Structural Representations in Knowledge Acquisition.

ERIC Educational Resources Information Center

Gonzalvo, Pilar; And Others

1994-01-01

Multidimensional scaling (MDS) and Pathfinder techniques for assessing changes in the structural representation of a knowledge domain were studied with relatedness ratings collected from 72 Spanish college students. Comparison of student and expert similarity measures indicate that MDS and graph theoretic approaches are valid techniques. (SLD)

Approaching an Understanding of Omniscience from the Preschool Years to Early Adulthood

ERIC Educational Resources Information Center

Lane, Jonathan D.; Wellman, Henry M.; Evans, E. Margaret

2014-01-01

Individuals in many cultures believe in omniscient (all-knowing) beings, but everyday representations of omniscience have rarely been studied. To understand the nature of such representations requires knowing how they develop. Two studies examined the breadth of knowledge (i.e., types of knowledge) and depth of knowledge (i.e., amount of knowledge…

The Representation of Object-Directed Action and Function Knowledge in the Human Brain

PubMed Central

Chen, Quanjing; Garcea, Frank E.; Mahon, Bradford Z.

2016-01-01

The appropriate use of everyday objects requires the integration of action and function knowledge. Previous research suggests that action knowledge is represented in frontoparietal areas while function knowledge is represented in temporal lobe regions. Here we used multivoxel pattern analysis to investigate the representation of object-directed action and function knowledge while participants executed pantomimes of familiar tool actions. A novel approach for decoding object knowledge was used in which classifiers were trained on one pair of objects and then tested on a distinct pair; this permitted a measurement of classification accuracy over and above object-specific information. Region of interest (ROI) analyses showed that object-directed actions could be decoded in tool-preferring regions of both parietal and temporal cortex, while no independently defined tool-preferring ROI showed successful decoding of object function. However, a whole-brain searchlight analysis revealed that while frontoparietal motor and peri-motor regions are engaged in the representation of object-directed actions, medial temporal lobe areas in the left hemisphere are involved in the representation of function knowledge. These results indicate that both action and function knowledge are represented in a topographically coherent manner that is amenable to study with multivariate approaches, and that the left medial temporal cortex represents knowledge of object function. PMID:25595179

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

PubMed Central

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

2009-01-01

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

Assessing Students' Accounting Knowledge: A Structural Approach.

ERIC Educational Resources Information Center

Boldt, Margaret N.

2001-01-01

Comparisons of students' representations of financial accounting concepts with the knowledge structures of experts were depicted using Pathfinder networks. This structural approach identified the level of students' understanding of concepts and knowledge gaps that need to be addressed. (SK)

Lexical is as lexical does: computational approaches to lexical representation

PubMed Central

Woollams, Anna M.

2015-01-01

In much of neuroimaging and neuropsychology, regions of the brain have been associated with ‘lexical representation’, with little consideration as to what this cognitive construct actually denotes. Within current computational models of word recognition, there are a number of different approaches to the representation of lexical knowledge. Structural lexical representations, found in original theories of word recognition, have been instantiated in modern localist models. However, such a representational scheme lacks neural plausibility in terms of economy and flexibility. Connectionist models have therefore adopted distributed representations of form and meaning. Semantic representations in connectionist models necessarily encode lexical knowledge. Yet when equipped with recurrent connections, connectionist models can also develop attractors for familiar forms that function as lexical representations. Current behavioural, neuropsychological and neuroimaging evidence shows a clear role for semantic information, but also suggests some modality- and task-specific lexical representations. A variety of connectionist architectures could implement these distributed functional representations, and further experimental and simulation work is required to discriminate between these alternatives. Future conceptualisations of lexical representations will therefore emerge from a synergy between modelling and neuroscience. PMID:25893204

Learning multisensory representations for auditory-visual transfer of sequence category knowledge: a probabilistic language of thought approach.

PubMed

Yildirim, Ilker; Jacobs, Robert A

2015-06-01

If a person is trained to recognize or categorize objects or events using one sensory modality, the person can often recognize or categorize those same (or similar) objects and events via a novel modality. This phenomenon is an instance of cross-modal transfer of knowledge. Here, we study the Multisensory Hypothesis which states that people extract the intrinsic, modality-independent properties of objects and events, and represent these properties in multisensory representations. These representations underlie cross-modal transfer of knowledge. We conducted an experiment evaluating whether people transfer sequence category knowledge across auditory and visual domains. Our experimental data clearly indicate that we do. We also developed a computational model accounting for our experimental results. Consistent with the probabilistic language of thought approach to cognitive modeling, our model formalizes multisensory representations as symbolic "computer programs" and uses Bayesian inference to learn these representations. Because the model demonstrates how the acquisition and use of amodal, multisensory representations can underlie cross-modal transfer of knowledge, and because the model accounts for subjects' experimental performances, our work lends credence to the Multisensory Hypothesis. Overall, our work suggests that people automatically extract and represent objects' and events' intrinsic properties, and use these properties to process and understand the same (and similar) objects and events when they are perceived through novel sensory modalities.

On a categorial aspect of knowledge representation

NASA Astrophysics Data System (ADS)

Tataj, Emanuel; Mulawka, Jan; Nieznański, Edward

Adequate representation of data is crucial for modeling any type of data. To faithfully present and describe the relevant section of the world it is necessary to select the method that can easily be implemented on a computer system which will help in further description allowing reasoning. The main objective of this contribution is to present methods of knowledge representation using categorial approach. Next to identify the main advantages for computer implementation. Categorical aspect of knowledge representation is considered in semantic networks realisation. Such method borrows already known metaphysics properties for data modeling process. The potential topics of further development of categorical semantic networks implementations are also underlined.

Biologically Plausible, Human-scale Knowledge Representation

ERIC Educational Resources Information Center

Crawford, Eric; Gingerich, Matthew; Eliasmith, Chris

2016-01-01

Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, 1993), "mesh" binding (van der Velde & de Kamps, 2006), and conjunctive binding (Smolensky, 1990). Recent theoretical work has suggested that…

Teacher change in implementing a research-developed representation construction pedagogy

NASA Astrophysics Data System (ADS)

Hubber, Peter; Chittleborough, Gail

2016-05-01

The Representations in Learning Science (RiLS) project developed a representation construction approach to teaching and learning in science, which has successfully demonstrated enhanced student learning through sustained engagement with ideas, and enhancement of teachers' pedagogical knowledge and understandings of how knowledge in science is developed and communicated. The current Constructing Representations in Science Pedagogy (CRISP) project aims at wider scale implementation of the representation construction approach. This paper explores a range of issues that confronted four Year-8 teachers in implementing this research-developed approach, such as: preparedness of the teacher in terms of epistemological positioning and positioning as a learner, significant support for planning and modelling by the university expert, and a team ethos where teachers share ideas and plan jointly. The Year-8 teachers implemented a representation construction approach to the teaching of the topic of astronomy. The Interconnected Model of Teacher Growth (IMTG) (Clarke and Hollingworth, Teach. Educ., 18 (2001) 947) was used to analyse the teachers' experience in planning and delivering the teaching sequence. This model was found to be flexible in identifying the experiences of teachers in different situations and useful in identifying issues for implementation of a research-developed pedagogy.

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

PubMed

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

2009-09-01

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

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

PubMed

An, Gary C

2010-01-01

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

The Representation of Object-Directed Action and Function Knowledge in the Human Brain.

PubMed

Chen, Quanjing; Garcea, Frank E; Mahon, Bradford Z

2016-04-01

The appropriate use of everyday objects requires the integration of action and function knowledge. Previous research suggests that action knowledge is represented in frontoparietal areas while function knowledge is represented in temporal lobe regions. Here we used multivoxel pattern analysis to investigate the representation of object-directed action and function knowledge while participants executed pantomimes of familiar tool actions. A novel approach for decoding object knowledge was used in which classifiers were trained on one pair of objects and then tested on a distinct pair; this permitted a measurement of classification accuracy over and above object-specific information. Region of interest (ROI) analyses showed that object-directed actions could be decoded in tool-preferring regions of both parietal and temporal cortex, while no independently defined tool-preferring ROI showed successful decoding of object function. However, a whole-brain searchlight analysis revealed that while frontoparietal motor and peri-motor regions are engaged in the representation of object-directed actions, medial temporal lobe areas in the left hemisphere are involved in the representation of function knowledge. These results indicate that both action and function knowledge are represented in a topographically coherent manner that is amenable to study with multivariate approaches, and that the left medial temporal cortex represents knowledge of object function. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Decision support system for nursing management control

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

Ernst, C.J.

A knowledge representation approach for expert systems supporting decision processes in business is proposed. A description of a knowledge representation schema using a logic programming metalanguage is described, then the role of such a schema in a management expert system is demonstrated through the problem of nursing management control in hospitals. 18 references.

Foundation: Transforming data bases into knowledge bases

NASA Technical Reports Server (NTRS)

Purves, R. B.; Carnes, James R.; Cutts, Dannie E.

1987-01-01

One approach to transforming information stored in relational data bases into knowledge based representations and back again is described. This system, called Foundation, allows knowledge bases to take advantage of vast amounts of pre-existing data. A benefit of this approach is inspection, and even population, of data bases through an intelligent knowledge-based front-end.

Representations of the Nature of Scientific Knowledge in Turkish Biology Textbooks

ERIC Educational Resources Information Center

Irez, Serhat

2016-01-01

Considering the impact of textbooks on learning, this study set out to assess representations of the nature of scientific knowledge in Turkish 9th grade biology textbooks. To this end, the ten most commonly used 9th grade biology textbooks were analyzed. A qualitative research approach was utilized and the textbooks were analyzed using…

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.

Knowledge-based vision and simple visual machines.

PubMed Central

Cliff, D; Noble, J

1997-01-01

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong. PMID:9304684

VStops: A Thinking Strategy and Visual Representation Approach in Mathematical Word Problem Solving toward Enhancing STEM Literacy

ERIC Educational Resources Information Center

Abdullah, Nasarudin; Halim, Lilia; Zakaria, Effandi

2014-01-01

This study aimed to determine the impact of strategic thinking and visual representation approaches (VStops) on the achievement, conceptual knowledge, metacognitive awareness, awareness of problem-solving strategies, and student attitudes toward mathematical word problem solving among primary school students. The experimental group (N = 96)…

The Effects of Representations, Constructivist Approaches, and Engagement on Middle School Students' Algebraic Procedure and Conceptual Understanding

ERIC Educational Resources Information Center

Ross, Amanda; Willson, Victor

2012-01-01

This study examined the effects of types of representations, constructivist teaching approaches, and student engagement on middle school algebra students' procedural knowledge and conceptual understanding. Data gathered from 16 video lessons and algebra pretest/posttests were used to run three multilevel structural equation models. Symbolic…

Eliciting candidate anatomical routes for protein interactions: a scenario from endocrine physiology

PubMed Central

2013-01-01

Background In this paper, we use: i) formalised anatomical knowledge of connectivity between body structures and ii) a formal theory of physiological transport between fluid compartments in order to define and make explicit the routes followed by proteins to a site of interaction. The underlying processes are the objects of mathematical models of physiology and, therefore, the motivation for the approach can be understood as using knowledge representation and reasoning methods to propose concrete candidate routes corresponding to correlations between variables in mathematical models of physiology. In so doing, the approach projects physiology models onto a representation of the anatomical and physiological reality which underpins them. Results The paper presents a method based on knowledge representation and reasoning for eliciting physiological communication routes. In doing so, the paper presents the core knowledge representation and algorithms using it in the application of the method. These are illustrated through the description of a prototype implementation and the treatment of a simple endocrine scenario whereby a candidate route of communication between ANP and its receptors on the external membrane of smooth muscle cells in renal arterioles is elicited. The potential of further development of the approach is illustrated through the informal discussion of a more complex scenario. Conclusions The work presented in this paper supports research in intercellular communication by enabling knowledge‐based inference on physiologically‐related biomedical data and models. PMID:23590598

Proceedings of the Workshop on Change of Representation and Problem Reformulation

NASA Technical Reports Server (NTRS)

Lowry, Michael R.

1992-01-01

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

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

PubMed

Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin

2018-05-01

Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.

Knowledge representation and management: transforming textual information into useful knowledge.

PubMed

Rassinoux, A-M

2010-01-01

To summarize current outstanding research in the field of knowledge representation and management. Synopsis of the articles selected for the IMIA Yearbook 2010. Four interesting papers, dealing with structured knowledge, have been selected for the section knowledge representation and management. Combining the newest techniques in computational linguistics and natural language processing with the latest methods in statistical data analysis, machine learning and text mining has proved to be efficient for turning unstructured textual information into meaningful knowledge. Three of the four selected papers for the section knowledge representation and management corroborate this approach and depict various experiments conducted to .extract meaningful knowledge from unstructured free texts such as extracting cancer disease characteristics from pathology reports, or extracting protein-protein interactions from biomedical papers, as well as extracting knowledge for the support of hypothesis generation in molecular biology from the Medline literature. Finally, the last paper addresses the level of formally representing and structuring information within clinical terminologies in order to render such information easily available and shareable among the health informatics community. Delivering common powerful tools able to automatically extract meaningful information from the huge amount of electronically unstructured free texts is an essential step towards promoting sharing and reusability across applications, domains, and institutions thus contributing to building capacities worldwide.

Dynamic speech representations in the human temporal lobe.

PubMed

Leonard, Matthew K; Chang, Edward F

2014-09-01

Speech perception requires rapid integration of acoustic input with context-dependent knowledge. Recent methodological advances have allowed researchers to identify underlying information representations in primary and secondary auditory cortex and to examine how context modulates these representations. We review recent studies that focus on contextual modulations of neural activity in the superior temporal gyrus (STG), a major hub for spectrotemporal encoding. Recent findings suggest a highly interactive flow of information processing through the auditory ventral stream, including influences of higher-level linguistic and metalinguistic knowledge, even within individual areas. Such mechanisms may give rise to more abstract representations, such as those for words. We discuss the importance of characterizing representations of context-dependent and dynamic patterns of neural activity in the approach to speech perception research. Copyright © 2014 Elsevier Ltd. All rights reserved.

Team knowledge representation: a network perspective.

PubMed

Espinosa, J Alberto; Clark, Mark A

2014-03-01

We propose a network perspective of team knowledge that offers both conceptual and methodological advantages, expanding explanatory value through representation and measurement of component structure and content. Team knowledge has typically been conceptualized and measured with relatively simple aggregates, without fully accounting for differing knowledge configurations among team members. Teams with similar aggregate values of team knowledge may have very different team dynamics depending on how knowledge isolates, cliques, and densities are distributed across the team; which members are the most knowledgeable; who shares knowledge with whom; and how knowledge clusters are distributed. We illustrate our proposed network approach through a sample of 57 teams, including how to compute, analyze, and visually represent team knowledge. Team knowledge network structures (isolation, centrality) are associated with outcomes of, respectively, task coordination, strategy coordination, and the proportion of team knowledge cliques, all after controlling for shared team knowledge. Network analysis helps to represent, measure, and understand the relationship of team knowledge to outcomes of interest to team researchers, members, and managers. Our approach complements existing team knowledge measures. Researchers and managers can apply network concepts and measures to help understand where team knowledge is held within a team and how this relational structure may influence team coordination, cohesion, and performance.

Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules.

PubMed

Lezcano, Leonardo; Sicilia, Miguel-Angel; Rodríguez-Solano, Carlos

2011-04-01

Semantic interoperability is essential to facilitate the computerized support for alerts, workflow management and evidence-based healthcare across heterogeneous electronic health record (EHR) systems. Clinical archetypes, which are formal definitions of specific clinical concepts defined as specializations of a generic reference (information) model, provide a mechanism to express data structures in a shared and interoperable way. However, currently available archetype languages do not provide direct support for mapping to formal ontologies and then exploiting reasoning on clinical knowledge, which are key ingredients of full semantic interoperability, as stated in the SemanticHEALTH report [1]. This paper reports on an approach to translate definitions expressed in the openEHR Archetype Definition Language (ADL) to a formal representation expressed using the Ontology Web Language (OWL). The formal representations are then integrated with rules expressed with Semantic Web Rule Language (SWRL) expressions, providing an approach to apply the SWRL rules to concrete instances of clinical data. Sharing the knowledge expressed in the form of rules is consistent with the philosophy of open sharing, encouraged by archetypes. Our approach also allows the reuse of formal knowledge, expressed through ontologies, and extends reuse to propositions of declarative knowledge, such as those encoded in clinical guidelines. This paper describes the ADL-to-OWL translation approach, describes the techniques to map archetypes to formal ontologies, and demonstrates how rules can be applied to the resulting representation. We provide examples taken from a patient safety alerting system to illustrate our approach. Copyright © 2010 Elsevier Inc. All rights reserved.

Representation and Re-Presentation in Litigation Science

PubMed Central

Jasanoff, Sheila

2008-01-01

Federal appellate courts have devised several criteria to help judges distinguish between reliable and unreliable scientific evidence. The best known are the U.S. Supreme Court’s criteria offered in 1993 in Daubert v. Merrell Dow Pharmaceuticals, Inc. This article focuses on another criterion, offered by the Ninth Circuit Court of Appeals, that instructs judges to assign lower credibility to “litigation science” than to science generated before litigation. In this article I argue that the criterion-based approach to judicial screening of scientific evidence is deeply flawed. That approach buys into the faulty premise that there are external criteria, lying outside the legal process, by which judges can distinguish between good and bad science. It erroneously assumes that judges can ascertain the appropriate criteria and objectively apply them to challenged evidence before litigation unfolds, and before methodological disputes are sorted out during that process. Judicial screening does not take into account the dynamics of litigation itself, including gaming by the parties and framing by judges, as constitutive factors in the production and representation of knowledge. What is admitted through judicial screening, in other words, is not precisely what a jury would see anyway. Courts are sites of repeated re-representations of scientific knowledge. In sum, the screening approach fails to take account of the wealth of existing scholarship on the production and validation of scientific facts. An unreflective application of that approach thus puts courts at risk of relying upon a “junk science” of the nature of scientific knowledge. PMID:18197311

Representation and re-presentation in litigation science.

PubMed

Jasanoff, Sheila

2008-01-01

Federal appellate courts have devised several criteria to help judges distinguish between reliable and unreliable scientific evidence. The best known are the U.S. Supreme Court's criteria offered in 1993 in Daubert v. Merrell Dow Pharmaceuticals, Inc. This article focuses on another criterion, offered by the Ninth Circuit Court of Appeals, that instructs judges to assign lower credibility to "litigation science" than to science generated before litigation. In this article I argue that the criterion-based approach to judicial screening of scientific evidence is deeply flawed. That approach buys into the faulty premise that there are external criteria, lying outside the legal process, by which judges can distinguish between good and bad science. It erroneously assumes that judges can ascertain the appropriate criteria and objectively apply them to challenged evidence before litigation unfolds, and before methodological disputes are sorted out during that process. Judicial screening does not take into account the dynamics of litigation itself, including gaming by the parties and framing by judges, as constitutive factors in the production and representation of knowledge. What is admitted through judicial screening, in other words, is not precisely what a jury would see anyway. Courts are sites of repeated re-representations of scientific knowledge. In sum, the screening approach fails to take account of the wealth of existing scholarship on the production and validation of scientific facts. An unreflective application of that approach thus puts courts at risk of relying upon a "junk science" of the nature of scientific knowledge.

Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

PubMed

Chaudhri, Vinay K; Elenius, Daniel; Goldenkranz, Andrew; Gong, Allison; Martone, Maryann E; Webb, William; Yorke-Smith, Neil

2014-01-01

Using knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms? Our existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important. With some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels.

Understanding the Role of Representation in Interorganizational Knowledge Integration: A Case Study of an IT Outsourcing Project

ERIC Educational Resources Information Center

Werr, Andreas; Runsten, Philip

2013-01-01

Purpose: The current paper aims at contributing to the understanding of interorganizational knowledge integration by highlighting the role of individuals' understandings of the task and how they shape knowledge integrating behaviours. Design/methodology/approach: The paper presents a framework of knowledge integration as heedful interrelating.…

A Knowledge-Based Approach to Language Production

DTIC Science & Technology

1985-08-01

representation -- the internal structures which the system is generating from. and (3) the choice problem -- how the intricate relationship between the...texts from several different internal representations. One example of the output produced by MUMBLE is the following text, produced from a...brackets. This notation is used to illustrate some templates which are encoded in Ace. The internal representation of these templates is achieved using

Practical and generalizable architecture for an intelligent tutoring system

NASA Astrophysics Data System (ADS)

Kaplan, Randy M.; Trenholm, Harriet

1993-03-01

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

Optimize scientific communication skills on work and energy concept with implementation of interactive conceptual instruction and multi representation approach

NASA Astrophysics Data System (ADS)

Patriot, E. A.; Suhandi, A.; Chandra, D. T.

2018-05-01

The ultimate goal of learning in the curriculum 2013 is that learning must improve and balance between soft skills and hard skills of learners. In addition to the knowledge aspect, one of the other skills to be trained in the learning process using a scientific approach is communication skills. This study aims to get an overview of the implementation of interactive conceptual instruction with multi representation to optimize the achievement of students’ scientific communication skills on work and energy concept. The scientific communication skills contains the sub-skills were searching the information, scientific writing, group discussion and knowledge presentation. This study was descriptive research with observation method. Subjects in this study were 35 students of class X in Senior High School at Sumedang. The results indicate an achievement of optimal scientific communication skills. The greatest achievement of KKI based on observation is at fourth meeting of KKI-3, which is a sub-skill of resume writing of 89%. Allmost students responded positively to the implication of interactive conceptual instruction with multi representation approach. It can be concluded that the implication of interactive conceptual instruction with multi representation approach can optimize the achievement of students’ scientific communication skill on work and energy concept.

Probability and possibility-based representations of uncertainty in fault tree analysis.

PubMed

Flage, Roger; Baraldi, Piero; Zio, Enrico; Aven, Terje

2013-01-01

Expert knowledge is an important source of input to risk analysis. In practice, experts might be reluctant to characterize their knowledge and the related (epistemic) uncertainty using precise probabilities. The theory of possibility allows for imprecision in probability assignments. The associated possibilistic representation of epistemic uncertainty can be combined with, and transformed into, a probabilistic representation; in this article, we show this with reference to a simple fault tree analysis. We apply an integrated (hybrid) probabilistic-possibilistic computational framework for the joint propagation of the epistemic uncertainty on the values of the (limiting relative frequency) probabilities of the basic events of the fault tree, and we use possibility-probability (probability-possibility) transformations for propagating the epistemic uncertainty within purely probabilistic and possibilistic settings. The results of the different approaches (hybrid, probabilistic, and possibilistic) are compared with respect to the representation of uncertainty about the top event (limiting relative frequency) probability. Both the rationale underpinning the approaches and the computational efforts they require are critically examined. We conclude that the approaches relevant in a given setting depend on the purpose of the risk analysis, and that further research is required to make the possibilistic approaches operational in a risk analysis context. © 2012 Society for Risk Analysis.

On the biological plausibility of grandmother cells: implications for neural network theories in psychology and neuroscience.

PubMed

Bowers, Jeffrey S

2009-01-01

A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned in connectionist models and neural coding in brain and often dismiss localist (grandmother cell) theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-cell recording studies. The author also contrast local and alternative distributed coding schemes (sparse and coarse coding) and argues that common rejection of grandmother cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models.

Knowledge representation of motor activity of patients with Parkinson's disease.

PubMed

Kostek, Bożena; Kupryjanow, Adam; Czyżewski, Andrzej

An approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity disorders in patients. Obtained results indicate that it is possible to interpret some selected patient's body movements with a sufficiently high effectiveness.

Artificial intelligence, expert systems, computer vision, and natural language processing

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

Standard model of knowledge representation

NASA Astrophysics Data System (ADS)

Yin, Wensheng

2016-09-01

Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.

Reasoning about procedural knowledge

NASA Technical Reports Server (NTRS)

Georgeff, M. P.

1985-01-01

A crucial aspect of automated reasoning about space operations is that knowledge of the problem domain is often procedural in nature - that is, the knowledge is often in the form of sequences of actions or procedures for achieving given goals or reacting to certain situations. In this paper a system is described that explicitly represents and reasons about procedural knowledge. The knowledge representation used is sufficiently rich to describe the effects of arbitrary sequences of tests and actions, and the inference mechanism provides a means for directly using this knowledge to reach desired operational goals. Furthermore, the representation has a declarative semantics that provides for incremental changes to the system, rich explanatory capabilities, and verifiability. The approach also provides a mechanism for reasoning about the use of this knowledge, thus enabling the system to choose effectively between alternative courses of action.

Locating Object Knowledge in the Brain: Comment on Bowers's (2009) Attempt to Revive the Grandmother Cell Hypothesis

ERIC Educational Resources Information Center

Plaut, David C.; McClelland, James L.

2010-01-01

According to Bowers, the finding that there are neurons with highly selective responses to familiar stimuli supports theories positing localist representations over approaches positing the type of distributed representations typically found in parallel distributed processing (PDP) models. However, his conclusions derive from an overly narrow view…

An individual differences approach to semantic cognition: Divergent effects of age on representation, retrieval and selection.

PubMed

Hoffman, Paul

2018-05-25

Semantic cognition refers to the appropriate use of acquired knowledge about the world. This requires representation of knowledge as well as control processes which ensure that currently-relevant aspects of knowledge are retrieved and selected. Although these abilities can be impaired selectively following brain damage, the relationship between them in healthy individuals is unclear. It is also commonly assumed that semantic cognition is preserved in later life, because older people have greater reserves of knowledge. However, this claim overlooks the possibility of decline in semantic control processes. Here, semantic cognition was assessed in 100 young and older adults. Despite having a broader knowledge base, older people showed specific impairments in semantic control, performing more poorly than young people when selecting among competing semantic representations. Conversely, they showed preserved controlled retrieval of less salient information from the semantic store. Breadth of semantic knowledge was positively correlated with controlled retrieval but was unrelated to semantic selection ability, which was instead correlated with non-semantic executive function. These findings indicate that three distinct elements contribute to semantic cognition: semantic representations that accumulate throughout the lifespan, processes for controlled retrieval of less salient semantic information, which appear age-invariant, and mechanisms for selecting task-relevant aspects of semantic knowledge, which decline with age and may relate more closely to domain-general executive control.

The effect of training methodology on knowledge representation in categorization.

PubMed

Hélie, Sébastien; Shamloo, Farzin; Ell, Shawn W

2017-01-01

Category representations can be broadly classified as containing within-category information or between-category information. Although such representational differences can have a profound impact on decision-making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule-based (RB) category structures thought to promote between-category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between-category representations whereas concept training resulted in a bias toward within-category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within-category representations. With II structures, there was a bias toward within-category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within-category representations could support generalization during the test phase. These data suggest that within-category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization.

The effect of training methodology on knowledge representation in categorization

PubMed Central

Shamloo, Farzin; Ell, Shawn W.

2017-01-01

Category representations can be broadly classified as containing within–category information or between–category information. Although such representational differences can have a profound impact on decision–making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule–based (RB) category structures thought to promote between–category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between–category representations whereas concept training resulted in a bias toward within–category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within–category representations. With II structures, there was a bias toward within–category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within–category representations could support generalization during the test phase. These data suggest that within–category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization. PMID:28846732

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.

Materiality, Technology, and Constructing Social Knowledge through Bodily Representation: A View from Prehistoric Guernsey, Channel Islands.

PubMed

Kohring, Sheila

2015-04-22

The role of the human body in the creation of social knowledge-as an ontological and/or aesthetic category-has been applied across social theory. In all these approaches, the body is viewed as a locus for experience and knowledge. If the body is a source of subjective knowledge, then it can also become an important means of creating ontological categories of self and society. The materiality of human representations within art traditions, then, can be interpreted as providing a means for contextualizing and aestheticizing the body in order to produce a symbolic and structural knowledge category. This paper explores the effect of material choices and techniques of production when representing the human body on how societies order and categorize the world.

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

NASA Technical Reports Server (NTRS)

Logie, David S.; Kamil, Hasan

1990-01-01

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

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

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.

1990-01-01

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

An Ontological Representation of Learning Objects and Learning Designs as Codified Knowledge

ERIC Educational Resources Information Center

Sanchez-Alonso, Salvador; Frosch-Wilke, Dirk

2005-01-01

Purpose: The aim of this paper is discussing about the similarities between the life cycle of knowledge management and the processes in which learning objects are created, evaluated and used. Design/methodology/approach: The paper describes LO and learning designs and depicts their integration into the knowledge life cycle (KLC) of the KMCI,…

Taxonomy development and knowledge representation of nurses' personal cognitive artifacts.

PubMed

McLane, Sharon; Turley, James P

2009-11-14

Nurses prepare knowledge representations, or summaries of patient clinical data, each shift. These knowledge representations serve multiple purposes, including support of working memory, workload organization and prioritization, critical thinking, and reflection. This summary is integral to internal knowledge representations, working memory, and decision-making. Study of this nurse knowledge representation resulted in development of a taxonomy of knowledge representations necessary to nursing practice.This paper describes the methods used to elicit the knowledge representations and structures necessary for the work of clinical nurses, described the development of a taxonomy of this knowledge representation, and discusses translation of this methodology to the cognitive artifacts of other disciplines. Understanding the development and purpose of practitioner's knowledge representations provides important direction to informaticists seeking to create information technology alternatives. The outcome of this paper is to suggest a process template for transition of cognitive artifacts to an information system.

Oligomer formation in the troposphere: from experimental knowledge to 3-D modeling

NASA Astrophysics Data System (ADS)

Lemaire, V.; Coll, I.; Couvidat, F.; Mouchel-Vallon, C.; Seigneur, C.; Siour, G.

2015-10-01

The organic fraction of atmospheric aerosols has proven to be a critical element of air quality and climate issues. However, its composition and the aging processes it undergoes remain insufficiently understood. This work builds on laboratory knowledge to simulate the formation of oligomers from biogenic secondary organic aerosol (BSOA) in the troposphere at the continental scale. We compare the results of two different modeling approaches, a 1st-order kinetic process and a pH-dependent parameterization, both implemented in the CHIMERE air quality model (AQM), to simulate the spatial and temporal distribution of oligomerized SOA over western Europe. Our results show that there is a strong dependence of the results on the selected modeling approach: while the irreversible kinetic process leads to the oligomerization of about 50 % of the total BSOA mass, the pH-dependent approach shows a broader range of impacts, with a strong dependency on environmental parameters (pH and nature of aerosol) and the possibility for the process to be reversible. In parallel, we investigated the sensitivity of each modeling approach to the representation of SOA precursor solubility (Henry's law constant values). Finally, the pros and cons of each approach for the representation of SOA aging are discussed and recommendations are provided to improve current representations of oligomer formation in AQMs.

A knowledge-based system for prototypical reasoning

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Minieri, Andrea; Piana, Alberto; Radicioni, Daniele P.

2015-04-01

In this work we present a knowledge-based system equipped with a hybrid, cognitively inspired architecture for the representation of conceptual information. The proposed system aims at extending the classical representational and reasoning capabilities of the ontology-based frameworks towards the realm of the prototype theory. It is based on a hybrid knowledge base, composed of a classical symbolic component (grounded on a formal ontology) with a typicality based one (grounded on the conceptual spaces framework). The resulting system attempts to reconcile the heterogeneous approach to the concepts in Cognitive Science with the dual process theories of reasoning and rationality. The system has been experimentally assessed in a conceptual categorisation task where common sense linguistic descriptions were given in input, and the corresponding target concepts had to be identified. The results show that the proposed solution substantially extends the representational and reasoning 'conceptual' capabilities of standard ontology-based systems.

Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks.

PubMed

Tran, Son N; d'Avila Garcez, Artur S

2018-02-01

Developments in deep learning have seen the use of layerwise unsupervised learning combined with supervised learning for fine-tuning. With this layerwise approach, a deep network can be seen as a more modular system that lends itself well to learning representations. In this paper, we investigate whether such modularity can be useful to the insertion of background knowledge into deep networks, whether it can improve learning performance when it is available, and to the extraction of knowledge from trained deep networks, and whether it can offer a better understanding of the representations learned by such networks. To this end, we use a simple symbolic language-a set of logical rules that we call confidence rules-and show that it is suitable for the representation of quantitative reasoning in deep networks. We show by knowledge extraction that confidence rules can offer a low-cost representation for layerwise networks (or restricted Boltzmann machines). We also show that layerwise extraction can produce an improvement in the accuracy of deep belief networks. Furthermore, the proposed symbolic characterization of deep networks provides a novel method for the insertion of prior knowledge and training of deep networks. With the use of this method, a deep neural-symbolic system is proposed and evaluated, with the experimental results indicating that modularity through the use of confidence rules and knowledge insertion can be beneficial to network performance.

Class Energy Image Analysis for Video Sensor-Based Gait Recognition: A Review

PubMed Central

Lv, Zhuowen; Xing, Xianglei; Wang, Kejun; Guan, Donghai

2015-01-01

Gait is a unique perceptible biometric feature at larger distances, and the gait representation approach plays a key role in a video sensor-based gait recognition system. Class Energy Image is one of the most important gait representation methods based on appearance, which has received lots of attentions. In this paper, we reviewed the expressions and meanings of various Class Energy Image approaches, and analyzed the information in the Class Energy Images. Furthermore, the effectiveness and robustness of these approaches were compared on the benchmark gait databases. We outlined the research challenges and provided promising future directions for the field. To the best of our knowledge, this is the first review that focuses on Class Energy Image. It can provide a useful reference in the literature of video sensor-based gait representation approach. PMID:25574935

Dynamic Bayesian Networks for Student Modeling

ERIC Educational Resources Information Center

Kaser, Tanja; Klingler, Severin; Schwing, Alexander G.; Gross, Markus

2017-01-01

Intelligent tutoring systems adapt the curriculum to the needs of the individual student. Therefore, an accurate representation and prediction of student knowledge is essential. Bayesian Knowledge Tracing (BKT) is a popular approach for student modeling. The structure of BKT models, however, makes it impossible to represent the hierarchy and…

Interactive information retrieval systems with minimalist representation

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

Domeshek, E.; Kedar, S.; Gordon, A.

Almost any information you might want is becoming available on-line. The problem is how to find what you need. One strategy to improve access to existing information sources, is intelligent information agents - an approach based on extensive representation and inference. Another alternative is to simply concentrate on better information organization and indexing. Our systems use a form of conceptual indexing sensitive to users` task-specific information needs. We aim for minimalist representation, coding only select aspects of stored items. Rather than supporting reliable automated inference, the primary purpose of our representations is to provide sufficient discrimination and guidance to amore » user for a given domain and task. This paper argues, using case studies, that minimal representations can make strong contributions to the usefulness and usability of interactive information systems, while minimizing knowledge engineering effort. We demonstrate this approach in several broad spectrum applications including video retrieval and advisory systems.« less

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

PubMed Central

Nguyen, Vinh; Bodenreider, Olivier; Sheth, Amit

2015-01-01

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

EDNA: Expert fault digraph analysis using CLIPS

NASA Technical Reports Server (NTRS)

Dixit, Vishweshwar V.

1990-01-01

Traditionally fault models are represented by trees. Recently, digraph models have been proposed (Sack). Digraph models closely imitate the real system dependencies and hence are easy to develop, validate and maintain. However, they can also contain directed cycles and analysis algorithms are hard to find. Available algorithms tend to be complicated and slow. On the other hand, the tree analysis (VGRH, Tayl) is well understood and rooted in vast research effort and analytical techniques. The tree analysis algorithms are sophisticated and orders of magnitude faster. Transformation of a digraph (cyclic) into trees (CLP, LP) is a viable approach to blend the advantages of the representations. Neither the digraphs nor the trees provide the ability to handle heuristic knowledge. An expert system, to capture the engineering knowledge, is essential. We propose an approach here, namely, expert network analysis. We combine the digraph representation and tree algorithms. The models are augmented by probabilistic and heuristic knowledge. CLIPS, an expert system shell from NASA-JSC will be used to develop a tool. The technique provides the ability to handle probabilities and heuristic knowledge. Mixed analysis, some nodes with probabilities, is possible. The tool provides graphics interface for input, query, and update. With the combined approach it is expected to be a valuable tool in the design process as well in the capture of final design knowledge.

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

ERIC Educational Resources Information Center

Stevens, Ronald H.

1991-01-01

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

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

ERIC Educational Resources Information Center

Nguyen, Bao-An; Yang, Don-Lin

2012-01-01

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

Job Knowledge Test Design: A Cognitively-Oriented Approach. Institute Report No. 241.

ERIC Educational Resources Information Center

DuBois, David; And Others

Selected cognitive science methods were used to modify existing test development procedures so that the modified procedures could in turn be used to improve the usefulness of job knowledge tests as a proxy for hands-on performance. A plan-goal graph representation was used to capture the knowledge content and goal structure of the task of using a…

Job Knowledge Test Design: A Cognitively-Oriented Approach

DTIC Science & Technology

1993-07-01

protocol analyses and related methods. We employed a plan-goal graph representation to capture the knowledge content and goal structure of the studied task...between job knowledge and hands-on performance from previous studies was .38. For the subset of Marines in this sample who had recently been examined...the job knowledge test provided similar results to conventional, total number correct scoring. Conclusion The evidence provided by this study supports

Materiality, Technology, and Constructing Social Knowledge through Bodily Representation: A View from Prehistoric Guernsey, Channel Islands

PubMed Central

Kohring, Sheila

2015-01-01

The role of the human body in the creation of social knowledge—as an ontological and/or aesthetic category—has been applied across social theory. In all these approaches, the body is viewed as a locus for experience and knowledge. If the body is a source of subjective knowledge, then it can also become an important means of creating ontological categories of self and society. The materiality of human representations within art traditions, then, can be interpreted as providing a means for contextualizing and aestheticizing the body in order to produce a symbolic and structural knowledge category. This paper explores the effect of material choices and techniques of production when representing the human body on how societies order and categorize the world. PMID:26290654

Computer integrated documentation

NASA Technical Reports Server (NTRS)

Boy, Guy

1991-01-01

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

Biologically Plausible, Human-Scale Knowledge Representation.

PubMed

Crawford, Eric; Gingerich, Matthew; Eliasmith, Chris

2016-05-01

Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, ), "mesh" binding (van der Velde & de Kamps, ), and conjunctive binding (Smolensky, ). Recent theoretical work has suggested that most of these methods will not scale well, that is, that they cannot encode structured representations using any of the tens of thousands of terms in the adult lexicon without making implausible resource assumptions. Here, we empirically demonstrate that the biologically plausible structured representations employed in the Semantic Pointer Architecture (SPA) approach to modeling cognition (Eliasmith, ) do scale appropriately. Specifically, we construct a spiking neural network of about 2.5 million neurons that employs semantic pointers to successfully encode and decode the main lexical relations in WordNet, which has over 100,000 terms. In addition, we show that the same representations can be employed to construct recursively structured sentences consisting of arbitrary WordNet concepts, while preserving the original lexical structure. We argue that these results suggest that semantic pointers are uniquely well-suited to providing a biologically plausible account of the structured representations that underwrite human cognition. Copyright © 2015 Cognitive Science Society, Inc.

Advanced techniques for the storage and use of very large, heterogeneous spatial databases. The representation of geographic knowledge: Toward a universal framework. [relations (mathematics)

NASA Technical Reports Server (NTRS)

Peuquet, Donna J.

1987-01-01

A new approach to building geographic data models that is based on the fundamental characteristics of the data is presented. An overall theoretical framework for representing geographic data is proposed. An example of utilizing this framework in a Geographic Information System (GIS) context by combining artificial intelligence techniques with recent developments in spatial data processing techniques is given. Elements of data representation discussed include hierarchical structure, separation of locational and conceptual views, and the ability to store knowledge at variable levels of completeness and precision.

A Pedagogical Challenge: Integrative Thinking.

ERIC Educational Resources Information Center

Peterson, Nils S.; And Others

An instructional framework which provides opportunities for students to synthesize knowledge and recognize general approaches to problem representation and solution is advocated and discussed in this paper. The need for a combination of an interdisciplinary approach with the new technologies of the information age is emphasized. Major ideas…

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques

PubMed Central

2014-01-01

Background Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. Results We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. Conclusions SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats. PMID:25093070

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques.

PubMed

Bölling, Christian; Weidlich, Michael; Holzhütter, Hermann-Georg

2014-01-01

Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats.

Towards a Framework for Evaluating and Comparing Diagnosis Algorithms

NASA Technical Reports Server (NTRS)

Kurtoglu, Tolga; Narasimhan, Sriram; Poll, Scott; Garcia,David; Kuhn, Lukas; deKleer, Johan; vanGemund, Arjan; Feldman, Alexander

2009-01-01

Diagnostic inference involves the detection of anomalous system behavior and the identification of its cause, possibly down to a failed unit or to a parameter of a failed unit. Traditional approaches to solving this problem include expert/rule-based, model-based, and data-driven methods. Each approach (and various techniques within each approach) use different representations of the knowledge required to perform the diagnosis. The sensor data is expected to be combined with these internal representations to produce the diagnosis result. In spite of the availability of various diagnosis technologies, there have been only minimal efforts to develop a standardized software framework to run, evaluate, and compare different diagnosis technologies on the same system. This paper presents a framework that defines a standardized representation of the system knowledge, the sensor data, and the form of the diagnosis results and provides a run-time architecture that can execute diagnosis algorithms, send sensor data to the algorithms at appropriate time steps from a variety of sources (including the actual physical system), and collect resulting diagnoses. We also define a set of metrics that can be used to evaluate and compare the performance of the algorithms, and provide software to calculate the metrics.

All for one but not one for all: how multiple number representations are recruited in one numerical task.

PubMed

Wood, Guilherme; Nuerk, Hans-Christoph; Moeller, Korbinian; Geppert, Barbara; Schnitker, Ralph; Weber, Jochen; Willmes, Klaus

2008-01-02

Number processing recruits a complex network of multiple numerical representations. Usually the components of this network are examined in a between-task approach with the disadvantage of relying upon different instructions, tasks, and inhomogeneous stimulus sets across different studies. A within-task approach may avoid these disadvantages and access involved numerical representations more specifically. In the present study we employed a within-task approach to investigate numerical representations activated in the number bisection task (NBT) using parametric rapid event-related fMRI. Participants were to judge whether the central number of a triplet was also its arithmetic mean (e.g. 23_26_29) or not (e.g. 23_25_29). Activation in the left inferior parietal cortex was associated with the deployment of arithmetic fact knowledge, while activation of the intraparietal cortex indicated more intense magnitude processing, instrumental aspects of calculation and integration of the base-10 structure of two-digit numbers. These results replicate evidence from the literature. Furthermore, activation in the dorsolateral and ventrolateral prefrontal cortex revealed mechanisms of feature monitoring and inhibition as well as allocation of cognitive resources recruited to solve a specific triplet. We conclude that the network of numerical representations should rather be studied in a within-task approach than in varying between-task approaches.

Incorporating linguistic knowledge for learning distributed word representations.

PubMed

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

Incorporating Linguistic Knowledge for Learning Distributed Word Representations

PubMed Central

Wang, Yan; Liu, Zhiyuan; Sun, Maosong

2015-01-01

Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR) to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining. PMID:25874581

Detailed clinical models: representing knowledge, data and semantics in healthcare information technology.

PubMed

Goossen, William T F

2014-07-01

This paper will present an overview of the developmental effort in harmonizing clinical knowledge modeling using the Detailed Clinical Models (DCMs), and will explain how it can contribute to the preservation of Electronic Health Records (EHR) data. Clinical knowledge modeling is vital for the management and preservation of EHR and data. Such modeling provides common data elements and terminology binding with the intention of capturing and managing clinical information over time and location independent from technology. Any EHR data exchange without an agreed clinical knowledge modeling will potentially result in loss of information. Many attempts exist from the past to model clinical knowledge for the benefits of semantic interoperability using standardized data representation and common terminologies. The objective of each project is similar with respect to consistent representation of clinical data, using standardized terminologies, and an overall logical approach. However, the conceptual, logical, and the technical expressions are quite different in one clinical knowledge modeling approach versus another. There currently are synergies under the Clinical Information Modeling Initiative (CIMI) in order to create a harmonized reference model for clinical knowledge models. The goal for the CIMI is to create a reference model and formalisms based on for instance the DCM (ISO/TS 13972), among other work. A global repository of DCMs may potentially be established in the future.

Surveying Medieval Archaeology: a New Form for Harris Paradigm Linking Photogrammetry and Temporal Relations

NASA Astrophysics Data System (ADS)

Drap, P.; Papini, O.; Pruno, E.; Nucciotti, M.; Vannini, G.

2017-02-01

The paper presents some reflexions concerning an interdisciplinary project between Medieval Archaeologists from the University of Florence (Italy) and ICT researchers from CNRS LSIS of Marseille (France), aiming towards a connection between 3D spatial representation and archaeological knowledge. It is well known that Laser Scanner, Photogrammetry and Computer Vision are very attractive tools for archaeologists, although the integration of representation of space and representation of archaeological time has not yet found a methodological standard of reference. We try to develop an integrated system for archaeological 3D survey and all other types of archaeological data and knowledge through integrating observable (material) and non-graphic (interpretive) data. Survey plays a central role, since it is both a metric representation of the archaeological site and, to a wider extent, an interpretation of it (being also a common basis for communication between the 2 teams). More specifically 3D survey is crucial, allowing archaeologists to connect actual spatial assets to the stratigraphic formation processes (i.e. to the archaeological time) and to translate spatial observations into historical interpretation of the site. We propose a common formalism for describing photogrammetrical survey and archaeological knowledge stemming from ontologies: Indeed, ontologies are fully used to model and store 3D data and archaeological knowledge. Xe equip this formalism with a qualitative representation of time. Stratigraphic analyses (both of excavated deposits and of upstanding structures) are closely related to E. C. Harris theory of "Stratigraphic Unit" ("US" from now on). Every US is connected to the others by geometric, topological and, eventually, temporal links, and are recorded by the 3D photogrammetric survey. However, the limitations of the Harris Matrix approach lead to use another representation formalism for stratigraphic relationships, namely Qualitative Constraints Networks (QCN) successfully used in the domain of knowledge representation and reasoning in artificial intelligence for representing temporal relations.

Increasing High School Students' Chemistry Performance and Reducing Cognitive Load through an Instructional Strategy Based on the Interaction of Multiple Levels of Knowledge Representation

ERIC Educational Resources Information Center

Milenkovic´, Dus?ica D.; Segedinac, Mirjana D.; Hrin, Tamara N.

2014-01-01

The central goal of this study was to examine the extent to which a teaching approach focused on the interaction between macroscopic, submicroscopic, and symbolic levels of chemistry representations could affect high school students' performance in the field of inorganic reactions, as well as to examine how the applied instruction influences…

Incorporating Feature-Based Annotations into Automatically Generated Knowledge Representations

NASA Astrophysics Data System (ADS)

Lumb, L. I.; Lederman, J. I.; Aldridge, K. D.

2006-12-01

Earth Science Markup Language (ESML) is efficient and effective in representing scientific data in an XML- based formalism. However, features of the data being represented are not accounted for in ESML. Such features might derive from events (e.g., a gap in data collection due to instrument servicing), identifications (e.g., a scientifically interesting area/volume in an image), or some other source. In order to account for features in an ESML context, we consider them from the perspective of annotation, i.e., the addition of information to existing documents without changing the originals. Although it is possible to extend ESML to incorporate feature-based annotations internally (e.g., by extending the XML schema for ESML), there are a number of complicating factors that we identify. Rather than pursuing the ESML-extension approach, we focus on an external representation for feature-based annotations via XML Pointer Language (XPointer). In previous work (Lumb &Aldridge, HPCS 2006, IEEE, doi:10.1109/HPCS.2006.26), we have shown that it is possible to extract relationships from ESML-based representations, and capture the results in the Resource Description Format (RDF). Thus we explore and report on this same requirement for XPointer-based annotations of ESML representations. As in our past efforts, the Global Geodynamics Project (GGP) allows us to illustrate with a real-world example this approach for introducing annotations into automatically generated knowledge representations.

A Knowledge Engineering Approach to Develop Domain Ontology

ERIC Educational Resources Information Center

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

2011-01-01

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

Structured representation for core elements of common clinical decision support interventions to facilitate knowledge sharing.

PubMed

Zhou, Li; Hongsermeier, Tonya; Boxwala, Aziz; Lewis, Janet; Kawamoto, Kensaku; Maviglia, Saverio; Gentile, Douglas; Teich, Jonathan M; Rocha, Roberto; Bell, Douglas; Middleton, Blackford

2013-01-01

At present, there are no widely accepted, standard approaches for representing computer-based clinical decision support (CDS) intervention types and their structural components. This study aimed to identify key requirements for the representation of five widely utilized CDS intervention types: alerts and reminders, order sets, infobuttons, documentation templates/forms, and relevant data presentation. An XML schema was proposed for representing these interventions and their core structural elements (e.g., general metadata, applicable clinical scenarios, CDS inputs, CDS outputs, and CDS logic) in a shareable manner. The schema was validated by building CDS artifacts for 22 different interventions, targeted toward guidelines and clinical conditions called for in the 2011 Meaningful Use criteria. Custom style sheets were developed to render the XML files in human-readable form. The CDS knowledge artifacts were shared via a public web portal. Our experience also identifies gaps in existing standards and informs future development of standards for CDS knowledge representation and sharing.

A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs.

PubMed

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-02-28

We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the $\\mathcal {E}$SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base-phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.

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

DTIC Science & Technology

1988-04-13

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

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

PubMed

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

2009-01-01

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

What recent research on diagrams suggests about learning with rather than learning from visual representations in science

NASA Astrophysics Data System (ADS)

Tippett, Christine D.

2016-03-01

The move from learning science from representations to learning science with representations has many potential and undocumented complexities. This thematic analysis partially explores the trends of representational uses in science instruction, examining 80 research studies on diagram use in science. These studies, published during 2000-2014, were located through searches of journal databases and books. Open coding of the studies identified 13 themes, 6 of which were identified in at least 10% of the studies: eliciting mental models, classroom-based research, multimedia principles, teaching and learning strategies, representational competence, and student agency. A shift in emphasis on learning with rather than learning from representations was evident across the three 5-year intervals considered, mirroring a pedagogical shift from science instruction as transmission of information to constructivist approaches in which learners actively negotiate understanding and construct knowledge. The themes and topics in recent research highlight areas of active interest and reveal gaps that may prove fruitful for further research, including classroom-based studies, the role of prior knowledge, and the use of eye-tracking. The results of the research included in this thematic review of the 2000-2014 literature suggest that both interpreting and constructing representations can lead to better understanding of science concepts.

Research in Knowledge Representation for Natural Language Understanding

DTIC Science & Technology

1980-11-01

artificial intelligence, natural language understanding , parsing, syntax, semantics, speaker meaning, knowledge representation, semantic networks...TinB PAGE map M W006 1Report No. 4513 L RESEARCH IN KNOWLEDGE REPRESENTATION FOR NATURAL LANGUAGE UNDERSTANDING Annual Report 1 September 1979 to 31... understanding , knowledge representation, and knowledge based inference. The work that we have been doing falls into three classes, successively motivated by

A Non-Cognitive Formal Approach to Knowledge Representation in Artificial Intelligence.

DTIC Science & Technology

1986-06-01

example, Duda and others translated production rules into a partitioned semantic network (73). Representations were also translated into production...153. Berlin: Springer-Verlag, 1982. 38. Blikle, Andrzej . "Equational Languages," Information and Control, 21: 134-147 (September 1972). 285 39. Ezawa...Conference on Artificial Intelligence, IJCAI-75. 115-121. William Kaufmann, Inc., Los Altos CA, 1975. 73. Duda , Richard 0. and others. "Semantic

Large-Scale Urban Localisation with a Pushbroom LIDAR

DTIC Science & Technology

2012-10-01

the sole means of gen- erating full 6-DOF poses from a previously-surveyed workspace. In this approach, Normalised Information Distance is used as the...vehicle to have good knowledge of its position at system- initialization. We now turn to an overview of the use of point-based registration methods for...combination of reference vertices, and provides a convenient representation for the intersection test . Using this parametric representation, the coordinates

Learning Multisensory Representations

DTIC Science & Technology

2016-05-23

public release. Erdogan , G., Yildirim, I., & Jacobs, R. A. (2014). Transfer of object shape knowledge across visual and haptic modalities. Proceedings...2014). The adaptive nature of visual working memory. Current Directions in Psychological Science, 23, 164-170. Erdogan , G., Yildirim, I...sequence category knowledge: A probabilistic language of thought approach. Psychonomic Bulletin and Review, 22, 673-686. Erdogan , G., Chen, Q., Garcea, F

Formalizing nursing knowledge: from theories and models to ontologies.

PubMed

Peace, Jane; Brennan, Patricia Flatley

2009-01-01

Knowledge representation in nursing is poised to address the depth of nursing knowledge about the specific phenomena of importance to nursing. Nursing theories and models may provide a starting point for making this knowledge explicit in representations. We combined knowledge building methods from nursing and ontology design methods from biomedical informatics to create a nursing representation of family health history. Our experience provides an example of how knowledge representations may be created to facilitate electronic support for nursing practice and knowledge development.

Knowledge Construction and Knowledge Representation in High School Students' Design of Hypermedia Documents

ERIC Educational Resources Information Center

Chen, Pearl; McGrath, Diane

2003-01-01

This study documented the processes of knowledge construction and knowledge representation in high school students' hypermedia design projects. Analysis of knowledge construction in linking and structural building yielded distinct types and subtypes of hypermedia documents, which were characterized by four features of knowledge representation: (a)…

Uncertainty management by relaxation of conflicting constraints in production process scheduling

NASA Technical Reports Server (NTRS)

Dorn, Juergen; Slany, Wolfgang; Stary, Christian

1992-01-01

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.

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.

Using Knowledge Space Theory To Assess Student Understanding of Stoichiometry

NASA Astrophysics Data System (ADS)

Arasasingham, Ramesh D.; Taagepera, Mare; Potter, Frank; Lonjers, Stacy

2004-10-01

Using the concept of stoichiometry we examined the ability of beginning college chemistry students to make connections among the molecular, symbolic, and graphical representations of chemical phenomena, as well as to conceptualize, visualize, and solve numerical problems. Students took a test designed to follow conceptual development; we then analyzed student responses and the connectivities of their responses, or the cognitive organization of the material or thinking patterns, applying knowledge space theory (KST). The results reveal that the students' logical frameworks of conceptual understanding were very weak and lacked an integrated understanding of some of the fundamental aspects of chemical reactivity. Analysis of response states indicates that the overall thinking patterns began with symbolic representations, moved to numerical problem solving, and then lastly to visualization: the acquisition of visualization skills comes later in the knowledge structure. The results strongly suggest the need for teaching approaches that help students integrate their knowledge by emphasizing the relationships between the different representations and presenting them concurrently during instruction. Also, the results indicate that KST is a useful tool for revealing various aspects of students' cognitive structure in chemistry and can be used as an assessment tool or as a pedagogical tool to address a number of student-learning issues.

An Argument from Acquisition: Comparing English Metrical Stress Representations by How Learnable They Are from Child-Directed Speech

ERIC Educational Resources Information Center

Pearl, Lisa; Ho, Timothy; Detrano, Zephyr

2017-01-01

It has long been recognized that there is a natural dependence between theories of knowledge representation and theories of knowledge acquisition, with the idea that the right knowledge representation enables acquisition to happen as reliably as it does. Given this, a reasonable criterion for a theory of knowledge representation is that it be…

Research in Knowledge Representation for Natural Language Understanding.

DTIC Science & Technology

1984-09-01

TYPE OF REPORT & PERIOO COVERED RESEARCH IN KNOWLEDGE REPRESENTATION Annual Report FOR NATURAL LANGUAGE UNDERSTANDING 9/1/83 - 8/31/84 S. PERFORMING...nhaber) Artificial intelligence, natural language understanding , knowledge representation, semantics, semantic networks, KL-TWO, NIKL, belief and...attempting to understand and react to a complex, evolving situation. This report summarizes our research in knowledge representation and natural language

Representational task formats and problem solving strategies in kinematics and work

NASA Astrophysics Data System (ADS)

Ibrahim, Bashirah; Rebello, N. Sanjay

2012-06-01

Previous studies have reported that students employed different problem solving approaches when presented with the same task structured with different representations. In this study, we explored and compared students’ strategies as they attempted tasks from two topical areas, kinematics and work. Our participants were 19 engineering students taking a calculus-based physics course. The tasks were presented in linguistic, graphical, and symbolic forms and requested either a qualitative solution or a value. The analysis was both qualitative and quantitative in nature focusing principally on the characteristics of the strategies employed as well as the underlying reasoning for their applications. A comparison was also made for the same student’s approach with the same kind of representation across the two topics. Additionally, the participants’ overall strategies across the different tasks, in each topic, were considered. On the whole, we found that the students prefer manipulating equations irrespective of the representational format of the task. They rarely recognized the applicability of a “qualitative” approach to solve the problem although they were aware of the concepts involved. Even when the students included visual representations in their solutions, they seldom used these representations in conjunction with the mathematical part of the problem. Additionally, the students were not consistent in their approach for interpreting and solving problems with the same kind of representation across the two topical areas. The representational format, level of prior knowledge, and familiarity with a topic appeared to influence their strategies, their written responses, and their ability to recognize qualitative ways to attempt a problem. The nature of the solution does not seem to impact the strategies employed to handle the problem.

Embodied effects of conceptual knowledge continuously perturb the hand in flight.

PubMed

Till, Bernie C; Masson, Michael E J; Bub, Daniel N; Driessen, Peter F

2014-08-01

Attending to a manipulable object evokes a mental representation of hand actions associated with the object's form and function. In one view, these representations are sufficiently abstract that their competing influence on an unrelated action is confined to the planning stages of movement and does not affect its on-line control. Alternatively, an object may evoke action representations that affect the entire trajectory of an unrelated grasping action. We developed a new methodology to statistically analyze the forward motion and rotation of the hand and fingers under different task conditions. Using this novel approach, we established that a grasping action executed after seeing a photograph of an object is systematically perturbed even into the late stages of its trajectory by the competing influence of the grasping posture associated with the object. Our results show that embodied effects of conceptual knowledge continuously modulate the hand in flight. © The Author(s) 2014.

Formal Representations of Eligibility Criteria: A Literature Review

PubMed Central

Weng, Chunhua; Tu, Samson W.; Sim, Ida; Richesson, Rachel

2010-01-01

Standards-based, computable knowledge representations for eligibility criteria are increasingly needed to provide computer-based decision support for automated research participant screening, clinical evidence application, and clinical research knowledge management. We surveyed the literature and identified five aspects of eligibility criteria knowledge representations that contribute to the various research and clinical applications: the intended use of computable eligibility criteria, the classification of eligibility criteria, the expression language for representing eligibility rules, the encoding of eligibility concepts, and the modeling of patient data. We consider three of them (expression language, codification of eligibility concepts, and patient data modeling), to be essential constructs of a formal knowledge representation for eligibility criteria. The requirements for each of the three knowledge constructs vary for different use cases, which therefore should inform the development and choice of the constructs toward cost-effective knowledge representation efforts. We discuss the implications of our findings for standardization efforts toward sharable knowledge representation of eligibility criteria. PMID:20034594

A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs

PubMed Central

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-01-01

Abstract We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$\\mathcal {E}$\\end{document}SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base–phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation. PMID:29272539

Comparative study of representations of professional autonomy produced by first and last-period undergraduate nursing students 1

PubMed Central

dos Santos, Érick Igor; Gomes, Antonio Marcos Tosoli; Marques, Sergio Corrêa; Ramos, Raquel de Souza; da Silva, Aline Cerqueira Santos Santana; de Oliveira, Francimar Tinoco

2017-01-01

ABSTRACT Objective: to compare the social representations of professional nurse autonomy produced by first and last-period undergraduate nursing students. Method: qualitative, descriptive and exploratory study, based on the structural approach of social representations, the Central Core Theory, carried out with 171 students from three federal public universities, using the free association technique on the object “professional nurse autonomy”. The data were submitted to EVOC 2005 software and to similarity analysis. Results: care was the central core of the representational structure identified among the students of the first period. Among last-period students, knowledge stood out as a core element. The term responsibility was identified as common to both central cores. Conclusion: regarding professional autonomy, the results point to an overlapping process of the reified and consensual universes during the undergraduate course. However, responsibility, inherent in the profession, remains cross-sectional. For the first period students, autonomy is resignified in a practical and attitudinal way, whereas for the last period students, the knowledge acquired stimulates them to assign meaning to professional autonomy with a cognitive and attitudinal representation. The data can support the use of innovative teaching practices in nursing undergraduate courses.

Detailed qualitative dynamic knowledge representation using a BioNetGen model of TLR-4 signaling and preconditioning.

PubMed

An, Gary C; Faeder, James R

2009-01-01

Intracellular signaling/synthetic pathways are being increasingly extensively characterized. However, while these pathways can be displayed in static diagrams, in reality they exist with a degree of dynamic complexity that is responsible for heterogeneous cellular behavior. Multiple parallel pathways exist and interact concurrently, limiting the ability to integrate the various identified mechanisms into a cohesive whole. Computational methods have been suggested as a means of concatenating this knowledge to aid in the understanding of overall system dynamics. Since the eventual goal of biomedical research is the identification and development of therapeutic modalities, computational representation must have sufficient detail to facilitate this 'engineering' process. Adding to the challenge, this type of representation must occur in a perpetual state of incomplete knowledge. We present a modeling approach to address this challenge that is both detailed and qualitative. This approach is termed 'dynamic knowledge representation,' and is intended to be an integrated component of the iterative cycle of scientific discovery. BioNetGen (BNG), a software platform for modeling intracellular signaling pathways, was used to model the toll-like receptor 4 (TLR-4) signal transduction cascade. The informational basis of the model was a series of reference papers on modulation of (TLR-4) signaling, and some specific primary research papers to aid in the characterization of specific mechanistic steps in the pathway. This model was detailed with respect to the components of the pathway represented, but qualitative with respect to the specific reaction coefficients utilized to execute the reactions. Responsiveness to simulated lipopolysaccharide (LPS) administration was measured by tumor necrosis factor (TNF) production. Simulation runs included evaluation of initial dose-dependent response to LPS administration at 10, 100, 1000 and 10,000, and a subsequent examination of preconditioning behavior with increasing LPS at 10, 100, 1000 and 10,000 and a secondary dose of LPS at 10,000 administered at approximately 27h of simulated time. Simulations of 'knockout' versions of the model allowed further examination of the interactions within the signaling cascade. The model demonstrated a dose-dependent TNF response curve to increasing stimulus by LPS. Preconditioning simulations demonstrated a similar dose-dependency of preconditioning doses leading to attenuation of response to subsequent LPS challenge - a 'tolerance' dynamic. These responses match dynamics reported in the literature. Furthermore, the simulated 'knockout' results suggested the existence and need for dual negative feedback control mechanisms, represented by the zinc ring-finger protein A20 and inhibitor kappa B proteins (IkappaB), in order for both effective attenuation of the initial stimulus signal and subsequent preconditioned 'tolerant' behavior. We present an example of detailed, qualitative dynamic knowledge representation using the TLR-4 signaling pathway, its control mechanisms and overall behavior with respect to preconditioning. The intent of this approach is to demonstrate a method of translating the extensive mechanistic knowledge being generated at the basic science level into an executable framework that can provide a means of 'conceptual model verification.' This allows for both the 'checking' of the dynamic consequences of a mechanistic hypothesis and the creation of a modular component of an overall model directed at the engineering goal of biomedical research. It is hoped that this paper will increase the use of knowledge representation and communication in this fashion, and facilitate the concatenation and integration of community-wide knowledge.

Cognitive, perceptual and action-oriented representations of falling objects.

PubMed

Zago, Myrka; Lacquaniti, Francesco

2005-01-01

We interact daily with moving objects. How accurate are our predictions about objects' motions? What sources of information do we use? These questions have received wide attention from a variety of different viewpoints. On one end of the spectrum are the ecological approaches assuming that all the information about the visual environment is present in the optic array, with no need to postulate conscious or unconscious representations. On the other end of the spectrum are the constructivist approaches assuming that a more or less accurate representation of the external world is built in the brain using explicit or implicit knowledge or memory besides sensory inputs. Representations can be related to naive physics or to context cue-heuristics or to the construction of internal copies of environmental invariants. We address the issue of prediction of objects' fall at different levels. Cognitive understanding and perceptual judgment of simple Newtonian dynamics can be surprisingly inaccurate. By contrast, motor interactions with falling objects are often very accurate. We argue that the pragmatic action-oriented behaviour and the perception-oriented behaviour may use different modes of operation and different levels of representation.

Improving students’ mathematical representational ability through RME-based progressive mathematization

NASA Astrophysics Data System (ADS)

Warsito; Darhim; Herman, T.

2018-01-01

This study aims to determine the differences in the improving of mathematical representation ability based on progressive mathematization with realistic mathematics education (PMR-MP) with conventional learning approach (PB). The method of research is quasi-experiments with non-equivalent control group designs. The study population is all students of class VIII SMPN 2 Tangerang consisting of 6 classes, while the sample was taken two classes with purposive sampling technique. The experimental class is treated with PMR-MP while the control class is treated with PB. The instruments used are test of mathematical representation ability. Data analysis was done by t-test, ANOVA test, post hoc test, and descriptive analysis. The result of analysis can be concluded that: 1) there are differences of mathematical representation ability improvement between students treated by PMR-MP and PB, 2) no interaction between learning approach (PMR-MP, PB) and prior mathematics knowledge (PAM) to improve students’ mathematical representation; 3) Students’ mathematical representation improvement in the level of higher PAM is better than medium, and low PAM students. Thus, based on the process of mathematization, it is very important when the learning direction of PMR-MP emphasizes on the process of building mathematics through a mathematical model.

Knowledge-Based Vision Techniques for the Autonomous Land Vehicle Program

DTIC Science & Technology

1991-10-01

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

Peer Commentaries on "New Approaches to Concepts in Bilingual Memory."

ERIC Educational Resources Information Center

Appel, Rene; de Groot, Annette M. B.; Ervin-Tripp, Susan; Francis, Wendy S.; Green, David W.; Jarvis, Scott; Paradis, Michel; Roelofs, Ardi; Vaid, Jyotsna

2000-01-01

Responds to an article that argues that in the study of bilingualism, conceptual representations should be treated as related but not equivalent to word meanings, as knowledge-based, dynamic and language- and culture-specific. (Author/VWL)

[Social representations of illness: Comparison of "expert" knowledge and "naïve" knowledge].

PubMed

Jeoffrion, C; Dupont, P; Tripodi, D; Roland-Lévy, C

2016-06-01

The link between social practices and representations is now well known. But while many studies have focused on the social representation of mental illness, in various populations, few studies have focused on the notion of disease/illness by comparing professionals and non-professionals health workers representations. Indeed, the disease is both a reality described, explained and treated by medicine; for those who are affected by a disease, it is an individual experience with psychological, social and cultural impacts. The social representation is determined by the structure of the social groups in which it develops; therefore, it is a form of knowledge socially shaped and shared by the members of a social group. Several theoretical extensions have been elaborated and particularly, the structural approach and the central core theory. These approaches sustain the arguments of a hierarchical organization of a social representation with a central core surrounded by peripheral zones. The central core is common and shared by the majority of the members of a given group, whereas the peripheral zones provide space for the individualization of the social knowledge. The main goal of our study is to highlight the social representations of disease in health professionals (HP) and in non-health professionals (NHP). The group of HP has been differentiated into three subgroups: "medical doctors", "nurses" and "pharmacists", while that of NHP in two subgroups: those submitted to a "long period medical treatment" and those "without treatment". Our aim is to show that there are different social and professional Representations of disease. The professional representations are specific social representations related to professional contexts. We formulate the following assumptions (a) that the social representations of HP and NHP will be articulated around a common central core. Nevertheless, we expect to find specific peripheral elements related to professional status, based on different knowledge and a differentiated "practice"; (b) the HP should refer to more descriptive aspects of the disease and monitoring of patients, while (c) NHP should refer more to the experience of illness around emotional aspects. Our sample is composed of 270 participants (135 HP and 135 HNP). Representations are measured by a free association task based on the target term: disease. The data have been submitted to prototypical and categorical analyses in agreement with the central core theory. The results confirm that there is a common social representation of disease shared by the two groups, which refers essentially to suffering and pain. The analysis of each group brings to light two different registers: the one of the HP with more descriptive words referring to the nature and the illness's characteristics, and the other ones of the HNP with more words connected to emotions and referring to personal real experience of the illness. As expected, the social representation of the HP is referring to the "professional representations" of the disease, while the one for the HNP is linked to "practices" of an illness. An analysis of intra-group differences shows specificities for each of the questioned subgroups. In the HP, medical doctors focus on the diagnosis and consequences of the disease, pharmacists refer to the treatment of the disease and its management, while nurses focus on the treatment and on the relation while monitoring patients. In the NHP, people submitted to a "long period medical treatment" refer to the emotional aspects and to the consequences of the illness on their live, while those without treatment use more descriptive and formal terms. These results suggest to the PS to expand exchanges related to the disease in order to facilitate communication centered on taking care of the patient, considered in its wholeness and not only as an actual or potential patient. This is an important step in improving the health of the patient. Copyright © 2015 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

NASA Astrophysics Data System (ADS)

Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

2017-11-01

The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

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

ERIC Educational Resources Information Center

Alkis Küçükaydin, Mensure; Uluçinar Sagir, Safak

2016-01-01

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

Factors shaping the evolution of electronic documentation systems

NASA Technical Reports Server (NTRS)

Dede, Christopher J.; Sullivan, Tim R.; Scace, Jacque R.

1990-01-01

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments.

Reasoning with inaccurate spatial knowledge. [for Planetary Rover

NASA Technical Reports Server (NTRS)

Doshi, Rajkumar S.; White, James E.; Lam, Raymond; Atkinson, David J.

1988-01-01

This paper describes work in progress on spatial planning for a semiautonomous mobile robot vehicle. The overall objective is to design a semiautonomous rover to plan routes in unknown, natural terrains. The approach to spatial planning involves deduction of common-sense spatial knowledge using geographical information, natural terrain representations, and assimilation of new and possibly conflicting terrain information. This report describes the ongoing research and implementation.

Knowledge Management for Command and Control

DTIC Science & Technology

2004-06-01

interfaces relies on rich visual and conceptual understanding of what is sketched, rather than the pattern-recognition technologies that most systems use...recognizers) required by other approaches. • The underlying conceptual representations that nuSketch uses enable it to serve as a front end to knowledge...constructing enemy-intent hypotheses via mixed visual and conceptual analogies. II.C. Multi-ViewPoint Clustering Analysis (MVP-CA) technology To

Knowledge Based Consultation for Finite Element Structural Analysis.

DTIC Science & Technology

1980-05-01

Intelligence Finite Element Program Tutorial 20 ABSTRACT (Continue. on rees side If necessary and ide.n’ty b,’ bit,, k nionh.) In recent years, techniques of...involved in Artificial Intelligence at Stanford University developed the program MYCIN F2], for clinical consultation of diseases that require...and Rules The basic backward chaining logic, characteristic to Artificial Intelligence . approaching 1he problem of knowledge representation was

Oligomer formation in the troposphere: from experimental knowledge to 3-D modeling

NASA Astrophysics Data System (ADS)

Lemaire, Vincent; Coll, Isabelle; Couvidat, Florian; Mouchel-Vallon, Camille; Seigneur, Christian; Siour, Guillaume

2016-04-01

The organic fraction of atmospheric aerosols has proven to be a critical element of air quality and climate issues. However, its composition and the aging processes it undergoes remain insufficiently understood. This work builds on laboratory knowledge to simulate the formation of oligomers from biogenic secondary organic aerosol (BSOA) in the troposphere at the continental scale. We compare the results of two different modeling approaches, a first-order kinetic process and a pH-dependent parameterization, both implemented in the CHIMERE air quality model (AQM) (www.lmd.polytechnique.fr/chimere), to simulate the spatial and temporal distribution of oligomerized secondary organic aerosol (SOA) over western Europe. We also included a comparison of organic carbon (OC) concentrations at two EMEP (European Monitoring and Evaluation Programme) stations. Our results show that there is a strong dependence of the results on the selected modeling approach: while the irreversible kinetic process leads to the oligomerization of about 50 % of the total BSOA mass, the pH-dependent approach shows a broader range of impacts, with a strong dependency on environmental parameters (pH and nature of aerosol) and the possibility for the process to be reversible. In parallel, we investigated the sensitivity of each modeling approach to the representation of SOA precursor solubility (Henry's law constant values). Finally, the pros and cons of each approach for the representation of SOA aging are discussed and recommendations are provided to improve current representations of oligomer formation in AQMs.

Wissensstrukturierung im Unterricht: Neuere Forschung zur Wissensreprasentation und ihre Anwendung in der Didaktik (Knowledge Structuring in Instruction: Recent Research on Knowledge Representation and Its Application in the Classroom).

ERIC Educational Resources Information Center

Einsiedler, Wolfgang

1996-01-01

Asks whether theories of knowledge representation provide a basis for the development of theories of knowledge structuring in instruction. Discusses codes of knowledge, surface versus deep structures, semantic networks, and multiple memory systems. Reviews research on teaching, external representation of cognitive structures, hierarchical…

Artificial intelligence techniques for scheduling Space Shuttle missions

NASA Technical Reports Server (NTRS)

Henke, Andrea L.; Stottler, Richard H.

1994-01-01

Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

Students' understandings of electrochemistry

NASA Astrophysics Data System (ADS)

O'Grady-Morris, Kathryn

Electrochemistry is considered by students to be a difficult topic in chemistry. This research was a mixed methods study guided by the research question: At the end of a unit of study, what are students' understandings of electrochemistry? The framework of analysis used for the qualitative and quantitative data collected in this study was comprised of three categories: types of knowledge used in problem solving, levels of representation of knowledge in chemistry (macroscopic, symbolic, and particulate), and alternative conceptions. Although individually each of the three categories has been reported in previous studies, the contribution of this study is the inter-relationships among them. Semi-structured, task-based interviews were conducted while students were setting up and operating electrochemical cells in the laboratory, and a two-tiered, multiple-choice diagnostic instrument was designed to identify alternative conceptions that students held at the end of the unit. For familiar problems, those involving routine voltaic cells, students used a working-forwards problem-solving strategy, two or three levels of representation of knowledge during explanations, scored higher on both procedural and conceptual knowledge questions in the diagnostic instrument, and held fewer alternative conceptions related to the operation of these cells. For less familiar problems, those involving non-routine voltaic cells and electrolytic cells, students approached problem-solving with procedural knowledge, used only one level of representation of knowledge when explaining the operation of these cells, scored higher on procedural knowledge than conceptual knowledge questions in the diagnostic instrument, and held a greater number of alternative conceptions. Decision routines that involved memorized formulas and procedures were used to solve both quantitative and qualitative problems and the main source of alternative conceptions in this study was the overgeneralization of theory related to the particulate level of representation of knowledge. The findings from this study may contribute further to our understanding of students' conceptions in electrochemistry. Furthermore, understanding the influence of the three categories in the framework of analysis and their inter-relationships on how students make sense of this field may result in a better understanding of classroom practice that could promote the acquisition of conceptual knowledge --- knowledge that is "rich in relationships".

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

PubMed Central

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

2011-01-01

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

Abstraction in perceptual symbol systems.

PubMed Central

Barsalou, Lawrence W

2003-01-01

After reviewing six senses of abstraction, this article focuses on abstractions that take the form of summary representations. Three central properties of these abstractions are established: ( i ) type-token interpretation; (ii) structured representation; and (iii) dynamic realization. Traditional theories of representation handle interpretation and structure well but are not sufficiently dynamical. Conversely, connectionist theories are exquisitely dynamic but have problems with structure. Perceptual symbol systems offer an approach that implements all three properties naturally. Within this framework, a loose collection of property and relation simulators develops to represent abstractions. Type-token interpretation results from binding a property simulator to a region of a perceived or simulated category member. Structured representation results from binding a configuration of property and relation simulators to multiple regions in an integrated manner. Dynamic realization results from applying different subsets of property and relation simulators to category members on different occasions. From this standpoint, there are no permanent or complete abstractions of a category in memory. Instead, abstraction is the skill to construct temporary online interpretations of a category's members. Although an infinite number of abstractions are possible, attractors develop for habitual approaches to interpretation. This approach provides new ways of thinking about abstraction phenomena in categorization, inference, background knowledge and learning. PMID:12903648

A Knowledge-based System for Intelligent Support in Pharmacogenomics Evidence Assessment: Ontology-driven Evidence Representation and Retrieval.

PubMed

Lee, Chia-Ju; Devine, Beth; Tarczy-Hornoch, Peter

2017-01-01

Pharmacogenomics holds promise as a critical component of precision medicine. Yet, the use of pharmacogenomics in routine clinical care is minimal, partly due to the lack of efficient and effective use of existing evidence. This paper describes the design, development, implementation and evaluation of a knowledge-based system that fulfills three critical features: a) providing clinically relevant evidence, b) applying an evidence-based approach, and c) using semantically computable formalism, to facilitate efficient evidence assessment to support timely decisions on adoption of pharmacogenomics in clinical care. To illustrate functionality, the system was piloted in the context of clopidogrel and warfarin pharmacogenomics. In contrast to existing pharmacogenomics knowledge bases, the developed system is the first to exploit the expressivity and reasoning power of logic-based representation formalism to enable unambiguous expression and automatic retrieval of pharmacogenomics evidence to support systematic review with meta-analysis.

An Integrated Planning Representation Using Macros, Abstractions, and Cases

NASA Technical Reports Server (NTRS)

Baltes, Jacky; MacDonald, Bruce

1992-01-01

Planning will be an essential part of future autonomous robots and integrated intelligent systems. This paper focuses on learning problem solving knowledge in planning systems. The system is based on a common representation for macros, abstractions, and cases. Therefore, it is able to exploit both classical and case based techniques. The general operators in a successful plan derivation would be assessed for their potential usefulness, and some stored. The feasibility of this approach was studied through the implementation of a learning system for abstraction. New macros are motivated by trying to improve the operatorset. One heuristic used to improve the operator set is generating operators with more general preconditions than existing ones. This heuristic leads naturally to abstraction hierarchies. This investigation showed promising results on the towers of Hanoi problem. The paper concludes by describing methods for learning other problem solving knowledge. This knowledge can be represented by allowing operators at different levels of abstraction in a refinement.

[Representations and induced pain: benchmarks, memory, discussion...towards the premises of comprehension].

PubMed

Peoc'h, Nadia; Lopez, Ghyslaine; Castes, Nadine

2007-03-01

As part of qualitative research for the CLUD of the Hospitals of Toulouse, we studied for two years how the social representations of health professionals could contribute to clarify the practices of consideration of "pain resulting from care". As part of the theory of social representations, we rested on the notion of professional representation. Professional representations are representations concerning outstanding objects (pain resulting from care) belonging to a specific professional environment (health professionals). Divided within the considered profession, they constitute a dissimilar process, taking shape and getting out of shape, with which individuals evolve in professional situation (care situations): opinions, behavior, strong lines, knowledge.... The notion was made operational here with 302 health professionals from all social and occupational groups. Although the elements put forward in this article only represent a brief part of the research undertaken, they enable to register our qualitative research in a hermeneutic approach of the studied phenomenon. The examination of the professional representation brought back to the various categories of health actors shows that the status of some of them and of the others is the first differential criterion of strong lines relative to the mentioned professional object. Besides, the own story of the health actor, in his knowledge and opinions, reveals a second particular marker. Yes, "pain resulting from care" is an outstanding object, which is acknowledged within the care units. Yes, "what I am (I, a nurse) would influence my way of taking care of the pain resulting from care".

Benchmarking Ontologies: Bigger or Better?

PubMed Central

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

2011-01-01

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

Apes, skulls and drums: using images to make ethnographic knowledge in imperial Germany.

PubMed

Petrou, Marissa H

2018-03-01

In this paper, I discuss the development and use of images employed by the Dresden Royal Museum for Zoology, Anthropology and Ethnography to resolve debates about how to use visual representation as a means of making ethnographic knowledge. Through experimentation with techniques of visual representation, the founding director, A.B. Meyer (1840-1911), proposed a historical, non-essentialist approach to understanding racial and cultural difference. Director Meyer's approach was inspired by the new knowledge he had gained through field research in Asia-Pacific as well as new forms of imaging that made highly detailed representations of objects possible. Through a combination of various techniques, he developed new visual methods that emphasized intimate familiarity with variations within any one ethnic group, from skull shape to material ornamentation, as integral to the new disciplines of physical and cultural anthropology. It is well known that photographs were a favoured form of visual documentation among the anthropological and ethnographic sciences at the fin de siècle. However, in the scholarly journals of the Dresden museum, photographs, drawings, tables and etchings were frequently displayed alongside one another. Meyer sought to train the reader's eye through organized arrangements that represented objects from multiple angles and at various levels of magnification. Focusing on chimpanzees, skulls and kettledrums from Asia-Pacific, I track the development of new modes of making and reading images, from zoology and physical anthropology to ethnography, to demonstrate how the museum visually historicized humankind.

Cross-domain Collaborative Research and People Interoperability: Beyond Knowledge Representation Frameworks

NASA Astrophysics Data System (ADS)

Fox, P. A.; Diviacco, P.; Busato, A.

2016-12-01

Geo-scientific research collaboration commonly faces of complex systems where multiple skills and competences are needed at the same time. Efficacy of such collaboration among researchers then becomes of paramount importance. Multidisciplinary studies draw from domains that are far from each other. Researchers also need to understand: how to extract what data they need and eventually produce something that can be used by others. The management of information and knowledge in this perspective is non-trivial. Interoperability is frequently sought in computer-to-computer environements, so-as to overcome mismatches in vocabulary, data formats, coordinate reference system and so on. Successful researcher collaboration also relies on interoperability of the people! Smaller, synchronous and face-to-face settings for researchers are knownn to enhance people interoperability. However changing settings; either geographically; temporally; or with increasing the team size, diversity, and expertise requires people-computer-people-computer (...) interoperability. To date, knowledge representation framework have been proposed but not proven as necessary and sufficient to achieve multi-way interoperability. In this contribution, we address epistemology and sociology of science advocating for a fluid perspective where science is mostly a social construct, conditioned by cognitive issues; especially cognitive bias. Bias cannot be obliterated. On the contrary it must be carefully taken into consideration. Information-centric interfaces built from different perspectives and ways of thinking by actors with different point of views, approaches and aims, are proposed as a means for enhancing people interoperability in computer-based settings. The contribution will provide details on the approach of augmenting and interfacing to knowledge representation frameworks to the cognitive-conceptual frameworks for people that are needed to meet and exceed collaborative research goals in the 21st century. A web based collaborative portal has been developed that integrates both approaches and will be presented. Reports will be given on initial tests that have encouraging results.

Public health situation awareness: toward a semantic approach

NASA Astrophysics Data System (ADS)

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

2004-04-01

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

A survey on the design of multiprocessing systems for artificial intelligence applications

NASA Technical Reports Server (NTRS)

Wah, Benjamin W.; Li, Guo Jie

1989-01-01

Some issues in designing computers for artificial intelligence (AI) processing are discussed. These issues are divided into three levels: the representation level, the control level, and the processor level. The representation level deals with the knowledge and methods used to solve the problem and the means to represent it. The control level is concerned with the detection of dependencies and parallelism in the algorithmic and program representations of the problem, and with the synchronization and sheduling of concurrent tasks. The processor level addresses the hardware and architectural components needed to evaluate the algorithmic and program representations. Solutions for the problems of each level are illustrated by a number of representative systems. Design decisions in existing projects on AI computers are classed into top-down, bottom-up, and middle-out approaches.

Knowledge Representation: A Brief Review.

ERIC Educational Resources Information Center

Vickery, B. C.

1986-01-01

Reviews different structures and techniques of knowledge representation: structure of database records and files, data structures in computer programming, syntatic and semantic structure of natural language, knowledge representation in artificial intelligence, and models of human memory. A prototype expert system that makes use of some of these…

Differential involvement of knowledge representation and executive control in episodic memory performance in young and older adults.

PubMed

Bouazzaoui, Badiâa; Fay, Séverine; Taconnat, Laurence; Angel, Lucie; Vanneste, Sandrine; Isingrini, Michel

2013-06-01

Craik and Bialystok (2006, 2008) postulated that examining the evolution of knowledge representation and control processes across the life span could help in understanding age-related cognitive changes. The present study explored the hypothesis that knowledge representation and control processes are differentially involved in the episodic memory performance of young and older adults. Young and older adults were administered a cued-recall task and tests of crystallized knowledge and executive functioning to measure representation and control processes, respectively. Results replicate the classic finding that executive and cued-recall performance decline with age, but crystallized-knowledge performance does not. Factor analysis confirmed the independence of representation and control. Correlation analyses showed that the memory performance of younger adults was correlated with representation but not with control measures, whereas the memory performance of older adults was correlated with both representation and control measures. Regression analyses indicated that the control factor was the main predictor of episodic-memory performance for older adults, with the representation factor adding an independent contribution, but the representation factor was the sole predictor for young adults. This finding supports the view that factors sustaining episodic memory vary from young adulthood to old age; representation was shown to be important throughout adulthood, and control was also important for older adults. The results also indicated that control and representation modulate age-group-related variance in episodic memory.

Knowledge Organization through Multiple Representations in a Computer-Supported Collaborative Learning Environment

ERIC Educational Resources Information Center

Namdar, Bahadir; Shen, Ji

2018-01-01

Computer-supported collaborative learning (CSCL) environments provide learners with multiple representational tools for storing, sharing, and constructing knowledge. However, little is known about how learners organize knowledge through multiple representations about complex socioscientific issues. Therefore, the purpose of this study was to…

Do Knowledge-Component Models Need to Incorporate Representational Competencies?

ERIC Educational Resources Information Center

Rau, Martina Angela

2017-01-01

Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…

From knowledge presentation to knowledge representation to knowledge construction: Future directions for hypermedia

NASA Technical Reports Server (NTRS)

Palumbo, David B.

1990-01-01

Relationships between human memory systems and hypermedia systems are discussed with particular emphasis on the underlying importance of associational memory. The distinctions between knowledge presentation, knowledge representation, and knowledge constructions are addressed. Issues involved in actually developing individualizable hypermedia based knowledge construction tools are presented.

Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI

PubMed Central

Serrano, Miguel Ángel; Gómez-Romero, Juan; Patricio, Miguel Ángel; García, Jesús; Molina, José Manuel

2012-01-01

Recent advances in technologies for capturing video data have opened a vast amount of new application areas in visual sensor networks. Among them, the incorporation of light wave cameras on Ambient Intelligence (AmI) environments provides more accurate tracking capabilities for activity recognition. Although the performance of tracking algorithms has quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted to smart environments. This lack of representation does not allow to take advantage of the semantic quality of the information provided by new sensors. This paper advocates for the introduction of a part-based representational level in cognitive-based systems in order to accurately represent the novel sensors' knowledge. The paper also reviews the theoretical and practical issues in part-whole relationships proposing a specific taxonomy for computer vision approaches. General part-based patterns for human body and transitive part-based representation and inference are incorporated to an ontology-based previous framework to enhance scene interpretation in the area of video-based AmI. The advantages and new features of the model are demonstrated in a Social Signal Processing (SSP) application for the elaboration of live market researches.

Application of spatial pedotransfer functions to understand soil modulation of vegetation response to climate

USDA-ARS?s Scientific Manuscript database

A fundamental knowledge gap in understanding land-atmosphere interactions is accurate, high resolution spatial representation of soil physical and hydraulic properties. We present a novel approach to predict hydraulic soil parameters by combining digital soil mapping techniques with pedotransfer fun...

Using a Multimodal Learning System to Support Music Instruction

ERIC Educational Resources Information Center

Yu, Pao-Ta; Lai, Yen-Shou; Tsai, Hung-Hsu; Chang, Yuan-Hou

2010-01-01

This paper describes a multimodality approach that helps primary-school students improve their learning performance during music instruction. Multimedia instruction is an effective way to help learners create meaningful knowledge and to make referential connections between mental representations. This paper proposes a multimodal, dual-channel,…

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

PubMed Central

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

2000-01-01

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

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

Neuro-symbolic representation learning on biological knowledge graphs.

PubMed

Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar; Kinjo, Akira R; Queralt-Rosinach, Núria; Hoehndorf, Robert

2017-09-01

Biological data and knowledge bases increasingly rely on Semantic Web technologies and the use of knowledge graphs for data integration, retrieval and federated queries. In the past years, feature learning methods that are applicable to graph-structured data are becoming available, but have not yet widely been applied and evaluated on structured biological knowledge. Results: We develop a novel method for feature learning on biological knowledge graphs. Our method combines symbolic methods, in particular knowledge representation using symbolic logic and automated reasoning, with neural networks to generate embeddings of nodes that encode for related information within knowledge graphs. Through the use of symbolic logic, these embeddings contain both explicit and implicit information. We apply these embeddings to the prediction of edges in the knowledge graph representing problems of function prediction, finding candidate genes of diseases, protein-protein interactions, or drug target relations, and demonstrate performance that matches and sometimes outperforms traditional approaches based on manually crafted features. Our method can be applied to any biological knowledge graph, and will thereby open up the increasing amount of Semantic Web based knowledge bases in biology to use in machine learning and data analytics. https://github.com/bio-ontology-research-group/walking-rdf-and-owl. robert.hoehndorf@kaust.edu.sa. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

A novel knowledge-based system for interpreting complex engineering drawings: theory, representation, and implementation.

PubMed

Lu, Tong; Tai, Chiew-Lan; Yang, Huafei; Cai, Shijie

2009-08-01

We present a novel knowledge-based system to automatically convert real-life engineering drawings to content-oriented high-level descriptions. The proposed method essentially turns the complex interpretation process into two parts: knowledge representation and knowledge-based interpretation. We propose a new hierarchical descriptor-based knowledge representation method to organize the various types of engineering objects and their complex high-level relations. The descriptors are defined using an Extended Backus Naur Form (EBNF), facilitating modification and maintenance. When interpreting a set of related engineering drawings, the knowledge-based interpretation system first constructs an EBNF-tree from the knowledge representation file, then searches for potential engineering objects guided by a depth-first order of the nodes in the EBNF-tree. Experimental results and comparisons with other interpretation systems demonstrate that our knowledge-based system is accurate and robust for high-level interpretation of complex real-life engineering projects.

Conceptual knowledge representation: A cross-section of current research.

PubMed

Rogers, Timothy T; Wolmetz, Michael

2016-01-01

How is conceptual knowledge encoded in the brain? This special issue of Cognitive Neuropsychology takes stock of current efforts to answer this question through a variety of methods and perspectives. Across this work, three questions recur, each fundamental to knowledge representation in the mind and brain. First, what are the elements of conceptual representation? Second, to what extent are conceptual representations embodied in sensory and motor systems? Third, how are conceptual representations shaped by context, especially linguistic context? In this introductory article we provide relevant background on these themes and introduce how they are addressed by our contributing authors.

Using a Knowledge Representations Approach to Cognitive Task Analysis.

ERIC Educational Resources Information Center

Black, John B.; And Others

Task analyses have traditionally been framed in terms of overt behaviors performed in accomplishing tasks and goals. Pioneering work at the Learning Research and Development Center looked at what contribution a cognitive analysis might make to current task analysis procedures, since traditional task analysis methods neither elicit nor capture…

Parent Emotion Representations and the Socialization of Emotion Regulation in the Family

ERIC Educational Resources Information Center

Meyer, Sara; Raikes, H. Abigail; Virmani, Elita A.; Waters, Sara; Thompson, Ross A.

2014-01-01

There is considerable knowledge of parental socialization processes that directly and indirectly influence the development of children's emotion self-regulation, but little understanding of the specific beliefs and values that underlie parents' socialization approaches. This study examined multiple aspects of parents' self-reported…

Styling the Occidental Other: Interculturality in Chinese University Performances

ERIC Educational Resources Information Center

Grimshaw, Trevor

2010-01-01

Essentialist representations of the Orientalised Other abound within the literature of intercultural communication. The dominant discourse constructs Chinese-speaking students as members of a homogenised collective: passive recipients of knowledge who are reliant on a reproductive approach to learning. This article seeks to offer a corrective to…

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

ERIC Educational Resources Information Center

Ramakishnan, Sadhu Balasundaram; Ramadoss, Balakrishnan

2009-01-01

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

Effects of Virtual Manipulatives with Different Approaches on Students' Knowledge of Slope

ERIC Educational Resources Information Center

Demir, Mustafa

2018-01-01

Virtual Manipulatives (VMs) are computer-based, dynamic, and visual representations of mathematical concepts, provide interactive learning environments to advance mathematics instruction (Moyer et al., 2002). Despite their broad use, few research explored the integration of VMs into mathematics instruction (Moyer-Packenham & Westenskow, 2013).…

How students learn to coordinate knowledge of physical and mathematical models in cellular physiology

NASA Astrophysics Data System (ADS)

Lira, Matthew

This dissertation explores the Knowledge in Pieces (KiP) theory to account for how students learn to coordinate knowledge of mathematical and physical models in biology education. The KiP approach characterizes student knowledge as a fragmented collection of knowledge elements as opposed to stable and theory-like knowledge. This dissertation sought to use this theoretical lens to account for how students understand and learn with mathematical models and representations, such as equations. Cellular physiology provides a quantified discipline that leverages concepts from mathematics, physics, and chemistry to understand cellular functioning. Therefore, this discipline provides an exemplary context for assessing how biology students think and learn with mathematical models. In particular, the resting membrane potential provides an exemplary concept well defined by models of dynamic equilibrium borrowed from physics and chemistry. In brief, membrane potentials, or voltages, "rest" when the electrical and chemical driving forces for permeable ionic species are equal in magnitude but opposite in direction. To assess students' understandings of this concept, this dissertation employed three studies: the first study employed the cognitive clinical interview to assess student thinking in the absence and presence of equations. The second study employed an intervention to assess student learning and the affordances of an innovative assessment. The third student employed a human-computer-interaction paradigm to assess how students learn with a novel multi-representational technology. Study 1 revealed that students saw only one influence--the chemical gradient--and that students coordinated knowledge of only this gradient with the related equations. Study 2 revealed that students benefited from learning with the multi-representational technology and that the assessment detected performance gains across both calculation and explanation tasks. Last, Study 3 revealed how students shift from recognizing one influence to recognizing both the chemical and the electrical gradients as responsible for a cell's membrane potential reaching dynamic equilibrium. Together, the studies illustrate that to coordinate knowledge, students need opportunities to reflect upon relations between representations of mathematical and physical models as well as distinguish between physical quantities such as molarities for ions and transmembrane voltages.

Knowledge represented using RDF semantic network in the concept of semantic web

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

Lukasova, A., E-mail: alena.lukasova@osu.cz; Vajgl, M., E-mail: marek.vajgl@osu.cz; Zacek, M., E-mail: martin.zacek@osu.cz

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDFmore » to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.« less

Optimal graph search segmentation using arc-weighted graph for simultaneous surface detection of bladder and prostate.

PubMed

Song, Qi; Wu, Xiaodong; Liu, Yunlong; Smith, Mark; Buatti, John; Sonka, Milan

2009-01-01

We present a novel method for globally optimal surface segmentation of multiple mutually interacting objects, incorporating both edge and shape knowledge in a 3-D graph-theoretic approach. Hard surface interacting constraints are enforced in the interacting regions, preserving the geometric relationship of those partially interacting surfaces. The soft smoothness a priori shape compliance is introduced into the energy functional to provide shape guidance. The globally optimal surfaces can be simultaneously achieved by solving a maximum flow problem based on an arc-weighted graph representation. Representing the segmentation problem in an arc-weighted graph, one can incorporate a wider spectrum of constraints into the formulation, thus increasing segmentation accuracy and robustness in volumetric image data. To the best of our knowledge, our method is the first attempt to introduce the arc-weighted graph representation into the graph-searching approach for simultaneous segmentation of multiple partially interacting objects, which admits a globally optimal solution in a low-order polynomial time. Our new approach was applied to the simultaneous surface detection of bladder and prostate. The result was quite encouraging in spite of the low saliency of the bladder and prostate in CT images.

Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

DTIC Science & Technology

1987-04-20

Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

Object-oriented knowledge representation for expert systems

NASA Technical Reports Server (NTRS)

Scott, Stephen L.

1991-01-01

Object oriented techniques have generated considerable interest in the Artificial Intelligence (AI) community in recent years. This paper discusses an approach for representing expert system knowledge using classes, objects, and message passing. The implementation is in version 4.3 of NASA's C Language Integrated Production System (CLIPS), an expert system tool that does not provide direct support for object oriented design. The method uses programmer imposed conventions and keywords to structure facts, and rules to provide object oriented capabilities.

Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework.

PubMed

Zhang, Yi-Fan; Gou, Ling; Tian, Yu; Li, Tian-Chang; Zhang, Mao; Li, Jing-Song

2016-05-01

Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.

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.

Representation of illness in Familial Amyloidotic Polyneuropathy Portuguese Association newspaper: A documental study.

PubMed

Novais, Sónia Alexandra de Lemos; Mendes, Felismina Rosa Parreira

2016-03-01

This study explores illness representations within Familial Amyloidotic Polyneuropathy Portuguese Association newspaper . A content analysis was performed of the issue data using provisional coding related to the conceptual framework of the study. All dimensions of illness representation in Leventhal's Common Sense Model of illness cognitions and behaviors are present in the data and reflect the experience of living with this disease. Understanding how a person living with an hereditary, rare, neurodegenerative illness is important for developing community nursing interventions. In conclusion, we suggest an integration of common sense knowledge with other approaches for designing an intervention program centered on people living with an hereditary neurodegenerative illness, such as familial amyloidotic polyneuropathy. © 2015 Wiley Publishing Asia Pty Ltd.

Knowledge Representation Of CT Scans Of The Head

NASA Astrophysics Data System (ADS)

Ackerman, Laurens V.; Burke, M. W.; Rada, Roy

1984-06-01

We have been investigating diagnostic knowledge models which assist in the automatic classification of medical images by combining information extracted from each image with knowledge specific to that class of images. In a more general sense we are trying to integrate verbal and pictorial descriptions of disease via representations of knowledge, study automatic hypothesis generation as related to clinical medicine, evolve new mathematical image measures while integrating them into the total diagnostic process, and investigate ways to augment the knowledge of the physician. Specifically, we have constructed an artificial intelligence knowledge model using the technique of a production system blending pictorial and verbal knowledge about the respective CT scan and patient history. It is an attempt to tie together different sources of knowledge representation, picture feature extraction and hypothesis generation. Our knowledge reasoning and representation system (KRRS) works with data at the conscious reasoning level of the practicing physician while at the visual perceptional level we are building another production system, the picture parameter extractor (PPE). This paper describes KRRS and its relationship to PPE.

Investigating the Implementation of Knowledge Representation in the COMBATXXI System

DTIC Science & Technology

2015-06-01

mechanism. Finally, follow-on research can work towards more cognitive modeling in order to distinguish between manned systems and unmanned systems in...Approved for public release; distribution is unlimited INVESTIGATING THE IMPLEMENTATION OF KNOWLEDGE REPRESENTATION IN THE COMBATXXI SYSTEM by Mongi...INVESTIGATING THE IMPLEMENTATION OF KNOWLEDGE REPRESENTATION IN THE COMBATXXI SYSTEM 5. FUNDING NUMBERS GM10331601, National Institute of General

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.

Towards symbiosis in knowledge representation and natural language processing for structuring clinical practice guidelines.

PubMed

Weng, Chunhua; Payne, Philip R O; Velez, Mark; Johnson, Stephen B; Bakken, Suzanne

2014-01-01

The successful adoption by clinicians of evidence-based clinical practice guidelines (CPGs) contained in clinical information systems requires efficient translation of free-text guidelines into computable formats. Natural language processing (NLP) has the potential to improve the efficiency of such translation. However, it is laborious to develop NLP to structure free-text CPGs using existing formal knowledge representations (KR). In response to this challenge, this vision paper discusses the value and feasibility of supporting symbiosis in text-based knowledge acquisition (KA) and KR. We compare two ontologies: (1) an ontology manually created by domain experts for CPG eligibility criteria and (2) an upper-level ontology derived from a semantic pattern-based approach for automatic KA from CPG eligibility criteria text. Then we discuss the strengths and limitations of interweaving KA and NLP for KR purposes and important considerations for achieving the symbiosis of KR and NLP for structuring CPGs to achieve evidence-based clinical practice.

Approaches to a cortical vision prosthesis: implications of electrode size and placement

NASA Astrophysics Data System (ADS)

Christie, Breanne P.; Ashmont, Kari R.; House, Paul A.; Greger, Bradley

2016-04-01

Objective. In order to move forward with the development of a cortical vision prosthesis, the critical issues in the field must be identified. Approach. To begin this process, we performed a brief review of several different cortical and retinal stimulation techniques that can be used to restore vision. Main results. Intracortical microelectrodes and epicortical macroelectrodes have been evaluated as the basis of a vision prosthesis. We concluded that an important knowledge gap necessitates an experimental in vivo performance evaluation of microelectrodes placed on the surface of the visual cortex. A comparison of the level of vision restored by intracortical versus epicortical microstimulation is necessary. Because foveal representation in the primary visual cortex involves more cortical columns per degree of visual field than does peripheral vision, restoration of foveal vision may require a large number of closely spaced microelectrodes. Based on previous studies of epicortical macrostimulation, it is possible that stimulation via surface microelectrodes could produce a lower spatial resolution, making them better suited for restoring peripheral vision. Significance. The validation of epicortical microstimulation in addition to the comparison of epicortical and intracortical approaches for vision restoration will fill an important knowledge gap and may have important implications for surgical strategies and device longevity. It is possible that the best approach to vision restoration will utilize both epicortical and intracortical microstimulation approaches, applying them appropriately to different visual representations in the primary visual cortex.

The nature and development of preservice science teachers' conceptions of subject matter and pedagogy

NASA Astrophysics Data System (ADS)

Lederman, Norman G.; Gess-Newsome, Julie; Latz, Mark S.

The purpose of this study was to assess the development and changes in preservice science teachers' subject matter and pedagogy knowledge structures as they proceeded through a professional teacher education program. Twelve secondary preservice science teachers were asked to create representations of their subject matter and pedagogy knowledge structures periodically (four times spanning the entirety of their subject-specific teacher education program) and participate in a videotaped interview concerning the eight knowledge structure representations immediately following student teaching. Qualitative analyses of knowledge structure representations and transcribed interviews within and between subjects were performed by one of the researchers and blindly corroborated by the other two researchers. Initial knowledge structure representations were typically linear and lacked coherence. Both types of knowledge structure representations were highly susceptible to change as a consequence of the act of teaching. Although there was some overlap between subject matter and pedagogy knowledge structures, they were reported to exert separate influences on classroom practice, with the pedagogy knowledge structure having primary influence on instructional decisions. Furthermore, the complexity of one's subject matter structure appeared to be a critical factor in determining whether the structure directly influences classroom practice.Received: 5 February 1993; Revised: 28 July 1993;

The interaction of representation and reasoning.

PubMed

Bundy, Alan

2013-09-08

Automated reasoning is an enabling technology for many applications of informatics. These applications include verifying that a computer program meets its specification; enabling a robot to form a plan to achieve a task and answering questions by combining information from diverse sources, e.g. on the Internet, etc. How is automated reasoning possible? Firstly, knowledge of a domain must be stored in a computer, usually in the form of logical formulae. This knowledge might, for instance, have been entered manually, retrieved from the Internet or perceived in the environment via sensors, such as cameras. Secondly, rules of inference are applied to old knowledge to derive new knowledge. Automated reasoning techniques have been adapted from logic, a branch of mathematics that was originally designed to formalize the reasoning of humans, especially mathematicians. My special interest is in the way that representation and reasoning interact. Successful reasoning is dependent on appropriate representation of both knowledge and successful methods of reasoning. Failures of reasoning can suggest changes of representation. This process of representational change can also be automated. We will illustrate the automation of representational change by drawing on recent work in my research group.

A standard based approach for biomedical knowledge representation.

PubMed

Farkash, Ariel; Neuvirth, Hani; Goldschmidt, Yaara; Conti, Costanza; Rizzi, Federica; Bianchi, Stefano; Salvi, Erika; Cusi, Daniele; Shabo, Amnon

2011-01-01

The new generation of health information standards, where the syntax and semantics of the content is explicitly formalized, allows for interoperability in healthcare scenarios and analysis in clinical research settings. Studies involving clinical and genomic data include accumulating knowledge as relationships between genotypic and phenotypic information as well as associations within the genomic and clinical worlds. Some involve analysis results targeted at a specific disease; others are of a predictive nature specific to a patient and may be used by decision support applications. Representing knowledge is as important as representing data since data is more useful when coupled with relevant knowledge. Any further analysis and cross-research collaboration would benefit from persisting knowledge and data in a unified way. This paper describes a methodology used in Hypergenes, an EC FP7 project targeting Essential Hypertension, which captures data and knowledge using standards such as HL7 CDA and Clinical Genomics, aligned with the CEN EHR 13606 specification. We demonstrate the benefits of such an approach for clinical research as well as in healthcare oriented scenarios.

Social representations of nurses about professional autonomy and the use of technologies in the care of patients with wounds.

PubMed

Dos Santos, Érick Igor; Grativol Aguiar Dias de Oliveira, Jéssica

2016-06-01

To identify the social representations by nurses about professional autonomy in the care of patients with wounds and analyze their interfaces with the constant incorporation of technologies in this care. This is a qualitative research, outlined from the Theory and method of social representations in its procedural approach and performed with 31 nurses. The interviews were submitted to thematic content analysis software NVivo instrumentalized by 10. The representational content on autonomy is linked mainly to the level of knowledge, power of decision, vocational training and institutional factors. The subjects are positioned favorably to the incorporation of care technologies in professional practice, which involves elements such as cost-effective structure, training, and other resources. It is concluded that autonomy is configured as a prerequisite for the full use of technology and technology is configured as a facilitator for nurses to become more autonomous.

Kernel-PCA data integration with enhanced interpretability

PubMed Central

2014-01-01

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge. PMID:25032747

Hypermedia-Assisted Instruction and Second Language Learning: A Semantic-Network-Based Approach.

ERIC Educational Resources Information Center

Liu, Min

This literature review examines a hypermedia learning environment from a semantic network basis and the application of such an environment to second language learning. (A semantic network is defined as a conceptual representation of knowledge in human memory). The discussion is organized under the following headings and subheadings: (1) Advantages…

[The representation of scientific research through a poster].

PubMed

Dupin, Cécile-Marie

2013-12-01

The poster is a medium of scientific communication. When presented in public, it optimises the value of an original research approach. The poster sessions are devoted to one-to-one exchanges with peers on the subject of the research. The poster can help to integrate scientific knowledge into the nursing decision-making process.

Genetic algorithms for adaptive real-time control in space systems

NASA Technical Reports Server (NTRS)

Vanderzijp, J.; Choudry, A.

1988-01-01

Genetic Algorithms that are used for learning as one way to control the combinational explosion associated with the generation of new rules are discussed. The Genetic Algorithm approach tends to work best when it can be applied to a domain independent knowledge representation. Applications to real time control in space systems are discussed.

Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience.

PubMed

Matiasz, Nicholas J; Wood, Justin; Wang, Wei; Silva, Alcino J; Hsu, William

2017-01-01

Computers help neuroscientists to analyze experimental results by automating the application of statistics; however, computer-aided experiment planning is far less common, due to a lack of similar quantitative formalisms for systematically assessing evidence and uncertainty. While ontologies and other Semantic Web resources help neuroscientists to assimilate required domain knowledge, experiment planning requires not only ontological but also epistemological (e.g., methodological) information regarding how knowledge was obtained. Here, we outline how epistemological principles and graphical representations of causality can be used to formalize experiment planning toward causal discovery. We outline two complementary approaches to experiment planning: one that quantifies evidence per the principles of convergence and consistency, and another that quantifies uncertainty using logical representations of constraints on causal structure. These approaches operationalize experiment planning as the search for an experiment that either maximizes evidence or minimizes uncertainty. Despite work in laboratory automation, humans must still plan experiments and will likely continue to do so for some time. There is thus a great need for experiment-planning frameworks that are not only amenable to machine computation but also useful as aids in human reasoning.

How Pictorial Knowledge Representations Mediate Collaborative Knowledge Construction in Groups

ERIC Educational Resources Information Center

Naykki, Piia; Jarvela, Sanna

2008-01-01

This study investigates the process of collaborative knowledge construction when technology and pictorial knowledge representations are used for visualizing individual and groups' shared ideas. The focus of the study is on how teacher-students contribute to the group's collaborative knowledge construction and use each other's ideas and tools as an…

RelFinder: Revealing Relationships in RDF Knowledge Bases

NASA Astrophysics Data System (ADS)

Heim, Philipp; Hellmann, Sebastian; Lehmann, Jens; Lohmann, Steffen; Stegemann, Timo

The Semantic Web has recently seen a rise of large knowledge bases (such as DBpedia) that are freely accessible via SPARQL endpoints. The structured representation of the contained information opens up new possibilities in the way it can be accessed and queried. In this paper, we present an approach that extracts a graph covering relationships between two objects of interest. We show an interactive visualization of this graph that supports the systematic analysis of the found relationships by providing highlighting, previewing, and filtering features.

Teachers and Students' Conceptions of Computer-Based Models in the Context of High School Chemistry: Elicitations at the Pre-intervention Stage

NASA Astrophysics Data System (ADS)

Waight, Noemi; Gillmeister, Kristina

2014-04-01

This study examined teachers' and students' initial conceptions of computer-based models—Flash and NetLogo models—and documented how teachers and students reconciled notions of multiple representations featuring macroscopic, submicroscopic and symbolic representations prior to actual intervention in eight high school chemistry classrooms. Individual in-depth interviews were conducted with 32 students and 6 teachers. Findings revealed an interplay of complex factors that functioned as opportunities and obstacles in the implementation of technologies in science classrooms. Students revealed preferences for the Flash models as opposed to the open-ended NetLogo models. Altogether, due to lack of content and modeling background knowledge, students experienced difficulties articulating coherent and blended understandings of multiple representations. Concurrently, while the aesthetic and interactive features of the models were of great value, they did not sustain students' initial curiosity and opportunities to improve understandings about chemistry phenomena. Most teachers recognized direct alignment of the Flash model with their existing curriculum; however, the benefits were relegated to existing procedural and passive classroom practices. The findings have implications for pedagogical approaches that address the implementation of computer-based models, function of models, models as multiple representations and the role of background knowledge and cognitive load, and the role of teacher vision and classroom practices.

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.

Beyond rules: The next generation of expert systems

NASA Technical Reports Server (NTRS)

Ferguson, Jay C.; Wagner, Robert E.

1987-01-01

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

Linking Somatic and Symbolic Representation in Semantic Memory: The Dynamic Multilevel Reactivation Framework

PubMed Central

Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J

2016-01-01

Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: 1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? 2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework, an integrative model premised upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the Dynamic Multilevel Reactivation Framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of ‘abstract conceptual features’ does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the material on which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation. PMID:27294419

Linking somatic and symbolic representation in semantic memory: the dynamic multilevel reactivation framework.

PubMed

Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J

2016-08-01

Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: (1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? (2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework-an integrative model predicated upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the dynamic multilevel reactivation framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of 'abstract conceptual features' does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the materials upon which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation.

RGSS-ID: an approach to new radiologic reporting system.

PubMed

Ikeda, M; Sakuma, S; Maruyama, K

1990-01-01

RGSS-ID is a developmental computer system that applies artificial intelligence (AI) methods to a reporting system. The representation scheme called Generalized Finding Representation (GFR) is proposed to bridge the gap between natural language expressions in the radiology report and AI methods. The entry process of RGSS-ID is made mainly by selecting items; our system allows a radiologist to compose a sentence which can be completely parsed by the computer. Further RGSS-ID encodes findings into the expression corresponding to GFR, and stores this expression into the knowledge data base. The final printed report is made in the natural language.

Domain adaptation via transfer component analysis.

PubMed

Pan, Sinno Jialin; Tsang, Ivor W; Kwok, James T; Yang, Qiang

2011-02-01

Domain adaptation allows knowledge from a source domain to be transferred to a different but related target domain. Intuitively, discovering a good feature representation across domains is crucial. In this paper, we first propose to find such a representation through a new learning method, transfer component analysis (TCA), for domain adaptation. TCA tries to learn some transfer components across domains in a reproducing kernel Hilbert space using maximum mean miscrepancy. In the subspace spanned by these transfer components, data properties are preserved and data distributions in different domains are close to each other. As a result, with the new representations in this subspace, we can apply standard machine learning methods to train classifiers or regression models in the source domain for use in the target domain. Furthermore, in order to uncover the knowledge hidden in the relations between the data labels from the source and target domains, we extend TCA in a semisupervised learning setting, which encodes label information into transfer components learning. We call this extension semisupervised TCA. The main contribution of our work is that we propose a novel dimensionality reduction framework for reducing the distance between domains in a latent space for domain adaptation. We propose both unsupervised and semisupervised feature extraction approaches, which can dramatically reduce the distance between domain distributions by projecting data onto the learned transfer components. Finally, our approach can handle large datasets and naturally lead to out-of-sample generalization. The effectiveness and efficiency of our approach are verified by experiments on five toy datasets and two real-world applications: cross-domain indoor WiFi localization and cross-domain text classification.

Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles

NASA Astrophysics Data System (ADS)

Cook, Michelle Patrick

2006-11-01

Visual representations are essential for communicating ideas in the science classroom; however, the design of such representations is not always beneficial for learners. This paper presents instructional design considerations providing empirical evidence and integrating theoretical concepts related to cognitive load. Learners have a limited working memory, and instructional representations should be designed with the goal of reducing unnecessary cognitive load. However, cognitive architecture alone is not the only factor to be considered; individual differences, especially prior knowledge, are critical in determining what impact a visual representation will have on learners' cognitive structures and processes. Prior knowledge can determine the ease with which learners can perceive and interpret visual representations in working memory. Although a long tradition of research has compared experts and novices, more research is necessary to fully explore the expert-novice continuum and maximize the potential of visual representations.

EliXR-TIME: A Temporal Knowledge Representation for Clinical Research Eligibility Criteria.

PubMed

Boland, Mary Regina; Tu, Samson W; Carini, Simona; Sim, Ida; Weng, Chunhua

2012-01-01

Effective clinical text processing requires accurate extraction and representation of temporal expressions. Multiple temporal information extraction models were developed but a similar need for extracting temporal expressions in eligibility criteria (e.g., for eligibility determination) remains. We identified the temporal knowledge representation requirements of eligibility criteria by reviewing 100 temporal criteria. We developed EliXR-TIME, a frame-based representation designed to support semantic annotation for temporal expressions in eligibility criteria by reusing applicable classes from well-known clinical temporal knowledge representations. We used EliXR-TIME to analyze a training set of 50 new temporal eligibility criteria. We evaluated EliXR-TIME using an additional random sample of 20 eligibility criteria with temporal expressions that have no overlap with the training data, yielding 92.7% (76 / 82) inter-coder agreement on sentence chunking and 72% (72 / 100) agreement on semantic annotation. We conclude that this knowledge representation can facilitate semantic annotation of the temporal expressions in eligibility criteria.

Representing Medical Knowledge in a Terminological Language is Difficult1

PubMed Central

Haimowits, Ira J.; Patil, Ramesh S.; Szolovits, Peter

1988-01-01

We report on an experiment to use a modern knowledge representation language, NIKL, to express the knowledge of a sophisticated medical reasoning program, ABEL. We are attempting to put the development of more capable medical programs on firmer representational grounds by moving from the ad hoc representations typical of current programs toward more principled representation languages now in use or under construction. Our experience with the project reported here suggests caution, however. Attempts at cleanliness and efficiency in the design of representation languages lead to a poverty of expressiveness that makes it difficult if not impossible to say in such languages what needs to be stated to support the application.

Problem-Oriented Corporate Knowledge Base Models on the Case-Based Reasoning Approach Basis

NASA Astrophysics Data System (ADS)

Gluhih, I. N.; Akhmadulin, R. K.

2017-07-01

One of the urgent directions of efficiency enhancement of production processes and enterprises activities management is creation and use of corporate knowledge bases. The article suggests a concept of problem-oriented corporate knowledge bases (PO CKB), in which knowledge is arranged around possible problem situations and represents a tool for making and implementing decisions in such situations. For knowledge representation in PO CKB a case-based reasoning approach is encouraged to use. Under this approach, the content of a case as a knowledge base component has been defined; based on the situation tree a PO CKB knowledge model has been developed, in which the knowledge about typical situations as well as specific examples of situations and solutions have been represented. A generalized problem-oriented corporate knowledge base structural chart and possible modes of its operation have been suggested. The obtained models allow creating and using corporate knowledge bases for support of decision making and implementing, training, staff skill upgrading and analysis of the decisions taken. The universal interpretation of terms “situation” and “solution” adopted in the work allows using the suggested models to develop problem-oriented corporate knowledge bases in different subject domains. It has been suggested to use the developed models for making corporate knowledge bases of the enterprises that operate engineer systems and networks at large production facilities.

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

NASA Technical Reports Server (NTRS)

Mcmanus, Shawn; Mcdaniel, Michael

1989-01-01

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

Natural language generation of surgical procedures.

PubMed

Wagner, J C; Rogers, J E; Baud, R H; Scherrer, J R

1999-01-01

A number of compositional Medical Concept Representation systems are being developed. Although these provide for a detailed conceptual representation of the underlying information, they have to be translated back to natural language for used by end-users and applications. The GALEN programme has been developing one such representation and we report here on a tool developed to generate natural language phrases from the GALEN conceptual representations. This tool can be adapted to different source modelling schemes and to different destination languages or sublanguages of a domain. It is based on a multilingual approach to natural language generation, realised through a clean separation of the domain model from the linguistic model and their link by well defined structures. Specific knowledge structures and operations have been developed for bridging between the modelling 'style' of the conceptual representation and natural language. Using the example of the scheme developed for modelling surgical operative procedures within the GALEN-IN-USE project, we show how the generator is adapted to such a scheme. The basic characteristics of the surgical procedures scheme are presented together with the basic principles of the generation tool. Using worked examples, we discuss the transformation operations which change the initial source representation into a form which can more directly be translated to a given natural language. In particular, the linguistic knowledge which has to be introduced--such as definitions of concepts and relationships is described. We explain the overall generator strategy and how particular transformation operations are triggered by language-dependent and conceptual parameters. Results are shown for generated French phrases corresponding to surgical procedures from the urology domain.

Panacea, a semantic-enabled drug recommendations discovery framework.

PubMed

Doulaverakis, Charalampos; Nikolaidis, George; Kleontas, Athanasios; Kompatsiaris, Ioannis

2014-03-06

Personalized drug prescription can be benefited from the use of intelligent information management and sharing. International standard classifications and terminologies have been developed in order to provide unique and unambiguous information representation. Such standards can be used as the basis of automated decision support systems for providing drug-drug and drug-disease interaction discovery. Additionally, Semantic Web technologies have been proposed in earlier works, in order to support such systems. The paper presents Panacea, a semantic framework capable of offering drug-drug and drug-diseases interaction discovery. For enabling this kind of service, medical information and terminology had to be translated to ontological terms and be appropriately coupled with medical knowledge of the field. International standard classifications and terminologies, provide the backbone of the common representation of medical data while the medical knowledge of drug interactions is represented by a rule base which makes use of the aforementioned standards. Representation is based on a lightweight ontology. A layered reasoning approach is implemented where at the first layer ontological inference is used in order to discover underlying knowledge, while at the second layer a two-step rule selection strategy is followed resulting in a computationally efficient reasoning approach. Details of the system architecture are presented while also giving an outline of the difficulties that had to be overcome. Panacea is evaluated both in terms of quality of recommendations against real clinical data and performance. The quality recommendation gave useful insights regarding requirements for real world deployment and revealed several parameters that affected the recommendation results. Performance-wise, Panacea is compared to a previous published work by the authors, a service for drug recommendations named GalenOWL, and presents their differences in modeling and approach to the problem, while also pinpointing the advantages of Panacea. Overall, the paper presents a framework for providing an efficient drug recommendations service where Semantic Web technologies are coupled with traditional business rule engines.

Teacher spatial skills are linked to differences in geometry instruction.

PubMed

Otumfuor, Beryl Ann; Carr, Martha

2017-12-01

Spatial skills have been linked to better performance in mathematics. The purpose of this study was to examine the relationship between teacher spatial skills and their instruction, including teacher content and pedagogical knowledge, use of pictorial representations, and use of gestures during geometry instruction. Fifty-six middle school teachers participated in the study. The teachers were administered spatial measures of mental rotations and spatial visualization. Next, a single geometry class was videotaped. Correlational analyses revealed that spatial skills significantly correlate with teacher's use of representational gestures and content and pedagogical knowledge during instruction of geometry. Spatial skills did not independently correlate with the use of pointing gestures or the use of pictorial representations. However, an interaction term between spatial skills and content and pedagogical knowledge did correlate significantly with the use of pictorial representations. Teacher experience as measured by the number of years of teaching and highest degree did not appear to affect the relationships among the variables with the exception of the relationship between spatial skills and teacher content and pedagogical knowledge. Teachers with better spatial skills are also likely to use representational gestures and to show better content and pedagogical knowledge during instruction. Spatial skills predict pictorial representation use only as a function of content and pedagogical knowledge. © 2017 The British Psychological Society.

Modelling and representation issues in automated feature extraction from aerial and satellite images

NASA Astrophysics Data System (ADS)

Sowmya, Arcot; Trinder, John

New digital systems for the processing of photogrammetric and remote sensing images have led to new approaches to information extraction for mapping and Geographic Information System (GIS) applications, with the expectation that data can become more readily available at a lower cost and with greater currency. Demands for mapping and GIS data are increasing as well for environmental assessment and monitoring. Hence, researchers from the fields of photogrammetry and remote sensing, as well as computer vision and artificial intelligence, are bringing together their particular skills for automating these tasks of information extraction. The paper will review some of the approaches used in knowledge representation and modelling for machine vision, and give examples of their applications in research for image understanding of aerial and satellite imagery.

Knowledge synthesis with maps of neural connectivity.

PubMed

Tallis, Marcelo; Thompson, Richard; Russ, Thomas A; Burns, Gully A P C

2011-01-01

This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called "Knowledge Engineering from Experimental Design" (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features.

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

PubMed Central

2014-01-01

Background Combining different sources of knowledge to build improved structure activity relationship models is not easy owing to the variety of knowledge formats and the absence of a common framework to interoperate between learning techniques. Most of the current approaches address this problem by using consensus models that operate at the prediction level. We explore the possibility to directly combine these sources at the knowledge level, with the aim to harvest potentially increased synergy at an earlier stage. Our goal is to design a general methodology to facilitate knowledge discovery and produce accurate and interpretable models. Results To combine models at the knowledge level, we propose to decouple the learning phase from the knowledge application phase using a pivot representation (lingua franca) based on the concept of hypothesis. A hypothesis is a simple and interpretable knowledge unit. Regardless of its origin, knowledge is broken down into a collection of hypotheses. These hypotheses are subsequently organised into hierarchical network. This unification permits to combine different sources of knowledge into a common formalised framework. The approach allows us to create a synergistic system between different forms of knowledge and new algorithms can be applied to leverage this unified model. This first article focuses on the general principle of the Self Organising Hypothesis Network (SOHN) approach in the context of binary classification problems along with an illustrative application to the prediction of mutagenicity. Conclusion It is possible to represent knowledge in the unified form of a hypothesis network allowing interpretable predictions with performances comparable to mainstream machine learning techniques. This new approach offers the potential to combine knowledge from different sources into a common framework in which high level reasoning and meta-learning can be applied; these latter perspectives will be explored in future work. PMID:24959206

Mental representation of normal subjects about the sources of knowledge in different semantic categories and unique entities.

PubMed

Gainotti, Guido; Ciaraffa, Francesca; Silveri, Maria Caterina; Marra, Camillo

2009-11-01

According to the "sensory-motor model of semantic knowledge," different categories of knowledge differ for the weight that different "sources of knowledge" have in their representation. Our study aimed to evaluate this model, checking if subjective evaluations given by normal subjects confirm the different weight that various sources of knowledge have in the representation of different biological and artifact categories and of unique entities, such as famous people or monuments. Results showed that the visual properties are considered as the main source of knowledge for all the living and nonliving categories (as well as for unique entities), but that the clustering of these "sources of knowledge" is different for biological and artifacts categories. Visual data are, indeed, mainly associated with other perceptual (auditory, olfactory, gustatory, and tactual) attributes in the mental representation of living beings and unique entities, whereas they are associated with action-related properties and tactile information in the case of artifacts.

Locating object knowledge in the brain: comment on Bowers's (2009) attempt to revive the grandmother cell hypothesis.

PubMed

Plaut, David C; McClelland, James L

2010-01-01

According to Bowers, the finding that there are neurons with highly selective responses to familiar stimuli supports theories positing localist representations over approaches positing the type of distributed representations typically found in parallel distributed processing (PDP) models. However, his conclusions derive from an overly narrow view of the range of possible distributed representations and of the role that PDP models can play in exploring their properties. Although it is true that current distributed theories face challenges in accounting for both neural and behavioral data, the proposed localist account--to the extent that it is articulated at all--runs into more fundamental difficulties. Central to these difficulties is the problem of specifying the set of entities a localist unit represents.

The interaction of representation and reasoning

PubMed Central

Bundy, Alan

2013-01-01

Automated reasoning is an enabling technology for many applications of informatics. These applications include verifying that a computer program meets its specification; enabling a robot to form a plan to achieve a task and answering questions by combining information from diverse sources, e.g. on the Internet, etc. How is automated reasoning possible? Firstly, knowledge of a domain must be stored in a computer, usually in the form of logical formulae. This knowledge might, for instance, have been entered manually, retrieved from the Internet or perceived in the environment via sensors, such as cameras. Secondly, rules of inference are applied to old knowledge to derive new knowledge. Automated reasoning techniques have been adapted from logic, a branch of mathematics that was originally designed to formalize the reasoning of humans, especially mathematicians. My special interest is in the way that representation and reasoning interact. Successful reasoning is dependent on appropriate representation of both knowledge and successful methods of reasoning. Failures of reasoning can suggest changes of representation. This process of representational change can also be automated. We will illustrate the automation of representational change by drawing on recent work in my research group. PMID:24062623

Thinking/acting locally/globally: Western science and environmental education in a global knowledge economy

NASA Astrophysics Data System (ADS)

Gough, Noel

2002-11-01

This paper critically appraises a number of approaches to 'thinking globally' in environmental education, with particular reference to popular assumptions about the universal applicability of Western science. Although the transnational character of many environmental issues demands that we 'think globally', I argue that the contribution of Western science to understanding and resolving environmental problems might be enhanced by seeing it as one among many local knowledge traditions. The production of a 'global knowledge economy' in/for environmental education can then be understood as creating transnational 'spaces' in which local knowledge traditions can be performed together, rather than as creating a 'common market' in which representations of local knowledge must be translated into (or exchanged for) the terms of a universal discourse.

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.

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.

Student Teachers' Knowledge about Chemical Representations

ERIC Educational Resources Information Center

Taskin, Vahide; Bernholt, Sascha; Parchmann, Ilka

2017-01-01

Chemical representations serve as a communication tool not only in exchanges between scientists but also in chemistry lessons. The goals of the present study were to measure the extent of student teachers' knowledge about chemical representations, focusing on chemical formulae and structures in particular, and to explore which factors related to…

Examining the Task and Knowledge Demands Needed to Teach with Representations

ERIC Educational Resources Information Center

Mitchell, Rebecca; Charalambous, Charalambos Y.; Hill, Heather C.

2014-01-01

Representations are often used in instruction to highlight key mathematical ideas and support student learning. Despite their centrality in scaffolding teaching and learning, most of our understanding about the tasks involved with using representations in instruction and the knowledge requirements imposed on teachers when using these aids is…

Interleaved Practice with Multiple Representations: Analyses with Knowledge Tracing Based Techniques

ERIC Educational Resources Information Center

Rau, Martina A.; Pardos, Zachary A.

2012-01-01

The goal of this paper is to use Knowledge Tracing to augment the results obtained from an experiment that investigated the effects of practice schedules using an intelligent tutoring system for fractions. Specifically, this experiment compared different practice schedules of multiple representations of fractions: representations were presented to…

Knowledge Acquisition of Generic Queries for Information Retrieval

PubMed Central

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

2002-01-01

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

NetWeaver for EMDS user guide (version 1.1): a knowledge base development system.

Treesearch

Keith M. Reynolds

1999-01-01

The guide describes use of the NetWeaver knowledge base development system. Knowledge representation in NetWeaver is based on object-oriented fuzzy-logic networks that offer several significant advantages over the more traditional rulebased representation. Compared to rule-based knowledge bases, NetWeaver knowledge bases are easier to build, test, and maintain because...

Conceptualizations of Representation Forms and Knowledge Organization of High School Teachers in Finland: "Magnetostatics"

ERIC Educational Resources Information Center

Majidi, Sharareh; Emden, Markus

2013-01-01

One of the main components of teachers' pedagogical content knowledge refers to their use of representation forms. In a similar vein, organizing concepts logically and meaningfully is an essential element of teachers' subject matter knowledge. Since subject matter and pedagogical content knowledge of teachers are tightly connected as categories…

Designing a Knowledge Representation Approach for the Generation of Pedagogical Interventions by MTTs

ERIC Educational Resources Information Center

Paquette, Luc; Lebeau, Jean-François; Beaulieu, Gabriel; Mayers, André

2015-01-01

Model-tracing tutors (MTTs) have proven effective for the tutoring of well-defined tasks, but the pedagogical interventions they produce are limited and usually require the inclusion of pedagogical content, such as text message templates, in the model of the task. The capability to generate pedagogical content would be beneficial to MTT…

Abstract Knowledge of Word Order by 19 Months: An Eye-Tracking Study

ERIC Educational Resources Information Center

Franck, Julie; Millotte, Severine; Posada, Andres; Rizzi, Luigi

2013-01-01

Word order is one of the earliest aspects of grammar that the child acquires, because her early utterances already respect the basic word order of the target language. However, the question of the nature of early syntactic representations is subject to debate. Approaches inspired by formal syntax assume that the head-complement order,…

Beyond Keyword Search: Representations and Models for Personalization

ERIC Educational Resources Information Center

El-Arini, Khalid

2013-01-01

We live in an era of information overload. From online news to online shopping to scholarly research, we are inundated with a torrent of information on a daily basis. With our limited time, money and attention, we often struggle to extract actionable knowledge from this deluge of data. A common approach for addressing this challenge is…

EXPECT: Explicit Representations for Flexible Acquisition

NASA Technical Reports Server (NTRS)

Swartout, BIll; Gil, Yolanda

1995-01-01

To create more powerful knowledge acquisition systems, we not only need better acquisition tools, but we need to change the architecture of the knowledge based systems we create so that their structure will provide better support for acquisition. Current acquisition tools permit users to modify factual knowledge but they provide limited support for modifying problem solving knowledge. In this paper, the authors argue that this limitation (and others) stem from the use of incomplete models of problem-solving knowledge and inflexible specification of the interdependencies between problem-solving and factual knowledge. We describe the EXPECT architecture which addresses these problems by providing an explicit representation for problem-solving knowledge and intent. Using this more explicit representation, EXPECT can automatically derive the interdependencies between problem-solving and factual knowledge. By deriving these interdependencies from the structure of the knowledge-based system itself EXPECT supports more flexible and powerful knowledge acquisition.

Institutional Memory Preservation at NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

Coffey, J.; Moreman, Douglas; Dyer, J.; Hemminger, J. A.

1999-01-01

In this era of downsizing and deficit reduction, the preservation of institutional memory is a widespread concern for U.S. companies and governmental agencies. The National Aeronautical and Space Administration faces the pending retirement of many of the agency's long-term, senior engineers. NASA has a marvelous long-term history of success, but the agency faces a recurring problem caused by the loss of these engineers' unique knowledge and perspectives on NASA's role in aeronautics and space exploration. The current work describes a knowledge elicitation effort aimed at demonstrating the feasibility of preserving the more personal, heuristic knowledge accumulated over the years by NASA engineers, as contrasted with the "textbook" knowledge of launch vehicles. Work on this project was performed at NASA Glenn Research Center and elsewhere, and focused on launch vehicle systems integration. The initial effort was directed toward an historic view of the Centaur upper stage which is powered by two RL-10 engines. Various experts were consulted, employing a variety of knowledge elicitation techniques, regarding the Centaur and RL-10. Their knowledge is represented in searchable Web-based multimedia presentations. This paper discusses the various approaches to knowledge elicitation and knowledge representation employed, and assesses successes and challenges in trying to perform large-scale knowledge preservation of institutional memory. It is anticipated that strategies for knowledge elicitation and representation that have been developed in this grant will be utilized to elicit knowledge in a variety of domains including the complex heuristics that underly use of simulation software packages such as that being explored in the Expert System Architecture for Rocket Engine Numerical Simulators.

Beyond Re/Presentation: A Case for Updating the Epistemology of Schooling

ERIC Educational Resources Information Center

Biesta, Gert J. J.; Osberg, Deborah

2007-01-01

In this paper we wish to argue that despite strong challenges to representational epistemology in the last two centuries, modern schooling is still organised around a representational view of knowledge. This is the case despite teaching practices being modified to accommodate different views of knowledge that have emerged in the last two…

Why Use Multiple Representations in the Mathematics Classroom? Views of English and German Preservice Teachers

ERIC Educational Resources Information Center

Dreher, Anika; Kuntze, Sebastian; Lerman, Stephen

2016-01-01

Dealing with multiple representations and their connections plays a key role for learners to build up conceptual knowledge in the mathematics classroom. Hence, professional knowledge and views of mathematics teachers regarding the use of multiple representations certainly merit attention. In particular, investigating such views of preservice…

Formal ontologies in biomedical knowledge representation.

PubMed

Schulz, S; Jansen, L

2013-01-01

Medical decision support and other intelligent applications in the life sciences depend on increasing amounts of digital information. Knowledge bases as well as formal ontologies are being used to organize biomedical knowledge and data. However, these two kinds of artefacts are not always clearly distinguished. Whereas the popular RDF(S) standard provides an intuitive triple-based representation, it is semantically weak. Description logics based ontology languages like OWL-DL carry a clear-cut semantics, but they are computationally expensive, and they are often misinterpreted to encode all kinds of statements, including those which are not ontological. We distinguish four kinds of statements needed to comprehensively represent domain knowledge: universal statements, terminological statements, statements about particulars and contingent statements. We argue that the task of formal ontologies is solely to represent universal statements, while the non-ontological kinds of statements can nevertheless be connected with ontological representations. To illustrate these four types of representations, we use a running example from parasitology. We finally formulate recommendations for semantically adequate ontologies that can efficiently be used as a stable framework for more context-dependent biomedical knowledge representation and reasoning applications like clinical decision support systems.

Research on knowledge representation, machine learning, and knowledge acquisition

NASA Technical Reports Server (NTRS)

Buchanan, Bruce G.

1987-01-01

Research in knowledge representation, machine learning, and knowledge acquisition performed at Knowledge Systems Lab. is summarized. The major goal of the research was to develop flexible, effective methods for representing the qualitative knowledge necessary for solving large problems that require symbolic reasoning as well as numerical computation. The research focused on integrating different representation methods to describe different kinds of knowledge more effectively than any one method can alone. In particular, emphasis was placed on representing and using spatial information about three dimensional objects and constraints on the arrangement of these objects in space. Another major theme is the development of robust machine learning programs that can be integrated with a variety of intelligent systems. To achieve this goal, learning methods were designed, implemented and experimented within several different problem solving environments.

Elementary student teachers' science content representations

NASA Astrophysics Data System (ADS)

Zembal-Saul, Carla; Krajcik, Joseph; Blumenfeld, Phyllis

2002-08-01

This purpose of this study was to examine the ways in which three prospective teachers who had early opportunities to teach science would approach representing science content within the context of their student teaching experiences. The study is framed in the literature on pedagogical content knowledge and learning to teach. A situated perspective on cognition is applied to better understand the influence of context and the role of the cooperating teacher. The three participants were enrolled in an experimental teacher preparation program designed to enhance the teaching of science at the elementary level. Qualitative case study design guided the collection, organization, and analysis of data. Multiple forms of data associated with student teachers' content representations were collected, including audiotaped planning and reflection interviews, written lesson plans and reflections, and videotaped teaching experiences. Broad analysis categories were developed and refined around the subconstructs of content representation (i.e., knowledge of instructional strategies that promote learning and knowledge of students and their requirements for meaningful science learning). Findings suggest that when prospective teachers are provided with opportunities to apply and reflect substantively on their developing considerations for supporting children's science learning, they are able to maintain a subject matter emphasis. However, in the absence of such opportunities, student teachers abandon their subject matter emphasis, even when they have had extensive background and experiences addressing subject-specific considerations for teaching and learning.

Sparsest representations and approximations of an underdetermined linear system

NASA Astrophysics Data System (ADS)

Tardivel, Patrick J. C.; Servien, Rémi; Concordet, Didier

2018-05-01

In an underdetermined linear system of equations, constrained l 1 minimization methods such as the basis pursuit or the lasso are often used to recover one of the sparsest representations or approximations of the system. The null space property is a sufficient and ‘almost’ necessary condition to recover a sparsest representation with the basis pursuit. Unfortunately, this property cannot be easily checked. On the other hand, the mutual coherence is an easily checkable sufficient condition insuring the basis pursuit to recover one of the sparsest representations. Because the mutual coherence condition is too strong, it is hardly met in practice. Even if one of these conditions holds, to our knowledge, there is no theoretical result insuring that the lasso solution is one of the sparsest approximations. In this article, we study a novel constrained problem that gives, without any condition, one of the sparsest representations or approximations. To solve this problem, we provide a numerical method and we prove its convergence. Numerical experiments show that this approach gives better results than both the basis pursuit problem and the reweighted l 1 minimization problem.

Design of Computer-aided Instruction for Radiology Interpretation: The Role of Cognitive Task Analysis

PubMed Central

Pusic, Martin V.; LeBlanc, Vicki; Patel, Vimla L.

2001-01-01

Traditional task analysis for instructional design has emphasized the importance of precisely defining behavioral educational objectives and working back to select objective-appropriate instructional strategies. However, this approach may miss effective strategies. Cognitive task analysis, on the other hand, breaks a process down into its component knowledge representations. Selection of instructional strategies based on all such representations in a domain is likely to lead to optimal instructional design. In this demonstration, using the interpretation of cervical spine x-rays as an educational example, we show how a detailed cognitive task analysis can guide the development of computer-aided instruction.

Pedagogy and the Art of Death: Reparative Readings of Death and Dying in Margaret Edson's Wit.

PubMed

Gottlieb, Christine M

2015-11-19

Wit explores modes of reading representations of death and dying, both through the play's sustained engagement with Donne's Holy Sonnets and through Vivian's self-reflexive approach to her illness and death. I argue that the play dramatizes reparative readings, a term coined by Eve Kosofsky Sedgwick to describe an alternative to the paranoid reading practices that have come to dominate literary criticism. By analyzing the play's reparative readings of death and dying (as well as its representation of the shortcomings of paranoid readings), I show how Wit provides lessons about knowledge-making and reading practices in the field of health humanities.

Structured Semantic Knowledge Can Emerge Automatically from Predicting Word Sequences in Child-Directed Speech

PubMed Central

Huebner, Philip A.; Willits, Jon A.

2018-01-01

Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory) to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM) and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing semantic system. PMID:29520243

A knowledge base of the chemical compounds of intermediary metabolism.

PubMed

Karp, P D

1992-08-01

This paper describes a publicly available knowledge base of the chemical compounds involved in intermediary metabolism. We consider the motivations for constructing a knowledge base of metabolic compounds, the methodology by which it was constructed, and the information that it currently contains. Currently the knowledge base describes 981 compounds, listing for each: synonyms for its name, a systematic name, CAS registry number, chemical formula, molecular weight, chemical structure and two-dimensional display coordinates for the structure. The Compound Knowledge Base (CompoundKB) illustrates several methodological principles that should guide the development of biological knowledge bases. I argue that biological datasets should be made available in multiple representations to increase their accessibility to end users, and I present multiple representations of the CompoundKB (knowledge base, relational data base and ASN. 1 representations). I also analyze the general characteristics of these representations to provide an understanding of their relative advantages and disadvantages. Another principle is that the error rate of biological data bases should be estimated and documented-this analysis is performed for the CompoundKB.

Semantic representation of CDC-PHIN vocabulary using Simple Knowledge Organization System.

PubMed

Zhu, Min; Mirhaji, Parsa

2008-11-06

PHIN Vocabulary Access and Distribution System (VADS) promotes the use of standards based vocabulary within CDC information systems. However, the current PHIN vocabulary representation hinders its wide adoption. Simple Knowledge Organization System (SKOS) is a W3C draft specification to support the formal representation of Knowledge Organization Systems (KOS) within the framework of the Semantic Web. We present a method of adopting SKOS to represent PHIN vocabulary in order to enable automated information sharing and integration.

A Representational Approach to Knowledge and Multiple Skill Levels for Broad Classes of Computer Generated Forces

DTIC Science & Technology

1997-12-01

that I’ll turn my attention to that computer game we’ve talked so much about... Dave Van Veldhuizen and Scott Brown (soon-to-be Drs. Van Veldhuizen and...Industry Training Systems Conference. 1988. 37. Van Veldhuizen , D. A. and L. J Hutson. "A Design Methodology for Domain Inde- pendent Computer...proposed by Van Veld- huizen and Hutson (37), extends the general architecture to support both a domain- independent approach to implementing CGFs and

[Representations of the body: with the word one group of adolescents from popular classes].

PubMed

Braga, Patrícia Déa; Molina, Maria del Carmen Bisi; de Figueiredo, Túlio Alberto Martins

2010-01-01

In view of the great body aesthetic concern demonstrated by a group of adolescents from popular classes, this study had the purpose of getting to know and analyze the social representations of the body. It investigated the qualitative approach carried out with adolescent workers from the Centro Salesiano do Menor, in Vitória, Espírito Santo State. A random sample was selected from a group of 334 individuals. Eight girls and seven boys were approached by means of non-structured interview. From the analysis of their speeches, a categorization was performed and the theory of the Social Representations was used for discussion. The results pointed out that body perception, for boys as well as for girls, are focused on the ideas of proportionality, normality and perfection. Regarding the consequences of not having an ideal body, both stated situations such as: exclusion, illnesses, unhappiness and even death. In-depth knowledge on opinion, thoughts and feelings of the adolescents relative to the body, may contribute to subside interventions in this group, extending significantly the scope of professional performance in the health sector.

Examining the Influences of Epistemic Beliefs and Knowledge Representations on Cognitive Processing and Conceptual Change When Learning Physics

ERIC Educational Resources Information Center

Franco, Gina M.; Muis, Krista R.; Kendeou, Panayiota; Ranellucci, John; Sampasivam, Lavanya; Wang, Xihui

2012-01-01

The purpose of this study was to investigate the role of epistemic beliefs and knowledge representations in cognitive and metacognitive processing when learning about physics concepts through text. Specifically, we manipulated the representation of physics concepts in texts about Newtonian mechanics and explored how these texts interacted with…

Students and Teacher Academic Evaluation Perceptions: Methodology to Construct a Representation Based on Actionable Knowledge Discovery Framework

ERIC Educational Resources Information Center

Molina, Otilia Alejandro; Ratté, Sylvie

2017-01-01

This research introduces a method to construct a unified representation of teachers and students perspectives based on the actionable knowledge discovery (AKD) and delivery framework. The representation is constructed using two models: one obtained from student evaluations and the other obtained from teachers' reflections about their teaching…

The Effects of Idealized and Grounded Materials on Learning, Transfer, and Interest: An Organizing Framework for Categorizing External Knowledge Representations

ERIC Educational Resources Information Center

Belenky, Daniel M.; Schalk, Lennart

2014-01-01

Research in both cognitive and educational psychology has explored the effect of different types of external knowledge representations (e.g., manipulatives, graphical/pictorial representations, texts) on a variety of important outcome measures. We place this large and multifaceted research literature into an organizing framework, classifying three…

Making Connections among Multiple Visual Representations: How Do Sense-Making Skills and Perceptual Fluency Relate to Learning of Chemistry Knowledge?

ERIC Educational Resources Information Center

Rau, Martina A.

2018-01-01

To learn content knowledge in science, technology, engineering, and math domains, students need to make connections among visual representations. This article considers two kinds of connection-making skills: (1) "sense-making skills" that allow students to verbally explain mappings among representations and (2) "perceptual…

Knowledge representation by connection matrices: A method for the on-board implementation of large expert systems

NASA Technical Reports Server (NTRS)

Kellner, A.

1987-01-01

Extremely large knowledge sources and efficient knowledge access characterizing future real-life artificial intelligence applications represent crucial requirements for on-board artificial intelligence systems due to obvious computer time and storage constraints on spacecraft. A type of knowledge representation and corresponding reasoning mechanism is proposed which is particularly suited for the efficient processing of such large knowledge bases in expert systems.

Knowledge Synthesis with Maps of Neural Connectivity

PubMed Central

Tallis, Marcelo; Thompson, Richard; Russ, Thomas A.; Burns, Gully A. P. C.

2011-01-01

This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called “Knowledge Engineering from Experimental Design” (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features. PMID:22053155

The Role of Meaning in Inflection: Why the Past Tense Does Not Require a Rule

ERIC Educational Resources Information Center

Ramscar, Michael

2002-01-01

How do we produce the past tenses of verbs? For the last 20 years this question has been the focal domain for conflicting theories of language, knowledge representation, and cognitive processing. On one side of the debate have been similarity-based or single-route approaches that propose that all past tenses are formed simply through phonological…

Looking and Touching: What Extant Approaches Reveal about the Structure of Early Word Knowledge

ERIC Educational Resources Information Center

Hendrickson, Kristi; Mitsven, Samantha; Poulin-Dubois, Diane; Zesiger, Pascal; Friend, Margaret

2015-01-01

The goal of the current study is to assess the temporal dynamics of vision and action to evaluate the underlying word representations that guide infants' responses. Sixteen-month-old infants participated in a two-alternative forced-choice word-picture matching task. We conducted a moment-by-moment analysis of looking and reaching behaviors as they…

Scholarisation, Apprenticeship and Social Differentiation. Analysis of the Non-Industrial Craft Sector in Morocco

ERIC Educational Resources Information Center

Gerard, Etienne

2012-01-01

The article approaches the question of the schooling processes in the particular environment of the Moroccan craftsmen of Fez. It shows that the weak schooling of the children is bound to the representations and to the ways of transmission of craft industry knowledge. Schooling is, indeed, the object of tensions between a school system of western…

Representation of AIDS in Televised Public Service Announcements: The Discursive Practices of Government in the Constitution of Knowledge about AIDS.

ERIC Educational Resources Information Center

Myrick, Roger; And Others

Using a textualist approach (looking at meaning above and beyond overt message elements), a study examined televised public service announcements (PSAs) about Acquired Immune Deficiency Syndrome (AIDS) produced by the Ad Council and the United States Department of Health and Human Services. Both ads identify young people who should be concerned…

Children's knowledge of the earth: a new methodological and statistical approach.

PubMed

Straatemeier, Marthe; van der Maas, Han L J; Jansen, Brenda R J

2008-08-01

In the field of children's knowledge of the earth, much debate has concerned the question of whether children's naive knowledge-that is, their knowledge before they acquire the standard scientific theory-is coherent (i.e., theory-like) or fragmented. We conducted two studies with large samples (N=328 and N=381) using a new paper-and-pencil test, denoted the EARTH (EArth Representation Test for cHildren), to discriminate between these two alternatives. We performed latent class analyses on the responses to the EARTH to test mental models associated with these alternatives. The naive mental models, as formulated by Vosniadou and Brewer, were not supported by the results. The results indicated that children's knowledge of the earth becomes more consistent as children grow older. These findings support the view that children's naive knowledge is fragmented.

MedRapid--medical community & business intelligence system.

PubMed

Finkeissen, E; Fuchs, H; Jakob, T; Wetter, T

2002-01-01

currently, it takes at least 6 months for researchers to communicate their results. This delay is caused (a) by partial lacks of machine support for both representation as well as communication and (b) by media breaks during the communication process. To make an integrated communication between researchers and practitioners possible, a general structure for medical content representation has been set up. The procedure for data entry and quality management has been generalized and implemented in a web-based authoring system. The MedRapid-system supports the medical experts in entering their knowledge into a database. Here, the level of detail is still below that of current medical guidelines representation. However, the symmetric structure for an area-wide medical knowledge representation is highly retrievable and thus can quickly be communicated into daily routine for the improvement of the treatment quality. In addition, other sources like journal articles and medical guidelines can be references within the MedRapid-system and thus be communicated into daily routine. The fundamental system for the representation of medical reference knowledge (from reference works/books) itself is not sufficient for the friction-less communication amongst medical staff. Rather, the process of (a) representing medical knowledge, (b) refereeing the represented knowledge, (c) communicating the represented knowledge, and (d) retrieving the represented knowledge has to be unified. MedRapid will soon support the whole process on one server system.

Seeing The "New Forest": A Visual Curricular Experiment

NASA Astrophysics Data System (ADS)

Garramone, Pariss Nicola

In contemporary Western contexts, human interaction with and interpretation of nature is a perpetually mediated process. Understandings and engagements with natural environments are informed by and often overlaid with meanings derived from representations. In other words, representations help constitute human relationships with nature. Thus learning how representations shape human understandings and experiences of nature and the resulting social, political, and ecological impact of these mediated relationships has emerged as an important field of inquiry within environmental education. This dissertation examines how a critical, self-reflexive act of looking at photographs can challenge an individual's concepts of nature/culture, real/imaginary, and self/other. The project engages in a curricular experiment where the researcher explores how photography meditates her abstract and embodied understandings of specific natural environments. A critical, self-reflexive approach to aesthetic engagement with photographs moves beyond simply deciphering or decoding representations; it incorporates the learner's own narrative and embodied responses to the photographic representations being explored. This approach also recognizes that pedagogy has a transformative effect; both the learner and the representations being explored are transformed through the process of engagement. In this dissertation, a selection of iconic photographs of Canadian tree planting from the collection of the National Gallery of Canada are looked at: Lorraine Gilbert's (1987-2004) series "Shaping the New Forest" and Sarah Anne Johnson's (2005) work "The Tree Planting Project." The aim of this project is twofold: to unravel how these photographs construct and transform knowledge of and relationships with the environment in Canada, and to demonstrate a model of environmental inquiry that can be integrated into critical environmental education curricula.

Influence of the Digital Anatomist Foundational Model on traditional representations of anatomical concepts.

PubMed

Agoncillo, A V; Mejino, J L; Rosse, C

1999-01-01

A principled and logical representation of the structure of the human body has led to conflicts with traditional representations of the same knowledge by anatomy textbooks. The examples which illustrate resolution of these conflicts suggest that stricter requirements must be met for semantic consistency, expressivity and specificity by knowledge sources intended to support inference than by textbooks and term lists. These next-generation resources should influence traditional concept representation, rather than be constrained by convention.

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

NASA Astrophysics Data System (ADS)

Jacobs, Clifford

2011-03-01

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

Semantic Clinical Guideline Documents

PubMed Central

Eriksson, Henrik; Tu, Samson W.; Musen, Mark

2005-01-01

Decision-support systems based on clinical practice guidelines can support physicians and other health-care personnel in the process of following best practice consistently. A knowledge-based approach to represent guidelines makes it possible to encode computer-interpretable guidelines in a formal manner, perform consistency checks, and use the guidelines directly in decision-support systems. Decision-support authors and guideline users require guidelines in human-readable formats in addition to computer-interpretable ones (e.g., for guideline review and quality assurance). We propose a new document-oriented information architecture that combines knowledge-representation models with electronic and paper documents. The approach integrates decision-support modes with standard document formats to create a combined clinical-guideline model that supports on-line viewing, printing, and decision support. PMID:16779037

How to Make a Good Animation: A Grounded Cognition Model of How Visual Representation Design Affects the Construction of Abstract Physics Knowledge

ERIC Educational Resources Information Center

Chen, Zhongzhou; Gladding, Gary

2014-01-01

Visual representations play a critical role in teaching physics. However, since we do not have a satisfactory understanding of how visual perception impacts the construction of abstract knowledge, most visual representations used in instructions are either created based on existing conventions or designed according to the instructor's intuition,…

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.

Modeling a flexible representation machinery of human concept learning.

PubMed

Matsuka, Toshihiko; Sakamoto, Yasuaki; Chouchourelou, Arieta

2008-01-01

It is widely acknowledged that categorically organized abstract knowledge plays a significant role in high-order human cognition. Yet, there are many unknown issues about the nature of how categories are internally represented in our mind. Traditionally, it has been considered that there is a single innate internal representation system for categorical knowledge, such as Exemplars, Prototypes, or Rules. However, results of recent empirical and computational studies collectively suggest that the human internal representation system is apparently capable of exhibiting behaviors consistent with various types of internal representation schemes. We, then, hypothesized that humans' representational system as a dynamic mechanism, capable of selecting a representation scheme that meets situational characteristics, including complexities of category structure. The present paper introduces a framework for a cognitive model that integrates robust and flexible internal representation machinery. Three simulation studies were conducted. The results showed that SUPERSET, our new model, successfully exhibited cognitive behaviors that are consistent with three main theories of the human internal representation system. Furthermore, a simulation study on social cognitive behaviors showed that the model was capable of acquiring knowledge with high commonality, even for a category structure with numerous valid conceptualizations.

Psychology of knowledge representation.

PubMed

Grimm, Lisa R

2014-05-01

Every cognitive enterprise involves some form of knowledge representation. Humans represent information about the external world and internal mental states, like beliefs and desires, and use this information to meet goals (e.g., classification or problem solving). Unfortunately, researchers do not have direct access to mental representations. Instead, cognitive scientists design experiments and implement computational models to develop theories about the mental representations present during task performance. There are several main types of mental representation and corresponding processes that have been posited: spatial, feature, network, and structured. Each type has a particular structure and a set of processes that are capable of accessing and manipulating information within the representation. The structure and processes determine what information can be used during task performance and what information has not been represented at all. As such, the different types of representation are likely used to solve different kinds of tasks. For example, structured representations are more complex and computationally demanding, but are good at representing relational information. Researchers interested in human psychology would benefit from considering how knowledge is represented in their domain of inquiry. For further resources related to this article, please visit the WIREs website. The author has declared no conflicts of interest for this article. © 2014 John Wiley & Sons, Ltd.

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

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

32 CFR 776.20 - Competence.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., and prompt representation to a client. Competent representation requires the legal knowledge, skill, access to evidence, thoroughness, and expeditious preparation reasonably necessary for representation...

32 CFR 776.20 - Competence.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., and prompt representation to a client. Competent representation requires the legal knowledge, skill, access to evidence, thoroughness, and expeditious preparation reasonably necessary for representation...

32 CFR 776.20 - Competence.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., and prompt representation to a client. Competent representation requires the legal knowledge, skill, access to evidence, thoroughness, and expeditious preparation reasonably necessary for representation...

32 CFR 776.20 - Competence.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., and prompt representation to a client. Competent representation requires the legal knowledge, skill, access to evidence, thoroughness, and expeditious preparation reasonably necessary for representation...

A knowledge-based machine vision system for space station automation

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

Visual Representation in Mathematics: Special Education Teachers' Knowledge and Emphasis for Instruction

ERIC Educational Resources Information Center

van Garderen, Delinda; Scheuermann, Amy; Poch, Apryl; Murray, Mary M.

2018-01-01

The use of visual representations (VRs) in mathematics is a strongly recommended practice in special education. Although recommended, little is known about special educators' knowledge of and instructional emphasis about VRs. Therefore, in this study, the authors examined special educators' own knowledge of and their instructional emphasis with…

Knowledge representation issues for explaining plans

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen; Johannes, James D.

1988-01-01

Explanations are recognized as an important facet of intelligent behavior. Unfortunately, expert systems are currently limited in their ability to provide useful, intelligent justifications of their results. We are currently investigating the issues involved in providing explanation facilities for expert planning systems. This investigation addresses three issues: knowledge content, knowledge representation, and explanation structure.

What Does Knowledge Look Like? Drawing as a Means of Knowledge Representation and Knowledge Construction

ERIC Educational Resources Information Center

Bowen, Tracey; Evans, M. Max

2015-01-01

The most common tools individuals use to articulate complex and abstract concepts are writing and spoken language, long privileged as primary forms of communication. However, our, explanations of these concepts may be more aptly communicated through visual means, such as drawings. Interpreting and analyzing abstract graphic representations is…

The representation of semantic knowledge in a child with Williams syndrome.

PubMed

Robinson, Sally J; Temple, Christine M

2009-05-01

This study investigated whether there are distinct types of semantic knowledge with distinct representational bases during development. The representation of semantic knowledge in a teenage child (S.T.) with Williams syndrome was explored for the categories of animals, fruit, and vegetables, manipulable objects, and nonmanipulable objects. S.T.'s lexical stores were of a normal size but the volume of "sensory feature" semantic knowledge she generated in oral descriptions was reduced. In visual recognition decisions, S.T. made more false positives to nonitems than did controls. Although overall naming of pictures was unimpaired, S.T. exhibited a category-specific anomia for nonmanipulable objects and impaired naming of visual-feature descriptions of animals. S.T.'s performance was interpreted as reflecting the impaired integration of distinctive features from perceptual input, which may impact upon nonmanipulable objects to a greater extent than the other knowledge categories. Performance was used to inform adult-based models of semantic representation, with category structure proposed to emerge due to differing degrees of dependency upon underlying knowledge types, feature correlations, and the acquisition of information from modality-specific processing modules.

37 CFR 11.101 - Competence.

Code of Federal Regulations, 2013 CFR

2013-07-01

... competent representation to a client. Competent representation requires the legal, scientific, and technical knowledge, skill, thoroughness and preparation reasonably necessary for the representation. ... COMMERCE REPRESENTATION OF OTHERS BEFORE THE UNITED STATES PATENT AND TRADEMARK OFFICE USPTO Rules of...

37 CFR 11.101 - Competence.

Code of Federal Regulations, 2014 CFR

2014-07-01

... competent representation to a client. Competent representation requires the legal, scientific, and technical knowledge, skill, thoroughness and preparation reasonably necessary for the representation. ... COMMERCE REPRESENTATION OF OTHERS BEFORE THE UNITED STATES PATENT AND TRADEMARK OFFICE USPTO Rules of...

Associations of Postural Knowledge and Basic Motor Skill with Dyspraxia in Autism: Implication for Abnormalities in Distributed Connectivity and Motor Learning

PubMed Central

Dowell, Lauren R.; Mahone, E. Mark; Mostofsky, Stewart H.

2009-01-01

Children with autism often have difficulty performing skilled movements. Praxis performance requires basic motor skill, knowledge of representations of the movement (mediated by parietal regions), and transcoding of these representations into movement plans (mediated by premotor circuits). The goals of this study were: (a) to determine whether dyspraxia in autism is associated with impaired representational (“postural”) knowledge, and (b) to examine the contributions of postural knowledge and basic motor skill to dyspraxia in autism. Thirty-seven children with autism spectrum disorder (ASD) and 50 typically developing (TD) children, ages 8–13, completed: (a) an examination of basic motor skills, (b) a postural knowledge test assessing praxis discrimination, and (c) a praxis examination. Children with ASD showed worse basic motor skill and postural knowledge than controls. The ASD group continued to show significantly poorer praxis than controls after accounting for age, IQ, basic motor skill, and postural knowledge. Dyspraxia in autism appears to be associated with impaired formation of spatial representations, as well as transcoding and execution. Distributed abnormality across parietal, premotor, and motor circuitry, as well as anomalous connectivity may be implicated. PMID:19702410

Knowledge From Pictures (KFP)

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Paterra, Frank; Bailin, Sidney

1993-01-01

The old maxim goes: 'A picture is worth a thousand words'. The objective of the research reported in this paper is to demonstrate this idea as it relates to the knowledge acquisition process and the automated development of an expert system's rule base. A prototype tool, the Knowledge From Pictures (KFP) tool, has been developed which configures an expert system's rule base by an automated analysis of and reasoning about a 'picture', i.e., a graphical representation of some target system to be supported by the diagnostic capabilities of the expert system under development. This rule base, when refined, could then be used by the expert system for target system monitoring and fault analysis in an operational setting. Most people, when faced with the problem of understanding the behavior of a complicated system, resort to the use of some picture or graphical representation of the system as an aid in thinking about it. This depiction provides a means of helping the individual to visualize the bahavior and dynamics of the system under study. An analysis of the picture augmented with the individual's background information, allows the problem solver to codify knowledge about the system. This knowledge can, in turn, be used to develop computer programs to automatically monitor the system's performance. The approach taken is this research was to mimic this knowledge acquisition paradigm. A prototype tool was developed which provides the user: (1) a mechanism for graphically representing sample system-configurations appropriate for the domain, and (2) a linguistic device for annotating the graphical representation with the behaviors and mutual influences of the components depicted in the graphic. The KFP tool, reasoning from the graphical depiction along with user-supplied annotations of component behaviors and inter-component influences, generates a rule base that could be used in automating the fault detection, isolation, and repair of the system.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

Knowledge inhibition and N400: a study with words that look like common words.

PubMed

Debruille, J B

1998-04-01

In addition to their own representations, low frequency words, such as BRIBE, can covertly activate the representations of higher frequency words they look like (e.g., BRIDE). Hence, look-alike words can activate knowledge that is incompatible with the knowledge corresponding to accurate representations. Comparatively, eccentric words, that is, low frequency words that do not look as much like higher frequency words, are less likely to activate incompatible knowledge. This study focuses on the hypothesis that the N400 component of the event-related potential reflects the inhibition of incompatible knowledge. This hypothesis predicts that look-alike words elicit N400s of greater amplitudes than eccentric words in conditions where incompatible knowledge is inhibited. Results from a single item lexical decision experiment are reported which support the inhibition hypothesis. Copyright 1998 Academic Press.

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

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

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.

Origins of Secure Base Script Knowledge and the Developmental Construction of Attachment Representations

PubMed Central

Waters, Theodore E. A.; Ruiz, Sarah K.; Roisman, Glenn I.

2016-01-01

Increasing evidence suggests that attachment representations take at least two forms—a secure base script and an autobiographical narrative of childhood caregiving experiences. This study presents data from the first 26 years of the Minnesota Longitudinal Study of Risk and Adaptation (N = 169), examining the developmental origins of secure base script knowledge in a high-risk sample, and testing alternative models of the developmental sequencing of the construction of attachment representations. Results demonstrated that secure base script knowledge was predicted by observations of maternal sensitivity across childhood and adolescence. Further, findings suggest that the construction of a secure base script supports the development of a coherent autobiographical representation of childhood attachment experiences with primary caregivers by early adulthood. PMID:27302650

Bayesian Networks for Modeling Dredging Decisions

DTIC Science & Technology

2011-10-01

change scenarios. Arctic Expert elicitation Netica Bacon et al . 2002 Identify factors that might lead to a change in land use from farming to...tree) algorithms developed by Lauritzen and Spiegelhalter (1988) and Jensen et al . (1990). Statistical inference is simply the process of...causality when constructing a Bayesian network (Kjaerulff and Madsen 2008, Darwiche 2009, Marcot et al . 2006). A knowledge representation approach is the

Asymmetric Warfare in the Simulation and Training Environment: Comprehensive Approach Wanted!

DTIC Science & Technology

2009-10-01

Covering Support to Operations, Human Behaviour Representation, Irregular Warfare, Defence against Terrorism and Coalition Tactical Force Integration...learned behaviours arising from shared knowledge and it is passed on from one generation to the next. The behaviours that have become embedded as part of...symbols and behaviours . While culture changes, the change is usually slow, particularly in terms of military operations timeframes. Urban environments

The Effects of the SUN Project on Teacher Knowledge and Self-Efficacy regarding Biological Energy Transfer Are Significant and Long-Lasting: Results of a Randomized Controlled Trial

ERIC Educational Resources Information Center

Batiza, Ann Finney; Gruhl, Mary; Zhang, Bo; Harrington, Tom; Roberts, Marisa; LaFlamme, Donna; Haasch, Mary Anne; Knopp, Jonathan; Vogt, Gina; Goodsell, David; Hagedorn, Eric; Marcey, David; Hoelzer, Mark; Nelson, Dave

2013-01-01

Biological energy flow has been notoriously difficult to teach. Our approach to this topic relies on abiotic and biotic examples of the energy released by moving electrons in thermodynamically spontaneous reactions. A series of analogical model-building experiences was supported with common language and representations including manipulatives.…

Abjection and Alterity in the Imagining of Transgender in Physical Education and Sport: A Pedagogical Approach in Higher Education

ERIC Educational Resources Information Center

Pérez-Samaniego, Víctor; Fuentes-Miguel, Jorge; Pereira-García, Sofía; Devís-Devís, José

2016-01-01

In physical education (PE) and sports there is little theoretical and empirical knowledge about transgender people, and particularly, on how they are and can be imagined within this context. In this paper, we present and analyze a pedagogical activity based on the reading and discussion of a fictional representation of a transgender person within…

Attitudes toward evaluation: An exploratory study of students' and stakeholders' social representations.

PubMed

Schultes, Marie-Therese; Kollmayer, Marlene; Mejeh, Mathias; Spiel, Christiane

2018-06-15

Positive attitudes toward evaluation among stakeholders are an important precondition for successful evaluation processes. However, empirical studies focusing on stakeholders' attitudes toward evaluation are scarce. The present paper explores the approach of assessing social representations as indicators of people's attitudes toward evaluation. In an exploratory study, two groups were surveyed: University students (n = 60) with rather theoretical knowledge of evaluation and stakeholders (n = 61) who had shortly before taken part in participatory evaluation studies. Both groups were asked to name their free associations with the term "evaluation", which were subsequently analyzed lexicographically. The results indicate different social representations of evaluation in the two groups. The student group primarily saw evaluation as an "appraisal", whereas the stakeholders emphasized the "improvement" resulting from evaluation. Implications for further evaluation research and practice are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Big data in medical informatics: improving education through visual analytics.

PubMed

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2014-01-01

A continuous effort to improve healthcare education today is currently driven from the need to create competent health professionals able to meet healthcare demands. Limited research reporting how educational data manipulation can help in healthcare education improvement. The emerging research field of visual analytics has the advantage to combine big data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognise visual patterns. The aim of this study was therefore to explore novel ways of representing curriculum and educational data using visual analytics. Three approaches of visualization and representation of educational data were presented. Five competencies at undergraduate medical program level addressed in courses were identified to inaccurately correspond to higher education board competencies. Different visual representations seem to have a potential in impacting on the ability to perceive entities and connections in the curriculum data.

My Corporis Fabrica Embryo: An ontology-based 3D spatio-temporal modeling of human embryo development.

PubMed

Rabattu, Pierre-Yves; Massé, Benoit; Ulliana, Federico; Rousset, Marie-Christine; Rohmer, Damien; Léon, Jean-Claude; Palombi, Olivier

2015-01-01

Embryology is a complex morphologic discipline involving a set of entangled mechanisms, sometime difficult to understand and to visualize. Recent computer based techniques ranging from geometrical to physically based modeling are used to assist the visualization and the simulation of virtual humans for numerous domains such as surgical simulation and learning. On the other side, the ontology-based approach applied to knowledge representation is more and more successfully adopted in the life-science domains to formalize biological entities and phenomena, thanks to a declarative approach for expressing and reasoning over symbolic information. 3D models and ontologies are two complementary ways to describe biological entities that remain largely separated. Indeed, while many ontologies providing a unified formalization of anatomy and embryology exist, they remain only descriptive and make the access to anatomical content of complex 3D embryology models and simulations difficult. In this work, we present a novel ontology describing the development of the human embryology deforming 3D models. Beyond describing how organs and structures are composed, our ontology integrates a procedural description of their 3D representations, temporal deformation and relations with respect to their developments. We also created inferences rules to express complex connections between entities. It results in a unified description of both the knowledge of the organs deformation and their 3D representations enabling to visualize dynamically the embryo deformation during the Carnegie stages. Through a simplified ontology, containing representative entities which are linked to spatial position and temporal process information, we illustrate the added-value of such a declarative approach for interactive simulation and visualization of 3D embryos. Combining ontologies and 3D models enables a declarative description of different embryological models that capture the complexity of human developmental anatomy. Visualizing embryos with 3D geometric models and their animated deformations perhaps paves the way towards some kind of hypothesis-driven application. These can also be used to assist the learning process of this complex knowledge. http://www.mycorporisfabrica.org/.

Adaptive windowing and windowless approaches to estimate dynamic functional brain connectivity

NASA Astrophysics Data System (ADS)

Yaesoubi, Maziar; Calhoun, Vince D.

2017-08-01

In this work, we discuss estimation of dynamic dependence of a multi-variate signal. Commonly used approaches are often based on a locality assumption (e.g. sliding-window) which can miss spontaneous changes due to blurring with local but unrelated changes. We discuss recent approaches to overcome this limitation including 1) a wavelet-space approach, essentially adapting the window to the underlying frequency content and 2) a sparse signal-representation which removes any locality assumption. The latter is especially useful when there is no prior knowledge of the validity of such assumption as in brain-analysis. Results on several large resting-fMRI data sets highlight the potential of these approaches.

[The representation of care in the cultural image of nursing].

PubMed

Vieira, M J

1999-12-01

We analyzed Sergipan nurses' life stories, related to the cultural image of Nursing perceived in their professional choice, in order to assist students in this professional identification. Subjects were divided into four chronological groups, from retired nurses to those who had been graduated for 5 years, all of whom chose Nursing as their preferred career. We used the Social Representation approach in the cultural systems to analyze the life stories. Findings were analyzed through categories and themes, and it was presented by graphics and tables. Care was identified as a permanent cultural trace and it was verbalized using words from charity, religion to scientific Nursing and professionalism, to describe scientific knowledge and humanism, with temporal configuration.

Cloud Model Bat Algorithm

PubMed Central

Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi

2014-01-01

Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425

On the representation matrices of the spin permutation group. [for atomic and molecular electronic structures

NASA Technical Reports Server (NTRS)

Wilson, S.

1977-01-01

A method is presented for the determination of the representation matrices of the spin permutation group (symmetric group), a detailed knowledge of these matrices being required in the study of the electronic structure of atoms and molecules. The method is characterized by the use of two different coupling schemes. Unlike the Yamanouchi spin algebraic scheme, the method is not recursive. The matrices for the fundamental transpositions can be written down directly in one of the two bases. The method results in a computationally significant reduction in the number of matrix elements that have to be stored when compared with, say, the standard Young tableaux group theoretical approach.

Preservice Secondary Mathematics Teachers' Development of Mathematical Knowledge for Teaching and Their Use of Knowledge in Their Instruction

ERIC Educational Resources Information Center

Moon, Kyunghee

2013-01-01

This study examined how preservice secondary mathematics teachers developed mathematical knowledge for teaching (MKT) around representations and big ideas through mathematics and mathematics education courses. The importance of big ideas and representations in mathematics has been emphasized in national standards as well as in literature. Yet,…

An Overview of OWL, a Language for Knowledge Representation.

ERIC Educational Resources Information Center

Szolovits, Peter; And Others

This is a description of the motivation and overall organization of the OWL language for knowledge representation. OWL consists of a linguistic memory system (LMS), a memory of concepts in terms of which all English phrases and all knowledge of an application domain are represented; a theory of English grammar which tells how to map English…

[Social and cultural representations in epilepsy awareness].

PubMed

Arborio, Sophie

2015-01-01

Representations relating to epilepsy have evolved over the centuries, but the manifestations of epilepsy awaken archaic images linked to death, violence and disgust. Indeed, the generalised epileptic seizure symbolises a rupture with the surrounding environment, "informs it", through the loss of social codes which it causes. The social and cultural context, as well as medical knowledge, influences the representations of the disease. As a result, popular knowledge is founded on the social and cultural representations of a given era, in a given society. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Knowledge Modeling in Prior Art Search

NASA Astrophysics Data System (ADS)

Graf, Erik; Frommholz, Ingo; Lalmas, Mounia; van Rijsbergen, Keith

This study explores the benefits of integrating knowledge representations in prior art patent retrieval. Key to the introduced approach is the utilization of human judgment available in the form of classifications assigned to patent documents. The paper first outlines in detail how a methodology for the extraction of knowledge from such an hierarchical classification system can be established. Further potential ways of integrating this knowledge with existing Information Retrieval paradigms in a scalable and flexible manner are investigated. Finally based on these integration strategies the effectiveness in terms of recall and precision is evaluated in the context of a prior art search task for European patents. As a result of this evaluation it can be established that in general the proposed knowledge expansion techniques are particularly beneficial to recall and, with respect to optimizing field retrieval settings, further result in significant precision gains.

Using texts in science education: cognitive processes and knowledge representation.

PubMed

van den Broek, Paul

2010-04-23

Texts form a powerful tool in teaching concepts and principles in science. How do readers extract information from a text, and what are the limitations in this process? Central to comprehension of and learning from a text is the construction of a coherent mental representation that integrates the textual information and relevant background knowledge. This representation engenders learning if it expands the reader's existing knowledge base or if it corrects misconceptions in this knowledge base. The Landscape Model captures the reading process and the influences of reader characteristics (such as working-memory capacity, reading goal, prior knowledge, and inferential skills) and text characteristics (such as content/structure of presented information, processing demands, and textual cues). The model suggests factors that can optimize--or jeopardize--learning science from text.

Conceptual model of knowledge base system

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Rough Set Approach to Incomplete Multiscale Information System

PubMed Central

Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu

2014-01-01

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

Representation in Memory.

ERIC Educational Resources Information Center

Rumelhart, David E.; Norman, Donald A.

This paper reviews work on the representation of knowledge from within psychology and artificial intelligence. The work covers the nature of representation, the distinction between the represented world and the representing world, and significant issues concerned with propositional, analogical, and superpositional representations. Specific topics…

Multimodal Literacies in Science: Currency, Coherence and Focus

NASA Astrophysics Data System (ADS)

Klein, Perry D.; Kirkpatrick, Lori C.

2010-01-01

Since the 1990s, researchers have increasingly drawn attention to the multiplicity of representations used in science. This issue of RISE advances this line of research by placing such representations at the centre of science teaching and learning. The authors show that representations do not simply transmit scientific information; they are integral to reasoning about scientific phenomena. This focus on thinking with representations mediates between well-resolved representations and formal reasoning of disciplinary science, and the capacity-limited, perceptually-driven nature of human cognition. The teaching practices described here build on three key principles: Each representation is interpreted through others; natural language is a sign system that is used to interpret a variety of other kinds of representations; and this chain of signs or representations is ultimately grounded in bodily experiences of perception and action. In these papers, the researchers provide examples and analysis of teachers scaffolding students in using representations to construct new knowledge, and in constructing new representations to express and develop their knowledge. The result is a new delineation of the power and the challenges of teaching science with multiple representations.

The effectiveness of multi modal representation text books to improve student's scientific literacy of senior high school students

NASA Astrophysics Data System (ADS)

Zakiya, Hanifah; Sinaga, Parlindungan; Hamidah, Ida

2017-05-01

The results of field studies showed the ability of science literacy of students was still low. One root of the problem lies in the books used in learning is not oriented toward science literacy component. This study focused on the effectiveness of the use of textbook-oriented provisioning capability science literacy by using multi modal representation. The text books development method used Design Representational Approach Learning to Write (DRALW). Textbook design which was applied to the topic of "Kinetic Theory of Gases" is implemented in XI grade students of high school learning. Effectiveness is determined by consideration of the effect and the normalized percentage gain value, while the hypothesis was tested using Independent T-test. The results showed that the textbooks which were developed using multi-mode representation science can improve the literacy skills of students. Based on the size of the effect size textbooks developed with representation multi modal was found effective in improving students' science literacy skills. The improvement was occurred in all the competence and knowledge of scientific literacy. The hypothesis testing showed that there was a significant difference on the ability of science literacy between class that uses textbooks with multi modal representation and the class that uses the regular textbook used in schools.

Investigating Years 7 to 12 students' knowledge of linear relationships through different contexts and representations

NASA Astrophysics Data System (ADS)

Wilkie, Karina J.; Ayalon, Michal

2018-02-01

A foundational component of developing algebraic thinking for meaningful calculus learning is the idea of "function" that focuses on the relationship between varying quantities. Students have demonstrated widespread difficulties in learning calculus, particularly interpreting and modeling dynamic events, when they have a poor understanding of relationships between variables. Yet, there are differing views on how to develop students' functional thinking over time. In the Australian curriculum context, linear relationships are introduced to lower secondary students with content that reflects a hybrid of traditional and reform algebra pedagogy. This article discusses an investigation into Australian secondary students' understanding of linear functional relationships from Years 7 to 12 (approximately 12 to 18 years old; n = 215) in their approaches to three tasks (finding rate of change, pattern generalisation and interpretation of gradient) involving four different representations (table, geometric growing pattern, equation and graph). From the findings, it appears that these students' knowledge of linear functions remains context-specific rather than becoming connected over time.

A Collaborative Reasoning Maintenance System for a Reliable Application of Legislations

NASA Astrophysics Data System (ADS)

Tamisier, Thomas; Didry, Yoann; Parisot, Olivier; Feltz, Fernand

Decision support systems are nowadays used to disentangle all kinds of intricate situations and perform sophisticated analysis. Moreover, they are applied in areas where the knowledge can be heterogeneous, partially un-formalized, implicit, or diffuse. The representation and management of this knowledge become the key point to ensure the proper functioning of the system and keep an intuitive view upon its expected behavior. This paper presents a generic architecture for implementing knowledge-base systems used in collaborative business, where the knowledge is organized into different databases, according to the usage, persistence and quality of the information. This approach is illustrated with Cadral, a customizable automated tool built on this architecture and used for processing family benefits applications at the National Family Benefits Fund of the Grand-Duchy of Luxembourg.

Theoretical foundations for information representation and constraint specification

NASA Technical Reports Server (NTRS)

Menzel, Christopher P.; Mayer, Richard J.

1991-01-01

Research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University is described. Outlined here are the theoretical foundations necessary to construct a Neutral Information Representation Scheme (NIRS), which will allow for automated data transfer and translation between model languages, procedural programming languages, database languages, transaction and process languages, and knowledge representation and reasoning control languages for information system specification.

Semantic knowledge fractionations: verbal propositions vs. perceptual input? Evidence from a child with Klinefelter syndrome.

PubMed

Robinson, Sally J; Temple, Christine M

2013-04-01

This paper addresses the relative independence of different types of lexical- and factually-based semantic knowledge in JM, a 9-year-old boy with Klinefelter syndrome (KS). JM was matched to typically developing (TD) controls on the basis of chronological age. Lexical-semantic knowledge was investigated for common noun (CN) and mathematical vocabulary items (MV). Factually-based semantic knowledge was investigated for general and number facts. For CN items, JM's lexical stores were of a normal size but the volume of correct 'sensory feature' semantic knowledge he generated within verbal item descriptions was significantly reduced. He was also significantly impaired at naming item descriptions and pictures, particularly for fruit and vegetables. There was also weak object decision for fruit and vegetables. In contrast, for MV items, JM's lexical stores were elevated, with no significant difference in the amount and type of correct semantic knowledge generated within verbal item descriptions and normal naming. JM's fact retrieval accuracy was normal for all types of factual knowledge. JM's performance indicated a dissociation between the representation of CN and MV vocabulary items during development. JM's preserved semantic knowledge of facts in the face of impaired semantic knowledge of vocabulary also suggests that factually-based semantic knowledge representation is not dependent on normal lexical-semantic knowledge during development. These findings are discussed in relation to the emergence of distinct semantic knowledge representations during development, due to differing degrees of dependency upon the acquisition and representation of semantic knowledge from verbal propositions and perceptual input.

Information integration from heterogeneous data sources: a Semantic Web approach.

PubMed

Kunapareddy, Narendra; Mirhaji, Parsa; Richards, David; Casscells, S Ward

2006-01-01

Although the decentralized and autonomous implementation of health information systems has made it possible to extend the reach of surveillance systems to a variety of contextually disparate domains, public health use of data from these systems is not primarily anticipated. The Semantic Web has been proposed to address both representational and semantic heterogeneity in distributed and collaborative environments. We introduce a semantic approach for the integration of health data using the Resource Definition Framework (RDF) and the Simple Knowledge Organization System (SKOS) developed by the Semantic Web community.

An AI-based approach to structural damage identification by modal analysis

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hanagud, S.

1990-01-01

Flexible-structure damage is presently addressed by a combined model- and parameter-identification approach which employs the AI methodologies of classification, heuristic search, and object-oriented model knowledge representation. The conditions for model-space search convergence to the best model are discussed in terms of search-tree organization and initial model parameter error. In the illustrative example of a truss structure presented, the use of both model and parameter identification is shown to lead to smaller parameter corrections than would be required by parameter identification alone.

Rigor in electronic health record knowledge representation: Lessons learned from a SNOMED CT clinical content encoding exercise.

PubMed

Monsen, Karen A; Finn, Robert S; Fleming, Thea E; Garner, Erin J; LaValla, Amy J; Riemer, Judith G

2016-01-01

Rigor in clinical knowledge representation is necessary foundation for meaningful interoperability, exchange and reuse of electronic health record (EHR) data. It is critical for clinicians to understand principles and implications of using clinical standards for knowledge representation within EHRs. To educate clinicians and students about knowledge representation and to evaluate their success of applying the manual lookups method for assigning Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) concept identifiers using formally mapped concepts from the Omaha System interface terminology. Clinicians who were students in a doctoral nursing program conducted 21 lookups for Omaha System terms in publicly available SNOMED CT browsers. Lookups were deemed successful if results matched exactly with the corresponding code from the January 2013 SNOMED CT-Omaha System terminology cross-map. Of the 21 manual lookups attempted, 12 (57.1%) were successful. Errors were due to semantic gaps differences in granularity and synonymy or partial term matching. Achieving rigor in clinical knowledge representation across settings, vendors and health systems is a globally recognized challenge. Cross-maps have potential to improve rigor in SNOMED CT encoding of clinical data. Further research is needed to evaluate outcomes of using of terminology cross-maps to encode clinical terms with SNOMED CT concept identifiers based on interface terminologies.

Neural alpha oscillations index the balance between self-other integration and segregation in real-time joint action.

PubMed

Novembre, Giacomo; Sammler, Daniela; Keller, Peter E

2016-08-01

Shared knowledge and interpersonal coordination are prerequisites for most forms of social behavior. Influential approaches to joint action have conceptualized these capacities in relation to the separate constructs of co-representation (knowledge) and self-other entrainment (coordination). Here we investigated how brain mechanisms involved in co-representation and entrainment interact to support joint action. To do so, we used a musical joint action paradigm to show that the neural mechanisms underlying co-representation and self-other entrainment are linked via a process - indexed by EEG alpha oscillations - regulating the balance between self-other integration and segregation in real time. Pairs of pianists performed short musical items while action familiarity and interpersonal (behavioral) synchronization accuracy were manipulated in a factorial design. Action familiarity referred to whether or not pianists had rehearsed the musical material performed by the other beforehand. Interpersonal synchronization was manipulated via congruent or incongruent tempo change instructions that biased performance timing towards the impending, new tempo. It was observed that, when pianists were familiar with each other's parts, millisecond variations in interpersonal synchronized behavior were associated with a modulation of alpha power over right centro-parietal scalp regions. Specifically, high behavioral entrainment was associated with self-other integration, as indexed by alpha suppression. Conversely, low behavioral entrainment encouraged reliance on internal knowledge and thus led to self-other segregation, indexed by alpha enhancement. These findings suggest that alpha oscillations index the processing of information about self and other depending on the compatibility of internal knowledge and external (environmental) events at finely resolved timescales. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic updating of hippocampal object representations reflects new conceptual knowledge

PubMed Central

Mack, Michael L.; Love, Bradley C.; Preston, Alison R.

2016-01-01

Concepts organize the relationship among individual stimuli or events by highlighting shared features. Often, new goals require updating conceptual knowledge to reflect relationships based on different goal-relevant features. Here, our aim is to determine how hippocampal (HPC) object representations are organized and updated to reflect changing conceptual knowledge. Participants learned two classification tasks in which successful learning required attention to different stimulus features, thus providing a means to index how representations of individual stimuli are reorganized according to changing task goals. We used a computational learning model to capture how people attended to goal-relevant features and organized object representations based on those features during learning. Using representational similarity analyses of functional magnetic resonance imaging data, we demonstrate that neural representations in left anterior HPC correspond with model predictions of concept organization. Moreover, we show that during early learning, when concept updating is most consequential, HPC is functionally coupled with prefrontal regions. Based on these findings, we propose that when task goals change, object representations in HPC can be organized in new ways, resulting in updated concepts that highlight the features most critical to the new goal. PMID:27803320

Knowledge-base browsing: an application of hybrid distributed/local connectionist networks

NASA Astrophysics Data System (ADS)

Samad, Tariq; Israel, Peggy

1990-08-01

We describe a knowledge base browser based on a connectionist (or neural network) architecture that employs both distributed and local representations. The distributed representations are used for input and output thereby enabling associative noise-tolerant interaction with the environment. Internally all representations are fully local. This simplifies weight assignment and facilitates network configuration for specific applications. In our browser concepts and relations in a knowledge base are represented using " microfeatures. " The microfeatures can encode semantic attributes structural features contextual information etc. Desired portions of the knowledge base can then be associatively retrieved based on a structured cue. An ordered list of partial matches is presented to the user for selection. Microfeatures can also be used as " bookmarks" they can be placed dynamically at appropriate points in the knowledge base and subsequently used as retrieval cues. A proof-of-concept system has been implemented for an internally developed Honeywell-proprietary knowledge acquisition tool. 1.

The Effect of Concept Mapping with Different Levels of Generativity and Learners' Self-Regulated Learning Skills on Knowledge Acquisition and Representation

ERIC Educational Resources Information Center

Lim, Kyu Yon

2008-01-01

The purpose of this study was to investigate the effectiveness of concept mapping strategies with different levels of generativity in terms of knowledge acquisition and knowledge representation. Also, it examined whether or not learners' self-regulated learning (SRL) skills influenced the effectiveness of concept mapping strategies with different…

Theorizing "Difficult Knowledge" in the Aftermath of the "Affective Turn": Implications for Curriculum and Pedagogy in Handling Traumatic Representations

ERIC Educational Resources Information Center

Zembylas, Michalinos

2014-01-01

This essay draws on the concept of "difficult knowledge" to think with some of the interventions and arguments of affect theory and discusses the implications for curriculum and pedagogy in handling traumatic representations. The author makes an argument that affect theory enables the theorization of difficult knowledge as an…

Knowledge Representation and Self-Regulatory Experiences of Expert and Novice Certified Athletic Trainers in College and University Settings

ERIC Educational Resources Information Center

Gardin, Fredrick Anthony

2009-01-01

The purpose of this study was to describe how male, collegiate, certified athletic trainers (AT's) represent knowledge during 5 injury evaluation scenarios. A second purpose of the study was to identify what self-regulatory behaviors participants engaged in to improve or maintain their skills. Knowledge representation was studied as cue selection…

Role of multiple representations in physics problem solving

NASA Astrophysics Data System (ADS)

Maries, Alexandru

This thesis explores the role of multiple representations in introductory physics students' problem solving performance through several investigations. Representations can help students focus on the conceptual aspects of physics and play a major role in effective problem solving. Diagrammatic representations can play a particularly important role in the initial stages of conceptual analysis and planning of the problem solution. Findings suggest that students who draw productive diagrams are more successful problem solvers even if their approach is primarily mathematical. Furthermore, students provided with a diagram of the physical situation presented in a problem sometimes exhibited deteriorated performance. Think-aloud interviews suggest that this deteriorated performance is in part due to reduced conceptual planning time which caused students to jump to the implementation stage without fully understanding the problem and planning problem solution. Another study investigated two interventions aimed at improving introductory students' representational consistency between mathematical and graphical representations and revealed that excessive scaffolding can have a detrimental effect. The detrimental effect was partly due to increased cognitive load brought on by the additional steps and instructions. Moreover, students who exhibited representational consistency also showed improved problem solving performance. The final investigation is centered on a problem solving task designed to provide information about the pedagogical content knowledge (PCK) of graduate student teaching assistants (TAs). In particular, the TAs identified what they considered to be the most common difficulties of introductory physics students related to graphical representations of kinematics concepts as they occur in the Test of Understanding Graphs in Kinematics (TUG-K). As an extension, the Force Concept Inventory (FCI) was also used to assess this aspect of PCK related to knowledge of student difficulties of both physics instructors and TAs. We find that teaching an independent course and recent teaching experience do not correlate with improved PCK. In addition, the performance of American TAs, Chinese TAs and other foreign TAs in identifying common student difficulties both in the context of the TUG-K and in the context of the FCI is similar. Moreover, there were many common difficulties of introductory physics students that were not identified by many instructors and TAs.

A collaborative filtering-based approach to biomedical knowledge discovery.

PubMed

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

2018-02-15

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

Semantic e-Science: From Microformats to Models

NASA Astrophysics Data System (ADS)

Lumb, L. I.; Freemantle, J. R.; Aldridge, K. D.

2009-05-01

A platform has been developed to transform semi-structured ASCII data into a representation based on the eXtensible Markup Language (XML). A subsequent transformation allows the XML-based representation to be rendered in the Resource Description Format (RDF). Editorial metadata, expressed as external annotations (via XML Pointer Language), also survives this transformation process (e.g., Lumb et al., http://dx.doi.org/10.1016/j.cageo.2008.03.009). Because the XML-to-RDF transformation uses XSLT (eXtensible Stylesheet Language Transformations), semantic microformats ultimately encode the scientific data (Lumb & Aldridge, http://dx.doi.org/10.1109/HPCS.2006.26). In building the relationship-centric representation in RDF, a Semantic Model of the scientific data is extracted. The systematic enhancement in the expressivity and richness of the scientific data results in representations of knowledge that are readily understood and manipulated by intelligent software agents. Thus scientists are able to draw upon various resources within and beyond their discipline to use in their scientific applications. Since the resulting Semantic Models are independent conceptualizations of the science itself, the representation of scientific knowledge and interaction with the same can stimulate insight from different perspectives. Using the Global Geodynamics Project (GGP) for the purpose of illustration, the introduction of GGP microformats enable a Semantic Model for the GGP that can be semantically queried (e.g., via SPARQL, http://www.w3.org/TR/rdf-sparql-query). Although the present implementation uses the Open Source Redland RDF Libraries (http://librdf.org/), the approach is generalizable to other platforms and to projects other than the GGP (e.g., Baker et al., Informatics and the 2007-2008 Electronic Geophysical Year, Eos Trans. Am. Geophys. Un., 89(48), 485-486, 2008).

Quantitative and qualitative analysis of the knowledge, attitudes and social representations of cholera in the extreme northern region of Cameroon: the case of Maroua I, Maroua Ii And Mokolo

PubMed Central

Amaah, Penn

2014-01-01

Introduction An effective fight against cholera requires an in-depth consideration of the knowledge, attitudes and social representations of cholera within a population. Cholera outbreaks persist in the Extreme North of Cameroon because of the inadequate integration of representations of cholera, water and hygiene in the fight against this disease. Through a constructivist intercultural approach not conflicting with the western ethnocentric model, socio-cultural/religious and historical ideologies can be reconciled to provide optimal and sustainable healthcare solutions to the repeated and long lasting cholera epidemics using participative research, intercultural mediation and dialogue in Cameroon. Methods Through a cross-sectional, ethnographic and participative study, data was generated using semi-directed in-depth interviews of key informants, collection of videos, pictures and the completion of 2 pre-tested questionnaire types in 3 communities (Maroua I, Maroua II and Mokolo). Quantitative data was entered using Ms Excel and Epi Info 7, and analysed using Epi Info 7. Qualitative data was analysed inductively using the concept of social representations. Results Results show evidence of the inadequate integration of cultural and socio-cultural factors favouring cholera spread and a respondent population majority unable to identify this (92.82%). Equally identifying environmental and cultural factors, the results bring out the impact of the on-going cholera combating strategy. Conclusion Representations of cholera, cultural and socio-cultural values are not adequately considered in the fight against cholera. We recommend policy-makers and health actors to improve on the integration of these through advocacy, in designing, communicating and implementing effective prevention strategies via participative research, intercultural mediation and dialogue. PMID:25309653

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

NASA Astrophysics Data System (ADS)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

Acquisition, representation and rule generation for procedural knowledge

NASA Technical Reports Server (NTRS)

Ortiz, Chris; Saito, Tim; Mithal, Sachin; Loftin, R. Bowen

1991-01-01

Current research into the design and continuing development of a system for the acquisition of procedural knowledge, its representation in useful forms, and proposed methods for automated C Language Integrated Production System (CLIPS) rule generation is discussed. The Task Analysis and Rule Generation Tool (TARGET) is intended to permit experts, individually or collectively, to visually describe and refine procedural tasks. The system is designed to represent the acquired knowledge in the form of graphical objects with the capacity for generating production rules in CLIPS. The generated rules can then be integrated into applications such as NASA's Intelligent Computer Aided Training (ICAT) architecture. Also described are proposed methods for use in translating the graphical and intermediate knowledge representations into CLIPS rules.

Knowledge representation in fuzzy logic

NASA Technical Reports Server (NTRS)

Zadeh, Lotfi A.

1989-01-01

The author presents a summary of the basic concepts and techniques underlying the application of fuzzy logic to knowledge representation. He then describes a number of examples relating to its use as a computational system for dealing with uncertainty and imprecision in the context of knowledge, meaning, and inference. It is noted that one of the basic aims of fuzzy logic is to provide a computational framework for knowledge representation and inference in an environment of uncertainty and imprecision. In such environments, fuzzy logic is effective when the solutions need not be precise and/or it is acceptable for a conclusion to have a dispositional rather than categorical validity. The importance of fuzzy logic derives from the fact that there are many real-world applications which fit these conditions, especially in the realm of knowledge-based systems for decision-making and control.

38 CFR 14.632 - Standards of conduct for persons providing representation before the Department

Code of Federal Regulations, 2013 CFR

2013-07-01

... the knowledge, skill, thoroughness, and preparation necessary for the representation. This includes... persons providing representation before the Department 14.632 Section 14.632 Pensions, Bonuses, and... Representation of Department of Veterans Affairs Claimants; Recognition of Organizations, Accredited...

38 CFR 14.632 - Standards of conduct for persons providing representation before the Department

Code of Federal Regulations, 2011 CFR

2011-07-01

... the knowledge, skill, thoroughness, and preparation necessary for the representation. This includes... persons providing representation before the Department 14.632 Section 14.632 Pensions, Bonuses, and... Representation of Department of Veterans Affairs Claimants; Recognition of Organizations, Accredited...

38 CFR 14.632 - Standards of conduct for persons providing representation before the Department

Code of Federal Regulations, 2014 CFR

2014-07-01

... the knowledge, skill, thoroughness, and preparation necessary for the representation. This includes... persons providing representation before the Department 14.632 Section 14.632 Pensions, Bonuses, and... Representation of Department of Veterans Affairs Claimants; Recognition of Organizations, Accredited...

38 CFR 14.632 - Standards of conduct for persons providing representation before the Department

Code of Federal Regulations, 2010 CFR

2010-07-01

... the knowledge, skill, thoroughness, and preparation necessary for the representation. This includes... persons providing representation before the Department 14.632 Section 14.632 Pensions, Bonuses, and... Representation of Department of Veterans Affairs Claimants; Recognition of Organizations, Accredited...

38 CFR 14.632 - Standards of conduct for persons providing representation before the Department

Code of Federal Regulations, 2012 CFR

2012-07-01

... the knowledge, skill, thoroughness, and preparation necessary for the representation. This includes... persons providing representation before the Department 14.632 Section 14.632 Pensions, Bonuses, and... Representation of Department of Veterans Affairs Claimants; Recognition of Organizations, Accredited...

An Ontology for Representing Geoscience Theories and Related Knowledge

NASA Astrophysics Data System (ADS)

Brodaric, B.

2009-12-01

Online scientific research, or e-science, is increasingly reliant on machine-readable representations of scientific data and knowledge. At present, much of the knowledge is represented in ontologies, which typically contain geoscience categories such as ‘water body’, ‘aquifer’, ‘granite’, ‘temperature’, ‘density’, ‘Co2’. While extremely useful for many e-science activities, such categorical representations constitute only a fragment of geoscience knowledge. Also needed are online representations of elements such as geoscience theories, to enable geoscientists to pose and evaluate hypotheses online. To address this need, the Science Knowledge Infrastructure ontology (SKIo) specializes the DOLCE foundational ontology with basic science knowledge primitives such as theory, model, observation, and prediction. Discussed will be SKIo as well as its implementation in the geosciences, including case studies from marine science, environmental science, and geologic mapping. These case studies demonstrate SKIo’s ability to represent a wide spectrum of geoscience knowledge types, to help fuel next generation e-science.

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.

Semantic representation of reported measurements in radiology.

PubMed

Oberkampf, Heiner; Zillner, Sonja; Overton, James A; Bauer, Bernhard; Cavallaro, Alexander; Uder, Michael; Hammon, Matthias

2016-01-22

In radiology, a vast amount of diverse data is generated, and unstructured reporting is standard. Hence, much useful information is trapped in free-text form, and often lost in translation and transmission. One relevant source of free-text data consists of reports covering the assessment of changes in tumor burden, which are needed for the evaluation of cancer treatment success. Any change of lesion size is a critical factor in follow-up examinations. It is difficult to retrieve specific information from unstructured reports and to compare them over time. Therefore, a prototype was implemented that demonstrates the structured representation of findings, allowing selective review in consecutive examinations and thus more efficient comparison over time. We developed a semantic Model for Clinical Information (MCI) based on existing ontologies from the Open Biological and Biomedical Ontologies (OBO) library. MCI is used for the integrated representation of measured image findings and medical knowledge about the normal size of anatomical entities. An integrated view of the radiology findings is realized by a prototype implementation of a ReportViewer. Further, RECIST (Response Evaluation Criteria In Solid Tumors) guidelines are implemented by SPARQL queries on MCI. The evaluation is based on two data sets of German radiology reports: An oncologic data set consisting of 2584 reports on 377 lymphoma patients and a mixed data set consisting of 6007 reports on diverse medical and surgical patients. All measurement findings were automatically classified as abnormal/normal using formalized medical background knowledge, i.e., knowledge that has been encoded into an ontology. A radiologist evaluated 813 classifications as correct or incorrect. All unclassified findings were evaluated as incorrect. The proposed approach allows the automatic classification of findings with an accuracy of 96.4 % for oncologic reports and 92.9 % for mixed reports. The ReportViewer permits efficient comparison of measured findings from consecutive examinations. The implementation of RECIST guidelines with SPARQL enhances the quality of the selection and comparison of target lesions as well as the corresponding treatment response evaluation. The developed MCI enables an accurate integrated representation of reported measurements and medical knowledge. Thus, measurements can be automatically classified and integrated in different decision processes. The structured representation is suitable for improved integration of clinical findings during decision-making. The proposed ReportViewer provides a longitudinal overview of the measurements.

From infotainment to tools of interaction - A critical perspective on the use of film/video in geoscience

NASA Astrophysics Data System (ADS)

Ickert, Johanna

2017-04-01

In times of omnipresent digitisation and interconnectedness, the way how we generate and experience knowledge on geo-related themes is strongly influenced by audiovisual media representations. Moving images are powerful tools and have significant potential to communicate science in novel ways. Major research frameworks such as Horizon 2020 strongly encourage the use of audiovisual media in order to communicate science "more effectively" to the public. An increasing number of geoscientists produce films themselves, while most of them still delegate this task to media professionals to whom they provide their scientific expert knowledge. Usually, the intention behind these outreach efforts is to take advantage of the suitability of the medium to convey "scientific facts", or to motivate certain cognitive/behavioural responses of different target audiences. Undoubtedly, film has a great potential for representing geoscientific knowledge and thus has become a key instrument for geoscience communication. However, the use of images also raises fundamental ethical and representational concerns. While the latter have provoked intense debates in sub-disciplines such as visual anthropology or film geography, the geosciences have paid only little attention to questions on how distinct practices and disciplinary paradigms create filmic representations. Given the fact that the use of scientific images and film is far from being "objective" and that the way how we create and experience images is always context-specific and strongly influenced by the relationship between film maker, film subjects/informants and audience, a series of important question arises: What do we know about the use of film in geosciences beyond the realm of information and representational purposes? What can we learn from using film as a reflexive, process-oriented and dialogue-based medium? How can film help us to better understand ethical and representational dimensions of our interaction with the public? What are the phenomenological qualities of film and how can they be made productive for science communication? This article explores the potential for novel approaches to use film in geology not only as outreach tool, but also as method of joint knowledge production in inter- and transdisciplinary collaboration. In order to provide evidence for the above-mentioned observations, a historical perspective on the use of film in geosciences as well as an in-depth analysis of recent art-science-collaborations will be given.

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.

Report to the President of the United States on Sexual Assault Prevention and Response

DTIC Science & Technology

2014-11-01

established research history based on laboratory- tested principles of memory retrieval, knowledge representation, and communication. AFOSI has been using CI...analysis methods, including scientific research , data analysis, focus groups , and on -site assessments to evaluate the Department’s SAPR program...131 Report to the President of the United States on SAPR DMDC’s focus group methodology employs a standard qualitative research approach to

Mapping university students' epistemic framing of computational physics using network analysis

NASA Astrophysics Data System (ADS)

Bodin, Madelen

2012-06-01

Solving physics problem in university physics education using a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modeling. These competences are in turn related to students’ beliefs about the domains as well as about learning. These knowledge and beliefs components are referred to here as epistemic elements, which together represent the students’ epistemic framing of the situation. The purpose of this study was to investigate university physics students’ epistemic framing when solving and visualizing a physics problem using a particle-spring model system. Students’ epistemic framings are analyzed before and after the task using a network analysis approach on interview transcripts, producing visual representations as epistemic networks. The results show that students change their epistemic framing from a modeling task, with expectancies about learning programming, to a physics task, in which they are challenged to use physics principles and conservation laws in order to troubleshoot and understand their simulations. This implies that the task, even though it is not introducing any new physics, helps the students to develop a more coherent view of the importance of using physics principles in problem solving. The network analysis method used in this study is shown to give intelligible representations of the students’ epistemic framing and is proposed as a useful method of analysis of textual data.

Methodological Developments in Geophysical Assimilation Modeling

NASA Astrophysics Data System (ADS)

Christakos, George

2005-06-01

This work presents recent methodological developments in geophysical assimilation research. We revisit the meaning of the term "solution" of a mathematical model representing a geophysical system, and we examine its operational formulations. We argue that an assimilation solution based on epistemic cognition (which assumes that the model describes incomplete knowledge about nature and focuses on conceptual mechanisms of scientific thinking) could lead to more realistic representations of the geophysical situation than a conventional ontologic assimilation solution (which assumes that the model describes nature as is and focuses on form manipulations). Conceptually, the two approaches are fundamentally different. Unlike the reasoning structure of conventional assimilation modeling that is based mainly on ad hoc technical schemes, the epistemic cognition approach is based on teleologic criteria and stochastic adaptation principles. In this way some key ideas are introduced that could open new areas of geophysical assimilation to detailed understanding in an integrated manner. A knowledge synthesis framework can provide the rational means for assimilating a variety of knowledge bases (general and site specific) that are relevant to the geophysical system of interest. Epistemic cognition-based assimilation techniques can produce a realistic representation of the geophysical system, provide a rigorous assessment of the uncertainty sources, and generate informative predictions across space-time. The mathematics of epistemic assimilation involves a powerful and versatile spatiotemporal random field theory that imposes no restriction on the shape of the probability distributions or the form of the predictors (non-Gaussian distributions, multiple-point statistics, and nonlinear models are automatically incorporated) and accounts rigorously for the uncertainty features of the geophysical system. In the epistemic cognition context the assimilation concept may be used to investigate critical issues related to knowledge reliability, such as uncertainty due to model structure error (conceptual uncertainty).

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine.

PubMed

Kawamoto, Kensaku; Lobach, David F; Willard, Huntington F; Ginsburg, Geoffrey S

2009-03-23

In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs. Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government. A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.

Rubber airplane: Constraint-based component-modeling for knowledge representation in computer-aided conceptual design

NASA Technical Reports Server (NTRS)

Kolb, Mark A.

1990-01-01

Viewgraphs on Rubber Airplane: Constraint-based Component-Modeling for Knowledge Representation in Computer Aided Conceptual Design are presented. Topics covered include: computer aided design; object oriented programming; airfoil design; surveillance aircraft; commercial aircraft; aircraft design; and launch vehicles.

Translation between representation languages

NASA Technical Reports Server (NTRS)

Vanbaalen, Jeffrey

1994-01-01

A capability for translating between representation languages is critical for effective knowledge base reuse. A translation technology for knowledge representation languages based on the use of an interlingua for communicating knowledge is described. The interlingua-based translation process consists of three major steps: translation from the source language into a subset of the interlingua, translation between subsets of the interlingua, and translation from a subset of the interlingua into the target language. The first translation step into the interlingua can typically be specified in the form of a grammar that describes how each top-level form in the source language translates into the interlingua. In cases where the source language does not have a declarative semantics, such a grammar is also a specification of a declarative semantics for the language. A methodology for building translators that is currently under development is described. A 'translator shell' based on this methodology is also under development. The shell has been used to build translators for multiple representation languages and those translators have successfully translated nontrivial knowledge bases.

Robust fault diagnosis of physical systems in operation. Ph.D. Thesis - Rutgers - The State Univ.

NASA Technical Reports Server (NTRS)

Abbott, Kathy Hamilton

1991-01-01

Ideas are presented and demonstrated for improved robustness in diagnostic problem solving of complex physical systems in operation, or operative diagnosis. The first idea is that graceful degradation can be viewed as reasoning at higher levels of abstraction whenever the more detailed levels proved to be incomplete or inadequate. A form of abstraction is defined that applies this view to the problem of diagnosis. In this form of abstraction, named status abstraction, two levels are defined. The lower level of abstraction corresponds to the level of detail at which most current knowledge-based diagnosis systems reason. At the higher level, a graph representation is presented that describes the real-world physical system. An incremental, constructive approach to manipulating this graph representation is demonstrated that supports certain characteristics of operative diagnosis. The suitability of this constructive approach is shown for diagnosing fault propagation behavior over time, and for sometimes diagnosing systems with feedback. A way is shown to represent different semantics in the same type of graph representation to characterize different types of fault propagation behavior. An approach is demonstrated that threats these different behaviors as different fault classes, and the approach moves to other classes when previous classes fail to generate suitable hypotheses. These ideas are implemented in a computer program named Draphys (Diagnostic Reasoning About Physical Systems) and demonstrated for the domain of inflight aircraft subsystems, specifically a propulsion system (containing two turbofan systems and a fuel system) and hydraulic subsystem.

Modeling biochemical pathways in the gene ontology

DOE PAGES

Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.; ...

2016-09-01

The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less

Representation of Biomedical Expertise in Ontologies: a Case Study about Knowledge Acquisition on HTLV viruses and their clinical manifestations.

PubMed

Cardoso Coelho, Kátia; Barcellos Almeida, Maurício

2015-01-01

In this paper, we introduce a set of methodological steps for knowledge acquisition applied to the organization of biomedical information through ontologies. Those steps are tested in a real case involving Human T Cell Lymphotropic Virus (HTLV), which causes myriad infectious diseases. We hope to contribute to providing suitable knowledge representation of scientific domains.

Knowledge representation for fuzzy inference aided medical image interpretation.

PubMed

Gal, Norbert; Stoicu-Tivadar, Vasile

2012-01-01

Knowledge defines how an automated system transforms data into information. This paper suggests a representation method of medical imaging knowledge using fuzzy inference systems coded in XML files. The imaging knowledge incorporates features of the investigated objects in linguistic form and inference rules that can transform the linguistic data into information about a possible diagnosis. A fuzzy inference system is used to model the vagueness of the linguistic medical imaging terms. XML files are used to facilitate easy manipulation and deployment of the knowledge into the imaging software. Preliminary results are presented.

Making effective referrals: a knowledge-management approach.

PubMed Central

Einbinder, J. S.; Klein, D. A.; Safran, C. S.

1997-01-01

Patients and physicians often choose specially consultants with only limited knowledge of the available options. Access to information about specialists that was directly relevant to patient and clinician preferences could improve the effectiveness of the referral process. We have developed a prescriptive representation of the process of selecting consultants. This "referral map," based on decision theory, uses patient and provider preferences elicited through a literature review and interviews with physicians and provides a formal framework for representing referral knowledge and for evaluating referral options. Our method suggests that the goals and processes of selecting consultants can be managed more systematically using explicit repositories. Such systematic management promises to have a beneficial impact on the delivery of health care, as well as on patient satisfaction. PMID:9357642

On the acquisition and representation of procedural knowledge

NASA Technical Reports Server (NTRS)

Saito, T.; Ortiz, C.; Loftin, R. B.

1992-01-01

Historically knowledge acquisition has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some of some types of knowledge, little attention has been devoted to procedural knowledge. NASA personnel frequently perform tasks that are primarily procedural in nature. Previous work is reviewed in the field of knowledge acquisition and then focus on knowledge acquisition for procedural tasks with special attention devoted to the Navy's VISTA tool. The design and development is described of a system for the acquisition and representation of procedural knowledge-TARGET (Task Analysis and Rule Generation Tool). TARGET is intended as a tool that permits experts to visually describe procedural tasks and as a common medium for knowledge refinement by the expert and knowledge engineer. The system is designed to represent the acquired knowledge in the form of production rules. Systems such as TARGET have the potential to profoundly reduce the time, difficulties, and costs of developing knowledge-based systems for the performance of procedural tasks.

Social Representations and Practices Towards Triatomines and Chagas Disease in Calakmul, México.

PubMed

Valdez-Tah, Alba; Huicochea-Gómez, Laura; Ortega-Canto, Judith; Nazar-Beutelspacher, Austreberta; Ramsey, Janine M

2015-01-01

Vector-borne transmission of Trypanosoma cruzi (VBTTc) is dependent on the concomitant interaction between biological and environmental hazard over the entire landscape, and human vulnerability. Representations and practices of health-disease-care-seeking and territorial appropriation and use were analyzed for VBTTc in a qualitative ethnographic study in the Zoh-Laguna landscape, Campeche, Mexico. In-depth interviews and participatory observation explored representations and practices regarding ethno-ecological knowledge related to vector-transmission, health-disease-care-seeking, and land use processes. The population has a broad knowledge of biting insects, which they believe are all most abundant in the rainy season; the community´s proximity to natural areas is perceived as a barrier to control their abundance. Triatomines are mostly recognized by men, who have detailed knowledge regarding their occurrence and association with mammals in non-domestic fragments, where they report being bitten. Women emphasize the dermal consequences of triatomine bites, but have little knowledge about the disease. Triatomine bites and the chinchoma are "normalized" events which are treated using home remedies, if at all. The neglected condition of Chagas disease in Mexican public health policies, livelihoods which are dependent on primary production, and gender-related knowledge (or lack thereof) are structural circumstances which influence the environment and inhabitants´ living conditions; in turn, these trigger triatomine-human contact. The most important landscape practices producing vulnerability are the activities and mobility within and between landscape fragments causing greater exposure of inhabitants primarily in the dry season. A landscape approach to understanding vulnerability components of VBTTc from health-disease-care-seeking perspectives and based on territorial appropriation and use, is essential where there is continuous movement of vectors between and within all habitats. An understanding of the structural factors which motivate the population´s perceptions, beliefs, and practices and which create and maintain vulnerability is essential to develop culturally relevant and sustainable community-based VBTTc prevention and control.

Social Representations and Practices Towards Triatomines and Chagas Disease in Calakmul, México

PubMed Central

Valdez-Tah, Alba; Huicochea-Gómez, Laura; Ortega-Canto, Judith; Nazar-Beutelspacher, Austreberta; Ramsey, Janine M.

2015-01-01

Vector-borne transmission of Trypanosoma cruzi (VBTTc) is dependent on the concomitant interaction between biological and environmental hazard over the entire landscape, and human vulnerability. Representations and practices of health-disease-care-seeking and territorial appropriation and use were analyzed for VBTTc in a qualitative ethnographic study in the Zoh-Laguna landscape, Campeche, Mexico. In-depth interviews and participatory observation explored representations and practices regarding ethno-ecological knowledge related to vector-transmission, health-disease-care-seeking, and land use processes. The population has a broad knowledge of biting insects, which they believe are all most abundant in the rainy season; the community´s proximity to natural areas is perceived as a barrier to control their abundance. Triatomines are mostly recognized by men, who have detailed knowledge regarding their occurrence and association with mammals in non-domestic fragments, where they report being bitten. Women emphasize the dermal consequences of triatomine bites, but have little knowledge about the disease. Triatomine bites and the chinchoma are “normalized” events which are treated using home remedies, if at all. The neglected condition of Chagas disease in Mexican public health policies, livelihoods which are dependent on primary production, and gender-related knowledge (or lack thereof) are structural circumstances which influence the environment and inhabitants´ living conditions; in turn, these trigger triatomine-human contact. The most important landscape practices producing vulnerability are the activities and mobility within and between landscape fragments causing greater exposure of inhabitants primarily in the dry season. A landscape approach to understanding vulnerability components of VBTTc from health-disease-care-seeking perspectives and based on territorial appropriation and use, is essential where there is continuous movement of vectors between and within all habitats. An understanding of the structural factors which motivate the population´s perceptions, beliefs, and practices and which create and maintain vulnerability is essential to develop culturally relevant and sustainable community-based VBTTc prevention and control. PMID:26204555

Knowledge Representation and Management. From Ontology to Annotation. Findings from the Yearbook 2015 Section on Knowledge Representation and Management.

PubMed

Charlet, J; Darmoni, S J

2015-08-13

To summarize the best papers in the field of Knowledge Representation and Management (KRM). A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM published in 2014. Four articles were selected, two focused on annotation and information retrieval using an ontology. The two others focused mainly on ontologies, one dealing with the usage of a temporal ontology in order to analyze the content of narrative document, one describing a methodology for building multilingual ontologies. Semantic models began to show their efficiency, coupled with annotation tools.

Sentiments analysis at conceptual level making use of the Narrative Knowledge Representation Language.

PubMed

Zarri, Gian Piero

2014-10-01

This paper illustrates some of the knowledge representation structures and inference procedures proper to a high-level, fully implemented conceptual language, NKRL (Narrative Knowledge Representation Language). The aim is to show how these tools can be used to deal, in a sentiment analysis/opinion mining context, with some common types of human (and non-human) "behaviors". These behaviors correspond, in particular, to the concrete, mutual relationships among human and non-human characters that can be expressed under the form of non-fictional and real-time "narratives" (i.e., as logically and temporally structured sequences of "elementary events"). Copyright © 2014 Elsevier Ltd. All rights reserved.

TARGET: Rapid Capture of Process Knowledge

NASA Technical Reports Server (NTRS)

Ortiz, C. J.; Ly, H. V.; Saito, T.; Loftin, R. B.

1993-01-01

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper.

Origins of Secure Base Script Knowledge and the Developmental Construction of Attachment Representations.

PubMed

Waters, Theodore E A; Ruiz, Sarah K; Roisman, Glenn I

2017-01-01

Increasing evidence suggests that attachment representations take at least two forms: a secure base script and an autobiographical narrative of childhood caregiving experiences. This study presents data from the first 26 years of the Minnesota Longitudinal Study of Risk and Adaptation (N = 169), examining the developmental origins of secure base script knowledge in a high-risk sample and testing alternative models of the developmental sequencing of the construction of attachment representations. Results demonstrated that secure base script knowledge was predicted by observations of maternal sensitivity across childhood and adolescence. Furthermore, findings suggest that the construction of a secure base script supports the development of a coherent autobiographical representation of childhood attachment experiences with primary caregivers by early adulthood. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Evaluation of an Intelligent Tutoring System in Pathology: Effects of External Representation on Performance Gains, Metacognition, and Acceptance

PubMed Central

Crowley, Rebecca S.; Legowski, Elizabeth; Medvedeva, Olga; Tseytlin, Eugene; Roh, Ellen; Jukic, Drazen

2007-01-01

Objective Determine effects of computer-based tutoring on diagnostic performance gains, meta-cognition, and acceptance using two different problem representations. Describe impact of tutoring on spectrum of diagnostic skills required for task performance. Identify key features of student-tutor interaction contributing to learning gains. Design Prospective, between-subjects study, controlled for participant level of training. Resident physicians in two academic pathology programs spent four hours using one of two interfaces which differed mainly in external problem representation. The case-focused representation provided an open-learning environment in which students were free to explore evidence-hypothesis relationships within a case, but could not visualize the entire diagnostic space. The knowledge-focused representation provided an interactive representation of the entire diagnostic space, which more tightly constrained student actions. Measurements Metrics included results of pretest, post-test and retention-test for multiple choice and case diagnosis tests, ratios of performance to student reported certainty, results of participant survey, learning curves, and interaction behaviors during tutoring. Results Students had highly significant learning gains after one tutoring session. Learning was retained at one week. There were no differences between the two interfaces in learning gains on post-test or retention test. Only students in the knowledge-focused interface exhibited significant metacognitive gains from pretest to post-test and pretest to retention test. Students rated the knowledge-focused interface significantly higher than the case-focused interface. Conclusions Cognitive tutoring is associated with improved diagnostic performance in a complex medical domain. The effect is retained at one-week post-training. Knowledge-focused external problem representation shows an advantage over case-focused representation for metacognitive effects and user acceptance. PMID:17213494

Evaluation of an intelligent tutoring system in pathology: effects of external representation on performance gains, metacognition, and acceptance.

PubMed

Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Tseytlin, Eugene; Roh, Ellen; Jukic, Drazen

2007-01-01

Determine effects of computer-based tutoring on diagnostic performance gains, meta-cognition, and acceptance using two different problem representations. Describe impact of tutoring on spectrum of diagnostic skills required for task performance. Identify key features of student-tutor interaction contributing to learning gains. Prospective, between-subjects study, controlled for participant level of training. Resident physicians in two academic pathology programs spent four hours using one of two interfaces which differed mainly in external problem representation. The case-focused representation provided an open-learning environment in which students were free to explore evidence-hypothesis relationships within a case, but could not visualize the entire diagnostic space. The knowledge-focused representation provided an interactive representation of the entire diagnostic space, which more tightly constrained student actions. Metrics included results of pretest, post-test and retention-test for multiple choice and case diagnosis tests, ratios of performance to student reported certainty, results of participant survey, learning curves, and interaction behaviors during tutoring. Students had highly significant learning gains after one tutoring session. Learning was retained at one week. There were no differences between the two interfaces in learning gains on post-test or retention test. Only students in the knowledge-focused interface exhibited significant metacognitive gains from pretest to post-test and pretest to retention test. Students rated the knowledge-focused interface significantly higher than the case-focused interface. Cognitive tutoring is associated with improved diagnostic performance in a complex medical domain. The effect is retained at one-week post-training. Knowledge-focused external problem representation shows an advantage over case-focused representation for metacognitive effects and user acceptance.

Human white matter and knowledge representation

PubMed Central

2018-01-01

Understanding how knowledge is represented in the human brain is a fundamental challenge in neuroscience. To date, most of the work on this topic has focused on knowledge representation in cortical areas and debated whether knowledge is represented in a distributed or localized fashion. Fang and colleagues provide evidence that brain connections and the white matter supporting such connections might play a significant role. The work opens new avenues of investigation, breaking through disciplinary boundaries across network neuroscience, computational neuroscience, cognitive science, and classical lesion studies. PMID:29698391

Human white matter and knowledge representation.

PubMed

Pestilli, Franco

2018-04-01

Understanding how knowledge is represented in the human brain is a fundamental challenge in neuroscience. To date, most of the work on this topic has focused on knowledge representation in cortical areas and debated whether knowledge is represented in a distributed or localized fashion. Fang and colleagues provide evidence that brain connections and the white matter supporting such connections might play a significant role. The work opens new avenues of investigation, breaking through disciplinary boundaries across network neuroscience, computational neuroscience, cognitive science, and classical lesion studies.

Nursing Minimum Data Set Based on EHR Archetypes Approach.

PubMed

Spigolon, Dandara N; Moro, Cláudia M C

2012-01-01

The establishment of a Nursing Minimum Data Set (NMDS) can facilitate the use of health information systems. The adoption of these sets and represent them based on archetypes are a way of developing and support health systems. The objective of this paper is to describe the definition of a minimum data set for nursing in endometriosis represent with archetypes. The study was divided into two steps: Defining the Nursing Minimum Data Set to endometriosis, and Development archetypes related to the NMDS. The nursing data set to endometriosis was represented in the form of archetype, using the whole perception of the evaluation item, organs and senses. This form of representation is an important tool for semantic interoperability and knowledge representation for health information systems.

Nursing Minimum Data Set Based on EHR Archetypes Approach

PubMed Central

Spigolon, Dandara N.; Moro, Cláudia M.C.

2012-01-01

The establishment of a Nursing Minimum Data Set (NMDS) can facilitate the use of health information systems. The adoption of these sets and represent them based on archetypes are a way of developing and support health systems. The objective of this paper is to describe the definition of a minimum data set for nursing in endometriosis represent with archetypes. The study was divided into two steps: Defining the Nursing Minimum Data Set to endometriosis, and Development archetypes related to the NMDS. The nursing data set to endometriosis was represented in the form of archetype, using the whole perception of the evaluation item, organs and senses. This form of representation is an important tool for semantic interoperability and knowledge representation for health information systems. PMID:24199126

48 CFR 2052.209-71 - Contractor organizational conflicts of interest (representation).

Code of Federal Regulations, 2010 CFR

2010-10-01

... conflicts of interest (representation). 2052.209-71 Section 2052.209-71 Federal Acquisition Regulations... of Provisions and Clauses 2052.209-71 Contractor organizational conflicts of interest (representation... Organizational Conflicts of Interest Representation (OCT 1999) I represent to the best of my knowledge and belief...

Knowledge-Based Object Detection in Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

Knowledge-based approaches to the maintenance of a large controlled medical terminology.

PubMed Central

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

1994-01-01

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

God-mother-baby: what children think they know.

PubMed

Kiessling, Florian; Perner, Josef

2014-01-01

This study tested one hundred and nine 3- to 6-year-old children on a knowledge-ignorance task about knowledge in humans (mother, baby) and God. In their responses, participants not reliably grasping that seeing leads to knowing in humans (pre-representational) were significantly influenced by own knowledge and marginally by question format. Moreover, knowledge was attributed significantly more often to mother than baby and explained by agent-based characteristics. Of participants mastering the task for humans (representational), God was largely conceived as ignorant "man in the sky" by younger and increasingly as "supernatural agent in the sky" by older children. Evidence for egocentrism and for anthropomorphizing God lends support to an anthropomorphism hypothesis. First-time evidence for an agent-based conception of others' knowledge in pre-representational children is presented. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

Techniques for capturing expert knowledge - An expert systems/hypertext approach

NASA Technical Reports Server (NTRS)

Lafferty, Larry; Taylor, Greg; Schumann, Robin; Evans, Randy; Koller, Albert M., Jr.

1990-01-01

The knowledge-acquisition strategy developed for the Explosive Hazards Classification (EHC) Expert System is described in which expert systems and hypertext are combined, and broad applications are proposed. The EHC expert system is based on rapid prototyping in which primary knowledge acquisition from experts is not emphasized; the explosive hazards technical bulletin, technical guidance, and minimal interviewing are used to develop the knowledge-based system. Hypertext is used to capture the technical information with respect to four issues including procedural, materials, test, and classification issues. The hypertext display allows the integration of multiple knowlege representations such as clarifications or opinions, and thereby allows the performance of a broad range of tasks on a single machine. Among other recommendations, it is suggested that the integration of hypertext and expert systems makes the resulting synergistic system highly efficient.

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

NASA Astrophysics Data System (ADS)

Vajgl, Marek; Lukasová, Alena; Žáček, Martin

2017-06-01

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

Some Problems and Proposals for Knowledge Representation.

DTIC Science & Technology

1984-01-01

BROTHER(BiI, AI ) and FATHER( AI ,John) According to Woods, these both denote the fact that Bill is the uncle of John. However, we now must have two...34knowledge representation language being developed at the Berkeley Artificial Inteligience Research Project. KODIAK is an attempt to redress the above

Knowledge Representation in a Physics Tutor. COINS Technical Report 86-37.

ERIC Educational Resources Information Center

Murray, Tom; Woolf, Beverly

This paper is based on the idea that designing a knowledge representation for an intelligent physics computer tutoring system depends, in part, on the target behavior anticipated from the student. In addition, the document distinguishes between qualitative and quantitative competence in physics. These competencies are illustrated through questions…

Descriptive Analysis of the Graphic Representations of Science Textbooks

ERIC Educational Resources Information Center

Khine, Myint Swe; Liu, Yang

2017-01-01

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

Enhancing Conceptual Knowledge of Energy in Biology with Incorrect Representations

ERIC Educational Resources Information Center

Wernecke, Ulrike; Schütte, Kerstin; Schwanewedel, Julia; Harms, Ute

2018-01-01

Energy is an important concept in all natural sciences, and a challenging one for school science education. Students' conceptual knowledge of energy is often low, and they entertain misconceptions. Educational research in science and mathematics suggests that learning through depictive representations and learning from errors, based on the theory…

Software GOLUCA: Knowledge Representation in Mental Calculation

ERIC Educational Resources Information Center

Casas-Garcia, Luis M.; Luengo-Gonzalez, Ricardo; Godinho-Lopes, Vitor

2011-01-01

We present a new software, called Goluca (Godinho, Luengo, and Casas, 2007), based on the technique of Pathfinder Associative Networks (Schvaneveldt, 1989), which produces graphical representations of the cognitive structure of individuals in a given field knowledge. In this case, we studied the strategies used by teachers and its relationship…

Semantics vs. World Knowledge in Prefrontal Cortex

ERIC Educational Resources Information Center

Pylkkanen, Liina; Oliveri, Bridget; Smart, Andrew J.

2009-01-01

Humans have knowledge about the properties of their native language at various levels of representation; sound, structure, and meaning computation constitute the core components of any linguistic theory. Although the brain sciences have engaged with representational theories of sound and syntactic structure, the study of the neural bases of…

Systematic Representation of Knowledge of Ecology: Concepts and Relationships.

ERIC Educational Resources Information Center

Garb, Yaakov; And Others

This study describes efforts to apply principles of systematic knowledge representation (concept mapping and computer-based semantic networking techniques) to the domain of ecology. A set of 24 relationships and modifiers is presented that seem sufficient for describing all ecological relationships discussed in an introductory course. Many of…

Making Connections: Elementary Teachers' Construction of Division Word Problems and Representations

ERIC Educational Resources Information Center

Timmerman, Maria A.

2014-01-01

If teachers make few connections among multiple representations of division, supporting students in using representations to develop operation sense demanded by national standards will not occur. Studies have investigated how prospective and practicing teachers use representations to develop knowledge of fraction division. However, few studies…

Playing Linear Number Board Games Improves Children's Mathematical Knowledge

ERIC Educational Resources Information Center

Siegler, Robert S.; Ramani, Geetha

2009-01-01

The present study focused on two main goals. One was to test the "representational mapping hypothesis": The greater the transparency of the mapping between physical materials and desired internal representations, the greater the learning of the desired internal representation. The implication of the representational mapping hypothesis in the…

Exploring the Complexities of Children's Inquiries in Science: Knowledge Production Through Participatory Practices

NASA Astrophysics Data System (ADS)

Siry, Christina

2013-12-01

Beginning with the assumption that young children are capable of producing unprecedented knowledges about science phenomena, this paper explores the complexities of children's inquiries within open-ended investigations. I ask two central questions: (1) how can we (teachers, researchers, and children themselves) use and build upon children's explorations in science in practice? and (2) what pedagogical approaches can position children as experts on their experiences to facilitate children's sense of ownership in the process of learning science? Six vignettes from a Kindergarten classroom are analyzed to elaborate the central claim of this work, which is that when children are engaged in collaborative open-ended activities, science emerges from their interactions. Open-ended structures allowed for teachers and children to facilitate further investigations collaboratively, and participatory structures mediated children's representations and explanations of their investigations. Evidence of children's interactions is used to illustrate the complexities of children's explorations, and pedagogical approaches that create the spaces for children to create knowledge are highlighted.

Temporal and contextual knowledge in model-based expert systems

NASA Technical Reports Server (NTRS)

Toth-Fejel, Tihamer; Heher, Dennis

1987-01-01

A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware.

Decision support systems in health economics.

PubMed

Quaglini, S; Dazzi, L; Stefanelli, M; Barosi, G; Marchetti, M

1999-08-01

This article describes a system addressed to different health care professionals for building, using, and sharing decision support systems for resource allocation. The system deals with selected areas, namely the choice of diagnostic tests, the therapy planning, and the instrumentation purchase. Decision support is based on decision-analytic models, incorporating an explicit knowledge representation of both the medical domain knowledge and the economic evaluation theory. Application models are built on top of meta-models, that are used as guidelines for making explicit both the cost and effectiveness components. This approach improves the transparency and soundness of the collaborative decision-making process and facilitates the result interpretation.

From Data to Knowledge through Concept-oriented Terminologies

PubMed Central

Cimino, James J.

2000-01-01

Knowledge representation involves enumeration of conceptual symbols and arrangement of these symbols into some meaningful structure. Medical knowledge representation has traditionally focused more on the structure than the symbols. Several significant efforts are under way, at local, national, and international levels, to address the representation of the symbols though the creation of high-quality terminologies that are themselves knowledge based. This paper reviews these efforts, including the Medical Entities Dictionary (MED) in use at Columbia University and the New York Presbyterian Hospital. A decade's experience with the MED is summarized to serve as a proof-of-concept that knowledge-based terminologies can support the use of coded patient data for a variety of knowledge-based activities, including the improved understanding of patient data, the access of information sources relevant to specific patient care problems, the application of expert systems directly to the care of patients, and the discovery of new medical knowledge. The terminological knowledge in the MED has also been used successfully to support clinical application development and maintenance, including that of the MED itself. On the basis of this experience, current efforts to create standard knowledge-based terminologies appear to be justified. PMID:10833166

From data to knowledge through concept-oriented terminologies: experience with the Medical Entities Dictionary.

PubMed

Cimino, J J

2000-01-01

Knowledge representation involves enumeration of conceptual symbols and arrangement of these symbols into some meaningful structure. Medical knowledge representation has traditionally focused more on the structure than the symbols. Several significant efforts are under way, at local, national, and international levels, to address the representation of the symbols though the creation of high-quality terminologies that are themselves knowledge based. This paper reviews these efforts, including the Medical Entities Dictionary (MED) in use at Columbia University and the New York Presbyterian Hospital. A decade's experience with the MED is summarized to serve as a proof-of-concept that knowledge-based terminologies can support the use of coded patient data for a variety of knowledge-based activities, including the improved understanding of patient data, the access of information sources relevant to specific patient care problems, the application of expert systems directly to the care of patients, and the discovery of new medical knowledge. The terminological knowledge in the MED has also been used successfully to support clinical application development and maintenance, including that of the MED itself. On the basis of this experience, current efforts to create standard knowledge-based terminologies appear to be justified.

Inter-level Scaffolding and Sequences of Representational Activities in Teaching a Chemical System with Graphical Simulations

NASA Astrophysics Data System (ADS)

Li, Na; Black, John B.

2016-10-01

Chemistry knowledge can be represented at macro-, micro- and symbolic levels, and learning a chemistry topic requires students to engage in multiple representational activities. This study focused on scaffolding for inter-level connection-making in learning chemistry knowledge with graphical simulations. We also tested whether different sequences of representational activities produced different student learning outcomes in learning a chemistry topic. A sample of 129 seventh graders participated in this study. In a simulation-based environment, participants completed three representational activities to learn several ideal gas law concepts. We conducted a 2 × 3 factorial design experiment. We compared two scaffolding conditions: (1) the inter- level scaffolding condition in which participants received inter-level questions and experienced the dynamic link function in the simulation-based environment and (2) the intra- level scaffolding condition in which participants received intra-level questions and did not experience the dynamic link function. We also compared three different sequences of representational activities: macro-symbolic-micro, micro-symbolic-macro and symbolic-micro-macro. For the scaffolding variable, we found that the inter- level scaffolding condition produced significantly better performance in both knowledge comprehension and application, compared to the intra- level scaffolding condition. For the sequence variable, we found that the macro-symbolic-micro sequence produced significantly better knowledge comprehension performance than the other two sequences; however, it did not benefit knowledge application performance. There was a trend that the treatment group who experienced inter- level scaffolding and the micro-symbolic-macro sequence achieved the best knowledge application performance.

Knowledge representation in space flight operations

NASA Technical Reports Server (NTRS)

Busse, Carl

1989-01-01

In space flight operations rapid understanding of the state of the space vehicle is essential. Representation of knowledge depicting space vehicle status in a dynamic environment presents a difficult challenge. The NASA Jet Propulsion Laboratory has pursued areas of technology associated with the advancement of spacecraft operations environment. This has led to the development of several advanced mission systems which incorporate enhanced graphics capabilities. These systems include: (1) Spacecraft Health Automated Reasoning Prototype (SHARP); (2) Spacecraft Monitoring Environment (SME); (3) Electrical Power Data Monitor (EPDM); (4) Generic Payload Operations Control Center (GPOCC); and (5) Telemetry System Monitor Prototype (TSM). Knowledge representation in these systems provides a direct representation of the intrinsic images associated with the instrument and satellite telemetry and telecommunications systems. The man-machine interface includes easily interpreted contextual graphic displays. These interactive video displays contain multiple display screens with pop-up windows and intelligent, high resolution graphics linked through context and mouse-sensitive icons and text.

Secure Base Narrative Representations and Intimate Partner Violence: A Dyadic Perspective

PubMed Central

Karakurt, Gunnur; Silver, Kristin E.; Keiley, Margaret K.

2015-01-01

This study aimed to understand the relationship between secure base phenomena and dating violence among couples. Within a relationship, a secure base can be defined as a balancing act of proximity-seeking and exploration at various times and contexts with the assurance of a caregiver’s availability and responsiveness in emotionally distressing situations. Participants were 87 heterosexual couples. The Actor-Partner Interdependence Model was used to examine the relationship between each partner’s scores on secure base representational knowledge and intimate partner violence. Findings demonstrated that women’s secure base representational knowledge had a significant direct negative effect on the victimization of both men and women, while men’s secure base representational knowledge did not have any significant partner or actor effects. Therefore, findings suggest that women with insecure attachments may be more vulnerable to being both the victims and the perpetrators of PMID:27445432

Understanding Deep Representations Learned in Modeling Users Likes.

PubMed

Guntuku, Sharath Chandra; Zhou, Joey Tianyi; Roy, Sujoy; Lin, Weisi; Tsang, Ivor W

2016-08-01

Automatically understanding and discriminating different users' liking for an image is a challenging problem. This is because the relationship between image features (even semantic ones extracted by existing tools, viz., faces, objects, and so on) and users' likes is non-linear, influenced by several subtle factors. This paper presents a deep bi-modal knowledge representation of images based on their visual content and associated tags (text). A mapping step between the different levels of visual and textual representations allows for the transfer of semantic knowledge between the two modalities. Feature selection is applied before learning deep representation to identify the important features for a user to like an image. The proposed representation is shown to be effective in discriminating users based on images they like and also in recommending images that a given user likes, outperforming the state-of-the-art feature representations by  ∼ 15 %-20%. Beyond this test-set performance, an attempt is made to qualitatively understand the representations learned by the deep architecture used to model user likes.

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.

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.

a Voxel-Based Metadata Structure for Change Detection in Point Clouds of Large-Scale Urban Areas

NASA Astrophysics Data System (ADS)

Gehrung, J.; Hebel, M.; Arens, M.; Stilla, U.

2018-05-01

Mobile laser scanning has not only the potential to create detailed representations of urban environments, but also to determine changes up to a very detailed level. An environment representation for change detection in large scale urban environments based on point clouds has drawbacks in terms of memory scalability. Volumes, however, are a promising building block for memory efficient change detection methods. The challenge of working with 3D occupancy grids is that the usual raycasting-based methods applied for their generation lead to artifacts caused by the traversal of unfavorable discretized space. These artifacts have the potential to distort the state of voxels in close proximity to planar structures. In this work we propose a raycasting approach that utilizes knowledge about planar surfaces to completely prevent this kind of artifacts. To demonstrate the capabilities of our approach, a method for the iterative volumetric approximation of point clouds that allows to speed up the raycasting by 36 percent is proposed.

Using Ontologies to Formalize Services Specifications in Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Breitman, Karin Koogan; Filho, Aluizio Haendchen; Haeusler, Edward Hermann

2004-01-01

One key issue in multi-agent systems (MAS) is their ability to interact and exchange information autonomously across applications. To secure agent interoperability, designers must rely on a communication protocol that allows software agents to exchange meaningful information. In this paper we propose using ontologies as such communication protocol. Ontologies capture the semantics of the operations and services provided by agents, allowing interoperability and information exchange in a MAS. Ontologies are a formal, machine processable, representation that allows to capture the semantics of a domain and, to derive meaningful information by way of logical inference. In our proposal we use a formal knowledge representation language (OWL) that translates into Description Logics (a subset of first order logic), thus eliminating ambiguities and providing a solid base for machine based inference. The main contribution of this approach is to make the requirements explicit, centralize the specification in a single document (the ontology itself), at the same that it provides a formal, unambiguous representation that can be processed by automated inference machines.

Scientific Disclosure: Social Representations of Brazilian Researchers Acting in the Field of Astronomy

NASA Astrophysics Data System (ADS)

Carneiro, D. L. C. M.

2014-10-01

Science dissemination has unquestioned role on intermediate science and society and it is a wide subject of research in education, considering that the construction of knowledge flows in different spaces, and, consequently, produces and disseminates representations. It presents as a motivator for reflection and as a necessary tool to prevent that knowledge do not become synonymous with domination and power. Thereby, the Astronomy assumes a remarkable role as a trigger of scientific dissemination process, due to its interdisciplinary character. From this viewpoint and the theoretical and methodological framework of the Theory of Social Representations (TRS), grounded by Serge Moscovici, this research, qualitative in nature, seek to answer: What are the social representations about scientific dissemination of Brazilian researchers that act in the field of astronomy? The work was based on Longhini, Gomide and Fernandes (2013) research, which delineate the Brazilian scientific community involved in Astronomy, identifying two groups of researchers with different training paths: one with postgraduate in education and related fields, and other with postgraduate in Physics or Astronomy. Thus, this study had the subquestion: Does the researchers of these groups have different conceptions about the practices of science dissemination? A sample was composed of six subjects, three of each formative course, who participated in semi-structured interviews analyzed following the steps outlined by Spink (2012). The results show that the science dissemination is part of the researches schedule's, with a positive image relative to promote scientific knowledge to population and similar on practical approach between the two groups. Point to two social representations of science dissemination: one for society in general, moved by passion, anchored in values and beliefs, in satisfaction of seeing the results that their actions bring to people's lives; and the other to their pairs. Regarding the first, the core of this work, emerge gaps that hinder the practice of science dissemination, such as lack of professionalism and difficulty of using language accessible to the lay public; the lack of appreciation, so far, of the area and the bureaucracy required in the execution of projects, which come from institutions and sponsoring agencies, and the negative representation about the media, in general, are added to the list of obstacles, inferring that science dissemination is a paradigm in construction. Other considerations are that astronomy is not part of basic education systematic way or the media in general and, not infrequently, in these areas, this science presents with misconceptions. And there is an intersection between science education and science dissemination, wherein the researcher must approach to the elementary school teachers and the population. There is an indication of expanding non-formal spaces of education and the creation of a specific policy for Astronomy. In short, the found representations ponder some of the concerns currently present in society and that are echoed in the theoretical framework of this study, demonstrating that, in Brazil, despite advances, in general, science dissemination, science education, and, specifically, Astronomy Education, are in a social fragility context.

29 CFR 2570.34 - Information to be included in every exemption application.

Code of Federal Regulations, 2010 CFR

2010-07-01

... knowledge and belief, the representations made in such statement are true and correct. (c) An application... with the matters discussed in this application and, to the best of my knowledge and belief, the representations made in this application are true and correct. (ii) This declaration must be dated and signed by...

On the Roles of External Knowledge Representations in Assessment Design

ERIC Educational Resources Information Center

Mislevy, Robert J.; Behrens, John T.; Bennett, Randy E.; Demark, Sarah F.; Frezzo, Dennis C.; Levy, Roy; Robinson, Daniel H.; Rutstein, Daisy Wise; Shute, Valerie J.; Stanley, Ken; Winters, Fielding I.

2010-01-01

People use external knowledge representations (KRs) to identify, depict, transform, store, share, and archive information. Learning how to work with KRs is central to be-coming proficient in virtually every discipline. As such, KRs play central roles in curriculum, instruction, and assessment. We describe five key roles of KRs in assessment: (1)…

"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…

The Influence of Textbooks on Teachers' Knowledge of Chemical Bonding Representations Relative to Students' Difficulties Understanding

ERIC Educational Resources Information Center

Bergqvist, Anna; Chang Rundgren, Shu-Nu

2017-01-01

Background: Textbooks are integral tools for teachers' lessons. Several researchers observed that school teachers rely heavily on textbooks as informational sources when planning lessons. Moreover, textbooks are an important resource for developing students' knowledge as they contain various representations that influence students' learning.…

On the Roles of External Knowledge Representations in Assessment Design. CSE Report 722

ERIC Educational Resources Information Center

Mislevy, Robert J.; Behrens, John T.; Bennett, Randy E.; Demark, Sarah F.; Frezzo, Dennis C.; Levy, Roy; Robinson, Daniel H.; Rutstein, Daisy Wise; Shute, Valerie J.; Stanley, Ken; Winters, Fielding I.

2007-01-01

People use external knowledge representations (EKRs) to identify, depict, transform, store, share, and archive information. Learning how to work with EKRs is central to becoming proficient in virtually every discipline. As such, EKRs play central roles in curriculum, instruction, and assessment. Five key roles of EKRs in educational assessment are…

Disciplinary Representation on Institutional Websites: Changing Knowledge, Changing Power?

ERIC Educational Resources Information Center

O'Connor, Kate; Yates, Lyn

2014-01-01

This paper analyses shifts in the representation of history and physics as named organisational units on Australian university websites over the last 15 years in the context of broader questions about the production of knowledge in contemporary times. It derives from a broader project concerned with disciplinarity, changing university contexts and…

Inter-Level Scaffolding and Sequences of Representational Activities in Teaching a Chemical System with Graphical Simulations

ERIC Educational Resources Information Center

Li, Na; Black, John B.

2016-01-01

Chemistry knowledge can be represented at macro-, micro- and symbolic levels, and learning a chemistry topic requires students to engage in multiple representational activities. This study focused on scaffolding for inter-level connection-making in learning chemistry knowledge with graphical simulations. We also tested whether different sequences…

Developing Explanations and Developing Understanding: Students Explain the Phases of the Moon Using Visual Representations

ERIC Educational Resources Information Center

Parnafes, Orit

2012-01-01

This article presents a theoretical model of the process by which students construct and elaborate explanations of scientific phenomena using visual representations. The model describes progress in the underlying conceptual processes in students' explanations as a reorganization of fine-grained knowledge elements based on the Knowledge in Pieces…

Emerging Standards for Medical Logic

PubMed Central

Clayton, Paul D.; Hripcsak, George; Pryor, T. Allan

1990-01-01

Sharing medical logic has traditionally occurred in the form of lectures, conversations, books and journals. As knowledge based computer systems have demonstrated their utility in the health care arena, individuals have pondered the best way to transfer knowledge in a computer based representation (1). A simple representation which allows the knowledge to be shared can be constructed when the knowledge base is modular. Within this representation, units have been named Medical Logic Modules (MLM's) and a syntax has emerged which would allow multiple users to create, criticize, and share those types of medical logic which can be represented in this format. In this paper we talk about why standards exist and why they emerge in some areas and not in others. The appropriateness of using the proposed standards for medical logic modules is then examined against this broader context.

Students' Understanding of External Representations of the Potassium Ion Channel Protein Part II: Structure-Function Relationships and Fragmented Knowledge

ERIC Educational Resources Information Center

Harle, Marissa; Towns, Marcy H.

2012-01-01

Research that has focused on external representations in biochemistry has uncovered student difficulties in comprehending and interpreting external representations. This study focuses on students' understanding of three external representations (ribbon diagram, wireframe, and hydrophobic/hydrophilic) of the potassium ion channel protein. Analysis…

Learning About Semi Conductors for Teaching—the Role Played by Content Knowledge in Pedagogical Content Knowledge (PCK) Development

NASA Astrophysics Data System (ADS)

Rollnick, Marissa

2017-08-01

This study focuses on how teachers learn to teach a new topic and the role played by their developing content knowledge as they teach. The paper is based on seven high school science teachers' studies on the teaching of semiconductors, at the time a new topic in the curriculum. Analysis of artefacts such as teacher concept maps, video recordings of lessons, journals and other classroom-based evidence shows how the extent and type of teachers' content knowledge informed their choice of teaching approaches and how their learning of content took place alongside the development of teaching strategies. The development of content knowledge was combined with increased understanding of how to teach the topic in almost all cases. Evidence of development of teachers' PCK was found in their increased ability to design teaching strategies, and their use of representations and suitable assessment tasks for their lessons. Some specific common teaching strategies were identified across the teachers. These strategies could add to the canon of teachers' topic - specific professional knowledge for semiconductors. The study provides increased understanding of how teachers simultaneously master content and its teaching and how mediated self-reflection is a fruitful approach for assisting teachers to learn to teach a new topic.

The Representation of Self and Person Knowledge in the Medial Prefrontal Cortex

PubMed Central

Haxby, James V.; Heatherton, Todd F.

2012-01-01

Nearly forty years ago, social psychologists began applying the information processing framework of cognitive psychology to the question of how humans understand and represent knowledge about themselves and others. This approach gave rise to the immensely successful field of social cognition and fundamentally changed the way in which social psychological phenomena are studied. More recently, social scientists of many stripes have turned to the methods of cognitive neuroscience to understand the neural basis of social cognition. A pervasive finding from this research is that social knowledge, be it about one's self or of others, is represented in the medial prefrontal cortex. This review focuses on the social cognitive neuroscience of self and person knowledge in the medial prefrontal cortex. We begin with a brief historical overview of social cognition, followed by a review of recent and influential research on the brain basis of self and person knowledge. In the latter half of this review we discuss the role of familiarity and similarity in person perception and of spontaneous processes in self and other referential cognition. Throughout, we discuss the myriad ways in which the social cognitive neuroscience approach has provided new insights into the nature and structure of self and person knowledge. PMID:22712038

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.

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.

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

Social Context Disambiguates the Interpretation of Laughter.

PubMed

Curran, William; McKeown, Gary J; Rychlowska, Magdalena; André, Elisabeth; Wagner, Johannes; Lingenfelser, Florian

2017-01-01

Despite being a pan-cultural phenomenon, laughter is arguably the least understood behaviour deployed in social interaction. As well as being a response to humour, it has other important functions including promoting social affiliation, developing cooperation and regulating competitive behaviours. This multi-functional feature of laughter marks it as an adaptive behaviour central to facilitating social cohesion. However, it is not clear how laughter achieves this social cohesion. We consider two approaches to understanding how laughter facilitates social cohesion - the 'representational' approach and the 'affect-induction' approach. The representational approach suggests that laughter conveys information about the expresser's emotional state, and the listener decodes this information to gain knowledge about the laugher's felt state. The affect-induction approach views laughter as a tool to influence the affective state of listeners. We describe a modified version of the affect-induction approach, in which laughter is combined with additional factors - including social context, verbal information, other social signals and knowledge of the listener's emotional state - to influence an interaction partner. This view asserts that laughter by itself is ambiguous: the same laughter may induce positive or negative affect in a listener, with the outcome determined by the combination of these additional factors. Here we describe two experiments exploring which of these approaches accurately describes laughter. Participants judged the genuineness of audio-video recordings of social interactions containing laughter. Unknown to the participants the recordings contained either the original laughter or replacement laughter from a different part of the interaction. When replacement laughter was matched for intensity, genuineness judgements were similar to judgements of the original unmodified recordings. When replacement laughter was not matched for intensity, genuineness judgements were generally significantly lower. These results support the affect-induction view of laughter by suggesting that laughter is inherently underdetermined and ambiguous, and that its interpretation is determined by the context in which it occurs.

Two Different Approaches to Automated Mark Up of Emotions in Text

NASA Astrophysics Data System (ADS)

Francisco, Virginia; Hervás, Raqucl; Gervás, Pablo

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

New knowledge network evaluation method for design rationale management

NASA Astrophysics Data System (ADS)

Jing, Shikai; Zhan, Hongfei; Liu, Jihong; Wang, Kuan; Jiang, Hao; Zhou, Jingtao

2015-01-01

Current design rationale (DR) systems have not demonstrated the value of the approach in practice since little attention is put to the evaluation method of DR knowledge. To systematize knowledge management process for future computer-aided DR applications, a prerequisite is to provide the measure for the DR knowledge. In this paper, a new knowledge network evaluation method for DR management is presented. The method characterizes the DR knowledge value from four perspectives, namely, the design rationale structure scale, association knowledge and reasoning ability, degree of design justification support and degree of knowledge representation conciseness. The DR knowledge comprehensive value is also measured by the proposed method. To validate the proposed method, different style of DR knowledge network and the performance of the proposed measure are discussed. The evaluation method has been applied in two realistic design cases and compared with the structural measures. The research proposes the DR knowledge evaluation method which can provide object metric and selection basis for the DR knowledge reuse during the product design process. In addition, the method is proved to be more effective guidance and support for the application and management of DR knowledge.

Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS

NASA Astrophysics Data System (ADS)

Liu, Ying; Xiao, Han; Wang, Limin; Han, Jialing

2017-07-01

Lack of semantic interoperability in geographical information systems has been identified as the main obstacle for data sharing and database integration. The new method should be found to overcome the problems of semantic heterogeneity. Ontologies are considered to be one approach to support geographic information sharing. This paper presents an ontology-driven integration approach to help in detecting and possibly resolving semantic conflicts. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration through regulation of semantic integration algorithm. Finally, land classification in field GIS is described as the example.

Identifying knowledge activism in worker health and safety representation: A cluster analysis.

PubMed

Hall, Alan; Oudyk, John; King, Andrew; Naqvi, Syed; Lewchuk, Wayne

2016-01-01

Although worker representation in OHS has been widely recognized as contributing to health and safety improvements at work, few studies have examined the role that worker representatives play in this process. Using a large quantitative sample, this paper seeks to confirm findings from an earlier exploratory qualitative study that worker representatives can be differentiated by the knowledge intensive tactics and strategies that they use to achieve changes in their workplace. Just under 900 worker health and safety representatives in Ontario completed surveys which asked them to report on the amount of time they devoted to different types of representation activities (i.e., technical activities such as inspections and report writing vs. political activities such as mobilizing workers to build support), the kinds of conditions or hazards they tried to address through their representation (e.g., housekeeping vs. modifications in ventilation systems), and their reported success in making positive improvements. A cluster analysis was used to determine whether the worker representatives could be distinguished in terms of the relative time devoted to different activities and the clusters were then compared with reference to types of intervention efforts and outcomes. The cluster analysis identified three distinct groupings of representatives with significant differences in reported types of interventions and in their level of reported impact. Two of the clusters were consistent with the findings in the exploratory study, identified as knowledge activism for greater emphasis on knowledge based political activity and technical-legal representation for greater emphasis on formalized technical oriented procedures and legal regulations. Knowledge activists were more likely to take on challenging interventions and they reported more impact across the full range of interventions. This paper provides further support for the concepts of knowledge activism and technical-legal representation when differentiating the strategic orientations and impact of worker health and safety representatives, with important implications for education, political support and recruitment. © 2015 Wiley Periodicals, Inc.

Sparse representation of electrodermal activity with knowledge-driven dictionaries.

PubMed

Chaspari, Theodora; Tsiartas, Andreas; Stein, Leah I; Cermak, Sharon A; Narayanan, Shrikanth S

2015-03-01

Biometric sensors and portable devices are being increasingly embedded into our everyday life, creating the need for robust physiological models that efficiently represent, analyze, and interpret the acquired signals. We propose a knowledge-driven method to represent electrodermal activity (EDA), a psychophysiological signal linked to stress, affect, and cognitive processing. We build EDA-specific dictionaries that accurately model both the slow varying tonic part and the signal fluctuations, called skin conductance responses (SCR), and use greedy sparse representation techniques to decompose the signal into a small number of atoms from the dictionary. Quantitative evaluation of our method considers signal reconstruction, compression rate, and information retrieval measures, that capture the ability of the model to incorporate the main signal characteristics, such as SCR occurrences. Compared to previous studies fitting a predetermined structure to the signal, results indicate that our approach provides benefits across all aforementioned criteria. This paper demonstrates the ability of appropriate dictionaries along with sparse decomposition methods to reliably represent EDA signals and provides a foundation for automatic measurement of SCR characteristics and the extraction of meaningful EDA features.

Enhancing biomedical text summarization using semantic relation extraction.

PubMed

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

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.

Artificial muscles' enrichment text: Chemical Literacy Profile of pre-service teachers

NASA Astrophysics Data System (ADS)

Hernani, Ulum, Luthfi Lulul; Mudzakir, Ahmad

2017-08-01

This research aims to determine the profile of chemical literacy abilities of pre-service teachers based on scientific attitudes and scientific competencies in PISA 2015 through individualized learning by using an artificial muscle context based-enrichment book. This research uses descriptive method, involving 20 of the 90 randomly selected population. This research uses a multiple-choice questions instrument. The result of this research are : 1) in the attitude aspects of interest in science and technology, valuing scientific approaches to inquiry, and environmental awareness, the results obtained respectively for 90%, 80%, and 30%. 2) for scientific competence of apply appropriate scientific knowledge, identify models and representations, make appropriate predictions, and explain the potential implications of scientific knowledge for society, the results obtained respectively for 30%, 50%, 60%, and 55%. 3) For scientific competence of identify the question explored in a given scientific study and distinguish questions that could be investigated scientifically, the results obtained respectively for 30 % and 50%. 4) For scientific competence of transform data from one representation to another and draw appropriate conclusions, the results obtained respectively for 60% and 45%. Based on the results, which need to be developed in pre-service chemistry teachers are environmental awareness, apply appropriate scientific knowledge, identify the question explored in a given scientific study, and draw appropriate conclusions.

Functional Abstraction as a Method to Discover Knowledge in Gene Ontologies

PubMed Central

Ultsch, Alfred; Lötsch, Jörn

2014-01-01

Computational analyses of functions of gene sets obtained in microarray analyses or by topical database searches are increasingly important in biology. To understand their functions, the sets are usually mapped to Gene Ontology knowledge bases by means of over-representation analysis (ORA). Its result represents the specific knowledge of the functionality of the gene set. However, the specific ontology typically consists of many terms and relationships, hindering the understanding of the ‘main story’. We developed a methodology to identify a comprehensibly small number of GO terms as “headlines” of the specific ontology allowing to understand all central aspects of the roles of the involved genes. The Functional Abstraction method finds a set of headlines that is specific enough to cover all details of a specific ontology and is abstract enough for human comprehension. This method exceeds the classical approaches at ORA abstraction and by focusing on information rather than decorrelation of GO terms, it directly targets human comprehension. Functional abstraction provides, with a maximum of certainty, information value, coverage and conciseness, a representation of the biological functions in a gene set plays a role. This is the necessary means to interpret complex Gene Ontology results thus strengthening the role of functional genomics in biomarker and drug discovery. PMID:24587272

[Social representations on HIV/AIDS among adolescentes: implications for nursing care].

PubMed

Thiengo, Maria Aparecida; de Oliveira, Denize Cristina; Rodrigues, Benedita Maria Rêgo Deusdará

2005-03-01

With the objective of discussing the implications of the social representations of HIV/AIDS for the interpersonal relations and the practices for protection among adolescents, 15 semidirective interviews were carried out with adolescents, both with and without HIV, assisted at a Hospital School in Rio de Janeiro. The software ALCESTE 4.5 was used for the data analysis. It was observed that the social representation of AIDS is structured around cognitions connected to prevention, revealing a contradiction between the knowledge and the practices reported by the group. It is suggested that the nursing practices should be directed towards the reduction of the distance between practices, representations and scientific knowledge.

Neuronal foundations of human numerical representations.

PubMed

Eger, E

2016-01-01

The human species has developed complex mathematical skills which likely emerge from a combination of multiple foundational abilities. One of them seems to be a preverbal capacity to extract and manipulate the numerosity of sets of objects which is shared with other species and in humans is thought to be integrated with symbolic knowledge to result in a more abstract representation of numerical concepts. For what concerns the functional neuroanatomy of this capacity, neuropsychology and functional imaging have localized key substrates of numerical processing in parietal and frontal cortex. However, traditional fMRI mapping relying on a simple subtraction approach to compare numerical and nonnumerical conditions is limited to tackle with sufficient precision and detail the issue of the underlying code for number, a question which more easily lends itself to investigation by methods with higher spatial resolution, such as neurophysiology. In recent years, progress has been made through the introduction of approaches sensitive to within-category discrimination in combination with fMRI (adaptation and multivariate pattern recognition), and the present review summarizes what these have revealed so far about the neural coding of individual numbers in the human brain, the format of these representations and parallels between human and monkey neurophysiology findings. © 2016 Elsevier B.V. All rights reserved.

Designing Intelligent Computer Aided Instruction Systems with Integrated Knowledge Representation Schemes

DTIC Science & Technology

1990-06-01

the form of structured objects was first pioneered by Marvin Minsky . In his seminal article " A Framework for Representing Knowl- edge" he introduced... Minsky felt that the existing methods of knowledge representation were too finely grained and he proposed that knowledge is more than just a...not work" in realistic, complex domains. ( Minsky , 1981, pp. 95-128) According to Minsky "A frame is a data-structure for representing a stereo- typed

Decision support systems in water and wastewater treatment process selection and design: a review.

PubMed

Hamouda, M A; Anderson, W B; Huck, P M

2009-01-01

The continuously changing drivers of the water treatment industry, embodied by rigorous environmental and health regulations and the challenge of emerging contaminants, necessitates the development of decision support systems for the selection of appropriate treatment trains. This paper explores a systematic approach to developing decision support systems, which includes the analysis of the treatment problem(s), knowledge acquisition and representation, and the identification and evaluation of criteria controlling the selection of optimal treatment systems. The objective of this article is to review approaches and methods used in decision support systems developed to aid in the selection, sequencing of unit processes and design of drinking water, domestic wastewater, and industrial wastewater treatment systems. Not surprisingly, technical considerations were found to dominate the logic of the developed systems. Most of the existing decision-support tools employ heuristic knowledge. It has been determined that there is a need to develop integrated decision support systems that are generic, usable and consider a system analysis approach.

Improving the human readability of Arden Syntax medical logic modules using a concept-oriented terminology and object-oriented programming expressions.

PubMed

Choi, Jeeyae; Bakken, Suzanne; Lussier, Yves A; Mendonça, Eneida A

2006-01-01

Medical logic modules are a procedural representation for sharing task-specific knowledge for decision support systems. Based on the premise that clinicians may perceive object-oriented expressions as easier to read than procedural rules in Arden Syntax-based medical logic modules, we developed a method for improving the readability of medical logic modules. Two approaches were applied: exploiting the concept-oriented features of the Medical Entities Dictionary and building an executable Java program to replace Arden Syntax procedural expressions. The usability evaluation showed that 66% of participants successfully mapped all Arden Syntax rules to Java methods. These findings suggest that these approaches can play an essential role in the creation of human readable medical logic modules and can potentially increase the number of clinical experts who are able to participate in the creation of medical logic modules. Although our approaches are broadly applicable, we specifically discuss the relevance to concept-oriented nursing terminologies and automated processing of task-specific nursing knowledge.

Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

PubMed

An, Gary

2009-01-01

The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

Introducing the Big Knowledge to Use (BK2U) challenge.

PubMed

Perl, Yehoshua; Geller, James; Halper, Michael; Ochs, Christopher; Zheng, Ling; Kapusnik-Uner, Joan

2017-01-01

The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK), how can it be used properly and creatively? We call this secondary challenge, Big Knowledge to Use. Without a high-level mental representation of the kinds of knowledge in a BK knowledgebase, effective or innovative use of the knowledge may be limited. We describe summarization and visualization techniques that capture the big picture of a BK knowledgebase, possibly created from Big Data. In this research, we distinguish between assertion BK and rule-based BK (rule BK) and demonstrate the usefulness of summarization and visualization techniques of assertion BK for clinical phenotyping. As an example, we illustrate how a summary of many intracranial bleeding concepts can improve phenotyping, compared to the traditional approach. We also demonstrate the usefulness of summarization and visualization techniques of rule BK for drug-drug interaction discovery. © 2016 New York Academy of Sciences.

Introducing the Big Knowledge to Use (BK2U) challenge

PubMed Central

Perl, Yehoshua; Geller, James; Halper, Michael; Ochs, Christopher; Zheng, Ling; Kapusnik-Uner, Joan

2016-01-01

The purpose of the Big Data to Knowledge (BD2K) initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK), how can it be used properly and creatively? We call this secondary challenge, Big Knowledge to Use (BK2U). Without a high-level mental representation of the kinds of knowledge in a BK knowledgebase, effective or innovative use of the knowledge may be limited. We describe summarization and visualization techniques that capture the big picture of a BK knowledgebase, possibly created from Big Data. In this research, we distinguish between assertion BK and rule-based BK and demonstrate the usefulness of summarization and visualization techniques of assertion BK for clinical phenotyping. As an example, we illustrate how a summary of many intracranial bleeding concepts can improve phenotyping, compared to the traditional approach. We also demonstrate the usefulness of summarization and visualization techniques of rule-based BK for drug–drug interaction discovery. PMID:27750400

Der Aufbau mentaler Modelle durch bildliche Darstellungen: Eine experimentalle Studie uber die Bedeutung der Merkmalsdimensionen Elaboriertheit und Strukturierheit im Sachunterricht der Grundschule (The Development of Mental Processes through Graphic Representation with Diverging Degrees of Elaboration and Structurization: An Experimental Study Carried Out in Elementary Science Instruction in Primary School).

ERIC Educational Resources Information Center

Martschinke, Sabine

1996-01-01

Examines types of graphical representation as to their suitability for knowledge acquisition in primary grades. Uses the concept of mental models to clarify the relationship between external presentation and internal representation of knowledge. Finds that students who learned with highly elaborated and highly structured pictures displayed the…

Semantic framework for mapping object-oriented model to semantic web languages

PubMed Central

Ježek, Petr; Mouček, Roman

2015-01-01

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework. PMID:25762923

Semantic framework for mapping object-oriented model to semantic web languages.

PubMed

Ježek, Petr; Mouček, Roman

2015-01-01

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

Bag-of-visual-ngrams for histopathology image classification

NASA Astrophysics Data System (ADS)

López-Monroy, A. Pastor; Montes-y-Gómez, Manuel; Escalante, Hugo Jair; Cruz-Roa, Angel; González, Fabio A.

2013-11-01

This paper describes an extension of the Bag-of-Visual-Words (BoVW) representation for image categorization (IC) of histophatology images. This representation is one of the most used approaches in several high-level computer vision tasks. However, the BoVW representation has an important limitation: the disregarding of spatial information among visual words. This information may be useful to capture discriminative visual-patterns in specific computer vision tasks. In order to overcome this problem we propose the use of visual n-grams. N-grams based-representations are very popular in the field of natural language processing (NLP), in particular within text mining and information retrieval. We propose building a codebook of n-grams and then representing images by histograms of visual n-grams. We evaluate our proposal in the challenging task of classifying histopathology images. The novelty of our proposal lies in the fact that we use n-grams as attributes for a classification model (together with visual-words, i.e., 1-grams). This is common practice within NLP, although, to the best of our knowledge, this idea has not been explored yet within computer vision. We report experimental results in a database of histopathology images where our proposed method outperforms the traditional BoVWs formulation.

On acquiring decision making skills for endovascular interventions.

PubMed

Lanzer, Peter; Prechelt, Lutz

2008-11-01

To improve interventional training we propose a staged rational approach for decision making and skill acquisition. Education and training for endovascular interventions should start to develop the learners' decision-making skills by learning from explicit representations of master interventionist's tacit decision-making knowledge through implementation of the notions of generic interventional modules, interventional strategic and tactical designs. We hope that these suggestions will encourage action, stimulate dialogue and advance the precision of our learning, procedures, practice and patient care.

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology

PubMed Central

Roncaglia, Paola; Howe, Douglas G.; Laulederkind, Stanley J.F.; Khodiyar, Varsha K.; Berardini, Tanya Z.; Tweedie, Susan; Foulger, Rebecca E.; Osumi-Sutherland, David; Campbell, Nancy H.; Huntley, Rachael P.; Talmud, Philippa J.; Blake, Judith A.; Breckenridge, Ross; Riley, Paul R.; Lambiase, Pier D.; Elliott, Perry M.; Clapp, Lucie; Tinker, Andrew; Hill, David P.

2018-01-01

Background: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. Methods and Results: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. Conclusions: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. PMID:29440116

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

PubMed

Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

2018-02-01

A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

Enhancing students’ mathematical representation and selfefficacy through situation-based learning assisted by geometer’s sketchpad program

NASA Astrophysics Data System (ADS)

Sowanto; Kusumah, Y. S.

2018-05-01

This research was conducted based on the problem of a lack of students’ mathematical representation ability as well as self-efficacy in accomplishing mathematical tasks. To overcome this problem, this research used situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP). This research investigated students’ improvement of mathematical representation ability who were taught under situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP) and regular method that viewed from the whole students’ prior knowledge (high, average, and low level). In addition, this research investigated the difference of students’ self-efficacy after learning was given. This research belongs to quasi experiment research using non-equivalent control group design with purposive sampling. The result of this research showed that students’ enhancement in their mathematical representation ability taught under SBL assisted by GSP was better than the regular method. Also, there was no interaction between learning methods and students prior knowledge in student’ enhancement of mathematical representation ability. There was significant difference of students’ enhancement of mathematical representation ability taught under SBL assisted by GSP viewed from students’ prior knowledge. Furthermore, there was no significant difference in terms of self-efficacy between those who were taught by SBL assisted by GSP with the regular method.

In defense of abstract conceptual representations.

PubMed

Binder, Jeffrey R

2016-08-01

An extensive program of research in the past 2 decades has focused on the role of modal sensory, motor, and affective brain systems in storing and retrieving concept knowledge. This focus has led in some circles to an underestimation of the need for more abstract, supramodal conceptual representations in semantic cognition. Evidence for supramodal processing comes from neuroimaging work documenting a large, well-defined cortical network that responds to meaningful stimuli regardless of modal content. The nodes in this network correspond to high-level "convergence zones" that receive broadly crossmodal input and presumably process crossmodal conjunctions. It is proposed that highly conjunctive representations are needed for several critical functions, including capturing conceptual similarity structure, enabling thematic associative relationships independent of conceptual similarity, and providing efficient "chunking" of concept representations for a range of higher order tasks that require concepts to be configured as situations. These hypothesized functions account for a wide range of neuroimaging results showing modulation of the supramodal convergence zone network by associative strength, lexicality, familiarity, imageability, frequency, and semantic compositionality. The evidence supports a hierarchical model of knowledge representation in which modal systems provide a mechanism for concept acquisition and serve to ground individual concepts in external reality, whereas broadly conjunctive, supramodal representations play an equally important role in concept association and situation knowledge.

Dialect Variation and Phonological Knowledge: Phonological Representations and Metalinguistic Awareness among Beginning Readers who Speak Nonmainstream American English

ERIC Educational Resources Information Center

Terry, Nicole Patton

2014-01-01

Children's spoken nonmainstream American English (NMAE) dialect use and their knowledge about phonological representations of word pronunciations were assessed in a sample of 105 children in kindergarten through second grade. Children were given expressive and receptive tasks with dialect-sensitive stimuli. Students who produced many NMAE…

Meta-Representation in an Algebra I Classroom

ERIC Educational Resources Information Center

Izsak, Andrew; Caglayan, Gunhan; Olive, John

2009-01-01

We describe how 1 Algebra I teacher and her 8th-grade students used meta-representational knowledge when generating and evaluating equations to solve word problems. Analyzing data from a sequence of 4 lessons, we found that the teacher and her students used criteria for evaluating equations, in addition to other types of knowledge (e.g., different…

Exploring the Progression in Preservice Chemistry Teachers' Pedagogical Content Knowledge Representations: The Case of "Behavior of Gases"

ERIC Educational Resources Information Center

Adadan, Emine; Oner, Diler

2014-01-01

This multiple case study investigated how two preservice chemistry teachers' pedagogical content knowledge (PCK) representations of behavior of gases progressed in the context of a semester-long chemistry teaching methods course. The change in the participants' PCK components was interpreted with respect to the theoretical PCK learning…

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 Investigation of Pattern Problems Posed by Middle School Mathematics Preservice Teachers Using Multiple Representation

ERIC Educational Resources Information Center

Yilmaz, Yasemin; Durmus, Soner; Yaman, Hakan

2018-01-01

This study investigated the pattern problems posed by middle school mathematics preservice teachers using multiple representations to determine both their pattern knowledge levels and their abilities to transfer this knowledge to students. The design of the study is the survey method, one of the quantitative research methods. The study group was…

Advantages of Thesaurus Representation Using the Simple Knowledge Organization System (SKOS) Compared with Proposed Alternatives

ERIC Educational Resources Information Center

Pastor-Sanchez, Juan-Antonio; Martinez Mendez, Francisco Javier; Rodriguez-Munoz, Jose Vicente

2009-01-01

Introduction: This paper presents an analysis of the Simple Knowledge Organization System (SKOS) compared with other alternatives for thesaurus representation in the Semantic Web. Method: Based on functional and structural changes of thesauri, provides an overview of the current context in which lexical paradigm is abandoned in favour of the…

24 CFR 4001.116 - Representations and prohibitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 5 2012-04-01 2012-04-01 false Representations and prohibitions... Eligibility Requirements and Underwriting Procedures § 4001.116 Representations and prohibitions. (a... actual knowledge furnished material information known to be false for the purpose of obtaining the...

24 CFR 4001.116 - Representations and prohibitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Representations and prohibitions... Eligibility Requirements and Underwriting Procedures § 4001.116 Representations and prohibitions. (a... actual knowledge furnished material information known to be false for the purpose of obtaining the...

24 CFR 4001.116 - Representations and prohibitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 5 2011-04-01 2011-04-01 false Representations and prohibitions... Eligibility Requirements and Underwriting Procedures § 4001.116 Representations and prohibitions. (a... actual knowledge furnished material information known to be false for the purpose of obtaining the...

Evaluating views of lecturers on the consistency of teaching content with teaching approach: traditional versus reform calculus

NASA Astrophysics Data System (ADS)

Sevimli, Eyup

2016-08-01

This study aims to evaluate the consistency of teaching content with teaching approaches in calculus on the basis of lecturers' views. In this sense, the structures of the examples given in two commonly used calculus textbooks, both in traditional and reform classrooms, are compared. The content analysis findings show that the examples in both textbooks are presented in a rather formal language and generally highlight procedural knowledge. And, even though the examples in the reform book chosen are structured using multiple representations, only a small number of them incorporated the usage of instructional technology. The lecturers' views which were gathered indicated that, although, on the one hand, the example structures of the traditional textbook largely overlapped with the characteristics of the traditional approach, the example structures of the reform textbook, on the other hand, were found to be inconsistent with the characteristics of the reform approach, especially with regard to its environment and knowledge components. At the end of the paper, some suggestions for further studies are provided for book authors and researchers.

Mammographic mass classification based on possibility theory

NASA Astrophysics Data System (ADS)

Hmida, Marwa; Hamrouni, Kamel; Solaiman, Basel; Boussetta, Sana

2017-03-01

Shape and margin features are very important for differentiating between benign and malignant masses in mammographic images. In fact, benign masses are usually round and oval and have smooth contours. However, malignant tumors have generally irregular shape and appear lobulated or speculated in margins. This knowledge suffers from imprecision and ambiguity. Therefore, this paper deals with the problem of mass classification by using shape and margin features while taking into account the uncertainty linked to the degree of truth of the available information and the imprecision related to its content. Thus, in this work, we proposed a novel mass classification approach which provides a possibility based representation of the extracted shape features and builds a possibility knowledge basis in order to evaluate the possibility degree of malignancy and benignity for each mass. For experimentation, the MIAS database was used and the classification results show the great performance of our approach in spite of using simple features.

Automating a human factors evaluation of graphical user interfaces for NASA applications: An update on CHIMES

NASA Technical Reports Server (NTRS)

Jiang, Jian-Ping; Murphy, Elizabeth D.; Bailin, Sidney C.; Truszkowski, Walter F.

1993-01-01

Capturing human factors knowledge about the design of graphical user interfaces (GUI's) and applying this knowledge on-line are the primary objectives of the Computer-Human Interaction Models (CHIMES) project. The current CHIMES prototype is designed to check a GUI's compliance with industry-standard guidelines, general human factors guidelines, and human factors recommendations on color usage. Following the evaluation, CHIMES presents human factors feedback and advice to the GUI designer. The paper describes the approach to modeling human factors guidelines, the system architecture, a new method developed to convert quantitative RGB primaries into qualitative color representations, and the potential for integrating CHIMES with user interface management systems (UIMS). Both the conceptual approach and its implementation are discussed. This paper updates the presentation on CHIMES at the first International Symposium on Ground Data Systems for Spacecraft Control.

Getting Mental Models and Computer Models to Cooperate

NASA Technical Reports Server (NTRS)

Sheridan, T. B.; Roseborough, J.; Charney, L.; Mendel, M.

1984-01-01

A qualitative theory of supervisory control is outlined wherein the mental models of one or more human operators are related to the knowledge representations within automatic controllers (observers, estimators) and operator decision aids (expert systems, advice-givers). Methods of quantifying knowledge and the calibration of one knowledge representation to another (human, computer, or objective truth) are discussed. Ongoing experiments in the use of decision aids for exploring one's own objective function or exploring system constraints and control strategies are described.

Towards Ontology as Knowledge Representation for Intellectual Capital Measurement

NASA Astrophysics Data System (ADS)

Zadjabbari, B.; Wongthongtham, P.; Dillon, T. S.

For many years, physical asset indicators were the main evidence of an organization’s successful performance. However, the situation has changed after information technology revolution in the knowledge-based economy. Since 1980’s business performance has not been limited only to physical assets instead intellectual capital are increasingly playing a major role in business performance. In this paper, we utilize ontology as a tool for knowledge representation in the domain of intellectual capital measurement. The ontology classifies ways of intangible capital measurement.

Conceptual Tools for Understanding Nature - Proceedings of the 3rd International Symposium

NASA Astrophysics Data System (ADS)

Costa, G.; Calucci, M.

1997-04-01

The Table of Contents for the full book PDF is as follows: * Foreword * Some Limits of Science and Scientists * Three Limits of Scientific Knowledge * On Features and Meaning of Scientific Knowledge * How Science Approaches the World: Risky Truths versus Misleading Certitudes * On Discovery and Justification * Thought Experiments: A Philosophical Analysis * Causality: Epistemological Questions and Cognitive Answers * Scientific Inquiry via Rational Hypothesis Revision * Probabilistic Epistemology * The Transferable Belief Model for Uncertainty Representation * Chemistry and Complexity * The Difficult Epistemology of Medicine * Epidemiology, Causality and Medical Anthropology * Conceptual Tools for Transdisciplinary Unified Theory * Evolution and Learning in Economic Organizations * The Possible Role of Symmetry in Physics and Cosmology * Observational Cosmology and/or other Imaginable Models of the Universe

A fuzzy case based reasoning tool for model based approach to rocket engine health monitoring

NASA Technical Reports Server (NTRS)

Krovvidy, Srinivas; Nolan, Adam; Hu, Yong-Lin; Wee, William G.

1992-01-01

In this system we develop a fuzzy case based reasoner that can build a case representation for several past anomalies detected, and we develop case retrieval methods that can be used to index a relevant case when a new problem (case) is presented using fuzzy sets. The choice of fuzzy sets is justified by the uncertain data. The new problem can be solved using knowledge of the model along with the old cases. This system can then be used to generalize the knowledge from previous cases and use this generalization to refine the existing model definition. This in turn can help to detect failures using the model based algorithms.

Concepts, Control, and Context: A Connectionist Account of Normal and Disordered Semantic Cognition

PubMed Central

2018-01-01

Semantic cognition requires conceptual representations shaped by verbal and nonverbal experience and executive control processes that regulate activation of knowledge to meet current situational demands. A complete model must also account for the representation of concrete and abstract words, of taxonomic and associative relationships, and for the role of context in shaping meaning. We present the first major attempt to assimilate all of these elements within a unified, implemented computational framework. Our model combines a hub-and-spoke architecture with a buffer that allows its state to be influenced by prior context. This hybrid structure integrates the view, from cognitive neuroscience, that concepts are grounded in sensory-motor representation with the view, from computational linguistics, that knowledge is shaped by patterns of lexical co-occurrence. The model successfully codes knowledge for abstract and concrete words, associative and taxonomic relationships, and the multiple meanings of homonyms, within a single representational space. Knowledge of abstract words is acquired through (a) their patterns of co-occurrence with other words and (b) acquired embodiment, whereby they become indirectly associated with the perceptual features of co-occurring concrete words. The model accounts for executive influences on semantics by including a controlled retrieval mechanism that provides top-down input to amplify weak semantic relationships. The representational and control elements of the model can be damaged independently, and the consequences of such damage closely replicate effects seen in neuropsychological patients with loss of semantic representation versus control processes. Thus, the model provides a wide-ranging and neurally plausible account of normal and impaired semantic cognition. PMID:29733663

Representations and Rafts

ERIC Educational Resources Information Center

Hartweg, Kimberly Sipes

2011-01-01

To build on prior knowledge and mathematical understanding, middle school students need to be given the opportunity to make connections among a variety of representations. Graphs, tables, algebraic formulas, and models are just a few examples of representations that can help students explore quantitative relationships. As a mathematics educator,…

Ontology to relational database transformation for web application development and maintenance

NASA Astrophysics Data System (ADS)

Mahmudi, Kamal; Inggriani Liem, M. M.; Akbar, Saiful

2018-03-01

Ontology is used as knowledge representation while database is used as facts recorder in a KMS (Knowledge Management System). In most applications, data are managed in a database system and updated through the application and then they are transformed to knowledge as needed. Once a domain conceptor defines the knowledge in the ontology, application and database can be generated from the ontology. Most existing frameworks generate application from its database. In this research, ontology is used for generating the application. As the data are updated through the application, a mechanism is designed to trigger an update to the ontology so that the application can be rebuilt based on the newest ontology. By this approach, a knowledge engineer has a full flexibility to renew the application based on the latest ontology without dependency to a software developer. In many cases, the concept needs to be updated when the data changed. The framework is built and tested in a spring java environment. A case study was conducted to proof the concepts.

Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning.

PubMed

Hoehndorf, Robert; Dumontier, Michel; Oellrich, Anika; Rebholz-Schuhmann, Dietrich; Schofield, Paul N; Gkoutos, Georgios V

2011-01-01

Researchers design ontologies as a means to accurately annotate and integrate experimental data across heterogeneous and disparate data- and knowledge bases. Formal ontologies make the semantics of terms and relations explicit such that automated reasoning can be used to verify the consistency of knowledge. However, many biomedical ontologies do not sufficiently formalize the semantics of their relations and are therefore limited with respect to automated reasoning for large scale data integration and knowledge discovery. We describe a method to improve automated reasoning over biomedical ontologies and identify several thousand contradictory class definitions. Our approach aligns terms in biomedical ontologies with foundational classes in a top-level ontology and formalizes composite relations as class expressions. We describe the semi-automated repair of contradictions and demonstrate expressive queries over interoperable ontologies. Our work forms an important cornerstone for data integration, automatic inference and knowledge discovery based on formal representations of knowledge. Our results and analysis software are available at http://bioonto.de/pmwiki.php/Main/ReasonableOntologies.

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.

Improving the representation of photosynthesis in Earth system models

NASA Astrophysics Data System (ADS)

Rogers, A.; Medlyn, B. E.; Dukes, J.; Bonan, G. B.; von Caemmerer, S.; Dietze, M.; Kattge, J.; Leakey, A. D.; Mercado, L. M.; Niinemets, U.; Prentice, I. C. C.; Serbin, S.; Sitch, S.; Way, D. A.; Zaehle, S.

2015-12-01

Continued use of fossil fuel drives an accelerating increase in atmospheric CO2 concentration ([CO2]) and is the principal cause of global climate change. Many of the observed and projected impacts of rising [CO2] portend increasing environmental and economic risk, yet the uncertainty surrounding the projection of our future climate by Earth System Models (ESMs) is unacceptably high. Improving confidence in our estimation of future [CO2] is essential if we seek to project global change with greater confidence. There are critical uncertainties over the long term response of terrestrial CO2 uptake to global change, more specifically, over the size of the terrestrial carbon sink and over its sensitivity to rising [CO2] and temperature. Reducing the uncertainty associated with model representation of the largest CO2 flux on the planet is therefore an essential part of improving confidence in projections of global change. Here we have examined model representation of photosynthesis in seven process models including several global models that underlie the representation of photosynthesis in the land surface model component of ESMs that were part of the recent Fifth Assessment Report from the IPCC. Our approach was to focus on how physiological responses are represented by these models, and to better understand how structural and parametric differences drive variation in model responses to light, CO2, nutrients, temperature, vapor pressure deficit and soil moisture. We challenged each model to produce leaf and canopy responses to these factors to help us identify areas in which current process knowledge and emerging data sets could be used to improve model skill, and also identify knowledge gaps in current understanding that directly impact model outputs. We hope this work will provide a roadmap for the scientific activity that is necessary to advance process representation, parameterization and scaling of photosynthesis in the next generation of Earth System Models.

The Role of Functionality in the Mental Representations of Engineering Students: Some Differences in the Early Stages of Expertise

ERIC Educational Resources Information Center

Moss, Jarrod; Kotovsky, Kenneth; Cagan, Jonathan

2006-01-01

As engineers gain experience and become experts in their domain, the structure and content of their knowledge changes. Two studies are presented that examine differences in knowledge representation among freshman and senior engineering students. The first study examines recall of mechanical devices and chunking of components, and the second…

Promoting Pedagogical Content Knowledge Development for Early Career Secondary Teachers in Science and Technology Using Content Representations

ERIC Educational Resources Information Center

Williams, John; Eames, Chris; Hume, Anne; Lockley, John

2012-01-01

Background: This research addressed the key area of early career teacher education and aimed to explore the use of a "content representation" (CoRe) as a mediational tool to develop early career secondary teacher pedagogical content knowledge (PCK). This study was situated in the subject areas of science and technology, where sound…

Invisible Brain: Knowledge in Research Works and Neuron Activity.

PubMed

Segev, Aviv; Curtis, Dorothy; Jung, Sukhwan; Chae, Suhyun

2016-01-01

If the market has an invisible hand, does knowledge creation and representation have an "invisible brain"? While knowledge is viewed as a product of neuron activity in the brain, can we identify knowledge that is outside the brain but reflects the activity of neurons in the brain? This work suggests that the patterns of neuron activity in the brain can be seen in the representation of knowledge-related activity. Here we show that the neuron activity mechanism seems to represent much of the knowledge learned in the past decades based on published articles, in what can be viewed as an "invisible brain" or collective hidden neural networks. Similar results appear when analyzing knowledge activity in patents. Our work also tries to characterize knowledge increase as neuron network activity growth. The results propose that knowledge-related activity can be seen outside of the neuron activity mechanism. Consequently, knowledge might exist as an independent mechanism.

Invisible Brain: Knowledge in Research Works and Neuron Activity

PubMed Central

Segev, Aviv; Curtis, Dorothy; Jung, Sukhwan; Chae, Suhyun

2016-01-01

If the market has an invisible hand, does knowledge creation and representation have an “invisible brain”? While knowledge is viewed as a product of neuron activity in the brain, can we identify knowledge that is outside the brain but reflects the activity of neurons in the brain? This work suggests that the patterns of neuron activity in the brain can be seen in the representation of knowledge-related activity. Here we show that the neuron activity mechanism seems to represent much of the knowledge learned in the past decades based on published articles, in what can be viewed as an “invisible brain” or collective hidden neural networks. Similar results appear when analyzing knowledge activity in patents. Our work also tries to characterize knowledge increase as neuron network activity growth. The results propose that knowledge-related activity can be seen outside of the neuron activity mechanism. Consequently, knowledge might exist as an independent mechanism. PMID:27439199

Combinatorial approach to the representation of the Schur-Weyl duality in one-dimensional spin systems

NASA Astrophysics Data System (ADS)

Jakubczyk, Dorota; Jakubczyk, Paweł

2018-02-01

We propose combinatorial approach to the representation of Schur-Weyl duality in physical systems on the example of one-dimensional spin chains. Exploiting the Robinson-Schensted-Knuth algorithm, we perform decomposition of the dual group representations into irreducible representations in a fully combinatorial way. As representation space, we choose the Hilbert space of the spin chains, but this approach can be easily generalized to an arbitrary physical system where the Schur-Weyl duality works.

Multiple Domains of Parental Secure Base Support During Childhood and Adolescence Contribute to Adolescents’ Representations of Attachment as a Secure Base Script

PubMed Central

Vaughn, Brian E.; Waters, Theodore E. A.; Steele, Ryan D.; Roisman, Glenn I.; Bost, Kelly K.; Truitt, Warren; Waters, Harriet S.; Booth-LaForce, Cathryn

2016-01-01

Although attachment theory claims that early attachment representations reflecting the quality of the child’s “lived experiences” are maintained across developmental transitions, evidence that has emerged over the last decade suggests that the association between early relationship quality and adolescents’ attachment representations is fairly modest in magnitude. We used aspects of parenting beyond sensitivity over childhood and adolescence and early security to predict adolescents’ scripted attachment representations. At age 18 years, 673 participants from the NICHD Study of Early Child Care and Youth Development (SECCYD) completed the Attachment Script Assessment (ASA) from which we derived an assessment of secure base script knowledge. Measures of secure base support from childhood through age 15 years (e.g., parental monitoring of child activity, father presence in the home) were selected as predictors and accounted for an additional 8% of the variance in secure base script knowledge scores above and beyond direct observations of sensitivity and early attachment status alone, suggesting that adolescents’ scripted attachment representations reflect multiple domains of parenting. Cognitive and demographic variables also significantly increased predicted variance in secure base script knowledge by 2% each. PMID:27032953

Understanding primary school science teachers' pedagogical content knowledge: The case of teaching global warming

NASA Astrophysics Data System (ADS)

Chordnork, Boonliang; Yuenyong, Chokchai

2018-01-01

This aim of this research was to investigate primary school science teachers understanding and teaching practice as well as the influence on teaching and learning a topic like global warming. The participants were four primary science teachers, who were not graduated in science education. Methodology was the case study method, which was under the qualitative research regarded from interpretive paradigm. Data were collected by openended questionnaire, semi-structure interview, and document colleting. The questionnaire examined teachers' background, teachers' understanding of problems and threats of science teaching, desiring of development their PCK, sharing the teaching approaches, and their ideas of strength and weakness. a semi-structured interview was conducted based on the approach for capturing PCK of Loughran [23] content representation (CoRe). And, the document was collected to clarify what evidence which was invented to effect on students' learning. These document included lesson plan, students' task, and painting about global warming, science projects, the picture of activities of science learning, the exercise and test. Data analysis employed multiple approach of evidence looking an issue from each primary science teachers and used triangulation method to analyze the data with aiming to make meaning of teachers' representation of teaching practice. These included descriptive statistics, CoRe interpretation, and document analysis. The results show that teachers had misunderstanding of science teaching practice and they has articulated the pedagogical content knowledge in terms of assessment, goal of teaching and linking to the context of socio cultural. In contrast, knowledge and belief of curriculum, students' understanding of content global warming, and strategies of teaching were articulated indistinct by non-graduate science teacher. Constructing opportunities for personal development, the curiosity of the student learning center, and linking context of socio-culture were the creative factor in the teaching global warming. On the other hand, the teachers had an idea that lack of technology and the defect of child's intelligence were hinder factors teaching global warming.

Dissociations in mathematical knowledge: case studies in Down's syndrome and Williams syndrome.

PubMed

Robinson, Sally J; Temple, Christine M

2013-02-01

A study is reported of mathematical vocabulary and factual mathematical knowledge in PQ, a 22 year old with Down's syndrome (DS) who has a verbal mental age (MA) of 9 years 2 months and ST, a 15 year old with Williams syndrome (WS) who has a verbal MA of 9 years 6 months, matched to typically developing controls. The number of mathematical words contained within PQ's lexical stores was significantly reduced as reflected by performance on lexical decision. PQ was also impaired at both naming from descriptions and describing mathematical words. These results contrast with normal lexical decision and item descriptions for concrete words reported recently for PQ (Robinson and Temple, 2010). PQ's recall of mathematical facts was also impaired, whilst his recall of general knowledge facts was normal. This performance in DS indicates a deficit in both lexical representation and semantic knowledge for mathematical words and mathematical facts. In contrast, ST, the teenager with WS had good accuracy on lexical decision, naming and generating definitions for mathematical words. This contrasted with the atypical performance with concrete words recently reported for ST (Robinson and Temple, 2009). Knowledge of addition facts and general knowledge facts was also unimpaired for ST, though knowledge of multiplication facts was weak. Together the cases form a double dissociation and provide support for the distinct representation of mathematical and concrete items within the lexical-semantic system during development. The dissociations between mathematical and general factual knowledge also indicate that different types of factual knowledge may be selectively impaired during development. There is further support for a modular structure within which mathematical vocabulary and mathematical knowledge have distinct representations. This supports the case for the independent representation of factual and language-based knowledge within the semantic system during development. Copyright © 2011 Elsevier Ltd. All rights reserved.

HIV/AIDS among adolescents in Eastern Europe: knowledge of HIV/AIDS, social representations of risk and sexual activity among school children and homeless adolescents in Russia, Georgia and the Ukraine.

PubMed

Goodwin, Robin; Kozlova, Alexandra; Nizharadze, George; Polyakova, Galina

2004-05-01

The two studies reported here focus on knowledge and representations of HIV/AIDS (study 1) plus sexual behaviour and hedonistic values (study 2) among 14-17-year-old school children and similar aged shelter children. Results indicate that shelter children are more sexually active, less knowledgeable about means of HIV transmission and are more likely to hold stereotyped representations of those most at risk of infection. Russian respondents were the most sexually active, a finding which could at least be partly explained by their higher levels of hedonistic values. These findings are discussed in the context of a climate of continuing social change in this region.

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.

Contextual and temporal clinical guidelines.

PubMed Central

Guarnero, A.; Marzuoli, M.; Molino, G.; Terenziani, P.; Torchio, M.; Vanni, K.

1998-01-01

In this paper, we propose an approach for managing clinical guidelines. We sketch a modular architecture, allowing us to separate conceptually distinct aspects in the management and use of clinical guidelines. In particular, we describe the clinical guidelines knowledge representation module and we sketch the acquisition module. The main focus of the paper is the definition of an expressive formalism for representing clinical guidelines, which allows one to deal with the context dependent character of clinical guidelines and takes into account different temporal aspects. PMID:9929306

Information compression in the context model

NASA Technical Reports Server (NTRS)

Gebhardt, Joerg; Kruse, Rudolf; Nauck, Detlef

1992-01-01

The Context Model provides a formal framework for the representation, interpretation, and analysis of vague and uncertain data. The clear semantics of the underlying concepts make it feasible to compare well-known approaches to the modeling of imperfect knowledge like that given in Bayes Theory, Shafer's Evidence Theory, the Transferable Belief Model, and Possibility Theory. In this paper we present the basic ideas of the Context Model and show its applicability as an alternative foundation of Possibility Theory and the epistemic view of fuzzy sets.

Transforming Undergraduate Education Through the use of Analytical Reasoning (TUETAR)

NASA Astrophysics Data System (ADS)

Bishop, M. P.; Houser, C.; Lemmons, K.

2015-12-01

Traditional learning limits the potential for self-discovery, and the use of data and knowledge to understand Earth system relationships, processes, feedback mechanisms and system coupling. It is extremely difficult for undergraduate students to analyze, synthesize, and integrate quantitative information related to complex systems, as many concepts may not be mathematically tractable or yet to be formalized. Conceptual models have long served as a means for Earth scientists to organize their understanding of Earth's dynamics, and have served as a basis for human analytical reasoning and landscape interpretation. Consequently, we evaluated the use of conceptual modeling, knowledge representation and analytical reasoning to provide undergraduate students with an opportunity to develop and test geocomputational conceptual models based upon their understanding of Earth science concepts. This study describes the use of geospatial technologies and fuzzy cognitive maps to predict desertification across the South-Texas Sandsheet in an upper-level geomorphology course. Students developed conceptual models based on their understanding of aeolian processes from lectures, and then compared and evaluated their modeling results against an expert conceptual model and spatial predictions, and the observed distribution of dune activity in 2010. Students perceived that the analytical reasoning approach was significantly better for understanding desertification compared to traditional lecture, and promoted reflective learning, working with data, teamwork, student interaction, innovation, and creative thinking. Student evaluations support the notion that the adoption of knowledge representation and analytical reasoning in the classroom has the potential to transform undergraduate education by enabling students to formalize and test their conceptual understanding of Earth science. A model for developing and utilizing this geospatial technology approach in Earth science is presented.

Functional brain networks reconstruction using group sparsity-regularized learning.

PubMed

Zhao, Qinghua; Li, Will X Y; Jiang, Xi; Lv, Jinglei; Lu, Jianfeng; Liu, Tianming

2018-06-01

Investigating functional brain networks and patterns using sparse representation of fMRI data has received significant interests in the neuroimaging community. It has been reported that sparse representation is effective in reconstructing concurrent and interactive functional brain networks. To date, most of data-driven network reconstruction approaches rarely take consideration of anatomical structures, which are the substrate of brain function. Furthermore, it has been rarely explored whether structured sparse representation with anatomical guidance could facilitate functional networks reconstruction. To address this problem, in this paper, we propose to reconstruct brain networks utilizing the structure guided group sparse regression (S2GSR) in which 116 anatomical regions from the AAL template, as prior knowledge, are employed to guide the network reconstruction when performing sparse representation of whole-brain fMRI data. Specifically, we extract fMRI signals from standard space aligned with the AAL template. Then by learning a global over-complete dictionary, with the learned dictionary as a set of features (regressors), the group structured regression employs anatomical structures as group information to regress whole brain signals. Finally, the decomposition coefficients matrix is mapped back to the brain volume to represent functional brain networks and patterns. We use the publicly available Human Connectome Project (HCP) Q1 dataset as the test bed, and the experimental results indicate that the proposed anatomically guided structure sparse representation is effective in reconstructing concurrent functional brain networks.

[The brain and its representations in early modern Europe].

PubMed

Mandressi, Rafael

2011-01-01

The history of the representations of the brain is broadly the history of the brain itself, since observations and ideas which concern it are closely linked, and are even depending on each other. These representations are images, but are also materials produced by manipulating, cutting, fixing the brain; they are also the descriptions of these objects. The interpretations, structured by the representations, ultimately organize the knowledge.

24 CFR 257.116 - Representations and prohibitions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 24 Housing and Urban Development 2 2014-04-01 2014-04-01 false Representations and prohibitions... Representations and prohibitions. (a) Underwriting and appraisal standards. In order for the H4H program mortgage... willfully and with actual knowledge furnished material information known to be false for the purpose of...

Teacher's Representational Fluency in a Context of Technology Use

ERIC Educational Resources Information Center

Rocha, Helena

2016-01-01

This study focuses on teacher's Knowledge for Teaching Mathematics with Technology (KTMT), paying a special attention to teacher's representational fluency. It intends to characterize how the teacher uses and integrates the different representations provided by the graphing calculator on the process of teaching and learning functions at the high…

24 CFR 257.116 - Representations and prohibitions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 24 Housing and Urban Development 2 2013-04-01 2013-04-01 false Representations and prohibitions... Representations and prohibitions. (a) Underwriting and appraisal standards. In order for the H4H program mortgage... willfully and with actual knowledge furnished material information known to be false for the purpose of...

24 CFR 257.116 - Representations and prohibitions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 24 Housing and Urban Development 2 2012-04-01 2012-04-01 false Representations and prohibitions... Representations and prohibitions. (a) Underwriting and appraisal standards. In order for the H4H program mortgage... willfully and with actual knowledge furnished material information known to be false for the purpose of...

24 CFR 257.116 - Representations and prohibitions.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false Representations and prohibitions... Representations and prohibitions. (a) Underwriting and appraisal standards. In order for the H4H program mortgage... willfully and with actual knowledge furnished material information known to be false for the purpose of...

24 CFR 257.116 - Representations and prohibitions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 24 Housing and Urban Development 2 2011-04-01 2011-04-01 false Representations and prohibitions... Representations and prohibitions. (a) Underwriting and appraisal standards. In order for the H4H program mortgage... willfully and with actual knowledge furnished material information known to be false for the purpose of...

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…

The Microevolution of Mathematical Representations in Children's Activity.

ERIC Educational Resources Information Center

Meira, Luciano

1995-01-01

Discusses children's design of mathematical representations on paper. Suggests that the design of displays during problem solving shapes one's mathematical activity and sense making in crucial ways, and that knowledge of mathematical representations is not simply recalled and applied to problem solving, but also emerges out of one's interactions…

Developing Expert Systems for the Analysis of Syntactic and Semantic Patterns.

ERIC Educational Resources Information Center

Hellwig, Harold H.

Noting that expert computer systems respond to various contexts in terms of knowledge representation, this paper explains that heuristic rules of production, procedural representation, and frame representation have been adapted to such areas as medical diagnosis, signal interpretation, design and planning of electrical circuits and computer system…

Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning

ERIC Educational Resources Information Center

Rau, Martina A.

2017-01-01

Visual representations play a critical role in enhancing science, technology, engineering, and mathematics (STEM) learning. Educational psychology research shows that adding visual representations to text can enhance students' learning of content knowledge, compared to text-only. But should students learn with a single type of visual…

Drawings as Representations of Children's Conceptions

ERIC Educational Resources Information Center

Ehrlen, Karin

2009-01-01

Drawings are often used to obtain an idea of children's conceptions. Doing so takes for granted an unambiguous relation between conceptions and their representations in drawings. This study was undertaken to gain knowledge of the relation between children's conceptions and their representation of these conceptions in drawings. A theory of…

On Representations and Situated Tools.

ERIC Educational Resources Information Center

Moreno-Armella, Luis

This paper suggests that the systems of representations that we use in mathematics have a cultural origin and concludes that the knowledge produced with the help of these systems of representation likewise has a cultural origin. This assertion forces a reformulation of the issue of objectivity in terms that differ from those inherited from…

The representation of self and person knowledge in the medial prefrontal cortex.

PubMed

Wagner, Dylan D; Haxby, James V; Heatherton, Todd F

2012-07-01

Nearly 40 years ago, social psychologists began applying the information processing framework of cognitive psychology to the question of how humans understand and represent knowledge about themselves and others. This approach gave rise to the immensely successful field of social cognition and fundamentally changed the way in which social psychological phenomena are studied. More recently, social scientists of many stripes have turned to the methods of cognitive neuroscience to understand the neural basis of social cognition. A pervasive finding from this research is that social knowledge, be it about one's self or of others, is represented in the medial prefrontal cortex (MPFC). This review focuses on the social cognitive neuroscience of self and person knowledge in the MPFC. We begin with a brief historical overview of social cognition, followed by a review of recent and influential research on the brain basis of self and person knowledge. In the latter half of this review, we discuss the role of familiarity and similarity in person perception and of spontaneous processes in self and other-referential cognition. Throughout, we discuss the myriad ways in which the social cognitive neuroscience approach has provided new insights into the nature and structure of self and person knowledge. WIREs Cogn Sci 2012, 3:451-470. doi: 10.1002/wcs.1183 This article is categorized under: Neuroscience > Cognition. Copyright © 2012 John Wiley & Sons, Ltd.

REKRIATE: A Knowledge Representation System for Object Recognition and Scene Interpretation

NASA Astrophysics Data System (ADS)

Meystel, Alexander M.; Bhasin, Sanjay; Chen, X.

1990-02-01

What humans actually observe and how they comprehend this information is complex due to Gestalt processes and interaction of context in predicting the course of thinking and enforcing one idea while repressing another. How we extract the knowledge from the scene, what we get from the scene indeed and what we bring from our mechanisms of perception are areas separated by a thin, ill-defined line. The purpose of this paper is to present a system for Representing Knowledge and Recognizing and Interpreting Attention Trailed Entities dubbed as REKRIATE. It will be used as a tool for discovering the underlying principles involved in knowledge representation required for conceptual learning. REKRIATE has some inherited knowledge and is given a vocabulary which is used to form rules for identification of the object. It has various modalities of sensing and has the ability to measure the distance between the objects in the image as well as the similarity between different images of presumably the same object. All sensations received from matrix of different sensors put into an adequate form. The methodology proposed is applicable to not only the pictorial or visual world representation, but to any sensing modality. It is based upon the two premises: a) inseparability of all domains of the world representation including linguistic, as well as those formed by various sensor modalities. and b) representativity of the object at several levels of resolution simultaneously.

Knowledge Representation and Care Planning for Population Health Management.

PubMed

Merahn, Steven

2015-01-01

The traditional organizing principles of medical knowledge may be insufficient to allow for problem representations that are relevant to solution development in emerging models of care such as population health management. Operational classification and central management of clinical and quality objectives and associated strategies will allow for productive innovation in care design and better support goal-directed collaboration among patients and their health resource communities.

Similarity networks as a knowledge representation for space applications

NASA Technical Reports Server (NTRS)

Bailey, David; Thompson, Donna; Feinstein, Jerald

1987-01-01

Similarity networks are a powerful form of knowledge representation that are useful for many artificial intelligence applications. Similarity networks are used in applications ranging from information analysis and case based reasoning to machine learning and linking symbolic to neural processing. Strengths of similarity networks include simple construction, intuitive object storage, and flexible retrieval techniques that facilitate inferencing. Therefore, similarity networks provide great potential for space applications.

Young Children's Knowledge of the Representational Function of Pictorial Symbols: Development across the Preschool Years in Three Cultures

ERIC Educational Resources Information Center

Callaghan, Tara C.; Rochat, Philippe; Corbit, John

2012-01-01

Three- to 5-year-old children's knowledge that pictures have a representational function for others was investigated using a pictorial false-belief task. In Study 1, children passed the task at around 4 years old, and performance was correlated with standard false-belief and pictorial symbol tasks. In Study 2, the performance of children from two…

What Happens to Student Learning When Color Is Added to a New Knowledge Representation Strategy? Implications from Visual Thinking Networking.

ERIC Educational Resources Information Center

Longo, Palma J.

A long-term study was conducted to test the effectiveness of visual thinking networking (VTN), a new generation of knowledge representation strategies with 56 ninth grade earth science students. The recent findings about the brain's organization and processing conceptually ground VTN as a new cognitive tool used by learners when making their…

Broad phonetic class definition driven by phone confusions

NASA Astrophysics Data System (ADS)

Lopes, Carla; Perdigão, Fernando

2012-12-01

Intermediate representations between the speech signal and phones may be used to improve discrimination among phones that are often confused. These representations are usually found according to broad phonetic classes, which are defined by a phonetician. This article proposes an alternative data-driven method to generate these classes. Phone confusion information from the analysis of the output of a phone recognition system is used to find clusters at high risk of mutual confusion. A metric is defined to compute the distance between phones. The results, using TIMIT data, show that the proposed confusion-driven phone clustering method is an attractive alternative to the approaches based on human knowledge. A hierarchical classification structure to improve phone recognition is also proposed using a discriminative weight training method. Experiments show improvements in phone recognition on the TIMIT database compared to a baseline system.

A scalable architecture for incremental specification and maintenance of procedural and declarative clinical decision-support knowledge.

PubMed

Hatsek, Avner; Shahar, Yuval; Taieb-Maimon, Meirav; Shalom, Erez; Klimov, Denis; Lunenfeld, Eitan

2010-01-01

Clinical guidelines have been shown to improve the quality of medical care and to reduce its costs. However, most guidelines exist in a free-text representation and, without automation, are not sufficiently accessible to clinicians at the point of care. A prerequisite for automated guideline application is a machine-comprehensible representation of the guidelines. In this study, we designed and implemented a scalable architecture to support medical experts and knowledge engineers in specifying and maintaining the procedural and declarative aspects of clinical guideline knowledge, resulting in a machine comprehensible representation. The new framework significantly extends our previous work on the Digital electronic Guidelines Library (DeGeL) The current study designed and implemented a graphical framework for specification of declarative and procedural clinical knowledge, Gesher. We performed three different experiments to evaluate the functionality and usability of the major aspects of the new framework: Specification of procedural clinical knowledge, specification of declarative clinical knowledge, and exploration of a given clinical guideline. The subjects included clinicians and knowledge engineers (overall, 27 participants). The evaluations indicated high levels of completeness and correctness of the guideline specification process by both the clinicians and the knowledge engineers, although the best results, in the case of declarative-knowledge specification, were achieved by teams including a clinician and a knowledge engineer. The usability scores were high as well, although the clinicians' assessment was significantly lower than the assessment of the knowledge engineers.

Unpacking Exoplanet Detection Using Pedagogical Discipline Representations (PDRs)

NASA Astrophysics Data System (ADS)

Prather, Edward E.; Chambers, Timothy G.; Wallace, Colin Scott; Brissenden, Gina

2017-01-01

Successful educators know the importance of using multiple representations to teach the content of their disciplines. We have all seen the moments of epiphany that can be inspired when engaging with just the right representation of a difficult concept. The formal study of the cognitive impact of different representations on learners is now an active area of education research. The affordances of a particular representation are defined as the elements of disciplinary knowledge that students are able to access and reason about using that representation. Instructors with expert pedagogical content knowledge teach each topic using representations with complementary affordances, maximizing their students’ opportunity to develop fluency with all aspects of the topic. The work presented here examines how we have applied the theory of affordances to the development of pedagogical discipline representation (PDR) in an effort to provide access to, and help non-science-majors engage in expert-like reasoning about, general relativity as applied to detection of exoplanets. We define a pedagogical discipline representation (PDR) as a representation that has been uniquely tailored for the purpose of teaching a specific topic within a discipline. PDRs can be simplified versions of expert representations or can be highly contextualized with features that purposefully help unpack specific reasoning or concepts, and engage learners’ pre-existing mental models while promoting and enabling critical discourse. Examples of PDRs used for instruction and assessment will be provided along with preliminary results documenting the effectiveness of their use in the classroom.

The impact of social inequalities on children's knowledge and representation of health and cancer.

PubMed

Régnier Denois, Véronique; Bourmaud, Aurelie; Nekaa, Mabrouk; Bezzaz, Céline; Bousser, Véronique; Kalecinski, Julie; Dumesnil, Julia; Tinquaut, Fabien; Berger, Dominique; Chauvin, Franck

2018-05-28

Reducing inequalities in the field of cancer involves studying the knowledge and mental representations of cancer among children. A qualitative study was conducted on 191 children aged 9 to 12 using the "write and draw" technique to get spontaneous mental representations of "healthy things", "unhealthy things" and "cancer". We grouped the voluntary schools according to two deprivation levels. In response to the request to "write or draw anything you think keeps you healthy", the main responses categories were physical activity, healthy food and basic needs. Smoking, drinking alcohol, sedentary lifestyles/lack of sport were identified as "unhealthy". The first theme associated with "cancer" is the "cancer site" implying children have a segmented perception of cancer. Deprived children have radically different views about the key items representing cancer: they are more likely to believe the illness is systematically deadly. They are less likely to believe it is a treatable illness. They are less likely to associate cancer with risky behaviors, particularly alcohol consumption. Social inequalities affect representations of cancer and health literacy from early childhood. Prevention programs taking into account these representations need to be introduced at school. What is Known: • Social inequalities for cancer mortality are observed in all European countries and are particularly pronounced in France. • Reducing these inequalities in prevention programs implies studying the knowledge and mental representations of cancer among children. What is New: • This study identified representations of cancer in young children according to social level. • At age 9, children living in deprived areas are less able to produce content in discussions about cancer and have narrower mental representations and a more fatalistic view.

An atom is known by the company it keeps: Content, representation and pedagogy within the epistemic revolution of the complexity sciences

NASA Astrophysics Data System (ADS)

Blikstein, Paulo

The goal of this dissertation is to explore relations between content, representation, and pedagogy, so as to understand the impact of the nascent field of complexity sciences on science, technology, engineering and mathematics (STEM) learning. Wilensky & Papert coined the term "structurations" to express the relationship between knowledge and its representational infrastructure. A change from one representational infrastructure to another they call a "restructuration." The complexity sciences have introduced a novel and powerful structuration: agent-based modeling. In contradistinction to traditional mathematical modeling, which relies on equational descriptions of macroscopic properties of systems, agent-based modeling focuses on a few archetypical micro-behaviors of "agents" to explain emergent macro-behaviors of the agent collective. Specifically, this dissertation is about a series of studies of undergraduate students' learning of materials science, in which two structurations are compared (equational and agent-based), consisting of both design research and empirical evaluation. I have designed MaterialSim, a constructionist suite of computer models, supporting materials and learning activities designed within the approach of agent-based modeling, and over four years conducted an empirical inves3 tigation of an undergraduate materials science course. The dissertation is comprised of three studies: Study 1 - diagnosis . I investigate current representational and pedagogical practices in engineering classrooms. Study 2 - laboratory studies. I investigate the cognition of students engaging in scientific inquiry through programming their own scientific models. Study 3 - classroom implementation. I investigate the characteristics, advantages, and trajectories of scientific content knowledge that is articulated in epistemic forms and representational infrastructures unique to complexity sciences, as well as the feasibility of the integration of constructionist, agent-based learning environments in engineering classrooms. Data sources include classroom observations, interviews, videotaped sessions of model-building, questionnaires, analysis of computer-generated logfiles, and quantitative and qualitative analysis of artifacts. Results shows that (1) current representational and pedagogical practices in engineering classrooms were not up to the challenge of the complex content being taught, (2) by building their own scientific models, students developed a deeper understanding of core scientific concepts, and learned how to better identify unifying principles and behaviors in materials science, and (3) programming computer models was feasible within a regular engineering classroom.

A logic programming approach to medical errors in imaging.

PubMed

Rodrigues, Susana; Brandão, Paulo; Nelas, Luís; Neves, José; Alves, Victor

2011-09-01

In 2000, the Institute of Medicine reported disturbing numbers on the scope it covers and the impact of medical error in the process of health delivery. Nevertheless, a solution to this problem may lie on the adoption of adverse event reporting and learning systems that can help to identify hazards and risks. It is crucial to apply models to identify the adverse events root causes, enhance the sharing of knowledge and experience. The efficiency of the efforts to improve patient safety has been frustratingly slow. Some of this insufficiency of progress may be assigned to the lack of systems that take into account the characteristic of the information about the real world. In our daily lives, we formulate most of our decisions normally based on incomplete, uncertain and even forbidden or contradictory information. One's knowledge is less based on exact facts and more on hypothesis, perceptions or indications. From the data collected on our adverse event treatment and learning system on medical imaging, and through the use of Extended Logic Programming to knowledge representation and reasoning, and the exploitation of new methodologies for problem solving, namely those based on the perception of what is an agent and/or multi-agent systems, we intend to generate reports that identify the most relevant causes of error and define improvement strategies, concluding about the impact, place of occurrence, form or type of event recorded in the healthcare institutions. The Eindhoven Classification Model was extended and adapted to the medical imaging field and used to classify adverse events root causes. Extended Logic Programming was used for knowledge representation with defective information, allowing for the modelling of the universe of discourse in terms of data and knowledge default. A systematization of the evolution of the body of knowledge about Quality of Information embedded in the Root Cause Analysis was accomplished. An adverse event reporting and learning system was developed based on the presented approach to medical errors in imaging. This system was deployed in two Portuguese healthcare institutions, with an appealing outcome. The system enabled to verify that the majority of occurrences were concentrated in a few events that could be avoided. The developed system allowed automatic knowledge extraction, enabling report generation with strategies for the improvement of quality-of-care. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Certainty grids for mobile robots

NASA Technical Reports Server (NTRS)

Moravec, H. P.

1987-01-01

A numerical representation of uncertain and incomplete sensor knowledge called Certainty Grids has been used successfully in several mobile robot control programs, and has proven itself to be a powerful and efficient unifying solution for sensor fusion, motion planning, landmark identification, and many other central problems. Researchers propose to build a software framework running on processors onboard the new Uranus mobile robot that will maintain a probabilistic, geometric map of the robot's surroundings as it moves. The certainty grid representation will allow this map to be incrementally updated in a uniform way from various sources including sonar, stereo vision, proximity and contact sensors. The approach can correctly model the fuzziness of each reading, while at the same time combining multiple measurements to produce sharper map features, and it can deal correctly with uncertainties in the robot's motion. The map will be used by planning programs to choose clear paths, identify locations (by correlating maps), identify well-known and insufficiently sensed terrain, and perhaps identify objects by shape. The certainty grid representation can be extended in the same dimension and used to detect and track moving objects.

Learning high-level features for chord recognition using Autoencoder

NASA Astrophysics Data System (ADS)

Phongthongloa, Vilailukkana; Kamonsantiroj, Suwatchai; Pipanmaekaporn, Luepol

2016-07-01

Chord transcription is valuable to do by itself. It is known that the manual transcription of chords is very tiresome, time-consuming. It requires, moreover, musical knowledge. Automatic chord recognition has recently attracted a number of researches in the Music Information Retrieval field. It has known that a pitch class profile (PCP) is the commonly signal representation of musical harmonic analysis. However, the PCP may contain additional non-harmonic noise such as harmonic overtones and transient noise. The problem of non-harmonic might be generating the sound energy in term of frequency more than the actual notes of the respective chord. Autoencoder neural network may be trained to learn a mapping from low level feature to one or more higher-level representation. These high-level representations can explain dependencies of the inputs and reduce the effect of non-harmonic noise. Then these improve features are fed into neural network classifier. The proposed high-level musical features show 80.90% of accuracy. The experimental results have shown that the proposed approach can achieve better performance in comparison with other based method.

LIS Professionals as Knowledge Engineers.

ERIC Educational Resources Information Center

Poulter, Alan; And Others

1994-01-01

Considers the role of library and information science professionals as knowledge engineers. Highlights include knowledge acquisition, including personal experience, interviews, protocol analysis, observation, multidimensional sorting, printed sources, and machine learning; knowledge representation, including production rules and semantic nets;…

Underwater Photogrammetry and Object Modeling: A Case Study of Xlendi Wreck in Malta

PubMed Central

Drap, Pierre; Merad, Djamal; Hijazi, Bilal; Gaoua, Lamia; Nawaf, Mohamad Motasem; Saccone, Mauro; Chemisky, Bertrand; Seinturier, Julien; Sourisseau, Jean-Christophe; Gambin, Timmy; Castro, Filipe

2015-01-01

In this paper we present a photogrammetry-based approach for deep-sea underwater surveys conducted from a submarine and guided by knowledge-representation combined with a logical approach (ontology). Two major issues are discussed in this paper. The first concerns deep-sea surveys using photogrammetry from a submarine. Here the goal was to obtain a set of images that completely covered the selected site. Subsequently and based on these images, a low-resolution 3D model is obtained in real-time, followed by a very high-resolution model produced back in the laboratory. The second issue involves the extraction of known artefacts present on the site. This aspect of the research is based on an a priori representation of the knowledge involved using systematic reasoning. Two parallel processes were developed to represent the photogrammetric process used for surveying as well as for identifying archaeological artefacts visible on the sea floor. Mapping involved the use of the CIDOC-CRM system (International Committee for Documentation (CIDOC)—Conceptual Reference Model)—This is a system that has been previously utilised to in the heritage sector and is largely available to the established scientific community. The proposed theoretical representation is based on procedural attachment; moreover, a strong link is maintained between the ontological description of the modelled concepts and the Java programming language which permitted 3D structure estimation and modelling based on a set of oriented images. A very recently discovered shipwreck acted as a testing ground for this project; the Xelendi Phoenician shipwreck, found off the Maltese coast, is probably the oldest known shipwreck in the western Mediterranean. The approach presented in this paper was developed in the scope of the GROPLAN project (Généralisation du Relevé, avec Ontologies et Photogrammétrie, pour l'Archéologie Navale et Sous-marine). Financed by the French National Research Agency (ANR) for four years, this project associates two French research laboratories, an industrial partner, the University of Malta, and Texas A & M University. PMID:26690147

Underwater Photogrammetry and Object Modeling: A Case Study of Xlendi Wreck in Malta.

PubMed

Drap, Pierre; Merad, Djamal; Hijazi, Bilal; Gaoua, Lamia; Nawaf, Mohamad Motasem; Saccone, Mauro; Chemisky, Bertrand; Seinturier, Julien; Sourisseau, Jean-Christophe; Gambin, Timmy; Castro, Filipe

2015-12-04

In this paper we present a photogrammetry-based approach for deep-sea underwater surveys conducted from a submarine and guided by knowledge-representation combined with a logical approach (ontology). Two major issues are discussed in this paper. The first concerns deep-sea surveys using photogrammetry from a submarine. Here the goal was to obtain a set of images that completely covered the selected site. Subsequently and based on these images, a low-resolution 3D model is obtained in real-time, followed by a very high-resolution model produced back in the laboratory. The second issue involves the extraction of known artefacts present on the site. This aspect of the research is based on an a priori representation of the knowledge involved using systematic reasoning. Two parallel processes were developed to represent the photogrammetric process used for surveying as well as for identifying archaeological artefacts visible on the sea floor. Mapping involved the use of the CIDOC-CRM system (International Committee for Documentation (CIDOC)-Conceptual Reference Model)-This is a system that has been previously utilised to in the heritage sector and is largely available to the established scientific community. The proposed theoretical representation is based on procedural attachment; moreover, a strong link is maintained between the ontological description of the modelled concepts and the Java programming language which permitted 3D structure estimation and modelling based on a set of oriented images. A very recently discovered shipwreck acted as a testing ground for this project; the Xelendi Phoenician shipwreck, found off the Maltese coast, is probably the oldest known shipwreck in the western Mediterranean. The approach presented in this paper was developed in the scope of the GROPLAN project (Généralisation du Relevé, avec Ontologies et Photogrammétrie, pour l'Archéologie Navale et Sous-marine). Financed by the French National Research Agency (ANR) for four years, this project associates two French research laboratories, an industrial partner, the University of Malta, and Texas A & M University.

A knowledge based software engineering environment testbed

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

Web Ontologies to Categorialy Structure Reality: Representations of Human Emotional, Cognitive, and Motivational Processes

PubMed Central

López-Gil, Juan-Miguel; Gil, Rosa; García, Roberto

2016-01-01

This work presents a Web ontology for modeling and representation of the emotional, cognitive and motivational state of online learners, interacting with university systems for distance or blended education. The ontology is understood as a way to provide the required mechanisms to model reality and associate it to emotional responses, but without committing to a particular way of organizing these emotional responses. Knowledge representation for the contributed ontology is performed by using Web Ontology Language (OWL), a semantic web language designed to represent rich and complex knowledge about things, groups of things, and relations between things. OWL is a computational logic-based language such that computer programs can exploit knowledge expressed in OWL and also facilitates sharing and reusing knowledge using the global infrastructure of the Web. The proposed ontology has been tested in the field of Massive Open Online Courses (MOOCs) to check if it is capable of representing emotions and motivation of the students in this context of use. PMID:27199796

Intersection of argumentation and the use of multiple representations in the context of socioscientific issues

NASA Astrophysics Data System (ADS)

Namdar, Bahadir; Shen, Ji

2016-05-01

Using multiple representations and argumentation are two fundamental processes in science. With the advancements of information communication technologies, these two processes are blended more so than ever before. However, little is known about how these two processes interact with each other in student learning. Hence, we conducted a design-based study in order to distill the relationship between these two processes. Specifically, we designed a learning unit on nuclear energy and implemented it with a group of preservice middle school teachers. The participants used a web-based knowledge organization platform that incorporated three representational modes: textual, concept map, and pictorial. The participants organized their knowledge on nuclear energy by searching, sorting, clustering information through the use of these representational modes and argued about the nuclear energy issue. We found that the use of multiple representations and argumentation interacted with each other in a complex way. Based on our findings, we argue that the complexity can be unfolded in two aspects: (a) the use of multiple representations mediates argumentation in different forms and for different purposes; (b) the type of argumentation that leads to refinement of the use of multiple representations is often non-mediated and drawn from personal experience.

The association of personal semantic memory to identity representations: insight into higher-order networks of autobiographical contents.

PubMed

Grilli, Matthew D

2017-11-01

Identity representations are higher-order knowledge structures that organise autobiographical memories on the basis of personality and role-based themes of one's self-concept. In two experiments, the extent to which different types of personal semantic content are reflected in these higher-order networks of memories was investigated. Healthy, young adult participants generated identity representations that varied in remoteness of formation and verbally reflected on these themes in an open-ended narrative task. The narrative responses were scored for retrieval of episodic, experience-near personal semantic and experience-far (i.e., abstract) personal semantic contents. Results revealed that to reflect on remotely formed identity representations, experience-far personal semantic contents were retrieved more than experience-near personal semantic contents. In contrast, to reflect on recently formed identity representations, experience-near personal semantic contents were retrieved more than experience-far personal semantic contents. Although episodic memory contents were retrieved less than both personal semantic content types to reflect on remotely formed identity representations, this content type was retrieved at a similar frequency as experience-far personal semantic content to reflect on recently formed identity representations. These findings indicate that the association of personal semantic content to identity representations is robust and related to time since acquisition of these knowledge structures.

SIRE: A Simple Interactive Rule Editor for NICBES

NASA Technical Reports Server (NTRS)

Bykat, Alex

1988-01-01

To support evolution of domain expertise, and its representation in an expert system knowledge base, a user-friendly rule base editor is mandatory. The Nickel Cadmium Battery Expert System (NICBES), a prototype of an expert system for the Hubble Space Telescope power storage management system, does not provide such an editor. In the following, a description of a Simple Interactive Rule Base Editor (SIRE) for NICBES is described. The SIRE provides a consistent internal representation of the NICBES knowledge base. It supports knowledge presentation and provides a user-friendly and code language independent medium for rule addition and modification. The SIRE is integrated with NICBES via an interface module. This module provides translation of the internal representation to Prolog-type rules (Horn clauses), latter rule assertion, and a simple mechanism for rule selection for its Prolog inference engine.

Multiple representations and free-body diagrams: Do students benefit from using them?

NASA Astrophysics Data System (ADS)

Rosengrant, David R.

2007-12-01

Introductory physics students have difficulties understanding concepts and solving problems. When they solve problems, they use surface features of the problems to find an equation to calculate a numerical answer often not understanding the physics in the problem. How do we help students approach problem solving in an expert manner? A possible answer is to help them learn to represent knowledge in multiple ways and then use these different representations for conceptual understanding and problem solving. This solution follows from research in cognitive science and in physics education. However, there are no studies in physics that investigate whether students who learn to use multiple representations are in fact better problem solvers. This study focuses on one specific representation used in physics--a free body diagram. A free-body diagram is a graphical representation of forces exerted on an object of interest by other objects. I used the free-body diagram to investigate five main questions: (1) If students are in a course where they consistently use free body diagrams to construct and test concepts in mechanics, electricity and magnetism and to solve problems in class and in homework, will they draw free-body diagrams on their own when solving exam problems? (2) Are students who use free-body diagrams to solve problems more successful then those who do not? (3) Why do students draw free-body diagrams when solving problems? (4) Are students consistent in constructing diagrams for different concepts in physics and are they consistent in the quality of their diagrams? (5) What are possible relationships between features of a problem and how likely a student will draw a free body diagram to help them solve the problem? I utilized a mixed-methods approach to answer these questions. Questions 1, 2, 4 and 5 required a quantitative approach while question 3 required a qualitative approach, a case study. When I completed my study, I found that if students are in an environment which fosters the use of representations for problem solving and for concept development, then the majority of students will consistently construct helpful free-body diagrams and use them on their own to solve problems. Additionally, those that construct correct free-body diagrams are significantly more likely to successfully solve the problem. Finally, those students that are high achieving tend to use diagrams more and for more reasons then students who have low course grades. These findings will have major impacts on how introductory physics instructors run their classes and how curriculums are designed. These results favor a problem solving strategy that is rich with representations.

Modal Representations and Their Role in the Learning Process: A Theoretical and Pragmatic Analysis

ERIC Educational Resources Information Center

Gunel, Murat; Yesildag-Hasancebi, Funda

2016-01-01

In the construction and sharing of scientific knowledge, modal representations such as text, graphics, pictures, and mathematical expressions are commonly used. Due to the increasing importance of their role in the production and communication of science, modal representations have become a topic of growing interest in science education research…

The Representation of Abstract Words: Why Emotion Matters

ERIC Educational Resources Information Center

Kousta, Stavroula-Thaleia; Vigliocco, Gabriella; Vinson, David P.; Andrews, Mark; Del Campo, Elena

2011-01-01

Although much is known about the representation and processing of concrete concepts, knowledge of what abstract semantics might be is severely limited. In this article we first address the adequacy of the 2 dominant accounts (dual coding theory and the context availability model) put forward in order to explain representation and processing…

29 CFR 1912.9 - Representation on section 7(b) committees.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 7 2014-07-01 2014-07-01 false Representation on section 7(b) committees. 1912.9 Section... Representation on section 7(b) committees. (a) Any advisory committee appointed by the Assistant Secretary under... appoint who are qualified by knowledge and experience to make a useful contribution to the work of the...

29 CFR 1912.9 - Representation on section 7(b) committees.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 7 2013-07-01 2013-07-01 false Representation on section 7(b) committees. 1912.9 Section... Representation on section 7(b) committees. (a) Any advisory committee appointed by the Assistant Secretary under... appoint who are qualified by knowledge and experience to make a useful contribution to the work of the...