Toward a Unified Theory of Visual Area V4

PubMed Central

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

2016-01-01

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

Mapping the Structure of Knowledge for Teaching Nominal Categorical Data Analysis

ERIC Educational Resources Information Center

Groth, Randall E.; Bergner, Jennifer A.

2013-01-01

This report describes a model for mapping cognitive structures related to content knowledge for teaching. The model consists of knowledge elements pertinent to teaching a content domain, the nature of the connections among them, and a means for representing the elements and connections visually. The model is illustrated through empirical data…

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

PubMed

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

2013-11-01

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

Visualizing the Topical Structure of the Medical Sciences: A Self-Organizing Map Approach

PubMed Central

Skupin, André; Biberstine, Joseph R.; Börner, Katy

2013-01-01

Background We implement a high-resolution visualization of the medical knowledge domain using the self-organizing map (SOM) method, based on a corpus of over two million publications. While self-organizing maps have been used for document visualization for some time, (1) little is known about how to deal with truly large document collections in conjunction with a large number of SOM neurons, (2) post-training geometric and semiotic transformations of the SOM tend to be limited, and (3) no user studies have been conducted with domain experts to validate the utility and readability of the resulting visualizations. Our study makes key contributions to all of these issues. Methodology Documents extracted from Medline and Scopus are analyzed on the basis of indexer-assigned MeSH terms. Initial dimensionality is reduced to include only the top 10% most frequent terms and the resulting document vectors are then used to train a large SOM consisting of over 75,000 neurons. The resulting two-dimensional model of the high-dimensional input space is then transformed into a large-format map by using geographic information system (GIS) techniques and cartographic design principles. This map is then annotated and evaluated by ten experts stemming from the biomedical and other domains. Conclusions Study results demonstrate that it is possible to transform a very large document corpus into a map that is visually engaging and conceptually stimulating to subject experts from both inside and outside of the particular knowledge domain. The challenges of dealing with a truly large corpus come to the fore and require embracing parallelization and use of supercomputing resources to solve otherwise intractable computational tasks. Among the envisaged future efforts are the creation of a highly interactive interface and the elaboration of the notion of this map of medicine acting as a base map, onto which other knowledge artifacts could be overlaid. PMID:23554924

Seeking Information with an Information Visualization System: A Study of Cognitive Styles

ERIC Educational Resources Information Center

Yuan, Xiaojun; Zhang, Xiangman; Chen, Chaomei; Avery, Joshua M.

2011-01-01

Introduction: This study investigated the effect of cognitive styles on users' information-seeking task performance using a knowledge domain information visualization system called CiteSpace. Method: Sixteen graduate students participated in a user experiment. Each completed an extended cognitive style analysis wholistic-analytic test (the…

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

PubMed

Scott, Ryan B; Dienes, Zoltan

2010-03-01

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

Knowledge Discovery in Chess Using an Aesthetics Approach

ERIC Educational Resources Information Center

Iqbal, Azlan

2012-01-01

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

The Relationship between Visual Metaphor Comprehension and Recognition of Similarities in Children with Learning Disabilities

ERIC Educational Resources Information Center

Mashal, Nira; Kasirer, Anat

2012-01-01

Previous studies have shown metaphoric comprehension deficits in children with learning disabilities. To understand metaphoric language, children must have enough semantic knowledge about the metaphorical terms and the ability to recognize similarity between two different domains. In the current study visual and verbal metaphor understanding was…

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

PubMed

Axelrod, Vadim

2016-08-01

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

Assimilative Domain Proficiency and Performance in Chemistry Coursework

ERIC Educational Resources Information Center

Byrnes, Scott William

2010-01-01

The assimilation and synthesis of knowledge is essential for students to be successful in chemistry, yet not all students synthesize knowledge as intended. The study used the Learning Preference Checklist to classify students into one of three learning modalities--visual, auditory, or kinesthetic (VAK). It also used the Kolb Learning Style…

Bridging Theory with Practice: An Exploratory Study of Visualization Use and Design for Climate Model Comparison

DOE PAGES

Dasgupta, Aritra; Poco, Jorge; Wei, Yaxing; ...

2015-03-16

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domainmore » experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.« less

Bridging Theory with Practice: An Exploratory Study of Visualization Use and Design for Climate Model Comparison

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

Dasgupta, Aritra; Poco, Jorge; Wei, Yaxing

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domainmore » experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.« less

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

PubMed

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

2015-09-01

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

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

DTIC Science & Technology

2006-08-01

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

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

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.

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.

Transfer learning for visual categorization: a survey.

PubMed

Shao, Ling; Zhu, Fan; Li, Xuelong

2015-05-01

Regular machine learning and data mining techniques study the training data for future inferences under a major assumption that the future data are within the same feature space or have the same distribution as the training data. However, due to the limited availability of human labeled training data, training data that stay in the same feature space or have the same distribution as the future data cannot be guaranteed to be sufficient enough to avoid the over-fitting problem. In real-world applications, apart from data in the target domain, related data in a different domain can also be included to expand the availability of our prior knowledge about the target future data. Transfer learning addresses such cross-domain learning problems by extracting useful information from data in a related domain and transferring them for being used in target tasks. In recent years, with transfer learning being applied to visual categorization, some typical problems, e.g., view divergence in action recognition tasks and concept drifting in image classification tasks, can be efficiently solved. In this paper, we survey state-of-the-art transfer learning algorithms in visual categorization applications, such as object recognition, image classification, and human action recognition.

Symbolic modeling of human anatomy for visualization and simulation

NASA Astrophysics Data System (ADS)

Pommert, Andreas; Schubert, Rainer; Riemer, Martin; Schiemann, Thomas; Tiede, Ulf; Hoehne, Karl H.

1994-09-01

Visualization of human anatomy in a 3D atlas requires both spatial and more abstract symbolic knowledge. Within our 'intelligent volume' model which integrates these two levels, we developed and implemented a semantic network model for describing human anatomy. Concepts for structuring (abstraction levels, domains, views, generic and case-specific modeling, inheritance) are introduced. Model, tools for generation and exploration and applications in our 3D anatomical atlas are presented and discussed.

Applying research to practice: generalist and specialist (visual ergonomics) consultancy.

PubMed

Long, Jennifer; Long, Airdrie

2012-01-01

Ergonomics is a holistic discipline encompassing a wide range of special interest groups. The role of an ergonomics consultant is to provide integrated solutions to improve comfort, safety and productivity. In Australia, there are two types of consultants--generalists and specialists. Both have training in ergonomics but specialist knowledge may be the result of previous education or work experience. This paper presents three projects illustrating generalist and specialist (visual ergonomics) consultancy: development of a vision screening protocol, solving visual discomfort in an office environment and solving postural discomfort in heavy industry. These case studies demonstrate how multiple ergonomics consultants may work together to solve ergonomics problems. It also describes some of the challenges for consultants, for those engaging their services and for the ergonomics profession, e.g. recognizing the boundaries of expertise, sharing information with business competitors, the costs-benefits of engaging multiple consultants and the risk of fragmentation of ergonomics knowledge and solutions. Since ergonomics problems are often multifaceted, ergonomics consultants should have a solid grounding in all domains of ergonomics, even if they ultimately only practice in one specialty or domain. This will benefit the profession and ensure that ergonomics remains a holistic discipline.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2018-06-26

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

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

PubMed Central

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

2014-01-01

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

The representation of conceptual knowledge: visual, auditory, and olfactory imagery compared with semantic processing.

PubMed

Palmiero, Massimiliano; Di Matteo, Rosalia; Belardinelli, Marta Olivetti

2014-05-01

Two experiments comparing imaginative processing in different modalities and semantic processing were carried out to investigate the issue of whether conceptual knowledge can be represented in different format. Participants were asked to judge the similarity between visual images, auditory images, and olfactory images in the imaginative block, if two items belonged to the same category in the semantic block. Items were verbally cued in both experiments. The degree of similarity between the imaginative and semantic items was changed across experiments. Experiment 1 showed that the semantic processing was faster than the visual and the auditory imaginative processing, whereas no differentiation was possible between the semantic processing and the olfactory imaginative processing. Experiment 2 revealed that only the visual imaginative processing could be differentiated from the semantic processing in terms of accuracy. These results showed that the visual and auditory imaginative processing can be differentiated from the semantic processing, although both visual and auditory images strongly rely on semantic representations. On the contrary, no differentiation is possible within the olfactory domain. Results are discussed in the frame of the imagery debate.

Knowledge Domain and Emerging Trends in Organic Photovoltaic Technology: A Scientometric Review Based on CiteSpace Analysis.

PubMed

Xiao, Fengjun; Li, Chengzhi; Sun, Jiangman; Zhang, Lianjie

2017-01-01

To study the rapid growth of research on organic photovoltaic (OPV) technology, development trends in the relevant research are analyzed based on CiteSpace software of text mining and visualization in scientific literature. By this analytical method, the outputs and cooperation of authors, the hot research topics, the vital references and the development trend of OPV are identified and visualized. Different from the traditional review articles by the experts on OPV, this work provides a new method of visualizing information about the development of the OPV technology research over the past decade quantitatively.

Knowledge Domain and Emerging trends in Organic Photovoltaic Technology: A Scientometric Review Based on CiteSpace Analysis

NASA Astrophysics Data System (ADS)

Xiao, Fengjun; Li, Chengzhi; Sun, Jiangman; Zhang, Lianjie

2017-09-01

To study the rapid growth of research on organic photovoltaic (OPV) technology, development trends in the relevant research are analyzed based on CiteSpace software of text mining and visualization in scientific literature. By this analytical method, the outputs and cooperation of authors, the hot research topics, the vital references and the development trend of OPV are identified and visualized. Different from the traditional review articles by the experts on OPV, this work provides a new method of visualizing information about the development of the OPV technology research over the past decade quantitatively.

Attention and Vigilance in Children with Down Syndrome

ERIC Educational Resources Information Center

Trezise, Kim L.; Gray, Kylie M.; Sheppard, Dianne M.

2008-01-01

Background: Down syndrome (DS) has been the focus of much cognitive and developmental research; however, there is a gap in knowledge regarding sustained attention, particularly across different sensory domains. This research examined the hypothesis that children with DS would demonstrate superior visual rather than auditory performance on a…

Imagery Teaches Elementary Economics Schema Efficiently.

ERIC Educational Resources Information Center

McKenzie, Gary R.

In a complex domain such as economics, elementary school students' knowledge of formal systems beyond their immediate experience is often too incomplete, superficial, and disorganized to function as schema or model. However, visual imagery is a good technique for teaching young children a network of 10 to 20 propositions and the relationships…

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

PubMed

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

2011-11-01

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

FuryExplorer: visual-interactive exploration of horse motion capture data

NASA Astrophysics Data System (ADS)

Wilhelm, Nils; Vögele, Anna; Zsoldos, Rebeka; Licka, Theresia; Krüger, Björn; Bernard, Jürgen

2015-01-01

The analysis of equine motion has a long tradition in the past of mankind. Equine biomechanics aims at detecting characteristics of horses indicative of good performance. Especially, veterinary medicine gait analysis plays an important role in diagnostics and in the emerging research of long-term effects of athletic exercises. More recently, the incorporation of motion capture technology contributed to an easier and faster analysis, with a trend from mere observation of horses towards the analysis of multivariate time-oriented data. However, due to the novelty of this topic being raised within an interdisciplinary context, there is yet a lack of visual-interactive interfaces to facilitate time series data analysis and information discourse for the veterinary and biomechanics communities. In this design study, we bring visual analytics technology into the respective domains, which, to our best knowledge, was never approached before. Based on requirements developed in the domain characterization phase, we present a visual-interactive system for the exploration of horse motion data. The system provides multiple views which enable domain experts to explore frequent poses and motions, but also to drill down to interesting subsets, possibly containing unexpected patterns. We show the applicability of the system in two exploratory use cases, one on the comparison of different gait motions, and one on the analysis of lameness recovery. Finally, we present the results of a summative user study conducted in the environment of the domain experts. The overall outcome was a significant improvement in effectiveness and efficiency in the analytical workflow of the domain experts.

MetaMapR: pathway independent metabolomic network analysis incorporating unknowns.

PubMed

Grapov, Dmitry; Wanichthanarak, Kwanjeera; Fiehn, Oliver

2015-08-15

Metabolic network mapping is a widely used approach for integration of metabolomic experimental results with biological domain knowledge. However, current approaches can be limited by biochemical domain or pathway knowledge which results in sparse disconnected graphs for real world metabolomic experiments. MetaMapR integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown. Network calculation is enhanced through an interface to the Chemical Translation System, which allows metabolite identifier translation between >200 common biochemical databases. Analysis results are presented as interactive visualizations or can be exported as high-quality graphics and numerical tables which can be imported into common network analysis and visualization tools. Freely available at http://dgrapov.github.io/MetaMapR/. Requires R and a modern web browser. Installation instructions, tutorials and application examples are available at http://dgrapov.github.io/MetaMapR/. ofiehn@ucdavis.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Visual analytics in cheminformatics: user-supervised descriptor selection for QSAR methods.

PubMed

Martínez, María Jimena; Ponzoni, Ignacio; Díaz, Mónica F; Vazquez, Gustavo E; Soto, Axel J

2015-01-01

The design of QSAR/QSPR models is a challenging problem, where the selection of the most relevant descriptors constitutes a key step of the process. Several feature selection methods that address this step are concentrated on statistical associations among descriptors and target properties, whereas the chemical knowledge is left out of the analysis. For this reason, the interpretability and generality of the QSAR/QSPR models obtained by these feature selection methods are drastically affected. Therefore, an approach for integrating domain expert's knowledge in the selection process is needed for increase the confidence in the final set of descriptors. In this paper a software tool, which we named Visual and Interactive DEscriptor ANalysis (VIDEAN), that combines statistical methods with interactive visualizations for choosing a set of descriptors for predicting a target property is proposed. Domain expertise can be added to the feature selection process by means of an interactive visual exploration of data, and aided by statistical tools and metrics based on information theory. Coordinated visual representations are presented for capturing different relationships and interactions among descriptors, target properties and candidate subsets of descriptors. The competencies of the proposed software were assessed through different scenarios. These scenarios reveal how an expert can use this tool to choose one subset of descriptors from a group of candidate subsets or how to modify existing descriptor subsets and even incorporate new descriptors according to his or her own knowledge of the target property. The reported experiences showed the suitability of our software for selecting sets of descriptors with low cardinality, high interpretability, low redundancy and high statistical performance in a visual exploratory way. Therefore, it is possible to conclude that the resulting tool allows the integration of a chemist's expertise in the descriptor selection process with a low cognitive effort in contrast with the alternative of using an ad-hoc manual analysis of the selected descriptors. Graphical abstractVIDEAN allows the visual analysis of candidate subsets of descriptors for QSAR/QSPR. In the two panels on the top, users can interactively explore numerical correlations as well as co-occurrences in the candidate subsets through two interactive graphs.

Rating knowledge sharing in cross-domain collaborative filtering.

PubMed

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

2015-05-01

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

Finding the Secret of Image Saliency in the Frequency Domain.

PubMed

Li, Jia; Duan, Ling-Yu; Chen, Xiaowu; Huang, Tiejun; Tian, Yonghong

2015-12-01

There are two sides to every story of visual saliency modeling in the frequency domain. On the one hand, image saliency can be effectively estimated by applying simple operations to the frequency spectrum. On the other hand, it is still unclear which part of the frequency spectrum contributes the most to popping-out targets and suppressing distractors. Toward this end, this paper tentatively explores the secret of image saliency in the frequency domain. From the results obtained in several qualitative and quantitative experiments, we find that the secret of visual saliency may mainly hide in the phases of intermediate frequencies. To explain this finding, we reinterpret the concept of discrete Fourier transform from the perspective of template-based contrast computation and thus develop several principles for designing the saliency detector in the frequency domain. Following these principles, we propose a novel approach to design the saliency detector under the assistance of prior knowledge obtained through both unsupervised and supervised learning processes. Experimental results on a public image benchmark show that the learned saliency detector outperforms 18 state-of-the-art approaches in predicting human fixations.

A Bayesian generative model for learning semantic hierarchies

PubMed Central

Mittelman, Roni; Sun, Min; Kuipers, Benjamin; Savarese, Silvio

2014-01-01

Building fine-grained visual recognition systems that are capable of recognizing tens of thousands of categories, has received much attention in recent years. The well known semantic hierarchical structure of categories and concepts, has been shown to provide a key prior which allows for optimal predictions. The hierarchical organization of various domains and concepts has been subject to extensive research, and led to the development of the WordNet domains hierarchy (Fellbaum, 1998), which was also used to organize the images in the ImageNet (Deng et al., 2009) dataset, in which the category count approaches the human capacity. Still, for the human visual system, the form of the hierarchy must be discovered with minimal use of supervision or innate knowledge. In this work, we propose a new Bayesian generative model for learning such domain hierarchies, based on semantic input. Our model is motivated by the super-subordinate organization of domain labels and concepts that characterizes WordNet, and accounts for several important challenges: maintaining context information when progressing deeper into the hierarchy, learning a coherent semantic concept for each node, and modeling uncertainty in the perception process. PMID:24904452

IMPAIRED VERBAL COMPREHENSION OF QUANTIFIERS IN CORTICOBASAL SYNDROME

PubMed Central

Troiani, Vanessa; Clark, Robin; Grossman, Murray

2011-01-01

Objective Patients with Corticobasal Syndrome (CBS) have atrophy in posterior parietal cortex. This region of atrophy has been previously linked with their quantifier comprehension difficulty, but previous studies used visual stimuli, making it difficult to account for potential visuospatial deficits in CBS patients. The current study evaluated comprehension of generalized quantifiers using strictly verbal materials. Method CBS patients, a brain-damaged control group (consisting of Alzheimer's Disease and frontotemporal dementia), and age-matched controls participated in this study. We assessed familiar temporal, spatial, and monetary domains of verbal knowledge comparatively. Judgment accuracy was only evaluated in statements for which patients demonstrated accurate factual knowledge about the target domain. Results We found that patients with CBS are significantly impaired in their ability to evaluate quantifiers compared to healthy seniors and a brain-damaged control group, even in this strictly visual task. This impairment was seen in the vast majority of individual CBS patients. Conclusions These findings offer additional evidence of quantifier impairment in CBS patients and emphasize that this impairment cannot be attributed to potential spatial processing impairments in patients with parietal disease. PMID:21381823

Associated impairment of the categories of conspecifics and biological entities: cognitive and neuroanatomical aspects of a new case.

PubMed

Capitani, Erminio; Chieppa, Francesca; Laiacona, Marcella

2010-05-01

Case A.C.A. presented an associated impairment of visual recognition and semantic knowledge for celebrities and biological objects. This case was relevant for (a) the neuroanatomical correlations, and (b) the relationship between visual recognition and semantics within the biological domain and the conspecifics domain. A.C.A. was not affected by anterior temporal damage. Her bilateral vascular lesions were localized on the medial and inferior temporal gyrus on the right and on the intermediate fusiform gyrus on the left, without concomitant lesions of the parahippocampal gyrus or posterior fusiform. Data analysis was based on a novel methodology developed to estimate the rate of stored items in the visual structural description system (SDS) or in the face recognition unit. For each biological object, no particular correlation was found between the visual information accessed through the semantic system and that tapped by the picture reality judgement. Findings are discussed with reference to whether a putative resource commonality is likely between biological objects and conspecifics, and whether or not either category may depend on an exclusive neural substrate.

Assimilative domain proficiency and performance in chemistry coursework

NASA Astrophysics Data System (ADS)

Byrnes, Scott William

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

Utilizing AI in Temporal, Spatial, and Resource Scheduling

NASA Technical Reports Server (NTRS)

Stottler, Richard; Kalton, Annaka; Bell, Aaron

2006-01-01

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

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

Learning Resources Organization Using Ontological Framework

NASA Astrophysics Data System (ADS)

Gavrilova, Tatiana; Gorovoy, Vladimir; Petrashen, Elena

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

[Working memory and work with memory: visual-spatial and further components of processing].

PubMed

Velichkovsky, B M; Challis, B H; Pomplun, M

1995-01-01

Empirical and theoretical evidence for the concept of working memory is considered. We argue that the major weakness of this concept is its loose connection with the knowledge about background perceptive and cognitive processes. Results of two relevant experiments are provided. The first study demonstrated the classical chunking effect in a speeded visual search and comparison task, the proper domain of a large-capacity very short term sensory store. Our second study was a kind of extended levels-of-processing experiment. We attempted to manipulate visual, phonological, and (different) executive components of long-term memory in the hope of finding some systematic relationships between these forms of processing. Indeed, the results demonstrated a high degree of systematicity without any apparent need for a concept such as working memory for the explanation. Accordingly, the place for working memory is at all the interfaces where our metacognitive strategies interfere with mostly domain-specific cognitive mechanisms. Working memory is simply our work with memory.

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

ERIC Educational Resources Information Center

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

2008-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

Pfaff, Matthias; Krcmar, Helmut

2018-03-01

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

Characterizing Provenance in Visualization and Data Analysis: An Organizational Framework of Provenance Types and Purposes.

PubMed

Ragan, Eric D; Endert, Alex; Sanyal, Jibonananda; Chen, Jian

2016-01-01

While the primary goal of visual analytics research is to improve the quality of insights and findings, a substantial amount of research in provenance has focused on the history of changes and advances throughout the analysis process. The term, provenance, has been used in a variety of ways to describe different types of records and histories related to visualization. The existing body of provenance research has grown to a point where the consolidation of design knowledge requires cross-referencing a variety of projects and studies spanning multiple domain areas. We present an organizational framework of the different types of provenance information and purposes for why they are desired in the field of visual analytics. Our organization is intended to serve as a framework to help researchers specify types of provenance and coordinate design knowledge across projects. We also discuss the relationships between these factors and the methods used to capture provenance information. In addition, our organization can be used to guide the selection of evaluation methodology and the comparison of study outcomes in provenance research.

Characterizing Provenance in Visualization and Data Analysis: An Organizational Framework of Provenance Types and Purposes

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

Ragan, Eric; Alex, Endert; Sanyal, Jibonananda

While the primary goal of visual analytics research is to improve the quality of insights and findings, a substantial amount of research in provenance has focused on the history of changes and advances throughout the analysis process. The term, provenance, has been used in a variety of ways to describe different types of records and histories related to visualization. The existing body of provenance research has grown to a point where the consolidation of design knowledge requires cross-referencing a variety of projects and studies spanning multiple domain areas. We present an organizational framework of the different types of provenance informationmore » and purposes for why they are desired in the field of visual analytics. Our organization is intended to serve as a framework to help researchers specify types of provenance and coordinate design knowledge across projects. We also discuss the relationships between these factors and the methods used to capture provenance information. In addition, our organization can be used to guide the selection of evaluation methodology and the comparison of study outcomes in provenance research« less

Characterizing Provenance in Visualization and Data Analysis: An Organizational Framework of Provenance Types and Purposes

DOE PAGES

Ragan, Eric; Alex, Endert; Sanyal, Jibonananda; ...

2016-01-01

While the primary goal of visual analytics research is to improve the quality of insights and findings, a substantial amount of research in provenance has focused on the history of changes and advances throughout the analysis process. The term, provenance, has been used in a variety of ways to describe different types of records and histories related to visualization. The existing body of provenance research has grown to a point where the consolidation of design knowledge requires cross-referencing a variety of projects and studies spanning multiple domain areas. We present an organizational framework of the different types of provenance informationmore » and purposes for why they are desired in the field of visual analytics. Our organization is intended to serve as a framework to help researchers specify types of provenance and coordinate design knowledge across projects. We also discuss the relationships between these factors and the methods used to capture provenance information. In addition, our organization can be used to guide the selection of evaluation methodology and the comparison of study outcomes in provenance research« less

An integrated measure of display clutter based on feature content, user knowledge and attention allocation factors.

PubMed

Pankok, Carl; Kaber, David B

2018-05-01

Existing measures of display clutter in the literature generally exhibit weak correlations with task performance, which limits their utility in safety-critical domains. A literature review led to formulation of an integrated display data- and user knowledge-driven measure of display clutter. A driving simulation experiment was conducted in which participants were asked to search 'high' and 'low' clutter displays for navigation information. Data-driven measures and subjective perceptions of clutter were collected along with patterns of visual attention allocation and driving performance responses during time periods in which participants searched the navigation display for information. The new integrated measure was more strongly correlated with driving performance than other, previously developed measures of clutter, particularly in the case of low-clutter displays. Integrating display data and user knowledge factors with patterns of visual attention allocation shows promise for measuring display clutter and correlation with task performance, particularly for low-clutter displays. Practitioner Summary: A novel measure of display clutter was formulated, accounting for display data content, user knowledge states and patterns of visual attention allocation. The measure was evaluated in terms of correlations with driver performance in a safety-critical driving simulation study. The measure exhibited stronger correlations with task performance than previously defined measures.

DisEpi: Compact Visualization as a Tool for Applied Epidemiological Research.

PubMed

Benis, Arriel; Hoshen, Moshe

2017-01-01

Outcomes research and evidence-based medical practice is being positively impacted by proliferation of healthcare databases. Modern epidemiologic studies require complex data comprehension. A new tool, DisEpi, facilitates visual exploration of epidemiological data supporting Public Health Knowledge Discovery. It provides domain-experts a compact visualization of information at the population level. In this study, DisEpi is applied to Attention-Deficit/Hyperactivity Disorder (ADHD) patients within Clalit Health Services, analyzing the socio-demographic and ADHD filled prescription data between 2006 and 2016 of 1,605,800 children aged 6 to 17 years. DisEpi's goals facilitate the identification of (1) Links between attributes and/or events, (2) Changes in these relationships over time, and (3) Clusters of population attributes for similar trends. DisEpi combines hierarchical clustering graphics and a heatmap where color shades reflect disease time-trends. In the ADHD context, DisEpi allowed the domain-expert to visually analyze a snapshot summary of data mining results. Accordingly, the domain-expert was able to efficiently identify that: (1) Relatively younger children and particularly youngest children in class are treated more often, (2) Medication incidence increased between 2006 and 2011 but then stabilized, and (3) Progression rates of medication incidence is different for each of the 3 main discovered clusters (aka: profiles) of treated children. DisEpi delivered results similar to those previously published which used classical statistical approaches. DisEpi requires minimal preparation and fewer iterations, generating results in a user-friendly format for the domain-expert. DisEpi will be wrapped as a package containing the end-to-end discovery process. Optionally, it may provide automated annotation using calendar events (such as policy changes or media interests), which can improve discovery efficiency, interpretation, and policy implementation.

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

PubMed

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

2015-01-01

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

Effects of VR system fidelity on analyzing isosurface visualization of volume datasets.

PubMed

Laha, Bireswar; Bowman, Doug A; Socha, John J

2014-04-01

Volume visualization is an important technique for analyzing datasets from a variety of different scientific domains. Volume data analysis is inherently difficult because volumes are three-dimensional, dense, and unfamiliar, requiring scientists to precisely control the viewpoint and to make precise spatial judgments. Researchers have proposed that more immersive (higher fidelity) VR systems might improve task performance with volume datasets, and significant results tied to different components of display fidelity have been reported. However, more information is needed to generalize these results to different task types, domains, and rendering styles. We visualized isosurfaces extracted from synchrotron microscopic computed tomography (SR-μCT) scans of beetles, in a CAVE-like display. We ran a controlled experiment evaluating the effects of three components of system fidelity (field of regard, stereoscopy, and head tracking) on a variety of abstract task categories that are applicable to various scientific domains, and also compared our results with those from our prior experiment using 3D texture-based rendering. We report many significant findings. For example, for search and spatial judgment tasks with isosurface visualization, a stereoscopic display provides better performance, but for tasks with 3D texture-based rendering, displays with higher field of regard were more effective, independent of the levels of the other display components. We also found that systems with high field of regard and head tracking improve performance in spatial judgment tasks. Our results extend existing knowledge and produce new guidelines for designing VR systems to improve the effectiveness of volume data analysis.

[Visualizing Research Lines in Public Health: An analysis Based on Bibliometric Maps Applied to the Revista Española de Salud Pública (2006-2015)].

PubMed

Gálvez, Carmen

2016-12-01

Identifying research lines is essential to understand the knowledge structure of a scientific domain. The aim of this study was to identify the main research topics of within the domain of public health, in the Revista Española de Saslud Pública during 2006-2015. Original articles included in the Social Sciences Citation Index (SSCI) database, available online through the Web of Science (WoS), were selected. The analysis units used were the keywords, KeyWords Plus (KW+), extracted automatically by SSCI. With KW+ obtained bibliometric, maps were created using a methodology based on the combination of co-word analysis, co-word analysis, clustering techniques and visualization techniques. We analyzed 512 documents, of which 176 KW+ were obtained with a frequency greater than or equal to 3. The results were bidimensional bibliometric maps with thematic groupings of KW+, representing the main research fronts: i) epidemiology, risk control programs disease and, in general, service organization and health policies; ii) infectious diseases, principally HIV; iii) a progressive increase in several lines interrelated with cardiovascular diseases (CVD); iv) a line multidimensional dedicated to different aspects associated to the quality of life related to health (HRQoL); and v) an emerging line linked to binge drinking. For the multidisciplinary and multidimensional nature of public health, the construction of bibliometric maps is an appropriate methodology to understand the knowledge structure of this scientific domain.

Webly-Supervised Fine-Grained Visual Categorization via Deep Domain Adaptation.

PubMed

Xu, Zhe; Huang, Shaoli; Zhang, Ya; Tao, Dacheng

2018-05-01

Learning visual representations from web data has recently attracted attention for object recognition. Previous studies have mainly focused on overcoming label noise and data bias and have shown promising results by learning directly from web data. However, we argue that it might be better to transfer knowledge from existing human labeling resources to improve performance at nearly no additional cost. In this paper, we propose a new semi-supervised method for learning via web data. Our method has the unique design of exploiting strong supervision, i.e., in addition to standard image-level labels, our method also utilizes detailed annotations including object bounding boxes and part landmarks. By transferring as much knowledge as possible from existing strongly supervised datasets to weakly supervised web images, our method can benefit from sophisticated object recognition algorithms and overcome several typical problems found in webly-supervised learning. We consider the problem of fine-grained visual categorization, in which existing training resources are scarce, as our main research objective. Comprehensive experimentation and extensive analysis demonstrate encouraging performance of the proposed approach, which, at the same time, delivers a new pipeline for fine-grained visual categorization that is likely to be highly effective for real-world applications.

Enhancing divergent thinking in visual arts education: Effects of explicit instruction of meta-cognition.

PubMed

van de Kamp, Marie-Thérèse; Admiraal, Wilfried; van Drie, Jannet; Rijlaarsdam, Gert

2015-03-01

The main purposes of visual arts education concern the enhancement of students' creative processes and the originality of their art products. Divergent thinking is crucial for finding original ideas in the initial phase of a creative process that aims to result in an original product. This study aims to examine the effects of explicit instruction of meta-cognition on students' divergent thinking. A quasi-experimental design was implemented with 147 secondary school students in visual arts education. In the experimental condition, students attended a series of regular lessons with assignments on art reception and production, and they attended one intervention lesson with explicit instruction of meta-cognition. In the control condition, students attended a series of regular lessons only. Pre-test and post-test instances tests measured fluency, flexibility, and originality as indicators of divergent thinking. Explicit instruction of meta-cognitive knowledge had a positive effect on fluency and flexibility, but not on originality. This study implies that in the domain of visual arts, instructional support in building up meta-cognitive knowledge about divergent thinking may improve students' creative processes. This study also discusses possible reasons for the demonstrated lack of effect for originality. © 2014 The British Psychological Society.

A Visual Analytics Approach to Structured Data Analysis to Enhance Nonproliferation and Arms Control Verification Activities

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

Gillen, David S.

Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in thismore » domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.« less

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

PubMed Central

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

2015-01-01

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

An optical color image watermarking scheme by using compressive sensing with human visual characteristics in gyrator domain

NASA Astrophysics Data System (ADS)

Liansheng, Sui; Bei, Zhou; Zhanmin, Wang; Ailing, Tian

2017-05-01

A novel optical color image watermarking scheme considering human visual characteristics is presented in gyrator transform domain. Initially, an appropriate reference image is constructed of significant blocks chosen from the grayscale host image by evaluating visual characteristics such as visual entropy and edge entropy. Three components of the color watermark image are compressed based on compressive sensing, and the corresponding results are combined to form the grayscale watermark. Then, the frequency coefficients of the watermark image are fused into the frequency data of the gyrator-transformed reference image. The fused result is inversely transformed and partitioned, and eventually the watermarked image is obtained by mapping the resultant blocks into their original positions. The scheme can reconstruct the watermark with high perceptual quality and has the enhanced security due to high sensitivity of the secret keys. Importantly, the scheme can be implemented easily under the framework of double random phase encoding with the 4f optical system. To the best of our knowledge, it is the first report on embedding the color watermark into the grayscale host image which will be out of attacker's expectation. Simulation results are given to verify the feasibility and its superior performance in terms of noise and occlusion robustness.

Mathematics skills in good readers with hydrocephalus.

PubMed

Barnes, Marcia A; Pengelly, Sarah; Dennis, Maureen; Wilkinson, Margaret; Rogers, Tracey; Faulkner, Heather

2002-01-01

Children with hydrocephalus have poor math skills. We investigated the nature of their arithmetic computation errors by comparing written subtraction errors in good readers with hydrocephalus, typically developing good readers of the same age, and younger children matched for math level to the children with hydrocephalus. Children with hydrocephalus made more procedural errors (although not more fact retrieval or visual-spatial errors) than age-matched controls; they made the same number of procedural errors as younger, math-level matched children. We also investigated a broad range of math abilities, and found that children with hydrocephalus performed more poorly than age-matched controls on tests of geometry and applied math skills such as estimation and problem solving. Computation deficits in children with hydrocephalus reflect delayed development of procedural knowledge. Problems in specific math domains such as geometry and applied math, were associated with deficits in constituent cognitive skills such as visual spatial competence, memory, and general knowledge.

Analytic Steering: Inserting Context into the Information Dialog

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

Bohn, Shawn J.; Calapristi, Augustin J.; Brown, Shyretha D.

2011-10-23

An analyst’s intrinsic domain knowledge is a primary asset in almost any analysis task. Unstructured text analysis systems that apply un-supervised content analysis approaches can be more effective if they can leverage this domain knowledge in a manner that augments the information discovery process without obfuscating new or unexpected content. Current unsupervised approaches rely upon the prowess of the analyst to submit the right queries or observe generalized document and term relationships from ranked or visual results. We propose a new approach which allows the user to control or steer the analytic view within the unsupervised space. This process ismore » controlled through the data characterization process via user supplied context in the form of a collection of key terms. We show that steering with an appropriate choice of key terms can provide better relevance to the analytic domain and still enable the analyst to uncover un-expected relationships; this paper discusses cases where various analytic steering approaches can provide enhanced analysis results and cases where analytic steering can have a negative impact on the analysis process.« less

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

NASA Astrophysics Data System (ADS)

Bodin, Madelen

2012-06-01

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

Diy Geospatial Web Service Chains: Geochaining Make it Easy

NASA Astrophysics Data System (ADS)

Wu, H.; You, L.; Gui, Z.

2011-08-01

It is a great challenge for beginners to create, deploy and utilize a Geospatial Web Service Chain (GWSC). People in Computer Science are usually not familiar with geospatial domain knowledge. Geospatial practitioners may lack the knowledge about web services and service chains. The end users may lack both. However, integrated visual editing interfaces, validation tools, and oneclick deployment wizards may help to lower the learning curve and improve modelling skills so beginners will have a better experience. GeoChaining is a GWSC modelling tool designed and developed based on these ideas. GeoChaining integrates visual editing, validation, deployment, execution etc. into a unified platform. By employing a Virtual Globe, users can intuitively visualize raw data and results produced by GeoChaining. All of these features allow users to easily start using GWSC, regardless of their professional background and computer skills. Further, GeoChaining supports GWSC model reuse, meaning that an entire GWSC model created or even a specific part can be directly reused in a new model. This greatly improves the efficiency of creating a new GWSC, and also contributes to the sharing and interoperability of GWSC.

Towards human-computer synergetic analysis of large-scale biological data.

PubMed

Singh, Rahul; Yang, Hui; Dalziel, Ben; Asarnow, Daniel; Murad, William; Foote, David; Gormley, Matthew; Stillman, Jonathan; Fisher, Susan

2013-01-01

Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself. In context of the aforementioned background, the results presented in this paper describe advancements along two methodological directions. First, given the context of biological data, we utilize and extend a design approach called experiential computing from multimedia information system design. This paradigm combines information visualization and human-computer interaction with algorithms for exploratory analysis of large-scale and complex data. In the proposed approach, emphasis is laid on: (1) allowing users to directly visualize, interact, experience, and explore the data through interoperable visualization-based and algorithmic components, (2) supporting unified query and presentation spaces to facilitate experimentation and exploration, (3) providing external contextual information by assimilating relevant supplementary data, and (4) encouraging user-directed information visualization, data exploration, and hypotheses formulation. Second, to illustrate the proposed design paradigm and measure its efficacy, we describe two prototype web applications. The first, called XMAS (Experiential Microarray Analysis System) is designed for analysis of time-series transcriptional data. The second system, called PSPACE (Protein Space Explorer) is designed for holistic analysis of structural and structure-function relationships using interactive low-dimensional maps of the protein structure space. Both these systems promote and facilitate human-computer synergy, where cognitive elements such as domain knowledge, contextual reasoning, and purpose-driven exploration, are integrated with a host of powerful algorithmic operations that support large-scale data analysis, multifaceted data visualization, and multi-source information integration. The proposed design philosophy, combines visualization, algorithmic components and cognitive expertise into a seamless processing-analysis-exploration framework that facilitates sense-making, exploration, and discovery. Using XMAS, we present case studies that analyze transcriptional data from two highly complex domains: gene expression in the placenta during human pregnancy and reaction of marine organisms to heat stress. With PSPACE, we demonstrate how complex structure-function relationships can be explored. These results demonstrate the novelty, advantages, and distinctions of the proposed paradigm. Furthermore, the results also highlight how domain insights can be combined with algorithms to discover meaningful knowledge and formulate evidence-based hypotheses during the data analysis process. Finally, user studies against comparable systems indicate that both XMAS and PSPACE deliver results with better interpretability while placing lower cognitive loads on the users. XMAS is available at: http://tintin.sfsu.edu:8080/xmas. PSPACE is available at: http://pspace.info/.

Towards human-computer synergetic analysis of large-scale biological data

PubMed Central

2013-01-01

Background Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself. Results In context of the aforementioned background, the results presented in this paper describe advancements along two methodological directions. First, given the context of biological data, we utilize and extend a design approach called experiential computing from multimedia information system design. This paradigm combines information visualization and human-computer interaction with algorithms for exploratory analysis of large-scale and complex data. In the proposed approach, emphasis is laid on: (1) allowing users to directly visualize, interact, experience, and explore the data through interoperable visualization-based and algorithmic components, (2) supporting unified query and presentation spaces to facilitate experimentation and exploration, (3) providing external contextual information by assimilating relevant supplementary data, and (4) encouraging user-directed information visualization, data exploration, and hypotheses formulation. Second, to illustrate the proposed design paradigm and measure its efficacy, we describe two prototype web applications. The first, called XMAS (Experiential Microarray Analysis System) is designed for analysis of time-series transcriptional data. The second system, called PSPACE (Protein Space Explorer) is designed for holistic analysis of structural and structure-function relationships using interactive low-dimensional maps of the protein structure space. Both these systems promote and facilitate human-computer synergy, where cognitive elements such as domain knowledge, contextual reasoning, and purpose-driven exploration, are integrated with a host of powerful algorithmic operations that support large-scale data analysis, multifaceted data visualization, and multi-source information integration. Conclusions The proposed design philosophy, combines visualization, algorithmic components and cognitive expertise into a seamless processing-analysis-exploration framework that facilitates sense-making, exploration, and discovery. Using XMAS, we present case studies that analyze transcriptional data from two highly complex domains: gene expression in the placenta during human pregnancy and reaction of marine organisms to heat stress. With PSPACE, we demonstrate how complex structure-function relationships can be explored. These results demonstrate the novelty, advantages, and distinctions of the proposed paradigm. Furthermore, the results also highlight how domain insights can be combined with algorithms to discover meaningful knowledge and formulate evidence-based hypotheses during the data analysis process. Finally, user studies against comparable systems indicate that both XMAS and PSPACE deliver results with better interpretability while placing lower cognitive loads on the users. XMAS is available at: http://tintin.sfsu.edu:8080/xmas. PSPACE is available at: http://pspace.info/. PMID:24267485

A design space of visualization tasks.

PubMed

Schulz, Hans-Jörg; Nocke, Thomas; Heitzler, Magnus; Schumann, Heidrun

2013-12-01

Knowledge about visualization tasks plays an important role in choosing or building suitable visual representations to pursue them. Yet, tasks are a multi-faceted concept and it is thus not surprising that the many existing task taxonomies and models all describe different aspects of tasks, depending on what these task descriptions aim to capture. This results in a clear need to bring these different aspects together under the common hood of a general design space of visualization tasks, which we propose in this paper. Our design space consists of five design dimensions that characterize the main aspects of tasks and that have so far been distributed across different task descriptions. We exemplify its concrete use by applying our design space in the domain of climate impact research. To this end, we propose interfaces to our design space for different user roles (developers, authors, and end users) that allow users of different levels of expertise to work with it.

Creating big data from small: using semantic web technology to facilitate the aggregation of diverse European contaminant data for regulatory assessments

NASA Astrophysics Data System (ADS)

Thomas, R.; Kokkinaki, A.; Lowry, R. K.

2016-12-01

The European Marine Strategy Framework Directive (MSFD) requires evidence-based reporting to assess the quality of European seas by member states to determine whether they are achieving Good Ecological Status by 2020. One descriptor addresses contaminants; fertilizers, pesticides, antifoulants, heavy metals, etc. There are large amounts of contaminant data available to support this process: >600000 data granules identified, ingested and made available from 303 organizations in 38 countries through the EU funded EMODNet Chemistry program, built on the SeaDataNet (SDN) infrastructure. However when marked up consistently with SDN vocabularies the number of unique parameters available is huge (>3000). While many parameters might superficially appear similar the concentrations reported cannot always be considered equivalent, particularly in sediment and biota. The planned regional-scale data products risked being limited to localized patterns. The strategy adopted to make meaningful aggregations for data product development was to capture the knowledge of domain experts about what could be considered equivalent and publish this knowledge as a thesaurus (or SKOS schema) through the NERC Vocabulary Server (NVS). Of the >3000 parameters identified, so far 1095 have been mapped to 222 aggregated terms. This "captured domain knowledge" has been used to harmonize the data granules into aggregated data collections. The publication of this knowledge through NVS allows transparency and reproducibility of the aggregation process. Gridded data products are derived from the data collection with visualizations available as products generated from the gridded data collections: currently 140 products available either as WFS visualization or netCDF file download. This approach shows how small data sets integrated into larger-scale products, some of which can be targeted at non-scientists, have much greater value than envisaged when the data were originally collected.

Perception, Cognition, and Effectiveness of Visualizations with Applications in Science and Engineering

NASA Astrophysics Data System (ADS)

Borkin, Michelle A.

Visualization is a powerful tool for data exploration and analysis. With data ever-increasing in quantity and becoming integrated into our daily lives, having effective visualizations is necessary. But how does one design an effective visualization? To answer this question we need to understand how humans perceive, process, and understand visualizations. Through visualization evaluation studies we can gain deeper insight into the basic perception and cognition theory of visualizations, both through domain-specific case studies as well as generalized laboratory experiments. This dissertation presents the results of four evaluation studies, each of which contributes new knowledge to the theory of perception and cognition of visualizations. The results of these studies include a deeper clearer understanding of how color, data representation dimensionality, spatial layout, and visual complexity affect a visualization's effectiveness, as well as how visualization types and visual attributes affect the memorability of a visualization. We first present the results of two domain-specific case study evaluations. The first study is in the field of biomedicine in which we developed a new heart disease diagnostic tool, and conducted a study to evaluate the effectiveness of 2D versus 3D data representations as well as color maps. In the second study, we developed a new visualization tool for filesystem provenance data with applications in computer science and the sciences more broadly. We additionally developed a new time-based hierarchical node grouping method. We then conducted a study to evaluate the effectiveness of the new tool with its radial layout versus the conventional node-link diagram, and the new node grouping method. Finally, we discuss the results of two generalized studies designed to understand what makes a visualization memorable. In the first evaluation we focused on visualization memorability and conducted an online study using Amazon's Mechanical Turk with hundreds of users and thousands of visualizations. For the second evaluation we designed an eye-tracking laboratory study to gain insight into precisely which elements of a visualization contribute to memorability as well as visualization recognition and recall.

UBioLab: a web-LABoratory for Ubiquitous in-silico experiments.

PubMed

Bartocci, E; Di Berardini, M R; Merelli, E; Vito, L

2012-03-01

The huge and dynamic amount of bioinformatic resources (e.g., data and tools) available nowadays in Internet represents a big challenge for biologists -for what concerns their management and visualization- and for bioinformaticians -for what concerns the possibility of rapidly creating and executing in-silico experiments involving resources and activities spread over the WWW hyperspace. Any framework aiming at integrating such resources as in a physical laboratory has imperatively to tackle -and possibly to handle in a transparent and uniform way- aspects concerning physical distribution, semantic heterogeneity, co-existence of different computational paradigms and, as a consequence, of different invocation interfaces (i.e., OGSA for Grid nodes, SOAP for Web Services, Java RMI for Java objects, etc.). The framework UBioLab has been just designed and developed as a prototype following the above objective. Several architectural features -as those ones of being fully Web-based and of combining domain ontologies, Semantic Web and workflow techniques- give evidence of an effort in such a direction. The integration of a semantic knowledge management system for distributed (bioinformatic) resources, a semantic-driven graphic environment for defining and monitoring ubiquitous workflows and an intelligent agent-based technology for their distributed execution allows UBioLab to be a semantic guide for bioinformaticians and biologists providing (i) a flexible environment for visualizing, organizing and inferring any (semantics and computational) "type" of domain knowledge (e.g., resources and activities, expressed in a declarative form), (ii) a powerful engine for defining and storing semantic-driven ubiquitous in-silico experiments on the domain hyperspace, as well as (iii) a transparent, automatic and distributed environment for correct experiment executions.

Groups: knowledge spreadsheets for symbolic biocomputing.

PubMed

Travers, Michael; Paley, Suzanne M; Shrager, Jeff; Holland, Timothy A; Karp, Peter D

2013-01-01

Knowledge spreadsheets (KSs) are a visual tool for interactive data analysis and exploration. They differ from traditional spreadsheets in that rather than being oriented toward numeric data, they work with symbolic knowledge representation structures and provide operations that take into account the semantics of the application domain. 'Groups' is an implementation of KSs within the Pathway Tools system. Groups allows Pathway Tools users to define a group of objects (e.g. groups of genes or metabolites) from a Pathway/Genome Database. Groups can be transformed (e.g. by transforming a metabolite group to the group of pathways in which those metabolites are substrates); combined through set operations; analysed (e.g. through enrichment analysis); and visualized (e.g. by painting onto a metabolic map diagram). Users of the Pathway Tools-based BioCyc.org website have made extensive use of Groups, and an informal survey of Groups users suggests that Groups has achieved the goal of allowing biologists themselves to perform some data manipulations that previously would have required the assistance of a programmer. Database URL: BioCyc.org.

Knowledge Interaction Design for Creative Knowledge Work

NASA Astrophysics Data System (ADS)

Nakakoji, Kumiyo; Yamamoto, Yasuhiro

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

Data Model Management for Space Information Systems

NASA Technical Reports Server (NTRS)

Hughes, J. Steven; Crichton, Daniel J.; Ramirez, Paul; Mattmann, chris

2006-01-01

The Reference Architecture for Space Information Management (RASIM) suggests the separation of the data model from software components to promote the development of flexible information management systems. RASIM allows the data model to evolve independently from the software components and results in a robust implementation that remains viable as the domain changes. However, the development and management of data models within RASIM are difficult and time consuming tasks involving the choice of a notation, the capture of the model, its validation for consistency, and the export of the model for implementation. Current limitations to this approach include the lack of ability to capture comprehensive domain knowledge, the loss of significant modeling information during implementation, the lack of model visualization and documentation capabilities, and exports being limited to one or two schema types. The advent of the Semantic Web and its demand for sophisticated data models has addressed this situation by providing a new level of data model management in the form of ontology tools. In this paper we describe the use of a representative ontology tool to capture and manage a data model for a space information system. The resulting ontology is implementation independent. Novel on-line visualization and documentation capabilities are available automatically, and the ability to export to various schemas can be added through tool plug-ins. In addition, the ingestion of data instances into the ontology allows validation of the ontology and results in a domain knowledge base. Semantic browsers are easily configured for the knowledge base. For example the export of the knowledge base to RDF/XML and RDFS/XML and the use of open source metadata browsers provide ready-made user interfaces that support both text- and facet-based search. This paper will present the Planetary Data System (PDS) data model as a use case and describe the import of the data model into an ontology tool. We will also describe the current effort to provide interoperability with the European Space Agency (ESA)/Planetary Science Archive (PSA) which is critically dependent on a common data model.

WIRM: An Open Source Toolkit for Building Biomedical Web Applications

PubMed Central

Jakobovits, Rex M.; Rosse, Cornelius; Brinkley, James F.

2002-01-01

This article describes an innovative software toolkit that allows the creation of web applications that facilitate the acquisition, integration, and dissemination of multimedia biomedical data over the web, thereby reducing the cost of knowledge sharing. There is a lack of high-level web application development tools suitable for use by researchers, clinicians, and educators who are not skilled programmers. Our Web Interfacing Repository Manager (WIRM) is a software toolkit that reduces the complexity of building custom biomedical web applications. WIRM’s visual modeling tools enable domain experts to describe the structure of their knowledge, from which WIRM automatically generates full-featured, customizable content management systems. PMID:12386108

LenVarDB: database of length-variant protein domains.

PubMed

Mutt, Eshita; Mathew, Oommen K; Sowdhamini, Ramanathan

2014-01-01

Protein domains are functionally and structurally independent modules, which add to the functional variety of proteins. This array of functional diversity has been enabled by evolutionary changes, such as amino acid substitutions or insertions or deletions, occurring in these protein domains. Length variations (indels) can introduce changes at structural, functional and interaction levels. LenVarDB (freely available at http://caps.ncbs.res.in/lenvardb/) traces these length variations, starting from structure-based sequence alignments in our Protein Alignments organized as Structural Superfamilies (PASS2) database, across 731 structural classification of proteins (SCOP)-based protein domain superfamilies connected to 2 730 625 sequence homologues. Alignment of sequence homologues corresponding to a structural domain is available, starting from a structure-based sequence alignment of the superfamily. Orientation of the length-variant (indel) regions in protein domains can be visualized by mapping them on the structure and on the alignment. Knowledge about location of length variations within protein domains and their visual representation will be useful in predicting changes within structurally or functionally relevant sites, which may ultimately regulate protein function. Non-technical summary: Evolutionary changes bring about natural changes to proteins that may be found in many organisms. Such changes could be reflected as amino acid substitutions or insertions-deletions (indels) in protein sequences. LenVarDB is a database that provides an early overview of observed length variations that were set among 731 protein families and after examining >2 million sequences. Indels are followed up to observe if they are close to the active site such that they can affect the activity of proteins. Inclusion of such information can aid the design of bioengineering experiments.

Open cyberGIS software for geospatial research and education in the big data era

NASA Astrophysics Data System (ADS)

Wang, Shaowen; Liu, Yan; Padmanabhan, Anand

CyberGIS represents an interdisciplinary field combining advanced cyberinfrastructure, geographic information science and systems (GIS), spatial analysis and modeling, and a number of geospatial domains to improve research productivity and enable scientific breakthroughs. It has emerged as new-generation GIS that enable unprecedented advances in data-driven knowledge discovery, visualization and visual analytics, and collaborative problem solving and decision-making. This paper describes three open software strategies-open access, source, and integration-to serve various research and education purposes of diverse geospatial communities. These strategies have been implemented in a leading-edge cyberGIS software environment through three corresponding software modalities: CyberGIS Gateway, Toolkit, and Middleware, and achieved broad and significant impacts.

Factors associated with visual acuity in patients with cystoid macular oedema and Retinitis Pigmentosa.

PubMed

Liew, Gerald; Moore, Anthony T; Bradley, Patrick D; Webster, Andrew R; Michaelides, Michel

2018-06-01

Retinitis pigmentosa is the most common inherited retinal dystrophy. The factors associated with visual acuity in patients with other retinal diseases are well known, but are poorly understood in patients with retinitis pigmentosa. This knowledge is useful for prognosis and to support secondary endpoints in clinical trials. We conducted a cross-sectional study of consecutive patients recruited from the inherited retinal disease service from January 2012 to December 2012. Central macular thickness (CMT) was measured using spectral domain optical coherence tomography. Data were available for 81 patients and 162 eyes. After multivariable analyses, older age, earlier age of onset of symptoms, and thicker CMT were associated with lower visual acuity. Gender and inheritance pattern were not associated with visual acuity. Each decade older age, younger age of onset, and thicker CMT was associated with 0.12, 0.10, and 0.11 worse logarithm of the minimal angle of resolution units of visual acuity, respectively (p < 0.05 for all). Age, age of onset, and CMT are associated with visual acuity and important factors to measure in studies of retinitis pigmentosa.

Visual management of large scale data mining projects.

PubMed

Shah, I; Hunter, L

2000-01-01

This paper describes a unified framework for visualizing the preparations for, and results of, hundreds of machine learning experiments. These experiments were designed to improve the accuracy of enzyme functional predictions from sequence, and in many cases were successful. Our system provides graphical user interfaces for defining and exploring training datasets and various representational alternatives, for inspecting the hypotheses induced by various types of learning algorithms, for visualizing the global results, and for inspecting in detail results for specific training sets (functions) and examples (proteins). The visualization tools serve as a navigational aid through a large amount of sequence data and induced knowledge. They provided significant help in understanding both the significance and the underlying biological explanations of our successes and failures. Using these visualizations it was possible to efficiently identify weaknesses of the modular sequence representations and induction algorithms which suggest better learning strategies. The context in which our data mining visualization toolkit was developed was the problem of accurately predicting enzyme function from protein sequence data. Previous work demonstrated that approximately 6% of enzyme protein sequences are likely to be assigned incorrect functions on the basis of sequence similarity alone. In order to test the hypothesis that more detailed sequence analysis using machine learning techniques and modular domain representations could address many of these failures, we designed a series of more than 250 experiments using information-theoretic decision tree induction and naive Bayesian learning on local sequence domain representations of problematic enzyme function classes. In more than half of these cases, our methods were able to perfectly discriminate among various possible functions of similar sequences. We developed and tested our visualization techniques on this application.

Voice-enabled Knowledge Engine using Flood Ontology and Natural Language Processing

NASA Astrophysics Data System (ADS)

Sermet, M. Y.; Demir, I.; Krajewski, W. F.

2015-12-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts, flood-related data, information and interactive visualizations for communities in Iowa. The IFIS is designed for use by general public, often people with no domain knowledge and limited general science background. To improve effective communication with such audience, we have introduced a voice-enabled knowledge engine on flood related issues in IFIS. Instead of navigating within many features and interfaces of the information system and web-based sources, the system provides dynamic computations based on a collection of built-in data, analysis, and methods. The IFIS Knowledge Engine connects to real-time stream gauges, in-house data sources, analysis and visualization tools to answer natural language questions. Our goal is the systematization of data and modeling results on flood related issues in Iowa, and to provide an interface for definitive answers to factual queries. The goal of the knowledge engine is to make all flood related knowledge in Iowa easily accessible to everyone, and support voice-enabled natural language input. We aim to integrate and curate all flood related data, implement analytical and visualization tools, and make it possible to compute answers from questions. The IFIS explicitly implements analytical methods and models, as algorithms, and curates all flood related data and resources so that all these resources are computable. The IFIS Knowledge Engine computes the answer by deriving it from its computational knowledge base. The knowledge engine processes the statement, access data warehouse, run complex database queries on the server-side and return outputs in various formats. This presentation provides an overview of IFIS Knowledge Engine, its unique information interface and functionality as an educational tool, and discusses the future plans for providing knowledge on flood related issues and resources. IFIS Knowledge Engine provides an alternative access method to these comprehensive set of tools and data resources available in IFIS. Current implementation of the system accepts free-form input and voice recognition capabilities within browser and mobile applications.

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

Knowledge-based public health situation awareness

NASA Astrophysics Data System (ADS)

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

2004-09-01

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

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

PubMed

Miles, James D; Proctor, Robert W

2009-10-01

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

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

PubMed

Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

2014-10-01

Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall correlation>0.4). Clustering results are largely improved based on our anchor concept method (accuracy>70% and mutual information>80%). Physicians' spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. Copyright © 2014 Elsevier B.V. All rights reserved.

KNODWAT: A scientific framework application for testing knowledge discovery methods for the biomedical domain

PubMed Central

2013-01-01

Background Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. Results A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. Conclusions The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework. PMID:23763826

KNODWAT: a scientific framework application for testing knowledge discovery methods for the biomedical domain.

PubMed

Holzinger, Andreas; Zupan, Mario

2013-06-13

Professionals in the biomedical domain are confronted with an increasing mass of data. Developing methods to assist professional end users in the field of Knowledge Discovery to identify, extract, visualize and understand useful information from these huge amounts of data is a huge challenge. However, there are so many diverse methods and methodologies available, that for biomedical researchers who are inexperienced in the use of even relatively popular knowledge discovery methods, it can be very difficult to select the most appropriate method for their particular research problem. A web application, called KNODWAT (KNOwledge Discovery With Advanced Techniques) has been developed, using Java on Spring framework 3.1. and following a user-centered approach. The software runs on Java 1.6 and above and requires a web server such as Apache Tomcat and a database server such as the MySQL Server. For frontend functionality and styling, Twitter Bootstrap was used as well as jQuery for interactive user interface operations. The framework presented is user-centric, highly extensible and flexible. Since it enables methods for testing using existing data to assess suitability and performance, it is especially suitable for inexperienced biomedical researchers, new to the field of knowledge discovery and data mining. For testing purposes two algorithms, CART and C4.5 were implemented using the WEKA data mining framework.

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.

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Analytical Judgment Using Visualizations

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

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

Scientists working in a particular domain often adhere to conventional data analysis and presentation methods and this leads to familiarity with these methods over time. But does high familiarity always lead to better analytical judgment? This question is especially relevant when visualizations are used in scientific tasks, as there can be discrepancies between visualization best practices and domain conventions. However, there is little empirical evidence of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their effect on scientific judgment. To address this gap and to study these factors, we focus on the climatemore » science domain, specifically on visualizations used for comparison of model performance. We present a comprehensive user study with 47 climate scientists where we explored the following factors: i) relationships between scientists’ familiarity, their perceived levels of com- fort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

PSQM-based RR and NR video quality metrics

NASA Astrophysics Data System (ADS)

Lu, Zhongkang; Lin, Weisi; Ong, Eeping; Yang, Xiaokang; Yao, Susu

2003-06-01

This paper presents a new and general concept, PQSM (Perceptual Quality Significance Map), to be used in measuring the visual distortion. It makes use of the selectivity characteristic of HVS (Human Visual System) that it pays more attention to certain area/regions of visual signal due to one or more of the following factors: salient features in image/video, cues from domain knowledge, and association of other media (e.g., speech or audio). PQSM is an array whose elements represent the relative perceptual-quality significance levels for the corresponding area/regions for images or video. Due to its generality, PQSM can be incorporated into any visual distortion metrics: to improve effectiveness or/and efficiency of perceptual metrics; or even to enhance a PSNR-based metric. A three-stage PQSM estimation method is also proposed in this paper, with an implementation of motion, texture, luminance, skin-color and face mapping. Experimental results show the scheme can improve the performance of current image/video distortion metrics.

Progress in high-level exploratory vision

NASA Astrophysics Data System (ADS)

Brand, Matthew

1993-08-01

We have been exploring the hypothesis that vision is an explanatory process, in which causal and functional reasoning about potential motion plays an intimate role in mediating the activity of low-level visual processes. In particular, we have explored two of the consequences of this view for the construction of purposeful vision systems: Causal and design knowledge can be used to (1) drive focus of attention, and (2) choose between ambiguous image interpretations. An important result of visual understanding is an explanation of the scene's causal structure: How action is originated, constrained, and prevented, and what will happen in the immediate future. In everyday visual experience, most action takes the form of motion, and most causal analysis takes the form of dynamical analysis. This is even true of static scenes, where much of a scene's interest lies in how possible motions are arrested. This paper describes our progress in developing domain theories and visual processes for the understanding of various kinds of structured scenes, including structures built out of children's constructive toys and simple mechanical devices.

Smart markers for watershed-based cell segmentation.

PubMed

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

2012-01-01

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

The Role of Teamwork in the Analysis of Big Data: A Study of Visual Analytics and Box Office Prediction.

PubMed

Buchanan, Verica; Lu, Yafeng; McNeese, Nathan; Steptoe, Michael; Maciejewski, Ross; Cooke, Nancy

2017-03-01

Historically, domains such as business intelligence would require a single analyst to engage with data, develop a model, answer operational questions, and predict future behaviors. However, as the problems and domains become more complex, organizations are employing teams of analysts to explore and model data to generate knowledge. Furthermore, given the rapid increase in data collection, organizations are struggling to develop practices for intelligence analysis in the era of big data. Currently, a variety of machine learning and data mining techniques are available to model data and to generate insights and predictions, and developments in the field of visual analytics have focused on how to effectively link data mining algorithms with interactive visuals to enable analysts to explore, understand, and interact with data and data models. Although studies have explored the role of single analysts in the visual analytics pipeline, little work has explored the role of teamwork and visual analytics in the analysis of big data. In this article, we present an experiment integrating statistical models, visual analytics techniques, and user experiments to study the role of teamwork in predictive analytics. We frame our experiment around the analysis of social media data for box office prediction problems and compare the prediction performance of teams, groups, and individuals. Our results indicate that a team's performance is mediated by the team's characteristics such as openness of individual members to others' positions and the type of planning that goes into the team's analysis. These findings have important implications for how organizations should create teams in order to make effective use of information from their analytic models.

Evaluating rehabilitation goals of visually impaired children in multidisciplinary care according to ICF-CY guidelines.

PubMed

Rainey, Linda; van Nispen, Ruth; van Rens, Ger

2014-11-01

To gain qualitative insight into the rehabilitation goals of visually impaired children and how these goals relate to the structure of the International Classification of Functioning, Disability and Health (ICF) and patient characteristics. A patient record study was conducted, analysing rehabilitation goals and characteristics of children with a suspected visual impairment in the Netherlands (<18 years) who applied for multidisciplinary services in 2012 (N = 289). Chi-square analyses for trend in rehabilitation content across age bands and additional analyses were performed. The three most common diagnoses were nystagmus (21.2%), cerebral visual impairment (16.2%) and albinism (6.1%). Rehabilitation goals for children aged <7 years were mostly aimed at 'physical (visual) functioning' (36.7%) and 'environmental factors' (36.7%). For children ≥7 years, significantly more goals were identified on activity and participation (A&P) domains (52.2%). Three A and P domains presented a significant linear trend on the number of rehabilitation goals across age bands: (1) 'Learning and applying knowledge' (13.042, p < 0.001), (4) 'Mobility' (31.340, p < 0.001) and (8) 'Major life areas' (5.925, p = 0.015). Regression analysis showed that both age and visual acuity significantly contributed to the number of A and P goals. Although analyses were based on a selection of patient records, the number and nature of rehabilitation goals differ significantly with age. Many A and P goals seem underrepresented at the intake procedure, for example: communication, peer interaction and participating in leisure activities. A systematic, standardized procedure is required to catalogue all existing goals and to be able to evaluate progress and potential new or other important goals. © 2013 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

ERIC Educational Resources Information Center

Tricot, André; Sweller, John

2014-01-01

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

Audiovisual perception in amblyopia: A review and synthesis.

PubMed

Richards, Michael D; Goltz, Herbert C; Wong, Agnes M F

2018-05-17

Amblyopia is a common developmental sensory disorder that has been extensively and systematically investigated as a unisensory visual impairment. However, its effects are increasingly recognized to extend beyond vision to the multisensory domain. Indeed, amblyopia is associated with altered cross-modal interactions in audiovisual temporal perception, audiovisual spatial perception, and audiovisual speech perception. Furthermore, although the visual impairment in amblyopia is typically unilateral, the multisensory abnormalities tend to persist even when viewing with both eyes. Knowledge of the extent and mechanisms of the audiovisual impairments in amblyopia, however, remains in its infancy. This work aims to review our current understanding of audiovisual processing and integration deficits in amblyopia, and considers the possible mechanisms underlying these abnormalities. Copyright © 2018. Published by Elsevier Ltd.

Ultra-high resolution spectral domain optical coherence tomography using supercontinuum light source

NASA Astrophysics Data System (ADS)

Lim, Yiheng; Yatagai, Toyohiko; Otani, Yukitoshi

2016-04-01

An ultra-high resolution spectral domain optical coherence tomography (SD-OCT) was developed using a cost-effective supercontinuum laser. A spectral filter consists of a dispersive prism, a cylindrical lens and a right-angle prism was built to transmit the wavelengths in range 680-940 nm to the OCT system. The SD-OCT has achieved 1.9 μm axial resolution and the sensitivity was estimated to be 91.5 dB. A zero-crossing fringes matching method which maps the wavelengths to the pixel indices of the spectrometer was proposed for the OCT spectral calibration. A double sided foam tape as a static sample and the tip of a middle finger as a biological sample were measured by the OCT. The adhesive and the internal structure of the foam of the tape were successfully visualized in three dimensions. Sweat ducts was clearly observed in the OCT images at very high resolution. To the best of our knowledge, this is the first demonstration of ultra-high resolution visualization of sweat duct by OCT.

Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT)

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

Williams, Dean N.

2011-07-20

This report summarizes work carried out by the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Team for the period of January 1, 2011 through June 30, 2011. It discusses highlights, overall progress, period goals, and collaborations and lists papers and presentations. To learn more about our project, please visit our UV-CDAT website (URL: http://uv-cdat.org). This report will be forwarded to the program manager for the Department of Energy (DOE) Office of Biological and Environmental Research (BER), national and international collaborators and stakeholders, and to researchers working on a wide range of other climate model, reanalysis, and observation evaluation activities. Themore » UV-CDAT executive committee consists of Dean N. Williams of Lawrence Livermore National Laboratory (LLNL); Dave Bader and Galen Shipman of Oak Ridge National Laboratory (ORNL); Phil Jones and James Ahrens of Los Alamos National Laboratory (LANL), Claudio Silva of Polytechnic Institute of New York University (NYU-Poly); and Berk Geveci of Kitware, Inc. The UV-CDAT team consists of researchers and scientists with diverse domain knowledge whose home institutions also include the National Aeronautics and Space Administration (NASA) and the University of Utah. All work is accomplished under DOE open-source guidelines and in close collaboration with the project's stakeholders, domain researchers, and scientists. Working directly with BER climate science analysis projects, this consortium will develop and deploy data and computational resources useful to a wide variety of stakeholders, including scientists, policymakers, and the general public. Members of this consortium already collaborate with other institutions and universities in researching data discovery, management, visualization, workflow analysis, and provenance. The UV-CDAT team will address the following high-level visualization requirements: (1) Alternative parallel streaming statistics and analysis pipelines - Data parallelism, Task parallelism, Visualization parallelism; (2) Optimized parallel input/output (I/O); (3) Remote interactive execution; (4) Advanced intercomparison visualization; (5) Data provenance processing and capture; and (6) Interfaces for scientists - Workflow data analysis and visualization construction tools, and Visualization interfaces.« less

An efficient depth map preprocessing method based on structure-aided domain transform smoothing for 3D view generation

PubMed Central

Ma, Liyan; Qiu, Bo; Cui, Mingyue; Ding, Jianwei

2017-01-01

Depth image-based rendering (DIBR), which is used to render virtual views with a color image and the corresponding depth map, is one of the key techniques in the 2D to 3D conversion process. Due to the absence of knowledge about the 3D structure of a scene and its corresponding texture, DIBR in the 2D to 3D conversion process, inevitably leads to holes in the resulting 3D image as a result of newly-exposed areas. In this paper, we proposed a structure-aided depth map preprocessing framework in the transformed domain, which is inspired by recently proposed domain transform for its low complexity and high efficiency. Firstly, our framework integrates hybrid constraints including scene structure, edge consistency and visual saliency information in the transformed domain to improve the performance of depth map preprocess in an implicit way. Then, adaptive smooth localization is cooperated and realized in the proposed framework to further reduce over-smoothness and enhance optimization in the non-hole regions. Different from the other similar methods, the proposed method can simultaneously achieve the effects of hole filling, edge correction and local smoothing for typical depth maps in a united framework. Thanks to these advantages, it can yield visually satisfactory results with less computational complexity for high quality 2D to 3D conversion. Numerical experimental results demonstrate the excellent performances of the proposed method. PMID:28407027

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

PubMed Central

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

2016-01-01

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

Semantics driven approach for knowledge acquisition from EMRs.

PubMed

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

2014-03-01

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

Temporal Processing Capacity in High-Level Visual Cortex Is Domain Specific.

PubMed

Stigliani, Anthony; Weiner, Kevin S; Grill-Spector, Kalanit

2015-09-09

Prevailing hierarchical models propose that temporal processing capacity--the amount of information that a brain region processes in a unit time--decreases at higher stages in the ventral stream regardless of domain. However, it is unknown if temporal processing capacities are domain general or domain specific in human high-level visual cortex. Using a novel fMRI paradigm, we measured temporal capacities of functional regions in high-level visual cortex. Contrary to hierarchical models, our data reveal domain-specific processing capacities as follows: (1) regions processing information from different domains have differential temporal capacities within each stage of the visual hierarchy and (2) domain-specific regions display the same temporal capacity regardless of their position in the processing hierarchy. In general, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. Notably, domain-specific temporal processing capacities are not apparent in V1 and have perceptual implications. Behavioral testing revealed that the encoding capacity of body images is higher than that of characters, faces, and places, and there is a correspondence between peak encoding rates and cortical capacities for characters and bodies. The present evidence supports a model in which the natural statistics of temporal information in the visual world may affect domain-specific temporal processing and encoding capacities. These findings suggest that the functional organization of high-level visual cortex may be constrained by temporal characteristics of stimuli in the natural world, and this temporal capacity is a characteristic of domain-specific networks in high-level visual cortex. Significance statement: Visual stimuli bombard us at different rates every day. For example, words and scenes are typically stationary and vary at slow rates. In contrast, bodies are dynamic and typically change at faster rates. Using a novel fMRI paradigm, we measured temporal processing capacities of functional regions in human high-level visual cortex. Contrary to prevailing theories, we find that different regions have different processing capacities, which have behavioral implications. In general, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. These results suggest that temporal processing capacity is a characteristic of domain-specific networks in high-level visual cortex and contributes to the segregation of cortical regions. Copyright © 2015 the authors 0270-6474/15/3512412-13$15.00/0.

Effects of Computer-Based Visual Representation on Mathematics Learning and Cognitive Load

ERIC Educational Resources Information Center

Yung, Hsin I.; Paas, Fred

2015-01-01

Visual representation has been recognized as a powerful learning tool in many learning domains. Based on the assumption that visual representations can support deeper understanding, we examined the effects of visual representations on learning performance and cognitive load in the domain of mathematics. An experimental condition with visual…

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

PubMed

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

2010-11-01

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

[Visual perception and its disorders].

PubMed

Ruf-Bächtiger, L

1989-11-21

It's the brain and not the eye that decides what is perceived. In spite of this fact, quite a lot is known about the functioning of the eye and the first sections of the optic tract, but little about the actual process of perception. Examination of visual perception and its malfunctions relies therefore on certain hypotheses. Proceeding from the model of functional brain systems, variant functional domains of visual perception can be distinguished. Among the more important of these domains are: digit span, visual discrimination and figure-ground discrimination. Evaluation of these functional domains allows us to understand those children with disorders of visual perception better and to develop more effective treatment methods.

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

ERIC Educational Resources Information Center

Spilich, George J.; And Others

1979-01-01

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

Visualization of semantic relations in geosicences

NASA Astrophysics Data System (ADS)

Ritschel, Bernd; Pfeiffer, Sabine; Mende, Vivien

2010-05-01

The discovery of semantic relations related to the content and context of scientific geophysical and geodetic data and information is a fundamental concept for an integrated scientific approach for the research of multidisciplinary and complex questions of the permanent changing Earth system. Large high-quality and multi-domain geosciences datasets which are qualified by significant and standardized metadata describing the content and especially the context of the data are suitable for the search and discovery of semantic relations. Nowadays such data collections are ingested and provided by many national and international geoscientific data centers, such as e.g. the GFZ ISDC(1). Beside automatic and machine-based algorithm for the discovery of semantic relations, the graphical visualization of such relations are extremely capable for scientist in order to analyze complex datasets and to find sophisticated relations as well as for the public in order to understand the relations within geosciences and between geosciences and societal domains. There are different tools for the visualization of relations, especially in the object-oriented based analysis and development of systems and software. The tool eyePlorer(2) is an awarded program for the visualization of multi-domain semantic relations in the public world of Wikipedia. The data and information for the visualization of keyword based terms and concepts within one domain or topic as well as the relations to other topics are mainly based on wiki content and appropriate structures. eyePlorer's main topics structured and combined in super topics are Health, Species and Life Sciences, Persons and Organisations, Work and Society, Science & Technology as well as Time and Places. Considering the domains or topics of the conceptual model of the GFZ ISDC's data collection, such topics as geosciences-related project, platform, instrument, product type, publication and institution as well as space and time are disjunct and complement sets or subsets or intersections of eyePlorer's topics. The introduction of new topics and the enhancement of the conceptual data model of the eyePlorer as well as the transformation of GFZ ISDC's metadata into a wiki structure or into eyePlorer's internal data format are necessary for the use in eyePlorer for the visualization of geosciences and societal relations based on both, the Wikipedia information collection and the GFZ ISDC metadata. This paper deals with the analysis of eyePlorer's and GFZ ISDC's concepts for the creation of an integrated conceptual model. Furthermore, the transformation model for the conversion of ISDC's metadata into appropriate structures for the use of eyePlorer is described. Finally, the process of semantic visualization of geosciences and societal relations within eyePlorer and using eyePlorer's GUI are illustrated on a climate research related example which is capable to generate knowledge not only for geoscientists but also for the public. (1) GFZ ISDC: GFZ Information System and Data Center, http://isdc.gfz-potsdam.de (2) eyePlorer: http://en.eyeplorer.com/show/

Information Communication using Knowledge Engine on Flood Issues

NASA Astrophysics Data System (ADS)

Demir, I.; Krajewski, W. F.

2012-04-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to and visualization of flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, and other flood-related data for communities in Iowa. The system is designed for use by general public, often people with no domain knowledge and poor general science background. To improve effective communication with such audience, we have introduced a new way in IFIS to get information on flood related issues - instead of by navigating within hundreds of features and interfaces of the information system and web-based sources-- by providing dynamic computations based on a collection of built-in data, analysis, and methods. The IFIS Knowledge Engine connects to distributed sources of real-time stream gauges, and in-house data sources, analysis and visualization tools to answer questions grouped into several categories. Users will be able to provide input based on the query within the categories of rainfall, flood conditions, forecast, inundation maps, flood risk and data sensors. Our goal is the systematization of knowledge on flood related issues, and to provide a single source for definitive answers to factual queries. Long-term goal of this knowledge engine is to make all flood related knowledge easily accessible to everyone, and provide educational geoinformatics tool. The future implementation of the system will be able to accept free-form input and voice recognition capabilities within browser and mobile applications. We intend to deliver increasing capabilities for the system over the coming releases of IFIS. This presentation provides an overview of our Knowledge Engine, its unique information interface and functionality as an educational tool, and discusses the future plans for providing knowledge on flood related issues and resources.

A knowledgebase system to enhance scientific discovery: Telemakus

PubMed Central

Fuller, Sherrilynne S; Revere, Debra; Bugni, Paul F; Martin, George M

2004-01-01

Background With the rapid expansion of scientific research, the ability to effectively find or integrate new domain knowledge in the sciences is proving increasingly difficult. Efforts to improve and speed up scientific discovery are being explored on a number of fronts. However, much of this work is based on traditional search and retrieval approaches and the bibliographic citation presentation format remains unchanged. Methods Case study. Results The Telemakus KnowledgeBase System provides flexible new tools for creating knowledgebases to facilitate retrieval and review of scientific research reports. In formalizing the representation of the research methods and results of scientific reports, Telemakus offers a potential strategy to enhance the scientific discovery process. While other research has demonstrated that aggregating and analyzing research findings across domains augments knowledge discovery, the Telemakus system is unique in combining document surrogates with interactive concept maps of linked relationships across groups of research reports. Conclusion Based on how scientists conduct research and read the literature, the Telemakus KnowledgeBase System brings together three innovations in analyzing, displaying and summarizing research reports across a domain: (1) research report schema, a document surrogate of extracted research methods and findings presented in a consistent and structured schema format which mimics the research process itself and provides a high-level surrogate to facilitate searching and rapid review of retrieved documents; (2) research findings, used to index the documents, allowing searchers to request, for example, research studies which have studied the relationship between neoplasms and vitamin E; and (3) visual exploration interface of linked relationships for interactive querying of research findings across the knowledgebase and graphical displays of what is known as well as, through gaps in the map, what is yet to be tested. The rationale and system architecture are described and plans for the future are discussed. PMID:15507158

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

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

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

Familiarity Vs Trust: A Comparative Study of Domain Scientists' Trust in Visual Analytics and Conventional Analysis Methods.

PubMed

Dasgupta, Aritra; Lee, Joon-Yong; Wilson, Ryan; Lafrance, Robert A; Cramer, Nick; Cook, Kristin; Payne, Samuel

2017-01-01

Combining interactive visualization with automated analytical methods like statistics and data mining facilitates data-driven discovery. These visual analytic methods are beginning to be instantiated within mixed-initiative systems, where humans and machines collaboratively influence evidence-gathering and decision-making. But an open research question is that, when domain experts analyze their data, can they completely trust the outputs and operations on the machine-side? Visualization potentially leads to a transparent analysis process, but do domain experts always trust what they see? To address these questions, we present results from the design and evaluation of a mixed-initiative, visual analytics system for biologists, focusing on analyzing the relationships between familiarity of an analysis medium and domain experts' trust. We propose a trust-augmented design of the visual analytics system, that explicitly takes into account domain-specific tasks, conventions, and preferences. For evaluating the system, we present the results of a controlled user study with 34 biologists where we compare the variation of the level of trust across conventional and visual analytic mediums and explore the influence of familiarity and task complexity on trust. We find that despite being unfamiliar with a visual analytic medium, scientists seem to have an average level of trust that is comparable with the same in conventional analysis medium. In fact, for complex sense-making tasks, we find that the visual analytic system is able to inspire greater trust than other mediums. We summarize the implications of our findings with directions for future research on trustworthiness of visual analytic systems.

Student participation in World Wide Web-based curriculum development of general chemistry

NASA Astrophysics Data System (ADS)

Hunter, William John Forbes

1998-12-01

This thesis describes an action research investigation of improvements to instruction in General Chemistry at Purdue University. Specifically, the study was conducted to guide continuous reform of curriculum materials delivered via the World Wide Web by involving students, instructors, and curriculum designers. The theoretical framework for this study was based upon constructivist learning theory and knowledge claims were developed using an inductive analysis procedure. This results of this study are assertions made in three domains: learning chemistry content via the World Wide Web, learning about learning via the World Wide Web, and learning about participation in an action research project. In the chemistry content domain, students were able to learn chemical concepts that utilized 3-dimensional visualizations, but not textual and graphical information delivered via the Web. In the learning via the Web domain, the use of feedback, the placement of supplementary aids, navigation, and the perception of conceptual novelty were all important to students' use of the Web. In the participation in action research domain, students learned about the complexity of curriculum. development, and valued their empowerment as part of the process.

Finite-difference time-domain modelling of through-the-Earth radio signal propagation

NASA Astrophysics Data System (ADS)

Ralchenko, M.; Svilans, M.; Samson, C.; Roper, M.

2015-12-01

This research seeks to extend the knowledge of how a very low frequency (VLF) through-the-Earth (TTE) radio signal behaves as it propagates underground, by calculating and visualizing the strength of the electric and magnetic fields for an arbitrary geology through numeric modelling. To achieve this objective, a new software tool has been developed using the finite-difference time-domain method. This technique is particularly well suited to visualizing the distribution of electromagnetic fields in an arbitrary geology. The frequency range of TTE radio (400-9000 Hz) and geometrical scales involved (1 m resolution for domains a few hundred metres in size) involves processing a grid composed of millions of cells for thousands of time steps, which is computationally expensive. Graphics processing unit acceleration was used to reduce execution time from days and weeks, to minutes and hours. Results from the new modelling tool were compared to three cases for which an analytic solution is known. Two more case studies were done featuring complex geologic environments relevant to TTE communications that cannot be solved analytically. There was good agreement between numeric and analytic results. Deviations were likely caused by numeric artifacts from the model boundaries; however, in a TTE application in field conditions, the uncertainty in the conductivity of the various geologic formations will greatly outweigh these small numeric errors.

Fitting the Jigsaw of Citation: Information Visualization in Domain Analysis.

ERIC Educational Resources Information Center

Chen, Chaomei; Paul, Ray J.; O'Keefe, Bob

2001-01-01

Discusses the role of information visualization in modeling and representing intellectual structures associated with scientific disciplines and visualizes the domain of computer graphics based on bibliographic data from author cocitation patterns. Highlights include author cocitation maps, citation time lines, animation of a high-dimensional…

Mapping scientific frontiers : the quest for knowledge visualization.

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

Boyack, Kevin W.

Visualization of scientific frontiers is a relatively new field, yet it has a long history and many predecessors. The application of science to science itself has been undertaken for decades with notable early contributions by Derek Price, Thomas Kuhn, Diana Crane, Eugene Garfield, and many others. What is new is the field of information visualization and application of its techniques to help us understand the process of science in the making. In his new book, Chaomei Chen takes us on a journey through this history, touching on predecessors, and then leading us firmly into the new world of Mapping Scientificmore » Frontiers. Building on the foundation of his earlier book, Information Visualization and Virtual Environments, Chen's new offering is much less a tutorial in how to do information visualization, and much more a conceptual exploration of why and how the visualization of science can change the way we do science, amplified by real examples. Chen's stated intents for the book are: (1) to focus on principles of visual thinking that enable the identification of scientific frontiers; (2) to introduce a way to systematize the identification of scientific frontiers (or paradigms) through visualization techniques; and (3) to stimulate interdisciplinary research between information visualization and information science researchers. On all these counts, he succeeds. Chen's book can be broken into two parts which focus on the first two purposes stated above. The first, consisting of the initial four chapters, covers history and predecessors. Kuhn's theory of normal science punctuated by periods of revolution, now commonly known as paradigm shifts, motivates the work. Relevant predecessors outside the traditional field of information science such as cartography (both terrestrial and celestial), mapping the mind, and principles of visual association and communication, are given ample coverage. Chen also describes enabling techniques known to information scientists, such as multi-dimensional scaling, advanced dimensional reduction, social network analysis, Pathfinder network scaling, and landscape visualizations. No algorithms are given here; rather, these techniques are described from the point of view of enabling 'visual thinking'. The Generalized Similarity Analysis (GSA) technique used by Chen in his recent published papers is also introduced here. Information and computer science professionals would be wise not to skip through these early chapters. Although principles of gestalt psychology, cartography, thematic maps, and association techniques may be outside their technology comfort zone, or interest, these predecessors lay a groundwork for the 'visual thinking' that is required to create effective visualizations. Indeed, the great challenge in information visualization is to transform the abstract and intangible into something visible, concrete, and meaningful to the user. The second part of the book, covering the final three chapters, extends the mapping metaphor into the realm of scientific discovery through the structuring of literatures in a way that enables us to see scientific frontiers or paradigms. Case studies are used extensively to show the logical progression that has been made in recent years to get us to this point. Homage is paid to giants of the last 20 years including Michel Callon for co-word mapping, Henry Small for document co-citation analysis and specialty narratives (charting a path linking the different sciences), and Kate McCain for author co-citation analysis, whose work has led to the current state-of-the-art. The last two chapters finally answer the question - 'What does a scientific paradigm look like?' The visual answer given is specific to the GSA technique used by Chen, but does satisfy the intent of the book - to introduce a way to visually identify scientific frontiers. A variety of case studies, mostly from Chen's previously published work - supermassive black holes, cross-domain applications of Pathfinder networks, mass extinction debates, impact of Don Swanson's work, and mad cow disease and vCJD in humans - succeed in explaining how visualization can be used to show the development of, competition between, and eventual acceptance (or replacement) of scientific paradigms. Although not addressed specifically, Chen's work nonetheless makes the persuasive argument that visual maps alone are not sufficient to explain 'the making of science' to a non-expert in a particular field. Rather, expert knowledge is still required to interpret these maps and to explain the paradigms. This combination of visual maps and expert knowledge, used jointly to good effect in the book, becomes a potent means for explaining progress in science to the expert and non-expert alike. Work to extend the GSA technique to explore latent domain knowledge (important work that falls below the citation thresholds typically used in GSA) is also explored here.« less

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

ERIC Educational Resources Information Center

Hambrick, David Z.; Engle, Randall W.

2002-01-01

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

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

PubMed

Hambrick, David Z; Engle, Randall W

2002-06-01

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

Research in computer science

NASA Technical Reports Server (NTRS)

Ortega, J. M.

1984-01-01

Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system.

A cognitive prosthesis for complex decision-making.

PubMed

Tremblay, Sébastien; Gagnon, Jean-François; Lafond, Daniel; Hodgetts, Helen M; Doiron, Maxime; Jeuniaux, Patrick P J M H

2017-01-01

While simple heuristics can be ecologically rational and effective in naturalistic decision making contexts, complex situations require analytical decision making strategies, hypothesis-testing and learning. Sub-optimal decision strategies - using simplified as opposed to analytic decision rules - have been reported in domains such as healthcare, military operational planning, and government policy making. We investigate the potential of a computational toolkit called "IMAGE" to improve decision-making by developing structural knowledge and increasing understanding of complex situations. IMAGE is tested within the context of a complex military convoy management task through (a) interactive simulations, and (b) visualization and knowledge representation capabilities. We assess the usefulness of two versions of IMAGE (desktop and immersive) compared to a baseline. Results suggest that the prosthesis helped analysts in making better decisions, but failed to increase their structural knowledge about the situation once the cognitive prosthesis is removed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Examining a knowledge domain: Interactive visualization of the Geographic Information Science and Technology Body of Knowledge 1

NASA Astrophysics Data System (ADS)

Stowell, Marilyn Ruth

This research compared the effectiveness and performance of interactive visualizations of the GIS&T Body of Knowledge 1. The visualizations were created using Processing, and display the structure and content of the Body of Knowledge using various spatial layout methods: the Indented List, Tree Graph, treemap and Similarity Graph. The first three methods utilize the existing hierarchical structure of the BoK text, while the fourth method (Similarity Graph) serves as a jumping off point for exploring content-based visualizations of the BoK. The following questions have guided the framework of this research: (1) Which of the spatial layouts is most effective for completing tasks related to the GIS&T; BoK overall? How do they compare to each other in terms of performance? (2) Is one spatial layout significantly more or less effective than others for completing a particular cognitive task? (3) Is the user able to utilize the BoK as a basemap or reference system and make inferences based on BoK scorecard overlays? (4) Which design aspects of the interface assist in carrying out the survey objectives? Which design aspects of the application detract from fulfilling the objectives? To answer these questions, human subjects were recruited to participate in a survey, during which they were assigned a random spatial layout and were asked questions about the BoK based on their interaction with the visualization tool. 75 users were tested, 25 for each spatial layout. Statistical analysis revealed that there were no statistically significant differences between means for overall accuracy when comparing the three visualizations. In looking at individual questions, Tree Graph and Indented List yielded statistically significant higher scores for questions regarding the structure of the Body of Knowledge, as compared to the treemap. There was a significant strong positive correlation between the time taken to complete the survey and the final survey score. This correlation was particularly strong with treemap, possibly confirming the steeper learning curve with the more complex layout. Users were asked for feedback on the perceived "ease" of using the interface, and though few users said the interface was easy to use, there was a positive correlation between perceived "ease" and overall score. Qualitative feedback revealed that the external controls on the interface were not inviting to use, and the interface overall was not intuitive. Additional human subjects were recruited from the professional GIS community to participate in testing remotely. These results weren't significant due to small sample size, but helped to verify the feedback and results from the controlled testing.

Beta oscillations define discrete perceptual cycles in the somatosensory domain.

PubMed

Baumgarten, Thomas J; Schnitzler, Alfons; Lange, Joachim

2015-09-29

Whether seeing a movie, listening to a song, or feeling a breeze on the skin, we coherently experience these stimuli as continuous, seamless percepts. However, there are rare perceptual phenomena that argue against continuous perception but, instead, suggest discrete processing of sensory input. Empirical evidence supporting such a discrete mechanism, however, remains scarce and comes entirely from the visual domain. Here, we demonstrate compelling evidence for discrete perceptual sampling in the somatosensory domain. Using magnetoencephalography (MEG) and a tactile temporal discrimination task in humans, we find that oscillatory alpha- and low beta-band (8-20 Hz) cycles in primary somatosensory cortex represent neurophysiological correlates of discrete perceptual cycles. Our results agree with several theoretical concepts of discrete perceptual sampling and empirical evidence of perceptual cycles in the visual domain. Critically, these results show that discrete perceptual cycles are not domain-specific, and thus restricted to the visual domain, but extend to the somatosensory domain.

Enhanced visual short-term memory in action video game players.

PubMed

Blacker, Kara J; Curby, Kim M

2013-08-01

Visual short-term memory (VSTM) is critical for acquiring visual knowledge and shows marked individual variability. Previous work has illustrated a VSTM advantage among action video game players (Boot et al. Acta Psychologica 129:387-398, 2008). A growing body of literature has suggested that action video game playing can bolster visual cognitive abilities in a domain-general manner, including abilities related to visual attention and the speed of processing, providing some potential bases for this VSTM advantage. In the present study, we investigated the VSTM advantage among video game players and assessed whether enhanced processing speed can account for this advantage. Experiment 1, using simple colored stimuli, revealed that action video game players demonstrate a similar VSTM advantage over nongamers, regardless of whether they are given limited or ample time to encode items into memory. Experiment 2, using complex shapes as the stimuli to increase the processing demands of the task, replicated this VSTM advantage, irrespective of encoding duration. These findings are inconsistent with a speed-of-processing account of this advantage. An alternative, attentional account, grounded in the existing literature on the visuo-cognitive consequences of video game play, is discussed.

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

DOE PAGES

Steed, Chad A.; Halsey, William; Dehoff, Ryan; ...

2017-02-16

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

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

Steed, Chad A.; Halsey, William; Dehoff, Ryan

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Visual scan-path analysis with feature space transient fixation moments

NASA Astrophysics Data System (ADS)

Dempere-Marco, Laura; Hu, Xiao-Peng; Yang, Guang-Zhong

2003-05-01

The study of eye movements provides useful insight into the cognitive processes underlying visual search tasks. The analysis of the dynamics of eye movements has often been approached from a purely spatial perspective. In many cases, however, it may not be possible to define meaningful or consistent dynamics without considering the features underlying the scan paths. In this paper, the definition of the feature space has been attempted through the concept of visual similarity and non-linear low dimensional embedding, which defines a mapping from the image space into a low dimensional feature manifold that preserves the intrinsic similarity of image patterns. This has enabled the definition of perceptually meaningful features without the use of domain specific knowledge. Based on this, this paper introduces a new concept called Feature Space Transient Fixation Moments (TFM). The approach presented tackles the problem of feature space representation of visual search through the use of TFM. We demonstrate the practical values of this concept for characterizing the dynamics of eye movements in goal directed visual search tasks. We also illustrate how this model can be used to elucidate the fundamental steps involved in skilled search tasks through the evolution of transient fixation moments.

Tile-based parallel coordinates and its application in financial visualization

NASA Astrophysics Data System (ADS)

Alsakran, Jamal; Zhao, Ye; Zhao, Xinlei

2010-01-01

Parallel coordinates technique has been widely used in information visualization applications and it has achieved great success in visualizing multivariate data and perceiving their trends. Nevertheless, visual clutter usually weakens or even diminishes its ability when the data size increases. In this paper, we first propose a tile-based parallel coordinates, where the plotting area is divided into rectangular tiles. Each tile stores an intersection density that counts the total number of polylines intersecting with that tile. Consequently, the intersection density is mapped to optical attributes, such as color and opacity, by interactive transfer functions. The method visualizes the polylines efficiently and informatively in accordance with the density distribution, and thus, reduces visual cluttering and promotes knowledge discovery. The interactivity of our method allows the user to instantaneously manipulate the tiles distribution and the transfer functions. Specifically, the classic parallel coordinates rendering is a special case of our method when each tile represents only one pixel. A case study on a real world data set, U.S. stock mutual fund data of year 2006, is presented to show the capability of our method in visually analyzing financial data. The presented visual analysis is conducted by an expert in the domain of finance. Our method gains the support from professionals in the finance field, they embrace it as a potential investment analysis tool for mutual fund managers, financial planners, and investors.

Individual differences in solving arithmetic word problems

PubMed Central

2013-01-01

Background With the present functional magnetic resonance imaging (fMRI) study at 3 T, we investigated the neural correlates of visualization and verbalization during arithmetic word problem solving. In the domain of arithmetic, visualization might mean to visualize numbers and (intermediate) results while calculating, and verbalization might mean that numbers and (intermediate) results are verbally repeated during calculation. If the brain areas involved in number processing are domain-specific as assumed, that is, that the left angular gyrus (AG) shows an affinity to the verbal domain, and that the left and right intraparietal sulcus (IPS) shows an affinity to the visual domain, the activation of these areas should show a dependency on an individual’s cognitive style. Methods 36 healthy young adults participated in the fMRI study. The participants habitual use of visualization and verbalization during solving arithmetic word problems was assessed with a short self-report assessment. During the fMRI measurement, arithmetic word problems that had to be solved by the participants were presented in an event-related design. Results We found that visualizers showed greater brain activation in brain areas involved in visual processing, and that verbalizers showed greater brain activation within the left angular gyrus. Conclusions Our results indicate that cognitive styles or preferences play an important role in understanding brain activation. Our results confirm, that strong visualizers use mental imagery more strongly than weak visualizers during calculation. Moreover, our results suggest that the left AG shows a specific affinity to the verbal domain and subserves number processing in a modality-specific way. PMID:23883107

{Semantic metadata application for information resources systematization in water spectroscopy} A.Fazliev (1), A.Privezentsev (1), J.Tennyson (2) (1) Institute of Atmospheric Optics SB RAS, Tomsk, Russia, (2) University College London, London, UK (faz@iao

NASA Astrophysics Data System (ADS)

Fazliev, A.

2009-04-01

The information and knowledge layers of information-computational system for water spectroscopy are described. Semantic metadata for all the tasks of domain information model that are the basis of the layers have been studied. The principle of semantic metadata determination and mechanisms of the usage during information systematization in molecular spectroscopy has been revealed. The software developed for the work with semantic metadata is described as well. Formation of domain model in the framework of Semantic Web is based on the use of explicit specification of its conceptualization or, in other words, its ontologies. Formation of conceptualization for molecular spectroscopy was described in Refs. 1, 2. In these works two chains of task are selected for zeroth approximation for knowledge domain description. These are direct tasks chain and inverse tasks chain. Solution schemes of these tasks defined approximation of data layer for knowledge domain conceptualization. Spectroscopy tasks solutions properties lead to a step-by-step extension of molecular spectroscopy conceptualization. Information layer of information system corresponds to this extension. An advantage of molecular spectroscopy model designed in a form of tasks chain is actualized in the fact that one can explicitly define data and metadata at each step of solution of these molecular spectroscopy chain tasks. Metadata structure (tasks solutions properties) in knowledge domain also has form of a chain in which input data and metadata of the previous task become metadata of the following tasks. The term metadata is used in its narrow sense: metadata are the properties of spectroscopy tasks solutions. Semantic metadata represented with the help of OWL 3 are formed automatically and they are individuals of classes (A-box). Unification of T-box and A-box is an ontology that can be processed with the help of inference engine. In this work we analyzed the formation of individuals of molecular spectroscopy applied ontologies as well as the software used for their creation by means of OWL DL language. The results of this work are presented in a form of an information layer and a knowledge layer in W@DIS information system 4. 1 FORMATION OF INDIVIDUALS OF WATER SPECTROSCOPY APPLIED ONTOLOGY Applied tasks ontology contains explicit description of input an output data of physical tasks solved in two chains of molecular spectroscopy tasks. Besides physical concepts, related to spectroscopy tasks solutions, an information source, which is a key concept of knowledge domain information model, is also used. Each solution of knowledge domain task is linked to the information source which contains a reference on published task solution, molecule and task solution properties. Each information source allows us to identify a certain knowledge domain task solution contained in the information system. Water spectroscopy applied ontology classes are formed on the basis of molecular spectroscopy concepts taxonomy. They are defined by constrains on properties of the selected conceptualization. Extension of applied ontology in W@DIS information system is actualized according to two scenarios. Individuals (ontology facts or axioms) formation is actualized during the task solution upload in the information system. Ontology user operation that implies molecular spectroscopy taxonomy and individuals is performed solely by the user. For this purpose Protege ontology editor was used. For the formation, processing and visualization of knowledge domain tasks individuals a software was designed and implemented. Method of individual formation determines the sequence of steps of created ontology individuals' generation. Tasks solutions properties (metadata) have qualitative and quantitative values. Qualitative metadata are regarded as metadata describing qualitative side of a task such as solution method or other information that can be explicitly specified by object properties of OWL DL language. Quantitative metadata are metadata that describe quantitative properties of task solution such as minimal and maximal data value or other information that can be explicitly obtained by programmed algorithmic operations. These metadata are related to DatatypeProperty properties of OWL specification language Quantitative metadata can be obtained automatically during data upload into information system. Since ObjectProperty values are objects, processing of qualitative metadata requires logical constraints. In case of the task solved in W@DIS ICS qualitative metadata can be formed automatically (for example in spectral functions calculation task). The used methods of translation of qualitative metadata into quantitative is characterized as roughened representation of knowledge in knowledge domain. The existence of two ways of data obtainment is a key moment in the formation of applied ontology of molecular spectroscopy task. experimental method (metadata for experimental data contain description of equipment, experiment conditions and so on) on the initial stage and inverse task solution on the following stages; calculation method (metadata for calculation data are closely related to the metadata used for the description of physical and mathematical models of molecular spectroscopy) 2 SOFTWARE FOR ONTOLOGY OPERATION Data collection in water spectroscopy information system is organized in a form of workflow that contains such operations as information source creation, entry of bibliographic data on publications, formation of uploaded data schema an so on. Metadata are generated in information source as well. Two methods are used for their formation: automatic metadata generation and manual metadata generation (performed by user). Software implementation of support of actions related to metadata formation is performed by META+ module. Functions of META+ module can be divided into two groups. The first groups contains the functions necessary to software developer while the second one the functions necessary to a user of the information system. META+ module functions necessary to the developer are: 1. creation of taxonomy (T-boxes) of applied ontology classes of knowledge domain tasks; 2. creation of instances of task classes; 3. creation of data schemes of tasks in a form of an XML-pattern and based on XML-syntax. XML-pattern is developed for instances generator and created according to certain rules imposed on software generator implementation. 4. implementation of metadata values calculation algorithms; 5. creation of a request interface and additional knowledge processing function for the solution of these task; 6. unification of the created functions and interfaces into one information system The following sequence is universal for the generation of task classes' individuals that form chains. Special interfaces for user operations management are designed for software developer in META+ module. There are means for qualitative metadata values updating during data reuploading to information source. The list of functions necessary to end user contains: - data sets visualization and editing, taking into account their metadata, e.g.: display of unique number of bands in transitions for a certain data source; - export of OWL/RDF models from information system to the environment in XML-syntax; - visualization of instances of classes of applied ontology tasks on molecular spectroscopy; - import of OWL/RDF models into the information system and their integration with domain vocabulary; - formation of additional knowledge of knowledge domain for the construction of ontological instances of task classes using GTML-formats and their processing; - formation of additional knowledge in knowledge domain for the construction of instances of task classes, using software algorithm for data sets processing; - function of semantic search implementation using an interface that formulates questions in a form of related triplets in order for getting an adequate answer. 3 STRUCTURE OF META+ MODULE META+ software module that provides the above functions contains the following components: - a knowledge base that stores semantic metadata and taxonomies of information system; - software libraries POWL and RAP 5 created by third-party developer and providing access to ontological storage; - function classes and libraries that form the core of the module and perform the tasks of formation, storage and visualization of classes instances; - configuration files and module patterns that allow one to adjust and organize operation of different functional blocks; META+ module also contains scripts and patterns implemented according to the rules of W@DIS information system development environment. - scripts for interaction with environment by means of the software core of information system. These scripts provide organizing web-oriented interactive communication; - patterns for the formation of functionality visualization realized by the scripts Software core of scientific information-computational system W@DIS is created with the help of MVC (Model - View - Controller) design pattern that allows us to separate logic of application from its representation. It realizes the interaction of three logical components, actualizing interactivity with the environment via Web and performing its preprocessing. Functions of «Controller» logical component are realized with the help of scripts designed according to the rules imposed by software core of the information system. Each script represents a definite object-oriented class with obligatory class method of script initiation called "start". Functions of actualization of domain application operation results representation (i.e. "View" component) are sets of HTML-patterns that allow one to visualize the results of domain applications operation with the help of additional constructions processed by software core of the system. Besides the interaction with the software core of the scientific information system this module also deals with configuration files of software core and its database. Such organization of work provides closer integration with software core and deeper and more adequate connection in operating system support. 4 CONCLUSION In this work the problems of semantic metadata creation in information system oriented on information representation in the area of molecular spectroscopy have been discussed. The described method of semantic metadata and functions formation as well as realization and structure of META+ module have been described. Architecture of META+ module is closely related to the existing software of "Molecular spectroscopy" scientific information system. Realization of the module is performed with the use of modern approaches to Web-oriented applications development. It uses the existing applied interfaces. The developed software allows us to: - perform automatic metadata annotation of calculated tasks solutions directly in the information system; - perform automatic annotation of metadata on the solution of tasks on task solution results uploading outside the information system forming an instance of the solved task on the basis of entry data; - use ontological instances of task solution for identification of data in information tasks of viewing, comparison and search solved by information system; - export applied tasks ontologies for the operation with them by external means; - solve the task of semantic search according to the pattern and using question-answer type interface. 5 ACKNOWLEDGEMENT The authors are grateful to RFBR for the financial support of development of distributed information system for molecular spectroscopy. REFERENCES A.D.Bykov, A.Z. Fazliev, N.N.Filippov, A.V. Kozodoev, A.I.Privezentsev, L.N.Sinitsa, M.V.Tonkov and M.Yu.Tretyakov, Distributed information system on atmospheric spectroscopy // Geophysical Research Abstracts, SRef-ID: 1607-7962/gra/EGU2007-A-01906, 2007, v. 9, p. 01906. A.I.Prevezentsev, A.Z. Fazliev Applied task ontology for molecular spectroscopy information resources systematization. The Proceedings of 9th Russian scientific conference "Electronic libraries: advanced methods and technologies, electronic collections" - RCDL'2007, Pereslavl Zalesskii, 2007, part.1, 2007, P.201-210. OWL Web Ontology Language Semantics and Abstract Syntax, W3C Recommendation 10 February 2004, http://www.w3.org/TR/2004/REC-owl-semantics-20040210/ W@DIS information system, http://wadis.saga.iao.ru RAP library, http://www4.wiwiss.fu-berlin.de/bizer/rdfapi/.

The KASE approach to domain-specific software systems

NASA Technical Reports Server (NTRS)

Bhansali, Sanjay; Nii, H. Penny

1992-01-01

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

Conceptual Structure within and between Modalities

PubMed Central

Dilkina, Katia; Lambon Ralph, Matthew A.

2012-01-01

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

Domain knowledge patterns in pedagogical diagnostics

NASA Astrophysics Data System (ADS)

Miarka, Rostislav

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

Xuan, Albert L.; Shinghal, Rajjan

1989-03-01

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

'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

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

Sukumar, Sreenivas R; Ferrell, Regina Kay

2013-01-01

As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elementsmore » of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.« less

Distributed Fast Self-Organized Maps for Massive Spectrophotometric Data Analysis †.

PubMed

Dafonte, Carlos; Garabato, Daniel; Álvarez, Marco A; Manteiga, Minia

2018-05-03

Analyzing huge amounts of data becomes essential in the era of Big Data, where databases are populated with hundreds of Gigabytes that must be processed to extract knowledge. Hence, classical algorithms must be adapted towards distributed computing methodologies that leverage the underlying computational power of these platforms. Here, a parallel, scalable, and optimized design for self-organized maps (SOM) is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA) Gaia spacecraft, although it could be extrapolated to other domains. The performance comparison between the sequential implementation and the distributed ones based on Apache Hadoop and Apache Spark is an important part of the work, as well as the detailed analysis of the proposed optimizations. Finally, a domain-specific visualization tool to explore astronomical SOMs is presented.

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

A workflow for the 3D visualization of meteorological data

NASA Astrophysics Data System (ADS)

Helbig, Carolin; Rink, Karsten

2014-05-01

In the future, climate change will strongly influence our environment and living conditions. To predict possible changes, climate models that include basic and process conditions have been developed and big data sets are produced as a result of simulations. The combination of various variables of climate models with spatial data from different sources helps to identify correlations and to study key processes. For our case study we use results of the weather research and forecasting (WRF) model of two regions at different scales that include various landscapes in Northern Central Europe and Baden-Württemberg. We visualize these simulation results in combination with observation data and geographic data, such as river networks, to evaluate processes and analyze if the model represents the atmospheric system sufficiently. For this purpose, a continuous workflow that leads from the integration of heterogeneous raw data to visualization using open source software (e.g. OpenGeoSys Data Explorer, ParaView) is developed. These visualizations can be displayed on a desktop computer or in an interactive virtual reality environment. We established a concept that includes recommended 3D representations and a color scheme for the variables of the data based on existing guidelines and established traditions in the specific domain. To examine changes over time in observation and simulation data, we added the temporal dimension to the visualization. In a first step of the analysis, the visualizations are used to get an overview of the data and detect areas of interest such as regions of convection or wind turbulences. Then, subsets of data sets are extracted and the included variables can be examined in detail. An evaluation by experts from the domains of visualization and atmospheric sciences establish if they are self-explanatory and clearly arranged. These easy-to-understand visualizations of complex data sets are the basis for scientific communication. In addition, they have become an essential medium for the evaluation and verification of models. Particularly in interdisciplinary research projects, they support the scientists in discussions and help to set a general level of knowledge.

Optic disc pit with sectorial retinitis pigmentosa.

PubMed

Balikoglu-Yilmaz, Melike; Taskapili, Muhittin; Yilmaz, Tolga; Teke, Mehmet Yasin

2013-01-01

Sectorial retinitis pigmentosa (RP) and optic disc pit (ODP) are rare clinical conditions. We present a 40-year-old woman with a history of mild night blindness and decreased vision in the right eye for about 5 years. Fundus examination revealed retinal pigmentary changes in the superior and inferotemporal sectors covering the macula and reduced arterial calibre and ODP at the temporal edge of the optic disc. In addition, fundus autofluorescence, spectral-domain optical coherence tomography, fluorescein angiography, and multifocal electroretinogram scans confirmed these clinical findings. Visual acuity was decreased due to an atrophic-appearing foveal lesion. No intervention was suggested because of the poor visual potential. To the best of our knowledge, the present study is the first to describe coexistent optic disc pit and sectorial RP in the superior and inferotemporal sectors covering the macula in the same eye with figures.

Visual Knowledge in Tactical Planning: Preliminary Knowledge Acquisition Phase 1 Technical Report

DTIC Science & Technology

1990-04-05

MANAGEMENT INFORMATION , COMMUNICATIONS, AND COMPUTER SCIENCES Visual Knowledge in Tactical Planning: Preliminary Knowledge Acquisition Phase I Technical...perceived provides information in multiple modalities and, in fact, we may rely on a non-verbal mode for much of our understanding of the situation...some tasks, almost all the pertinent information is provided via diagrams, maps, znd other illustrations. Visual Knowledge Visual experience forms a

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

PubMed Central

Marai, G. Elisabeta

2018-01-01

Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage—and its evaluation—of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature. PMID:28866550

Examining the Use of a Visual Analytics System for Sensemaking Tasks: Case Studies with Domain Experts.

PubMed

Kang, Youn-Ah; Stasko, J

2012-12-01

While the formal evaluation of systems in visual analytics is still relatively uncommon, particularly rare are case studies of prolonged system use by domain analysts working with their own data. Conducting case studies can be challenging, but it can be a particularly effective way to examine whether visual analytics systems are truly helping expert users to accomplish their goals. We studied the use of a visual analytics system for sensemaking tasks on documents by six analysts from a variety of domains. We describe their application of the system along with the benefits, issues, and problems that we uncovered. Findings from the studies identify features that visual analytics systems should emphasize as well as missing capabilities that should be addressed. These findings inform design implications for future systems.

Development of a Visual System Interface to Support a Domain-Oriented Application Composition System

DTIC Science & Technology

1993-03-23

Austin Texas, 1990. 25. Kang, Kyo C. and others. Feature-Oriented Domain Analysis ( FODA ) Feasibility Study. Tech- nical Report CMU/SEI-90-TR-21, Software...Validation and Analysis of the Architect Visual System. .. .. .. .. .... ....... 5-1 5.1 Validation Domain...5-2 5.3 Analysis .. .. .. .. .. .. .... .. .... .... .. .... .... .. ....... 5-2 5.3.1 The REFINE Environment

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.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics.

PubMed

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-10-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

PubMed Central

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-01-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation. PMID:27699416

Knowledge discovery from data as a framework to decision support in medical domains

PubMed Central

Gibert, Karina

2009-01-01

Introduction Knowledge discovery from data (KDD) is a multidisciplinary discipline which appeared in 1996 for “non trivial identifying of valid, novel, potentially useful, ultimately understandable patterns in data”. Pre-treatment of data and post-processing is as important as the data exploitation (Data Mining) itself. Different analysis techniques can be properly combined to produce explicit knowledge from data. Methods Hybrid KDD methodologies combining Artificial Intelligence with Statistics and visualization have been used to identify patterns in complex medical phenomena: experts provide prior knowledge (pK); it biases the search of distinguishable groups of homogeneous objects; support-interpretation tools (CPG) assisted experts in conceptualization and labelling of discovered patterns, consistently with pK. Results Patterns of dependency in mental disabilities supported decision-making on legislation of the Spanish Dependency Law in Catalonia. Relationships between type of neurorehabilitation treatment and patterns of response for brain damage are assessed. Patterns of the perceived QOL along time are used in spinal cord lesion to improve social inclusion. Conclusion Reality is more and more complex and classical data analyses are not powerful enough to model it. New methodologies are required including multidisciplinarity and stressing on production of understandable models. Interaction with the experts is critical to generate meaningful results which can really support decision-making, particularly convenient transferring the pK to the system, as well as interpreting results in close interaction with experts. KDD is a valuable paradigm, particularly when facing very complex domains, not well understood yet, like many medical phenomena.

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

PubMed

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

Fast Deep Tracking via Semi-Online Domain Adaptation

NASA Astrophysics Data System (ADS)

Li, Xiaoping; Luo, Wenbing; Zhu, Yi; Li, Hanxi; Wang, Mingwen

2018-04-01

Deep tracking has been illustrating overwhelming superiorities over the shallow methods. Unfortunately, it also suffers from low FPS rates. To alleviate the problem, a number of real-time deep trackers have been proposed via removing the online updating procedure on the CNN model. However, the absent of the online update leads to a significant drop on tracking accuracy. In this work, we propose to perform the domain adaptation for visual tracking in two stages for transferring the information from the visual tracking domain and the instance domain respectively. In this way, the proposed visual tracker achieves comparable tracking accuracy to the state-of-the-art trackers and runs at real-time speed on an average consuming GPU.

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

PubMed

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

2013-02-01

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

Is Domain Highlighting Actually Helpful in Identifying Phishing Web Pages?

PubMed

Xiong, Aiping; Proctor, Robert W; Yang, Weining; Li, Ninghui

2017-06-01

To evaluate the effectiveness of domain highlighting in helping users identify whether Web pages are legitimate or spurious. As a component of the URL, a domain name can be overlooked. Consequently, browsers highlight the domain name to help users identify which Web site they are visiting. Nevertheless, few studies have assessed the effectiveness of domain highlighting, and the only formal study confounded highlighting with instructions to look at the address bar. We conducted two phishing detection experiments. Experiment 1 was run online: Participants judged the legitimacy of Web pages in two phases. In Phase 1, participants were to judge the legitimacy based on any information on the Web page, whereas in Phase 2, they were to focus on the address bar. Whether the domain was highlighted was also varied. Experiment 2 was conducted similarly but with participants in a laboratory setting, which allowed tracking of fixations. Participants differentiated the legitimate and fraudulent Web pages better than chance. There was some benefit of attending to the address bar, but domain highlighting did not provide effective protection against phishing attacks. Analysis of eye-gaze fixation measures was in agreement with the task performance, but heat-map results revealed that participants' visual attention was attracted by the highlighted domains. Failure to detect many fraudulent Web pages even when the domain was highlighted implies that users lacked knowledge of Web page security cues or how to use those cues. Potential applications include development of phishing prevention training incorporating domain highlighting with other methods to help users identify phishing Web pages.

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

PubMed

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

2008-08-15

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

A taxonomy of visualization tasks for the analysis of biological pathway data.

PubMed

Murray, Paul; McGee, Fintan; Forbes, Angus G

2017-02-15

Understanding complicated networks of interactions and chemical components is essential to solving contemporary problems in modern biology, especially in domains such as cancer and systems research. In these domains, biological pathway data is used to represent chains of interactions that occur within a given biological process. Visual representations can help researchers understand, interact with, and reason about these complex pathways in a number of ways. At the same time, these datasets offer unique challenges for visualization, due to their complexity and heterogeneity. Here, we present taxonomy of tasks that are regularly performed by researchers who work with biological pathway data. The generation of these tasks was done in conjunction with interviews with several domain experts in biology. These tasks require further classification than is provided by existing taxonomies. We also examine existing visualization techniques that support each task, and we discuss gaps in the existing visualization space revealed by our taxonomy. Our taxonomy is designed to support the development and design of future biological pathway visualization applications. We conclude by suggesting future research directions based on our taxonomy and motivated by the comments received by our domain experts.

TelCoVis: Visual Exploration of Co-occurrence in Urban Human Mobility Based on Telco Data.

PubMed

Wu, Wenchao; Xu, Jiayi; Zeng, Haipeng; Zheng, Yixian; Qu, Huamin; Ni, Bing; Yuan, Mingxuan; Ni, Lionel M

2016-01-01

Understanding co-occurrence in urban human mobility (i.e. people from two regions visit an urban place during the same time span) is of great value in a variety of applications, such as urban planning, business intelligence, social behavior analysis, as well as containing contagious diseases. In recent years, the widespread use of mobile phones brings an unprecedented opportunity to capture large-scale and fine-grained data to study co-occurrence in human mobility. However, due to the lack of systematic and efficient methods, it is challenging for analysts to carry out in-depth analyses and extract valuable information. In this paper, we present TelCoVis, an interactive visual analytics system, which helps analysts leverage their domain knowledge to gain insight into the co-occurrence in urban human mobility based on telco data. Our system integrates visualization techniques with new designs and combines them in a novel way to enhance analysts' perception for a comprehensive exploration. In addition, we propose to study the correlations in co-occurrence (i.e. people from multiple regions visit different places during the same time span) by means of biclustering techniques that allow analysts to better explore coordinated relationships among different regions and identify interesting patterns. The case studies based on a real-world dataset and interviews with domain experts have demonstrated the effectiveness of our system in gaining insights into co-occurrence and facilitating various analytical tasks.

The seven S's for successful management.

PubMed

Davidhizar, R

1995-03-01

Becoming a successful manager in a health care agency is, for most new managers, an awesome goal. Successful management is more than knowledge of leadership roles and management functions that can be learned in school or educational workshops. Successful management involves effective use of both the manager's affective and cognitive domains. Mentoring and apprenticeship with a successful nurse leader is for many novice managers a highly valuable way to learn management skills since this allows for techniques with a successful nurse manager to be visualized and then modeled. "Seven S's" that provide a framework for managerial success are discussed.

Adult Age Differences in Knowledge-Driven Reading

ERIC Educational Resources Information Center

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

2004-01-01

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

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

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1992-01-01

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

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

NASA Technical Reports Server (NTRS)

Keller, Richard M.

1992-01-01

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

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

PubMed

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

2016-01-01

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

Selective impairment of living things and musical instruments on a verbal 'Semantic Knowledge Questionnaire' in a case of apperceptive visual agnosia.

PubMed

Masullo, Carlo; Piccininni, Chiara; Quaranta, Davide; Vita, Maria Gabriella; Gaudino, Simona; Gainotti, Guido

2012-10-01

Semantic memory was investigated in a patient (MR) affected by a severe apperceptive visual agnosia, due to an ischemic cerebral lesion, bilaterally affecting the infero-mesial parts of the temporo-occipital cortices. The study was made by means of a Semantic Knowledge Questionnaire (Laiacona, Barbarotto, Trivelli, & Capitani, 1993), which takes separately into account four categories of living beings (animals, fruits, vegetables and body parts) and of artefacts (furniture, tools, vehicles and musical instruments), does not require a visual analysis and allows to distinguish errors concerning super-ordinate categorization, perceptual features and functional/encyclopedic knowledge. When the total number of errors obtained on all the categories of living and non-living beings was considered, a non-significant trend toward a higher number of errors in living stimuli was observed. This difference, however, became significant when body parts and musical instruments were excluded from the analysis. Furthermore, the number of errors obtained on the musical instruments was similar to that obtained on the living categories of animals, fruits and vegetables and significantly higher of that obtained in the other artefact categories. This difference was still significant when familiarity, frequency of use and prototypicality of each stimulus entered into a logistic regression analysis. On the other hand, a separate analysis of errors obtained on questions exploring super-ordinate categorization, perceptual features and functional/encyclopedic attributes showed that the differences between living and non-living stimuli and between musical instruments and other artefact categories were mainly due to errors obtained on questions exploring perceptual features. All these data are at variance with the 'domains of knowledge' hypothesis', which assumes that the breakdown of different categories of living and non-living things respects the distinction between biological entities and artefacts and support the models assuming that 'category-specific semantic disorders' are the by-product of the differential weighting that visual-perceptual and functional (or action-related) attributes have in the construction of different biological and artefacts categories. Copyright © 2012 Elsevier Inc. All rights reserved.

Cognitive functioning following traumatic brain injury: A five-year follow-up.

PubMed

Marsh, Nigel V; Ludbrook, Maria R; Gaffaney, Lauren C

2016-01-01

To describe the long-term prevalence and severity of cognitive deficits following significant (i.e., ventilation required for >24 hours) traumatic brain injury. To assess a comprehensive range of cognitive functions using psychometric measures with established normative, reliability, and validity data. A group of 71 adults was assessed at approximately five years (mean = 66 months) following injury. Assessment of cognitive functioning covered the domains of intelligence, attention, verbal and visual memory, visual-spatial construction, and executive functions. Impairment was evident across all domains but prevalence varied both within and between domains. Across aspects of intelligence clinical impairment ranged from 8-25% , attention 39-62% , verbal memory 16-46% , visual memory 23-51% , visual-spatial construction 38% , and executive functions (verbal fluency) 13% . In addition, 3-23% of performances across the measures were in the borderline range, suggesting a high prevalence of subclinical deficit. Although the prevalence of impairment may vary across cognitive domains, long-term follow-up documented deficits in all six domains. These findings provide further evidence that while improvement of cognitive functioning following significant traumatic brain injury may be possible, recovery of function is unlikely.

Visual and spatial working memory are not that dissociated after all: a time-based resource-sharing account.

PubMed

Vergauwe, Evie; Barrouillet, Pierre; Camos, Valérie

2009-07-01

Examinations of interference between visual and spatial materials in working memory have suggested domain- and process-based fractionations of visuo-spatial working memory. The present study examined the role of central time-based resource sharing in visuo-spatial working memory and assessed its role in obtained interference patterns. Visual and spatial storage were combined with both visual and spatial on-line processing components in computer-paced working memory span tasks (Experiment 1) and in a selective interference paradigm (Experiment 2). The cognitive load of the processing components was manipulated to investigate its impact on concurrent maintenance for both within-domain and between-domain combinations of processing and storage components. In contrast to both domain- and process-based fractionations of visuo-spatial working memory, the results revealed that recall performance was determined by the cognitive load induced by the processing of items, rather than by the domain to which those items pertained. These findings are interpreted as evidence for a time-based resource-sharing mechanism in visuo-spatial working memory.

Development of the Preverbal Visual Assessment (PreViAs) questionnaire.

PubMed

Pueyo, Victoria; García-Ormaechea, Inés; González, Inmaculada; Ferrer, Concepción; de la Mata, Guillermo; Duplá, María; Orós, Pedro; Andres, Eva

2014-04-01

Visual cognitive functions of preverbal infants are evaluated by means of a behavioral assessment. Parents or primary caregivers may be appropriate to certify the acquisition of certain abilities. To develop the PreViAs (Preverbal Visual Assessment) questionnaire to assess visual behavior of infants under 24 months of age and to assess the normative outcomes for each item at each age. The process was divided into three phases: scale development (items and domains generation), pilot testing, and exploratory analysis. The final version of the PreViAs questionnaire consisted of 30 items, each related to one or more of four domains (visual attention, visual communication, visual-motor coordination, and visual processing). For the exploratory analysis, 298 children (159 boys and 139 girls) were recruited. Their ages ranged from 0.1 to 24 months (mean, 11.2 months). Internal consistency of the questionnaire was high for all domains (Cronbach's α coefficients of 0.85-0.94). The PreViAs questionnaire is a useful scale for assessing visual cognitive abilities of infants under 24 months of age. It is easy and feasible to complete by primary caregivers. Copyright © 2014 Elsevier Ltd. All rights reserved.

Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning.

PubMed

Sadeghi, Zahra; Testolin, Alberto

2017-08-01

In humans, efficient recognition of written symbols is thought to rely on a hierarchical processing system, where simple features are progressively combined into more abstract, high-level representations. Here, we present a computational model of Persian character recognition based on deep belief networks, where increasingly more complex visual features emerge in a completely unsupervised manner by fitting a hierarchical generative model to the sensory data. Crucially, high-level internal representations emerging from unsupervised deep learning can be easily read out by a linear classifier, achieving state-of-the-art recognition accuracy. Furthermore, we tested the hypothesis that handwritten digits and letters share many common visual features: A generative model that captures the statistical structure of the letters distribution should therefore also support the recognition of written digits. To this aim, deep networks trained on Persian letters were used to build high-level representations of Persian digits, which were indeed read out with high accuracy. Our simulations show that complex visual features, such as those mediating the identification of Persian symbols, can emerge from unsupervised learning in multilayered neural networks and can support knowledge transfer across related domains.

Evaluation of software maintain ability with open EHR - a comparison of architectures.

PubMed

Atalag, Koray; Yang, Hong Yul; Tempero, Ewan; Warren, James R

2014-11-01

To assess whether it is easier to maintain a clinical information system developed using open EHR model driven development versus mainstream methods. A new open source application (GastrOS) has been developed following open EHR's multi-level modelling approach using .Net/C# based on the same requirements of an existing clinically used application developed using Microsoft Visual Basic and Access database. Almost all the domain knowledge was embedded into the software code and data model in the latter. The same domain knowledge has been expressed as a set of open EHR Archetypes in GastrOS. We then introduced eight real-world change requests that had accumulated during live clinical usage, and implemented these in both systems while measuring time for various development tasks and change in software size for each change request. Overall it took half the time to implement changes in GastrOS. However it was the more difficult application to modify for one change request, suggesting the nature of change is also important. It was not possible to implement changes by modelling only. Comparison of relative measures of time and software size change within each application highlights how architectural differences affected maintain ability across change requests. The use of open EHR model driven development can result in better software maintain ability. The degree to which open EHR affects software maintain ability depends on the extent and nature of domain knowledge involved in changes. Although we used relative measures for time and software size, confounding factors could not be totally excluded as a controlled study design was not feasible. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A conceptual framework for the domain of evidence-based design.

PubMed

Ulrich, Roger S; Berry, Leonard L; Quan, Xiaobo; Parish, Janet Turner

2010-01-01

The physical facilities in which healthcare services are performed play an important role in the healing process. Evidence-based design in healthcare is a developing field of study that holds great promise for benefiting key stakeholders: patients, families, physicians, and nurses, as well as other healthcare staff and organizations. In this paper, the authors present and discuss a conceptual framework intended to capture the current domain of evidence-based design in healthcare. In this framework, the built environment is represented by nine design variable categories: audio environment, visual environment, safety enhancement, wayfinding system, sustainability, patient room, family support spaces, staff support spaces, and physician support spaces. Furthermore, a series of matrices is presented that indicates knowledge gaps concerning the relationship between specific healthcare facility design variable categories and participant and organizational outcomes. From this analysis, the authors identify fertile research opportunities from the perspectives of key stakeholders.

An ontology based trust verification of software license agreement

NASA Astrophysics Data System (ADS)

Lu, Wenhuan; Li, Xiaoqing; Gan, Zengqin; Wei, Jianguo

2017-08-01

When we install software or download software, there will show up so big mass document to state the rights and obligations, for which lots of person are not patient to read it or understand it. That would may make users feel distrust for the software. In this paper, we propose an ontology based verification for Software License Agreement. First of all, this work proposed an ontology model for domain of Software License Agreement. The domain ontology is constructed by proposed methodology according to copyright laws and 30 software license agreements. The License Ontology can act as a part of generalized copyright law knowledge model, and also can work as visualization of software licenses. Based on this proposed ontology, a software license oriented text summarization approach is proposed which performances showing that it can improve the accuracy of software licenses summarizing. Based on the summarization, the underline purpose of the software license can be explicitly explored for trust verification.

iTTVis: Interactive Visualization of Table Tennis Data.

PubMed

Wu, Yingcai; Lan, Ji; Shu, Xinhuan; Ji, Chenyang; Zhao, Kejian; Wang, Jiachen; Zhang, Hui

2018-01-01

The rapid development of information technology paved the way for the recording of fine-grained data, such as stroke techniques and stroke placements, during a table tennis match. This data recording creates opportunities to analyze and evaluate matches from new perspectives. Nevertheless, the increasingly complex data poses a significant challenge to make sense of and gain insights into. Analysts usually employ tedious and cumbersome methods which are limited to watching videos and reading statistical tables. However, existing sports visualization methods cannot be applied to visualizing table tennis competitions due to different competition rules and particular data attributes. In this work, we collaborate with data analysts to understand and characterize the sophisticated domain problem of analysis of table tennis data. We propose iTTVis, a novel interactive table tennis visualization system, which to our knowledge, is the first visual analysis system for analyzing and exploring table tennis data. iTTVis provides a holistic visualization of an entire match from three main perspectives, namely, time-oriented, statistical, and tactical analyses. The proposed system with several well-coordinated views not only supports correlation identification through statistics and pattern detection of tactics with a score timeline but also allows cross analysis to gain insights. Data analysts have obtained several new insights by using iTTVis. The effectiveness and usability of the proposed system are demonstrated with four case studies.

Perspectives on knowledge in engineering design

NASA Technical Reports Server (NTRS)

Rasdorf, W. J.

1985-01-01

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

Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

NASA Astrophysics Data System (ADS)

Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

1994-09-01

A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Visual Analytic Judgments

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

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

2017-05-08

Scientists often use specific data analysis and presentation methods familiar within their domain. But does high familiarity drive better analytical judgment? This question is especially relevant when familiar methods themselves can have shortcomings: many visualizations used conventionally for scientific data analysis and presentation do not follow established best practices. This necessitates new methods that might be unfamiliar yet prove to be more effective. But there is little empirical understanding of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their visual analytic judgments. To address this gap and to study these factors, we focusmore » on visualizations used for comparison of climate model performance. We report on a comprehensive survey-based user study with 47 climate scientists and present an analysis of : i) relationships among scientists’ familiarity, their perceived lev- els of comfort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

In-situ visualization of stress-dependent bulk magnetic domain formation by neutron grating interferometry

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

Betz, B.; École Polytechnique Fédérale de Lausanne, NXMM Laboratory, IMX, CH-1015 Lausanne; Rauscher, P.

The performance and degree of efficiency of industrial transformers are directly influenced by the magnetic properties of high-permeability steel laminations (HPSLs). Industrial transformer cores are built of stacks of single HPSLs. While the insulating coating on each HPSL reduces eddy-current losses in the transformer core, the coating also induces favorable inter-granular tensile stresses that significantly influence the underlying magnetic domain structure. Here, we show that the neutron dark-field image can be used to analyze the influence of the coating on the volume and supplementary surface magnetic domain structures. To visualize the stress effect of the coating on the bulk domainmore » formation, we used an uncoated HPSL and stepwise increased the applied external tensile stress up to 20 MPa. We imaged the domain configuration of the intermediate stress states and were able to reproduce the original domain structure of the coated state. Furthermore, we were able to visualize how the applied stresses lead to a refinement of the volume domain structure and the suppression and reoccurrence of supplementary domains.« less

Autonomous mental development with selective attention, object perception, and knowledge representation

NASA Astrophysics Data System (ADS)

Ban, Sang-Woo; Lee, Minho

2008-04-01

Knowledge-based clustering and autonomous mental development remains a high priority research topic, among which the learning techniques of neural networks are used to achieve optimal performance. In this paper, we present a new framework that can automatically generate a relevance map from sensory data that can represent knowledge regarding objects and infer new knowledge about novel objects. The proposed model is based on understating of the visual what pathway in our brain. A stereo saliency map model can selectively decide salient object areas by additionally considering local symmetry feature. The incremental object perception model makes clusters for the construction of an ontology map in the color and form domains in order to perceive an arbitrary object, which is implemented by the growing fuzzy topology adaptive resonant theory (GFTART) network. Log-polar transformed color and form features for a selected object are used as inputs of the GFTART. The clustered information is relevant to describe specific objects, and the proposed model can automatically infer an unknown object by using the learned information. Experimental results with real data have demonstrated the validity of this approach.

Motion cue effects on human pilot dynamics in manual control

NASA Technical Reports Server (NTRS)

Washizu, K.; Tanaka, K.; Endo, S.; Itoko, T.

1977-01-01

Two experiments were conducted to study the motion cue effects on human pilots during tracking tasks. The moving-base simulator of National Aerospace Laboratory was employed as the motion cue device, and the attitude director indicator or the projected visual field was employed as the visual cue device. The chosen controlled elements were second-order unstable systems. It was confirmed that with the aid of motion cues the pilot workload was lessened and consequently the human controllability limits were enlarged. In order to clarify the mechanism of these effects, the describing functions of the human pilots were identified by making use of the spectral and the time domain analyses. The results of these analyses suggest that the sensory system of the motion cues can yield the differential informations of the signal effectively, which coincides with the existing knowledges in the physiological area.

On Crowd-verification of Biological Networks

PubMed Central

Ansari, Sam; Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Hayes, William; Hoeng, Julia; Iskandar, Anita; Kleiman, Robin; Norel, Raquel; O’Neel, Bruce; Peitsch, Manuel C.; Poussin, Carine; Pratt, Dexter; Rhrissorrakrai, Kahn; Schlage, Walter K.; Stolovitzky, Gustavo; Talikka, Marja

2013-01-01

Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community. PMID:24151423

Optic Disc Pit with Sectorial Retinitis Pigmentosa

PubMed Central

Taskapili, Muhittin; Yilmaz, Tolga; Teke, Mehmet Yasin

2013-01-01

Sectorial retinitis pigmentosa (RP) and optic disc pit (ODP) are rare clinical conditions. We present a 40-year-old woman with a history of mild night blindness and decreased vision in the right eye for about 5 years. Fundus examination revealed retinal pigmentary changes in the superior and inferotemporal sectors covering the macula and reduced arterial calibre and ODP at the temporal edge of the optic disc. In addition, fundus autofluorescence, spectral-domain optical coherence tomography, fluorescein angiography, and multifocal electroretinogram scans confirmed these clinical findings. Visual acuity was decreased due to an atrophic-appearing foveal lesion. No intervention was suggested because of the poor visual potential. To the best of our knowledge, the present study is the first to describe coexistent optic disc pit and sectorial RP in the superior and inferotemporal sectors covering the macula in the same eye with figures. PMID:23781365

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Teachers' Spatial Literacy as Visualization, Reasoning, and Communication

ERIC Educational Resources Information Center

Moore-Russo, Deborah; Viglietti, Janine M.; Chiu, Ming Ming; Bateman, Susan M.

2013-01-01

This paper conceptualizes spatial literacy as consisting of three overlapping domains: visualization, reasoning, and communication. By considering these domains, this study explores different aspects of spatial literacy to better understand how a group of mathematics teachers reasoned about spatial tasks. Seventy-five preservice and inservice…

Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke

PubMed Central

Ramsey, Lenny E.; Metcalf, Nicholas V.; Chacko, Ravi V.; Weinberger, Kilian; Baldassarre, Antonello; Hacker, Carl D.; Shulman, Gordon L.; Corbetta, Maurizio

2016-01-01

Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain–behavior relationships in stroke. PMID:27402738

Articulation Management for Intelligent Integration of Information

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

In Situ Visualization of Lipid Raft Domains by Fluorescent Glycol Chitosan Derivatives.

PubMed

Jiang, Yao-Wen; Guo, Hao-Yue; Chen, Zhan; Yu, Zhi-Wu; Wang, Zhifei; Wu, Fu-Gen

2016-07-05

Lipid rafts are highly ordered small microdomains mainly composed of glycosphingolipids, cholesterol, and protein receptors. Optically distinguishing lipid raft domains in cell membranes would greatly facilitate the investigations on the structure and dynamics of raft-related cellular behaviors, such as signal transduction, membrane transport (endocytosis), adhesion, and motility. However, current strategies about the visualization of lipid raft domains usually suffer from the low biocompatibility of the probes, invasive detection, or ex situ observation. At the same time, naturally derived biomacromolecules have been extensively used in biomedical field and their interaction with cells remains a long-standing topic since it is closely related to various fundamental studies and potential applications. Herein, noninvasive visualization of lipid raft domains in model lipid bilayers (supported lipid bilayers and giant unilamellar vesicles) and live cells was successfully realized in situ using fluorescent biomacromolecules: the fluorescein isothiocyanate (FITC)-labeled glycol chitosan molecules. We found that the lipid raft domains in model or real membranes could be specifically stained by the FITC-labeled glycol chitosan molecules, which could be attributed to the electrostatic attractive interaction and/or hydrophobic interaction between the probes and the lipid raft domains. Since the FITC-labeled glycol chitosan molecules do not need to completely insert into the lipid bilayer and will not disturb the organization of lipids, they can more accurately visualize the raft domains as compared with other fluorescent dyes that need to be premixed with the various lipid molecules prior to the fabrication of model membranes. Furthermore, the FITC-labeled glycol chitosan molecules were found to be able to resist cellular internalization and could successfully visualize rafts in live cells. The present work provides a new way to achieve the imaging of lipid rafts and also sheds new light on the interaction between biomacromolecules and lipid membranes.

Reducing the Analytical Bottleneck for Domain Scientists: Lessons from a Climate Data Visualization Case Study

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

Dasgupta, Aritra; Poco, Jorge; Bertini, Enrico

2016-01-01

The gap between large-scale data production rate and the rate of generation of data-driven scientific insights has led to an analytical bottleneck in scientific domains like climate, biology, etc. This is primarily due to the lack of innovative analytical tools that can help scientists efficiently analyze and explore alternative hypotheses about the data, and communicate their findings effectively to a broad audience. In this paper, by reflecting on a set of successful collaborative research efforts between with a group of climate scientists and visualization researchers, we introspect how interactive visualization can help reduce the analytical bottleneck for domain scientists.

In situ visualization of domain structure evolution during field cooling in 0.67PMN-0.33PT single crystal

NASA Astrophysics Data System (ADS)

Ushakov, A. D.; Esin, A. A.; Chezganov, D. S.; Turygin, A. P.; Akhmatkhanov, A. R.; Hu, Q.; Sun, L.; Wei, X.; Shur, V. Ya

2017-10-01

The evolution of the domain structure during in-field cooling was in situ studied in [001]-cut single crystals of relaxor ferroelectric (1-x)Pb(Mg1/3Nb2/3)O3-xPbTiO3 (PMN-PT) with x = 0.33 with maximum of dielectric permittivity at 150°C. The main stages of domain evolution have been separated. The visualization of the static as-grown and polarized domain structures with high spatial resolution by piezoresponse force microscopy and scanning electron microscopy allowed measuring the characteristic features of maze and needle-like domain structures.

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

PubMed

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

2013-10-01

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

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

PubMed

Chrysafiadi, Konstantina; Virvou, Maria

2013-12-01

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

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks.

PubMed

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

2015-08-01

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

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks

PubMed Central

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

2015-01-01

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

Inferential reasoning by exclusion in great apes, lesser apes, and spider monkeys.

PubMed

Hill, Andrew; Collier-Baker, Emma; Suddendorf, Thomas

2011-02-01

Using the cups task, in which subjects are presented with limited visual or auditory information that can be used to deduce the location of a hidden reward, Call (2004) found prima facie evidence of inferential reasoning by exclusion in several great ape species. One bonobo (Pan paniscus) and two gorillas (Gorilla gorilla) appeared to make such inferences in both the visual and auditory domains. However, common chimpanzees (Pan troglodytes) were successful only in the visual domain, and Bornean orangutans (Pongo pygmaeus) in neither. The present research built on this paradigm, and Experiment 1 yielded prima facie evidence of inference by exclusion in both domains for two common chimpanzees, and in the visual domain for two Sumatran orangutans (Pongo abelii). Experiments 2 and 3 demonstrated that two specific associative learning explanations could not readily account for these results. Because an important focus of the program of research was to assess the cognitive capacities of lesser apes (family Hylobatidae), we modified Call's original procedures to better suit their attentional and dispositional characteristics. In Experiment 1, testing was also attempted with three gibbon genera (Symphalangus, Nomascus, Hylobates), but none of the subjects completed the standard task. Further testing of three siamangs (Symphalangus syndactylus) and a spider monkey (Ateles geoffroyi) using a faster method yielded prima facie evidence of inferential reasoning by exclusion in the visual domain among the siamangs (Experiment 4).

Early auditory evoked potential is modulated by selective attention and related to individual differences in visual working memory capacity.

PubMed

Giuliano, Ryan J; Karns, Christina M; Neville, Helen J; Hillyard, Steven A

2014-12-01

A growing body of research suggests that the predictive power of working memory (WM) capacity for measures of intellectual aptitude is due to the ability to control attention and select relevant information. Crucially, attentional mechanisms implicated in controlling access to WM are assumed to be domain-general, yet reports of enhanced attentional abilities in individuals with larger WM capacities are primarily within the visual domain. Here, we directly test the link between WM capacity and early attentional gating across sensory domains, hypothesizing that measures of visual WM capacity should predict an individual's capacity to allocate auditory selective attention. To address this question, auditory ERPs were recorded in a linguistic dichotic listening task, and individual differences in ERP modulations by attention were correlated with estimates of WM capacity obtained in a separate visual change detection task. Auditory selective attention enhanced ERP amplitudes at an early latency (ca. 70-90 msec), with larger P1 components elicited by linguistic probes embedded in an attended narrative. Moreover, this effect was associated with greater individual estimates of visual WM capacity. These findings support the view that domain-general attentional control mechanisms underlie the wide variation of WM capacity across individuals.

Assessment of visual disability using the WHO disability assessment scale (WHO-DAS-II): role of gender.

PubMed

Badr, H E; Mourad, H

2009-10-01

To study the role of gender in coping with disability in young visually impaired students attending two schools for blindness. The WHO Disability Assessment Schedule (WHODAS II), 36-Item Interviewer Administered translated Arabic version was used. It evaluates six domains of everyday living in the last 30 days. These domains are: understanding and communicating, getting around, self care, getting along with people, household activities and participation in society. Face-to-face interviews were conducted with 200 students who represented the target population of the study. Binary logistic regression analysis of the scores of the six domains revealed that in all of the domains except getting along with people and coping with school activities, females significantly faced more difficulties in coping with daily life activities than did their male counterparts. Increasing age significantly increased difficulties in coping with school activities. Genetic causes of blindness were associated with increased difficulties. Females face more difficulties in coping with visual disability. Genetic counselling is needed to decrease the prevalence of visual disability. Girls with blindness need additional inputs to help cope with blindness. Early intervention facilitates dealing with school activities of the visually impaired.

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Visual research in clinical education.

PubMed

Bezemer, Jeff

2017-01-01

The aim of this paper is to explore what might be gained from collecting and analysing visual data, such as photographs, scans, drawings, video and screen recordings, in clinical educational research. Its focus is on visual research that looks at teaching and learning 'as it naturally occurs' in the work place, in simulation centres and other sites, and also involves the collection and analysis of visual learning materials circulating in these sites. With the ubiquity of digital recording devices, video data and visual learning materials are now relatively cheap to collect. Compared to other domains of education research visual materials are not widely used in clinical education research. The paper sets out to identify and reflect on the possibilities for visual research using examples from an ethnographic study on surgical and inter-professional learning in the operating theatres of a London hospital. The paper shows how visual research enables recognition, analysis and critical evaluation of (1) the hidden curriculum, such as the meanings implied by embodied, visible actions of clinicians; (2) the ways in which clinical teachers design multimodal learning environments using a range of modes of communication available to them, combining, for instance, gesture and speech; (3) the informal assessment of clinical skills, and the intricate relation between trainee performance and supervisor feedback; (4) the potentialities and limitations of different visual learning materials, such as textbooks and videos, for representing medical knowledge. The paper concludes with theoretical and methodological reflections on what can be made visible, and therefore available for analysis, explanation and evaluation if visual materials are used for clinical education research, and what remains unaccounted for if written language remains the dominant mode in the research cycle. Opportunities for quantitative analysis and ethical implications are also discussed. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

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

ERIC Educational Resources Information Center

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

2017-01-01

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

Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

PubMed

Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

2008-10-01

Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

Use of Context in Video Processing

NASA Astrophysics Data System (ADS)

Wu, Chen; Aghajan, Hamid

Interpreting an event or a scene based on visual data often requires additional contextual information. Contextual information may be obtained from different sources. In this chapter, we discuss two broad categories of contextual sources: environmental context and user-centric context. Environmental context refers to information derived from domain knowledge or from concurrently sensed effects in the area of operation. User-centric context refers to information obtained and accumulated from the user. Both types of context can include static or dynamic contextual elements. Examples from a smart home environment are presented to illustrate how different types of contextual data can be applied to aid the decision-making process.

Complementary and conventional medicine: a concept map

PubMed Central

Baldwin, Carol M; Kroesen, Kendall; Trochim, William M; Bell, Iris R

2004-01-01

Background Despite the substantive literature from survey research that has accumulated on complementary and alternative medicine (CAM) in the United States and elsewhere, very little research has been done to assess conceptual domains that CAM and conventional providers would emphasize in CAM survey studies. The objective of this study is to describe and interpret the results of concept mapping with conventional and CAM practitioners from a variety of backgrounds on the topic of CAM. Methods Concept mapping, including free sorts, ratings, and multidimensional scaling was used to organize conceptual domains relevant to CAM into a visual "cluster map." The panel consisted of CAM providers, conventional providers, and university faculty, and was convened to help formulate conceptual domains to guide the development of a CAM survey for use with United States military veterans. Results Eight conceptual clusters were identified: 1) Self-assessment, Self-care, and Quality of Life; 2) Health Status, Health Behaviors; 3) Self-assessment of Health; 4) Practical/Economic/ Environmental Concerns; 5) Needs Assessment; 6) CAM vs. Conventional Medicine; 7) Knowledge of CAM; and 8) Experience with CAM. The clusters suggest panelists saw interactions between CAM and conventional medicine as a critical component of the current medical landscape. Conclusions Concept mapping provided insight into how CAM and conventional providers view the domain of health care, and was shown to be a useful tool in the formulation of CAM-related conceptual domains. PMID:15018623

An Ebola virus-centered knowledge base

PubMed Central

Kamdar, Maulik R.; Dumontier, Michel

2015-01-01

Ebola virus (EBOV), of the family Filoviridae viruses, is a NIAID category A, lethal human pathogen. It is responsible for causing Ebola virus disease (EVD) that is a severe hemorrhagic fever and has a cumulative death rate of 41% in the ongoing epidemic in West Africa. There is an ever-increasing need to consolidate and make available all the knowledge that we possess on EBOV, even if it is conflicting or incomplete. This would enable biomedical researchers to understand the molecular mechanisms underlying this disease and help develop tools for efficient diagnosis and effective treatment. In this article, we present our approach for the development of an Ebola virus-centered Knowledge Base (Ebola-KB) using Linked Data and Semantic Web Technologies. We retrieve and aggregate knowledge from several open data sources, web services and biomedical ontologies. This knowledge is transformed to RDF, linked to the Bio2RDF datasets and made available through a SPARQL 1.1 Endpoint. Ebola-KB can also be explored using an interactive Dashboard visualizing the different perspectives of this integrated knowledge. We showcase how different competency questions, asked by domain users researching the druggability of EBOV, can be formulated as SPARQL Queries or answered using the Ebola-KB Dashboard. Database URL: http://ebola.semanticscience.org. PMID:26055098

An Ebola virus-centered knowledge base.

PubMed

Kamdar, Maulik R; Dumontier, Michel

2015-01-01

Ebola virus (EBOV), of the family Filoviridae viruses, is a NIAID category A, lethal human pathogen. It is responsible for causing Ebola virus disease (EVD) that is a severe hemorrhagic fever and has a cumulative death rate of 41% in the ongoing epidemic in West Africa. There is an ever-increasing need to consolidate and make available all the knowledge that we possess on EBOV, even if it is conflicting or incomplete. This would enable biomedical researchers to understand the molecular mechanisms underlying this disease and help develop tools for efficient diagnosis and effective treatment. In this article, we present our approach for the development of an Ebola virus-centered Knowledge Base (Ebola-KB) using Linked Data and Semantic Web Technologies. We retrieve and aggregate knowledge from several open data sources, web services and biomedical ontologies. This knowledge is transformed to RDF, linked to the Bio2RDF datasets and made available through a SPARQL 1.1 Endpoint. Ebola-KB can also be explored using an interactive Dashboard visualizing the different perspectives of this integrated knowledge. We showcase how different competency questions, asked by domain users researching the druggability of EBOV, can be formulated as SPARQL Queries or answered using the Ebola-KB Dashboard. © The Author(s) 2015. Published by Oxford University Press.

Semantics of the visual environment encoded in parahippocampal cortex

PubMed Central

Bonner, Michael F.; Price, Amy Rose; Peelle, Jonathan E.; Grossman, Murray

2016-01-01

Semantic representations capture the statistics of experience and store this information in memory. A fundamental component of this memory system is knowledge of the visual environment, including knowledge of objects and their associations. Visual semantic information underlies a range of behaviors, from perceptual categorization to cognitive processes such as language and reasoning. Here we examine the neuroanatomic system that encodes visual semantics. Across three experiments, we found converging evidence indicating that knowledge of verbally mediated visual concepts relies on information encoded in a region of the ventral-medial temporal lobe centered on parahippocampal cortex. In an fMRI study, this region was strongly engaged by the processing of concepts relying on visual knowledge but not by concepts relying on other sensory modalities. In a study of patients with the semantic variant of primary progressive aphasia (semantic dementia), atrophy that encompassed this region was associated with a specific impairment in verbally mediated visual semantic knowledge. Finally, in a structural study of healthy adults from the fMRI experiment, gray matter density in this region related to individual variability in the processing of visual concepts. The anatomic location of these findings aligns with recent work linking the ventral-medial temporal lobe with high-level visual representation, contextual associations, and reasoning through imagination. Together this work suggests a critical role for parahippocampal cortex in linking the visual environment with knowledge systems in the human brain. PMID:26679216

Semantics of the Visual Environment Encoded in Parahippocampal Cortex.

PubMed

Bonner, Michael F; Price, Amy Rose; Peelle, Jonathan E; Grossman, Murray

2016-03-01

Semantic representations capture the statistics of experience and store this information in memory. A fundamental component of this memory system is knowledge of the visual environment, including knowledge of objects and their associations. Visual semantic information underlies a range of behaviors, from perceptual categorization to cognitive processes such as language and reasoning. Here we examine the neuroanatomic system that encodes visual semantics. Across three experiments, we found converging evidence indicating that knowledge of verbally mediated visual concepts relies on information encoded in a region of the ventral-medial temporal lobe centered on parahippocampal cortex. In an fMRI study, this region was strongly engaged by the processing of concepts relying on visual knowledge but not by concepts relying on other sensory modalities. In a study of patients with the semantic variant of primary progressive aphasia (semantic dementia), atrophy that encompassed this region was associated with a specific impairment in verbally mediated visual semantic knowledge. Finally, in a structural study of healthy adults from the fMRI experiment, gray matter density in this region related to individual variability in the processing of visual concepts. The anatomic location of these findings aligns with recent work linking the ventral-medial temporal lobe with high-level visual representation, contextual associations, and reasoning through imagination. Together, this work suggests a critical role for parahippocampal cortex in linking the visual environment with knowledge systems in the human brain.

Statistical learning using real-world scenes: extracting categorical regularities without conscious intent.

PubMed

Brady, Timothy F; Oliva, Aude

2008-07-01

Recent work has shown that observers can parse streams of syllables, tones, or visual shapes and learn statistical regularities in them without conscious intent (e.g., learn that A is always followed by B). Here, we demonstrate that these statistical-learning mechanisms can operate at an abstract, conceptual level. In Experiments 1 and 2, observers incidentally learned which semantic categories of natural scenes covaried (e.g., kitchen scenes were always followed by forest scenes). In Experiments 3 and 4, category learning with images of scenes transferred to words that represented the categories. In each experiment, the category of the scenes was irrelevant to the task. Together, these results suggest that statistical-learning mechanisms can operate at a categorical level, enabling generalization of learned regularities using existing conceptual knowledge. Such mechanisms may guide learning in domains as disparate as the acquisition of causal knowledge and the development of cognitive maps from environmental exploration.

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

ERIC Educational Resources Information Center

Alexander, Patricia A.; And Others

1995-01-01

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

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

ERIC Educational Resources Information Center

Kuhara-Kojima, Keiko; Hatano, Giyoo

1991-01-01

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

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

ERIC Educational Resources Information Center

McFarland, Daniel; Klopfer, Eric

2010-01-01

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

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

ERIC Educational Resources Information Center

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

2005-01-01

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

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

ERIC Educational Resources Information Center

Hao, Ning

2010-01-01

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

Visualization of decision processes using a cognitive architecture

NASA Astrophysics Data System (ADS)

Livingston, Mark A.; Murugesan, Arthi; Brock, Derek; Frost, Wende K.; Perzanowski, Dennis

2013-01-01

Cognitive architectures are computational theories of reasoning the human mind engages in as it processes facts and experiences. A cognitive architecture uses declarative and procedural knowledge to represent mental constructs that are involved in decision making. Employing a model of behavioral and perceptual constraints derived from a set of one or more scenarios, the architecture reasons about the most likely consequence(s) of a sequence of events. Reasoning of any complexity and depth involving computational processes, however, is often opaque and challenging to comprehend. Arguably, for decision makers who may need to evaluate or question the results of autonomous reasoning, it would be useful to be able to inspect the steps involved in an interactive, graphical format. When a chain of evidence and constraint-based decision points can be visualized, it becomes easier to explore both how and why a scenario of interest will likely unfold in a particular way. In initial work on a scheme for visualizing cognitively-based decision processes, we focus on generating graphical representations of models run in the Polyscheme cognitive architecture. Our visualization algorithm operates on a modified version of Polyscheme's output, which is accomplished by augmenting models with a simple set of tags. We provide example visualizations and discuss properties of our technique that pose challenges for our representation goals. We conclude with a summary of feedback solicited from domain experts and practitioners in the field of cognitive modeling.

Domain and Specification Models for Software Engineering

NASA Technical Reports Server (NTRS)

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

1992-01-01

This paper discusses our approach to representing application domain knowledge for specific software engineering tasks. Application domain knowledge is embodied in a domain model. Domain models are used to assist in the creation of specification models. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model. One aspect of the system-hierarchical organization is described in detail.

Temporal dynamics of the knowledge-mediated visual disambiguation process in humans: a magnetoencephalography study.

PubMed

Urakawa, Tomokazu; Ogata, Katsuya; Kimura, Takahiro; Kume, Yuko; Tobimatsu, Shozo

2015-01-01

Disambiguation of a noisy visual scene with prior knowledge is an indispensable task of the visual system. To adequately adapt to a dynamically changing visual environment full of noisy visual scenes, the implementation of knowledge-mediated disambiguation in the brain is imperative and essential for proceeding as fast as possible under the limited capacity of visual image processing. However, the temporal profile of the disambiguation process has not yet been fully elucidated in the brain. The present study attempted to determine how quickly knowledge-mediated disambiguation began to proceed along visual areas after the onset of a two-tone ambiguous image using magnetoencephalography with high temporal resolution. Using the predictive coding framework, we focused on activity reduction for the two-tone ambiguous image as an index of the implementation of disambiguation. Source analysis revealed that a significant activity reduction was observed in the lateral occipital area at approximately 120 ms after the onset of the ambiguous image, but not in preceding activity (about 115 ms) in the cuneus when participants perceptually disambiguated the ambiguous image with prior knowledge. These results suggested that knowledge-mediated disambiguation may be implemented as early as approximately 120 ms following an ambiguous visual scene, at least in the lateral occipital area, and provided an insight into the temporal profile of the disambiguation process of a noisy visual scene with prior knowledge. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Autonomously acquiring declarative and procedural knowledge for ICAT systems

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1993-01-01

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

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

PubMed

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

2013-01-01

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

Fine-Grained Semantic Categorization across the Abstract and Concrete Domains

PubMed Central

Tettamanti, Marco

2013-01-01

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

Visual Sequence Learning in Infancy: Domain-General and Domain-Specific Associations with Language

ERIC Educational Resources Information Center

Shafto, Carissa L.; Conway, Christopher M.; Field, Suzanne L.; Houston, Derek M.

2012-01-01

Research suggests that nonlinguistic sequence learning abilities are an important contributor to language development (Conway, Bauernschmidt, Huang, & Pisoni, 2010). The current study investigated visual sequence learning (VSL) as a possible predictor of vocabulary development in infants. Fifty-eight 8.5-month-old infants were presented with a…

Uncertainty Representation in Visualizations of Learning Analytics for Learners: Current Approaches and Opportunities

ERIC Educational Resources Information Center

Demmans Epp, Carrie; Bull, Susan

2015-01-01

Adding uncertainty information to visualizations is becoming increasingly common across domains since its addition helps ensure that informed decisions are made. This work has shown the difficulty that is inherent to representing uncertainty. Moreover, the representation of uncertainty has yet to be thoroughly explored in educational domains even…

Domain Coloring and the Argument Principle

ERIC Educational Resources Information Center

Farris, Frank A.

2017-01-01

The "domain-coloring algorithm" allows us to visualize complex-valued functions on the plane in a single image--an alternative to before-and-after mapping diagrams. It helps us see when a function is analytic and aids in understanding contour integrals. The culmination of this article is a visual discovery and subsequent proof of the…

Enhancing Autonomy of Aerial Systems Via Integration of Visual Sensors into Their Avionics Suite

DTIC Science & Technology

2016-09-01

aerial platform for subsequent visual sensor integration. 14. SUBJECT TERMS autonomous system, quadrotors, direct method, inverse ...CONTROLLER ARCHITECTURE .....................................................43 B. INVERSE DYNAMICS IN THE VIRTUAL DOMAIN ......................45 1...control station GPS Global-Positioning System IDVD inverse dynamics in the virtual domain ILP integer linear program INS inertial-navigation system

Integration of color, orientation, and size functional domains in the ventral pathway

PubMed Central

Ghose, Geoffrey M.; Ts’o, Daniel Y.

2017-01-01

Abstract. Functional specialization within the extrastriate areas of the ventral pathway associated with visual form analysis is poorly understood. Studies comparing the functional selectivities of neurons within the early visual areas have found that there are more similar than different between the areas. We simultaneously imaged visually evoked activation over regions of V2 and V4 and parametrically varied three visual attributes for which selectivity exists in both areas: color, orientation, and size. We found that color selective regions were observed in both areas and were of similar size and spatial distribution. However, two major areal distinctions were observed: V4 contained a greater number and diversity of color-specific regions than V2 and exhibited a higher degree of overlap between domains for different functional attributes. In V2, size and color regions were largely segregated from orientation domains, whereas in V4 both color and size regions overlapped considerably with orientation regions. Our results suggest that higher-order composite selectivities in the extrastriate cortex may arise organically from the interactions afforded by an overlap of functional domains for lower order selectivities. PMID:28573155

Flow Charts: Visualization of Vector Fields on Arbitrary Surfaces

PubMed Central

Li, Guo-Shi; Tricoche, Xavier; Weiskopf, Daniel; Hansen, Charles

2009-01-01

We introduce a novel flow visualization method called Flow Charts, which uses a texture atlas approach for the visualization of flows defined over curved surfaces. In this scheme, the surface and its associated flow are segmented into overlapping patches, which are then parameterized and packed in the texture domain. This scheme allows accurate particle advection across multiple charts in the texture domain, providing a flexible framework that supports various flow visualization techniques. The use of surface parameterization enables flow visualization techniques requiring the global view of the surface over long time spans, such as Unsteady Flow LIC (UFLIC), particle-based Unsteady Flow Advection Convolution (UFAC), or dye advection. It also prevents visual artifacts normally associated with view-dependent methods. Represented as textures, Flow Charts can be naturally integrated into hardware accelerated flow visualization techniques for interactive performance. PMID:18599918

Ontology-Driven Search and Triage: Design of a Web-Based Visual Interface for MEDLINE.

PubMed

Demelo, Jonathan; Parsons, Paul; Sedig, Kamran

2017-02-02

Diverse users need to search health and medical literature to satisfy open-ended goals such as making evidence-based decisions and updating their knowledge. However, doing so is challenging due to at least two major difficulties: (1) articulating information needs using accurate vocabulary and (2) dealing with large document sets returned from searches. Common search interfaces such as PubMed do not provide adequate support for exploratory search tasks. Our objective was to improve support for exploratory search tasks by combining two strategies in the design of an interactive visual interface by (1) using a formal ontology to help users build domain-specific knowledge and vocabulary and (2) providing multi-stage triaging support to help mitigate the information overload problem. We developed a Web-based tool, Ontology-Driven Visual Search and Triage Interface for MEDLINE (OVERT-MED), to test our design ideas. We implemented a custom searchable index of MEDLINE, which comprises approximately 25 million document citations. We chose a popular biomedical ontology, the Human Phenotype Ontology (HPO), to test our solution to the vocabulary problem. We implemented multistage triaging support in OVERT-MED, with the aid of interactive visualization techniques, to help users deal with large document sets returned from searches. Formative evaluation suggests that the design features in OVERT-MED are helpful in addressing the two major difficulties described above. Using a formal ontology seems to help users articulate their information needs with more accurate vocabulary. In addition, multistage triaging combined with interactive visualizations shows promise in mitigating the information overload problem. Our strategies appear to be valuable in addressing the two major problems in exploratory search. Although we tested OVERT-MED with a particular ontology and document collection, we anticipate that our strategies can be transferred successfully to other contexts. ©Jonathan Demelo, Paul Parsons, Kamran Sedig. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.02.2017.

Ontology-Driven Search and Triage: Design of a Web-Based Visual Interface for MEDLINE

PubMed Central

2017-01-01

Background Diverse users need to search health and medical literature to satisfy open-ended goals such as making evidence-based decisions and updating their knowledge. However, doing so is challenging due to at least two major difficulties: (1) articulating information needs using accurate vocabulary and (2) dealing with large document sets returned from searches. Common search interfaces such as PubMed do not provide adequate support for exploratory search tasks. Objective Our objective was to improve support for exploratory search tasks by combining two strategies in the design of an interactive visual interface by (1) using a formal ontology to help users build domain-specific knowledge and vocabulary and (2) providing multi-stage triaging support to help mitigate the information overload problem. Methods We developed a Web-based tool, Ontology-Driven Visual Search and Triage Interface for MEDLINE (OVERT-MED), to test our design ideas. We implemented a custom searchable index of MEDLINE, which comprises approximately 25 million document citations. We chose a popular biomedical ontology, the Human Phenotype Ontology (HPO), to test our solution to the vocabulary problem. We implemented multistage triaging support in OVERT-MED, with the aid of interactive visualization techniques, to help users deal with large document sets returned from searches. Results Formative evaluation suggests that the design features in OVERT-MED are helpful in addressing the two major difficulties described above. Using a formal ontology seems to help users articulate their information needs with more accurate vocabulary. In addition, multistage triaging combined with interactive visualizations shows promise in mitigating the information overload problem. Conclusions Our strategies appear to be valuable in addressing the two major problems in exploratory search. Although we tested OVERT-MED with a particular ontology and document collection, we anticipate that our strategies can be transferred successfully to other contexts. PMID:28153818

Fundus autofluorescence and optical coherence tomography findings in thiamine responsive megaloblastic anemia.

PubMed

Ach, Thomas; Kardorff, Rüdiger; Rohrschneider, Klaus

2015-01-01

To report ophthalmologic fundus autofluorescence and spectral domain optical coherence tomography findings in a patient with thiamine responsive megaloblastic anemia (TRMA). A 13-year-old girl with genetically proven TRMA was ophthalmologically (visual acuity, funduscopy, perimetry, electroretinogram) followed up over >5 years. Fundus imaging also included autofluorescence and spectral domain optical coherence tomography. During a 5-year follow-up, visual acuity and visual field decreased, despite a special TRMA diet. Funduscopy revealed bull's eye appearance, whereas fundus autofluorescence showed central and peripheral hyperfluorescence and perifoveal hypofluorescence. Spectral domain optical coherence tomography revealed affected inner segment ellipsoid band and irregularities in the retinal pigment epithelium and choroidea. Autofluorescence and spectral domain optical coherence tomography findings in a patient with TRMA show retinitis pigmentosa-like retina, retinal pigment epithelium, and choroid alterations. These findings might progress even under special TRMA diet, indispensable to life. Ophthalmologist should consider TRMA in patients with deafness and ophthalmologic disorders.

The effect of observational learning on students' performance, processes, and motivation in two creative domains.

PubMed

Groenendijk, Talita; Janssen, Tanja; Rijlaarsdam, Gert; van den Bergh, Huub

2013-03-01

Previous research has shown that observation can be effective for learning in various domains, for example, argumentative writing and mathematics. The question in this paper is whether observational learning can also be beneficial when learning to perform creative tasks in visual and verbal arts. We hypothesized that observation has a positive effect on performance, process, and motivation. We expected similarity in competence between the model and the observer to influence the effectiveness of observation. Sample.  A total of 131 Dutch students (10(th) grade, 15 years old) participated. Two experiments were carried out (one for visual and one for verbal arts). Participants were randomly assigned to one of three conditions; two observational learning conditions and a control condition (learning by practising). The observational learning conditions differed in instructional focus (on the weaker or the more competent model of a pair to be observed). We found positive effects of observation on creative products, creative processes, and motivation in the visual domain. In the verbal domain, observation seemed to affect the creative process, but not the other variables. The model similarity hypothesis was not confirmed. Results suggest that observation may foster learning in creative domains, especially in the visual arts. © 2011 The British Psychological Society.

Early Auditory Evoked Potential Is Modulated by Selective Attention and Related to Individual Differences in Visual Working Memory Capacity

PubMed Central

Giuliano, Ryan J.; Karns, Christina M.; Neville, Helen J.; Hillyard, Steven A.

2015-01-01

A growing body of research suggests that the predictive power of working memory (WM) capacity for measures of intellectual aptitude is due to the ability to control attention and select relevant information. Crucially, attentional mechanisms implicated in controlling access to WM are assumed to be domain-general, yet reports of enhanced attentional abilities in individuals with larger WM capacities are primarily within the visual domain. Here, we directly test the link between WM capacity and early attentional gating across sensory domains, hypothesizing that measures of visual WM capacity should predict an individual’s capacity to allocate auditory selective attention. To address this question, auditory ERPs were recorded in a linguistic dichotic listening task, and individual differences in ERP modulations by attention were correlated with estimates of WM capacity obtained in a separate visual change detection task. Auditory selective attention enhanced ERP amplitudes at an early latency (ca. 70–90 msec), with larger P1 components elicited by linguistic probes embedded in an attended narrative. Moreover, this effect was associated with greater individual estimates of visual WM capacity. These findings support the view that domain-general attentional control mechanisms underlie the wide variation of WM capacity across individuals. PMID:25000526

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

ERIC Educational Resources Information Center

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

2005-01-01

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

AuthorSynth: a collaboration network and behaviorally-based visualization tool of activation reports from the neuroscience literature.

PubMed

Sochat, Vanessa V

2015-01-01

Targeted collaboration is becoming more challenging with the ever-increasing number of publications, conferences, and academic responsibilities that the modern-day researcher must synthesize. Specifically, the field of neuroimaging had roughly 10,000 new papers in PubMed for the year 2013, presenting tens of thousands of international authors, each a potential collaborator working on some sub-domain in the field. To remove the burden of synthesizing an entire corpus of publications, talks, and conference interactions to find and assess collaborations, we combine meta-analytical neuroimaging informatics methods with machine learning and network analysis toward this goal. We present "AuthorSynth," a novel application prototype that includes (1) a collaboration network to identify researchers with similar results reported in the literature; and (2) a 2D plot-"brain lattice"-to visually summarize a single author's contribution to the field, and allow for searching of authors based on behavioral terms. This method capitalizes on intelligent synthesis of the neuroimaging literature, and demonstrates that data-driven approaches can be used to confirm existing collaborations, reveal potential ones, and identify gaps in published knowledge. We believe this tool exemplifies how methods from neuroimaging informatics can better inform researchers about progress and knowledge in the field, and enhance the modern workflow of finding collaborations.

Effects of prenatal methamphetamine exposure: a review of cognitive and neuroimaging studies.

PubMed

Kwiatkowski, Maja A; Roos, Annerine; Stein, Dan J; Thomas, Kevin G F; Donald, Kirsty

2014-06-01

Prenatal methamphetamine exposure (PME) is a significant problem in several parts of the world and poses important health risks for the developing fetus. Research on the short- and long-term outcomes of PME is scarce, however. Here, we summarize present knowledge on the cognitive and behavioral outcomes of PME, based on a review of the neuroimaging, neuropsychology, and neuroscience literature published in the past 15 years. Several studies have reported that the behavioral and cognitive sequelae of PME include broad deficits in the domains of attention, memory, and visual-motor integration. Knowledge regarding brain-behavior relationships is poor, however, in large part because imaging studies are rare. Hence, the effects of PME on developing neurocircuitry and brain architecture remain speculative, and are largely deductive. Some studies have implicated the dopamine-rich fronto-striatal pathways; however, cognitive deficits (e.g., impaired visual-motor integration) that should be associated with damage to those pathways are not manifested consistently across studies. We conclude by discussing challenges endemic to research on prenatal drug exposure, and argue that they may account for some of the inconsistencies in the extant research on PME. Studies confirming predicted brain-behavior relationships in PME, and exploring possible mechanisms underlying those relationships, are needed if neuroscience is to address the urgency of this growing public health problem.

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

PubMed

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

2004-09-01

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Seeing faces is necessary for face-domain formation.

PubMed

Arcaro, Michael J; Schade, Peter F; Vincent, Justin L; Ponce, Carlos R; Livingstone, Margaret S

2017-10-01

Here we report that monkeys raised without exposure to faces did not develop face domains, but did develop domains for other categories and did show normal retinotopic organization, indicating that early face deprivation leads to a highly selective cortical processing deficit. Therefore, experience must be necessary for the formation (or maintenance) of face domains. Gaze tracking revealed that control monkeys looked preferentially at faces, even at ages prior to the emergence of face domains, but face-deprived monkeys did not, indicating that face looking is not innate. A retinotopic organization is present throughout the visual system at birth, so selective early viewing behavior could bias category-specific visual responses toward particular retinotopic representations, thereby leading to domain formation in stereotyped locations in inferotemporal cortex, without requiring category-specific templates or biases. Thus, we propose that environmental importance influences viewing behavior, viewing behavior drives neuronal activity, and neuronal activity sculpts domain formation.

Evaluation of a visual risk communication tool: effects on knowledge and perception of blood transfusion risk.

PubMed

Lee, D H; Mehta, M D

2003-06-01

Effective risk communication in transfusion medicine is important for health-care consumers, but understanding the numerical magnitude of risks can be difficult. The objective of this study was to determine the effect of a visual risk communication tool on the knowledge and perception of transfusion risk. Laypeople were randomly assigned to receive transfusion risk information with either a written or a visual presentation format for communicating and comparing the probabilities of transfusion risks relative to other hazards. Knowledge of transfusion risk was ascertained with a multiple-choice quiz and risk perception was ascertained by psychometric scaling and principal components analysis. Two-hundred subjects were recruited and randomly assigned. Risk communication with both written and visual presentation formats increased knowledge of transfusion risk and decreased the perceived dread and severity of transfusion risk. Neither format changed the perceived knowledge and control of transfusion risk, nor the perceived benefit of transfusion. No differences in knowledge or risk perception outcomes were detected between the groups randomly assigned to written or visual presentation formats. Risk communication that incorporates risk comparisons in either written or visual presentation formats can improve knowledge and reduce the perception of transfusion risk in laypeople.

Intuitive Exploration of Volumetric Data Using Dynamic Galleries.

PubMed

Jönsson, Daniel; Falk, Martin; Ynnerman, Anders

2016-01-01

In this work we present a volume exploration method designed to be used by novice users and visitors to science centers and museums. The volumetric digitalization of artifacts in museums is of rapidly increasing interest as enhanced user experience through interactive data visualization can be achieved. This is, however, a challenging task since the vast majority of visitors are not familiar with the concepts commonly used in data exploration, such as mapping of visual properties from values in the data domain using transfer functions. Interacting in the data domain is an effective way to filter away undesired information but it is difficult to predict where the values lie in the spatial domain. In this work we make extensive use of dynamic previews instantly generated as the user explores the data domain. The previews allow the user to predict what effect changes in the data domain will have on the rendered image without being aware that visual parameters are set in the data domain. Each preview represents a subrange of the data domain where overview and details are given on demand through zooming and panning. The method has been designed with touch interfaces as the target platform for interaction. We provide a qualitative evaluation performed with visitors to a science center to show the utility of the approach.

Domain Differences in the Weights of Perceptual and Conceptual Information in Children's Categorization

ERIC Educational Resources Information Center

Diesendruck, Gil; Peretz, Shimon

2013-01-01

Visual appearance is one of the main cues children rely on when categorizing novel objects. In 3 studies, testing 128 3-year-olds and 192 5-year-olds, we investigated how various kinds of information may differentially lead children to overlook visual appearance in their categorization decisions across domains. Participants saw novel animals or…

Teaching Turkish as a Foreign Language: Extrapolating from Experimental Psychology

ERIC Educational Resources Information Center

Erdener, Dogu

2017-01-01

Speech perception is beyond the auditory domain and a multimodal process, specifically, an auditory-visual one--we process lip and face movements during speech. In this paper, the findings in cross-language studies of auditory-visual speech perception in the past two decades are interpreted to the applied domain of second language (L2)…

Visualizing ferromagnetic domains in magnetic topological insulators

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

Wang, Wenbo; Gu, G. D.; Yang, Fang

2015-05-13

We report a systematic study of ferromagnetic domains in both single-crystal and thin-film specimens of magnetic topological insulators Cr doped (Bi 0.1Sb 0.9) 2Te 3 using magnetic force microscopy (MFM). The temperature and field dependences of MFM and in situ resistance data are consistent with previous bulk transport and magnetic characterization. Bubble-like ferromagnetic domains were observed in both single crystals and thin films. Significantly, smaller domain size (~500 nm) with narrower domain wall (~150 – 300 nm) was observed in thin films of magnetic topological insulators, likely due to vertical confinement effect. As a result, these results suggest that thinmore » films are more promising for visualization of chiral edge states.« less

Multi Agent Reward Analysis for Learning in Noisy Domains

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian K.

2005-01-01

In many multi agent learning problems, it is difficult to determine, a priori, the agent reward structure that will lead to good performance. This problem is particularly pronounced in continuous, noisy domains ill-suited to simple table backup schemes commonly used in TD(lambda)/Q-learning. In this paper, we present a new reward evaluation method that allows the tradeoff between coordination among the agents and the difficulty of the learning problem each agent faces to be visualized. This method is independent of the learning algorithm and is only a function of the problem domain and the agents reward structure. We then use this reward efficiency visualization method to determine an effective reward without performing extensive simulations. We test this method in both a static and a dynamic multi-rover learning domain where the agents have continuous state spaces and where their actions are noisy (e.g., the agents movement decisions are not always carried out properly). Our results show that in the more difficult dynamic domain, the reward efficiency visualization method provides a two order of magnitude speedup in selecting a good reward. Most importantly it allows one to quickly create and verify rewards tailored to the observational limitations of the domain.

The Knowing Eye: An Applied Arts Approach to Visual Knowledge.

ERIC Educational Resources Information Center

Barnhurst, Kevin G.

Since visual knowledge of the specialties within graphics and photography is difficult to pinpoint because it is nonverbal and intuitive, graphics educators fall back on teaching technical expertise--the procedures and equipment used for newspapers, magazines, and television stations. For centuries visual knowledge was the realm of the unlettered,…

Structure-function relationships using spectral-domain optical coherence tomography: comparison with scanning laser polarimetry.

PubMed

Aptel, Florent; Sayous, Romain; Fortoul, Vincent; Beccat, Sylvain; Denis, Philippe

2010-12-01

To evaluate and compare the regional relationships between visual field sensitivity and retinal nerve fiber layer (RNFL) thickness as measured by spectral-domain optical coherence tomography (OCT) and scanning laser polarimetry. Prospective cross-sectional study. One hundred and twenty eyes of 120 patients (40 with healthy eyes, 40 with suspected glaucoma, and 40 with glaucoma) were tested on Cirrus-OCT, GDx VCC, and standard automated perimetry. Raw data on RNFL thickness were extracted for 256 peripapillary sectors of 1.40625 degrees each for the OCT measurement ellipse and 64 peripapillary sectors of 5.625 degrees each for the GDx VCC measurement ellipse. Correlations between peripapillary RNFL thickness in 6 sectors and visual field sensitivity in the 6 corresponding areas were evaluated using linear and logarithmic regression analysis. Receiver operating curve areas were calculated for each instrument. With spectral-domain OCT, the correlations (r(2)) between RNFL thickness and visual field sensitivity ranged from 0.082 (nasal RNFL and corresponding visual field area, linear regression) to 0.726 (supratemporal RNFL and corresponding visual field area, logarithmic regression). By comparison, with GDx-VCC, the correlations ranged from 0.062 (temporal RNFL and corresponding visual field area, linear regression) to 0.362 (supratemporal RNFL and corresponding visual field area, logarithmic regression). In pairwise comparisons, these structure-function correlations were generally stronger with spectral-domain OCT than with GDx VCC and with logarithmic regression than with linear regression. The largest areas under the receiver operating curve were seen for OCT superior thickness (0.963 ± 0.022; P < .001) in eyes with glaucoma and for OCT average thickness (0.888 ± 0.072; P < .001) in eyes with suspected glaucoma. The structure-function relationship was significantly stronger with spectral-domain OCT than with scanning laser polarimetry, and was better expressed logarithmically than linearly. Measurements with these 2 instruments should not be considered to be interchangeable. Copyright © 2010 Elsevier Inc. All rights reserved.

How the Human Brain Represents Perceived Dangerousness or “Predacity” of Animals

PubMed Central

Sha, Long; Guntupalli, J. Swaroop; Oosterhof, Nikolaas; Halchenko, Yaroslav O.; Nastase, Samuel A.; di Oleggio Castello, Matteo Visconti; Abdi, Hervé; Jobst, Barbara C.; Gobbini, M. Ida; Haxby, James V.

2016-01-01

Common or folk knowledge about animals is dominated by three dimensions: (1) level of cognitive complexity or “animacy;” (2) dangerousness or “predacity;” and (3) size. We investigated the neural basis of the perceived dangerousness or aggressiveness of animals, which we refer to more generally as “perception of threat.” Using functional magnetic resonance imaging (fMRI), we analyzed neural activity evoked by viewing images of animal categories that spanned the dissociable semantic dimensions of threat and taxonomic class. The results reveal a distributed network for perception of threat extending along the right superior temporal sulcus. We compared neural representational spaces with target representational spaces based on behavioral judgments and a computational model of early vision and found a processing pathway in which perceived threat emerges as a dominant dimension: whereas visual features predominate in early visual cortex and taxonomy in lateral occipital and ventral temporal cortices, these dimensions fall away progressively from posterior to anterior temporal cortices, leaving threat as the dominant explanatory variable. Our results suggest that the perception of threat in the human brain is associated with neural structures that underlie perception and cognition of social actions and intentions, suggesting a broader role for these regions than has been thought previously, one that includes the perception of potential threat from agents independent of their biological class. SIGNIFICANCE STATEMENT For centuries, philosophers have wondered how the human mind organizes the world into meaningful categories and concepts. Today this question is at the core of cognitive science, but our focus has shifted to understanding how knowledge manifests in dynamic activity of neural systems in the human brain. This study advances the young field of empirical neuroepistemology by characterizing the neural systems engaged by an important dimension in our cognitive representation of the animal kingdom ontological subdomain: how the brain represents the perceived threat, dangerousness, or “predacity” of animals. Our findings reveal how activity for domain-specific knowledge of animals overlaps the social perception networks of the brain, suggesting domain-general mechanisms underlying the representation of conspecifics and other animals. PMID:27170133

Self-Taught Low-Rank Coding for Visual Learning.

PubMed

Li, Sheng; Li, Kang; Fu, Yun

2018-03-01

The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data. In this paper, we focus on building a self-taught coding framework, which can effectively utilize the rich low-level pattern information abstracted from the auxiliary domain, in order to characterize the high-level structural information in the target domain. By leveraging a high quality dictionary learned across auxiliary and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given target set. The proposed representation learning framework is called self-taught low-rank (S-Low) coding, which can be formulated as a nonconvex rank-minimization and dictionary learning problem. We devise an efficient majorization-minimization augmented Lagrange multiplier algorithm to solve it. Based on the proposed S-Low coding mechanism, both unsupervised and supervised visual learning algorithms are derived. Extensive experiments on five benchmark data sets demonstrate the effectiveness of our approach.

Buildings classification from airborne LiDAR point clouds through OBIA and ontology driven approach

NASA Astrophysics Data System (ADS)

Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.

2013-04-01

In the last years, airborne Light Detection and Ranging (LiDAR) data proved to be a valuable information resource for a vast number of applications ranging from land cover mapping to individual surface feature extraction from complex urban environments. To extract information from LiDAR data, users apply prior knowledge. Unfortunately, there is no consistent initiative for structuring this knowledge into data models that can be shared and reused across different applications and domains. The absence of such models poses great challenges to data interpretation, data fusion and integration as well as information transferability. The intention of this work is to describe the design, development and deployment of an ontology-based system to classify buildings from airborne LiDAR data. The novelty of this approach consists of the development of a domain ontology that specifies explicitly the knowledge used to extract features from airborne LiDAR data. The overall goal of this approach is to investigate the possibility for classification of features of interest from LiDAR data by means of domain ontology. The proposed workflow is applied to the building extraction process for the region of "Biberach an der Riss" in South Germany. Strip-adjusted and georeferenced airborne LiDAR data is processed based on geometrical and radiometric signatures stored within the point cloud. Region-growing segmentation algorithms are applied and segmented regions are exported to the GeoJSON format. Subsequently, the data is imported into the ontology-based reasoning process used to automatically classify exported features of interest. Based on the ontology it becomes possible to define domain concepts, associated properties and relations. As a consequence, the resulting specific body of knowledge restricts possible interpretation variants. Moreover, ontologies are machinable and thus it is possible to run reasoning on top of them. Available reasoners (FACT++, JESS, Pellet) are used to check the consistency of the developed ontologies, and logical reasoning is performed to infer implicit relations between defined concepts. The ontology for the definition of building is specified using the Ontology Web Language (OWL). It is the most widely used ontology language that is based on Description Logics (DL). DL allows the description of internal properties of modelled concepts (roof typology, shape, area, height etc.) and relationships between objects (IS_A, MEMBER_OF/INSTANCE_OF). It captures terminological knowledge (TBox) as well as assertional knowledge (ABox) - that represents facts about concept instances, i.e. the buildings in airborne LiDAR data. To assess the classification accuracy, ground truth data generated by visual interpretation and calculated classification results in terms of precision and recall are used. The advantages of this approach are: (i) flexibility, (ii) transferability, and (iii) extendibility - i.e. ontology can be extended with further concepts, data properties and object properties.

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

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

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

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

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

PubMed Central

Yang, Zhiliang; Dienes, Zoltan

2013-01-01

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

Impact of distributed virtual reality on engineering knowledge retention and student engagement

NASA Astrophysics Data System (ADS)

Sulbaran, Tulio Alberto

Engineering Education is facing many problems, one of which is poor knowledge retention among engineering students. This problem affects the Architecture, Engineering, and Construction (A/E/C) industry, because students are unprepared for many necessary job skills. This problem of poor knowledge retention is caused by many factors, one of which is the mismatch between student learning preferences and the media used to teach engineering. The purpose of this research is to assess the impact of Distributed Virtual Reality (DVR) as an engineering teaching tool. The implementation of DVR addresses the issue of poor knowledge retention by impacting the mismatch between learning and teaching style in the visual versus verbal spectrum. Using as a point of departure three knowledge domain areas (Learning and Instruction, Distributed Virtual Reality and Crane Selection as Part of Crane Lift Planning), a DVR engineering teaching tool is developed, deployed and assessed in engineering classrooms. The statistical analysis of the data indicates that: (1) most engineering students are visual learners; (2) most students would like more classes using DVR; (3) engineering students find DVR more engaging than traditional learning methods; (4) most students find the responsiveness of the DVR environments to be either good or very good; (5) all students are able to interact with DVR and most of the students found it easy or very easy to navigate (without previous formal training in how to use DVR); (6) students' knowledge regarding the subject (crane selection) is higher after the experiment; and, (7) students' using different instructional media do not demonstrate statistical difference in knowledge retained after the experiment. This inter-disciplinary research offers opportunities for direct and immediate application in education, research, and industry, due to the fact that the instructional module developed (on crane selection as part of construction crane lift planning) can be used to convey knowledge to engineers beyond the classrooms. This instructional module can also be used as a workbench to assess parameters on engineering education such as time on task, assessment media, and long-term retention among others.

Language in Context: MEG Evidence for Modality-General and -Specific Responses to Reference Resolution

PubMed Central

2016-01-01

Abstract Successful language comprehension critically depends on our ability to link linguistic expressions to the entities they refer to. Without reference resolution, newly encountered language cannot be related to previously acquired knowledge. The human experience includes many different types of referents, some visual, some auditory, some very abstract. Does the neural basis of reference resolution depend on the nature of the referents, or do our brains use a modality-general mechanism for linking meanings to referents? Here we report evidence for both. Using magnetoencephalography (MEG), we varied both the modality of referents, which consisted either of visual or auditory objects, and the point at which reference resolution was possible within sentences. Source-localized MEG responses revealed brain activity associated with reference resolution that was independent of the modality of the referents, localized to the medial parietal lobe and starting ∼415 ms after the onset of reference resolving words. A modality-specific response to reference resolution in auditory domains was also found, in the vicinity of auditory cortex. Our results suggest that referential language processing cannot be reduced to processing in classical language regions and representations of the referential domain in modality-specific neural systems. Instead, our results suggest that reference resolution engages medial parietal cortex, which supports a mechanism for referential processing regardless of the content modality. PMID:28058272

Visual Analytics of Surveillance Data on Foodborne Vibriosis, United States, 1973–2010

PubMed Central

Sims, Jennifer N.; Isokpehi, Raphael D.; Cooper, Gabrielle A.; Bass, Michael P.; Brown, Shyretha D.; St John, Alison L.; Gulig, Paul A.; Cohly, Hari H.P.

2011-01-01

Foodborne illnesses caused by microbial and chemical contaminants in food are a substantial health burden worldwide. In 2007, human vibriosis (non-cholera Vibrio infections) became a notifiable disease in the United States. In addition, Vibrio species are among the 31 major known pathogens transmitted through food in the United States. Diverse surveillance systems for foodborne pathogens also track outbreaks, illnesses, hospitalization and deaths due to non-cholera vibrios. Considering the recognition of vibriosis as a notifiable disease in the United States and the availability of diverse surveillance systems, there is a need for the development of easily deployed visualization and analysis approaches that can combine diverse data sources in an interactive manner. Current efforts to address this need are still limited. Visual analytics is an iterative process conducted via visual interfaces that involves collecting information, data preprocessing, knowledge representation, interaction, and decision making. We have utilized public domain outbreak and surveillance data sources covering 1973 to 2010, as well as visual analytics software to demonstrate integrated and interactive visualizations of data on foodborne outbreaks and surveillance of Vibrio species. Through the data visualization, we were able to identify unique patterns and/or novel relationships within and across datasets regarding (i) causative agent; (ii) foodborne outbreaks and illness per state; (iii) location of infection; (iv) vehicle (food) of infection; (v) anatomical site of isolation of Vibrio species; (vi) patients and complications of vibriosis; (vii) incidence of laboratory-confirmed vibriosis and V. parahaemolyticus outbreaks. The additional use of emerging visual analytics approaches for interaction with data on vibriosis, including non-foodborne related disease, can guide disease control and prevention as well as ongoing outbreak investigations. PMID:22174586

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

PubMed

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

2016-09-01

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

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.

Technosocial Predictive Analytics in Support of Naturalistic Decision Making

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

Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.

2009-06-23

A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledgemore » management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.« less

Building Better Decision-Support by Using Knowledge Discovery.

ERIC Educational Resources Information Center

Jurisica, Igor

2000-01-01

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

End-Stopping Predicts Curvature Tuning along the Ventral Stream.

PubMed

Ponce, Carlos R; Hartmann, Till S; Livingstone, Margaret S

2017-01-18

Neurons in primate inferotemporal cortex (IT) are clustered into patches of shared image preferences. Functional imaging has shown that these patches are activated by natural categories (e.g., faces, body parts, and places), artificial categories (numerals, words) and geometric features (curvature and real-world size). These domains develop in the same cortical locations across monkeys and humans, which raises the possibility of common innate mechanisms. Although these commonalities could be high-level template-based categories, it is alternatively possible that the domain locations are constrained by low-level properties such as end-stopping, eccentricity, and the shape of the preferred images. To explore this, we looked for correlations among curvature preference, receptive field (RF) end-stopping, and RF eccentricity in the ventral stream. We recorded from sites in V1, V4, and posterior IT (PIT) from six monkeys using microelectrode arrays. Across all visual areas, we found a tendency for end-stopped sites to prefer curved over straight contours. Further, we found a progression in population curvature preferences along the visual hierarchy, where, on average, V1 sites preferred straight Gabors, V4 sites preferred curved stimuli, and many PIT sites showed a preference for curvature that was concave relative to fixation. Our results provide evidence that high-level functional domains may be mapped according to early rudimentary properties of the visual system. The macaque occipitotemporal cortex contains clusters of neurons with preferences for categories such as faces, body parts, and places. One common question is how these clusters (or "domains") acquire their cortical position along the ventral stream. We and other investigators previously established an fMRI-level correlation among these category domains, retinotopy, and curvature preferences: for example, in inferotemporal cortex, face- and curvature-preferring domains show a central visual field bias whereas place- and rectilinear-preferring domains show a more peripheral visual field bias. Here, we have found an electrophysiological-level explanation for the correlation among domain preference, curvature, and retinotopy based on neuronal preference for short over long contours, also called end-stopping. Copyright © 2017 the authors 0270-6474/17/370648-12$15.00/0.

PATTERNS OF CLINICALLY SIGNIFICANT COGNITIVE IMPAIRMENT IN HOARDING DISORDER.

PubMed

Mackin, R Scott; Vigil, Ofilio; Insel, Philip; Kivowitz, Alana; Kupferman, Eve; Hough, Christina M; Fekri, Shiva; Crothers, Ross; Bickford, David; Delucchi, Kevin L; Mathews, Carol A

2016-03-01

The cognitive characteristics of individuals with hoarding disorder (HD) are not well understood. Existing studies are relatively few and somewhat inconsistent but suggest that individuals with HD may have specific dysfunction in the cognitive domains of categorization, speed of information processing, and decision making. However, there have been no studies evaluating the degree to which cognitive dysfunction in these domains reflects clinically significant cognitive impairment (CI). Participants included 78 individuals who met DSM-V criteria for HD and 70 age- and education-matched controls. Cognitive performance on measures of memory, attention, information processing speed, abstract reasoning, visuospatial processing, decision making, and categorization ability was evaluated for each participant. Rates of clinical impairment for each measure were compared, as were age- and education-corrected raw scores for each cognitive test. HD participants showed greater incidence of CI on measures of visual memory, visual detection, and visual categorization relative to controls. Raw-score comparisons between groups showed similar results with HD participants showing lower raw-score performance on each of these measures. In addition, in raw-score comparisons HD participants also demonstrated relative strengths compared to control participants on measures of verbal and visual abstract reasoning. These results suggest that HD is associated with a pattern of clinically significant CI in some visually mediated neurocognitive processes including visual memory, visual detection, and visual categorization. Additionally, these results suggest HD individuals may also exhibit relative strengths, perhaps compensatory, in abstract reasoning in both verbal and visual domains. © 2015 Wiley Periodicals, Inc.

Embedding Open-domain Common-sense Knowledge from Text

PubMed Central

Goodwin, Travis; Harabagiu, Sanda

2017-01-01

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

Knowledge of Dental Health and Oral Hygiene Practices of Taiwanese Visually Impaired and Sighted Students

ERIC Educational Resources Information Center

Chang, Chien-Huey Sophie; Shih, Yeng-Hung

2004-01-01

This study investigated the dental health knowledge and oral hygiene practices of 95 students with visual impairments and 286 sighted students in Taiwan. It found that the students with visual impairments were less knowledgeable about dental health and less frequently completed oral hygiene practices than did the sighted students.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

PubMed

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A; Fells, James I; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

NASA Astrophysics Data System (ADS)

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

A meta-analysis of perceptual and cognitive functions involved in useful-field-of-view test performance.

PubMed

Woutersen, Karlijn; Guadron, Leslie; van den Berg, Albert V; Boonstra, F Nienke; Theelen, Thomas; Goossens, Jeroen

2017-12-01

The useful-field-of-view (UFOV) test measures the amount of information someone can extract from a visual scene in one glance. Its scores show relatively strong relationships with everyday activities. The UFOV test consists of three computer tests, suggested to measure processing speed and central vision, divided attention, and selective attention. However, other functions seem to be involved as well. In order to investigate the contribution of these suggested and other perceptual and cognitive functions, we performed a meta-analysis of 116 Pearson's correlation coefficients between UFOV scores and other test scores reported in 18 peer-reviewed articles. We divided these correlations into nine domains: attention, executive functioning, general cognition, memory, spatial ability, visual closure, contrast sensitivity, visual processing speed, and visual acuity. A multivariate mixed-effects model analysis revealed that each domain correlated significantly with each of the UFOV subtest scores. These correlations were stronger for Subtests 2 and 3 than for Subtest 1. Furthermore, some domains were more strongly correlated to the UFOV than others across subtests. We did not find interaction effects between subtest and domain, indicating that none of the UFOV subtests is more selectively sensitive to a particular domain than the others. Thus, none of the three UFOV subtests seem to measure one clear construct. Instead, a range of visual and cognitive functions is involved. Perhaps this is the reason for the UFOV's high ecological validity, as it involves many functions at once, making it harder to compensate if one of them fails.

Semantics of directly manipulating spatializations.

PubMed

Hu, Xinran; Bradel, Lauren; Maiti, Dipayan; House, Leanna; North, Chris; Leman, Scotland

2013-12-01

When high-dimensional data is visualized in a 2D plane by using parametric projection algorithms, users may wish to manipulate the layout of the data points to better reflect their domain knowledge or to explore alternative structures. However, few users are well-versed in the algorithms behind the visualizations, making parameter tweaking more of a guessing game than a series of decisive interactions. Translating user interactions into algorithmic input is a key component of Visual to Parametric Interaction (V2PI) [13]. Instead of adjusting parameters, users directly move data points on the screen, which then updates the underlying statistical model. However, we have found that some data points that are not moved by the user are just as important in the interactions as the data points that are moved. Users frequently move some data points with respect to some other 'unmoved' data points that they consider as spatially contextual. However, in current V2PI interactions, these points are not explicitly identified when directly manipulating the moved points. We design a richer set of interactions that makes this context more explicit, and a new algorithm and sophisticated weighting scheme that incorporates the importance of these unmoved data points into V2PI.

Visual graph query formulation and exploration: a new perspective on information retrieval at the edge

NASA Astrophysics Data System (ADS)

Kase, Sue E.; Vanni, Michelle; Knight, Joanne A.; Su, Yu; Yan, Xifeng

2016-05-01

Within operational environments decisions must be made quickly based on the information available. Identifying an appropriate knowledge base and accurately formulating a search query are critical tasks for decision-making effectiveness in dynamic situations. The spreading of graph data management tools to access large graph databases is a rapidly emerging research area of potential benefit to the intelligence community. A graph representation provides a natural way of modeling data in a wide variety of domains. Graph structures use nodes, edges, and properties to represent and store data. This research investigates the advantages of information search by graph query initiated by the analyst and interactively refined within the contextual dimensions of the answer space toward a solution. The paper introduces SLQ, a user-friendly graph querying system enabling the visual formulation of schemaless and structureless graph queries. SLQ is demonstrated with an intelligence analyst information search scenario focused on identifying individuals responsible for manufacturing a mosquito-hosted deadly virus. The scenario highlights the interactive construction of graph queries without prior training in complex query languages or graph databases, intuitive navigation through the problem space, and visualization of results in graphical format.

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

ERIC Educational Resources Information Center

Rusli, Yazmin Ahmad; Montgomery, James W.

2017-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Sizes of X-ray radiation coherent domains in thin SmS films and their visualization

NASA Astrophysics Data System (ADS)

Sharenkova, N. V.; Kaminskii, V. V.; Petrov, S. N.

2011-09-01

The size of X-ray radiation coherent domains (250 ± 20 Å) is determined in a thin polycrystalline SmS film using X-ray diffraction patterns (θ-2θ scanning, DRON-2 diffractometer, Cu K α radiation) and the Selyakov-Scherrer formula with allowance for the effect of microstrains. An image of this film is taken with a transmission electron microscope, and regions with a characteristic size of 240 Å are clearly visible in it. It is concluded that X-ray radiation coherent domains are visualized.

Incomplete Multisource Transfer Learning.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2018-02-01

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

Scrambling for anonymous visual communications

NASA Astrophysics Data System (ADS)

Dufaux, Frederic; Ebrahimi, Touradj

2005-08-01

In this paper, we present a system for anonymous visual communications. Target application is an anonymous video chat. The system is identifying faces in the video sequence by means of face detection or skin detection. The corresponding regions are subsequently scrambled. We investigate several approaches for scrambling, either in the image-domain or in the transform-domain. Experiment results show the effectiveness of the proposed system.

Visualization of evolving laser-generated structures by frequency domain tomography

NASA Astrophysics Data System (ADS)

Chang, Yenyu; Li, Zhengyan; Wang, Xiaoming; Zgadzaj, Rafal; Downer, Michael

2011-10-01

We introduce frequency domain tomography (FDT) for single-shot visualization of time-evolving refractive index structures (e.g. laser wakefields, nonlinear index structures) moving at light-speed. Previous researchers demonstrated single-shot frequency domain holography (FDH), in which a probe-reference pulse pair co- propagates with the laser-generated structure, to obtain snapshot-like images. However, in FDH, information about the structure's evolution is averaged. To visualize an evolving structure, we use several frequency domain streak cameras (FDSCs), in each of which a probe-reference pulse pair propagates at an angle to the propagation direction of the laser-generated structure. The combination of several FDSCs constitutes the FDT system. We will present experimental results for a 4-probe FDT system that has imaged the whole-beam self-focusing of a pump pulse propagating through glass in a single laser shot. Combining temporal and angle multiplexing methods, we successfully processed data from four probe pulses in one spectrometer in a single-shot. The output of data processing is a multi-frame movie of the self- focusing pulse. Our results promise the possibility of visualizing evolving laser wakefield structures that underlie laser-plasma accelerators used for multi-GeV electron acceleration.

Automatic movie skimming with general tempo analysis

NASA Astrophysics Data System (ADS)

Lee, Shih-Hung; Yeh, Chia-Hung; Kuo, C. C. J.

2003-11-01

Story units are extracted by general tempo analysis including tempos analysis including tempos of audio and visual information in this research. Although many schemes have been proposed to successfully segment video data into shots using basic low-level features, how to group shots into meaningful units called story units is still a challenging problem. By focusing on a certain type of video such as sport or news, we can explore models with the specific application domain knowledge. For movie contents, many heuristic rules based on audiovisual clues have been proposed with limited success. We propose a method to extract story units using general tempo analysis. Experimental results are given to demonstrate the feasibility and efficiency of the proposed technique.

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

PubMed

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

1995-06-01

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

Spectral Domain Optical Coherence Tomography in Glaucoma: Qualitative and Quantitative Analysis of the Optic Nerve Head and Retinal Nerve Fiber Layer (An AOS Thesis)

PubMed Central

Chen, Teresa C.

2009-01-01

Purpose: To demonstrate that video-rate spectral domain optical coherence tomography (SDOCT) can qualitatively and quantitatively evaluate optic nerve head (ONH) and retinal nerve fiber layer (RNFL) glaucomatous structural changes. To correlate quantitative SDOCT parameters with disc photography and visual fields. Methods: SDOCT images from 4 glaucoma eyes (4 patients) with varying stages of open-angle glaucoma (ie, early, moderate, late) were qualitatively contrasted with 2 age-matched normal eyes (2 patients). Of 61 other consecutive patients recruited in an institutional setting, 53 eyes (33 patients) met inclusion/exclusion criteria for quantitative studies. Images were obtained using two experimental SDOCT systems, one utilizing a superluminescent diode and the other a titanium:sapphire laser source, with axial resolutions of about 6 μm and 3 μm, respectively. Results: Classic glaucomatous ONH and RNFL structural changes were seen in SDOCT images. An SDOCT reference plane 139 μm above the retinal pigment epithelium yielded cup-disc ratios that best correlated with masked physician disc photography cup-disc ratio assessments. The minimum distance band, a novel SDOCT neuroretinal rim parameter, showed good correlation with physician cup-disc ratio assessments, visual field mean deviation, and pattern standard deviation (P values range, .0003–.024). RNFL and retinal thickness maps correlated well with disc photography and visual field testing. Conclusions: To our knowledge, this thesis presents the first comprehensive qualitative and quantitative evaluation of SDOCT images of the ONH and RNFL in glaucoma. This pilot study provides basis for developing more automated quantitative SDOCT-specific glaucoma algorithms needed for future prospective multicenter national trials. PMID:20126502

Correlated individual differences suggest a common mechanism underlying metacognition in visual perception and visual short-term memory.

PubMed

Samaha, Jason; Postle, Bradley R

2017-11-29

Adaptive behaviour depends on the ability to introspect accurately about one's own performance. Whether this metacognitive ability is supported by the same mechanisms across different tasks is unclear. We investigated the relationship between metacognition of visual perception and metacognition of visual short-term memory (VSTM). Experiments 1 and 2 required subjects to estimate the perceived or remembered orientation of a grating stimulus and rate their confidence. We observed strong positive correlations between individual differences in metacognitive accuracy between the two tasks. This relationship was not accounted for by individual differences in task performance or average confidence, and was present across two different metrics of metacognition and in both experiments. A model-based analysis of data from a third experiment showed that a cross-domain correlation only emerged when both tasks shared the same task-relevant stimulus feature. That is, metacognition for perception and VSTM were correlated when both tasks required orientation judgements, but not when the perceptual task was switched to require contrast judgements. In contrast with previous results comparing perception and long-term memory, which have largely provided evidence for domain-specific metacognitive processes, the current findings suggest that metacognition of visual perception and VSTM is supported by a domain-general metacognitive architecture, but only when both domains share the same task-relevant stimulus feature. © 2017 The Author(s).

Visual Data Exploration and Analysis - Report on the Visualization Breakout Session of the SCaLeS Workshop

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

Bethel, E. Wes; Frank, Randy; Fulcomer, Sam

Scientific visualization is the transformation of abstract information into images, and it plays an integral role in the scientific process by facilitating insight into observed or simulated phenomena. Visualization as a discipline spans many research areas from computer science, cognitive psychology and even art. Yet the most successful visualization applications are created when close synergistic interactions with domain scientists are part of the algorithmic design and implementation process, leading to visual representations with clear scientific meaning. Visualization is used to explore, to debug, to gain understanding, and as an analysis tool. Visualization is literally everywhere--images are present in this report,more » on television, on the web, in books and magazines--the common theme is the ability to present information visually that is rapidly assimilated by human observers, and transformed into understanding or insight. As an indispensable part a modern science laboratory, visualization is akin to the biologist's microscope or the electrical engineer's oscilloscope. Whereas the microscope is limited to small specimens or use of optics to focus light, the power of scientific visualization is virtually limitless: visualization provides the means to examine data that can be at galactic or atomic scales, or at any size in between. Unlike the traditional scientific tools for visual inspection, visualization offers the means to ''see the unseeable.'' Trends in demographics or changes in levels of atmospheric CO{sub 2} as a function of greenhouse gas emissions are familiar examples of such unseeable phenomena. Over time, visualization techniques evolve in response to scientific need. Each scientific discipline has its ''own language,'' verbal and visual, used for communication. The visual language for depicting electrical circuits is much different than the visual language for depicting theoretical molecules or trends in the stock market. There is no ''one visualization too'' that can serve as a panacea for all science disciplines. Instead, visualization researchers work hand in hand with domain scientists as part of the scientific research process to define, create, adapt and refine software that ''speaks the visual language'' of each scientific domain.« less

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

PubMed Central

Roth, Dan

2013-01-01

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

Trident: scalable compute archives: workflows, visualization, and analysis

NASA Astrophysics Data System (ADS)

Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Kotulla, Ralf; Henschel, Robert; Harbeck, Daniel

2016-08-01

The Astronomy scientific community has embraced Big Data processing challenges, e.g. associated with time-domain astronomy, and come up with a variety of novel and efficient data processing solutions. However, data processing is only a small part of the Big Data challenge. Efficient knowledge discovery and scientific advancement in the Big Data era requires new and equally efficient tools: modern user interfaces for searching, identifying and viewing data online without direct access to the data; tracking of data provenance; searching, plotting and analyzing metadata; interactive visual analysis, especially of (time-dependent) image data; and the ability to execute pipelines on supercomputing and cloud resources with minimal user overhead or expertise even to novice computing users. The Trident project at Indiana University offers a comprehensive web and cloud-based microservice software suite that enables the straight forward deployment of highly customized Scalable Compute Archive (SCA) systems; including extensive visualization and analysis capabilities, with minimal amount of additional coding. Trident seamlessly scales up or down in terms of data volumes and computational needs, and allows feature sets within a web user interface to be quickly adapted to meet individual project requirements. Domain experts only have to provide code or business logic about handling/visualizing their domain's data products and about executing their pipelines and application work flows. Trident's microservices architecture is made up of light-weight services connected by a REST API and/or a message bus; a web interface elements are built using NodeJS, AngularJS, and HighCharts JavaScript libraries among others while backend services are written in NodeJS, PHP/Zend, and Python. The software suite currently consists of (1) a simple work flow execution framework to integrate, deploy, and execute pipelines and applications (2) a progress service to monitor work flows and sub-work flows (3) ImageX, an interactive image visualization service (3) an authentication and authorization service (4) a data service that handles archival, staging and serving of data products, and (5) a notification service that serves statistical collation and reporting needs of various projects. Several other additional components are under development. Trident is an umbrella project, that evolved from the One Degree Imager, Portal, Pipeline, and Archive (ODI-PPA) project which we had initially refactored toward (1) a powerful analysis/visualization portal for Globular Cluster System (GCS) survey data collected by IU researchers, 2) a data search and download portal for the IU Electron Microscopy Center's data (EMC-SCA), 3) a prototype archive for the Ludwig Maximilian University's Wide Field Imager. The new Trident software has been used to deploy (1) a metadata quality control and analytics portal (RADY-SCA) for DICOM formatted medical imaging data produced by the IU Radiology Center, 2) Several prototype work flows for different domains, 3) a snapshot tool within IU's Karst Desktop environment, 4) a limited component-set to serve GIS data within the IU GIS web portal. Trident SCA systems leverage supercomputing and storage resources at Indiana University but can be configured to make use of any cloud/grid resource, from local workstations/servers to (inter)national supercomputing facilities such as XSEDE.

Knowledge Distance, Cognitive-Search Processes, and Creativity

PubMed Central

Acar, Oguz Ali; van den Ende, Jan

2016-01-01

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

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

PubMed

Acar, Oguz Ali; van den Ende, Jan

2016-05-01

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

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

PubMed

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

2017-06-01

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

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

PubMed Central

Halatchliyski, Iassen; Cress, Ulrike

2014-01-01

Using a longitudinal network analysis approach, we investigate the structural development of the knowledge base of Wikipedia in order to explain the appearance of new knowledge. The data consists of the articles in two adjacent knowledge domains: psychology and education. We analyze the development of networks of knowledge consisting of interlinked articles at seven snapshots from 2006 to 2012 with an interval of one year between them. Longitudinal data on the topological position of each article in the networks is used to model the appearance of new knowledge over time. Thus, the structural dimension of knowledge is related to its dynamics. Using multilevel modeling as well as eigenvector and betweenness measures, we explain the significance of pivotal articles that are either central within one of the knowledge domains or boundary-crossing between the two domains at a given point in time for the future development of new knowledge in the knowledge base. PMID:25365319

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

PubMed

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

2009-05-19

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

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

PubMed Central

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

2009-01-01

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

Machine Detection of Enhanced Electromechanical Energy Conversion in PbZr 0.2Ti 0.8O 3 Thin Films

DOE PAGES

Agar, Joshua C.; Cao, Ye; Naul, Brett; ...

2018-05-28

Many energy conversion, sensing, and microelectronic applications based on ferroic materials are determined by the domain structure evolution under applied stimuli. New hyperspectral, multidimensional spectroscopic techniques now probe dynamic responses at relevant length and time scales to provide an understanding of how these nanoscale domain structures impact macroscopic properties. Such approaches, however, remain limited in use because of the difficulties that exist in extracting and visualizing scientific insights from these complex datasets. Using multidimensional band-excitation scanning probe spectroscopy and adapting tools from both computer vision and machine learning, an automated workflow is developed to featurize, detect, and classify signatures ofmore » ferroelectric/ferroelastic switching processes in complex ferroelectric domain structures. This approach enables the identification and nanoscale visualization of varied modes of response and a pathway to statistically meaningful quantification of the differences between those modes. Lastly, among other things, the importance of domain geometry is spatially visualized for enhancing nanoscale electromechanical energy conversion.« less

Machine Detection of Enhanced Electromechanical Energy Conversion in PbZr 0.2Ti 0.8O 3 Thin Films

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

Agar, Joshua C.; Cao, Ye; Naul, Brett

Many energy conversion, sensing, and microelectronic applications based on ferroic materials are determined by the domain structure evolution under applied stimuli. New hyperspectral, multidimensional spectroscopic techniques now probe dynamic responses at relevant length and time scales to provide an understanding of how these nanoscale domain structures impact macroscopic properties. Such approaches, however, remain limited in use because of the difficulties that exist in extracting and visualizing scientific insights from these complex datasets. Using multidimensional band-excitation scanning probe spectroscopy and adapting tools from both computer vision and machine learning, an automated workflow is developed to featurize, detect, and classify signatures ofmore » ferroelectric/ferroelastic switching processes in complex ferroelectric domain structures. This approach enables the identification and nanoscale visualization of varied modes of response and a pathway to statistically meaningful quantification of the differences between those modes. Lastly, among other things, the importance of domain geometry is spatially visualized for enhancing nanoscale electromechanical energy conversion.« less

Beyond Ball-and-Stick: Students' Processing of Novel STEM Visualizations

ERIC Educational Resources Information Center

Hinze, Scott R.; Rapp, David N.; Williamson, Vickie M.; Shultz, Mary Jane; Deslongchamps, Ghislain; Williamson, Kenneth C.

2013-01-01

Students are frequently presented with novel visualizations introducing scientific concepts and processes normally unobservable to the naked eye. Despite being unfamiliar, students are expected to understand and employ the visualizations to solve problems. Domain experts exhibit more competency than novices when using complex visualizations, but…

Generic domain models in software engineering

NASA Technical Reports Server (NTRS)

Maiden, Neil

1992-01-01

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

Students with Low Vision Describe Their Visual Impairments and Visual Functioning

ERIC Educational Resources Information Center

Guerette, Amy R.; Lewis, Sandra; Mattingly, Cameron

2011-01-01

In the study reported here, the responses to a survey that was designed to determine the knowledge of their visual impairment of 51 students with low vision were analyzed. Although the students described their visual weaknesses and strengths, they had limited knowledge of, and difficulty communicating about, the medical aspects of their…

[Spatial domain display for interference image dataset].

PubMed

Wang, Cai-Ling; Li, Yu-Shan; Liu, Xue-Bin; Hu, Bing-Liang; Jing, Juan-Juan; Wen, Jia

2011-11-01

The requirements of imaging interferometer visualization is imminent for the user of image interpretation and information extraction. However, the conventional researches on visualization only focus on the spectral image dataset in spectral domain. Hence, the quick show of interference spectral image dataset display is one of the nodes in interference image processing. The conventional visualization of interference dataset chooses classical spectral image dataset display method after Fourier transformation. In the present paper, the problem of quick view of interferometer imager in image domain is addressed and the algorithm is proposed which simplifies the matter. The Fourier transformation is an obstacle since its computation time is very large and the complexion would be even deteriorated with the size of dataset increasing. The algorithm proposed, named interference weighted envelopes, makes the dataset divorced from transformation. The authors choose three interference weighted envelopes respectively based on the Fourier transformation, features of interference data and human visual system. After comparing the proposed with the conventional methods, the results show the huge difference in display time.

Effectiveness of touch and feel (TAF) technique on first aid measures for visually challenged.

PubMed

Mary, Helen; Sasikalaz, D; Venkatesan, Latha

2013-01-01

There is a common perception that a blind person cannot even help his own self. In order to challenge that view, a workshop for visually-impaired people to develop the skills to be independent and productive members of society was conceived. An experimental study was conducted at National Institute of Visually Handicapped, Chennai with the objective to assess the effectiveness of Touch and Feel (TAF) technique on first aid measures for the visually challenged. Total 25 visually challenged people were selected by non-probability purposive sampling technique and data was collected using demographic variable and structured knowledge questionnaire. The score obtained was categorised into three levels: inadequate (0-8), moderately adequate (8 - 17), adequate (17 -25). The study revealed that most of the visually challenged (40%) had inadequate knowledge, and 56 percent had moderately adequate and only few (4%) had adequate knowledge in the pre-test, whereas most (68%) of them had adequate knowledge in the post-test which is statistically significant at p < 0.000 with t-value 6.779. This proves that TAF technique was effective for the visually challenged. There was no association between the demographic variables and their level of knowledge regarding first aid.

Memory and linguistic/executive functions of children with borderline intellectual functioning.

PubMed

Água Dias, Andrea B; Albuquerque, Cristina P; Simões, Mário R

2017-11-08

Children with Borderline Intellectual Functioning (BIF) have received a minimal amount of research attention and have been studied in conjunction with Intellectual and Developmental Disabilities. The present study intends to broaden the knowledge of BIF, by analyzing domains such as verbal memory and visual memory, as well as tasks that rely simultaneously on memory, executive functions, and language. A cross-sectional, comparison study was carried out between a group of 40 children with BIF (mean age = 10.03; 24 male and 16 female), and a control group of 40 normal children of the same age, gender, and socioeconomic level as the BIF group. The WISC-III Full Scale IQs of the BIF group ranged from 71 to 84. The following instruments were used: Word List, Narrative Memory, Rey Complex Figure, Face Memory, Rapid Naming (both RAN and RAS tests), and Verbal Fluency. The results showed deficits in children with BIF in verbal short-term memory, rapid naming, phonemic verbal fluency, and visual short-term memory, specifically in a visual recognition task, when compared with the control group. Long-term verbal memory was impaired only in older children with BIF and long-term visual memory showed no deficit. Verbal short-term memory stands out as a limitation and visual long-term memory as a strength. Correlations between the WISC-III and neuropsychological tests scores were predominantly low. The study expands the neuropsychological characterization of children with BIF and the implications of the deficits and strengths are stressed.

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

PubMed

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

2016-01-01

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

Supporting interruption management and multimodal interface design: three meta-analyses of task performance as a function of interrupting task modality.

PubMed

Lu, Sara A; Wickens, Christopher D; Prinet, Julie C; Hutchins, Shaun D; Sarter, Nadine; Sebok, Angelia

2013-08-01

The aim of this study was to integrate empirical data showing the effects of interrupting task modality on the performance of an ongoing visual-manual task and the interrupting task itself. The goal is to support interruption management and the design of multimodal interfaces. Multimodal interfaces have been proposed as a promising means to support interruption management.To ensure the effectiveness of this approach, their design needs to be based on an analysis of empirical data concerning the effectiveness of individual and redundant channels of information presentation. Three meta-analyses were conducted to contrast performance on an ongoing visual task and interrupting tasks as a function of interrupting task modality (auditory vs. tactile, auditory vs. visual, and single modality vs. redundant auditory-visual). In total, 68 studies were included and six moderator variables were considered. The main findings from the meta-analyses are that response times are faster for tactile interrupting tasks in case of low-urgency messages.Accuracy is higher with tactile interrupting tasks for low-complexity signals but higher with auditory interrupting tasks for high-complexity signals. Redundant auditory-visual combinations are preferable for communication tasks during high workload and with a small visual angle of separation. The three meta-analyses contribute to the knowledge base in multimodal information processing and design. They highlight the importance of moderator variables in predicting the effects of interruption task modality on ongoing and interrupting task performance. The findings from this research will help inform the design of multimodal interfaces in data-rich, event-driven domains.

Beyond perceptual expertise: revisiting the neural substrates of expert object recognition

PubMed Central

Harel, Assaf; Kravitz, Dwight; Baker, Chris I.

2013-01-01

Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing primarily on results from functional brain imaging, and propose an interactive framework that incorporates the impact of high-level factors, such as attention and conceptual knowledge, in supporting expertise. This framework contrasts with the perceptual view of object expertise that has concentrated largely on stimulus-driven processing in visual cortex. One prominent version of this perceptual account has almost exclusively focused on the relation of expertise to face processing and, in terms of the neural substrates, has centered on face-selective cortical regions such as the Fusiform Face Area (FFA). We discuss the limitations of this face-centric approach as well as the more general perceptual view, and highlight that expert related activity is: (i) found throughout visual cortex, not just FFA, with a strong relationship between neural response and behavioral expertise even in the earliest stages of visual processing, (ii) found outside visual cortex in areas such as parietal and prefrontal cortices, and (iii) modulated by the attentional engagement of the observer suggesting that it is neither automatic nor driven solely by stimulus properties. These findings strongly support a framework in which object expertise emerges from extensive interactions within and between the visual system and other cognitive systems, resulting in widespread, distributed patterns of expertise-related activity across the entire cortex. PMID:24409134

Structural analysis of key gap junction domains--Lessons from genome data and disease-linked mutants.

PubMed

Bai, Donglin

2016-02-01

A gap junction (GJ) channel is formed by docking of two GJ hemichannels and each of these hemichannels is a hexamer of connexins. All connexin genes have been identified in human, mouse, and rat genomes and their homologous genes in many other vertebrates are available in public databases. The protein sequences of these connexins align well with high sequence identity in the same connexin across different species. Domains in closely related connexins and several residues in all known connexins are also well-conserved. These conserved residues form signatures (also known as sequence logos) in these domains and are likely to play important biological functions. In this review, the sequence logos of individual connexins, groups of connexins with common ancestors, and all connexins are analyzed to visualize natural evolutionary variations and the hot spots for human disease-linked mutations. Several gap junction domains are homologous, likely forming similar structures essential for their function. The availability of a high resolution Cx26 GJ structure and the subsequently-derived homology structure models for other connexin GJ channels elevated our understanding of sequence logos at the three-dimensional GJ structure level, thus facilitating the understanding of how disease-linked connexin mutants might impair GJ structure and function. This knowledge will enable the design of complementary variants to rescue disease-linked mutants. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sensitivity of visual evoked potentials and spectral domain optical coherence tomography in early relapsing remitting multiple sclerosis.

PubMed

Behbehani, Raed; Ahmed, Samar; Al-Hashel, Jasem; Rousseff, Rossen T; Alroughani, Raed

2017-02-01

Visual evoked potentials and spectral-domain optical coherence tomography are common ancillary studies that assess the visual pathways from a functional and structural aspect, respectively. To compare prevalence of abnormalities of Visual evoked potentials (VEP) and spectral-domain optical coherence tomography (SDOCT) in patients with relapsing remitting multiple sclerosis (RRMS). A cross-sectional study of 100 eyes with disease duration of less than 5 years since the diagnosis. Correlation between retinal nerve fiber layer and ganglion-cell/inner plexiform layer with pattern-reversal visual evoked potentials amplitude and latency and contrast sensitivity was performed. The prevalence of abnormalities in pattern-reversal visual VEP was 56% while that of SOCT was 48% in all eyes. There was significant negative correlations between the average RNFL (r=-0.34, p=0.001) and GCIPL (r=-0.39, p<0.001) with VEP latency. In eyes with prior optic neuritis, a significant negative correlation was seen between average RNFL (r=-0.33, p=0.037) and GCIPL (r=-0.40, p=0.010) with VEP latency. We have found higher prevalence of VEP abnormalities than SCOCT in early relapsing-remitting multiple sclerosis. This suggests that VEP has a higher sensitivity for detecting lesions of the visual pathway in patients with early RRMS. Copyright © 2016 Elsevier B.V. All rights reserved.

Visual arts training is linked to flexible attention to local and global levels of visual stimuli.

PubMed

Chamberlain, Rebecca; Wagemans, Johan

2015-10-01

Observational drawing skill has been shown to be associated with the ability to focus on local visual details. It is unclear whether superior performance in local processing is indicative of the ability to attend to, and flexibly switch between, local and global levels of visual stimuli. It is also unknown whether these attentional enhancements remain specific to observational drawing skill or are a product of a wide range of artistic activities. The current study aimed to address these questions by testing if flexible visual processing predicts artistic group membership and observational drawing skill in a sample of first-year bachelor's degree art students (n=23) and non-art students (n=23). A pattern of local and global visual processing enhancements was found in relation to artistic group membership and drawing skill, with local processing ability found to be specifically related to individual differences in drawing skill. Enhanced global processing and more fluent switching between local and global levels of hierarchical stimuli predicted both drawing skill and artistic group membership, suggesting that these are beneficial attentional mechanisms for art-making in a range of domains. These findings support a top-down attentional model of artistic expertise and shed light on the domain specific and domain-general attentional enhancements induced by proficiency in the visual arts. Copyright © 2015 Elsevier B.V. All rights reserved.

Using component technologies for web based wavelet enhanced mammographic image visualization.

PubMed

Sakellaropoulos, P; Costaridou, L; Panayiotakis, G

2000-01-01

The poor contrast detectability of mammography can be dealt with by domain specific software visualization tools. Remote desktop client access and time performance limitations of a previously reported visualization tool are addressed, aiming at more efficient visualization of mammographic image resources existing in web or PACS image servers. This effort is also motivated by the fact that at present, web browsers do not support domain-specific medical image visualization. To deal with desktop client access the tool was redesigned by exploring component technologies, enabling the integration of stand alone domain specific mammographic image functionality in a web browsing environment (web adaptation). The integration method is based on ActiveX Document Server technology. ActiveX Document is a part of Object Linking and Embedding (OLE) extensible systems object technology, offering new services in existing applications. The standard DICOM 3.0 part 10 compatible image-format specification Papyrus 3.0 is supported, in addition to standard digitization formats such as TIFF. The visualization functionality of the tool has been enhanced by including a fast wavelet transform implementation, which allows for real time wavelet based contrast enhancement and denoising operations. Initial use of the tool with mammograms of various breast structures demonstrated its potential in improving visualization of diagnostic mammographic features. Web adaptation and real time wavelet processing enhance the potential of the previously reported tool in remote diagnosis and education in mammography.

Eyes-on training and radiological expertise: an examination of expertise development and its effects on visual working memory.

PubMed

Beck, Melissa R; Martin, Benjamin A; Smitherman, Emily; Gaschen, Lorrie

2013-08-01

Our aim was to examine the specificity of the effects of acquiring expertise on visual working memory (VWM) and the degree to which higher levels of experience within the domain of expertise are associated with more efficient use of VWM. Previous research is inconsistent on whether expertise effects are specific to the area of expertise or generalize to other tasks that also involve the same cognitive processes. It is also unclear whether more training and/or experience will lead to continued improvement on domain-relevant tasks or whether a plateau could be reached. In Experiment I, veterinary medicine students completed a one-shot visual change detection task. In Experiment 2, veterinarians completed a flicker change detection task. Both experiments involved stimuli specific to the domain of radiology and general stimuli. In Experiment I, veterinary medicine students who had completed an "eyes-on" radiological training demonstrated a domain-specific effect in which performance was better on the domain-specific stimuli than on the domain-general stimuli. In Experiment 2, veterinarians again showed a domain-specific effect, but performance was unrelated to the amount of experience veterinarians had accumulated. The effect of experience is domain specific and occurs during the first few years of training, after which a plateau is reached. VWM training in one domain may not lead to improved performance on other VWM tasks. In acquiring expertise, eyes-on training is important initially, but continued experience may not be associated with further improvements in the efficiency of VWM.

Optical defocus: differential effects on size and contrast letter recognition thresholds.

PubMed

Rabin, J

1994-02-01

To determine if optical defocus produces a greater reduction in visual acuity or small-letter contrast sensitivity. Letter charts were used to measure visual acuity and small-letter contrast sensitivity (20/25 Snellen equivalent) as a function of optical defocus. Letter size (acuity) and contrast (contrast sensitivity) were varied in equal logarithmic steps to make the task the same for the two types of measurement. Both visual acuity and contrast sensitivity declined with optical defocus, but the effect was far greater in the contrast domain. However, measurement variability also was greater for contrast sensitivity. After correction for this variability, measurement in the contrast domain still proved to be a more sensitive (1.75x) index of optical defocus. Small-letter contrast sensitivity is a powerful technique for detecting subtle amounts of optical defocus. This adjunctive approach may be useful when there are small changes in resolution that are not detected by standard measures of visual acuity. Potential applications include evaluating the course of vision in refractive surgery, classification of cataracts, detection of corneal or macular edema, and detection of visual loss in the aging eye. Evaluation of candidates for occupations requiring unique visual abilities also may be enhanced by measuring resolution in the contrast domain.

Creating visual explanations improves learning.

PubMed

Bobek, Eliza; Tversky, Barbara

2016-01-01

Many topics in science are notoriously difficult for students to learn. Mechanisms and processes outside student experience present particular challenges. While instruction typically involves visualizations, students usually explain in words. Because visual explanations can show parts and processes of complex systems directly, creating them should have benefits beyond creating verbal explanations. We compared learning from creating visual or verbal explanations for two STEM domains, a mechanical system (bicycle pump) and a chemical system (bonding). Both kinds of explanations were analyzed for content and learning assess by a post-test. For the mechanical system, creating a visual explanation increased understanding particularly for participants of low spatial ability. For the chemical system, creating both visual and verbal explanations improved learning without new teaching. Creating a visual explanation was superior and benefitted participants of both high and low spatial ability. Visual explanations often included crucial yet invisible features. The greater effectiveness of visual explanations appears attributable to the checks they provide for completeness and coherence as well as to their roles as platforms for inference. The benefits should generalize to other domains like the social sciences, history, and archeology where important information can be visualized. Together, the findings provide support for the use of learner-generated visual explanations as a powerful learning tool.

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

PubMed

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

2011-01-01

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

Reliability and Validity of the Visual, Musculoskeletal, and Balance Complaints Questionnaire.

PubMed

Lundqvist, Lars-Olov; Zetterlund, Christina; Richter, Hans O

2016-09-01

To evaluate the reliability and validity of the 15-item Visual, Musculoskeletal, and Balance Complaints Questionnaire (VMB) for people with visual impairments, using confirmatory factor analysis (CFA) and with Rasch analysis for use as an outcome measure. Two studies evaluated the VMB. In Study 1, VMB data were collected from 1249 out of 3063 individuals between 18 and 104 years old who were registered at a low vision center. CFA evaluated VMB factor structure and Rasch analysis evaluated VMB scale properties. In Study 2, a subsample of 52 individuals between 27 and 67 years old with visual impairments underwent further measurements. Visual clinical assessments, neck/scapular pain, and balance assessments were collected to evaluate the convergent validity of the VMB (i.e. the domain relationship with other, theoretically predicted measures). CFA supported the a priori three-factor structure of the VMB. The factor loadings of the items on their respective domains were all statistically significant. Rasch analysis indicated disordered categories and the original 10-point scale was subsequently replaced with a 5-point scale. Each VMB domain fitted the Rasch model, showing good metric properties, including unidimensionality (explained variances ≥66% and eigenvalues <1.9), person separation (1.86 to 2.29), reliability (0.87 to 0.94), item fit (infit MnSq's >0.72 and outfit MnSq's <1.47), targeting (0.30 to 0.50 logits), and insignificant differential item functioning (all DIFs but one <0.50 logits) from gender, age, and visual status. The three VMB domains correlated significantly with relevant visual, musculoskeletal, and balance assessments, demonstrating adequate convergent validity of the VMB. The VMB is a simple, inexpensive, and quick yet reliable and valid way to screen and evaluate concurrent visual, musculoskeletal, and balance complaints, with contribution to epidemiological and intervention research and potential clinical implications for the field of health services and low vision rehabilitation.

Reliability and Validity of the Visual, Musculoskeletal, and Balance Complaints Questionnaire

PubMed Central

Lundqvist, Lars-Olov; Zetterlund, Christina; Richter, Hans O.

2016-01-01

ABSTRACT Purpose To evaluate the reliability and validity of the 15-item Visual, Musculoskeletal, and Balance Complaints Questionnaire (VMB) for people with visual impairments, using confirmatory factor analysis (CFA) and with Rasch analysis for use as an outcome measure. Methods Two studies evaluated the VMB. In Study 1, VMB data were collected from 1249 out of 3063 individuals between 18 and 104 years old who were registered at a low vision center. CFA evaluated VMB factor structure and Rasch analysis evaluated VMB scale properties. In Study 2, a subsample of 52 individuals between 27 and 67 years old with visual impairments underwent further measurements. Visual clinical assessments, neck/scapular pain, and balance assessments were collected to evaluate the convergent validity of the VMB (i.e. the domain relationship with other, theoretically predicted measures). Results CFA supported the a priori three-factor structure of the VMB. The factor loadings of the items on their respective domains were all statistically significant. Rasch analysis indicated disordered categories and the original 10-point scale was subsequently replaced with a 5-point scale. Each VMB domain fitted the Rasch model, showing good metric properties, including unidimensionality (explained variances ≥66% and eigenvalues <1.9), person separation (1.86 to 2.29), reliability (0.87 to 0.94), item fit (infit MnSq’s >0.72 and outfit MnSq’s <1.47), targeting (0.30 to 0.50 logits), and insignificant differential item functioning (all DIFs but one <0.50 logits) from gender, age, and visual status. The three VMB domains correlated significantly with relevant visual, musculoskeletal, and balance assessments, demonstrating adequate convergent validity of the VMB. Conclusions The VMB is a simple, inexpensive, and quick yet reliable and valid way to screen and evaluate concurrent visual, musculoskeletal, and balance complaints, with contribution to epidemiological and intervention research and potential clinical implications for the field of health services and low vision rehabilitation. PMID:27309524

Knowledge is power: how conceptual knowledge transforms visual cognition.

PubMed

Collins, Jessica A; Olson, Ingrid R

2014-08-01

In this review, we synthesize the existing literature demonstrating the dynamic interplay between conceptual knowledge and visual perceptual processing. We consider two theoretical frameworks that demonstrate interactions between processes and brain areas traditionally considered perceptual or conceptual. Specifically, we discuss categorical perception, in which visual objects are represented according to category membership, and highlight studies showing that category knowledge can penetrate early stages of visual analysis. We next discuss the embodied account of conceptual knowledge, which holds that concepts are instantiated in the same neural regions required for specific types of perception and action, and discuss the limitations of this framework. We additionally consider studies showing that gaining abstract semantic knowledge about objects and faces leads to behavioral and electrophysiological changes that are indicative of more efficient stimulus processing. Finally, we consider the role that perceiver goals and motivation may play in shaping the interaction between conceptual and perceptual processing. We hope to demonstrate how pervasive such interactions between motivation, conceptual knowledge, and perceptual processing are in our understanding of the visual environment, and to demonstrate the need for future research aimed at understanding how such interactions arise in the brain.

Knowledge is Power: How Conceptual Knowledge Transforms Visual Cognition

PubMed Central

Collins, Jessica A.; Olson, Ingrid R.

2014-01-01

In this review we synthesize the existing literature demonstrating the dynamic interplay between conceptual knowledge and visual perceptual processing. We consider two theoretical frameworks demonstrating interactions between processes and brain areas traditionally considered perceptual or conceptual. Specifically, we discuss categorical perception, in which visual objects are represented according to category membership, and highlight studies showing that category knowledge can penetrate early stages of visual analysis. We next discuss the embodied account of conceptual knowledge, which holds that concepts are instantiated in the same neural regions required for specific types of perception and action, and discuss the limitations of this framework. We additionally consider studies showing that gaining abstract semantic knowledge about objects and faces leads to behavioral and electrophysiological changes that are indicative of more efficient stimulus processing. Finally, we consider the role that perceiver goals and motivation may play in shaping the interaction between conceptual and perceptual processing. We hope to demonstrate how pervasive such interactions between motivation, conceptual knowledge, and perceptual processing are to our understanding of the visual environment, and demonstrate the need for future research aimed at understanding how such interactions arise in the brain. PMID:24402731

cellVIEW: a Tool for Illustrative and Multi-Scale Rendering of Large Biomolecular Datasets

PubMed Central

Le Muzic, Mathieu; Autin, Ludovic; Parulek, Julius; Viola, Ivan

2017-01-01

In this article we introduce cellVIEW, a new system to interactively visualize large biomolecular datasets on the atomic level. Our tool is unique and has been specifically designed to match the ambitions of our domain experts to model and interactively visualize structures comprised of several billions atom. The cellVIEW system integrates acceleration techniques to allow for real-time graphics performance of 60 Hz display rate on datasets representing large viruses and bacterial organisms. Inspired by the work of scientific illustrators, we propose a level-of-detail scheme which purpose is two-fold: accelerating the rendering and reducing visual clutter. The main part of our datasets is made out of macromolecules, but it also comprises nucleic acids strands which are stored as sets of control points. For that specific case, we extend our rendering method to support the dynamic generation of DNA strands directly on the GPU. It is noteworthy that our tool has been directly implemented inside a game engine. We chose to rely on a third party engine to reduce software development work-load and to make bleeding-edge graphics techniques more accessible to the end-users. To our knowledge cellVIEW is the only suitable solution for interactive visualization of large bimolecular landscapes on the atomic level and is freely available to use and extend. PMID:29291131

MotionFlow: Visual Abstraction and Aggregation of Sequential Patterns in Human Motion Tracking Data.

PubMed

Jang, Sujin; Elmqvist, Niklas; Ramani, Karthik

2016-01-01

Pattern analysis of human motions, which is useful in many research areas, requires understanding and comparison of different styles of motion patterns. However, working with human motion tracking data to support such analysis poses great challenges. In this paper, we propose MotionFlow, a visual analytics system that provides an effective overview of various motion patterns based on an interactive flow visualization. This visualization formulates a motion sequence as transitions between static poses, and aggregates these sequences into a tree diagram to construct a set of motion patterns. The system also allows the users to directly reflect the context of data and their perception of pose similarities in generating representative pose states. We provide local and global controls over the partition-based clustering process. To support the users in organizing unstructured motion data into pattern groups, we designed a set of interactions that enables searching for similar motion sequences from the data, detailed exploration of data subsets, and creating and modifying the group of motion patterns. To evaluate the usability of MotionFlow, we conducted a user study with six researchers with expertise in gesture-based interaction design. They used MotionFlow to explore and organize unstructured motion tracking data. Results show that the researchers were able to easily learn how to use MotionFlow, and the system effectively supported their pattern analysis activities, including leveraging their perception and domain knowledge.

Nodes on ropes: a comprehensive data and control flow for steering ensemble simulations.

PubMed

Waser, Jürgen; Ribičić, Hrvoje; Fuchs, Raphael; Hirsch, Christian; Schindler, Benjamin; Blöschl, Günther; Gröller, M Eduard

2011-12-01

Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and management. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done. This is in part due to the lack of a comprehensive framework which integrates and facilitates these efforts. In this paper, we tackle several problems which are related to steering a flood simulation. One issue is related to uncertainty. We need to account for uncertain knowledge about the environment, such as levee-breach locations. Furthermore, the steering process has to reveal how these uncertainties in the boundary conditions affect the confidence in the simulation outcome. Another important problem is that the simulation setup is often hidden in a black-box. We expose system internals and show that simulation steering can be comprehensible at the same time. This is important because the domain expert needs to be able to modify the simulation setup in order to include local knowledge and experience. In the proposed solution, users steer parameter studies through the World Lines interface to account for input uncertainties. The transport of steering information to the underlying data-flow components is handled by a novel meta-flow. The meta-flow is an extension to a standard data-flow network, comprising additional nodes and ropes to abstract parameter control. The meta-flow has a visual representation to inform the user about which control operations happen. Finally, we present the idea to use the data-flow diagram itself for visualizing steering information and simulation results. We discuss a case-study in collaboration with a domain expert who proposes different actions to protect a virtual city from imminent flooding. The key to choosing the best response strategy is the ability to compare different regions of the parameter space while retaining an understanding of what is happening inside the data-flow system. © 2011 IEEE

Consistent visualizations of changing knowledge

PubMed Central

Tipney, Hannah J.; Schuyler, Ronald P.; Hunter, Lawrence

2009-01-01

Networks are increasingly used in biology to represent complex data in uncomplicated symbolic form. However, as biological knowledge is continually evolving, so must those networks representing this knowledge. Capturing and presenting this type of knowledge change over time is particularly challenging due to the intimate manner in which researchers customize those networks they come into contact with. The effective visualization of this knowledge is important as it creates insight into complex systems and stimulates hypothesis generation and biological discovery. Here we highlight how the retention of user customizations, and the collection and visualization of knowledge associated provenance supports effective and productive network exploration. We also present an extension of the Hanalyzer system, ReOrient, which supports network exploration and analysis in the presence of knowledge change. PMID:21347184

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

ERIC Educational Resources Information Center

Garritz, Andoni

2010-01-01

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

End-Stopping Predicts Curvature Tuning along the Ventral Stream

PubMed Central

Hartmann, Till S.; Livingstone, Margaret S.

2017-01-01

Neurons in primate inferotemporal cortex (IT) are clustered into patches of shared image preferences. Functional imaging has shown that these patches are activated by natural categories (e.g., faces, body parts, and places), artificial categories (numerals, words) and geometric features (curvature and real-world size). These domains develop in the same cortical locations across monkeys and humans, which raises the possibility of common innate mechanisms. Although these commonalities could be high-level template-based categories, it is alternatively possible that the domain locations are constrained by low-level properties such as end-stopping, eccentricity, and the shape of the preferred images. To explore this, we looked for correlations among curvature preference, receptive field (RF) end-stopping, and RF eccentricity in the ventral stream. We recorded from sites in V1, V4, and posterior IT (PIT) from six monkeys using microelectrode arrays. Across all visual areas, we found a tendency for end-stopped sites to prefer curved over straight contours. Further, we found a progression in population curvature preferences along the visual hierarchy, where, on average, V1 sites preferred straight Gabors, V4 sites preferred curved stimuli, and many PIT sites showed a preference for curvature that was concave relative to fixation. Our results provide evidence that high-level functional domains may be mapped according to early rudimentary properties of the visual system. SIGNIFICANCE STATEMENT The macaque occipitotemporal cortex contains clusters of neurons with preferences for categories such as faces, body parts, and places. One common question is how these clusters (or “domains”) acquire their cortical position along the ventral stream. We and other investigators previously established an fMRI-level correlation among these category domains, retinotopy, and curvature preferences: for example, in inferotemporal cortex, face- and curvature-preferring domains show a central visual field bias whereas place- and rectilinear-preferring domains show a more peripheral visual field bias. Here, we have found an electrophysiological-level explanation for the correlation among domain preference, curvature, and retinotopy based on neuronal preference for short over long contours, also called end-stopping. PMID:28100746

Expertise in Problem Solving.

ERIC Educational Resources Information Center

Chi, Michelene T. H.; And Others

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

Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.

Semi-Supervised Geographical Feature Detection

NASA Astrophysics Data System (ADS)

Yu, H.; Yu, L.; Kuo, K. S.

2016-12-01

Extraction and tracking geographical features is a fundamental requirement in many geoscience fields. However, this operation has become an increasingly challenging task for domain scientists when tackling a large amount of geoscience data. Although domain scientists may have a relatively clear definition of features, it is difficult to capture the presence of features in an accurate and efficient fashion. We propose a semi-supervised approach to address large geographical feature detection. Our approach has two main components. First, we represent a heterogeneous geoscience data in a unified high-dimensional space, which can facilitate us to evaluate the similarity of data points with respect to geolocation, time, and variable values. We characterize the data from these measures, and use a set of hash functions to parameterize the initial knowledge of the data. Second, for any user query, our approach can automatically extract the initial results based on the hash functions. To improve the accuracy of querying, our approach provides a visualization interface to display the querying results and allow users to interactively explore and refine them. The user feedback will be used to enhance our knowledge base in an iterative manner. In our implementation, we use high-performance computing techniques to accelerate the construction of hash functions. Our design facilitates a parallelization scheme for feature detection and extraction, which is a traditionally challenging problem for large-scale data. We evaluate our approach and demonstrate the effectiveness using both synthetic and real world datasets.

Knowledge Discovery for Smart Grid Operation, Control, and Situation Awareness -- A Big Data Visualization Platform

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

Gu, Yi; Jiang, Huaiguang; Zhang, Yingchen

In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmitmore » the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.« less

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

PubMed

Naeymi-Rad, F

1989-01-01

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

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

PubMed

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

2016-01-01

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

Cognitive penetrability and emotion recognition in human facial expressions

PubMed Central

Marchi, Francesco

2015-01-01

Do our background beliefs, desires, and mental images influence our perceptual experience of the emotions of others? In this paper, we will address the possibility of cognitive penetration (CP) of perceptual experience in the domain of social cognition. In particular, we focus on emotion recognition based on the visual experience of facial expressions. After introducing the current debate on CP, we review examples of perceptual adaptation for facial expressions of emotion. This evidence supports the idea that facial expressions are perceptually processed as wholes. That is, the perceptual system integrates lower-level facial features, such as eyebrow orientation, mouth angle etc., into facial compounds. We then present additional experimental evidence showing that in some cases, emotion recognition on the basis of facial expression is sensitive to and modified by the background knowledge of the subject. We argue that such sensitivity is best explained as a difference in the visual experience of the facial expression, not just as a modification of the judgment based on this experience. The difference in experience is characterized as the result of the interference of background knowledge with the perceptual integration process for faces. Thus, according to the best explanation, we have to accept CP in some cases of emotion recognition. Finally, we discuss a recently proposed mechanism for CP in the face-based recognition of emotion. PMID:26150796

Creativity, brain, and art: biological and neurological considerations.

PubMed

Zaidel, Dahlia W

2014-01-01

Creativity is commonly thought of as a positive advance for society that transcends the status quo knowledge. Humans display an inordinate capacity for it in a broad range of activities, with art being only one. Most work on creativity's neural substrates measures general creativity, and that is done with laboratory tasks, whereas specific creativity in art is gleaned from acquired brain damage, largely in observing established visual artists, and some in visual de novo artists (became artists after the damage). The verb "to create" has been erroneously equated with creativity; creativity, in the classic sense, does not appear to be enhanced following brain damage, regardless of etiology. The turning to communication through art in lieu of language deficits reflects a biological survival strategy. Creativity in art, and in other domains, is most likely dependent on intact and healthy knowledge and semantic conceptual systems, which are represented in several pathways in the cortex. It is adversely affected when these systems are dysfunctional, for congenital reasons (savant autism) or because of acquired brain damage (stroke, dementia, Parkinson's), whereas inherent artistic talent and skill appear less affected. Clues to the neural substrates of general creativity and specific art creativity can be gleaned from considering that art is produced spontaneously mainly by humans, that there are unique neuroanatomical and neurofunctional organizations in the human brain, and that there are biological antecedents of innovation in animals.

Creativity, brain, and art: biological and neurological considerations

PubMed Central

Zaidel, Dahlia W.

2014-01-01

Creativity is commonly thought of as a positive advance for society that transcends the status quo knowledge. Humans display an inordinate capacity for it in a broad range of activities, with art being only one. Most work on creativity’s neural substrates measures general creativity, and that is done with laboratory tasks, whereas specific creativity in art is gleaned from acquired brain damage, largely in observing established visual artists, and some in visual de novo artists (became artists after the damage). The verb “to create” has been erroneously equated with creativity; creativity, in the classic sense, does not appear to be enhanced following brain damage, regardless of etiology. The turning to communication through art in lieu of language deficits reflects a biological survival strategy. Creativity in art, and in other domains, is most likely dependent on intact and healthy knowledge and semantic conceptual systems, which are represented in several pathways in the cortex. It is adversely affected when these systems are dysfunctional, for congenital reasons (savant autism) or because of acquired brain damage (stroke, dementia, Parkinson’s), whereas inherent artistic talent and skill appear less affected. Clues to the neural substrates of general creativity and specific art creativity can be gleaned from considering that art is produced spontaneously mainly by humans, that there are unique neuroanatomical and neurofunctional organizations in the human brain, and that there are biological antecedents of innovation in animals. PMID:24917807

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2016-02-01

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

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

PubMed

Rusli, Yazmin Ahmad; Montgomery, James W

2017-10-17

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

English Orthographic Learning in Chinese-L1 Young EFL Beginners.

PubMed

Cheng, Yu-Lin

2017-12-01

English orthographic learning, among Chinese-L1 children who were beginning to learn English as a foreign language, was documented when: (1) only visual memory was at their disposal, (2) visual memory and either some letter-sound knowledge or some semantic information was available, and (3) visual memory, some letter-sound knowledge and some semantic information were all available. When only visual memory was available, orthographic learning (measured via an orthographic choice test) was meagre. Orthographic learning was significant when either semantic information or letter-sound knowledge supplemented visual memory, with letter-sound knowledge generating greater significance. Although the results suggest that letter-sound knowledge plays a more important role than semantic information, letter-sound knowledge alone does not suffice to achieve perfect orthographic learning, as orthographic learning was greatest when letter-sound knowledge and semantic information were both available. The present findings are congruent with a view that the orthography of a foreign language drives its orthographic learning more than L1 orthographic learning experience, thus extending Share's (Cognition 55:151-218, 1995) self-teaching hypothesis to include non-alphabetic L1 children's orthographic learning of an alphabetic foreign language. The little letter-sound knowledge development observed in the experiment-I control group indicates that very little letter-sound knowledge develops in the absence of dedicated letter-sound training. Given the important role of letter-sound knowledge in English orthographic learning, dedicated letter-sound instruction is highly recommended.

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,…

A Core Knowledge Architecture of Visual Working Memory

ERIC Educational Resources Information Center

Wood, Justin N.

2011-01-01

Visual working memory (VWM) is widely thought to contain specialized buffers for retaining spatial and object information: a "spatial-object architecture." However, studies of adults, infants, and nonhuman animals show that visual cognition builds on core knowledge systems that retain more specialized representations: (1) spatiotemporal…

Experiences of building a medical data acquisition system based on two-level modeling.

PubMed

Li, Bei; Li, Jianbin; Lan, Xiaoyun; An, Ying; Gao, Wuqiang; Jiang, Yuqiao

2018-04-01

Compared to traditional software development strategies, the two-level modeling approach is more flexible and applicable to build an information system in the medical domain. However, the standards of two-level modeling such as openEHR appear complex to medical professionals. This study aims to investigate, implement, and improve the two-level modeling approach, and discusses the experience of building a unified data acquisition system for four affiliated university hospitals based on this approach. After the investigation, we simplified the approach of archetype modeling and developed a medical data acquisition system where medical experts can define the metadata for their own specialties by using a visual easy-to-use tool. The medical data acquisition system for multiple centers, clinical specialties, and diseases has been developed, and integrates the functions of metadata modeling, form design, and data acquisition. To date, 93,353 data items and 6,017 categories for 285 specific diseases have been created by medical experts, and over 25,000 patients' information has been collected. OpenEHR is an advanced two-level modeling method for medical data, but its idea to separate domain knowledge and technical concern is not easy to realize. Moreover, it is difficult to reach an agreement on archetype definition. Therefore, we adopted simpler metadata modeling, and employed What-You-See-Is-What-You-Get (WYSIWYG) tools to further improve the usability of the system. Compared with the archetype definition, our approach lowers the difficulty. Nevertheless, to build such a system, every participant should have some knowledge in both medicine and information technology domains, as these interdisciplinary talents are necessary. Copyright © 2018 Elsevier B.V. All rights reserved.

UBioLab: a web-laboratory for ubiquitous in-silico experiments.

PubMed

Bartocci, Ezio; Cacciagrano, Diletta; Di Berardini, Maria Rita; Merelli, Emanuela; Vito, Leonardo

2012-07-09

The huge and dynamic amount of bioinformatic resources (e.g., data and tools) available nowadays in Internet represents a big challenge for biologists –for what concerns their management and visualization– and for bioinformaticians –for what concerns the possibility of rapidly creating and executing in-silico experiments involving resources and activities spread over the WWW hyperspace. Any framework aiming at integrating such resources as in a physical laboratory has imperatively to tackle –and possibly to handle in a transparent and uniform way– aspects concerning physical distribution, semantic heterogeneity, co-existence of different computational paradigms and, as a consequence, of different invocation interfaces (i.e., OGSA for Grid nodes, SOAP for Web Services, Java RMI for Java objects, etc.). The framework UBioLab has been just designed and developed as a prototype following the above objective. Several architectural features –as those ones of being fully Web-based and of combining domain ontologies, Semantic Web and workflow techniques– give evidence of an effort in such a direction. The integration of a semantic knowledge management system for distributed (bioinformatic) resources, a semantic-driven graphic environment for defining and monitoring ubiquitous workflows and an intelligent agent-based technology for their distributed execution allows UBioLab to be a semantic guide for bioinformaticians and biologists providing (i) a flexible environment for visualizing, organizing and inferring any (semantics and computational) "type" of domain knowledge (e.g., resources and activities, expressed in a declarative form), (ii) a powerful engine for defining and storing semantic-driven ubiquitous in-silico experiments on the domain hyperspace, as well as (iii) a transparent, automatic and distributed environment for correct experiment executions.

The Influence of Linguistic Proficiency on Masked Text Recognition Performance in Adults With and Without Congenital Hearing Impairment.

PubMed

Huysmans, Elke; Bolk, Elske; Zekveld, Adriana A; Festen, Joost M; de Groot, Annette M B; Goverts, S Theo

2016-01-01

The authors first examined the influence of moderate to severe congenital hearing impairment (CHI) on the correctness of samples of elicited spoken language. Then, the authors used this measure as an indicator of linguistic proficiency and examined its effect on performance in language reception, independent of bottom-up auditory processing. In groups of adults with normal hearing (NH, n = 22), acquired hearing impairment (AHI, n = 22), and moderate to severe CHI (n = 21), the authors assessed linguistic proficiency by analyzing the morphosyntactic correctness of their spoken language production. Language reception skills were examined with a task for masked sentence recognition in the visual domain (text), at a readability level of 50%, using grammatically correct sentences and sentences with distorted morphosyntactic cues. The actual performance on the tasks was compared between groups. Adults with CHI made more morphosyntactic errors in spoken language production than adults with NH, while no differences were observed between the AHI and NH group. This outcome pattern sustained when comparisons were restricted to subgroups of AHI and CHI adults, matched for current auditory speech reception abilities. The data yielded no differences between groups in performance in masked text recognition of grammatically correct sentences in a test condition in which subjects could fully take advantage of their linguistic knowledge. Also, no difference between groups was found in the sensitivity to morphosyntactic distortions when processing short masked sentences, presented visually. These data showed that problems with the correct use of specific morphosyntactic knowledge in spoken language production are a long-term effect of moderate to severe CHI, independent of current auditory processing abilities. However, moderate to severe CHI generally does not impede performance in masked language reception in the visual modality, as measured in this study with short, degraded sentences. Aspects of linguistic proficiency that are affected by CHI thus do not seem to play a role in masked sentence recognition in the visual modality.

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

PubMed

Webster, C; McLinden, S; Begler, K

1995-01-01

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

Visualizing hydrophobic domains in silicone hydrogel lenses with Sudan IV.

PubMed

Jacob, Jean T; Levet, Jacques; Edwards, Tamika A; Dassanayake, Nissanke; Ketelson, Howard

2012-06-08

A lipophilic dye is used to investigate the degree to which the surface and bulk hydrophobic domains of the lenses can be imaged and to identify specific changes in the availability of those domains after in vitro wear and cleaning conditions. The effect of a multipurpose solution (MPS), OPTI-FREE RepleniSH, on lens hydrophobic domains was also investigated. Hydrophobic domains were determined using a saturated solution of Sudan IV. Staining periods of 30 minutes and 16 hours were used to determine surface versus bulk hydrophobic domains. Four types of silicone hydrogel lens materials were tested. The degree of staining was visually documented by photography and quantitatively determined by extraction and analysis of the total amount of dye adsorbed. Specific differences in staining were found for all control lenses. Exposure to in vitro wear conditions significantly decreased the staining response for all lens types as compared with unworn lenses (P = 0.001). However, the trend of staining remained the same: balafilcon A > galyfilcon A > senofilcon A > lotrafilcon B. MPS decreased the extent of staining; the degree of its effect varied with lens type. Hydrophobic staining with Sudan IV visualized domains on and within silicone hydrogel lenses. Differences in staining response after exposure to wear and cleaning conditions indicate the potential for protein and lipid deposition on the different lens types and the ability of MPS to affect that deposition. Hydrophobic staining may be useful for determining differences in surface modification and lipophilicity of silicone hydrogel lenses.

Presentation planning using an integrated knowledge base

NASA Technical Reports Server (NTRS)

Arens, Yigal; Miller, Lawrence; Sondheimer, Norman

1988-01-01

A description is given of user interface research aimed at bringing together multiple input and output modes in a way that handles mixed mode input (commands, menus, forms, natural language), interacts with a diverse collection of underlying software utilities in a uniform way, and presents the results through a combination of output modes including natural language text, maps, charts and graphs. The system, Integrated Interfaces, derives much of its ability to interact uniformly with the user and the underlying services and to build its presentations, from the information present in a central knowledge base. This knowledge base integrates models of the application domain (Navy ships in the Pacific region, in the current demonstration version); the structure of visual displays and their graphical features; the underlying services (data bases and expert systems); and interface functions. The emphasis is on a presentation planner that uses the knowledge base to produce multi-modal output. There has been a flurry of recent work in user interface management systems. (Several recent examples are listed in the references). Existing work is characterized by an attempt to relieve the software designer of the burden of handcrafting an interface for each application. The work has generally focused on intelligently handling input. This paper deals with the other end of the pipeline - presentations.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

A Short Note on Rules and Higher Order Rules.

ERIC Educational Resources Information Center

Scandura, Joseph M.

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

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

ERIC Educational Resources Information Center

Scott, Brianna M.; Berman, Ashleigh F.

2013-01-01

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

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

ERIC Educational Resources Information Center

Ricks, Travis Rex; Wiley, Jennifer

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

Domain-Specific Knowledge and General Skills in Reading Comprehension.

ERIC Educational Resources Information Center

Kuhara-Kojima, Keiko; Hatano, Giyoo

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

Accelerated defect visualization of microelectronic systems using binary search with fixed pitch-catch distance laser ultrasonic scanning

NASA Astrophysics Data System (ADS)

Park, Byeongjin; Sohn, Hoon

2018-04-01

The practicality of laser ultrasonic scanning is limited because scanning at a high spatial resolution demands a prohibitively long scanning time. Inspired by binary search, an accelerated defect visualization technique is developed to visualize defect with a reduced scanning time. The pitch-catch distance between the excitation point and the sensing point is also fixed during scanning to maintain a high signal-to-noise ratio of measured ultrasonic responses. The approximate defect boundary is identified by examining the interactions between ultrasonic waves and defect observed at the scanning points that are sparsely selected by a binary search algorithm. Here, a time-domain laser ultrasonic response is transformed into a spatial ultrasonic domain response using a basis pursuit approach so that the interactions between ultrasonic waves and defect can be better identified in the spatial ultrasonic domain. Then, the area inside the identified defect boundary is visualized as defect. The performance of the proposed defect visualization technique is validated through an experiment on a semiconductor chip. The proposed defect visualization technique accelerates the defect visualization process in three aspects: (1) The number of measurements that is necessary for defect visualization is dramatically reduced by a binary search algorithm; (2) The number of averaging that is necessary to achieve a high signal-to-noise ratio is reduced by maintaining the wave propagation distance short; and (3) With the proposed technique, defect can be identified with a lower spatial resolution than the spatial resolution required by full-field wave propagation imaging.

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.

VisOHC: Designing Visual Analytics for Online Health Communities

PubMed Central

Kwon, Bum Chul; Kim, Sung-Hee; Lee, Sukwon; Choo, Jaegul; Huh, Jina; Yi, Ji Soo

2015-01-01

Through online health communities (OHCs), patients and caregivers exchange their illness experiences and strategies for overcoming the illness, and provide emotional support. To facilitate healthy and lively conversations in these communities, their members should be continuously monitored and nurtured by OHC administrators. The main challenge of OHC administrators' tasks lies in understanding the diverse dimensions of conversation threads that lead to productive discussions in their communities. In this paper, we present a design study in which three domain expert groups participated, an OHC researcher and two OHC administrators of online health communities, which was conducted to find with a visual analytic solution. Through our design study, we characterized the domain goals of OHC administrators and derived tasks to achieve these goals. As a result of this study, we propose a system called VisOHC, which visualizes individual OHC conversation threads as collapsed boxes–a visual metaphor of conversation threads. In addition, we augmented the posters' reply authorship network with marks and/or beams to show conversation dynamics within threads. We also developed unique measures tailored to the characteristics of OHCs, which can be encoded for thread visualizations at the users' requests. Our observation of the two administrators while using VisOHC showed that it supports their tasks and reveals interesting insights into online health communities. Finally, we share our methodological lessons on probing visual designs together with domain experts by allowing them to freely encode measurements into visual variables. PMID:26529688

VisOHC: Designing Visual Analytics for Online Health Communities.

PubMed

Kwon, Bum Chul; Kim, Sung-Hee; Lee, Sukwon; Choo, Jaegul; Huh, Jina; Yi, Ji Soo

2016-01-01

Through online health communities (OHCs), patients and caregivers exchange their illness experiences and strategies for overcoming the illness, and provide emotional support. To facilitate healthy and lively conversations in these communities, their members should be continuously monitored and nurtured by OHC administrators. The main challenge of OHC administrators' tasks lies in understanding the diverse dimensions of conversation threads that lead to productive discussions in their communities. In this paper, we present a design study in which three domain expert groups participated, an OHC researcher and two OHC administrators of online health communities, which was conducted to find with a visual analytic solution. Through our design study, we characterized the domain goals of OHC administrators and derived tasks to achieve these goals. As a result of this study, we propose a system called VisOHC, which visualizes individual OHC conversation threads as collapsed boxes-a visual metaphor of conversation threads. In addition, we augmented the posters' reply authorship network with marks and/or beams to show conversation dynamics within threads. We also developed unique measures tailored to the characteristics of OHCs, which can be encoded for thread visualizations at the users' requests. Our observation of the two administrators while using VisOHC showed that it supports their tasks and reveals interesting insights into online health communities. Finally, we share our methodological lessons on probing visual designs together with domain experts by allowing them to freely encode measurements into visual variables.

Neurodevelopmental variability in three young girls with a rare chromosomal disorder, 48, XXXX.

PubMed

Samango-Sprouse, Carole; Keen, Colleen; Mitchell, Francie; Sadeghin, Teresa; Gropman, Andrea

2015-10-01

Fourty eight, XXXX is a rare chromosomal aneuploidy associated with neurocognitive deficits, speech and language disorders and executive dysfunction but the scarcity and variability of reported cases limit our understanding of the 48, XXXX phenotype. To our knowledge, this is the first study to report on the neurodevelopmental profile of three young females with 48, XXXX. Patient 1 (age = 11.0), Patient 2 (age = 10.9), and Patient 3 (age = 6.4) were evaluated using comprehensive neurodevelopmental assessments. Parent questionnaires were completed to assess behavioral and psychosocial domains including executive function, ADHD and anxiety. Nonverbal intelligence quotients were 56, 80, and 91 for Patients 1, 2, and 3, respectively. There were significantly impaired visual motor capacities in graphomotor and perceptual domains below the 5th centile in Patients 1 and 2, and mildly impaired visual perception skills in Patient 3. All three patients had Childhood Apraxia of Speech (CAS) but of varying severity and similar executive dysfunction, externalizing problems and social difficulties. Familial learning disabilities (FLD) in Patient 1 and the co-occurrence of ADHD in Patient's 1 and 2 may contribute to their more impaired cognitive performances relative to Patient 3 who is the second reported case of 48, XXXX to have normal intellect. These distinct and overlapping characteristics expand the phenotypic profile of 48, XXXX and may be used in the counseling of families and treatment of children with 48, XXXX. © 2015 Wiley Periodicals, Inc.

Validation of the Preverbal Visual Assessment (PreViAs) questionnaire.

PubMed

García-Ormaechea, Inés; González, Inmaculada; Duplá, María; Andres, Eva; Pueyo, Victoria

2014-10-01

Visual cognitive integrative functions need to be evaluated by a behavioral assessment, which requires an experienced evaluator. The Preverbal Visual Assessment (PreViAs) questionnaire was designed to evaluate these functions, both in general pediatric population or in children with high risk of visual cognitive problems, through primary caregivers' answers. We aimed to validate the PreViAs questionnaire by comparing caregiver reports with results from a comprehensive clinical protocol. A total of 220 infants (<2 years old) were divided into two groups according to visual development, as determined by the clinical protocol. Their primary caregivers completed the PreViAs questionnaire, which consists of 30 questions related to one or more visual domains: visual attention, visual communication, visual-motor coordination, and visual processing. Questionnaire answers were compared with results of behavioral assessments performed by three pediatric ophthalmologists. Results of the clinical protocol classified 128 infants as having normal visual maturation, and 92 as having abnormal visual maturation. The specificity of PreViAs questionnaire was >80%, and sensitivity was 64%-79%. More than 80% of the infants were correctly classified, and test-retest reliability exceeded 0.9 for all domains. The PreViAs questionnaire is useful to detect abnormal visual maturation in infants from birth to 24months of age. It improves the anamnesis process in infants at risk of visual dysfunctions. Copyright © 2014. Published by Elsevier Ireland Ltd.

The Visual Representation and Acquisition of Driving Knowledge for Autonomous Vehicle

NASA Astrophysics Data System (ADS)

Zhang, Zhaoxia; Jiang, Qing; Li, Ping; Song, LiangTu; Wang, Rujing; Yu, Biao; Mei, Tao

2017-09-01

In this paper, the driving knowledge base of autonomous vehicle is designed. Based on the driving knowledge modeling system, the driving knowledge of autonomous vehicle is visually acquired, managed, stored, and maintenanced, which has vital significance for creating the development platform of intelligent decision-making systems of automatic driving expert systems for autonomous vehicle.

Combination of visual and symbolic knowledge: A survey in anatomy.

PubMed

Banerjee, Imon; Patané, Giuseppe; Spagnuolo, Michela

2017-01-01

In medicine, anatomy is considered as the most discussed field and results in a huge amount of knowledge, which is heterogeneous and covers aspects that are mostly independent in nature. Visual and symbolic modalities are mainly adopted for exemplifying knowledge about human anatomy and are crucial for the evolution of computational anatomy. In particular, a tight integration of visual and symbolic modalities is beneficial to support knowledge-driven methods for biomedical investigation. In this paper, we review previous work on the presentation and sharing of anatomical knowledge, and the development of advanced methods for computational anatomy, also focusing on the key research challenges for harmonizing symbolic knowledge and spatial 3D data. Copyright © 2016 Elsevier Ltd. All rights reserved.

A knowledge based system for scientific data visualization

NASA Technical Reports Server (NTRS)

Senay, Hikmet; Ignatius, Eve

1992-01-01

A knowledge-based system, called visualization tool assistant (VISTA), which was developed to assist scientists in the design of scientific data visualization techniques, is described. The system derives its knowledge from several sources which provide information about data characteristics, visualization primitives, and effective visual perception. The design methodology employed by the system is based on a sequence of transformations which decomposes a data set into a set of data partitions, maps this set of partitions to visualization primitives, and combines these primitives into a composite visualization technique design. Although the primary function of the system is to generate an effective visualization technique design for a given data set by using principles of visual perception the system also allows users to interactively modify the design, and renders the resulting image using a variety of rendering algorithms. The current version of the system primarily supports visualization techniques having applicability in earth and space sciences, although it may easily be extended to include other techniques useful in other disciplines such as computational fluid dynamics, finite-element analysis and medical imaging.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2015-01-01

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

Tracking real-time neural activation of conceptual knowledge using single-trial event-related potentials.

PubMed

Amsel, Ben D

2011-04-01

Empirically derived semantic feature norms categorized into different types of knowledge (e.g., visual, functional, auditory) can be summed to create number-of-feature counts per knowledge type. Initial evidence suggests several such knowledge types may be recruited during language comprehension. The present study provides a more detailed understanding of the timecourse and intensity of influence of several such knowledge types on real-time neural activity. A linear mixed-effects model was applied to single trial event-related potentials for 207 visually presented concrete words measured on total number of features (semantic richness), imageability, and number of visual motion, color, visual form, smell, taste, sound, and function features. Significant influences of multiple feature types occurred before 200ms, suggesting parallel neural computation of word form and conceptual knowledge during language comprehension. Function and visual motion features most prominently influenced neural activity, underscoring the importance of action-related knowledge in computing word meaning. The dynamic time courses and topographies of these effects are most consistent with a flexible conceptual system wherein temporally dynamic recruitment of representations in modal and supramodal cortex are a crucial element of the constellation of processes constituting word meaning computation in the brain. Copyright © 2011 Elsevier Ltd. All rights reserved.

Superimposition, symbology, visual attention, and the head-up display

NASA Technical Reports Server (NTRS)

Martin-Emerson, R.; Wickens, C. D.

1997-01-01

In two experiments we examined a number of related factors postulated to influence head-up display (HUD) performance. We addressed the benefit of reduced scanning and the cost of increasing the number of elements in the visual field by comparing a superimposed HUD with an identical display in a head-down position in varying visibility conditions. We explored the extent to which the characteristics of HUD symbology support a division of attention by contrasting conformal symbology (which links elements of the display image to elements of the far domain) with traditional instrument landing system (ILS) symbology. Together the two experiments provide strong evidence that minimizing scanning between flight instruments and the far domain contributes substantially to the observed HUD performance advantage. Experiment 1 provides little evidence for a performance cost attributable to visual clutter. In Experiment 2 the pattern of differences in lateral tracking error between conformal and traditional ILS symbology supports the hypothesis that, to the extent that the symbology forms an object with the far domain, attention may be divided between the superimposed image and its counterpart in the far domain.

Supporting students' knowledge integration with technology-enhanced inquiry curricula

NASA Astrophysics Data System (ADS)

Chiu, Jennifer Lopseen

Dynamic visualizations of scientific phenomena have the potential to transform how students learn and understand science. Dynamic visualizations enable interaction and experimentation with unobservable atomic-level phenomena. A series of studies clarify the conditions under which embedding dynamic visualizations in technology-enhanced inquiry instruction can help students develop robust and durable chemistry knowledge. Using the knowledge integration perspective, I designed Chemical Reactions, a technology-enhanced curriculum unit, with a partnership of teachers, educational researchers, and chemists. This unit guides students in an exploration of how energy and chemical reactions relate to climate change. It uses powerful dynamic visualizations to connect atomic level interactions to the accumulation of greenhouse gases. The series of studies were conducted in typical classrooms in eleven high schools across the country. This dissertation describes four studies that contribute to understanding of how visualizations can be used to transform chemistry learning. The efficacy study investigated the impact of the Chemical Reactions unit compared to traditional instruction using pre-, post- and delayed posttest assessments. The self-monitoring study used self-ratings in combination with embedded assessments to explore how explanation prompts help students learn from dynamic visualizations. The self-regulation study used log files of students' interactions with the learning environment to investigate how external feedback and explanation prompts influence students' exploration of dynamic visualizations. The explanation study compared specific and general explanation prompts to explore the processes by which explanations benefit learning with dynamic visualizations. These studies delineate the conditions under which dynamic visualizations embedded in inquiry instruction can enhance student outcomes. The studies reveal that visualizations can be deceptively clear, deterring learners from exploring details. Asking students to generate explanations helps them realize what they don't understand and can spur students to revisit visualizations to remedy gaps in their knowledge. The studies demonstrate that science instruction focused on complex topics can succeed by combining visualizations with generative activities to encourage knowledge integration. Students are more successful at monitoring their progress and remedying gaps in knowledge when required to distinguish among alternative explanations. The results inform the design of technology-enhanced science instruction for typical classrooms.

Real-Time Single Molecule Visualization of SH2 Domain Membrane Recruitment in Growth Factor Stimulated Cells.

PubMed

Oh, Dongmyung

2017-01-01

In the last decade, single molecule tracking (SMT) techniques have emerged as a versatile tool for molecular cell biology research. This approach allows researchers to monitor the real-time behavior of individual molecules in living cells with nanometer and millisecond resolution. As a result, it is possible to visualize biological processes as they occur at a molecular level in real time. Here we describe a method for the real-time visualization of SH2 domain membrane recruitment from the cytoplasm to epidermal growth factor (EGF) induced phosphotyrosine sites on the EGF receptor. Further, we describe methods that utilize SMT data to define SH2 domain membrane dynamics parameters such as binding (τ), dissociation (k d ), and diffusion (D) rates. Together these methods may allow us to gain greater understanding of signal transduction dynamics and the molecular basis of disease-related aberrant pathways.

Functional implications of orientation maps in primary visual cortex

NASA Astrophysics Data System (ADS)

Koch, Erin; Jin, Jianzhong; Alonso, Jose M.; Zaidi, Qasim

2016-11-01

Stimulus orientation in the primary visual cortex of primates and carnivores is mapped as iso-orientation domains radiating from pinwheel centres, where orientation preferences of neighbouring cells change circularly. Whether this orientation map has a function is currently debated, because many mammals, such as rodents, do not have such maps. Here we show that two fundamental properties of visual cortical responses, contrast saturation and cross-orientation suppression, are stronger within cat iso-orientation domains than at pinwheel centres. These differences develop when excitation (not normalization) from neighbouring oriented neurons is applied to different cortical orientation domains and then balanced by inhibition from un-oriented neurons. The functions of the pinwheel mosaic emerge from these local intra-cortical computations: Narrower tuning, greater cross-orientation suppression and higher contrast gain of iso-orientation cells facilitate extraction of object contours from images, whereas broader tuning, greater linearity and less suppression of pinwheel cells generate selectivity for surface patterns and textures.

Human-computer interface including haptically controlled interactions

DOEpatents

Anderson, Thomas G.

2005-10-11

The present invention provides a method of human-computer interfacing that provides haptic feedback to control interface interactions such as scrolling or zooming within an application. Haptic feedback in the present method allows the user more intuitive control of the interface interactions, and allows the user's visual focus to remain on the application. The method comprises providing a control domain within which the user can control interactions. For example, a haptic boundary can be provided corresponding to scrollable or scalable portions of the application domain. The user can position a cursor near such a boundary, feeling its presence haptically (reducing the requirement for visual attention for control of scrolling of the display). The user can then apply force relative to the boundary, causing the interface to scroll the domain. The rate of scrolling can be related to the magnitude of applied force, providing the user with additional intuitive, non-visual control of scrolling.

DelPhiForce web server: electrostatic forces and energy calculations and visualization.

PubMed

Li, Lin; Jia, Zhe; Peng, Yunhui; Chakravorty, Arghya; Sun, Lexuan; Alexov, Emil

2017-11-15

Electrostatic force is an essential component of the total force acting between atoms and macromolecules. Therefore, accurate calculations of electrostatic forces are crucial for revealing the mechanisms of many biological processes. We developed a DelPhiForce web server to calculate and visualize the electrostatic forces at molecular level. DelPhiForce web server enables modeling of electrostatic forces on individual atoms, residues, domains and molecules, and generates an output that can be visualized by VMD software. Here we demonstrate the usage of the server for various biological problems including protein-cofactor, domain-domain, protein-protein, protein-DNA and protein-RNA interactions. The DelPhiForce web server is available at: http://compbio.clemson.edu/delphi-force. delphi@clemson.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

MEVA--An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices.

PubMed

Helbig, Carolin; Bilke, Lars; Bauer, Hans-Stefan; Böttinger, Michael; Kolditz, Olaf

2015-01-01

To achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work. Instead of attempting to develop yet another new visualization system to fulfill all possible needs in this application domain, our approach is to provide a flexible workflow that combines different existing state-of-the-art visualization software components in order to hide the complexity of 3D data visualization tools from the end user. To complete the workflow and to enable the domain scientists to interactively visualize their data without advanced skills in 3D visualization systems, we developed a lightweight custom visualization application (MEVA - multifaceted environmental data visualization application) that supports the most relevant visualization and interaction techniques and can be easily deployed. Specifically, our workflow combines a variety of different data abstraction methods provided by a state-of-the-art 3D visualization application with the interaction and presentation features of a computer-games engine. Our customized application includes solutions for the analysis of multirun data, specifically with respect to data uncertainty and differences between simulation runs. In an iterative development process, our easy-to-use application was developed in close cooperation with meteorologists and visualization experts. The usability of the application has been validated with user tests. We report on how this application supports the users to prove and disprove existing hypotheses and discover new insights. In addition, the application has been used at public events to communicate research results.

MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices

PubMed Central

Helbig, Carolin; Bilke, Lars; Bauer, Hans-Stefan; Böttinger, Michael; Kolditz, Olaf

2015-01-01

Background To achieve more realistic simulations, meteorologists develop and use models with increasing spatial and temporal resolution. The analyzing, comparing, and visualizing of resulting simulations becomes more and more challenging due to the growing amounts and multifaceted character of the data. Various data sources, numerous variables and multiple simulations lead to a complex database. Although a variety of software exists suited for the visualization of meteorological data, none of them fulfills all of the typical domain-specific requirements: support for quasi-standard data formats and different grid types, standard visualization techniques for scalar and vector data, visualization of the context (e.g., topography) and other static data, support for multiple presentation devices used in modern sciences (e.g., virtual reality), a user-friendly interface, and suitability for cooperative work. Methods and Results Instead of attempting to develop yet another new visualization system to fulfill all possible needs in this application domain, our approach is to provide a flexible workflow that combines different existing state-of-the-art visualization software components in order to hide the complexity of 3D data visualization tools from the end user. To complete the workflow and to enable the domain scientists to interactively visualize their data without advanced skills in 3D visualization systems, we developed a lightweight custom visualization application (MEVA - multifaceted environmental data visualization application) that supports the most relevant visualization and interaction techniques and can be easily deployed. Specifically, our workflow combines a variety of different data abstraction methods provided by a state-of-the-art 3D visualization application with the interaction and presentation features of a computer-games engine. Our customized application includes solutions for the analysis of multirun data, specifically with respect to data uncertainty and differences between simulation runs. In an iterative development process, our easy-to-use application was developed in close cooperation with meteorologists and visualization experts. The usability of the application has been validated with user tests. We report on how this application supports the users to prove and disprove existing hypotheses and discover new insights. In addition, the application has been used at public events to communicate research results. PMID:25915061

Assessment of nutritional status in the elderly: a proposed function-driven model.

PubMed

Engelheart, Stina; Brummer, Robert

2018-01-01

There is no accepted or standardized definition of 'malnutrition'. Hence, there is also no definition of what constitutes an adequate nutritional status. In elderly people, assessment of nutritional status is complex and is complicated by multi-morbidity and disabilities combined with nutrition-related problems, such as dysphagia, decreased appetite, fatigue, and muscle weakness. We propose a nutritional status model that presents nutritional status from a comprehensive functional perspective. This model visualizes the complexity of the nutritional status in elderly people. The presented model could be interpreted as the nutritional status is conditional to a person's optimal function or situation. Another way of looking at it might be that a person's nutritional status affects his or her optimal situation. The proposed model includes four domains: (1) physical function and capacity; (2) health and somatic disorders; (3) food and nutrition; and (4) cognitive, affective, and sensory function. Each domain has a major impact on nutritional status, which in turn has a major impact on the outcome of each domain. Nutritional status is a multifaceted concept and there exist several knowledge gaps in the diagnosis, prevention, and optimization of treatment of inadequate nutritional status in elderly people. The nutritional status model may be useful in nutritional assessment research, as well as in the clinical setting.

Good vibrations: tactile feedback in support of attention allocation and human-automation coordination in event-driven domains.

PubMed

Sklar, A E; Sarter, N B

1999-12-01

Observed breakdowns in human-machine communication can be explained, in part, by the nature of current automation feedback, which relies heavily on focal visual attention. Such feedback is not well suited for capturing attention in case of unexpected changes and events or for supporting the parallel processing of large amounts of data in complex domains. As suggested by multiple-resource theory, one possible solution to this problem is to distribute information across various sensory modalities. A simulator study was conducted to compare the effectiveness of visual, tactile, and redundant visual and tactile cues for indicating unexpected changes in the status of an automated cockpit system. Both tactile conditions resulted in higher detection rates for, and faster response times to, uncommanded mode transitions. Tactile feedback did not interfere with, nor was its effectiveness affected by, the performance of concurrent visual tasks. The observed improvement in task-sharing performance indicates that the introduction of tactile feedback is a promising avenue toward better supporting human-machine communication in event-driven, information-rich domains.

Model-based software design

NASA Technical Reports Server (NTRS)

Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui; Yenne, Britt; Vansickle, Larry; Ballantyne, Michael

1992-01-01

Domain-specific knowledge is required to create specifications, generate code, and understand existing systems. Our approach to automating software design is based on instantiating an application domain model with industry-specific knowledge and then using that model to achieve the operational goals of specification elicitation and verification, reverse engineering, and code generation. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model.

Sentiment classification technology based on Markov logic networks

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

Supporting Knowledge Integration in Chemistry with a Visualization-Enhanced Inquiry Unit

ERIC Educational Resources Information Center

Chiu, Jennifer L.; Linn, Marcia C.

2014-01-01

This paper describes the design and impact of an inquiry-oriented online curriculum that takes advantage of dynamic molecular visualizations to improve students' understanding of chemical reactions. The visualization-enhanced unit uses research-based guidelines following the knowledge integration framework to help students develop coherent…

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

NASA Astrophysics Data System (ADS)

Wu, Jiangning; Wang, Xiaohuan

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

Effective domain-dependent reuse in medical knowledge bases.

PubMed

Dojat, M; Pachet, F

1995-12-01

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

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

PubMed

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

2015-10-01

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

High-power graphic computers for visual simulation: a real-time--rendering revolution

NASA Technical Reports Server (NTRS)

Kaiser, M. K.

1996-01-01

Advances in high-end graphics computers in the past decade have made it possible to render visual scenes of incredible complexity and realism in real time. These new capabilities make it possible to manipulate and investigate the interactions of observers with their visual world in ways once only dreamed of. This paper reviews how these developments have affected two preexisting domains of behavioral research (flight simulation and motion perception) and have created a new domain (virtual environment research) which provides tools and challenges for the perceptual psychologist. Finally, the current limitations of these technologies are considered, with an eye toward how perceptual psychologist might shape future developments.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Using a Foundational Ontology for Reengineering a Software Enterprise Ontology

NASA Astrophysics Data System (ADS)

Perini Barcellos, Monalessa; de Almeida Falbo, Ricardo

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

Multilevel analysis of sports video sequences

NASA Astrophysics Data System (ADS)

Han, Jungong; Farin, Dirk; de With, Peter H. N.

2006-01-01

We propose a fully automatic and flexible framework for analysis and summarization of tennis broadcast video sequences, using visual features and specific game-context knowledge. Our framework can analyze a tennis video sequence at three levels, which provides a broad range of different analysis results. The proposed framework includes novel pixel-level and object-level tennis video processing algorithms, such as a moving-player detection taking both the color and the court (playing-field) information into account, and a player-position tracking algorithm based on a 3-D camera model. Additionally, we employ scene-level models for detecting events, like service, base-line rally and net-approach, based on a number real-world visual features. The system can summarize three forms of information: (1) all court-view playing frames in a game, (2) the moving trajectory and real-speed of each player, as well as relative position between the player and the court, (3) the semantic event segments in a game. The proposed framework is flexible in choosing the level of analysis that is desired. It is effective because the framework makes use of several visual cues obtained from the real-world domain to model important events like service, thereby increasing the accuracy of the scene-level analysis. The paper presents attractive experimental results highlighting the system efficiency and analysis capabilities.

Visual search and autism symptoms: What young children search for and co-occurring ADHD matter.

PubMed

Doherty, Brianna R; Charman, Tony; Johnson, Mark H; Scerif, Gaia; Gliga, Teodora

2018-05-03

Superior visual search is one of the most common findings in the autism spectrum disorder (ASD) literature. Here, we ascertain how generalizable these findings are across task and participant characteristics, in light of recent replication failures. We tested 106 3-year-old children at familial risk for ASD, a sample that presents high ASD and ADHD symptoms, and 25 control participants, in three multi-target search conditions: easy exemplar search (look for cats amongst artefacts), difficult exemplar search (look for dogs amongst chairs/tables perceptually similar to dogs), and categorical search (look for animals amongst artefacts). Performance was related to dimensional measures of ASD and ADHD, in agreement with current research domain criteria (RDoC). We found that ASD symptom severity did not associate with enhanced performance in search, but did associate with poorer categorical search in particular, consistent with literature describing impairments in categorical knowledge in ASD. Furthermore, ASD and ADHD symptoms were both associated with more disorganized search paths across all conditions. Thus, ASD traits do not always convey an advantage in visual search; on the contrary, ASD traits may be associated with difficulties in search depending upon the nature of the stimuli (e.g., exemplar vs. categorical search) and the presence of co-occurring symptoms. © 2018 John Wiley & Sons Ltd.

A New System To Support Knowledge Discovery: Telemakus.

ERIC Educational Resources Information Center

Revere, Debra; Fuller, Sherrilynne S.; Bugni, Paul F.; Martin, George M.

2003-01-01

The Telemakus System builds on the areas of concept representation, schema theory, and information visualization to enhance knowledge discovery from scientific literature. This article describes the underlying theories and an overview of a working implementation designed to enhance the knowledge discovery process through retrieval, visual and…

DataHub knowledge based assistance for science visualization and analysis using large distributed databases

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Collins, Donald J.; Doyle, Richard J.; Jacobson, Allan S.

1991-01-01

Viewgraphs on DataHub knowledge based assistance for science visualization and analysis using large distributed databases. Topics covered include: DataHub functional architecture; data representation; logical access methods; preliminary software architecture; LinkWinds; data knowledge issues; expert systems; and data management.

d-Omix: a mixer of generic protein domain analysis tools.

PubMed

Wichadakul, Duangdao; Numnark, Somrak; Ingsriswang, Supawadee

2009-07-01

Domain combination provides important clues to the roles of protein domains in protein function, interaction and evolution. We have developed a web server d-Omix (a Mixer of Protein Domain Analysis Tools) aiming as a unified platform to analyze, compare and visualize protein data sets in various aspects of protein domain combinations. With InterProScan files for protein sets of interest provided by users, the server incorporates four services for domain analyses. First, it constructs protein phylogenetic tree based on a distance matrix calculated from protein domain architectures (DAs), allowing the comparison with a sequence-based tree. Second, it calculates and visualizes the versatility, abundance and co-presence of protein domains via a domain graph. Third, it compares the similarity of proteins based on DA alignment. Fourth, it builds a putative protein network derived from domain-domain interactions from DOMINE. Users may select a variety of input data files and flexibly choose domain search tools (e.g. hmmpfam, superfamily) for a specific analysis. Results from the d-Omix could be interactively explored and exported into various formats such as SVG, JPG, BMP and CSV. Users with only protein sequences could prepare an InterProScan file using a service provided by the server as well. The d-Omix web server is freely available at http://www.biotec.or.th/isl/Domix.

Modeling software systems by domains

NASA Technical Reports Server (NTRS)

Dippolito, Richard; Lee, Kenneth

1992-01-01

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

Knowledge representation for commonality

NASA Technical Reports Server (NTRS)

Yeager, Dorian P.

1990-01-01

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

Memetic Algorithms, Domain Knowledge, and Financial Investing

ERIC Educational Resources Information Center

Du, Jie

2012-01-01

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

Cognitive and psychomotor effects of risperidone in schizophrenia and schizoaffective disorder.

PubMed

Houthoofd, Sofie A M K; Morrens, Manuel; Sabbe, Bernard G C

2008-09-01

The aim of this review was to discuss data from double-blind, randomized controlled trials (RCTs) that have investigated the effects of oral and long-acting injectable risperidone on cognitive and psychomotor functioning in patients with schizophrenia or schizoaffective disorder. PubMed/MEDLINE and the Institute of Scientific Information Web of Science database were searched for relevant English-language double-blind RCTs published between March 2000 and July 2008, using the terms schizophrenia, schizoaffective disorder, cognition, risperidone, psychomotor, processing speed, attention, vigilance, working memory, verbal learning, visual learning, reasoning, problem solving, social cognition, MATRICS, and long-acting. Relevant studies included patients with schizophrenia or schizoaffective disorder. Cognitive domains were delineated at the Consensus Conferences of the National Institute of Mental Health-Measurement And Treatment Research to Improve Cognition in Schizophrenia (NIMH-MATRICS). The tests employed to assess each domain and psychomotor functioning, and the within-group and between-group comparisons of risperidone with haloperidol and other atypical antipsychotics, are presented. The results of individual tests were included when they were individually presented and interpretable for either drug; outcomes that were presented as cluster scores or factor structures were excluded. A total of 12 articles were included in this review. Results suggested that the use of oral risperidone appeared to be associated with within-group improvements on the cognitive domains of processing speed, attention/vigilance, verbal and visual learning and memory, and reasoning and problem solving in patients with schizophrenia or schizoaffective disorder. Risperidone and haloperidol seemed to generate similar beneficial effects (on the domains of processing speed, attention/vigilance, [verbal and nonverbal] working memory, and visual learning and memory, as well as psychomotor functioning), although the results for verbal fluency, verbal learning and memory, and reasoning and problem solving were not unanimous, and no comparative data on social cognition were available. Similar cognitive effects were found with risperidone, olanzapine, and quetiapine on the domains of verbal working memory and reasoning and problem solving, as well as verbal fluency. More research is needed on the domains in which study results were contradictory. For olanzapine versus risperidone, these were verbal and visual learning and memory and psychomotor functioning. No comparative data for olanzapine and risperidone were available for the social cognition domain. For quetiapine versus risperidone, the domains in which no unanimity was found were processing speed, attention/vigilance, nonverbal working memory, and verbal learning and memory. The limited available reports on risperidone versus clozapine suggest that: risperidone was associated with improved, and clozapine with worsened, performance on the nonverbal working memory domain; risperidone improved and clozapine did not improve reasoning and problem-solving performance; clozapine improved, and risperidone did not improve, social cognition performance. Use of long-acting injectable risperidone seemed to be associated with improved performance in the domains of attention/vigilance, verbal learning and memory, and reasoning and problem solving, as well as psychomotor functioning. The results for the nonverbal working memory domain were indeterminate, and no clear improvement was seen in the social cognition domain. The domains of processing speed, verbal working memory, and visual learning and memory, as well as verbal fluency, were not assessed. The results of this review of within-group comparisons of oral risperidone suggest that the agent appeared to be associated with improved functioning in the cognitive domains of processing speed, attention/vigilance, verbal and visual learning and memory, and reasoning and problem solving in patients with schizophrenia or schizoaffective disorder. Long-acting injectable risperidone seemed to be associated with improved functioning in the domains of attention/vigilance, verbal learning and memory, and reasoning and problem solving, as well as psychomotor functioning, in patients with schizophrenia or schizoaffective disorder.

Clinically Meaningful Rehabilitation Outcomes of Low Vision Patients Served by Outpatient Clinical Centers.

PubMed

Goldstein, Judith E; Jackson, Mary Lou; Fox, Sandra M; Deremeik, James T; Massof, Robert W

2015-07-01

To facilitate comparative clinical outcome research in low vision rehabilitation, we must use patient-centered measurements that reflect clinically meaningful changes in visual ability. To quantify the effects of currently provided low vision rehabilitation (LVR) on patients who present for outpatient LVR services in the United States. Prospective, observational study of new patients seeking outpatient LVR services. From April 2008 through May 2011, 779 patients from 28 clinical centers in the United States were enrolled in the Low Vision Rehabilitation Outcomes Study. The Activity Inventory, a visual function questionnaire, was administered to measure overall visual ability and visual ability in 4 functional domains (reading, mobility, visual motor function, and visual information processing) at baseline and 6 to 9 months after usual LVR care. The Geriatric Depression Scale, Telephone Interview for Cognitive Status, and Medical Outcomes Study 36-Item Short-Form Health Survey physical functioning questionnaires were also administered to measure patients' psychological, cognitive, and physical health states, respectively, and clinical findings of patients were provided by study centers. Mean changes in the study population and minimum clinically important differences in the individual in overall visual ability and in visual ability in 4 functional domains as measured by the Activity Inventory. Baseline and post-rehabilitation measures were obtained for 468 patients. Minimum clinically important differences (95% CIs) were observed in nearly half (47% [95% CI, 44%-50%]) of patients in overall visual ability. The prevalence rates of patients with minimum clinically important differences in visual ability in functional domains were reading (44% [95% CI, 42%-48%]), visual motor function (38% [95% CI, 36%-42%]), visual information processing (33% [95% CI, 31%-37%]), and mobility (27% [95% CI, 25%-31%]). The largest average effect size (Cohen d = 0.87) for the population was observed in overall visual ability. Age (P = .006) was an independent predictor of changes in overall visual ability, and logMAR visual acuity (P = .002) was predictive of changes in visual information processing. Forty-four to fifty percent of patients presenting for outpatient LVR show clinically meaningful differences in overall visual ability after LVR, and the average effect sizes in overall visual ability are large, close to 1 SD.

Verbal and visual-spatial working memory and mathematical ability in different domains throughout primary school.

PubMed

Van de Weijer-Bergsma, Eva; Kroesbergen, Evelyn H; Van Luit, Johannes E H

2015-04-01

The relative importance of visual-spatial and verbal working memory for mathematics performance and learning seems to vary with age, the novelty of the material, and the specific math domain that is investigated. In this study, the relations between verbal and visual-spatial working memory and performance in four math domains (i.e., addition, subtraction, multiplication, and division) at different ages during primary school are investigated. Children (N = 4337) from grades 2 through 6 participated. Visual-spatial and verbal working memory were assessed using online computerized tasks. Math performance was assessed at the start, middle, and end of the school year using a speeded arithmetic test. Multilevel Multigroup Latent Growth Modeling was used to model individual differences in level and growth in math performance, and examine the predictive value of working memory per grade, while controlling for effects of classroom membership. The results showed that as grade level progressed, the predictive value of visual-spatial working memory for individual differences in level of mathematics performance waned, while the predictive value of verbal working memory increased. Working memory did not predict individual differences between children in their rate of performance growth throughout the school year. These findings are discussed in relation to three, not mutually exclusive, explanations for such age-related findings.

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

NASA Technical Reports Server (NTRS)

Gomaa, Hassan; Kerschberg, Larry; Sugumaran, Vijayan

1992-01-01

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

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

PubMed Central

An, Donggun; Runco, Mark A.

2016-01-01

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

One year study on the integrative intervention of acupressure and interactive multimedia for visual health in school children.

PubMed

Yeh, Mei-Ling; Chen, Hsing-Hsia; Chung, Yu-Chu

2012-12-01

This study used a larger sample size, added a long-term observation of the effect of intervention, and provided an integrated intervention of acupressure and interactive multimedia of visual health instruction for school children. The short- and long-term effects of the interventions were then evaluated by visual health knowledge, visual acuity, and refractive error. A repeated pretest-posttest controlled trial was used with two experimental groups and one control group. Four elementary schools in northern Taiwan. 287 School children with visual impairment in fourth grade were recruited. One experimental group received the integrative intervention of acupressure and interactive multimedia of visual health instruction (ACIMU), and another received auricular acupressure (AC) alone; whereas a control group received no intervention. Two 10-week interventions were separately given in the fall and spring semesters. The short- and long-term effects of the interventions were then evaluated by visual health knowledge, visual acuity, and refractive error. During the school year the visual health knowledge was significantly higher in the ACIMU group than the control group (p<0.001). A significant difference in the changing visual acuity was in the three groups (p<0.001), with the improvement in the ACIMU group. No difference in the refractive error was found between any two groups (p>0.05). This study demonstrated that a long-term period of acupressure is required to improve school children's visual health. School children receiving the intervention of acupressure combined with interactive multimedia had better improvement of visual health and related knowledge than others. Further study is suggested in which visual health and preventative needs can be established for early childhood. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

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

2004-06-01

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

Interface Metaphors for Interactive Machine Learning

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

Jasper, Robert J.; Blaha, Leslie M.

To promote more interactive and dynamic machine learn- ing, we revisit the notion of user-interface metaphors. User-interface metaphors provide intuitive constructs for supporting user needs through interface design elements. A user-interface metaphor provides a visual or action pattern that leverages a user’s knowledge of another domain. Metaphors suggest both the visual representations that should be used in a display as well as the interactions that should be afforded to the user. We argue that user-interface metaphors can also offer a method of extracting interaction-based user feedback for use in machine learning. Metaphors offer indirect, context-based information that can be usedmore » in addition to explicit user inputs, such as user-provided labels. Implicit information from user interactions with metaphors can augment explicit user input for active learning paradigms. Or it might be leveraged in systems where explicit user inputs are more challenging to obtain. Each interaction with the metaphor provides an opportunity to gather data and learn. We argue this approach is especially important in streaming applications, where we desire machine learning systems that can adapt to dynamic, changing data.« less

Classification of document page images based on visual similarity of layout structures

NASA Astrophysics Data System (ADS)

Shin, Christian K.; Doermann, David S.

1999-12-01

Searching for documents by their type or genre is a natural way to enhance the effectiveness of document retrieval. The layout of a document contains a significant amount of information that can be used to classify a document's type in the absence of domain specific models. A document type or genre can be defined by the user based primarily on layout structure. Our classification approach is based on 'visual similarity' of the layout structure by building a supervised classifier, given examples of the class. We use image features, such as the percentages of tex and non-text (graphics, image, table, and ruling) content regions, column structures, variations in the point size of fonts, the density of content area, and various statistics on features of connected components which can be derived from class samples without class knowledge. In order to obtain class labels for training samples, we conducted a user relevance test where subjects ranked UW-I document images with respect to the 12 representative images. We implemented our classification scheme using the OC1, a decision tree classifier, and report our findings.

Crossmaps: Visualization of overlapping relationships in collections of journal papers

PubMed Central

Morris, Steven A.; Yen, Gary G.

2004-01-01

A crossmapping technique is introduced for visualizing multiple and overlapping relations among entity types in collections of journal articles. Groups of entities from two entity types are crossplotted to show correspondence of relations. For example, author collaboration groups are plotted on the x axis against groups of papers (research fronts) on the y axis. At the intersection of each pair of author group/research front pairs a circular symbol is plotted whose size is proportional to the number of times that authors in the group appear as authors in papers in the research front. Entity groups are found by agglomerative hierarchical clustering using conventional similarity measures. Crossmaps comprise a simple technique that is particularly suited to showing overlap in relations among entity groups. Particularly useful crossmaps are: research fronts against base reference clusters, research fronts against author collaboration groups, and research fronts against term co-occurrence clusters. When exploring the knowledge domain of a collection of journal papers, it is useful to have several crossmaps of different entity pairs, complemented by research front timelines and base reference cluster timelines. PMID:14762168

Human visual system-based smoking event detection

NASA Astrophysics Data System (ADS)

Odetallah, Amjad D.; Agaian, Sos S.

2012-06-01

Human action (e.g. smoking, eating, and phoning) analysis is an important task in various application domains like video surveillance, video retrieval, human-computer interaction systems, and so on. Smoke detection is a crucial task in many video surveillance applications and could have a great impact to raise the level of safety of urban areas, public parks, airplanes, hospitals, schools and others. The detection task is challenging since there is no prior knowledge about the object's shape, texture and color. In addition, its visual features will change under different lighting and weather conditions. This paper presents a new scheme of a system for detecting human smoking events, or small smoke, in a sequence of images. In developed system, motion detection and background subtraction are combined with motion-region-saving, skin-based image segmentation, and smoke-based image segmentation to capture potential smoke regions which are further analyzed to decide on the occurrence of smoking events. Experimental results show the effectiveness of the proposed approach. As well, the developed method is capable of detecting the small smoking events of uncertain actions with various cigarette sizes, colors, and shapes.

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

ERIC Educational Resources Information Center

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

2018-01-01

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

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Biomarkers of a five-domain translational substrate for schizophrenia and schizoaffective psychosis.

PubMed

Fryar-Williams, Stephanie; Strobel, Jörg E

2015-01-01

The Mental Health Biomarker Project (2010-2014) selected commercial biochemistry markers related to monoamine synthesis and metabolism and measures of visual and auditory processing performance. Within a case-control discovery design with exclusion criteria designed to produce a highly characterised sample, results from 67 independently DSM IV-R-diagnosed cases of schizophrenia and schizoaffective disorder were compared with those from 67 control participants selected from a local hospital, clinic and community catchment area. Participants underwent protocol-based diagnostic-checking, functional-rating, biological sample-collection for thirty candidate markers and sensory-processing assessment. Fifteen biomarkers were identified on ROC analysis. Using these biomarkers, odds ratios, adjusted for a case-control design, indicated that schizophrenia and schizoaffective disorder were highly associated with dichotic listening disorder, delayed visual processing, low visual span, delayed auditory speed of processing, low reverse digit span as a measure of auditory working memory and elevated levels of catecholamines. Other nutritional and biochemical biomarkers were identified as elevated hydroxyl pyrroline-2-one as a marker of oxidative stress, vitamin D, B6 and folate deficits with elevation of serum B12 and free serum copper to zinc ratio. When individual biomarkers were ranked by odds ratio and correlated with clinical severity, five functional domains of visual processing, auditory processing, oxidative stress, catecholamines and nutritional-biochemical variables were formed. When the strengths of their inter-domain relationships were predicted by Lowess (non-parametric) regression, predominant bidirectional relationships were found between visual processing and catecholamine domains. At a cellular level, the nutritional-biochemical domain exerted a pervasive influence on the auditory domain as well as on all other domains. The findings of this biomarker research point towards a much-required advance in Psychiatry: quantification of some theoretically-understandable, translationally-informative, treatment-relevant underpinnings of serious mental illness. This evidence reveals schizophrenia and schizoaffective disorder in a somewhat different manner, as a conglomerate of several disorders many of which are not currently being assessed-for or treated in clinical settings. Currently available remediation techniques for these underlying conditions have potential to reduce treatment-resistance, relapse-prevention, cost burden and social stigma in these conditions. If replicated and validated in prospective trials, such findings will improve progress-monitoring and treatment-response for schizophrenia and schizoaffective disorder.

Bulk magnetic domain structures visualized by neutron dark-field imaging

NASA Astrophysics Data System (ADS)

Grünzweig, C.; David, C.; Bunk, O.; Dierolf, M.; Frei, G.; Kühne, G.; Schäfer, R.; Pofahl, S.; Rønnow, H. M. R.; Pfeiffer, F.

2008-09-01

We report on how a neutron grating interferometer can yield projection images of the internal domain structure in bulk ferromagnetic samples. The image contrast relies on the ultrasmall angle scattering of unpolarized neutrons at domain wall structures in the specimen. The results show the basic domains of (110)-oriented sheets in an FeSi test sample. The obtained domain structures could be correlated with surface sensitive magneto-optical Kerr effect micrographs.

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

ERIC Educational Resources Information Center

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

2007-01-01

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

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

ERIC Educational Resources Information Center

Sahin, Feyzullah

2016-01-01

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

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

ERIC Educational Resources Information Center

Schneider, Wolfgang; And Others

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

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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

ERIC Educational Resources Information Center

Choi, Jung-Min

2010-01-01

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

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

ERIC Educational Resources Information Center

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

2017-01-01

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

User-Centered Evaluation of Visual Analytics

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

Scholtz, Jean C.

Visual analytics systems are becoming very popular. More domains now use interactive visualizations to analyze the ever-increasing amount and heterogeneity of data. More novel visualizations are being developed for more tasks and users. We need to ensure that these systems can be evaluated to determine that they are both useful and usable. A user-centered evaluation for visual analytics needs to be developed for these systems. While many of the typical human-computer interaction (HCI) evaluation methodologies can be applied as is, others will need modification. Additionally, new functionality in visual analytics systems needs new evaluation methodologies. There is a difference betweenmore » usability evaluations and user-centered evaluations. Usability looks at the efficiency, effectiveness, and user satisfaction of users carrying out tasks with software applications. User-centered evaluation looks more specifically at the utility provided to the users by the software. This is reflected in the evaluations done and in the metrics used. In the visual analytics domain this is very challenging as users are most likely experts in a particular domain, the tasks they do are often not well defined, the software they use needs to support large amounts of different kinds of data, and often the tasks last for months. These difficulties are discussed more in the section on User-centered Evaluation. Our goal is to provide a discussion of user-centered evaluation practices for visual analytics, including existing practices that can be carried out and new methodologies and metrics that need to be developed and agreed upon by the visual analytics community. The material provided here should be of use for both researchers and practitioners in the field of visual analytics. Researchers and practitioners in HCI and interested in visual analytics will find this information useful as well as a discussion on changes that need to be made to current HCI practices to make them more suitable to visual analytics. A history of analysis and analysis techniques and problems is provided as well as an introduction to user-centered evaluation and various evaluation techniques for readers from different disciplines. The understanding of these techniques is imperative if we wish to support analysis in the visual analytics software we develop. Currently the evaluations that are conducted and published for visual analytics software are very informal and consist mainly of comments from users or potential users. Our goal is to help researchers in visual analytics to conduct more formal user-centered evaluations. While these are time-consuming and expensive to carryout, the outcomes of these studies will have a defining impact on the field of visual analytics and help point the direction for future features and visualizations to incorporate. While many researchers view work in user-centered evaluation as a less-than-exciting area to work, the opposite is true. First of all, the goal is user-centered evaluation is to help visual analytics software developers, researchers, and designers improve their solutions and discover creative ways to better accommodate their users. Working with the users is extremely rewarding as well. While we use the term “users” in almost all situations there are a wide variety of users that all need to be accommodated. Moreover, the domains that use visual analytics are varied and expanding. Just understanding the complexities of a number of these domains is exciting. Researchers are trying out different visualizations and interactions as well. And of course, the size and variety of data are expanding rapidly. User-centered evaluation in this context is rapidly changing. There are no standard processes and metrics and thus those of us working on user-centered evaluation must be creative in our work with both the users and with the researchers and developers.« less

Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex

PubMed Central

Coppola, David; White, Leonard E.; Wolf, Fred

2015-01-01

The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1’s intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models. PMID:26575467

PSYCHE: An Object-Oriented Approach to Simulating Medical Education

PubMed Central

Mullen, Jamie A.

1990-01-01

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

Evaluation of an Audio-Visual Novela to Improve Beliefs, Attitudes and Knowledge toward Dementia: A Mixed-Methods Approach.

PubMed

Grigsby, Timothy J; Unger, Jennifer B; Molina, Gregory B; Baron, Mel

2017-01-01

Dementia is a clinical syndrome characterized by progressive degeneration in cognitive ability that limits the capacity for independent living. Interventions are needed to target the medical, social, psychological, and knowledge needs of caregivers and patients. This study used a mixed methods approach to evaluate the effectiveness of a dementia novela presented in an audio-visual format in improving dementia attitudes, beliefs and knowledge. Adults from Los Angeles (N = 42, 83% female, 90% Hispanic/Latino, mean age = 42.2 years, 41.5% with less than a high school education) viewed an audio-visual novela on dementia. Participants completed surveys immediately before and after viewing the material. The novela produced significant improvements in overall knowledge (t(41) = -9.79, p < .0001) and led to positive increases in specific attitudes toward people with dementia but not in beliefs that screening would be beneficial. Qualitative results provided concordant and discordant evidence for the quantitative findings. Results indicate that an audio-visual novela can be useful for improving attitudes and knowledge about dementia, but further work is needed to investigate the relation with health disparities in screening and treatment behaviors. Audio visual novelas are an innovative format for health education and change attitudes and knowledge about dementia.

Domain Selectivity in the Parahippocampal Gyrus Is Predicted by the Same Structural Connectivity Patterns in Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; He, Chenxi; Peelen, Marius V; Zhong, Suyu; Gong, Gaolang; Caramazza, Alfonso; Bi, Yanchao

2017-05-03

Human ventral occipital temporal cortex contains clusters of neurons that show domain-preferring responses during visual perception. Recent studies have reported that some of these clusters show surprisingly similar domain selectivity in congenitally blind participants performing nonvisual tasks. An important open question is whether these functional similarities are driven by similar innate connections in blind and sighted groups. Here we addressed this question focusing on the parahippocampal gyrus (PHG), a region that is selective for large objects and scenes. Based on the assumption that patterns of long-range connectivity shape local computation, we examined whether domain selectivity in PHG is driven by similar structural connectivity patterns in the two populations. Multiple regression models were built to predict the selectivity of PHG voxels for large human-made objects from white matter (WM) connectivity patterns in both groups. These models were then tested using independent data from participants with similar visual experience (two sighted groups) and using data from participants with different visual experience (blind and sighted groups). Strikingly, the WM-based predictions between blind and sighted groups were as successful as predictions between two independent sighted groups. That is, the functional selectivity for large objects of a PHG voxel in a blind participant could be accurately predicted by its WM pattern using the connection-to-function model built from the sighted group data, and vice versa. Regions that significantly predicted PHG selectivity were located in temporal and frontal cortices in both sighted and blind populations. These results show that the large-scale network driving domain selectivity in PHG is independent of vision. SIGNIFICANCE STATEMENT Recent studies have reported intriguingly similar domain selectivity in sighted and congenitally blind individuals in regions within the ventral visual cortex. To examine whether these similarities originate from similar innate connectional roots, we investigated whether the domain selectivity in one population could be predicted by the structural connectivity pattern of the other. We found that the selectivity for large objects of a PHG voxel in a blind participant could be predicted by its structural connectivity pattern using the connection-to-function model built from the sighted group data, and vice versa. These results reveal that the structural connectivity underlying domain selectivity in the PHG is independent of visual experience, providing evidence for nonvisual representations in this region. Copyright © 2017 the authors 0270-6474/17/374706-12$15.00/0.

The Evolution of a Drawing.

ERIC Educational Resources Information Center

Delicio, Gail; Reardon Linda

Does a drawing embody the form and focus of what the artist actually sees, or instead, is it only after seeing the finished drawing that the artist knows the true meaning of his or her visual experience? It is the knowledge of the visual experience that drives the representation of it. Knowledge of the visual experience is present in varying…

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…

An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition.

PubMed

Niu, Li; Li, Wen; Xu, Dong; Cai, Jianfei

2018-02-01

In this paper, we propose a new exemplar-based multi-view domain generalization (EMVDG) framework for visual recognition by learning robust classifier that are able to generalize well to arbitrary target domain based on the training samples with multiple types of features (i.e., multi-view features). In this framework, we aim to address two issues simultaneously. First, the distribution of training samples (i.e., the source domain) is often considerably different from that of testing samples (i.e., the target domain), so the performance of the classifiers learnt on the source domain may drop significantly on the target domain. Moreover, the testing data are often unseen during the training procedure. Second, when the training data are associated with multi-view features, the recognition performance can be further improved by exploiting the relation among multiple types of features. To address the first issue, considering that it has been shown that fusing multiple SVM classifiers can enhance the domain generalization ability, we build our EMVDG framework upon exemplar SVMs (ESVMs), in which a set of ESVM classifiers are learnt with each one trained based on one positive training sample and all the negative training samples. When the source domain contains multiple latent domains, the learnt ESVM classifiers are expected to be grouped into multiple clusters. To address the second issue, we propose two approaches under the EMVDG framework based on the consensus principle and the complementary principle, respectively. Specifically, we propose an EMVDG_CO method by adding a co-regularizer to enforce the cluster structures of ESVM classifiers on different views to be consistent based on the consensus principle. Inspired by multiple kernel learning, we also propose another EMVDG_MK method by fusing the ESVM classifiers from different views based on the complementary principle. In addition, we further extend our EMVDG framework to exemplar-based multi-view domain adaptation (EMVDA) framework when the unlabeled target domain data are available during the training procedure. The effectiveness of our EMVDG and EMVDA frameworks for visual recognition is clearly demonstrated by comprehensive experiments on three benchmark data sets.

iPixel: a visual content-based and semantic search engine for retrieving digitized mammograms by using collective intelligence.

PubMed

Alor-Hernández, Giner; Pérez-Gallardo, Yuliana; Posada-Gómez, Rubén; Cortes-Robles, Guillermo; Rodríguez-González, Alejandro; Aguilar-Laserre, Alberto A

2012-09-01

Nowadays, traditional search engines such as Google, Yahoo and Bing facilitate the retrieval of information in the format of images, but the results are not always useful for the users. This is mainly due to two problems: (1) the semantic keywords are not taken into consideration and (2) it is not always possible to establish a query using the image features. This issue has been covered in different domains in order to develop content-based image retrieval (CBIR) systems. The expert community has focussed their attention on the healthcare domain, where a lot of visual information for medical analysis is available. This paper provides a solution called iPixel Visual Search Engine, which involves semantics and content issues in order to search for digitized mammograms. iPixel offers the possibility of retrieving mammogram features using collective intelligence and implementing a CBIR algorithm. Our proposal compares not only features with similar semantic meaning, but also visual features. In this sense, the comparisons are made in different ways: by the number of regions per image, by maximum and minimum size of regions per image and by average intensity level of each region. iPixel Visual Search Engine supports the medical community in differential diagnoses related to the diseases of the breast. The iPixel Visual Search Engine has been validated by experts in the healthcare domain, such as radiologists, in addition to experts in digital image analysis.

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

DTIC Science & Technology

2002-06-14

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

Is improved contrast sensitivity a natural consequence of visual training?

PubMed Central

Levi, Aaron; Shaked, Danielle; Tadin, Duje; Huxlin, Krystel R.

2015-01-01

Many studies have shown that training and testing conditions modulate specificity of visual learning to trained stimuli and tasks. In visually impaired populations, generalizability of visual learning to untrained stimuli/tasks is almost always reported, with contrast sensitivity (CS) featuring prominently among these collaterally-improved functions. To understand factors underlying this difference, we measured CS for direction and orientation discrimination in the visual periphery of three groups of visually-intact subjects. Group 1 trained on an orientation discrimination task with static Gabors whose luminance contrast was decreased as performance improved. Group 2 trained on a global direction discrimination task using high-contrast random dot stimuli previously used to recover motion perception in cortically blind patients. Group 3 underwent no training. Both forms of training improved CS with some degree of specificity for basic attributes of the trained stimulus/task. Group 1's largest enhancement was in CS around the trained spatial/temporal frequencies; similarly, Group 2's largest improvements occurred in CS for discriminating moving and flickering stimuli. Group 3 saw no significant CS changes. These results indicate that CS improvements may be a natural consequence of multiple forms of visual training in visually intact humans, albeit with some specificity to the trained visual domain(s). PMID:26305736

Visualization studies on evidence-based medicine domain knowledge (series 3): visualization for dissemination of evidence based medicine information.

PubMed

Shen, Jiantong; Yao, Leye; Li, Youping; Clarke, Mike; Gan, Qi; Li, Yifei; Fan, Yi; Gou, Yongchao; Wang, Li

2011-05-01

To identify patterns in information sharing between a series of Chinese evidence based medicine (EBM) journals and the Cochrane Database of Systematic Reviews, to determine key evidence dissemination areas for EBM and to provide a scientific basis for improving the dissemination of EBM research. Data were collected on citing and cited from the Chinese Journal of Evidence-Based Medicine (CJEBM), Journal of Evidence-Based Medicine (JEBMc), Chinese Journal of Evidence Based Pediatrics (CJEBP), and the Cochrane Database of Systematic Reviews (CDSR). Relationships between citations were visualized. High-frequency key words from these sources were identified, to build a word co-occurrence matrix and to map research subjects. CDSR contains a large collection of information of relevance to EBM and its contents are widely cited across many journals, suggesting a well-developed citation environment. The content and citation of the Chinese journals have been increasing in recent years. However, their citation environments are much less developed, and there is a wide variation in the breadth and strength of their knowledge communication, with the ranking from highest to lowest being CJEBM, JEBMc and CJEBP. The content of CDSR is almost exclusively Cochrane intervention reviews examining the effects of healthcare interventions, so it's contribution to EBM is mostly in disease control and treatment. On the other hand, the Chinese journals on evidence-based medicine and practice focused more on areas such as education and research, design and quality of clinical trials, evidence based policymaking, evidence based clinical practice, tumor treatment, and pediatrics. Knowledge and findings of EBM are widely communicated and disseminated. However, citation environments and range of knowledge communication differ greatly between the journals examined in this study. This finds that Chinese EBM has focused mainly on clinical medicine, Traditional Chinese Medicine, pediatrics, tumor treatment, nursing, health economic and management, and medical education. Internationally, EBM research topics have begun to shift, from drug treatment to surgery or other non-pharmacological treatments; from therapy to diagnosis, rehabilitation, and prevention; from evidence based clinical practice to evidence based management and policymaking. The philosophy and method of EBM, evidence production and translation are also shifting from well resourced settings to low- and middle-income countries, especially those in which English is not a major language. © 2011 Blackwell Publishing Asia Pty Ltd and Chinese Cochrane Center, West China Hospital of Sichuan University.

The confidence of speech-language pathology students regarding communicating with people with aphasia

PubMed Central

2013-01-01

Background Aphasia is an acquired language disorder that can present a significant barrier to patient involvement in healthcare decisions. Speech-language pathologists (SLPs) are viewed as experts in the field of communication. However, many SLP students do not receive practical training in techniques to communicate with people with aphasia (PWA) until they encounter PWA during clinical education placements. Methods This study investigated the confidence and knowledge of SLP students in communicating with PWA prior to clinical placements using a customised questionnaire. Confidence in communicating with people with aphasia was assessed using a 100-point visual analogue scale. Linear, and logistic, regressions were used to examine the association between confidence and age, as well as confidence and course type (graduate-entry masters or undergraduate), respectively. Knowledge of strategies to assist communication with PWA was examined by asking respondents to list specific strategies that could assist communication with PWA. Results SLP students were not confident with the prospect of communicating with PWA; reporting a median 29-points (inter-quartile range 17–47) on the visual analogue confidence scale. Only, four (8.2%) of respondents rated their confidence greater than 55 (out of 100). Regression analyses indicated no relationship existed between confidence and students‘ age (p = 0.31, r-squared = 0.02), or confidence and course type (p = 0.22, pseudo r-squared = 0.03). Students displayed limited knowledge about communication strategies. Thematic analysis of strategies revealed four overarching themes; Physical, Verbal Communication, Visual Information and Environmental Changes. While most students identified potential use of resources (such as images and written information), fewer students identified strategies to alter their verbal communication (such as reduced speech rate). Conclusions SLP students who had received aphasia related theoretical coursework, but not commenced clinical placements with PWA, were not confident in their ability to communicate with PWA. Students may benefit from an educational intervention or curriculum modification to incorporate practical training in effective strategies to communicate with PWA, before they encounter PWA in clinical settings. Ensuring students have confidence and knowledge of potential communication strategies to assist communication with PWA may allow them to focus their learning experiences in more specific clinical domains, such as clinical reasoning, rather than building foundation interpersonal communication skills. PMID:23806028

The confidence of speech-language pathology students regarding communicating with people with aphasia.

PubMed

Finch, Emma; Fleming, Jennifer; Brown, Kyla; Lethlean, Jennifer; Cameron, Ashley; McPhail, Steven M

2013-06-27

Aphasia is an acquired language disorder that can present a significant barrier to patient involvement in healthcare decisions. Speech-language pathologists (SLPs) are viewed as experts in the field of communication. However, many SLP students do not receive practical training in techniques to communicate with people with aphasia (PWA) until they encounter PWA during clinical education placements. This study investigated the confidence and knowledge of SLP students in communicating with PWA prior to clinical placements using a customised questionnaire. Confidence in communicating with people with aphasia was assessed using a 100-point visual analogue scale. Linear, and logistic, regressions were used to examine the association between confidence and age, as well as confidence and course type (graduate-entry masters or undergraduate), respectively. Knowledge of strategies to assist communication with PWA was examined by asking respondents to list specific strategies that could assist communication with PWA. SLP students were not confident with the prospect of communicating with PWA; reporting a median 29-points (inter-quartile range 17-47) on the visual analogue confidence scale. Only, four (8.2%) of respondents rated their confidence greater than 55 (out of 100). Regression analyses indicated no relationship existed between confidence and students' age (p = 0.31, r-squared = 0.02), or confidence and course type (p = 0.22, pseudo r-squared = 0.03). Students displayed limited knowledge about communication strategies. Thematic analysis of strategies revealed four overarching themes; Physical, Verbal Communication, Visual Information and Environmental Changes. While most students identified potential use of resources (such as images and written information), fewer students identified strategies to alter their verbal communication (such as reduced speech rate). SLP students who had received aphasia related theoretical coursework, but not commenced clinical placements with PWA, were not confident in their ability to communicate with PWA. Students may benefit from an educational intervention or curriculum modification to incorporate practical training in effective strategies to communicate with PWA, before they encounter PWA in clinical settings. Ensuring students have confidence and knowledge of potential communication strategies to assist communication with PWA may allow them to focus their learning experiences in more specific clinical domains, such as clinical reasoning, rather than building foundation interpersonal communication skills.

Disentangling the Role of Domain-Specific Knowledge in Student Modeling

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Enabling Data Discovery and Reuse by Improving Software Usability:Data Science Experiences, Lessons, and Gaps

NASA Astrophysics Data System (ADS)

Rosati, A.; Yarmey, L.

2014-12-01

It is well understood that a good data scientist needs domain science, analysis, programming, and communication skills to create finished data products, visualizations, and reports. Articles and blogs tout the need for "expert" skill levels in domain knowledge, statistics, storytelling, graphic design, technology…and the list goes on. Since it seems impossible that one person would encompass all these skills, it is often suggested that data science be done by a team instead of an individual. This research into, and experience with, data product design offers an augmented definition - one that elevates relationships and engagement with the final user of a product. Essentially, no matter how fantastic or technically advanced a product appears, the intended audience of that product must be able to understand, use, and find value in the product in order for it to be considered a success. Usability is often misunderstood and seen as common sense or common knowledge, but it is actually an important and challenging piece of product development. This paper describes the National Snow and Ice Data Center's process to usability test the Arctic Data Explorer (ADE). The ADE is a federated data search tool for interdisciplinary Arctic science data that has been improved in features, appearance, functionality, and quality through a series of strategic and targeted usability testing and assessments. Based on the results, it is recommended that usability testing be incorporated into the skill set of each data science team.

A middle man approach to knowledge acquisition in expert systems

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

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.

A reusable knowledge acquisition shell: KASH

NASA Technical Reports Server (NTRS)

Westphal, Christopher; Williams, Stephen; Keech, Virginia

1991-01-01

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

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

PubMed

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

2017-12-01

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

The Relationship among Beginning and Advanced American Sign Language Students and Credentialed Interpreters across Two Domains of Visual Imagery: Vividness and Manipulation

ERIC Educational Resources Information Center

Stauffer, Linda K.

2010-01-01

Given the visual-gestural nature of ASL it is reasonable to assume that visualization abilities may be one predictor of aptitude for learning ASL. This study tested a hypothesis that visualization abilities are a foundational aptitude for learning a signed language and that measurements of these skills will increase as students progress from…

Gps-Denied Geo-Localisation Using Visual Odometry

NASA Astrophysics Data System (ADS)

Gupta, Ashish; Chang, Huan; Yilmaz, Alper

2016-06-01

The primary method for geo-localization is based on GPS which has issues of localization accuracy, power consumption, and unavailability. This paper proposes a novel approach to geo-localization in a GPS-denied environment for a mobile platform. Our approach has two principal components: public domain transport network data available in GIS databases or OpenStreetMap; and a trajectory of a mobile platform. This trajectory is estimated using visual odometry and 3D view geometry. The transport map information is abstracted as a graph data structure, where various types of roads are modelled as graph edges and typically intersections are modelled as graph nodes. A search for the trajectory in real time in the graph yields the geo-location of the mobile platform. Our approach uses a simple visual sensor and it has a low memory and computational footprint. In this paper, we demonstrate our method for trajectory estimation and provide examples of geolocalization using public-domain map data. With the rapid proliferation of visual sensors as part of automated driving technology and continuous growth in public domain map data, our approach has the potential to completely augment, or even supplant, GPS based navigation since it functions in all environments.

Frequency and Correlates of Distant Visual Impairment in Patients with Schizophrenia, Bipolar Disorder, and Major Depressive Disorder.

PubMed

Zheng, W; Tang, L R; Correll, C U; Ungvari, G S; Chiu, H F K; Xiang, Y Q; Xiang, Y T

2015-09-01

Distant visual impairment in the severely mentally ill is under-researched. This study aimed to assess the frequency and correlates of distant visual impairment in a cohort of Chinese psychiatric patients, including its effect on their quality of life. Adult psychiatric inpatients with schizophrenia, bipolar disorder, and major depressive disorder consecutively admitted to a psychiatric hospital in Beijing, China underwent assessments of psychopathology (Brief Psychiatric Rating Scale, 16-item Quick Inventory of Depressive Symptomatology [Self-Report]), quality of life (12-item Short-Form Medical Outcomes Study [SF-12], 25-item National Eye Institute Visual Function Questionnaire [NEI-VFQ25]), adverse effects (Udvalg for Kliniske Undersøgelser Side Effect Rating Scale), and presenting (as opposed to uncorrected) distant visual acuity (Logarithm of the Minimum Angle of Resolution [LogMAR] chart with patients wearing spectacles, if they owned them). Distant visual impairment was defined as binocular distant visual acuity of a LogMAR score of ≥ 0.5 (< 6/18 Snellen acuity). Among 356 patients who met the study criteria, the frequency of distant visual impairment was 12.6% (15.2% with schizophrenia, 11.9% with bipolar disorder, 8.8% with major depressive disorder). In multiple logistic regression analysis, distant visual impairment was significantly associated with ocular disease only (p = 0.002, odds ratio = 3.2, 95% confidence interval = 1.5-6.7). Controlling for the confounding effect of ocular disease, patients with distant visual impairment had a lower quality of life in the general vision domain of the NEI-VFQ25 (F[2, 353] = 9.5, p = 0.002) compared with those without. No differences in the physical and mental domains of the SF-12 and in other domains of the NEI-VFQ25 were noted in these 2 groups. One-eighth of middle-aged severely mentally ill patients had distant visual impairment. Considering the impact of distant visual impairment on daily functioning, severely mentally ill patients need to be screened for impaired eyesight as part of their comprehensive health assessment.

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

DTIC Science & Technology

2004-06-01

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

Building Learning Modules for Undergraduate Education Using LEAD Technology

NASA Astrophysics Data System (ADS)

Clark, R. D.; Yalda, S.

2006-12-01

Linked Environments for Atmospheric Discovery (LEAD) has as its goal to make meteorological data, forecast models, and analysis and visualization tools available to anyone who wants to interactively explore the weather as it evolves. LEAD advances through the development and beta-deployment of Integrated Test Beds (ITBs), which are technology build-outs that are the fruition of collaborative IT and meteorological research. As the ITBs mature, opportunities emerge for the integration of this new technological capability into the education arena. The LEAD education and outreach initiative is aimed at bringing new capabilities into classroom from the middle school level to graduate education and beyond, and ensuring the congruency of this technology with curricular. One of the principal goals of LEAD is to democratize the availability of advanced weather technologies for research and education. The degree of democratization is tied to the growth of student knowledge and skills, and is correlated with education level (though not for every student in the same way). The average high school student may experience LEAD through an environment that retains a higher level of instructor control compared to the undergraduate and graduate student. This is necessary to accommodate not only differences in knowledge and skills, but the computer capabilities in the classroom such that the "teachable moment" is not lost.Undergraduates will have the opportunity to query observation data and model output, explore and discover relationships through concept mapping using an ontology service, select domains of interest based on current weather, and employ an experiment builder within the LEAD portal as an interface to configure, launch the WRF model, monitor the workflow, and visualize results using Unidata's Integrated Data Viewer (IDV), whether it be on a local server or across the TeraGrid. Such a robust and comprehensive suite of tools and services can create new paradigms for embedding students in an authentic, contextualized environment where the knowledge domain is an extension, yet integral supplement, to the classroom experience.This presentation describes two different approaches for the use of LEAD in undergraduate education: 1) a use-case for integrating LEAD technology into undergraduate subject material; and 2) making LEAD capability available to a select group of students participating in the National Collegiate Forecasting Contest (NCFC). The use-case (1) is designed to have students explore a particular weather phenomenon (e.g., a frontal boundary, jet streak, or lake effect snow event) through self-guided inquiry, and is intended as a supplement to classroom instruction. Students will use interactive, Web-based, LEAD-to-Learn modules created specifically to build conceptual knowledge of the phenomenon, adjoin germane terminology, explore relationships between concepts and similar phenomena using the LEAD ontology, and guide them through the experiment builder and workflow orchestration process in order to establish a high-resolution WRF run over a region that exhibits the characteristics of the phenomenon they wish to study. The results of the experiment will be stored in the student's MyLEAD workspace from which it can be retrieved, visualized and analyzed for atmospheric signatures characteristic of the phenomenon. The learning process is authentic in that students will be exposed to the same process of investigation, and will have available many of the same tools, as researchers. The modules serve to build content knowledge, guide discovery, and provide assessment while the LEAD portal opens the gateway to real-time observations, model accessibility, and a variety of tools, services, and resources.

Canadian residents' perceived manager training needs.

PubMed

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

2010-01-01

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

Factors influencing self-reported vision-related activity limitation in the visually impaired.

PubMed

Tabrett, Daryl R; Latham, Keziah

2011-07-15

The use of patient-reported outcome (PRO) measures to assess self-reported difficulty in visual activities is common in patients with impaired vision. This study determines the visual and psychosocial factors influencing patients' responses to self-report measures, to aid in understanding what is being measured. One hundred visually impaired participants completed the Activity Inventory (AI), which assesses self-reported, vision-related activity limitation (VRAL) in the task domains of reading, mobility, visual information, and visual motor tasks. Participants also completed clinical tests of visual function (distance visual acuity and near reading performance both with and without low vision aids [LVAs], contrast sensitivity, visual fields, and depth discrimination), and questionnaires assessing depressive symptoms, social support, adjustment to visual loss, and personality. Multiple regression analyses identified that an acuity measure (distance or near), and, to a lesser extent, near reading performance without LVAs, visual fields, and contrast sensitivity best explained self-reported VRAL (28%-50% variance explained). Significant psychosocial correlates were depression and adjustment, explaining an additional 6% to 19% unique variance. Dependent on task domain, the parameters assessed explained 59% to 71% of the variance in self-reported VRAL. Visual function, most notably acuity without LVAs, is the best predictor of self-reported VRAL assessed by the AI. Depression and adjustment to visual loss also significantly influence self-reported VRAL, largely independent of the severity of visual loss and most notably in the less vision-specific tasks. The results suggest that rehabilitation strategies addressing depression and adjustment could improve perceived visual disability.

Diabetes ongoing sustainable care and treatment (DOST): A strategy for informational deliverance through visual dynamic modules sustained by near peer mentoring.

PubMed

Joshi, Ankur; Arutagi, Vishwanath; Nahar, Nitin; Tiwari, Sharad; Singh, Daneshwar; Sethia, Soumitra

2016-01-01

The informational continuity for a diabetic patient is of paramount importance. This study on a pilot basis explores the process utility of structured educational modular sessions grounded on the principle of near-peer mentoring. Visual modules were prepared for diabetic patients. These modules were instituted to 25 diabetic patients in logical sequences. In the next phase, 4 persons of these 25 patients were designated as diabetic-diabetes ongoing sustainable care and treatment (DOST). Each diabetic-DOST was clubbed with two patients for modular session and informational deliverance during the next 7 days. Process analysis was performed with "proxy-indicators," namely, monthly glycemic status, knowledge assessment scores, and quality of life. Data were analyzed by interval estimates and through nonparametric analysis. Nonparametric analysis indicated a significant improvement in glycemic status in terms with fasting blood sugar (W = 78 z = 3.04, P = 0.002), 2 h-postprandial blood sugar (W = 54, z = 2.01, P = 0.035), and in knowledge score (χ 2 = 19.53, df = 3; P = 0.0002). Quality of life score showed significant improvement in 2 out of 7 domains, namely, satisfaction with treatment ([difference in mean score = 1.40 [1.94 to 0.85]) and symptom botherness (difference in mean score = 0.98 [1.3-0.65]). Because of inherent methodological limitations and innate biases, at this juncture no conclusive statement can be drawn. Although, primitive process evidences indicate the promising role of the diabetic-DOST strategy.

SPECTRAL DOMAIN VERSUS SWEPT SOURCE OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY OF THE RETINAL CAPILLARY PLEXUSES IN SICKLE CELL MACULOPATHY.

PubMed

Jung, Jesse J; Chen, Michael H; Frambach, Caroline R; Rofagha, Soraya; Lee, Scott S

2018-01-01

To compare the spectral domain and swept source optical coherence tomography angiography findings in two cases of sickle cell maculopathy. A 53-year-old man and a 24-year-old man both with sickle cell disease (hemoglobin SS) presented with no visual complaints; Humphrey visual field testing demonstrated asymptomatic paracentral scotomas that extended nasally in the involved eyes. Clinical examination and multimodal imaging including spectral domain and swept source optical coherence tomography, and spectral domain optical coherence tomography angiography and swept source optical coherence tomography angiography (Carl Zeiss Meditec Inc, Dublin, CA) were performed. Fundus examination of both patients revealed subtle thinning of the macula. En-face swept source optical coherence tomography confirmed the extent of the thinning correlating with the functional paracentral scotomas on Humphrey visual field. Swept source optical coherence tomography B-scan revealed multiple confluent areas of inner nuclear thinning and significant temporal retinal atrophy. En-face 6 × 6-mm spectral domain optical coherence tomography angiography of the macula demonstrated greater loss of the deep capillary plexus compared with the superficial capillary plexus. Swept source optical coherence tomography angiography 12 × 12-mm imaging captured the same macular findings and loss of both plexuses temporally outside the macula. In these two cases of sickle cell maculopathy, deep capillary plexus ischemia is more extensive within the macula, whereas both the superficial capillary plexus and deep capillary plexus are involved outside the macula likely due to the greater oxygen demands and watershed nature of these areas. Swept source optical coherence tomography angiography clearly demonstrates the angiographic extent of the disease correlating with the Humphrey visual field scotomas and confluent areas of inner nuclear atrophy.

Picture Book Exposure Elicits Positive Visual Preferences in Toddlers

ERIC Educational Resources Information Center

Houston-Price, Carmel; Burton, Eliza; Hickinson, Rachel; Inett, Jade; Moore, Emma; Salmon, Katherine; Shiba, Paula

2009-01-01

Although the relationship between "mere exposure" and attitude enhancement is well established in the adult domain, there has been little similar work with children. This article examines whether toddlers' visual attention toward pictures of foods can be enhanced by repeated visual exposure to pictures of foods in a parent-administered picture…

Reading Acquisition Enhances an Early Visual Process of Contour Integration

ERIC Educational Resources Information Center

Szwed, Marcin; Ventura, Paulo; Querido, Luis; Cohen, Laurent; Dehaene, Stanislas

2012-01-01

The acquisition of reading has an extensive impact on the developing brain and leads to enhanced abilities in phonological processing and visual letter perception. Could this expertise also extend to early visual abilities outside the reading domain? Here we studied the performance of illiterate, ex-illiterate and literate adults closely matched…

Expertise in Clinical Pathology: Combining the Visual and Cognitive Perspective

ERIC Educational Resources Information Center

Jaarsma, Thomas; Jarodzka, Halszka; Nap, Marius; van Merriënboer, Jeroen J. G.; Boshuizen, Henny P. A.

2015-01-01

Expertise studies in the medical domain often focus on either visual or cognitive aspects of expertise. As a result, characteristics of expert behaviour are often described as either cognitive or visual abilities. This study focuses on both aspects of expertise and analyses them along three overarching constructs: (1) encapsulations, (2)…

Toward a hybrid brain-computer interface based on repetitive visual stimuli with missing events.

PubMed

Wu, Yingying; Li, Man; Wang, Jing

2016-07-26

Steady-state visually evoked potentials (SSVEPs) can be elicited by repetitive stimuli and extracted in the frequency domain with satisfied performance. However, the temporal information of such stimulus is often ignored. In this study, we utilized repetitive visual stimuli with missing events to present a novel hybrid BCI paradigm based on SSVEP and omitted stimulus potential (OSP). Four discs flickering from black to white with missing flickers served as visual stimulators to simultaneously elicit subject's SSVEPs and OSPs. Key parameters in the new paradigm, including flicker frequency, optimal electrodes, missing flicker duration and intervals of missing events were qualitatively discussed with offline data. Two omitted flicker patterns including missing black/white disc were proposed and compared. Averaging times were optimized with Information Transfer Rate (ITR) in online experiments, where SSVEPs and OSPs were identified using Canonical Correlation Analysis in the frequency domain and Support Vector Machine (SVM)-Bayes fusion in the time domain, respectively. The online accuracy and ITR (mean ± standard deviation) over nine healthy subjects were 79.29 ± 18.14 % and 19.45 ± 11.99 bits/min with missing black disc pattern, and 86.82 ± 12.91 % and 24.06 ± 10.95 bits/min with missing white disc pattern, respectively. The proposed BCI paradigm, for the first time, demonstrated that SSVEPs and OSPs can be simultaneously elicited in single visual stimulus pattern and recognized in real-time with satisfied performance. Besides the frequency features such as SSVEP elicited by repetitive stimuli, we found a new feature (OSP) in the time domain to design a novel hybrid BCI paradigm by adding missing events in repetitive stimuli.

Behavioral, Modeling, and Electrophysiological Evidence for Supramodality in Human Metacognition.

PubMed

Faivre, Nathan; Filevich, Elisa; Solovey, Guillermo; Kühn, Simone; Blanke, Olaf

2018-01-10

Human metacognition, or the capacity to introspect on one's own mental states, has been mostly characterized through confidence reports in visual tasks. A pressing question is to what extent results from visual studies generalize to other domains. Answering this question allows determining whether metacognition operates through shared, supramodal mechanisms or through idiosyncratic, modality-specific mechanisms. Here, we report three new lines of evidence for decisional and postdecisional mechanisms arguing for the supramodality of metacognition. First, metacognitive efficiency correlated among auditory, tactile, visual, and audiovisual tasks. Second, confidence in an audiovisual task was best modeled using supramodal formats based on integrated representations of auditory and visual signals. Third, confidence in correct responses involved similar electrophysiological markers for visual and audiovisual tasks that are associated with motor preparation preceding the perceptual judgment. We conclude that the supramodality of metacognition relies on supramodal confidence estimates and decisional signals that are shared across sensory modalities. SIGNIFICANCE STATEMENT Metacognitive monitoring is the capacity to access, report, and regulate one's own mental states. In perception, this allows rating our confidence in what we have seen, heard, or touched. Although metacognitive monitoring can operate on different cognitive domains, we ignore whether it involves a single supramodal mechanism common to multiple cognitive domains or modality-specific mechanisms idiosyncratic to each domain. Here, we bring evidence in favor of the supramodality hypothesis by showing that participants with high metacognitive performance in one modality are likely to perform well in other modalities. Based on computational modeling and electrophysiology, we propose that supramodality can be explained by the existence of supramodal confidence estimates and by the influence of decisional cues on confidence estimates. Copyright © 2018 the authors 0270-6474/18/380263-15$15.00/0.

Sequence Diversity Diagram for comparative analysis of multiple sequence alignments.

PubMed

Sakai, Ryo; Aerts, Jan

2014-01-01

The sequence logo is a graphical representation of a set of aligned sequences, commonly used to depict conservation of amino acid or nucleotide sequences. Although it effectively communicates the amount of information present at every position, this visual representation falls short when the domain task is to compare between two or more sets of aligned sequences. We present a new visual presentation called a Sequence Diversity Diagram and validate our design choices with a case study. Our software was developed using the open-source program called Processing. It loads multiple sequence alignment FASTA files and a configuration file, which can be modified as needed to change the visualization. The redesigned figure improves on the visual comparison of two or more sets, and it additionally encodes information on sequential position conservation. In our case study of the adenylate kinase lid domain, the Sequence Diversity Diagram reveals unexpected patterns and new insights, for example the identification of subgroups within the protein subfamily. Our future work will integrate this visual encoding into interactive visualization tools to support higher level data exploration tasks.

Modality-Driven Classification and Visualization of Ensemble Variance

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

Bensema, Kevin; Gosink, Luke; Obermaier, Harald

Paper for the IEEE Visualization Conference Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space.

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

Eric A. Wernert; William R. Sherman; Patrick O'Leary

Immersive visualization makes use of the medium of virtual reality (VR) - it is a subset of virtual reality focused on the application of VR technologies to scientific and information visualization. As the name implies, there is a particular focus on the physically immersive aspect of VR that more fully engages the perceptual and kinesthetic capabilities of the scientist with the goal of producing greater insight. The immersive visualization community is uniquely positioned to address the analysis needs of the wide spectrum of domain scientists who are becoming increasingly overwhelmed by data. The outputs of computational science simulations and high-resolutionmore » sensors are creating a data deluge. Data is coming in faster than it can be analyzed, and there are countless opportunities for discovery that are missed as the data speeds by. By more fully utilizing the scientists visual and other sensory systems, and by offering a more natural user interface with which to interact with computer-generated representations, immersive visualization offers great promise in taming this data torrent. However, increasing the adoption of immersive visualization in scientific research communities can only happen by simultaneously lowering the engagement threshold while raising the measurable benefits of adoption. Scientists time spent immersed with their data will thus be rewarded with higher productivity, deeper insight, and improved creativity. Immersive visualization ties together technologies and methodologies from a variety of related but frequently disjoint areas, including hardware, software and human-computer interaction (HCI) disciplines. In many ways, hardware is a solved problem. There are well established technologies including large walk-in systems such as the CAVE{trademark} and head-based systems such as the Wide-5{trademark}. The advent of new consumer-level technologies now enable an entirely new generation of immersive displays, with smaller footprints and costs, widening the potential consumer base. While one would be hard-pressed to call software a solved problem, we now understand considerably more about best practices for designing and developing sustainable, scalable software systems, and we have useful software examples that illuminate the way to even better implementations. As with any research endeavour, HCI will always be exploring new topics in interface design, but we now have a sizable knowledge base of the strengths and weaknesses of the human perceptual systems and we know how to design effective interfaces for immersive systems. So, in a research landscape with a clear need for better visualization and analysis tools, a methodology in immersive visualization that has been shown to effectively address some of those needs, and vastly improved supporting technologies and knowledge of hardware, software, and HCI, why hasn't immersive visualization 'caught on' more with scientists? What can we do as a community of immersive visualization researchers and practitioners to facilitate greater adoption by scientific communities so as to make the transition from 'the promise of virtual reality' to 'the reality of virtual reality'.« less

A spectral power analysis of driving behavior changes during the transition from nondistraction to distraction.

PubMed

Wang, Yuan; Bao, Shan; Du, Wenjun; Ye, Zhirui; Sayer, James R

2017-11-17

This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving. Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual-manual task) and distracted (poststarting of visual-manual task) driving periods. Average relative spectral power in a low frequency range (0-0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses. Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual-manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving. This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses.

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

PubMed Central

Kuleshov, Maxim V.; Jones, Matthew R.; Rouillard, Andrew D.; Fernandez, Nicolas F.; Duan, Qiaonan; Wang, Zichen; Koplev, Simon; Jenkins, Sherry L.; Jagodnik, Kathleen M.; Lachmann, Alexander; McDermott, Michael G.; Monteiro, Caroline D.; Gundersen, Gregory W.; Ma'ayan, Avi

2016-01-01

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr. PMID:27141961

P300 as a measure of processing capacity in auditory and visual domains in Specific Language Impairment

PubMed Central

Evans, Julia L.; Pollak, Seth D.

2011-01-01

This study examined the electrophysiological correlates of auditory and visual working memory in children with Specific Language Impairments (SLI). Children with SLI and age-matched controls (11;9 – 14;10) completed visual and auditory working memory tasks while event-related potentials (ERPs) were recorded. In the auditory condition, children with SLI performed similarly to controls when the memory load was kept low (1-back memory load). As expected, when demands for auditory working memory were higher, children with SLI showed decreases in accuracy and attenuated P3b responses. However, children with SLI also evinced difficulties in the visual working memory tasks. In both the low (1-back) and high (2-back) memory load conditions, P3b amplitude was significantly lower for the SLI as compared to CA groups. These data suggest a domain-general working memory deficit in SLI that is manifested across auditory and visual modalities. PMID:21316354

Sight over sound in the judgment of music performance.

PubMed

Tsay, Chia-Jung

2013-09-03

Social judgments are made on the basis of both visual and auditory information, with consequential implications for our decisions. To examine the impact of visual information on expert judgment and its predictive validity for performance outcomes, this set of seven experiments in the domain of music offers a conservative test of the relative influence of vision versus audition. People consistently report that sound is the most important source of information in evaluating performance in music. However, the findings demonstrate that people actually depend primarily on visual information when making judgments about music performance. People reliably select the actual winners of live music competitions based on silent video recordings, but neither musical novices nor professional musicians were able to identify the winners based on sound recordings or recordings with both video and sound. The results highlight our natural, automatic, and nonconscious dependence on visual cues. The dominance of visual information emerges to the degree that it is overweighted relative to auditory information, even when sound is consciously valued as the core domain content.

Sight over sound in the judgment of music performance

PubMed Central

Tsay, Chia-Jung

2013-01-01

Social judgments are made on the basis of both visual and auditory information, with consequential implications for our decisions. To examine the impact of visual information on expert judgment and its predictive validity for performance outcomes, this set of seven experiments in the domain of music offers a conservative test of the relative influence of vision versus audition. People consistently report that sound is the most important source of information in evaluating performance in music. However, the findings demonstrate that people actually depend primarily on visual information when making judgments about music performance. People reliably select the actual winners of live music competitions based on silent video recordings, but neither musical novices nor professional musicians were able to identify the winners based on sound recordings or recordings with both video and sound. The results highlight our natural, automatic, and nonconscious dependence on visual cues. The dominance of visual information emerges to the degree that it is overweighted relative to auditory information, even when sound is consciously valued as the core domain content. PMID:23959902

Subcortical orientation biases explain orientation selectivity of visual cortical cells.

PubMed

Vidyasagar, Trichur R; Jayakumar, Jaikishan; Lloyd, Errol; Levichkina, Ekaterina V

2015-04-01

The primary visual cortex of carnivores and primates shows an orderly progression of domains of neurons that are selective to a particular orientation of visual stimuli such as bars and gratings. We recorded from single-thalamic afferent fibers that terminate in these domains to address the issue whether the orientation sensitivity of these fibers could form the basis of the remarkable orientation selectivity exhibited by most cortical cells. We first performed optical imaging of intrinsic signals to obtain a map of orientation domains on the dorsal aspect of the anaesthetized cat's area 17. After confirming using electrophysiological recordings the orientation preferences of single neurons within one or two domains in each animal, we pharmacologically silenced the cortex to leave only the afferent terminals active. The inactivation of cortical neurons was achieved by the superfusion of either kainic acid or muscimol. Responses of single geniculate afferents were then recorded by the use of high impedance electrodes. We found that the orientation preferences of the afferents matched closely with those of the cells in the orientation domains that they terminated in (Pearson's r = 0.633, n = 22, P = 0.002). This suggests a possible subcortical origin for cortical orientation selectivity. © 2015 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Sociocultural Knowledge and Visual Re(-)Presentations of Black Masculinity and Community: Reading "The Wire" for Critical Multicultural Teacher Education

ERIC Educational Resources Information Center

Brown, Keffrelyn D.; Kraehe, Amelia

2011-01-01

In this article we consider the implications of using popular visual media as a pedagogic tool for helping teachers acquire critical sociocultural knowledge to work more effectively with students of color, particularly Black males. Drawing from a textual analysis (McKee 2001, 2003; Rose 2001) conducted in the critical visual studies tradition…

The D3 Middleware Architecture

NASA Technical Reports Server (NTRS)

Walton, Joan; Filman, Robert E.; Korsmeyer, David J.; Lee, Diana D.; Mak, Ron; Patel, Tarang

2002-01-01

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid-dynamics) model executions. DARWIN captures, stores and indexes data; manages derived knowledge (such as visualizations across multiple datasets); and provides an environment for designers to collaborate in the analysis of test results. DARWIN is an interesting application because it supports high-volumes of data. integrates multiple modalities of data display (e.g., images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and views of data. Here we provide an overview of the architecture of D3, the third generation of DARWIN. Earlier versions of DARWIN were characterized by browser-based interfaces and a hodge-podge of server technologies: CGI scripts, applets, PERL, and so forth. But browsers proved difficult to control, and a proliferation of computational mechanisms proved inefficient and difficult to maintain. D3 substitutes a pure-Java approach for that medley: A Java client communicates (though RMI over HTTPS) with a Java-based application server. Code on the server accesses information from JDBC databases, distributed LDAP security services, and a collaborative information system. D3 is a three tier-architecture, but unlike 'E-commerce' applications, the data usage pattern suggests different strategies than traditional Enterprise Java Beans - we need to move volumes of related data together, considerable processing happens on the client, and the 'business logic' on the server-side is primarily data integration and collaboration. With D3, we are extending DARWIN to handle other data domains and to be a distributed system, where a single login allows a user transparent access to test results from multiple servers and authority domains.

Accelerated damage visualization using binary search with fixed pitch-catch distance laser ultrasonic scanning

NASA Astrophysics Data System (ADS)

Park, Byeongjin; Sohn, Hoon

2017-07-01

Laser ultrasonic scanning, especially full-field wave propagation imaging, is attractive for damage visualization thanks to its noncontact nature, sensitivity to local damage, and high spatial resolution. However, its practicality is limited because scanning at a high spatial resolution demands a prohibitively long scanning time. Inspired by binary search, an accelerated damage visualization technique is developed to visualize damage with a reduced scanning time. The pitch-catch distance between the excitation point and the sensing point is also fixed during scanning to maintain a high signal-to-noise ratio (SNR) of measured ultrasonic responses. The approximate damage boundary is identified by examining the interactions between ultrasonic waves and damage observed at the scanning points that are sparsely selected by a binary search algorithm. Here, a time-domain laser ultrasonic response is transformed into a spatial ultrasonic domain response using a basis pursuit approach so that the interactions between ultrasonic waves and damage, such as reflections and transmissions, can be better identified in the spatial ultrasonic domain. Then, the area inside the identified damage boundary is visualized as damage. The performance of the proposed damage visualization technique is validated excusing a numerical simulation performed on an aluminum plate with a notch and experiments performed on an aluminum plate with a crack and a wind turbine blade with delamination. The proposed damage visualization technique accelerates the damage visualization process in three aspects: (1) the number of measurements that is necessary for damage visualization is dramatically reduced by a binary search algorithm; (2) the number of averaging that is necessary to achieve a high SNR is reduced by maintaining the wave propagation distance short; and (3) with the proposed technique, the same damage can be identified with a lower spatial resolution than the spatial resolution required by full-field wave propagation imaging.

Workplace nutrition knowledge questionnaire: psychometric validation and application.

PubMed

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

2016-11-01

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

A learning apprentice for software parts composition

NASA Technical Reports Server (NTRS)

Allen, Bradley P.; Holtzman, Peter L.

1987-01-01

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

Expert Knowledge-Based Automatic Sleep Stage Determination by Multi-Valued Decision Making Method

NASA Astrophysics Data System (ADS)

Wang, Bei; Sugi, Takenao; Kawana, Fusae; Wang, Xingyu; Nakamura, Masatoshi

In this study, an expert knowledge-based automatic sleep stage determination system working on a multi-valued decision making method is developed. Visual inspection by a qualified clinician is adopted to obtain the expert knowledge database. The expert knowledge database consists of probability density functions of parameters for various sleep stages. Sleep stages are determined automatically according to the conditional probability. Totally, four subjects were participated. The automatic sleep stage determination results showed close agreements with the visual inspection on sleep stages of awake, REM (rapid eye movement), light sleep and deep sleep. The constructed expert knowledge database reflects the distributions of characteristic parameters which can be adaptive to variable sleep data in hospitals. The developed automatic determination technique based on expert knowledge of visual inspection can be an assistant tool enabling further inspection of sleep disorder cases for clinical practice.

Knowledge acquisition for temporal abstraction.

PubMed

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

1996-01-01

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

Optical, analog and digital domain architectural considerations for visual communications

NASA Astrophysics Data System (ADS)

Metz, W. A.

2008-01-01

The end of the performance entitlement historically achieved by classic scaling of CMOS devices is within sight, driven ultimately by fundamental limits. Performance entitlements predicted by classic CMOS scaling have progressively failed to be realized in recent process generations due to excessive leakage, increasing interconnect delays and scaling of gate dielectrics. Prior to reaching fundamental limits, trends in technology, architecture and economics will pressure the industry to adopt new paradigms. A likely response is to repartition system functions away from digital implementations and into new architectures. Future architectures for visual communications will require extending the implementation into the optical and analog processing domains. The fundamental properties of these domains will in turn give rise to new architectural concepts. The limits of CMOS scaling and impact on architectures will be briefly reviewed. Alternative approaches in the optical, electronic and analog domains will then be examined for advantages, architectural impact and drawbacks.

Seeing faces is necessary for face-patch formation

PubMed Central

Arcaro, Michael J.; Schade, Peter F.; Vincent, Justin L.; Ponce, Carlos R.; Livingstone, Margaret S.

2017-01-01

Here we report that monkeys raised without exposure to faces did not develop face patches, but did develop domains for other categories, and did show normal retinotopic organization, indicating that early face deprivation leads to a highly selective cortical processing deficit. Therefore experience must be necessary for the formation, or maintenance, of face domains. Gaze tracking revealed that control monkeys looked preferentially at faces, even at ages prior to the emergence of face patches, but face-deprived monkeys did not, indicating that face looking is not innate. A retinotopic organization is present throughout the visual system at birth, so selective early viewing behavior could bias category-specific visual responses towards particular retinotopic representations, thereby leading to domain formation in stereotyped locations in IT, without requiring category-specific templates or biases. Thus we propose that environmental importance influences viewing behavior, viewing behavior drives neuronal activity, and neuronal activity sculpts domain formation. PMID:28869581

Volumetric Optical Frequency Domain Imaging of Pulmonary Pathology With Precise Correlation to Histopathology

PubMed Central

Hariri, Lida P.; Applegate, Matthew B.; Mino-Kenudson, Mari; Mark, Eugene J.; Medoff, Benjamin D.; Luster, Andrew D.; Bouma, Brett E.; Tearney, Guillermo J.

2013-01-01

Background: Lung cancer is the leading cause of cancer-related mortality. Radiology and bronchoscopy techniques do not have the necessary resolution to evaluate lung lesions on the microscopic scale, which is critical for diagnosis. Bronchial biopsy specimens can be limited by sampling error and small size. Optical frequency domain imaging (OFDI) provides volumetric views of tissue microstructure at near-histologic resolution and may be useful for evaluating pulmonary lesions to increase diagnostic accuracy. Bronchoscopic OFDI has been evaluated in vivo, but a lack of correlated histopathology has limited the ability to develop accurate image interpretation criteria. Methods: We performed OFDI through two approaches (airway-centered and parenchymal imaging) in 22 ex vivo lung specimens, using tissue dye to precisely correlate imaging and histology. Results: OFDI of normal airway allowed visualization of epithelium, lamina propria, cartilage, and alveolar attachments. Carcinomas exhibited architectural disarray, loss of normal airway and alveolar structure, and rapid light attenuation. Squamous cell carcinomas showed nested architecture. Atypical glandular formation was appreciated in adenocarcinomas, and uniform trabecular gland formation was seen in salivary gland carcinomas. Mucinous adenocarcinomas showed alveolar wall thickening with intraalveolar mucin. Interstitial fibrosis was visualized as signal-dense tissue, with an interstitial distribution in mild interstitial fibrotic disease and a diffuse subpleural pattern with cystic space formation in usual interstitial pneumonitis. Conclusions: To our knowledge, this study is the first demonstration of volumetric OFDI with precise correlation to histopathology in lung pathology. We anticipate that OFDI may play a role in assessing airway and parenchymal pathology, providing fresh insights into the volumetric features of pulmonary disease. PMID:22459781

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

ERIC Educational Resources Information Center

Kostousov, Sergei; Kudryavtsev, Dmitry

2017-01-01

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

US Urban Elementary Teachers' Knowledge and Practices in Teaching Science to English Language Learners: Results from the First Year of a Professional Development Intervention

ERIC Educational Resources Information Center

Santau, Alexandra O.; Secada, Walter; Maerten-Rivera, Jaime; Cone, Neporcha; Lee, Okhee

2010-01-01

The study examined US elementary teachers' knowledge and practices in four key domains of science instruction with English language learning (ELL) students. The four domains included: (1) teachers' knowledge of science content, (2) teaching practices to promote scientific understanding, (3) teaching practices to promote scientific inquiry, and (4)…

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

ERIC Educational Resources Information Center

Cai, Yuyang; Kunnan, Antony John

2018-01-01

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

Processing of Visual Imagery by an Adaptive Model of the Visual System: Its Performance and its Significance. Final Report, June 1969-March 1970.

ERIC Educational Resources Information Center

Tallman, Oliver H.

A digital simulation of a model for the processing of visual images is derived from known aspects of the human visual system. The fundamental principle of computation suggested by a biological model is a transformation that distributes information contained in an input stimulus everywhere in a transform domain. Each sensory input contributes under…

Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization: Human Factors in Streaming Data Analysis

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

Dasgupta, Aritra; Arendt, Dustin L.; Franklin, Lyndsey R.

Real-world systems change continuously and across domains like traffic monitoring, cyber security, etc., such changes occur within short time scales. This leads to a streaming data problem and produces unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. In this paper, our goal is to study how the state-of-the-art in streaming data visualization handles these challenges and reflect on the gaps and opportunities. To this end, we have three contributions: i) problem characterization for identifying domain-specific goals and challenges for handling streaming data, ii) a survey andmore » analysis of the state-of-the-art in streaming data visualization research with a focus on the visualization design space, and iii) reflections on the perceptually motivated design challenges and potential research directions for addressing them.« less

Does silent reading speed in normal adult readers depend on early visual processes? evidence from event-related brain potentials.

PubMed

Korinth, Sebastian Peter; Sommer, Werner; Breznitz, Zvia

2012-01-01

Little is known about the relationship of reading speed and early visual processes in normal readers. Here we examined the association of the early P1, N170 and late N1 component in visual event-related potentials (ERPs) with silent reading speed and a number of additional cognitive skills in a sample of 52 adult German readers utilizing a Lexical Decision Task (LDT) and a Face Decision Task (FDT). Amplitudes of the N170 component in the LDT but, interestingly, also in the FDT correlated with behavioral tests measuring silent reading speed. We suggest that reading speed performance can be at least partially accounted for by the extraction of essential structural information from visual stimuli, consisting of a domain-general and a domain-specific expertise-based portion. © 2011 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Zhang, Yunliang

2018-01-01

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

Requirements analysis, domain knowledge, and design

NASA Technical Reports Server (NTRS)

Potts, Colin

1988-01-01

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

Using the Biodatamation(TM) strategy to learn introductory college biology: Value-added effects on selected students' conceptual understanding and conceptual integration of the processes of photosynthesis and cellular respiration

NASA Astrophysics Data System (ADS)

Reuter, Jewel Jurovich

The purpose of this exploratory research was to study how students learn photosynthesis and cellular respiration and to determine the value added to the student's learning by each of the three technology-scaffolded learning strategy components (animated concept presentations and WebQuest-style activities, data collection, and student-constructed animations) of the BioDatamation(TM) (BDM) Program. BDM learning strategies utilized the Theory of Interacting Visual Fields(TM) (TIVF) (Reuter & Wandersee, 2002a, 2002b; 2003a, 2003b) which holds that meaningful knowledge is hierarchically constructed using the past, present, and future visual fields, with visual metacognitive components that are derived from the principles of Visual Behavior (Jones, 1995), Human Constructivist Theory (Mintzes & Wandersee, 1998a), and Visual Information Design Theory (Tufte, 1990, 1997, 2001). Student alternative conceptions of photosynthesis and cellular respiration were determined by the item analysis of 263,267 Biology Advanced Placement Examinations and were used to develop the BDM instructional strategy and interview questions. The subjects were 24 undergraduate students of high and low biology prior knowledge enrolled in an introductory-level General Biology course at a major research university in the Deep South. Fifteen participants received BDM instruction which included original and innovative learning materials and laboratories in 6 phases; 8 of the 15 participants were the subject of in depth, extended individual analysis. The other 9 participants received traditional, non-BDM instruction. Interviews which included participants' creation of concept maps and visual field diagrams were conducted after each phase. Various content analyses, including Chi's Verbal Analysis and quantitizing/qualitizing were used for data analysis. The total value added to integrative knowledge during BDM instruction with the three visual fields was an average increase of 56% for cellular respiration and 62% increase for photosynthesis knowledge, improved long-term memory of concepts, and enhanced biological literacy to the multidimensional level, as determined by the BSCS literacy model. WebQuest-style activities and data collection provided for animated prior knowledge in the past visual field, and detailed content knowledge construction in the present visual field. During student construction of animated presentations, layering required participants to think by rearranging words and images for improved hierarchical organization of knowledge with real-life applications.

Sports Stars: Analyzing the Performance of Astronomers at Visualization-based Discovery

NASA Astrophysics Data System (ADS)

Fluke, C. J.; Parrington, L.; Hegarty, S.; MacMahon, C.; Morgan, S.; Hassan, A. H.; Kilborn, V. A.

2017-05-01

In this data-rich era of astronomy, there is a growing reliance on automated techniques to discover new knowledge. The role of the astronomer may change from being a discoverer to being a confirmer. But what do astronomers actually look at when they distinguish between “sources” and “noise?” What are the differences between novice and expert astronomers when it comes to visual-based discovery? Can we identify elite talent or coach astronomers to maximize their potential for discovery? By looking to the field of sports performance analysis, we consider an established, domain-wide approach, where the expertise of the viewer (i.e., a member of the coaching team) plays a crucial role in identifying and determining the subtle features of gameplay that provide a winning advantage. As an initial case study, we investigate whether the SportsCode performance analysis software can be used to understand and document how an experienced Hi astronomer makes discoveries in spectral data cubes. We find that the process of timeline-based coding can be applied to spectral cube data by mapping spectral channels to frames within a movie. SportsCode provides a range of easy to use methods for annotation, including feature-based codes and labels, text annotations associated with codes, and image-based drawing. The outputs, including instance movies that are uniquely associated with coded events, provide the basis for a training program or team-based analysis that could be used in unison with discipline specific analysis software. In this coordinated approach to visualization and analysis, SportsCode can act as a visual notebook, recording the insight and decisions in partnership with established analysis methods. Alternatively, in situ annotation and coding of features would be a valuable addition to existing and future visualization and analysis packages.

Development of a knowledge management system for complex domains.

PubMed

Perott, André; Schader, Nils; Bruder, Ralph; Leonhardt, Jörg

2012-01-01

Deutsche Flugsicherung GmbH, the German Air Navigation Service Provider, follows a systematic approach, called HERA, for investigating incidents. The HERA analysis shows a distinctive occurrence of incidents in German air traffic control in which the visual perception of information plays a key role. The reasons can be partially traced back to workstation design, where basic ergonomic rules and principles are not sufficiently followed by the designers in some cases. In cooperation with the Institute of Ergonomics in Darmstadt the DFS investigated possible approaches that may support designers to implement ergonomic systems. None of the currently available tools were found to be able to meet the identified user requirements holistically. Therefore it was suggested to develop an enhanced software tool called Design Process Guide. The name Design Process Guide indicates that this tool exceeds the classic functions of currently available Knowledge Management Systems. It offers "design element" based access, shows processual and content related topics, and shows the implications of certain design decisions. Furthermore, it serves as documentation, detailing why a designer made to a decision under a particular set of conditions.

Pain as metaphor: metaphor and medicine

PubMed Central

Neilson, Shane

2016-01-01

Like many other disciplines, medicine often resorts to metaphor in order to explain complicated concepts that are imperfectly understood. But what happens when medicine's metaphors close off thinking, restricting interpretations and opinions to those of the negative kind? This paper considers the deleterious effects of destructive metaphors that cluster around pain. First, the metaphoric basis of all knowledge is introduced. Next, a particular subset of medical metaphors in the domain of neurology (doors/keys/wires) are shown to encourage mechanistic thinking. Because schematics are often used in medical textbooks to simplify the complex, this paper traces the visual metaphors implied in such schematics. Mechanistic-metaphorical thinking results in the accumulation of vast amounts of data through experimentation, but this paper asks what the real value of the information is since patients can generally only expect modest benefits – or none at all – for relief from chronic pain conditions. Elucidation of mechanism through careful experimentation creates an illusion of vast medical knowledge that, to a significant degree, is metaphor-based. This paper argues that for pain outcomes to change, our metaphors must change first. PMID:26253331

PsyGeNET: a knowledge platform on psychiatric disorders and their genes.

PubMed

Gutiérrez-Sacristán, Alba; Grosdidier, Solène; Valverde, Olga; Torrens, Marta; Bravo, Àlex; Piñero, Janet; Sanz, Ferran; Furlong, Laura I

2015-09-15

PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform for the exploratory analysis of psychiatric diseases and their associated genes. PsyGeNET is composed of a database and a web interface supporting data search, visualization, filtering and sharing. PsyGeNET integrates information from DisGeNET and data extracted from the literature by text mining, which has been curated by domain experts. It currently contains 2642 associations between 1271 genes and 37 psychiatric disease concepts. In its first release, PsyGeNET is focused on three psychiatric disorders: major depression, alcohol and cocaine use disorders. PsyGeNET represents a comprehensive, open access resource for the analysis of the molecular mechanisms underpinning psychiatric disorders and their comorbidities. The PysGeNET platform is freely available at http://www.psygenet.org/. The PsyGeNET database is made available under the Open Database License (http://opendatacommons.org/licenses/odbl/1.0/). lfurlong@imim.es Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

The Ascendancy of the Visual and Issues of Gender: Equality versus Difference.

ERIC Educational Resources Information Center

Damarin, Suzanne K.

1993-01-01

Discussion of visual literacy, visual cognition, visual thinking and learning, and visual knowledge focuses on women and gender differences. Topics addressed include educational equality and the visual, including equality versus difference; women and mass culture; difference and the design of visual instruction; and feminist education and the…

Assessment of nutritional status in the elderly: a proposed function-driven model

PubMed Central

Engelheart, Stina; Brummer, Robert

2018-01-01

Background There is no accepted or standardized definition of ‘malnutrition’. Hence, there is also no definition of what constitutes an adequate nutritional status. In elderly people, assessment of nutritional status is complex and is complicated by multi-morbidity and disabilities combined with nutrition-related problems, such as dysphagia, decreased appetite, fatigue, and muscle weakness. Objective We propose a nutritional status model that presents nutritional status from a comprehensive functional perspective. This model visualizes the complexity of the nutritional status in elderly people. Design and results The presented model could be interpreted as the nutritional status is conditional to a person’s optimal function or situation. Another way of looking at it might be that a person’s nutritional status affects his or her optimal situation. The proposed model includes four domains: (1) physical function and capacity; (2) health and somatic disorders; (3) food and nutrition; and (4) cognitive, affective, and sensory function. Each domain has a major impact on nutritional status, which in turn has a major impact on the outcome of each domain. Conclusions Nutritional status is a multifaceted concept and there exist several knowledge gaps in the diagnosis, prevention, and optimization of treatment of inadequate nutritional status in elderly people. The nutritional status model may be useful in nutritional assessment research, as well as in the clinical setting. PMID:29720931

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

PubMed Central

Jiang, Feng; Han, Ji-zhong

2018-01-01

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

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

PubMed

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

2018-01-01

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

Guidance of visual search by memory and knowledge.

PubMed

Hollingworth, Andrew

2012-01-01

To behave intelligently in the world, humans must be able to find objects efficiently within the complex environments they inhabit. A growing proportion of the literature on visual search is devoted to understanding this type of natural search. In the present chapter, I review the literature on visual search through natural scenes, focusing on the role of memory and knowledge in guiding attention to task-relevant objects.

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

EPA Science Inventory

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

Learning from Instructional Animations: How Does Prior Knowledge Mediate the Effect of Visual Cues?

ERIC Educational Resources Information Center

Arslan-Ari, I.

2018-01-01

The purpose of this study was to investigate the effects of cueing and prior knowledge on learning and mental effort of students studying an animation with narration. This study employed a 2 (no cueing vs. visual cueing) × 2 (low vs. high prior knowledge) between-subjects factorial design. The results revealed a significant interaction effect…

A multi-agent intelligent environment for medical knowledge.

PubMed

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

2003-03-01

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

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

PubMed

Shek, Daniel T L; Lee, Tak Yan

2007-01-01

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

Timing of Visual Bodily Behavior in Repair Sequences: Evidence from Three Languages

ERIC Educational Resources Information Center

Floyd, Simeon; Manrique, Elizabeth; Rossi, Giovanni; Torreira, Francisco

2016-01-01

This article expands the study of other-initiated repair in conversation--when one party signals a problem with producing or perceiving another's turn at talk--into the domain of visual bodily behavior. It presents one primary cross-linguistic finding about the timing of visual bodily behavior in repair sequences: if the party who initiates repair…

Brief Report: Early VEPs to Pattern-Reversal in Adolescents and Adults with Autism

ERIC Educational Resources Information Center

Kovarski, K.; Thillay, A.; Houy-Durand, E.; Roux, S.; Bidet-Caulet, A.; Bonnet-Brilhault, F.; Batty, M.

2016-01-01

Autism spectrum disorder (ASD) is characterized by atypical visual perception both in the social and nonsocial domain. In order to measure a reliable visual response, visual evoked potentials were recorded during a passive pattern-reversal stimulation in adolescents and adults with and without ASD. While the present results show the same…

Visual and Spatial Working Memory Are Not that Dissociated after All: A Time-Based Resource-Sharing Account

ERIC Educational Resources Information Center

Vergauwe, Evie; Barrouillet, Pierre; Camos, Valerie

2009-01-01

Examinations of interference between visual and spatial materials in working memory have suggested domain- and process-based fractionations of visuo-spatial working memory. The present study examined the role of central time-based resource sharing in visuo-spatial working memory and assessed its role in obtained interference patterns. Visual and…

Beyond rules: The next generation of expert systems

NASA Technical Reports Server (NTRS)

Ferguson, Jay C.; Wagner, Robert E.

1987-01-01

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

A Collaborative Knowledge Management Process for Implementing Healthcare Enterprise Information Systems

NASA Astrophysics Data System (ADS)

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

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

Metacognition Difficulty of Students with Visual-Spatial Intelligence during Solving Open-Ended Problem

NASA Astrophysics Data System (ADS)

Rimbatmojo, S.; Kusmayadi, T. A.; Riyadi, R.

2017-09-01

This study aims to find out students metacognition difficulty during solving open-ended problem in mathematics. It focuses on analysing the metacognition difficulty of students with visual-spatial intelligence in solving open-ended problem. A qualitative research with case study strategy is used in this study. Data in the form of visual-spatial intelligence test result and recorded interview during solving open-ended problems were analysed qualitatively. The results show that: (1) students with high visual-spatial intelligence have no difficulty on each metacognition aspects, (2) students with medium visual-spatial intelligence have difficulty on knowledge aspect on strategy and cognitive tasks, (3) students with low visual-spatial intelligence have difficulty on three metacognition aspects, namely knowledge on strategy, cognitive tasks and self-knowledge. Even though, several researches about metacognition process and metacognition literature recommended the steps to know the characteristics. It is still important to discuss that the difficulties of metacognitive is happened because of several factors, one of which on the characteristics of student’ visual-spatial intelligence. Therefore, it is really important for mathematics educators to consider and pay more attention toward students’ visual-spatial intelligence and metacognition difficulty in designing better mathematics learning.

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.

The Digital Space Shuttle, 3D Graphics, and Knowledge Management

NASA Technical Reports Server (NTRS)

Gomez, Julian E.; Keller, Paul J.

2003-01-01

The Digital Shuttle is a knowledge management project that seeks to define symbiotic relationships between 3D graphics and formal knowledge representations (ontologies). 3D graphics provides geometric and visual content, in 2D and 3D CAD forms, and the capability to display systems knowledge. Because the data is so heterogeneous, and the interrelated data structures are complex, 3D graphics combined with ontologies provides mechanisms for navigating the data and visualizing relationships.

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

PubMed Central

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

2012-01-01

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

Applying Knowledge Management to an Organization's Transformation

NASA Technical Reports Server (NTRS)

Potter, Shannon; Gill, Tracy; Fritsche, Ralph

2008-01-01

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

A neural basis for category and modality specificity of semantic knowledge.

PubMed

Thompson-Schill, S L; Aguirre, G K; D'Esposito, M; Farah, M J

1999-06-01

Prevalent theories hold that semantic memory is organized by sensorimotor modality (e.g., visual knowledge, motor knowledge). While some neuroimaging studies support this idea, it cannot account for the category specific (e.g., living things) knowledge impairments seen in some brain damaged patients that cut across modalities. In this article we test an alternative model of how damage to interactive, modality-specific neural regions might give rise to these categorical impairments. Functional MRI was used to examine a cortical area with a known modality-specific function during the retrieval of visual and non-visual knowledge about living and non-living things. The specific predictions of our model regarding the signal observed in this area were confirmed, supporting the notion that semantic memory is functionally segregated into anatomically discrete, but highly interactive, modality-specific regions.

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

NASA Astrophysics Data System (ADS)

Brodaric, B.; Probst, F.

2007-12-01

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

Prevalence of Dental Caries, Oral Hygiene Knowledge, Status, and Practices among Visually Impaired Individuals in Chennai, Tamil Nadu.

PubMed

John, James Rufus; Daniel, Breena; Paneerselvam, Dakshaini; Rajendran, Ganesh

2017-01-01

Aim . To assess the prevalence of dental caries, oral hygiene knowledge, status, and practices among visually impaired individuals in Chennai, Tamil Nadu. Materials and Methods . A cross-sectional study was conducted among 404 visually impaired individuals in Chennai city, Tamil Nadu. Four schools were randomly selected for conducting the study. The oral hygiene status, prevalence of caries, and knowledge and attitude towards oral care among visually impaired individuals were collected and analysed. Results . In the present study, whilst 42% of individuals had fair oral hygiene status, 33% had good hygiene followed by 25% having poor oral hygiene. The overall mean number of DMFT was estimated to be 4.5 ± 2.7. The mean number of decayed teeth was 3.1 ± 2.2, mean number of missing teeth was 0.8 ± 1.4, and mean number of filled teeth was 0.5 ± 1.3. Conclusion . Whilst oral hygiene status was found to be relatively fair, there was a high rate of dental caries among the sample population. This shows that there is lack of knowledge regarding oral health maintenance. Therefore, early identification of caries coupled with effective oral health promotion programs providing practical knowledge to visually impaired students would prove beneficial.

Prevalence of Dental Caries, Oral Hygiene Knowledge, Status, and Practices among Visually Impaired Individuals in Chennai, Tamil Nadu

PubMed Central

Daniel, Breena; Paneerselvam, Dakshaini; Rajendran, Ganesh

2017-01-01

Aim. To assess the prevalence of dental caries, oral hygiene knowledge, status, and practices among visually impaired individuals in Chennai, Tamil Nadu. Materials and Methods. A cross-sectional study was conducted among 404 visually impaired individuals in Chennai city, Tamil Nadu. Four schools were randomly selected for conducting the study. The oral hygiene status, prevalence of caries, and knowledge and attitude towards oral care among visually impaired individuals were collected and analysed. Results. In the present study, whilst 42% of individuals had fair oral hygiene status, 33% had good hygiene followed by 25% having poor oral hygiene. The overall mean number of DMFT was estimated to be 4.5 ± 2.7. The mean number of decayed teeth was 3.1 ± 2.2, mean number of missing teeth was 0.8 ± 1.4, and mean number of filled teeth was 0.5 ± 1.3. Conclusion. Whilst oral hygiene status was found to be relatively fair, there was a high rate of dental caries among the sample population. This shows that there is lack of knowledge regarding oral health maintenance. Therefore, early identification of caries coupled with effective oral health promotion programs providing practical knowledge to visually impaired students would prove beneficial. PMID:28458691

Looking and touching: What extant approaches reveal about the structure of early word knowledge

PubMed Central

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

2014-01-01

The goal of the current study is to assess the temporal dynamics of vision and action to evaluate the underlying word representations that guide infants’ responses. Sixteen-month-old infants participated in a two-alternative forced-choice word-picture matching task. We conducted a moment-by-moment analysis of looking and reaching behaviors as they occurred in tandem to assess the speed with which a prompted word was processed (visual reaction time) as a function of the type of haptic response: Target, Distractor, or No Touch. Visual reaction times (visual RTs) were significantly slower during No Touches compared to Distractor and Target Touches, which were statistically indistinguishable. The finding that visual RTs were significantly faster during Distractor Touches compared to No Touches suggests that incorrect and absent haptic responses appear to index distinct knowledge states: incorrect responses are associated with partial knowledge whereas absent responses appear to reflect a true failure to map lexical items to their target referents. Further, we found that those children who were faster at processing words were also those children who exhibited better haptic performance. This research provides a methodological clarification on knowledge measured by the visual and haptic modalities and new evidence for a continuum of word knowledge in the second year of life. PMID:25444711