Gender-heterogeneous working groups produce higher quality science.

PubMed

Campbell, Lesley G; Mehtani, Siya; Dozier, Mary E; Rinehart, Janice

2013-01-01

Here we present the first empirical evidence to support the hypothesis that a gender-heterogeneous problem-solving team generally produced journal articles perceived to be higher quality by peers than a team comprised of highly-performing individuals of the same gender. Although women were historically underrepresented as principal investigators of working groups, their frequency as PIs at the National Center for Ecological Analysis and Synthesis is now comparable to the national frequencies in biology and they are now equally qualified, in terms of their impact on the accumulation of ecological knowledge (as measured by the h-index). While women continue to be underrepresented as working group participants, peer-reviewed publications with gender-heterogeneous authorship teams received 34% more citations than publications produced by gender-uniform authorship teams. This suggests that peers citing these publications perceive publications that also happen to have gender-heterogeneous authorship teams as higher quality than publications with gender uniform authorship teams. Promoting diversity not only promotes representation and fairness but may lead to higher quality science.

Gender-Heterogeneous Working Groups Produce Higher Quality Science

PubMed Central

Campbell, Lesley G.; Mehtani, Siya; Dozier, Mary E.; Rinehart, Janice

2013-01-01

Here we present the first empirical evidence to support the hypothesis that a gender-heterogeneous problem-solving team generally produced journal articles perceived to be higher quality by peers than a team comprised of highly-performing individuals of the same gender. Although women were historically underrepresented as principal investigators of working groups, their frequency as PIs at the National Center for Ecological Analysis and Synthesis is now comparable to the national frequencies in biology and they are now equally qualified, in terms of their impact on the accumulation of ecological knowledge (as measured by the h-index). While women continue to be underrepresented as working group participants, peer-reviewed publications with gender-heterogeneous authorship teams received 34% more citations than publications produced by gender-uniform authorship teams. This suggests that peers citing these publications perceive publications that also happen to have gender-heterogeneous authorship teams as higher quality than publications with gender uniform authorship teams. Promoting diversity not only promotes representation and fairness but may lead to higher quality science. PMID:24205372

Supporting Multi-view User Ontology to Understand Company Value Chains

NASA Astrophysics Data System (ADS)

Zuo, Landong; Salvadores, Manuel; Imtiaz, Sm Hazzaz; Darlington, John; Gibbins, Nicholas; Shadbolt, Nigel R.; Dobree, James

The objective of the Market Blended Insight (MBI) project is to develop web based techniques to improve the performance of UK Business to Business (B2B) marketing activities. The analysis of company value chains is a fundamental task within MBI because it is an important model for understanding the market place and the company interactions within it. The project has aggregated rich data profiles of 3.7 million companies that form the active UK business community. The profiles are augmented by Web extractions from heterogeneous sources to provide unparalleled business insight. Advances by the Semantic Web in knowledge representation and logic reasoning allow flexible integration of data from heterogeneous sources, transformation between different representations and reasoning about their meaning. The MBI project has identified that the market insight and analysis interests of different types of users are difficult to maintain using a single domain ontology. Therefore, the project has developed a technique to undertake a plurality of analyses of value chains by deploying a distributed multi-view ontology to capture different user views over the classification of companies and their various relationships.

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.

Volume and Value of Big Healthcare Data.

PubMed

Dinov, Ivo D

Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions.

Towards a Ubiquitous User Model for Profile Sharing and Reuse

PubMed Central

de Lourdes Martinez-Villaseñor, Maria; Gonzalez-Mendoza, Miguel; Hernandez-Gress, Neil

2012-01-01

People interact with systems and applications through several devices and are willing to share information about preferences, interests and characteristics. Social networking profiles, data from advanced sensors attached to personal gadgets, and semantic web technologies such as FOAF and microformats are valuable sources of personal information that could provide a fair understanding of the user, but profile information is scattered over different user models. Some researchers in the ubiquitous user modeling community envision the need to share user model's information from heterogeneous sources. In this paper, we address the syntactic and semantic heterogeneity of user models in order to enable user modeling interoperability. We present a dynamic user profile structure based in Simple Knowledge Organization for the Web (SKOS) to provide knowledge representation for ubiquitous user model. We propose a two-tier matching strategy for concept schemas alignment to enable user modeling interoperability. Our proposal is proved in the application scenario of sharing and reusing data in order to deal with overweight and obesity. PMID:23201995

Volume and Value of Big Healthcare Data

PubMed Central

Dinov, Ivo D.

2016-01-01

Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions. PMID:26998309

The heterogeneity of mental representation: Ending the imagery debate.

PubMed

Pearson, Joel; Kosslyn, Stephen M

2015-08-18

The possible ways that information can be represented mentally have been discussed often over the past thousand years. However, this issue could not be addressed rigorously until late in the 20th century. Initial empirical findings spurred a debate about the heterogeneity of mental representation: Is all information stored in propositional, language-like, symbolic internal representations, or can humans use at least two different types of representations (and possibly many more)? Here, in historical context, we describe recent evidence that humans do not always rely on propositional internal representations but, instead, can also rely on at least one other format: depictive representation. We propose that the debate should now move on to characterizing all of the different forms of human mental representation.

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.

The importance of topography controlled sub-grid process heterogeneity in distributed hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, R. C.; Samaniego, L.; Mai, J.; Kumar, R.; Thober, S.; Zink, M.; Schäfer, D.; Savenije, H. H. G.; Hrachowitz, M.

2015-12-01

Heterogeneity of landscape features like terrain, soil, and vegetation properties affect the partitioning of water and energy. However, it remains unclear to which extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated in the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge based model constraints reduces model uncertainty; and (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both, the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as overall measure for model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 % respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. Besides, it was shown that suitable semi-quantitative prior constraints in combination with the transfer function based regularization approach of mHM, can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Samaniego, Luis; Mai, Juliane; Kumar, Rohini; Thober, Stephan; Zink, Matthias; Schäfer, David; Savenije, Hubert H. G.; Hrachowitz, Markus

2016-03-01

Heterogeneity of landscape features like terrain, soil, and vegetation properties affects the partitioning of water and energy. However, it remains unclear to what extent an explicit representation of this heterogeneity at the sub-grid scale of distributed hydrological models can improve the hydrological consistency and the robustness of such models. In this study, hydrological process complexity arising from sub-grid topography heterogeneity was incorporated into the distributed mesoscale Hydrologic Model (mHM). Seven study catchments across Europe were used to test whether (1) the incorporation of additional sub-grid variability on the basis of landscape-derived response units improves model internal dynamics, (2) the application of semi-quantitative, expert-knowledge-based model constraints reduces model uncertainty, and whether (3) the combined use of sub-grid response units and model constraints improves the spatial transferability of the model. Unconstrained and constrained versions of both the original mHM and mHMtopo, which allows for topography-based sub-grid heterogeneity, were calibrated for each catchment individually following a multi-objective calibration strategy. In addition, four of the study catchments were simultaneously calibrated and their feasible parameter sets were transferred to the remaining three receiver catchments. In a post-calibration evaluation procedure the probabilities of model and transferability improvement, when accounting for sub-grid variability and/or applying expert-knowledge-based model constraints, were assessed on the basis of a set of hydrological signatures. In terms of the Euclidian distance to the optimal model, used as an overall measure of model performance with respect to the individual signatures, the model improvement achieved by introducing sub-grid heterogeneity to mHM in mHMtopo was on average 13 %. The addition of semi-quantitative constraints to mHM and mHMtopo resulted in improvements of 13 and 19 %, respectively, compared to the base case of the unconstrained mHM. Most significant improvements in signature representations were, in particular, achieved for low flow statistics. The application of prior semi-quantitative constraints further improved the partitioning between runoff and evaporative fluxes. In addition, it was shown that suitable semi-quantitative prior constraints in combination with the transfer-function-based regularization approach of mHM can be beneficial for spatial model transferability as the Euclidian distances for the signatures improved on average by 2 %. The effect of semi-quantitative prior constraints combined with topography-guided sub-grid heterogeneity on transferability showed a more variable picture of improvements and deteriorations, but most improvements were observed for low flow statistics.

ProphTools: general prioritization tools for heterogeneous biological networks.

PubMed

Navarro, Carmen; Martínez, Victor; Blanco, Armando; Cano, Carlos

2017-12-01

Networks have been proven effective representations for the analysis of biological data. As such, there exist multiple methods to extract knowledge from biological networks. However, these approaches usually limit their scope to a single biological entity type of interest or they lack the flexibility to analyze user-defined data. We developed ProphTools, a flexible open-source command-line tool that performs prioritization on a heterogeneous network. ProphTools prioritization combines a Flow Propagation algorithm similar to a Random Walk with Restarts and a weighted propagation method. A flexible model for the representation of a heterogeneous network allows the user to define a prioritization problem involving an arbitrary number of entity types and their interconnections. Furthermore, ProphTools provides functionality to perform cross-validation tests, allowing users to select the best network configuration for a given problem. ProphTools core prioritization methodology has already been proven effective in gene-disease prioritization and drug repositioning. Here we make ProphTools available to the scientific community as flexible, open-source software and perform a new proof-of-concept case study on long noncoding RNAs (lncRNAs) to disease prioritization. ProphTools is robust prioritization software that provides the flexibility not present in other state-of-the-art network analysis approaches, enabling researchers to perform prioritization tasks on any user-defined heterogeneous network. Furthermore, the application to lncRNA-disease prioritization shows that ProphTools can reach the performance levels of ad hoc prioritization tools without losing its generality. © The Authors 2017. Published by Oxford University Press.

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

Ontological modelling of knowledge management for human-machine integrated design of ultra-precision grinding machine

NASA Astrophysics Data System (ADS)

Hong, Haibo; Yin, Yuehong; Chen, Xing

2016-11-01

Despite the rapid development of computer science and information technology, an efficient human-machine integrated enterprise information system for designing complex mechatronic products is still not fully accomplished, partly because of the inharmonious communication among collaborators. Therefore, one challenge in human-machine integration is how to establish an appropriate knowledge management (KM) model to support integration and sharing of heterogeneous product knowledge. Aiming at the diversity of design knowledge, this article proposes an ontology-based model to reach an unambiguous and normative representation of knowledge. First, an ontology-based human-machine integrated design framework is described, then corresponding ontologies and sub-ontologies are established according to different purposes and scopes. Second, a similarity calculation-based ontology integration method composed of ontology mapping and ontology merging is introduced. The ontology searching-based knowledge sharing method is then developed. Finally, a case of human-machine integrated design of a large ultra-precision grinding machine is used to demonstrate the effectiveness of the method.

Spatiotemporal integration of molecular and anatomical data in virtual reality using semantic mapping.

PubMed

Soh, Jung; Turinsky, Andrei L; Trinh, Quang M; Chang, Jasmine; Sabhaney, Ajay; Dong, Xiaoli; Gordon, Paul Mk; Janzen, Ryan Pw; Hau, David; Xia, Jianguo; Wishart, David S; Sensen, Christoph W

2009-01-01

We have developed a computational framework for spatiotemporal integration of molecular and anatomical datasets in a virtual reality environment. Using two case studies involving gene expression data and pharmacokinetic data, respectively, we demonstrate how existing knowledge bases for molecular data can be semantically mapped onto a standardized anatomical context of human body. Our data mapping methodology uses ontological representations of heterogeneous biomedical datasets and an ontology reasoner to create complex semantic descriptions of biomedical processes. This framework provides a means to systematically combine an increasing amount of biomedical imaging and numerical data into spatiotemporally coherent graphical representations. Our work enables medical researchers with different expertise to simulate complex phenomena visually and to develop insights through the use of shared data, thus paving the way for pathological inference, developmental pattern discovery and biomedical hypothesis testing.

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

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.

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.

Understanding as Integration of Heterogeneous Representations

NASA Astrophysics Data System (ADS)

Martínez, Sergio F.

2014-03-01

The search for understanding is a major aim of science. Traditionally, understanding has been undervalued in the philosophy of science because of its psychological underpinnings; nowadays, however, it is widely recognized that epistemology cannot be divorced from psychology as sharp as traditional epistemology required. This eliminates the main obstacle to give scientific understanding due attention in philosophy of science. My aim in this paper is to describe an account of scientific understanding as an emergent feature of our mastering of different (causal) explanatory frameworks that takes place through the mastering of scientific practices. Different practices lead to different kinds of representations. Such representations are often heterogeneous. The integration of such representations constitute understanding.

Robust and efficient anomaly detection using heterogeneous representations

NASA Astrophysics Data System (ADS)

Hu, Xing; Hu, Shiqiang; Xie, Jinhua; Zheng, Shiyou

2015-05-01

Various approaches have been proposed for video anomaly detection. Yet these approaches typically suffer from one or more limitations: they often characterize the pattern using its internal information, but ignore its external relationship which is important for local anomaly detection. Moreover, the high-dimensionality and the lack of robustness of pattern representation may lead to problems, including overfitting, increased computational cost and memory requirements, and high false alarm rate. We propose a video anomaly detection framework which relies on a heterogeneous representation to account for both the pattern's internal information and external relationship. The internal information is characterized by slow features learned by slow feature analysis from low-level representations, and the external relationship is characterized by the spatial contextual distances. The heterogeneous representation is compact, robust, efficient, and discriminative for anomaly detection. Moreover, both the pattern's internal information and external relationship can be taken into account in the proposed framework. Extensive experiments demonstrate the robustness and efficiency of our approach by comparison with the state-of-the-art approaches on the widely used benchmark datasets.

The role of phonological alternation in speech production: evidence from Mandarin tone sandhi

PubMed Central

Politzer-Ahles, Stephen; Zhang, Jie

2014-01-01

We investigate the role of phonological alternation during speech production in Mandarin using implicit priming, a paradigm in which participants respond faster to words in sets that are phonologically homogeneous than in sets that are phonologically heterogeneous. We test whether priming is obtained when words in a set share the same tones at the underlying level but have different tones at the surface level-i.e., when the set includes a word that undergoes a phonological alternation which changes the tone. Sets that are heterogeneous at the surface level (in which the heterogeneity is due to a phonological operation) failed to elicit priming, as did sets that are heterogeneous at the underlying and surface levels (in which the heterogeneity is due to the lexical representations). This finding suggests that the phonological alternation was computed before the initiation of articulation, offering evidence that the progression from underlying phonological representations to articulatory execution may be mediated online by phonological input-to-output mapping. Furthermore, sets of words that are heterogeneous only at the surface level showed a different trend than sets of words that are heterogeneous at both levels, suggesting that both the surface and underlying levels of representation play a role during speech production. PMID:24967001

Heterogeneous recurrence monitoring and control of nonlinear stochastic processes

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

Yang, Hui, E-mail: huiyang@usf.edu; Chen, Yun

Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., valuesmore » and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system.« less

Evaluation, Use, and Refinement of Knowledge Representations through Acquisition Modeling

ERIC Educational Resources Information Center

Pearl, Lisa

2017-01-01

Generative approaches to language have long recognized the natural link between theories of knowledge representation and theories of knowledge acquisition. The basic idea is that the knowledge representations provided by Universal Grammar enable children to acquire language as reliably as they do because these representations highlight the…

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

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.

Network embedding-based representation learning for single cell RNA-seq data.

PubMed

Li, Xiangyu; Chen, Weizheng; Chen, Yang; Zhang, Xuegong; Gu, Jin; Zhang, Michael Q

2017-11-02

Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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)…

Simultaneous Local Binary Feature Learning and Encoding for Homogeneous and Heterogeneous Face Recognition.

PubMed

Lu, Jiwen; Erin Liong, Venice; Zhou, Jie

2017-08-09

In this paper, we propose a simultaneous local binary feature learning and encoding (SLBFLE) approach for both homogeneous and heterogeneous face recognition. Unlike existing hand-crafted face descriptors such as local binary pattern (LBP) and Gabor features which usually require strong prior knowledge, our SLBFLE is an unsupervised feature learning approach which automatically learns face representation from raw pixels. Unlike existing binary face descriptors such as the LBP, discriminant face descriptor (DFD), and compact binary face descriptor (CBFD) which use a two-stage feature extraction procedure, our SLBFLE jointly learns binary codes and the codebook for local face patches so that discriminative information from raw pixels from face images of different identities can be obtained by using a one-stage feature learning and encoding procedure. Moreover, we propose a coupled simultaneous local binary feature learning and encoding (C-SLBFLE) method to make the proposed approach suitable for heterogeneous face matching. Unlike most existing coupled feature learning methods which learn a pair of transformation matrices for each modality, we exploit both the common and specific information from heterogeneous face samples to characterize their underlying correlations. Experimental results on six widely used face datasets are presented to demonstrate the effectiveness of the proposed method.

Cirrus Susceptibility to Changes in Ice Nuclei: Physical Processes, Model Uncertainties, and Measurement Needs

NASA Technical Reports Server (NTRS)

Jensen, Eric

2017-01-01

In this talk, I will begin by discussing the physical processes that govern the competition between heterogeneous and homogeneous ice nucleation in upper tropospheric cirrus clouds. Next, I will review the current knowledge of low-temperature ice nucleation from laboratory experiments and field measurements. I will then discuss the uncertainties and deficiencies in representations of cirrus processes in global models used to estimate the climate impacts of changes in cirrus clouds. Lastly, I will review the critical field measurements needed to advance our understanding of cirrus and their susceptibility to changes in aerosol properties.

Teenage Queerness: Negotiating Heteronormativity in the Representation of Gay Teenagers in "Glee"

ERIC Educational Resources Information Center

Dhaenens, Frederik

2013-01-01

Despite a significant increase in gay representation in contemporary television fiction, many media scholars argue that the representation of gay men and women is governed by heteronormativity. They postulate that even rounded and heterogeneous representations of gay men and women are characters that desire to participate in institutions,…

A knowledge-based system for patient image pre-fetching in heterogeneous database environments--modeling, design, and evaluation.

PubMed

Wei, C P; Hu, P J; Sheng, O R

2001-03-01

When performing primary reading on a newly taken radiological examination, a radiologist often needs to reference relevant prior images of the same patient for confirmation or comparison purposes. Support of such image references is of clinical importance and may have significant effects on radiologists' examination reading efficiency, service quality, and work satisfaction. To effectively support such image reference needs, we proposed and developed a knowledge-based patient image pre-fetching system, addressing several challenging requirements of the application that include representation and learning of image reference heuristics and management of data-intensive knowledge inferencing. Moreover, the system demands an extensible and maintainable architecture design capable of effectively adapting to a dynamic environment characterized by heterogeneous and autonomous data source systems. In this paper, we developed a synthesized object-oriented entity- relationship model, a conceptual model appropriate for representing radiologists' prior image reference heuristics that are heuristic oriented and data intensive. We detailed the system architecture and design of the knowledge-based patient image pre-fetching system. Our architecture design is based on a client-mediator-server framework, capable of coping with a dynamic environment characterized by distributed, heterogeneous, and highly autonomous data source systems. To adapt to changes in radiologists' patient prior image reference heuristics, ID3-based multidecision-tree induction and CN2-based multidecision induction learning techniques were developed and evaluated. Experimentally, we examined effects of the pre-fetching system we created on radiologists' examination readings. Preliminary results show that the knowledge-based patient image pre-fetching system more accurately supports radiologists' patient prior image reference needs than the current practice adopted at the study site and that radiologists may become more efficient, consultatively effective, and better satisfied when supported by the pre-fetching system than when relying on the study site's pre-fetching practice.

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

Roughness Versus Charge Contributions to Representative Discrete Heterogeneity Underlying Mechanistic Prediction of Colloid Attachment, Detachment and Breakthrough-Elution Behavior Under Environmental Conditions.

NASA Astrophysics Data System (ADS)

Johnson, William; Farnsworth, Anna; Vanness, Kurt; Hilpert, Markus

2017-04-01

The key element of a mechanistic theory to predict colloid attachment in porous media under environmental conditions where colloid-collector repulsion exists (unfavorable conditions for attachment) is representation of the nano-scale surface heterogeneity (herein called discrete heterogeneity) that drives colloid attachment under unfavorable conditions. The observed modes of colloid attachment under unfavorable conditions emerge from simulations that incorporate discrete heterogeneity. Quantitative prediction of attachment (and detachment) requires capturing the sizes, spatial frequencies, and other properties of roughness asperities and charge heterodomains in discrete heterogeneity representations of different surfaces. The fact that a given discrete heterogeneity representation will interact differently with different-sized colloids as well as different ionic strengths for a given sized colloid allows backing out representative discrete heterogeneity via comparison of simulations to experiments performed across a range of colloid size, solution IS, and fluid velocity. This has been achieved on unfavorable smooth surfaces yielding quantitative prediction of attachment, and qualitative prediction of detachment in response to ionic strength or flow perturbations. Extending this treatment to rough surfaces, and representing the contributions of nanoscale roughness as well as charge heterogeneity is a focus of this talk. Another focus of this talk is the upscaling the pore scale simulations to produce contrasting breakthrough-elution behaviors at the continuum (column) scale that are observed, for example, for different-sized colloids, or same-sized colloids under different ionic strength conditions. The outcome of mechanistic pore scale simulations incorporating discrete heterogeneity and subsequent upscaling is that temporal processes such as blocking and ripening will emerge organically from these simulations, since these processes fundamentally stem from the limited sites available for attachment as represented in discrete heterogeneity.

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

KaBOB: ontology-based semantic integration of biomedical databases.

PubMed

Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

2015-04-23

The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.

Using conceptual spaces to fuse knowledge from heterogeneous robot platforms

NASA Astrophysics Data System (ADS)

Kira, Zsolt

2010-04-01

As robots become more common, it becomes increasingly useful for many applications to use them in teams that sense the world in a distributed manner. In such situations, the robots or a central control center must communicate and fuse information received from multiple sources. A key challenge for this problem is perceptual heterogeneity, where the sensors, perceptual representations, and training instances used by the robots differ dramatically. In this paper, we use Gärdenfors' conceptual spaces, a geometric representation with strong roots in cognitive science and psychology, in order to represent the appearance of objects and show how the problem of heterogeneity can be intuitively explored by looking at the situation where multiple robots differ in their conceptual spaces at different levels. To bridge low-level sensory differences, we abstract raw sensory data into properties (such as color or texture categories), represented as Gaussian Mixture Models, and demonstrate that this facilitates both individual learning and the fusion of concepts between robots. Concepts (e.g. objects) are represented as a fuzzy mixture of these properties. We then treat the problem where the conceptual spaces of two robots differ and they only share a subset of these properties. In this case, we use joint interaction and statistical metrics to determine which properties are shared. Finally, we show how conceptual spaces can handle the combination of such missing properties when fusing concepts received from different robots. We demonstrate the fusion of information in real-robot experiments with a Mobile Robots Amigobot and Pioneer 2DX with significantly different cameras and (on one robot) a SICK lidar.ÿÿÿÿ

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.

Stock markets as Minority Games: cognitive heterogeneity and equilibrium emergence

NASA Astrophysics Data System (ADS)

Brandouy, O.

2005-04-01

Standard finance theory generally assumes homogeneous agents relatively to their preferences, heuristics and investment strategies. We propose to study, in an agent-based simulation, the emergence of equilibrium under various heterogeneous conditions. Market interaction is stylized with the Minority Game representation. It is shown that inductive rational equilibrium emerges even though agents do not share the same representations of the value. This may lead to consider again the roots of EMH and REH.

A development framework for distributed artificial intelligence

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1989-01-01

The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

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…

Model Based Analysis and Test Generation for Flight Software

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

2009-01-01

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

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

PubMed

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

2008-08-15

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

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.

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

PubMed

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

2011-01-01

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

Learning Compact Binary Face Descriptor for Face Recognition.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Xiuzhuang; Zhou, Jie

2015-10-01

Binary feature descriptors such as local binary patterns (LBP) and its variations have been widely used in many face recognition systems due to their excellent robustness and strong discriminative power. However, most existing binary face descriptors are hand-crafted, which require strong prior knowledge to engineer them by hand. In this paper, we propose a compact binary face descriptor (CBFD) feature learning method for face representation and recognition. Given each face image, we first extract pixel difference vectors (PDVs) in local patches by computing the difference between each pixel and its neighboring pixels. Then, we learn a feature mapping to project these pixel difference vectors into low-dimensional binary vectors in an unsupervised manner, where 1) the variance of all binary codes in the training set is maximized, 2) the loss between the original real-valued codes and the learned binary codes is minimized, and 3) binary codes evenly distribute at each learned bin, so that the redundancy information in PDVs is removed and compact binary codes are obtained. Lastly, we cluster and pool these binary codes into a histogram feature as the final representation for each face image. Moreover, we propose a coupled CBFD (C-CBFD) method by reducing the modality gap of heterogeneous faces at the feature level to make our method applicable to heterogeneous face recognition. Extensive experimental results on five widely used face datasets show that our methods outperform state-of-the-art face descriptors.

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

PubMed

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

2013-06-01

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

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…

Dual PECCS: a cognitive system for conceptual representation and categorization

NASA Astrophysics Data System (ADS)

Lieto, Antonio; Radicioni, Daniele P.; Rho, Valentina

2017-03-01

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and - in addition - that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual- PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation.

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…

OC-2-KB: A software pipeline to build an evidence-based obesity and cancer knowledge base.

PubMed

Lossio-Ventura, Juan Antonio; Hogan, William; Modave, François; Guo, Yi; He, Zhe; Hicks, Amanda; Bian, Jiang

2017-11-01

Obesity has been linked to several types of cancer. Access to adequate health information activates people's participation in managing their own health, which ultimately improves their health outcomes. Nevertheless, the existing online information about the relationship between obesity and cancer is heterogeneous and poorly organized. A formal knowledge representation can help better organize and deliver quality health information. Currently, there are several efforts in the biomedical domain to convert unstructured data to structured data and store them in Semantic Web knowledge bases (KB). In this demo paper, we present, OC-2-KB (Obesity and Cancer to Knowledge Base), a system that is tailored to guide the automatic KB construction for managing obesity and cancer knowledge from free-text scientific literature (i.e., PubMed abstracts) in a systematic way. OC-2-KB has two important modules which perform the acquisition of entities and the extraction then classification of relationships among these entities. We tested the OC-2-KB system on a data set with 23 manually annotated obesity and cancer PubMed abstracts and created a preliminary KB with 765 triples. We conducted a preliminary evaluation on this sample of triples and reported our evaluation results.

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.

Genome Microscale Heterogeneity among Wild Potatoes Revealed by Diversity Arrays Technology Marker Sequences.

PubMed

Traini, Alessandra; Iorizzo, Massimo; Mann, Harpartap; Bradeen, James M; Carputo, Domenico; Frusciante, Luigi; Chiusano, Maria Luisa

2013-01-01

Tuber-bearing potato species possess several genes that can be exploited to improve the genetic background of the cultivated potato Solanum tuberosum. Among them, S. bulbocastanum and S. commersonii are well known for their strong resistance to environmental stresses. However, scant information is available for these species in terms of genome organization, gene function, and regulatory networks. Consequently, genomic tools to assist breeding are meager, and efficient exploitation of these species has been limited so far. In this paper, we employed the reference genome sequences from cultivated potato and tomato and a collection of sequences of 1,423 potato Diversity Arrays Technology (DArT) markers that show polymorphic representation across the genomes of S. bulbocastanum and/or S. commersonii genotypes. Our results highlighted microscale genome sequence heterogeneity that may play a significant role in functional and structural divergence between related species. Our analytical approach provides knowledge of genome structural and sequence variability that could not be detected by transcriptome and proteome approaches.

A common type system for clinical natural language processing

PubMed Central

2013-01-01

Background One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. Results We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. Conclusions We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types. PMID:23286462

A common type system for clinical natural language processing.

PubMed

Wu, Stephen T; Kaggal, Vinod C; Dligach, Dmitriy; Masanz, James J; Chen, Pei; Becker, Lee; Chapman, Wendy W; Savova, Guergana K; Liu, Hongfang; Chute, Christopher G

2013-01-03

One challenge in reusing clinical data stored in electronic medical records is that these data are heterogenous. Clinical Natural Language Processing (NLP) plays an important role in transforming information in clinical text to a standard representation that is comparable and interoperable. Information may be processed and shared when a type system specifies the allowable data structures. Therefore, we aim to define a common type system for clinical NLP that enables interoperability between structured and unstructured data generated in different clinical settings. We describe a common type system for clinical NLP that has an end target of deep semantics based on Clinical Element Models (CEMs), thus interoperating with structured data and accommodating diverse NLP approaches. The type system has been implemented in UIMA (Unstructured Information Management Architecture) and is fully functional in a popular open-source clinical NLP system, cTAKES (clinical Text Analysis and Knowledge Extraction System) versions 2.0 and later. We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured data types.

Knowledge representation and management enabling intelligent interoperability - principles and standards.

PubMed

Blobel, Bernd

2013-01-01

Based on the paradigm changes for health, health services and underlying technologies as well as the need for at best comprehensive and increasingly automated interoperability, the paper addresses the challenge of knowledge representation and management for medical decision support. After introducing related definitions, a system-theoretical, architecture-centric approach to decision support systems (DSSs) and appropriate ways for representing them using systems of ontologies is given. Finally, existing and emerging knowledge representation and management standards are presented. The paper focuses on the knowledge representation and management part of DSSs, excluding the reasoning part from consideration.

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.

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.

Sensory feedback in a bump attractor model of path integration.

PubMed

Poll, Daniel B; Nguyen, Khanh; Kilpatrick, Zachary P

2016-04-01

Mammalian spatial navigation systems utilize several different sensory information channels. This information is converted into a neural code that represents the animal's current position in space by engaging place cell, grid cell, and head direction cell networks. In particular, sensory landmark (allothetic) cues can be utilized in concert with an animal's knowledge of its own velocity (idiothetic) cues to generate a more accurate representation of position than path integration provides on its own (Battaglia et al. The Journal of Neuroscience 24(19):4541-4550 (2004)). We develop a computational model that merges path integration with feedback from external sensory cues that provide a reliable representation of spatial position along an annular track. Starting with a continuous bump attractor model, we explore the impact of synaptic spatial asymmetry and heterogeneity, which disrupt the position code of the path integration process. We use asymptotic analysis to reduce the bump attractor model to a single scalar equation whose potential represents the impact of asymmetry and heterogeneity. Such imperfections cause errors to build up when the network performs path integration, but these errors can be corrected by an external control signal representing the effects of sensory cues. We demonstrate that there is an optimal strength and decay rate of the control signal when cues appear either periodically or randomly. A similar analysis is performed when errors in path integration arise from dynamic noise fluctuations. Again, there is an optimal strength and decay of discrete control that minimizes the path integration error.

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.

Modeling the effects of vegetation heterogeneity on wildland fire behavior

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Sieg, C.; Middleton, R. S.

2017-12-01

Vegetation structure and densities are known to drive fire-spread rate and burn severity. Many fire-spread models incorporate an average, homogenous fuel density in the model domain to drive fire behavior. However, vegetation communities are rarely homogenous and instead present significant heterogeneous structure and fuel densities in the fires path. This results in observed patches of varied burn severities and mosaics of disturbed conditions that affect ecological recovery and hydrologic response. Consequently, to understand the interactions of fire and ecosystem functions, representations of spatially heterogeneous conditions need to be incorporated into fire models. Mechanistic models of fire disturbance offer insight into how fuel load characterization and distribution result in varied fire behavior. Here we use a physically-based 3D combustion model—FIRETEC—that solves conservation of mass, momentum, energy, and chemical species to compare fire behavior on homogenous representations to a heterogeneous vegetation distribution. Results demonstrate the impact vegetation heterogeneity has on the spread rate, intensity, and extent of simulated wildfires thus providing valuable insight in predicted wildland fire evolution and enhanced ability to estimate wildland fire inputs into regional and global climate models.

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…

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.

Spatial navigation by congenitally blind individuals.

PubMed

Schinazi, Victor R; Thrash, Tyler; Chebat, Daniel-Robert

2016-01-01

Spatial navigation in the absence of vision has been investigated from a variety of perspectives and disciplines. These different approaches have progressed our understanding of spatial knowledge acquisition by blind individuals, including their abilities, strategies, and corresponding mental representations. In this review, we propose a framework for investigating differences in spatial knowledge acquisition by blind and sighted people consisting of three longitudinal models (i.e., convergent, cumulative, and persistent). Recent advances in neuroscience and technological devices have provided novel insights into the different neural mechanisms underlying spatial navigation by blind and sighted people and the potential for functional reorganization. Despite these advances, there is still a lack of consensus regarding the extent to which locomotion and wayfinding depend on amodal spatial representations. This challenge largely stems from methodological limitations such as heterogeneity in the blind population and terminological ambiguity related to the concept of cognitive maps. Coupled with an over-reliance on potential technological solutions, the field has diffused into theoretical and applied branches that do not always communicate. Here, we review research on navigation by congenitally blind individuals with an emphasis on behavioral and neuroscientific evidence, as well as the potential of technological assistance. Throughout the article, we emphasize the need to disentangle strategy choice and performance when discussing the navigation abilities of the blind population. For further resources related to this article, please visit the WIREs website. © 2015 The Authors. WIREs Cognitive Science published by Wiley Periodicals, Inc.

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.

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

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

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE PAGES

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith; ...

2017-11-06

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

Representation and Exchange of Knowledge as a Basis of Information Processes. Proceedings of the International Research Forum in Information Science (5th, Heidelberg, West Germany, September 5-7, 1983).

ERIC Educational Resources Information Center

Dietschmann, Hans, Ed.

This 22-paper collection addresses a variety of issues related to representation and transfer of knowledge. Individual papers include an explanation of the usefulness of general scientific models versus case-specific approaches and a discussion of different empirical approaches to the general problem of knowledge representation for information…

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.

Heterogeneous iris image hallucination using sparse representation on a learned heterogeneous patch dictionary

NASA Astrophysics Data System (ADS)

Li, Yung-Hui; Zheng, Bo-Ren; Ji, Dai-Yan; Tien, Chung-Hao; Liu, Po-Tsun

2014-09-01

Cross sensor iris matching may seriously degrade the recognition performance because of the sensor mis-match problem of iris images between the enrollment and test stage. In this paper, we propose two novel patch-based heterogeneous dictionary learning method to attack this problem. The first method applies the latest sparse representation theory while the second method tries to learn the correspondence relationship through PCA in heterogeneous patch space. Both methods learn the basic atoms in iris textures across different image sensors and build connections between them. After such connections are built, at test stage, it is possible to hallucinate (synthesize) iris images across different sensors. By matching training images with hallucinated images, the recognition rate can be successfully enhanced. The experimental results showed the satisfied results both visually and in terms of recognition rate. Experimenting with an iris database consisting of 3015 images, we show that the EER is decreased 39.4% relatively by the proposed method.

Building distributed rule-based systems using the AI Bus

NASA Technical Reports Server (NTRS)

Schultz, Roger D.; Stobie, Iain C.

1990-01-01

The AI Bus software architecture was designed to support the construction of large-scale, production-quality applications in areas of high technology flux, running heterogeneous distributed environments, utilizing a mix of knowledge-based and conventional components. These goals led to its current development as a layered, object-oriented library for cooperative systems. This paper describes the concepts and design of the AI Bus and its implementation status as a library of reusable and customizable objects, structured by layers from operating system interfaces up to high-level knowledge-based agents. Each agent is a semi-autonomous process with specialized expertise, and consists of a number of knowledge sources (a knowledge base and inference engine). Inter-agent communication mechanisms are based on blackboards and Actors-style acquaintances. As a conservative first implementation, we used C++ on top of Unix, and wrapped an embedded Clips with methods for the knowledge source class. This involved designing standard protocols for communication and functions which use these protocols in rules. Embedding several CLIPS objects within a single process was an unexpected problem because of global variables, whose solution involved constructing and recompiling a C++ version of CLIPS. We are currently working on a more radical approach to incorporating CLIPS, by separating out its pattern matcher, rule and fact representations and other components as true object oriented modules.

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.

Biopsy variability of lymphocytic infiltration in breast cancer subtypes and the ImmunoSkew score

NASA Astrophysics Data System (ADS)

Khan, Adnan Mujahid; Yuan, Yinyin

2016-11-01

The number of tumour biopsies required for a good representation of tumours has been controversial. An important factor to consider is intra-tumour heterogeneity, which can vary among cancer types and subtypes. Immune cells in particular often display complex infiltrative patterns, however, there is a lack of quantitative understanding of the spatial heterogeneity of immune cells and how this fundamental biological nature of human tumours influences biopsy variability and treatment resistance. We systematically investigate biopsy variability for the lymphocytic infiltrate in 998 breast tumours using a novel virtual biopsy method. Across all breast cancers, we observe a nonlinear increase in concordance between the biopsy and whole-tumour score of lymphocytic infiltrate with increasing number of biopsies, yet little improvement is gained with more than four biopsies. Interestingly, biopsy variability of lymphocytic infiltrate differs considerably among breast cancer subtypes, with the human epidermal growth factor receptor 2-positive (HER2+) subtype having the highest variability. We subsequently identify a quantitative measure of spatial variability that predicts disease-specific survival in HER2+ subtype independent of standard clinical variables (node status, tumour size and grade). Our study demonstrates how systematic methods provide new insights that can influence future study design based on a quantitative knowledge of tumour heterogeneity.

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.

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

Large-Scale Modeling of Wordform Learning and Representation

ERIC Educational Resources Information Center

Sibley, Daragh E.; Kello, Christopher T.; Plaut, David C.; Elman, Jeffrey L.

2008-01-01

The forms of words as they appear in text and speech are central to theories and models of lexical processing. Nonetheless, current methods for simulating their learning and representation fail to approach the scale and heterogeneity of real wordform lexicons. A connectionist architecture termed the "sequence encoder" is used to learn…

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…

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…

Employees and Creativity: Social Ties and Access to Heterogeneous Knowledge

ERIC Educational Resources Information Center

Huang, Chiung-En; Liu, Chih-Hsing Sam

2015-01-01

This study dealt with employee social ties, knowledge heterogeneity contacts, and the generation of creativity. Although prior studies demonstrated a relationship between network position and creativity, inadequate attention has been paid to network ties and heterogeneity knowledge contacts. This study considered the social interaction processes…

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

PubMed

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

2013-03-01

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

Design and Evaluation of a Bacterial Clinical Infectious Diseases Ontology

PubMed Central

Gordon, Claire L.; Pouch, Stephanie; Cowell, Lindsay G.; Boland, Mary Regina; Platt, Heather L.; Goldfain, Albert; Weng, Chunhua

2013-01-01

With antimicrobial resistance increasing worldwide, there is a great need to use automated antimicrobial decision support systems (ADSSs) to lower antimicrobial resistance rates by promoting appropriate antimicrobial use. However, they are infrequently used mostly because of their poor interoperability with different health information technologies. Ontologies can augment portable ADSSs by providing an explicit knowledge representation for biomedical entities and their relationships, helping to standardize and integrate heterogeneous data resources. We developed a bacterial clinical infectious diseases ontology (BCIDO) using Protégé-OWL. BCIDO defines a controlled terminology for clinical infectious diseases along with domain knowledge commonly used in hospital settings for clinical infectious disease treatment decision-making. BCIDO has 599 classes and 2355 object properties. Terms were imported from or mapped to Systematized Nomenclature of Medicine, Unified Medical Language System, RxNorm and National Center for Bitechnology Information Organismal Classification where possible. Domain expert evaluation using the “laddering” technique, ontology visualization, and clinical notes and scenarios, confirmed the correctness and potential usefulness of BCIDO. PMID:24551353

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.

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.

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…

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

Representation and matching of knowledge to design digital systems

NASA Technical Reports Server (NTRS)

Jones, J. U.; Shiva, S. G.

1988-01-01

A knowledge-based expert system is described that provides an approach to solve a problem requiring an expert with considerable domain expertise and facts about available digital hardware building blocks. To design digital hardware systems from their high level VHDL (Very High Speed Integrated Circuit Hardware Description Language) representation to their finished form, a special data representation is required. This data representation as well as the functioning of the overall system is described.

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.

Action representation: crosstalk between semantics and pragmatics.

PubMed

Prinz, Wolfgang

2014-03-01

Marc Jeannerod pioneered a representational approach to movement and action. In his approach, motor representations provide both, declarative knowledge about action and procedural knowledge for action (action semantics and action pragmatics, respectively). Recent evidence from language comprehension and action simulation supports the claim that action pragmatics and action semantics draw on common representational resources, thus challenging the traditional divide between declarative and procedural action knowledge. To account for these observations, three kinds of theoretical frameworks are discussed: (i) semantics is grounded in pragmatics, (ii) pragmatics is anchored in semantics, and (iii) pragmatics is part and parcel of semantics. © 2013 Elsevier Ltd. All rights reserved.

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.

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Ensemble representations: effects of set size and item heterogeneity on average size perception.

PubMed

Marchant, Alexander P; Simons, Daniel J; de Fockert, Jan W

2013-02-01

Observers can accurately perceive and evaluate the statistical properties of a set of objects, forming what is now known as an ensemble representation. The accuracy and speed with which people can judge the mean size of a set of objects have led to the proposal that ensemble representations of average size can be computed in parallel when attention is distributed across the display. Consistent with this idea, judgments of mean size show little or no decrement in accuracy when the number of objects in the set increases. However, the lack of a set size effect might result from the regularity of the item sizes used in previous studies. Here, we replicate these previous findings, but show that judgments of mean set size become less accurate when set size increases and the heterogeneity of the item sizes increases. This pattern can be explained by assuming that average size judgments are computed using a limited capacity sampling strategy, and it does not necessitate an ensemble representation computed in parallel across all items in a display. Copyright © 2012 Elsevier B.V. All rights reserved.

ARIANE: integration of information databases within a hospital intranet.

PubMed

Joubert, M; Aymard, S; Fieschi, D; Volot, F; Staccini, P; Robert, J J; Fieschi, M

1998-05-01

Large information systems handle massive volume of data stored in heterogeneous sources. Each server has its own model of representation of concepts with regard to its aims. One of the main problems end-users encounter when accessing different servers is to match their own viewpoint on biomedical concepts with the various representations that are made in the databases servers. The aim of the project ARIANE is to provide end-users with easy-to-use and natural means to access and query heterogeneous information databases. The objectives of this research work consist in building a conceptual interface by means of the Internet technology inside an enterprise Intranet and to propose a method to realize it. This method is based on the knowledge sources provided by the Unified Medical Language System (UMLS) project of the US National Library of Medicine. Experiments concern queries to three different information servers: PubMed, a Medline server of the NLM; Thériaque, a French database on drugs implemented in the Hospital Intranet; and a Web site dedicated to Internet resources in gastroenterology and nutrition, located at the Faculty of Medicine of Nice (France). Accessing to each of these servers is different according to the kind of information delivered and according to the technology used to query it. Dealing with health care professional workstation, the authors introduced in the ARIANE project quality criteria in order to attempt a homogeneous and efficient way to build a query system able to be integrated in existing information systems and to integrate existing and new information sources.

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.

Response variance in functional maps: neural darwinism revisited.

PubMed

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response Variance in Functional Maps: Neural Darwinism Revisited

PubMed Central

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population. PMID:23874733

A discontinuous control volume finite element method for multi-phase flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Salinas, P.; Pavlidis, D.; Xie, Z.; Osman, H.; Pain, C. C.; Jackson, M. D.

2018-01-01

We present a new, high-order, control-volume-finite-element (CVFE) method for multiphase porous media flow with discontinuous 1st-order representation for pressure and discontinuous 2nd-order representation for velocity. The method has been implemented using unstructured tetrahedral meshes to discretize space. The method locally and globally conserves mass. However, unlike conventional CVFE formulations, the method presented here does not require the use of control volumes (CVs) that span the boundaries between domains with differing material properties. We demonstrate that the approach accurately preserves discontinuous saturation changes caused by permeability variations across such boundaries, allowing efficient simulation of flow in highly heterogeneous models. Moreover, accurate solutions are obtained at significantly lower computational cost than using conventional CVFE methods. We resolve a long-standing problem associated with the use of classical CVFE methods to model flow in highly heterogeneous porous media.

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.

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…

Mobile Knowledge, Karma Points and Digital Peers: The Tacit Epistemology and Linguistic Representation of MOOCs

ERIC Educational Resources Information Center

Portmess, Lisa

2013-01-01

Media representations of massive open online courses (MOOCs) such as those offered by Coursera, edX and Udacity reflect tension and ambiguity in their bold promise of democratized education and global knowledge sharing. An approach to MOOCs that emphasizes the tacit epistemology of such representations suggests a richer account of the ambiguities…

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.

Calibration of an Unsteady Groundwater Flow Model for a Complex, Strongly Heterogeneous Aquifer

NASA Astrophysics Data System (ADS)

Curtis, Z. K.; Liao, H.; Li, S. G.; Phanikumar, M. S.; Lusch, D.

2016-12-01

Modeling of groundwater systems characterized by complex three-dimensional structure and heterogeneity remains a significant challenge. Most of today's groundwater models are developed based on relatively simple conceptual representations in favor of model calibratibility. As more complexities are modeled, e.g., by adding more layers and/or zones, or introducing transient processes, more parameters have to be estimated and issues related to ill-posed groundwater problems and non-unique calibration arise. Here, we explore the use of an alternative conceptual representation for groundwater modeling that is fully three-dimensional and can capture complex 3D heterogeneity (both systematic and "random") without over-parameterizing the aquifer system. In particular, we apply Transition Probability (TP) geostatistics on high resolution borehole data from a water well database to characterize the complex 3D geology. Different aquifer material classes, e.g., `AQ' (aquifer material), `MAQ' (marginal aquifer material'), `PCM' (partially confining material), and `CM' (confining material), are simulated, with the hydraulic properties of each material type as tuning parameters during calibration. The TP-based approach is applied to simulate unsteady groundwater flow in a large, complex, and strongly heterogeneous glacial aquifer system in Michigan across multiple spatial and temporal scales. The resulting model is calibrated to observed static water level data over a time span of 50 years. The results show that the TP-based conceptualization enables much more accurate and robust calibration/simulation than that based on conventional deterministic layer/zone based conceptual representations.

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.

Towards a category theory approach to analogy: Analyzing re-representation and acquisition of numerical knowledge.

PubMed

Navarrete, Jairo A; Dartnell, Pablo

2017-08-01

Category Theory, a branch of mathematics, has shown promise as a modeling framework for higher-level cognition. We introduce an algebraic model for analogy that uses the language of category theory to explore analogy-related cognitive phenomena. To illustrate the potential of this approach, we use this model to explore three objects of study in cognitive literature. First, (a) we use commutative diagrams to analyze an effect of playing particular educational board games on the learning of numbers. Second, (b) we employ a notion called coequalizer as a formal model of re-representation that explains a property of computational models of analogy called "flexibility" whereby non-similar representational elements are considered matches and placed in structural correspondence. Finally, (c) we build a formal learning model which shows that re-representation, language processing and analogy making can explain the acquisition of knowledge of rational numbers. These objects of study provide a picture of acquisition of numerical knowledge that is compatible with empirical evidence and offers insights on possible connections between notions such as relational knowledge, analogy, learning, conceptual knowledge, re-representation and procedural knowledge. This suggests that the approach presented here facilitates mathematical modeling of cognition and provides novel ways to think about analogy-related cognitive phenomena.

Towards a category theory approach to analogy: Analyzing re-representation and acquisition of numerical knowledge

PubMed Central

2017-01-01

Category Theory, a branch of mathematics, has shown promise as a modeling framework for higher-level cognition. We introduce an algebraic model for analogy that uses the language of category theory to explore analogy-related cognitive phenomena. To illustrate the potential of this approach, we use this model to explore three objects of study in cognitive literature. First, (a) we use commutative diagrams to analyze an effect of playing particular educational board games on the learning of numbers. Second, (b) we employ a notion called coequalizer as a formal model of re-representation that explains a property of computational models of analogy called “flexibility” whereby non-similar representational elements are considered matches and placed in structural correspondence. Finally, (c) we build a formal learning model which shows that re-representation, language processing and analogy making can explain the acquisition of knowledge of rational numbers. These objects of study provide a picture of acquisition of numerical knowledge that is compatible with empirical evidence and offers insights on possible connections between notions such as relational knowledge, analogy, learning, conceptual knowledge, re-representation and procedural knowledge. This suggests that the approach presented here facilitates mathematical modeling of cognition and provides novel ways to think about analogy-related cognitive phenomena. PMID:28841643

Representation and presentation of requirements knowledge

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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.

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,…

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.

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

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer

PubMed Central

González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Taruscio, Domenica; Lochmüller, Hanns

2017-01-01

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries. PMID:29214177

Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer.

PubMed

Sernadela, Pedro; González-Castro, Lorena; Carta, Claudio; van der Horst, Eelke; Lopes, Pedro; Kaliyaperumal, Rajaram; Thompson, Mark; Thompson, Rachel; Queralt-Rosinach, Núria; Lopez, Estrella; Wood, Libby; Robertson, Agata; Lamanna, Claudia; Gilling, Mette; Orth, Michael; Merino-Martinez, Roxana; Posada, Manuel; Taruscio, Domenica; Lochmüller, Hanns; Robinson, Peter; Roos, Marco; Oliveira, José Luís

2017-01-01

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.

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.

DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer.

PubMed

Saha, Abhijoy; Banerjee, Sayantan; Kurtek, Sebastian; Narang, Shivali; Lee, Joonsang; Rao, Ganesh; Martinez, Juan; Bharath, Karthik; Rao, Arvind U K; Baladandayuthapani, Veerabhadran

2016-01-01

Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher-Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.

Interconnecting heterogeneous database management systems

NASA Technical Reports Server (NTRS)

Gligor, V. D.; Luckenbaugh, G. L.

1984-01-01

It is pointed out that there is still a great need for the development of improved communication between remote, heterogeneous database management systems (DBMS). Problems regarding the effective communication between distributed DBMSs are primarily related to significant differences between local data managers, local data models and representations, and local transaction managers. A system of interconnected DBMSs which exhibit such differences is called a network of distributed, heterogeneous DBMSs. In order to achieve effective interconnection of remote, heterogeneous DBMSs, the users must have uniform, integrated access to the different DBMs. The present investigation is mainly concerned with an analysis of the existing approaches to interconnecting heterogeneous DBMSs, taking into account four experimental DBMS projects.

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 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.

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.

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...

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

PubMed

Chrysafiadi, Konstantina; Virvou, Maria

2013-12-01

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

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

PubMed

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

2013-09-01

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

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

Operator assistant systems - An experimental approach using a telerobotics application

NASA Technical Reports Server (NTRS)

Boy, Guy A.; Mathe, Nathalie

1993-01-01

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

Knowledge 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

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

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…

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…

Heterogeneous classifier fusion for ligand-based virtual screening: or, how decision making by committee can be a good thing.

PubMed

Riniker, Sereina; Fechner, Nikolas; Landrum, Gregory A

2013-11-25

The concept of data fusion - the combination of information from different sources describing the same object with the expectation to generate a more accurate representation - has found application in a very broad range of disciplines. In the context of ligand-based virtual screening (VS), data fusion has been applied to combine knowledge from either different active molecules or different fingerprints to improve similarity search performance. Machine-learning (ML) methods based on fusion of multiple homogeneous classifiers, in particular random forests, have also been widely applied in the ML literature. The heterogeneous version of classifier fusion - fusing the predictions from different model types - has been less explored. Here, we investigate heterogeneous classifier fusion for ligand-based VS using three different ML methods, RF, naïve Bayes (NB), and logistic regression (LR), with four 2D fingerprints, atom pairs, topological torsions, RDKit fingerprint, and circular fingerprint. The methods are compared using a previously developed benchmarking platform for 2D fingerprints which is extended to ML methods in this article. The original data sets are filtered for difficulty, and a new set of challenging data sets from ChEMBL is added. Data sets were also generated for a second use case: starting from a small set of related actives instead of diverse actives. The final fused model consistently outperforms the other approaches across the broad variety of targets studied, indicating that heterogeneous classifier fusion is a very promising approach for ligand-based VS. The new data sets together with the adapted source code for ML methods are provided in the Supporting Information .

Modeling tracer transport in randomly heterogeneous porous media by nonlocal moment equations: Anomalous transport

NASA Astrophysics Data System (ADS)

Morales-Casique, E.; Lezama-Campos, J. L.; Guadagnini, A.; Neuman, S. P.

2013-05-01

Modeling tracer transport in geologic porous media suffers from the corrupt characterization of the spatial distribution of hydrogeologic properties of the system and the incomplete knowledge of processes governing transport at multiple scales. Representations of transport dynamics based on a Fickian model of the kind considered in the advection-dispersion equation (ADE) fail to capture (a) the temporal variation associated with the rate of spreading of a tracer, and (b) the distribution of early and late arrival times which are often observed in field and/or laboratory scenarios and are considered as the signature of anomalous transport. Elsewhere we have presented exact stochastic moment equations to model tracer transport in randomly heterogeneous aquifers. We have also developed a closure scheme which enables one to provide numerical solutions of such moment equations at different orders of approximations. The resulting (ensemble) average and variance of concentration fields were found to display a good agreement against Monte Carlo - based simulation results for mildly heterogeneous (or well-conditioned strongly heterogeneous) media. Here we explore the ability of the moment equations approach to describe the distribution of early arrival times and late time tailing effects which can be observed in Monte-Carlo based breakthrough curves (BTCs) of the (ensemble) mean concentration. We show that BTCs of mean resident concentration calculated at a fixed space location through higher-order approximations of moment equations display long tailing features of the kind which is typically associated with anomalous transport behavior and are not represented by an ADE model with constant dispersive parameter, such as the zero-order approximation.

[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.

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.

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 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.

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.

Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case.

PubMed

Martínez-Costa, Catalina; Cornet, Ronald; Karlsson, Daniel; Schulz, Stefan; Kalra, Dipak

2015-05-01

To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

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.

Maximum entropy production allows a simple representation of heterogeneity in semiarid ecosystems.

PubMed

Schymanski, Stanislaus J; Kleidon, Axel; Stieglitz, Marc; Narula, Jatin

2010-05-12

Feedbacks between water use, biomass and infiltration capacity in semiarid ecosystems have been shown to lead to the spontaneous formation of vegetation patterns in a simple model. The formation of patterns permits the maintenance of larger overall biomass at low rainfall rates compared with homogeneous vegetation. This results in a bias of models run at larger scales neglecting subgrid-scale variability. In the present study, we investigate the question whether subgrid-scale heterogeneity can be parameterized as the outcome of optimal partitioning between bare soil and vegetated area. We find that a two-box model reproduces the time-averaged biomass of the patterns emerging in a 100 x 100 grid model if the vegetated fraction is optimized for maximum entropy production (MEP). This suggests that the proposed optimality-based representation of subgrid-scale heterogeneity may be generally applicable to different systems and at different scales. The implications for our understanding of self-organized behaviour and its modelling are discussed.

Data-driven heterogeneity in mathematical learning disabilities based on the triple code model.

PubMed

Peake, Christian; Jiménez, Juan E; Rodríguez, Cristina

2017-12-01

Many classifications of heterogeneity in mathematical learning disabilities (MLD) have been proposed over the past four decades, however no empirical research has been conducted until recently, and none of the classifications are derived from Triple Code Model (TCM) postulates. The TCM proposes MLD as a heterogeneous disorder, with two distinguishable profiles: a representational subtype and a verbal subtype. A sample of elementary school 3rd to 6th graders was divided into two age cohorts (3rd - 4th grades, and 5th - 6th grades). Using data-driven strategies, based on the cognitive classification variables predicted by the TCM, our sample of children with MLD clustered as expected: a group with representational deficits and a group with number-fact retrieval deficits. In the younger group, a spatial subtype also emerged, while in both cohorts a non-specific cluster was produced whose profile could not be explained by this theoretical approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

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…

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

PubMed

Dinov, Ivo D

2016-01-01

Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'.

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.

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)

Multi-Disciplinary Knowledge Synthesis for Human Health Assessment on Earth and in Space

NASA Astrophysics Data System (ADS)

Christakos, G.

We discuss methodological developments in multi-disciplinary knowledge synthesis (KS) of human health assessment. A theoretical KS framework can provide the rational means for the assimilation of various information bases (general, site-specific etc.) that are relevant to the life system of interest. KS-based techniques produce a realistic representation of the system, provide a rigorous assessment of the uncertainty sources, and generate informative health state predictions across space-time. The underlying epistemic cognition methodology is based on teleologic criteria and stochastic logic principles. The mathematics of KS involves a powerful and versatile spatiotemporal random field model that accounts rigorously for the uncertainty features of the life system and imposes no restriction on the shape of the probability distributions or the form of the predictors. KS theory is instrumental in understanding natural heterogeneities, assessing crucial human exposure correlations and laws of physical change, and explaining toxicokinetic mechanisms and dependencies in a spatiotemporal life system domain. It is hoped that a better understanding of KS fundamentals would generate multi-disciplinary models that are useful for the maintenance of human health on Earth and in Space.

Evaluation of research in biomedical ontologies

PubMed Central

Dumontier, Michel; Gkoutos, Georgios V.

2013-01-01

Ontologies are now pervasive in biomedicine, where they serve as a means to standardize terminology, to enable access to domain knowledge, to verify data consistency and to facilitate integrative analyses over heterogeneous biomedical data. For this purpose, research on biomedical ontologies applies theories and methods from diverse disciplines such as information management, knowledge representation, cognitive science, linguistics and philosophy. Depending on the desired applications in which ontologies are being applied, the evaluation of research in biomedical ontologies must follow different strategies. Here, we provide a classification of research problems in which ontologies are being applied, focusing on the use of ontologies in basic and translational research, and we demonstrate how research results in biomedical ontologies can be evaluated. The evaluation strategies depend on the desired application and measure the success of using an ontology for a particular biomedical problem. For many applications, the success can be quantified, thereby facilitating the objective evaluation and comparison of research in biomedical ontology. The objective, quantifiable comparison of research results based on scientific applications opens up the possibility for systematically improving the utility of ontologies in biomedical research. PMID:22962340

An integrated system for interactive continuous learning of categorical knowledge

NASA Astrophysics Data System (ADS)

Skočaj, Danijel; Vrečko, Alen; Mahnič, Marko; Janíček, Miroslav; Kruijff, Geert-Jan M.; Hanheide, Marc; Hawes, Nick; Wyatt, Jeremy L.; Keller, Thomas; Zhou, Kai; Zillich, Michael; Kristan, Matej

2016-09-01

This article presents an integrated robot system capable of interactive learning in dialogue with a human. Such a system needs to have several competencies and must be able to process different types of representations. In this article, we describe a collection of mechanisms that enable integration of heterogeneous competencies in a principled way. Central to our design is the creation of beliefs from visual and linguistic information, and the use of these beliefs for planning system behaviour to satisfy internal drives. The system is able to detect gaps in its knowledge and to plan and execute actions that provide information needed to fill these gaps. We propose a hierarchy of mechanisms which are capable of engaging in different kinds of learning interactions, e.g. those initiated by a tutor or by the system itself. We present the theory these mechanisms are build upon and an instantiation of this theory in the form of an integrated robot system. We demonstrate the operation of the system in the case of learning conceptual models of objects and their visual properties.

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.

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

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...

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.

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.

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.

Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

PubMed

Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

2014-01-01

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.

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.

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.

Signifying Zika: heterogeneity in the representations of the virus by history of infection.

PubMed

Guedes, Gilvan Ramalho; Coutinho, Raquel Zanatta; Marteleto, Leticia; Pereira, Wesley Henrique Silva; Duarte, Denise

2018-06-07

Despite having been broadly advertised by the mass media, many negative consequences of the Zika virus have been less significant than originally predicted. It is likely that after a few months from the epidemic's onset, personal experience with the virus has altered the person's way to deal with the disease. This study explores the relation between exposure to Zika virus and the social representation of the epidemic. More specifically, one analyzes if increased exposure to the risk of Zika infection changes the characteristics of the web of meanings surrounding the epidemic. Between August and November of 2016, 150 interviews were conducted in the municipality of Governador Valadares, Minas Gerais State, Brazil. Based on the Free Words Association Technique, data on evocations related to the Zika virus were modeled by social network analysis, allowing the characterization of the web of meanings by level of exposure to the risk of Zika infection. The analysis performed here suggests that those never infected by any disease transmitted by the Aedes aegypti mosquito have a lesser representation, incorporating information from the media through lay thinking. In contrast to those with low levels of exposure, the social representation of people infected by Zika is associated with meanings related to the most common symptoms, such as pain, rash, and itching. Personal experience seems to shape the social representation of the disease, increasing the focus on its proximate consequences. Public campaigns designed to foster protective behavior should take into consideration the heterogeneity in the representations of this epidemic to improve adherence to preventive behavior.

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.

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.

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...

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.

Distant failure prediction for early stage NSCLC by analyzing PET with sparse representation

NASA Astrophysics Data System (ADS)

Hao, Hongxia; Zhou, Zhiguo; Wang, Jing

2017-03-01

Positron emission tomography (PET) imaging has been widely explored for treatment outcome prediction. Radiomicsdriven methods provide a new insight to quantitatively explore underlying information from PET images. However, it is still a challenging problem to automatically extract clinically meaningful features for prognosis. In this work, we develop a PET-guided distant failure predictive model for early stage non-small cell lung cancer (NSCLC) patients after stereotactic ablative radiotherapy (SABR) by using sparse representation. The proposed method does not need precalculated features and can learn intrinsically distinctive features contributing to classification of patients with distant failure. The proposed framework includes two main parts: 1) intra-tumor heterogeneity description; and 2) dictionary pair learning based sparse representation. Tumor heterogeneity is initially captured through anisotropic kernel and represented as a set of concatenated vectors, which forms the sample gallery. Then, given a test tumor image, its identity (i.e., distant failure or not) is classified by applying the dictionary pair learning based sparse representation. We evaluate the proposed approach on 48 NSCLC patients treated by SABR at our institute. Experimental results show that the proposed approach can achieve an area under the characteristic curve (AUC) of 0.70 with a sensitivity of 69.87% and a specificity of 69.51% using a five-fold cross validation.

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…

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.

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…

Heterogeneity of PTEN and ERG expression in prostate cancer on core needle biopsies: implications for cancer risk stratification and biomarker sampling.

PubMed

Shah, Rajal B; Bentley, James; Jeffery, Zach; DeMarzo, Angelo M

2015-05-01

ERG and PTEN biomarkers are increasingly being analyzed on prostate core biopsies (NBXs); ERG as a marker of clonality and number of separately arising tumor foci and PTEN for prognostic information. Yet, in patients with multiple biopsy cores positive for cancer (PCa), there is no standardized approach for interrogation of these biomarkers in terms of the number of positive cores to evaluate. A total of 194 NBX cases containing more than one positive core with cancer were evaluated for ERG overexpression and PTEN loss by immunostaining (immunohistochemistry) of all positive cores. ERG overexpression or PTEN loss in at least one cancer core was present in 111 (57%) and 69 (36%) cases respectively. ERG overexpression was significantly associated with PTEN loss (P < .0001), and PTEN loss was associated with a high Gleason score (P < .0001). Inter- and intra-tumor core staining heterogeneity for ERG overexpression occurred in 42% and 5% cases and for PTEN loss both intra- and inter-tumor core heterogeneity was 68%. PTEN staining was highly discordant between PCa sites regardless of laterality. When the Gleason score was non-uniform across PCa sites, the combination of cores showing the highest Gleason score and largest tumor volume provided the best representation of ERG overexpression (92%) and PTEN loss (98%). When grades were uniform across cancer sites, the highest tumor volume core was generally representative of ERG overexpression (90%) but was less representative for PTEN loss (76%). Our results suggest that knowledge of this heterogeneity is critical for developing optimal yet cost-effective strategies to identify these underlying molecular abnormalities. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Chemical and physical characterization of fertile soil-derived ice residuals from the Fifth International Ice Nucleation workshop in November 2014 (FIN-1)

NASA Astrophysics Data System (ADS)

Hiranuma, Naruki; Möhler, Ottmar; Kulkarni, Gourihar; Laskin, Alexander; Zelenyuk, Alla

2017-04-01

The climate impact of ice-nucleating particles (INPs) derived from fertile soils on global scale has been recently accented by their diversity and efficient freezing ability. However, their representation in atmospheric models is limited in part due to our incomplete knowledge of fertile soil composition, abundance and associated sensitivity to heterogeneous ice nucleation. To fill given knowledge gap, we have investigated a unique/rich set of ice crystal residual samples derived from a variety of fertile soil samples obtained through our participation in the Fifth International Ice Nucleation workshop (FIN-1). FIN-1 was held at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) facility at Karlsruhe Institute of Technology (KIT), which is the world's foremost facility for studying ice clouds in a controlled setting, in November 2014 to comprehensively study the heterogeneous ice formation in the atmosphere with collaboration among 10 international groups that were funded through European consortium, NSF and USDOE agencies. Here, we will present the nanoscale surface morphology and elemental/molecular composition of ice crystal residuals as well as that of total aerosol samples from the FIN-1 activity to identify and classify any specific mineral and organic inclusions that may have promoted nucleation of ice. Comparing total aerosols to residuals will shed light on the composition and abundance of certain particle types in INPs. Acknowledgements: The valuable contributions of the INUIT (Ice Nuclei Research Unit) collaborators, the FIN organizers, their institutions and the FIN-1 Workshop science team are gratefully acknowledged.

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.

Facilitating insights with a user adaptable dashboard, illustrated by airport connectivity data

NASA Astrophysics Data System (ADS)

Dobraja, Ieva; Kraak, Menno-Jan; Engelhardt, Yuri

2018-05-01

Since the movement data exist, there have been approaches to collect and analyze them to get insights. This kind of data is often heterogeneous, multiscale and multi-temporal. Those interested in spatio-temporal patterns of movement data do not gain insights from textual descriptions. Therefore, visualization is required. As spatio-temporal movement data can be complex because size and characteristics, it is even challenging to create an overview of it. Plotting all the data on the screen will not be the solution as it likely will result into cluttered images where no data exploration is possible. To ensure that users will receive the information they are interested in, it is important to provide a graphical data representation environment where exploration to gain insights are possible not only in the overall level but at sub-levels as well. A dashboard would be a solution the representation of heterogeneous spatio- temporal data. It provides an overview and helps to unravel the complexity of data by splitting data in multiple data representation views. The adaptability of dashboard will help to reveal the information which cannot be seen in the overview.

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

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

PubMed

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

2009-02-05

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

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.

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.

Process Consistency in Models: the Importance of System Signatures, Expert Knowledge and Process Complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, Markus; Fovet, Ophelie; Ruiz, Laurent; Gascuel-Odoux, Chantal; Savenije, Hubert

2014-05-01

Hydrological models are frequently characterized by what is often considered to be adequate calibration performances. In many cases, however, these models experience a substantial uncertainty and performance decrease in validation periods, thus resulting in poor predictive power. Besides the likely presence of data errors, this observation can point towards wrong or insufficient representations of the underlying processes and their heterogeneity. In other words, right results are generated for the wrong reasons. Thus ways are sought to increase model consistency and to thereby satisfy the contrasting priorities of the need a) to increase model complexity and b) to limit model equifinality. In this study a stepwise model development approach is chosen to test the value of an exhaustive and systematic combined use of hydrological signatures, expert knowledge and readily available, yet anecdotal and rarely exploited, hydrological information for increasing model consistency towards generating the right answer for the right reasons. A simple 3-box, 7 parameter, conceptual HBV-type model, constrained by 4 calibration objective functions was able to adequately reproduce the hydrograph with comparatively high values for the 4 objective functions in the 5-year calibration period. However, closer inspection of the results showed a dramatic decrease of model performance in the 5-year validation period. In addition, assessing the model's skill to reproduce a range of 20 hydrological signatures including, amongst others, the flow duration curve, the autocorrelation function and the rising limb density, showed that it could not adequately reproduce the vast majority of these signatures, indicating a lack of model consistency. Subsequently model complexity was increased in a stepwise way to allow for more process heterogeneity. To limit model equifinality, increase in complexity was counter-balanced by a stepwise application of "realism constraints", inferred from expert knowledge (e.g. unsaturated storage capacity of hillslopes should exceed the one of wetlands) and anecdotal hydrological information (e.g. long-term estimates of actual evaporation obtained from the Budyko framework and long-term estimates of baseflow contribution) to ensure that the model is well behaved with respect to the modeller's perception of the system. A total of 11 model set-ups with increased complexity and an increased number of realism constraints was tested. It could be shown that in spite of largely unchanged calibration performance, compared to the simplest set-up, the most complex model set-up (12 parameters, 8 constraints) exhibited significantly increased performance in the validation period while uncertainty did not increase. In addition, the most complex model was characterized by a substantially increased skill to reproduce all 20 signatures, indicating a more suitable representation of the system. The results suggest that a model, "well" constrained by 4 calibration objective functions may still be an inadequate representation of the system and that increasing model complexity, if counter-balanced by realism constraints, can indeed increase predictive performance of a model and its skill to reproduce a range of hydrological signatures, but that it does not necessarily result in increased uncertainty. The results also strongly illustrate the need to move away from automated model calibration towards a more general expert-knowledge driven strategy of constraining models if a certain level of model consistency is to be achieved.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

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

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…

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.

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.

A FFT-based formulation for discrete dislocation dynamics in heterogeneous media

NASA Astrophysics Data System (ADS)

Bertin, N.; Capolungo, L.

2018-02-01

In this paper, an extension of the DDD-FFT approach presented in [1] is developed for heterogeneous elasticity. For such a purpose, an iterative spectral formulation in which convolutions are calculated in the Fourier space is developed to solve for the mechanical state associated with the discrete eigenstrain-based microstructural representation. With this, the heterogeneous DDD-FFT approach is capable of treating anisotropic and heterogeneous elasticity in a computationally efficient manner. In addition, a GPU implementation is presented to allow for further acceleration. As a first example, the approach is used to investigate the interaction between dislocations and second-phase particles, thereby demonstrating its ability to inherently incorporate image forces arising from elastic inhomogeneities.

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…

Preface of the "Symposium on Mathematical Models and Methods to investigate Heterogeneity in Cell and Cell Population Biology"

NASA Astrophysics Data System (ADS)

Clairambault, Jean

2016-06-01

This session investigates hot topics related to mathematical representations of cell and cell population dynamics in biology and medicine, in particular, but not only, with applications to cancer. Methods in mathematical modelling and analysis, and in statistical inference using single-cell and cell population data, should contribute to focus this session on heterogeneity in cell populations. Among other methods are proposed: a) Intracellular protein dynamics and gene regulatory networks using ordinary/partial/delay differential equations (ODEs, PDEs, DDEs); b) Representation of cell population dynamics using agent-based models (ABMs) and/or PDEs; c) Hybrid models and multiscale models to integrate single-cell dynamics into cell population behaviour; d) Structured cell population dynamics and asymptotic evolution w.r.t. relevant traits; e) Heterogeneity in cancer cell populations: origin, evolution, phylogeny and methods of reconstruction; f) Drug resistance as an evolutionary phenotype: predicting and overcoming it in therapeutics; g) Theoretical therapeutic optimisation of combined drug treatments in cancer cell populations and in populations of other organisms, such as bacteria.

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.

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

An Ontology-based Architecture for Integration of Clinical Trials Management Applications

PubMed Central

Shankar, Ravi D.; Martins, Susana B.; O’Connor, Martin; Parrish, David B.; Das, Amar K.

2007-01-01

Management of complex clinical trials involves coordinated-use of a myriad of software applications by trial personnel. The applications typically use distinct knowledge representations and generate enormous amount of information during the course of a trial. It becomes vital that the applications exchange trial semantics in order for efficient management of the trials and subsequent analysis of clinical trial data. Existing model-based frameworks do not address the requirements of semantic integration of heterogeneous applications. We have built an ontology-based architecture to support interoperation of clinical trial software applications. Central to our approach is a suite of clinical trial ontologies, which we call Epoch, that define the vocabulary and semantics necessary to represent information on clinical trials. We are continuing to demonstrate and validate our approach with different clinical trials management applications and with growing number of clinical trials. PMID:18693919

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.

[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.

Modeling reactive transport processes in fractured rock using the time domain random walk approach within a dual-porosity framework

NASA Astrophysics Data System (ADS)

Roubinet, D.; Russian, A.; Dentz, M.; Gouze, P.

2017-12-01

Characterizing and modeling hydrodynamic reactive transport in fractured rock are critical challenges for various research fields and applications including environmental remediation, geological storage, and energy production. To this end, we consider a recently developed time domain random walk (TDRW) approach, which is adapted to reproduce anomalous transport behaviors and capture heterogeneous structural and physical properties. This method is also very well suited to optimize numerical simulations by memory-shared massive parallelization and provide numerical results at various scales. So far, the TDRW approach has been applied for modeling advective-diffusive transport with mass transfer between mobile and immobile regions and simple (theoretical) reactions in heterogeneous porous media represented as single continuum domains. We extend this approach to dual-continuum representations considering a highly permeable fracture network embedded into a poorly permeable rock matrix with heterogeneous geochemical reactions occurring in both geological structures. The resulting numerical model enables us to extend the range of the modeled heterogeneity scales with an accurate representation of solute transport processes and no assumption on the Fickianity of these processes. The proposed model is compared to existing particle-based methods that are usually used to model reactive transport in fractured rocks assuming a homogeneous surrounding matrix, and is used to evaluate the impact of the matrix heterogeneity on the apparent reaction rates for different 2D and 3D simple-to-complex fracture network configurations.

Developing integrated crop knowledge networks to advance candidate gene discovery.

PubMed

Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher

2016-12-01

The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

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

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.

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.

Frontal lobe damage impairs process and content in semantic memory: evidence from category-specific effects in progressive non-fluent aphasia.

PubMed

Reilly, Jamie; Rodriguez, Amy D; Peelle, Jonathan E; Grossman, Murray

2011-06-01

Portions of left inferior frontal cortex have been linked to semantic memory both in terms of the content of conceptual representation (e.g., motor aspects in an embodied semantics framework) and the cognitive processes used to access these representations (e.g., response selection). Progressive non-fluent aphasia (PNFA) is a neurodegenerative condition characterized by progressive atrophy of left inferior frontal cortex. PNFA can, therefore, provide a lesion model for examining the impact of frontal lobe damage on semantic processing and content. In the current study we examined picture naming in a cohort of PNFA patients across a variety of semantic categories. An embodied approach to semantic memory holds that sensorimotor features such as self-initiated action may assume differential importance for the representation of manufactured artifacts (e.g., naming hand tools). Embodiment theories might therefore predict that patients with frontal damage would be differentially impaired on manufactured artifacts relative to natural kinds, and this prediction was borne out. We also examined patterns of naming errors across a wide range of semantic categories and found that naming error distributions were heterogeneous. Although PNFA patients performed worse overall on naming manufactured artifacts, there was no reliable relationship between anomia and manipulability across semantic categories. These results add to a growing body of research arguing against a purely sensorimotor account of semantic memory, suggesting instead a more nuanced balance of process and content in how the brain represents conceptual knowledge. Copyright © 2010 Elsevier Srl. All rights reserved.

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…

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.

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

PubMed Central

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

1999-01-01

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

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…

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…

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…

Deep graphs—A general framework to represent and analyze heterogeneous complex systems across scales

NASA Astrophysics Data System (ADS)

Traxl, Dominik; Boers, Niklas; Kurths, Jürgen

2016-06-01

Network theory has proven to be a powerful tool in describing and analyzing systems by modelling the relations between their constituent objects. Particularly in recent years, a great progress has been made by augmenting "traditional" network theory in order to account for the multiplex nature of many networks, multiple types of connections between objects, the time-evolution of networks, networks of networks and other intricacies. However, existing network representations still lack crucial features in order to serve as a general data analysis tool. These include, most importantly, an explicit association of information with possibly heterogeneous types of objects and relations, and a conclusive representation of the properties of groups of nodes as well as the interactions between such groups on different scales. In this paper, we introduce a collection of definitions resulting in a framework that, on the one hand, entails and unifies existing network representations (e.g., network of networks and multilayer networks), and on the other hand, generalizes and extends them by incorporating the above features. To implement these features, we first specify the nodes and edges of a finite graph as sets of properties (which are permitted to be arbitrary mathematical objects). Second, the mathematical concept of partition lattices is transferred to the network theory in order to demonstrate how partitioning the node and edge set of a graph into supernodes and superedges allows us to aggregate, compute, and allocate information on and between arbitrary groups of nodes. The derived partition lattice of a graph, which we denote by deep graph, constitutes a concise, yet comprehensive representation that enables the expression and analysis of heterogeneous properties, relations, and interactions on all scales of a complex system in a self-contained manner. Furthermore, to be able to utilize existing network-based methods and models, we derive different representations of multilayer networks from our framework and demonstrate the advantages of our representation. On the basis of the formal framework described here, we provide a rich, fully scalable (and self-explanatory) software package that integrates into the PyData ecosystem and offers interfaces to popular network packages, making it a powerful, general-purpose data analysis toolkit. We exemplify an application of deep graphs using a real world dataset, comprising 16 years of satellite-derived global precipitation measurements. We deduce a deep graph representation of these measurements in order to track and investigate local formations of spatio-temporal clusters of extreme precipitation events.

Deep graphs-A general framework to represent and analyze heterogeneous complex systems across scales.

PubMed

Traxl, Dominik; Boers, Niklas; Kurths, Jürgen

2016-06-01

Network theory has proven to be a powerful tool in describing and analyzing systems by modelling the relations between their constituent objects. Particularly in recent years, a great progress has been made by augmenting "traditional" network theory in order to account for the multiplex nature of many networks, multiple types of connections between objects, the time-evolution of networks, networks of networks and other intricacies. However, existing network representations still lack crucial features in order to serve as a general data analysis tool. These include, most importantly, an explicit association of information with possibly heterogeneous types of objects and relations, and a conclusive representation of the properties of groups of nodes as well as the interactions between such groups on different scales. In this paper, we introduce a collection of definitions resulting in a framework that, on the one hand, entails and unifies existing network representations (e.g., network of networks and multilayer networks), and on the other hand, generalizes and extends them by incorporating the above features. To implement these features, we first specify the nodes and edges of a finite graph as sets of properties (which are permitted to be arbitrary mathematical objects). Second, the mathematical concept of partition lattices is transferred to the network theory in order to demonstrate how partitioning the node and edge set of a graph into supernodes and superedges allows us to aggregate, compute, and allocate information on and between arbitrary groups of nodes. The derived partition lattice of a graph, which we denote by deep graph, constitutes a concise, yet comprehensive representation that enables the expression and analysis of heterogeneous properties, relations, and interactions on all scales of a complex system in a self-contained manner. Furthermore, to be able to utilize existing network-based methods and models, we derive different representations of multilayer networks from our framework and demonstrate the advantages of our representation. On the basis of the formal framework described here, we provide a rich, fully scalable (and self-explanatory) software package that integrates into the PyData ecosystem and offers interfaces to popular network packages, making it a powerful, general-purpose data analysis toolkit. We exemplify an application of deep graphs using a real world dataset, comprising 16 years of satellite-derived global precipitation measurements. We deduce a deep graph representation of these measurements in order to track and investigate local formations of spatio-temporal clusters of extreme precipitation events.

Addressing the Heterogeneity of Subject Indexing in the ADS Databases

NASA Astrophysics Data System (ADS)

Dubin, David S.

A drawback of the current document representation scheme in the ADS abstract service is its heterogeneous subject indexing. Several related but inconsistent indexing languages are represented in ADS. A method of reconciling some indexing inconsistencies is described. Using lexical similarity alone, one out of six ADS descriptors can be automatically mapped to some other descriptor. Analysis of postings data can direct administrators to those mergings it is most important to check for errors.

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...

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.

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

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

On the validity of effective formulations for transport through heterogeneous porous media

NASA Astrophysics Data System (ADS)

de Dreuzy, Jean-Raynald; Carrera, Jesus

2016-04-01

Geological heterogeneity enhances spreading of solutes and causes transport to be anomalous (i.e., non-Fickian), with much less mixing than suggested by dispersion. This implies that modeling transport requires adopting either stochastic approaches that model heterogeneity explicitly or effective transport formulations that acknowledge the effects of heterogeneity. A number of such formulations have been developed and tested as upscaled representations of enhanced spreading. However, their ability to represent mixing has not been formally tested, which is required for proper reproduction of chemical reactions and which motivates our work. We propose that, for an effective transport formulation to be considered a valid representation of transport through heterogeneous porous media (HPM), it should honor mean advection, mixing and spreading. It should also be flexible enough to be applicable to real problems. We test the capacity of the multi-rate mass transfer (MRMT) model to reproduce mixing observed in HPM, as represented by the classical multi-Gaussian log-permeability field with a Gaussian correlation pattern. Non-dispersive mixing comes from heterogeneity structures in the concentration fields that are not captured by macrodispersion. These fine structures limit mixing initially, but eventually enhance it. Numerical results show that, relative to HPM, MRMT models display a much stronger memory of initial conditions on mixing than on dispersion because of the sensitivity of the mixing state to the actual values of concentration. Because MRMT does not restitute the local concentration structures, it induces smaller non-dispersive mixing than HPM. However long-lived trapping in the immobile zones may sustain the deviation from dispersive mixing over much longer times. While spreading can be well captured by MRMT models, in general non-dispersive mixing cannot.

On the validity of effective formulations for transport through heterogeneous porous media

NASA Astrophysics Data System (ADS)

de Dreuzy, J.-R.; Carrera, J.

2015-11-01

Geological heterogeneity enhances spreading of solutes, and causes transport to be anomalous (i.e., non-Fickian), with much less mixing than suggested by dispersion. This implies that modeling transport requires adopting either stochastic approaches that model heterogeneity explicitly or effective transport formulations that acknowledge the effects of heterogeneity. A number of such formulations have been developed and tested as upscaled representations of enhanced spreading. However, their ability to represent mixing has not been formally tested, which is required for proper reproduction of chemical reactions and which motivates our work. We propose that, for an effective transport formulation to be considered a valid representation of transport through Heterogeneous Porous Media (HPM), it should honor mean advection, mixing and spreading. It should also be flexible enough to be applicable to real problems. We test the capacity of the Multi-Rate Mass Transfer (MRMT) to reproduce mixing observed in HPM, as represented by the classical multi-Gaussian log-permeability field with a Gaussian correlation pattern. Non-dispersive mixing comes from heterogeneity structures in the concentration fields that are not captured by macrodispersion. These fine structures limit mixing initially, but eventually enhance it. Numerical results show that, relative to HPM, MRMT models display a much stronger memory of initial conditions on mixing than on dispersion because of the sensitivity of the mixing state to the actual values of concentration. Because MRMT does not restitute the local concentration structures, it induces smaller non-dispersive mixing than HPM. However long-lived trapping in the immobile zones may sustain the deviation from dispersive mixing over much longer times. While spreading can be well captured by MRMT models, non-dispersive mixing cannot.

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,…

A Multi-factorial Model for Examining Racial and Ethnic Disparities in Acute Asthma Visits by Children

PubMed Central

Feldman, Jonathan M.; Serebrisky, Denise; Spray, Amanda

2012-01-01

Background Causes of children’s asthma health disparities are complex. Parents’ asthma illness representations may play a role. Purpose The study aims to test a theoretically based, multi-factorial model for ethnic disparities in children’s acute asthma visits through parental illness representations. Methods Structural equation modeling investigated the association of parental asthma illness representations, sociodemographic characteristics, health care provider factors, and social–environmental context with children’s acute asthma visits among 309 White, Puerto Rican, and African American families was conducted. Results Forty-five percent of the variance in illness representations and 30% of the variance in acute visits were accounted for. Statistically significant differences in illness representations were observed by ethnic group. Approximately 30% of the variance in illness representations was explained for whites, 23% for African Americans, and 26% for Puerto Ricans. The model accounted for >30% of the variance in acute visits for African Americans and Puerto Ricans but only 19% for the whites. Conclusion The model provides preliminary support that ethnic heterogeneity in asthma illness representations affects children’s health outcomes. PMID:22160799

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

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

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.

Mesoscale Modeling of Dynamic Failure of Ceramic Polycrystals

DTIC Science & Technology

2011-08-01

Wu, R. Feng, 2005. Micromechanical investigation of heterogeneous microplasticity in ceramics deformed under high confining stresses. Mechanics of...Boyce, 2010. The effect of microstructural representation on simulations of microplastic ratcheting. International Journal of Plasticity 26: 617

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.

Thalamic input to auditory cortex is locally heterogeneous but globally tonotopic

PubMed Central

Vasquez-Lopez, Sebastian A; Weissenberger, Yves; Lohse, Michael; Keating, Peter; King, Andrew J

2017-01-01

Topographic representation of the receptor surface is a fundamental feature of sensory cortical organization. This is imparted by the thalamus, which relays information from the periphery to the cortex. To better understand the rules governing thalamocortical connectivity and the origin of cortical maps, we used in vivo two-photon calcium imaging to characterize the properties of thalamic axons innervating different layers of mouse auditory cortex. Although tonotopically organized at a global level, we found that the frequency selectivity of individual thalamocortical axons is surprisingly heterogeneous, even in layers 3b/4 of the primary cortical areas, where the thalamic input is dominated by the lemniscal projection. We also show that thalamocortical input to layer 1 includes collaterals from axons innervating layers 3b/4 and is largely in register with the main input targeting those layers. Such locally varied thalamocortical projections may be useful in enabling rapid contextual modulation of cortical frequency representations. PMID:28891466

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

Jones, J.P.; Bangs, A.L.; Butler, P.L.

Hetero Helix is a programming environment which simulates shared memory on a heterogeneous network of distributed-memory computers. The machines in the network may vary with respect to their native operating systems and internal representation of numbers. Hetero Helix presents a simple programming model to developers, and also considers the needs of designers, system integrators, and maintainers. The key software technology underlying Hetero Helix is the use of a compiler'' which analyzes the data structures in shared memory and automatically generates code which translates data representations from the format native to each machine into a common format, and vice versa. Themore » design of Hetero Helix was motivated in particular by the requirements of robotics applications. Hetero Helix has been used successfully in an integration effort involving 27 CPUs in a heterogeneous network and a body of software totaling roughly 100,00 lines of code. 25 refs., 6 figs.« less

Naming a Lego world. The role of language in the acquisition of abstract concepts.

PubMed

Granito, Carmen; Scorolli, Claudia; Borghi, Anna Maria

2015-01-01

While embodied approaches of cognition have proved to be successful in explaining concrete concepts and words, they have more difficulties in accounting for abstract concepts and words, and several proposals have been put forward. This work aims to test the Words As Tools proposal, according to which both abstract and concrete concepts are grounded in perception, action and emotional systems, but linguistic information is more important for abstract than for concrete concept representation, due to the different ways they are acquired: while for the acquisition of the latter linguistic information might play a role, for the acquisition of the former it is instead crucial. We investigated the acquisition of concrete and abstract concepts and words, and verified its impact on conceptual representation. In Experiment 1, participants explored and categorized novel concrete and abstract entities, and were taught a novel label for each category. Later they performed a categorical recognition task and an image-word matching task to verify a) whether and how the introduction of language changed the previously formed categories, b) whether language had a major weight for abstract than for concrete words representation, and c) whether this difference had consequences on bodily responses. The results confirm that, even though both concrete and abstract concepts are grounded, language facilitates the acquisition of the latter and plays a major role in their representation, resulting in faster responses with the mouth, typically associated with language production. Experiment 2 was a rating test aiming to verify whether the findings of Experiment 1 were simply due to heterogeneity, i.e. to the fact that the members of abstract categories were more heterogeneous than those of concrete categories. The results confirmed the effectiveness of our operationalization, showing that abstract concepts are more associated with the mouth and concrete ones with the hand, independently from heterogeneity.

Naming a Lego World. The Role of Language in the Acquisition of Abstract Concepts

PubMed Central

Granito, Carmen; Scorolli, Claudia; Borghi, Anna Maria

2015-01-01

While embodied approaches of cognition have proved to be successful in explaining concrete concepts and words, they have more difficulties in accounting for abstract concepts and words, and several proposals have been put forward. This work aims to test the Words As Tools proposal, according to which both abstract and concrete concepts are grounded in perception, action and emotional systems, but linguistic information is more important for abstract than for concrete concept representation, due to the different ways they are acquired: while for the acquisition of the latter linguistic information might play a role, for the acquisition of the former it is instead crucial. We investigated the acquisition of concrete and abstract concepts and words, and verified its impact on conceptual representation. In Experiment 1, participants explored and categorized novel concrete and abstract entities, and were taught a novel label for each category. Later they performed a categorical recognition task and an image-word matching task to verify a) whether and how the introduction of language changed the previously formed categories, b) whether language had a major weight for abstract than for concrete words representation, and c) whether this difference had consequences on bodily responses. The results confirm that, even though both concrete and abstract concepts are grounded, language facilitates the acquisition of the latter and plays a major role in their representation, resulting in faster responses with the mouth, typically associated with language production. Experiment 2 was a rating test aiming to verify whether the findings of Experiment 1 were simply due to heterogeneity, i.e. to the fact that the members of abstract categories were more heterogeneous than those of concrete categories. The results confirmed the effectiveness of our operationalization, showing that abstract concepts are more associated with the mouth and concrete ones with the hand, independently from heterogeneity. PMID:25629816

[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…

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…

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.

Places, attitudes and moments during the epidemics: representations of yellow fever and cholera in the city of Buenos Aires, 1867-1871.

PubMed

Fiquepron, Maximiliano Ricardo

2018-01-01

The goal of this article is to analyze the different representations of health and disease associated with the epidemics of yellow fever and cholera that took place from 1867-1871 in the city of Buenos Aires. It argues that there was a very broad and heterogeneous repertoire of representations that resulted in a variety of attitudes on the part of individuals dealing with the crisis, and led to the transformation of space and social time. In order to handle this traumatic experience, people chose very different methods for maintaining social contact, which was also a way of maintaining their health.

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.

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;…

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

Evolving a Simulation Model Product Line Software Architecture from Heterogeneous Model Representations

DTIC Science & Technology

2003-09-01

resolution M&S concept for integrating heterogeneous M&S into the hierarchy has existed since the early 1980s [DH92a, DH92b]. 25...groups [PAD78]. The need for credible M&S grew in the Nation’s private and public sectors. By 1980 , information from computer-based simulations...formal) identified in the [GMS+96 and RPG00]. We noted that systemic issues identi- fied in by reports, studies, and assessments the early 1980s

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.

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...

29 CFR 1912.9 - Representation on section 7(b) committees.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 7 2012-07-01 2012-07-01 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...

Comparing Tactile Maps and Haptic Digital Representations of a Maritime Environment

ERIC Educational Resources Information Center

Simonnet, Mathieu; Vieilledent, Steephane; Jacobson, R. Daniel; Tisseau, Jacques

2011-01-01

A map exploration and representation exercise was conducted with participants who were totally blind. Representations of maritime environments were presented either with a tactile map or with a digital haptic virtual map. We assessed the knowledge of spatial configurations using a triangulation technique. The results revealed that both types of…

Lexical and Syntactic Representations in the Brain: An fMRI Investigation with Multi-Voxel Pattern Analyses

ERIC Educational Resources Information Center

Fedorenko, Evelina; Nieto-Castanon, Alfonso; Kanwisher, Nancy

2012-01-01

Work in theoretical linguistics and psycholinguistics suggests that human linguistic knowledge forms a continuum between individual lexical items and abstract syntactic representations, with most linguistic representations falling between the two extremes and taking the form of lexical items stored together with the syntactic/semantic contexts in…

The Role of Training, Individual Differences and Knowledge Representation in Cognitive-Oriented Task Performance.

ERIC Educational Resources Information Center

Koubek, Richard J.

The roles of training, problem representation, and individual differences on performance of both automated (simple) and controlled (complex) process tasks were studied. The following hypotheses were tested: (1) training and cognitive style affect the representation developed; (2) training and cognitive style affect the development and performance…

Visual Representations in Science Education: The Influence of Prior Knowledge and Cognitive Load Theory on Instructional Design Principles

ERIC Educational Resources Information Center

Cook, Michelle Patrick

2006-01-01

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…

The Role of Metarepresentation in the Production and Resolution of Referring Expressions.

PubMed

Horton, William S; Brennan, Susan E

2016-01-01

In this paper we consider the potential role of metarepresentation-the representation of another representation, or as commonly considered within cognitive science, the mental representation of another individual's knowledge and beliefs-in mediating definite reference and common ground in conversation. Using dialogues from a referential communication study in which speakers conversed in succession with two different addressees, we highlight ways in which interlocutors work together to successfully refer to objects, and achieve shared conceptualizations. We briefly review accounts of how such shared conceptualizations could be represented in memory, from simple associations between label and referent, to "triple co-presence" representations that track interlocutors in an episode of referring, to more elaborate metarepresentations that invoke theory of mind, mutual knowledge, or a model of a conversational partner. We consider how some forms of metarepresentation, once created and activated, could account for definite reference in conversation by appealing to ordinary processes in memory. We conclude that any representations that capture information about others' perspectives are likely to be relatively simple and subject to the same kinds of constraints on attention and memory that influence other kinds of cognitive representations.

Does my face FIT?: a face image task reveals structure and distortions of facial feature representation.

PubMed

Fuentes, Christina T; Runa, Catarina; Blanco, Xenxo Alvarez; Orvalho, Verónica; Haggard, Patrick

2013-01-01

Despite extensive research on face perception, few studies have investigated individuals' knowledge about the physical features of their own face. In this study, 50 participants indicated the location of key features of their own face, relative to an anchor point corresponding to the tip of the nose, and the results were compared to the true location of the same individual's features from a standardised photograph. Horizontal and vertical errors were analysed separately. An overall bias to underestimate vertical distances revealed a distorted face representation, with reduced face height. Factor analyses were used to identify separable subconfigurations of facial features with correlated localisation errors. Independent representations of upper and lower facial features emerged from the data pattern. The major source of variation across individuals was in representation of face shape, with a spectrum from tall/thin to short/wide representation. Visual identification of one's own face is excellent, and facial features are routinely used for establishing personal identity. However, our results show that spatial knowledge of one's own face is remarkably poor, suggesting that face representation may not contribute strongly to self-awareness.

Measuring Beliefs in Centimeters: Private Knowledge Biases Preschoolers' and Adults' Representation of Others' Beliefs

ERIC Educational Resources Information Center

Sommerville, Jessica A.; Bernstein, Daniel M.; Meltzoff, Andrew N.

2013-01-01

A novel task, using a continuous spatial layout, was created to investigate the degree to which (in centimeters) 3-year-old children's ("N" = 63), 5-year-old children's ("N" = 60), and adults' ("N" = 60) own privileged knowledge of the location of an object biased their representation of a…

Getting to Know a Place: Built Environment Walkability and Children's Spatial Representation of Their Home-School (h-s) Route.

PubMed

Moran, Mika R; Eizenberg, Efrat; Plaut, Pnina

2017-06-06

The literature on environmental walkability to date has mainly focused on walking and related health outcomes. While previous studies suggest associations between walking and spatial knowledge, the associations between environmental walkability and spatial knowledge is yet to be explored. The current study addresses this lacuna in research by exploring children's mental representations of their home-school (h-s) route, vis.

The Development of Veteran 9th-Grade Physics Teachers' Knowledge for Using Representations to Teach the Topics of Energy Transformation and Transfer

ERIC Educational Resources Information Center

West, Andrew

2011-01-01

The purpose of this study was to explore and identify the experiences that informed the development of three veteran (15+ years of teaching experience) 9th grade physics teachers' specialized knowledge, or PCK, for using representations to teach the topics of energy transformation and transfer. Through the lens of phenomenography, the study…

Knowledge representation in metabolic pathway databases.

PubMed

Stobbe, Miranda D; Jansen, Gerbert A; Moerland, Perry D; van Kampen, Antoine H C

2014-05-01

The accurate representation of all aspects of a metabolic network in a structured format, such that it can be used for a wide variety of computational analyses, is a challenge faced by a growing number of researchers. Analysis of five major metabolic pathway databases reveals that each database has made widely different choices to address this challenge, including how to deal with knowledge that is uncertain or missing. In concise overviews, we show how concepts such as compartments, enzymatic complexes and the direction of reactions are represented in each database. Importantly, also concepts which a database does not represent are described. Which aspects of the metabolic network need to be available in a structured format and to what detail differs per application. For example, for in silico phenotype prediction, a detailed representation of gene-protein-reaction relations and the compartmentalization of the network is essential. Our analysis also shows that current databases are still limited in capturing all details of the biology of the metabolic network, further illustrated with a detailed analysis of three metabolic processes. Finally, we conclude that the conceptual differences between the databases, which make knowledge exchange and integration a challenge, have not been resolved, so far, by the exchange formats in which knowledge representation is standardized.

A Domain-Specific Language for Aviation Domain Interoperability

ERIC Educational Resources Information Center

Comitz, Paul

2013-01-01

Modern information systems require a flexible, scalable, and upgradeable infrastructure that allows communication and collaboration between heterogeneous information processing and computing environments. Aviation systems from different organizations often use differing representations and distribution policies for the same data and messages,…

Coordinating Representations

DTIC Science & Technology

2006-04-07

4 COGNITIVE THEORY OF INTERSUBJECTIVITY...adaptive component that is created and that the use of that component improves their performance. 2 Project Summary Objectives Develop cognitive theory of...distributed collaboration among a heterogeneous team of actors. Theory explains how collaborators share a common understanding of their cooperative

Modeling and formal representation of geospatial knowledge for the Geospatial Semantic Web

NASA Astrophysics Data System (ADS)

Huang, Hong; Gong, Jianya

2008-12-01

GML can only achieve geospatial interoperation at syntactic level. However, it is necessary to resolve difference of spatial cognition in the first place in most occasions, so ontology was introduced to describe geospatial information and services. But it is obviously difficult and improper to let users to find, match and compose services, especially in some occasions there are complicated business logics. Currently, with the gradual introduction of Semantic Web technology (e.g., OWL, SWRL), the focus of the interoperation of geospatial information has shifted from syntactic level to Semantic and even automatic, intelligent level. In this way, Geospatial Semantic Web (GSM) can be put forward as an augmentation to the Semantic Web that additionally includes geospatial abstractions as well as related reasoning, representation and query mechanisms. To advance the implementation of GSM, we first attempt to construct the mechanism of modeling and formal representation of geospatial knowledge, which are also two mostly foundational phases in knowledge engineering (KE). Our attitude in this paper is quite pragmatical: we argue that geospatial context is a formal model of the discriminate environment characters of geospatial knowledge, and the derivation, understanding and using of geospatial knowledge are located in geospatial context. Therefore, first, we put forward a primitive hierarchy of geospatial knowledge referencing first order logic, formal ontologies, rules and GML. Second, a metamodel of geospatial context is proposed and we use the modeling methods and representation languages of formal ontologies to process geospatial context. Thirdly, we extend Web Process Service (WPS) to be compatible with local DLL for geoprocessing and possess inference capability based on OWL.

45 CFR 1626.9 - Change in circumstances.

Code of Federal Regulations, 2011 CFR

2011-10-01

... ON LEGAL ASSISTANCE TO ALIENS § 1626.9 Change in circumstances. If, to the knowledge of the recipient... representation is prohibited by this part and a recipient must discontinue representation consistent with...

45 CFR 1626.9 - Change in circumstances.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ON LEGAL ASSISTANCE TO ALIENS § 1626.9 Change in circumstances. If, to the knowledge of the recipient... representation is prohibited by this part and a recipient must discontinue representation consistent with...

45 CFR 1626.9 - Change in circumstances.

Code of Federal Regulations, 2012 CFR

2012-10-01

... ON LEGAL ASSISTANCE TO ALIENS § 1626.9 Change in circumstances. If, to the knowledge of the recipient... representation is prohibited by this part and a recipient must discontinue representation consistent with...

45 CFR 1626.9 - Change in circumstances.

Code of Federal Regulations, 2010 CFR

2010-10-01

... ON LEGAL ASSISTANCE TO ALIENS § 1626.9 Change in circumstances. If, to the knowledge of the recipient... representation is prohibited by this part and a recipient must discontinue representation consistent with...

45 CFR 1626.9 - Change in circumstances.

Code of Federal Regulations, 2013 CFR

2013-10-01

... ON LEGAL ASSISTANCE TO ALIENS § 1626.9 Change in circumstances. If, to the knowledge of the recipient... representation is prohibited by this part and a recipient must discontinue representation consistent with...

The use of Multiple Representations to Enhance Student Mental Model Development of a Complex Earth System in an Introductory Geoscience Course

NASA Astrophysics Data System (ADS)

Sell, K. S.; Heather, M. R.; Herbert, B. E.

2004-12-01

Exposing earth system science (ESS) concepts into introductory geoscience courses may present new and unique cognitive learning issues for students including understanding the role of positive and negative feedbacks in system responses to perturbations, spatial heterogeneity, and temporal dynamics, especially when systems exhibit complex behavior. Implicit learning goals of typical introductory undergraduate geoscience courses are more focused on building skill-sets and didactic knowledge in learners than developing a deeper understanding of the dynamics and processes of complex earth systems through authentic inquiry. Didactic teaching coupled with summative assessment of factual knowledge tends to limit student¡¦s understanding of the nature of science, their belief in the relevancy of science to their lives, and encourages memorization and regurgitation; this is especially true among the non-science majors who compose the majority of students in introductory courses within the large university setting. Students organize scientific knowledge and reason about earth systems by manipulating internally constructed mental models. This pilot study focuses on characterizing the impact of inquiry-based learning with multiple representations to foster critical thinking and mental model development about authentic environmental issues of coastal systems in an introductory geoscience course. The research was conducted in nine introductory physical geology laboratory sections (N ˜ 150) at Texas A&M University as part of research connected with the Information Technology in Science (ITS) Center. Participants were randomly placed into experimental and control groups. Experimental groups were exposed to multiple representations including both web-based learning materials (i.e. technology-supported visualizations and analysis of multiple datasets) and physical models, whereas control groups were provided with the traditional ¡workbook style¡" laboratory assignments. Assessment of pre- and post-test results was performed to provide indications of content knowledge and mental model expression improvements between groups. A rubric was used as the assessment instrument to evaluate student products (Cronbach alpha: 0.84 ¡V 0.98). Characterization of student performance based on a Student¡¦s t-test indicates that significant differences (p < 0.05) in pre-post achievement occurred primarily within the experimental group; this illustrates that the use of multiple representations had an impact on student learning of ESS concepts, particularly in regard to mental model constructions. Analysis of variance also suggests that student mental model constructions were significantly different (p < 0.10) between test groups. Factor analysis extracted three principle components (eigenvalue > 1) which show similar clustering of variables that influence cognition, indicating that the cognitive processes driving student understanding of geoscience do not vary among student test groups. Categories of cognition include critical thinking skills (percent variance = 22.16%), understanding of the nature of science (percent variance = 25.16%), and ability to interpret results (percent variance = 28.89%). Lower numbers of students completed all of the required assignments of this research than expected (65.3%), restricting the quality of the results and therefore the ability to make more significant interpretations; this was likely due to the non-supportive learning environment in which the research was implemented.

Expansion of Biology Teachers' Pedagogical Content Knowledge (PCK) During a Long-Term Professional Development Program

NASA Astrophysics Data System (ADS)

Rozenszajn, Ronit; Yarden, Anat

2014-02-01

Experienced teachers possess a unique teaching knowledge comprised of an inter-related set of knowledge and beliefs that gives direction and justification to a teacher's actions. This study examined the expansion of two components of pedagogical content knowledge (PCK) of three in-service teachers in the course of a professional development program aimed at designing new teaching and learning materials suggested by the teachers themselves. The research presents an enlargement of previous PCK representations by focusing on a detailed representation of two main PCK domains: teaching and learning, including ten PCK components that emerged in the course of data analysis. This representation enabled revealing the unique PCK held by each teacher and to characterize the expansion of the two components of the participating teachers' PCK during the long-term professional development program. Retention of major parts of the expanded PCK a year after termination of the program implies that designing and implementing new teaching and learning materials based on the teachers' experiences, needs, and knowledge in a workshop format accompanied by biology and science education courses might provide a powerful means for PCK expansion. We recommend that designers of professional development programs be aware of the unique PCK held by each teacher in order to promote meaningful professional development of each teacher. Moreover, the PCK representations that were identified in the course of this study enabled clarifying the "orientation toward teaching science" category of PCK which appears to be unclear in current literature.

Combined effects of climatic gradient and domestic livestock grazing on reptile community structure in a heterogeneous agroecosystem.

PubMed

Rotem, Guy; Gavish, Yoni; Shacham, Boaz; Giladi, Itamar; Bouskila, Amos; Ziv, Yaron

2016-01-01

Grazing plays an important role in shaping ecological communities in human-related ecosystems. Although myriad studies have explored the joint effect of grazing and climate on plant communities, this interactive effect has rarely been studied in animals. We hypothesized that the effect of grazing on the reptile community varies along a climatic gradient in relation to the effect of grazing on habitat characteristics, and that grazing differentially affects reptiles of different biogeographic regions. We tested our hypotheses by collecting data on environmental characteristics and by trapping reptiles in four heterogeneous landscapes experiencing differing grazing intensities and distributed along a sharp climatic gradient. We found that while reptile diversity increased with grazing intensity at the mesic end of the gradient, it decreased with grazing intensity at the arid end. Moreover, the proportion of reptile species of differing biogeographic origins varied with the interactive effect of climate and grazing. The representation of species originating in arid biogeographic zones was highest at the arid end of the climatic gradient, and representation increased with grazing intensity within this area. Regardless of the climatic context, increased grazing pressure results in a reduction in vegetation cover and thus in changes in habitat characteristics. By reducing vegetation cover, grazing increased habitat heterogeneity in the dense mesic sites and decreased habitat heterogeneity in the arid sites. Thus, our results suggest that the same direction of habitat alteration caused by grazing may have opposite effects on biodiversity and community composition in different climatic contexts.

An Inventory for Measuring Student Teachers' Knowledge of Chemical Representations: Design, Validation, and Psychometric Analysis

ERIC Educational Resources Information Center

Taskin, V.; Bernholt, S.; Parchmann, I.

2015-01-01

Chemical representations play an important role in helping learners to understand chemical contents. Thus, dealing with chemical representations is a necessity for learning chemistry, but at the same time, it presents a great challenge to learners. Due to this great challenge, it is not surprising that numerous national and international studies…

A Cross-Talk between Brain-Damage Patients and Infants on Action and Language

ERIC Educational Resources Information Center

Papeo, Liuba; Hochmann, Jean-Remy

2012-01-01

Sensorimotor representations in the brain encode the sensory and motor aspects of one's own bodily activity. It is highly debated whether sensorimotor representations are the core basis for the representation of action-related knowledge and, in particular, action words, such as verbs. In this review, we will address this question by bringing to…

Making the Invisible Visible: Enhancing Students' Conceptual Understanding by Introducing Representations of Abstract Objects in a Simulation

ERIC Educational Resources Information Center

Olympiou, Georgios; Zacharias, Zacharia; deJong, Ton

2013-01-01

This study aimed to identify if complementing representations of concrete objects with representations of abstract objects improves students' conceptual understanding as they use a simulation to experiment in the domain of "Light and Color". Moreover, we investigated whether students' prior knowledge is a factor that must be considered in deciding…

Social Representations of the Development of Intelligence, Parental Values and Parenting Styles: A Theoretical Model for Analysis

ERIC Educational Resources Information Center

Miguel, Isabel; Valentim, Joaquim Pires; Carugati, Felice

2013-01-01

Within the theoretical framework of social representations theory, a substantial body of literature has advocated and shown that, as interpretative systems and forms of knowledge concurring in the construction of a social reality, social representations are guides for action, influencing behaviours and social relations. Based on this assumption,…

Impact of Professional Learning on Teachers' Representational Strategies and Students' Cognitive Engagement with Molecular Genetics Concepts

ERIC Educational Resources Information Center

Nichols, Kim

2018-01-01

A variety of practices and specialised representational systems are required to understand, communicate and construct molecular genetics knowledge. This study describes teachers' use of multimodal representations of molecular genetics concepts and how their strategies and choice of resources were interpreted, understood and used by students to…

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".

Foundation of a Knowledge Representation System for Image Understanding.

DTIC Science & Technology

1980-10-01

This is useful for holding the system together, for computing similarity between objects, for quickly retrieving desired information in as detailed a...mined by how much precision is needed to carry through the current computation . In Section 2, we discuss the OVS system itself, its structure and how...2.0 OVS SYSTEM Our goal here is to present the computational constraints involved in the design of a knowledge representation system which is

Building on prior knowledge without building it in.

PubMed

Hansen, Steven S; Lampinen, Andrew K; Suri, Gaurav; McClelland, James L

2017-01-01

Lake et al. propose that people rely on "start-up software," "causal models," and "intuitive theories" built using compositional representations to learn new tasks more efficiently than some deep neural network models. We highlight the many drawbacks of a commitment to compositional representations and describe our continuing effort to explore how the ability to build on prior knowledge and to learn new tasks efficiently could arise through learning in deep neural networks.

Enhanced recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-04-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

Predictive modelling of flow in a two-dimensional intermediate-scale, heterogeneous porous media

USGS Publications Warehouse

Barth, Gilbert R.; Hill, M.C.; Illangasekare, T.H.; Rajaram, H.

2000-01-01

To better understand the role of sedimentary structures in flow through porous media, and to determine how small-scale laboratory-measured values of hydraulic conductivity relate to in situ values this work deterministically examines flow through simple, artificial structures constructed for a series of intermediate-scale (10 m long), two-dimensional, heterogeneous, laboratory experiments. Nonlinear regression was used to determine optimal values of in situ hydraulic conductivity, which were compared to laboratory-measured values. Despite explicit numerical representation of the heterogeneity, the optimized values were generally greater than the laboratory-measured values. Discrepancies between measured and optimal values varied depending on the sand sieve size, but their contribution to error in the predicted flow was fairly consistent for all sands. Results indicate that, even under these controlled circumstances, laboratory-measured values of hydraulic conductivity need to be applied to models cautiously.To better understand the role of sedimentary structures in flow through porous media, and to determine how small-scale laboratory-measured values of hydraulic conductivity relate to in situ values this work deterministically examines flow through simple, artificial structures constructed for a series of intermediate-scale (10 m long), two-dimensional, heterogeneous, laboratory experiments. Nonlinear regression was used to determine optimal values of in situ hydraulic conductivity, which were compared to laboratory-measured values. Despite explicit numerical representation of the heterogeneity, the optimized values were generally greater than the laboratory-measured values. Discrepancies between measured and optimal values varied depending on the sand sieve size, but their contribution to error in the predicted flow was fairly consistent for all sands. Results indicate that, even under these controlled circumstances, laboratory-measured values of hydraulic conductivity need to be applied to models cautiously.

Illness representations, knowledge and motivation to perform presymptomatic testing for late-onset genetic diseases.

PubMed

Leite, Ângela; Dinis, Maria Alzira P; Sequeiros, Jorge; Paúl, Constança

2017-02-01

This study addresses the relation between illness representations, knowledge and motivation to perform the presymptomatic testing (PST) of subjects at-risk for Familial Amyloydotic Polyneuropathy (FAP), Huntington's disease (HD) and Machado-Joseph disease (MJD), compared with subjects at-risk for Hereditary Hemochromatosis (HH). The sample comprised a clinical group of 213 subjects at genetic risk for FAP, HD and MJD, and a comparison group of 31 subjects at genetic risk for HH, that answered three open-ended questions relating illness representations, knowledge about the disease, and motivation to perform PST. People at-risk for FAP, HD and MJD use more metaphors, make more references to the family, are more concerned with the future and feel more out of curiosity and to learn, than for HH. These subjects at-risk correspond to the profile of somatic individual or personhood, wherein the unsubjectivation of the disease can function as a coping mechanism.

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.

The Head Bone's Connected to the Neck Bone: When do Toddlers Represent Their Own Body Topography?

PubMed Central

Brownell, Celia A.; Nichols, Sara R.; Svetlova, Margarita; Zerwas, Stephanie; Ramani, Geetha

2010-01-01

Developments in very young children's topographic representations of their own bodies were examined. Sixty one 20- and 30-month old children were administered tasks that indexed the ability to locate specific body parts on oneself and knowledge of how one's body parts are spatially organized, as well as body-size knowledge and self-awareness. Age differences in performance emerged for every task. Body-part localization and body spatial configuration knowledge were associated; however, body topography knowledge was not associated with body-size knowledge. Both were related to traditional measures of self-awareness, mediated by their common associations with age. It is concluded that children possess an explicit, if rudimentary, topographic representation of their own body's shape, structure, and size by 30 months of age. PMID:20573105

Interoperable Data Sharing for Diverse Scientific Disciplines

NASA Astrophysics Data System (ADS)

Hughes, John S.; Crichton, Daniel; Martinez, Santa; Law, Emily; Hardman, Sean

2016-04-01

For diverse scientific disciplines to interoperate they must be able to exchange information based on a shared understanding. To capture this shared understanding, we have developed a knowledge representation framework using ontologies and ISO level archive and metadata registry reference models. This framework provides multi-level governance, evolves independent of implementation technologies, and promotes agile development, namely adaptive planning, evolutionary development, early delivery, continuous improvement, and rapid and flexible response to change. The knowledge representation framework is populated through knowledge acquisition from discipline experts. It is also extended to meet specific discipline requirements. The result is a formalized and rigorous knowledge base that addresses data representation, integrity, provenance, context, quantity, and their relationships within the community. The contents of the knowledge base is translated and written to files in appropriate formats to configure system software and services, provide user documentation, validate ingested data, and support data analytics. This presentation will provide an overview of the framework, present the Planetary Data System's PDS4 as a use case that has been adopted by the international planetary science community, describe how the framework is being applied to other disciplines, and share some important lessons learned.

A Working Framework for Enabling International Science Data System Interoperability

NASA Astrophysics Data System (ADS)

Hughes, J. Steven; Hardman, Sean; Crichton, Daniel J.; Martinez, Santa; Law, Emily; Gordon, Mitchell K.

2016-07-01

For diverse scientific disciplines to interoperate they must be able to exchange information based on a shared understanding. To capture this shared understanding, we have developed a knowledge representation framework that leverages ISO level reference models for metadata registries and digital archives. This framework provides multi-level governance, evolves independent of the implementation technologies, and promotes agile development, namely adaptive planning, evolutionary development, early delivery, continuous improvement, and rapid and flexible response to change. The knowledge representation is captured in an ontology through a process of knowledge acquisition. Discipline experts in the role of stewards at the common, discipline, and project levels work to design and populate the ontology model. The result is a formal and consistent knowledge base that provides requirements for data representation, integrity, provenance, context, identification, and relationship. The contents of the knowledge base are translated and written to files in suitable formats to configure system software and services, provide user documentation, validate input, and support data analytics. This presentation will provide an overview of the framework, present a use case that has been adopted by an entire science discipline at the international level, and share some important lessons learned.

Student filmmakers' attitudes towards mental illness and its cinematic representation - an evaluation of a training intervention for film students.

PubMed

Dale, Jenny; Richards, Felicity; Bradburn, John; Tadros, George; Salama, Rafik

2014-02-01

Government strategy for mental health places tackling stigma as a main priority. National initiatives have attempted to tackle stigma by challenging negative media reporting and the use of stereotyped representations of mental illness, with mixed results. Educational interventions have attempted to address stigmatising attitudes in young people but no studies have explored the value of such interventions for film students. The study aimed to assess the value of a lecture-based training intervention designed to improve the knowledge and attitudes of student filmmakers towards mental illness and its cinematic representation. A self-report questionnaire was administered before and after the intervention, which measured the knowledge and attitudes of the subjects. 32 out of 54 students (59.3%) showed statistically significant improvement in attitudes and knowledge overall, although this was less marked in responses to the attitudinal subset questions compared with knowledge-based questions. Feedback was positive. The training session was successful in its aims for most but not all students. The intervention is reproducible but further work needs to be done to clarify how best to influence attitudes and behaviour as well as knowledge.

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - a review

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2017-07-01

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Representation in incremental learning

NASA Technical Reports Server (NTRS)

1993-01-01

Work focused on two areas in machine learning: representation for inductive learning and how to apply concept learning techniques to learning state preferences, which can represent search control knowledge for problem solving. Specifically, in the first area the issues of the effect of representation on learning, on how learning formalisms are biased, and how concept learning can benefit from the use of a hybrid formalism are addressed. In the second area, the issues of developing an agent to learn search control knowledge from the relative values of states, of the source of that qualitative information, and of the ability to use both quantitative and qualitative information in order to develop an effective problem-solving policy are examined.

How to make a good animation: A grounded cognition model of how visual representation design affects the construction of abstract physics knowledge

NASA Astrophysics Data System (ADS)

Chen, Zhongzhou; Gladding, Gary

2014-06-01

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, which leads to a significant variance in their effectiveness. In this paper we propose a cognitive mechanism based on grounded cognition, suggesting that visual perception affects understanding by activating "perceptual symbols": the basic cognitive unit used by the brain to construct a concept. A good visual representation activates perceptual symbols that are essential for the construction of the represented concept, whereas a bad representation does the opposite. As a proof of concept, we conducted a clinical experiment in which participants received three different versions of a multimedia tutorial teaching the integral expression of electric potential. The three versions were only different by the details of the visual representation design, only one of which contained perceptual features that activate perceptual symbols essential for constructing the idea of "accumulation." On a following post-test, participants receiving this version of tutorial significantly outperformed those who received the other two versions of tutorials designed to mimic conventional visual representations used in classrooms.

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.

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.

Evaluation of an educational program on deciphering heterogeneity for medical coverage decisions.

PubMed

Warholak, Terri L; Hilgaertner, Jianhua W; Dean, Joni L; Taylor, Ann M; Hines, Lisa E; Hurwitz, Jason; Brown, Mary; Malone, Daniel C

2014-06-01

It is increasingly important for decision makers, such as medical and pharmacy managers (or pharmacy therapeutics committee members and staff), to understand the variation and diversity in treatment response as decisions shift from an individual patient perspective to optimizing care for populations of patients. To assess the effectiveness of an instructional program on heterogeneity designed for medical and pharmacy managers. A live educational program was offered to members of the Academy of Managed Care Pharmacy at the fall 2012 educational meeting and also to medical directors and managers attending a national payer roundtable meeting in October 2012. Participants completed a retrospective pretest-posttest assessment of their knowledge, attitudes, and self-efficacy immediately following the program. Participants were offered the opportunity to participate in a follow-up assessment 6 months later. Willing participants for the follow-up assessment were contacted via e-mail and telephone. Rasch rating scale models were used to compare pre- and postscores measuring participants' knowledge about and attitude towards heterogeneity. A total of 49 individuals completed the retrospective pretest-posttest assessment and agreed to be a part of the program evaluation. Fifty percent (n = 25) of participants had heard of the phrase "heterogeneity of treatment effect," and 36 (72%) were familiar with the phrase "individualized treatment effect" prior to the live program. Participants reported a significant improvement in knowledge of heterogeneity (P  less than  0.01) and attitudes about heterogeneity (P  less than  0.01) immediately after attending the program. At the time of the educational program, participants had either never considered heterogeneity (26%) or reported not knowing (28%) whether their organizations considered it when determining basic coverage. Participants were more likely to report "sometimes" considering heterogeneity for determining necessity for individual appeals, prior authorization, tier placement for pharmaceutical therapies, and other types of medical management. At the 6-month follow-up, 21 of the 49 willing participants (43% response rate) completed the evaluation; participants continued to have a good understanding of heterogeneity, but there was no significant difference in attitudes towards heterogeneity between pre- and 6-month follow-up. A live educational program was effective in improving participants' immediate knowledge and attitudes regarding the topic of heterogeneity. Participating managed care pharmacists and medical managers indicated that heterogeneity of treatment effect was likely to be used in determining prior authorizations and determining necessity.

Meaningful main effects or intriguing interactions? Examining the influences of epistemic beliefs and knowledge representations on cognitive processing and conceptual change when learning physics

NASA Astrophysics Data System (ADS)

Franco, Gina M.

The purpose of this study was to investigate the role of epistemic beliefs and knowledge representations in cognitive and metacognitive processing and conceptual change when learning about physics concepts through text. Specifically, I manipulated the representation of physics concepts in texts about Newtonian mechanics and explored how these texts interacted with individuals' epistemic beliefs to facilitate or constrain learning. In accordance with definitions from Royce's (1983) framework of psychological epistemology, texts were developed to present Newtonian concepts in either a rational or a metaphorical format. Seventy-five undergraduate students completed questionnaires designed to measure their epistemic beliefs and their misconceptions about Newton's laws of motion. Participants then read the first of two instructional texts (in either a rational or metaphorical format), and were asked to think aloud while reading. After reading the text, participants completed a recall task and a post-test of selected items regarding Newtonian concepts. These steps were repeated with a second instructional text (in either a rational or metaphorical format, depending on which format was assigned previously). Participants' think-aloud sessions were audio-recorded, transcribed, and then blindly coded, and their recalls were scored for total number of correctly recalled ideas from the text. Changes in misconceptions were analyzed by examining changes in participants' responses to selected questions about Newtonian concepts from pretest to posttest. Results revealed that when individuals' epistemic beliefs were congruent with the knowledge representations in their assigned texts, they performed better on both online measures of learning (e.g., use of processing strategies) and offline products of learning (e.g., text recall, changes in misconceptions) than when their epistemic beliefs were incongruent with the knowledge representations. These results have implications for how researchers conceptualize epistemic beliefs and are in line with contemporary views regarding the context sensitivity of individuals' epistemic beliefs. Moreover, the findings from this study not only support current theory about the dynamic and interactive nature of conceptual change, but also advance empirical work in this area by identifying knowledge representations as a text characteristic that may play an important role in the change process.

Individual movement behavior, matrix heterogeneity, and the dynamics of spatially structured populations.

PubMed

Revilla, Eloy; Wiegand, Thorsten

2008-12-09

The dynamics of spatially structured populations is characterized by within- and between-patch processes. The available theory describes the latter with simple distance-dependent functions that depend on landscape properties such as interpatch distance or patch size. Despite its potential role, we lack a good mechanistic understanding of how the movement of individuals between patches affects the dynamics of these populations. We used the theoretical framework provided by movement ecology to make a direct representation of the processes determining how individuals connect local populations in a spatially structured population of Iberian lynx. Interpatch processes depended on the heterogeneity of the matrix where patches are embedded and the parameters defining individual movement behavior. They were also very sensitive to the dynamic demographic variables limiting the time moving, the within-patch dynamics of available settlement sites (both spatiotemporally heterogeneous) and the response of individuals to the perceived risk while moving. These context-dependent dynamic factors are an inherent part of the movement process, producing connectivities and dispersal kernels whose variability is affected by other demographic processes. Mechanistic representations of interpatch movements, such as the one provided by the movement-ecology framework, permit the dynamic interaction of birth-death processes and individual movement behavior, thus improving our understanding of stochastic spatially structured populations.

Universal Index System

NASA Technical Reports Server (NTRS)

Kelley, Steve; Roussopoulos, Nick; Sellis, Timos; Wallace, Sarah

1993-01-01

The Universal Index System (UIS) is an index management system that uses a uniform interface to solve the heterogeneity problem among database management systems. UIS provides an easy-to-use common interface to access all underlying data, but also allows different underlying database management systems, storage representations, and access methods.

Automated solar collector installation design including ability to define heterogeneous design preferences

DOEpatents

Wayne, Gary; Frumkin, Alexander; Zaydman, Michael; Lehman, Scott; Brenner, Jules

2014-04-29

Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of pre -defined "features" with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Embodiments may also include definition of one or more design apertures, each of which may correspond to boundaries in which solar collector layouts should comply with distinct sets of user-defined design preferences. Distinct apertures may provide heterogeneous regions of collector layout according to the user-defined design preferences.

Automated solar collector installation design including ability to define heterogeneous design preferences

DOEpatents

Wayne, Gary; Frumkin, Alexander; Zaydman, Michael; Lehman, Scott; Brenner, Jules

2013-01-08

Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of pre-defined "features" with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Embodiments may also include definition of one or more design apertures, each of which may correspond to boundaries in which solar collector layouts should comply with distinct sets of user-defined design preferences. Distinct apertures may provide heterogeneous regions of collector layout according to the user-defined design preferences.

Integration of heterogeneous data for classification in hyperspectral satellite imagery

NASA Astrophysics Data System (ADS)

Benedetto, J.; Czaja, W.; Dobrosotskaya, J.; Doster, T.; Duke, K.; Gillis, D.

2012-06-01

As new remote sensing modalities emerge, it becomes increasingly important to nd more suitable algorithms for fusion and integration of dierent data types for the purposes of target/anomaly detection and classication. Typical techniques that deal with this problem are based on performing detection/classication/segmentation separately in chosen modalities, and then integrating the resulting outcomes into a more complete picture. In this paper we provide a broad analysis of a new approach, based on creating fused representations of the multi- modal data, which then can be subjected to analysis by means of the state-of-the-art classiers or detectors. In this scenario we shall consider the hyperspectral imagery combined with spatial information. Our approach involves machine learning techniques based on analysis of joint data-dependent graphs and their associated diusion kernels. Then, the signicant eigenvectors of the derived fused graph Laplace operator form the new representation, which provides integrated features from the heterogeneous input data. We compare these fused approaches with analysis of integrated outputs of spatial and spectral graph methods.

A Knowledge-Based Arrangement of Prototypical Neural Representation Prior to Experience Contributes to Selectivity in Upcoming Knowledge Acquisition.

PubMed

Kurashige, Hiroki; Yamashita, Yuichi; Hanakawa, Takashi; Honda, Manabu

2018-01-01

Knowledge acquisition is a process in which one actively selects a piece of information from the environment and assimilates it with prior knowledge. However, little is known about the neural mechanism underlying selectivity in knowledge acquisition. Here we executed a 2-day human experiment to investigate the involvement of characteristic spontaneous activity resembling a so-called "preplay" in selectivity in sentence comprehension, an instance of knowledge acquisition. On day 1, we presented 10 sentences (prior sentences) that were difficult to understand on their own. On the following day, we first measured the resting-state functional magnetic resonance imaging (fMRI). Then, we administered a sentence comprehension task using 20 new sentences (posterior sentences). The posterior sentences were also difficult to understand on their own, but some could be associated with prior sentences to facilitate their understanding. Next, we measured the posterior sentence-induced fMRI to identify the neural representation. From the resting-state fMRI, we extracted the appearances of activity patterns similar to the neural representations for posterior sentences. Importantly, the resting-state fMRI was measured before giving the posterior sentences, and thus such appearances could be considered as preplay-like or prototypical neural representations. We compared the intensities of such appearances with the understanding of posterior sentences. This gave a positive correlation between these two variables, but only if posterior sentences were associated with prior sentences. Additional analysis showed the contribution of the entorhinal cortex, rather than the hippocampus, to the correlation. The present study suggests that prior knowledge-based arrangement of neural activity before an experience contributes to the active selection of information to be learned. Such arrangement prior to an experience resembles preplay activity observed in the rodent brain. In terms of knowledge acquisition, the present study leads to a new view of the brain (or more precisely of the brain's knowledge) as an autopoietic system in which the brain (or knowledge) selects what it should learn by itself, arranges preplay-like activity as a position for the new information in advance, and actively reorganizes itself.

A Knowledge-Based Arrangement of Prototypical Neural Representation Prior to Experience Contributes to Selectivity in Upcoming Knowledge Acquisition

PubMed Central

Kurashige, Hiroki; Yamashita, Yuichi; Hanakawa, Takashi; Honda, Manabu

2018-01-01

Knowledge acquisition is a process in which one actively selects a piece of information from the environment and assimilates it with prior knowledge. However, little is known about the neural mechanism underlying selectivity in knowledge acquisition. Here we executed a 2-day human experiment to investigate the involvement of characteristic spontaneous activity resembling a so-called “preplay” in selectivity in sentence comprehension, an instance of knowledge acquisition. On day 1, we presented 10 sentences (prior sentences) that were difficult to understand on their own. On the following day, we first measured the resting-state functional magnetic resonance imaging (fMRI). Then, we administered a sentence comprehension task using 20 new sentences (posterior sentences). The posterior sentences were also difficult to understand on their own, but some could be associated with prior sentences to facilitate their understanding. Next, we measured the posterior sentence-induced fMRI to identify the neural representation. From the resting-state fMRI, we extracted the appearances of activity patterns similar to the neural representations for posterior sentences. Importantly, the resting-state fMRI was measured before giving the posterior sentences, and thus such appearances could be considered as preplay-like or prototypical neural representations. We compared the intensities of such appearances with the understanding of posterior sentences. This gave a positive correlation between these two variables, but only if posterior sentences were associated with prior sentences. Additional analysis showed the contribution of the entorhinal cortex, rather than the hippocampus, to the correlation. The present study suggests that prior knowledge-based arrangement of neural activity before an experience contributes to the active selection of information to be learned. Such arrangement prior to an experience resembles preplay activity observed in the rodent brain. In terms of knowledge acquisition, the present study leads to a new view of the brain (or more precisely of the brain’s knowledge) as an autopoietic system in which the brain (or knowledge) selects what it should learn by itself, arranges preplay-like activity as a position for the new information in advance, and actively reorganizes itself. PMID:29662446

Specificity of Structural Assessment of Knowledge

ERIC Educational Resources Information Center

Trumpower, David L.; Sharara, Harold; Goldsmith, Timothy E.

2010-01-01

This study examines the specificity of information provided by structural assessment of knowledge (SAK). SAK is a technique which uses the Pathfinder scaling algorithm to transform ratings of concept relatedness into network representations (PFnets) of individuals' knowledge. Inferences about individuals' overall domain knowledge based on the…

Exploring the Role of Physics Representations: An Illustrative Example from Students Sharing Knowledge about Refraction

ERIC Educational Resources Information Center

Fredlund, Tobias; Airey, John; Linder, Cedric

2012-01-01

Research has shown that interactive engagement enhances student learning outcomes. A growing body of research suggests that the representations we use in physics are important in such learning environments. In this paper we draw on a number of sources in the literature to explore the role of representations in interactive engagement in physics. In…

The Design and Study of a Learning Environment to Support Growth and Change in Students' Knowledge of Fraction Multiplication

ERIC Educational Resources Information Center

Brar, Rozy

2010-01-01

There is a strong push from within mathematics education reform to incorporate representations in math classrooms (Behr, Harel, Post, & Lesh, 1993; Kieren, 1993; NCTM, 2000). However, questions regarding what representations should be used (for a given topic) and how representations should be used (such that students gain a deep understanding of…

Analysis of Student Understanding of Science Concepts Including Mathematical Representations: Ph Values and the Relative Differences of pH Values

ERIC Educational Resources Information Center

Park, Eun-Jung; Choi, Kyunghee

2013-01-01

In general, mathematical representations such as formulae, numbers, and graphs are the inseparable components in science used to better describe or explain scientific phenomena or knowledge. Regardless of their necessity and benefit, science seems to be difficult for some students, as a result of the mathematical representations and problem…

Increasing verbal knowledge mediates development of multidimensional emotion representations

PubMed Central

Nook, Erik C.; Sasse, Stephanie F.; Lambert, Hilary K.; McLaughlin, Katie A.; Somerville, Leah H.

2017-01-01

How do people represent their own and others’ emotional experiences? Contemporary emotion theories and growing evidence suggest that the conceptual representation of emotion plays a central role in how people understand the emotions both they and other people feel.1–6 Although decades of research indicate that adults typically represent emotion concepts as multidimensional, with valence (positive—negative) and arousal (activating—deactivating) as two primary dimensions,7–10 little is known about how this bidimensional (or circumplex) representation arises.11 Here we show that emotion representations develop from a monodimensional focus on valence to a bidimensional focus on both valence and arousal from age 6 to age 25. We investigated potential mechanisms underlying this effect and found that increasing verbal knowledge mediated emotion representation development over and above three other potential mediators: (i) fluid reasoning, (ii) the general ability to represent non-emotional stimuli bidimensionally, and (iii) task-related behaviors (e.g., using extreme ends of rating scales). These results suggest that verbal development facilitates the expansion of emotion concept representations (and potentially emotional experiences) from a “positive or negative” dichotomy in childhood to a multidimensional organization in adulthood. PMID:29399639

Is the difference between right and left ATLs due to the distinction between general and social cognition or between verbal and non-verbal representations?

PubMed

Gainotti, Guido

2015-04-01

The present review aimed to check two proposals alternative to the original version of the 'semantic hub' hypothesis, based on semantic dementia (SD) data, which assumed that left and right anterior temporal lobes (ATLs) store in a unitary, amodal format all kinds of semantic representations. The first alternative proposal is that the right ATL might subsume non-verbal representations and the left ATL lexical-semantic representations and that only in the advanced stages of SD, when atrophy affects the ATLs bilaterally, the semantic impairment becomes 'multi-modal'. The second alternative suggestion is that right and left ATLs might underlie two different domains of knowledge, because general conceptual knowledge might be supported by the left ATL, and social cognition by the right ATL. Results of the review substantially support the first proposal, showing that the right ATL subsumes non-verbal representations and the left ATL lexical-semantic representations. They are less conclusive about the second suggestion, because the right ATL seems to play a more important role in behavioral and emotional functions than in higher level social cognition. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lexical-semantic body knowledge in 5- to 11-year-old children: How spatial body representation influences body semantics.

PubMed

Auclair, Laurent; Jambaqué, Isabelle

2015-01-01

This study addresses the relation between lexico-semantic body knowledge (i.e., body semantics) and spatial body representation (i.e., structural body representation) by analyzing naming performances as a function of body structural topography. One hundred and forty-one children ranging from 5 years 2 months to 10 years 5 months old were asked to provide a lexical label for isolated body part pictures. We compared the children's naming performances according to the location of the body parts (body parts vs. head features and also upper vs. lower limbs) or to their involvement in motor skills (distal segments, joints, and broader body parts). The results showed that the children's naming performance was better for facial body parts than for other body parts. Furthermore, it was found that the naming of body parts was better for body parts related to action. These findings suggest that the development of a spatial body representation shapes the elaboration of semantic body representation processing. Moreover, this influence was not limited to younger children. In our discussion of these results, we focus on the important role of action in the development of body representations and semantic organization.

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.

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

Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

Homogeneous and heterogeneous chemistry along air parcel trajectories

NASA Technical Reports Server (NTRS)

Jones, R. L.; Mckenna, D. L.; Poole, L. R.; Solomon, S.

1990-01-01

The study of coupled heterogeneous and homogeneous chemistry due to polar stratospheric clouds (PSC's) using Lagrangian parcel trajectories for interpretation of the Airborne Arctic Stratosphere Experiment (AASE) is discussed. This approach represents an attempt to quantitatively model the physical and chemical perturbation to stratospheric composition due to formation of PSC's using the fullest possible representation of the relevant processes. Further, the meteorological fields from the United Kingdom Meteorological office global model were used to deduce potential vorticity and inferred regions of PSC's as an input to flight planning during AASE.

Relationships between magnitude representation, counting and memory in 4- to 7-year-old children: a developmental study.

PubMed

Soltész, Fruzsina; Szucs, Dénes; Szucs, Lívia

2010-02-18

The development of an evolutionarily grounded analogue magnitude representation linked to the parietal lobes is frequently thought to be a major factor in the arithmetic development of humans. We investigated the relationship between counting and the development of magnitude representation in children, assessing also children's knowledge of number symbols, their arithmetic fact retrieval, their verbal skills, and their numerical and verbal short-term memory. The magnitude representation was tested by a non-symbolic magnitude comparison task. We have perfected previous experimental designs measuring magnitude discrimination skills in 65 children kindergarten (4-7-year-olds) by controlling for several variables which were not controlled for in previous similar research. We also used a large number of trials which allowed for running a full factorial ANOVA including all relevant factors. Tests of verbal counting, of short term memory, of number knowledge, of problem solving abilities and of verbal fluency were administered and correlated with performance in the magnitude comparison task. Verbal counting knowledge and performance on simple arithmetic tests did not correlate with non-symbolic magnitude comparison at any age. Older children performed successfully on the number comparison task, showing behavioural patterns consistent with an analogue magnitude representation. In contrast, 4-year-olds were unable to discriminate number independently of task-irrelevant perceptual variables. Sensitivity to irrelevant perceptual features of the magnitude discrimination task was also affected by age, and correlated with memory, suggesting that more general cognitive abilities may play a role in performance in magnitude comparison tasks. We conclude that young children are not able to discriminate numerical magnitudes when co-varying physical magnitudes are methodically pitted against number. We propose, along with others, that a rather domain general magnitude representation provides the later basis for a specialized representation of numerical magnitudes. For this representational specialization, the acquisition of the concept of abstract numbers, together with the development of other cognitive abilities, is indispensable.

Relationships between magnitude representation, counting and memory in 4- to 7-year-old children: A developmental study

PubMed Central

2010-01-01

Background The development of an evolutionarily grounded analogue magnitude representation linked to the parietal lobes is frequently thought to be a major factor in the arithmetic development of humans. We investigated the relationship between counting and the development of magnitude representation in children, assessing also children's knowledge of number symbols, their arithmetic fact retrieval, their verbal skills, and their numerical and verbal short-term memory. Methods The magnitude representation was tested by a non-symbolic magnitude comparison task. We have perfected previous experimental designs measuring magnitude discrimination skills in 65 children kindergarten (4-7-year-olds) by controlling for several variables which were not controlled for in previous similar research. We also used a large number of trials which allowed for running a full factorial ANOVA including all relevant factors. Tests of verbal counting, of short term memory, of number knowledge, of problem solving abilities and of verbal fluency were administered and correlated with performance in the magnitude comparison task. Results and discussion Verbal counting knowledge and performance on simple arithmetic tests did not correlate with non-symbolic magnitude comparison at any age. Older children performed successfully on the number comparison task, showing behavioural patterns consistent with an analogue magnitude representation. In contrast, 4-year-olds were unable to discriminate number independently of task-irrelevant perceptual variables. Sensitivity to irrelevant perceptual features of the magnitude discrimination task was also affected by age, and correlated with memory, suggesting that more general cognitive abilities may play a role in performance in magnitude comparison tasks. Conclusion We conclude that young children are not able to discriminate numerical magnitudes when co-varying physical magnitudes are methodically pitted against number. We propose, along with others, that a rather domain general magnitude representation provides the later basis for a specialized representation of numerical magnitudes. For this representational specialization, the acquisition of the concept of abstract numbers, together with the development of other cognitive abilities, is indispensable. PMID:20167066

[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.

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.

Final Technical Report - Investigation into the Relationship between Heterogeneity and Heavy-Tailed Solute Transport

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

Weissmann, Gary S

2013-12-06

The objective of this project was to characterize the influence that naturally complex geologic media has on anomalous dispersion and to determine if the nature of dispersion can be estimated from the underlying heterogeneous media. The UNM portion of this project was to provide detailed representations of aquifer heterogeneity through producing highly-resolved models of outcrop analogs to aquifer materials. This project combined outcrop-scale heterogeneity characterization (conducted at the University of New Mexico), laboratory experiments (conducted at Sandia National Laboratory), and numerical simulations (conducted at Sandia National Laboratory and Colorado School of Mines). The study was designed to test whether establishedmore » dispersion theory accurately predicts the behavior of solute transport through heterogeneous media and to investigate the relationship between heterogeneity and the parameters that populate these models. The dispersion theory tested by this work was based upon the fractional advection-dispersion equation (fADE) model. Unlike most dispersion studies that develop a solute transport model by fitting the solute transport breakthrough curve, this project explored the nature of the heterogeneous media to better understand the connection between the model parameters and the aquifer heterogeneity. We also evaluated methods for simulating the heterogeneity to see whether these approaches (e.g., geostatistical) could reasonably replicate realistic heterogeneity. The UNM portion of this study focused on capturing realistic geologic heterogeneity of aquifer analogs using advanced outcrop mapping methods.« less

Mapping out the Integration of the Components of Pedagogical Content Knowledge (PCK): Examples from High School Biology Classrooms

ERIC Educational Resources Information Center

Park, Soonhye; Chen, Ying-Chih

2012-01-01

This study explored the nature of the integration of the five components of pedagogical content knowledge (PCK): (a) Orientations toward Teaching Science, (b) Knowledge of Student Understanding, (c) Knowledge of Instructional Strategies and Representations, (d) Knowledge of Science Curriculum, and (e) Knowledge of Assessment of Science Learning.…

Effector-independent motor sequence representations exist in extrinsic and intrinsic reference frames.

PubMed

Wiestler, Tobias; Waters-Metenier, Sheena; Diedrichsen, Jörn

2014-04-02

Many daily activities rely on the ability to produce meaningful sequences of movements. Motor sequences can be learned in an effector-specific fashion (such that benefits of training are restricted to the trained hand) or an effector-independent manner (meaning that learning also facilitates performance with the untrained hand). Effector-independent knowledge can be represented in extrinsic/world-centered or in intrinsic/body-centered coordinates. Here, we used functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis to determine the distribution of intrinsic and extrinsic finger sequence representations across the human neocortex. Participants practiced four sequences with one hand for 4 d, and then performed these sequences during fMRI with both left and right hand. Between hands, these sequences were equivalent in extrinsic or intrinsic space, or were unrelated. In dorsal premotor cortex (PMd), we found that sequence-specific activity patterns correlated higher for extrinsic than for unrelated pairs, providing evidence for an extrinsic sequence representation. In contrast, primary sensory and motor cortices showed effector-independent representations in intrinsic space, with considerable overlap of the two reference frames in caudal PMd. These results suggest that effector-independent representations exist not only in world-centered, but also in body-centered coordinates, and that PMd may be involved in transforming sequential knowledge between the two. Moreover, although effector-independent sequence representations were found bilaterally, they were stronger in the hemisphere contralateral to the trained hand. This indicates that intermanual transfer relies on motor memories that are laid down during training in both hemispheres, but preferentially draws upon sequential knowledge represented in the trained hemisphere.

Effector-Independent Motor Sequence Representations Exist in Extrinsic and Intrinsic Reference Frames

PubMed Central

Wiestler, Tobias; Waters-Metenier, Sheena

2014-01-01

Many daily activities rely on the ability to produce meaningful sequences of movements. Motor sequences can be learned in an effector-specific fashion (such that benefits of training are restricted to the trained hand) or an effector-independent manner (meaning that learning also facilitates performance with the untrained hand). Effector-independent knowledge can be represented in extrinsic/world-centered or in intrinsic/body-centered coordinates. Here, we used functional magnetic resonance imaging (fMRI) and multivoxel pattern analysis to determine the distribution of intrinsic and extrinsic finger sequence representations across the human neocortex. Participants practiced four sequences with one hand for 4 d, and then performed these sequences during fMRI with both left and right hand. Between hands, these sequences were equivalent in extrinsic or intrinsic space, or were unrelated. In dorsal premotor cortex (PMd), we found that sequence-specific activity patterns correlated higher for extrinsic than for unrelated pairs, providing evidence for an extrinsic sequence representation. In contrast, primary sensory and motor cortices showed effector-independent representations in intrinsic space, with considerable overlap of the two reference frames in caudal PMd. These results suggest that effector-independent representations exist not only in world-centered, but also in body-centered coordinates, and that PMd may be involved in transforming sequential knowledge between the two. Moreover, although effector-independent sequence representations were found bilaterally, they were stronger in the hemisphere contralateral to the trained hand. This indicates that intermanual transfer relies on motor memories that are laid down during training in both hemispheres, but preferentially draws upon sequential knowledge represented in the trained hemisphere. PMID:24695723

Ince-Gaussian series representation of the two-dimensional fractional Fourier transform.

PubMed

Bandres, Miguel A; Gutiérrez-Vega, Julio C

2005-03-01

We introduce the Ince-Gaussian series representation of the two-dimensional fractional Fourier transform in elliptical coordinates. A physical interpretation is provided in terms of field propagation in quadratic graded-index media whose eigenmodes in elliptical coordinates are derived for the first time to our knowledge. The kernel of the new series representation is expressed in terms of Ince-Gaussian functions. The equivalence among the Hermite-Gaussian, Laguerre-Gaussian, and Ince-Gaussian series representations is verified by establishing the relation among the three definitions.

Hologram representation of design data in an expert system knowledge base

NASA Technical Reports Server (NTRS)

Shiva, S. G.; Klon, Peter F.

1988-01-01

A novel representational scheme for design object descriptions is presented. An abstract notion of modules and signals is developed as a conceptual foundation for the scheme. This abstraction relates the objects to the meaning of system descriptions. Anchored on this abstraction, a representational model which incorporates dynamic semantics for these objects is presented. This representational model is called a hologram scheme since it represents dual level information, namely, structural and semantic. The benefits of this scheme are presented.

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

16 CFR 1115.11 - Imputed knowledge.

Code of Federal Regulations, 2014 CFR

2014-01-01

... care to ascertain the truth of complaints or other representations. This includes the knowledge a firm... 16 Commercial Practices 2 2014-01-01 2014-01-01 false Imputed knowledge. 1115.11 Section 1115.11... PRODUCT HAZARD REPORTS General Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether or...

16 CFR 1115.11 - Imputed knowledge.

Code of Federal Regulations, 2010 CFR

2010-01-01

... care to ascertain the truth of complaints or other representations. This includes the knowledge a firm... 16 Commercial Practices 2 2010-01-01 2010-01-01 false Imputed knowledge. 1115.11 Section 1115.11... PRODUCT HAZARD REPORTS General Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether or...

16 CFR 1115.11 - Imputed knowledge.

Code of Federal Regulations, 2011 CFR

2011-01-01

... care to ascertain the truth of complaints or other representations. This includes the knowledge a firm... 16 Commercial Practices 2 2011-01-01 2011-01-01 false Imputed knowledge. 1115.11 Section 1115.11... PRODUCT HAZARD REPORTS General Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether or...

16 CFR 1115.11 - Imputed knowledge.

Code of Federal Regulations, 2012 CFR

2012-01-01

... care to ascertain the truth of complaints or other representations. This includes the knowledge a firm... 16 Commercial Practices 2 2012-01-01 2012-01-01 false Imputed knowledge. 1115.11 Section 1115.11... PRODUCT HAZARD REPORTS General Interpretation § 1115.11 Imputed knowledge. (a) In evaluating whether or...

Digital Learning Characteristics and Principles of Information Resources Knowledge Structuring

ERIC Educational Resources Information Center

Belichenko, Margarita; Davidovitch, Nitza; Kravchenko, Yuri

2017-01-01

Analysis of principles knowledge representation in information systems led to the necessity of improving the structuring knowledge. It is caused by the development of software component and new possibilities of information technologies. The article combines methodological aspects of structuring knowledge and effective usage of information…

Supporting Problem-Solving Performance Through the Construction of Knowledge Maps

ERIC Educational Resources Information Center

Lee, Youngmin; Baylor, Amy L.; Nelson, David W.

2005-01-01

The purpose of this article is to provide five empirically-derived guidelines for knowledge map construction tools that facilitate problem solving. First, the combinational representation principle proposes that conceptual and corresponding procedural knowledge should be represented together (rather than separately) within the knowledge map.…

Domain knowledge patterns in pedagogical diagnostics

NASA Astrophysics Data System (ADS)

Miarka, Rostislav

2017-07-01

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

Multi-representation ability of students on the problem solving physics

NASA Astrophysics Data System (ADS)

Theasy, Y.; Wiyanto; Sujarwata

2018-03-01

Accuracy in representing knowledge possessed by students will show how the level of student understanding. The multi-representation ability of students on the problem solving of physics has been done through qualitative method of grounded theory model and implemented on physics education student of Unnes academic year 2016/2017. Multiforms of representation used are verbal (V), images/diagrams (D), graph (G), and mathematically (M). High and low category students have an accurate use of graphical representation (G) of 83% and 77.78%, and medium category has accurate use of image representation (D) equal to 66%.

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

PubMed

Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

2017-08-10

Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

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.

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)

Assessing the Benefits of U.S. Customs and Border Protection Regulatory Actions to Reduce Terrorism Risks

DTIC Science & Technology

2012-01-01

conceptual, mathematical , etc.  More formally, models are approximations, representations, or idealizations of selected aspects of the structure...essential – Actuarial estimates inadequate – limited data, great heterogeneity over time & location, conditions change so present & future may not be

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.

Secure base representations in middle childhood across two Western cultures: Associations with parental attachment representations and maternal reports of behavior problems.

PubMed

Waters, Theodore E A; Bosmans, Guy; Vandevivere, Eva; Dujardin, Adinda; Waters, Harriet S

2015-08-01

Recent work examining the content and organization of attachment representations suggests that 1 way in which we represent the attachment relationship is in the form of a cognitive script. This work has largely focused on early childhood or adolescence/adulthood, leaving a large gap in our understanding of script-like attachment representations in the middle childhood period. We present 2 studies and provide 3 critical pieces of evidence regarding the presence of a script-like representation of the attachment relationship in middle childhood. We present evidence that a middle childhood attachment script assessment tapped a stable underlying script using samples drawn from 2 western cultures, the United States (Study 1) and Belgium (Study 2). We also found evidence suggestive of the intergenerational transmission of secure base script knowledge (Study 1) and relations between secure base script knowledge and symptoms of psychopathology in middle childhood (Study 2). The results from this investigation represent an important downward extension of the secure base script construct. (c) 2015 APA, all rights reserved).

Secure Base Representations in Middle Childhood Across Two Western Cultures: Associations with Parental Attachment Representations and Maternal Reports of Behavior Problems

PubMed Central

Waters, Theodore E. A.; Bosmans, Guy; Vandevivere, Eva; Dujardin, Adinda; Waters, Harriet S.

2015-01-01

Recent work examining the content and organization of attachment representations suggests that one way in which we represent the attachment relationship is in the form of a cognitive script. That said, this work has largely focused on early childhood or adolescence/adulthood, leaving a large gap in our understanding of script-like attachment representations in the middle childhood period. We present two studies and provide three critical pieces of evidence regarding the presence of a script-like representation of the attachment relationship in middle childhood. We present evidence that a middle childhood attachment script assessment tapped a stable underlying script using samples drawn from two western cultures, the United States (Study 1) and Belgium (Study 2). We also found evidence suggestive of the intergenerational transmission of secure base script knowledge (Study 1) and relations between secure base script knowledge and symptoms of psychopathology in middle childhood (Study 2). The results from this investigation represent an important downward extension of the secure base script construct. PMID:26147774

Social representations of memory and gender in later medieval England.

PubMed

Kane, Bronach

2012-12-01

Social representations in later medieval culture have attracted little attention amongst psychologists, pre-dating the development of the so-called 'public sphere' in the eighteenth century. In addition, the association of pre-modern societies with 'traditional' modes of communication in social psychology places implicit limits on areas that may be studied through the lens of social representation theory. This article analyses the way in which knowledge circulated in late medieval society, noting initially the plural nature of representations of events and marginal groups, and the myriad channels through which beliefs were consolidated. In later medieval England perceptions of the past depended on collective and group memory, with customary rights and local histories forged through 'common knowledge', hearsay and the opinions of 'trustworthy men' of the village. The final section of this commentary provides an analysis of testimony from the late medieval church courts, in which witnesses articulated gender ideologies that reflected perceptions drawn from everyday life. Social representations of women were thus deployed in ecclesiastical suits, on the one hand supporting evidence of female witnesses and on the other justifying misogynistic stereotypes of women's behaviour.

XML-based approaches for the integration of heterogeneous bio-molecular data.

PubMed

Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

2009-10-15

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

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.

Metaphores et representations du cerveau plurilingue: conceptions naives ou construction du savior? Exemples dans le contexte d'enseignement andorran (Metaphors and Representations of the Multilingual Brain: Naive Conceptions or Knowledge Construction? Examples in the Context of Andorran Education).

ERIC Educational Resources Information Center

Larruy, Martine Marquillo

2000-01-01

This article concentrates on the use of metaphors characterizing a multilingual brain in a corpus of oral interactions drawn from the Andorran part of an international research study. First, the situation and the status of metaphors in fields connected to the elaboration of knowledge is questioned. Next, the most important metaphors associated to…

Expert systems and simulation models; Proceedings of the Seminar, Tucson, AZ, November 18, 19, 1985

NASA Technical Reports Server (NTRS)

1986-01-01

The seminar presents papers on modeling and simulation methodology, artificial intelligence and expert systems, environments for simulation/expert system development, and methodology for simulation/expert system development. Particular attention is given to simulation modeling concepts and their representation, modular hierarchical model specification, knowledge representation, and rule-based diagnostic expert system development. Other topics include the combination of symbolic and discrete event simulation, real time inferencing, and the management of large knowledge-based simulation projects.

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

The Role of Visual Representations in Scientific Practices: From Conceptual Understanding and Knowledge Generation to 'Seeing' How Science Works

ERIC Educational Resources Information Center

Evagorou, Maria; Erduran, Sibel; Mäntylä, Terhi

2015-01-01

Background: The use of visual representations (i.e., photographs, diagrams, models) has been part of science, and their use makes it possible for scientists to interact with and represent complex phenomena, not observable in other ways. Despite a wealth of research in science education on visual representations, the emphasis of such research has…

Reimagining Game Design: Exploring the Design of Constructible Authentic Representations for Science Reasoning

NASA Astrophysics Data System (ADS)

Holbert, Nathan Ryan

Video games have recently become a popular space for educational design due to their interactive and engaging nature and the ubiquity of the gaming experience among youth. Though many researchers argue video games can provide opportunities for learning, educational game design has focused on the classroom rather than the informal settings where games are typically played. Educational games have been moderately successful at achieving learning gains on standardized items, but have failed to show improvements on related but distal problems. In this dissertation I develop and assess a new design principle, called constructible authentic representations for creating informal gaming experiences that players will actively draw on when reasoning in formal and real world contexts. These games provide players with opportunities to engage in meaningful construction with components that integrate relevant concepts to create in-game representations that visually and epistemologically align with related tools and representations utilized in the target domain. In the first phase of the dissertation, I observed children playing popular video games to better understand what in-game representations children attend to and how interactions with these representations contribute to intuitive ideas of encountered STEM content. Results from this study fed into the iterative design of two prototype video games, FormulaT Racing and Particles!, intending to give players useful knowledge resources for reasoning about kinematics and the particulate nature of matter respectively. Designed games encourage players to utilize and refine intuitive ideas about target content through the construction of domain relevant representations. To assess the effectiveness of these designs I conducted two studies of children ages 7-14 playing prototype games in informal settings. An analysis of pre- and post-game clinical interviews, domain specific tasks, and video and logging data of gameplay suggests players developed useful knowledge resources, likely gained and/or refined from experiences in-game, that are employed to solve non-game problems and tasks. Furthermore, players utilized in-game representations as objects-to-think-with when explaining real world phenomena and formal concepts. The results suggest that games designed to include constructible authentic representations can provide players with powerful and useful knowledge resources accessible when thinking and reasoning in a variety of contexts.

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.

PubMed

Katić, Darko; Julliard, Chantal; Wekerle, Anna-Laura; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie; Jannin, Pierre; Gibaud, Bernard

2015-09-01

The rise of intraoperative information threatens to outpace our abilities to process it. Context-aware systems, filtering information to automatically adapt to the current needs of the surgeon, are necessary to fully profit from computerized surgery. To attain context awareness, representation of medical knowledge is crucial. However, most existing systems do not represent knowledge in a reusable way, hindering also reuse of data. Our purpose is therefore to make our computational models of medical knowledge sharable, extensible and interoperational with established knowledge representations in the form of the LapOntoSPM ontology. To show its usefulness, we apply it to situation interpretation, i.e., the recognition of surgical phases based on surgical activities. Considering best practices in ontology engineering and building on our ontology for laparoscopy, we formalized the workflow of laparoscopic adrenalectomies, cholecystectomies and pancreatic resections in the framework of OntoSPM, a new standard for surgical process models. Furthermore, we provide a rule-based situation interpretation algorithm based on SQWRL to recognize surgical phases using the ontology. The system was evaluated on ground-truth data from 19 manually annotated surgeries. The aim was to show that the phase recognition capabilities are equal to a specialized solution. The recognition rates of the new system were equal to the specialized one. However, the time needed to interpret a situation rose from 0.5 to 1.8 s on average which is still viable for practical application. We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data representation in the field on context awareness and thus toward unified benchmark data sets.

16 CFR § 1115.11 - Imputed knowledge.

Code of Federal Regulations, 2013 CFR

2013-01-01

... due care to ascertain the truth of complaints or other representations. This includes the knowledge a... 16 Commercial Practices 2 2013-01-01 2013-01-01 false Imputed knowledge. § 1115.11 Section Â... SUBSTANTIAL PRODUCT HAZARD REPORTS General Interpretation § 1115.11 Imputed knowledge. (a) In evaluating...

Measuring Learning in Serious Games: A Case Study with Structural Assessment

ERIC Educational Resources Information Center

Wouters, Pieter; van der Spek, Erik D.; van Oostendorp, Herre

2011-01-01

The effectiveness of serious games is often measured with verbal assessment. As an alternative we propose Pathfinder structural assessment (defined as measuring the learners' knowledge organization and compare this with a referent structure) which comprises three steps: knowledge elicitation, knowledge representation and knowledge evaluation. We…

Geological modeling of submeter scale heterogeneity and its influence on tracer transport in a fluvial aquifer

NASA Astrophysics Data System (ADS)

Ronayne, Michael J.; Gorelick, Steven M.; Zheng, Chunmiao

2010-10-01

We developed a new model of aquifer heterogeneity to analyze data from a single-well injection-withdrawal tracer test conducted at the Macrodispersion Experiment (MADE) site on the Columbus Air Force Base in Mississippi (USA). The physical heterogeneity model is a hybrid that combines 3-D lithofacies to represent submeter scale, highly connected channels within a background matrix based on a correlated multivariate Gaussian hydraulic conductivity field. The modeled aquifer architecture is informed by a variety of field data, including geologic core sampling. Geostatistical properties of this hybrid heterogeneity model are consistent with the statistics of the hydraulic conductivity data set based on extensive borehole flowmeter testing at the MADE site. The representation of detailed, small-scale geologic heterogeneity allows for explicit simulation of local preferential flow and slow advection, processes that explain the complex tracer response from the injection-withdrawal test. Based on the new heterogeneity model, advective-dispersive transport reproduces key characteristics of the observed tracer recovery curve, including a delayed concentration peak and a low-concentration tail. Importantly, our results suggest that intrafacies heterogeneity is responsible for local-scale mass transfer.

Use of paired simple and complex models to reduce predictive bias and quantify uncertainty

NASA Astrophysics Data System (ADS)

Doherty, John; Christensen, Steen

2011-12-01

Modern environmental management and decision-making is based on the use of increasingly complex numerical models. Such models have the advantage of allowing representation of complex processes and heterogeneous system property distributions inasmuch as these are understood at any particular study site. The latter are often represented stochastically, this reflecting knowledge of the character of system heterogeneity at the same time as it reflects a lack of knowledge of its spatial details. Unfortunately, however, complex models are often difficult to calibrate because of their long run times and sometimes questionable numerical stability. Analysis of predictive uncertainty is also a difficult undertaking when using models such as these. Such analysis must reflect a lack of knowledge of spatial hydraulic property details. At the same time, it must be subject to constraints on the spatial variability of these details born of the necessity for model outputs to replicate observations of historical system behavior. In contrast, the rapid run times and general numerical reliability of simple models often promulgates good calibration and ready implementation of sophisticated methods of calibration-constrained uncertainty analysis. Unfortunately, however, many system and process details on which uncertainty may depend are, by design, omitted from simple models. This can lead to underestimation of the uncertainty associated with many predictions of management interest. The present paper proposes a methodology that attempts to overcome the problems associated with complex models on the one hand and simple models on the other hand, while allowing access to the benefits each of them offers. It provides a theoretical analysis of the simplification process from a subspace point of view, this yielding insights into the costs of model simplification, and into how some of these costs may be reduced. It then describes a methodology for paired model usage through which predictive bias of a simplified model can be detected and corrected, and postcalibration predictive uncertainty can be quantified. The methodology is demonstrated using a synthetic example based on groundwater modeling environments commonly encountered in northern Europe and North America.

31 CFR 10.37 - Requirements for written advice.

Code of Federal Regulations, 2014 CFR

2014-07-01

...' professional knowledge on Federal tax matters are not considered written advice on a Federal tax matter for... representations, statements, findings, or agreements (including projections, financial forecasts, or appraisals... on representations, statements, findings, or agreements is unreasonable if the practitioner knows or...

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…

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.

Representing sentence information

NASA Astrophysics Data System (ADS)

Perkins, Walton A., III

1991-03-01

This paper describes a computer-oriented representation for sentence information. Whereas many Artificial Intelligence (AI) natural language systems start with a syntactic parse of a sentence into the linguist's components: noun, verb, adjective, preposition, etc., we argue that it is better to parse the input sentence into 'meaning' components: attribute, attribute value, object class, object instance, and relation. AI systems need a representation that will allow rapid storage and retrieval of information and convenient reasoning with that information. The attribute-of-object representation has proven useful for handling information in relational databases (which are well known for their efficiency in storage and retrieval) and for reasoning in knowledge- based systems. On the other hand, the linguist's syntactic representation of the works in sentences has not been shown to be useful for information handling and reasoning. We think it is an unnecessary and misleading intermediate form. Our sentence representation is semantic based in terms of attribute, attribute value, object class, object instance, and relation. Every sentence is segmented into one or more components with the form: 'attribute' of 'object' 'relation' 'attribute value'. Using only one format for all information gives the system simplicity and good performance as a RISC architecture does for hardware. The attribute-of-object representation is not new; it is used extensively in relational databases and knowledge-based systems. However, we will show that it can be used as a meaning representation for natural language sentences with minor extensions. In this paper we describe how a computer system can parse English sentences into this representation and generate English sentences from this representation. Much of this has been tested with computer implementation.

Knowledge Representation and Management: a Linked Data Perspective.

PubMed

Barros, M; Couto, F M

2016-11-10

Biomedical research is increasingly becoming a data-intensive science in several areas, where prodigious amounts of data is being generated that has to be stored, integrated, shared and analyzed. In an effort to improve the accessibility of data and knowledge, the Linked Data initiative proposed a well-defined set of recommendations for exposing, sharing and integrating data, information and knowledge, using semantic web technologies. The main goal of this paper is to identify the current status and future trends of knowledge representation and management in Life and Health Sciences, mostly with regard to linked data technologies. We selected three prominent linked data studies, namely Bio2RDF, Open PHACTS and EBI RDF platform, and selected 14 studies published after 2014 (inclusive) that cited any of the three studies. We manually analyzed these 14 papers in relation to how they use linked data techniques. The analyses show a tendency to use linked data techniques in Life and Health Sciences, and even if some studies do not follow all of the recommendations, many of them already represent and manage their knowledge using RDF and biomedical ontologies. These insights from RDF and biomedical ontologies are having a strong impact on how knowledge is generated from biomedical data, by making data elements increasingly connected and by providing a better description of their semantics. As health institutes become more data centric, we believe that the adoption of linked data techniques will continue to grow and be an effective solution to knowledge representation and management.

Semantically-enabled Knowledge Discovery in the Deep Carbon Observatory

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.; Ma, X.; Erickson, J. S.; West, P.; Fox, P. A.

2013-12-01

The Deep Carbon Observatory (DCO) is a decadal effort aimed at transforming scientific and public understanding of carbon in the complex deep earth system from the perspectives of Deep Energy, Deep Life, Extreme Physics and Chemistry, and Reservoirs and Fluxes. Over the course of the decade DCO scientific activities will generate a massive volume of data across a variety of disciplines, presenting significant challenges in terms of data integration, management, analysis and visualization, and ultimately limiting the ability of scientists across disciplines to make insights and unlock new knowledge. The DCO Data Science Team (DCO-DS) is applying Semantic Web methodologies to construct a knowledge representation focused on the DCO Earth science disciplines, and use it together with other technologies (e.g. natural language processing and data mining) to create a more expressive representation of the distributed corpus of DCO artifacts including datasets, metadata, instruments, sensors, platforms, deployments, researchers, organizations, funding agencies, grants and various awards. The embodiment of this knowledge representation is the DCO Data Science Infrastructure, in which unique entities within the DCO domain and the relations between them are recognized and explicitly identified. The DCO-DS Infrastructure will serve as a platform for more efficient and reliable searching, discovery, access, and publication of information and knowledge for the DCO scientific community and beyond.

The Influence of Prior Knowledge on the Retrieval-Directed Function of Note Taking in Prior Knowledge Activation

ERIC Educational Resources Information Center

Wetzels, Sandra A. J.; Kester, Liesbeth; van Merrienboer, Jeroen J. G.; Broers, Nick J.

2011-01-01

Background: Prior knowledge activation facilitates learning. Note taking during prior knowledge activation (i.e., note taking directed at retrieving information from memory) might facilitate the activation process by enabling learners to build an external representation of their prior knowledge. However, taking notes might be less effective in…

Handling Heterogeneity in English Geography Textbooks 1850-2000

ERIC Educational Resources Information Center

Taylor, Liz

2017-01-01

Teaching demands engagement with a diverse world. When teaching about distant places, school textbooks commonly employ mediation devices of comparison, contrast and narratives of change. To what extent are such pedagogical strategies inherently othering? This question is addressed in the context of representations of Japan in English geography…

A global representation of vitamin D status in healthy populations

USDA-ARS?s Scientific Manuscript database

This paper provides an overview of vitamin D status in countries for which data were available, examines the existing heterogeneities in vitamin D status and identifies research gaps. A graphical illustration of global vitamin D status was developed based on a systematic review of the world wide lit...

Guidelines for Developing Habitat-Based Threatened and Endangered Species Population Goals on Army Installations

DTIC Science & Technology

2005-10-01

Many plants have both sexual and vegetative reproduction, and this may be best handled with separate classes that reflect meaningful differ- ences in... Transmutation and functional representation of heterogeneous landscapes.” Landscape Ecology 5: 239-253. LaGro, J.Jr. 1991. “Assessing patch

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.

Relating brain signal variability to knowledge representation.

PubMed

Heisz, Jennifer J; Shedden, Judith M; McIntosh, Anthony R

2012-11-15

We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. In Experiment 1, individuals with greater familiarity for a group of famous faces displayed more brain signal variability. In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

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.

19 CFR 10.704 - Declaration.

Code of Federal Regulations, 2012 CFR

2012-04-01

... document is true and accurate and I assume the responsibility for proving such representations. I... representations; The goods comply with all the requirements for preferential tariff treatment specified for those... responsible official of the importer or by the importer's authorized agent having knowledge of the relevant...

19 CFR 10.704 - Declaration.

Code of Federal Regulations, 2011 CFR

2011-04-01

... document is true and accurate and I assume the responsibility for proving such representations. I... representations; The goods comply with all the requirements for preferential tariff treatment specified for those... responsible official of the importer or by the importer's authorized agent having knowledge of the relevant...

19 CFR 10.704 - Declaration.

Code of Federal Regulations, 2014 CFR

2014-04-01

... document is true and accurate and I assume the responsibility for proving such representations. I... representations; The goods comply with all the requirements for preferential tariff treatment specified for those... responsible official of the importer or by the importer's authorized agent having knowledge of the relevant...

19 CFR 10.704 - Declaration.

Code of Federal Regulations, 2010 CFR

2010-04-01

... document is true and accurate and I assume the responsibility for proving such representations. I... representations; The goods comply with all the requirements for preferential tariff treatment specified for those... responsible official of the importer or by the importer's authorized agent having knowledge of the relevant...

Computable visually observed phenotype ontological framework for plants

PubMed Central

2011-01-01

Background The ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed. Results We have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a novel quantitative view of descriptions of plant phenotypes that leverages existing bio-ontologies and utilizes a computational approach to capture and represent domain knowledge in a machine-interpretable form. This is accomplished by means of a robust and accurate semantic mapping module that automatically maps high-level semantics to low-level measurements computed from phenotype imagery. The framework was applied to two different plant species with semantic rules mined and an ontology constructed. Rule quality was evaluated and showed high quality rules for most semantics. This framework also facilitates automatic annotation of phenotype images and can be adopted by different plant communities to aid in their research. Conclusions The Computable Visually Observed Phenotype Ontological Framework for plants has been developed for more efficient and accurate management of visually observed phenotypes, which play a significant role in plant genomics research. The uniqueness of this framework is its ability to bridge the knowledge of informaticians and plant science researchers by translating descriptions of visually observed phenotypes into standardized, machine-understandable representations, thus enabling the development of advanced information retrieval and phenotype annotation analysis tools for the plant science community. PMID:21702966

Context-Aware Local Binary Feature Learning for Face Recognition.

PubMed

Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2018-05-01

In this paper, we propose a context-aware local binary feature learning (CA-LBFL) method for face recognition. Unlike existing learning-based local face descriptors such as discriminant face descriptor (DFD) and compact binary face descriptor (CBFD) which learn each feature code individually, our CA-LBFL exploits the contextual information of adjacent bits by constraining the number of shifts from different binary bits, so that more robust information can be exploited for face representation. Given a face image, we first extract pixel difference vectors (PDV) in local patches, and learn a discriminative mapping in an unsupervised manner to project each pixel difference vector into a context-aware binary vector. Then, we perform clustering on the learned binary codes to construct a codebook, and extract a histogram feature for each face image with the learned codebook as the final representation. In order to exploit local information from different scales, we propose a context-aware local binary multi-scale feature learning (CA-LBMFL) method to jointly learn multiple projection matrices for face representation. To make the proposed methods applicable for heterogeneous face recognition, we present a coupled CA-LBFL (C-CA-LBFL) method and a coupled CA-LBMFL (C-CA-LBMFL) method to reduce the modality gap of corresponding heterogeneous faces in the feature level, respectively. Extensive experimental results on four widely used face datasets clearly show that our methods outperform most state-of-the-art face descriptors.

Representing Mutually Exclusive Knowledge in a Property Hierarchy for a Reasoning System in Clinical Gynecology

PubMed Central

Small, Steven L.; Muechler, Eberhard K.

1985-01-01

The education and practice of clinical medicine can benefit significantly from the use of computational assistants. This article describes the development of a prototype system called SURGES (Strong/University of Rochester Gynecological Expert System) for representing medical knowledge and then applying this knowledge to suggest diagnostic procedures in medical gynecology. The paper focuses on the representation technique of property inheritance, which facilitates the simple common sense reasoning required to enable execution of the more complex medical inferences. Such common sense can be viewed as a collection mundane inferences, which are the simple conclusions drawn from knowledge that an exclusive or (XOR) relation (i.e., mutual exclusion) holds among a number of facts. The paper discusses the use of a property hierarchy for this purpose and shows how it simplifies knowledge representation in medical artificial intelligence (AIM) computer systems.

37 CFR 10.24 - Disclosure of information to authorities.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., DEPARTMENT OF COMMERCE REPRESENTATION OF OTHERS BEFORE THE PATENT AND TRADEMARK OFFICE Patent and Trademark... practitioner possessing unprivileged knowledge of a violation of a Disciplinary Rule shall report such knowledge to the Director. (b) A practitioner possessing unprivileged knowledge or evidence concerning...

37 CFR 10.24 - Disclosure of information to authorities.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., DEPARTMENT OF COMMERCE REPRESENTATION OF OTHERS BEFORE THE PATENT AND TRADEMARK OFFICE Patent and Trademark... practitioner possessing unprivileged knowledge of a violation of a Disciplinary Rule shall report such knowledge to the Director. (b) A practitioner possessing unprivileged knowledge or evidence concerning...

Relational Knowledge in Higher Cognitive Processes.

ERIC Educational Resources Information Center

Halford, Graeme S.

Explicit representation of relations plays some role in virtually all higher cognitive processes, but relational knowledge has seldom been investigated systematically. This paper considers how relational knowledge is involved in some tasks that have been important to cognitive development, including transitivity, the balance scale, classification…

Medical Named Entity Recognition for Indonesian Language Using Word Representations

NASA Astrophysics Data System (ADS)

Rahman, Arief

2018-03-01

Nowadays, Named Entity Recognition (NER) system is used in medical texts to obtain important medical information, like diseases, symptoms, and drugs. While most NER systems are applied to formal medical texts, informal ones like those from social media (also called semi-formal texts) are starting to get recognition as a gold mine for medical information. We propose a theoretical Named Entity Recognition (NER) model for semi-formal medical texts in our medical knowledge management system by comparing two kinds of word representations: cluster-based word representation and distributed representation.

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.…

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.

Knowledge Transfer in Biology and Translation across External Representations: Experts' Views and Challenges for Learning

ERIC Educational Resources Information Center

Schonborn, Konrad J.; Bogeholz, Susanne

2009-01-01

Recent curriculum reform promotes core competencies such as desired "content knowledge" and "communication" for meaningful learning in biology. Understanding in biology is demonstrated when pupils can apply acquired knowledge to new tasks. This process requires the transfer of knowledge and the subordinate process of translation across external…

Development of the Neuron Assessment for Measuring Biology Students’ Use of Experimental Design Concepts and Representations

PubMed Central

Dasgupta, Annwesa P.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

Researchers, instructors, and funding bodies in biology education are unanimous about the importance of developing students’ competence in experimental design. Despite this, only limited measures are available for assessing such competence development, especially in the areas of molecular and cellular biology. Also, existing assessments do not measure how well students use standard symbolism to visualize biological experiments. We propose an assessment-design process that 1) provides background knowledge and questions for developers of new “experimentation assessments,” 2) elicits practices of representing experiments with conventional symbol systems, 3) determines how well the assessment reveals expert knowledge, and 4) determines how well the instrument exposes student knowledge and difficulties. To illustrate this process, we developed the Neuron Assessment and coded responses from a scientist and four undergraduate students using the Rubric for Experimental Design and the Concept-Reasoning Mode of representation (CRM) model. Some students demonstrated sound knowledge of concepts and representations. Other students demonstrated difficulty with depicting treatment and control group data or variability in experimental outcomes. Our process, which incorporates an authentic research situation that discriminates levels of visualization and experimentation abilities, shows potential for informing assessment design in other disciplines. PMID:27146159

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.

Public discourse on mental health and psychiatry: Representations in Swedish newspapers.

PubMed

Ohlsson, Robert

2018-05-01

Mass media plays a central role in shaping public discourse on health and illness. In order to examine media representations of mental health and expert knowledge in this field, two major Swedish daily newspapers from the year 2009 were qualitatively analysed. Drawing on the theory of social representations, the analysis focused on how issues concerning mental health and different perspectives are represented. The results show how the concept of mental illness is used in different and often taken-for-granted ways and how the distinction between normal and pathological is a central underlying question. Laypersons' perspectives are supplemented by views of professionals in the newspapers, where signs of confidence and dependence on expert knowledge are juxtaposed with critique and expressions of distrust. The newspaper discourse thus has salient argumentative features and the way that conflicts are made explicit and issues concerning authoritative knowledge are addressed indicates ambivalence towards the authoritative role of expert knowledge concerning mental health. In this way, the newspapers provide a complex epistemic context for everyday sense-making that can be assumed to have implications for relations between laypersons and professionals in the field of mental health.

Unified method of knowledge representation in the evolutionary artificial intelligence systems

NASA Astrophysics Data System (ADS)

Bykov, Nickolay M.; Bykova, Katherina N.

2003-03-01

The evolution of artificial intelligence systems called by complicating of their operation topics and science perfecting has resulted in a diversification of the methods both the algorithms of knowledge representation and usage in these systems. Often by this reason it is very difficult to design the effective methods of knowledge discovering and operation for such systems. In the given activity the authors offer a method of unitized representation of the systems knowledge about objects of an external world by rank transformation of their descriptions, made in the different features spaces: deterministic, probabilistic, fuzzy and other. The proof of a sufficiency of the information about the rank configuration of the object states in the features space for decision making is presented. It is shown that the geometrical and combinatorial model of the rank configurations set introduce their by group of some system of incidence, that allows to store the information on them in a convolute kind. The method of the rank configuration description by the DRP - code (distance rank preserving code) is offered. The problems of its completeness, information capacity, noise immunity and privacy are reviewed. It is shown, that the capacity of a transmission channel for such submission of the information is more than unit, as the code words contain the information both about the object states, and about the distance ranks between them. The effective algorithm of the data clustering for the object states identification, founded on the given code usage, is described. The knowledge representation with the help of the rank configurations allows to unitize and to simplify algorithms of the decision making by fulfillment of logic operations above the DRP - code words. Examples of the proposed clustering techniques operation on the given samples set, the rank configuration of resulted clusters and its DRP-codes are presented.

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.

COALA-System for Visual Representation of Cryptography Algorithms

ERIC Educational Resources Information Center

Stanisavljevic, Zarko; Stanisavljevic, Jelena; Vuletic, Pavle; Jovanovic, Zoran

2014-01-01

Educational software systems have an increasingly significant presence in engineering sciences. They aim to improve students' attitudes and knowledge acquisition typically through visual representation and simulation of complex algorithms and mechanisms or hardware systems that are often not available to the educational institutions. This paper…

Knowledge Acquisition from Structural Descriptions.

ERIC Educational Resources Information Center

Hayes-Roth, Frederick; McDermott, John

The learning machine described in this paper acquires concepts representable as conjunctive forms of the predicate calculus and behaviors representable as productions (antecedent-consequent pairs of such conjunctive forms): these concepts and behavior rules are inferred from sequentially presented pairs of examples by an algorithm that is probably…

Geophysical constraints on contaminant transport modeling in a heterogeneous fluvial aquifer.

PubMed

Bowling, Jerry C; Zheng, Chunmiao; Rodriguez, Antonio B; Harry, Dennis L

2006-05-05

Approximately 3000 measurements of hydraulic conductivity in over 50 flowmeter boreholes were available at the Macro-Dispersion Experiment (MADE) site in Columbus, Mississippi, USA to quantify the heterogeneity in hydraulic conductivity at the site scale. This high-density measurement approach is perhaps infeasible for time and expense in typical groundwater remediation sites. A natural-gradient tracer experiment from the MADE site was simulated by a groundwater flow and solute transport model incorporating direct-current (DC) resistivity data collected over the observed plume location. Hydraulic conductivity from one borehole collected during the original site characterization was used to calibrate the electrical resistivity data to hydraulic conductivity using a previously derived log-log relationship. Application of this relationship, using site-specific empirical constants determined from the data, transforms the 3D electrical resistivity data into a 3D description of hydraulic conductivity that can be used in groundwater models. The validity of this approach was tested by using the geophysically derived hydraulic conductivity representation in numerical simulations of the natural-gradient tracer experiment. The agreement between the simulated and observed tracer plumes was quantified to gauge the effectiveness of geophysically derived and flowmeter based representations of the hydraulic conductivity field. This study demonstrates that a highly heterogeneous aquifer can be modeled with minimal hydrological data supplemented with geophysical data at least as well as previous models of the site using purely hydrologic data.

Computer Aided Program Synthesis.

DTIC Science & Technology

1980-01-01

Representations 18 .2 Refinements and Reductions 18.:2.3 Dependenc ies 20 3.3 The Programming Knowledge Base 21 3.4 Linguistic Knowledge 22 3.5...strategy selection knowledge, i.e. knowledge representing a context sensitive discrimination among alternate methods; and knowledge of logical...program, each supplying his expertise. The client describes his task to the consultant and supplies answers and explanations to the consultant’s

Executable medical guidelines with Arden Syntax-Applications in dermatology and obstetrics.

PubMed

Seitinger, Alexander; Rappelsberger, Andrea; Leitich, Harald; Binder, Michael; Adlassnig, Klaus-Peter

2016-08-12

Clinical decision support systems (CDSSs) are being developed to assist physicians in processing extensive data and new knowledge based on recent scientific advances. Structured medical knowledge in the form of clinical alerts or reminder rules, decision trees or tables, clinical protocols or practice guidelines, score algorithms, and others, constitute the core of CDSSs. Several medical knowledge representation and guideline languages have been developed for the formal computerized definition of such knowledge. One of these languages is Arden Syntax for Medical Logic Systems, an International Health Level Seven (HL7) standard whose development started in 1989. Its latest version is 2.10, which was presented in 2014. In the present report we discuss Arden Syntax as a modern medical knowledge representation and processing language, and show that this language is not only well suited to define clinical alerts, reminders, and recommendations, but can also be used to implement and process computerized medical practice guidelines. This section describes how contemporary software such as Java, server software, web-services, XML, is used to implement CDSSs based on Arden Syntax. Special emphasis is given to clinical decision support (CDS) that employs practice guidelines as its clinical knowledge base. Two guideline-based applications using Arden Syntax for medical knowledge representation and processing were developed. The first is a software platform for implementing practice guidelines from dermatology. This application employs fuzzy set theory and logic to represent linguistic and propositional uncertainty in medical data, knowledge, and conclusions. The second application implements a reminder system based on clinically published standard operating procedures in obstetrics to prevent deviations from state-of-the-art care. A to-do list with necessary actions specifically tailored to the gestational week/labor/delivery is generated. Today, with the latest versions of Arden Syntax and the application of contemporary software development methods, Arden Syntax has become a powerful and versatile medical knowledge representation and processing language, well suited to implement a large range of CDSSs, including clinical-practice-guideline-based CDSSs. Moreover, such CDS is provided and can be shared as a service by different medical institutions, redefining the sharing of medical knowledge. Arden Syntax is also highly flexible and provides developers the freedom to use up-to-date software design and programming patterns for external patient data access. Copyright © 2016. Published by Elsevier B.V.

LookSeq: a browser-based viewer for deep sequencing data.

PubMed

Manske, Heinrich Magnus; Kwiatkowski, Dominic P

2009-11-01

Sequencing a genome to great depth can be highly informative about heterogeneity within an individual or a population. Here we address the problem of how to visualize the multiple layers of information contained in deep sequencing data. We propose an interactive AJAX-based web viewer for browsing large data sets of aligned sequence reads. By enabling seamless browsing and fast zooming, the LookSeq program assists the user to assimilate information at different levels of resolution, from an overview of a genomic region to fine details such as heterogeneity within the sample. A specific problem, particularly if the sample is heterogeneous, is how to depict information about structural variation. LookSeq provides a simple graphical representation of paired sequence reads that is more revealing about potential insertions and deletions than are conventional methods.

The Influence of Fisher Knowledge on the Susceptibility of Reef Fish Aggregations to Fishing

PubMed Central

Robinson, Jan; Cinner, Joshua E.; Graham, Nicholas A. J.

2014-01-01

Reef fishes that exhibit predictable aggregating behaviour are often considered vulnerable to overexploitation. However, fisher knowledge of this behaviour is often heterogeneous and, coupled with socioeconomic factors that constrain demand for or access to aggregated fish, will influence susceptibility to fishing. At two case study locations in Papua New Guinea, Ahus and Karkar islands, we conducted interview-based surveys to examine how local context influenced heterogeneity in knowledge of fish aggregations. We then explored the role of fisher knowledge in conferring susceptibility to fishing relative to socioeconomic drivers of fishing effort. Local heterogeneity in knowledge of aggregating behaviour differed between our case studies. At Ahus, variable access rights among fishers and genders to the main habitats were sources of heterogeneity in knowledge. By contrast, knowledge was more homogenous at Karkar and the sole source of variation was gear type. Differences between locations in the susceptibility of aggregations to fishing depended primarily on socioeconomic drivers of fishing effort rather than catchability. While Ahus fishers were knowledgeable of fish aggregations and used more selective gears, Karkar fishers were less constrained by tenure in their access to aggregation habitat. However, fishing effort was greater at Ahus and likely related to high dependency on fishing, greater access to provincial capital markets than Karkar and a weakening of customary management. Moreover, highly efficient fishing techniques have emerged at Ahus to exploit the non-reproductive aggregating behaviour of target species. Understanding how knowledge is structured within fishing communities and its relation to socioeconomic drivers of fishing effort is important if customary practices for conservation, such as tambu areas, are to be supported. The findings of this study call for a holistic approach to assessing the risks posed to reef fish aggregations by fishing, grounded in the principals of fisheries science and emerging social-ecological thinking. PMID:24646910

The influence of fisher knowledge on the susceptibility of reef fish aggregations to fishing.

PubMed

Robinson, Jan; Cinner, Joshua E; Graham, Nicholas A J

2014-01-01

Reef fishes that exhibit predictable aggregating behaviour are often considered vulnerable to overexploitation. However, fisher knowledge of this behaviour is often heterogeneous and, coupled with socioeconomic factors that constrain demand for or access to aggregated fish, will influence susceptibility to fishing. At two case study locations in Papua New Guinea, Ahus and Karkar islands, we conducted interview-based surveys to examine how local context influenced heterogeneity in knowledge of fish aggregations. We then explored the role of fisher knowledge in conferring susceptibility to fishing relative to socioeconomic drivers of fishing effort. Local heterogeneity in knowledge of aggregating behaviour differed between our case studies. At Ahus, variable access rights among fishers and genders to the main habitats were sources of heterogeneity in knowledge. By contrast, knowledge was more homogenous at Karkar and the sole source of variation was gear type. Differences between locations in the susceptibility of aggregations to fishing depended primarily on socioeconomic drivers of fishing effort rather than catchability. While Ahus fishers were knowledgeable of fish aggregations and used more selective gears, Karkar fishers were less constrained by tenure in their access to aggregation habitat. However, fishing effort was greater at Ahus and likely related to high dependency on fishing, greater access to provincial capital markets than Karkar and a weakening of customary management. Moreover, highly efficient fishing techniques have emerged at Ahus to exploit the non-reproductive aggregating behaviour of target species. Understanding how knowledge is structured within fishing communities and its relation to socioeconomic drivers of fishing effort is important if customary practices for conservation, such as tambu areas, are to be supported. The findings of this study call for a holistic approach to assessing the risks posed to reef fish aggregations by fishing, grounded in the principals of fisheries science and emerging social-ecological thinking.

The influence of textbooks on teachers' knowledge of chemical bonding representations relative to students' difficulties understanding

NASA Astrophysics Data System (ADS)

Bergqvist, Anna; Chang Rundgren, Shu-Nu

2017-04-01

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. However, several studies report that students have difficulties understanding models in general, and chemical bonding models in particular, and that students' difficulties understanding chemical bonding are partly due to the way it is taught by teachers and presented in textbooks.