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.

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.'

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…

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…

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.

Domains and naïve theories.

PubMed

Gelman, Susan A; Noles, Nicholaus S

2011-09-01

Human cognition entails domain-specific cognitive processes that influence memory, attention, categorization, problem-solving, reasoning, and knowledge organization. This article examines domain-specific causal theories, which are of particular interest for permitting an examination of how knowledge structures change over time. We first describe the properties of commonsense theories, and how commonsense theories differ from scientific theories, illustrating with children's classification of biological and nonbiological kinds. We next consider the implications of domain-specificity for broader issues regarding cognitive development and conceptual change. We then examine the extent to which domain-specific theories interact, and how people reconcile competing causal frameworks. Future directions for research include examining how different content domains interact, the nature of theory change, the role of context (including culture, language, and social interaction) in inducing different frameworks, and the neural bases for domain-specific reasoning. WIREs Cogni Sci 2011 2 490-502 DOI: 10.1002/wcs.124 This article is categorized under: Psychology > Reasoning and Decision Making. Copyright © 2010 John Wiley & Sons, Ltd.

Why Johnny can't reengineer health care processes with information technology.

PubMed

Webster, C; McLinden, S; Begler, K

1995-01-01

Many educational institutions are developing curricula that integrate computer and business knowledge and skills concerning a specific industry, such as banking or health care. We have developed a curriculum that emphasizes, equally, medical, computer, and business management concepts. Along the way we confronted a formidable obstacle, namely the domain specificity of the reference disciplines. Knowledge within each domain is sufficiently different from other domains that it reduces the leverage of building on preexisting knowledge and skills. We review this problem from the point of view of cognitive science (in particular, knowledge representation and machine learning) to suggest strategies for coping with incommensurate domain ontologies. These strategies include reflective judgment, implicit learning, abstraction, generalization, analogy, multiple inheritance, project-orientation, selectivity, goal- and failure-driven learning, and case- and story-based learning.

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.

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.

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…

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…

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.

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.

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

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.

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.

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…

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.

User Interface Technology for Formal Specification Development

NASA Technical Reports Server (NTRS)

Lowry, Michael; Philpot, Andrew; Pressburger, Thomas; Underwood, Ian; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

Formal specification development and modification are an essential component of the knowledge-based software life cycle. User interface technology is needed to empower end-users to create their own formal specifications. This paper describes the advanced user interface for AMPHION1 a knowledge-based software engineering system that targets scientific subroutine libraries. AMPHION is a generic, domain-independent architecture that is specialized to an application domain through a declarative domain theory. Formal specification development and reuse is made accessible to end-users through an intuitive graphical interface that provides semantic guidance in creating diagrams denoting formal specifications in an application domain. The diagrams also serve to document the specifications. Automatic deductive program synthesis ensures that end-user specifications are correctly implemented. The tables that drive AMPHION's user interface are automatically compiled from a domain theory; portions of the interface can be customized by the end-user. The user interface facilitates formal specification development by hiding syntactic details, such as logical notation. It also turns some of the barriers for end-user specification development associated with strongly typed formal languages into active sources of guidance, without restricting advanced users. The interface is especially suited for specification modification. AMPHION has been applied to the domain of solar system kinematics through the development of a declarative domain theory. Testing over six months with planetary scientists indicates that AMPHION's interactive specification acquisition paradigm enables users to develop, modify, and reuse specifications at least an order of magnitude more rapidly than manual program development.

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…

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.

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.

AMPHION: Specification-based programming for scientific subroutine libraries

NASA Technical Reports Server (NTRS)

Lowry, Michael; Philpot, Andrew; Pressburger, Thomas; Underwood, Ian; Waldinger, Richard; Stickel, Mark

1994-01-01

AMPHION is a knowledge-based software engineering (KBSE) system that guides a user in developing a diagram representing a formal problem specification. It then automatically implements a solution to this specification as a program consisting of calls to subroutines from a library. The diagram provides an intuitive domain oriented notation for creating a specification that also facilitates reuse and modification. AMPHION'S architecture is domain independent. AMPHION is specialized to an application domain by developing a declarative domain theory. Creating a domain theory is an iterative process that currently requires the joint expertise of domain experts and experts in automated formal methods for software development.

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…

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.

Knowledge-based requirements analysis for automating software development

NASA Technical Reports Server (NTRS)

Markosian, Lawrence Z.

1988-01-01

We present a new software development paradigm that automates the derivation of implementations from requirements. In this paradigm, informally-stated requirements are expressed in a domain-specific requirements specification language. This language is machine-understable and requirements expressed in it are captured in a knowledge base. Once the requirements are captured, more detailed specifications and eventually implementations are derived by the system using transformational synthesis. A key characteristic of the process is that the required human intervention is in the form of providing problem- and domain-specific engineering knowledge, not in writing detailed implementations. We describe a prototype system that applies the paradigm in the realm of communication engineering: the prototype automatically generates implementations of buffers following analysis of the requirements on each buffer.

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.

Issues Related to the Construction of a Purpose-Built Domain-Specific Word Corpus

ERIC Educational Resources Information Center

Thomas, Lisa; Pfister, H. Peter; Peterson, Peter

2004-01-01

There is growing interest in the use of semantic collections in order to identify and analyse domain knowledge. This paper describes some technical issues to consider when contemplating research which incorporates small-to-medium domain-specific word sets. The purpose of the corpus construction described was to provide an external word collection…

Meta-tools for software development and knowledge acquisition

NASA Technical Reports Server (NTRS)

Eriksson, Henrik; Musen, Mark A.

1992-01-01

The effectiveness of tools that provide support for software development is highly dependent on the match between the tools and their task. Knowledge-acquisition (KA) tools constitute a class of development tools targeted at knowledge-based systems. Generally, KA tools that are custom-tailored for particular application domains are more effective than are general KA tools that cover a large class of domains. The high cost of custom-tailoring KA tools manually has encouraged researchers to develop meta-tools for KA tools. Current research issues in meta-tools for knowledge acquisition are the specification styles, or meta-views, for target KA tools used, and the relationships between the specification entered in the meta-tool and other specifications for the target program under development. We examine different types of meta-views and meta-tools. Our current project is to provide meta-tools that produce KA tools from multiple specification sources--for instance, from a task analysis of the target application.

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

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.

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

"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…

An Ada Based Expert System for the Ada Version of SAtool II. Volume 1 and 2

DTIC Science & Technology

1991-06-06

Integrated Computer-Aided Manufacturing (ICAM) (20). In fact, IDEF 0 stands for ICAM Definition Method Zero . IDEF0 defines a subset of SA that omits...reasoning that has been programmed). An expert’s knowledge is specific to one problem domain as opposed to knowledge about general problem-solving...techniques. General problem domains are medicine, finance, science or engineering and so forth in which an expert can solve specific problems very well

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.

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

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…

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.

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.

Integrating natural language processing and web GIS for interactive knowledge domain visualization

NASA Astrophysics Data System (ADS)

Du, Fangming

Recent years have seen a powerful shift towards data-rich environments throughout society. This has extended to a change in how the artifacts and products of scientific knowledge production can be analyzed and understood. Bottom-up approaches are on the rise that combine access to huge amounts of academic publications with advanced computer graphics and data processing tools, including natural language processing. Knowledge domain visualization is one of those multi-technology approaches, with its aim of turning domain-specific human knowledge into highly visual representations in order to better understand the structure and evolution of domain knowledge. For example, network visualizations built from co-author relations contained in academic publications can provide insight on how scholars collaborate with each other in one or multiple domains, and visualizations built from the text content of articles can help us understand the topical structure of knowledge domains. These knowledge domain visualizations need to support interactive viewing and exploration by users. Such spatialization efforts are increasingly looking to geography and GIS as a source of metaphors and practical technology solutions, even when non-georeferenced information is managed, analyzed, and visualized. When it comes to deploying spatialized representations online, web mapping and web GIS can provide practical technology solutions for interactive viewing of knowledge domain visualizations, from panning and zooming to the overlay of additional information. This thesis presents a novel combination of advanced natural language processing - in the form of topic modeling - with dimensionality reduction through self-organizing maps and the deployment of web mapping/GIS technology towards intuitive, GIS-like, exploration of a knowledge domain visualization. A complete workflow is proposed and implemented that processes any corpus of input text documents into a map form and leverages a web application framework to let users explore knowledge domain maps interactively. This workflow is implemented and demonstrated for a data set of more than 66,000 conference abstracts.

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.

Synergy between Teacher Practices and Curricular Scaffolds to Support Students in Using Domain-Specific and Domain-General Knowledge in Writing Arguments to Explain Phenomena

ERIC Educational Resources Information Center

McNeill, Katherine L.; Krajcik, Joseph

2009-01-01

We investigated how 2 different curricular scaffolds (context-specific vs. generic), teacher instructional practices, and the interaction between these 2 types of support influenced students' learning of science content and their ability to write scientific arguments to explain phenomena. The context-specific scaffolds provided students with hints…

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…

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'…

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.

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.

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…

Early Domain-Specific Knowledge? Nonlinear Developmental Trajectories Further Erode a House of Sand

ERIC Educational Resources Information Center

Deak, Gedeon O.

2011-01-01

Rakison and Yermolayeva (this issue) argue that domain specificity is difficult to reconcile with U-, N-, or M-shaped developmental trends. They are justified because: (1) There is no compelling evidence that nonlinear trends require mechanisms beyond general, well-known cognitive processes; and (2) epigenetic neuroscience provides no clear…

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.

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.

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.

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.

Premorbid expertise produces category-specific impairment in a domain-general semantic disorder.

PubMed

Jefferies, Elizabeth; Rogers, Timothy T; Ralph, Matthew A Lambon

2011-10-01

For decades, category-specific semantic impairment - i.e., better comprehension of items from one semantic category than another - has been the driving force behind many claims about the organisation of conceptual knowledge in the brain. Double dissociations between patients with category-specific disorders are widely interpreted as showing that different conceptual domains are necessarily supported by functionally independent systems. We show that, to the contrary, even strong or classical dissociations can also arise from individual differences in premorbid expertise. We examined two patients with global and progressive semantic degradation who, unusually, had known areas of premorbid expertise. Patient 1, a former automotive worker, showed selective preservation of car knowledge, whereas Patient 2, a former botanist, showed selective preservation of information about plants. In non-expert domains, these patients showed the typical pattern: i.e., an inability to differentiate between highly similar concepts (e.g., rose and daisy), but retention of broader distinctions (e.g., between rose and cat). Parallel distributed processing (PDP) models of semantic cognition show that expertise in a particular domain increases the differentiation of specific-level concepts, such that the semantic distance between these items resembles non-expert basic-level distinctions. We propose that these structural changes interact with global semantic degradation, particularly when expert knowledge is acquired early and when exposure to expert concepts continues during disease progression. Therefore, category-specific semantic impairment can arise from at least two distinct mechanisms: damage to representations that are critical for a particular category (e.g., knowledge of hand shape and action for the category 'tools') and differences in premorbid experience. Copyright © 2011 Elsevier Ltd. All rights reserved.

Specific Previous Experience Affects Perception of Harmony and Meter

ERIC Educational Resources Information Center

Creel, Sarah C.

2011-01-01

Prior knowledge shapes our experiences, but which prior knowledge shapes which experiences? This question is addressed in the domain of music perception. Three experiments were used to determine whether listeners activate specific musical memories during music listening. Each experiment provided listeners with one of two musical contexts that was…

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.

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.

Preservation of person-specific knowledge in semantic memory disorder: a longitudinal investigation in two cases of dementia.

PubMed

Haslam, Catherine; Sabah, Mazen

2013-03-01

The double dissociation involving person-specific and general semantic knowledge is supported by numerous patient studies, though cases with preservation of the former are few. In this paper, we report longitudinal data from two cases. Their knowledge in both domains was preserved at the start of the investigation, but progressive deterioration was primarily observed on tests of general semantics. These data strengthen the evidence-base for preservation of person-specific knowledge in semantic memory disorder, and support its separate representation from object knowledge. © 2012 The British Psychological Society.

Modeling software systems by domains

NASA Technical Reports Server (NTRS)

Dippolito, Richard; Lee, Kenneth

1992-01-01

The Software Architectures Engineering (SAE) Project at the Software Engineering Institute (SEI) has developed engineering modeling techniques that both reduce the complexity of software for domain-specific computer systems and result in systems that are easier to build and maintain. These techniques allow maximum freedom for system developers to apply their domain expertise to software. We have applied these techniques to several types of applications, including training simulators operating in real time, engineering simulators operating in non-real time, and real-time embedded computer systems. Our modeling techniques result in software that mirrors both the complexity of the application and the domain knowledge requirements. We submit that the proper measure of software complexity reflects neither the number of software component units nor the code count, but the locus of and amount of domain knowledge. As a result of using these techniques, domain knowledge is isolated by fields of engineering expertise and removed from the concern of the software engineer. In this paper, we will describe kinds of domain expertise, describe engineering by domains, and provide relevant examples of software developed for simulator applications using the techniques.

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…

Improving Reliability of Spectrum Analysis for Software Quality Requirements Using TCM

NASA Astrophysics Data System (ADS)

Kaiya, Haruhiko; Tanigawa, Masaaki; Suzuki, Shunichi; Sato, Tomonori; Osada, Akira; Kaijiri, Kenji

Quality requirements are scattered over a requirements specification, thus it is hard to measure and trace such quality requirements to validate the specification against stakeholders' needs. We proposed a technique called “spectrum analysis for quality requirements” which enabled analysts to sort a requirements specification to measure and track quality requirements in the specification. In the same way as a spectrum in optics, a quality spectrum of a specification shows a quantitative feature of the specification with respect to quality. Therefore, we can compare a specification of a system to another one with respect to quality. As a result, we can validate such a specification because we can check whether the specification has common quality features and know its specific features against specifications of existing similar systems. However, our first spectrum analysis for quality requirements required a lot of effort and knowledge of a problem domain and it was hard to reuse such knowledge to reduce the effort. We thus introduce domain knowledge called term-characteristic map (TCM) to reuse the knowledge for our quality spectrum analysis. Through several experiments, we evaluate our spectrum analysis, and main finding are as follows. First, we confirmed specifications of similar systems have similar quality spectra. Second, results of spectrum analysis using TCM are objective, i.e., different analysts can generate almost the same spectra when they analyze the same specification.

Simplifying the construction of domain-specific automatic programming systems: The NASA automated software development workstation project

NASA Technical Reports Server (NTRS)

Allen, Bradley P.; Holtzman, Peter L.

1987-01-01

An overview is presented of the Automated Software Development Workstation Project, an effort to explore knowledge-based approaches to increasing software productivity. The project focuses on applying the concept of domain specific automatic programming systems (D-SAPSs) to application domains at NASA's Johnson Space Center. A version of a D-SAPS developed in Phase 1 of the project for the domain of space station momentum management is described. How problems encountered during its implementation led researchers to concentrate on simplifying the process of building and extending such systems is discussed. Researchers propose to do this by attacking three observed bottlenecks in the D-SAPS development process through the increased automation of the acquisition of programming knowledge and the use of an object oriented development methodology at all stages of the program design. How these ideas are being implemented in the Bauhaus, a prototype workstation for D-SAPS development is discussed.

Simplifying the construction of domain-specific automatic programming systems: The NASA automated software development workstation project

NASA Technical Reports Server (NTRS)

Allen, Bradley P.; Holtzman, Peter L.

1988-01-01

An overview is presented of the Automated Software Development Workstation Project, an effort to explore knowledge-based approaches to increasing software productivity. The project focuses on applying the concept of domain specific automatic programming systems (D-SAPSs) to application domains at NASA's Johnson Space Flight Center. A version of a D-SAPS developed in Phase 1 of the project for the domain of space station momentum management is described. How problems encountered during its implementation led researchers to concentrate on simplifying the process of building and extending such systems is discussed. Researchers propose to do this by attacking three observed bottlenecks in the D-SAPS development process through the increased automation of the acquisition of programming knowledge and the use of an object oriented development methodology at all stages of the program design. How these ideas are being implemented in the Bauhaus, a prototype workstation for D-SAPS development is discussed.

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.

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

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.

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.

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.

Using domain knowledge and domain-inspired discourse model for coreference resolution for clinical narratives

PubMed Central

Roth, Dan

2013-01-01

Objective This paper presents a coreference resolution system for clinical narratives. Coreference resolution aims at clustering all mentions in a single document to coherent entities. Materials and methods A knowledge-intensive approach for coreference resolution is employed. The domain knowledge used includes several domain-specific lists, a knowledge intensive mention parsing, and task informed discourse model. Mention parsing allows us to abstract over the surface form of the mention and represent each mention using a higher-level representation, which we call the mention's semantic representation (SR). SR reduces the mention to a standard form and hence provides better support for comparing and matching. Existing coreference resolution systems tend to ignore discourse aspects and rely heavily on lexical and structural cues in the text. The authors break from this tradition and present a discourse model for “person” type mentions in clinical narratives, which greatly simplifies the coreference resolution. Results This system was evaluated on four different datasets which were made available in the 2011 i2b2/VA coreference challenge. The unweighted average of F1 scores (over B-cubed, MUC and CEAF) varied from 84.2% to 88.1%. These experiments show that domain knowledge is effective for different mention types for all the datasets. Discussion Error analysis shows that most of the recall errors made by the system can be handled by further addition of domain knowledge. The precision errors, on the other hand, are more subtle and indicate the need to understand the relations in which mentions participate for building a robust coreference system. Conclusion This paper presents an approach that makes an extensive use of domain knowledge to significantly improve coreference resolution. The authors state that their system and the knowledge sources developed will be made publicly available. PMID:22781192

"I Prefer Success": Subject Specificity in a First Grade

ERIC Educational Resources Information Center

Levstik, Linda S.; Yessin, Ruby

Research on restructuring domain-specific knowledge suggests that inferences made by a learner are based more on what and how concepts are structured and organized in particular domains than on the age of the learner. In this view, it is possible for children to operate more expertly in a particular area than could be explained by global stage or…

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.

Maintaining consistency between planning hierarchies: Techniques and applications

NASA Technical Reports Server (NTRS)

Zoch, David R.

1987-01-01

In many planning and scheduling environments, it is desirable to be able to view and manipulate plans at different levels of abstraction, allowing the users the option of viewing and manipulating either a very detailed representation of the plan or a high-level more abstract version of the plan. Generating a detailed plan from a more abstract plan requires domain-specific planning/scheduling knowledge; the reverse process of generating a high-level plan from a detailed plan Reverse Plan Maintenance, or RPM) requires having the system remember the actions it took based on its domain-specific knowledge and its reasons for taking those actions. This reverse plan maintenance process is described as implemented in a specific planning and scheduling tool, The Mission Operations Planning Assistant (MOPA), as well as the applications of RPM to other planning and scheduling problems; emphasizing the knowledge that is needed to maintain the correspondence between the different hierarchical planning levels.

Elucidation of the binding preferences of peptide recognition modules: SH3 and PDZ domains.

PubMed

Teyra, Joan; Sidhu, Sachdev S; Kim, Philip M

2012-08-14

Peptide-binding domains play a critical role in regulation of cellular processes by mediating protein interactions involved in signalling. In recent years, the development of large-scale technologies has enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. These efforts have provided significant insights into the binding specificities of these modular domains. Many research groups have taken advantage of this unprecedented volume of specificity data and have developed a variety of new algorithms for the prediction of binding specificities of peptide-binding domains and for the prediction of their natural binding targets. This knowledge has also been applied to the design of synthetic peptide-binding domains in order to rewire protein-protein interaction networks. Here, we describe how these experimental technologies have impacted on our understanding of peptide-binding domain specificities and on the elucidation of their natural ligands. We discuss SH3 and PDZ domains as well characterized examples, and we explore the feasibility of expanding high-throughput experiments to other peptide-binding domains. Copyright © 2012. Published by Elsevier B.V.

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.

How to Identify a Domain-General Learning Mechanism when You See One

ERIC Educational Resources Information Center

Rakison, David H.; Yermolayeva, Yevdokiya

2011-01-01

A longstanding and fundamental debate in developmental science is whether knowledge is acquired through domain-specific or domain-general mechanisms. To date, there exists no tool to determine whether experimental data support one theoretical approach or the other. In this article, we argue that the U- and N-shaped curves found in a number of…

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.

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…

Signaling Text-Picture Relations in Multimedia Learning: The Influence of Prior Knowledge

ERIC Educational Resources Information Center

Richter, Juliane; Scheiter, Katharina; Eitel, Alexander

2018-01-01

Multimedia integration signals highlight correspondences between text and pictures with the aim of supporting learning from multimedia. A recent meta-analysis revealed that only learners with low domain-specific prior knowledge benefit from multimedia integration signals. To more thoroughly investigate the influence of prior knowledge on the…

Intersecting Domains of Assessment Knowledge: School Typologies Based on Interviews with Secondary Teachers

ERIC Educational Resources Information Center

Howley, Marged D.; Howley, Aimee; Henning, John E.; Gillam, Mary Beth; Weade, Ginger

2013-01-01

This study used qualitative interviewing with teachers at three high schools to answer research questions about teachers' assessment knowledge, school-specific assessment cultures, and teachers' perceptions of the assessment literacy of other key stakeholders. Data analysis revealed shared knowledge and practices across schools--use of formative…

Automating the design of scientific computing software

NASA Technical Reports Server (NTRS)

Kant, Elaine

1992-01-01

SINAPSE is a domain-specific software design system that generates code from specifications of equations and algorithm methods. This paper describes the system's design techniques (planning in a space of knowledge-based refinement and optimization rules), user interaction style (user has option to control decision making), and representation of knowledge (rules and objects). It also summarizes how the system knowledge has evolved over time and suggests some issues in building software design systems to facilitate reuse.

From data repositories to submission portals: rethinking the role of domain-specific databases in CollecTF.

PubMed

Kılıç, Sefa; Sagitova, Dinara M; Wolfish, Shoshannah; Bely, Benoit; Courtot, Mélanie; Ciufo, Stacy; Tatusova, Tatiana; O'Donovan, Claire; Chibucos, Marcus C; Martin, Maria J; Erill, Ivan

2016-01-01

Domain-specific databases are essential resources for the biomedical community, leveraging expert knowledge to curate published literature and provide access to referenced data and knowledge. The limited scope of these databases, however, poses important challenges on their infrastructure, visibility, funding and usefulness to the broader scientific community. CollecTF is a community-oriented database documenting experimentally validated transcription factor (TF)-binding sites in the Bacteria domain. In its quest to become a community resource for the annotation of transcriptional regulatory elements in bacterial genomes, CollecTF aims to move away from the conventional data-repository paradigm of domain-specific databases. Through the adoption of well-established ontologies, identifiers and collaborations, CollecTF has progressively become also a portal for the annotation and submission of information on transcriptional regulatory elements to major biological sequence resources (RefSeq, UniProtKB and the Gene Ontology Consortium). This fundamental change in database conception capitalizes on the domain-specific knowledge of contributing communities to provide high-quality annotations, while leveraging the availability of stable information hubs to promote long-term access and provide high-visibility to the data. As a submission portal, CollecTF generates TF-binding site information through direct annotation of RefSeq genome records, definition of TF-based regulatory networks in UniProtKB entries and submission of functional annotations to the Gene Ontology. As a database, CollecTF provides enhanced search and browsing, targeted data exports, binding motif analysis tools and integration with motif discovery and search platforms. This innovative approach will allow CollecTF to focus its limited resources on the generation of high-quality information and the provision of specialized access to the data.Database URL: http://www.collectf.org/. © The Author(s) 2016. Published by Oxford University Press.

Concept Mapping Assessment of Media Assisted Learning in Interdisciplinary Science Education

NASA Astrophysics Data System (ADS)

Schaal, Steffen; Bogner, Franz X.; Girwidz, Raimund

2010-05-01

Acquisition of conceptual knowledge is a central aim in science education. In this study we monitored an interdisciplinary hypermedia assisted learning unit on hibernation and thermodynamics based on cooperative learning. We used concept mapping for the assessment, applying a pre-test/post-test design. In our study, 106 9th graders cooperated by working in pairs ( n = 53) for six lessons. As an interdisciplinary learning activity in such complex knowledge domains has to combine many different aspects, we focused on long-term knowledge. Learners working cooperatively in dyads constructed computer-supported concept maps which were analysed by specific software. The data analysis encompassed structural aspects of the knowledge corresponding to a target reference map. After the learning unit, the results showed the acquisition of higher-order domain-specific knowledge structures which indicates successful interdisciplinary learning through the hypermedia learning environment. The benefit of using a computer-assisted concept mapping assessment for research in science education, and in science classrooms is considered.

ADO: a disease ontology representing the domain knowledge specific to Alzheimer's disease.

PubMed

Malhotra, Ashutosh; Younesi, Erfan; Gündel, Michaela; Müller, Bernd; Heneka, Michael T; Hofmann-Apitius, Martin

2014-03-01

Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases such as Alzheimer's disease, there is a lack of formal representation of the relevant knowledge domain. Alzheimer's disease ontology (ADO) is constructed in accordance to the ontology building life cycle. The Protégé OWL editor was used as a tool for building ADO in Ontology Web Language format. ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references. Validation of the lexicalized ontology by means of named entity recognition-based methods showed a satisfactory performance (F score = 72%). In addition to structural and functional evaluation, a clinical expert in the field performed a manual evaluation and curation of ADO. Through integration of ADO into an information retrieval environment, we show that the ontology supports semantic search in scientific text. The usefulness of ADO is authenticated by dedicated use case scenarios. Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

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 Advantages of Abstract Control Knowledge in Expert System Design. Technical Report #7.

ERIC Educational Resources Information Center

Clancey, William J.

This paper argues that an important design principle for building expert systems is to represent all control knowledge abstractly and separately from the domain knowledge upon which it operates. Abstract control knowledge is defined as the specifications of when and how a program is to carry out its operations, such as pursuing a goal, focusing,…

Generating target system specifications from a domain model using CLIPS

NASA Technical Reports Server (NTRS)

Sugumaran, Vijayan; Gomaa, Hassan; Kerschberg, Larry

1991-01-01

The quest for reuse in software engineering is still being pursued and researchers are actively investigating the domain modeling approach to software construction. There are several domain modeling efforts reported in the literature and they all agree that the components that are generated from domain modeling are more conducive to reuse. Once a domain model is created, several target systems can be generated by tailoring the domain model or by evolving the domain model and then tailoring it according to the specified requirements. This paper presents the Evolutionary Domain Life Cycle (EDLC) paradigm in which a domain model is created using multiple views, namely, aggregation hierarchy, generalization/specialization hierarchies, object communication diagrams and state transition diagrams. The architecture of the Knowledge Based Requirements Elicitation Tool (KBRET) which is used to generate target system specifications is also presented. The preliminary version of KBRET is implemented in the C Language Integrated Production System (CLIPS).

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

A RULE-BASED SYSTEM FOR EVALUATING FINAL COVERS FOR HAZARDOUS WASTE LANDFILLS

EPA Science Inventory

This chapter examines how rules are used as a knowledge representation formalism in the domain of hazardous waste management. A specific example from this domain involves performance evaluation of final covers used to close hazardous waste landfills. Final cover design and associ...

Semantic technologies in a decision support system

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2015-10-01

The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

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.

Comparing the Effects of Representational Tools in Collaborative and Individual Inquiry Learning

ERIC Educational Resources Information Center

Kolloffel, Bas; Eysink, Tessa H. S.; de Jong, Ton

2011-01-01

Constructing a representation in which students express their domain understanding can help them improve their knowledge. Many different representational formats can be used to express one's domain understanding (e.g., concept maps, textual summaries, mathematical equations). The format can direct students' attention to specific aspects of the…

Factors That Influence the Difficulty of Science Words

ERIC Educational Resources Information Center

Cervetti, Gina N.; Hiebert, Elfrieda H.; Pearson, P. David; McClung, Nicola A.

2015-01-01

This study examines, within the domain of science, the characteristics of words that predict word knowledge and word learning. The authors identified a set of word characteristics--length, part of speech, polysemy, frequency, morphological frequency, domain specificity, and concreteness--that, based on earlier research, were prime candidates to…

Representing and Inferring Visual Perceptual Skills in Dermatological Image Understanding

ERIC Educational Resources Information Center

Li, Rui

2013-01-01

Experts have a remarkable capability of locating, perceptually organizing, identifying, and categorizing objects in images specific to their domains of expertise. Eliciting and representing their visual strategies and some aspects of domain knowledge will benefit a wide range of studies and applications. For example, image understanding may be…

Mental Constructions and Constructions of Web Sites: Learner and Teacher Points of View

ERIC Educational Resources Information Center

Hazzan, Orit

2004-01-01

This research focuses on knowledge and ways in which knowledge may be constructed in the learner's mind. Specifically, it addresses the Web as a cognitive supporter for learning, organising and constructing a new domain of knowledge. In particular, the research analyses student reflection on constructing web sites. The analysis is based on an…

Conservation of species, volume, and belief in patients with Alzheimer's disease: the issue of domain specificity and conceptual impairment.

PubMed

Zaitchik, Deborah; Solomon, Gregg E A

2009-09-01

Two studies investigated whether patients with Alzheimer's disease (AD) suffer high-level and category-specific impairment in the conceptual domain of living things. In Experiment 1, AD patients and healthy young and healthy elderly controls took part in three tasks: the conservation of species, volume, and belief. All 3 tasks required tracking an object's identity in the face of irrelevant but salient transformations. Healthy young and elderly controls performed at or near ceiling on all tasks. AD patients were at or near ceiling on the volume and belief tasks, but only about half succeeded on the species task. Experiment 2 demonstrated that the results were not due to simple task demands. AD patients' failure to conserve species indicates that they are impaired in their theoretical understanding of living things, and their success on the volume and belief tasks suggests that the impairment is domain-specific. Two hypotheses are put forward to explain the phenomenon: The first, a category-specific account, holds that the intuitive theory of biology undergoes pervasive degradation; the second, a hybrid domain-general/domain-specific account, holds that impairment to domain-general processes such as executive function interacts with core cognition, the primitive elements that are the foundation of domain-specific knowledge.

Conservation of species, volume, and belief in patients with Alzheimer’s disease: the issue of domain-specificity and conceptual impairment

PubMed Central

Zaitchik, Deborah; Solomon, Gregg E. A.

2009-01-01

Two studies investigated whether patients with Alzheimer’s disease (AD) suffer high-level and category-specific impairment in the conceptual domain of living things. In Study 1, AD patients and healthy young and healthy elderly controls took part in three tasks: the Conservation of Species, Volume, and Belief. All 3 tasks required tracking an object’s identity in the face of irrelevant but salient transformations. Healthy young and elderly controls performed at or near ceiling on all tasks. AD patients were at or near ceiling on the Volume and Belief tasks, but only about half succeeded on the Species task. Study 2 demonstrated that the results were not due to simple task demands. AD patients’ failure to conserve species indicates that they are impaired in their theoretical understanding of living things, and their success on the Volume and Belief tasks suggests that the impairment is domain-specific. Two hypotheses are put forward to explain the phenomenon: the first, a category-specific account, holds that the intuitive theory of biology undergoes pervasive degradation; the second, a hybrid domain-general/domain-specific account, holds that impairment to domain-general processes such as executive function interacts with core cognition, the primitive elements that are the foundation of domain-specific knowledge. PMID:20043252

Musical Creativity “Revealed” in Brain Structure: Interplay between Motor, Default Mode, and Limbic Networks

PubMed Central

Bashwiner, David M.; Wertz, Christopher J.; Flores, Ranee A.; Jung, Rex E.

2016-01-01

Creative behaviors are among the most complex that humans engage in, involving not only highly intricate, domain-specific knowledge and skill, but also domain-general processing styles and the affective drive to create. This study presents structural imaging data indicating that musically creative people (as indicated by self-report) have greater cortical surface area or volume in a) regions associated with domain-specific higher-cognitive motor activity and sound processing (dorsal premotor cortex, supplementary and pre-supplementary motor areas, and planum temporale), b) domain-general creative-ideation regions associated with the default mode network (dorsomedial prefrontal cortex, middle temporal gyrus, and temporal pole), and c) emotion-related regions (orbitofrontal cortex, temporal pole, and amygdala). These findings suggest that domain-specific musical expertise, default-mode cognitive processing style, and intensity of emotional experience might all coordinate to motivate and facilitate the drive to create music. PMID:26888383

Individual Differences in Reprocessing of Text.

ERIC Educational Resources Information Center

Haenggi, Dieter; Perfetti, Charles A.

1992-01-01

Decoding, working memory, and domain-specific prior knowledge were studied as predictors of comprehension for 48 university undergraduate students after rewriting notes, rereading notes, or rereading a text. Working memory was most important for comprehension of text-implicit information, whereas knowledge was relatively more important for…

The relationship between immediate relevant basic science knowledge and clinical knowledge: physiology knowledge and transthoracic echocardiography image interpretation.

PubMed

Nielsen, Dorte Guldbrand; Gotzsche, Ole; Sonne, Ole; Eika, Berit

2012-10-01

Two major views on the relationship between basic science knowledge and clinical knowledge stand out; the Two-world view seeing basic science and clinical science as two separate knowledge bases and the encapsulated knowledge view stating that basic science knowledge plays an overt role being encapsulated in the clinical knowledge. However, resent research has implied that a more complex relationship between the two knowledge bases exists. In this study, we explore the relationship between immediate relevant basic science (physiology) and clinical knowledge within a specific domain of medicine (echocardiography). Twenty eight medical students in their 3rd year and 45 physicians (15 interns, 15 cardiology residents and 15 cardiology consultants) took a multiple-choice test of physiology knowledge. The physicians also viewed images of a transthoracic echocardiography (TTE) examination and completed a checklist of possible pathologies found. A total score for each participant was calculated for the physiology test, and for all physicians also for the TTE checklist. Consultants scored significantly higher on the physiology test than did medical students and interns. A significant correlation between physiology test scores and TTE checklist scores was found for the cardiology residents only. Basic science knowledge of immediate relevance for daily clinical work expands with increased work experience within a specific domain. Consultants showed no relationship between physiology knowledge and TTE interpretation indicating that experts do not use basic science knowledge in routine daily practice, but knowledge of immediate relevance remains ready for use.

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.

What the Logs Can Tell You: Mediation to Implement Feedback in Training

NASA Technical Reports Server (NTRS)

Maluf, David; Wiederhold, Gio; Abou-Khalil, Ali; Norvig, Peter (Technical Monitor)

2000-01-01

The problem addressed by Mediation to Implement Feedback in Training (MIFT) is to customize the feedback from training exercizes by exploiting knowledge about the training scenario, training objectives, and specific student/teacher needs. We achieve this by inserting an intelligent mediation layer into the information flow from observations collected during training exercises to the display and user interface. Knowledge about training objectives, scenarios, and tasks is maintained in the mediating layer. A designer constraint is that domain experts must be able to extend mediators by adding domain-specific knowledge that supports additional aggregations, abstractions, and views of the results of training exercises. The MIFT mediation concept is intended to be integrated with existing military training exercise management tools and reduce the cost of developing and maintaining separate feedback and evaluation tools for every training simulator and every set of customer needs. The MIFT Architecture is designed as a set of independently reusable components which interact with each other through standardized formalisms such as the Knowledge Interchange Format (KIF) and Knowledge Query and Manipulation Language (KQML).

A web-based system architecture for ontology-based data integration in the domain of IT benchmarking

NASA Astrophysics Data System (ADS)

Pfaff, Matthias; Krcmar, Helmut

2018-03-01

In the domain of IT benchmarking (ITBM), a variety of data and information are collected. Although these data serve as the basis for business analyses, no unified semantic representation of such data yet exists. Consequently, data analysis across different distributed data sets and different benchmarks is almost impossible. This paper presents a system architecture and prototypical implementation for an integrated data management of distributed databases based on a domain-specific ontology. To preserve the semantic meaning of the data, the ITBM ontology is linked to data sources and functions as the central concept for database access. Thus, additional databases can be integrated by linking them to this domain-specific ontology and are directly available for further business analyses. Moreover, the web-based system supports the process of mapping ontology concepts to external databases by introducing a semi-automatic mapping recommender and by visualizing possible mapping candidates. The system also provides a natural language interface to easily query linked databases. The expected result of this ontology-based approach of knowledge representation and data access is an increase in knowledge and data sharing in this domain, which will enhance existing business analysis methods.

Learning Search Control Knowledge for Deep Space Network Scheduling

NASA Technical Reports Server (NTRS)

Gratch, Jonathan; Chien, Steve; DeJong, Gerald

1993-01-01

While the general class of most scheduling problems is NP-hard in worst-case complexity, in practice, for specific distributions of problems and constraints, domain-specific solutions have been shown to perform in much better than exponential time.

An adaptive signal-processing approach to online adaptive tutoring.

PubMed

Bergeron, Bryan; Cline, Andrew

2011-01-01

Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

Teaching Thinking and Problem Solving.

ERIC Educational Resources Information Center

Bransford, John; And Others

1986-01-01

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

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

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.

Pedagogical Tools to Address Clinical Anatomy and Athletic Training Student Learning Styles

ERIC Educational Resources Information Center

Mazerolle, Stephanie; Yeargin, Susan

2010-01-01

Context: A thorough knowledge of anatomy is needed in four of the six domains of athletic training: prevention, injury/condition recognition, immediate care, and treatment/rehabilitation. Students with a solid foundation can achieve competency in these specific domains. Objective: To provide educators with pedagogical tools to promote a deeper…

Domain Specificity of Personal Epistemology: Resolved Questions, Persistent Issues, New Models

ERIC Educational Resources Information Center

Hofer, Barbara K.

2006-01-01

Beliefs that individuals hold about knowledge and knowing, or what has been termed ''personal epistemology'', are related to learning and achievement in complex ways. These beliefs are also differentiated by discipline (e.g., math, science, history) as well as by judgment domains (e.g., personal taste, morality, meaning). This commentary on five…

The Role of Human Expertise in Enhancing Data Mining

ERIC Educational Resources Information Center

Kaddouri, Abdelaaziz

2011-01-01

Current data mining (DM) technology is not domain-specific and therefore rarely generates reliable, business actionable knowledge that can be used to improve the effectiveness of the decision-making process in the banking industry. DM is mainly an autonomous, data-driven process with little focus on domain expertise, constraints, or requirements…

Evidentials and Source Knowledge in Turkish

ERIC Educational Resources Information Center

Aksu-Koc, Ayhan; Ogel-Balaban, Hale; Alp, Ercan

2009-01-01

Recent research has indicated that conceptual development in a specific domain may not be independent of the way it is mapped linguistically. We explore this claim in the semantic domain of evidentiality by considering various sets of data from Turkish-speaking children between one and a half to six years. We present evidence for (1) the…

Progress in knowledge representation research

NASA Technical Reports Server (NTRS)

Lum, Henry

1985-01-01

Brief descriptions are given of research being carried out in the field of knowledge representation. Dynamic simulation and modelling of planning systems with real-time sensor inputs; development of domain-independent knowledge representation tools which can be used in the development of application-specific expert and planning systems; and development of a space-borne very high speed integrated circuit processor are among the projects discussed.

Grammatical Difficulties in Children with Specific Language Impairment: Is Learning Deficient?

ERIC Educational Resources Information Center

Hsu, Hsinjen Julie; Bishop, Dorothy V. M.

2010-01-01

Theoretical accounts of grammatical limitations in specific language impairment (SLI) have been polarized between those that postulate problems with domain-specific grammatical knowledge, and those that regard grammatical deficits as downstream consequences of perceptual or memory limitations. Here we consider an alternative view that grammatical…

The relation between prior knowledge and students' collaborative discovery learning processes

NASA Astrophysics Data System (ADS)

Gijlers, Hannie; de Jong, Ton

2005-03-01

In this study we investigate how prior knowledge influences knowledge development during collaborative discovery learning. Fifteen dyads of students (pre-university education, 15-16 years old) worked on a discovery learning task in the physics field of kinematics. The (face-to-face) communication between students was recorded and the interaction with the environment was logged. Based on students' individual judgments of the truth-value and testability of a series of domain-specific propositions, a detailed description of the knowledge configuration for each dyad was created before they entered the learning environment. Qualitative analyses of two dialogues illustrated that prior knowledge influences the discovery learning processes, and knowledge development in a pair of students. Assessments of student and dyad definitional (domain-specific) knowledge, generic (mathematical and graph) knowledge, and generic (discovery) skills were related to the students' dialogue in different discovery learning processes. Results show that a high level of definitional prior knowledge is positively related to the proportion of communication regarding the interpretation of results. Heterogeneity with respect to generic prior knowledge was positively related to the number of utterances made in the discovery process categories hypotheses generation and experimentation. Results of the qualitative analyses indicated that collaboration between extremely heterogeneous dyads is difficult when the high achiever is not willing to scaffold information and work in the low achiever's zone of proximal development.

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

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.

Modularising ontology and designing inference patterns to personalise health condition assessment: the case of obesity.

PubMed

Sojic, Aleksandra; Terkaj, Walter; Contini, Giorgia; Sacco, Marco

2016-05-04

The public health initiatives for obesity prevention are increasingly exploiting the advantages of smart technologies that can register various kinds of data related to physical, physiological, and behavioural conditions. Since individual features and habits vary among people, the design of appropriate intervention strategies for motivating changes in behavioural patterns towards a healthy lifestyle requires the interpretation and integration of collected information, while considering individual profiles in a personalised manner. The ontology-based modelling is recognised as a promising approach in facing the interoperability and integration of heterogeneous information related to characterisation of personal profiles. The presented ontology captures individual profiles across several obesity-related knowledge-domains structured into dedicated modules in order to support inference about health condition, physical features, behavioural habits associated with a person, and relevant changes over time. The modularisation strategy is designed to facilitate ontology development, maintenance, and reuse. The domain-specific modules formalised in the Web Ontology Language (OWL) integrate the domain-specific sets of rules formalised in the Semantic Web Rule Language (SWRL). The inference rules follow a modelling pattern designed to support personalised assessment of health condition as age- and gender-specific. The test cases exemplify a personalised assessment of the obesity-related health conditions for the population of teenagers. The paper addresses several issues concerning the modelling of normative concepts related to obesity and depicts how the public health concern impacts classification of teenagers according to their phenotypes. The modelling choices regarding the ontology-structure are explained in the context of the modelling goal to integrate multiple knowledge-domains and support reasoning about the individual changes over time. The presented modularisation pattern enhances reusability of the domain-specific modules across various health care domains.

Common Ground? How the Encoding of Specialist Vocabulary Affects Peer-to-Peer Online Discourse

ERIC Educational Resources Information Center

Paus, Elisabeth; Jucks, Regina

2012-01-01

Using the same specialist terms in online discourse can indicate knowledge overlaps between partners. However, linguistic overlaps do not automatically ensure overlaps in conceptual representations. In particular, learning situations, which typically focus on knowledge acquisition, require a sufficient understanding of domain-specific concepts.…

Expert Views on TPACK for Early Literacy: Priorities for Teacher Education

ERIC Educational Resources Information Center

McKenney, Susan; Voogt, Joke

2017-01-01

Technology applications can make important contributions to improving learning outcomes in the domain of early literacy. However, to fully exploit the potential of educational technologies, teachers must have specific knowledge and skills. This study aimed to articulate the technological pedagogical content knowledge teachers need to make…

The Novice-Expert Continuum in Astronomy Knowledge

ERIC Educational Resources Information Center

Bryce, T. G. K.; Blown, E. J.

2012-01-01

The nature of expertise in astronomy was investigated across a broad spectrum of ages and experience in China and New Zealand. Five hypotheses (capable of quantification and statistical analysis) were used to probe types of expertise identified by previous researchers: (a) domain-specific knowledge-skill in the use of scientific vocabulary and…

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

The effect of expert knowledge on medical search: medical experts have specialized abilities for detecting serious lesions.

PubMed

Nakashima, Ryoichi; Watanabe, Chisaki; Maeda, Eriko; Yoshikawa, Takeharu; Matsuda, Izuru; Miki, Soichiro; Yokosawa, Kazuhiko

2015-09-01

How does domain-specific knowledge influence the experts' performance in their domain of expertise? Specifically, can visual search experts find, with uniform efficiency, any type of target in their domain of expertise? We examined whether acquired knowledge of target importance influences an expert's visual search performance. In some professional searches (e.g., medical screenings), certain targets are rare; one aim of this study was to examine the extent to which experts miss such targets in their searches. In one experiment, radiologists (medical experts) engaged in a medical lesion search task in which both the importance (i.e., seriousness/gravity) and the prevalence of targets varied. Results showed decreased target detection rates in the low prevalence conditions (i.e., the prevalence effect). Also, experts were better at detecting important (versus unimportant) lesions. Results of an experiment using novices ruled out the possibility that decreased performance with unimportant targets was due to low target noticeability/visibility. Overall, the findings suggest that radiologists do not have a generalized ability to detect any type of lesion; instead, they have acquired a specialized ability to detect only those important lesions relevant for effective medical practices.

Walking and cycling for commuting, leisure and errands: relations with individual characteristics and leisure-time physical activity in a cross-sectional survey (the ACTI-Cités project).

PubMed

Menai, Mehdi; Charreire, Hélène; Feuillet, Thierry; Salze, Paul; Weber, Christiane; Enaux, Christophe; Andreeva, Valentina A; Hercberg, Serge; Nazare, Julie-Anne; Perchoux, Camille; Simon, Chantal; Oppert, Jean-Michel

2015-12-09

Increasing active transport behavior (walking, cycling) throughout the life-course is a key element of physical activity promotion for health. There is, however, a need to better understand the correlates of specific domains of walking and cycling to identify more precisely at-risk populations for public health interventions. In addition, current knowledge of interactions between domains of walking and cycling remains limited. We assessed past-month self-reported time spent walking and cycling in three specific domains (commuting, leisure and errands) in 39,295 French adult participants (76.5% women) of the on-going NutriNet Santé web-cohort. Multivariate logistic regression models were used to investigate the associations with socio-demographic and physical activity correlates. Having a transit pass was strongly positively associated with walking for commuting and for errands but was unrelated to walking for leisure or to all domains of cycling. Having a parking space at work was strongly negatively associated with walking for commuting and cycling for commuting. BMI was negatively associated with both walking for leisure and errands, and with the three domains of cycling. Leisure-time physical activity was negatively associated with walking for commuting but was positively associated with the two other domains of walking and with cycling (three domains). Walking for commuting was positively associated with the other domains of walking; cycling for commuting was also positively associated with the other domains of cycling. Walking for commuting was not associated with cycling for commuting. In adults walking and cycling socio-demographic and physical activity correlates differ by domain (commuting, leisure and errands). Better knowledge of relationships between domains should help to develop interventions focusing not only the right population, but also the right behavior.

Domain Generality and Specificity in Children's Causal Inference about Ambiguous Data

ERIC Educational Resources Information Center

Sobel, David M.; Munro, Sarah E.

2009-01-01

In 5 experiments the authors examined children's understanding of causal mechanisms and their reasoning about base rates across domains of knowledge. Experiment 1 showed that 3-year-olds interpret objects activating a machine differently from a novel agent liking each object; children are more likely to treat the latter as indicating the objects…

Teaching towards Historical Expertise. Developing a Pedagogy for Fostering Causal Reasoning in History

ERIC Educational Resources Information Center

Stoel, G. L.; van Drie, J. P.; van Boxtel, C. A. M.

2015-01-01

The present study seeks to develop a pedagogy aimed at fostering a student's ability to reason causally about history. The Model of Domain Learning was used as a framework to align domain-specific content with pedagogical principles. Developing causal historical reasoning was conceptualized as a multidimensional process, in which knowledge of…

The Role of Domain-Specific Knowledge in Generative Reasoning about Complicated Multileveled Phenomena

ERIC Educational Resources Information Center

Duncan, Ravit Golan

2007-01-01

Promoting the ability to reason generatively about novel phenomena and problems students may encounter in their everyday lives is a major goal of science education. This goal proves to be a formidable challenge in domains, such as molecular genetics, for which the accumulated scientific understandings are daunting in both amount and complexity. To…

Data Mining and Domain Knowledge: An Exploration of Methods to Advance Medical Research

ERIC Educational Resources Information Center

Engle, Kelley M.

2013-01-01

Researchers in the medical domain consider the double-blind placebo controlled clinical trial the gold standard. The data for these clinical trials are collected for a specifically defined hypothesis and there is very little in the realm of secondary data analyses conducted. The underlying purpose of this work is to demonstrate the value and…

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

SLEEC: Semantics-Rich Libraries for Effective Exascale Computation. Final Technical Report

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

Milind, Kulkarni

SLEEC (Semantics-rich Libraries for Effective Exascale Computation) was a project funded by the Department of Energy X-Stack Program, award number DE-SC0008629. The initial project period was September 2012–August 2015. The project was renewed for an additional year, expiring August 2016. Finally, the project received a no-cost extension, leading to a final expiry date of August 2017. Modern applications, especially those intended to run at exascale, are not written from scratch. Instead, they are built by stitching together various carefully-written, hand-tuned libraries. Correctly composing these libraries is difficult, but traditional compilers are unable to effectively analyze and transform across abstraction layers.more » Domain specific compilers integrate semantic knowledge into compilers, allowing them to transform applications that use particular domain-specific languages, or domain libraries. But they do not help when new domains are developed, or applications span multiple domains. SLEEC aims to fix these problems. To do so, we are building generic compiler and runtime infrastructures that are semantics-aware but not domain-specific. By performing optimizations related to the semantics of a domain library, the same infrastructure can be made generic and apply across multiple domains.« 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.

Premorbid Expertise Produces Category-Specific Impairment in a Domain-General Semantic Disorder

ERIC Educational Resources Information Center

Jefferies, Elizabeth; Rogers, Timothy T.; Ralph, Matthew A. Lambon

2011-01-01

For decades, category-specific semantic impairment--i.e., better comprehension of items from one semantic category than another--has been the driving force behind many claims about the organisation of conceptual knowledge in the brain. Double dissociations between patients with category-specific disorders are widely interpreted as showing that…

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.

A FYVE zinc finger domain protein specifically links mRNA transport to endosome trafficking.

PubMed

Pohlmann, Thomas; Baumann, Sebastian; Haag, Carl; Albrecht, Mario; Feldbrügge, Michael

2015-05-18

An emerging theme in cellular logistics is the close connection between mRNA and membrane trafficking. A prominent example is the microtubule-dependent transport of mRNAs and associated ribosomes on endosomes. This coordinated process is crucial for correct septin filamentation and efficient growth of polarised cells, such as fungal hyphae. Despite detailed knowledge on the key RNA-binding protein and the molecular motors involved, it is unclear how mRNAs are connected to membranes during transport. Here, we identify a novel factor containing a FYVE zinc finger domain for interaction with endosomal lipids and a new PAM2-like domain required for interaction with the MLLE domain of the key RNA-binding protein. Consistently, loss of this FYVE domain protein leads to specific defects in mRNA, ribosome, and septin transport without affecting general functions of endosomes or their movement. Hence, this is the first endosomal component specific for mRNP trafficking uncovering a new mechanism to couple mRNPs to endosomes.

Sentiment Analysis Using Common-Sense and Context Information

PubMed Central

Mittal, Namita; Bansal, Pooja; Garg, Sonal

2015-01-01

Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods. PMID:25866505

Sentiment analysis using common-sense and context information.

PubMed

Agarwal, Basant; Mittal, Namita; Bansal, Pooja; Garg, Sonal

2015-01-01

Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods.

When Relationships Depicted Diagrammatically Conflict with Prior Knowledge: An Investigation of Students' Interpretations of Evolutionary Trees

ERIC Educational Resources Information Center

Novick, Laura R.; Catley, Kefyn M.

2014-01-01

Science is an important domain for investigating students' responses to information that contradicts their prior knowledge. In previous studies of this topic, this information was communicated verbally. The present research used diagrams, specifically trees (cladograms) depicting evolutionary relationships among taxa. Effects of college…

The Relations between Scientific Epistemological Beliefs and Goal Orientations of Pre-Service Teachers

ERIC Educational Resources Information Center

Kaya, Gamze Inan

2017-01-01

The purpose of this study was to investigate the relations between pre-service teachers' scientific epistemological beliefs and goal orientations in 2X2 framework. Scientific epistemological beliefs are domain-specific views of people about nature and acquisition of scientific knowledge, how scientific knowledge is produced, how reliable and valid…

Epistemic Metacognition in Context: Evaluating and Learning Online Information

ERIC Educational Resources Information Center

Mason, Lucia; Boldrin, Angela; Ariasi, Nicola

2010-01-01

This study examined epistemic metacognition as a reflective activity about knowledge and knowing in the context of online information searching on the Web, and whether it was related to prior knowledge on the topic, study approach, and domain-specific beliefs about science. In addition, we investigated whether Internet-based learning was…

The Influence of Instruction, Prior Knowledge, and Values on Climate Change Risk Perception among Undergraduates

ERIC Educational Resources Information Center

Aksit, Osman; McNeal, Karen S.; Gold, Anne U.; Libarkin, Julie C.; Harris, Sara

2018-01-01

We evaluated influences on the climate change risk perceptions of undergraduate students in an introductory Earth Science course. For this sample, domain-specific content knowledge about climate change was a significant predictor of students' risk perception of climate change while cultural worldviews (individualism, hierarchy) and political…

Specification, Design, and Analysis of Advanced HUMS Architectures

NASA Technical Reports Server (NTRS)

Mukkamala, Ravi

2004-01-01

During the two-year project period, we have worked on several aspects of domain-specific architectures for HUMS. In particular, we looked at using scenario-based approach for the design and designed a language for describing such architectures. The language is now being used in all aspects of our HUMS design. In particular, we have made contributions in the following areas. 1) We have employed scenarios in the development of HUMS in three main areas. They are: (a) To improve reusability by using scenarios as a library indexing tool and as a domain analysis tool; (b) To improve maintainability by recording design rationales from two perspectives - problem domain and solution domain; (c) To evaluate the software architecture. 2) We have defined a new architectural language called HADL or HUMS Architectural Definition Language. It is a customized version of xArch/xADL. It is based on XML and, hence, is easily portable from domain to domain, application to application, and machine to machine. Specifications written in HADL can be easily read and parsed using the currently available XML parsers. Thus, there is no need to develop a plethora of software to support HADL. 3) We have developed an automated design process that involves two main techniques: (a) Selection of solutions from a large space of designs; (b) Synthesis of designs. However, the automation process is not an absolute Artificial Intelligence (AI) approach though it uses a knowledge-based system that epitomizes a specific HUMS domain. The process uses a database of solutions as an aid to solve the problems rather than creating a new design in the literal sense. Since searching is adopted as the main technique, the challenges involved are: (a) To minimize the effort in searching the database where a very large number of possibilities exist; (b) To develop representations that could conveniently allow us to depict design knowledge evolved over many years; (c) To capture the required information that aid the automation process.

Learning the facts in medical school is not enough: which factors predict successful application of procedural knowledge in a laboratory setting?

PubMed

Schmidmaier, Ralf; Eiber, Stephan; Ebersbach, Rene; Schiller, Miriam; Hege, Inga; Holzer, Matthias; Fischer, Martin R

2013-02-22

Medical knowledge encompasses both conceptual (facts or "what" information) and procedural knowledge ("how" and "why" information). Conceptual knowledge is known to be an essential prerequisite for clinical problem solving. Primarily, medical students learn from textbooks and often struggle with the process of applying their conceptual knowledge to clinical problems. Recent studies address the question of how to foster the acquisition of procedural knowledge and its application in medical education. However, little is known about the factors which predict performance in procedural knowledge tasks. Which additional factors of the learner predict performance in procedural knowledge? Domain specific conceptual knowledge (facts) in clinical nephrology was provided to 80 medical students (3rd to 5th year) using electronic flashcards in a laboratory setting. Learner characteristics were obtained by questionnaires. Procedural knowledge in clinical nephrology was assessed by key feature problems (KFP) and problem solving tasks (PST) reflecting strategic and conditional knowledge, respectively. Results in procedural knowledge tests (KFP and PST) correlated significantly with each other. In univariate analysis, performance in procedural knowledge (sum of KFP+PST) was significantly correlated with the results in (1) the conceptual knowledge test (CKT), (2) the intended future career as hospital based doctor, (3) the duration of clinical clerkships, and (4) the results in the written German National Medical Examination Part I on preclinical subjects (NME-I). After multiple regression analysis only clinical clerkship experience and NME-I performance remained independent influencing factors. Performance in procedural knowledge tests seems independent from the degree of domain specific conceptual knowledge above a certain level. Procedural knowledge may be fostered by clinical experience. More attention should be paid to the interplay of individual clinical clerkship experiences and structured teaching of procedural knowledge and its assessment in medical education curricula.

Varieties of (Scientific) Creativity: A Hierarchical Model of Domain-Specific Disposition, Development, and Achievement.

PubMed

Simonton, Dean Keith

2009-09-01

Prior research supports the inference that scientific disciplines can be ordered into a hierarchy ranging from the "hard" natural sciences to the "soft" social sciences. This ordering corresponds with such objective criteria as disciplinary consensus, knowledge obsolescence rate, anticipation frequency, theories-to-laws ratio, lecture disfluency, and age at recognition. It is then argued that this hierarchy can be extrapolated to encompass the humanities and arts and interpolated within specific domains to accommodate contrasts in subdomains (e.g., revolutionary versus normal science). This expanded and more finely differentiated hierarchy is then shown to have a partial psychological basis in terms of dispositional traits (e.g., psychopathology) and developmental experiences (e.g., family background). This demonstration then leads to three hypotheses about how a creator's domain-specific impact depends on his or her disposition and development: the domain-progressive, domain-typical, and domain-regressive creator hypotheses. Studies published thus far lend the most support to the domain-regressive creator hypothesis. In particular, major contributors to a domain are more likely to have dispositional traits and developmental experiences most similar to those that prevail in a domain lower in the disciplinary hierarchy. However, some complications to this generalization suggest the need for more research on the proposed hierarchical model. © 2009 Association for Psychological Science.

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.

Goal specificity and knowledge acquisition in statistics problem solving: evidence for attentional focus.

PubMed

Trumpower, David L; Goldsmith, Timothy E; Guynn, Melissa J

2004-12-01

Solving training problems with nonspecific goals (NG; i.e., solving for all possible unknown values) often results in better transfer than solving training problems with standard goals (SG; i.e., solving for one particular unknown value). In this study, we evaluated an attentional focus explanation of the goal specificity effect. According to the attentional focus view, solving NG problems causes attention to be directed to local relations among successive problem states, whereas solving SG problems causes attention to be directed to relations between the various problem states and the goal state. Attention to the former is thought to enhance structural knowledge about the problem domain and thus promote transfer. Results supported this view because structurally different transfer problems were solved faster following NG training than following SG training. Moreover, structural knowledge representations revealed more links depicting local relations following NG training and more links to the training goal following SG training. As predicted, these effects were obtained only by domain novices.

Knowledge-Directed Theory Revision

NASA Astrophysics Data System (ADS)

Ali, Kamal; Leung, Kevin; Konik, Tolga; Choi, Dongkyu; Shapiro, Dan

Using domain knowledge to speed up learning is widely accepted but theory revision of such knowledge continues to use general syntactic operators. Using such operators for theory revision of teleoreactive logic programs is especially expensive in which proof of a top-level goal involves playing a game. In such contexts, one should have the option to complement general theory revision with domain-specific knowledge. Using American football as an example, we use Icarus' multi-agent teleoreactive logic programming ability to encode a coach agent whose concepts correspond to faults recognized in execution of the play and whose skills correspond to making repairs in the goals of the player agents. Our results show effective learning using as few as twenty examples. We also show that structural changes made by such revision can produce performance gains that cannot be matched by doing only numeric optimization.

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

Semantic layers for illustrative volume rendering.

PubMed

Rautek, Peter; Bruckner, Stefan; Gröller, Eduard

2007-01-01

Direct volume rendering techniques map volumetric attributes (e.g., density, gradient magnitude, etc.) to visual styles. Commonly this mapping is specified by a transfer function. The specification of transfer functions is a complex task and requires expert knowledge about the underlying rendering technique. In the case of multiple volumetric attributes and multiple visual styles the specification of the multi-dimensional transfer function becomes more challenging and non-intuitive. We present a novel methodology for the specification of a mapping from several volumetric attributes to multiple illustrative visual styles. We introduce semantic layers that allow a domain expert to specify the mapping in the natural language of the domain. A semantic layer defines the mapping of volumetric attributes to one visual style. Volumetric attributes and visual styles are represented as fuzzy sets. The mapping is specified by rules that are evaluated with fuzzy logic arithmetics. The user specifies the fuzzy sets and the rules without special knowledge about the underlying rendering technique. Semantic layers allow for a linguistic specification of the mapping from attributes to visual styles replacing the traditional transfer function specification.

Sex Differences in General Knowledge: Meta-Analysis and New Data on the Contribution of School-Related Moderators among High-School Students

PubMed Central

Tran, Ulrich S.; Hofer, Agnes A.; Voracek, Martin

2014-01-01

Research from various countries consistently reported an advantage of boys over girls in general knowledge and was also suggestive of some overall trends regarding specific domains of general knowledge that were speculated to stem from biologically differentiated interests. However, results were heterogeneous and, as of yet, had not been evaluated meta-analytically. Moreover, previous research drew on overly homogeneous high-school or undergraduate samples whose representativeness appears problematic; mostly, likely moderators, such as school type, student age or parental education, were also not directly investigated or controlled for. We provide a meta-analytical aggregation of available results regarding sex differences in general knowledge and present new data, investigating the psychometric properties of the General Knowledge Test (GKT), on which previous research primarily relied, and explored sex differences in a large and heterogeneous Austrian high-school student sample (N = 1088). The aggregated sex effect in general knowledge was of medium size in previous research, but differences in specific domains were heterogeneous across countries and only modest at best. Large sex differences in our data could be explained to a large part by school-related moderators (school type, school, student age, parental education) and selection processes. Boys had a remaining advantage over girls that was only small in size and that was consistent with the magnitude of sex differences in general intelligence. Analysis of the GKT yielded no evidence of biologically differentiated interests, but of a specific interest in the humanities among girls. In conclusion, previous research likely overestimated sex differences in general knowledge. PMID:25347190

Sex differences in general knowledge: meta-analysis and new data on the contribution of school-related moderators among high-school students.

PubMed

Tran, Ulrich S; Hofer, Agnes A; Voracek, Martin

2014-01-01

Research from various countries consistently reported an advantage of boys over girls in general knowledge and was also suggestive of some overall trends regarding specific domains of general knowledge that were speculated to stem from biologically differentiated interests. However, results were heterogeneous and, as of yet, had not been evaluated meta-analytically. Moreover, previous research drew on overly homogeneous high-school or undergraduate samples whose representativeness appears problematic; mostly, likely moderators, such as school type, student age or parental education, were also not directly investigated or controlled for. We provide a meta-analytical aggregation of available results regarding sex differences in general knowledge and present new data, investigating the psychometric properties of the General Knowledge Test (GKT), on which previous research primarily relied, and explored sex differences in a large and heterogeneous Austrian high-school student sample (N = 1088). The aggregated sex effect in general knowledge was of medium size in previous research, but differences in specific domains were heterogeneous across countries and only modest at best. Large sex differences in our data could be explained to a large part by school-related moderators (school type, school, student age, parental education) and selection processes. Boys had a remaining advantage over girls that was only small in size and that was consistent with the magnitude of sex differences in general intelligence. Analysis of the GKT yielded no evidence of biologically differentiated interests, but of a specific interest in the humanities among girls. In conclusion, previous research likely overestimated sex differences in general knowledge.

Semantic Relevance, Domain Specificity and the Sensory/Functional Theory of Category-Specificity

ERIC Educational Resources Information Center

Sartori, Giuseppe; Gnoato, Francesca; Mariani, Ilenia; Prioni, Sara; Lombardi, Luigi

2007-01-01

According to the sensory/functional theory of semantic memory, Living items rely more on Sensory knowledge than Non-living ones. The sensory/functional explanation of category-specificity assumes that semantic features are organised on the basis of their content. We report here a study on DAT patients with impaired performance on Living items and…

A methodology for evaluation of a markup-based specification of clinical guidelines.

PubMed

Shalom, Erez; Shahar, Yuval; Taieb-Maimon, Meirav; Lunenfeld, Eitan

2008-11-06

We introduce a three-phase, nine-step methodology for specification of clinical guidelines (GLs) by expert physicians, clinical editors, and knowledge engineers, and for quantitative evaluation of the specification's quality. We applied this methodology to a particular framework for incremental GL structuring (mark-up) and to GLs in three clinical domains with encouraging results.

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.

Simultaneous prediction of binding free energy and specificity for PDZ domain-peptide interactions

NASA Astrophysics Data System (ADS)

Crivelli, Joseph J.; Lemmon, Gordon; Kaufmann, Kristian W.; Meiler, Jens

2013-12-01

Interactions between protein domains and linear peptides underlie many biological processes. Among these interactions, the recognition of C-terminal peptides by PDZ domains is one of the most ubiquitous. In this work, we present a mathematical model for PDZ domain-peptide interactions capable of predicting both affinity and specificity of binding based on X-ray crystal structures and comparative modeling with R osetta. We developed our mathematical model using a large phage display dataset describing binding specificity for a wild type PDZ domain and 91 single mutants, as well as binding affinity data for a wild type PDZ domain binding to 28 different peptides. Structural refinement was carried out through several R osetta protocols, the most accurate of which included flexible peptide docking and several iterations of side chain repacking and backbone minimization. Our findings emphasize the importance of backbone flexibility and the energetic contributions of side chain-side chain hydrogen bonds in accurately predicting interactions. We also determined that predicting PDZ domain-peptide interactions became increasingly challenging as the length of the peptide increased in the N-terminal direction. In the training dataset, predicted binding energies correlated with those derived through calorimetry and specificity switches introduced through single mutations at interface positions were recapitulated. In independent tests, our best performing protocol was capable of predicting dissociation constants well within one order of magnitude of the experimental values and specificity profiles at the level of accuracy of previous studies. To our knowledge, this approach represents the first integrated protocol for predicting both affinity and specificity for PDZ domain-peptide interactions.

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

ERIC Educational Resources Information Center

Stranieri, Andrew; Yearwood, John

2008-01-01

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

Professional Knowledge Required When Teaching Mathematics for Numeracy in the Multiplicative Domain

ERIC Educational Resources Information Center

Mills, Judith

2015-01-01

This paper presents findings as part of a wider study that investigated the professional knowledge of teachers when teaching mathematics for numeracy in the primary school classroom. This paper focuses on teachers in action as they taught two lessons on multiplication. It outlines the specific pedagogical categories the teachers used and the…

Objective and Subjective Knowledge and HIV Testing among College Students

ERIC Educational Resources Information Center

Hou, Su-I

2004-01-01

Little research has been conducted on the knowledge domain specifically related to HIV testing among college students. Students (age 18-24) were recruited from a major university in the southeastern United States to participate in a Web-based survey during spring 2003 (N=440). About 21% of the students reported previous voluntary HIV tests.…

The Role of E-Vocabularies in the Description and Retrieval of Digital Educational Resources

ERIC Educational Resources Information Center

Fernández-Pampillón, Ana M.

2017-01-01

Vocabularies are linguistic resources that make it possible to access knowledge through words. They can constitute a mechanism to identify, describe, explore, and access all the digital resources with informational content pertaining to a specific knowledge domain. In this regard, they play a key role as systems for the representation and…

Does Problem Solving = Prior Knowledge + Reasoning Skills in Earth Science? An Exploratory Study

ERIC Educational Resources Information Center

Chang, Chun-Yen

2010-01-01

This study examined the interrelationship between tenth-grade students' problem solving ability (PSA) and their domain-specific knowledge (DSK) as well as reasoning skills (RS) in a secondary school of Taiwan. The PSA test was designed to emphasize students' divergent-thinking ability (DTA) and convergent-thinking ability (CTA) subscales in the…

The Role of Opportunities to Learn in Teacher Preparation for EFL Teachers' Pedagogical Content Knowledge

ERIC Educational Resources Information Center

König, Johannes; Tachtsoglou, Sarantis; Lammerding, Sandra; Strauß, Sarah; Nold, Günter; Rohde, Andreas

2017-01-01

The study examines the connection between domain-specific learning opportunities in English as a foreign language (EFL) teacher preparation and preservice EFL teachers' pedagogical content knowledge (PCK). Using a sample of 444 preservice EFL teachers for secondary schools, it contrasts groups at the end of the 2 phases required in German teacher…

Using a Word Association Test for the Assessment of High School Students' Cognitive Structures on Dissolution

ERIC Educational Resources Information Center

Derman, Aysegul; Eilks, Ingo

2016-01-01

Understanding students' cognitive structures in a specific knowledge domain helps to determine the ''what, how and why'' features of such knowledge, so that we can take these structures into consideration in teaching. The purpose of the present study was to identify students' cognitive structures about solution and dissolution concepts. The study…

Statistical Word Learning in Children with Autism Spectrum Disorder and Specific Language Impairment

ERIC Educational Resources Information Center

Haebig, Eileen; Saffran, Jenny R.; Ellis Weismer, Susan

2017-01-01

Background: Word learning is an important component of language development that influences child outcomes across multiple domains. Despite the importance of word knowledge, word-learning mechanisms are poorly understood in children with specific language impairment (SLI) and children with autism spectrum disorder (ASD). This study examined…

Arabic Morphology in the Neural Language System

ERIC Educational Resources Information Center

Boudelaa, Sami; Pulvermuller, Friedemann; Hauk, Olaf; Shtyrov, Yury; Marslen-Wilson, William

2010-01-01

There are two views about morphology, the aspect of language concerned with the internal structure of words. One view holds that morphology is a domain of knowledge with a specific type of neurocognitive representation supported by specific brain mechanisms lateralized to left fronto-temporal cortex. The alternate view characterizes morphological…

Development of a Palliative Education Assessment Tool for Medical Student Education.

ERIC Educational Resources Information Center

Meekin, Sharon Abele; Klein, Jason E.; Fleischman, Alan R.; Fins, Joseph J.

2000-01-01

Describes the Palliative Education Assessment Tool (PEAT), an innovative assessment to facilitate curricular mapping of palliative care education. The PEAT comprises seven palliative care domains, each of which details specific objectives of knowledge, skills, and attitudes. PEAT enables educators to describe a specific multidimensional aspect of…

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

PubMed

Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

2014-07-01

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. © 2013 Wiley Periodicals, Inc.

Class Model Development Using Business Rules

NASA Astrophysics Data System (ADS)

Skersys, Tomas; Gudas, Saulius

New developments in the area of computer-aided system engineering (CASE) greatly improve processes of the information systems development life cycle (ISDLC). Much effort is put into the quality improvement issues, but IS development projects still suffer from the poor quality of models during the system analysis and design cycles. At some degree, quality of models that are developed using CASE tools can be assured using various. automated. model comparison, syntax. checking procedures. It. is also reasonable to check these models against the business domain knowledge, but the domain knowledge stored in the repository of CASE tool (enterprise model) is insufficient (Gudas et al. 2004). Involvement of business domain experts into these processes is complicated because non- IT people often find it difficult to understand models that were developed by IT professionals using some specific modeling language.

Improving Cyber-Security of Smart Grid Systems via Anomaly Detection and Linguistic Domain Knowledge

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

Ondrej Linda; Todd Vollmer; Milos Manic

The planned large scale deployment of smart grid network devices will generate a large amount of information exchanged over various types of communication networks. The implementation of these critical systems will require appropriate cyber-security measures. A network anomaly detection solution is considered in this work. In common network architectures multiple communications streams are simultaneously present, making it difficult to build an anomaly detection solution for the entire system. In addition, common anomaly detection algorithms require specification of a sensitivity threshold, which inevitably leads to a tradeoff between false positives and false negatives rates. In order to alleviate these issues, thismore » paper proposes a novel anomaly detection architecture. The designed system applies the previously developed network security cyber-sensor method to individual selected communication streams allowing for learning accurate normal network behavior models. Furthermore, the developed system dynamically adjusts the sensitivity threshold of each anomaly detection algorithm based on domain knowledge about the specific network system. It is proposed to model this domain knowledge using Interval Type-2 Fuzzy Logic rules, which linguistically describe the relationship between various features of the network communication and the possibility of a cyber attack. The proposed method was tested on experimental smart grid system demonstrating enhanced cyber-security.« less

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.

Autonomous Vehicle Mission Planning Using AI (Artificial Intelligence) Techniques.

DTIC Science & Technology

1985-12-01

it uses are declarative patterns that encode facts about how goals may give rise to - . plans. The program processes a story a sentence at a time...the planning process. By separating the knowledge about how to plan from the specific domain knowledge, an understander can use this knowledge about how ...path planning program developed in a previous thesis effort will be incorporated into the overall program in order to demonstrate the operating system

A Domain-Specific System for Representing Knowledge of Both Man-Made Objects and Human Actions. Evidence from a Case with an Association of Deficits

ERIC Educational Resources Information Center

Vannuscorps, Gilles; Pillon, Agnesa

2011-01-01

We report the single-case study of a brain-damaged individual, JJG, presenting with a conceptual deficit and whose knowledge of living things, man-made objects, and actions was assessed. The aim was to seek for empirical evidence pertaining to the issue of how conceptual knowledge of objects, both living things and man-made objects, is related to…

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.

Domain-independent information extraction in unstructured text

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

Irwin, N.H.

Extracting information from unstructured text has become an important research area in recent years due to the large amount of text now electronically available. This status report describes the findings and work done during the second year of a two-year Laboratory Directed Research and Development Project. Building on the first-year`s work of identifying important entities, this report details techniques used to group words into semantic categories and to output templates containing selective document content. Using word profiles and category clustering derived during a training run, the time-consuming knowledge-building task can be avoided. Though the output still lacks in completeness whenmore » compared to systems with domain-specific knowledge bases, the results do look promising. The two approaches are compatible and could complement each other within the same system. Domain-independent approaches retain appeal as a system that adapts and learns will soon outpace a system with any amount of a priori knowledge.« less

A FYVE zinc finger domain protein specifically links mRNA transport to endosome trafficking

PubMed Central

Pohlmann, Thomas; Baumann, Sebastian; Haag, Carl; Albrecht, Mario; Feldbrügge, Michael

2015-01-01

An emerging theme in cellular logistics is the close connection between mRNA and membrane trafficking. A prominent example is the microtubule-dependent transport of mRNAs and associated ribosomes on endosomes. This coordinated process is crucial for correct septin filamentation and efficient growth of polarised cells, such as fungal hyphae. Despite detailed knowledge on the key RNA-binding protein and the molecular motors involved, it is unclear how mRNAs are connected to membranes during transport. Here, we identify a novel factor containing a FYVE zinc finger domain for interaction with endosomal lipids and a new PAM2-like domain required for interaction with the MLLE domain of the key RNA-binding protein. Consistently, loss of this FYVE domain protein leads to specific defects in mRNA, ribosome, and septin transport without affecting general functions of endosomes or their movement. Hence, this is the first endosomal component specific for mRNP trafficking uncovering a new mechanism to couple mRNPs to endosomes. DOI: http://dx.doi.org/10.7554/eLife.06041.001 PMID:25985087

When concepts lose their color: A case of object color knowledge impairment

PubMed Central

Stasenko, Alena; Garcea, Frank E.; Dombovy, Mary; Mahon, Bradford Z.

2014-01-01

Color is important in our daily interactions with objects, and plays a role in both low- and high-level visual processing. Previous neuropsychological studies have shown that color perception and object-color knowledge can doubly dissociate, and that both can dissociate from processing of object form. We present a case study of an individual who displayed an impairment for knowledge of the typical colors of objects, with preserved color perception and color naming. Our case also presented with a pattern of, if anything, worse performance for naming living items compared to nonliving things. The findings of the experimental investigation are evaluated in light of two theories of conceptual organization in the brain: the Sensory Functional Theory and the Domain-Specific Hypothesis. The dissociations observed in this case compel a model in which sensory/motor modality and semantic domain jointly constrain the organization of object knowledge. PMID:25058612

Domain Specific Language Support for Exascale

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

Mellor-Crummey, John

A multi-institutional project known as D-TEC (short for “Domain- specific Technology for Exascale Computing”) set out to explore technologies to support the construction of Domain Specific Languages (DSLs) to map application programs to exascale architectures. DSLs employ automated code transformation to shift the burden of delivering portable performance from application programmers to compilers. Two chief properties contribute: DSLs permit expression at a high level of abstraction so that a programmer’s intent is clear to a compiler and DSL implementations encapsulate human domain-specific optimization knowledge so that a compiler can be smart enough to achieve good results on specific hardware. Domainmore » specificity is what makes these properties possible in a programming language. If leveraging domain specificity is the key to keep exascale software tractable, a corollary is that many different DSLs will be needed to encompass the full range of exascale computing applications; moreover, a single application may well need to use several different DSLs in conjunction. As a result, developing a general toolkit for building domain-specific languages was a key goal for the D-TEC project. Different aspects of the D-TEC research portfolio were the focus of work at each of the partner institutions in the multi-institutional project. D-TEC research and development work at Rice University focused on on three principal topics: understanding how to automate the tuning of code for complex architectures, research and development of the Rosebud DSL engine, and compiler technology to support complex execution platforms. This report provides a summary of the research and development work on the D-TEC project at Rice University.« less

The integration of automated knowledge acquisition with computer-aided software engineering for space shuttle expert systems

NASA Technical Reports Server (NTRS)

Modesitt, Kenneth L.

1990-01-01

A prediction was made that the terms expert systems and knowledge acquisition would begin to disappear over the next several years. This is not because they are falling into disuse; it is rather that practitioners are realizing that they are valuable adjuncts to software engineering, in terms of problem domains addressed, user acceptance, and in development methodologies. A specific problem was discussed, that of constructing an automated test analysis system for the Space Shuttle Main Engine. In this domain, knowledge acquisition was part of requirements systems analysis, and was performed with the aid of a powerful inductive ESBT in conjunction with a computer aided software engineering (CASE) tool. The original prediction is not a very risky one -- it has already been accomplished.

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)

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.

Motor knowledge is one dimension for concept organization: further evidence from a Chinese semantic dementia case.

PubMed

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

2011-11-01

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 well as the integrity of other modality-specific knowledge (e.g., visual). We present a Chinese case, XRK, who suffered from semantic dementia with left temporal lobe atrophy. In naming and comprehension tasks, he performed better at nonliving items than at living items, and better at verbs than at nouns. Critically, multiple regression method revealed that these two categorical effects could be both accounted for by the charade rating, a continuous measurement of the significance of motor knowledge for a concept or a semantic feature. Furthermore, charade rating also predicted his performances on the generation frequency of semantic features of various modalities. These findings consolidate the significance of motor knowledge in conceptual organization and further highlights the interactions between different types of semantic knowledge. Copyright © 2010 Elsevier Inc. All rights reserved.

Domain-Specific Aspects of Technological Pedagogical Content Knowledge: Music Education and the Importance of Affect

ERIC Educational Resources Information Center

Macrides, Elena; Angeli, Charoula

2018-01-01

The present study addresses the lack of a theoretical framework for the integration of technology in music teaching and learning, and explores, within the framework of Technological Pedagogical Content Knowledge (TPACK), the importance of affect in the instructional design of music lessons. The purpose of this study is twofold: (a) to extend the…

Semi-Automated Methods for Refining a Domain-Specific Terminology Base

DTIC Science & Technology

2011-02-01

only as a resource for written and oral translation, but also for Natural Language Processing ( NLP ) applications, text retrieval, document indexing...Natural Language Processing ( NLP ) applications, text retrieval, document indexing, and other knowledge management tasks. The objective of this...also for Natural Language Processing ( NLP ) applications, text retrieval (1), document indexing, and other knowledge management tasks. The National

The Validity and Incremental Validity of Knowledge Tests, Low-Fidelity Simulations, and High-Fidelity Simulations for Predicting Job Performance in Advanced-Level High-Stakes Selection

ERIC Educational Resources Information Center

Lievens, Filip; Patterson, Fiona

2011-01-01

In high-stakes selection among candidates with considerable domain-specific knowledge and experience, investigations of whether high-fidelity simulations (assessment centers; ACs) have incremental validity over low-fidelity simulations (situational judgment tests; SJTs) are lacking. Therefore, this article integrates research on the validity of…

Preparing Special Education Teachers for Teaching Mathematics and Science with Technology by Integrating the TPACK Framework into the Curriculum: A Study of Teachers' Perceptions

ERIC Educational Resources Information Center

Tournaki, Nelly; Lyublinskaya, Irina

2014-01-01

This study examined the development of Technological Pedagogical And Content Knowledge (TPACK) in mathematics and science of pre-service special education teachers via one course. The course focused on the three domains of knowledge related specifically to integrating instructional technology into mathematics and science teaching and learning…

When Less Is More in Cognitive Diagnosis: A Rapid Online Method for Diagnosing Learner Task-Specific Expertise

ERIC Educational Resources Information Center

Kalyuga, Slava

2008-01-01

Rapid cognitive diagnosis allows measuring current levels of learner domain-specific knowledge in online learning environments. Such measures are required for individualizing instructional support in real time, as students progress through a learning session. This article describes 2 experiments designed to validate a rapid online diagnostic…

Cross-domain latent space projection for person re-identification

NASA Astrophysics Data System (ADS)

Pu, Nan; Wu, Song; Qian, Li; Xiao, Guoqiang

2018-04-01

In this paper, we research the problem of person re-identification and propose a cross-domain latent space projection (CDLSP) method to address the problems of the absence or insufficient labeled data in the target domain. Under the assumption that the visual features in the source domain and target domain share the similar geometric structure, we transform the visual features from source domain and target domain to a common latent space by optimizing the object function defined in the manifold alignment method. Moreover, the proposed object function takes into account the specific knowledge in the re-id with the aim to improve the performance of re-id under complex situations. Extensive experiments conducted on four benchmark datasets show the proposed CDLSP outperforms or is competitive with stateof- the-art methods for person re-identification.

Lightweight Adaptation of Classifiers to Users and Contexts: Trends of the Emerging Domain

PubMed Central

Vildjiounaite, Elena; Gimel'farb, Georgy; Kyllönen, Vesa; Peltola, Johannes

2015-01-01

Intelligent computer applications need to adapt their behaviour to contexts and users, but conventional classifier adaptation methods require long data collection and/or training times. Therefore classifier adaptation is often performed as follows: at design time application developers define typical usage contexts and provide reasoning models for each of these contexts, and then at runtime an appropriate model is selected from available ones. Typically, definition of usage contexts and reasoning models heavily relies on domain knowledge. However, in practice many applications are used in so diverse situations that no developer can predict them all and collect for each situation adequate training and test databases. Such applications have to adapt to a new user or unknown context at runtime just from interaction with the user, preferably in fairly lightweight ways, that is, requiring limited user effort to collect training data and limited time of performing the adaptation. This paper analyses adaptation trends in several emerging domains and outlines promising ideas, proposed for making multimodal classifiers user-specific and context-specific without significant user efforts, detailed domain knowledge, and/or complete retraining of the classifiers. Based on this analysis, this paper identifies important application characteristics and presents guidelines to consider these characteristics in adaptation design. PMID:26473165

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.

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.

[Trends of doctoral dissertations in nursing science: focused on studies submitted since 2000].

PubMed

Shin, Hyunsook; Sung, Kyung-Mi; Jeong, Seok Hee; Kim, Dae-Ran

2008-02-01

The purpose of this study was to identify the characteristics of doctoral dissertations in nursing science submitted since 2000. Three-hundred and five dissertations of six schools of nursing published from 2000 to 2006 in Korea were analyzed with the categories of philosophy, method, body of knowledge, research design, and nursing domain. In philosophy, 82% of all dissertations were identified as scientific realism, 15% were relativism, and 3% were practicism. Two-hundred and fifty dissertations (82%) were divided into a quantitative methodology and 55 dissertations (18%) were qualitative methodology. Specifically, 45% were experimental, 23% methodological, 13% survey and 17% qualitative designed researches. Prescriptive knowledge was created in 47% of dissertations, explanatory knowledge in 29%, and descriptive knowledge in 24%. Over 50% of all research was studied with a community-based population. In the nursing domain, dissertations of the practice domain were highest (48.2%). Dissertations since 2000 were markedly different from the characteristics of the previous studies (1982-1999) in the increase of situation-related, prescriptive and community-based population studies. A picture of current nursing science identified in this study may provide a future guideline for the doctoral education for nursing.

Learning the facts in medical school is not enough: which factors predict successful application of procedural knowledge in a laboratory setting?

PubMed Central

2013-01-01

Background Medical knowledge encompasses both conceptual (facts or “what” information) and procedural knowledge (“how” and “why” information). Conceptual knowledge is known to be an essential prerequisite for clinical problem solving. Primarily, medical students learn from textbooks and often struggle with the process of applying their conceptual knowledge to clinical problems. Recent studies address the question of how to foster the acquisition of procedural knowledge and its application in medical education. However, little is known about the factors which predict performance in procedural knowledge tasks. Which additional factors of the learner predict performance in procedural knowledge? Methods Domain specific conceptual knowledge (facts) in clinical nephrology was provided to 80 medical students (3rd to 5th year) using electronic flashcards in a laboratory setting. Learner characteristics were obtained by questionnaires. Procedural knowledge in clinical nephrology was assessed by key feature problems (KFP) and problem solving tasks (PST) reflecting strategic and conditional knowledge, respectively. Results Results in procedural knowledge tests (KFP and PST) correlated significantly with each other. In univariate analysis, performance in procedural knowledge (sum of KFP+PST) was significantly correlated with the results in (1) the conceptual knowledge test (CKT), (2) the intended future career as hospital based doctor, (3) the duration of clinical clerkships, and (4) the results in the written German National Medical Examination Part I on preclinical subjects (NME-I). After multiple regression analysis only clinical clerkship experience and NME-I performance remained independent influencing factors. Conclusions Performance in procedural knowledge tests seems independent from the degree of domain specific conceptual knowledge above a certain level. Procedural knowledge may be fostered by clinical experience. More attention should be paid to the interplay of individual clinical clerkship experiences and structured teaching of procedural knowledge and its assessment in medical education curricula. PMID:23433202

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).

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…

The heritability of aptitude and exceptional talent across different domains in adolescents and young adults.

PubMed

Vinkhuyzen, Anna A E; van der Sluis, Sophie; Posthuma, Danielle; Boomsma, Dorret I

2009-07-01

The origin of individual differences in aptitude, defined as a domain-specific skill within the normal ability range, and talent, defined as a domain specific skill of exceptional quality, is under debate. The nature of the variation in aptitudes and exceptional talents across different domains was investigated in a population based twin sample. Self-report data from 1,685 twin pairs (12-24 years) were analyzed for Music, Arts, Writing, Language, Chess, Mathematics, Sports, Memory, and Knowledge. The influence of shared environment was small for both aptitude and talent. Additive and non-additive genetic effects explained the major part of the substantial familial clustering in the aptitude measures with heritability estimates ranging between .32 and .71. Heritability estimates for talents were higher and ranged between .50 and .92. In general, the genetic architecture for aptitude and talent was similar in men and women. Genetic factors contribute to a large extent to variation in aptitude and talent across different domains of intellectual, creative, and sports abilities.

Decoding rule search domain in the left inferior frontal gyrus

PubMed Central

Babcock, Laura; Vallesi, Antonino

2018-01-01

Traditionally, the left hemisphere has been thought to extract mainly verbal patterns of information, but recent evidence has shown that the left Inferior Frontal Gyrus (IFG) is active during inductive reasoning in both the verbal and spatial domains. We aimed to understand whether the left IFG supports inductive reasoning in a domain-specific or domain-general fashion. To do this we used Multi-Voxel Pattern Analysis to decode the representation of domain during a rule search task. Thirteen participants were asked to extract the rule underlying streams of letters presented in different spatial locations. Each rule was either verbal (letters forming words) or spatial (positions forming geometric figures). Our results show that domain was decodable in the left prefrontal cortex, suggesting that this region represents domain-specific information, rather than processes common to the two domains. A replication study with the same participants tested two years later confirmed these findings, though the individual representations changed, providing evidence for the flexible nature of representations. This study extends our knowledge on the neural basis of goal-directed behaviors and on how information relevant for rule extraction is flexibly mapped in the prefrontal cortex. PMID:29547623

A domain-specific system for representing knowledge of both man-made objects and human actions. Evidence from a case with an association of deficits.

PubMed

Vannuscorps, Gilles; Pillon, Agnesa

2011-07-01

We report the single-case study of a brain-damaged individual, JJG, presenting with a conceptual deficit and whose knowledge of living things, man-made objects, and actions was assessed. The aim was to seek for empirical evidence pertaining to the issue of how conceptual knowledge of objects, both living things and man-made objects, is related to conceptual knowledge of actions at the functional level. We first found that JJG's conceptual knowledge of both man-made objects and actions was similarly impaired while his conceptual knowledge of living things was spared as well as his knowledge of unique entities. We then examined whether this pattern of association of a conceptual deficit for both man-made objects and actions could be accounted for, first, by the "sensory/functional" and, second, the "manipulability" account for category-specific conceptual impairments advocated within the Feature-Based-Organization theory of conceptual knowledge organization, by assessing, first, patient's knowledge of sensory compared to functional features, second, his knowledge of manipulation compared to functional features and, third, his knowledge of manipulable compared to non-manipulable objects and actions. The later assessment also allowed us to evaluate an account for the deficits in terms of failures of simulating the hand movements implied by manipulable objects and manual actions. The findings showed that, contrary to the predictions made by the "sensory/functional", the "manipulability", and the "failure-of-simulating" accounts for category-specific conceptual impairments, the patient's association of deficits for both man-made objects and actions was not associated with a disproportionate impairment of functional compared to sensory knowledge or of manipulation compared to functional knowledge; manipulable items were not more impaired than non-manipulable items either. In the general discussion, we propose to account for the patient's association of deficits by the hypothesis that concepts whose core property is that of being a mean of achieving a goal - like the concepts of man-made objects and of actions - are learned, represented and processed by a common domain-specific conceptual system, which would have evolved to allow human beings to quickly and efficiently design and understand means to achieve goals and purposes. Copyright © 2011 Elsevier Ltd. All rights reserved.

Unraveling the development of scientific literacy: Domain-specific inquiry support in a system of cognitive and social interactions

NASA Astrophysics Data System (ADS)

Tabak, Iris Ellen

The goal of this dissertation was to study how to harness technological tools in service of establishing a climate of inquiry in science classrooms. The research is a design experiment drawing on sociocultural and cognitive theory. As part of the BGuILE project, I developed software to support observational research of natural selection, and a complementary high school unit on evolution. Focusing on urban schools, I employed interpretive methods to examine learning as it unfolds in the classroom. I present design principles for realizing a climate of inquiry in technology-infused classrooms. This research contributes to technology design, teaching practice and educational and cognitive research. My pedagogical approach, Domain-Specific Strategic Support (DSSS), helps students analyze and synthesize primary data by making experts' considerations of content knowledge explicit. Students query data by constructing questions from a selection of comparison and variable types that are privileged in the domain. Students organize their data according to evidence categories that comprise a natural selection argument. I compared the inquiry process of contrastive cases: an honor group, a regular group and a lower track group. DSSS enabled students at different achievement levels to set up systematic comparisons, and construct empirically-based explanations. Prior knowledge and inquiry experience influenced spontaneous strategy use. Teacher guidance compensated for lack of experience, and enabled regular level students to employ strategies as frequently as honor students. I extend earlier research by proposing a taxonomy of both general and domain-specific reflective inquiry strategies. I argue that software, teacher and curriculum work in concert to sustain a climate of inquiry. Teachers help realize the potential that technological tools invite. Teachers reinforce software supports by encouraging students utilize technological tools, and by modeling their use. They also establish classroom norms that reflect scientific values. Discussions at the computer allow teachers to provide just-in-time guidance on inquiry actions. Whole class discussions afford sharing insights across groups, and relating finding to normative knowledge. Pretest to posttest improvements in both conceptual and strategic knowledge suggest that DSSS helps reconcile the tension that can exist between content and process goals in inquiry settings.

The Role of Ontologies in Schema-based Program Synthesis

NASA Technical Reports Server (NTRS)

Bures, Tomas; Denney, Ewen; Fischer, Bernd; Nistor, Eugen C.

2004-01-01

Program synthesis is the process of automatically deriving executable code from (non-executable) high-level specifications. It is more flexible and powerful than conventional code generation techniques that simply translate algorithmic specifications into lower-level code or only create code skeletons from structural specifications (such as UML class diagrams). Key to building a successful synthesis system is specializing to an appropriate application domain. The AUTOBAYES and AUTOFILTER systems, under development at NASA Ames, operate in the two domains of data analysis and state estimation, respectively. The central concept of both systems is the schema, a representation of reusable computational knowledge. This can take various forms, including high-level algorithm templates, code optimizations, datatype refinements, or architectural information. A schema also contains applicability conditions that are used to determine when it can be applied safely. These conditions can refer to the initial specification, to intermediate results, or to elements of the partially-instantiated code. Schema-based synthesis uses AI technology to recursively apply schemas to gradually refine a specification into executable code. This process proceeds in two main phases. A front-end gradually transforms the problem specification into a program represented in an abstract intermediate code. A backend then compiles this further down into a concrete target programming language of choice. A core engine applies schemas on the initial problem specification, then uses the output of those schemas as the input for other schemas, until the full implementation is generated. Since there might be different schemas that implement different solutions to the same problem this process can generate an entire solution tree. AUTOBAYES and AUTOFILTER have reached the level of maturity where they enable users to solve interesting application problems, e.g., the analysis of Hubble Space Telescope images. They are large (in total around 100kLoC Prolog), knowledge intensive systems that employ complex symbolic reasoning to generate a wide range of non-trivial programs for complex application do- mains. Their schemas can have complex interactions, which make it hard to change them in isolation or even understand what an existing schema actually does. Adding more capabilities by increasing the number of schemas will only worsen this situation, ultimately leading to the entropy death of the synthesis system. The root came of this problem is that the domain knowledge is scattered throughout the entire system and only represented implicitly in the schema implementations. In our current work, we are addressing this problem by making explicit the knowledge from Merent parts of the synthesis system. Here; we discuss how Gruber's definition of an ontology as an explicit specification of a conceptualization matches our efforts in identifying and explicating the domain-specific concepts. We outline the dual role ontologies play in schema-based synthesis and argue that they address different audiences and serve different purposes. Their first role is descriptive: they serve as explicit documentation, and help to understand the internal structure of the system. Their second role is prescriptive: they provide the formal basis against which the other parts of the system (e.g., schemas) can be checked. Their final role is referential: ontologies also provide semantically meaningful "hooks" which allow schemas and tools to access the internal state of the program derivation process (e.g., fragments of the generated code) in domain-specific rather than language-specific terms, and thus to modify it in a controlled fashion. For discussion purposes we use AUTOLINEAR, a small synthesis system we are currently experimenting with, which can generate code for solving a system of linear equations, Az = b.

Research on an expert system for database operation of simulation-emulation math models. Volume 1, Phase 1: Results

NASA Technical Reports Server (NTRS)

Kawamura, K.; Beale, G. O.; Schaffer, J. D.; Hsieh, B. J.; Padalkar, S.; Rodriguez-Moscoso, J. J.

1985-01-01

The results of the first phase of Research on an Expert System for Database Operation of Simulation/Emulation Math Models, is described. Techniques from artificial intelligence (AI) were to bear on task domains of interest to NASA Marshall Space Flight Center. One such domain is simulation of spacecraft attitude control systems. Two related software systems were developed to and delivered to NASA. One was a generic simulation model for spacecraft attitude control, written in FORTRAN. The second was an expert system which understands the usage of a class of spacecraft attitude control simulation software and can assist the user in running the software. This NASA Expert Simulation System (NESS), written in LISP, contains general knowledge about digital simulation, specific knowledge about the simulation software, and self knowledge.

Indexing Guidelines: Applications in Use of Pulmonary Artery Catheters and Pressure Ulcer Prevention

PubMed Central

Jenders, Robert A.; Estey, Greg; Martin, Martha; Hamilton, Glenys; Ford-Carleton, Penny; Thompson, B. Taylor; Oliver, Diane E.; Eccles, Randy; Barnett, G. Octo; Zielstorff, Rita D.; Fitzmaurice, Joan B.

1994-01-01

In a busy clinical environment, access to knowledge must be rapid and specific to the clinical query at hand. This requires indices which support easy navigation within a knowledge source. We have developed a computer-based tool for trouble-shooting pulmonary artery waveforms using a graphical index. Preliminary results of domain knowledge tests for a group of clinicians exposed to the system (N=33) show a mean improvement on a 30-point test of 5.33 (p<0.001) compared to a control group (N=19) improvement of 0.47 (p=0.61). Survey of the experimental group (N=25) showed 84% (p=0.001) found the system easy to use. We discuss lessons learned in indexing this domain area to computer-based indexing of guidelines for pressure ulcer prevention. PMID:7950035

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

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems.

PubMed

Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A

2017-03-01

The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework.

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems

PubMed Central

Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A.

2017-01-01

Abstract The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework. PMID:28328252

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.

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.

RT-Syn: A real-time software system generator

NASA Technical Reports Server (NTRS)

Setliff, Dorothy E.

1992-01-01

This paper presents research into providing highly reusable and maintainable components by using automatic software synthesis techniques. This proposal uses domain knowledge combined with automatic software synthesis techniques to engineer large-scale mission-critical real-time software. The hypothesis centers on a software synthesis architecture that specifically incorporates application-specific (in this case real-time) knowledge. This architecture synthesizes complex system software to meet a behavioral specification and external interaction design constraints. Some examples of these external constraints are communication protocols, precisions, timing, and space limitations. The incorporation of application-specific knowledge facilitates the generation of mathematical software metrics which are used to narrow the design space, thereby making software synthesis tractable. Success has the potential to dramatically reduce mission-critical system life-cycle costs not only by reducing development time, but more importantly facilitating maintenance, modifications, and extensions of complex mission-critical software systems, which are currently dominating life cycle costs.

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.

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.

Towards a semantic lexicon for biological language processing

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

Verspoor, K.

It is well understood that natural language processing (NLP) applications require sophisticated lexical resources to support their processing goals. In the biomedical domain, we are privileged to have access to extensive terminological resources in the form of controlled vocabularies and ontologies, which have been integrated into the framework of the National Library of Medicine's Unified Medical Language System's (UMLS) Metathesaurus. However, the existence of such terminological resources does not guarantee their utility for NLP. In particular, we have two core requirements for lexical resources for NLP in addition to the basic enumeration of important domain terms: representation of morphosyntactic informationmore » about those terms, specifically part of speech information and inflectional patterns to support parsing and lemma assignment, and representation of semantic information indicating general categorical information about terms, and significant relations between terms to support text understanding and inference (Hahn et at, 1999). Biomedical vocabularies by and large commonly leave out morphosyntactic information, and where they address semantic considerations, they often do so in an unprincipled manner, for instance by indicating a relation between two concepts without indicating the type of that relation. But all is not lost. The UMLS knowledge sources include two additional resources which are relevant - the SPECIALIST lexicon, a lexicon addressing our morphosyntactic requirements, and the Semantic Network, a representation of core conceptual categories in the biomedical domain. The coverage of these two knowledge sources with respect to the full coverage of the Metathesaurus is, however, not entirely clear. Furthermore, when our goals are specifically to process biological text - and often more specifically, text in the molecular biology domain - it is difficult to say whether the coverage of these resources is meaningful. The utility of the UMLS knowledge sources for medical language processing (MLP) has been explored (Johnson, 1999; Friedman et al 2001); the time has now come to repeat these experiments with respect to biological language processing (BLP). To that end, this paper presents an analysis of ihe UMLS resources, specifically with an eye towards constructing lexical resources suitable for BLP. We follow the paradigm presented in Johnson (1999) for medical language, exploring overlap between the UMLS Metathesaurus and SPECIALIST lexicon to construct a morphosyntactic and semantically-specified lexicon, and then further explore the overlap with a relevant domain corpus for molecular biology.« less

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

Knowledge-acquisition tools for medical knowledge-based systems.

PubMed

Lanzola, G; Quaglini, S; Stefanelli, M

1995-03-01

Knowledge-based systems (KBS) have been proposed to solve a large variety of medical problems. A strategic issue for KBS development and maintenance are the efforts required for both knowledge engineers and domain experts. The proposed solution is building efficient knowledge acquisition (KA) tools. This paper presents a set of KA tools we are developing within a European Project called GAMES II. They have been designed after the formulation of an epistemological model of medical reasoning. The main goal is that of developing a computational framework which allows knowledge engineers and domain experts to interact cooperatively in developing a medical KBS. To this aim, a set of reusable software components is highly recommended. Their design was facilitated by the development of a methodology for KBS construction. It views this process as comprising two activities: the tailoring of the epistemological model to the specific medical task to be executed and the subsequent translation of this model into a computational architecture so that the connections between computational structures and their knowledge level counterparts are maintained. The KA tools we developed are illustrated taking examples from the behavior of a KBS we are building for the management of children with acute myeloid leukemia.

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.

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).

Impact of Different Levels of Epistemic Beliefs on Learning Processes and Outcomes in Vocational Education and Training

ERIC Educational Resources Information Center

Berding, Florian; Rolf-Wittlake, Katharina; Buschenlange, Janes

2017-01-01

Epistemic beliefs are individuals' beliefs about knowledge and knowing. Modelling them is currently based on two central assumptions. First, epistemic beliefs are conceptualized as a multi-level construct, i.e. they exist on a general, academic, domain-specific and/or topic-specific level. Second, research assumes that their more concrete levels…

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

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.

Modeling And Detecting Anomalies In Scada Systems

NASA Astrophysics Data System (ADS)

Svendsen, Nils; Wolthusen, Stephen

The detection of attacks and intrusions based on anomalies is hampered by the limits of specificity underlying the detection techniques. However, in the case of many critical infrastructure systems, domain-specific knowledge and models can impose constraints that potentially reduce error rates. At the same time, attackers can use their knowledge of system behavior to mask their manipulations, causing adverse effects to observed only after a significant period of time. This paper describes elementary statistical techniques that can be applied to detect anomalies in critical infrastructure networks. A SCADA system employed in liquefied natural gas (LNG) production is used as a case study.

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.

Semantics-informed geological maps: Conceptual modeling and knowledge encoding

NASA Astrophysics Data System (ADS)

Lombardo, Vincenzo; Piana, Fabrizio; Mimmo, Dario

2018-07-01

This paper introduces a novel, semantics-informed geologic mapping process, whose application domain is the production of a synthetic geologic map of a large administrative region. A number of approaches concerning the expression of geologic knowledge through UML schemata and ontologies have been around for more than a decade. These approaches have yielded resources that concern specific domains, such as, e.g., lithology. We develop a conceptual model that aims at building a digital encoding of several domains of geologic knowledge, in order to support the interoperability of the sources. We apply the devised terminological base to the classification of the elements of a geologic map of the Italian Western Alps and northern Apennines (Piemonte region). The digitally encoded knowledge base is a merged set of ontologies, called OntoGeonous. The encoding process identifies the objects of the semantic encoding, the geologic units, gathers the relevant information about such objects from authoritative resources, such as GeoSciML (giving priority to the application schemata reported in the INSPIRE Encoding Cookbook), and expresses the statements by means of axioms encoded in the Web Ontology Language (OWL). To support interoperability, OntoGeonous interlinks the general concepts by referring to the upper part level of ontology SWEET (developed by NASA), and imports knowledge that is already encoded in ontological format (e.g., ontology Simple Lithology). Machine-readable knowledge allows for consistency checking and for classification of the geological map data through algorithms of automatic reasoning.

Metaphorically Feeling: Comprehending Textural Metaphors Activates Somatosensory Cortex

ERIC Educational Resources Information Center

Lacey, Simon; Stilla, Randall; Sathian, K.

2012-01-01

Conceptual metaphor theory suggests that knowledge is structured around metaphorical mappings derived from physical experience. Segregated processing of object properties in sensory cortex allows testing of the hypothesis that metaphor processing recruits activity in domain-specific sensory cortex. Using functional magnetic resonance imaging…

Personal networks: a tool for gaining insight into the transmission of knowledge about food and medicinal plants among Tyrolean (Austrian) migrants in Australia, Brazil and Peru

PubMed Central

2014-01-01

Background Investigations into knowledge about food and medicinal plants in a certain geographic area or within a specific group are an important element of ethnobotanical research. This knowledge is context specific and dynamic due to changing ecological, social and economic circumstances. Migration processes affect food habits and the knowledge and use of medicinal plants as a result of adaptations that have to be made to new surroundings and changing environments. This study analyses and compares the different dynamics in the transmission of knowledge about food and medicinal plants among Tyrolean migrants in Australia, Brazil and Peru. Methods A social network approach was used to collect data on personal networks of knowledge about food and medicinal plants among Tyroleans who have migrated to Australia, Brazil and Peru and their descendants. A statistical analysis of the personal network maps and a qualitative analysis of the narratives were combined to provide insight into the process of transmitting knowledge about food and medicinal plants. Results 56 personal networks were identified in all (food: 30; medicinal plants: 26) across all the field sites studied here. In both sets of networks, the main source of knowledge is individual people (food: 71%; medicinal plants: 68%). The other sources mentioned are print and audiovisual media, organisations and institutions. Personal networks of food knowledge are larger than personal networks of medicinal plant knowledge in all areas of investigation. Relatives play a major role as transmitters of knowledge in both domains. Conclusions Human sources, especially relatives, play an important role in knowledge transmission in both domains. Reference was made to other sources as well, such as books, television, the internet, schools and restaurants. By taking a personal network approach, this study reveals the mode of transmission of knowledge about food and medicinal plants within a migrational context. PMID:24398225

Personal networks: a tool for gaining insight into the transmission of knowledge about food and medicinal plants among Tyrolean (Austrian) migrants in Australia, Brazil and Peru.

PubMed

Haselmair, Ruth; Pirker, Heidemarie; Kuhn, Elisabeth; Vogl, Christian R

2014-01-07

Investigations into knowledge about food and medicinal plants in a certain geographic area or within a specific group are an important element of ethnobotanical research. This knowledge is context specific and dynamic due to changing ecological, social and economic circumstances. Migration processes affect food habits and the knowledge and use of medicinal plants as a result of adaptations that have to be made to new surroundings and changing environments. This study analyses and compares the different dynamics in the transmission of knowledge about food and medicinal plants among Tyrolean migrants in Australia, Brazil and Peru. A social network approach was used to collect data on personal networks of knowledge about food and medicinal plants among Tyroleans who have migrated to Australia, Brazil and Peru and their descendants. A statistical analysis of the personal network maps and a qualitative analysis of the narratives were combined to provide insight into the process of transmitting knowledge about food and medicinal plants. 56 personal networks were identified in all (food: 30; medicinal plants: 26) across all the field sites studied here. In both sets of networks, the main source of knowledge is individual people (food: 71%; medicinal plants: 68%). The other sources mentioned are print and audiovisual media, organisations and institutions. Personal networks of food knowledge are larger than personal networks of medicinal plant knowledge in all areas of investigation. Relatives play a major role as transmitters of knowledge in both domains. Human sources, especially relatives, play an important role in knowledge transmission in both domains. Reference was made to other sources as well, such as books, television, the internet, schools and restaurants. By taking a personal network approach, this study reveals the mode of transmission of knowledge about food and medicinal plants within a migrational context.

Researcher readiness for participating in community-engaged dissemination and implementation research: a conceptual framework of core competencies.

PubMed

Shea, Christopher M; Young, Tiffany L; Powell, Byron J; Rohweder, Catherine; Enga, Zoe K; Scott, Jennifer E; Carter-Edwards, Lori; Corbie-Smith, Giselle

2017-09-01

Participating in community-engaged dissemination and implementation (CEDI) research is challenging for a variety of reasons. Currently, there is not specific guidance or a tool available for researchers to assess their readiness to conduct CEDI research. We propose a conceptual framework that identifies detailed competencies for researchers participating in CEDI and maps these competencies to domains. The framework is a necessary step toward developing a CEDI research readiness survey that measures a researcher's attitudes, willingness, and self-reported ability for acquiring the knowledge and performing the behaviors necessary for effective community engagement. The conceptual framework for CEDI competencies was developed by a team of eight faculty and staff affiliated with a university's Clinical and Translational Science Award (CTSA). The authors developed CEDI competencies by identifying the attitudes, knowledge, and behaviors necessary for carrying out commonly accepted CE principles. After collectively developing an initial list of competencies, team members individually mapped each competency to a single domain that provided the best fit. Following the individual mapping, the group held two sessions in which the sorting preferences were shared and discrepancies were discussed until consensus was reached. During this discussion, modifications to wording of competencies and domains were made as needed. The team then engaged five community stakeholders to review and modify the competencies and domains. The CEDI framework consists of 40 competencies organized into nine domains: perceived value of CE in D&I research, introspection and openness, knowledge of community characteristics, appreciation for stakeholder's experience with and attitudes toward research, preparing the partnership for collaborative decision-making, collaborative planning for the research design and goals, communication effectiveness, equitable distribution of resources and credit, and sustaining the partnership. Delineation of CEDI competencies advances the broader CE principles and D&I research goals found in the literature and facilitates development of readiness assessments tied to specific training resources for researchers interested in conducting CEDI research.

Issues on the use of meta-knowledge in expert systems

NASA Technical Reports Server (NTRS)

Facemire, Jon; Chen, Imao

1988-01-01

Meta knowledge is knowledge about knowledge; knowledge that is not domain specific but is concerned instead with its own internal structure. Several past systems have used meta-knowledge to improve the nature of the user interface, to maintain the knowledge base, and to control the inference engine. More extensive use of meta-knowledge is probable for the future as larger scale problems are considered. A proposed system architecture is presented and discussed in terms of meta-knowledge applications. The principle components of this system: the user support subsystem, the control structure, the knowledge base, the inference engine, and a learning facility are all outlined and discussed in light of the use of meta-knowledge. Problems with meta-constructs are also mentioned but it is concluded that the use of meta-knowledge is crucial for increasingly autonomous operations.

Family Context, Mexican-Origin Adolescent Mothers' Parenting Knowledge, and Children's Subsequent Developmental Outcomes

PubMed Central

Jahromi, Laudan B.; Guimond, Amy B.; Umaña-Taylor, Adriana J.; Updegraff, Kimberly A.; Toomey, Russell B.

2014-01-01

This study examined parenting knowledge among Mexican-origin adolescent mothers (N = 191; M age = 16.26 years), family contextual factors associated with adolescents' parenting knowledge, and toddlers' (M age = 2.01 years) subsequent developmental outcomes. Data came from home interviews and direct child assessments. Adolescents both under- and over-estimated children's developmental timing, and showed differences in their knowledge of specific developmental domains. Instrumental support from mother figures was positively linked to adolescents' knowledge accuracy, whereas emotional support was negatively related to adolescents' knowledge confidence. Furthermore, whereas mother figures' autonomy-granting was positively linked to knowledge confidence, psychological control was associated with less accurate adolescent parenting knowledge. Toddlers of adolescents with more accurate knowledge showed positive developmental functioning. Intervention implications are discussed. PMID:24004448

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.

Polar Domain Discovery with Sparkler

NASA Astrophysics Data System (ADS)

Duerr, R.; Khalsa, S. J. S.; Mattmann, C. A.; Ottilingam, N. K.; Singh, K.; Lopez, L. A.

2017-12-01

The scientific web is vast and ever growing. It encompasses millions of textual, scientific and multimedia documents describing research in a multitude of scientific streams. Most of these documents are hidden behind forms which require user action to retrieve and thus can't be directly accessed by content crawlers. These documents are hosted on web servers across the world, most often on outdated hardware and network infrastructure. Hence it is difficult and time-consuming to aggregate documents from the scientific web, especially those relevant to a specific domain. Thus generating meaningful domain-specific insights is currently difficult. We present an automated discovery system (Figure 1) using Sparkler, an open-source, extensible, horizontally scalable crawler which facilitates high throughput and focused crawling of documents pertinent to a particular domain such as information about polar regions. With this set of highly domain relevant documents, we show that it is possible to answer analytical questions about that domain. Our domain discovery algorithm leverages prior domain knowledge to reach out to commercial/scientific search engines to generate seed URLs. Subject matter experts then annotate these seed URLs manually on a scale from highly relevant to irrelevant. We leverage this annotated dataset to train a machine learning model which predicts the `domain relevance' of a given document. We extend Sparkler with this model to focus crawling on documents relevant to that domain. Sparkler avoids disruption of service by 1) partitioning URLs by hostname such that every node gets a different host to crawl and by 2) inserting delays between subsequent requests. With an NSF-funded supercomputer Wrangler, we scaled our domain discovery pipeline to crawl about 200k polar specific documents from the scientific web, within a day.

Smart markers for watershed-based cell segmentation.

PubMed

Koyuncu, Can Fahrettin; Arslan, Salim; Durmaz, Irem; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2012-01-01

Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

A Hybrid Approach to Finding Relevant Social Media Content for Complex Domain Specific Information Needs.

PubMed

Cameron, Delroy; Sheth, Amit P; Jaykumar, Nishita; Thirunarayan, Krishnaprasad; Anand, Gaurish; Smith, Gary A

2014-12-01

While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and "intelligible constructs" not typically modeled in ontologies. These intelligible constructs convey essential information that include notions of intensity, frequency, interval, dosage and sentiments, which could be important to the holistic needs of the information seeker. In this paper, we present a hybrid approach to domain specific information retrieval that integrates ontology-driven query interpretation with synonym-based query expansion and domain specific rules, to facilitate search in social media on prescription drug abuse. Our framework is based on a context-free grammar (CFG) that defines the query language of constructs interpretable by the search system. The grammar provides two levels of semantic interpretation: 1) a top-level CFG that facilitates retrieval of diverse textual patterns, which belong to broad templates and 2) a low-level CFG that enables interpretation of specific expressions belonging to such textual patterns. These low-level expressions occur as concepts from four different categories of data: 1) ontological concepts, 2) concepts in lexicons (such as emotions and sentiments), 3) concepts in lexicons with only partial ontology representation, called lexico-ontology concepts (such as side effects and routes of administration (ROA)), and 4) domain specific expressions (such as date, time, interval, frequency and dosage) derived solely through rules. Our approach is embodied in a novel Semantic Web platform called PREDOSE, which provides search support for complex domain specific information needs in prescription drug abuse epidemiology. When applied to a corpus of over 1 million drug abuse-related web forum posts, our search framework proved effective in retrieving relevant documents when compared with three existing search systems.

A Hybrid Approach to Finding Relevant Social Media Content for Complex Domain Specific Information Needs

PubMed Central

Cameron, Delroy; Sheth, Amit P.; Jaykumar, Nishita; Thirunarayan, Krishnaprasad; Anand, Gaurish; Smith, Gary A.

2015-01-01

While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and “intelligible constructs” not typically modeled in ontologies. These intelligible constructs convey essential information that include notions of intensity, frequency, interval, dosage and sentiments, which could be important to the holistic needs of the information seeker. In this paper, we present a hybrid approach to domain specific information retrieval that integrates ontology-driven query interpretation with synonym-based query expansion and domain specific rules, to facilitate search in social media on prescription drug abuse. Our framework is based on a context-free grammar (CFG) that defines the query language of constructs interpretable by the search system. The grammar provides two levels of semantic interpretation: 1) a top-level CFG that facilitates retrieval of diverse textual patterns, which belong to broad templates and 2) a low-level CFG that enables interpretation of specific expressions belonging to such textual patterns. These low-level expressions occur as concepts from four different categories of data: 1) ontological concepts, 2) concepts in lexicons (such as emotions and sentiments), 3) concepts in lexicons with only partial ontology representation, called lexico-ontology concepts (such as side effects and routes of administration (ROA)), and 4) domain specific expressions (such as date, time, interval, frequency and dosage) derived solely through rules. Our approach is embodied in a novel Semantic Web platform called PREDOSE, which provides search support for complex domain specific information needs in prescription drug abuse epidemiology. When applied to a corpus of over 1 million drug abuse-related web forum posts, our search framework proved effective in retrieving relevant documents when compared with three existing search systems. PMID:25814917

Towards Building an AOP-based Prenatal Developmental Toxicity Ontology (CEFIC LRI Workshop - Brussels)

EPA Science Inventory

Ontologies are a way to formalize domain-specific scientific knowledge. A developmental ontology would help researchers describe the pathways and processes critical to embryonic development and provide a way to link their chemical disruption to adverse outcomes. Designing one for...

Learning Outcomes in Affective Domain within Contemporary Architectural Curricula

ERIC Educational Resources Information Center

Savic, Marko; Kashef, Mohamad

2013-01-01

Contemporary architectural education has shifted from the traditional focus on providing students with specific knowledge and skill sets or "inputs" to outcome based, student-centred educational approach. Within the outcome based model, students' performance is assessed against measureable objectives that relate acquired knowledge…

Possible Brain Mechanisms of Creativity.

PubMed

Heilman, Kenneth M

2016-06-01

Creativity is the new discovery, understanding, development and expression of orderly and meaningful relationships. Creativity has three major stages: preparation, the development (nature and nurture) of critical knowledge and skills; innovation, the development of a creative solution; and creative production. Successful preparation requires a basic level of general intelligence and domain specific knowledge and skills and highly creative people may have anatomic alterations of specific neocortical regions. Innovation requires disengagement and divergent thinking primarily mediated by frontal networks. Creative people are often risk-takers and novelty seekers, behaviors that activate their ventral striatal reward system. Innovation also requires associative and convergent thinking, activities that are dependent on the integration of highly distributed networks. People are often most creative when they are in mental states associated with reduced levels of brain norepinephrine, which may enhance the communication between distributed networks. We, however, need to learn more about the brain mechanisms of creativity. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

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…

An Integrated Architecture for Engineering Problem Solving

DTIC Science & Technology

1998-12-01

mentioned in the problem statement In the next section, we describe the definition of qualitative state and our extension to Gizmo (Forbus & de Kleer...possible qualitative transitions Figure 28: Mapping from problem specification to qualitative states We use Gizmo (Forbus, 1984b), developed by Ken...Forbus, to perform the necessary qualitative analysis. The initial partial problem specification becomes the scenario for Gizmo . The domain knowledge

Impaired Performance on See-Know Tasks amongst Children with Autism: Evidence of Specific Difficulties with Theory of Mind or Domain-General Task Factors?

ERIC Educational Resources Information Center

Lind, Sophie E.; Bowler, Dermot M.

2010-01-01

It is widely assumed that children with autism have a diminished understanding of the perception-knowledge relationship, as a specific manifestation of a theory of mind (ToM) impairment. However, such a conclusion may not be justified on the basis of previous studies, which have suffered from significant methodological weaknesses. The current…

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.

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.

Understanding the role of knowledge in the practice of expert nephrology nurses in Australia.

PubMed

Bonner, Ann

2007-09-01

This paper, which is abstracted from a larger study into the acquisition and exercise of nephrology nursing expertise, aims to explore the role of knowledge in expert practice. Using grounded theory methodology, the study involved 17 registered nurses who were practicing in a metropolitan renal unit in New South Wales, Australia. Concurrent data collection and analysis was undertaken, incorporating participants' observations and interviews. Having extensive nephrology nursing knowledge was a striking characteristic of a nursing expert. Expert nurses clearly relied on and utilized extensive nephrology nursing knowledge to practice. Of importance for nursing, the results of this study indicate that domain-specific knowledge is a crucial feature of expert practice.

Design and isolation of ribozyme-substrate pairs using RNase P-based ribozymes containing altered substrate binding sites.

PubMed Central

Mobley, E M; Pan, T

1999-01-01

Substrate recognition and cleavage by the bacterial RNase P RNA requires two domains, a specificity domain, or S-domain, and a catalytic domain, or C-domain. The S-domain binds the T stem-loop region in a pre-tRNA substrate to confer specificity for tRNA substrates. In this work, the entire S-domain of the Bacillus subtilis RNase P RNA is replaced with an artificial substrate binding module. New RNA substrates are isolated by in vitro selection using two libraries containing random regions of 60 nt. At the end of the selection, the cleavage rates of the substrate library are approximately 0.7 min(-1)in 10 mM MgCl(2)at 37 degrees C, approximately 4-fold better than the cleavage of a pre-tRNA substrate by the wild-type RNase P RNA under the same conditions. The contribution of the S-domain replacement to the catalytic efficiency is from 6- to 22 000-fold. Chemical and nuclease mapping of two ribozyme-product complexes shows that this contribution correlates with direct interactions between the S-domain replacement and the selected substrate. These results demonstrate the feasibility of design and isolation of RNase P-based, matching ribozyme-substrate pairs without prior knowledge of the sequence or structure of the interactive modules in the ribozyme or substrate. PMID:10518624

Disciplinary Literacy from a Speech-Language Pathologist's Perspective

ERIC Educational Resources Information Center

Ehren, Barbara J.; Murza, Kimberly A.; Malani, Melissa D.

2012-01-01

Disciplinary literacy is an increasingly popular focal area in adolescent literacy. In disciplinary literacy, the discourse features of specific knowledge domains (e.g., literature, history, science, and math) assume major importance in understanding and constructing meaning in each discipline. Because language plays a significant role in…

Understanding the Chinese Approach to Creative Teaching in Mathematics Classrooms

ERIC Educational Resources Information Center

Niu, Weihua; Zhou, Zheng; Zhou, Xinlin

2017-01-01

Using Amabile's componential theory of creativity as a framework, this paper analyzes how Chinese mathematics teachers achieve creative teaching through acquiring in-depth domain-specific knowledge in mathematics, developing creativity-related skills, as well as stimulating student interest in learning mathematics, through well-crafted,…

Co-occurrence graphs for word sense disambiguation in the biomedical domain.

PubMed

Duque, Andres; Stevenson, Mark; Martinez-Romo, Juan; Araujo, Lourdes

2018-05-01

Word sense disambiguation is a key step for many natural language processing tasks (e.g. summarization, text classification, relation extraction) and presents a challenge to any system that aims to process documents from the biomedical domain. In this paper, we present a new graph-based unsupervised technique to address this problem. The knowledge base used in this work is a graph built with co-occurrence information from medical concepts found in scientific abstracts, and hence adapted to the specific domain. Unlike other unsupervised approaches based on static graphs such as UMLS, in this work the knowledge base takes the context of the ambiguous terms into account. Abstracts downloaded from PubMed are used for building the graph and disambiguation is performed using the personalized PageRank algorithm. Evaluation is carried out over two test datasets widely explored in the literature. Different parameters of the system are also evaluated to test robustness and scalability. Results show that the system is able to outperform state-of-the-art knowledge-based systems, obtaining more than 10% of accuracy improvement in some cases, while only requiring minimal external resources. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Anselmi, Fabio; Poggio, Tomaso

2015-01-01

Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition system’s optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions. PMID:26496457

Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks.

PubMed

González-Ferrer, Arturo; ten Teije, Annette; Fdez-Olivares, Juan; Milian, Krystyna

2013-02-01

This paper describes a methodology which enables computer-aided support for the planning, visualization and execution of personalized patient treatments in a specific healthcare process, taking into account complex temporal constraints and the allocation of institutional resources. To this end, a translation from a time-annotated computer-interpretable guideline (CIG) model of a clinical protocol into a temporal hierarchical task network (HTN) planning domain is presented. The proposed method uses a knowledge-driven reasoning process to translate knowledge previously described in a CIG into a corresponding HTN Planning and Scheduling domain, taking advantage of HTNs known ability to (i) dynamically cope with temporal and resource constraints, and (ii) automatically generate customized plans. The proposed method, focusing on the representation of temporal knowledge and based on the identification of workflow and temporal patterns in a CIG, makes it possible to automatically generate time-annotated and resource-based care pathways tailored to the needs of any possible patient profile. The proposed translation is illustrated through a case study based on a 70 pages long clinical protocol to manage Hodgkin's disease, developed by the Spanish Society of Pediatric Oncology. We show that an HTN planning domain can be generated from the corresponding specification of the protocol in the Asbru language, providing a running example of this translation. Furthermore, the correctness of the translation is checked and also the management of ten different types of temporal patterns represented in the protocol. By interpreting the automatically generated domain with a state-of-art HTN planner, a time-annotated care pathway is automatically obtained, customized for the patient's and institutional needs. The generated care pathway can then be used by clinicians to plan and manage the patients long-term care. The described methodology makes it possible to automatically generate patient-tailored care pathways, leveraging an incremental knowledge-driven engineering process that starts from the expert knowledge of medical professionals. The presented approach makes the most of the strengths inherent in both CIG languages and HTN planning and scheduling techniques: for the former, knowledge acquisition and representation of the original clinical protocol, and for the latter, knowledge reasoning capabilities and an ability to deal with complex temporal and resource constraints. Moreover, the proposed approach provides immediate access to technologies such as business process management (BPM) tools, which are increasingly being used to support healthcare processes. Copyright © 2012 Elsevier B.V. All rights reserved.

Leadership emergence: the application of the Cynefin framework during a bio-social HIV/AIDS risk-reduction pilot.

PubMed

Burman, Christopher J; Aphane, Marota A

2016-09-01

This article focuses on the utility of a knowledge management heuristic called the Cynefin framework, which was applied during an ongoing pilot intervention in the Limpopo province, South Africa. The intervention aimed to identify and then consolidate low-cost, innovative bio-social responses to reinforce the biomedical opportunities that now have the potential to "end AIDS by 2030″. The Cynefin framework is designed to enable leaders to identify specific decision-making domain typologies as a mechanism to maximise the effectiveness of leadership responses to both opportunities and challenges that emerge during interventions. In this instance the Cynefin framework was used to: (1) provide an indication to the project managers whether the early stages of the intervention had been effective; (2) provide the participants an opportunity to identify emergent knowledge action spaces (opportunities and challenges); and (3) categorise them into appropriate decision-making domains in preparation for the next phases of the intervention. A qualitative methodology was applied to collect and analyse the findings. The findings indicate that applying the Cynefin framework enabled the participants to situate knowledge action spaces into appropriate decision-making domains. From this participatory evaluation a targeted management strategy was developed for the next phases of the initiative. The article concludes by arguing that the Cynefin framework was an effective mechanism for situating emergent knowledge action spaces into appropriate decision-making domains, which enabled them to prepare for the next phases of the intervention. This process of responsive decision making could have utility in other development related interventions.

Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge.

PubMed

Moehring, Anne; Schroeders, Ulrich; Wilhelm, Oliver

2018-01-01

Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET) was examined for medical assistant students ( n = 448). Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge.

Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge

PubMed Central

Moehring, Anne; Schroeders, Ulrich; Wilhelm, Oliver

2018-01-01

Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET) was examined for medical assistant students (n = 448). Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge. PMID:29449819

Technological Pedagogical Content Knowledge of Prospective Mathematics Teacher in Three Dimensional Material Based on Sex Differences

NASA Astrophysics Data System (ADS)

Aqib, M. A.; Budiarto, M. T.; Wijayanti, P.

2018-01-01

The effectiveness of learning in this era can be seen from 3 factors such as: technology, content, and pedagogy that covered in Technological Pedagogical Content Knowledge (TPCK). This research was a qualitative research which aimed to describe each domain from TPCK include Content Knowledge, Pedagogical Knowledge, Pedagogical Content Knowledge, Technological Knowledge, Technological Content Knowledge, Technological Pedagogical Knowledge and Technological, Pedagogical, and Content Knowledge. The subjects of this research were male and female mathematics college students at least 5th semester who has almost the same ability for some course like innovative learning, innovative learning II, school mathematics I, school mathematics II, computer applications and instructional media. Research began by spreading the questionnaire of subject then continued with the assignment and interview. The obtained data was validated by time triangulation.This research has result that male and female prospective teacher was relatively same for Content Knowledge and Pedagogical Knowledge domain. While it was difference in the Technological Knowledge domain. The difference in this domain certainly has an impact on other domains that has technology components on it. Although it can be minimized by familiarizing the technology.

Theory and ontology for sharing temporal knowledge

NASA Technical Reports Server (NTRS)

Loganantharaj, Rasiah

1996-01-01

Using current technology, the sharing or re-using of knowledge-bases is very difficult, if not impossible. ARPA has correctly recognized the problem and funded a knowledge sharing initiative. One of the outcomes of this project is a formal language called Knowledge Interchange Format (KIF) for representing knowledge that could be translated into other languages. Capturing and representing design knowledge and reasoning with them have become very important for NASA who is a pioneer of innovative design of unique products. For upgrading an existing design for changing technology, needs, or requirements, it is essential to understand the design rationale, design choices, options and other relevant information associated with the design. Capturing such information and presenting them in the appropriate form are part of the ongoing Design Knowledge Capture project of NASA. The behavior of an object and various other aspects related to time are captured by the appropriate temporal knowledge. The captured design knowledge will be represented in such a way that various groups of NASA who are interested in various aspects of the design cycle should be able to access and use the design knowledge effectively. To facilitate knowledge sharing among these groups, one has to develop a very well defined ontology. Ontology is a specification of conceptualization. In the literature several specific domains were studied and some well defined ontologies were developed for such domains. However, very little, or no work has been done in the area of representing temporal knowledge to facilitate sharing. During the ASEE summer program, I have investigated several temporal models and have proposed a theory for time that is flexible to accommodate the time elements, such as, points and intervals, and is capable of handling the qualitative and quantitative temporal constraints. I have also proposed a primitive temporal ontology using which other relevant temporal ontologies can be built. I have investigated various issues of sharing knowledge and have proposed a formal framework for modeling the concept of knowledge sharing. This work may be implemented and tested in the software environment supplied by Knowledge Based System, Inc.

Generic Educational Knowledge Representation for Adaptive and Cognitive Systems

ERIC Educational Resources Information Center

Caravantes, Arturo; Galan, Ramon

2011-01-01

The interoperability of educational systems, encouraged by the development of specifications, standards and tools related to the Semantic Web is limited to the exchange of information in domain and student models. High system interoperability requires that a common framework be defined that represents the functional essence of educational systems.…

Problem Solving and the Development of Expertise in Management.

ERIC Educational Resources Information Center

Lash, Fredrick B.

This study investigated novice and expert problem solving behavior in management to examine the role of domain specific knowledge on problem solving processes. Forty-one middle level marketing managers in a large petrochemical organization provided think aloud protocols in response to two hypothetical management scenarios. Protocol analysis…

Implicit Learning of Semantic Preferences of Verbs

ERIC Educational Resources Information Center

Paciorek, Albertyna; Williams, John N.

2015-01-01

Previous studies of semantic implicit learning in language have only examined learning grammatical form-meaning connections in which learning could have been supported by prior linguistic knowledge. In this study we target the domain of verb meaning, specifically semantic preferences regarding novel verbs (e.g., the preference for a novel verb to…

Leadership Coaching: Building the Capacity of Urban Principals in Underperforming Schools

ERIC Educational Resources Information Center

Warren, Susan R.; Kelsen, Virginia E.

2013-01-01

This investigation assesses the effects of leadership coaching on the knowledge, skills, and dispositions of urban public school administrators in P-12 underperforming schools. The study specifically examines leadership, management, and student achievement growth during the time of coaching. Utilizing a mixed-methods approach, three domains were…

Taking a Closer Look at Your Informational Writing Instruction

ERIC Educational Resources Information Center

Beschorner, Beth; Hall, Anna H.

2018-01-01

When students write informational text, they have the opportunity to engage with meaningful topics, become curious about the world, learn domain-specific knowledge, and use academic vocabulary. Given the possibilities for learning through writing informational text, it is important for teachers to reflect on and improve their informational writing…

Intelligent Tutoring Systems for Scientific Inquiry Skills.

ERIC Educational Resources Information Center

Shute, Valerie; Bonar, Jeffrey

Described are the initial prototypes of several intelligent tutoring systems designed to build students' scientific inquiry skills. These inquiry skills are taught in the context of acquiring knowledge of principles from a microworld that models a specific domain. This paper discusses microworlds that have been implemented for microeconomics,…

Intelligent Tutoring Systems and Learning Outcomes: A Meta-Analysis

ERIC Educational Resources Information Center

Ma, Wenting; Adesope, Olusola O.; Nesbit, John C.; Liu, Qing

2014-01-01

Intelligent Tutoring Systems (ITS) are computer programs that model learners' psychological states to provide individualized instruction. They have been developed for diverse subject areas (e.g., algebra, medicine, law, reading) to help learners acquire domain-specific, cognitive and metacognitive knowledge. A meta-analysis was conducted on…

Rethinking the Boundaries of Cognitive Load Theory in Complex Learning

ERIC Educational Resources Information Center

Kalyuga, Slava; Singh, Anne-Marie

2016-01-01

In the traditional framework of cognitive load theory, it is assumed that the acquisition of domain-specific knowledge structures (or schemas) is the only instructional goal, and therefore, the theory is applicable to any instructional task. Accordingly, the basic concepts of intrinsic (productive) and extraneous (unproductive) types of cognitive…

The Contribution of Domain-Specific Knowledge in Predicting Students' Proportional Word Problem Solving Performance

ERIC Educational Resources Information Center

Jitendra, Asha K.; Lein, Amy E.; Star, Jon R.; Dupuis, Danielle N.

2013-01-01

Proportional thinking, which requires understanding fractions, ratios, and proportions, is an area of mathematics that is cognitively challenging for many children and adolescents (Fujimura, 2001; Lamon, 2007; Lobato, Ellis, Charles, & Zbiek, 2010; National Mathematics Advisory Panel [NMAP], 2008) and "transcends topical barriers in adult…

Creativity in Fashion Design Students

ERIC Educational Resources Information Center

Robinson, Joyce Robin

2011-01-01

The purpose of this study was to examine relationships among environmental influences, changes in domain specific knowledge, and changes in tolerance of ambiguity as well as changes in creativity of individuals majoring in fashion design at four-year universities. This study was based on the confluence theoretical approach which holds that…

Encoding of Geological knowledge in the GeoPiemonte Map Data Base

NASA Astrophysics Data System (ADS)

Piana, Fabrizio; Lombardo, Vincenzo; Mimmo, Dario; Barale, Luca; Irace, Andrea; Mulazzano, Elia

2017-04-01

In modern digital geological maps and geo-database, namely those devoted to interactive WebGIS services, there is the need to make explicit the geological assumptions in the process of the design and compilation of the Map Geodatabase. The Geodatabase of the Piemonte Geological Map, which consists of several thousands of Geologic Units and Geologic Structures, was designed in a way suitable for linking the knowledge of the geological domain at hand to more general levels of knowledge, represented in existing Earth Sciences ontologies and in a domain ontology (OntoGeonous), specifically designed for the project, though with a wide applicability in mind. The Geologic Units and Geologic Structures of the GeoPiemonte Map have been spatially correlated through the whole region, referring to a non-formal hierarchical scheme, which gives the parental relations between several orders of Geologic Units, putting them in relations with some main Geologic Events. The scheme reports the subdivisions we did on the Alps-Apennines orogenic belt (which constitutes the Piemonte geological framework) on which the architecture of the GeoDB relied. This contribution describes how the two different knowledge levels (specific domain vs. general knowledge) are assimilated within the GeoPiemonte informative system, providing relations between the contents of the geodatabase and the encoded concepts of the reference ontologies. Initiatives such as GeoScience Markup Language (GeoSciML 4.01, 2016 (1) and INSPIRE "Data Specification on Geology" (an operative simplification of GeoSciML, last version is 3.0, 2013) (2), as well as the recent terminological shepherding of the Geoscience Terminology Working Group (GTWG), provided us the authoritative standard geological source for knowledge encoding. Consistency and interoperability of geological data were thus sought, by classifying geologic features in an ontology-driven Data Model, while objects were described using GeoSciML controlled vocabularies and concepts derived from NASA SWEET ontology (3) (4) (5). At the state of the art the GeoPiemonte Map informative system is thus suitable for integration in trans-national Data Infrastructures and/or WebMap Services that require interoperability and harmonised semantic approaches. References (1)http://www.geosciml.org/geosciml/4.0/documentation/html/ - GeoSciML Data Model - (2)http://inspire.ec.europa.eu/documents/Data_Specifications/INSPIRE_DataSpecification_GE_v3.0.pdf - INSPIRE DS Technical Guidelines (3)http://resource.geosciml.org/vocabulary/cgi/201211/simplelithology.html (4)http://resource.geosciml.org/vocabulary/cgi/ - CGI GTWG controlled vocabularies repository (5) SWEET (Semantic Web for Earth and Environmental Terminology), http://www.sweet.jpl.nasa.govAppel Piana et al., 2017a. Geology of Piemonte Region (NW Italy, Alps-Apennines junction zone). Journal of Maps, in press. Piana et al., 2017b. The Geodatabase of the Piemonte Geological Map: conceptual design for knowledge encoding. ROL Soc. Geol. It., in press.

Distinct neural substrates for visual short-term memory of actions.

PubMed

Cai, Ying; Urgolites, Zhisen; Wood, Justin; Chen, Chuansheng; Li, Siyao; Chen, Antao; Xue, Gui

2018-06-26

Fundamental theories of human cognition have long posited that the short-term maintenance of actions is supported by one of the "core knowledge" systems of human visual cognition, yet its neural substrates are still not well understood. In particular, it is unclear whether the visual short-term memory (VSTM) of actions has distinct neural substrates or, as proposed by the spatio-object architecture of VSTM, shares them with VSTM of objects and spatial locations. In two experiments, we tested these two competing hypotheses by directly contrasting the neural substrates for VSTM of actions with those for objects and locations. Our results showed that the bilateral middle temporal cortex (MT) was specifically involved in VSTM of actions because its activation and its functional connectivity with the frontal-parietal network (FPN) were only modulated by the memory load of actions, but not by that of objects/agents or locations. Moreover, the brain regions involved in the maintenance of spatial location information (i.e., superior parietal lobule, SPL) was also recruited during the maintenance of actions, consistent with the temporal-spatial nature of actions. Meanwhile, the frontoparietal network (FPN) was commonly involved in all types of VSTM and showed flexible functional connectivity with the domain-specific regions, depending on the current working memory tasks. Together, our results provide clear evidence for a distinct neural system for maintaining actions in VSTM, which supports the core knowledge system theory and the domain-specific and domain-general architectures of VSTM. © 2018 Wiley Periodicals, Inc.

Is risk analysis scientific?

PubMed

Hansson, Sven Ove; Aven, Terje

2014-07-01

This article discusses to what extent risk analysis is scientific in view of a set of commonly used definitions and criteria. We consider scientific knowledge to be characterized by its subject matter, its success in developing the best available knowledge in its fields of study, and the epistemic norms and values that guide scientific investigations. We proceed to assess the field of risk analysis according to these criteria. For this purpose, we use a model for risk analysis in which science is used as a base for decision making on risks, which covers the five elements evidence, knowledge base, broad risk evaluation, managerial review and judgment, and the decision; and that relates these elements to the domains experts and decisionmakers, and to the domains fact-based or value-based. We conclude that risk analysis is a scientific field of study, when understood as consisting primarily of (i) knowledge about risk-related phenomena, processes, events, etc., and (ii) concepts, theories, frameworks, approaches, principles, methods and models to understand, assess, characterize, communicate, and manage risk, in general and for specific applications (the instrumental part). © 2014 Society for Risk Analysis.

Public attitudes toward biofuels. Effects of knowledge, political partisanship, and media use.

PubMed

Cacciatore, Michael A; Binder, Andrew R; Scheufele, Dietram A; Shaw, Bret R

2012-01-01

Despite large-scale investments and government mandates to expand biofuels development and infrastructure in the United States, little is known about how the public conceives of this alternative fuel technology. This study examines public opinion of biofuels by focusing on citizen knowledge and the motivated processing of media information. Specifically, we explore the direct effects of biofuels knowledge and the moderating effect of partisanship on the relationship between media use and benefit vs. risk perceptions in the following four domains: environmental impacts, economic consequences, ethical/social implications, and political ramifications. Our results suggest that more knowledgeable respondents see fewer benefits of biofuels relative to risks, and that Democrats and Republicans are affected differently by media use when forming opinions about biofuels. Among Democrats, greater attention to political media content leads to a more favorable outlook toward the technology across several domains of interest, while among Republicans, an increase in attention to political content has the opposite effect. Possible reasons for these results, as well as implications of the findings at the intersection of politics and the life sciences, are discussed.

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.

Articulation Management for Intelligent Integration of Information

NASA Technical Reports Server (NTRS)

Maluf, David A.; Tran, Peter B.; Clancy, Daniel (Technical Monitor)

2001-01-01

When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies and heterogeneity of representations, problems arise in combining multiple domains when the domains are merged. The knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. This heterogeneity problem can be eliminated by mediating the conflicts and managing the intersections of the domains. For interoperation and intelligent access to heterogeneous information, the focus is on the intersection of the knowledge, since intersection will define the required articulation rules. An algebra over domain has been proposed to use articulation rules to support disciplined manipulation of domain knowledge resources. The objective of a domain algebra is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The algebra supports formally the tasks of selecting, combining, extending, specializing, and modifying Components from a diverse set of domains. This paper presents a domain algebra and demonstrates the use of articulation rules to link declarative interfaces for Internet and enterprise applications. In particular, it discusses the articulation implementation as part of a production system capable of operating over the domain described by the IDL (interface description language) of objects registered in multiple CORBA servers.

Sources of Group and Individual Differences in Emerging Fraction Skills

PubMed Central

Hecht, Steven A.; Vagi, Kevin J.

2010-01-01

Results from a two year longitudinal study of 181 children from fourth through fifth grade are reported. Levels of growth in children’s computation, word problem, and estimation skills using common fractions were predicted by working memory, attentive classroom behavior, conceptual knowledge about fractions, and simple arithmetic fluency. Comparisons of 55 participants identified as having mathematical difficulties to those without mathematical difficulties revealed that group differences in emerging fraction skills were consistently mediated by attentive classroom behavior and conceptual knowledge about fractions. Neither working memory nor arithmetic fluency mediated group differences in growth in fraction skills. It was also found that the development of basic fraction skills and conceptual knowledge are bidirectional in that conceptual knowledge exerted strong influences on all three types of basic fraction skills, and basic fraction skills exerted a more modest influence on subsequent conceptual knowledge. Results are discussed with reference to how the identification of potentially malleable student characteristics that contribute to the difficulties that some students have with fractions informs interventions and also will contribute to a future theoretical account concerning how domain general and domain specific factors influence the development of basic fraction skills. PMID:21170171

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.

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration

PubMed Central

2011-01-01

Background Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. Results Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. Conclusions By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full preservation of data correspondence and provenance. Our representation builds on existing cheminformatics technologies and, by the virtue of RDF specification, remains flexible and amenable to application- and domain-specific annotations without compromising chemical data integration. We conclude that the adoption of a consistent and semantically-enabled chemical specification is imperative for surviving the coming chemical data deluge and supporting systems science research. PMID:21595881

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration.

PubMed

Chepelev, Leonid L; Dumontier, Michel

2011-05-19

Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full preservation of data correspondence and provenance. Our representation builds on existing cheminformatics technologies and, by the virtue of RDF specification, remains flexible and amenable to application- and domain-specific annotations without compromising chemical data integration. We conclude that the adoption of a consistent and semantically-enabled chemical specification is imperative for surviving the coming chemical data deluge and supporting systems science research.

Conceptual Structure within and between Modalities

PubMed Central

Dilkina, Katia; Lambon Ralph, Matthew A.

2012-01-01

Current views of semantic memory share the assumption that conceptual representations are based on multimodal experience, which activates distinct modality-specific brain regions. This proposition is widely accepted, yet little is known about how each modality contributes to conceptual knowledge and how the structure of this contribution varies across these multiple information sources. We used verbal feature lists, features from drawings, and verbal co-occurrence statistics from latent semantic analysis to examine the informational structure in four domains of knowledge: perceptual, functional, encyclopedic, and verbal. The goals of the analysis were three-fold: (1) to assess the structure within individual modalities; (2) to compare structures between modalities; and (3) to assess the degree to which concepts organize categorically or randomly. Our results indicated significant and unique structure in all four modalities: perceptually, concepts organize based on prominent features such as shape, size, color, and parts; functionally, they group based on use and interaction; encyclopedically, they arrange based on commonality in location or behavior; and verbally, they group associatively or relationally. Visual/perceptual knowledge gives rise to the strongest hierarchical organization and is closest to classic taxonomic structure. Information is organized somewhat similarly in the perceptual and encyclopedic domains, which differs significantly from the structure in the functional and verbal domains. Notably, the verbal modality has the most unique organization, which is not at all categorical but also not random. The idiosyncrasy and complexity of conceptual structure across modalities raise the question of how all of these modality-specific experiences are fused together into coherent, multifaceted yet unified concepts. Accordingly, both methodological and theoretical implications of the present findings are discussed. PMID:23293593

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.

Representation and presentation of requirements knowledge

NASA Technical Reports Server (NTRS)

Johnson, W. L.; Feather, Martin S.; Harris, David R.

1992-01-01

An approach to representation and presentation of knowledge used in the ARIES, an experimental requirements/specification environment, is described. The approach applies the notion of a representation architecture to the domain of software engineering and incorporates a strong coupling to a transformation system. It is characterized by a single highly expressive underlying representation, interfaced simultaneously to multiple presentations, each with notations of differing degrees of expressivity. This enables analysts to use multiple languages for describing systems and have these descriptions yield a single consistent model of the system.

Methodology for the specification of communication activities within the framework of a multi-layered architecture: Toward the definition of a knowledge base

NASA Astrophysics Data System (ADS)

Amyay, Omar

A method defined in terms of synthesis and verification steps is presented. The specification of the services and protocols of communication within a multilayered architecture of the Open Systems Interconnection (OSI) type is an essential issue for the design of computer networks. The aim is to obtain an operational specification of the protocol service couple of a given layer. Planning synthesis and verification steps constitute a specification trajectory. The latter is based on the progressive integration of the 'initial data' constraints and verification of the specification originating from each synthesis step, through validity constraints that characterize an admissible solution. Two types of trajectories are proposed according to the style of the initial specification of the service protocol couple: operational type and service supplier viewpoint; knowledge property oriented type and service viewpoint. Synthesis and verification activities were developed and formalized in terms of labeled transition systems, temporal logic and epistemic logic. The originality of the second specification trajectory and the use of the epistemic logic are shown. An 'artificial intelligence' approach enables a conceptual model to be defined for a knowledge base system for implementing the method proposed. It is structured in three levels of representation of the knowledge relating to the domain, the reasoning characterizing synthesis and verification activities and the planning of the steps of a specification trajectory.

Organizing knowledge for tutoring fire loss prevention

NASA Astrophysics Data System (ADS)

Schmoldt, Daniel L.

1989-09-01

The San Bernardino National Forest in southern California has recently developed a systematic approach to wildfire prevention planning. However, a comprehensive document or other mechanism for teaching this process to other prevention personnel does not exist. An intelligent tutorial expert system is being constructed to provide a means for learning the process and to assist in the creation of specific prevention plans. An intelligent tutoring system (ITS) contains two types of knowledge—domain and tutoring. The domain knowledge for wildfire prevention is structured around several foci: (1) individual concepts used in prevention planning; (2) explicitly specified interrelationships between concepts; (3) deductive methods that contain subjective judgment normally unavailable to less-experienced users; (4) analytical models of fire behavior used for identification of hazard areas; (5) how-to guidance needed for performance of planning tasks; and (6) expository information that provides a rationale for planning steps and ideas. Combining analytical, procedure, inferential, conceptual, and expositional knowledge into a tutoring environment provides the student and/or user with a multiple perspective of the subject matter. A concept network provides a unifying framework for structuring and utilizing these diverse forms of prevention planning knowledge. This network structure borrows from and combines semantic networks and frame-based knowledge representations. The flexibility of this organization facilitates an effective synthesis and organization of multiple knowledge forms.

Toward a Unified Theory of Visual Area V4

PubMed Central

Roe, Anna W.; Chelazzi, Leonardo; Connor, Charles E.; Conway, Bevil R.; Fujita, Ichiro; Gallant, Jack L.; Lu, Haidong; Vanduffel, Wim

2016-01-01

Visual area V4 is a midtier cortical area in the ventral visual pathway. It is crucial for visual object recognition and has been a focus of many studies on visual attention. However, there is no unifying view of V4’s role in visual processing. Neither is there an understanding of how its role in feature processing interfaces with its role in visual attention. This review captures our current knowledge of V4, largely derived from electrophysiological and imaging studies in the macaque monkey. Based on recent discovery of functionally specific domains in V4, we propose that the unifying function of V4 circuitry is to enable selective extraction of specific functional domain-based networks, whether it be by bottom-up specification of object features or by top-down attentionally driven selection. PMID:22500626

Knowledge vs. Action: Discrepancies in University Students' Knowledge about and Self-Reported Use of Self-Regulated Learning Strategies.

PubMed

Foerst, Nora M; Klug, Julia; Jöstl, Gregor; Spiel, Christiane; Schober, Barbara

2017-01-01

University students are supposed to be autonomous learners, able to adapt to an educational environment significantly less guided than school. Entering higher education poses a challenge of self-regulation, in which beginning students are often not prepared with self-regulation strategies needed. Since there are many studies assessing self-regulated learning (SRL) via classical self-reports, we know a lot about how students generally self-assess their SRL strategies. However, SRL and performance do not always correlate highly in these studies. The aim of the present study is to determine whether there are discrepancies between students' knowledge about SRL and their action in applying adequate SRL strategies in relevant learning situations. We also want to know whether such discrepancies generalize across domains and what the reasons for discrepancies are. The situation-specific Self-Regulated Learning Questionnaire for Action and Knowledge (SRL-QuAK) was used in a sample of 408 psychology and economic sciences students. Descriptive data analysis was conducted to determine potential discrepancies between SRL knowledge and action and differences between the study domains in an explorative way. The reasons for not using SRL-strategies were derived via qualitative content analysis. The results showed that although students had quite advanced knowledge of SRL strategies, they did not put this knowledge into action. This dissonance between SRL knowledge and action was found in both domains. In terms of reasons, students stated that they (a) lacked the time to use SRL strategies, (b) would not benefit from SRL strategies in the given situation, (c) would not be able to put the strategies to use effectively or (d) found it too arduous to use SRL strategies. The implications of these results will be discussed, e.g., the consequences for measures to overcome students' dissonance between knowledge and action and therefore to promote academic performance and well-being.

Knowledge vs. Action: Discrepancies in University Students' Knowledge about and Self-Reported Use of Self-Regulated Learning Strategies

PubMed Central

Foerst, Nora M.; Klug, Julia; Jöstl, Gregor; Spiel, Christiane; Schober, Barbara

2017-01-01

University students are supposed to be autonomous learners, able to adapt to an educational environment significantly less guided than school. Entering higher education poses a challenge of self-regulation, in which beginning students are often not prepared with self-regulation strategies needed. Since there are many studies assessing self-regulated learning (SRL) via classical self-reports, we know a lot about how students generally self-assess their SRL strategies. However, SRL and performance do not always correlate highly in these studies. The aim of the present study is to determine whether there are discrepancies between students' knowledge about SRL and their action in applying adequate SRL strategies in relevant learning situations. We also want to know whether such discrepancies generalize across domains and what the reasons for discrepancies are. The situation-specific Self-Regulated Learning Questionnaire for Action and Knowledge (SRL-QuAK) was used in a sample of 408 psychology and economic sciences students. Descriptive data analysis was conducted to determine potential discrepancies between SRL knowledge and action and differences between the study domains in an explorative way. The reasons for not using SRL-strategies were derived via qualitative content analysis. The results showed that although students had quite advanced knowledge of SRL strategies, they did not put this knowledge into action. This dissonance between SRL knowledge and action was found in both domains. In terms of reasons, students stated that they (a) lacked the time to use SRL strategies, (b) would not benefit from SRL strategies in the given situation, (c) would not be able to put the strategies to use effectively or (d) found it too arduous to use SRL strategies. The implications of these results will be discussed, e.g., the consequences for measures to overcome students' dissonance between knowledge and action and therefore to promote academic performance and well-being. PMID:28798713

Automating FEA programming

NASA Technical Reports Server (NTRS)

Sharma, Naveen

1992-01-01

In this paper we briefly describe a combined symbolic and numeric approach for solving mathematical models on parallel computers. An experimental software system, PIER, is being developed in Common Lisp to synthesize computationally intensive and domain formulation dependent phases of finite element analysis (FEA) solution methods. Quantities for domain formulation like shape functions, element stiffness matrices, etc., are automatically derived using symbolic mathematical computations. The problem specific information and derived formulae are then used to generate (parallel) numerical code for FEA solution steps. A constructive approach to specify a numerical program design is taken. The code generator compiles application oriented input specifications into (parallel) FORTRAN77 routines with the help of built-in knowledge of the particular problem, numerical solution methods and the target computer.

Structure-based multiscale approach for identification of interaction partners of PDZ domains.

PubMed

Tiwari, Garima; Mohanty, Debasisa

2014-04-28

PDZ domains are peptide recognition modules which mediate specific protein-protein interactions and are known to have a complex specificity landscape. We have developed a novel structure-based multiscale approach which identifies crucial specificity determining residues (SDRs) of PDZ domains from explicit solvent molecular dynamics (MD) simulations on PDZ-peptide complexes and uses these SDRs in combination with knowledge-based scoring functions for proteomewide identification of their interaction partners. Multiple explicit solvent simulations ranging from 5 to 50 ns duration have been carried out on 28 PDZ-peptide complexes with known binding affinities. MM/PBSA binding energy values calculated from these simulations show a correlation coefficient of 0.755 with the experimental binding affinities. On the basis of the SDRs of PDZ domains identified by MD simulations, we have developed a simple scoring scheme for evaluating binding energies for PDZ-peptide complexes using residue based statistical pair potentials. This multiscale approach has been benchmarked on a mouse PDZ proteome array data set by calculating the binding energies for 217 different substrate peptides in binding pockets of 64 different mouse PDZ domains. Receiver operating characteristic (ROC) curve analysis indicates that, the area under curve (AUC) values for binder vs nonbinder classification by our structure based method is 0.780. Our structure based method does not require experimental PDZ-peptide binding data for training.

Mechanisms and neural basis of object and pattern recognition: a study with chess experts.

PubMed

Bilalić, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

2010-11-01

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.

NovelFam3000 – Uncharacterized human protein domains conserved across model organisms

PubMed Central

Kemmer, Danielle; Podowski, Raf M; Arenillas, David; Lim, Jonathan; Hodges, Emily; Roth, Peggy; Sonnhammer, Erik LL; Höög, Christer; Wasserman, Wyeth W

2006-01-01

Background Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins. Description From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system. Conclusion Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families. PMID:16533400

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

PubMed

Abidi, Samina

2017-10-26

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

Age and Gender Differences in the Relation between Self-Concept Facets and Self-Esteem

ERIC Educational Resources Information Center

Arens, A. Katrin; Hasselhorn, Marcus

2014-01-01

This study tested whether the gender intensification hypothesis applies to relations between multiple domain-specific self-concept facets and self-esteem. This hypothesis predicts gender-stereotypic differences in these relations and assumes they intensify with age. Furthermore, knowledge about gender-related or age-related differences in…

Development and Validation of a Supportive Learning Environment for Expertise Development Questionnaire (SLEED-Q)

ERIC Educational Resources Information Center

Elvira, Quincy; Beausaert, Simon; Segers, Mien; Imants, Jeroen; Dankbaar, Ben

2016-01-01

Development of professional expertise is the process of continually transforming the repertoire of knowledge, skills and attitudes necessary to solve domain-specific problems which begins in late secondary education and continues during higher education and throughout professional life. One educational goal is to train students to think more like…

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis

PubMed Central

Miller, Matthew James; McGuire, Kerry M.; Feigh, Karen M.

2016-01-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity. The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design. PMID:28491008

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.

Decision Support System Requirements Definition for Human Extravehicular Activity Based on Cognitive Work Analysis.

PubMed

Miller, Matthew James; McGuire, Kerry M; Feigh, Karen M

2017-06-01

The design and adoption of decision support systems within complex work domains is a challenge for cognitive systems engineering (CSE) practitioners, particularly at the onset of project development. This article presents an example of applying CSE techniques to derive design requirements compatible with traditional systems engineering to guide decision support system development. Specifically, it demonstrates the requirements derivation process based on cognitive work analysis for a subset of human spaceflight operations known as extravehicular activity . The results are presented in two phases. First, a work domain analysis revealed a comprehensive set of work functions and constraints that exist in the extravehicular activity work domain. Second, a control task analysis was performed on a subset of the work functions identified by the work domain analysis to articulate the translation of subject matter states of knowledge to high-level decision support system requirements. This work emphasizes an incremental requirements specification process as a critical component of CSE analyses to better situate CSE perspectives within the early phases of traditional systems engineering design.

A matter of fact? Adolescents' assumptions about crime, laws, and authority and their domain-specific beliefs about punishment.

PubMed

Oosterhoff, Benjamin; Shook, Natalie J; Metzger, Aaron

2018-01-01

This study examined adolescents' beliefs about the amount of punishment individuals should receive for violating different laws and whether these beliefs are connected with their informational assumptions (i.e., perceived facts) about crime, laws, and authority. American adolescents (N = 340; M age  = 16.64, 58.2% female) reported their judgments concerning the appropriate punishment for violating laws regulating domain-specific behaviors and their informational assumptions regarding the prevalence and causes of crime, beliefs that authority is knowledgeable, and the purpose of punishment. Greater internal attributions for crime was associated with stronger punishment judgments for violating laws that regulate moral and conventional issues. Greater beliefs that punishment teaches right from wrong was associated with stronger punishment judgments for violating laws that regulate drug-related prudential issues, and lower punishment judgments for violating laws that regulate personal issues. Greater beliefs that authorities are more knowledgeable than others was associated with stronger punishment judgments for violating laws that regulate personal issues. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Design and evaluation of a digital module with guided peer feedback for student learning biotechnology and molecular life sciences, attitudinal change, and satisfaction.

PubMed

Noroozi, Omid; Mulder, Martin

2017-01-02

This study aims to investigate the impacts of a digital learning module with guided peer feedback on students' domain-specific knowledge gain and their attitudinal change in the field of biotechnology and molecular life sciences. The extent to which the use of this module is appreciated by students is studied as well. A pre-test, post-test design was used with 203 students who were randomly assigned to groups of three. They were asked to work on the digital module with the aim of exploring various perspectives, and the "pros and cons" on the topic of "Genetically Modified Organisms (GMOs)." The results suggest that the module can be used to foster students' domain-specific knowledge gain and their attitudinal change. Furthermore, the module was evaluated positively in terms of students' motivation and satisfaction with the learning experiences. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(1):31-39, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

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…

A filter-mediated communication model for design collaboration in building construction.

PubMed

Lee, Jaewook; Jeong, Yongwook; Oh, Minho; Hong, Seung Wan

2014-01-01

Multidisciplinary collaboration is an important aspect of modern engineering activities, arising from the growing complexity of artifacts whose design and construction require knowledge and skills that exceed the capacities of any one professional. However, current collaboration in the architecture, engineering, and construction industries often fails due to lack of shared understanding between different participants and limitations of their supporting tools. To achieve a high level of shared understanding, this study proposes a filter-mediated communication model. In the proposed model, participants retain their own data in the form most appropriate for their needs with domain-specific filters that transform the neutral representations into semantically rich ones, as needed by the participants. Conversely, the filters can translate semantically rich, domain-specific data into a neutral representation that can be accessed by other domain-specific filters. To validate the feasibility of the proposed model, we computationally implement the filter mechanism and apply it to a hypothetical test case. The result acknowledges that the filter mechanism can let the participants know ahead of time what will be the implications of their proposed actions, as seen from other participants' points of view.

Promoting Experimental Problem-solving Ability in Sixth-grade Students Through Problem-oriented Teaching of Ecology: Findings of an intervention study in a complex domain

NASA Astrophysics Data System (ADS)

Roesch, Frank; Nerb, Josef; Riess, Werner

2015-03-01

Our study investigated whether problem-oriented designed ecology lessons with phases of direct instruction and of open experimentation foster the development of cross-domain and domain-specific components of experimental problem-solving ability better than conventional lessons in science. We used a paper-and-pencil test to assess students' abilities in a quasi-experimental intervention study utilizing a pretest/posttest control-group design (N = 340; average performing sixth-grade students). The treatment group received lessons on forest ecosystems consistent with the principle of education for sustainable development. This learning environment was expected to help students enhance their ecological knowledge and their theoretical and methodological experimental competencies. Two control groups received either the teachers' usual lessons on forest ecosystems or non-specific lessons on other science topics. We found that the treatment promoted specific components of experimental problem-solving ability (generating epistemic questions, planning two-factorial experiments, and identifying correct experimental controls). However, the observed effects were small, and awareness for aspects of higher ecological experimental validity was not promoted by the treatment.

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

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.

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.

Memory integration in amnesia: prior knowledge supports verbal short-term memory.

PubMed

Race, Elizabeth; Palombo, Daniela J; Cadden, Margaret; Burke, Keely; Verfaellie, Mieke

2015-04-01

Short-term memory (STM) and long-term memory (LTM) have traditionally been considered cognitively distinct. However, it is known that STM can improve when to-be-remembered information appears in contexts that make contact with prior knowledge, suggesting a more interactive relationship between STM and LTM. The current study investigated whether the ability to leverage LTM in support of STM critically depends on the integrity of the hippocampus. Specifically, we investigated whether the hippocampus differentially supports between-domain versus within-domain STM-LTM integration given prior evidence that the representational domain of the elements being integrated in memory is a critical determinant of whether memory performance depends on the hippocampus. In Experiment 1, we investigated hippocampal contributions to within-domain STM-LTM integration by testing whether immediate verbal recall of words improves in MTL amnesic patients when words are presented in familiar verbal contexts (meaningful sentences) compared to unfamiliar verbal contexts (random word lists). Patients demonstrated a robust sentence superiority effect, whereby verbal STM performance improved in familiar compared to unfamiliar verbal contexts, and the magnitude of this effect did not differ from that in controls. In Experiment 2, we investigated hippocampal contributions to between-domain STM-LTM integration by testing whether immediate verbal recall of digits improves in MTL amnesic patients when digits are presented in a familiar visuospatial context (a typical keypad layout) compared to an unfamiliar visuospatial context (a random keypad layout). Immediate verbal recall improved in both patients and controls when digits were presented in the familiar compared to the unfamiliar keypad array, indicating a preserved ability to integrate activated verbal information with stored visuospatial knowledge. Together, these results demonstrate that immediate verbal recall in amnesia can benefit from two distinct types of semantic support, verbal and visuospatial, and that the hippocampus is not critical for leveraging stored semantic knowledge to improve memory performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Memory integration in amnesia: Prior knowledge supports verbal short-term memory

PubMed Central

Race, Elizabeth; Palombo, Daniela J.; Cadden, Margaret; Burke, Keely; Verfaellie, Mieke

2015-01-01

Short-term memory (STM) and long-term memory (LTM) have traditionally been considered cognitively distinct. However, it is known that STM can improve when to-be-remembered information appears in contexts that make contact with prior knowledge, suggesting a more interactive relationship between STM and LTM. The current study investigated whether the ability to leverage LTM in support of STM critically depends on the integrity of the hippocampus. Specifically, we investigated whether the hippocampus differentially supports between-domain versus within-domain STM–LTM integration given prior evidence that the representational domain of the elements being integrated in memory is a critical determinant of whether memory performance depends on the hippocampus. In Experiment 1, we investigated hippocampal contributions to within-domain STM–LTM integration by testing whether immediate verbal recall of words improves in MTL amnesic patients when words are presented in familiar verbal contexts (meaningful sentences) compared to unfamiliar verbal contexts (random word lists). Patients demonstrated a robust sentence superiority effect, whereby verbal STM performance improved in familiar compared to unfamiliar verbal contexts, and the magnitude of this effect did not differ from that in controls. In Experiment 2, we investigated hippocampal contributions to between-domain STM–LTM integration by testing whether immediate verbal recall of digits improves in MTL amnesic patients when digits are presented in a familiar visuospatial context (a typical keypad layout) compared to an unfamiliar visuospatial context (a random keypad layout). Immediate verbal recall improved in both patients and controls when digits were presented in the familiar compared to the unfamiliar keypad array, indicating a preserved ability to integrate activated verbal information with stored visuospatial knowledge. Together, these results demonstrate that immediate verbal recall in amnesia can benefit from two distinct types of semantic support, verbal and visuospatial, and that the hippocampus is not critical for leveraging stored semantic knowledge to improve memory performance. PMID:25752585

Exploring creative activity: a software environment for multimedia systems

NASA Astrophysics Data System (ADS)

Farrett, Peter W.; Jardine, David A.

1992-03-01

This paper examines various issues related to the theory, design, and implementation of a system that supports creative activity for a multimedia environment. The system incorporates artificial intelligence notions to acquire concepts of the problem domain. This paper investigates this environment by considering a model that is a basis for a system, which supports a history of user interaction. A multimedia system that supports creative activity is problematic. It must function as a tool allowing users to experiment dynamically with their own creative reasoning process--a very nebulous task environment. It should also support the acquisition of domain knowledge so that empirical observation can be further evaluated. This paper aims to illustrate that via the reuse of domain-specific knowledge, closely related ideas can be quickly developed. This approach is useful in the following sense: Multimedia navigational systems hardcode referential links with respect to a web or network. Although users can access or control navigation in a nonlinear (static) manner, these referential links are 'frozen' and can not capture their creative actions, which are essential in tutoring or learning applications. This paper describes a multimedia assistant based on the notion of knowledge- links, which allows users to navigate through creative information in a nonlinear (dynamic) fashion. A selection of prototype code based on object-oriented techniques and logic programming partially demonstrates this.

Selective deficit for people's names following left temporal damage: an impairment of domain-specific conceptual knowledge.

PubMed

Miceli, G; Capasso, R; Daniele, A; Esposito, T; Magarelli, M; Tomaiuolo, F

2000-09-01

As a consequence of a head trauma, APA presented with selective anomia for the names of familiar people, in the absence of comparable disorders for common names and other proper names. Face recognition was normal; and naming performance was unaffected by stimulus and response types. Selective proper name anomia was not due to effects of frequency of usage or of age of acquisition, or to selective memory/learning deficits for the names of people. Even though APA was able to provide at least some information on many celebrities whom she failed to name, she was clearly impaired in all tasks that required full conceptual information on the same people (but she performed flawlessly in similar tasks that involved common names). This pattern of performance indicates that in our subject the inability to name familiar persons results from damage to conceptual information. It is argued that detailed analyses of conceptual knowledge are necessary before it is concluded that a subject with proper name anomia suffers from a purely output disorder, as opposed to a conceptual disorder. The behaviour observed in APA is consistent with the domain-specific hypothesis of conceptual organisation (Caramazza & Shelton, 1998), and in this framework can be explained by assuming selective damage to knowledge of conspecifics. The anatomo-clinical correlates of our subject's disorder are discussed with reference to recent hypotheses on the neural structures representing knowledge of familiar people.

A viewpoint-based case-based reasoning approach utilising an enterprise architecture ontology for experience management

NASA Astrophysics Data System (ADS)

Martin, Andreas; Emmenegger, Sandro; Hinkelmann, Knut; Thönssen, Barbara

2017-04-01

The accessibility of project knowledge obtained from experiences is an important and crucial issue in enterprises. This information need about project knowledge can be different from one person to another depending on the different roles he or she has. Therefore, a new ontology-based case-based reasoning (OBCBR) approach that utilises an enterprise ontology is introduced in this article to improve the accessibility of this project knowledge. Utilising an enterprise ontology improves the case-based reasoning (CBR) system through the systematic inclusion of enterprise-specific knowledge. This enterprise-specific knowledge is captured using the overall structure given by the enterprise ontology named ArchiMEO, which is a partial ontological realisation of the enterprise architecture framework (EAF) ArchiMate. This ontological representation, containing historical cases and specific enterprise domain knowledge, is applied in a new OBCBR approach. To support the different information needs of different stakeholders, this OBCBR approach has been built in such a way that different views, viewpoints, concerns and stakeholders can be considered. This is realised using a case viewpoint model derived from the ISO/IEC/IEEE 42010 standard. The introduced approach was implemented as a demonstrator and evaluated using an application case that has been elicited from a business partner in the Swiss research project.

How Engineers Negotiate Domain Boundaries in a Complex, Interdisciplinary Engineering Project

NASA Technical Reports Server (NTRS)

Panther, Grace; Montfort, Devlin; Pirtle, Zachary

2017-01-01

Engineering educators have an essential role in preparing engineers to work in a complex, interdisciplinary workforce. While much engineering education focuses on teaching students to develop disciplinary expertise in specific engineering domains, there is a strong need to teach engineers about the knowledge that they develop or use in their work (Bucciarelli 1994, Allenby Sarewitz, 2011; Frodeman, 2013). The purpose of this research is to gain a better understanding of the knowledge systems of practicing engineers through observations of their practices such that the insights learned can guide future education efforts. Using an example from a complex and interdisciplinary engineering project, this paper presents a case study overviewing the types of epistemological (or knowledge-acquiring or using) complexities that engineers navigate. Specifically, we looked at a discussion of the thermal design of a CubeSat that occurred during an engineering review at NASA. We analyzed the review using a framework that we call 'peak events', or pointed discussions between reviewers, project engineers, and managers. We examined the dialog within peak events to identify the ways that knowledge was brought to bear, highlighting discussions of uncertainty and the boundaries of knowledge claims. We focus on one example discussion surrounding the thermal design of the CubeSat, which provides a particularly thorough example of a knowledge system since the engineers present explained, justified, negotiated, and defended knowledge within a social setting. Engineering students do not get much practice or instruction in explicitly negotiating knowledge systems and epistemic standards in this way. We highlight issues that should matter to engineering educators, such as the need to discuss what level of uncertainty is sufficient and the need to negotiate boundaries of system responsibility. Although this analysis is limited to a single discussion or 'peak event', our case shows that this type of discussion can occur in engineering and suggests that it could be important for future engineering education research.

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.

PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain.

PubMed

Younesi, Erfan; Malhotra, Ashutosh; Gündel, Michaela; Scordis, Phil; Kodamullil, Alpha Tom; Page, Matt; Müller, Bernd; Springstubbe, Stephan; Wüllner, Ullrich; Scheller, Dieter; Hofmann-Apitius, Martin

2015-09-22

Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson's disease. In the area of Parkinson's research, there is a pressing need to integrate various pieces of information into a meaningful context of presumed disease mechanism(s). Disease ontologies provide a novel means for organizing, integrating, and standardizing the knowledge domains specific to disease in a compact, formalized and computer-readable form and serve as a reference for knowledge exchange or systems modeling of disease mechanism. The Parkinson's disease ontology was built according to the life cycle of ontology building. Structural, functional, and expert evaluation of the ontology was performed to ensure the quality and usability of the ontology. A novelty metric has been introduced to measure the gain of new knowledge using the ontology. Finally, a cause-and-effect model was built around PINK1 and two gene expression studies from the Gene Expression Omnibus database were re-annotated to demonstrate the usability of the ontology. The Parkinson's disease ontology with a subclass-based taxonomic hierarchy covers the broad spectrum of major biomedical concepts from molecular to clinical features of the disease, and also reflects different views on disease features held by molecular biologists, clinicians and drug developers. The current version of the ontology contains 632 concepts, which are organized under nine views. The structural evaluation showed the balanced dispersion of concept classes throughout the ontology. The functional evaluation demonstrated that the ontology-driven literature search could gain novel knowledge not present in the reference Parkinson's knowledge map. The ontology was able to answer specific questions related to Parkinson's when evaluated by experts. Finally, the added value of the Parkinson's disease ontology is demonstrated by ontology-driven modeling of PINK1 and re-annotation of gene expression datasets relevant to Parkinson's disease. Parkinson's disease ontology delivers the knowledge domain of Parkinson's disease in a compact, computer-readable form, which can be further edited and enriched by the scientific community and also to be used to construct, represent and automatically extend Parkinson's-related computable models. A practical version of the Parkinson's disease ontology for browsing and editing can be publicly accessed at http://bioportal.bioontology.org/ontologies/PDON .

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

PubMed

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

2004-01-01

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

Specific previous experience affects perception of harmony and meter.

PubMed

Creel, Sarah C

2011-10-01

Prior knowledge shapes our experiences, but which prior knowledge shapes which experiences? This question is addressed in the domain of music perception. Three experiments were used to determine whether listeners activate specific musical memories during music listening. Each experiment provided listeners with one of two musical contexts that was presented simultaneously with a melody. After a listener was familiarized with melodies embedded in contexts, the listener heard melodies in isolation and judged the fit of a final harmonic or metrical probe event. The probe event matched either the familiar (but absent) context or an unfamiliar context. For both harmonic (Experiments 1 and 3) and metrical (Experiment 2) information, exposure to context shifted listeners' preferences toward a probe matching the context that they had been familiarized with. This suggests that listeners rapidly form specific musical memories without explicit instruction, which are then activated during music listening. These data pose an interesting challenge for models of music perception which implicitly assume that the listener's knowledge base is predominantly schematic or abstract.

Automated analysis of complex data

NASA Technical Reports Server (NTRS)

Saintamant, Robert; Cohen, Paul R.

1994-01-01

We have examined some of the issues involved in automating exploratory data analysis, in particular the tradeoff between control and opportunism. We have proposed an opportunistic planning solution for this tradeoff, and we have implemented a prototype, Igor, to test the approach. Our experience in developing Igor was surprisingly smooth. In contrast to earlier versions that relied on rule representation, it was straightforward to increment Igor's knowledge base without causing the search space to explode. The planning representation appears to be both general and powerful, with high level strategic knowledge provided by goals and plans, and the hooks for domain-specific knowledge are provided by monitors and focusing heuristics.

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…

Nursing constraint models for electronic health records: a vision for domain knowledge governance.

PubMed

Hovenga, Evelyn; Garde, Sebastian; Heard, Sam

2005-12-01

Various forms of electronic health records (EHRs) are currently being introduced in several countries. Nurses are primary stakeholders and need to ensure that their information and knowledge needs are being met by such systems information sharing between health care providers to enable them to improve the quality and efficiency of health care service delivery for all subjects of care. The latest international EHR standards have adopted the openEHR approach of two-level modelling. The first level is a stable information model determining structure, while the second level consists of constraint models or 'archetypes' that reflect the specifications or clinician rules for how clinical information needs to be represented to enable unambiguous data sharing. The current state of play in terms of international health informatics standards development activities is providing the nursing profession with a unique opportunity and challenge. Much work has been undertaken internationally in the area of nursing terminologies and evidence-based practice. This paper argues that to make the most of these emerging technologies and EHRs we must now concentrate on developing a process to identify, document, implement, manage and govern our nursing domain knowledge as well as contribute to the development of relevant international standards. It is argued that one comprehensive nursing terminology, such as the ICNP or SNOMED CT is simply too complex and too difficult to maintain. As the openEHR archetype approach does not rely heavily on big standardised terminologies, it offers more flexibility during standardisation of clinical concepts and it ensures open, future-proof electronic health records. We conclude that it is highly desirable for the nursing profession to adopt this openEHR approach as a means of documenting and governing the nursing profession's domain knowledge. It is essential for the nursing profession to develop its domain knowledge constraint models (archetypes) collaboratively in an international context.

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.

Reasoning in molecular genetics: From a cognitive model to instructional design

NASA Astrophysics Data System (ADS)

Duncan, Ravit Golan

Effective instruction strives to help students construct deep and meaningful understandings in a domain. A key component of designing such instruction is a good understanding of relevant aspects of student cognition in the domain. This entails understanding both the cognitive obstacles to learning and the knowledge elements that are crucial to successful reasoning in the domain. While understandings of student cognition are not a prescription for design, they can nonetheless help instructional-designers and design-researchers focus the design and suggest where and what scaffolding should be incorporated into the instructional sequence and activities. In this dissertation I first discuss my research of the cognitive aspects of reasoning in molecular genetics. By studying both high school and college level students' reasoning about genetic phenomena, I have constructed a conceptual model of reasoning in this domain. The model depicts critical types of domain-specific knowledge, the relationships between them, and their role in facilitating reasoning about genetic phenomena. I then describe the design and evaluation of a high school project-based curricular unit in genetics. The unit was developed by a collaborative team of teachers and a researcher and was enacted in a local public high school. The design process was closely guided by our understandings of student cognition in genetics and the resulting instructional intervention was aimed at scaffolding student engagement with important disciplinary strategies and concepts.

Involvement of family members in life with type 2 diabetes: Six interconnected problem domains of significance for family health identity and healthcare authenticity

PubMed Central

Grabowski, Dan; Andersen, Tue Helms; Varming, Annemarie; Ommundsen, Christine; Willaing, Ingrid

2017-01-01

Objectives: Family involvement plays a key role in diabetes management. Problems and challenges related to type 2-diabetes often affect the whole family, and relatives are at increased risk of developing diabetes themselves. We highlight these issues in our objectives: (1) to uncover specific family problems associated with mutual involvement in life with type 2-diabetes and (2) to analytically look at ways of approaching these problems in healthcare settings. Methods: Qualitative data were gathered in participatory problem assessment workshops. The data were analysed in three rounds using radical hermeneutics. Results: Problems were categorized in six domains: knowledge, communication, support, everyday life, roles and worries. The final cross-analysis focusing on the link between family identity and healthcare authenticity provided information on how the six domains can be approached in healthcare settings. Conclusion: The study generated important knowledge about problems associated with family involvement in life with type 2 diabetes and about how family involvement can be supported in healthcare practice. PMID:28839943

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

NASA Astrophysics Data System (ADS)

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

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

Evidence-based selection of theories for designing behaviour change interventions: using methods based on theoretical construct domains to understand clinicians' blood transfusion behaviour.

PubMed

Francis, Jill J; Stockton, Charlotte; Eccles, Martin P; Johnston, Marie; Cuthbertson, Brian H; Grimshaw, Jeremy M; Hyde, Chris; Tinmouth, Alan; Stanworth, Simon J

2009-11-01

Many theories of behaviour are potentially relevant to predictive and intervention studies but most studies investigate a narrow range of theories. Michie et al. (2005) agreed 12 'theoretical domains' from 33 theories that explain behaviour change. They developed a 'Theoretical Domains Interview' (TDI) for identifying relevant domains for specific clinical behaviours, but the framework has not been used for selecting theories for predictive studies. It was used here to investigate clinicians' transfusion behaviour in intensive care units (ICU). Evidence suggests that red blood cells transfusion could be reduced for some patients without reducing quality of care. (1) To identify the domains relevant to transfusion practice in ICUs and neonatal intensive care units (NICUs), using the TDI. (2) To use the identified domains to select appropriate theories for a study predicting transfusion behaviour. An adapted TDI about managing a patient with borderline haemoglobin by watching and waiting instead of transfusing red blood cells was used to conduct semi-structured, one-to-one interviews with 18 intensive care consultants and neonatologists across the UK. Relevant theoretical domains were: knowledge, beliefs about capabilities, beliefs about consequences, social influences, behavioural regulation. Further analysis at the construct level resulted in selection of seven theoretical approaches relevant to this context: Knowledge-Attitude-Behaviour Model, Theory of Planned Behaviour, Social Cognitive Theory, Operant Learning Theory, Control Theory, Normative Model of Work Team Effectiveness and Action Planning Approaches. This study illustrated, the use of the TDI to identify relevant domains in a complex area of inpatient care. This approach is potentially valuable for selecting theories relevant to predictive studies and resulted in greater breadth of potential explanations than would be achieved if a single theoretical model had been adopted.

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

PubMed

Beyan, Oya D; Baykal, Nazife

2012-02-01

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

Developing an Advanced Environment for Collaborative Computing

NASA Technical Reports Server (NTRS)

Becerra-Fernandez, Irma; Stewart, Helen; DelAlto, Martha; DelAlto, Martha; Knight, Chris

1999-01-01

Knowledge management in general tries to organize and make available important know-how, whenever and where ever is needed. Today, organizations rely on decision-makers to produce "mission critical" decisions that am based on inputs from multiple domains. The ideal decision-maker has a profound understanding of specific domains that influence the decision-making process coupled with the experience that allows them to act quickly and decisively on the information. In addition, learning companies benefit by not repeating costly mistakes, and by reducing time-to-market in Research & Development projects. Group-decision making tools can help companies make better decisions by capturing the knowledge from groups of experts. Furthermore, companies that capture their customers preferences can improve their customer service, which translates to larger profits. Therefore collaborative computing provides a common communication space, improves sharing of knowledge, provides a mechanism for real-time feedback on the tasks being performed, helps to optimize processes, and results in a centralized knowledge warehouse. This paper presents the research directions. of a project which seeks to augment an advanced collaborative web-based environment called Postdoc, with workflow capabilities. Postdoc is a "government-off-the-shelf" document management software developed at NASA-Ames Research Center (ARC).

An approach for formalising the supply chain operations

NASA Astrophysics Data System (ADS)

Zdravković, Milan; Panetto, Hervé; Trajanović, Miroslav; Aubry, Alexis

2011-11-01

Reference models play an important role in the knowledge management of the various complex collaboration domains (such as supply chain networks). However, they often show a lack of semantic precision and, they are sometimes incomplete. In this article, we present an approach to overcome semantic inconsistencies and incompleteness of the Supply Chain Operations Reference (SCOR) model and hence improve its usefulness and expand the application domain. First, we describe a literal web ontology language (OWL) specification of SCOR concepts (and related tools) built with the intention to preserve the original approach in the classification of process reference model entities, and hence enable the effectiveness of usage in original contexts. Next, we demonstrate the system for its exploitation, in specific - tools for SCOR framework browsing and rapid supply chain process configuration. Then, we describe the SCOR-Full ontology, its relations with relevant domain ontology and show how it can be exploited for improvement of SCOR ontological framework competence. Finally, we elaborate the potential impact of the presented approach, to interoperability of systems in supply chain networks.

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…

Reasoning about Benefits, Costs, and Risks of Chemical Substances: Mapping Different Levels of Sophistication

ERIC Educational Resources Information Center

Cullipher, S.; Sevian, H.; Talanquer, V.

2015-01-01

The ability to evaluate options and make informed decisions about problems in relevant contexts is a core competency in science education that requires the use of both domain-general and discipline-specific knowledge and reasoning strategies. In this study we investigated the implicit assumptions and modes of reasoning applied by individuals with…

Human vs. Computer Diagnosis of Students' Natural Selection Knowledge: Testing the Efficacy of Text Analytic Software

ERIC Educational Resources Information Center

Nehm, Ross H.; Haertig, Hendrik

2012-01-01

Our study examines the efficacy of Computer Assisted Scoring (CAS) of open-response text relative to expert human scoring within the complex domain of evolutionary biology. Specifically, we explored whether CAS can diagnose the explanatory elements (or Key Concepts) that comprise undergraduate students' explanatory models of natural selection with…

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,...

Dual Processes in the Psychology of Mathematics Education and Cognitive Psychology

ERIC Educational Resources Information Center

Gillard, Ellen; Van Dooren, Wim; Schaeken, Walter; Verschaffel, Lieven

2009-01-01

Research in the psychology of mathematics education has been confronted with the fact that people blatantly fail to solve tasks they are supposed to be able to solve correctly given their available domain-specific knowledge and skills. Also researchers in cognitive psychology have encountered such phenomena. In this paper, theories that have been…

PISA for Development System-Level Data. PISA for Development Brief 18

ERIC Educational Resources Information Center

OECD Publishing, 2017

2017-01-01

The PISA for Development brief series is a set of concise monthly education policy-oriented notes published by the OECD which are designed to describe a specific PISA for Development topic. In this brief, the role of PISA-D to assesses students' skills and knowledge in three cognitive domains--reading, mathematics and science--and collection of…

Conceptual Integration of Arithmetic Operations with Real-World Knowledge: Evidence from Event-Related Potentials

ERIC Educational Resources Information Center

Guthormsen, Amy M.; Fisher, Kristie J.; Bassok, Miriam; Osterhout, Lee; DeWolf, Melissa; Holyoak, Keith J.

2016-01-01

Research on language processing has shown that the disruption of conceptual integration gives rise to specific patterns of event-related brain potentials (ERPs)--N400 and P600 effects. Here, we report similar ERP effects when adults performed cross-domain conceptual integration of analogous semantic and mathematical relations. In a problem-solving…

Influence of Previous Knowledge, Language Skills and Domain-Specific Interest on Observation Competency

ERIC Educational Resources Information Center

Kohlhauf, Lucia; Rutke, Ulrike; Neuhaus, Birgit

2011-01-01

Many epoch-making biological discoveries (e.g. Darwinian Theory) were based upon observations. Nevertheless, observation is often regarded as "just looking" rather than a basic scientific skill. As observation is one of the main research methods in biological sciences, it must be considered as an independent research method and systematic practice…

Rethinking Research in Early Care and Education: Joining Sally's Quest

ERIC Educational Resources Information Center

New, Rebecca S.

2008-01-01

The article considers three domains of Sally Lubeck's scholarship as illustrations of her orientation to research on early care and education: her critique of positivism in general and the field of developmental psychology (and the sub-discipline of child development) specifically as the primary source of a "knowledge base" for the field of early…

A Kind of Expertise Reversal Effect: Personalisation Effect Can Depend on Domain-Specific Prior Knowledge

ERIC Educational Resources Information Center

Stiller, Klaus D.; Jedlicka, Rosemarie

2010-01-01

In instructional multimedia design, it is often recommended that text accompanying pictures be presented in a personalised style to promote learning. The superiority of personalised over formal text is may be explained using social agency theory (Mayer, 2005b), but it has not been investigated empirically whether such effects are valid in…

Newborns' Face Recognition Is Based on Spatial Frequencies below 0.5 Cycles per Degree

ERIC Educational Resources Information Center

de Heering, Adelaide; Turati, Chiara; Rossion, Bruno; Bulf, Hermann; Goffaux, Valerie; Simion, Francesca

2008-01-01

A critical question in Cognitive Science concerns how knowledge of specific domains emerges during development. Here we examined how limitations of the visual system during the first days of life may shape subsequent development of face processing abilities. By manipulating the bands of spatial frequencies of face images, we investigated what is…

The Role of Domain Knowledge in Creative Generation

ERIC Educational Resources Information Center

Ward, Thomas B.

2008-01-01

Previous studies have shown that a predominant tendency in creative generation tasks is to base new ideas on well-known, specific instances of previous ideas (e.g., basing ideas for imaginary aliens on dogs, cats or bears). However, a substantial minority of individuals has been shown to adopt more abstract approaches to the task and to develop…

What Are Standardized Literacy and Numeracy Tests Testing? Evidence of the Domain-General Contributions to Students' Standardized Educational Test Performance

ERIC Educational Resources Information Center

Howard, Steven J.; Woodcock, Stuart; Ehrich, John; Bokosmaty, Sahar

2017-01-01

Background: A fundamental aim of standardized educational assessment is to achieve reliable discrimination between students differing in the knowledge, skills and abilities assessed. However, questions of the purity with which these tests index students' genuine abilities have arisen. Specifically, literacy and numeracy assessments may also engage…

Policy Space and the Governance of Education: Transnational Influences on Institutions and Identities in the Netherlands and the UK

ERIC Educational Resources Information Center

Alexiadou, Nafsika; van de Bunt-Kokhuis, Sylvia

2013-01-01

This article presents a comparative analysis of two country-specific cases. The comparative analysis is situated within the broad domain of the changing knowledge economy landscape for educational policy. The two cases examine the transfer, embedding and enactment of policies during the interactions between supranational, national, institutional…

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…

Academic Self-Efficacy in Study-Related Skills and Behaviours: Relations with Learning-related Emotions and Academic Success

ERIC Educational Resources Information Center

Putwain, Dave; Sander, Paul; Larkin, Derek

2013-01-01

Background: Academic self-efficacy, when operationalized as mastery over domain-specific knowledge, has been found to be a predictor of academic achievement and emotions. Although academic emotions are also a predictor of academic achievement, there is limited evidence for reciprocal relations with academic achievement. Aims: To examine whether…

Accelerating Preschoolers' Early Literacy Development through Classroom-Based Teacher-Child Storybook Reading and Explicit Print Referencing

ERIC Educational Resources Information Center

Justice, Laura M.; Kaderavek, Joan N.; Fan, Xitao; Sofka, Amy; Hunt, Aileen

2009-01-01

Purpose: This study examined the impact of teacher use of a print referencing style during classroom-based storybook reading sessions conducted over an academic year. Impacts on preschoolers' early literacy development were examined, focusing specifically on the domain of print knowledge. Method: This randomized, controlled trial examined the…

Cooperative analysis expert situation assessment research

NASA Technical Reports Server (NTRS)

Mccown, Michael G.

1987-01-01

For the past few decades, Rome Air Development Center (RADC) has been conducting research in Artificial Intelligence (AI). When the recent advances in hardware technology made many AI techniques practical, the Intelligence and Reconnaissance Directorate of RADC initiated an applications program entitled Knowledge Based Intelligence Systems (KBIS). The goal of the program is the development of a generic Intelligent Analyst System, an open machine with the framework for intelligence analysis, natural language processing, and man-machine interface techniques, needing only the specific problem domain knowledge to be operationally useful. The development of KBIS is described.

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

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.

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.

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…

Model compilation: An approach to automated model derivation

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning.

PubMed

Pilarski, Patrick M; Dawson, Michael R; Degris, Thomas; Fahimi, Farbod; Carey, Jason P; Sutton, Richard S

2011-01-01

As a contribution toward the goal of adaptable, intelligent artificial limbs, this work introduces a continuous actor-critic reinforcement learning method for optimizing the control of multi-function myoelectric devices. Using a simulated upper-arm robotic prosthesis, we demonstrate how it is possible to derive successful limb controllers from myoelectric data using only a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees. To our knowledge, this is the first my-oelectric control approach that facilitates the online learning of new amputee-specific motions based only on a one-dimensional (scalar) feedback signal provided by the user of the prosthesis. © 2011 IEEE

Computer vision for general purpose visual inspection: a fuzzy logic approach

NASA Astrophysics Data System (ADS)

Chen, Y. H.

In automatic visual industrial inspection, computer vision systems have been widely used. Such systems are often application specific, and therefore require domain knowledge in order to have a successful implementation. Since visual inspection can be viewed as a decision making process, it is argued that the integration of fuzzy logic analysis and computer vision systems provides a practical approach to general purpose visual inspection applications. This paper describes the development of an integrated fuzzy-rule-based automatic visual inspection system. Domain knowledge about a particular application is represented as a set of fuzzy rules. From the status of predefined fuzzy variables, the set of fuzzy rules are defuzzified to give the inspection results. A practical application where IC marks (often in the forms of English characters and a company logo) inspection is demonstrated, which shows a more consistent result as compared to a conventional thresholding method.

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.

Query-oriented evidence extraction to support evidence-based medicine practice.

PubMed

Sarker, Abeed; Mollá, Diego; Paris, Cecile

2016-02-01

Evidence-based medicine practice requires medical practitioners to rely on the best available evidence, in addition to their expertise, when making clinical decisions. The medical domain boasts a large amount of published medical research data, indexed in various medical databases such as MEDLINE. As the size of this data grows, practitioners increasingly face the problem of information overload, and past research has established the time-associated obstacles faced by evidence-based medicine practitioners. In this paper, we focus on the problem of automatic text summarisation to help practitioners quickly find query-focused information from relevant documents. We utilise an annotated corpus that is specialised for the task of evidence-based summarisation of text. In contrast to past summarisation approaches, which mostly rely on surface level features to identify salient pieces of texts that form the summaries, our approach focuses on the use of corpus-based statistics, and domain-specific lexical knowledge for the identification of summary contents. We also apply a target-sentence-specific summarisation technique that reduces the problem of underfitting that persists in generic summarisation models. In automatic evaluations run over a large number of annotated summaries, our extractive summarisation technique statistically outperforms various baseline and benchmark summarisation models with a percentile rank of 96.8%. A manual evaluation shows that our extractive summarisation approach is capable of selecting content with high recall and precision, and may thus be used to generate bottom-line answers to practitioners' queries. Our research shows that the incorporation of specialised data and domain-specific knowledge can significantly improve text summarisation performance in the medical domain. Due to the vast amounts of medical text available, and the high growth of this form of data, we suspect that such summarisation techniques will address the time-related obstacles associated with evidence-based medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

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:…

Toward an interim standard for patient-centered knowledge-access.

PubMed Central

Tuttle, M. S.; Sherertz, D. D.; Fagan, L. M.; Carlson, R. W.; Cole, W. G.; Schipma, P. B.; Nelson, S. J.

1993-01-01

Most care-giver "knowledge" needs arise at the point of care and are "patient-centered." Many of these knowledge needs can be met using existing on-line knowledge sources, but the process is too time-consuming, currently, for even the computer-proficient. We are developing a set of public domain standards aimed at bringing potentially relevant knowledge to the point of care in a straight-forward and timely fashion. The standards will a) make use of selected items from a Computer-based Patient Record (CPR), e.g., a diagnosis and measure of severity, b) anticipate certain care-giver knowledge needs, e.g., "therapy," "protocols," "complications," and c) try to satisfy those needs from available knowledge sources, e.g., knowledge-bases, citation databases, practice guidelines, and on-line textbooks. The standards will use templates, i.e., fill-in-the-blank structures, to anticipate knowledge needs and UMLS Metathesaurus enhancements to represent the content of knowledge sources. Together, the standards will form the specification for a "Knowledge-Server" (KS) designed to be accessed from any CPR system. Plans are in place to test an interim version of this specification in the context of medical oncology. We are accumulating anecdotal evidence that a KS operating in conjunction with a CPR is much more compelling to users than either a CPR or a KS operating alone. PMID:8130537

Toward More Accurate Iris Recognition Using Cross-Spectral Matching.

PubMed

Nalla, Pattabhi Ramaiah; Kumar, Ajay

2017-01-01

Iris recognition systems are increasingly deployed for large-scale applications such as national ID programs, which continue to acquire millions of iris images to establish identity among billions. However, with the availability of variety of iris sensors that are deployed for the iris imaging under different illumination/environment, significant performance degradation is expected while matching such iris images acquired under two different domains (either sensor-specific or wavelength-specific). This paper develops a domain adaptation framework to address this problem and introduces a new algorithm using Markov random fields model to significantly improve cross-domain iris recognition. The proposed domain adaptation framework based on the naive Bayes nearest neighbor classification uses a real-valued feature representation, which is capable of learning domain knowledge. Our approach to estimate corresponding visible iris patterns from the synthesis of iris patches in the near infrared iris images achieves outperforming results for the cross-spectral iris recognition. In this paper, a new class of bi-spectral iris recognition system that can simultaneously acquire visible and near infra-red images with pixel-to-pixel correspondences is proposed and evaluated. This paper presents experimental results from three publicly available databases; PolyU cross-spectral iris image database, IIITD CLI and UND database, and achieve outperforming results for the cross-sensor and cross-spectral iris matching.

Incomplete Multisource Transfer Learning.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2018-02-01

Transfer learning is generally exploited to adapt well-established source knowledge for learning tasks in weakly labeled or unlabeled target domain. Nowadays, it is common to see multiple sources available for knowledge transfer, each of which, however, may not include complete classes information of the target domain. Naively merging multiple sources together would lead to inferior results due to the large divergence among multiple sources. In this paper, we attempt to utilize incomplete multiple sources for effective knowledge transfer to facilitate the learning task in target domain. To this end, we propose an incomplete multisource transfer learning through two directional knowledge transfer, i.e., cross-domain transfer from each source to target, and cross-source transfer. In particular, in cross-domain direction, we deploy latent low-rank transfer learning guided by iterative structure learning to transfer knowledge from each single source to target domain. This practice reinforces to compensate for any missing data in each source by the complete target data. While in cross-source direction, unsupervised manifold regularizer and effective multisource alignment are explored to jointly compensate for missing data from one portion of source to another. In this way, both marginal and conditional distribution discrepancy in two directions would be mitigated. Experimental results on standard cross-domain benchmarks and synthetic data sets demonstrate the effectiveness of our proposed model in knowledge transfer from incomplete multiple sources.

IMAGESEER - IMAGEs for Education and Research

NASA Technical Reports Server (NTRS)

Le Moigne, Jacqueline; Grubb, Thomas; Milner, Barbara

2012-01-01

IMAGESEER is a new Web portal that brings easy access to NASA image data for non-NASA researchers, educators, and students. The IMAGESEER Web site and database are specifically designed to be utilized by the university community, to enable teaching image processing (IP) techniques on NASA data, as well as to provide reference benchmark data to validate new IP algorithms. Along with the data and a Web user interface front-end, basic knowledge of the application domains, benchmark information, and specific NASA IP challenges (or case studies) are provided.

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

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

PubMed

Shin, Jaeho; Ré, Christopher; Cafarella, Michael

2015-08-01

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

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.

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.

Knowledge-based public health situation awareness

NASA Astrophysics Data System (ADS)

Mirhaji, Parsa; Zhang, Jiajie; Srinivasan, Arunkumar; Richesson, Rachel L.; Smith, Jack W.

2004-09-01

There have been numerous efforts to create comprehensive databases from multiple sources to monitor the dynamics of public health and most specifically to detect the potential threats of bioterrorism before widespread dissemination. But there are not many evidences for the assertion that these systems are timely and dependable, or can reliably identify man made from natural incident. One must evaluate the value of so called 'syndromic surveillance systems' along with the costs involved in design, development, implementation and maintenance of such systems and the costs involved in investigation of the inevitable false alarms1. In this article we will introduce a new perspective to the problem domain with a shift in paradigm from 'surveillance' toward 'awareness'. As we conceptualize a rather different approach to tackle the problem, we will introduce a different methodology in application of information science, computer science, cognitive science and human-computer interaction concepts in design and development of so called 'public health situation awareness systems'. We will share some of our design and implementation concepts for the prototype system that is under development in the Center for Biosecurity and Public Health Informatics Research, in the University of Texas Health Science Center at Houston. The system is based on a knowledgebase containing ontologies with different layers of abstraction, from multiple domains, that provide the context for information integration, knowledge discovery, interactive data mining, information visualization, information sharing and communications. The modular design of the knowledgebase and its knowledge representation formalism enables incremental evolution of the system from a partial system to a comprehensive knowledgebase of 'public health situation awareness' as it acquires new knowledge through interactions with domain experts or automatic discovery of new knowledge.

Deep transfer learning for automatic target classification: MWIR to LWIR

NASA Astrophysics Data System (ADS)

Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

2016-05-01

Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

PubMed

Willemsen, A M; Jansen, G A; Komen, J C; van Hooff, S; Waterham, H R; Brites, P M T; Wanders, R J A; van Kampen, A H C

2008-08-15

One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

A cross-country comparison of intensive care physicians' beliefs about their transfusion behaviour: a qualitative study using the Theoretical Domains Framework.

PubMed

Islam, Rafat; Tinmouth, Alan T; Francis, Jill J; Brehaut, Jamie C; Born, Jennifer; Stockton, Charlotte; Stanworth, Simon J; Eccles, Martin P; Cuthbertson, Brian H; Hyde, Chris; Grimshaw, Jeremy M

2012-09-21

Evidence of variations in red blood cell transfusion practices have been reported in a wide range of clinical settings. Parallel studies in Canada and the United Kingdom were designed to explore transfusion behaviour in intensive care physicians. The aim of this paper is three-fold: first, to explore beliefs that influence Canadian intensive care physicians' transfusion behaviour; second, to systematically select relevant theories and models using the Theoretical Domains Framework (TDF) to inform a future predictive study; and third, to compare its results with the UK study. Ten intensive care unit (ICU) physicians throughout Canada were interviewed. Physicians' responses were coded into theoretical domains, and specific beliefs were generated for each response. Theoretical domains relevant to behaviour change were identified, and specific constructs from the relevant domains were used to select psychological theories. The results from Canada and the United Kingdom were compared. Seven theoretical domains populated by 31 specific beliefs were identified as relevant to the target behaviour. The domains Beliefs about capabilities (confident to not transfuse if patients' clinical condition is stable), Beliefs about consequences (positive beliefs of reducing infection and saving resources and negative beliefs about risking patients' clinical outcome and potentially more work), Social influences (transfusion decision is influenced by team members and patients' relatives), and Behavioural regulation (wide range of approaches to encourage restrictive transfusion) that were identified in the UK study were also relevant in the Canadian context. Three additional domains, Knowledge (it requires more evidence to support restrictive transfusion), Social/professional role and identity (conflicting beliefs about not adhering to guidelines, referring to evidence, believing restrictive transfusion as professional standard, and believing that guideline is important for other professionals), and Motivation and goals (opposing beliefs about the importance of restrictive transfusion and compatibility with other goals), were also identified in this study. Similar to the UK study, the Theory of Planned Behaviour, Social Cognitive Theory, Operant Learning Theory, Action Planning, and Knowledge-Attitude-Behaviour model were identified as potentially relevant theories and models for further study. Personal project analysis was added to the Canadian study to explore the Motivation and goals domain in further detail. A wide range of beliefs was identified by the Canadian ICU physicians as likely to influence their transfusion behaviour. We were able to demonstrate similar though not identical results in a cross-country comparison. Designing targeted behaviour-change interventions based on unique beliefs identified by physicians from two countries are more likely to encourage restrictive transfusion in ICU physicians in respective countries. This needs to be tested in future prospective clinical trials.

A cross-country comparison of intensive care physicians’ beliefs about their transfusion behaviour: A qualitative study using the theoretical domains framework

PubMed Central

2012-01-01

Background Evidence of variations in red blood cell transfusion practices have been reported in a wide range of clinical settings. Parallel studies in Canada and the United Kingdom were designed to explore transfusion behaviour in intensive care physicians. The aim of this paper is three-fold: first, to explore beliefs that influence Canadian intensive care physicians’ transfusion behaviour; second, to systematically select relevant theories and models using the Theoretical Domains Framework (TDF) to inform a future predictive study; and third, to compare its results with the UK study. Methods Ten intensive care unit (ICU) physicians throughout Canada were interviewed. Physicians’ responses were coded into theoretical domains, and specific beliefs were generated for each response. Theoretical domains relevant to behaviour change were identified, and specific constructs from the relevant domains were used to select psychological theories. The results from Canada and the United Kingdom were compared. Results Seven theoretical domains populated by 31 specific beliefs were identified as relevant to the target behaviour. The domains Beliefs about capabilities (confident to not transfuse if patients’ clinical condition is stable), Beliefs about consequences (positive beliefs of reducing infection and saving resources and negative beliefs about risking patients’ clinical outcome and potentially more work), Social influences (transfusion decision is influenced by team members and patients’ relatives), and Behavioural regulation (wide range of approaches to encourage restrictive transfusion) that were identified in the UK study were also relevant in the Canadian context. Three additional domains, Knowledge (it requires more evidence to support restrictive transfusion), Social/professional role and identity (conflicting beliefs about not adhering to guidelines, referring to evidence, believing restrictive transfusion as professional standard, and believing that guideline is important for other professionals), and Motivation and goals (opposing beliefs about the importance of restrictive transfusion and compatibility with other goals), were also identified in this study. Similar to the UK study, the Theory of Planned Behaviour, Social Cognitive Theory, Operant Learning Theory, Action Planning, and Knowledge-Attitude-Behaviour model were identified as potentially relevant theories and models for further study. Personal project analysis was added to the Canadian study to explore the Motivation and goals domain in further detail. Conclusions A wide range of beliefs was identified by the Canadian ICU physicians as likely to influence their transfusion behaviour. We were able to demonstrate similar though not identical results in a cross-country comparison. Designing targeted behaviour-change interventions based on unique beliefs identified by physicians from two countries are more likely to encourage restrictive transfusion in ICU physicians in respective countries. This needs to be tested in future prospective clinical trials. PMID:22999460

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.

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.

Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge

NASA Astrophysics Data System (ADS)

van Elk, Michiel; van Schie, Hein; Bekkering, Harold

2014-06-01

Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain.

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

What can management theories offer evidence-based practice? A comparative analysis of measurement tools for organisational context.

PubMed

French, Beverley; Thomas, Lois H; Baker, Paula; Burton, Christopher R; Pennington, Lindsay; Roddam, Hazel

2009-05-19

Given the current emphasis on networks as vehicles for innovation and change in health service delivery, the ability to conceptualize and measure organisational enablers for the social construction of knowledge merits attention. This study aimed to develop a composite tool to measure the organisational context for evidence-based practice (EBP) in healthcare. A structured search of the major healthcare and management databases for measurement tools from four domains: research utilisation (RU), research activity (RA), knowledge management (KM), and organisational learning (OL). Included studies were reports of the development or use of measurement tools that included organisational factors. Tools were appraised for face and content validity, plus development and testing methods. Measurement tool items were extracted, merged across the four domains, and categorised within a constructed framework describing the absorptive and receptive capacities of organisations. Thirty measurement tools were identified and appraised. Eighteen tools from the four domains were selected for item extraction and analysis. The constructed framework consists of seven categories relating to three core organisational attributes of vision, leadership, and a learning culture, and four stages of knowledge need, acquisition of new knowledge, knowledge sharing, and knowledge use. Measurement tools from RA or RU domains had more items relating to the categories of leadership, and acquisition of new knowledge; while tools from KM or learning organisation domains had more items relating to vision, learning culture, knowledge need, and knowledge sharing. There was equal emphasis on knowledge use in the different domains. If the translation of evidence into knowledge is viewed as socially mediated, tools to measure the organisational context of EBP in healthcare could be enhanced by consideration of related concepts from the organisational and management sciences. Comparison of measurement tools across domains suggests that there is scope within EBP for supplementing the current emphasis on human and technical resources to support information uptake and use by individuals. Consideration of measurement tools from the fields of KM and OL shows more content related to social mechanisms to facilitate knowledge recognition, translation, and transfer between individuals and groups.

What can management theories offer evidence-based practice? A comparative analysis of measurement tools for organisational context

PubMed Central

French, Beverley; Thomas, Lois H; Baker, Paula; Burton, Christopher R; Pennington, Lindsay; Roddam, Hazel

2009-01-01

Background Given the current emphasis on networks as vehicles for innovation and change in health service delivery, the ability to conceptualise and measure organisational enablers for the social construction of knowledge merits attention. This study aimed to develop a composite tool to measure the organisational context for evidence-based practice (EBP) in healthcare. Methods A structured search of the major healthcare and management databases for measurement tools from four domains: research utilisation (RU), research activity (RA), knowledge management (KM), and organisational learning (OL). Included studies were reports of the development or use of measurement tools that included organisational factors. Tools were appraised for face and content validity, plus development and testing methods. Measurement tool items were extracted, merged across the four domains, and categorised within a constructed framework describing the absorptive and receptive capacities of organisations. Results Thirty measurement tools were identified and appraised. Eighteen tools from the four domains were selected for item extraction and analysis. The constructed framework consists of seven categories relating to three core organisational attributes of vision, leadership, and a learning culture, and four stages of knowledge need, acquisition of new knowledge, knowledge sharing, and knowledge use. Measurement tools from RA or RU domains had more items relating to the categories of leadership, and acquisition of new knowledge; while tools from KM or learning organisation domains had more items relating to vision, learning culture, knowledge need, and knowledge sharing. There was equal emphasis on knowledge use in the different domains. Conclusion If the translation of evidence into knowledge is viewed as socially mediated, tools to measure the organisational context of EBP in healthcare could be enhanced by consideration of related concepts from the organisational and management sciences. Comparison of measurement tools across domains suggests that there is scope within EBP for supplementing the current emphasis on human and technical resources to support information uptake and use by individuals. Consideration of measurement tools from the fields of KM and OL shows more content related to social mechanisms to facilitate knowledge recognition, translation, and transfer between individuals and groups. PMID:19454008

CSEO – the Cigarette Smoke Exposure Ontology

PubMed Central

2014-01-01

Background In the past years, significant progress has been made to develop and use experimental settings for extensive data collection on tobacco smoke exposure and tobacco smoke exposure-associated diseases. Due to the growing number of such data, there is a need for domain-specific standard ontologies to facilitate the integration of tobacco exposure data. Results The CSEO (version 1.0) is composed of 20091 concepts. The ontology in its current form is able to capture a wide range of cigarette smoke exposure concepts within the knowledge domain of exposure science with a reasonable sensitivity and specificity. Moreover, it showed a promising performance when used to answer domain expert questions. The CSEO complies with standard upper-level ontologies and is freely accessible to the scientific community through a dedicated wiki at https://publicwiki-01.fraunhofer.de/CSEO-Wiki/index.php/Main_Page. Conclusions The CSEO has potential to become a widely used standard within the academic and industrial community. Mainly because of the emerging need of systems toxicology to controlled vocabularies and also the lack of suitable ontologies for this domain, the CSEO prepares the ground for integrative systems-based research in the exposure science. PMID:25093069

Graph-based biomedical text summarization: An itemset mining and sentence clustering approach.

PubMed

Nasr Azadani, Mozhgan; Ghadiri, Nasser; Davoodijam, Ensieh

2018-06-12

Automatic text summarization offers an efficient solution to access the ever-growing amounts of both scientific and clinical literature in the biomedical domain by summarizing the source documents while maintaining their most informative contents. In this paper, we propose a novel graph-based summarization method that takes advantage of the domain-specific knowledge and a well-established data mining technique called frequent itemset mining. Our summarizer exploits the Unified Medical Language System (UMLS) to construct a concept-based model of the source document and mapping the document to the concepts. Then, it discovers frequent itemsets to take the correlations among multiple concepts into account. The method uses these correlations to propose a similarity function based on which a represented graph is constructed. The summarizer then employs a minimum spanning tree based clustering algorithm to discover various subthemes of the document. Eventually, it generates the final summary by selecting the most informative and relative sentences from all subthemes within the text. We perform an automatic evaluation over a large number of summaries using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics. The results demonstrate that the proposed summarization system outperforms various baselines and benchmark approaches. The carried out research suggests that the incorporation of domain-specific knowledge and frequent itemset mining equips the summarization system in a better way to address the informativeness measurement of the sentences. Moreover, clustering the graph nodes (sentences) can enable the summarizer to target different main subthemes of a source document efficiently. The evaluation results show that the proposed approach can significantly improve the performance of the summarization systems in the biomedical domain. Copyright © 2018. Published by Elsevier Inc.

Affective cognition: Exploring lay theories of emotion.

PubMed

Ong, Desmond C; Zaki, Jamil; Goodman, Noah D

2015-10-01

Humans skillfully reason about others' emotions, a phenomenon we term affective cognition. Despite its importance, few formal, quantitative theories have described the mechanisms supporting this phenomenon. We propose that affective cognition involves applying domain-general reasoning processes to domain-specific content knowledge. Observers' knowledge about emotions is represented in rich and coherent lay theories, which comprise consistent relationships between situations, emotions, and behaviors. Observers utilize this knowledge in deciphering social agents' behavior and signals (e.g., facial expressions), in a manner similar to rational inference in other domains. We construct a computational model of a lay theory of emotion, drawing on tools from Bayesian statistics, and test this model across four experiments in which observers drew inferences about others' emotions in a simple gambling paradigm. This work makes two main contributions. First, the model accurately captures observers' flexible but consistent reasoning about the ways that events and others' emotional responses to those events relate to each other. Second, our work models the problem of emotional cue integration-reasoning about others' emotion from multiple emotional cues-as rational inference via Bayes' rule, and we show that this model tightly tracks human observers' empirical judgments. Our results reveal a deep structural relationship between affective cognition and other forms of inference, and suggest wide-ranging applications to basic psychological theory and psychiatry. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

A randomized trial testing the superiority of a post-discharge care management model for stroke survivors

PubMed Central

Allen, Kyle; Hazelett, Susan; Jarjoura, David; Hua, Keding; Wright, Kathy; Weinhardt, Janice; Kropp, Denise

2009-01-01

Objective To evaluate whether comprehensive post-discharge care management for stroke survivors is superior to organized acute stroke unit care with enhanced discharge planning in improving a profile of health and well-being. Methods This was a randomized trial of a comprehensive post-discharge care management intervention for ischemic stroke patients with NIH Stroke Scale scores ≥1 discharged from an acute stroke unit. An Advanced Practice Nurse (APN) performed an in-home assessment for the intervention group from which an Interdisciplinary Team developed patient-specific care plans. The APN worked with the primary care physician (PCP) and patient to implement the plan over the next 6 months. Main outcome measures The intervention and usual care groups were compared using a global and closed hypothesis testing strategy. Outcomes fell into 5 domains: 1) Neuromotor Function, 2) Institution Time or Death, 3) Quality of Life, 4) Management of Risk, and 5) Stroke Knowledge and Lifestyle. Results Treatment effect was near zero standard deviations for all but the stroke knowledge and lifestyle domain which showed a significant effect of the intervention (p=0.0003). Conclusions Post discharge care management was not more effective than organized stroke unit care with enhanced discharge planning in most domains in this population. The intervention did, however, fill a post-discharge knowledge gap. PMID:19900646

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.

Addictions Neuroclinical Assessment: A reverse translational approach.

PubMed

Kwako, Laura E; Momenan, Reza; Grodin, Erica N; Litten, Raye Z; Koob, George F; Goldman, David

2017-08-01

Incentive salience, negative emotionality, and executive function are functional domains that are etiologic in the initiation and progression of addictive disorders, having been implicated in humans with addictive disorders and in animal models of addictions. Measures of these three neuroscience-based functional domains can capture much of the effects of inheritance and early exposures that lead to trait vulnerability shared across different addictive disorders. For specific addictive disorders, these measures can be supplemented by agent specific measures such as those that access pharmacodynamic and pharmacokinetic variation attributable to agent-specific gatekeeper molecules including receptors and drug-metabolizing enzymes. Herein, we focus on the translation and reverse translation of knowledge derived from animal models of addiction to the human condition via measures of neurobiological processes that are orthologous in animals and humans, and that are shared in addictions to different agents. Based on preclinical data and human studies, measures of these domains in a general framework of an Addictions Neuroclinical Assessment (ANA) can transform the assessment and nosology of addictive disorders, and can be informative for staging disease progression. We consider next steps and challenges for implementation of ANA in clinical care and research. This article is part of the Special Issue entitled "Alcoholism". Published by Elsevier Ltd.

A Filter-Mediated Communication Model for Design Collaboration in Building Construction

PubMed Central

Oh, Minho

2014-01-01

Multidisciplinary collaboration is an important aspect of modern engineering activities, arising from the growing complexity of artifacts whose design and construction require knowledge and skills that exceed the capacities of any one professional. However, current collaboration in the architecture, engineering, and construction industries often fails due to lack of shared understanding between different participants and limitations of their supporting tools. To achieve a high level of shared understanding, this study proposes a filter-mediated communication model. In the proposed model, participants retain their own data in the form most appropriate for their needs with domain-specific filters that transform the neutral representations into semantically rich ones, as needed by the participants. Conversely, the filters can translate semantically rich, domain-specific data into a neutral representation that can be accessed by other domain-specific filters. To validate the feasibility of the proposed model, we computationally implement the filter mechanism and apply it to a hypothetical test case. The result acknowledges that the filter mechanism can let the participants know ahead of time what will be the implications of their proposed actions, as seen from other participants' points of view. PMID:25309958

Tool Use and the Development of the Function Concept: From Repeated Calculations to Functional Thinking

ERIC Educational Resources Information Center

Doorman, Michiel; Drijvers, Paul; Gravemeijer, Koeno; Boon, Peter; Reed, Helen

2012-01-01

The concept of function is a central but difficult topic in secondary school mathematics curricula, which encompasses a transition from an operational to a structural view. The question in this paper is how the use of computer tools may foster this transition. With domain-specific pedagogical knowledge on the learning of function as a point of…

Evaluating and Improving a Learning Trajectory for Linear Measurement in Elementary Grades 2 and 3: A Longitudinal Study

ERIC Educational Resources Information Center

Barrett, Jeffrey E.; Sarama, Julie; Clements, Douglas H.; Cullen, Craig; McCool, Jenni; Witkowski-Rumsey, Chepina; Klanderman, David

2012-01-01

We examined children's development of strategic and conceptual knowledge for linear measurement. We conducted teaching experiments with eight students in grades 2 and 3, based on our hypothetical learning trajectory for length to check its coherence and to strengthen the domain-specific model for learning and teaching. We checked the hierarchical…

Cognitive Rehabilitation of Episodic Memory Disorders: From Theory to Practice

PubMed Central

Ptak, Radek; der Linden, Martial Van; Schnider, Armin

2010-01-01

Memory disorders are among the most frequent and most debilitating cognitive impairments following acquired brain damage. Cognitive remediation strategies attempt to restore lost memory capacity, provide compensatory techniques or teach the use of external memory aids. Memory rehabilitation has strongly been influenced by memory theory, and the interaction between both has stimulated the development of techniques such as spaced retrieval, vanishing cues or errorless learning. These techniques partly rely on implicit memory and therefore enable even patients with dense amnesia to acquire new information. However, knowledge acquired in this way is often strongly domain-specific and inflexible. In addition, individual patients with amnesia respond differently to distinct interventions. The factors underlying these differences have not yet been identified. Behavioral management of memory failures therefore often relies on a careful description of environmental factors and measurement of associated behavioral disorders such as unawareness of memory failures. The current evidence suggests that patients with less severe disorders benefit from self-management techniques and mnemonics whereas rehabilitation of severely amnesic patients should focus on behavior management, the transmission of domain-specific knowledge through implicit memory processes and the compensation for memory deficits with memory aids. PMID:20700383

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.

On the domain-specificity of the visual and non-visual face-selective regions.

PubMed

Axelrod, Vadim

2016-08-01

What happens in our brains when we see a face? The neural mechanisms of face processing - namely, the face-selective regions - have been extensively explored. Research has traditionally focused on visual cortex face-regions; more recently, the role of face-regions outside the visual cortex (i.e., non-visual-cortex face-regions) has been acknowledged as well. The major quest today is to reveal the functional role of each this region in face processing. To make progress in this direction, it is essential to understand the extent to which the face-regions, and particularly the non-visual-cortex face-regions, process only faces (i.e., face-specific, domain-specific processing) or rather are involved in a more domain-general cognitive processing. In the current functional MRI study, we systematically examined the activity of the whole face-network during face-unrelated reading task (i.e., written meaningful sentences with content unrelated to faces/people and non-words). We found that the non-visual-cortex (i.e., right lateral prefrontal cortex and posterior superior temporal sulcus), but not the visual cortex face-regions, responded significantly stronger to sentences than to non-words. In general, some degree of sentence selectivity was found in all non-visual-cortex cortex. Present result highlights the possibility that the processing in the non-visual-cortex face-selective regions might not be exclusively face-specific, but rather more or even fully domain-general. In this paper, we illustrate how the knowledge about domain-general processing in face-regions can help to advance our general understanding of face processing mechanisms. Our results therefore suggest that the problem of face processing should be approached in the broader scope of cognition in general. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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.

Reusable design: A proposed approach to Public Health Informatics system design

PubMed Central

2011-01-01

Background Since it was first defined in 1995, Public Health Informatics (PHI) has become a recognized discipline, with a research agenda, defined domain-specific competencies and a specialized corpus of technical knowledge. Information systems form a cornerstone of PHI research and implementation, representing significant progress for the nascent field. However, PHI does not advocate or incorporate standard, domain-appropriate design methods for implementing public health information systems. Reusable design is generalized design advice that can be reused in a range of similar contexts. We propose that PHI create and reuse information design knowledge by taking a systems approach that incorporates design methods from the disciplines of Human-Computer Interaction, Interaction Design and other related disciplines. Discussion Although PHI operates in a domain with unique characteristics, many design problems in public health correspond to classic design problems, suggesting that existing design methods and solution approaches are applicable to the design of public health information systems. Among the numerous methodological frameworks used in other disciplines, we identify scenario-based design and participatory design as two widely-employed methodologies that are appropriate for adoption as PHI standards. We make the case that these methods show promise to create reusable design knowledge in PHI. Summary We propose the formalization of a set of standard design methods within PHI that can be used to pursue a strategy of design knowledge creation and reuse for cost-effective, interoperable public health information systems. We suggest that all public health informaticians should be able to use these design methods and the methods should be incorporated into PHI training. PMID:21333000

Inferring protein domains associated with drug side effects based on drug-target interaction network.

PubMed

Iwata, Hiroaki; Mizutani, Sayaka; Tabei, Yasuo; Kotera, Masaaki; Goto, Susumu; Yamanishi, Yoshihiro

2013-01-01

Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains.

The Unique Protein-to-Protein Carotenoid Transfer Mechanism.

PubMed

Maksimov, Eugene G; Sluchanko, Nikolai N; Slonimskiy, Yury B; Mironov, Kirill S; Klementiev, Konstantin E; Moldenhauer, Marcus; Friedrich, Thomas; Los, Dmitry A; Paschenko, Vladimir Z; Rubin, Andrew B

2017-07-25

Orange Carotenoid Protein (OCP) is known as an effector and regulator of cyanobacterial photoprotection. This 35 kDa water-soluble protein provides specific environment for blue-green light absorbing keto-carotenoids, which excitation causes dramatic but fully reversible rearrangements of the OCP structure, including carotenoid translocation and separation of C- and N-terminal domains upon transition from the basic orange to photoactivated red OCP form. Although recent studies greatly improved our understanding of the OCP photocycle and interaction with phycobilisomes and the fluorescence recovery protein, the mechanism of OCP assembly remains unclear. Apparently, this process requires targeted delivery and incorporation of a highly hydrophobic carotenoid molecule into the water-soluble apoprotein of OCP. Recently, we introduced, to our knowledge, a novel carotenoid carrier protein, COCP, which consists of dimerized C-domain(s) of OCP and can combine with the isolated N-domain to form transient OCP-like species. Here, we demonstrate that in vitro COCP efficiently transfers otherwise tightly bound carotenoid to the full-length OCP apoprotein, resulting in formation of photoactive OCP from completely photoinactive species. We accurately analyze the peculiarities of this process that, to the best of our knowledge, appears unique, a previously uncharacterized protein-to-protein carotenoid transfer mechanism. We hypothesize that a similar OCP assembly can occur in vivo, substantiating specific roles of the COCP carotenoid carrier in cyanobacterial photoprotection. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Stakeholder perspectives on land-use strategies for adapting to climate-change-enhanced coastal hazards: Sarasota, Florida

USGS Publications Warehouse

Frazier, Tim G.; Wood, Nathan; Yarnal, Brent

2010-01-01

Sustainable land-use planning requires decision makers to balance community growth with resilience to natural hazards. This balance is especially difficult in many coastal communities where planners must grapple with significant growth projections, the persistent threat of extreme events (e.g., hurricanes), and climate-change-driven sea level rise that not only presents a chronic hazard but also alters the spatial extent of sudden-onset hazards such as hurricanes. We examine these stressors on coastal, long-term land-use planning by reporting the results of a one-day community workshop held in Sarasota County, Florida that included focus groups and participatory mapping exercises. Workshop participants reflected various political agendas and socioeconomic interests of five local knowledge domains: business, environment, emergency management and infrastructure, government, and planning. Through a series of alternating domain-specific focus groups and interactive plenary sessions, participants compared the county 2050 comprehensive land-use plan to maps of contemporary hurricane storm-surge hazard zones and projected storm-surge hazard zones enlarged by sea level rise scenarios. This interactive, collaborative approach provided each group of domain experts the opportunity to combine geographically-specific, scientific knowledge on natural hazards and climate change with local viewpoints and concerns. Despite different agendas, interests, and proposed adaptation strategies, there was common agreement among participants for the need to increase community resilience to contemporary hurricane storm-surge hazards and to explore adaptation strategies to combat the projected, enlarged storm-surge hazard zones.

Concepts and Categories: A Cognitive Neuropsychological Perspective

PubMed Central

Mahon, Bradford Z.; Caramazza, Alfonso

2010-01-01

One of the most provocative and exciting issues in cognitive science is how neural specificity for semantic categories of common objects arises in the functional architecture of the brain. More than two decades of research on the neuropsychological phenomenon of category-specific semantic deficits has generated detailed claims about the organization and representation of conceptual knowledge. More recently, researchers have sought to test hypotheses developed on the basis of neuropsychological evidence with functional imaging. From those two fields, the empirical generalization emerges that object domain and sensory modality jointly constrain the organization of knowledge in the brain. At the same time, research within the embodied cognition framework has highlighted the need to articulate how information is communicated between the sensory and motor systems, and processes that represent and generalize abstract information. Those developments point toward a new approach for understanding category specificity in terms of the coordinated influences of diverse regions and cognitive systems. PMID:18767921

MorTAL Kombat: the story of defense against TAL effectors through loss-of-susceptibility

PubMed Central

Hutin, Mathilde; Pérez-Quintero, Alvaro L.; Lopez, Camilo; Szurek, Boris

2015-01-01

Many plant-pathogenic xanthomonads rely on Transcription Activator-Like (TAL) effectors to colonize their host. This particular family of type III effectors functions as specific plant transcription factors via a programmable DNA-binding domain. Upon binding to the promoters of plant disease susceptibility genes in a sequence-specific manner, the expression of these host genes is induced. However, plants have evolved specific strategies to counter the action of TAL effectors and confer resistance. One mechanism is to avoid the binding of TAL effectors by mutations of their DNA binding sites, resulting in resistance by loss-of-susceptibility. This article reviews our current knowledge of the susceptibility hubs targeted by Xanthomonas TAL effectors, possible evolutionary scenarios for plants to combat the pathogen with loss-of-function alleles, and how this knowledge can be used overall to develop new pathogen-informed breeding strategies and improve crop resistance. PMID:26236326

Massive expansion of the calpain gene family in unicellular eukaryotes.

PubMed

Zhao, Sen; Liang, Zhe; Demko, Viktor; Wilson, Robert; Johansen, Wenche; Olsen, Odd-Arne; Shalchian-Tabrizi, Kamran

2012-09-29

Calpains are Ca2+-dependent cysteine proteases that participate in a range of crucial cellular processes. Dysfunction of these enzymes may cause, for instance, life-threatening diseases in humans, the loss of sex determination in nematodes and embryo lethality in plants. Although the calpain family is well characterized in animal and plant model organisms, there is a great lack of knowledge about these genes in unicellular eukaryote species (i.e. protists). Here, we study the distribution and evolution of calpain genes in a wide range of eukaryote genomes from major branches in the tree of life. Our investigations reveal 24 types of protein domains that are combined with the calpain-specific catalytic domain CysPc. In total we identify 41 different calpain domain architectures, 28 of these domain combinations have not been previously described. Based on our phylogenetic inferences, we propose that at least four calpain variants were established in the early evolution of eukaryotes, most likely before the radiation of all the major supergroups of eukaryotes. Many domains associated with eukaryotic calpain genes can be found among eubacteria or archaebacteria but never in combination with the CysPc domain. The analyses presented here show that ancient modules present in prokaryotes, and a few de novo eukaryote domains, have been assembled into many novel domain combinations along the evolutionary history of eukaryotes. Some of the new calpain genes show a narrow distribution in a few branches in the tree of life, likely representing lineage-specific innovations. Hence, the functionally important classical calpain genes found among humans and vertebrates make up only a tiny fraction of the calpain family. In fact, a massive expansion of the calpain family occurred by domain shuffling among unicellular eukaryotes and contributed to a wealth of functionally different genes.

Massive expansion of the calpain gene family in unicellular eukaryotes

PubMed Central

2012-01-01

Background Calpains are Ca2+-dependent cysteine proteases that participate in a range of crucial cellular processes. Dysfunction of these enzymes may cause, for instance, life-threatening diseases in humans, the loss of sex determination in nematodes and embryo lethality in plants. Although the calpain family is well characterized in animal and plant model organisms, there is a great lack of knowledge about these genes in unicellular eukaryote species (i.e. protists). Here, we study the distribution and evolution of calpain genes in a wide range of eukaryote genomes from major branches in the tree of life. Results Our investigations reveal 24 types of protein domains that are combined with the calpain-specific catalytic domain CysPc. In total we identify 41 different calpain domain architectures, 28 of these domain combinations have not been previously described. Based on our phylogenetic inferences, we propose that at least four calpain variants were established in the early evolution of eukaryotes, most likely before the radiation of all the major supergroups of eukaryotes. Many domains associated with eukaryotic calpain genes can be found among eubacteria or archaebacteria but never in combination with the CysPc domain. Conclusions The analyses presented here show that ancient modules present in prokaryotes, and a few de novo eukaryote domains, have been assembled into many novel domain combinations along the evolutionary history of eukaryotes. Some of the new calpain genes show a narrow distribution in a few branches in the tree of life, likely representing lineage-specific innovations. Hence, the functionally important classical calpain genes found among humans and vertebrates make up only a tiny fraction of the calpain family. In fact, a massive expansion of the calpain family occurred by domain shuffling among unicellular eukaryotes and contributed to a wealth of functionally different genes. PMID:23020305

Personal Reflection: Pedagogical Content Knowledge and the Affective Domain of Scholarship of Teaching and Learning

ERIC Educational Resources Information Center

Garritz, Andoni

2010-01-01

The question of these reflections is if among those content-dependent instructional conditions necessary to attain conceptual understanding, those belonging to the affective domain of teaching and learning must be included in Pedagogical Content Knowledge (PCK), the special amalgam of content knowledge and knowledge of general pedagogy that a…

Review on the Role of Planetary Factors on Habitability.

PubMed

Kereszturi, A; Noack, L

2016-11-01

In this work various factors on the habitability were considered, focusing on conditions irrespective of the central star's radiation, to see the role of specific planetary body related effects. These so called planetary factors were evaluated to identify those trans-domain issues where important information is missing but good chance exit to be filled by new knowledge that might be gained in the next decade(s). Among these strategic knowledge gaps, specific issues are listed, like occurrence of radioactive nucleides in star forming regions, models to estimate the existence of subsurface liquid water from bulk parameters plus evolutionary context of the given system, estimation on the existence of redox gradient depending on the environment type etc. These issues require substantial improvement of modelling and statistical handling of various cases, as "planetary environment types". Based on our current knowledge it is probable that subsurface habitability is at least as frequent, or more frequent than surface habitability. Unfortunately it is more difficult from observations to infer conditions for subsurface habitability, but specific argumentation might help with indirect ways, which might result in new methods to approach habitability in general.

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed

Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

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.

Preface to MOST-ONISW 2009

NASA Astrophysics Data System (ADS)

Doerr, Martin; Freitas, Fred; Guizzardi, Giancarlo; Han, Hyoil

Ontology is a cross-disciplinary field concerned with the study of concepts and theories that can be used for representing shared conceptualizations of specific domains. Ontological Engineering is a discipline in computer and information science concerned with the development of techniques, methods, languages and tools for the systematic construction of concrete artifacts capturing these representations, i.e., models (e.g., domain ontologies) and metamodels (e.g., upper-level ontologies). In recent years, there has been a growing interest in the application of formal ontology and ontological engineering to solve modeling problems in diverse areas in computer science such as software and data engineering, knowledge representation, natural language processing, information science, among many others.

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.

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.

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.

A cooperative-binding split aptamer assay for rapid, specific and ultra-sensitive fluorescence detection of cocaine in saliva.

PubMed

Yu, Haixiang; Canoura, Juan; Guntupalli, Bhargav; Lou, Xinhui; Xiao, Yi

2017-01-01

Sensors employing split aptamers that reassemble in the presence of a target can achieve excellent specificity, but the accompanying reduction of target affinity mitigates any overall gains in sensitivity. We for the first time have developed a split aptamer that achieves enhanced target-binding affinity through cooperative binding. We have generated a split cocaine-binding aptamer that incorporates two binding domains, such that target binding at one domain greatly increases the affinity of the second domain. We experimentally demonstrate that the resulting cooperative-binding split aptamer (CBSA) exhibits higher target binding affinity and is far more responsive in terms of target-induced aptamer assembly compared to the single-domain parent split aptamer (PSA) from which it was derived. We further confirm that the target-binding affinity of our CBSA can be affected by the cooperativity of its binding domains and the intrinsic affinity of its PSA. To the best of our knowledge, CBSA-5335 has the highest cocaine affinity of any split aptamer described to date. The CBSA-based assay also demonstrates excellent performance in target detection in complex samples. Using this CBSA, we achieved specific, ultra-sensitive, one-step fluorescence detection of cocaine within fifteen minutes at concentrations as low as 50 nM in 10% saliva without signal amplification. This limit of detection meets the standards recommended by the European Union's Driving under the Influence of Drugs, Alcohol and Medicines program. Our assay also demonstrates excellent reproducibility of results, confirming that this CBSA-platform represents a robust and sensitive means for cocaine detection in actual clinical samples.

What Case Managers Should Know About Their Roles and Functions: A National Study From the Commission for Case Manager Certification: Part 1.

PubMed

Tahan, Hussein M; Watson, Annette C; Sminkey, Patrice V

2015-01-01

The purpose of this national role and function study was to identify the essential activities and necessary knowledge areas for effective case manager practice from the perspective of those currently functioning in various care settings and across diverse professional disciplines. The national study covered all case management practices and/or work settings across the full continuum of health care. This cross-sectional descriptive study used the practice analysis method and online survey research design. It employed a purposive sample of case managers, in which 52,370 individuals received an invitation to participate. Data collection completed over a 4-week period, resulting in 7,668 useable survey responses (nearly a 15% response rate). The study identified the common activities and knowledge areas necessary for competent and effective performance of case managers, as is highlighted in this article, which is the first of a 2-part series on the role and function study. The results informed the needed update of the test specifications for the Certified Case Manager (CCM) certification examination, as will be delineated in Part 2 of the article series, to ensure that it continues to be substantiated in current practice. Of special note are the emergence of specific activity and knowledge domains in the area of case management ethical, legal, and practice standards, and an increase in the number of employers requiring certified case managers to fill vacant positions and compensating them financially for such qualifications. This study helps keep the CCM credentialing examination evidence-based and maintain its validity for evaluating competency of case managers. Specifically, the study identified essential activities and knowledge domains that define competent case management practice. Findings can be used for developing programs and curricula for the training and development of case managers. The study instrument also can be used for further research of case management practice.

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

PubMed

Schmalhofer, F J; Tschaitschian, B

1998-11-01

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

Professional Development in a Reform Context: Understanding the Design and Enactment of Learning Experiences Created by Teacher Leaders for Science Educators

NASA Astrophysics Data System (ADS)

Shafer, Laura

Teacher in-service learning about education reforms like NGSS often begin with professional development (PD) as a foundational component (Supovitz & Turner, 2000). Teacher Leaders, who are early implementers of education reform, are positioned to play a contributing role to the design of PD. As early implementers of reforms, Teacher Leaders are responsible for interpreting the purposes of reform, enacting reforms with fidelity to meet those intended goals, and are positioned to share their expertise with others. However, Teacher Leader knowledge is rarely accessed as a resource for the design of professional development programs. This study is unique in that I analyze the knowledge Teacher Leaders, who are positioned as developers of PD, bring to the design of PD around science education reform. I use the extended interconnected model of professional growth (Clarke & Hollingsworth, 2002; Coenders & Terlouw, 2015) to analyze the knowledge pathways Teacher Leaders' access as PD developers. I found that Teacher Leaders accessed knowledge pathways that cycled through their personal domain, domain of practice and domain of consequence. Additionally the findings indicated when Teacher Leaders did not have access to these knowledge domains they were unwilling to continue with PD design. These findings point to how Teacher Leaders prioritize their classroom experience to ground PD design and use their perceptions of student learning outcomes as an indicator of the success of the reform. Because professional development (PD) is viewed as an important resource for influencing teachers' knowledge and beliefs around the implementation of education reform efforts (Garet, et al., 2001; Suppovitz & Turner, 2000), I offer that Teacher Leaders, who are early implementers of reform measures, can contribute to the professional development system. The second part of this dissertation documents the instantiation of the knowledge of Teacher Leaders, who are positioned as designers and facilitators of PD. I examine the extent to which Teacher Leader knowledge is instantiated into specific resources and tasks during PD specifically for the Next Generation Science Standards (NGSS). The findings indicate that Teacher Leaders' knowledge is instantiated in tasks that promote and facilitate alignment of Teacher Leader goals for NGSS science practices-based instruction, which are framed around student learning outcomes. I offer a number of ways in which these findings can help educators and PD developers to better structure activities that present an alternative vision for science education that also provides the needed resources to shape how classroom tasks are designed and managed in ways that attend to and build on the practical knowledge of Teacher Leaders. The third part of this dissertation addresses the role Teacher Leaders play in this reform context with respect to their contributions to the professional development system. Based on the analyses of the Teacher Leaders in this study, I claim Teacher Leaders are essential contributors to the professional development system that extends beyond their typical role of participant. I argue that Teacher Leaders bring special expertise to the role of designers and facilitators of PD programs, and to the role of ambassadors for professional learning communities in a reform context. Because Teacher Leaders have a broader influence on the professional development system as pictured here, the Teacher Leaders in this study represent an essential piece of the reform puzzle.

Fine-grained semantic categorization across the abstract and concrete domains.

PubMed

Ghio, Marta; Vaghi, Matilde Maria Serena; Tettamanti, Marco

2013-01-01

A consolidated approach to the study of the mental representation of word meanings has consisted in contrasting different domains of knowledge, broadly reflecting the abstract-concrete dichotomy. More fine-grained semantic distinctions have emerged in neuropsychological and cognitive neuroscience work, reflecting semantic category specificity, but almost exclusively within the concrete domain. Theoretical advances, particularly within the area of embodied cognition, have more recently put forward the idea that distributed neural representations tied to the kinds of experience maintained with the concepts' referents might distinguish conceptual meanings with a high degree of specificity, including those within the abstract domain. Here we report the results of two psycholinguistic rating studies incorporating such theoretical advances with two main objectives: first, to provide empirical evidence of fine-grained distinctions within both the abstract and the concrete semantic domains with respect to relevant psycholinguistic dimensions; second, to develop a carefully controlled linguistic stimulus set that may be used for auditory as well as visual neuroimaging studies focusing on the parametrization of the semantic space beyond the abstract-concrete dichotomy. Ninety-six participants rated a set of 210 sentences across pre-selected concrete (mouth, hand, or leg action-related) and abstract (mental state-, emotion-, mathematics-related) categories, with respect either to different semantic domain-related scales (rating study 1), or to concreteness, familiarity, and context availability (rating study 2). Inferential statistics and correspondence analyses highlighted distinguishing semantic and psycholinguistic traits for each of the pre-selected categories, indicating that a simple abstract-concrete dichotomy is not sufficient to account for the entire semantic variability within either domains.

Fine-Grained Semantic Categorization across the Abstract and Concrete Domains

PubMed Central

Tettamanti, Marco

2013-01-01

A consolidated approach to the study of the mental representation of word meanings has consisted in contrasting different domains of knowledge, broadly reflecting the abstract-concrete dichotomy. More fine-grained semantic distinctions have emerged in neuropsychological and cognitive neuroscience work, reflecting semantic category specificity, but almost exclusively within the concrete domain. Theoretical advances, particularly within the area of embodied cognition, have more recently put forward the idea that distributed neural representations tied to the kinds of experience maintained with the concepts' referents might distinguish conceptual meanings with a high degree of specificity, including those within the abstract domain. Here we report the results of two psycholinguistic rating studies incorporating such theoretical advances with two main objectives: first, to provide empirical evidence of fine-grained distinctions within both the abstract and the concrete semantic domains with respect to relevant psycholinguistic dimensions; second, to develop a carefully controlled linguistic stimulus set that may be used for auditory as well as visual neuroimaging studies focusing on the parametrization of the semantic space beyond the abstract-concrete dichotomy. Ninety-six participants rated a set of 210 sentences across pre-selected concrete (mouth, hand, or leg action-related) and abstract (mental state-, emotion-, mathematics-related) categories, with respect either to different semantic domain-related scales (rating study 1), or to concreteness, familiarity, and context availability (rating study 2). Inferential statistics and correspondence analyses highlighted distinguishing semantic and psycholinguistic traits for each of the pre-selected categories, indicating that a simple abstract-concrete dichotomy is not sufficient to account for the entire semantic variability within either domains. PMID:23825625

Biological knowledge is more tentative than physics knowledge: Taiwan high school adolescents' views about the nature of biology and physics.

PubMed

Tsai, Chin-Chung

2006-01-01

Many educational psychologists believe that students' beliefs about the nature of knowledge, called epistemological beliefs, play an essential role in their learning process. Educators also stress the importance of helping students develop a better understanding of the nature of knowledge. The tentative and creative nature of science is often highlighted by contemporary science educators. However, few previous studies have investigated students' views of more specific knowledge domains, such as biology and physics. Consequently, this study developed a questionnaire to assess students' views specifically about the tentative and creative nature of biology and physics. From a survey of 428 Taiwanese high school adolescents, this study found that although students showed an understanding of the tentative and creative nature of biology and physics, they expressed stronger agreement as to the tentativeness of biology than that of physics. In addition, male students tended to agree more than did females that physics had tentative and creative features and that biology had tentative features. Also, students with more years of science education tended to show more agreement regarding the creative nature of physics and biology than those with fewer years.

Community/public health nursing faculty's knowledge, skills and attitudes of the Quad Council Competencies for Public Health Nurses.

PubMed

Joyce, Barbara L; Harmon, Monica; Johnson, Regina Gina H; Hicks, Vicki; Brown-Schott, Nancy; Pilling, Lucille; Brownrigg, Vicki

2018-05-02

A multisite collaborative team of community/public health nursing (C/PHN) faculty surveyed baccalaureate nursing faculty to explore their knowledge, skills, attitudes, and application of the Quad Council Competencies for Public Health Nurses (QCC-PHN). (1) Evaluate the knowledge, skills, and attitudes of the 2011 QCC-PHN by academic C/PHN faculty; (2) Evaluate the application of 2011 QCC-PHN by C/PHN faculty in the clinical practicum for undergraduate baccalaureate C/PHN students; and (3) Determine if a significant difference existed in the knowledge for each domain. A mixed methods descriptive research design was used to answer three specific hypotheses related to the study objectives. A convenience sample of 143 faculty teaching C/PHN in baccalaureate schools of nursing completed an online survey. ANOVA was used to determine the difference between knowledge, skills, attitudes, and application of nursing faculty regarding the QCC-PHN based on years of nursing experience, C/PHN experience, and nursing specialty preparation. Participants' qualitative comments for each domain were analyzed for themes. C/PHN nursing faculty are described and differences in knowledge, skills, and attitudes delineated. A statistically significant difference was found in skills based on years of experience in C/PHN and in the application of the competencies based on nursing specialty preparation. Variations in knowledge of the QCC-PHN are identified. Ten recommendations are proposed for key skill sets and necessary preparation for faculty to effectively teach C/PHN in baccalaureate schools of nursing. © 2018 Wiley Periodicals, Inc.

Detecting Coevolution in and among Protein Domains

PubMed Central

Yeang, Chen-Hsiang; Haussler, David

2007-01-01

Correlated changes of nucleic or amino acids have provided strong information about the structures and interactions of molecules. Despite the rich literature in coevolutionary sequence analysis, previous methods often have to trade off between generality, simplicity, phylogenetic information, and specific knowledge about interactions. Furthermore, despite the evidence of coevolution in selected protein families, a comprehensive screening of coevolution among all protein domains is still lacking. We propose an augmented continuous-time Markov process model for sequence coevolution. The model can handle different types of interactions, incorporate phylogenetic information and sequence substitution, has only one extra free parameter, and requires no knowledge about interaction rules. We employ this model to large-scale screenings on the entire protein domain database (Pfam). Strikingly, with 0.1 trillion tests executed, the majority of the inferred coevolving protein domains are functionally related, and the coevolving amino acid residues are spatially coupled. Moreover, many of the coevolving positions are located at functionally important sites of proteins/protein complexes, such as the subunit linkers of superoxide dismutase, the tRNA binding sites of ribosomes, the DNA binding region of RNA polymerase, and the active and ligand binding sites of various enzymes. The results suggest sequence coevolution manifests structural and functional constraints of proteins. The intricate relations between sequence coevolution and various selective constraints are worth pursuing at a deeper level. PMID:17983264

Factors affecting emergency preparedness competency of public health inspectors: a cross-sectional study in northeastern China

PubMed Central

Ning, Ning; Kang, Zheng; Jiao, Mingli; Hao, Yanhua; Gao, Lijun; Sun, Hong; Wu, Qunhong

2014-01-01

Objectives To determine the emergency preparedness competency specific to public health inspectors (PHIs), preparedness limitations and needs of the workforce, as well as to identify important factors that affect the preparedness competency of PHIs. Setting Cross-sectional survey was conducted in Heilongjiang, a province in northeastern China. Participants A questionnaire was administered to a sample of 368 PHIs from 17 public health inspection agencies, chosen by stratified cluster sampling strategy. 9 PHIs and 6 agency's leaders were invited to participate in an in-depth interview. Outcome measures Self-rated preparedness competency in quantitative study was measured. Multivariate logistic regression model was used to test the associations between individual determinants and self-rated preparedness competency. Key themes relating to preparedness competency of PHIs in qualitative study were analysed. Results Although 82% of PHIs highly rated their general preparedness competency, there were significant differences among the assessment on specific domains of their competency. Comparing with attitude, the domains of skills and knowledge tend to be lower (p=0.000). Awareness on one's own responsibilities regarding emergency response work was identified as the most important factor associated with preparedness competency (adjusted OR=6.33, 95% CI 3.30 to 12.16). Lack of explicit national job requirements, overlapping responsibilities and poor collaboration among agencies, together with poor knowledge and skills level of personnel, led to an ambiguity of responsibility, and hindered the preparedness competency enhancement of PHIs furthermore. Conclusions Ambiguity responsibility in emergency response is still a prominent issue that hinders the further improvement on the preparedness competency for PHIs’ in China. Intensified capacity-building activities targeting at individuals’ weakness in specific knowledge and skills are urgently needed; in addition, capacity building at policy and system level as well as agency levels is of equal importance. PMID:24384897

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…

Detection of phenols using engineered bacteria

DOEpatents

Wise, Arlene A.; Kuske, Cheryl R.; Terwilliger, Thomas C.

2007-12-04

Detection of phenols using engineered bacteria. A biosensor can be created by placing a reporter gene under control of an inducible promoter. The reporter gene produces a signal when a cognate transcriptional activator senses the inducing chemical. Creation of bacterial biosensors is currently restricted by limited knowledge of the genetic systems of bacteria that catabolize xenobiotics. By using mutagenic PCR to change the chemical specificity of the Pseudomonas species CF600 DmpR protein, the potential for engineering novel biosensors for detection of phenols has been demonstrated. DmpR, a well-characterized transcriptional activator of the P. CF600's dmp operon mediates growth on simple phenols. Transcription from Po, the promoter heading the dmp operon, is activated when the sensor domain of DmpR interacts with phenol and mono-substituted phenols. By altering the sensor domain of the DmpR, a group of DmpR derivatives that activate transcription of a Po-lacZ fusion in response to eight of the EPA's eleven priority pollutant phenols has been created. The assays and the sensor domain mutations that alter the chemical specificity of DmpR is described.

Detection of phenols using engineered bacteria

DOEpatents

Wise, Arlene A.; Kuske, Cheryl R.; Terwilliger, Thomas C.

2004-08-10

Detection of phenols using engineered bacteria. A biosensor can be created by placing a reporter gene under control of an inducible promoter. The reporter gene produces a signal when a cognate transcriptional activator senses the inducing chemical. Creation of bacterial biosensors is currently restricted by limited knowledge of the genetic systems of bacteria that catabolize xenobiotics. By using mutagenic PCR to change the chemical specificity of the Pseudomonas species CF600 DmpR protein, the potential for engineering novel biosensors for detection of phenols has been demonstrated. DmpR, a well-characterized transcriptional activator of the P. CF600's dmp operon mediates growth on simple phenols. Transcription from Po, the promoter heading the dmp operon, is activated when the sensor domain of DmpR interacts with phenol and mono-substituted phenols. By altering the sensor domain of the DmpR, a group of DmpR derivatives that activate transcription of a Po-lacZ fusion in response to eight of the EPA's eleven priority pollutant phenols has been created. The assays and the sensor domain mutations that alter the chemical specificity of DmpR is described.

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).

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

PubMed Central

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

1999-01-01

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

The role of knowledge structures in fault diagnosis

NASA Technical Reports Server (NTRS)

Smith, P. J.; Giffin, W. C.; Rockwell, T. H.; Thomas, M. E.

1984-01-01

The use of human memory and knowledge structures to direct fault diagnosis performance was investigated. The performances of 20 pilots with instrument flight ratings were studied in a fault diagnosis task. The pilots were read a scenario which described flight conditions under which the symptoms which are indicative of a problem were detected. They were asked to think out loud as they requested and interpreted various pieces of information to diagnose the cause of the problem. Only 11 of the 20 pilots successfully diagnosed the problem. Pilot performance on this fault diagnosis task was modeled in the use of domain specific knowledge organized in a frame system. Eighteen frames, with a common structure, were necessary to account for the data from all twenty subjects.

An information extraction framework for cohort identification using electronic health records.

PubMed

Liu, Hongfang; Bielinski, Suzette J; Sohn, Sunghwan; Murphy, Sean; Wagholikar, Kavishwar B; Jonnalagadda, Siddhartha R; Ravikumar, K E; Wu, Stephen T; Kullo, Iftikhar J; Chute, Christopher G

2013-01-01

Information extraction (IE), a natural language processing (NLP) task that automatically extracts structured or semi-structured information from free text, has become popular in the clinical domain for supporting automated systems at point-of-care and enabling secondary use of electronic health records (EHRs) for clinical and translational research. However, a high performance IE system can be very challenging to construct due to the complexity and dynamic nature of human language. In this paper, we report an IE framework for cohort identification using EHRs that is a knowledge-driven framework developed under the Unstructured Information Management Architecture (UIMA). A system to extract specific information can be developed by subject matter experts through expert knowledge engineering of the externalized knowledge resources used in the framework.

The Cognitive Advantages of Counting Specifically: A Representational Analysis of Verbal Numeration Systems in Oceanic Languages.

PubMed

Bender, Andrea; Schlimm, Dirk; Beller, Sieghard

2015-10-01

The domain of numbers provides a paradigmatic case for investigating interactions of culture, language, and cognition: Numerical competencies are considered a core domain of knowledge, and yet the development of specifically human abilities presupposes cultural and linguistic input by way of counting sequences. These sequences constitute systems with distinct structural properties, the cross-linguistic variability of which has implications for number representation and processing. Such representational effects are scrutinized for two types of verbal numeration systems-general and object-specific ones-that were in parallel use in several Oceanic languages (English with its general system is included for comparison). The analysis indicates that the object-specific systems outperform the general systems with respect to counting and mental arithmetic, largely due to their regular and more compact representation. What these findings reveal on cognitive diversity, how the conjectures involved speak to more general issues in cognitive science, and how the approach taken here might help to bridge the gap between anthropology and other cognitive sciences is discussed in the conclusion. Copyright © 2015 Cognitive Science Society, Inc.

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.

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.

[Sex and gender: Two different scientific domains to be clarified].

PubMed

Fernández, Juan

2010-05-01

Nowadays, the word sex and its related terms (sexual differences, sexual roles and stereotypes), so common not long ago, seems to have been replaced by gender and its related terms (gender differences, gender roles and stereotypes). We can sometimes find both sex and gender sharing the same space in scientific articles, although referring to different domains. In this paper, I try to explain the need for a model that can integrate both of these complex domains of sex and gender, leading to two independent, although complementary, disciplines: Sexology and Genderology. In both cases, I start from a functional standpoint, which will give meaning to both disciplines' specificities, as it is meant to link contributions from different fields of knowledge. This approach can have consequences for research, education, the experience of women, men, and ambiguous individuals, and therapy.

Preschoolers’ Emotion Knowledge and the Differential Effects of Harsh Punishment

PubMed Central

Berzenski, Sara R.; Yates, Tuppett M.

2013-01-01

This study examined the influence of caregiver-reported harsh physical and verbal punishment on children’s behavioral and self-system adjustment. Children’s emotion knowledge was evaluated as a heretofore unrecognized moderator of these relations. Two hundred fifty preschool age children (50% female; Mage=49.06 months) from diverse backgrounds (50% Hispanic, 18% African American, 10.4% Caucasian, 21.6% Multiracial/Other) were assessed through teacher, caregiver, self, and observer report in the domains of harsh punishment (Parent Child Conflict Tactics Scale), conduct problems (Teacher Report Form, California Child Q-Sort), self concept (Self Description Questionnaire for Preschoolers, California Child Q-Sort), and emotion knowledge (Kuschè Emotion Inventory). Emotion knowledge moderated the relation between harsh punishment and child adjustment. Harsh physical punishment was associated with conduct problems for children with higher emotion knowledge, especially for boys. Harsh verbal punishment was associated with self concept deficits among children with higher emotion knowledge, especially for girls. These relations were also specifically applicable to non-Hispanic children. These results highlight the importance of investigating hypothesis driven interactive effects and the specificity of experience to understand the psychosocial sequelae of parenting practices broadly, and to clarify the mixed evidence in the punishment literature specifically. Clinical implications point to the salience of emotion processes in parent-child disciplinary interventions for understanding the prevalence and pattern of child behavioral adjustment and self concept, as well as more broadly to the role of individual differences in children’s responses to adversity and subsequent therapeutic needs. PMID:23750528

Bridging the guideline implementation gap: a systematic, document-centered approach to guideline implementation.

PubMed

Shiffman, Richard N; Michel, George; Essaihi, Abdelwaheb; Thornquist, Elizabeth

2004-01-01

A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems. This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification. The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institute's guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system. Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge.

Action semantics: A unifying conceptual framework for the selective use of multimodal and modality-specific object knowledge.

PubMed

van Elk, Michiel; van Schie, Hein; Bekkering, Harold

2014-06-01

Our capacity to use tools and objects is often considered one of the hallmarks of the human species. Many objects greatly extend our bodily capabilities to act in the physical world, such as when using a hammer or a saw. In addition, humans have the remarkable capability to use objects in a flexible fashion and to combine multiple objects in complex actions. We prepare coffee, cook dinner and drive our car. In this review we propose that humans have developed declarative and procedural knowledge, i.e. action semantics that enables us to use objects in a meaningful way. A state-of-the-art review of research on object use is provided, involving behavioral, developmental, neuropsychological and neuroimaging studies. We show that research in each of these domains is characterized by similar discussions regarding (1) the role of object affordances, (2) the relation between goals and means in object use and (3) the functional and neural organization of action semantics. We propose a novel conceptual framework of action semantics to address these issues and to integrate the previous findings. We argue that action semantics entails both multimodal object representations and modality-specific sub-systems, involving manipulation knowledge, functional knowledge and representations of the sensory and proprioceptive consequences of object use. Furthermore, we argue that action semantics are hierarchically organized and selectively activated and used depending on the action intention of the actor and the current task context. Our framework presents an integrative account of multiple findings and perspectives on object use that may guide future studies in this interdisciplinary domain. Copyright © 2013 Elsevier B.V. All rights reserved.

Knowledge-driven enhancements for task composition in bioinformatics.

PubMed

Sutherland, Karen; McLeod, Kenneth; Ferguson, Gus; Burger, Albert

2009-10-01

A key application area of semantic technologies is the fast-developing field of bioinformatics. Sealife was a project within this field with the aim of creating semantics-based web browsing capabilities for the Life Sciences. This includes meaningfully linking significant terms from the text of a web page to executable web services. It also involves the semantic mark-up of biological terms, linking them to biomedical ontologies, then discovering and executing services based on terms that interest the user. A system was produced which allows a user to identify terms of interest on a web page and subsequently connects these to a choice of web services which can make use of these inputs. Elements of Artificial Intelligence Planning build on this to present a choice of higher level goals, which can then be broken down to construct a workflow. An Argumentation System was implemented to evaluate the results produced by three different gene expression databases. An evaluation of these modules was carried out on users from a variety of backgrounds. Users with little knowledge of web services were able to achieve tasks that used several services in much less time than they would have taken to do this manually. The Argumentation System was also considered a useful resource and feedback was collected on the best way to present results. Overall the system represents a move forward in helping users to both construct workflows and analyse results by incorporating specific domain knowledge into the software. It also provides a mechanism by which web pages can be linked to web services. However, this work covers a specific domain and much co-ordinated effort is needed to make all web services available for use in such a way, i.e. the integration of underlying knowledge is a difficult but essential task.

Learning a theory of causality.

PubMed

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 learned from co-occurrence of events. We begin by phrasing the causal Bayes nets theory of causality and a range of alternatives in a logical language for relational theories. This allows us to explore simultaneous inductive learning of an abstract theory of causality and a causal model for each of several causal systems. We find that the correct theory of causality can be learned relatively quickly, often becoming available before specific causal theories have been learned--an effect we term the blessing of abstraction. We then explore the effect of providing a variety of auxiliary evidence and find that a collection of simple perceptual input analyzers can help to bootstrap abstract knowledge. Together, these results suggest that the most efficient route to causal knowledge may be to build in not an abstract notion of causality but a powerful inductive learning mechanism and a variety of perceptual supports. While these results are purely computational, they have implications for cognitive development, which we explore in the conclusion.

Looking at practice: revealing the knowledge demands of teaching data handling in the primary classroom

NASA Astrophysics Data System (ADS)

Leavy, Aisling

2015-09-01

In the evolving field of mathematics education, there is the need to maintain the relationship between what is presented in college level preparation courses and the skills required to teach mathematics in classrooms. This research examines the knowledge demands placed on 73 pre-service primary teachers as they use lesson study to plan and teach data handling in primary classrooms. Pre-service teachers are observed as they plan, teach and re-teach data lessons in classrooms. Problems of practice are identified and categorized using the Ball, Thames and Phelps (2008) subdomains of common content knowledge (CCK), specialized content knowledge (SCK), knowledge of content and students (KCS) and knowledge of content and teaching (KCT). The results provide insights into the specific knowledge demands placed on early career teachers when teaching data and statistics and identifies foci area that can be addressed in teacher preparation programs. The results illustrate that development of understandings in one knowledge subdomain can motivate and impact learning in another subdomain. These interrelationships were found to exist both within and between the domains of content and pedagogical content knowledge.

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

NASA Astrophysics Data System (ADS)

Wu, Jiangning; Wang, Xiaohuan

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

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.

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.

Genetic specificity of face recognition.

PubMed

Shakeshaft, Nicholas G; Plomin, Robert

2015-10-13

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.

Genetic specificity of face recognition

PubMed Central

Shakeshaft, Nicholas G.; Plomin, Robert

2015-01-01

Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities. PMID:26417086

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…

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.

Non-intentional but not automatic: reduction of word- and arrow-based compatibility effects by sound distractors in the same categorical domain.

PubMed

Miles, James D; Proctor, Robert W

2009-10-01

In the current study, we show that the non-intentional processing of visually presented words and symbols can be attenuated by sounds. Importantly, this attenuation is dependent on the similarity in categorical domain between the sounds and words or symbols. Participants performed a task in which left or right responses were made contingent on the color of a centrally presented target that was either a location word (LEFT or RIGHT) or a left or right arrow. Responses were faster when they were on the side congruent with the word or arrow. This bias was reduced for location words by a neutral spoken word and for arrows by a tone series, but not vice versa. We suggest that words and symbols are processed with minimal attentional requirements until they are categorized into specific knowledge domains, but then become sensitive to other information within the same domain regardless of the similarity between modalities.

Person-Centeredness in Home- and Community-Based Services and Supports: Domains, Attributes, and Assisted Living Indicators.

PubMed

Zimmerman, Sheryl; Love, Karen; Cohen, Lauren W; Pinkowitz, Jackie; Nyrop, Kirsten A

2014-01-01

As a result of the Centers for Medicare & Medicaid Services (CMS) interest in creating a unifying definition of "community living" for its Medicaid Home and Community Based Services and Support (HCBS) programs, it needed clarifying descriptors of person-centered (PC) practices in assisted living to distinguish them from institutional ones. Additionally, CMS's proposed language defining "community living" had the unintended potential to exclude many assisted living communities and disadvantage residents who receive Medicaid. This manuscript describes the consensus process through which clarifying language for "community living" and a framework for HCBS PC domains, attributes, and indicators specific to assisted living were developed. It examines the validity of those domains based on literature review, surveys, and stakeholder focus groups, and identifies nine domains and 43 indicators that provide a foundation for defining and measuring PC practice in assisted living. Ongoing efforts using community-based participatory research methods are further refining and testing PC indicators for assisted living to advance knowledge, operational policies, practices, and quality outcomes.

Automating document classification for the Immune Epitope Database

PubMed Central

Wang, Peng; Morgan, Alexander A; Zhang, Qing; Sette, Alessandro; Peters, Bjoern

2007-01-01

Background The Immune Epitope Database contains information on immune epitopes curated manually from the scientific literature. Like similar projects in other knowledge domains, significant effort is spent on identifying which articles are relevant for this purpose. Results We here report our experience in automating this process using Naïve Bayes classifiers trained on 20,910 abstracts classified by domain experts. Improvements on the basic classifier performance were made by a) utilizing information stored in PubMed beyond the abstract itself b) applying standard feature selection criteria and c) extracting domain specific feature patterns that e.g. identify peptides sequences. We have implemented the classifier into the curation process determining if abstracts are clearly relevant, clearly irrelevant, or if no certain classification can be made, in which case the abstracts are manually classified. Testing this classification scheme on an independent dataset, we achieve 95% sensitivity and specificity in the 51.1% of abstracts that were automatically classified. Conclusion By implementing text classification, we have sped up the reference selection process without sacrificing sensitivity or specificity of the human expert classification. This study provides both practical recommendations for users of text classification tools, as well as a large dataset which can serve as a benchmark for tool developers. PMID:17655769

The Impact of Secondary School Students' Preconceptions on the Evolution of their Mental Models of the Greenhouse effect and Global Warming

NASA Astrophysics Data System (ADS)

Reinfried, Sibylle; Tempelmann, Sebastian

2014-01-01

This paper provides a video-based learning process study that investigates the kinds of mental models of the atmospheric greenhouse effect 13-year-old learners have and how these mental models change with a learning environment, which is optimised in regard to instructional psychology. The objective of this explorative study was to observe and analyse the learners' learning pathways according to their previous knowledge in detail and to understand the mental model formation processes associated with them more precisely. For the analysis of the learning pathways, drawings, texts, video and interview transcripts from 12 students were studied using qualitative methods. The learning pathways pursued by the learners significantly depend on their domain-specific previous knowledge. The learners' preconceptions could be typified based on specific characteristics, whereby three preconception types could be formed. The 'isolated pieces of knowledge' type of learners, who have very little or no previous knowledge about the greenhouse effect, build new mental models that are close to the target model. 'Reduced heat output' type of learners, who have previous knowledge that indicates compliances with central ideas of the normative model, reconstruct their knowledge by reorganising and interpreting their existing knowledge structures. 'Increasing heat input' type of learners, whose previous knowledge consists of subjective worldly knowledge, which has a greater personal explanatory value than the information from the learning environment, have more difficulties changing their mental models. They have to fundamentally reconstruct their mental models.

Identification of preliminary core outcome domains for communication about childhood vaccination: An online Delphi survey.

PubMed

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

2017-08-20

Communication interventions for childhood vaccination are promising strategies to address vaccine hesitancy, but current research is limited by the outcomes measured. Most studies measure only vaccination-related outcomes, with minimal consideration of vaccine hesitancy-relevant intermediate outcomes. This impedes understanding of which interventions or elements are effective. It is also unknown which outcomes are important to the range of stakeholders affected by vaccine hesitancy. Outcome selection shapes the evidence base, informing future interventions and trials, and should reflect stakeholder priorities. Therefore, our aim was to identify which outcome domains (i.e. broad outcome categories) are most important to different stakeholders, identifying preliminary core outcome domains to inform evaluation of three common vaccination communication types: (i) communication to inform or educate, (ii) remind or recall, and (iii) enhance community ownership. We conducted a two-stage online Delphi survey, involving four stakeholder groups: parents or community members, healthcare providers, researchers, and government or non-governmental organisation representatives. Participants rated the importance of eight outcome domains for each of the three communication types. They also rated specific outcomes within one domain ("attitudes or beliefs") and provided feedback about the survey. Collectively, stakeholder groups prioritised outcome domains differently when considering the effects of different communication types. For communication that aims to (i) inform or educate, the most important outcome domain is "knowledge or understanding"; for (ii) reminder communication, "vaccination status and behaviours"; and for (iii) community engagement communication, "community participation". All stakeholder groups rated most outcome domains as very important or critical. The highest rated specific outcome within the "attitudes or beliefs" domain was "trust". This Delphi survey expands the field of core outcomes research and identifies preliminary core outcome domains for measuring the effects of communication about childhood vaccination. The findings support the argument that vaccination communication is not a single homogenous intervention - it has a range of purposes, and vaccination communication evaluators should select outcomes accordingly. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Concept Formation in Environmental Education: 14-Year Olds' Work on the Intensified Greenhouse Effect and the Depletion of the Ozone Layer. Research Report

ERIC Educational Resources Information Center

Osterlind, Karolina

2005-01-01

A case study is presented describing the work of three pupils in the upper level of compulsory school. The pupils were learning about the intensified greenhouse effect and the depletion of the ozone layer. In their work, the need for certain domain-specific knowledge becomes apparent; for example, understanding such concepts as photosynthesis,…

Racializing Experiences of Foreign-Born and Ethnically Diverse Black Male Engineering Graduate Students: Implications for Student Affairs Practice, Policy, and Research

ERIC Educational Resources Information Center

Burt, Brian A.; Knight, Alexander; Robeson, Justin

2017-01-01

Despite a growing body of work on the experiences of Black collegians, the higher education knowledge base lacks scholarship focused on Black men in graduate programs who are foreign-born and/or identify ethnically as other than African American. In this article, we provide a domain-specific investigation (i.e., based on students' field of study),…

Inferring protein domains associated with drug side effects based on drug-target interaction network

PubMed Central

2013-01-01

Background Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. Results In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. Conclusion The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains. PMID:24565527

Magical thinking decreases across adulthood.

PubMed

Brashier, Nadia M; Multhaup, Kristi S

2017-12-01

Magical thinking, or illogical causal reasoning such as superstitions, decreases across childhood, but almost no data speak to whether this developmental trajectory continues across the life span. In four experiments, magical thinking decreased across adulthood. This pattern replicated across two judgment domains and could not be explained by age-related differences in tolerance of ambiguity, domain-specific knowledge, or search for meaning. These data complement and extend findings that experience, accumulated over decades, guides older adults' judgments so that they match, or even exceed, young adults' performance. They also counter participants' expectations, and cultural sayings (e.g., "old wives' tales"), that suggest that older adults are especially superstitious. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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…

A programmable rules engine to provide clinical decision support using HTML forms.

PubMed Central

Heusinkveld, J.; Geissbuhler, A.; Sheshelidze, D.; Miller, R.

1999-01-01

The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser. Images Figure 1 PMID:10566470

The impact of creative tendency, academic performance, and self-concept on creative science problem-finding.

PubMed

Liu, Mingxin; Hu, Weiping; Adey, Philip; Cheng, Li; Zhang, Xingli

2013-04-01

This study was designed to address the impacts of science performance, science self-concept, and creative tendency on the creative science problem-finding (CSPF) ability of a sample of Chinese middle-school students. Structural equation modeling was used to indicate that CSPF could be directly predicted by creative tendency and academic performance, and indirectly predicted by science self-concept. The findings strongly support the idea that curiosity, imagination, and domain-specific knowledge are important for CSPF, and science self-concept could be mediated by knowledge that affects CSPF. © 2012 The Institute of Psychology, Chinese Academy of Sciences and Blackwell Publishing Asia Pty Ltd.

Design of an assessment to probe teachers' content knowledge for teaching: An example from energy in high school physics

NASA Astrophysics Data System (ADS)

Etkina, Eugenia; Gitomer, Drew; Iaconangelo, Charles; Phelps, Geoffrey; Seeley, Lane; Vokos, Stamatis

2018-06-01

Research into teacher learning and practice over the last three decades shows that the teachers of a specific subject need to possess knowledge that is different from the knowledge of other content experts. Yet this specialized version of content knowledge that teachers need to plan instruction, respond to student ideas, and assess student understanding in real time is a theoretically elusive construct. It is crucial for the fields of precollege teacher preparation, teacher professional education, and postsecondary faculty professional development to (a) clarify the construct that underlies this specialized content knowledge, (b) operationalize it in some domain, (c) measure it in both static contexts and as it is enacted in the classroom, and (d) correlate its presence with "richness" of classroom instruction and its effect on student learning. This paper documents a piece of a multiyear, multi-institutional effort to investigate points (a)-(d) in the domain of energy in the first high school physics course. In particular, we describe the framework that we developed to clarify content knowledge for teaching in the context of high school energy learning. We then outline the process through which we developed, tested, and refined a "paper-and-pencil" assessment administered on a computer and discuss the substantive and psychometric features of several items based on a field test of the final form of the assessment. We choose to discuss these items for a dual purpose: to illustrate the application of our general framework and to present performance findings from a sample of 362 practicing high school teachers of physics.

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.

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…

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.

Problems and hopes perceived by mothers, fathers and physicians of children receiving palliative care.

PubMed

Hill, Douglas L; Miller, Victoria A; Hexem, Kari R; Carroll, Karen W; Faerber, Jennifer A; Kang, Tammy; Feudtner, Chris

2015-10-01

The quality of shared decision making for children with serious illness may depend on whether parents and physicians share similar perceptions of problems and hopes for the child. (i) Describe the problems and hopes reported by mothers, fathers and physicians of children receiving palliative care; (ii) examine the observed concordance between participants; (iii) examine parental perceived agreement; and (iv) examine whether parents who identified specific problems also specified corresponding hopes, or whether the problems were left 'hopeless'. Seventy-one parents and 43 physicians were asked to report problems and hopes and perceived agreement for 50 children receiving palliative care. Problems and hopes were classified into eight domains. Observed concordance was calculated between parents and between each parent and the physicians. The most common problem domains were physical body (88%), quality of life (74%) and medical knowledge (48%). The most common hope domains were quality of life (88%), suffering (76%) and physical body (39%). Overall parental dyads demonstrated a high percentage of concordance (82%) regarding reported problem domains and a lower percentage of concordance on hopes (65%). Concordance between parents and physicians regarding specific children was lower on problem (65-66%) and hope domains (59-63%). Respondents who identified problems regarding a child's quality of life or suffering were likely to also report corresponding hopes in these domains (93 and 82%, respectively). Asking parents and physicians to talk about problems and hopes may provide a straightforward means to improve the quality of shared decision making for critically ill children. © 2013 John Wiley & Sons Ltd.

The new meaning of quality in the information age.

PubMed

Prahalad, C K; Krishnan, M S

1999-01-01

Software applications are now a mission-critical source of competitive advantage for most companies. They are also a source of great risk, as the Y2K bug has made clear. Yet many line managers still haven't confronted software issues--partly because they aren't sure how best to define the quality of the applications in their IT infrastructures. Some companies such as Wal-Mart and the Gap have successfully integrated the software in their networks, but most have accumulated an unwidely number of incompatible applications--all designed to perform the same tasks. The authors provide a framework for measuring the performance of software in a company's IT portfolio. Quality traditionally has been measured according to a product's ability to meet certain specifications; other views of quality have emerged that measure a product's adaptability to customers' needs and a product's ability to encourage innovation. To judge software quality properly, argue the authors, managers must measure applications against all three approaches. Understanding the domain of a software application is an important part of that process. The domain is the body of knowledge about a user's needs and expectations for a product. Software domains change frequently based on how a consumer chooses to use, for example, Microsoft Word or a spreadsheet application. The domain can also be influenced by general changes in technology, such as the development of a new software platform. Thus, applications can't be judged only according to whether they conform to specifications. The authors discuss how to identify domain characteristics and software risks and suggest ways to reduce the variability of software domains.

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.

ISYMOD: a knowledge warehouse for the identification, assembly and analysis of bacterial integrated systems.

PubMed

Chabalier, Julie; Capponi, Cécile; Quentin, Yves; Fichant, Gwennaele

2005-04-01

Complex biological functions emerge from interactions between proteins in stable supra-molecular assemblies and/or through transitory contacts. Most of the time protein partners of the assemblies are composed of one or several domains which exhibit different biochemical functions. Thus the study of cellular process requires the identification of different functional units and their integration in an interaction network; such complexes are referred to as integrated systems. In order to exploit with optimum efficiency the increased release of data, automated bioinformatics strategies are needed to identify, reconstruct and model such systems. For that purpose, we have developed a knowledge warehouse dedicated to the representation and acquisition of bacterial integrated systems involved in the exchange of the bacterial cell with its environment. ISYMOD is a knowledge warehouse that consistently integrates in the same environment the data and the methods used for their acquisition. This is achieved through the construction of (1) a domain knowledge base (DKB) devoted to the storage of the knowledge about the systems, their functional specificities, their partners and how they are related and (2) a methodological knowledge base (MKB) which depicts the task layout used to identify and reconstruct functional integrated systems. Instantiation of the DKB is obtained by solving the tasks of the MKB, whereas some tasks need instances of the DKB to be solved. AROM, an object-based knowledge representation system, has been used to design the DKB, and its task manager, AROMTasks, for developing the MKB. In this study two integrated systems, ABC transporters and two component systems, both involved in adaptation processes of a bacterial cell to its biotope, have been used to evaluate the feasibility of the approach.

Knowledge-guided mutation in classification rules for autism treatment efficacy.

PubMed

Engle, Kelley; Rada, Roy

2017-03-01

Data mining methods in biomedical research might benefit by combining genetic algorithms with domain-specific knowledge. The objective of this research is to show how the evolution of treatment rules for autism might be guided. The semantic distance between two concepts in the taxonomy is measured by the number of relationships separating the concepts in the taxonomy. The hypothesis is that replacing a concept in a treatment rule will change the accuracy of the rule in direct proportion to the semantic distance between the concepts. The method uses a patient database and autism taxonomies. Treatment rules are developed with an algorithm that exploits the taxonomies. The results support the hypothesis. This research should both advance the understanding of autism data mining in particular and of knowledge-guided evolutionary search in biomedicine in general.

An Information Extraction Framework for Cohort Identification Using Electronic Health Records

PubMed Central

Liu, Hongfang; Bielinski, Suzette J.; Sohn, Sunghwan; Murphy, Sean; Wagholikar, Kavishwar B.; Jonnalagadda, Siddhartha R.; Ravikumar, K.E.; Wu, Stephen T.; Kullo, Iftikhar J.; Chute, Christopher G

Information extraction (IE), a natural language processing (NLP) task that automatically extracts structured or semi-structured information from free text, has become popular in the clinical domain for supporting automated systems at point-of-care and enabling secondary use of electronic health records (EHRs) for clinical and translational research. However, a high performance IE system can be very challenging to construct due to the complexity and dynamic nature of human language. In this paper, we report an IE framework for cohort identification using EHRs that is a knowledge-driven framework developed under the Unstructured Information Management Architecture (UIMA). A system to extract specific information can be developed by subject matter experts through expert knowledge engineering of the externalized knowledge resources used in the framework. PMID:24303255

Development of an Agile Knowledge Engineering Framework in Support of Multi-Disciplinary Translational Research

PubMed Central

Borlawsky, Tara B.; Dhaval, Rakesh; Hastings, Shannon L.; Payne, Philip R. O.

2009-01-01

In October 2006, the National Institutes of Health launched a new national consortium, funded through Clinical and Translational Science Awards (CTSA), with the primary objective of improving the conduct and efficiency of the inherently multi-disciplinary field of translational research. To help meet this goal, the Ohio State University Center for Clinical and Translational Science has launched a knowledge management initiative that is focused on facilitating widespread semantic interoperability among administrative, basic science, clinical and research computing systems, both internally and among the translational research community at-large, through the integration of domain-specific standard terminologies and ontologies with local annotations. This manuscript describes an agile framework that builds upon prevailing knowledge engineering and semantic interoperability methods, and will be implemented as part this initiative. PMID:21347164

Development of an agile knowledge engineering framework in support of multi-disciplinary translational research.

PubMed

Borlawsky, Tara B; Dhaval, Rakesh; Hastings, Shannon L; Payne, Philip R O

2009-03-01

In October 2006, the National Institutes of Health launched a new national consortium, funded through Clinical and Translational Science Awards (CTSA), with the primary objective of improving the conduct and efficiency of the inherently multi-disciplinary field of translational research. To help meet this goal, the Ohio State University Center for Clinical and Translational Science has launched a knowledge management initiative that is focused on facilitating widespread semantic interoperability among administrative, basic science, clinical and research computing systems, both internally and among the translational research community at-large, through the integration of domain-specific standard terminologies and ontologies with local annotations. This manuscript describes an agile framework that builds upon prevailing knowledge engineering and semantic interoperability methods, and will be implemented as part this initiative.

Examining, Documenting, and Modeling the Problem Space of a Variable Domain

DTIC Science & Technology

2002-06-14

Feature-Oriented Domain Analysis ( FODA ) .............................................................................................. 9...development of this proposed process include: Feature-Oriented Domain Analysis ( FODA ) [3,4], Organization Domain Modeling (ODM) [2,5,6], Family-Oriented...configuration knowledge using generators [2]. 8 Existing Methods of Domain Engineering Feature-Oriented Domain Analysis ( FODA ) FODA is a domain

Structure of glycosylated NPC1 luminal domain C reveals insights into NPC2 and Ebola virus interactions.

PubMed

Zhao, Yuguang; Ren, Jingshan; Harlos, Karl; Stuart, David I

2016-03-01

Niemann-pick type C1 (NPC1) is an endo/lysosomal membrane protein involved in intracellular cholesterol trafficking, and its luminal domain C is an essential endosomal receptor for Ebola and Marburg viruses. We have determined the crystal structure of glycosylated NPC1 luminal domain C and find all seven possible sites are glycosylated. Mapping the disease mutations onto the glycosylated structure reveals a potential binding face for NPC2. Knowledge-based docking of NPC1 onto Ebola viral glycoprotein and sequence analysis of filovirus susceptible and refractory species reveals four critical residues, H418, Q421, F502 and F504, some or all of which are likely responsible for the species-specific susceptibility to the virus infection. © 2016 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

A web-portal for interactive data exploration, visualization, and hypothesis testing

PubMed Central

Bartsch, Hauke; Thompson, Wesley K.; Jernigan, Terry L.; Dale, Anders M.

2014-01-01

Clinical research studies generate data that need to be shared and statistically analyzed by their participating institutions. The distributed nature of research and the different domains involved present major challenges to data sharing, exploration, and visualization. The Data Portal infrastructure was developed to support ongoing research in the areas of neurocognition, imaging, and genetics. Researchers benefit from the integration of data sources across domains, the explicit representation of knowledge from domain experts, and user interfaces providing convenient access to project specific data resources and algorithms. The system provides an interactive approach to statistical analysis, data mining, and hypothesis testing over the lifetime of a study and fulfills a mandate of public sharing by integrating data sharing into a system built for active data exploration. The web-based platform removes barriers for research and supports the ongoing exploration of data. PMID:24723882

Supporting diagnosis and treatment in medical care based on Big Data processing.

PubMed

Lupşe, Oana-Sorina; Crişan-Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara; Bernard, Elena

2014-01-01

With information and data in all domains growing every day, it is difficult to manage and extract useful knowledge for specific situations. This paper presents an integrated system architecture to support the activity in the Ob-Gin departments with further developments in using new technology to manage Big Data processing - using Google BigQuery - in the medical domain. The data collected and processed with Google BigQuery results from different sources: two Obstetrics & Gynaecology Departments, the TreatSuggest application - an application for suggesting treatments, and a home foetal surveillance system. Data is uploaded in Google BigQuery from Bega Hospital Timişoara, Romania. The analysed data is useful for the medical staff, researchers and statisticians from public health domain. The current work describes the technological architecture and its processing possibilities that in the future will be proved based on quality criteria to lead to a better decision process in diagnosis and public health.

Finding the music of speech: Musical knowledge influences pitch processing in speech.

PubMed

Vanden Bosch der Nederlanden, Christina M; Hannon, Erin E; Snyder, Joel S

2015-10-01

Few studies comparing music and language processing have adequately controlled for low-level acoustical differences, making it unclear whether differences in music and language processing arise from domain-specific knowledge, acoustic characteristics, or both. We controlled acoustic characteristics by using the speech-to-song illusion, which often results in a perceptual transformation to song after several repetitions of an utterance. Participants performed a same-different pitch discrimination task for the initial repetition (heard as speech) and the final repetition (heard as song). Better detection was observed for pitch changes that violated rather than conformed to Western musical scale structure, but only when utterances transformed to song, indicating that music-specific pitch representations were activated and influenced perception. This shows that music-specific processes can be activated when an utterance is heard as song, suggesting that the high-level status of a stimulus as either language or music can be behaviorally dissociated from low-level acoustic factors. Copyright © 2015 Elsevier B.V. All rights reserved.

Automating software design system DESTA

NASA Technical Reports Server (NTRS)

Lovitsky, Vladimir A.; Pearce, Patricia D.

1992-01-01

'DESTA' is the acronym for the Dialogue Evolutionary Synthesizer of Turnkey Algorithms by means of a natural language (Russian or English) functional specification of algorithms or software being developed. DESTA represents the computer-aided and/or automatic artificial intelligence 'forgiving' system which provides users with software tools support for algorithm and/or structured program development. The DESTA system is intended to provide support for the higher levels and earlier stages of engineering design of software in contrast to conventional Computer Aided Design (CAD) systems which provide low level tools for use at a stage when the major planning and structuring decisions have already been taken. DESTA is a knowledge-intensive system. The main features of the knowledge are procedures, functions, modules, operating system commands, batch files, their natural language specifications, and their interlinks. The specific domain for the DESTA system is a high level programming language like Turbo Pascal 6.0. The DESTA system is operational and runs on an IBM PC computer.

Semantically Enabling Knowledge Representation of Metamorphic Petrology Data

NASA Astrophysics Data System (ADS)

West, P.; Fox, P. A.; Spear, F. S.; Adali, S.; Nguyen, C.; Hallett, B. W.; Horkley, L. K.

2012-12-01

More and more metamorphic petrology data is being collected around the world, and is now being organized together into different virtual data portals by means of virtual organizations. For example, there is the virtual data portal Petrological Database (PetDB, http://www.petdb.org) of the Ocean Floor that is organizing scientific information about geochemical data of ocean floor igneous and metamorphic rocks; and also The Metamorphic Petrology Database (MetPetDB, http://metpetdb.rpi.edu) that is being created by a global community of metamorphic petrologists in collaboration with software engineers and data managers at Rensselaer Polytechnic Institute. The current focus is to provide the ability for scientists and researchers to register their data and search the databases for information regarding sample collections. What we present here is the next step in evolution of the MetPetDB portal, utilizing semantically enabled features such as discovery, data casting, faceted search, knowledge representation, and linked data as well as organizing information about the community and collaboration within the virtual community itself. We take the information that is currently represented in a relational database and make it available through web services, SPARQL endpoints, semantic and triple-stores where inferencing is enabled. We will be leveraging research that has taken place in virtual observatories, such as the Virtual Solar Terrestrial Observatory (VSTO) and the Biological and Chemical Oceanography Data Management Office (BCO-DMO); vocabulary work done in various communities such as Observations and Measurements (ISO 19156), FOAF (Friend of a Friend), Bibo (Bibliography Ontology), and domain specific ontologies; enabling provenance traces of samples and subsamples using the different provenance ontologies; and providing the much needed linking of data from the various research organizations into a common, collaborative virtual observatory. In addition to better representing and presenting the actual data, we also look to organize and represent the knowledge information and expertise behind the data. Domain experts hold a lot of knowledge in their minds, in their presentations and publications, and elsewhere. Not only is this a technical issue, this is also a social issue in that we need to be able to encourage the domain experts to share their knowledge in a way that can be searched and queried over. With this additional focus in MetPetDB the site can be used more efficiently by other domain experts, but can also be utilized by non-specialists as well in order to educate people of the importance of the work being done as well as enable future domain experts.

Credentialing Data Scientists: A Domain Repository Perspective

NASA Astrophysics Data System (ADS)

Lehnert, K. A.; Furukawa, H.

2015-12-01

A career in data science can have many paths: data curation, data analysis, metadata modeling - all of these in different commercial or scientific applications. Can a certification as 'data scientist' provide the guarantee that an applicant or candidate for a data science position has just the right skills? How valuable is a 'generic' certification as data scientist for an employer looking to fill a data science position? Credentials that are more specific and discipline-oriented may be more valuable to both the employer and the job candidate. One employment sector for data scientists are the data repositories that provide discipline-specific data services for science communities. Data science positions within domain repositories include a wide range of responsibilities in support of the full data life cycle - from data preservation and curation to development of data models, ontologies, and user interfaces, to development of data analysis and visualization tools to community education and outreach, and require a substantial degree of discipline-specific knowledge of scientific data acquisition and analysis workflows, data quality measures, and data cultures. Can there be certification programs for domain-specific data scientists that help build the urgently needed workforce for the repositories? The American Geophysical Union has recently started an initiative to develop a program for data science continuing education and data science professional certification for the Earth and space sciences. An Editorial Board has been charged to identify and develop curricula and content for these programs and to provide input and feedback in the implementation of the program. This presentation will report on the progress of this initiative and evaluate its utility for the needs of domain repositories in the Earth and space sciences.