domain knowledge is analysed and shows a direct influence on the volume and significance of the data mining results. The method proposed in this paper is an efficient alternative to numerical methods for data selection based on domain knowledge. In turn, the results of this study may be reused in ontology modelling and data integration.

Relations among conceptual knowledge, procedural knowledge, and procedural flexibility in two samples differing in prior knowledge.

PubMed

Schneider, Michael; Rittle-Johnson, Bethany; Star, Jon R

2011-11-01

Competence in many domains rests on children developing conceptual and procedural knowledge, as well as procedural flexibility. However, research on the developmental relations between these different types of knowledge has yielded unclear results, in part because little attention has been paid to the validity of the measures or to the effects of prior knowledge on the relations. To overcome these problems, we modeled the three constructs in the domain of equation solving as latent factors and tested (a) whether the predictive relations between conceptual and procedural knowledge were bidirectional, (b) whether these interrelations were moderated by prior knowledge, and (c) how both constructs contributed to procedural flexibility. We analyzed data from 2 measurement points each from two samples (Ns = 228 and 304) of middle school students who differed in prior knowledge. Conceptual and procedural knowledge had stable bidirectional relations that were not moderated by prior knowledge. Both kinds of knowledge contributed independently to procedural flexibility. The results demonstrate how changes in complex knowledge structures contribute to competence development.

A methodology for extending domain coverage in SemRep.

PubMed

Rosemblat, Graciela; Shin, Dongwook; Kilicoglu, Halil; Sneiderman, Charles; Rindflesch, Thomas C

2013-12-01

We describe a domain-independent methodology to extend SemRep coverage beyond the biomedical domain. SemRep, a natural language processing application originally designed for biomedical texts, uses the knowledge sources provided by the Unified Medical Language System (UMLS©). Ontological and terminological extensions to the system are needed in order to support other areas of knowledge. We extended SemRep's application by developing a semantic representation of a previously unsupported domain. This was achieved by adapting well-known ontology engineering phases and integrating them with the UMLS knowledge sources on which SemRep crucially depends. While the process to extend SemRep coverage has been successfully applied in earlier projects, this paper presents in detail the step-wise approach we followed and the mechanisms implemented. A case study in the field of medical informatics illustrates how the ontology engineering phases have been adapted for optimal integration with the UMLS. We provide qualitative and quantitative results, which indicate the validity and usefulness of our methodology. Published by Elsevier Inc.

Assessing knowledge on fibromyalgia among Internet users.

PubMed

Moretti, Felipe Azevedo; Heymann, Roberto Ezequiel; Marvulle, Valdecir; Pollak, Daniel Feldman; Riera, Rachel

2011-01-01

To assess knowledge on fibromyalgia in a sample of patients, their families, and professionals interested on the theme from some Brazilian states. Analysis of the results of an electronic fibromyalgia knowledge questionnaire completed by 362 adults who had access to the the support group for fibromyalgia site (www.unifesp.br/grupos/fibromialgia). The answers were grouped according to age, sex, years of schooling, and type of interest in the condition. 92% of the responders were women and 62% had higher educational level. The worst results were observed in the "joint protection and energy conservation" domain, followed by the "medication in fibromyalgia" domain. The best results were recorded in the "exercises in fibromyalgia" domain. The answers differed significantly between sexes, and women achieved a higher percentage of correct answers. The female sex accounted for a statistically superior result in five statistical analyses (four questions and one domain). The study suggests the need for a strategic planning for an educational approach to fibromyalgia in Brazil.

Relationship between expressed HIV/AIDS-related stigma and HIV-beliefs/knowledge and behaviour in families of HIV infected children in Kenya.

PubMed

Hamra, Mary; Ross, Michael W; Orrs, Mark; D'Agostino, Angelo

2006-04-01

To quantify expressed stigma in clients of the Kangemi program for HIV+ children, and to characterize the association between stigma and other population characteristics. By means of a household survey we created a stigma index and indices for other social and knowledge domains that influence HIV-related healthcare. We used chi2, anova, and correlation to identify associations between domains. The mean (+/-SD) expressed stigma on a six points scale (6 = least stigma) was 3.65 +/- 1.64. Composite scores on knowledge about AIDS were skewed toward more knowledge; and analysis of individual knowledge items indicates that most respondents reject erroneous traditional beliefs and myths about the causes and transmission routes of AIDS. Respondents who were younger, had never married, and had less education expressed greater stigma. Differences in stigma were associated with poor knowledge about AIDS and negative attitudes toward testing, but not with gender or tribal affiliation. Condom use at last intercourse, unrelated to stigma, was only 40% (n = 218). While this population has good knowledge about AIDS and appraises risks realistically, it fails to reduce these risks. Associations between stigma and other domains can inform interventions that improve HIV care and mitigate spread of HIV.

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

Sound credit scores and financial decisions despite cognitive aging

PubMed Central

Li, Ye; Gao, Jie; Enkavi, A. Zeynep; Zaval, Lisa; Weber, Elke U.; Johnson, Eric J.

2015-01-01

Age-related deterioration in cognitive ability may compromise the ability of older adults to make major financial decisions. We explore whether knowledge and expertise accumulated from past decisions can offset cognitive decline to maintain decision quality over the life span. Using a unique dataset that combines measures of cognitive ability (fluid intelligence) and of general and domain-specific knowledge (crystallized intelligence), credit report data, and other measures of decision quality, we show that domain-specific knowledge and expertise provide an alternative route for sound financial decisions. That is, cognitive aging does not spell doom for financial decision-making in domains where the decision maker has developed expertise. These results have important implications for public policy and for the design of effective interventions and decision aids. PMID:25535381

Developmental Foundations of Children’s Fraction Magnitude Knowledge

PubMed Central

Mou, Yi; Li, Yaoran; Hoard, Mary K.; Nugent, Lara D.; Chu, Felicia W.; Rouder, Jeffrey N.; Geary, David C.

2016-01-01

The conceptual insight that fractions represent magnitudes is a critical yet daunting step in children’s mathematical development, and the knowledge of fraction magnitudes influences children’s later mathematics learning including algebra. In this study, longitudinal data were analyzed to identify the mathematical knowledge and domain-general competencies that predicted 8th and 9th graders’ (n=122) knowledge of fraction magnitudes and its cross-grade gains. Performance on the fraction magnitude measures predicted 9th grade algebra achievement. Understanding and fluently identifying the numerator-denominator relation in 7th grade emerged as the key predictor of later fraction magnitudes knowledge in both 8th and 9th grades. Competence at using fraction procedures, knowledge of whole number magnitudes, and the central executive contributed to 9th but not 8th graders’ fraction magnitude knowledge, and knowledge of whole number magnitude contributed to cross-grade gains. The key results suggest fluent processing of numerator-denominator relations presages students’ understanding of fractions as magnitudes and that the integration of whole number and fraction magnitudes occurs gradually. PMID:27773965

The role of domain expertise and judgment in dealing with unexpected events

NASA Astrophysics Data System (ADS)

Kochan, Janeen Adrion

Unexpected events, particularly those creating surprise, interrupt ongoing mental and behavioral processes, creating an increased potential for unwanted outcomes to the situation. Human reactions to unexpected events vary. One can hypothesize a number of reasons for this variation, including level of domain expertise, previous experience with similar events, emotional connotation, and the contextual surround of the event. Whereas interrupting ongoing activities and focusing attention temporarily on a surprising event may be a useful evolutionary response to a threatening situation, the same process may be maladaptive in today's highly dynamic world. The purpose of this study was to investigate how different aspects of expertise affected one's ability to detect and react to an unexpected event. It was hypothesized that there were two general types of expertise, domain expertise and judgment (Hammond, 2000), which influenced one's performance on dealing with an unexpected event. The goal of the research was to parse out the relative contribution of domain expertise, so the role of judgment could be revealed. The research questions for this study were: (a) Can we identify specific knowledges and skills which enhance one's ability to deal with unexpected events? (b) Are these skills "automatically" included in domain expertise? (c) How does domain expertise improve or deter one's reaction and response to unexpected events? (d) What role does judgment play in responding to surprise? The general hypothesis was that good judgment would influence the process of surprise at different stages and in different ways than would domain expertise. The conclusions from this research indicated that good judgment had a significant positive effect in helping pilots deal with unexpected events. This was most pronounced when domain expertise was low.

Preservice Teachers' Professional Knowledge and Its Relation to Academic Self-Concept

ERIC Educational Resources Information Center

Paulick, Isabell; Großschedl, Jörg; Harms, Ute; Möller, Jens

2016-01-01

We investigated the factorial structure of preservice teachers' academic self-concept with regard to three domains of professional knowledge (content knowledge [CK], pedagogical content knowledge [PCK], and pedagogical/psychological knowledge [PPK]). We also analyzed the relation between preservice teachers' academic self-concept and their…

A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis

PubMed Central

Lee, Kyubum; Kim, Byounggun; Jeon, Minji; Kim, Jihye; Tan, Aik Choon

2018-01-01

Background With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. Objective This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since there is no dataset for the biomedical literature comprehension task, our work includes generating a large-scale question answering dataset using PubMed and manually evaluating the generated dataset. Methods We present an attention-based deep neural model tailored to the biomedical domain. To further enhance the performance of our model, we used a pretrained word vector and biomedical entity type embedding. We also developed an ensemble method of combining the results of several independent models to reduce the variance of the answers from the models. Results The experimental results showed that our proposed deep neural network model outperformed the baseline model by more than 7% on the new dataset. We also evaluated human performance on the new dataset. The human evaluation result showed that our deep neural model outperformed humans in comprehension by 22% on average. Conclusions In this work, we introduced a new task of machine comprehension in the biomedical domain using a deep neural model. Since there was no large-scale dataset for training deep neural models in the biomedical domain, we created the new cloze-style datasets Biomedical Knowledge Comprehension Title (BMKC_T) and Biomedical Knowledge Comprehension Last Sentence (BMKC_LS) (together referred to as BioMedical Knowledge Comprehension) using the PubMed corpus. The experimental results showed that the performance of our model is much higher than that of humans. We observed that our model performed consistently better regardless of the degree of difficulty of a text, whereas humans have difficulty when performing biomedical literature comprehension tasks that require expert level knowledge. PMID:29305341

Human systems integration in remotely piloted aircraft operations.

PubMed

Tvaryanas, Anthony P

2006-12-01

The role of humans in remotely piloted aircraft (RPAs) is qualitatively different from manned aviation, lessening the applicability of aerospace medicine human factors knowledge derived from traditional cockpits. Aerospace medicine practitioners should expect to be challenged in addressing RPA crewmember performance. Human systems integration (HSI) provides a model for explaining human performance as a function of the domains of: human factors engineering; personnel; training; manpower; environment, safety, and occupational health (ESOH); habitability; and survivability. RPA crewmember performance is being particularly impacted by issues involving the domains of human factors engineering, personnel, training, manpower, ESOH, and habitability. Specific HSI challenges include: 1) changes in large RPA operator selection and training; 2) human factors engineering deficiencies in current RPA ground control station design and their impact on human error including considerations pertaining to multi-aircraft control; and 3) the combined impact of manpower shortfalls, shiftwork-related fatigue, and degraded crewmember effectiveness. Limited experience and available research makes it difficult to qualitatively or quantitatively predict the collective impact of these issues on RPA crewmember performance. Attending to HSI will be critical for the success of current and future RPA crewmembers. Aerospace medicine practitioners working with RPA crewmembers should gain first-hand knowledge of their task environment while the larger aerospace medicine community needs to address the limited information available on RPA-related aerospace medicine human factors. In the meantime, aeromedical decisions will need to be made based on what is known about other aerospace occupations, realizing this knowledge may have only partial applicability.

An Effective Assessment of Knowledge Sharing and E-Learning Portals

ERIC Educational Resources Information Center

Subramanian, D. Venkata; Geetha, Angelina; Shankar, P.

2015-01-01

In recent years, most of the companies have increasingly realized the importance of the knowledge sharing portal and E-Learning portals to provide competitive knowledge for their employees. The knowledge stored in these portals varies from technical, process and project knowledge functional or domain specific knowledge to face the competitiveness…

Prompted Journal Writing Supports Preservice History Teachers in Drawing on Multiple Knowledge Domains for Designing Learning Tasks

ERIC Educational Resources Information Center

Wäschle, Kristin; Lehmann, Thomas; Brauch, Nicola; Nückles, Matthias

2015-01-01

Becoming a history teacher requires the integration of pedagogical knowledge, pedagogical content knowledge, and content knowledge. Because the integration of knowledge from different disciplines is a complex task, we investigated prompted learning journals as a method to support teacher students' knowledge integration. Fifty-two preservice…

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.

Inference of domain-disease associations from domain-protein, protein-disease and disease-disease relationships.

PubMed

Zhang, Wangshu; Coba, Marcelo P; Sun, Fengzhu

2016-01-11

Protein domains can be viewed as portable units of biological function that defines the functional properties of proteins. Therefore, if a protein is associated with a disease, protein domains might also be associated and define disease endophenotypes. However, knowledge about such domain-disease relationships is rarely available. Thus, identification of domains associated with human diseases would greatly improve our understanding of the mechanism of human complex diseases and further improve the prevention, diagnosis and treatment of these diseases. Based on phenotypic similarities among diseases, we first group diseases into overlapping modules. We then develop a framework to infer associations between domains and diseases through known relationships between diseases and modules, domains and proteins, as well as proteins and disease modules. Different methods including Association, Maximum likelihood estimation (MLE), Domain-disease pair exclusion analysis (DPEA), Bayesian, and Parsimonious explanation (PE) approaches are developed to predict domain-disease associations. We demonstrate the effectiveness of all the five approaches via a series of validation experiments, and show the robustness of the MLE, Bayesian and PE approaches to the involved parameters. We also study the effects of disease modularization in inferring novel domain-disease associations. Through validation, the AUC (Area Under the operating characteristic Curve) scores for Bayesian, MLE, DPEA, PE, and Association approaches are 0.86, 0.84, 0.83, 0.83 and 0.79, respectively, indicating the usefulness of these approaches for predicting domain-disease relationships. Finally, we choose the Bayesian approach to infer domains associated with two common diseases, Crohn's disease and type 2 diabetes. The Bayesian approach has the best performance for the inference of domain-disease relationships. The predicted landscape between domains and diseases provides a more detailed view about the disease mechanisms.

Defense Small Business Innovation Research Program (SBIR) Abstracts of Phase 1 Awards 1983.

DTIC Science & Technology

1984-04-06

STRATEGY, THE INTERPLAY BETWEEN ELECTROMAGNETIC EMISSION CON- TROL AND FLEET OPERATION. THE TECHNICAL APPROACH IS BASED ON AN ANALYSIS OF EMCON...THEM AND A BOTTOM UP APPROACH . THE REQUIREMENTS AND ARCHITECTURAL ASPECTS WILL BE EXPLORED FROM THE MORE ENCOMPASSING PERSPECTIVE OF THE TOTAL...AN AI APPROACH TO INFORMATION FUSION INCLUDING KNOW- LEDGE ORGANIZATION, HYPOTHESIS REPRESENTATIVES, DOMAIN KNOWLEDGE RE- PRESENTATION, HYPOTHESIS

The Motivated Strategies for Learning Questionnaire: score validity among medicine residents.

PubMed

Cook, David A; Thompson, Warren G; Thomas, Kris G

2011-12-01

The Motivated Strategies for Learning Questionnaire (MSLQ) purports to measure motivation using the expectancy-value model. Although it is widely used in other fields, this instrument has received little study in health professions education. The purpose of this study was to evaluate the validity of MSLQ scores. We conducted a validity study evaluating the relationships of MSLQ scores to other variables and their internal structure (reliability and factor analysis). Participants included 210 internal medicine and family medicine residents participating in a web-based course on ambulatory medicine at an academic medical centre. Measurements included pre-course MSLQ scores, pre- and post-module motivation surveys, post-module knowledge test and post-module Instructional Materials Motivation Survey (IMMS) scores. Internal consistency was universally high for all MSLQ items together (Cronbach's α = 0.93) and for each domain (α ≥ 0.67). Total MSLQ scores showed statistically significant positive associations with post-test knowledge scores. For example, a 1-point rise in total MSLQ score was associated with a 4.4% increase in post-test scores (β = 4.4; p < 0.0001). Total MSLQ scores showed moderately strong, statistically significant associations with several other measures of effort, motivation and satisfaction. Scores on MSLQ domains demonstrated associations that generally aligned with our hypotheses. Self-efficacy and control of learning belief scores demonstrated the strongest domain-specific relationships with knowledge scores (β = 2.9 for both). Confirmatory factor analysis showed a borderline model fit. Follow-up exploratory factor analysis revealed the scores of five factors (self-efficacy, intrinsic interest, test anxiety, extrinsic goals, attribution) demonstrated psychometric and predictive properties similar to those of the original scales. Scores on the MSLQ are reliable and predict meaningful outcomes. However, the factor structure suggests a simplified model might better fit the empiric data. Future research might consider how assessing and responding to motivation could enhance learning. © Blackwell Publishing Ltd 2011.

Chapter 1: Biomedical knowledge integration.

PubMed

Payne, Philip R O

2012-01-01

The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems.

Chapter 1: Biomedical Knowledge Integration

PubMed Central

Payne, Philip R. O.

2012-01-01

The modern biomedical research and healthcare delivery domains have seen an unparalleled increase in the rate of innovation and novel technologies over the past several decades. Catalyzed by paradigm-shifting public and private programs focusing upon the formation and delivery of genomic and personalized medicine, the need for high-throughput and integrative approaches to the collection, management, and analysis of heterogeneous data sets has become imperative. This need is particularly pressing in the translational bioinformatics domain, where many fundamental research questions require the integration of large scale, multi-dimensional clinical phenotype and bio-molecular data sets. Modern biomedical informatics theory and practice has demonstrated the distinct benefits associated with the use of knowledge-based systems in such contexts. A knowledge-based system can be defined as an intelligent agent that employs a computationally tractable knowledge base or repository in order to reason upon data in a targeted domain and reproduce expert performance relative to such reasoning operations. The ultimate goal of the design and use of such agents is to increase the reproducibility, scalability, and accessibility of complex reasoning tasks. Examples of the application of knowledge-based systems in biomedicine span a broad spectrum, from the execution of clinical decision support, to epidemiologic surveillance of public data sets for the purposes of detecting emerging infectious diseases, to the discovery of novel hypotheses in large-scale research data sets. In this chapter, we will review the basic theoretical frameworks that define core knowledge types and reasoning operations with particular emphasis on the applicability of such conceptual models within the biomedical domain, and then go on to introduce a number of prototypical data integration requirements and patterns relevant to the conduct of translational bioinformatics that can be addressed via the design and use of knowledge-based systems. PMID:23300416

Unsupervised domain adaptation for early detection of drought stress in hyperspectral images

NASA Astrophysics Data System (ADS)

Schmitter, P.; Steinrücken, J.; Römer, C.; Ballvora, A.; Léon, J.; Rascher, U.; Plümer, L.

2017-09-01

Hyperspectral images can be used to uncover physiological processes in plants if interpreted properly. Machine Learning methods such as Support Vector Machines (SVM) and Random Forests have been applied to estimate development of biomass and detect and predict plant diseases and drought stress. One basic requirement of machine learning implies, that training and testing is done in the same domain and the same distribution. Different genotypes, environmental conditions, illumination and sensors violate this requirement in most practical circumstances. Here, we present an approach, which enables the detection of physiological processes by transferring the prior knowledge within an existing model into a related target domain, where no label information is available. We propose a two-step transformation of the target features, which enables a direct application of an existing model. The transformation is evaluated by an objective function including additional prior knowledge about classification and physiological processes in plants. We have applied the approach to three sets of hyperspectral images, which were acquired with different plant species in different environments observed with different sensors. It is shown, that a classification model, derived on one of the sets, delivers satisfying classification results on the transformed features of the other data sets. Furthermore, in all cases early non-invasive detection of drought stress was possible.

Validation of a Survey Questionnaire on Organ Donation: An Arabic World Scenario

PubMed Central

Agarwal, Tulika Mehta; Al-Thani, Hassan; Al Maslamani, Yousuf

2018-01-01

Objective To validate a questionnaire for measuring factors influencing organ donation and transplant. Methods The constructed questionnaire was based on the theory of planned behavior by Ajzen Icek and had 45 questions including general inquiry and demographic information. Four experts on the topic, Arabic culture, and the Arabic and English languages established content validity through review. It was quantified by content validity index (CVI). Construct validity was established by principal component analysis (PCA), whereas internal consistency was checked by Cronbach's Alpha and intraclass correlation coefficient (ICC). Statistical analysis was performed by SPSS 22.0 statistical package. Results Content validity in the form of S-CVI/Average and S-CVI/UA was 0.95 and 0.82, respectively, suggesting adequate relevance content of the questionnaire. Factor analysis indicated that the construct validity for each domain (knowledge, attitudes, beliefs, and intention) was 65%, 71%, 77%, and 70%, respectively. Cronbach's Alpha and ICC coefficients were 0.90, 0.67, 0.75, and 0.74 and 0.82, 0.58, 0.61, and 0.74, respectively, for the domains. Conclusion The questionnaire consists of 39 items on knowledge, attitudes, beliefs, and intention domains which is valid and reliable tool to use for organ donation and transplant survey. PMID:29593894

Analysing Teacher Knowledge for Technology Education in Primary Schools

ERIC Educational Resources Information Center

Rohaan, Ellen J.; Taconis, Ruurd; Jochems, Wim M. G.

2012-01-01

Teacher knowledge guides a teacher's behaviour in the classroom. Teacher knowledge for technology education is generally assumed to play an important role in affecting pupils' learning in technology. There are an abundant number of teacher knowledge models that visualise different domains of teacher knowledge, but clear empirical evidence on how…

Developing expectations regarding the boundaries of expertise.

PubMed

Landrum, Asheley R; Mills, Candice M

2015-01-01

Three experiments examined elementary school-aged children's and adults' expectations regarding what specialists (i.e., those with narrow domains of expertise) and generalists (i.e., those with broad domains of expertise) are likely to know. Experiment 1 demonstrated developmental differences in the ability to differentiate between generalists and specialists, with younger children believing generalists have more specific trivia knowledge than older children and adults believed. Experiment 2 demonstrated that children and adults expected generalists to have more underlying principles knowledge than specific trivia knowledge about unfamiliar animals. However, they believed that generalists would have more of both types of knowledge than themselves. Finally, Experiment 3 demonstrated that children and adults recognized that underlying principles knowledge can be generalized between topics closely related to the specialists' domains of expertise. However, they did not recognize when this knowledge was generalizable to topics slightly less related, expecting generalists to know only as much as they would. Importantly, this work contributes to the literature by showing how much of and what kinds of knowledge different types of experts are expected to have. In sum, this work provides insight into some of the ways children's notions of expertise change over development. The current research demonstrates that between the ages of 5 and 10, children are developing the ability to recognize how experts' knowledge is likely to be limited. That said, even older children at times struggle to determine the breadth of an experts' knowledge. Copyright © 2014 Elsevier B.V. All rights reserved.

Assimilative domain proficiency and performance in chemistry coursework

NASA Astrophysics Data System (ADS)

Byrnes, Scott William

The assimilation and synthesis of knowledge is essential for students to be successful in chemistry, yet not all students synthesize knowledge as intended. The study used the Learning Preference Checklist to classify students into one of three learning modalities -- visual, auditory, or kinesthetic (VAK). It also used the Kolb Learning Style Inventory (KLSI), which utilizes four learning domains - Converging, Accommodating, Diverging, and Assimilating - to explain the students' maturation process by showing shift from any domain towards the Assimilating domain. A shift approaching this domain was considered as improvement in the assimilation and synthesis of knowledge. This pre-experimental one-group pretest-posttest study was used to test the hypothesis that modifying a high school chemistry curriculum to accentuate a student's learning preference would result in a shift towards the Assimilative domain on the KLSI and if there was a correlation between the improvement in student learning and a shift towards the KLSI Assimilating domain. Forty-two high school students were issued the VAK and provided with differentiated instruction via homologous cooperative learning groups. Pre- and post-KLSI and chemistry concepts tests were administered. T test analyses showed no significant shift towards the Assimilating domain. Further Pearson's r analyses showed no significant correlation between the KLSI and exam scores. This study contributes to social change by providing empirical evidence related to the effectiveness infusing learning styles into the science curriculum and the integration of the KLSI to monitor cognitive development as tools in raising standardized test scores and enhancing academic achievement. Results from the study can also inform future research into learning styles through their incorporation into the science curriculum.

Ontology-based classification of remote sensing images using spectral rules

NASA Astrophysics Data System (ADS)

Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

2017-05-01

Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications

PubMed Central

Chang, Hang; Han, Ju; Zhong, Cheng; Snijders, Antoine M.; Mao, Jian-Hua

2017-01-01

The capabilities of (I) learning transferable knowledge across domains; and (II) fine-tuning the pre-learned base knowledge towards tasks with considerably smaller data scale are extremely important. Many of the existing transfer learning techniques are supervised approaches, among which deep learning has the demonstrated power of learning domain transferrable knowledge with large scale network trained on massive amounts of labeled data. However, in many biomedical tasks, both the data and the corresponding label can be very limited, where the unsupervised transfer learning capability is urgently needed. In this paper, we proposed a novel multi-scale convolutional sparse coding (MSCSC) method, that (I) automatically learns filter banks at different scales in a joint fashion with enforced scale-specificity of learned patterns; and (II) provides an unsupervised solution for learning transferable base knowledge and fine-tuning it towards target tasks. Extensive experimental evaluation of MSCSC demonstrates the effectiveness of the proposed MSCSC in both regular and transfer learning tasks in various biomedical domains. PMID:28129148

What Sensing Tells Us: Towards a Formal Theory of Testing for Dynamical Systems

NASA Technical Reports Server (NTRS)

McIlraith, Sheila; Scherl, Richard

2005-01-01

Just as actions can have indirect effects on the state of the world, so too can sensing actions have indirect effects on an agent's state of knowledge. In this paper, we investigate "what sensing actions tell us", i.e., what an agent comes to know indirectly from the outcome of a sensing action, given knowledge of its actions and state constraints that hold in the world. To this end, we propose a formalization of the notion of testing within a dialect of the situation calculus that includes knowledge and sensing actions. Realizing this formalization requires addressing the ramification problem for sensing actions. We formalize simple tests as sensing actions. Complex tests are expressed in the logic programming language Golog. We examine what it means to perform a test, and how the outcome of a test affects an agent's state of knowledge. Finally, we propose automated reasoning techniques for test generation and complex-test verification, under certain restrictions. The work presented in this paper is relevant to a number of application domains including diagnostic problem solving, natural language understanding, plan recognition, and active vision.

Transcriptomics of the Bed Bug (Cimex lectularius)

PubMed Central

Rajarapu, Swapna P.; Jones, Susan C.; Mittapalli, Omprakash

2011-01-01

Background Bed bugs (Cimex lectularius) are blood-feeding insects poised to become one of the major pests in households throughout the United States. Resistance of C. lectularius to insecticides/pesticides is one factor thought to be involved in its sudden resurgence. Despite its high-impact status, scant knowledge exists at the genomic level for C. lectularius. Hence, we subjected the C. lectularius transcriptome to 454 pyrosequencing in order to identify potential genes involved in pesticide resistance. Methodology and Principal Findings Using 454 pyrosequencing, we obtained a total of 216,419 reads with 79,596,412 bp, which were assembled into 35,646 expressed sequence tags (3902 contigs and 31744 singletons). Nearly 85.9% of the C. lectularius sequences showed similarity to insect sequences, but 44.8% of the deduced proteins of C. lectularius did not show similarity with sequences in the GenBank non-redundant database. KEGG analysis revealed putative members of several detoxification pathways involved in pesticide resistance. Lamprin domains, Protein Kinase domains, Protein Tyrosine Kinase domains and cytochrome P450 domains were among the top Pfam domains predicted for the C. lectularius sequences. An initial assessment of putative defense genes, including a cytochrome P450 and a glutathione-S-transferase (GST), revealed high transcript levels for the cytochrome P450 (CYP9) in pesticide-exposed versus pesticide-susceptible C. lectularius populations. A significant number of single nucleotide polymorphisms (296) and microsatellite loci (370) were predicted in the C. lectularius sequences. Furthermore, 59 putative sequences of Wolbachia were retrieved from the database. Conclusions To our knowledge this is the first study to elucidate the genetic makeup of C. lectularius. This pyrosequencing effort provides clues to the identification of potential detoxification genes involved in pesticide resistance of C. lectularius and lays the foundation for future functional genomics studies. PMID:21283830

Event extraction of bacteria biotopes: a knowledge-intensive NLP-based approach

PubMed Central

2012-01-01

Background Bacteria biotopes cover a wide range of diverse habitats including animal and plant hosts, natural, medical and industrial environments. The high volume of publications in the microbiology domain provides a rich source of up-to-date information on bacteria biotopes. This information, as found in scientific articles, is expressed in natural language and is rarely available in a structured format, such as a database. This information is of great importance for fundamental research and microbiology applications (e.g., medicine, agronomy, food, bioenergy). The automatic extraction of this information from texts will provide a great benefit to the field. Methods We present a new method for extracting relationships between bacteria and their locations using the Alvis framework. Recognition of bacteria and their locations was achieved using a pattern-based approach and domain lexical resources. For the detection of environment locations, we propose a new approach that combines lexical information and the syntactic-semantic analysis of corpus terms to overcome the incompleteness of lexical resources. Bacteria location relations extend over sentence borders, and we developed domain-specific rules for dealing with bacteria anaphors. Results We participated in the BioNLP 2011 Bacteria Biotope (BB) task with the Alvis system. Official evaluation results show that it achieves the best performance of participating systems. New developments since then have increased the F-score by 4.1 points. Conclusions We have shown that the combination of semantic analysis and domain-adapted resources is both effective and efficient for event information extraction in the bacteria biotope domain. We plan to adapt the method to deal with a larger set of location types and a large-scale scientific article corpus to enable microbiologists to integrate and use the extracted knowledge in combination with experimental data. PMID:22759462

Pharmacy executive leadership issues and associated skills, knowledge, and abilities.

PubMed

Meadows, Andrew B; Maine, Lucinda L; Keyes, Elizabeth K; Pearson, Kathy; Finstuen, Kenn

2005-01-01

To identify challenges that current and future pharmacy executives are facing or will face in the future and to define what skills, knowledge, and abilities (SKAs) are required to successfully negotiate these challenges. Delphi method for executive decision making. Civilian pharmacy profession. 110 pharmacists who graduated from the GlaxoSmithKline Executive Management Program for Pharmacy Leaders. Two iterations of the Delphi method for executive decision making separated by an expert panel content analysis. Round 1--participants were asked to identify five major issues they believed to be of greatest importance to pharmacy leaders in the next 5-10 years and name specific SKAs that might be needed by future leaders to successfully deal with those issues. An expert panel reviewed the issues, classified issues into specific domains, and titled each domain. Round 2-participants rated the SKAs on a 7-point scale according to their individual assessment of importance in each domain. For Delphi rounds 1 and 2, response rates were 21.8% and 18.2%, respectively. More than 100 total issue statements were identified. The expert panel sorted the issues into five domains: management and development of the pharmacy workforce, pharmacy finance, total quality management of work-flow systems, influences on the practice of pharmacy, and professional pharmacy leadership. Five of the top 15 SKAs-and all four highest ranked items--came from the professional pharmacy leadership domain, including ability to see the big picture, ability to demonstrate the value of pharmacy services, ability to lead and manage in an ethical manner, and skills for influencing an organization's senior leadership. Through successful integration of communication skills, critical thinking, and problem solving techniques, future public-sector pharmacy executives will be better equipped to effectively position their organizations and the profession for the challenges that lie ahead.

Event extraction of bacteria biotopes: a knowledge-intensive NLP-based approach.

PubMed

Ratkovic, Zorana; Golik, Wiktoria; Warnier, Pierre

2012-06-26

Bacteria biotopes cover a wide range of diverse habitats including animal and plant hosts, natural, medical and industrial environments. The high volume of publications in the microbiology domain provides a rich source of up-to-date information on bacteria biotopes. This information, as found in scientific articles, is expressed in natural language and is rarely available in a structured format, such as a database. This information is of great importance for fundamental research and microbiology applications (e.g., medicine, agronomy, food, bioenergy). The automatic extraction of this information from texts will provide a great benefit to the field. We present a new method for extracting relationships between bacteria and their locations using the Alvis framework. Recognition of bacteria and their locations was achieved using a pattern-based approach and domain lexical resources. For the detection of environment locations, we propose a new approach that combines lexical information and the syntactic-semantic analysis of corpus terms to overcome the incompleteness of lexical resources. Bacteria location relations extend over sentence borders, and we developed domain-specific rules for dealing with bacteria anaphors. We participated in the BioNLP 2011 Bacteria Biotope (BB) task with the Alvis system. Official evaluation results show that it achieves the best performance of participating systems. New developments since then have increased the F-score by 4.1 points. We have shown that the combination of semantic analysis and domain-adapted resources is both effective and efficient for event information extraction in the bacteria biotope domain. We plan to adapt the method to deal with a larger set of location types and a large-scale scientific article corpus to enable microbiologists to integrate and use the extracted knowledge in combination with experimental data.

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.

Rating knowledge sharing in cross-domain collaborative filtering.

PubMed

Li, Bin; Zhu, Xingquan; Li, Ruijiang; Zhang, Chengqi

2015-05-01

Cross-domain collaborative filtering (CF) aims to share common rating knowledge across multiple related CF domains to boost the CF performance. In this paper, we view CF domains as a 2-D site-time coordinate system, on which multiple related domains, such as similar recommender sites or successive time-slices, can share group-level rating patterns. We propose a unified framework for cross-domain CF over the site-time coordinate system by sharing group-level rating patterns and imposing user/item dependence across domains. A generative model, say ratings over site-time (ROST), which can generate and predict ratings for multiple related CF domains, is developed as the basic model for the framework. We further introduce cross-domain user/item dependence into ROST and extend it to two real-world cross-domain CF scenarios: 1) ROST (sites) for alleviating rating sparsity in the target domain, where multiple similar sites are viewed as related CF domains and some items in the target domain depend on their correspondences in the related ones; and 2) ROST (time) for modeling user-interest drift over time, where a series of time-slices are viewed as related CF domains and a user at current time-slice depends on herself in the previous time-slice. All these ROST models are instances of the proposed unified framework. The experimental results show that ROST (sites) can effectively alleviate the sparsity problem to improve rating prediction performance and ROST (time) can clearly track and visualize user-interest drift over time.

Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

PubMed

Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

2013-03-01

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

Young Children Bet On Their Numerical Skills: Metacognition in the Numerical Domain

PubMed Central

Vo, Vy A.; Li, Rosa; Kornell, Nate; Pouget, Alexandre; Cantlon, Jessica F.

2014-01-01

Metacognition, the ability to assess one’s own knowledge, has been targeted as a critical learning mechanism in mathematics education. Yet, the early childhood origins of metacognition have proven difficult to study. Using a novel nonverbal task and a comprehensive set of metacognitive measures, we provide the strongest evidence to date that young children are metacognitive. We show that children as young as 5 years make metacognitive “bets” on their numerical discriminations in a wagering task. However, contrary to previous reports from adults, children’s metacognition proved to be domain-specific: children’s metacognition in the numerical domain was unrelated to their metacognition in another domain (emotion discrimination). Moreover, children’s metacognitive ability in only the numerical domain predicted their school-based mathematics knowledge. The data provide novel evidence that metacognition is a fundamental, domain-dependent cognitive ability in children. The findings have implications for theories of uncertainty and reveal new avenues for training metacognition in children. PMID:24973137

Tetraspanins and Transmembrane Adaptor Proteins As Plasma Membrane Organizers-Mast Cell Case.

PubMed

Halova, Ivana; Draber, Petr

2016-01-01

The plasma membrane contains diverse and specialized membrane domains, which include tetraspanin-enriched domains (TEMs) and transmembrane adaptor protein (TRAP)-enriched domains. Recent biophysical, microscopic, and functional studies indicated that TEMs and TRAP-enriched domains are involved in compartmentalization of physicochemical events of such important processes as immunoreceptor signal transduction and chemotaxis. Moreover, there is evidence of a cross-talk between TEMs and TRAP-enriched domains. In this review we discuss the presence and function of such domains and their crosstalk using mast cells as a model. The combined data based on analysis of selected mast cell-expressed tetraspanins [cluster of differentiation (CD)9, CD53, CD63, CD81, CD151)] or TRAPs [linker for activation of T cells (LAT), non-T cell activation linker (NTAL), and phosphoprotein associated with glycosphingolipid-enriched membrane microdomains (PAG)] using knockout mice or specific antibodies point to a diversity within these two families and bring evidence of the important roles of these molecules in signaling events. An example of this diversity is physical separation of two TRAPs, LAT and NTAL, which are in many aspects similar but show plasma membrane location in different microdomains in both non-activated and activated cells. Although our understanding of TEMs and TRAP-enriched domains is far from complete, pharmaceutical applications of the knowledge about these domains are under way.

Ground Operations Autonomous Control and Integrated Health Management

NASA Technical Reports Server (NTRS)

Daniels, James

2014-01-01

The Ground Operations Autonomous Control and Integrated Health Management plays a key role for future ground operations at NASA. The software that is integrated into this system is called G2 2011 Gensym. The purpose of this report is to describe the Ground Operations Autonomous Control and Integrated Health Management with the use of the G2 Gensym software and the G2 NASA toolkit for Integrated System Health Management (ISHM) which is a Computer Software Configuration Item (CSCI). The decision rationale for the use of the G2 platform is to develop a modular capability for ISHM and AC. Toolkit modules include knowledge bases that are generic and can be applied in any application domain module. That way, there's a maximization of reusability, maintainability, and systematic evolution, portability, and scalability. Engine modules are generic, while application modules represent the domain model of a specific application. Furthermore, the NASA toolkit, developed since 2006 (a set of modules), makes it possible to create application domain models quickly, using pre-defined objects that include sensors and components libraries for typical fluid, electrical, and mechanical systems.

[Attrition and poor performance in general practice training: age, competence and knowledge play a role].

PubMed

Vermeulen, Margit I; Kuyvenhoven, Marijke M; Zuithoff, N P A Peter; van der Graaf, Yolanda; Pieters, H M Ron

2011-01-01

To investigate which determinants are related to poor performance and forced attrition in the first year residency in general practice (GP). Observational retrospective cohort study. We collected data relating to personal characteristics such as age, sex and clinical experience from residents who started the GP training in Utrecht, the Netherlands, in the period March 2005-August 2007. We also collected competence scores from the domains 'medical expertise', 'doctor-patient communication' and 'professionalism', as well as scores on a national GP knowledge test. The outcome measures were 'poor performance' and 'forced attrition'. Multivariate logistic regression was used to analyse correlations between personal characteristics, competence scores on the 3 domains and knowledge scores in the first trimester on the one hand and poor performance or forced attrition on the other. 215 residents started the GP training. In the first trimester a quarter of the residents had an insufficient score in 1 or more of the domains. Competence scores were mutually correlated, but did not correlate with the knowledge score. 18 residents showed poor performance and 3 were forced to stop their training. Poor performance and forced attrition were correlated with age (adjusted odds ratio (OR): 1.1; 95% CI: 1.0-1.3), insufficient knowledge (adjusted OR: 8.9; 3.0-26.3) and medical expertise (adjusted OR: 2.1; 1.1-4.0) at the beginning of the training. Age, insufficient knowledge of general practice, and insufficient competence in the domain of 'medical expertise' at the beginning of the training are risk factors for poor performance by residents and attrition from their GP training.

A qualitative study using the Theoretical Domains Framework to investigate why patients were or were not assessed for rehabilitation after stroke.

PubMed

Lynch, Elizabeth A; Luker, Julie A; Cadilhac, Dominique A; Fryer, Caroline E; Hillier, Susan L

2017-07-01

To explore the factors perceived to affect rehabilitation assessment and referral practices for patients with stroke. Qualitative study using data from focus groups analysed thematically and then mapped to the Theoretical Domains Framework. Eight acute stroke units in two states of Australia. Health professionals working in acute stroke units. Health professionals at all sites had participated in interventions to improve rehabilitation assessment and referral practices, which included provision of copies of an evidence-based decision-making rehabilitation Assessment Tool and pathway. Eight focus groups were conducted (32 total participants). Reported rehabilitation assessment and referral practices varied markedly between units. Continence and mood were not routinely assessed (4 units), and people with stroke symptoms were not consistently referred to rehabilitation (4 units). Key factors influencing practice were identified and included whether health professionals perceived that use of the Assessment Tool would improve rehabilitation assessment practices (theoretical domain 'social and professional role'); beliefs about outcomes from changing practice such as increased equity for patients or conversely that changing rehabilitation referral patterns would not affect access to rehabilitation ('belief about consequences'); the influence of the unit's relationships with other groups including rehabilitation teams ('social influences' domain) and understanding within the acute stroke unit team of the purpose of changing assessment practices ('knowledge' domain). This study has identified that health professionals' perceived roles, beliefs about consequences from changing practice and relationships with rehabilitation service providers were perceived to influence rehabilitation assessment and referral practices on Australian acute stroke units.

An Ontology Based Approach to Information Security

NASA Astrophysics Data System (ADS)

Pereira, Teresa; Santos, Henrique

The semantically structure of knowledge, based on ontology approaches have been increasingly adopted by several expertise from diverse domains. Recently ontologies have been moved from the philosophical and metaphysics disciplines to be used in the construction of models to describe a specific theory of a domain. The development and the use of ontologies promote the creation of a unique standard to represent concepts within a specific knowledge domain. In the scope of information security systems the use of an ontology to formalize and represent the concepts of security information challenge the mechanisms and techniques currently used. This paper intends to present a conceptual implementation model of an ontology defined in the security domain. The model presented contains the semantic concepts based on the information security standard ISO/IEC_JTC1, and their relationships to other concepts, defined in a subset of the information security domain.

NOUS: Construction and Querying of Dynamic Knowledge Graphs

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

Choudhury, Sutanay; Agarwal, Khushbu; Purohit, Sumit

The ability to construct domain specific knowledge graphs (KG) and perform question-answering or hypothesis generation is a trans- formative capability. Despite their value, automated construction of knowledge graphs remains an expensive technical challenge that is beyond the reach for most enterprises and academic institutions. We propose an end-to-end framework for developing custom knowl- edge graph driven analytics for arbitrary application domains. The uniqueness of our system lies A) in its combination of curated KGs along with knowledge extracted from unstructured text, B) support for advanced trending and explanatory questions on a dynamic KG, and C) the ability to answer queriesmore » where the answer is embedded across multiple data sources.« less

What's in a domain: Understanding how students approach questioning in history and science

NASA Astrophysics Data System (ADS)

Portnoy, Lindsay Blau

During their education, students are presented with information across a variety of academic domains. How students ask questions as they learn has implications for understanding, retention, and problem solving. The current research investigates the influence of age and prior knowledge on the ways students approach questioning across history and science content. In two studies, students read history and science passages and then generated questions they would ask to make sense of the content. Nine categories of questions were identified to discern patterns of inquiry across both domains. Results indicate that while age and prior knowledge may play a role in the way students ask questions by domain there are persistent main effects of domain across both studies. Specifically, across both studies students ask questions regarding the purpose or function of ideas in science passages, whereas history passage are more regularly met with questions for supplemental information to complete a student's understanding. In contrast to extant research on developmental status or experience within a content area, current work suggests that domains themselves hold unique properties, which may influence how students approach questioning across domains.

Conceptualising forensic science and forensic reconstruction. Part II: The critical interaction between research, policy/law and practice.

PubMed

Morgan, R M

2017-11-01

This paper builds on the FoRTE conceptual model presented in part I to address the forms of knowledge that are integral to the four components of the model. Articulating the different forms of knowledge within effective forensic reconstructions is valuable. It enables a nuanced approach to the development and use of evidence bases to underpin decision-making at every stage of a forensic reconstruction by enabling transparency in the reporting of inferences. It also enables appropriate methods to be developed to ensure quality and validity. It is recognised that the domains of practice, research, and policy/law intersect to form the nexus where forensic science is situated. Each domain has a distinctive infrastructure that influences the production and application of different forms of knowledge in forensic science. The channels that can enable the interaction between these domains, enhance the impact of research in theory and practice, increase access to research findings, and support quality are presented. The particular strengths within the different domains to deliver problem solving forensic reconstructions are thereby identified and articulated. It is argued that a conceptual understanding of forensic reconstruction that draws on the full range of both explicit and tacit forms of knowledge, and incorporates the strengths of the different domains pertinent to forensic science, offers a pathway to harness the full value of trace evidence for context sensitive, problem-solving forensic applications. Copyright © 2017 The Author. Published by Elsevier B.V. All rights reserved.

Documentation and knowledge acquisition

NASA Technical Reports Server (NTRS)

Rochowiak, Daniel; Moseley, Warren

1990-01-01

Traditional approaches to knowledge acquisition have focused on interviews. An alternative focuses on the documentation associated with a domain. Adopting a documentation approach provides some advantages during familiarization. A knowledge management tool was constructed to gain these advantages.

Large system change challenges: addressing complex critical issues in linked physical and social domains

NASA Astrophysics Data System (ADS)

Waddell, Steve; Cornell, Sarah; Hsueh, Joe; Ozer, Ceren; McLachlan, Milla; Birney, Anna

2015-04-01

Most action to address contemporary complex challenges, including the urgent issues of global sustainability, occurs piecemeal and without meaningful guidance from leading complex change knowledge and methods. The potential benefit of using such knowledge is greater efficacy of effort and investment. However, this knowledge and its associated tools and methods are under-utilized because understanding about them is low, fragmented between diverse knowledge traditions, and often requires shifts in mindsets and skills from expert-led to participant-based action. We have been engaged in diverse action-oriented research efforts in Large System Change for sustainability. For us, "large" systems can be characterized as large-scale systems - up to global - with many components, of many kinds (physical, biological, institutional, cultural/conceptual), operating at multiple levels, driven by multiple forces, and presenting major challenges for people involved. We see change of such systems as complex challenges, in contrast with simple or complicated problems, or chaotic situations. In other words, issues and sub-systems have unclear boundaries, interact with each other, and are often contradictory; dynamics are non-linear; issues are not "controllable", and "solutions" are "emergent" and often paradoxical. Since choices are opportunity-, power- and value-driven, these social, institutional and cultural factors need to be made explicit in any actionable theory of change. Our emerging network is sharing and building a knowledge base of experience, heuristics, and theories of change from multiple disciplines and practice domains. We will present our views on focal issues for the development of the field of large system change, which include processes of goal-setting and alignment; leverage of systemic transitions and transformation; and the role of choice in influencing critical change processes, when only some sub-systems or levels of the system behave in purposeful ways, while others are undeniably and unavoidably deterministic.

Using Doubly Latent Multilevel Analysis to Elucidate Relationships between Science Teachers' Professional Knowledge and Students' Performance

ERIC Educational Resources Information Center

Mahler, Daniela; Großschedl, Jörg; Harms, Ute

2017-01-01

Teachers make a difference for the outcome of their students in science classrooms. One focus in this context lies on teachers' professional knowledge. We describe this knowledge according to three domains, namely (1) content knowledge (CK), (2) pedagogical content knowledge (PCK), and (3) curricular knowledge (CuK). We hypothesise a positive…

Building Scalable Knowledge Graphs for Earth Science

NASA Technical Reports Server (NTRS)

Ramachandran, Rahul; Maskey, Manil; Gatlin, Patrick; Zhang, Jia; Duan, Xiaoyi; Miller, J. J.; Bugbee, Kaylin; Christopher, Sundar; Freitag, Brian

2017-01-01

Knowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.

Domain adaptation via transfer component analysis.

PubMed

Pan, Sinno Jialin; Tsang, Ivor W; Kwok, James T; Yang, Qiang

2011-02-01

Domain adaptation allows knowledge from a source domain to be transferred to a different but related target domain. Intuitively, discovering a good feature representation across domains is crucial. In this paper, we first propose to find such a representation through a new learning method, transfer component analysis (TCA), for domain adaptation. TCA tries to learn some transfer components across domains in a reproducing kernel Hilbert space using maximum mean miscrepancy. In the subspace spanned by these transfer components, data properties are preserved and data distributions in different domains are close to each other. As a result, with the new representations in this subspace, we can apply standard machine learning methods to train classifiers or regression models in the source domain for use in the target domain. Furthermore, in order to uncover the knowledge hidden in the relations between the data labels from the source and target domains, we extend TCA in a semisupervised learning setting, which encodes label information into transfer components learning. We call this extension semisupervised TCA. The main contribution of our work is that we propose a novel dimensionality reduction framework for reducing the distance between domains in a latent space for domain adaptation. We propose both unsupervised and semisupervised feature extraction approaches, which can dramatically reduce the distance between domain distributions by projecting data onto the learned transfer components. Finally, our approach can handle large datasets and naturally lead to out-of-sample generalization. The effectiveness and efficiency of our approach are verified by experiments on five toy datasets and two real-world applications: cross-domain indoor WiFi localization and cross-domain text classification.

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.

Specificity of Structural Assessment of Knowledge

ERIC Educational Resources Information Center

Trumpower, David L.; Sharara, Harold; Goldsmith, Timothy E.

2010-01-01

This study examines the specificity of information provided by structural assessment of knowledge (SAK). SAK is a technique which uses the Pathfinder scaling algorithm to transform ratings of concept relatedness into network representations (PFnets) of individuals' knowledge. Inferences about individuals' overall domain knowledge based on the…

The Challenge of Learning Physics Before Mathematics: A Case Study of Curriculum Change in Taiwan

NASA Astrophysics Data System (ADS)

Chiu, Mei-Shiu

2016-12-01

The aim of this study was to identify challenges in implementing a physics-before- 10 mathematics curriculum. Obviously, students need to learn necessary mathematics skills in order to develop advanced physics knowledge. In the 2010 high school curriculum in Taiwan, however, grade 11 science students study two-dimensional motion in physics without prior learning experiences of trigonometry in mathematics. The perspectives of three curriculum developers, 22 mathematics and physics teachers, two principals, and 45 science students were obtained by interview. The results of qualitative data analysis revealed six challenges and suggested likely solutions. The national level includes political and social challenges, resolved by respecting teachers as professionals; the teacher level includes knowledge and teaching challenges, resolved by increasing teacher trans-literal capacities; and the student level includes learning and justice challenges, resolved by focusing on students' diverse developments in cross-domain learning.

Succession Planning in State Health Agencies in the United States: A Brief Report.

PubMed

Harper, Elizabeth; Leider, Jonathon P; Coronado, Fatima; Beck, Angela J

2017-11-02

Approximately 25% of the public health workforce plans to retire by 2020. Succession planning is a core capability of the governmental public health enterprise; however, limited data are available regarding these efforts in state health agencies (SHAs). We analyzed 2016 Workforce Gaps Survey data regarding succession planning in SHAs using the US Office of Personnel Management's (OPM's) succession planning model, including 6 domains and 27 activities. Descriptive statistics were calculated for all 41 responding SHAs. On average, SHAs self-reported adequately addressing 11 of 27 succession planning activities, with 93% of SHAs adequately addressing 1 or more activities and 61% adequately addressing 1 or more activities in each domain. The majority of OPM-recommended succession planning activities are not being addressed, and limited succession planning occurs across SHAs. Greater activity in the OPM-identified succession planning domains may help SHAs contend with significant turnover and better preserve institutional knowledge.

The Effects of Using Multimedia Presentations and Modular Worked-Out Examples as Instructional Methodologies to Manage the Cognitive Processing Associated with Information Literacy Instruction at the Graduate and Undergraduate Levels of Nursing Education

ERIC Educational Resources Information Center

Calhoun, Shawn P.

2012-01-01

Information literacy is a complex knowledge domain. Cognitive processing theory describes the effects an instructional subject and the learning environment have on working memory. Essential processing is one component of cognitive processing theory that explains the inherent complexity of knowledge domains such as information literacy. Prior…

Effects of Process-Oriented and Product-Oriented Worked Examples and Prior Knowledge on Learner Problem Solving and Attitude: A Study in the Domain of Microeconomics

ERIC Educational Resources Information Center

Brooks, Christopher Darren

2009-01-01

The purpose of this study was to investigate the effectiveness of process-oriented and product-oriented worked example strategies and the mediating effect of prior knowledge (high versus low) on problem solving and learner attitude in the domain of microeconomics. In addition, the effect of these variables on learning efficiency as well as the…

The use of concept maps during knowledge elicitation in ontology development processes – the nutrigenomics use case

PubMed Central

Castro, Alexander Garcia; Rocca-Serra, Philippe; Stevens, Robert; Taylor, Chris; Nashar, Karim; Ragan, Mark A; Sansone, Susanna-Assunta

2006-01-01

Background Incorporation of ontologies into annotations has enabled 'semantic integration' of complex data, making explicit the knowledge within a certain field. One of the major bottlenecks in developing bio-ontologies is the lack of a unified methodology. Different methodologies have been proposed for different scenarios, but there is no agreed-upon standard methodology for building ontologies. The involvement of geographically distributed domain experts, the need for domain experts to lead the design process, the application of the ontologies and the life cycles of bio-ontologies are amongst the features not considered by previously proposed methodologies. Results Here, we present a methodology for developing ontologies within the biological domain. We describe our scenario, competency questions, results and milestones for each methodological stage. We introduce the use of concept maps during knowledge acquisition phases as a feasible transition between domain expert and knowledge engineer. Conclusion The contributions of this paper are the thorough description of the steps we suggest when building an ontology, example use of concept maps, consideration of applicability to the development of lower-level ontologies and application to decentralised environments. We have found that within our scenario conceptual maps played an important role in the development process. PMID:16725019

STEM learning research through a funds of knowledge lens

NASA Astrophysics Data System (ADS)

Civil, Marta

2016-03-01

This article examines STEM learning as a cultural process with a focus on non-dominant communities. Building on my work in funds of knowledge and mathematics education, I present three vignettes to raise some questions around connections between in-school and out-of-school mathematics. How do we define competence? How do task and environment affect engagement? What is the role of affect, language, and cognition in different settings? These vignettes serve to highlight the complexity of moving across different domains of STEM practice—everyday life, school, and STEM disciplines. Based on findings from occupational interviews I discuss characteristics of learning and engaging in everyday practices and propose several areas for further research, including the nature of everyday STEM practices, valorization of knowledge, language choice, and different forms of engagement.

Comparing Four Instructional Techniques for Promoting Robust Knowledge

ERIC Educational Resources Information Center

Richey, J. Elizabeth; Nokes-Malach, Timothy J.

2015-01-01

Robust knowledge serves as a common instructional target in academic settings. Past research identifying characteristics of experts' knowledge across many domains can help clarify the features of robust knowledge as well as ways of assessing it. We review the expertise literature and identify three key features of robust knowledge (deep,…

Measuring Teachers' Pedagogical Content Knowledge in Primary Technology Education

ERIC Educational Resources Information Center

Rohaan, Ellen J.; Taconis, Ruurd; Jochems, Wim M. G.

2009-01-01

Pedagogical content knowledge is found to be a crucial part of the knowledge base for teaching. Studies in the field of primary technology education showed that this domain of teacher knowledge is related to pupils' increased learning, motivation, and interest. The common methods to investigate teachers' pedagogical content knowledge are often…

Visualizing the Topical Structure of the Medical Sciences: A Self-Organizing Map Approach

PubMed Central

Skupin, André; Biberstine, Joseph R.; Börner, Katy

2013-01-01

Background We implement a high-resolution visualization of the medical knowledge domain using the self-organizing map (SOM) method, based on a corpus of over two million publications. While self-organizing maps have been used for document visualization for some time, (1) little is known about how to deal with truly large document collections in conjunction with a large number of SOM neurons, (2) post-training geometric and semiotic transformations of the SOM tend to be limited, and (3) no user studies have been conducted with domain experts to validate the utility and readability of the resulting visualizations. Our study makes key contributions to all of these issues. Methodology Documents extracted from Medline and Scopus are analyzed on the basis of indexer-assigned MeSH terms. Initial dimensionality is reduced to include only the top 10% most frequent terms and the resulting document vectors are then used to train a large SOM consisting of over 75,000 neurons. The resulting two-dimensional model of the high-dimensional input space is then transformed into a large-format map by using geographic information system (GIS) techniques and cartographic design principles. This map is then annotated and evaluated by ten experts stemming from the biomedical and other domains. Conclusions Study results demonstrate that it is possible to transform a very large document corpus into a map that is visually engaging and conceptually stimulating to subject experts from both inside and outside of the particular knowledge domain. The challenges of dealing with a truly large corpus come to the fore and require embracing parallelization and use of supercomputing resources to solve otherwise intractable computational tasks. Among the envisaged future efforts are the creation of a highly interactive interface and the elaboration of the notion of this map of medicine acting as a base map, onto which other knowledge artifacts could be overlaid. PMID:23554924

PREDOSE: a semantic web platform for drug abuse epidemiology using social media.

PubMed

Cameron, Delroy; Smith, Gary A; Daniulaityte, Raminta; Sheth, Amit P; Dave, Drashti; Chen, Lu; Anand, Gaurish; Carlson, Robert; Watkins, Kera Z; Falck, Russel

2013-12-01

The role of social media in biomedical knowledge mining, including clinical, medical and healthcare informatics, prescription drug abuse epidemiology and drug pharmacology, has become increasingly significant in recent years. Social media offers opportunities for people to share opinions and experiences freely in online communities, which may contribute information beyond the knowledge of domain professionals. This paper describes the development of a novel semantic web platform called PREDOSE (PREscription Drug abuse Online Surveillance and Epidemiology), which is designed to facilitate the epidemiologic study of prescription (and related) drug abuse practices using social media. PREDOSE uses web forum posts and domain knowledge, modeled in a manually created Drug Abuse Ontology (DAO--pronounced dow), to facilitate the extraction of semantic information from User Generated Content (UGC), through combination of lexical, pattern-based and semantics-based techniques. In a previous study, PREDOSE was used to obtain the datasets from which new knowledge in drug abuse research was derived. Here, we report on various platform enhancements, including an updated DAO, new components for relationship and triple extraction, and tools for content analysis, trend detection and emerging patterns exploration, which enhance the capabilities of the PREDOSE platform. Given these enhancements, PREDOSE is now more equipped to impact drug abuse research by alleviating traditional labor-intensive content analysis tasks. Using custom web crawlers that scrape UGC from publicly available web forums, PREDOSE first automates the collection of web-based social media content for subsequent semantic annotation. The annotation scheme is modeled in the DAO, and includes domain specific knowledge such as prescription (and related) drugs, methods of preparation, side effects, and routes of administration. The DAO is also used to help recognize three types of data, namely: (1) entities, (2) relationships and (3) triples. PREDOSE then uses a combination of lexical and semantic-based techniques to extract entities and relationships from the scraped content, and a top-down approach for triple extraction that uses patterns expressed in the DAO. In addition, PREDOSE uses publicly available lexicons to identify initial sentiment expressions in text, and then a probabilistic optimization algorithm (from related research) to extract the final sentiment expressions. Together, these techniques enable the capture of fine-grained semantic information, which facilitate search, trend analysis and overall content analysis using social media on prescription drug abuse. Moreover, extracted data are also made available to domain experts for the creation of training and test sets for use in evaluation and refinements in information extraction techniques. A recent evaluation of the information extraction techniques applied in the PREDOSE platform indicates 85% precision and 72% recall in entity identification, on a manually created gold standard dataset. In another study, PREDOSE achieved 36% precision in relationship identification and 33% precision in triple extraction, through manual evaluation by domain experts. Given the complexity of the relationship and triple extraction tasks and the abstruse nature of social media texts, we interpret these as favorable initial results. Extracted semantic information is currently in use in an online discovery support system, by prescription drug abuse researchers at the Center for Interventions, Treatment and Addictions Research (CITAR) at Wright State University. A comprehensive platform for entity, relationship, triple and sentiment extraction from such abstruse texts has never been developed for drug abuse research. PREDOSE has already demonstrated the importance of mining social media by providing data from which new findings in drug abuse research were uncovered. Given the recent platform enhancements, including the refined DAO, components for relationship and triple extraction, and tools for content, trend and emerging pattern analysis, it is expected that PREDOSE will play a significant role in advancing drug abuse epidemiology in future. Copyright © 2013 Elsevier Inc. All rights reserved.

On-site comprehensive curriculum to teach reproductive health to female adolescents in Kenya.

PubMed

Gaughran, Margaret; Asgary, Ramin

2014-04-01

Rates of sexually transmitted infections (STIs) and unplanned pregnancy are high in Kenya, and limited reproductive health education exists in schools. We designed and implemented a 6-week reproductive health curriculum in Laikipia District, Kenya, in 2011, which included didactic sessions, educational games, and open discussions. We applied a mixed quantitative and qualitative methods to evaluate this curriculum including a comprehensive 35-item survey to assess pre- and post-training knowledge, attitudes, and practices of female teenagers regarding STIs/HIV and family planning using paired t-test as well as complementary focus groups (n=42) and individual interviews (n=20). Average age for 42 female teenagers was 16.5 (± 1.31) years. Pre-test questionnaires revealed lack of knowledge about different types of STIs, specifically chlamydia, but adequate knowledge of basic contraception including abstinence and condom use. By the conclusion of the study, we observed improvement in following educational domains: general knowledge of HIV/AIDS (85% ± 7.5% to 94% ± 5.6%) (p<0.001); general knowledge of teen pregnancy and STIs (57% ± 19% to 82% ± 13%) (p<0.001); and overall scores of knowledge, attitude, and self-efficacy (81% ± 6.6% to 90% ± 5%) (p<0.001). Focus group discussions, however, revealed persistent misconceptions and knowledge gaps with themes regarding HIV transmission risk factors, perceived difficulty negotiating condom use, masturbation and its perceived consequences, and issues surrounding female circumcision. Important misconceptions and gaps in reproductive practices were identified and addressed using a mixed methods approach. Despite prior basic knowledge and positive attitudes on STI prevention and family planning, complementary teaching approaches were instrumental in improving overall knowledge of STIs other than HIV as well as family planning. The curriculum was feasible, well received, and achieved its educational goals.

[Knowledge about the relationship through protagonist-director interactions in psychodrama groups].

PubMed

Erdélyi, Ildikó

2005-01-01

This report follows emotional behavior in two psychodrama groups from the "present moment" until "moment of contact" using the Consensus Rorschach method. In the analysis of verbal and nonverbal material of protagonist-director dyads the following patterns were distinguished: a) early relationship patterns; b) affective attunement; c) fit of knowledge about the relationship. The author describes the relationship between the concept of "present moment" in therapy and the role of eye contact. Eye contact produces emotional tension in the context of the "present moment". Moments of contact, however, require implicit and explicit knowledge about the relationship to be constructed simultaneously as well as development of affective interactions. Emotional impulses are stored in implicit memory, which has no immediate availability. However, therapy--including psychodrama--attaches words to behaviors that are beyond the verbal levels as well, and therefore it extends the domain of memory. This is the way in which non-symbolized emotional behavior (including eye contact) and the play's verbal level with symbolic representations of memories are interconnected.

An ambiguity principle for assigning protein structural domains.

PubMed

Postic, Guillaume; Ghouzam, Yassine; Chebrek, Romain; Gelly, Jean-Christophe

2017-01-01

Ambiguity is the quality of being open to several interpretations. For an image, it arises when the contained elements can be delimited in two or more distinct ways, which may cause confusion. We postulate that it also applies to the analysis of protein three-dimensional structure, which consists in dividing the molecule into subunits called domains. Because different definitions of what constitutes a domain can be used to partition a given structure, the same protein may have different but equally valid domain annotations. However, knowledge and experience generally displace our ability to accept more than one way to decompose the structure of an object-in this case, a protein. This human bias in structure analysis is particularly harmful because it leads to ignoring potential avenues of research. We present an automated method capable of producing multiple alternative decompositions of protein structure (web server and source code available at www.dsimb.inserm.fr/sword/). Our innovative algorithm assigns structural domains through the hierarchical merging of protein units, which are evolutionarily preserved substructures that describe protein architecture at an intermediate level, between domain and secondary structure. To validate the use of these protein units for decomposing protein structures into domains, we set up an extensive benchmark made of expert annotations of structural domains and including state-of-the-art domain parsing algorithms. The relevance of our "multipartitioning" approach is shown through numerous examples of applications covering protein function, evolution, folding, and structure prediction. Finally, we introduce a measure for the structural ambiguity of protein molecules.

Metacognition, risk behavior, and risk outcomes: the role of perceived intelligence and perceived knowledge.

PubMed

Jaccard, James; Dodge, Tonya; Guilamo-Ramos, Vincent

2005-03-01

The present study explores 2 key variables in social metacognition: perceived intelligence and perceived levels of knowledge about a specific content domain. The former represents a judgment of one's knowledge at an abstract level, whereas the latter represents a judgment of one's knowledge in a specific content domain. Data from interviews of approximately 8,411 female adolescents from a national sample were analyzed in a 2-wave panel design with a year between assessments. Higher levels of perceived intelligence at Wave 1 were associated with a lower probability of the occurrence of a pregnancy over the ensuing year independent of actual IQ, self-esteem, and academic aspirations. Higher levels of perceived knowledge about the accurate use of birth control were associated with a higher probability of the occurrence of a pregnancy independent of actual knowledge about accurate use, perceived intelligence, self-esteem, and academic aspirations.

Identified research directions for using manufacturing knowledge earlier in the product lifecycle

PubMed Central

Hedberg, Thomas D.; Hartman, Nathan W.; Rosche, Phil; Fischer, Kevin

2016-01-01

Design for Manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within Computer-Aided Design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customization on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities, or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is how can manufacturing knowledge, depending on its definition, be used earlier in the product lifecycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behavior, and context characteristics of product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product lifecycle. PMID:27990027

Identified research directions for using manufacturing knowledge earlier in the product lifecycle.

PubMed

Hedberg, Thomas D; Hartman, Nathan W; Rosche, Phil; Fischer, Kevin

2017-01-01

Design for Manufacturing (DFM), especially the use of manufacturing knowledge to support design decisions, has received attention in the academic domain. However, industry practice has not been studied enough to provide solutions that are mature for industry. The current state of the art for DFM is often rule-based functionality within Computer-Aided Design (CAD) systems that enforce specific design requirements. That rule-based functionality may or may not dynamically affect geometry definition. And, if rule-based functionality exists in the CAD system, it is typically a customization on a case-by-case basis. Manufacturing knowledge is a phrase with vast meanings, which may include knowledge on the effects of material properties decisions, machine and process capabilities, or understanding the unintended consequences of design decisions on manufacturing. One of the DFM questions to answer is how can manufacturing knowledge, depending on its definition, be used earlier in the product lifecycle to enable a more collaborative development environment? This paper will discuss the results of a workshop on manufacturing knowledge that highlights several research questions needing more study. This paper proposes recommendations for investigating the relationship of manufacturing knowledge with shape, behavior, and context characteristics of product to produce a better understanding of what knowledge is most important. In addition, the proposal includes recommendations for investigating the system-level barriers to reusing manufacturing knowledge and how model-based manufacturing may ease the burden of knowledge sharing. Lastly, the proposal addresses the direction of future research for holistic solutions of using manufacturing knowledge earlier in the product lifecycle.

Knowledge of Curriculum Embedded Mathematics: Exploring a Critical Domain of Teaching

ERIC Educational Resources Information Center

Remillard, Janine; Kim, Ok-Kyeong

2017-01-01

This paper proposes a framework for identifying the mathematical knowledge teachers activate when using curriculum resources. We use the term "knowledge of curriculum embedded mathematics" (KCEM) to refer to the mathematics knowledge activated by teachers when reading and interpreting mathematical tasks, instructional designs, and…

Factors in Patient Empowerment: A Survey of an Online Patient Research Network.

PubMed

Chiauzzi, Emil; DasMahapatra, Pronabesh; Cochin, Elisenda; Bunce, Mikele; Khoury, Raya; Dave, Purav

2016-12-01

Providers and healthcare organizations have begun recognizing the importance of patient empowerment as a driver of patient-centered care. Unfortunately, most studies have investigated empowerment with single diseases. Identifying factors of empowerment across conditions and populations would enable a greater understanding of this construct. The purpose of this study was to understand empowerment in relation to health information-seeking, interactions with providers and peers, and healthcare access in chronic disease patients. This study also sought to identify key empowerment factors and their association with patient characteristics. Participants were recruited through PatientsLikeMe, an online research platform where patients share their personal and medical history data. Patients completed an online survey that assessed self-reported health behavior (e.g. knowledge-seeking, experiences with healthcare providers, and peer interactions) and healthcare access. An exploratory factor analysis identified key empowerment domains. Domain level sum scores and sum of all domains (total score) were compared across patient characteristics and diseases. Overall, 3988 participants were included in the study, with the majority actively involved in their healthcare, but many cited difficulties with matching their treatment goals with those of their physician (34 %) and spending sufficient time with the physician (36 %). Factor analysis identified two domains-Positive Patient-Provider Interaction, and Knowledge and Personal Control-that explained >60 % of the overall variance in the observed variables. Mean total empowerment scores for patients with a primary complaint of Parkinson's disease (61.8) and multiple sclerosis (60.3) were significantly greater than fibromyalgia (55.3) and chronic fatigue syndrome (54.8). Patients who were older, male, more educated, and insured also reported significantly greater levels of empowerment. The two domains of empowerment identified in this study are consistent with previous studies, but the differences in empowerment levels across diseases suggest a need for further studies on disease-related attributes of empowerment. Future research should examine the pathways for empowerment, as well as the relationship between empowerment domains and clinical outcomes.

Missing Modality Transfer Learning via Latent Low-Rank Constraint.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2015-11-01

Transfer learning is usually exploited to leverage previously well-learned source domain for evaluating the unknown target domain; however, it may fail if no target data are available in the training stage. This problem arises when the data are multi-modal. For example, the target domain is in one modality, while the source domain is in another. To overcome this, we first borrow an auxiliary database with complete modalities, then consider knowledge transfer across databases and across modalities within databases simultaneously in a unified framework. The contributions are threefold: 1) a latent factor is introduced to uncover the underlying structure of the missing modality from the known data; 2) transfer learning in two directions allows the data alignment between both modalities and databases, giving rise to a very promising recovery; and 3) an efficient solution with theoretical guarantees to the proposed latent low-rank transfer learning algorithm. Comprehensive experiments on multi-modal knowledge transfer with missing target modality verify that our method can successfully inherit knowledge from both auxiliary database and source modality, and therefore significantly improve the recognition performance even when test modality is inaccessible in the training stage.

Scientific Training in the Era of Big Data: A New Pedagogy for Graduate Education.

PubMed

Aikat, Jay; Carsey, Thomas M; Fecho, Karamarie; Jeffay, Kevin; Krishnamurthy, Ashok; Mucha, Peter J; Rajasekar, Arcot; Ahalt, Stanley C

2017-03-01

The era of "big data" has radically altered the way scientific research is conducted and new knowledge is discovered. Indeed, the scientific method is rapidly being complemented and even replaced in some fields by data-driven approaches to knowledge discovery. This paradigm shift is sometimes referred to as the "fourth paradigm" of data-intensive and data-enabled scientific discovery. Interdisciplinary research with a hard emphasis on translational outcomes is becoming the norm in all large-scale scientific endeavors. Yet, graduate education remains largely focused on individual achievement within a single scientific domain, with little training in team-based, interdisciplinary data-oriented approaches designed to translate scientific data into new solutions to today's critical challenges. In this article, we propose a new pedagogy for graduate education: data-centered learning for the domain-data scientist. Our approach is based on four tenets: (1) Graduate training must incorporate interdisciplinary training that couples the domain sciences with data science. (2) Graduate training must prepare students for work in data-enabled research teams. (3) Graduate training must include education in teaming and leadership skills for the data scientist. (4) Graduate training must provide experiential training through academic/industry practicums and internships. We emphasize that this approach is distinct from today's graduate training, which offers training in either data science or a domain science (e.g., biology, sociology, political science, economics, and medicine), but does not integrate the two within a single curriculum designed to prepare the next generation of domain-data scientists. We are in the process of implementing the proposed pedagogy through the development of a new graduate curriculum based on the above four tenets, and we describe herein our strategy, progress, and lessons learned. While our pedagogy was developed in the context of graduate education, the general approach of data-centered learning can and should be applied to students and professionals at any stage of their education, including at the K-12, undergraduate, graduate, and professional levels. We believe that the time is right to embed data-centered learning within our educational system and, thus, generate the talent required to fully harness the potential of big data.

Improving Employment Prospects for Soldiers Leaving the Regular Army

DTIC Science & Technology

2017-01-01

difficulties in the civilian job market . Furthermore, since 2012, the Army has been reducing its active component end strength; this has increased the number...Domains and Focus Domains (Number of Questions) Domain Focus Knowledge (33) Sets of facts and principles needed to address problems and issues that are part

How Information Visualization Systems Change Users' Understandings of Complex Data

ERIC Educational Resources Information Center

Allendoerfer, Kenneth Robert

2009-01-01

User-centered evaluations of information systems often focus on the usability of the system rather its usefulness. This study examined how a using an interactive knowledge-domain visualization (KDV) system affected users' understanding of a domain. Interactive KDVs allow users to create graphical representations of domains that depict important…

Perspectives on the Role and Synergies of Architecture and Social and Built Environment in Enabling Active Healthy Aging

PubMed Central

Rabnett, Richard; Tziraki, Chariklia

2016-01-01

Research has demonstrated that enabling societal and physical infrastructure and personal accommodations enhance healthy and active aging throughout the lifespan. Yet, there is a paucity of research on how to bring together the various disciplines involved in a multidomain synergistic collaboration to create new living environments for aging. This paper aims to explore the key domains of skills and knowledge that need to be considered for a conceptual prototype of an enabling educational process and environments where healthcare professionals, architects, planners, and entrepreneurs may establish a shared theoretical and experiential knowledge base, vocabulary, and implementation strategies, for the creation of the next generation of living communities of active healthy adults, for persons with disabilities and chronic disease conditions. We focus on synergistic, paradigmatic, simple, and practical issues that can be easily upscaled through market mechanisms. This practical and physically concrete approach may also become linked with more elaborate neuroscientific and technologically sophisticated interventions. We examine the domains of knowledge to be included in establishing a learning model that focuses on the still-understudied impact of the benefits toward active and healthy aging, where architects, urban planners, clinicians, and healthcare facility managers are educated toward a synergistic approach at the operational level. PMID:27656295

Building capacity for knowledge translation in occupational therapy: learning through participatory action research.

PubMed

Bennett, Sally; Whitehead, Mary; Eames, Sally; Fleming, Jennifer; Low, Shanling; Caldwell, Elizabeth

2016-10-01

There has been widespread acknowledgement of the need to build capacity in knowledge translation however much of the existing work focuses on building capacity amongst researchers rather than with clinicians directly. This paper's aim is to describe a research project for developing a knowledge translation capacity building program for occupational therapy clinicians. Participatory action research methods were used to both develop and evaluate the knowledge translation capacity-building program. Participants were occupational therapists from a large metropolitan hospital in Australia. Researchers and clinicians worked together to use the action cycle of the Knowledge to Action Framework to increase use of knowledge translation itself within the department in general, within their clinical teams, and to facilitate knowledge translation becoming part of the department's culture. Barriers and enablers to using knowledge translation were identified through a survey based on the Theoretical Domains Framework and through focus groups. Multiple interventions were used to develop a knowledge translation capacity-building program. Fifty-two occupational therapists participated initially, but only 20 across the first 18 months of the project. Barriers and enablers were identified across all domains of the Theoretical Domains Framework. Interventions selected to address these barriers or facilitate enablers were categorised into ten different categories: educational outreach; teams working on clinical knowledge translation case studies; identifying time blocks for knowledge translation; mentoring; leadership strategies; communication strategies; documentation and resources to support knowledge translation; funding a knowledge translation champion one day per week; setting goals for knowledge translation; and knowledge translation reporting strategies. Use of these strategies was, and continues to be monitored. Participants continue to be actively involved in learning and shaping the knowledge translation program across the department and within their specific clinical areas. To build capacity for knowledge translation, it is important to involve clinicians. The action cycle of the Knowledge to Action framework is a useful guide to introduce the knowledge translation process to clinicians. It may be used to engage the department as a whole, and facilitate the learning and application of knowledge translation within specific clinical areas. Research evaluating this knowledge translation program is being conducted.

European Scientific Notes. Volume 38, Number 4.

DTIC Science & Technology

1984-04-01

R.L. Carovillano 218 The Seventh European Regional Astronomy meeting dealt with almost every area of astronomy; coverage included solar ...in the 25- to found in areas as diverse as electro- 35-m range at the Comitato Nazionale optics and pharmacology. Energia Nucleare laboratory in...physics research has led to knowledge gained in one area (or param- many discoveries in the solar system and eter domain) to another area that lacks to

Validating Domains of Patient Contextual Factors Essential to Preventing Contextual Errors: A Qualitative Study Conducted at Chicago Area Veterans Health Administration Sites.

PubMed

Binns-Calvey, Amy E; Malhiot, Alex; Kostovich, Carol T; LaVela, Sherri L; Stroupe, Kevin; Gerber, Ben S; Burkhart, Lisa; Weiner, Saul J; Weaver, Frances M

2017-09-01

"Patient context" indicates patient circumstances and characteristics or states that are essential to address when planning patient care. Specific patient "contextual factors," if overlooked, result in an inappropriate plan of care, a medical error termed a "contextual error." The myriad contextual factors that constitute patient context have been grouped into broad domains to create a taxonomy of challenges to consider when planning care. This study sought to validate a previously identified list of contextual domains. This qualitative study used directed content analysis. In 2014, 19 Department of Veterans Affairs (VA) providers (84% female) and 49 patients (86% male) from two VA medical centers and four outpatient clinics in the Chicago area participated in semistructured interviews and focus groups. Topics included patient-specific, community, and resource-related factors that affect patients' abilities to manage their care. Transcripts were analyzed with a previously identified list of contextual domains as a framework. Analysis of responses revealed that patients and providers identified the same 10 domains previously published, plus 3 additional ones. Based on comments made by patients and providers, the authors created a revised list of 12 domains from themes that emerged. Six pertain to patient circumstances such as access to care and financial situation, and 6 to patient characteristics/states including skills, abilities, and knowledge. Contextual factors in patients' lives may be essential to address for effective care planning. The rubric developed can serve as a "contextual differential" for clinicians to consider when addressing challenges patients face when planning their care.

Factors that influence effective perioperative temperature management by anesthesiologists: a qualitative study using the Theoretical Domains Framework.

PubMed

Boet, Sylvain; Patey, Andrea M; Baron, Justine S; Mohamed, Karim; Pigford, Ashlee-Ann E; Bryson, Gregory L; Brehaut, Jamie C; Grimshaw, Jeremy M

2017-06-01

Inadvertent perioperative hypothermia (IPH) is associated with a range of adverse outcomes. Safe and effective warming techniques exist to prevent IPH; however, IPH remains common. This study aimed to identify factors that anesthesiologists perceive may influence temperature management during the perioperative period. After Research Ethics Board approval, semi-structured interviews were conducted with staff anesthesiologists at a Canadian academic hospital. An interview guide based on the Theoretical Domains Framework (TDF) was used to capture 14 theoretical domains that may influence temperature management. The interview transcripts were coded using direct content analysis to generate specific beliefs and to identify relevant TDF domains perceived to influence temperature management behaviour. Data saturation was achieved after 15 interviews. The following nine theoretical domains were identified as relevant to designing an intervention for practices in perioperative temperature management: knowledge, beliefs about capabilities, beliefs about consequences, reinforcement, memory/attention/decision-making, environmental context and resources, social/professional role/identity, social influences, and behavioural regulation. Potential target areas to improve temperature management practices include interventions that address information needs about individual temperature management behaviour as well as patient outcome (feedback), increasing awareness of possible temperature management strategies and guidelines, and a range of equipment and surgical team dynamics that influence temperature management. This study identified several potential target areas for future interventions from nine of the TDF behavioural domains that anesthesiologists perceive to drive their temperature management practices. Future interventions that aim to close the evidence-practice gap in perioperative temperature management may include these targets.

Defining Tobacco Regulatory Science Competencies.

PubMed

Wipfli, Heather L; Berman, Micah; Hanson, Kacey; Kelder, Steven; Solis, Amy; Villanti, Andrea C; Ribeiro, Carla M P; Meissner, Helen I; Anderson, Roger

2017-02-01

In 2013, the National Institutes of Health and the Food and Drug Administration funded a network of 14 Tobacco Centers of Regulatory Science (TCORS) with a mission that included research and training. A cross-TCORS Panel was established to define tobacco regulatory science (TRS) competencies to help harmonize and guide their emerging educational programs. The purpose of this paper is to describe the Panel's work to develop core TRS domains and competencies. The Panel developed the list of domains and competencies using a semistructured Delphi method divided into four phases occurring between November 2013 and August 2015. The final proposed list included a total of 51 competencies across six core domains and 28 competencies across five specialized domains. There is a need for continued discussion to establish the utility of the proposed set of competencies for emerging TRS curricula and to identify the best strategies for incorporating these competencies into TRS training programs. Given the field's broad multidisciplinary nature, further experience is needed to refine the core domains that should be covered in TRS training programs versus knowledge obtained in more specialized programs. Regulatory science to inform the regulation of tobacco products is an emerging field. The paper provides an initial list of core and specialized domains and competencies to be used in developing curricula for new and emerging training programs aimed at preparing a new cohort of scientists to conduct critical TRS research. © The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

Time Domain Simulations of Arm Locking in LISA

NASA Technical Reports Server (NTRS)

Thorpe, J. I.; Maghami, P.; Livas, Jeff

2011-01-01

Arm locking is a technique that has been proposed for reducing laser frequency fluctuations in the Laser Interferometer Space Antenna (LISA). a gravitational-wave observatory sensitive' in the milliHertz frequency band. Arm locking takes advantage of the geometric stability of the triangular constellation of three spacecraft that comprise LISA to provide a frequency reference with a stability in the LISA measurement band that exceeds that available from a standard reference such as an optical cavity or molecular absorption line. We have implemented a time-domain simulation of arm locking including the expected limiting noise sources (shot noise, clock noise. spacecraft jitter noise. and residual laser frequency noise). The effect of imperfect a priori knowledge of the LISA heterodyne frequencies and associated "pulling" of an arm locked laser is included. We find that our implementation meets requirements both on the noise and dynamic range of the laser frequency.

A Modern Understanding of the Traditional and Nontraditional Biological Functions of Angiotensin-Converting Enzyme

PubMed Central

Ong, Frank S.; Blackwell, Wendell-Lamar B.; Shah, Kandarp H.; Giani, Jorge F.; Gonzalez-Villalobos, Romer A.; Shen, Xiao Z.; Fuchs, Sebastien

2013-01-01

Angiotensin-converting enzyme (ACE) is a zinc-dependent peptidase responsible for converting angiotensin I into the vasoconstrictor angiotensin II. However, ACE is a relatively nonspecific peptidase that is capable of cleaving a wide range of substrates. Because of this, ACE and its peptide substrates and products affect many physiologic processes, including blood pressure control, hematopoiesis, reproduction, renal development, renal function, and the immune response. The defining feature of ACE is that it is composed of two homologous and independently catalytic domains, the result of an ancient gene duplication, and ACE-like genes are widely distributed in nature. The two ACE catalytic domains contribute to the wide substrate diversity of ACE and, by extension, the physiologic impact of the enzyme. Several studies suggest that the two catalytic domains have different biologic functions. Recently, the X-ray crystal structure of ACE has elucidated some of the structural differences between the two ACE domains. This is important now that ACE domain-specific inhibitors have been synthesized and characterized. Once widely available, these reagents will undoubtedly be powerful tools for probing the physiologic actions of each ACE domain. In turn, this knowledge should allow clinicians to envision new therapies for diseases not currently treated with ACE inhibitors. PMID:23257181

Knowledge Innovation System: The Common Language.

ERIC Educational Resources Information Center

Rogers, Debra M. Amidon

1993-01-01

The Knowledge Innovation System is a management technique in which a networked enterprise uses knowledge flow as a collaborative advantage. Enterprise Management System-Architecture, which can be applied to collaborative activities, has five domains: economic, sociological, psychological, managerial, and technological. (SK)

Interactions of the Auxilin-1 PTEN-like Domain with Model Membranes Result in Nanoclustering of Phosphatidyl Inositol Phosphates

PubMed Central

Kalli, Antreas C.; Morgan, Gareth; Sansom, Mark S.P.

2013-01-01

Auxilin-1 is a neuron-specific membrane-binding protein involved in a late stage of clathrin-mediated endocytosis. It recruits Hsc70, thus initiating uncoating of the clathrin-coated vesicles. Interactions of auxilin-1 with the vesicle membrane are crucial for this function and are mediated via an N-terminal PTEN-like domain. We have used multiscale molecular dynamics simulations to probe the interactions of the auxilin-1 PTEN-like domain with lipid bilayers containing differing phospholipid composition, including bilayers containing phosphatidyl inositol phosphates. Our results suggest a novel, to our knowledge, model for the auxilin/membrane encounter and subsequent interactions. Negatively charged lipids (especially PIP2) enhance binding of auxilin to lipid bilayers and facilitate its correct orientation relative to the membrane. Mutations in three basic residues (R301E/R307E/K311E) of the C2 subdomain of the PTEN-like domain perturbed its interaction with the bilayer, changing its orientation. The interaction of membrane-bound auxilin-1 PTEN-like domain with negatively charged lipid headgroups results in nanoclustering of PIP2 molecules in the adjacent bilayer leaflet. PMID:23823232

Description of research interests and current work related to automating software design

NASA Technical Reports Server (NTRS)

Kaindl, Hermann

1992-01-01

Enclosed is a list of selected and recent publications. Most of these publications concern applied research in the areas of software engineering and human-computer interaction. It is felt that domain-specific knowledge plays a major role in software development. Additionally, it is believed that improvements in the general software development process (e.g., object-oriented approaches) will have to be combined with the use of large domain-specific knowledge bases.

The public understanding of nanotechnology in the food domain: the hidden role of views on science, technology, and nature.

PubMed

Vandermoere, Frederic; Blanchemanche, Sandrine; Bieberstein, Andrea; Marette, Stephan; Roosen, Jutta

2011-03-01

In spite of great expectations about the potential of nanotechnology, this study shows that people are rather ambiguous and pessimistic about nanotechnology applications in the food domain. Our findings are drawn from a survey of public perceptions about nanotechnology food and nanotechnology food packaging (N = 752). Multinomial logistic regression analyses further reveal that knowledge about food risks and nanotechnology significantly influences people's views about nanotechnology food packaging. However, knowledge variables were unrelated to support for nanofood, suggesting that an increase in people's knowledge might not be sufficient to bridge the gap between the excitement some business leaders in the food sector have and the restraint of the public. Additionally, opposition to nanofood was not related to the use of heuristics but to trust in governmental agencies. Furthermore, the results indicate that public perceptions of nanoscience in the food domain significantly relate to views on science, technology, and nature.

Science beyond fiction. A revolution of knowledge transfer in research, education, and practice is on the horizon.

PubMed

Ammann, Alexander

2016-01-01

"Digitality" (as opposed to "digitalization"--the conversion from the analog domain to the digital domain) will open up a whole new world that does not originate from the analog world. Contemporary research in the field of neural concepts and neuromorphic computing systems will lead to convergences between the world of digitality and the world of neuronality, giving the theme "Knowledge and Culture" a new meaning. The simulation of virtual multidimensional and contextual spaces will transform the transfer of knowledge from a uni- and bidirectional process into an interactive experience. We will learn to learn in a ubiquitous computing environment and will abandon conventional curriculum organization principles. The adaptation of individualized ontologies will result in the emergence of a new world of knowledge in which knowledge evolves from a cultural heritage into a commodity.

What Knowledge Is of Most Worth: Teacher Knowledge for 21st Century Learning

ERIC Educational Resources Information Center

Kereluik, Kristen; Mishra, Punya; Fahnoe, Chris; Terry, Laura

2013-01-01

This article offers a critical review of the literature on 21st century knowledge frameworks, with a particular focus on what this means for teachers and teacher educators. The authors accomplish this by identifying common themes and knowledge domains in 15 reports, books, and articles that describe the kinds of knowledge that researchers state…

Designing Tasks to Examine Mathematical Knowledge for Teaching Statistics for Primary Teachers

NASA Astrophysics Data System (ADS)

Siswono, T. Y. E.; Kohar, A. W.; Hartono, S.

2018-01-01

Mathematical knowledge for teaching (MKT) is viewed as fuel resources for conducting an orchestra in a teaching and learning process. By understanding MKT, especially for primary teachers, it can predict the success of a goal of an instruction and analyze the weaknesses and improvements of it. To explore what teachers think about subject matters, pedagogical terms, and appropriate curriculum, it needs a task which can be identified the teachers’ MKT including the subject matter knowledge (SMK) and pedagogical content knowledge (PCK). This study aims to design an appropriate task for exploring primary teachers’ MKT for statistics in primary school. We designed six tasks to examine 40 primary teachers’ MKT, of which each respectively represents the categories of SMK (common content knowledge (CCK) and specialised content knowledge (SCK)) and PCK (knowledge of content and students (KCS), knowledge of content and teaching (KCT), and knowledge of content and curriculum (KCC)). While MKT has much attention of numbers of scholars, we consider knowledge of content and culture (KCCl) to be hypothesized in the domains of MKT. Thus, we added one more task examining how the primary teachers used their knowledge of content (KC) regarding to MKT in statistics. Some examples of the teachers’ responses on the tasks are discussed and some refinements of MKT task in statistics for primary teachers are suggested.

Phosphotyrosine recognition domains: the typical, the atypical and the versatile

PubMed Central

2012-01-01

SH2 domains are long known prominent players in the field of phosphotyrosine recognition within signaling protein networks. However, over the years they have been joined by an increasing number of other protein domain families that can, at least with some of their members, also recognise pTyr residues in a sequence-specific context. This superfamily of pTyr recognition modules, which includes substantial fractions of the PTB domains, as well as much smaller, or even single member fractions like the HYB domain, the PKCδ and PKCθ C2 domains and RKIP, represents a fascinating, medically relevant and hence intensely studied part of the cellular signaling architecture of metazoans. Protein tyrosine phosphorylation clearly serves a plethora of functions and pTyr recognition domains are used in a similarly wide range of interaction modes, which encompass, for example, partner protein switching, tandem recognition functionalities and the interaction with catalytically active protein domains. If looked upon closely enough, virtually no pTyr recognition and regulation event is an exact mirror image of another one in the same cell. Thus, the more we learn about the biology and ultrastructural details of pTyr recognition domains, the more does it become apparent that nature cleverly combines and varies a few basic principles to generate a sheer endless number of sophisticated and highly effective recognition/regulation events that are, under normal conditions, elegantly orchestrated in time and space. This knowledge is also valuable when exploring pTyr reader domains as diagnostic tools, drug targets or therapeutic reagents to combat human diseases. PMID:23134684

Is Domain Highlighting Actually Helpful in Identifying Phishing Web Pages?

PubMed

Xiong, Aiping; Proctor, Robert W; Yang, Weining; Li, Ninghui

2017-06-01

To evaluate the effectiveness of domain highlighting in helping users identify whether Web pages are legitimate or spurious. As a component of the URL, a domain name can be overlooked. Consequently, browsers highlight the domain name to help users identify which Web site they are visiting. Nevertheless, few studies have assessed the effectiveness of domain highlighting, and the only formal study confounded highlighting with instructions to look at the address bar. We conducted two phishing detection experiments. Experiment 1 was run online: Participants judged the legitimacy of Web pages in two phases. In Phase 1, participants were to judge the legitimacy based on any information on the Web page, whereas in Phase 2, they were to focus on the address bar. Whether the domain was highlighted was also varied. Experiment 2 was conducted similarly but with participants in a laboratory setting, which allowed tracking of fixations. Participants differentiated the legitimate and fraudulent Web pages better than chance. There was some benefit of attending to the address bar, but domain highlighting did not provide effective protection against phishing attacks. Analysis of eye-gaze fixation measures was in agreement with the task performance, but heat-map results revealed that participants' visual attention was attracted by the highlighted domains. Failure to detect many fraudulent Web pages even when the domain was highlighted implies that users lacked knowledge of Web page security cues or how to use those cues. Potential applications include development of phishing prevention training incorporating domain highlighting with other methods to help users identify phishing Web pages.

Knowledge discovery from data as a framework to decision support in medical domains

PubMed Central

Gibert, Karina

2009-01-01

Introduction Knowledge discovery from data (KDD) is a multidisciplinary discipline which appeared in 1996 for “non trivial identifying of valid, novel, potentially useful, ultimately understandable patterns in data”. Pre-treatment of data and post-processing is as important as the data exploitation (Data Mining) itself. Different analysis techniques can be properly combined to produce explicit knowledge from data. Methods Hybrid KDD methodologies combining Artificial Intelligence with Statistics and visualization have been used to identify patterns in complex medical phenomena: experts provide prior knowledge (pK); it biases the search of distinguishable groups of homogeneous objects; support-interpretation tools (CPG) assisted experts in conceptualization and labelling of discovered patterns, consistently with pK. Results Patterns of dependency in mental disabilities supported decision-making on legislation of the Spanish Dependency Law in Catalonia. Relationships between type of neurorehabilitation treatment and patterns of response for brain damage are assessed. Patterns of the perceived QOL along time are used in spinal cord lesion to improve social inclusion. Conclusion Reality is more and more complex and classical data analyses are not powerful enough to model it. New methodologies are required including multidisciplinarity and stressing on production of understandable models. Interaction with the experts is critical to generate meaningful results which can really support decision-making, particularly convenient transferring the pK to the system, as well as interpreting results in close interaction with experts. KDD is a valuable paradigm, particularly when facing very complex domains, not well understood yet, like many medical phenomena.

Clinical Research Informatics: Challenges, Opportunities and Definition for an Emerging Domain

PubMed Central

Embi, Peter J.; Payne, Philip R.O.

2009-01-01

Objectives Clinical Research Informatics, an emerging sub-domain of Biomedical Informatics, is currently not well defined. A formal description of CRI including major challenges and opportunities is needed to direct progress in the field. Design Given the early stage of CRI knowledge and activity, we engaged in a series of qualitative studies with key stakeholders and opinion leaders to determine the range of challenges and opportunities facing CRI. These phases employed complimentary methods to triangulate upon our findings. Measurements Study phases included: 1) a group interview with key stakeholders, 2) an email follow-up survey with a larger group of self-identified CRI professionals, and 3) validation of our results via electronic peer-debriefing and member-checking with a group of CRI-related opinion leaders. Data were collected, transcribed, and organized for formal, independent content analyses by experienced qualitative investigators, followed by an iterative process to identify emergent categorizations and thematic descriptions of the data. Results We identified a range of challenges and opportunities facing the CRI domain. These included 13 distinct themes spanning academic, practical, and organizational aspects of CRI. These findings also informed the development of a formal definition of CRI and supported further representations that illustrate areas of emphasis critical to advancing the domain. Conclusions CRI has emerged as a distinct discipline that faces multiple challenges and opportunities. The findings presented summarize those challenges and opportunities and provide a framework that should help inform next steps to advance this important new discipline. PMID:19261934

Lessons from the business sector for successful knowledge management in health care: a systematic review.

PubMed

Kothari, Anita; Hovanec, Nina; Hastie, Robyn; Sibbald, Shannon

2011-07-25

The concept of knowledge management has been prevalent in the business sector for decades. Only recently has knowledge management been receiving attention by the health care sector, in part due to the ever growing amount of information that health care practitioners must handle. It has become essential to develop a way to manage the information coming in to and going out of a health care organization. The purpose of this paper was to summarize previous studies from the business literature that explored specific knowledge management tools, with the aim of extracting lessons that could be applied in the health domain. We searched seven databases using keywords such as "knowledge management", "organizational knowledge", and "business performance". We included articles published between 2000-2009; we excluded non-English articles. 83 articles were reviewed and data were extracted to: (1) uncover reasons for initiating knowledge management strategies, (2) identify potential knowledge management strategies/solutions, and (3) describe facilitators and barriers to knowledge management. KM strategies include such things as training sessions, communication technologies, process mapping and communities of practice. Common facilitators and barriers to implementing these strategies are discussed in the business literature, but rigorous studies about the effectiveness of such initiatives are lacking. The health care sector is at a pinnacle place, with incredible opportunities to design, implement (and evaluate) knowledge management systems. While more research needs to be done on how best to do this in healthcare, the lessons learned from the business sector can provide a foundation on which to build.

Lessons from the business sector for successful knowledge management in health care: A systematic review

PubMed Central

2011-01-01

Background The concept of knowledge management has been prevalent in the business sector for decades. Only recently has knowledge management been receiving attention by the health care sector, in part due to the ever growing amount of information that health care practitioners must handle. It has become essential to develop a way to manage the information coming in to and going out of a health care organization. The purpose of this paper was to summarize previous studies from the business literature that explored specific knowledge management tools, with the aim of extracting lessons that could be applied in the health domain. Methods We searched seven databases using keywords such as "knowledge management", "organizational knowledge", and "business performance". We included articles published between 2000-2009; we excluded non-English articles. Results 83 articles were reviewed and data were extracted to: (1) uncover reasons for initiating knowledge management strategies, (2) identify potential knowledge management strategies/solutions, and (3) describe facilitators and barriers to knowledge management. Conclusions KM strategies include such things as training sessions, communication technologies, process mapping and communities of practice. Common facilitators and barriers to implementing these strategies are discussed in the business literature, but rigorous studies about the effectiveness of such initiatives are lacking. The health care sector is at a pinnacle place, with incredible opportunities to design, implement (and evaluate) knowledge management systems. While more research needs to be done on how best to do this in healthcare, the lessons learned from the business sector can provide a foundation on which to build. PMID:21787403

Experts bodies, experts minds: How physical and mental training shape the brain

PubMed Central

Debarnot, Ursula; Sperduti, Marco; Di Rienzo, Franck; Guillot, Aymeric

2014-01-01

Skill learning is the improvement in perceptual, cognitive, or motor performance following practice. Expert performance levels can be achieved with well-organized knowledge, using sophisticated and specific mental representations and cognitive processing, applying automatic sequences quickly and efficiently, being able to deal with large amounts of information, and many other challenging task demands and situations that otherwise paralyze the performance of novices. The neural reorganizations that occur with expertise reflect the optimization of the neurocognitive resources to deal with the complex computational load needed to achieve peak performance. As such, capitalizing on neuronal plasticity, brain modifications take place over time-practice and during the consolidation process. One major challenge is to investigate the neural substrates and cognitive mechanisms engaged in expertise, and to define “expertise” from its neural and cognitive underpinnings. Recent insights showed that many brain structures are recruited during task performance, but only activity in regions related to domain-specific knowledge distinguishes experts from novices. The present review focuses on three expertise domains placed across a motor to mental gradient of skill learning: sequential motor skill, mental simulation of the movement (motor imagery), and meditation as a paradigmatic example of “pure” mental training. We first describe results on each specific domain from the initial skill acquisition to expert performance, including recent results on the corresponding underlying neural mechanisms. We then discuss differences and similarities between these domains with the aim to identify the highlights of the neurocognitive processes underpinning expertise, and conclude with suggestions for future research. PMID:24847236

The Future Cybersecurity Workforce: Going Beyond Technical Skills for Successful Cyber Performance.

PubMed

Dawson, Jessica; Thomson, Robert

2018-01-01

One of the challenges in writing an article reviewing the current state of cyber education and workforce development is that there is a paucity of quantitative assessment regarding the cognitive aptitudes, work roles, or team organization required by cybersecurity professionals to be successful. In this review, we argue that the people who operate within the cyber domain need a combination of technical skills, domain specific knowledge, and social intelligence to be successful. They, like the networks they operate, must also be reliable, trustworthy, and resilient. Defining the knowledge, skills, attributes, and other characteristics is not as simple as defining a group of technical skills that people can be trained on; the complexity of the cyber domain makes this a unique challenge. There has been little research devoted to exactly what attributes individuals in the cyber domain need. What research does exist places an emphasis on technical and engineering skills while discounting the important social and organizational influences that dictate success or failure in everyday settings. This paper reviews the literature on cyber expertise and cyber workforce development to identify gaps and then argues for the important contribution of social fit in the highly complex and heterogenous cyber workforce. We then identify six assumptions for the future of cybersecurity workforce development, including the requirement for systemic thinkers, team players, a love for continued learning, strong communication ability, a sense of civic duty, and a blend of technical and social skill. Finally, we make recommendations for social and cognitive metrics which may be indicative of future performance in cyber work roles to provide a roadmap for future scholars.

A new framing approach in guideline development to manage different sources of knowledge.

PubMed

Lukersmith, Sue; Hopman, Katherine; Vine, Kristina; Krahe, Lee; McColl, Alexander

2017-02-01

Contemporary guideline methodology struggles to consider context and information from different sources of knowledge besides quantitative research. Return to work programmes involve multiple components and stakeholders. If the guideline is to be relevant and practical for a complex intervention such as return to work, it is essential to use broad sources of knowledge. This paper reports on a new method in guideline development to manage different sources of knowledge. The method used framing for the return-to-work guidance within the Clinical Practice Guidelines for the Management of Rotator Cuff Syndrome in the Workplace. The development involved was a multi-disciplinary working party of experts including consumers. The researchers considered a broad range of research, expert (practice and experience) knowledge, the individual's and workplace contexts, and used framing with the International Classification of Functioning, Disability and Health. Following a systematic database search on four clinical questions, there were seven stages of knowledge management to extract, unpack, map and pack information to the ICF domains framework. Companion graded recommendations were developed. The results include practical examples, user and consumer guides, flow charts and six graded or consensus recommendations on best practice for return to work intervention. Our findings suggest using framing in guideline methodology with internationally accepted frames such as the ICF is a reliable and transparent framework to manage different sources of knowledge. Future research might examine other examples and methods for managing complexity and using different sources of knowledge in guideline development. © 2016 John Wiley & Sons, Ltd.

Deficits in Domains of Social Cognition in Schizophrenia: A Meta-Analysis of the Empirical Evidence

PubMed Central

Savla, Gauri N.

2013-01-01

Objective: Social cognition is strongly associated with functional outcome in schizophrenia, making it an important target for treatment. Our goal was to examine the average magnitude of differences between schizophrenia patients (SCs) and normal comparison (NCs) patients across multiple domains of social cognition recognized by the recent NIMH consensus statement: theory of mind (ToM), social perception, social knowledge, attributional bias, emotion perception, and emotion processing. Method: We conducted a meta-analysis of peer-reviewed studies of social cognition in schizophrenia, published between 1980 and November, 2011. Results: 112 studies reporting results from 3908 SCs and 3570 NCs met our inclusion criteria. SCs performed worse than NCs across all domains, with large effects for social perception (g = 1.04), ToM (g = 0.96), emotion perception (g = 0.89), and emotion processing (g = 0.88). Regression analyses showed that statistically significant heterogeneity in effects within domains was not explained by age, education, or gender. Greater deficits in social and emotion perception were associated with inpatient status, and greater deficits in emotion processing were associated with longer illness duration. Conclusions: Despite the limitations of existing studies, including lack of standardization or psychometric validation of measures, the evidence for deficits across multiple social cognitive domains in schizophrenia is clear. Future research should examine the role of neurobiological and psychosocial factors in models linking various aspects of deficit in schizophrenia, including social cognition, in order to identify targets for intervention. PMID:22949733

Realtime Knowledge Management (RKM): From an International Space Station (ISS) Point of View

NASA Technical Reports Server (NTRS)

Robinson, Peter I.; McDermott, William; Alena, Richard L.

2004-01-01

We are developing automated methods to provide realtime access to spacecraft domain knowledge relevant a spacecraft's current operational state. The method is based upon analyzing state-transition signatures in the telemetry stream. A key insight is that documentation relevant to a specific failure mode or operational state is related to the structure and function of spacecraft systems. This means that diagnostic dependency and state models can provide a roadmap for effective documentation navigation and presentation. Diagnostic models consume the telemetry and derive a high-level state description of the spacecraft. Each potential spacecraft state description is matched against the predictions of models that were developed from information found in the pages and sections in the relevant International Space Station (ISS) documentation and reference materials. By annotating each model fragment with the domain knowledge sources from which it was derived we can develop a system that automatically selects those documents representing the domain knowledge encapsulated by the models that compute the current spacecraft state. In this manner, when the spacecraft state changes, the relevant documentation context and presentation will also change.

The effects of activating prior topic and metacognitive knowledge on text comprehension scores.

PubMed

Kostons, Danny; van der Werf, Greetje

2015-09-01

Research on prior knowledge activation has consistently shown that activating learners' prior knowledge has beneficial effects on learning. If learners activate their prior knowledge, this activated knowledge serves as a framework for establishing relationships between the knowledge they already possess and new information provided to them. Thus far, prior knowledge activation has dealt primarily with topic knowledge in specific domains. Students, however, likely also possess at least some metacognitive knowledge useful in those domains, which, when activated, should aid in the deployment of helpful strategies during reading. In this study, we investigated the effects of both prior topic knowledge activation (PTKA) and prior metacognitive knowledge activation (PMKA) on text comprehension scores. Eighty-eight students in primary education were randomly distributed amongst the conditions of the 2 × 2 (PTKA yes/no × PMKA yes/no) designed experiment. Results show that activating prior metacognitive knowledge had a beneficial effect on text comprehension, whereas activating prior topic knowledge, after correcting for the amount of prior knowledge, did not. Most studies deal with explicit instruction of metacognitive knowledge, but our results show that this may not be necessary, specifically in the case of students who already have some metacognitive knowledge. However, existing metacognitive knowledge needs to be activated in order for students to make better use of this knowledge. © 2015 The British Psychological Society.

The Knowledge Base of the Evaluation Domain.

ERIC Educational Resources Information Center

Seels, Barbara

This paper is concerned with defining evaluation as a domain in instructional technology, and with specifying the sub-areas of the domain. In education, evaluation is the process of determining the adequacy of instruction. It begins with problem analysis, which refers to determining the nature of the solution and the parameters of the problem. A…

Mining e-Learning Domain Concept Map from Academic Articles

ERIC Educational Resources Information Center

Chen, Nian-Shing; Kinshuk; Wei, Chun-Wang; Chen, Hong-Jhe

2008-01-01

Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials, designers need to refer to the concept map of a subject domain. Moreover, concept maps can show the whole picture and core knowledge about a subject domain. Research…

Creativity Doesn't Develop in a Vacuum

ERIC Educational Resources Information Center

Barbot, Baptiste; Baer, John

2016-01-01

The skills, knowledge, attitudes, motivations, and personality traits that lead to creative thinking and creative behavior do not exist--and do not develop--in a vacuum. They are inextricably tied to content, to domains, in particular, and they therefore vary by domains. The more we learn about creativity, the more we discover how domain specific…

A Mixed-Response Intelligent Tutoring System Based on Learning from Demonstration

ERIC Educational Resources Information Center

Alvarez Xochihua, Omar

2012-01-01

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in…

A Framework and a Methodology for Developing Authentic Constructivist e-Learning Environments

ERIC Educational Resources Information Center

Zualkernan, Imran A.

2006-01-01

Semantically rich domains require operative knowledge to solve complex problems in real-world settings. These domains provide an ideal environment for developing authentic constructivist e-learning environments. In this paper we present a framework and a methodology for developing authentic learning environments for such domains. The framework is…

Using the Affective Domain to Enhance Teaching of the ACGME Competencies in Anesthesiology Training.

PubMed

Yanofsky, Samuel D; Nyquist, Julie G

2010-01-01

Teaching and assessing the advanced competencies will continue to be a challenge. Incorporating new and nontraditional skills into an already complex and challenging clinical curriculum and practice is not easy. This makes development of methods for curricular design, teaching and assessment of anesthesiology resident and fellow performance essential. The Domains of learning, particularly the Affective Domain can serve as an organizing structure for developing objectives and selecting teaching and assessment techniques. Using the Affective Domain to select targeted teaching techniques might help foster development of key beliefs and values that underlie the advanced competencies (and sub-competencies). Targeted teaching, outside of the patient care arena, when combined with traditional clinical teaching practices, may help to ensure continued performance of desired behaviors. These include acting in a consultative role for other health professionals (ICS), providing culturally responsive care (Professionalism), using evidence to enhance the care of patients (PBLI), and advocating for quality of care and working to enhance patient safety (SBP). As educators, our aim is not only to impact knowledge, attitudes and skills, but to impact the daily behavior of our graduates.

Using the Affective Domain to Enhance Teaching of the ACGME Competencies in Anesthesiology Training

PubMed Central

2010-01-01

Teaching and assessing the advanced competencies will continue to be a challenge. Incorporating new and nontraditional skills into an already complex and challenging clinical curriculum and practice is not easy. This makes development of methods for curricular design, teaching and assessment of anesthesiology resident and fellow performance essential. The Domains of learning, particularly the Affective Domain can serve as an organizing structure for developing objectives and selecting teaching and assessment techniques. Using the Affective Domain to select targeted teaching techniques might help foster development of key beliefs and values that underlie the advanced competencies (and sub-competencies). Targeted teaching, outside of the patient care arena, when combined with traditional clinical teaching practices, may help to ensure continued performance of desired behaviors. These include acting in a consultative role for other health professionals (ICS), providing culturally responsive care (Professionalism), using evidence to enhance the care of patients (PBLI), and advocating for quality of care and working to enhance patient safety (SBP). As educators, our aim is not only to impact knowledge, attitudes and skills, but to impact the daily behavior of our graduates. PMID:27175387

Experimentation in machine discovery

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Simon, Herbert A.

1990-01-01

KEKADA, a system that is capable of carrying out a complex series of experiments on problems from the history of science, is described. The system incorporates a set of experimentation strategies that were extracted from the traces of the scientists' behavior. It focuses on surprises to constrain its search, and uses its strategies to generate hypotheses and to carry out experiments. Some strategies are domain independent, whereas others incorporate knowledge of a specific domain. The domain independent strategies include magnification, determining scope, divide and conquer, factor analysis, and relating different anomalous phenomena. KEKADA represents an experiment as a set of independent and dependent entities, with apparatus variables and a goal. It represents a theory either as a sequence of processes or as abstract hypotheses. KEKADA's response is described to a particular problem in biochemistry. On this and other problems, the system is capable of carrying out a complex series of experiments to refine domain theories. Analysis of the system and its behavior on a number of different problems has established its generality, but it has also revealed the reasons why the system would not be a good experimental scientist.

Gene transfer strategies in animal transgenesis.

PubMed

Montoliu, Lluís

2002-01-01

Position effects in animal transgenesis have prevented the reproducible success and limited the initial expectations of this technique in many biotechnological projects. Historically, several strategies have been devised to overcome such position effects, including the progressive addition of regulatory elements belonging to the same or to a heterologous expression domain. An expression domain is thought to contain all regulatory elements that are needed to specifically control the expression of a given gene in time and space. The lack of profound knowledge on the chromatin structure of expression domains of biotechnological interest, such as mammary gland-specific genes, explains why most standard expression vectors have failed to drive high-level, position-independent, and copy-number-dependent expression of transgenes in a reproducible manner. In contrast, the application of artificial chromosome-type constructs to animal transgenesis usually ensures optimal expression levels. YACs, BACs, and PACs have become crucial tools in animal transgenesis, allowing the inclusion of distant key regulatory sequences, previously unknown, that are characteristic for each expression domain. These elements contribute to insulating the artificial chromosome-type constructs from chromosomal position effects and are fundamental in order to guarantee the correct expression of transgenes.

Recent Development of Anticancer Therapeutics Targeting Akt

PubMed Central

Morrow, John K.; Du-Cuny, Lei; Chen, Lu; Meuillet, Emmanuelle J.; Mash, Eugene A.; Powis, Garth; Zhang, Shuxing

2013-01-01

The serine/threonine kinase Akt has proven to be a significant signaling target, involved in various biological functions. Because of its cardinal role in numerous cellular responses, Akt has been implicated in many human diseases, particularly cancer. It has been established that Akt is a viable and feasible target for anticancer therapeutics. Analysis of all Akt kinases reveals conserved homology for an N-terminal regulatory domain, which contains a pleckstrin-homology (PH) domain for cellular translocation, a kinase domain with serine/threonine specificity, and a C-terminal extension domain. These well defined regions have been targeted, and various approaches, including in silico methods, have been implemented to develop Akt inhibitors. In spite of unique techniques and a prolific body of knowledge surrounding Akt, no targeted Akt therapeutics have reached the market yet. Here we will highlight successes and challenges to date on the development of anticancer agents modulating the Akt pathway in recent patents as well as discuss the methods employed for this task. Special attention will be given to patents with focus on those discoveries using computer-aided drug design approaches. PMID:21110830

Validation of the instrument of health literacy competencies for Chinese-speaking health professionals.

PubMed

Chang, Li-Chun; Chen, Yu-Chi; Liao, Li-Ling; Wu, Fei Ling; Hsieh, Pei-Lin; Chen, Hsiao-Jung

2017-01-01

The study aimed to illustrate the constructs and test the psychometric properties of an instrument of health literacy competencies (IOHLC) for health professionals. A multi-phase questionnaire development method was used to develop the scale. The categorization of the knowledge and practice domains achieved consensus through a modified Delphi process. To reduce the number of items, the 92-item IOHLC was psychometrically evaluated through internal consistency, Rasch modeling, and two-stage factor analysis. In total, 736 practitioners, including nurses, nurse practitioners, health educators, case managers, and dieticians completed the 92-item IOHLC online from May 2012 to January 2013. The final version of the IOHLC covered 9 knowledge items and 40 skill items containing 9 dimensions, with good model fit, and explaining 72% of total variance. All domains had acceptable internal consistency and discriminant validity. The tool in this study is the first to verify health literacy competencies rigorously. Moreover, through psychometric testing, the 49-item IOHLC demonstrates adequate reliability and validity. The IOHLC may serve as a reference for the theoretical and in-service training of Chinese-speaking individuals' health literacy competencies.

Chinese Immigrant Religious Institutions’ Variability in Views on Preventing Sexual Transmission of HIV

PubMed Central

Neilands, Torsten B.

2016-01-01

Objectives. We examined Chinese immigrant religious institutions’ views on teaching about preventing sexual transmission of HIV and the consistency of their views with public health best practices in HIV prevention. Methods. We used 2009 to 2011 survey data from 712 members of 20 New York City–based Chinese immigrant religious institutions to analyze their views on (1) teaching adolescents about condoms, (2) discussing homosexuality nonjudgmentally, and (3) promoting abstinence until marriage. Results. Religion type was a significant predictor of views in the 3 domains, with Evangelical Protestants in least agreement with public health best practices, Buddhists in most agreement, and mainline Protestants between them. Greater HIV knowledge was significantly associated with agreement with best practices in all 3 domains. The frequency of prayer, meditation, or chanting and the level of acculturation were significant predictors of views on teaching adolescents about condoms and promoting abstinence until marriage. Conclusions. The best practice messages about HIV prevention that Chinese immigrant religious institutions find acceptable vary according to religion type and several other key factors, including HIV knowledge; frequency of prayer, meditation, or chanting; and level of acculturation. PMID:26562121

A Study of the Use of Ontologies for Building Computer-Aided Control Engineering Self-Learning Educational Software

NASA Astrophysics Data System (ADS)

García, Isaías; Benavides, Carmen; Alaiz, Héctor; Alonso, Angel

2013-08-01

This paper describes research on the use of knowledge models (ontologies) for building computer-aided educational software in the field of control engineering. Ontologies are able to represent in the computer a very rich conceptual model of a given domain. This model can be used later for a number of purposes in different software applications. In this study, domain ontology about the field of lead-lag compensator design has been built and used for automatic exercise generation, graphical user interface population and interaction with the user at any level of detail, including explanations about why things occur. An application called Onto-CELE (ontology-based control engineering learning environment) uses the ontology for implementing a learning environment that can be used for self and lifelong learning purposes. The experience has shown that the use of knowledge models as the basis for educational software applications is capable of showing students the whole complexity of the analysis and design processes at any level of detail. A practical experience with postgraduate students has shown the mentioned benefits and possibilities of the approach.

Health care administration in the year 2000: practitioners' views of future issues and job requirements.

PubMed

Hudak, R P; Brooke, P P; Finstuen, K; Riley, P

1993-01-01

This research identifies the most important domains in health care administration (HCA) from now to the year 2000 and differentiates job skill, knowledge, and ability requirements necessary for successful management. Fellows of the American College of Healthcare Executives from about half of the United States responded to two iterations of a Delphi mail inquiry. Fellows identified 102 issues that were content-analyzed into nine domains by an HCA expert panel. Domains, in order of ranked importance, were cost/finance, leadership, professional staff interactions, health care delivery concepts, accessibility, ethics, quality/risk management, technology, and marketing. In the second Delphi iteration, Fellows reviewed domain results and rated job requirements on required job importance. Results indicated that while a business orientation is needed for organizational survival, an equal emphasis on person-oriented skills, knowledge, and abilities is required.

A prototype case-based reasoning human assistant for space crew assessment and mission management

NASA Technical Reports Server (NTRS)

Owen, Robert B.; Holland, Albert W.; Wood, Joanna

1993-01-01

We present a prototype human assistant system for space crew assessment and mission management. Our system is based on case episodes from American and Russian space missions and analog environments such as polar stations and undersea habitats. The general domain of small groups in isolated and confined environments represents a near ideal application area for case-based reasoning (CBR) - there are few reliable rules to follow, and most domain knowledge is in the form of cases. We define the problem domain and outline a unique knowledge representation system driven by conflict and communication triggers. The prototype system is able to represent, index, and retrieve case studies of human performance. We index by social, behavioral, and environmental factors. We present the problem domain, our current implementation, our research approach for an operational system, and prototype performance and results.

A systematic review of electronic audit and feedback: intervention effectiveness and use of behaviour change theory.

PubMed

Tuti, Timothy; Nzinga, Jacinta; Njoroge, Martin; Brown, Benjamin; Peek, Niels; English, Mike; Paton, Chris; van der Veer, Sabine N

2017-05-12

Audit and feedback is a common intervention for supporting clinical behaviour change. Increasingly, health data are available in electronic format. Yet, little is known regarding if and how electronic audit and feedback (e-A&F) improves quality of care in practice. The study aimed to assess the effectiveness of e-A&F interventions in a primary care and hospital context and to identify theoretical mechanisms of behaviour change underlying these interventions. In August 2016, we searched five electronic databases, including MEDLINE and EMBASE via Ovid, and the Cochrane Central Register of Controlled Trials for published randomised controlled trials. We included studies that evaluated e-A&F interventions, defined as a summary of clinical performance delivered through an interactive computer interface to healthcare providers. Data on feedback characteristics, underlying theoretical domains, effect size and risk of bias were extracted by two independent review authors, who determined the domains within the Theoretical Domains Framework (TDF). We performed a meta-analysis of e-A&F effectiveness, and a narrative analysis of the nature and patterns of TDF domains and potential links with the intervention effect. We included seven studies comprising of 81,700 patients being cared for by 329 healthcare professionals/primary care facilities. Given the extremely high heterogeneity of the e-A&F interventions and five studies having a medium or high risk of bias, the average effect was deemed unreliable. Only two studies explicitly used theory to guide intervention design. The most frequent theoretical domains targeted by the e-A&F interventions included 'knowledge', 'social influences', 'goals' and 'behaviour regulation', with each intervention targeting a combination of at least three. None of the interventions addressed the domains 'social/professional role and identity' or 'emotion'. Analyses identified the number of different domains coded in control arm to have the biggest role in heterogeneity in e-A&F effect size. Given the high heterogeneity of identified studies, the effects of e-A&F were found to be highly variable. Additionally, e-A&F interventions tend to implicitly target only a fraction of known theoretical domains, even after omitting domains presumed not to be linked to e-A&F. Also, little evaluation of comparative effectiveness across trial arms was conducted. Future research should seek to further unpack the theoretical domains essential for effective e-A&F in order to better support strategic individual and team goals.

Core Competencies for Injury and Violence Prevention

PubMed Central

Stephens-Stidham, Shelli; Peek-Asa, Corinne; Bou-Saada, Ingrid; Hunter, Wanda; Lindemer, Kristen; Runyan, Carol

2009-01-01

Efforts to reduce the burden of injury and violence require a workforce that is knowledgeable and skilled in prevention. However, there has been no systematic process to ensure that professionals possess the necessary competencies. To address this deficiency, we developed a set of core competencies for public health practitioners in injury and violence prevention programs. The core competencies address domains including public health significance, data, the design and implementation of prevention activities, evaluation, program management, communication, stimulating change, and continuing education. Specific learning objectives establish goals for training in each domain. The competencies assist in efforts to reduce the burden of injury and violence and can provide benchmarks against which to assess progress in professional capacity for injury and violence prevention. PMID:19197083

Deep learning for healthcare: review, opportunities and challenges.

PubMed

Miotto, Riccardo; Wang, Fei; Wang, Shuang; Jiang, Xiaoqian; Dudley, Joel T

2017-05-06

Gaining knowledge and actionable insights from complex, high-dimensional and heterogeneous biomedical data remains a key challenge in transforming health care. Various types of data have been emerging in modern biomedical research, including electronic health records, imaging, -omics, sensor data and text, which are complex, heterogeneous, poorly annotated and generally unstructured. Traditional data mining and statistical learning approaches typically need to first perform feature engineering to obtain effective and more robust features from those data, and then build prediction or clustering models on top of them. There are lots of challenges on both steps in a scenario of complicated data and lacking of sufficient domain knowledge. The latest advances in deep learning technologies provide new effective paradigms to obtain end-to-end learning models from complex data. In this article, we review the recent literature on applying deep learning technologies to advance the health care domain. Based on the analyzed work, we suggest that deep learning approaches could be the vehicle for translating big biomedical data into improved human health. However, we also note limitations and needs for improved methods development and applications, especially in terms of ease-of-understanding for domain experts and citizen scientists. We discuss such challenges and suggest developing holistic and meaningful interpretable architectures to bridge deep learning models and human interpretability. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

Creativity Doesn't Develop in a Vacuum.

PubMed

Baer, John

2016-01-01

The skills, knowledge, attitudes, motivations, and personality traits that lead to creative thinking and creative behavior do not exist-and do not develop-in a vacuum. They are inextricably tied to content, to domains, in particular, and they therefore vary by domains. The more we learn about creativity, the more we discover how domain specific creativity is. This means we cannot nurture creativity, or any of the skills or attributes that contribute to creativity, without thinking about content. One cannot become physically fit by doing just one kind of exercise that trains a single set of muscles; all-around fitness requires diverse exercises that use and train many different sets of muscles. So it is with creativity. Different domains require different creativity-relevant skills, knowledge, attitudes, motivations, and personality traits. If we want to help children and adolescents become more creative, then we need to attend to the domains we use in the development of creativity. © 2016 Wiley Periodicals, Inc.

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.

Word and World Knowledge among Deaf Learners with and without Cochlear Implants

ERIC Educational Resources Information Center

Convertino, Carol; Borgna, Georgianna; Marschark, Marc; Durkin, Andreana

2014-01-01

Deaf learners frequently demonstrate significantly less vocabulary knowledge than hearing age-mates. Studies involving other domains of knowledge, and perhaps deaf learners' academic performance, indicate similar lags with regard to world knowledge. Such gaps often are attributed to limitations on deaf children's incidental learning by…

Learning a Theory of Causality

ERIC Educational Resources Information Center

Goodman, Noah D.; Ullman, Tomer D.; Tenenbaum, Joshua B.

2011-01-01

The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be…

An object-relational model for structured representation of medical knowledge.

PubMed

Koch, S; Risch, T; Schneider, W; Wagner, I V

2006-07-01

Domain specific knowledge is often not static but continuously evolving. This is especially true for the medical domain. Furthermore, the lack of standardized structures for presenting knowledge makes it difficult or often impossible to assess new knowledge in the context of existing knowledge. Possibilities to compare knowledge easily and directly are often not given. It is therefore of utmost importance to create a model that allows for comparability, consistency and quality assurance of medical knowledge in specific work situations. For this purpose, we have designed on object-relational model based on structured knowledge elements that are dynamically reusable by different multi-media-based tools for case-based documentation, disease course simulation, and decision support. With this model, high-level components, such as patient case reports or simulations of the course of a disease, and low-level components (e.g., diagnoses, symptoms or treatments) as well as the relationships between these components are modeled. The resulting schema has been implemented in AMOS II, on object-relational multi-database system supporting different views with regard to search and analysis depending on different work situations.

Intelligent systems for human resources.

PubMed

Kline, K B

1988-11-01

An intelligent system contains knowledge about some domain; it has sophisticated decision-making processes and the ability to explain its actions. The most important aspect of an intelligent system is its ability to effectively interact with humans to teach or assist complex information processing. Two intelligent systems are Intelligent Tutoring Systems (ITs) and Expert Systems. The ITSs provide instruction to a student similar to a human tutor. The ITSs capture individual performance and tutor deficiencies. These systems consist of an expert module, which contains the knowledge or material to be taught; the student module, which contains a representation of the knowledge the student knows and does not know about the domain; and the instructional or teaching module, which selects specific knowledge to teach, the instructional strategy, and provides assistance to the student to tutor deficiencies. Expert systems contain an expert's knowledge about some domain and perform specialized tasks or aid a novice in the performance of certain tasks. The most important part of an expert system is the knowledge base. This knowledge base contains all the specialized and technical knowledge an expert possesses. For an expert system to interact effectively with humans, it must have the ability to explain its actions. Use of intelligent systems can have a profound effect on human resources. The ITSs can provide better training by tutoring on an individual basis, and the expert systems can make better use of human resources through job aiding and performing complex tasks. With increasing training requirements and "doing more with less," intelligent systems can have a positive effect on human resources.

An integrated knowledge system for wind tunnel testing - Project Engineers' Intelligent Assistant

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Shi, George Z.; Hoyt, W. A.; Steinle, Frank W., Jr.

1993-01-01

The Project Engineers' Intelligent Assistant (PEIA) is an integrated knowledge system developed using artificial intelligence technology, including hypertext, expert systems, and dynamic user interfaces. This system integrates documents, engineering codes, databases, and knowledge from domain experts into an enriched hypermedia environment and was designed to assist project engineers in planning and conducting wind tunnel tests. PEIA is a modular system which consists of an intelligent user-interface, seven modules and an integrated tool facility. Hypermedia technology is discussed and the seven PEIA modules are described. System maintenance and updating is very easy due to the modular structure and the integrated tool facility provides user access to commercial software shells for documentation, reporting, or database updating. PEIA is expected to provide project engineers with technical information, increase efficiency and productivity, and provide a realistic tool for personnel training.

Towards Cooperative Predictive Data Mining in Competitive Environments

NASA Astrophysics Data System (ADS)

Lisý, Viliam; Jakob, Michal; Benda, Petr; Urban, Štěpán; Pěchouček, Michal

We study the problem of predictive data mining in a competitive multi-agent setting, in which each agent is assumed to have some partial knowledge required for correctly classifying a set of unlabelled examples. The agents are self-interested and therefore need to reason about the trade-offs between increasing their classification accuracy by collaborating with other agents and disclosing their private classification knowledge to other agents through such collaboration. We analyze the problem and propose a set of components which can enable cooperation in this otherwise competitive task. These components include measures for quantifying private knowledge disclosure, data-mining models suitable for multi-agent predictive data mining, and a set of strategies by which agents can improve their classification accuracy through collaboration. The overall framework and its individual components are validated on a synthetic experimental domain.

Clinical Decision Support in Electronic Prescribing: Recommendations and an Action Plan

PubMed Central

Teich, Jonathan M.; Osheroff, Jerome A.; Pifer, Eric A.; Sittig, Dean F.; Jenders, Robert A.

2005-01-01

Clinical decision support (CDS) in electronic prescribing (eRx) systems can improve the safety, quality, efficiency, and cost-effectiveness of care. However, at present, these potential benefits have not been fully realized. In this consensus white paper, we set forth recommendations and action plans in three critical domains: (1) advances in system capabilities, including basic and advanced sets of CDS interventions and knowledge, supporting database elements, operational features to improve usability and measure performance, and management and governance structures; (2) uniform standards, vocabularies, and centralized knowledge structures and services that could reduce rework by vendors and care providers, improve dissemination of well-constructed CDS interventions, promote generally applicable research in CDS methods, and accelerate the movement of new medical knowledge from research to practice; and (3) appropriate financial and legal incentives to promote adoption. PMID:15802474

Relations among Conceptual Knowledge, Procedural Knowledge, and Procedural Flexibility in Two Samples Differing in Prior Knowledge

ERIC Educational Resources Information Center

Schneider, Michael; Rittle-Johnson, Bethany; Star, Jon R.

2011-01-01

Competence in many domains rests on children developing conceptual and procedural knowledge, as well as procedural flexibility. However, research on the developmental relations between these different types of knowledge has yielded unclear results, in part because little attention has been paid to the validity of the measures or to the effects of…

Inositol Pentakisphosphate Isomers Bind PH Domains with Varying Specificity and Inhibit Phosphoinositide Interactions

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

S Jackson; S Al-Saigh; C Schultz

2011-12-31

PH domains represent one of the most common domains in the human proteome. These domains are recognized as important mediators of protein-phosphoinositide and protein-protein interactions. Phosphoinositides are lipid components of the membrane that function as signaling molecules by targeting proteins to their sites of action. Phosphoinositide based signaling pathways govern a diverse range of important cellular processes including membrane remodeling, differentiation, proliferation and survival. Myo-Inositol phosphates are soluble signaling molecules that are structurally similar to the head groups of phosphoinositides. These molecules have been proposed to function, at least in part, by regulating PH domain-phosphoinositide interactions. Given the structural similaritymore » of inositol phosphates we were interested in examining the specificity of PH domains towards the family of myo-inositol pentakisphosphate isomers. In work reported here we demonstrate that the C-terminal PH domain of pleckstrin possesses the specificity required to discriminate between different myo-inositol pentakisphosphate isomers. The structural basis for this specificity was determined using high-resolution crystal structures. Moreover, we show that while the PH domain of Grp1 does not possess this high degree of specificity, the PH domain of protein kinase B does. These results demonstrate that some PH domains possess enough specificity to discriminate between myo-inositol pentakisphosphate isomers allowing for these molecules to differentially regulate interactions with phosphoinositides. Furthermore, this work contributes to the growing body of evidence supporting myo-inositol phosphates as regulators of important PH domain-phosphoinositide interactions. Finally, in addition to expanding our knowledge of cellular signaling, these results provide a basis for developing tools to probe biological pathway.« less

Cognitive flexibility and undergraduate physiology students: increasing advanced knowledge acquisition within an ill-structured domain.

PubMed

Rhodes, Ashley E; Rozell, Timothy G

2017-09-01

Cognitive flexibility is defined as the ability to assimilate previously learned information and concepts to generate novel solutions to new problems. This skill is crucial for success within ill-structured domains such as biology, physiology, and medicine, where many concepts are simultaneously required for understanding a complex problem, yet the problem consists of patterns or combinations of concepts that are not consistently used or needed across all examples. To succeed within ill-structured domains, a student must possess a certain level of cognitive flexibility: rigid thought processes and prepackaged informational retrieval schemes relying on rote memorization will not suffice. In this study, we assessed the cognitive flexibility of undergraduate physiology students using a validated instrument entitled Student's Approaches to Learning (SAL). The SAL evaluates how deeply and in what way information is processed, as well as the investment of time and mental energy that a student is willing to expend by measuring constructs such as elaboration and memorization. Our results indicate that students who rely primarily on memorization when learning new information have a smaller knowledge base about physiological concepts, as measured by a prior knowledge assessment and unit exams. However, students who rely primarily on elaboration when learning new information have a more well-developed knowledge base about physiological concepts, which is displayed by higher scores on a prior knowledge assessment and increased performance on unit exams. Thus students with increased elaboration skills possibly possess a higher level of cognitive flexibility and are more likely to succeed within ill-structured domains. Copyright © 2017 the American Physiological Society.

Knowledge Importance in Rehabilitation Counseling.

ERIC Educational Resources Information Center

Leahy, Michael J.; And Others

1993-01-01

Examined differences among certified rehabilitation counselors (n=1,535) in level of importance attributed to various knowledge domains. Found that grouping respondents according to employment setting and job title accounted for most frequent differences in knowledge importance among all variables examined. Respondents' educational background and…

A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis.

PubMed

Kim, Seongsoon; Park, Donghyeon; Choi, Yonghwa; Lee, Kyubum; Kim, Byounggun; Jeon, Minji; Kim, Jihye; Tan, Aik Choon; Kang, Jaewoo

2018-01-05

With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since there is no dataset for the biomedical literature comprehension task, our work includes generating a large-scale question answering dataset using PubMed and manually evaluating the generated dataset. We present an attention-based deep neural model tailored to the biomedical domain. To further enhance the performance of our model, we used a pretrained word vector and biomedical entity type embedding. We also developed an ensemble method of combining the results of several independent models to reduce the variance of the answers from the models. The experimental results showed that our proposed deep neural network model outperformed the baseline model by more than 7% on the new dataset. We also evaluated human performance on the new dataset. The human evaluation result showed that our deep neural model outperformed humans in comprehension by 22% on average. In this work, we introduced a new task of machine comprehension in the biomedical domain using a deep neural model. Since there was no large-scale dataset for training deep neural models in the biomedical domain, we created the new cloze-style datasets Biomedical Knowledge Comprehension Title (BMKC_T) and Biomedical Knowledge Comprehension Last Sentence (BMKC_LS) (together referred to as BioMedical Knowledge Comprehension) using the PubMed corpus. The experimental results showed that the performance of our model is much higher than that of humans. We observed that our model performed consistently better regardless of the degree of difficulty of a text, whereas humans have difficulty when performing biomedical literature comprehension tasks that require expert level knowledge. ©Seongsoon Kim, Donghyeon Park, Yonghwa Choi, Kyubum Lee, Byounggun Kim, Minji Jeon, Jihye Kim, Aik Choon Tan, Jaewoo Kang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.01.2018.

[Resuscitation training for lay persons in first aid courses: Transfer of knowledge, skills and attitude].

PubMed

Breckwoldt, J; Lingemann, C; Wagner, P

2016-01-01

Bystander cardiopulmonary resuscitation (CPR) is the most effective intervention for out of hospital sudden cardiac arrest; therefore, basic life support (BLS) courses for lay persons have become well established in industrialized countries, often since decades. Despite this favorable situation bystander CPR rates still remain low in some countries (e.g. in Germany), indicating serious implementation problems. The quality of instruction in these courses could be one reason for low bystander CPR rates. We therefore analyzed official lay BLS courses in terms of the teaching quality in the domains of knowledge, skills and attitudes (according to Bloom's taxonomy). A total of 20 officially accredited lay BLS courses in Berlin, Germany, were analyzed by a participating observer, who remained blinded to the instructor and course participants until the end of the course. Courses were offered by German rescue organizations and private providers according to European Resuscitation Council (ERC) guidelines. Teaching quality was rated by a standardized checklist including 21 observable criteria of teaching quality for transfer of knowledge (n = 10), skills (n = 8) and attitudes (n = 3). In order to achieve comparability between items the results of each criterion were quantified by Likert scales ranging from +2 (very good) to -2 (very poor). The average score of all courses was +0.47 (SD ±0.46) for transfer of knowledge, +0.03 (SD ±0.61) for skills and -1.08 (SD ±0.73) for attitudes. In the domain of knowledge transfer, learning atmosphere and course structure were rated to be generally good, whilst marked deficits were found with respect to correctness of content. In the domain of skills the more positive ratings were given for teaching of single BLS elements (e.g. compressions and ventilation), in contrast to the training of BLS context, where e.g. realistic scenarios were only used by 3 out of 20 instructors. The domain of attitude transfer had the worst rating. Detailed ratings were -0.90 for "reducing fear of doing harm to the victim", -1.25 for "positive attribution of practical training" and -1.10 for "explaining course relevance from the learners' perspective". Within the observed BLS courses the teaching quality revealed significant deficits, especially for the transfer of positive attitudes to learners. Also, the use of meaningful realistic scenario teaching was very scarce. These findings can significantly contribute to low bystander CPR rates because transfer of learned content into practice may be hampered.

Node-Expansion Operators for the UCT Algorithm

NASA Astrophysics Data System (ADS)

Yajima, Takayuki; Hashimoto, Tsuyoshi; Matsui, Toshiki; Hashimoto, Junichi; Spoerer, Kristian

Recent works on the MCTS and UCT framework in the domain of Go focused on introducing knowledge to the playout and on pruning variations from the tree, but so far node expansion has not been investigated. In this paper we show that delaying expansion according to the number of the siblings delivers a gain of more than 92% when compared to normal expansion. We propose three improvements; one that uses domain knowledge and two that are domain-independent methods. Experimental results show that all advanced operators significantly improve the UCT performance when compared to the basic delaying expansion. From the results we may conclude that the new expansion operators are an appropriate means to improve the UCT algorithm.

Cross-domain question classification in community question answering via kernel mapping

NASA Astrophysics Data System (ADS)

Su, Lei; Hu, Zuoliang; Yang, Bin; Li, Yiyang; Chen, Jun

2015-10-01

An increasingly popular method for retrieving information is via the community question answering (CQA) systems such as Yahoo! Answers and Baidu Knows. In CQA, question classification plays an important role to find the answers. However, the labeled training examples for statistical question classifier are fairly expensive to obtain, as they require the experienced human efforts. Meanwhile, unlabeled data are readily available. This paper employs the method of domain adaptation via kernel mapping to solve this problem. In detail, the kernel approach is utilized to map the target-domain data and the source-domain data into a common space, where the question classifiers are trained under the closer conditional probabilities. The kernel mapping function is constructed by domain knowledge. Therefore, domain knowledge could be transferred from the labeled examples in the source domain to the unlabeled ones in the targeted domain. The statistical training model can be improved by using a large number of unlabeled data. Meanwhile, the Hadoop Platform is used to construct the mapping mechanism to reduce the time complexity. Map/Reduce enable kernel mapping for domain adaptation in parallel in the Hadoop Platform. Experimental results show that the accuracy of question classification could be improved by the method of kernel mapping. Furthermore, the parallel method in the Hadoop Platform could effective schedule the computing resources to reduce the running time.

Re-making the global economy of knowledge: do new fields of research change the structure of North-South relations?

PubMed

Connell, Raewyn; Pearse, Rebecca; Collyer, Fran; Maia, João; Morrell, Robert

2017-08-17

How is global-North predominance in the making of organized knowledge affected by the rise of new domains of research? This question is examined empirically in three interdisciplinary areas - climate change, HIV-AIDS, and gender studies - through interviews with 70 researchers in Southern-tier countries Brazil, South Africa and Australia. The study found that the centrality of the North was reinstituted as these domains came into existence, through resource inequalities, workforce mechanisms, and intellectual framing. Yet there are tensions in the global economy of knowledge, around workforce formation, hierarchies of disciplines, neoliberal management strategies, and mismatches with social need. Intellectual workers in the Southern tier have built significant research centres, workforces and some distinctive knowledge projects. These create wider possibilities of change in the global structure of organized knowledge production. © London School of Economics and Political Science 2017.

Faculty Evaluations Correlate Poorly with Medical Student Examination Performance in a Fourth-Year Emergency Medicine Clerkship.

PubMed

Dubosh, Nicole M; Fisher, Jonathan; Lewis, Jason; Ullman, Edward A

2017-06-01

Clerkship directors routinely evaluate medical students using multiple modalities, including faculty assessment of clinical performance and written examinations. Both forms of evaluation often play a prominent role in final clerkship grade. The degree to which these modalities correlate in an emergency medicine (EM) clerkship is unclear. We sought to correlate faculty clinical evaluations with medical student performance on a written, standardized EM examination of medical knowledge. This is a retrospective study of fourth-year medical students in a 4-week EM elective at one academic medical center. EM faculty performed end of shift evaluations of students via a blinded online system using a 5-point Likert scale for 8 domains: data acquisition, data interpretation, medical knowledge base, professionalism, patient care and communication, initiative/reliability/dependability, procedural skills, and overall evaluation. All students completed the National EM M4 Examination in EM. Means, medians, and standard deviations for end of shift evaluation scores were calculated, and correlations with examination scores were assessed using a Spearman's rank correlation coefficient. Thirty-nine medical students with 224 discrete faculty evaluations were included. The median number of evaluations completed per student was 6. The mean score (±SD) on the examination was 78.6% ± 6.1%. The examination score correlated poorly with faculty evaluations across all 8 domains (ρ 0.074-0.316). Faculty evaluations of medical students across multiple domains of competency correlate poorly with written examination performance during an EM clerkship. Educators need to consider the limitations of examination score in assessing students' ability to provide quality patient clinical care. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Evaluation of need for ontologies to manage domain content for the Reportable Conditions Knowledge Management System.

PubMed

Eilbeck, Karen L; Lipstein, Julie; McGarvey, Sunanda; Staes, Catherine J

2014-01-01

The Reportable Condition Knowledge Management System (RCKMS) is envisioned to be a single, comprehensive, authoritative, real-time portal to author, view and access computable information about reportable conditions. The system is designed for use by hospitals, laboratories, health information exchanges, and providers to meet public health reporting requirements. The RCKMS Knowledge Representation Workgroup was tasked to explore the need for ontologies to support RCKMS functionality. The workgroup reviewed relevant projects and defined criteria to evaluate candidate knowledge domain areas for ontology development. The use of ontologies is justified for this project to unify the semantics used to describe similar reportable events and concepts between different jurisdictions and over time, to aid data integration, and to manage large, unwieldy datasets that evolve, and are sometimes externally managed.