Science.gov

Sample records for rule-based semantic integration

  1. Rule-based semantic web services matching strategy

    NASA Astrophysics Data System (ADS)

    Fan, Hong; Wang, Zhihua

    2011-12-01

    With the development of Web services technology, the number of service increases rapidly, and it becomes a challenge task that how to efficiently discovery the services that exactly match the user's requirements from the large scale of services library. Many semantic Web services discovery technologies proposed by the recent literatures only focus on the keyword-based or primary semantic based service's matching. This paper studies the rules and rule reasoning based service matching algorithm in the background of large scale services library. Firstly, the formal descriptions of semantic web services and service matching is presented. The services' matching are divided into four levels: Exact, Plugin, Subsume and Fail and their formal descriptions are also presented. Then, the service matching is regarded as rule-based reasoning issues. A set of match rules are firstly given and the related services set is retrieved from services ontology base through rule-based reasoning, and their matching levels are determined by distinguishing the relationships between service's I/O and user's request I/O. Finally, the experiment based on two services sets show that the proposed services matching strategy can easily implement the smart service discovery and obtains the high service discovery efficiency in comparison with the traditional global traversal strategy.

  2. Semantic classification of diseases in discharge summaries using a context-aware rule-based classifier.

    PubMed

    Solt, Illés; Tikk, Domonkos; Gál, Viktor; Kardkovács, Zsolt T

    2009-01-01

    OBJECTIVE Automated and disease-specific classification of textual clinical discharge summaries is of great importance in human life science, as it helps physicians to make medical studies by providing statistically relevant data for analysis. This can be further facilitated if, at the labeling of discharge summaries, semantic labels are also extracted from text, such as whether a given disease is present, absent, questionable in a patient, or is unmentioned in the document. The authors present a classification technique that successfully solves the semantic classification task. DESIGN The authors introduce a context-aware rule-based semantic classification technique for use on clinical discharge summaries. The classification is performed in subsequent steps. First, some misleading parts are removed from the text; then the text is partitioned into positive, negative, and uncertain context segments, then a sequence of binary classifiers is applied to assign the appropriate semantic labels. Measurement For evaluation the authors used the documents of the i2b2 Obesity Challenge and adopted its evaluation measures: F(1)-macro and F(1)-micro for measurements. RESULTS On the two subtasks of the Obesity Challenge (textual and intuitive classification) the system performed very well, and achieved a F(1)-macro = 0.80 for the textual and F(1)-macro = 0.67 for the intuitive tasks, and obtained second place at the textual and first place at the intuitive subtasks of the challenge. CONCLUSIONS The authors show in the paper that a simple rule-based classifier can tackle the semantic classification task more successfully than machine learning techniques, if the training data are limited and some semantic labels are very sparse.

  3. Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization

    PubMed Central

    Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

    2016-01-01

    Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. Availability and implementation: The annotation ontology for rule-based models can be found at http

  4. Rule-Based and Information-Integration Category Learning in Normal Aging

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M.

    2010-01-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated…

  5. Posterror slowing predicts rule-based but not information-integration category learning.

    PubMed

    Tam, Helen; Maddox, W Todd; Huang-Pollock, Cynthia L

    2013-12-01

    We examined whether error monitoring, operationalized as the degree to which individuals slow down after committing an error (i.e., posterror slowing), is differentially important in the learning of rule-based versus information-integration category structures. Rule-based categories are most efficiently solved through the application of an explicit verbal strategy (e.g., "sort by color"). In contrast, information-integration categories are believed to be learned in a trial-by-trial, associative manner. Our results indicated that posterror slowing predicts enhanced rule-based but not information-integration category learning. Implications for multiple category-learning systems are discussed.

  6. Toward Webscale, Rule-Based Inference on the Semantic Web Via Data Parallelism

    DTIC Science & Technology

    2013-02-01

    distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT This thesis considers the problem of scaling rule-based inference to large quantities of RDF data ...con- ditions are placed on the relationship between rules and distribution schemes, that is, the way in which data is assigned to processors. Then, a...special class of distribution schemes is considered called replication schemes. Replication schemes require that individual data either be replicated

  7. Rule-based and information-integration category learning in normal aging.

    PubMed

    Maddox, W Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M

    2010-08-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated processes, whereas information-integration is thought to involve implicit, striatally mediated processes. As a group, older adults showed rule-based and information-integration deficits. A series of models were applied that provided insights onto the type of strategy used to solve the task. Interestingly, when the analyses focused only on participants who used the task appropriate strategy in the final block of trials, the age-related rule-based deficit disappeared whereas the information-integration deficit remained. For this group of individuals, the final block information-integration deficit was due to less consistent application of the task appropriate strategy by older adults, and over the course of learning these older adults shifted from an explicit hypothesis-testing strategy to the task appropriate strategy later in learning. In addition, the use of the task appropriate strategy was associated with less interference and better inhibitory control for rule-based and information-information learning, whereas use of the task appropriate strategy was associated with greater working memory and better new verbal learning only for the rule-based task. These results suggest that normal aging impacts both forms of category learning and that there are some important similarities and differences in the explanatory locus of these deficits. The data also support a two-component model of information-integration category learning that includes a striatal component that mediated procedural-based learning, and a prefrontal cortical component that mediates the transition from hypothesis-testing to procedural-based strategies

  8. Prefrontal Contributions to Rule-Based and Information-Integration Category Learning

    ERIC Educational Resources Information Center

    Schnyer, David M.; Maddox, W. Todd; Ell, Shawn; Davis, Sarah; Pacheco, Jenni; Verfaellie, Mieke

    2009-01-01

    Previous research revealed that the basal ganglia play a critical role in category learning [Ell, S. W., Marchant, N. L., & Ivry, R. B. (2006). "Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks." "Neuropsychologia", 44(10), 1737-1751; Maddox, W. T. & Filoteo, J.…

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

    NASA Technical Reports Server (NTRS)

    Logie, David S.; Kamil, Hasan

    1990-01-01

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

  10. Feedback can be superior to observational training for both rule-based and information-integration category structures.

    PubMed

    Edmunds, C E R; Milton, Fraser; Wills, Andy J

    2015-01-01

    The effects of two different types of training on rule-based and information-integration category learning were investigated in two experiments. In observational training, a category label is presented, followed by an example of that category and the participant's response. In feedback training, the stimulus is presented, and the participant assigns it to a category and then receives feedback about the accuracy of that decision. Ashby, Maddox, and Bohil (2002. Observational versus feedback training in rule-based and information-integration category learning. Memory & Cognition, 30, 666-677) reported that feedback training was superior to observational training when learning information-integration category structures, but that training type had little effect on the acquisition of rule-based category structures. These results were argued to support the COVIS (competition between verbal and implicit systems) dual-process account of category learning. However, a number of nonessential differences between their rule-based and information-integration conditions complicate interpretation of these findings. Experiment 1 controlled between-category structures for participant error rates, category separation, and the number of stimulus dimensions relevant to the categorization. Under these more controlled conditions, rule-based and information-integration category structures both benefited from feedback training to a similar degree. Experiment 2 maintained this difference in training type when learning a rule-based category that had otherwise been matched, in terms of category overlap and overall performance, with the rule-based categories used in Ashby et al. These results indicate that differences in dimensionality between the category structures in Ashby et al. is a more likely explanation for the interaction between training type and category structure than the dual-system explanation that they offered.

  11. Project Integration Architecture: Formulation of Semantic Parameters

    NASA Technical Reports Server (NTRS)

    Jones, William Henry

    2005-01-01

    One of several key elements of the Project Integration Architecture (PIA) is the intention to formulate parameter objects which convey meaningful semantic information. In so doing, it is expected that a level of automation can be achieved in the consumption of information content by PIA-consuming clients outside the programmatic boundary of a presenting PIA-wrapped application. This paper discusses the steps that have been recently taken in formulating such semantically-meaningful parameters.

  12. Category Number Impacts Rule-Based but Not Information-Integration Category Learning: Further Evidence for Dissociable Category-Learning Systems

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Filoteo, J. Vincent; Hejl, Kelli D.; Ing, A. David

    2004-01-01

    Category number effects on rule-based and information-integration category learning were investigated. Category number affected accuracy and the distribution of best-fitting models in the rule-based task but had no effect on accuracy and little effect on the distribution of best-fining models in the information-integration task. In the 2 category…

  13. Semantic web for integrated network analysis in biomedicine.

    PubMed

    Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

    2009-03-01

    The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

  14. Semantic Web meets Integrative Biology: a survey.

    PubMed

    Chen, Huajun; Yu, Tong; Chen, Jake Y

    2013-01-01

    Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies. The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB.

  15. Semantic integration of data on transcriptional regulation

    PubMed Central

    Baitaluk, Michael; Ponomarenko, Julia

    2010-01-01

    Motivation: Experimental and predicted data concerning gene transcriptional regulation are distributed among many heterogeneous sources. However, there are no resources to integrate these data automatically or to provide a ‘one-stop shop’ experience for users seeking information essential for deciphering and modeling gene regulatory networks. Results: IntegromeDB, a semantic graph-based ‘deep-web’ data integration system that automatically captures, integrates and manages publicly available data concerning transcriptional regulation, as well as other relevant biological information, is proposed in this article. The problems associated with data integration are addressed by ontology-driven data mapping, multiple data annotation and heterogeneous data querying, also enabling integration of the user's data. IntegromeDB integrates over 100 experimental and computational data sources relating to genomics, transcriptomics, genetics, and functional and interaction data concerning gene transcriptional regulation in eukaryotes and prokaryotes. Availability: IntegromeDB is accessible through the integrated research environment BiologicalNetworks at http://www.BiologicalNetworks.org Contact: baitaluk@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20427517

  16. A Description and Functional Taxonomy of Rule-based Decision Support Content at a Large Integrated Delivery Network

    PubMed Central

    Wright, Adam; Goldberg, Howard; Hongsermeier, Tonya; Middleton, Blackford

    2007-01-01

    Objective This study sought to develop a functional taxonomy of rule-based clinical decision support. Design The rule-based clinical decision support content of a large integrated delivery network with a long history of computer-based point-of-care decision support was reviewed and analyzed along four functional dimensions: trigger, input data elements, interventions, and offered choices. Results A total of 181 rule types were reviewed, comprising 7,120 different instances of rule usage. A total of 42 taxa were identified across the four categories. Many rules fell into multiple taxa in a given category. Entered order and stored laboratory result were the most common triggers; laboratory result, drug list, and hospital unit were the most frequent data elements used. Notify and log were the most common interventions, and write order, defer warning, and override rule were the most common offered choices. Conclusion A relatively small number of taxa successfully described a large body of clinical knowledge. These taxa can be directly mapped to functions of clinical systems and decision support systems, providing feature guidance for developers, implementers, and certifiers of clinical information systems. PMID:17460131

  17. A Comparison of the neural correlates that underlie rule-based and information-integration category learning.

    PubMed

    Carpenter, Kathryn L; Wills, Andy J; Benattayallah, Abdelmalek; Milton, Fraser

    2016-10-01

    The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp 37:3557-3574, 2016. © 2016 Wiley Periodicals, Inc.

  18. Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

    PubMed

    Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F

    2017-03-01

    This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning.

  19. Integrated Estimation of Seismic Physical Vulnerability of Tehran Using Rule Based Granular Computing

    NASA Astrophysics Data System (ADS)

    Sheikhian, H.; Delavar, M. R.; Stein, A.

    2015-08-01

    Tehran, the capital of Iran, is surrounded by the North Tehran fault, the Mosha fault and the Rey fault. This exposes the city to possibly huge earthquakes followed by dramatic human loss and physical damage, in particular as it contains a large number of non-standard constructions and aged buildings. Estimation of the likely consequences of an earthquake facilitates mitigation of these losses. Mitigation of the earthquake fatalities may be achieved by promoting awareness of earthquake vulnerability and implementation of seismic vulnerability reduction measures. In this research, granular computing using generality and absolute support for rule extraction is applied. It uses coverage and entropy for rule prioritization. These rules are combined to form a granule tree that shows the order and relation of the extracted rules. In this way the seismic physical vulnerability is assessed, integrating the effects of the three major known faults. Effective parameters considered in the physical seismic vulnerability assessment are slope, seismic intensity, height and age of the buildings. Experts were asked to predict seismic vulnerability for 100 randomly selected samples among more than 3000 statistical units in Tehran. The integrated experts' point of views serve as input into granular computing. Non-redundant covering rules preserve the consistency in the model, which resulted in 84% accuracy in the seismic vulnerability assessment based on the validation of the predicted test data against expected vulnerability degree. The study concluded that granular computing is a useful method to assess the effects of earthquakes in an earthquake prone area.

  20. Semantic search integration to climate data

    SciTech Connect

    Devarakonda, Ranjeet; Palanisamy, Giri; Pouchard, Line Catherine; Shrestha, Biva

    2014-01-01

    In this paper we present how research projects at Oak Ridge National Laboratory are using Semantic Search capabilities to help scientists perform their research. We will discuss how the Mercury metadata search system, with the help of the semantic search capability, is being used to find, retrieve, and link climate change data. DOI: 10.1109/CTS.2014.6867639

  1. Semantic integration for mapping the underworld

    NASA Astrophysics Data System (ADS)

    Fu, Gaihua; Cohn, Anthony G.

    2008-10-01

    Utility infrastructure is vital to the daily life of modern society. As the vast majority of urban utility assets are buried underneath public roads, the need to install/repair utility assets often requires opening ground with busy traffic. Unfortunately, at present most excavation works are carried out without knowing exactly what is where, which causes far more street breakings than necessary. This research studies how maximum benefit can be gained from the existing knowledge of buried assets. The key challenge here is that utility data is heterogeneous, which arises due to different domain perceptions and varying data modelling practices. This research investigates factors which prevent utility knowledge from being fully exploited and suggests that integration techniques can be applied for reconciling semantic heterogeneity within the utility domain. In this paper we discuss the feasibility of a common utility ontology to describe underground assets, and present techniques for constructing a basic utility ontology in the form of a thesaurus. The paper also demonstrates how the utility thesaurus developed is employed as a shared ontology for mapping utility data. Experiments have been performed to evaluate the techniques proposed, and feedback from industrial partners is encouraging and shows that techniques work effectively with real world utility data.

  2. Category Number Impacts Rule-Based "and" Information-Integration Category Learning: A Reassessment of Evidence for Dissociable Category-Learning Systems

    ERIC Educational Resources Information Center

    Stanton, Roger D.; Nosofsky, Robert M.

    2013-01-01

    Researchers have proposed that an explicit reasoning system is responsible for learning rule-based category structures and that a separate implicit, procedural-learning system is responsible for learning information-integration category structures. As evidence for this multiple-system hypothesis, researchers report a dissociation based on…

  3. The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning.

    PubMed

    Hofman, Abe D; Visser, Ingmar; Jansen, Brenda R J; van der Maas, Han L J

    2015-01-01

    We propose and test three statistical models for the analysis of children's responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM) following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779), and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808). For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development.

  4. The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning

    PubMed Central

    Hofman, Abe D.; Visser, Ingmar; Jansen, Brenda R. J.; van der Maas, Han L. J.

    2015-01-01

    We propose and test three statistical models for the analysis of children’s responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM) following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779), and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808). For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development. PMID:26505905

  5. Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

    PubMed

    Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

    2016-01-13

    An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

  6. Two theories of consciousness: Semantic pointer competition vs. information integration.

    PubMed

    Thagard, Paul; Stewart, Terrence C

    2014-11-01

    Consciousness results from three mechanisms: representation by firing patterns in neural populations, binding of representations into more complex representations called semantic pointers, and competition among semantic pointers to capture the most important aspects of an organism's current state. We contrast the semantic pointer competition (SPC) theory of consciousness with the hypothesis that consciousness is the capacity of a system to integrate information (IIT). We describe computer simulations to show that SPC surpasses IIT in providing better explanations of key aspects of consciousness: qualitative features, onset and cessation, shifts in experiences, differences in kinds across different organisms, unity and diversity, and storage and retrieval.

  7. Specification and Enforcement of Semantic Integrity Constraints in Microsoft Access

    ERIC Educational Resources Information Center

    Dadashzadeh, Mohammad

    2007-01-01

    Semantic integrity constraints are business-specific rules that limit the permissible values in a database. For example, a university rule dictating that an "incomplete" grade cannot be changed to an A constrains the possible states of the database. To maintain database integrity, business rules should be identified in the course of database…

  8. Enriched Video Semantic Metadata: Authorization, Integration, and Presentation.

    ERIC Educational Resources Information Center

    Mu, Xiangming; Marchionini, Gary

    2003-01-01

    Presents an enriched video metadata framework including video authorization using the Video Annotation and Summarization Tool (VAST)-a video metadata authorization system that integrates both semantic and visual metadata-- metadata integration, and user level applications. Results demonstrated that the enriched metadata were seamlessly…

  9. Ontology alignment architecture for semantic sensor Web integration.

    PubMed

    Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

    2013-09-18

    Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  10. Mining integrated semantic networks for drug repositioning opportunities

    PubMed Central

    Mullen, Joseph; Tipney, Hannah

    2016-01-01

    Current research and development approaches to drug discovery have become less fruitful and more costly. One alternative paradigm is that of drug repositioning. Many marketed examples of repositioned drugs have been identified through serendipitous or rational observations, highlighting the need for more systematic methodologies to tackle the problem. Systems level approaches have the potential to enable the development of novel methods to understand the action of therapeutic compounds, but requires an integrative approach to biological data. Integrated networks can facilitate systems level analyses by combining multiple sources of evidence to provide a rich description of drugs, their targets and their interactions. Classically, such networks can be mined manually where a skilled person is able to identify portions of the graph (semantic subgraphs) that are indicative of relationships between drugs and highlight possible repositioning opportunities. However, this approach is not scalable. Automated approaches are required to systematically mine integrated networks for these subgraphs and bring them to the attention of the user. We introduce a formal framework for the definition of integrated networks and their associated semantic subgraphs for drug interaction analysis and describe DReSMin, an algorithm for mining semantically-rich networks for occurrences of a given semantic subgraph. This algorithm allows instances of complex semantic subgraphs that contain data about putative drug repositioning opportunities to be identified in a computationally tractable fashion, scaling close to linearly with network data. We demonstrate the utility of our approach by mining an integrated drug interaction network built from 11 sources. This work identified and ranked 9,643,061 putative drug-target interactions, showing a strong correlation between highly scored associations and those supported by literature. We discuss the 20 top ranked associations in more detail, of which

  11. Mining integrated semantic networks for drug repositioning opportunities.

    PubMed

    Mullen, Joseph; Cockell, Simon J; Tipney, Hannah; Woollard, Peter M; Wipat, Anil

    2016-01-01

    Current research and development approaches to drug discovery have become less fruitful and more costly. One alternative paradigm is that of drug repositioning. Many marketed examples of repositioned drugs have been identified through serendipitous or rational observations, highlighting the need for more systematic methodologies to tackle the problem. Systems level approaches have the potential to enable the development of novel methods to understand the action of therapeutic compounds, but requires an integrative approach to biological data. Integrated networks can facilitate systems level analyses by combining multiple sources of evidence to provide a rich description of drugs, their targets and their interactions. Classically, such networks can be mined manually where a skilled person is able to identify portions of the graph (semantic subgraphs) that are indicative of relationships between drugs and highlight possible repositioning opportunities. However, this approach is not scalable. Automated approaches are required to systematically mine integrated networks for these subgraphs and bring them to the attention of the user. We introduce a formal framework for the definition of integrated networks and their associated semantic subgraphs for drug interaction analysis and describe DReSMin, an algorithm for mining semantically-rich networks for occurrences of a given semantic subgraph. This algorithm allows instances of complex semantic subgraphs that contain data about putative drug repositioning opportunities to be identified in a computationally tractable fashion, scaling close to linearly with network data. We demonstrate the utility of our approach by mining an integrated drug interaction network built from 11 sources. This work identified and ranked 9,643,061 putative drug-target interactions, showing a strong correlation between highly scored associations and those supported by literature. We discuss the 20 top ranked associations in more detail, of which

  12. SCALEUS: Semantic Web Services Integration for Biomedical Applications.

    PubMed

    Sernadela, Pedro; González-Castro, Lorena; Oliveira, José Luís

    2017-04-01

    In recent years, we have witnessed an explosion of biological data resulting largely from the demands of life science research. The vast majority of these data are freely available via diverse bioinformatics platforms, including relational databases and conventional keyword search applications. This type of approach has achieved great results in the last few years, but proved to be unfeasible when information needs to be combined or shared among different and scattered sources. During recent years, many of these data distribution challenges have been solved with the adoption of semantic web. Despite the evident benefits of this technology, its adoption introduced new challenges related with the migration process, from existent systems to the semantic level. To facilitate this transition, we have developed Scaleus, a semantic web migration tool that can be deployed on top of traditional systems in order to bring knowledge, inference rules, and query federation to the existent data. Targeted at the biomedical domain, this web-based platform offers, in a single package, straightforward data integration and semantic web services that help developers and researchers in the creation process of new semantically enhanced information systems. SCALEUS is available as open source at http://bioinformatics-ua.github.io/scaleus/ .

  13. Category number impacts rule-based and information-integration category learning: a reassessment of evidence for dissociable category-learning systems.

    PubMed

    Stanton, Roger D; Nosofsky, Robert M

    2013-07-01

    Researchers have proposed that an explicit reasoning system is responsible for learning rule-based category structures and that a separate implicit, procedural-learning system is responsible for learning information-integration category structures. As evidence for this multiple-system hypothesis, researchers report a dissociation based on category-number manipulations in which rule-based category learning is worse when the category is composed of 4, rather than 2, response categories; however, information-integration category learning is unaffected by category-number manipulations. We argue that within the reported category-number manipulations, there exists a critical confound: Perceptual clusters used to construct the categories are spread apart in the 4-category condition relative to the 2-category one. The present research shows that when this confound is eliminated, performance on information-integration category learning is worse for 4 categories than for 2 categories, and this finding is demonstrated across 2 different information-integration category structures. Furthermore, model-based analyses indicate that a single-system learning model accounts well for both the original findings and the updated experimental findings reported here.

  14. Towards A Topological Framework for Integrating Semantic Information Sources

    SciTech Connect

    Joslyn, Cliff A.; Hogan, Emilie A.; Robinson, Michael

    2014-09-07

    In this position paper we argue for the role that topological modeling principles can play in providing a framework for sensor integration. While used successfully in standard (quantitative) sensors, we are developing this methodology in new directions to make it appropriate specifically for semantic information sources, including keyterms, ontology terms, and other general Boolean, categorical, ordinal, and partially-ordered data types. We illustrate the basics of the methodology in an extended use case/example, and discuss path forward.

  15. Project Integration Architecture: Formulation of Dimensionality in Semantic Parameters Outline

    NASA Technical Reports Server (NTRS)

    Jones, William Henry

    2005-01-01

    One of several key elements of the Project Integration Architecture (PIA) is the formulation of parameter objects which convey meaningful semantic information. The infusion of measurement dimensionality into such objects is an important part of that effort since it promises to automate the conversion of units between cooperating applications and, thereby, eliminate the mistakes that have occasionally beset other systems of information transport. This paper discusses the conceptualization of dimensionality developed as a result of that effort.

  16. Predicting Protein Function via Semantic Integration of Multiple Networks.

    PubMed

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

    2016-01-01

    Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

  17. Semantic Integrative Digital Pathology: Insights into Microsemiological Semantics and Image Analysis Scalability.

    PubMed

    Racoceanu, Daniel; Capron, Frédérique

    2016-01-01

    Being able to provide a traceable and dynamic second opinion has become an ethical priority for patients and health care professionals in modern computer-aided medicine. In this perspective, a semantic cognitive virtual microscopy approach has been recently initiated, the MICO project, by focusing on cognitive digital pathology. This approach supports the elaboration of pathology-compliant daily protocols dedicated to breast cancer grading, in particular mitotic counts and nuclear atypia. A proof of concept has thus been elaborated, and an extension of these approaches is now underway in a collaborative digital pathology framework, the FlexMIm project. As important milestones on the way to routine digital pathology, a series of pioneer international benchmarking initiatives have been launched for mitosis detection (MITOS), nuclear atypia grading (MITOS-ATYPIA) and glandular structure detection (GlaS), some of the fundamental grading components in diagnosis and prognosis. These initiatives allow envisaging a consolidated validation referential database for digital pathology in the very near future. This reference database will need coordinated efforts from all major teams working in this area worldwide, and it will certainly represent a critical bottleneck for the acceptance of all future imaging modules in clinical practice. In line with recent advances in molecular imaging and genetics, keeping the microscopic modality at the core of future digital systems in pathology is fundamental to insure the acceptance of these new technologies, as well as for a deeper systemic, structured comprehension of the pathologies. After all, at the scale of routine whole-slide imaging (WSI; ∼0.22 µm/pixel), the microscopic image represents a structured 'genomic cluster', enabling a naturally structured support for integrative digital pathology approaches. In order to accelerate and structure the integration of this heterogeneous information, a major effort is and will continue to

  18. Integrating Non-Semantic Knowledge into Image Segmentation Processes.

    DTIC Science & Technology

    1984-03-01

    D-A149 571 INTEGRATING NON-SEMANTIC KNOWLEDGE INTO IMAGE 1/2 SEGMENTATION PROCESSES(U) MRSSACHUSETTS UNIV AMHERST DEPT OF COMPUTER AND INFORMATION S... IMAGE SEGMENTATION PROCESSES Ralf R. Kohler COINS Technical Report 84-04 SJAN 1 7 1985) This work was supported in part by the Office of Naval Rearch...RR07048-16. DITPI~rN STTM!4 j~pwvq jx public 7le" Dwtnutlfl nlmited . .. Teatn Non-SanatIC Knowledge into Image Segmentation Proces A Dissertation

  19. Semantic Web integration of Cheminformatics resources with the SADI framework

    PubMed Central

    2011-01-01

    Background The diversity and the largely independent nature of chemical research efforts over the past half century are, most likely, the major contributors to the current poor state of chemical computational resource and database interoperability. While open software for chemical format interconversion and database entry cross-linking have partially addressed database interoperability, computational resource integration is hindered by the great diversity of software interfaces, languages, access methods, and platforms, among others. This has, in turn, translated into limited reproducibility of computational experiments and the need for application-specific computational workflow construction and semi-automated enactment by human experts, especially where emerging interdisciplinary fields, such as systems chemistry, are pursued. Fortunately, the advent of the Semantic Web, and the very recent introduction of RESTful Semantic Web Services (SWS) may present an opportunity to integrate all of the existing computational and database resources in chemistry into a machine-understandable, unified system that draws on the entirety of the Semantic Web. Results We have created a prototype framework of Semantic Automated Discovery and Integration (SADI) framework SWS that exposes the QSAR descriptor functionality of the Chemistry Development Kit. Since each of these services has formal ontology-defined input and output classes, and each service consumes and produces RDF graphs, clients can automatically reason about the services and available reference information necessary to complete a given overall computational task specified through a simple SPARQL query. We demonstrate this capability by carrying out QSAR analysis backed by a simple formal ontology to determine whether a given molecule is drug-like. Further, we discuss parameter-based control over the execution of SADI SWS. Finally, we demonstrate the value of computational resource envelopment as SADI services through

  20. Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

    NASA Astrophysics Data System (ADS)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2013-04-01

    Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total

  1. Semantic Integration for Marine Science Interoperability Using Web Technologies

    NASA Astrophysics Data System (ADS)

    Rueda, C.; Bermudez, L.; Graybeal, J.; Isenor, A. W.

    2008-12-01

    The Marine Metadata Interoperability Project, MMI (http://marinemetadata.org) promotes the exchange, integration, and use of marine data through enhanced data publishing, discovery, documentation, and accessibility. A key effort is the definition of an Architectural Framework and Operational Concept for Semantic Interoperability (http://marinemetadata.org/sfc), which is complemented with the development of tools that realize critical use cases in semantic interoperability. In this presentation, we describe a set of such Semantic Web tools that allow performing important interoperability tasks, ranging from the creation of controlled vocabularies and the mapping of terms across multiple ontologies, to the online registration, storage, and search services needed to work with the ontologies (http://mmisw.org). This set of services uses Web standards and technologies, including Resource Description Framework (RDF), Web Ontology language (OWL), Web services, and toolkits for Rich Internet Application development. We will describe the following components: MMI Ontology Registry: The MMI Ontology Registry and Repository provides registry and storage services for ontologies. Entries in the registry are associated with projects defined by the registered users. Also, sophisticated search functions, for example according to metadata items and vocabulary terms, are provided. Client applications can submit search requests using the WC3 SPARQL Query Language for RDF. Voc2RDF: This component converts an ASCII comma-delimited set of terms and definitions into an RDF file. Voc2RDF facilitates the creation of controlled vocabularies by using a simple form-based user interface. Created vocabularies and their descriptive metadata can be submitted to the MMI Ontology Registry for versioning and community access. VINE: The Vocabulary Integration Environment component allows the user to map vocabulary terms across multiple ontologies. Various relationships can be established, for example

  2. Electrophysiological Evidence for Incremental Lexical-Semantic Integration in Auditory Compound Comprehension

    ERIC Educational Resources Information Center

    Koester, Dirk; Holle, Henning; Gunter, Thomas C.

    2009-01-01

    The present study investigated the time-course of semantic integration in auditory compound word processing. Compounding is a productive mechanism of word formation that is used frequently in many languages. Specifically, we examined whether semantic integration is incremental or is delayed until the head, the last constituent in German, is…

  3. Semantic ambiguity within and across languages: an integrative review.

    PubMed

    Degani, Tamar; Tokowicz, Natasha

    2010-07-01

    Semantic ambiguity often occurs within a language (e.g., the word "organ" in English means both a body part and a musical instrument), but it can also cross a language boundary, such that a given word form is shared in two languages, but its meanings are different (e.g., the word "angel" means "sting" in Dutch). Bilingual individuals are therefore faced not only with ambiguity in each of their languages, but also with ambiguity across languages. The current review focuses on studies that explored such cross-language ambiguity and examines how the results from these studies can be integrated with what we have learned about within-language ambiguity resolution. In particular, this review examines how interactions of frequency and context manifest themselves in ambiguity that crosses a language boundary and call for the inclusion of language context as a contributing factor. An extension of the monolingual reordered access model (Duffy, Morris, & Rayner, 1988) is outlined to discuss the interactions between these factors. Furthermore, the effects of the similarity between the two meanings, task differences, and individual differences are explored. This review highlights the need for studies that test within- and cross-language ambiguity in the same individuals before strong conclusions can be made about the nature of interactions between frequency, semantic context, and language context.

  4. Integrated semantics service platform for the Internet of Things: a case study of a smart office.

    PubMed

    Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok

    2015-01-19

    The Internet of Things (IoT) allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP) to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability.

  5. Integrated Semantics Service Platform for the Internet of Things: A Case Study of a Smart Office

    PubMed Central

    Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok

    2015-01-01

    The Internet of Things (IoT) allows machines and devices in the world to connect with each other and generate a huge amount of data, which has a great potential to provide useful knowledge across service domains. Combining the context of IoT with semantic technologies, we can build integrated semantic systems to support semantic interoperability. In this paper, we propose an integrated semantic service platform (ISSP) to support ontological models in various IoT-based service domains of a smart city. In particular, we address three main problems for providing integrated semantic services together with IoT systems: semantic discovery, dynamic semantic representation, and semantic data repository for IoT resources. To show the feasibility of the ISSP, we develop a prototype service for a smart office using the ISSP, which can provide a preset, personalized office environment by interpreting user text input via a smartphone. We also discuss a scenario to show how the ISSP-based method would help build a smart city, where services in each service domain can discover and exploit IoT resources that are wanted across domains. We expect that our method could eventually contribute to providing people in a smart city with more integrated, comprehensive services based on semantic interoperability. PMID:25608216

  6. Distributed semantic networks and CLIPS

    NASA Technical Reports Server (NTRS)

    Snyder, James; Rodriguez, Tony

    1991-01-01

    Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.

  7. Altered semantic integration in autism beyond language: a cross-modal event-related potentials study.

    PubMed

    Ribeiro, Tatiane C; Valasek, Claudia A; Minati, Ludovico; Boggio, Paulo S

    2013-05-29

    Autism spectrum disorders (ASDs) are characterized by impaired communication, particularly pragmatic and semantic language, resulting in verbal comprehension deficits. Semantic processing in these conditions has been studied extensively, but mostly limited only to linguistic material. Emerging evidence, however, suggests that semantic integration deficits may extend beyond the verbal domain. Here, we explored cross-modal semantic integration using visual targets preceded by musical and linguistic cues. Particularly, we have recorded the event-related potentials to evaluate whether the N400 and late positive potential (LPP) components, two widely studied electrophysiological markers of semantic processing, are differently sensitive to congruence with respect to typically developing children. Seven ASD patients and seven neurotypical participants matched by age, education and intelligence quotient provided usable data. Neuroelectric activity was recorded in response to visual targets that were related or unrelated to a preceding spoken sentence or musical excerpt. The N400 was sensitive to semantic congruence in the controls but not the patients, whereas the LPP showed a complementary pattern. These results suggest that semantic processing in ASD children is also altered in the context of musical and visual stimuli, and point to a functional decoupling between the generators of the N400 and LPP, which may indicate delayed semantic processing. These novel findings underline the importance of exploring semantic integration across multiple modalities in ASDs and provide motivation for further investigation in large clinical samples.

  8. Disease Ontology: a backbone for disease semantic integration.

    PubMed

    Schriml, Lynn Marie; Arze, Cesar; Nadendla, Suvarna; Chang, Yu-Wei Wayne; Mazaitis, Mark; Felix, Victor; Feng, Gang; Kibbe, Warren Alden

    2012-01-01

    The Disease Ontology (DO) database (http://disease-ontology.org) represents a comprehensive knowledge base of 8043 inherited, developmental and acquired human diseases (DO version 3, revision 2510). The DO web browser has been designed for speed, efficiency and robustness through the use of a graph database. Full-text contextual searching functionality using Lucene allows the querying of name, synonym, definition, DOID and cross-reference (xrefs) with complex Boolean search strings. The DO semantically integrates disease and medical vocabularies through extensive cross mapping and integration of MeSH, ICD, NCI's thesaurus, SNOMED CT and OMIM disease-specific terms and identifiers. The DO is utilized for disease annotation by major biomedical databases (e.g. Array Express, NIF, IEDB), as a standard representation of human disease in biomedical ontologies (e.g. IDO, Cell line ontology, NIFSTD ontology, Experimental Factor Ontology, Influenza Ontology), and as an ontological cross mappings resource between DO, MeSH and OMIM (e.g. GeneWiki). The DO project (http://diseaseontology.sf.net) has been incorporated into open source tools (e.g. Gene Answers, FunDO) to connect gene and disease biomedical data through the lens of human disease. The next iteration of the DO web browser will integrate DO's extended relations and logical definition representation along with these biomedical resource cross-mappings.

  9. Semantic-JSON: a lightweight web service interface for Semantic Web contents integrating multiple life science databases.

    PubMed

    Kobayashi, Norio; Ishii, Manabu; Takahashi, Satoshi; Mochizuki, Yoshiki; Matsushima, Akihiro; Toyoda, Tetsuro

    2011-07-01

    Global cloud frameworks for bioinformatics research databases become huge and heterogeneous; solutions face various diametric challenges comprising cross-integration, retrieval, security and openness. To address this, as of March 2011 organizations including RIKEN published 192 mammalian, plant and protein life sciences databases having 8.2 million data records, integrated as Linked Open or Private Data (LOD/LPD) using SciNetS.org, the Scientists' Networking System. The huge quantity of linked data this database integration framework covers is based on the Semantic Web, where researchers collaborate by managing metadata across public and private databases in a secured data space. This outstripped the data query capacity of existing interface tools like SPARQL. Actual research also requires specialized tools for data analysis using raw original data. To solve these challenges, in December 2009 we developed the lightweight Semantic-JSON interface to access each fragment of linked and raw life sciences data securely under the control of programming languages popularly used by bioinformaticians such as Perl and Ruby. Researchers successfully used the interface across 28 million semantic relationships for biological applications including genome design, sequence processing, inference over phenotype databases, full-text search indexing and human-readable contents like ontology and LOD tree viewers. Semantic-JSON services of SciNetS.org are provided at http://semanticjson.org.

  10. Separate Brain Circuits Support Integrative and Semantic Priming in the Human Language System.

    PubMed

    Feng, Gangyi; Chen, Qi; Zhu, Zude; Wang, Suiping

    2016-07-01

    Semantic priming is a crucial phenomenon to study the organization of semantic memory. A novel type of priming effect, integrative priming, has been identified behaviorally, whereby a prime word facilitates recognition of a target word when the 2 concepts can be combined to form a unitary representation. We used both functional and anatomical imaging approaches to investigate the neural substrates supporting such integrative priming, and compare them with those in semantic priming. Similar behavioral priming effects for both semantic (Bread-Cake) and integrative conditions (Cherry-Cake) were observed when compared with an unrelated condition. However, a clearly dissociated brain response was observed between these 2 types of priming. The semantic-priming effect was localized to the posterior superior temporal and middle temporal gyrus. In contrast, the integrative-priming effect localized to the left anterior inferior frontal gyrus and left anterior temporal cortices. Furthermore, fiber tractography showed that the integrative-priming regions were connected via uncinate fasciculus fiber bundle forming an integrative circuit, whereas the semantic-priming regions connected to the posterior frontal cortex via separated pathways. The results point to dissociable neural pathways underlying the 2 distinct types of priming, illuminating the neural circuitry organization of semantic representation and integration.

  11. Semantic Integration and Age of Acquisition Effects in Code-Blend Comprehension

    PubMed Central

    Emmorey, Karen

    2016-01-01

    Semantic and lexical decision tasks were used to investigate the mechanisms underlying code-blend facilitation: the finding that hearing bimodal bilinguals comprehend signs in American Sign Language (ASL) and spoken English words more quickly when they are presented together simultaneously than when each is presented alone. More robust facilitation effects were observed for semantic decision than for lexical decision, suggesting that lexical integration of signs and words within a code-blend occurs primarily at the semantic level, rather than at the level of form. Early bilinguals exhibited greater facilitation effects than late bilinguals for English (the dominant language) in the semantic decision task, possibly because early bilinguals are better able to process early visual cues from ASL signs and use these to constrain English word recognition. Comprehension facilitation via semantic integration of words and signs is consistent with co-speech gesture research demonstrating facilitative effects of gesture integration on language comprehension. PMID:26657077

  12. Linked Metadata - lightweight semantics for data integration (Invited)

    NASA Astrophysics Data System (ADS)

    Hendler, J. A.

    2013-12-01

    The "Linked Open Data" cloud (http://linkeddata.org) is currently used to show how the linking of datasets, supported by SPARQL endpoints, is creating a growing set of linked data assets. This linked data space has been growing rapidly, and the last version collected is estimated to have had over 35 billion 'triples.' As impressive as this may sound, there is an inherent flaw in the way the linked data story is conceived. The idea is that all of the data is represented in a linked format (generally RDF) and applications will essentially query this cloud and provide mashup capabilities between the various kinds of data that are found. The view of linking in the cloud is fairly simple -links are provided by either shared URIs or by URIs that are asserted to be owl:sameAs. This view of the linking, which primarily focuses on shared objects and subjects in RDF's subject-predicate-object representation, misses a critical aspect of Semantic Web technology. Given triples such as * A:person1 foaf:knows A:person2 * B:person3 foaf:knows B:person4 * C:person5 foaf:name 'John Doe' this view would not consider them linked (barring other assertions) even though they share a common vocabulary. In fact, we get significant clues that there are commonalities in these data items from the shared namespaces and predicates, even if the traditional 'graph' view of RDF doesn't appear to join on these. Thus, it is the linking of the data descriptions, whether as metadata or other vocabularies, that provides the linking in these cases. This observation is crucial to scientific data integration where the size of the datasets, or even the individual relationships within them, can be quite large. (Note that this is not restricted to scientific data - search engines, social networks, and massive multiuser games also create huge amounts of data.) To convert all the triples into RDF and provide individual links is often unnecessary, and is both time and space intensive. Those looking to do on the

  13. Integrating Syntax, Semantics, and Discourse DARPA (Defense Advanced Research Projects Agency) Natural Language Understanding Program

    DTIC Science & Technology

    1988-08-01

    resolution of anaphoric references, and an analysis of temporal relations. The resulting data structure is known as the Integrated Discourse Representation... binding procedures * semantics.pl - the Semantic Interpreter * world.pl - general knowledge base procedures - Pragmatics * discourse-rules.pl - manage

  14. SemantEco: a semantically powered modular architecture for integrating distributed environmental and ecological data

    USGS Publications Warehouse

    Patton, Evan W.; Seyed, Patrice; Wang, Ping; Fu, Linyun; Dein, F. Joshua; Bristol, R. Sky; McGuinness, Deborah L.

    2014-01-01

    We aim to inform the development of decision support tools for resource managers who need to examine large complex ecosystems and make recommendations in the face of many tradeoffs and conflicting drivers. We take a semantic technology approach, leveraging background ontologies and the growing body of linked open data. In previous work, we designed and implemented a semantically enabled environmental monitoring framework called SemantEco and used it to build a water quality portal named SemantAqua. Our previous system included foundational ontologies to support environmental regulation violations and relevant human health effects. In this work, we discuss SemantEco’s new architecture that supports modular extensions and makes it easier to support additional domains. Our enhanced framework includes foundational ontologies to support modeling of wildlife observation and wildlife health impacts, thereby enabling deeper and broader support for more holistically examining the effects of environmental pollution on ecosystems. We conclude with a discussion of how, through the application of semantic technologies, modular designs will make it easier for resource managers to bring in new sources of data to support more complex use cases.

  15. A Bayesian framework for knowledge attribution: evidence from semantic integration.

    PubMed

    Powell, Derek; Horne, Zachary; Pinillos, N Ángel; Holyoak, Keith J

    2015-06-01

    We propose a Bayesian framework for the attribution of knowledge, and apply this framework to generate novel predictions about knowledge attribution for different types of "Gettier cases", in which an agent is led to a justified true belief yet has made erroneous assumptions. We tested these predictions using a paradigm based on semantic integration. We coded the frequencies with which participants falsely recalled the word "thought" as "knew" (or a near synonym), yielding an implicit measure of conceptual activation. Our experiments confirmed the predictions of our Bayesian account of knowledge attribution across three experiments. We found that Gettier cases due to counterfeit objects were not treated as knowledge (Experiment 1), but those due to intentionally-replaced evidence were (Experiment 2). Our findings are not well explained by an alternative account focused only on luck, because accidentally-replaced evidence activated the knowledge concept more strongly than did similar false belief cases (Experiment 3). We observed a consistent pattern of results across a number of different vignettes that varied the quality and type of evidence available to agents, the relative stakes involved, and surface details of content. Accordingly, the present findings establish basic phenomena surrounding people's knowledge attributions in Gettier cases, and provide explanations of these phenomena within a Bayesian framework.

  16. Life-Span Differences in Semantic Integration of Pictures and Sentences in Memory.

    ERIC Educational Resources Information Center

    Pezdek, Kathy

    1980-01-01

    Examines life-span developmental differences in spontaneous integration of semantically relevant material presented in pictures and sentences. Elementary school students, high school students, and adults were tested. (Author/SS)

  17. Integration of Sentence-Level Semantic Information in Parafovea: Evidence from the RSVP-Flanker Paradigm.

    PubMed

    Zhang, Wenjia; Li, Nan; Wang, Xiaoyue; Wang, Suiping

    2015-01-01

    During text reading, the parafoveal word was usually presented between 2° and 5° from the point of fixation. Whether semantic information of parafoveal words can be processed during sentence reading is a critical and long-standing issue. Recently, studies using the RSVP-flanker paradigm have shown that the incongruent parafoveal word, presented as right flanker, elicited a more negative N400 compared with the congruent parafoveal word. This suggests that the semantic information of parafoveal words can be extracted and integrated during sentence reading, because the N400 effect is a classical index of semantic integration. However, as most previous studies did not control the word-pair congruency of the parafoveal and the foveal words that were presented in the critical triad, it is still unclear whether such integration happened at the sentence level or just at the word-pair level. The present study addressed this question by manipulating verbs in Chinese sentences to yield either a semantically congruent or semantically incongruent context for the critical noun. In particular, the interval between the critical nouns and verbs was controlled to be 4 or 5 characters. Thus, to detect the incongruence of the parafoveal noun, participants had to integrate it with the global sentential context. The results revealed that the N400 time-locked to the critical triads was more negative in incongruent than in congruent sentences, suggesting that parafoveal semantic information can be integrated at the sentence level during Chinese reading.

  18. A semantic web framework to integrate cancer omics data with biological knowledge

    PubMed Central

    2012-01-01

    Background The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. Results For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. Conclusions We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily. PMID:22373303

  19. Precedency control and other semantic integrity issues in a workbench database

    NASA Technical Reports Server (NTRS)

    Dampney, C. N. G.

    1983-01-01

    Most database systems model the current state of a system of real world discrete and simple entities together with their relationships. By examining instead a database system that is a workbench and models more complicated entities, a fresh perspective is gained. Specifically, semantic integrity is analysed. Four aspects distinct from physical integrity are identified, namely - access, failure, concurrency and precedency. Access control is shown to be the consequence of semantic interdependency between data and its matching semantic routines. Failure, concurrency precedency controls are concerned with preventing processes interfering with each other. Precedency is a new concept in the database context. It expresses a constraint between processes that act on the database. As processes create, update and delete entities they in general obey a partial ordering imposed by the semantics of their actions. Precedency control ensures that data remains consistent with respect to this partial order.

  20. Reduced functional connectivity during controlled semantic integration in schizophrenia: A multivariate approach.

    PubMed

    Woodward, Todd S; Tipper, Christine M; Leung, Alexander L; Lavigne, Katie M; Sanford, Nicole; Metzak, Paul D

    2015-08-01

    Impairment in controlled semantic association is a central feature of schizophrenia, and the goal of the current functional magnetic resonance imaging study was to identify the neural correlates of this impairment. Thirty people with schizophrenia and 30 healthy age- and gender-matched control subjects performed a task requiring participants to match word pairs that varied in semantic distance (distant vs. close). A whole-brain multivariate connectivity analysis revealed three functional brain networks of primary interest engaged by the task: two configurations of a multiple demands network, in which brain activity did not differ between groups, and a semantic integration network, in which coordinated activity was reduced in schizophrenia patients relative to healthy controls, for distantly relative to closely related word pairs. The hypoactivity during controlled semantic integration in schizophrenia reported here, combined with hyperactivity in automatic semantic association reported in the literature, suggests an imbalance between controlled integration and automatic association. This provides a biological basis for Bleuler's concept of schizophrenia as a "split mind" arising from an impaired ability to form coherent associations between semantic concepts.

  1. Integrating Experiential and Distributional Data to Learn Semantic Representations

    ERIC Educational Resources Information Center

    Andrews, Mark; Vigliocco, Gabriella; Vinson, David

    2009-01-01

    The authors identify 2 major types of statistical data from which semantic representations can be learned. These are denoted as "experiential data" and "distributional data". Experiential data are derived by way of experience with the physical world and comprise the sensory-motor data obtained through sense receptors. Distributional data, by…

  2. Towards virtual knowledge broker services for semantic integration of life science literature and data sources.

    PubMed

    Harrow, Ian; Filsell, Wendy; Woollard, Peter; Dix, Ian; Braxenthaler, Michael; Gedye, Richard; Hoole, David; Kidd, Richard; Wilson, Jabe; Rebholz-Schuhmann, Dietrich

    2013-05-01

    Research in the life sciences requires ready access to primary data, derived information and relevant knowledge from a multitude of sources. Integration and interoperability of such resources are crucial for sharing content across research domains relevant to the life sciences. In this article we present a perspective review of data integration with emphasis on a semantics driven approach to data integration that pushes content into a shared infrastructure, reduces data redundancy and clarifies any inconsistencies. This enables much improved access to life science data from numerous primary sources. The Semantic Enrichment of the Scientific Literature (SESL) pilot project demonstrates feasibility for using already available open semantic web standards and technologies to integrate public and proprietary data resources, which span structured and unstructured content. This has been accomplished through a precompetitive consortium, which provides a cost effective approach for numerous stakeholders to work together to solve common problems.

  3. Electrophysiological correlates of cross-linguistic semantic integration in hearing signers: N400 and LPC.

    PubMed

    Zachau, Swantje; Korpilahti, Pirjo; Hämäläinen, Jarmo A; Ervast, Leena; Heinänen, Kaisu; Suominen, Kalervo; Lehtihalmes, Matti; Leppänen, Paavo H T

    2014-07-01

    We explored semantic integration mechanisms in native and non-native hearing users of sign language and non-signing controls. Event-related brain potentials (ERPs) were recorded while participants performed a semantic decision task for priming lexeme pairs. Pairs were presented either within speech or across speech and sign language. Target-related ERP responses were subjected to principal component analyses (PCA), and neurocognitive basis of semantic integration processes were assessed by analyzing the N400 and the late positive complex (LPC) components in response to spoken (auditory) and signed (visual) antonymic and unrelated targets. Semantically-related effects triggered across modalities would indicate a similar tight interconnection between the signers׳ two languages like that described for spoken language bilinguals. Remarkable structural similarity of the N400 and LPC components with varying group differences between the spoken and signed targets were found. The LPC was the dominant response. The controls׳ LPC differed from the LPC of the two signing groups. It was reduced to the auditory unrelated targets and was less frontal for all the visual targets. The visual LPC was more broadly distributed in native than non-native signers and was left-lateralized for the unrelated targets in the native hearing signers only. Semantic priming effects were found for the auditory N400 in all groups, but only native hearing signers revealed a clear N400 effect to the visual targets. Surprisingly, the non-native signers revealed no semantically-related processing effect to the visual targets reflected in the N400 or the LPC; instead they appeared to rely more on visual post-lexical analyzing stages than native signers. We conclude that native and non-native signers employed different processing strategies to integrate signed and spoken semantic content. It appeared that the signers׳ semantic processing system was affected by group-specific factors like language

  4. Semantic Elaboration through Integration: Hints Both Facilitate and Inform the Process

    ERIC Educational Resources Information Center

    Bauer, Patricia J.; Varga, Nicole L.; King, Jessica E.; Nolen, Ayla M.; White, Elizabeth A.

    2015-01-01

    Semantic knowledge can be extended in a variety of ways, including self-generation of new facts through integration of separate yet related episodes. We sought to promote integration and self-generation by providing "hints" to help 6-year-olds (Experiment 1) and 4-year-olds (Experiment 2) see the relevance of separate episodes to one…

  5. Multimodal Feature Integration in the Angular Gyrus during Episodic and Semantic Retrieval

    PubMed Central

    Bonnici, Heidi M.; Richter, Franziska R.; Yazar, Yasemin

    2016-01-01

    Much evidence from distinct lines of investigation indicates the involvement of angular gyrus (AnG) in the retrieval of both episodic and semantic information, but the region's precise function and whether that function differs across episodic and semantic retrieval have yet to be determined. We used univariate and multivariate fMRI analysis methods to examine the role of AnG in multimodal feature integration during episodic and semantic retrieval. Human participants completed episodic and semantic memory tasks involving unimodal (auditory or visual) and multimodal (audio-visual) stimuli. Univariate analyses revealed the recruitment of functionally distinct AnG subregions during the retrieval of episodic and semantic information. Consistent with a role in multimodal feature integration during episodic retrieval, significantly greater AnG activity was observed during retrieval of integrated multimodal episodic memories compared with unimodal episodic memories. Multivariate classification analyses revealed that individual multimodal episodic memories could be differentiated in AnG, with classification accuracy tracking the vividness of participants' reported recollections, whereas distinct unimodal memories were represented in sensory association areas only. In contrast to episodic retrieval, AnG was engaged to a statistically equivalent degree during retrieval of unimodal and multimodal semantic memories, suggesting a distinct role for AnG during semantic retrieval. Modality-specific sensory association areas exhibited corresponding activity during both episodic and semantic retrieval, which mirrored the functional specialization of these regions during perception. The results offer new insights into the integrative processes subserved by AnG and its contribution to our subjective experience of remembering. SIGNIFICANCE STATEMENT Using univariate and multivariate fMRI analyses, we provide evidence that functionally distinct subregions of angular gyrus (An

  6. Rule-based simulation models

    NASA Technical Reports Server (NTRS)

    Nieten, Joseph L.; Seraphine, Kathleen M.

    1991-01-01

    Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

  7. Organizational Knowledge Transfer Using Ontologies and a Rule-Based System

    NASA Astrophysics Data System (ADS)

    Okabe, Masao; Yoshioka, Akiko; Kobayashi, Keido; Yamaguchi, Takahira

    In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

  8. Novel word integration in the mental lexicon: evidence from unmasked and masked semantic priming.

    PubMed

    Tamminen, Jakke; Gaskell, M Gareth

    2013-01-01

    We sought to establish whether novel words can become integrated into existing semantic networks by teaching participants new meaningful words and then using these new words as primes in two semantic priming experiments, in which participants carried out a lexical decision task to familiar words. Importantly, at no point in training did the novel words co-occur with the familiar words that served as targets in the primed lexical decision task, allowing us to evaluate semantic priming in the absence of direct association. We found that familiar words were primed by the newly related novel words, both when the novel word prime was unmasked (experiment 1) and when it was masked (experiment 2), suggesting that the new words had been integrated into semantic memory. Furthermore, this integration was strongest after a 1-week delay and was independent of explicit recall of the novel word meanings: Forgetting of meanings did not attenuate priming. We argue that even after brief training, newly learned words become an integrated part of the adult mental lexicon rather than being episodically represented separately from the lexicon.

  9. An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework

    ERIC Educational Resources Information Center

    Gao, Wenlong

    2012-01-01

    The ontology approach has been accepted as a very promising approach to semantic integration today. However, because of the diversity of focuses and its various connections to other research domains, the core concepts, theoretical and technical approaches, and research areas of this domain still remain unclear. Such ambiguity makes it difficult to…

  10. Semantic integration of gene expression analysis tools and data sources using software connectors

    PubMed Central

    2013-01-01

    Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools

  11. Integration and Querying of Genomic and Proteomic Semantic Annotations for Biomedical Knowledge Extraction.

    PubMed

    Masseroli, Marco; Canakoglu, Arif; Ceri, Stefano

    2016-01-01

    Understanding complex biological phenomena involves answering complex biomedical questions on multiple biomolecular information simultaneously, which are expressed through multiple genomic and proteomic semantic annotations scattered in many distributed and heterogeneous data sources; such heterogeneity and dispersion hamper the biologists' ability of asking global queries and performing global evaluations. To overcome this problem, we developed a software architecture to create and maintain a Genomic and Proteomic Knowledge Base (GPKB), which integrates several of the most relevant sources of such dispersed information (including Entrez Gene, UniProt, IntAct, Expasy Enzyme, GO, GOA, BioCyc, KEGG, Reactome, and OMIM). Our solution is general, as it uses a flexible, modular, and multilevel global data schema based on abstraction and generalization of integrated data features, and a set of automatic procedures for easing data integration and maintenance, also when the integrated data sources evolve in data content, structure, and number. These procedures also assure consistency, quality, and provenance tracking of all integrated data, and perform the semantic closure of the hierarchical relationships of the integrated biomedical ontologies. At http://www.bioinformatics.deib.polimi.it/GPKB/, a Web interface allows graphical easy composition of queries, although complex, on the knowledge base, supporting also semantic query expansion and comprehensive explorative search of the integrated data to better sustain biomedical knowledge extraction.

  12. Large scale healthcare data integration and analysis using the semantic web.

    PubMed

    Timm, John; Renly, Sondra; Farkash, Ariel

    2011-01-01

    Healthcare data interoperability can only be achieved when the semantics of the content is well defined and consistently implemented across heterogeneous data sources. Achieving these objectives of interoperability requires the collaboration of experts from several domains. This paper describes tooling that integrates Semantic Web technologies with common tools to facilitate cross-domain collaborative development for the purposes of data interoperability. Our approach is divided into stages of data harmonization and representation, model transformation, and instance generation. We applied our approach on Hypergenes, an EU funded project, where we use our method to the Essential Hypertension disease model using a CDA template. Our domain expert partners include clinical providers, clinical domain researchers, healthcare information technology experts, and a variety of clinical data consumers. We show that bringing Semantic Web technologies into the healthcare interoperability toolkit increases opportunities for beneficial collaboration thus improving patient care and clinical research outcomes.

  13. Sharing human-generated observations by integrating HMI and the Semantic Sensor Web.

    PubMed

    Sigüenza, Alvaro; Díaz-Pardo, David; Bernat, Jesús; Vancea, Vasile; Blanco, José Luis; Conejero, David; Gómez, Luis Hernández

    2012-01-01

    Current "Internet of Things" concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C's Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers' observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound.

  14. Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web

    PubMed Central

    Sigüenza, Álvaro; Díaz-Pardo, David; Bernat, Jesús; Vancea, Vasile; Blanco, José Luis; Conejero, David; Gómez, Luis Hernández

    2012-01-01

    Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C's Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers' observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound. PMID:22778643

  15. Clinical evaluation of using semantic searching engine for radiological imaging services in RIS-integrated PACS

    NASA Astrophysics Data System (ADS)

    Ling, Tonghui; Zhang, Kai; Yang, Yuanyuan; Hua, Yanqing; Zhang, Jianguo

    2015-03-01

    We had designed a semantic searching engine (SSE) for radiological imaging to search both reports and images in RIS-integrated PACS environment. In this presentation, we present evaluation results of this SSE about how it impacting the radiologists' behaviors in reporting for different kinds of examinations, and how it improving the performance of retrieval and usage of historical images in RIS-integrated PACS.

  16. Rule-Based Runtime Verification

    NASA Technical Reports Server (NTRS)

    Barringer, Howard; Goldberg, Allen; Havelund, Klaus; Sen, Koushik

    2003-01-01

    We present a rule-based framework for defining and implementing finite trace monitoring logics, including future and past time temporal logic, extended regular expressions, real-time logics, interval logics, forms of quantified temporal logics, and so on. Our logic, EAGLE, is implemented as a Java library and involves novel techniques for rule definition, manipulation and execution. Monitoring is done on a state-by-state basis, without storing the execution trace.

  17. Addressing the Challenges of Multi-Domain Data Integration with the SemantEco Framework

    NASA Astrophysics Data System (ADS)

    Patton, E. W.; Seyed, P.; McGuinness, D. L.

    2013-12-01

    Data integration across multiple domains will continue to be a challenge with the proliferation of big data in the sciences. Data origination issues and how data are manipulated are critical to enable scientists to understand and consume disparate datasets as research becomes more multidisciplinary. We present the SemantEco framework as an exemplar for designing an integrative portal for data discovery, exploration, and interpretation that uses best practice W3C Recommendations. We use the Resource Description Framework (RDF) with extensible ontologies described in the Web Ontology Language (OWL) to provide graph-based data representation. Furthermore, SemantEco ingests data via the software package csv2rdf4lod, which generates data provenance using the W3C provenance recommendation (PROV). Our presentation will discuss benefits and challenges of semantic integration, their effect on runtime performance, and how the SemantEco framework assisted in identifying performance issues and improved query performance across multiple domains by an order of magnitude. SemantEco benefits from a semantic approach that provides an 'open world', which allows data to incrementally change just as it does in the real world. SemantEco modules may load new ontologies and data using the W3C's SPARQL Protocol and RDF Query Language via HTTP. Modules may also provide user interface elements for applications and query capabilities to support new use cases. Modules can associate with domains, which are first-class objects in SemantEco. This enables SemantEco to perform integration and reasoning both within and across domains on module-provided data. The SemantEco framework has been used to construct a web portal for environmental and ecological data. The portal includes water and air quality data from the U.S. Geological Survey (USGS) and Environmental Protection Agency (EPA) and species observation counts for birds and fish from the Avian Knowledge Network and the Santa Barbara Long Term

  18. Semantic Health Knowledge Graph: Semantic Integration of Heterogeneous Medical Knowledge and Services

    PubMed Central

    Yang, Xiaoran; Qi, Jiaheng; Pan, Gang; Zhou, Binbin

    2017-01-01

    With the explosion of healthcare information, there has been a tremendous amount of heterogeneous textual medical knowledge (TMK), which plays an essential role in healthcare information systems. Existing works for integrating and utilizing the TMK mainly focus on straightforward connections establishment and pay less attention to make computers interpret and retrieve knowledge correctly and quickly. In this paper, we explore a novel model to organize and integrate the TMK into conceptual graphs. We then employ a framework to automatically retrieve knowledge in knowledge graphs with a high precision. In order to perform reasonable inference on knowledge graphs, we propose a contextual inference pruning algorithm to achieve efficient chain inference. Our algorithm achieves a better inference result with precision and recall of 92% and 96%, respectively, which can avoid most of the meaningless inferences. In addition, we implement two prototypes and provide services, and the results show our approach is practical and effective. PMID:28299322

  19. An architecture for rule based system explanation

    NASA Technical Reports Server (NTRS)

    Fennel, T. R.; Johannes, James D.

    1990-01-01

    A system architecture is presented which incorporate both graphics and text into explanations provided by rule based expert systems. This architecture facilitates explanation of the knowledge base content, the control strategies employed by the system, and the conclusions made by the system. The suggested approach combines hypermedia and inference engine capabilities. Advantages include: closer integration of user interface, explanation system, and knowledge base; the ability to embed links to deeper knowledge underlying the compiled knowledge used in the knowledge base; and allowing for more direct control of explanation depth and duration by the user. User models are suggested to control the type, amount, and order of information presented.

  20. Applying Semantic Web Services and Wireless Sensor Networks for System Integration

    NASA Astrophysics Data System (ADS)

    Berkenbrock, Gian Ricardo; Hirata, Celso Massaki; de Oliveira Júnior, Frederico Guilherme Álvares; de Oliveira, José Maria Parente

    In environments like factories, buildings, and homes automation services tend to often change during their lifetime. Changes are concerned to business rules, process optimization, cost reduction, and so on. It is important to provide a smooth and straightforward way to deal with these changes so that could be handled in a faster and low cost manner. Some prominent solutions use the flexibility of Wireless Sensor Networks and the meaningful description of Semantic Web Services to provide service integration. In this work, we give an overview of current solutions for machinery integration that combine both technologies as well as a discussion about some perspectives and open issues when applying Wireless Sensor Networks and Semantic Web Services for automation services integration.

  1. Famous face identification in temporal lobe epilepsy: support for a multimodal integration model of semantic memory.

    PubMed

    Drane, Daniel L; Ojemann, Jeffrey G; Phatak, Vaishali; Loring, David W; Gross, Robert E; Hebb, Adam O; Silbergeld, Daniel L; Miller, John W; Voets, Natalie L; Saindane, Amit M; Barsalou, Lawrence; Meador, Kimford J; Ojemann, George A; Tranel, Daniel

    2013-06-01

    This study aims to demonstrate that the left and right anterior temporal lobes (ATLs) perform critical but unique roles in famous face identification, with damage to either leading to differing deficit patterns reflecting decreased access to lexical or semantic concepts but not their degradation. Famous face identification was studied in 22 presurgical and 14 postsurgical temporal lobe epilepsy (TLE) patients and 20 healthy comparison subjects using free recall and multiple choice (MC) paradigms. Right TLE patients exhibited presurgical deficits in famous face recognition, and postsurgical deficits in both famous face recognition and familiarity judgments. However, they did not exhibit any problems with naming before or after surgery. In contrast, left TLE patients demonstrated both pre- and postsurgical deficits in famous face naming but no significant deficits in recognition or familiarity. Double dissociations in performance between groups were alleviated by altering task demands. Postsurgical right TLE patients provided with MC options correctly identified greater than 70% of famous faces they initially rated as unfamiliar. Left TLE patients accurately chose the name for nearly all famous faces they recognized (based on their verbal description) but initially failed to name, although they tended to rapidly lose access to this name. We believe alterations in task demands activate alternative routes to semantic and lexical networks, demonstrating that unique pathways to such stored information exist, and suggesting a different role for each ATL in identifying visually presented famous faces. The right ATL appears to play a fundamental role in accessing semantic information from a visual route, with the left ATL serving to link semantic information to the language system to produce a specific name. These findings challenge several assumptions underlying amodal models of semantic memory, and provide support for the integrated multimodal theories of semantic memory

  2. Construction of an Ortholog Database Using the Semantic Web Technology for Integrative Analysis of Genomic Data

    PubMed Central

    Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

    2015-01-01

    Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis. PMID:25875762

  3. Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

    PubMed

    Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

    2015-01-01

    Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.

  4. Bim-Gis Integrated Geospatial Information Model Using Semantic Web and Rdf Graphs

    NASA Astrophysics Data System (ADS)

    Hor, A.-H.; Jadidi, A.; Sohn, G.

    2016-06-01

    In recent years, 3D virtual indoor/outdoor urban modelling becomes a key spatial information framework for many civil and engineering applications such as evacuation planning, emergency and facility management. For accomplishing such sophisticate decision tasks, there is a large demands for building multi-scale and multi-sourced 3D urban models. Currently, Building Information Model (BIM) and Geographical Information Systems (GIS) are broadly used as the modelling sources. However, data sharing and exchanging information between two modelling domains is still a huge challenge; while the syntactic or semantic approaches do not fully provide exchanging of rich semantic and geometric information of BIM into GIS or vice-versa. This paper proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graphs. The novelty of the proposed solution comes from the benefits of integrating BIM and GIS technologies into one unified model, so-called Integrated Geospatial Information Model (IGIM). The proposed approach consists of three main modules: BIM-RDF and GIS-RDF graphs construction, integrating of two RDF graphs, and query of information through IGIM-RDF graph using SPARQL. The IGIM generates queries from both the BIM and GIS RDF graphs resulting a semantically integrated model with entities representing both BIM classes and GIS feature objects with respect to the target-client application. The linkage between BIM-RDF and GIS-RDF is achieved through SPARQL endpoints and defined by a query using set of datasets and entity classes with complementary properties, relationships and geometries. To validate the proposed approach and its performance, a case study was also tested using IGIM system design.

  5. Integrating Syntax, Semantics, and Discourse DARPA Natural Language Understanding Program. Volume 1

    DTIC Science & Technology

    1987-05-14

    34•"tutttion Unlimited 17 i Deborah Dahi, John Dowding, Lynette Hirschman, Franpois Lang, Marcia Linebarger, Martha Palmer, Rebecca Passonneau, Leslie Riley...Linebarger, Martha Palmer, Rebecca Passonneau, Leslie Riley May 14, 1987 w Eflaa®«K®fflJffl5MMßSöföföÄ©^^ INTEGRATING SYNTAX, SEMANTICS, AND...Franpois Lang, Marcia Linebarger, Martha Palmer, Rebecca Passonneau, Leslie Rilev ARPA ORDER NUMBER: 5262 PROGRAM CODE NO. NR Ü49-602 dated 10 August

  6. A case study of data integration for aquatic resources using semantic web technologies

    USGS Publications Warehouse

    Gordon, Janice M.; Chkhenkeli, Nina; Govoni, David L.; Lightsom, Frances L.; Ostroff, Andrea; Schweitzer, Peter N.; Thongsavanh, Phethala; Varanka, Dalia E.; Zednik, Stephan

    2015-01-01

    Use cases, information modeling, and linked data techniques are Semantic Web technologies used to develop a prototype system that integrates scientific observations from four independent USGS and cooperator data systems. The techniques were tested with a use case goal of creating a data set for use in exploring potential relationships among freshwater fish populations and environmental factors. The resulting prototype extracts data from the BioData Retrieval System, the Multistate Aquatic Resource Information System, the National Geochemical Survey, and the National Hydrography Dataset. A prototype user interface allows a scientist to select observations from these data systems and combine them into a single data set in RDF format that includes explicitly defined relationships and data definitions. The project was funded by the USGS Community for Data Integration and undertaken by the Community for Data Integration Semantic Web Working Group in order to demonstrate use of Semantic Web technologies by scientists. This allows scientists to simultaneously explore data that are available in multiple, disparate systems beyond those they traditionally have used.

  7. A semantic data dictionary method for database schema integration in CIESIN

    NASA Astrophysics Data System (ADS)

    Hinds, N.; Huang, Y.; Ravishankar, C.

    1993-08-01

    CIESIN (Consortium for International Earth Science Information Network) is funded by NASA to investigate the technology necessary to integrate and facilitate the interdisciplinary use of Global Change information. A clear of this mission includes providing a link between the various global change data sets, in particular the physical sciences and the human (social) sciences. The typical scientist using the CIESIN system will want to know how phenomena in an outside field affects his/her work. For example, a medical researcher might ask: how does air-quality effect emphysema? This and many similar questions will require sophisticated semantic data integration. The researcher who raised the question may be familiar with medical data sets containing emphysema occurrences. But this same investigator may know little, if anything, about the existance or location of air-quality data. It is easy to envision a system which would allow that investigator to locate and perform a ``join'' on two data sets, one containing emphysema cases and the other containing air-quality levels. No such system exists today. One major obstacle to providing such a system will be overcoming the heterogeneity which falls into two broad categories. ``Database system'' heterogeneity involves differences in data models and packages. ``Data semantic'' heterogeneity involves differences in terminology between disciplines which translates into data semantic issues, and varying levels of data refinement, from raw to summary. Our work investigates a global data dictionary mechanism to facilitate a merged data service. Specially, we propose using a semantic tree during schema definition to aid in locating and integrating heterogeneous databases.

  8. Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control.

    PubMed

    Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

    2017-04-09

    Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

  9. The effect of discourse structure on depth of semantic integration in reading.

    PubMed

    Yang, Xiaohong; Chen, Lijing; Yang, Yufang

    2014-02-01

    A coherent discourse exhibits certain structures in that subunits of discourses are related to one another in various ways and in that subunits that contribute to the same discourse purpose are joined to create a larger unit so as to produce an effect on the reader. To date, this crucial aspect of discourse has been largely neglected in the psycholinguistic literature. In two experiments, we examined whether semantic integration in discourse context was influenced by the difference of discourse structure. Readers read discourses in which the last sentence was locally congruent but either semantically congruent or incongruent when interpreted with the preceding sentence. Furthermore, the last sentence was either in the same discourse unit or not in the same discourse unit as the preceding sentence, depending on whether they shared the same discourse purpose. Results from self-paced reading (Experiment 1) and eye tracking (Experiment 2) showed that discourse-incongruous words were read longer than discourse-congruous words only when the critical sentence and the preceding sentence were in the same discourse unit, but not when they belonged to different discourse units. These results establish discourse structure as a new factor in semantic integration and suggest that discourse effects depend both on the content of what is being said and on the way that the contents are organized.

  10. Entrez Neuron RDFa: a pragmatic semantic web application for data integration in neuroscience research.

    PubMed

    Samwald, Matthias; Lim, Ernest; Masiar, Peter; Marenco, Luis; Chen, Huajun; Morse, Thomas; Mutalik, Pradeep; Shepherd, Gordon; Miller, Perry; Cheung, Kei-Hoi

    2009-01-01

    The amount of biomedical data available in Semantic Web formats has been rapidly growing in recent years. While these formats are machine-friendly, user-friendly web interfaces allowing easy querying of these data are typically lacking. We present "Entrez Neuron", a pilot neuron-centric interface that allows for keyword-based queries against a coherent repository of OWL ontologies. These ontologies describe neuronal structures, physiology, mathematical models and microscopy images. The returned query results are organized hierarchically according to brain architecture. Where possible, the application makes use of entities from the Open Biomedical Ontologies (OBO) and the 'HCLS knowledgebase' developed by the W3C Interest Group for Health Care and Life Science. It makes use of the emerging RDFa standard to embed ontology fragments and semantic annotations within its HTML-based user interface. The application and underlying ontologies demonstrate how Semantic Web technologies can be used for information integration within a curated information repository and between curated information repositories. It also demonstrates how information integration can be accomplished on the client side, through simple copying and pasting of portions of documents that contain RDFa markup.

  11. Delineating the Effect of Semantic Congruency on Episodic Memory: The Role of Integration and Relatedness

    PubMed Central

    Bein, Oded; Livneh, Neta; Reggev, Niv; Gilead, Michael; Goshen-Gottstein, Yonatan; Maril, Anat

    2015-01-01

    A fundamental challenge in the study of learning and memory is to understand the role of existing knowledge in the encoding and retrieval of new episodic information. The importance of prior knowledge in memory is demonstrated in the congruency effect—the robust finding wherein participants display better memory for items that are compatible, rather than incompatible, with their pre-existing semantic knowledge. Despite its robustness, the mechanism underlying this effect is not well understood. In four studies, we provide evidence that demonstrates the privileged explanatory power of the elaboration-integration account over alternative hypotheses. Furthermore, we question the implicit assumption that the congruency effect pertains to the truthfulness/sensibility of a subject-predicate proposition, and show that congruency is a function of semantic relatedness between item and context words. PMID:25695759

  12. Mixing positive and negative valence: Affective-semantic integration of bivalent words.

    PubMed

    Kuhlmann, Michael; Hofmann, Markus J; Briesemeister, Benny B; Jacobs, Arthur M

    2016-08-05

    Single words have affective and aesthetic properties that influence their processing. Here we investigated the processing of a special case of word stimuli that are extremely difficult to evaluate, bivalent noun-noun-compounds (NNCs), i.e. novel words that mix a positive and negative noun, e.g. 'Bombensex' (bomb-sex). In a functional magnetic resonance imaging (fMRI) experiment we compared their processing with easier-to-evaluate non-bivalent NNCs in a valence decision task (VDT). Bivalent NNCs produced longer reaction times and elicited greater activation in the left inferior frontal gyrus (LIFG) than non-bivalent words, especially in contrast to words of negative valence. We attribute this effect to a LIFG-grounded process of semantic integration that requires greater effort for processing converse information, supporting the notion of a valence representation based on associations in semantic networks.

  13. Mixing positive and negative valence: Affective-semantic integration of bivalent words

    PubMed Central

    Kuhlmann, Michael; Hofmann, Markus J.; Briesemeister, Benny B.; Jacobs, Arthur M.

    2016-01-01

    Single words have affective and aesthetic properties that influence their processing. Here we investigated the processing of a special case of word stimuli that are extremely difficult to evaluate, bivalent noun-noun-compounds (NNCs), i.e. novel words that mix a positive and negative noun, e.g. ‘Bombensex’ (bomb-sex). In a functional magnetic resonance imaging (fMRI) experiment we compared their processing with easier-to-evaluate non-bivalent NNCs in a valence decision task (VDT). Bivalent NNCs produced longer reaction times and elicited greater activation in the left inferior frontal gyrus (LIFG) than non-bivalent words, especially in contrast to words of negative valence. We attribute this effect to a LIFG-grounded process of semantic integration that requires greater effort for processing converse information, supporting the notion of a valence representation based on associations in semantic networks. PMID:27491491

  14. Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

    PubMed

    Waagmeester, Andra; Kutmon, Martina; Riutta, Anders; Miller, Ryan; Willighagen, Egon L; Evelo, Chris T; Pico, Alexander R

    2016-06-01

    The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web.

  15. SIDD: A Semantically Integrated Database towards a Global View of Human Disease

    PubMed Central

    Cheng, Liang; Wang, Guohua; Li, Jie; Zhang, Tianjiao; Xu, Peigang; Wang, Yadong

    2013-01-01

    Background A number of databases have been developed to collect disease-related molecular, phenotypic and environmental features (DR-MPEs), such as genes, non-coding RNAs, genetic variations, drugs, phenotypes and environmental factors. However, each of current databases focused on only one or two DR-MPEs. There is an urgent demand to develop an integrated database, which can establish semantic associations among disease-related databases and link them to provide a global view of human disease at the biological level. This database, once developed, will facilitate researchers to query various DR-MPEs through disease, and investigate disease mechanisms from different types of data. Methodology To establish an integrated disease-associated database, disease vocabularies used in different databases are mapped to Disease Ontology (DO) through semantic match. 4,284 and 4,186 disease terms from Medical Subject Headings (MeSH) and Online Mendelian Inheritance in Man (OMIM) respectively are mapped to DO. Then, the relationships between DR-MPEs and diseases are extracted and merged from different source databases for reducing the data redundancy. Conclusions A semantically integrated disease-associated database (SIDD) is developed, which integrates 18 disease-associated databases, for researchers to browse multiple types of DR-MPEs in a view. A web interface allows easy navigation for querying information through browsing a disease ontology tree or searching a disease term. Furthermore, a network visualization tool using Cytoscape Web plugin has been implemented in SIDD. It enhances the SIDD usage when viewing the relationships between diseases and DR-MPEs. The current version of SIDD (Jul 2013) documents 4,465,131 entries relating to 139,365 DR-MPEs, and to 3,824 human diseases. The database can be freely accessed from: http://mlg.hit.edu.cn/SIDD. PMID:24146757

  16. A structure-based model of semantic integrity constraints for relational data bases

    NASA Technical Reports Server (NTRS)

    Rasdorf, William J.; Ulberg, Karen J.; Baugh, John W., Jr.

    1987-01-01

    Data base management systems (DBMSs) are in widespread use because of the ease and flexibility with which users access large volumes of data. Ensuring data accuracy through integrity constraints is a central aspect of DBMS use. However, many DBMSs still lack adequate integrity support. In additon, a comprehensive theoretical basis for such support the role of a constraint classification system - has yet to be developed. This paper presents a formalism that classifies semantic integrity constraints based on the structure of the relational model. Integrity constraints are characterized by the portion of the data base structure they access, whether one or more relations, attributes, or tuples. Thus, the model is completely general, allowing the arbitrary specification of any constraint. Examples of each type of constraint are illustrated using a small engineering data base, and various implementation issues are discussed.

  17. Automatic image orientation detection via confidence-based integration of low-level and semantic cues.

    PubMed

    Luo, Jiebo; Boutell, Matthew

    2005-05-01

    Automatic image orientation detection for natural images is a useful, yet challenging research topic. Humans use scene context and semantic object recognition to identify the correct image orientation. However, it is difficult for a computer to perform the task in the same way because current object recognition algorithms are extremely limited in their scope and robustness. As a result, existing orientation detection methods were built upon low-level vision features such as spatial distributions of color and texture. Discrepant detection rates have been reported for these methods in the literature. We have developed a probabilistic approach to image orientation detection via confidence-based integration of low-level and semantic cues within a Bayesian framework. Our current accuracy is 90 percent for unconstrained consumer photos, impressive given the findings of a psychophysical study conducted recently. The proposed framework is an attempt to bridge the gap between computer and human vision systems and is applicable to other problems involving semantic scene content understanding.

  18. Hands typing what hands do: Action-semantic integration dynamics throughout written verb production.

    PubMed

    García, Adolfo M; Ibáñez, Agustín

    2016-04-01

    Processing action verbs, in general, and manual action verbs, in particular, involves activations in gross and hand-specific motor networks, respectively. While this is well established for receptive language processes, no study has explored action-semantic integration during written production. Moreover, little is known about how such crosstalk unfolds from motor planning to execution. Here we address both issues through our novel "action semantics in typing" paradigm, which allows to time keystroke operations during word typing. Specifically, we created a primed-verb-copying task involving manual action verbs, non-manual action verbs, and non-action verbs. Motor planning processes were indexed by first-letter lag (the lapse between target onset and first keystroke), whereas execution dynamics were assessed considering whole-word lag (the lapse between first and last keystroke). Each phase was differently delayed by action verbs. When these were processed for over one second, interference was strong and magnified by effector compatibility during programming, but weak and effector-blind during execution. Instead, when they were processed for less than 900ms, interference was reduced by effector compatibility during programming and it faded during execution. Finally, typing was facilitated by prime-target congruency, irrespective of the verbs' motor content. Thus, action-verb semantics seems to extend beyond its embodied foundations, involving conceptual dynamics not tapped by classical reaction-time measures. These findings are compatible with non-radical models of language embodiment and with predictions of event coding theory.

  19. A Ubiquitous Sensor Network Platform for Integrating Smart Devices into the Semantic Sensor Web

    PubMed Central

    de Vera, David Díaz Pardo; Izquierdo, Álvaro Sigüenza; Vercher, Jesús Bernat; Gómez, Luis Alfonso Hernández

    2014-01-01

    Ongoing Sensor Web developments make a growing amount of heterogeneous sensor data available to smart devices. This is generating an increasing demand for homogeneous mechanisms to access, publish and share real-world information. This paper discusses, first, an architectural solution based on Next Generation Networks: a pilot Telco Ubiquitous Sensor Network (USN) Platform that embeds several OGC® Sensor Web services. This platform has already been deployed in large scale projects. Second, the USN-Platform is extended to explore a first approach to Semantic Sensor Web principles and technologies, so that smart devices can access Sensor Web data, allowing them also to share richer (semantically interpreted) information. An experimental scenario is presented: a smart car that consumes and produces real-world information which is integrated into the Semantic Sensor Web through a Telco USN-Platform. Performance tests revealed that observation publishing times with our experimental system were well within limits compatible with the adequate operation of smart safety assistance systems in vehicles. On the other hand, response times for complex queries on large repositories may be inappropriate for rapid reaction needs. PMID:24945678

  20. Automated revision of CLIPS rule-bases

    NASA Technical Reports Server (NTRS)

    Murphy, Patrick M.; Pazzani, Michael J.

    1994-01-01

    This paper describes CLIPS-R, a theory revision system for the revision of CLIPS rule-bases. CLIPS-R may be used for a variety of knowledge-base revision tasks, such as refining a prototype system, adapting an existing system to slightly different operating conditions, or improving an operational system that makes occasional errors. We present a description of how CLIPS-R revises rule-bases, and an evaluation of the system on three rule-bases.

  1. Learning new vocabulary during childhood: effects of semantic training on lexical consolidation and integration.

    PubMed

    Henderson, Lisa; Weighall, Anna; Gaskell, Gareth

    2013-11-01

    Research suggests that word learning is an extended process, with offline consolidation crucial for the strengthening of new lexical representations and their integration with existing lexical knowledge (as measured by engagement in lexical competition). This supports a dual memory systems account, in which new information is initially sparsely encoded separately from existing knowledge and integrated with long-term memory over time. However, previous studies of this type exploited unnatural learning contexts, involving fictitious words in the absence of word meaning. In this study, 5- to 9-year-old children learned real science words (e.g., hippocampus) with or without semantic information. Children in both groups were slower to detect pauses in familiar competitor words (e.g., hippopotamus) relative to control words 24h after training but not immediately, confirming that offline consolidation is required before new words are integrated with the lexicon and engage in lexical competition. Children recalled more new words 24h after training than immediately (with similar improvements shown for the recall and recognition of new word meanings); however, children who were exposed to the meanings during training showed further improvements in recall after 1 week and outperformed children who were not exposed to meanings. These findings support the dual memory systems account of vocabulary acquisition and suggest that the association of a new phonological form with semantic information is critical for the development of stable lexical representations.

  2. Missing semantic annotation in databases. The root cause for data integration and migration problems in information systems.

    PubMed

    Dugas, M

    2014-01-01

    Data integration is a well-known grand challenge in information systems. It is highly relevant in medicine because of the multitude of patient data sources. Semantic annotations of data items regarding concept and value domain, based on comprehensive terminologies can facilitate data integration and migration. Therefore it should be implemented in databases from the very beginning.

  3. Early Stages of Sensory Processing, but Not Semantic Integration, Are Altered in Dyslexic Adults

    PubMed Central

    Silva, Patrícia B.; Ueki, Karen; Oliveira, Darlene G.; Boggio, Paulo S.; Macedo, Elizeu C.

    2016-01-01

    The aim of this study was to verify which stages of language processing are impaired in individuals with dyslexia. For this, a visual-auditory crossmodal task with semantic judgment was used. The P100 potentials were chosen, related to visual processing and initial integration, and N400 potentials related to semantic processing. Based on visual-auditory crossmodal studies, it is understood that dyslexic individuals present impairments in the integration of these two types of tasks and impairments in processing spoken and musical auditory information. The present study sought to investigate and compare the performance of 32 adult participants (14 individuals with dyslexia), in semantic processing tasks in two situations with auditory stimuli: sentences and music, with integrated visual stimuli (pictures). From the analysis of the accuracy, both the sentence and the music blocks showed significant effects on the congruency variable, with both groups having higher scores for the incongruent items than for the congruent ones. Furthermore, there was also a group effect when the priming was music, with the dyslexic group showing an inferior performance to the control group, demonstrating greater impairments in processing when the priming was music. Regarding the reaction time variable, a group effect in music and sentence priming was found, with the dyslexic group being slower than the control group. The N400 and P100 components were analyzed. In items with judgment and music priming, a group effect was observed for the amplitude of the P100, with higher means produced by individuals with dyslexia, corroborating the literature that individuals with dyslexia have difficulties in early information processing. A congruency effect was observed in the items with music priming, with greater P100 amplitudes found in incongruous situations. Analyses of the N400 component showed the congruency effect for amplitude in both types of priming, with the mean amplitude for incongruent

  4. Two Neurocognitive Mechanisms of Semantic Integration during the Comprehension of Visual Real-world Events

    PubMed Central

    Sitnikova, Tatiana; Holcomb, Phillip J.; Kiyonaga, Kristi A.; Kuperberg, Gina R.

    2009-01-01

    How do comprehenders build up overall meaning representations of visual real-world events? This question was examined by recording event-related potentials (ERPs) while participants viewed short, silent movie clips depicting everyday events. In two experiments, it was demonstrated that presentation of the contextually inappropriate information in the movie endings evoked an anterior negativity. This effect was similar to the N400 component whose amplitude has been previously reported to inversely correlate with the strength of semantic relationship between the context and the eliciting stimulus in word and static picture paradigms. However, a second, somewhat later, ERP component—a posterior late positivity—was evoked specifically when target objects presented in the movie endings violated goal-related requirements of the action constrained by the scenario context (e.g., an electric iron that does not have a sharp-enough edge was used in place of a knife in a cutting bread scenario context). These findings suggest that comprehension of the visual real world might be mediated by two neurophysiologically distinct semantic integration mechanisms. The first mechanism, reflected by the anterior N400-like negativity, maps the incoming information onto the connections of various strengths between concepts in semantic memory. The second mechanism, reflected by the posterior late positivity, evaluates the incoming information against the discrete requirements of real-world actions. We suggest that there may be a tradeoff between these mechanisms in their utility for integrating across people, objects, and actions during event comprehension, in which the first mechanism is better suited for familiar situations, and the second mechanism is better suited for novel situations. PMID:18416681

  5. Francisella tularensis novicida proteomic and transcriptomic data integration and annotation based on semantic web technologies

    PubMed Central

    Anwar, Nadia; Hunt, Ela

    2009-01-01

    Background This paper summarises the lessons and experiences gained from a case study of the application of semantic web technologies to the integration of data from the bacterial species Francisella tularensis novicida (Fn). Fn data sources are disparate and heterogeneous, as multiple laboratories across the world, using multiple technologies, perform experiments to understand the mechanism of virulence. It is hard to integrate these data sources in a flexible manner that allows new experimental data to be added and compared when required. Results Public domain data sources were combined in RDF. Using this connected graph of database cross references, we extended the annotations of an experimental data set by superimposing onto it the annotation graph. Identifiers used in the experimental data automatically resolved and the data acquired annotations in the rest of the RDF graph. This happened without the expensive manual annotation that would normally be required to produce these links. This graph of resolved identifiers was then used to combine two experimental data sets, a proteomics experiment and a transcriptomic experiment studying the mechanism of virulence through the comparison of wildtype Fn with an avirulent mutant strain. Conclusion We produced a graph of Fn cross references which enabled the combination of two experimental datasets. Through combination of these data we are able to perform queries that compare the results of the two experiments. We found that data are easily combined in RDF and that experimental results are easily compared when the data are integrated. We conclude that semantic data integration offers a convenient, simple and flexible solution to the integration of published and unpublished experimental data. PMID:19796400

  6. Semantic Representation and Scale-Up of Integrated Air Traffic Management Data

    NASA Technical Reports Server (NTRS)

    Keller, Richard M.; Ranjan, Shubha; Wei, Mie; Eshow, Michelle

    2016-01-01

    Each day, the global air transportation industry generates a vast amount of heterogeneous data from air carriers, air traffic control providers, and secondary aviation entities handling baggage, ticketing, catering, fuel delivery, and other services. Generally, these data are stored in isolated data systems, separated from each other by significant political, regulatory, economic, and technological divides. These realities aside, integrating aviation data into a single, queryable, big data store could enable insights leading to major efficiency, safety, and cost advantages. In this paper, we describe an implemented system for combining heterogeneous air traffic management data using semantic integration techniques. The system transforms data from its original disparate source formats into a unified semantic representation within an ontology-based triple store. Our initial prototype stores only a small sliver of air traffic data covering one day of operations at a major airport. The paper also describes our analysis of difficulties ahead as we prepare to scale up data storage to accommodate successively larger quantities of data -- eventually covering all US commercial domestic flights over an extended multi-year timeframe. We review several approaches to mitigating scale-up related query performance concerns.

  7. A Case Study in Integrating Multiple E-commerce Standards via Semantic Web Technology

    NASA Astrophysics Data System (ADS)

    Yu, Yang; Hillman, Donald; Setio, Basuki; Heflin, Jeff

    Internet business-to-business transactions present great challenges in merging information from different sources. In this paper we describe a project to integrate four representative commercial classification systems with the Federal Cataloging System (FCS). The FCS is used by the US Defense Logistics Agency to name, describe and classify all items under inventory control by the DoD. Our approach uses the ECCMA Open Technical Dictionary (eOTD) as a common vocabulary to accommodate all different classifications. We create a semantic bridging ontology between each classification and the eOTD to describe their logical relationships in OWL DL. The essential idea is that since each classification has formal definitions in a common vocabulary, we can use subsumption to automatically integrate them, thus mitigating the need for pairwise mappings. Furthermore our system provides an interactive interface to let users choose and browse the results and more importantly it can translate catalogs that commit to these classifications using compiled mapping results.

  8. SENHANCE: A Semantic Web framework for integrating social and hardware sensors in e-Health.

    PubMed

    Pagkalos, Ioannis; Petrou, Loukas

    2016-09-01

    Self-reported data are very important in Healthcare, especially when combined with data from sensors. Social Networking Sites, such as Facebook, are a promising source of not only self-reported data but also social data, which are otherwise difficult to obtain. Due to their unstructured nature, providing information that is meaningful to health professionals from this source is a daunting task. To this end, we employ Social Network Applications as Social Sensors that gather structured data and use Semantic Web technologies to fuse them with hardware sensor data, effectively integrating both sources. We show that this combination of social and hardware sensor observations creates a novel space that can be used for a variety of feature-rich e-Health applications. We present the design of our prototype framework, SENHANCE, and our findings from its pilot application in the NutriHeAl project, where a Facebook app is integrated with Fitbit digital pedometers for Lifestyle monitoring.

  9. Causal Evidence for a Mechanism of Semantic Integration in the Angular Gyrus as Revealed by High-Definition Transcranial Direct Current Stimulation

    PubMed Central

    Peelle, Jonathan E.; Bonner, Michael F.; Grossman, Murray

    2016-01-01

    A defining aspect of human cognition is the ability to integrate conceptual information into complex semantic combinations. For example, we can comprehend “plaid” and “jacket” as individual concepts, but we can also effortlessly combine these concepts to form the semantic representation of “plaid jacket.” Many neuroanatomic models of semantic memory propose that heteromodal cortical hubs integrate distributed semantic features into coherent representations. However, little work has specifically examined these proposed integrative mechanisms and the causal role of these regions in semantic integration. Here, we test the hypothesis that the angular gyrus (AG) is critical for integrating semantic information by applying high-definition transcranial direct current stimulation (tDCS) to an fMRI-guided region-of-interest in the left AG. We found that anodal stimulation to the left AG modulated semantic integration but had no effect on a letter-string control task. Specifically, anodal stimulation to the left AG resulted in faster comprehension of semantically meaningful combinations like “tiny radish” relative to non-meaningful combinations, such as “fast blueberry,” when compared to the effects observed during sham stimulation and stimulation to a right-hemisphere control brain region. Moreover, the size of the effect from brain stimulation correlated with the degree of semantic coherence between the word pairs. These findings demonstrate that the left AG plays a causal role in the integration of lexical-semantic information, and that high-definition tDCS to an associative cortical hub can selectively modulate integrative processes in semantic memory. SIGNIFICANCE STATEMENT A major goal of neuroscience is to understand the neural basis of behaviors that are fundamental to human intelligence. One essential behavior is the ability to integrate conceptual knowledge from semantic memory, allowing us to construct an almost unlimited number of complex

  10. Integrating Syntax, Semantics, and Discourse DARPA Natural Language Understanding Program. Volume 2. Appendices.

    DTIC Science & Technology

    1987-05-14

    in Generative Semantics and in Montague’s PTQ. Dordrecht: D. Reidel. Jakobson , Roman . 1971 [1957]. Shifters, verbal categories and the Russian verb. In...new domain. 5T7s"k ( Jakobson , 1957) refers to the semantic effect of the presence or absence of the perfect auxiliary. lGrammatical aspect is signalled...log, with distinct syntactic, semantic and pragmatic components (cf. Dahi, 1986; Palmer at al., 1986). IT&"# ( Jakobson , 1967) refers to the semantic

  11. Integration of nursing assessment concepts into the medical entities dictionary using the LOINC semantic structure as a terminology model.

    PubMed Central

    Cieslowski, B. J.; Wajngurt, D.; Cimino, J. J.; Bakken, S.

    2001-01-01

    Recent investigations have tested the applicability of various terminology models for the representing nursing concepts including those related to nursing diagnoses, nursing interventions, and standardized nursing assessments as a prerequisite for building a reference terminology that supports the nursing domain. We used the semantic structure of Clinical LOINC (Logical Observations, Identifiers, Names, and Codes) as a reference terminology model to support the integration of standardized assessment terms from two nursing terminologies into the Medical Entities Dictionary (MED), the concept-oriented, metadata dictionary at New York Presbyterian Hospital. Although the LOINC semantic structure was used previously to represent laboratory terms in the MED, selected hierarchies and semantic slots required revisions in order to incorporate the nursing assessment concepts. This project was an initial step in integrating nursing assessment concepts into the MED in a manner consistent with evolving standards for reference terminology models. Moreover, the revisions provide the foundation for adding other types of standardized assessments to the MED. PMID:11825165

  12. A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare.

    PubMed

    Mezghani, Emna; Exposito, Ernesto; Drira, Khalil; Da Silveira, Marcos; Pruski, Cédric

    2015-12-01

    Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the "Knowledge as a Service" approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

  13. Drug repositioning by applying 'expression profiles' generated by integrating chemical structure similarity and gene semantic similarity.

    PubMed

    Tan, Fujian; Yang, Ruizhi; Xu, Xiaoxue; Chen, Xiujie; Wang, Yunfeng; Ma, Hongzhe; Liu, Xiangqiong; Wu, Xin; Chen, Yuelong; Liu, Lei; Jia, Xiaodong

    2014-05-01

    Drug repositioning, also known as drug repurposing or reprofiling, is the process of finding new indications for established drugs. Because drug repositioning can reduce costs and enhance the efficiency of drug development, it is of paramount importance in medical research. Here, we present a systematic computational method to identify potential novel indications for a given drug. This method utilizes some prior knowledge such as 3D drug chemical structure information, drug-target interactions and gene semantic similarity information. Its prediction is based on another form of 'expression profile', which contains scores ranging from -1 to 1, reflecting the consensus response scores (CRSs) between each drug of 965 and 1560 proteins. The CRS integrates chemical structure similarity and gene semantic similarity information. We define the degree of similarity between two drugs as the absolute value of their correlation coefficients. Finally, we establish a drug similarity network (DSN) and obtain 33 modules of drugs with similar modes of action, determining their common indications. Using these modules, we predict new indications for 143 drugs and identify previously unknown indications for 42 drugs without ATC codes. This method overcomes the instability of gene expression profiling derived from experiments due to experimental conditions, and predicts indications for a new compound feasibly, requiring only the 3D structure of the compound. In addition, the high literature validation rate of 71.8% also suggests that our method has the potential to discover novel drug indications for existing drugs.

  14. Towards an open-source semantic data infrastructure for integrating clinical and scientific data in cognition-guided surgery

    NASA Astrophysics Data System (ADS)

    Fetzer, Andreas; Metzger, Jasmin; Katic, Darko; März, Keno; Wagner, Martin; Philipp, Patrick; Engelhardt, Sandy; Weller, Tobias; Zelzer, Sascha; Franz, Alfred M.; Schoch, Nicolai; Heuveline, Vincent; Maleshkova, Maria; Rettinger, Achim; Speidel, Stefanie; Wolf, Ivo; Kenngott, Hannes; Mehrabi, Arianeb; Müller-Stich, Beat P.; Maier-Hein, Lena; Meinzer, Hans-Peter; Nolden, Marco

    2016-03-01

    In the surgical domain, individual clinical experience, which is derived in large part from past clinical cases, plays an important role in the treatment decision process. Simultaneously the surgeon has to keep track of a large amount of clinical data, emerging from a number of heterogeneous systems during all phases of surgical treatment. This is complemented with the constantly growing knowledge derived from clinical studies and literature. To recall this vast amount of information at the right moment poses a growing challenge that should be supported by adequate technology. While many tools and projects aim at sharing or integrating data from various sources or even provide knowledge-based decision support - to our knowledge - no concept has been proposed that addresses the entire surgical pathway by accessing the entire information in order to provide context-aware cognitive assistance. Therefore a semantic representation and central storage of data and knowledge is a fundamental requirement. We present a semantic data infrastructure for integrating heterogeneous surgical data sources based on a common knowledge representation. A combination of the Extensible Neuroimaging Archive Toolkit (XNAT) with semantic web technologies, standardized interfaces and a common application platform enables applications to access and semantically annotate data, perform semantic reasoning and eventually create individual context-aware surgical assistance. The infrastructure meets the requirements of a cognitive surgical assistant system and has been successfully applied in various use cases. The system is based completely on free technologies and is available to the community as an open-source package.

  15. Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

    PubMed

    Liang, Chen; Sun, Jingchun; Tao, Cui

    2015-01-01

    There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

  16. HUNTER-GATHERER: Three search techniques integrated for natural language semantics

    SciTech Connect

    Beale, S.; Nirenburg, S.; Mahesh, K.

    1996-12-31

    This work integrates three related Al search techniques - constraint satisfaction, branch-and-bound and solution synthesis - and applies the result to semantic processing in natural language (NL). We summarize the approach as {open_quote}Hunter-Gatherer:{close_quotes} (1) branch-and-bound and constraint satisfaction allow us to {open_quote}hunt down{close_quotes} non-optimal and impossible solutions and prune them from the search space. (2) solution synthesis methods then {open_quote}gather{close_quotes} all optimal solutions avoiding exponential complexity. Each of the three techniques is briefly described, as well as their extensions and combinations used in our system. We focus on the combination of solution synthesis and branch-and-bound methods which has enabled near-linear-time processing in our applications. Finally, we illustrate how the use of our technique in a large-scale MT project allowed a drastic reduction in search space.

  17. Once Is Enough: N400 Indexes Semantic Integration of Novel Word Meanings from a Single Exposure in Context

    ERIC Educational Resources Information Center

    Borovsky, Arielle; Elman, Jeffrey L.; Kutas, Marta

    2012-01-01

    We investigated the impact of contextual constraint on the integration of novel word meanings into semantic memory. Adults read strongly or weakly constraining sentences ending in known or unknown (novel) words as scalp-recorded electrical brain activity was recorded. Word knowledge was assessed via a lexical decision task in which recently seen…

  18. Semantic Repositories for eGovernment Initiatives: Integrating Knowledge and Services

    NASA Astrophysics Data System (ADS)

    Palmonari, Matteo; Viscusi, Gianluigi

    In recent years, public sector investments in eGovernment initiatives have depended on making more reliable existing governmental ICT systems and infrastructures. Furthermore, we assist at a change in the focus of public sector management, from the disaggregation, competition and performance measurements typical of the New Public Management (NPM), to new models of governance, aiming for the reintegration of services under a new perspective in bureaucracy, namely a holistic approach to policy making which exploits the extensive digitalization of administrative operations. In this scenario, major challenges are related to support effective access to information both at the front-end level, by means of highly modular and customizable content provision, and at the back-end level, by means of information integration initiatives. Repositories of information about data and services that exploit semantic models and technologies can support these goals by bridging the gap between the data-level representations and the human-level knowledge involved in accessing information and in searching for services. Moreover, semantic repository technologies can reach a new level of automation for different tasks involved in interoperability programs, both related to data integration techniques and service-oriented computing approaches. In this chapter, we discuss the above topics by referring to techniques and experiences where repositories based on conceptual models and ontologies are used at different levels in eGovernment initiatives: at the back-end level to produce a comprehensive view of the information managed in the public administrations' (PA) information systems, and at the front-end level to support effective service delivery.

  19. Semantic integration of audio-visual information of polyphonic characters in a sentence context: an event-related potential study.

    PubMed

    Liu, Hong; Zhang, Gaoyan; Liu, Baolin

    2017-04-01

    In the Chinese language, a polyphone is a kind of special character that has more than one pronunciation, with each pronunciation corresponding to a different meaning. Here, we aimed to reveal the cognitive processing of audio-visual information integration of polyphones in a sentence context using the event-related potential (ERP) method. Sentences ending with polyphones were presented to subjects simultaneously in both an auditory and a visual modality. Four experimental conditions were set in which the visual presentations were the same, but the pronunciations of the polyphones were: the correct pronunciation; another pronunciation of the polyphone; a semantically appropriate pronunciation but not the pronunciation of the polyphone; or a semantically inappropriate pronunciation but also not the pronunciation of the polyphone. The behavioral results demonstrated significant differences in response accuracies when judging the semantic meanings of the audio-visual sentences, which reflected the different demands on cognitive resources. The ERP results showed that in the early stage, abnormal pronunciations were represented by the amplitude of the P200 component. Interestingly, because the phonological information mediated access to the lexical semantics, the amplitude and latency of the N400 component changed linearly across conditions, which may reflect the gradually increased semantic mismatch in the four conditions when integrating the auditory pronunciation with the visual information. Moreover, the amplitude of the late positive shift (LPS) showed a significant correlation with the behavioral response accuracies, demonstrating that the LPS component reveals the demand of cognitive resources for monitoring and resolving semantic conflicts when integrating the audio-visual information.

  20. Ontology and rules based model for traffic query

    NASA Astrophysics Data System (ADS)

    Cheng, Gang; Du, Qingyun; Huang, Qian; Zhao, Haiyun

    2008-10-01

    This paper will combine ontology and rule based qualitative reason with real time calculation, designing a combined traffic model of national scope which contains highway, railroad, water carriage, scheduled flight etc. That method follows the sense of people to space, establishes ontologies and rules knowledge base, using concepts, instances, relations and rules of traffic field as the basic knowledge for qualitative reason to discover implicit semantic information and eliminate unnecessary ambiguities. The knowledge from the ontologies and rules provides abundant information for query which can lighten the burden of computation, in the mean time, real-time calculation guarantees the accuracy of the data, has raised accuracy and efficiency of the query, which has strengthened the ease of query service and improved web users' experience.

  1. When zebras become painted donkeys: Grammatical gender and semantic priming interact during picture integration in a spoken Spanish sentence

    PubMed Central

    Wicha, Nicole Y. Y.; Orozco-Figueroa, Araceli; Reyes, Iliana; Hernandez, Arturo; de Barreto, Lourdes Gavaldón; Bates, Elizabeth A.

    2012-01-01

    This study investigates the contribution of grammatical gender to integrating depicted nouns into sentences during on-line comprehension, and whether semantic congruity and gender agreement interact using two tasks: naming and semantic judgement of pictures. Native Spanish speakers comprehended spoken Spanish sentences with an embedded line drawing, which replaced a noun that either made sense or not with the preceding sentence context and either matched or mismatched the gender of the preceding article. In Experiment 1a (picture naming) slower naming times were found for gender mismatching pictures than matches, as well as for semantically incongruous pictures than congruous ones. In addition, the effects of gender agreement and semantic congruity interacted; specifically, pictures that were both semantically incongruous and gender mismatching were named slowest, but not as slow as if adding independent delays from both violations. Compared with a neutral baseline, with pictures embedded in simple command sentences like “Now please say ____”, both facilitative and inhibitory effects were observed. Experiment 1b replicated these results with low-cloze gender-neutral sentences, more similar in structure and processing demands to the experimental sentences. In Experiment 2, participants judged a picture’s semantic fit within a sentence by button-press; gender agreement and semantic congruity again interacted, with gender agreement having an effect on congruous but not incongruous pictures. Two distinct effects of gender are hypothesised: a “global” predictive effect (observed with and without overt noun production), and a “local” inhibitory effect (observed only with production of gender-discordant nouns). PMID:22773871

  2. Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration.

    PubMed

    Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

    2016-07-08

    This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) BACKGROUND: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) METHODS: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) RESULTS: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) CONCLUSION: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database.

  3. Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

    PubMed Central

    Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

    2016-01-01

    This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) Background: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database. PMID:27399717

  4. Integrating Syntax, Semantics, and Discourse DARPA Natural Language Understanding Program. Volume 3. Papers

    DTIC Science & Technology

    1989-09-30

    Theory. Linguistic Inquiry 18.3, 1987, pp. 369-411. [Jakobson57] Roman Jakobson , Shifters, Verbal Categories and the Russian Verb. In Selected Writings...Montague Grammar: The Semantics of Verbs and Times in Generative Semantics and in Montague’s PTQ. Dordrecht: D. Reidel. Jakobson , Roman . 1971 [1957...8217Taste ( Jakobson , 1957) refers to the semantic effect of the presence or absence or the perfect amilary. ’Aspect is both part of the inherent meaning of a

  5. Oscillatory neuronal activity reflects lexical-semantic feature integration within and across sensory modalities in distributed cortical networks.

    PubMed

    van Ackeren, Markus J; Schneider, Till R; Müsch, Kathrin; Rueschemeyer, Shirley-Ann

    2014-10-22

    Research from the previous decade suggests that word meaning is partially stored in distributed modality-specific cortical networks. However, little is known about the mechanisms by which semantic content from multiple modalities is integrated into a coherent multisensory representation. Therefore we aimed to characterize differences between integration of lexical-semantic information from a single modality compared with two sensory modalities. We used magnetoencephalography in humans to investigate changes in oscillatory neuronal activity while participants verified two features for a given target word (e.g., "bus"). Feature pairs consisted of either two features from the same modality (visual: "red," "big") or different modalities (auditory and visual: "red," "loud"). The results suggest that integrating modality-specific features of the target word is associated with enhanced high-frequency power (80-120 Hz), while integrating features from different modalities is associated with a sustained increase in low-frequency power (2-8 Hz). Source reconstruction revealed a peak in the anterior temporal lobe for low-frequency and high-frequency effects. These results suggest that integrating lexical-semantic knowledge at different cortical scales is reflected in frequency-specific oscillatory neuronal activity in unisensory and multisensory association networks.

  6. Using Linked Open Data and Semantic Integration to Search Across Geoscience Repositories

    NASA Astrophysics Data System (ADS)

    Mickle, A.; Raymond, L. M.; Shepherd, A.; Arko, R. A.; Carbotte, S. M.; Chandler, C. L.; Cheatham, M.; Fils, D.; Hitzler, P.; Janowicz, K.; Jones, M.; Krisnadhi, A.; Lehnert, K. A.; Narock, T.; Schildhauer, M.; Wiebe, P. H.

    2014-12-01

    The MBLWHOI Library is a partner in the OceanLink project, an NSF EarthCube Building Block, applying semantic technologies to enable knowledge discovery, sharing and integration. OceanLink is testing ontology design patterns that link together: two data repositories, Rolling Deck to Repository (R2R), Biological and Chemical Oceanography Data Management Office (BCO-DMO); the MBLWHOI Library Institutional Repository (IR) Woods Hole Open Access Server (WHOAS); National Science Foundation (NSF) funded awards; and American Geophysical Union (AGU) conference presentations. The Library is collaborating with scientific users, data managers, DSpace engineers, experts in ontology design patterns, and user interface developers to make WHOAS, a DSpace repository, linked open data enabled. The goal is to allow searching across repositories without any of the information providers having to change how they manage their collections. The tools developed for DSpace will be made available to the community of users. There are 257 registered DSpace repositories in the United Stated and over 1700 worldwide. Outcomes include: Integration of DSpace with OpenRDF Sesame triple store to provide SPARQL endpoint for the storage and query of RDF representation of DSpace resources, Mapping of DSpace resources to OceanLink ontology, and DSpace "data" add on to provide resolvable linked open data representation of DSpace resources.

  7. Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing

    PubMed Central

    Liang, Chen; Sun, Jingchun; Tao, Cui

    2016-01-01

    Despite ongoing progress towards treating mental illness, there remain significant difficulties in selecting probable candidate drugs from the existing database. We describe an ontology — oriented approach aims to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. Along with this approach, we report a case study in which we attempted to explore the candidate drugs that effective for both bipolar disorder and epilepsy. We constructed an ontology that incorporates the knowledge between the two diseases and performed semantic reasoning task on the ontology. The reasoning results suggested 48 candidate drugs that hold promise for a further breakthrough. The evaluation was performed and demonstrated the validity of the proposed ontology. The overarching goal of this research is to build a framework of ontology — based data integration underpinning psychiatric drug repurposing. This approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders. PMID:27570661

  8. Toward Semantic Interoperability in Home Health Care: Formally Representing OASIS Items for Integration into a Concept-oriented Terminology

    PubMed Central

    Choi, Jeungok; Jenkins, Melinda L.; Cimino, James J.; White, Thomas M.; Bakken, Suzanne

    2005-01-01

    Objective: The authors aimed to (1) formally represent OASIS-B1 concepts using the Logical Observation Identifiers, Names, and Codes (LOINC) semantic structure; (2) demonstrate integration of OASIS-B1 concepts into a concept-oriented terminology, the Medical Entities Dictionary (MED); (3) examine potential hierarchical structures within LOINC among OASIS-B1 and other nursing terms; and (4) illustrate a Web-based implementation for OASIS-B1 data entry using Dialogix, a software tool with a set of functions that supports complex data entry. Design and Measurements: Two hundred nine OASIS-B1 items were dissected into the six elements of the LOINC semantic structure and then integrated into the MED hierarchy. Each OASIS-B1 term was matched to LOINC-coded nursing terms, Home Health Care Classification, the Omaha System, and the Sign and Symptom Check-List for Persons with HIV, and the extent of the match was judged based on a scale of 0 (no match) to 4 (exact match). OASIS-B1 terms were implemented as a Web-based survey using Dialogix. Results: Of 209 terms, 204 were successfully dissected into the elements of the LOINC semantics structure and integrated into the MED with minor revisions of MED semantics. One hundred fifty-one OASIS-B1 terms were mapped to one or more of the LOINC-coded nursing terms. Conclusion: The LOINC semantic structure offers a standard way to add home health care data to a comprehensive patient record to facilitate data sharing for monitoring outcomes across sites and to further terminology management, decision support, and accurate information retrieval for evidence-based practice. The cross-mapping results support the possibility of a hierarchical structure of the OASIS-B1 concepts within nursing terminologies in the LOINC database. PMID:15802480

  9. Software Uncertainty in Integrated Environmental Modelling: the role of Semantics and Open Science

    NASA Astrophysics Data System (ADS)

    de Rigo, Daniele

    2013-04-01

    Computational aspects increasingly shape environmental sciences [1]. Actually, transdisciplinary modelling of complex and uncertain environmental systems is challenging computational science (CS) and also the science-policy interface [2-7]. Large spatial-scale problems falling within this category - i.e. wide-scale transdisciplinary modelling for environment (WSTMe) [8-10] - often deal with factors (a) for which deep-uncertainty [2,11-13] may prevent usual statistical analysis of modelled quantities and need different ways for providing policy-making with science-based support. Here, practical recommendations are proposed for tempering a peculiar - not infrequently underestimated - source of uncertainty. Software errors in complex WSTMe may subtly affect the outcomes with possible consequences even on collective environmental decision-making. Semantic transparency in CS [2,8,10,14,15] and free software [16,17] are discussed as possible mitigations (b) . Software uncertainty, black-boxes and free software. Integrated natural resources modelling and management (INRMM) [29] frequently exploits chains of nontrivial data-transformation models (D- TM), each of them affected by uncertainties and errors. Those D-TM chains may be packaged as monolithic specialized models, maybe only accessible as black-box executables (if accessible at all) [50]. For end-users, black-boxes merely transform inputs in the final outputs, relying on classical peer-reviewed publications for describing the internal mechanism. While software tautologically plays a vital role in CS, it is often neglected in favour of more theoretical aspects. This paradox has been provocatively described as "the invisibility of software in published science. Almost all published papers required some coding, but almost none mention software, let alone include or link to source code" [51]. Recently, this primacy of theory over reality [52-54] has been challenged by new emerging hybrid approaches [55] and by the

  10. Risk for Mild Cognitive Impairment Is Associated With Semantic Integration Deficits in Sentence Processing and Memory

    PubMed Central

    Stine-Morrow, Elizabeth A. L.

    2016-01-01

    Objectives. We examined the degree to which online sentence processing and offline sentence memory differed among older adults who showed risk for amnestic and nonamnestic varieties of mild cognitive impairment (MCI), based on psychometric classification. Method. Participants (N = 439) read a series of sentences in a self-paced word-by-word reading paradigm for subsequent recall and completed a standardized cognitive test battery. Participants were classified into 3 groups: unimpaired controls (N = 281), amnestic MCI (N = 94), or nonamnestic MCI (N = 64). Results. Relative to controls, both MCI groups had poorer sentence memory and showed reduced sentence wrap-up effects, indicating reduced allocation to semantic integration processes. Wrap-up effects predicted subsequent recall in the control and nonamnestic groups. The amnestic MCI group showed poorer recall than the nonamnestic MCI group, and only the amnestic MCI group showed no relationship between sentence wrap-up and recall. Discussion. Our findings suggest that psychometrically defined sub-types of MCI are associated with unique deficits in sentence processing and can differentiate between the engagement of attentional resources during reading and the effectiveness of engaging attentional resources in producing improved memory. PMID:25190209

  11. An Embedded Rule-Based Diagnostic Expert System in Ada

    NASA Technical Reports Server (NTRS)

    Jones, Robert E.; Liberman, Eugene M.

    1992-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  12. Audiovisual speech integration in autism spectrum disorders: ERP evidence for atypicalities in lexical-semantic processing.

    PubMed

    Megnin, Odette; Flitton, Atlanta; Jones, Catherine R G; de Haan, Michelle; Baldeweg, Torsten; Charman, Tony

    2012-02-01

    In typically developing (TD) individuals, behavioral and event-related potential (ERP) studies suggest that audiovisual (AV) integration enables faster and more efficient processing of speech. However, little is known about AV speech processing in individuals with autism spectrum disorders (ASD). This study examined ERP responses to spoken words to elucidate the effects of visual speech (the lip movements accompanying a spoken word) on the range of auditory speech processing stages from sound onset detection to semantic integration. The study also included an AV condition, which paired spoken words with a dynamic scrambled face in order to highlight AV effects specific to visual speech. Fourteen adolescent boys with ASD (15-17 years old) and 14 age- and verbal IQ-matched TD boys participated. The ERP of the TD group showed a pattern and topography of AV interaction effects consistent with activity within the superior temporal plane, with two dissociable effects over frontocentral and centroparietal regions. The posterior effect (200-300 ms interval) was specifically sensitive to lip movements in TD boys, and no AV modulation was observed in this region for the ASD group. Moreover, the magnitude of the posterior AV effect to visual speech correlated inversely with ASD symptomatology. In addition, the ASD boys showed an unexpected effect (P2 time window) over the frontocentral region (pooled electrodes F3, Fz, F4, FC1, FC2, FC3, FC4), which was sensitive to scrambled face stimuli. These results suggest that the neural networks facilitating processing of spoken words by visual speech are altered in individuals with ASD.

  13. The DebugIT core ontology: semantic integration of antibiotics resistance patterns.

    PubMed

    Schober, Daniel; Boeker, Martin; Bullenkamp, Jessica; Huszka, Csaba; Depraetere, Kristof; Teodoro, Douglas; Nadah, Nadia; Choquet, Remy; Daniel, Christel; Schulz, Stefan

    2010-01-01

    Antibiotics resistance development poses a significant problem in today's hospital care. Massive amounts of clinical data are being collected and stored in proprietary and unconnected systems in heterogeneous format. The DebugIT EU project promises to make this data geographically and semantically interoperable for case-based knowledge analysis approaches aiming at the discovery of patterns that help to align antibiotics treatment schemes. The semantic glue for this endeavor is DCO, an application ontology that enables data miners to query distributed clinical information systems in a semantically rich and content driven manner. DCO will hence serve as the core component of the interoperability platform for the DebugIT project. Here we present DCO and an approach thet uses the semantic web query language SPARQL to bind and ontologically query hospital database content using DCO and information model mediators. We provide a query example that indicates that ontological querying over heterogeneous information models is feasible via SPARQL construct- and resource mapping queries.

  14. Horizontal Integration of Warfighter Intelligence Data: A Shared Semantic Resource for the Intelligence Community

    DTIC Science & Technology

    2012-10-01

    This strategy, which draws on standard features of what is now called ‘semantic technology ’ [2], has been used successfully for over ten years to...realization of the Human Genome Project [3, 4]. The quantity and variety of such data – now spanning all species and species- interactions, at all life...public release; distribution unlimited 13. SUPPLEMENTARY NOTES Preprint, to be presented at SEMANTIC TECHNOLOGY FOR INTELLIGENCE, DEFENSE, AND

  15. Integrating semantic web technologies and geospatial catalog services for geospatial information discovery and processing in cyberinfrastructure

    SciTech Connect

    Yue, Peng; Gong, Jianya; Di, Liping; He, Lianlian; Wei, Yaxing

    2011-04-01

    Abstract A geospatial catalogue service provides a network-based meta-information repository and interface for advertising and discovering shared geospatial data and services. Descriptive information (i.e., metadata) for geospatial data and services is structured and organized in catalogue services. The approaches currently available for searching and using that information are often inadequate. Semantic Web technologies show promise for better discovery methods by exploiting the underlying semantics. Such development needs special attention from the Cyberinfrastructure perspective, so that the traditional focus on discovery of and access to geospatial data can be expanded to support the increased demand for processing of geospatial information and discovery of knowledge. Semantic descriptions for geospatial data, services, and geoprocessing service chains are structured, organized, and registered through extending elements in the ebXML Registry Information Model (ebRIM) of a geospatial catalogue service, which follows the interface specifications of the Open Geospatial Consortium (OGC) Catalogue Services for the Web (CSW). The process models for geoprocessing service chains, as a type of geospatial knowledge, are captured, registered, and discoverable. Semantics-enhanced discovery for geospatial data, services/service chains, and process models is described. Semantic search middleware that can support virtual data product materialization is developed for the geospatial catalogue service. The creation of such a semantics-enhanced geospatial catalogue service is important in meeting the demands for geospatial information discovery and analysis in Cyberinfrastructure.

  16. Toward Open Science at the European Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling

    NASA Astrophysics Data System (ADS)

    de Rigo, Daniele; Corti, Paolo; Caudullo, Giovanni; McInerney, Daniel; Di Leo, Margherita; San-Miguel-Ayanz, Jesús

    2013-04-01

    of the science-policy interface, INRMM should be able to provide citizens and policy-makers with a clear, accurate understanding of the implications of the technical apparatus on collective environmental decision-making [1]. Complexity of course should not be intended as an excuse for obscurity [27-29]. Geospatial Semantic Array Programming. Concise array-based mathematical formulation and implementation (with array programming tools, see (b) ) have proved helpful in supporting and mitigating the complexity of WSTMe [40-47] when complemented with generalized modularization and terse array-oriented semantic constraints. This defines the paradigm of Semantic Array Programming (SemAP) [35,36] where semantic transparency also implies free software use (although black-boxes [12] - e.g. legacy code - might easily be semantically interfaced). A new approach for WSTMe has emerged by formalizing unorganized best practices and experience-driven informal patterns. The approach introduces a lightweight (non-intrusive) integration of SemAP and geospatial tools (c) - called Geospatial Semantic Array Programming (GeoSemAP). GeoSemAP (d) exploits the joint semantics provided by SemAP and geospatial tools to split a complex D- TM into logical blocks which are easier to check by means of mathematical array-based and geospatial constraints. Those constraints take the form of precondition, invariant and postcondition semantic checks. This way, even complex WSTMe may be described as the composition of simpler GeoSemAP blocks, each of them structured as (d). GeoSemAP allows intermediate data and information layers to be more easily an formally semantically described so as to increase fault-tolerance [17], transparency and reproducibility of WSTMe. This might also help to better communicate part of the policy-relevant knowledge, often difficult to transfer from technical WSTMe to the science-policy interface [1,15]. References de Rigo, D., 2013. Behind the horizon of reproducible

  17. Automation and integration of components for generalized semantic markup of electronic medical texts.

    PubMed

    Dugan, J M; Berrios, D C; Liu, X; Kim, D K; Kaizer, H; Fagan, L M

    1999-01-01

    Our group has built an information retrieval system based on a complex semantic markup of medical textbooks. We describe the construction of a set of web-based knowledge-acquisition tools that expedites the collection and maintenance of the concepts required for text markup and the search interface required for information retrieval from the marked text. In the text markup system, domain experts (DEs) identify sections of text that contain one or more elements from a finite set of concepts. End users can then query the text using a predefined set of questions, each of which identifies a subset of complementary concepts. The search process matches that subset of concepts to relevant points in the text. The current process requires that the DE invest significant time to generate the required concepts and questions. We propose a new system--called ACQUIRE (Acquisition of Concepts and Queries in an Integrated Retrieval Environment)--that assists a DE in two essential tasks in the text-markup process. First, it helps her to develop, edit, and maintain the concept model: the set of concepts with which she marks the text. Second, ACQUIRE helps her to develop a query model: the set of specific questions that end users can later use to search the marked text. The DE incorporates concepts from the concept model when she creates the questions in the query model. The major benefit of the ACQUIRE system is a reduction in the time and effort required for the text-markup process. We compared the process of concept- and query-model creation using ACQUIRE to the process used in previous work by rebuilding two existing models that we previously constructed manually. We observed a significant decrease in the time required to build and maintain the concept and query models.

  18. The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

    USGS Publications Warehouse

    Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.; Brown, Jesslyn F.

    2015-01-01

    Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.

  19. Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

    PubMed

    Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F

    2014-02-01

    A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings.

  20. Neural Correlates of Verbal and Nonverbal Semantic Integration in Children with Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    McCleery, Joseph P.; Ceponiene, Rita; Burner, Karen M.; Townsend, Jeanne; Kinnear, Mikaela; Schreibman, Laura

    2010-01-01

    Background: Autism is a pervasive developmental disorder characterized by deficits in social-emotional, social-communicative, and language skills. Behavioral and neuroimaging studies have found that children with autism spectrum disorders (ASD) evidence abnormalities in semantic processing, with particular difficulties in verbal comprehension.…

  1. Semantic Integration as a Boundary Condition on Inhibitory Processes in Episodic Retrieval

    ERIC Educational Resources Information Center

    Goodmon, Leilani B.; Anderson, Michael C.

    2011-01-01

    Recalling an experience often impairs the later retention of related traces, a phenomenon known as retrieval-induced forgetting (RIF). Research has shown that episodic associations protect competing memories from RIF (Anderson & McCulloch, 1999). We report 4 experiments that examined whether semantic associations also protect against RIF. In…

  2. The 3rd DBCLS BioHackathon: improving life science data integration with Semantic Web technologies

    PubMed Central

    2013-01-01

    Background BioHackathon 2010 was the third in a series of meetings hosted by the Database Center for Life Sciences (DBCLS) in Tokyo, Japan. The overall goal of the BioHackathon series is to improve the quality and accessibility of life science research data on the Web by bringing together representatives from public databases, analytical tool providers, and cyber-infrastructure researchers to jointly tackle important challenges in the area of in silico biological research. Results The theme of BioHackathon 2010 was the 'Semantic Web', and all attendees gathered with the shared goal of producing Semantic Web data from their respective resources, and/or consuming or interacting those data using their tools and interfaces. We discussed on topics including guidelines for designing semantic data and interoperability of resources. We consequently developed tools and clients for analysis and visualization. Conclusion We provide a meeting report from BioHackathon 2010, in which we describe the discussions, decisions, and breakthroughs made as we moved towards compliance with Semantic Web technologies - from source provider, through middleware, to the end-consumer. PMID:23398680

  3. Semantic Integration and Age of Acquisition Effects in Code-Blend Comprehension

    ERIC Educational Resources Information Center

    Giezen, Marcel R.; Emmorey, Karen

    2016-01-01

    Semantic and lexical decision tasks were used to investigate the mechanisms underlying code-blend facilitation: the finding that hearing bimodal bilinguals comprehend signs in American Sign Language (ASL) and spoken English words more quickly when they are presented together simultaneously than when each is presented alone. More robust…

  4. CI-Miner: A Semantic Methodology to Integrate Scientists, Data and Documents through the Use of Cyber-Infrastructure

    NASA Astrophysics Data System (ADS)

    Pinheiro da Silva, P.; CyberShARE Center of Excellence

    2011-12-01

    Scientists today face the challenge of rethinking the manner in which they document and make available their processes and data in an international cyber-infrastructure of shared resources. Some relevant examples of new scientific practices in the realm of computational and data extraction sciences include: large scale data discovery; data integration; data sharing across distinct scientific domains, systematic management of trust and uncertainty; and comprehensive support for explaining processes and results. This talk introduces CI-Miner - an innovative hands-on, open-source, community-driven methodology to integrate these new scientific practices. It has been developed in collaboration with scientists, with the purpose of capturing, storing and retrieving knowledge about scientific processes and their products, thereby further supporting a new generation of science techniques based on data exploration. CI-Miner uses semantic annotations in the form of W3C Ontology Web Language-based ontologies and Proof Markup Language (PML)-based provenance to represent knowledge. This methodology specializes in general-purpose ontologies, projected into workflow-driven ontologies(WDOs) and into semantic abstract workflows (SAWs). Provenance in PML is CI-Miner's integrative component, which allows scientists to retrieve and reason with the knowledge represented in these new semantic documents. It serves additionally as a platform to share such collected knowledge with the scientific community participating in the international cyber-infrastructure. The integrated semantic documents that are tailored for the use of human epistemic agents may also be utilized by machine epistemic agents, since the documents are based on W3C Resource Description Framework (RDF) notation. This talk is grounded upon interdisciplinary lessons learned through the use of CI-Miner in support of government-funded national and international cyber-infrastructure initiatives in the areas of geo

  5. The anterior temporal lobes are critically involved in acquiring new conceptual knowledge: evidence for impaired feature integration in semantic dementia.

    PubMed

    Hoffman, Paul; Evans, Gemma A L; Lambon Ralph, Matthew A

    2014-01-01

    Recent evidence from multiple neuroscience techniques indicates that regions within the anterior temporal lobes (ATLs) are a critical node in the neural network for representing conceptual knowledge, yet their function remains elusive. The hub-and-spoke model holds that ATL regions act as a transmodal conceptual hub, distilling the various sensory-motor features of objects and words into integrated, coherent conceptual representations. Single-cell recordings in monkeys suggest that the ATLs are critically involved in visual associative learning; however, investigations of this region in humans have focused on existing knowledge rather than learning. We studied acquisition of new concepts in semantic dementia patients, who have cortical damage centred on the ventrolateral aspects of the ATLs. Patients learned to assign abstract visual stimuli to two categories. The categories conformed to a family resemblance structure in which no individual stimulus features were fully diagnostic; thus the task required participants to form representations that integrate multiple features into a single concept. Patients were unable to do this, instead responding only on the basis of individual features. The study reveals that integrating disparate sources of information into novel coherent concepts is a critical computational function of the ATLs. This explains the central role of this region in conceptual representation and the catastrophic breakdown of concepts in semantic dementia.

  6. SemFunSim: A New Method for Measuring Disease Similarity by Integrating Semantic and Gene Functional Association

    PubMed Central

    Ju, Peng; Peng, Jiajie; Wang, Yadong

    2014-01-01

    Background Measuring similarity between diseases plays an important role in disease-related molecular function research. Functional associations between disease-related genes and semantic associations between diseases are often used to identify pairs of similar diseases from different perspectives. Currently, it is still a challenge to exploit both of them to calculate disease similarity. Therefore, a new method (SemFunSim) that integrates semantic and functional association is proposed to address the issue. Methods SemFunSim is designed as follows. First of all, FunSim (Functional similarity) is proposed to calculate disease similarity using disease-related gene sets in a weighted network of human gene function. Next, SemSim (Semantic Similarity) is devised to calculate disease similarity using the relationship between two diseases from Disease Ontology. Finally, FunSim and SemSim are integrated to measure disease similarity. Results The high average AUC (area under the receiver operating characteristic curve) (96.37%) shows that SemFunSim achieves a high true positive rate and a low false positive rate. 79 of the top 100 pairs of similar diseases identified by SemFunSim are annotated in the Comparative Toxicogenomics Database (CTD) as being targeted by the same therapeutic compounds, while other methods we compared could identify 35 or less such pairs among the top 100. Moreover, when using our method on diseases without annotated compounds in CTD, we could confirm many of our predicted candidate compounds from literature. This indicates that SemFunSim is an effective method for drug repositioning. PMID:24932637

  7. Fuzzification of ASAT's rule based aimpoint selection

    NASA Astrophysics Data System (ADS)

    Weight, Thomas H.

    1993-06-01

    The aimpoint algorithms being developed at Dr. Weight and Associates are based on the concept of fuzzy logic. This approach does not require a particular type of sensor data or algorithm type, but allows the user to develop a fuzzy logic algorithm based on existing aimpoint algorithms and models. This provides an opportunity for the user to upgrade an existing system design to achieve higher performance at minimal cost. Many projects have aimpoint algorithms which are based on 'crisp' logic rule based algorithms. These algorithms are sensitive to glint, corner reflectors, or intermittent thruster firings, and to uncertainties in the a priori estimates of angle of attack. If these projects are continued through to a demonstration involving a launch to hit a target, it is quite possible that the crisp logic approaches will need to be upgraded to handle these important error sources.

  8. Semantics-Based Composition of Integrated Cardiomyocyte Models Motivated by Real-World Use Cases

    PubMed Central

    Neal, Maxwell L.; Carlson, Brian E.; Thompson, Christopher T.; James, Ryan C.; Kim, Karam G.; Tran, Kenneth; Crampin, Edmund J.; Cook, Daniel L.; Gennari, John H.

    2015-01-01

    Semantics-based model composition is an approach for generating complex biosimulation models from existing components that relies on capturing the biological meaning of model elements in a machine-readable fashion. This approach allows the user to work at the biological rather than computational level of abstraction and helps minimize the amount of manual effort required for model composition. To support this compositional approach, we have developed the SemGen software, and here report on SemGen’s semantics-based merging capabilities using real-world modeling use cases. We successfully reproduced a large, manually-encoded, multi-model merge: the “Pandit-Hinch-Niederer” (PHN) cardiomyocyte excitation-contraction model, previously developed using CellML. We describe our approach for annotating the three component models used in the PHN composition and for merging them at the biological level of abstraction within SemGen. We demonstrate that we were able to reproduce the original PHN model results in a semi-automated, semantics-based fashion and also rapidly generate a second, novel cardiomyocyte model composed using an alternative, independently-developed tension generation component. We discuss the time-saving features of our compositional approach in the context of these merging exercises, the limitations we encountered, and potential solutions for enhancing the approach. PMID:26716837

  9. Semantic confusion regarding the development of multisensory integration: a practical solution

    PubMed Central

    Stein, Barry E.; Burr, David; Constantinidis, Christos; Laurienti, Paul J.; Meredith, M. Alex; Perrault, Thomas J.; Ramachandran, Ramnarayan; Röder, Brigitte; Rowland, Benjamin A.; Sathian, K.; Schroeder, Charles E.; Shams, Ladan; Stanford, Terrence R.; Wallace, Mark T.; Yu, Liping; Lewkowicz, David J.

    2011-01-01

    There is now a good deal of data from neurophysiological studies in animals and behavioral studies in human infants regarding the development of multisensory processing capabilities. Although the conclusions drawn from these different datasets sometimes appear to conflict, many of the differences are due to the use of different terms to mean the same thing and, more problematic, the use of similar terms to mean different things. Semantic issues are pervasive in the field and complicate communication among groups using different methods to study similar issues. Achieving clarity of communication among different investigative groups is essential for each to make full use of the findings of others, and an important step in this direction is to identify areas of semantic confusion. In this way investigators can be encouraged to use terms whose meaning and underlying assumptions are unambiguous because they are commonly accepted. Although this issue is of obvious importance to the large and very rapidly growing number of researchers working on multisensory processes, it is perhaps even more important to the non-cognoscenti. Those who wish to benefit from the scholarship in this field but are unfamiliar with the issues identified here are most likely to be confused by semantic inconsistencies. The current discussion attempts to document some of the more problematic of these, begin a discussion about the nature of the confusion and suggest some possible solutions. PMID:20584174

  10. Lexicon-enhanced sentiment analysis framework using rule-based classification scheme

    PubMed Central

    Khan, Aurangzeb; Ahmad, Shakeel; Qasim, Maria; Khan, Imran Ali

    2017-01-01

    With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA) applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-specific words expressed in the public’s feedback about the products. However, the un-supervised learning approach employed in previous studies is becoming less efficient due to data sparseness, low accuracy due to non-consideration of emoticons, modifiers, and presence of domain specific words, as they may result in inaccurate classification of users’ reviews. Lexicon-enhanced sentiment analysis based on Rule-based classification scheme is an alternative approach for improving sentiment classification of users’ reviews in online communities. In addition to the sentiment terms used in general purpose sentiment analysis, we integrate emoticons, modifiers and domain specific terms to analyze the reviews posted in online communities. To test the effectiveness of the proposed method, we considered users reviews in three domains. The results obtained from different experiments demonstrate that the proposed method overcomes limitations of previous methods and the performance of the sentiment analysis is improved after considering emoticons, modifiers, negations, and domain specific terms when compared to baseline methods. PMID:28231286

  11. Ontology Design Patterns: Bridging the Gap Between Local Semantic Use Cases and Large-Scale, Long-Term Data Integration

    NASA Astrophysics Data System (ADS)

    Shepherd, Adam; Arko, Robert; Krisnadhi, Adila; Hitzler, Pascal; Janowicz, Krzysztof; Chandler, Cyndy; Narock, Tom; Cheatham, Michelle; Schildhauer, Mark; Jones, Matt; Raymond, Lisa; Mickle, Audrey; Finin, Tim; Fils, Doug; Carbotte, Suzanne; Lehnert, Kerstin

    2015-04-01

    Integrating datasets for new use cases is one of the common drivers for adopting semantic web technologies. Even though linked data principles enables this type of activity over time, the task of reconciling new ontological commitments for newer use cases can be daunting. This situation was faced by the Biological and Chemical Oceanography Data Management Office (BCO-DMO) as it sought to integrate its existing linked data with other data repositories to address newer scientific use cases as a partner in the GeoLink Project. To achieve a successful integration with other GeoLink partners, BCO-DMO's metadata would need to be described using the new ontologies developed by the GeoLink partners - a situation that could impact semantic inferencing, pre-existing software and external users of BCO-DMO's linked data. This presentation describes the process of how GeoLink is bridging the gap between local, pre-existing ontologies to achieve scientific metadata integration for all its partners through the use of ontology design patterns. GeoLink, an NSF EarthCube Building Block, brings together experts from the geosciences, computer science, and library science in an effort to improve discovery and reuse of data and knowledge. Its participating repositories include content from field expeditions, laboratory analyses, journal publications, conference presentations, theses/reports, and funding awards that span scientific studies from marine geology to marine ecology and biogeochemistry to paleoclimatology. GeoLink's outcomes include a set of reusable ontology design patterns (ODPs) that describe core geoscience concepts, a network of Linked Data published by participating repositories using those ODPs, and tools to facilitate discovery of related content in multiple repositories.

  12. An Unsupervised Rule-Based Method to Populate Ontologies from Text

    NASA Astrophysics Data System (ADS)

    Motta, Eduardo; Siqueira, Sean; Andreatta, Alexandre

    An increasing amount of information is available on the web and usually is expressed as text. Semantic information is implicit in these texts, since they are mainly intended for human consumption and interpretation. Because unstructured information is not easily handled automatically, an information extraction process has to be used to identify concepts and establish relations among them. Ontologies are an appropriate way to represent structured knowledge bases, enabling sharing, reuse and inference. In this paper, an information extraction process is used for populating a domain ontology. It targets Brazilian Portuguese texts from a biographical dictionary of music, which requires specific tools due to some language unique aspects. An unsupervised rule-based method is proposed. Through this process, latent concepts and relations expressed in natural language can be extracted and represented as an ontology, allowing new uses and visualizations of the content, such as semantically browsing and inferring new knowledge.

  13. Modified risk graph method using fuzzy rule-based approach.

    PubMed

    Nait-Said, R; Zidani, F; Ouzraoui, N

    2009-05-30

    The risk graph is one of the most popular methods used to determine the safety integrity level for safety instrumented functions. However, conventional risk graph as described in the IEC 61508 standard is subjective and suffers from an interpretation problem of risk parameters. Thus, it can lead to inconsistent outcomes that may result in conservative SILs. To overcome this difficulty, a modified risk graph using fuzzy rule-based system is proposed. This novel version of risk graph uses fuzzy scales to assess risk parameters and calibration may be made by varying risk parameter values. Furthermore, the outcomes which are numerical values of risk reduction factor (the inverse of the probability of failure on demand) can be compared directly with those given by quantitative and semi-quantitative methods such as fault tree analysis (FTA), quantitative risk assessment (QRA) and layers of protection analysis (LOPA).

  14. From ontology selection and semantic web to an integrated information system for food-borne diseases and food safety.

    PubMed

    Yan, Xianghe; Peng, Yun; Meng, Jianghong; Ruzante, Juliana; Fratamico, Pina M; Huang, Lihan; Juneja, Vijay; Needleman, David S

    2011-01-01

    Several factors have hindered effective use of information and resources related to food safety due to inconsistency among semantically heterogeneous data resources, lack of knowledge on profiling of food-borne pathogens, and knowledge gaps among research communities, government risk assessors/managers, and end-users of the information. This paper discusses technical aspects in the establishment of a comprehensive food safety information system consisting of the following steps: (a) computational collection and compiling publicly available information, including published pathogen genomic, proteomic, and metabolomic data; (b) development of ontology libraries on food-borne pathogens and design automatic algorithms with formal inference and fuzzy and probabilistic reasoning to address the consistency and accuracy of distributed information resources (e.g., PulseNet, FoodNet, OutbreakNet, PubMed, NCBI, EMBL, and other online genetic databases and information); (c) integration of collected pathogen profiling data, Foodrisk.org ( http://www.foodrisk.org ), PMP, Combase, and other relevant information into a user-friendly, searchable, "homogeneous" information system available to scientists in academia, the food industry, and government agencies; and (d) development of a computational model in semantic web for greater adaptability and robustness.

  15. Content-based image retrieval with semantic navigation for medical images with multifocal diseases in integrated RIS/PACS system

    NASA Astrophysics Data System (ADS)

    Zhu, Yanjie; Zhang, Jianguo

    2011-03-01

    In this paper, we proposed a novel architecture integrated with RIS/PACS system that combined image annotation, CBIR techniques and high-dimensional index to retrieve similar medical images with one or more relevant focus in large scale medical image database. In our designed system, regions of interest (ROIs) were labeled by symptom descriptions found in relevant radiology reports as semantic navigation. The annotations were saved as xml file with image makeup language (IML). Then low level features such as texture and statistic features were extracted from the ROIs of lesions and inserted into a database. Recursive feature elimination algorithm was applied to find a high performance feature subset for each symptom. These subsets were used to build high dimensional index with semantic labels guiding the searching path as the navigation. As there might be more than one focus in one image, weight values specified by the user were introduced to calculate the final similarities. The searching results of medical images with multi-focal diseases are likely to have the same pathologies and visual effects with example image and are valuable for imaging diagnosis. The system was implemented for lung CT images, but it could be easily extended to other organs.

  16. Integrating Dynamic Data and Sensors with Semantic 3D City Models in the Context of Smart Cities

    NASA Astrophysics Data System (ADS)

    Chaturvedi, K.; Kolbe, T. H.

    2016-10-01

    Smart cities provide effective integration of human, physical and digital systems operating in the built environment. The advancements in city and landscape models, sensor web technologies, and simulation methods play a significant role in city analyses and improving quality of life of citizens and governance of cities. Semantic 3D city models can provide substantial benefits and can become a central information backbone for smart city infrastructures. However, current generation semantic 3D city models are static in nature and do not support dynamic properties and sensor observations. In this paper, we propose a new concept called Dynamizer allowing to represent highly dynamic data and providing a method for injecting dynamic variations of city object properties into the static representation. The approach also provides direct capability to model complex patterns based on statistics and general rules and also, real-time sensor observations. The concept is implemented as an Application Domain Extension for the CityGML standard. However, it could also be applied to other GML-based application schemas including the European INSPIRE data themes and national standards for topography and cadasters like the British Ordnance Survey Mastermap or the German cadaster standard ALKIS.

  17. A rule-based software test data generator

    NASA Technical Reports Server (NTRS)

    Deason, William H.; Brown, David B.; Chang, Kai-Hsiung; Cross, James H., II

    1991-01-01

    Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

  18. Integrated Data Capturing Requirements for 3d Semantic Modelling of Cultural Heritage: the Inception Protocol

    NASA Astrophysics Data System (ADS)

    Di Giulio, R.; Maietti, F.; Piaia, E.; Medici, M.; Ferrari, F.; Turillazzi, B.

    2017-02-01

    The generation of high quality 3D models can be still very time-consuming and expensive, and the outcome of digital reconstructions is frequently provided in formats that are not interoperable, and therefore cannot be easily accessed. This challenge is even more crucial for complex architectures and large heritage sites, which involve a large amount of data to be acquired, managed and enriched by metadata. In this framework, the ongoing EU funded project INCEPTION - Inclusive Cultural Heritage in Europe through 3D semantic modelling proposes a workflow aimed at the achievements of efficient 3D digitization methods, post-processing tools for an enriched semantic modelling, web-based solutions and applications to ensure a wide access to experts and non-experts. In order to face these challenges and to start solving the issue of the large amount of captured data and time-consuming processes in the production of 3D digital models, an Optimized Data Acquisition Protocol (DAP) has been set up. The purpose is to guide the processes of digitization of cultural heritage, respecting needs, requirements and specificities of cultural assets.

  19. Rational integration of noisy evidence and prior semantic expectations in sentence interpretation

    PubMed Central

    Gibson, Edward; Bergen, Leon; Piantadosi, Steven T.

    2013-01-01

    Sentence processing theories typically assume that the input to our language processing mechanisms is an error-free sequence of words. However, this assumption is an oversimplification because noise is present in typical language use (for instance, due to a noisy environment, producer errors, or perceiver errors). A complete theory of human sentence comprehension therefore needs to explain how humans understand language given imperfect input. Indeed, like many cognitive systems, language processing mechanisms may even be “well designed”–in this case for the task of recovering intended meaning from noisy utterances. In particular, comprehension mechanisms may be sensitive to the types of information that an idealized statistical comprehender would be sensitive to. Here, we evaluate four predictions about such a rational (Bayesian) noisy-channel language comprehender in a sentence comprehension task: (i) semantic cues should pull sentence interpretation towards plausible meanings, especially if the wording of the more plausible meaning is close to the observed utterance in terms of the number of edits; (ii) this process should asymmetrically treat insertions and deletions due to the Bayesian “size principle”; such nonliteral interpretation of sentences should (iii) increase with the perceived noise rate of the communicative situation and (iv) decrease if semantically anomalous meanings are more likely to be communicated. These predictions are borne out, strongly suggesting that human language relies on rational statistical inference over a noisy channel. PMID:23637344

  20. Integrated Syntactic/Semantic XML Data Validation with a Reusable Software Component

    ERIC Educational Resources Information Center

    Golikov, Steven

    2013-01-01

    Data integration is a critical component of enterprise system integration, and XML data validation is the foundation for sound data integration of XML-based information systems. Since B2B e-commerce relies on data validation as one of the critical components for enterprise integration, it is imperative for financial industries and e-commerce…

  1. Implementing a commercial rule base as a medication order safety net.

    PubMed

    Reichley, Richard M; Seaton, Terry L; Resetar, Ervina; Micek, Scott T; Scott, Karen L; Fraser, Victoria J; Dunagan, W Claiborne; Bailey, Thomas C

    2005-01-01

    A commercial rule base (Cerner Multum) was used to identify medication orders exceeding recommended dosage limits at five hospitals within BJC HealthCare, an integrated health care system. During initial testing, clinical pharmacists determined that there was an excessive number of nuisance and clinically insignificant alerts, with an overall alert rate of 9.2%. A method for customizing the commercial rule base was implemented to increase rule specificity for problematic rules. The system was subsequently deployed at two facilities and achieved alert rates of less than 1%. Pharmacists screened these alerts and contacted ordering physicians in 21% of cases. Physicians made therapeutic changes in response to 38% of alerts presented to them. By applying simple techniques to customize rules, commercial rule bases can be used to rapidly deploy a safety net to screen drug orders for excessive dosages, while preserving the rule architecture for later implementations of more finely tuned clinical decision support.

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

    PubMed Central

    2011-01-01

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

  3. Adaptive Rule Based Fetal QRS Complex Detection Using Hilbert Transform

    PubMed Central

    Ulusar, Umit D.; Govindan, R.B.; Wilson, James D.; Lowery, Curtis L.; Preissl, Hubert; Eswaran, Hari

    2010-01-01

    In this paper we introduce an adaptive rule based QRS detection algorithm using the Hilbert transform (adHQRS) for fetal magnetocardiography processing. Hilbert transform is used to combine multiple channel measurements and the adaptive rule based decision process is used to eliminate spurious beats. The algorithm has been tested with a large number of datasets and promising results were obtained. PMID:19964648

  4. Adaptive rule based fetal QRS complex detection using Hilbert transform.

    PubMed

    Ulusar, Umit D; Govindan, R B; Wilson, James D; Lowery, Curtis L; Preissl, Hubert; Eswaran, Hari

    2009-01-01

    In this paper we introduce an adaptive rule based QRS detection algorithm using the Hilbert transform (adHQRS) for fetal magnetocardiography processing. Hilbert transform is used to combine multiple channel measurements and the adaptive rule based decision process is used to eliminate spurious beats. The algorithm has been tested with a large number of datasets and promising results were obtained.

  5. Dispositional mindfulness and semantic integration of emotional words: Evidence from event-related brain potentials.

    PubMed

    Dorjee, Dusana; Lally, Níall; Darrall-Rew, Jonathan; Thierry, Guillaume

    2015-08-01

    Initial research shows that mindfulness training can enhance attention and modulate the affective response. However, links between mindfulness and language processing remain virtually unexplored despite the prominent role of overt and silent negative ruminative speech in depressive and anxiety-related symptomatology. Here, we measured dispositional mindfulness and recorded participants' event-related brain potential responses to positive and negative target words preceded by words congruent or incongruent with the targets in terms of semantic relatedness and emotional valence. While the low mindfulness group showed similar N400 effect pattern for positive and negative targets, high dispositional mindfulness was associated with larger N400 effect to negative targets. This result suggests that negative meanings are less readily accessible in people with high dispositional mindfulness. Furthermore, high dispositional mindfulness was associated with reduced P600 amplitudes to emotional words, suggesting less post-analysis and attentional effort which possibly relates to a lower inclination to ruminate. Overall, these findings provide initial evidence on associations between modifications in language systems and mindfulness.

  6. Semantic Sensor Web

    NASA Astrophysics Data System (ADS)

    Sheth, A.; Henson, C.; Thirunarayan, K.

    2008-12-01

    Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the Semantic Sensor Web (SSW) [1] proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for situational knowledge. Kno.e.sis Center's approach to SSW is an evolutionary one. It adds semantic annotations to the existing standard sensor languages of the Sensor Web Enablement (SWE) defined by OGC. These annotations enhance primarily syntactic XML-based descriptions in OGC's SWE languages with microformats, and W3C's Semantic Web languages- RDF and OWL. In association with semantic annotation and semantic web capabilities including ontologies and rules, SSW supports interoperability, analysis and reasoning over heterogeneous multi-modal sensor data. In this presentation, we will also demonstrate a mashup with support for complex spatio-temporal-thematic queries [2] and semantic analysis that utilize semantic annotations, multiple ontologies and rules. It uses existing services (e.g., GoogleMap) and semantics enhanced SWE's Sensor Observation Service (SOS) over weather and road condition data from various sensors that are part of Ohio's transportation network. Our upcoming plans are to demonstrate end to end (heterogeneous sensor to application) semantics support and study scalability of SSW involving thousands of sensors to about a billion triples. Keywords: Semantic Sensor Web, Spatiotemporal thematic queries, Semantic Web Enablement, Sensor Observation Service [1] Amit Sheth, Cory Henson, Satya

  7. Visualising biological data: a semantic approach to tool and database integration

    PubMed Central

    Pettifer, Steve; Thorne, David; McDermott, Philip; Marsh, James; Villéger, Alice; Kell, Douglas B; Attwood, Teresa K

    2009-01-01

    Motivation In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are ad hoc collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research. Methods To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows

  8. Semantics by analogy for illustrative volume visualization.

    PubMed

    Gerl, Moritz; Rautek, Peter; Isenberg, Tobias; Gröller, Eduard

    2012-05-01

    We present an interactive graphical approach for the explicit specification of semantics for volume visualization. This explicit and graphical specification of semantics for volumetric features allows us to visually assign meaning to both input and output parameters of the visualization mapping. This is in contrast to the implicit way of specifying semantics using transfer functions. In particular, we demonstrate how to realize a dynamic specification of semantics which allows to flexibly explore a wide range of mappings. Our approach is based on three concepts. First, we use semantic shader augmentation to automatically add rule-based rendering functionality to static visualization mappings in a shader program, while preserving the visual abstraction that the initial shader encodes. With this technique we extend recent developments that define a mapping between data attributes and visual attributes with rules, which are evaluated using fuzzy logic. Second, we let users define the semantics by analogy through brushing on renderings of the data attributes of interest. Third, the rules are specified graphically in an interface that provides visual clues for potential modifications. Together, the presented methods offer a high degree of freedom in the specification and exploration of rule-based mappings and avoid the limitations of a linguistic rule formulation.

  9. Semantics by analogy for illustrative volume visualization☆

    PubMed Central

    Gerl, Moritz; Rautek, Peter; Isenberg, Tobias; Gröller, Eduard

    2012-01-01

    We present an interactive graphical approach for the explicit specification of semantics for volume visualization. This explicit and graphical specification of semantics for volumetric features allows us to visually assign meaning to both input and output parameters of the visualization mapping. This is in contrast to the implicit way of specifying semantics using transfer functions. In particular, we demonstrate how to realize a dynamic specification of semantics which allows to flexibly explore a wide range of mappings. Our approach is based on three concepts. First, we use semantic shader augmentation to automatically add rule-based rendering functionality to static visualization mappings in a shader program, while preserving the visual abstraction that the initial shader encodes. With this technique we extend recent developments that define a mapping between data attributes and visual attributes with rules, which are evaluated using fuzzy logic. Second, we let users define the semantics by analogy through brushing on renderings of the data attributes of interest. Third, the rules are specified graphically in an interface that provides visual clues for potential modifications. Together, the presented methods offer a high degree of freedom in the specification and exploration of rule-based mappings and avoid the limitations of a linguistic rule formulation. PMID:23576827

  10. The Development of the Ability to Semantically Integrate Information in Speech and Iconic Gesture in Comprehension.

    PubMed

    Sekine, Kazuki; Sowden, Hannah; Kita, Sotaro

    2015-11-01

    We examined whether children's ability to integrate speech and gesture follows the pattern of a broader developmental shift between 3- and 5-year-old children (Ramscar & Gitcho, 2007) regarding the ability to process two pieces of information simultaneously. In Experiment 1, 3-year-olds, 5-year-olds, and adults were presented with either an iconic gesture or a spoken sentence or a combination of the two on a computer screen, and they were instructed to select a photograph that best matched the message. The 3-year-olds did not integrate information in speech and gesture, but 5-year-olds and adults did. In Experiment 2, 3-year-old children were presented with the same speech and gesture as in Experiment 1 that were produced live by an experimenter. When presented live, 3-year-olds could integrate speech and gesture. We concluded that development of the integration ability is a part of the broader developmental shift; however, live-presentation facilitates the nascent integration ability in 3-year-olds.

  11. Developing a semantic web model for medical differential diagnosis recommendation.

    PubMed

    Mohammed, Osama; Benlamri, Rachid

    2014-10-01

    In this paper we describe a novel model for differential diagnosis designed to make recommendations by utilizing semantic web technologies. The model is a response to a number of requirements, ranging from incorporating essential clinical diagnostic semantics to the integration of data mining for the process of identifying candidate diseases that best explain a set of clinical features. We introduce two major components, which we find essential to the construction of an integral differential diagnosis recommendation model: the evidence-based recommender component and the proximity-based recommender component. Both approaches are driven by disease diagnosis ontologies designed specifically to enable the process of generating diagnostic recommendations. These ontologies are the disease symptom ontology and the patient ontology. The evidence-based diagnosis process develops dynamic rules based on standardized clinical pathways. The proximity-based component employs data mining to provide clinicians with diagnosis predictions, as well as generates new diagnosis rules from provided training datasets. This article describes the integration between these two components along with the developed diagnosis ontologies to form a novel medical differential diagnosis recommendation model. This article also provides test cases from the implementation of the overall model, which shows quite promising diagnostic recommendation results.

  12. Automated implementation of rule-based expert systems with neural networks for time-critical applications

    NASA Technical Reports Server (NTRS)

    Ramamoorthy, P. A.; Huang, Song; Govind, Girish

    1991-01-01

    In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

  13. Techniques and implementation of the embedded rule-based expert system using Ada

    NASA Technical Reports Server (NTRS)

    Liberman, Eugene M.; Jones, Robert E.

    1991-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  14. Semantic Domain-Specific Functional Integration for Action-Related vs. Abstract Concepts

    ERIC Educational Resources Information Center

    Ghio, Marta; Tettamanti, Marco

    2010-01-01

    A central topic in cognitive neuroscience concerns the representation of concepts and the specific neural mechanisms that mediate conceptual knowledge. Recently proposed modal theories assert that concepts are grounded on the integration of multimodal, distributed representations. The aim of the present work is to complement the available…

  15. The Development of the Ability to Semantically Integrate Information in Speech and Iconic Gesture in Comprehension

    ERIC Educational Resources Information Center

    Sekine, Kazuki; Sowden, Hannah; Kita, Sotaro

    2015-01-01

    We examined whether children's ability to integrate speech and gesture follows the pattern of a broader developmental shift between 3- and 5-year-old children (Ramscar & Gitcho, 2007) regarding the ability to process two pieces of information simultaneously. In Experiment 1, 3-year-olds, 5-year-olds, and adults were presented with either an…

  16. A Semantic Analysis of XML Schema Matching for B2B Systems Integration

    ERIC Educational Resources Information Center

    Kim, Jaewook

    2011-01-01

    One of the most critical steps to integrating heterogeneous e-Business applications using different XML schemas is schema matching, which is known to be costly and error-prone. Many automatic schema matching approaches have been proposed, but the challenge is still daunting because of the complexity of schemas and immaturity of technologies in…

  17. Case Study for Integration of an Oncology Clinical Site in a Semantic Interoperability Solution based on HL7 v3 and SNOMED-CT: Data Transformation Needs.

    PubMed

    Ibrahim, Ahmed; Bucur, Anca; Perez-Rey, David; Alonso, Enrique; de Hoog, Matthy; Dekker, Andre; Marshall, M Scott

    2015-01-01

    This paper describes the data transformation pipeline defined to support the integration of a new clinical site in a standards-based semantic interoperability environment. The available datasets combined structured and free-text patient data in Dutch, collected in the context of radiation therapy in several cancer types. Our approach aims at both efficiency and data quality. We combine custom-developed scripts, standard tools and manual validation by clinical and knowledge experts. We identified key challenges emerging from the several sources of heterogeneity in our case study (systems, language, data structure, clinical domain) and implemented solutions that we will further generalize for the integration of new sites. We conclude that the required effort for data transformation is manageable which supports the feasibility of our semantic interoperability solution. The achieved semantic interoperability will be leveraged for the deployment and evaluation at the clinical site of applications enabling secondary use of care data for research. This work has been funded by the European Commission through the INTEGRATE (FP7-ICT-2009-6-270253) and EURECA (FP7-ICT-2011-288048) projects.

  18. Case Study for Integration of an Oncology Clinical Site in a Semantic Interoperability Solution based on HL7 v3 and SNOMED-CT: Data Transformation Needs

    PubMed Central

    Ibrahim, Ahmed; Bucur, Anca; Perez-Rey, David; Alonso, Enrique; de Hoog, Matthy; Dekker, Andre; Marshall, M. Scott

    2015-01-01

    This paper describes the data transformation pipeline defined to support the integration of a new clinical site in a standards-based semantic interoperability environment. The available datasets combined structured and free-text patient data in Dutch, collected in the context of radiation therapy in several cancer types. Our approach aims at both efficiency and data quality. We combine custom-developed scripts, standard tools and manual validation by clinical and knowledge experts. We identified key challenges emerging from the several sources of heterogeneity in our case study (systems, language, data structure, clinical domain) and implemented solutions that we will further generalize for the integration of new sites. We conclude that the required effort for data transformation is manageable which supports the feasibility of our semantic interoperability solution. The achieved semantic interoperability will be leveraged for the deployment and evaluation at the clinical site of applications enabling secondary use of care data for research. This work has been funded by the European Commission through the INTEGRATE (FP7-ICT-2009-6-270253) and EURECA (FP7-ICT-2011-288048) projects. PMID:26306242

  19. Geo-Semantic Framework for Integrating Long-Tail Data and Model Resources for Advancing Earth System Science

    NASA Astrophysics Data System (ADS)

    Elag, M.; Kumar, P.

    2014-12-01

    Often, scientists and small research groups collect data, which target to address issues and have limited geographic or temporal range. A large number of such collections together constitute a large database that is of immense value to Earth Science studies. Complexity of integrating these data include heterogeneity in dimensions, coordinate systems, scales, variables, providers, users and contexts. They have been defined as long-tail data. Similarly, we use "long-tail models" to characterize a heterogeneous collection of models and/or modules developed for targeted problems by individuals and small groups, which together provide a large valuable collection. Complexity of integrating across these models include differing variable names and units for the same concept, model runs at different time steps and spatial resolution, use of differing naming and reference conventions, etc. Ability to "integrate long-tail models and data" will provide an opportunity for the interoperability and reusability of communities' resources, where not only models can be combined in a workflow, but each model will be able to discover and (re)use data in application specific context of space, time and questions. This capability is essential to represent, understand, predict, and manage heterogeneous and interconnected processes and activities by harnessing the complex, heterogeneous, and extensive set of distributed resources. Because of the staggering production rate of long-tail models and data resulting from the advances in computational, sensing, and information technologies, an important challenge arises: how can geoinformatics bring together these resources seamlessly, given the inherent complexity among model and data resources that span across various domains. We will present a semantic-based framework to support integration of "long-tail" models and data. This builds on existing technologies including: (i) SEAD (Sustainable Environmental Actionable Data) which supports curation

  20. An Integrated Assessment of Progress in Robotic Perception and Semantic Navigation

    DTIC Science & Technology

    2015-09-01

    can work. This requires the integration of fundamental and applied research in perception, artificial intelligence , and human-robot interaction. In...Proceedings of the 29th AAAI Conference on Artificial Intelligence ; 2015 Jan 25–30; Austin, TX. Palo Alto (CA): Association for the Advancement of Artificial ...platform, including the sensors and computational power that support the intelligence architecture. Next is the perceptual system, which identifies

  1. The Role of Semantics in Open-World, Integrative, Collaborative Science Data Platforms

    NASA Astrophysics Data System (ADS)

    Fox, Peter; Chen, Yanning; Wang, Han; West, Patrick; Erickson, John; Ma, Marshall

    2014-05-01

    As collaborative science spreads into more and more Earth and space science fields, both participants and funders are expressing stronger needs for highly functional data and information capabilities. Characteristics include a) easy to use, b) highly integrated, c) leverage investments, d) accommodate rapid technical change, and e) do not incur undue expense or time to build or maintain - these are not a small set of requirements. Based on our accumulated experience over the last ~ decade and several key technical approaches, we adapt, extend, and integrate several open source applications and frameworks to handle major portions of functionality for these platforms. This includes: an object-type repository, collaboration tools, identity management, all within a portal managing diverse content and applications. In this contribution, we present our methods and results of information models, adaptation, integration and evolution of a networked data science architecture based on several open source technologies (Drupal, VIVO, the Comprehensive Knowledge Archive Network; CKAN, and the Global Handle System; GHS). In particular we present the Deep Carbon Observatory - a platform for international science collaboration. We present and discuss key functional and non-functional attributes, and discuss the general applicability of the platform.

  2. Automatic Sleep Scoring Based on Modular Rule-Based Reasoning Units and Signal Processing Units

    DTIC Science & Technology

    2007-11-02

    scoring, rule-based reasoning, multi-staged I. INTRODUCTION Integrated analysis on the state of sleep through Polysomnography is crucial for...diagnosis for sleep related disease. But conventional analog-type Polysomnography systems need tremendous amount of papers and much labor of trained expert...In this sense to equip digital Polysomnography and its following automatic analysis system became trend. In the sleep analysis, sleep stage scoring is

  3. Integrating the automatic and the controlled: strategies in semantic priming in an attractor network with latching dynamics.

    PubMed

    Lerner, Itamar; Bentin, Shlomo; Shriki, Oren

    2014-01-01

    Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category-exemplar, mediated and backward prime-target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model.

  4. The Enterprise Data Trust at Mayo Clinic: a semantically integrated warehouse of biomedical data.

    PubMed

    Chute, Christopher G; Beck, Scott A; Fisk, Thomas B; Mohr, David N

    2010-01-01

    Mayo Clinic's Enterprise Data Trust is a collection of data from patient care, education, research, and administrative transactional systems, organized to support information retrieval, business intelligence, and high-level decision making. Structurally it is a top-down, subject-oriented, integrated, time-variant, and non-volatile collection of data in support of Mayo Clinic's analytic and decision-making processes. It is an interconnected piece of Mayo Clinic's Enterprise Information Management initiative, which also includes Data Governance, Enterprise Data Modeling, the Enterprise Vocabulary System, and Metadata Management. These resources enable unprecedented organization of enterprise information about patient, genomic, and research data. While facile access for cohort definition or aggregate retrieval is supported, a high level of security, retrieval audit, and user authentication ensures privacy, confidentiality, and respect for the trust imparted by our patients for the respectful use of information about their conditions.

  5. Semantic Bim and GIS Modelling for Energy-Efficient Buildings Integrated in a Healthcare District

    NASA Astrophysics Data System (ADS)

    Sebastian, R.; Böhms, H. M.; Bonsma, P.; van den Helm, P. W.

    2013-09-01

    The subject of energy-efficient buildings (EeB) is among the most urgent research priorities in the European Union (EU). In order to achieve the broadest impact, innovative approaches to EeB need to resolve challenges at the neighbourhood level, instead of only focusing on improvements of individual buildings. For this purpose, the design phase of new building projects as well as building retrofitting projects is the crucial moment for integrating multi-scale EeB solutions. In EeB design process, clients, architects, technical designers, contractors, and end-users altogether need new methods and tools for designing energy-efficiency buildings integrated in their neighbourhoods. Since the scope of designing covers multiple dimensions, the new design methodology relies on the inter-operability between Building Information Modelling (BIM) and Geospatial Information Systems (GIS). Design for EeB optimisation needs to put attention on the inter-connections between the architectural systems and the MEP/HVAC systems, as well as on the relation of Product Lifecycle Modelling (PLM), Building Management Systems (BMS), BIM and GIS. This paper is descriptive and it presents an actual EU FP7 large-scale collaborative research project titled STREAMER. The research on the inter-operability between BIM and GIS for holistic design of energy-efficient buildings in neighbourhood scale is supported by real case studies of mixed-use healthcare districts. The new design methodology encompasses all scales and all lifecycle phases of the built environment, as well as the whole lifecycle of the information models that comprises: Building Information Model (BIM), Building Assembly Model (BAM), Building Energy Model (BEM), and Building Operation Optimisation Model (BOOM).

  6. Semantic Web Research Trends and Directions

    DTIC Science & Technology

    2006-01-01

    social trust on the semantic web that builds upon the previous work to create end user applications that benefit from the semantic foundation. 2 Swoop...security, authentication, and privacy. However, the social component of trust is one that is both important and ideally suited for the Semantic Web. When the...Semantic Web-based social networks are augmented with trust information, it is possible to make computations over the values, and integrate the

  7. Fuzzy rule-based models for decision support in ecosystem management.

    PubMed

    Adriaenssens, Veronique; De Baets, Bernard; Goethals, Peter L M; De Pauw, Niels

    2004-02-05

    To facilitate decision support in the ecosystem management, ecological expertise and site-specific data need to be integrated. Fuzzy logic can deal with highly variable, linguistic, vague and uncertain data or knowledge and, therefore, has the ability to allow for a logical, reliable and transparent information stream from data collection down to data usage in decision-making. Several environmental applications already implicate the use of fuzzy logic. Most of these applications have been set up by trial and error and are mainly limited to the domain of environmental assessment. In this article, applications of fuzzy logic for decision support in ecosystem management are reviewed and assessed, with an emphasis on rule-based models. In particular, the identification, optimisation, validation, the interpretability and uncertainty aspects of fuzzy rule-based models for decision support in ecosystem management are discussed.

  8. Semantic Data Integration and Ontology Use within the Global Earth Observation System of Systems (GEOSS) Global Water Cycle Data Integration System

    NASA Astrophysics Data System (ADS)

    Pozzi, W.; Fekete, B.; Piasecki, M.; McGuinness, D.; Fox, P.; Lawford, R.; Vorosmarty, C.; Houser, P.; Imam, B.

    2008-12-01

    The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so

  9. A Semantic Rule-Based Framework for Efficient Retrieval of Educational Materials

    ERIC Educational Resources Information Center

    Mahmoudi, Maryam Tayefeh; Taghiyareh, Fattaneh; Badie, Kambiz

    2013-01-01

    Retrieving resources in an appropriate manner has a promising role in increasing the performance of educational support systems. A variety of works have been done to organize materials for educational purposes using tagging techniques. Despite the effectiveness of these techniques within certain domains, organizing resources in a way being…

  10. Context-Based Semantic Annotations in CoPEs: An Ontological and Rule-Based Approach

    ERIC Educational Resources Information Center

    Boudebza, Souâad; Berkani, Lamia; Azouaou, Faiçal

    2013-01-01

    Knowledge capitalization is one of many problems facing online communities of practice (CoPs). Knowledge accumulated through the participation in the community must be capitalized for future reuse. Most of proposals are specific and focus on knowledge modeling disregarding the reuse of that knowledge. In this paper, we are particularly interested…

  11. Optimal Test Design with Rule-Based Item Generation

    ERIC Educational Resources Information Center

    Geerlings, Hanneke; van der Linden, Wim J.; Glas, Cees A. W.

    2013-01-01

    Optimal test-design methods are applied to rule-based item generation. Three different cases of automated test design are presented: (a) test assembly from a pool of pregenerated, calibrated items; (b) test generation on the fly from a pool of calibrated item families; and (c) test generation on the fly directly from calibrated features defining…

  12. Rule-Based Category Learning in Down Syndrome

    ERIC Educational Resources Information Center

    Phillips, B. Allyson; Conners, Frances A.; Merrill, Edward; Klinger, Mark R.

    2014-01-01

    Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III (Woodcock, McGrew, & Mather, 2001). In regression-based…

  13. Rule based fuzzy logic approach for classification of fibromyalgia syndrome.

    PubMed

    Arslan, Evren; Yildiz, Sedat; Albayrak, Yalcin; Koklukaya, Etem

    2016-06-01

    Fibromyalgia syndrome (FMS) is a chronic muscle and skeletal system disease observed generally in women, manifesting itself with a widespread pain and impairing the individual's quality of life. FMS diagnosis is made based on the American College of Rheumatology (ACR) criteria. However, recently the employability and sufficiency of ACR criteria are under debate. In this context, several evaluation methods, including clinical evaluation methods were proposed by researchers. Accordingly, ACR had to update their criteria announced back in 1990, 2010 and 2011. Proposed rule based fuzzy logic method aims to evaluate FMS at a different angle as well. This method contains a rule base derived from the 1990 ACR criteria and the individual experiences of specialists. The study was conducted using the data collected from 60 inpatient and 30 healthy volunteers. Several tests and physical examination were administered to the participants. The fuzzy logic rule base was structured using the parameters of tender point count, chronic widespread pain period, pain severity, fatigue severity and sleep disturbance level, which were deemed important in FMS diagnosis. It has been observed that generally fuzzy predictor was 95.56 % consistent with at least of the specialists, who are not a creator of the fuzzy rule base. Thus, in diagnosis classification where the severity of FMS was classified as well, consistent findings were obtained from the comparison of interpretations and experiences of specialists and the fuzzy logic approach. The study proposes a rule base, which could eliminate the shortcomings of 1990 ACR criteria during the FMS evaluation process. Furthermore, the proposed method presents a classification on the severity of the disease, which was not available with the ACR criteria. The study was not limited to only disease classification but at the same time the probability of occurrence and severity was classified. In addition, those who were not suffering from FMS were

  14. Reading Development Electrified: Semantic and Syntactic Integration during Sentence Comprehension in School-Age Children and Young Adults

    ERIC Educational Resources Information Center

    VanDyke, Justine M.

    2011-01-01

    Adults are able to access semantic and syntactic information rapidly as they hear or read in real-time in order to interpret sentences. Young children, on the other hand, tend to rely on syntactically-based parsing routines, adopting the first noun as the agent of a sentence regardless of plausibility, at least during oral comprehension. Little is…

  15. Benefits and Costs of Lexical Decomposition and Semantic Integration during the Processing of Transparent and Opaque English Compounds

    ERIC Educational Resources Information Center

    Ji, Hongbo; Gagne, Christina L.; Spalding, Thomas L.

    2011-01-01

    Six lexical decision experiments were conducted to examine the influence of complex structure on the processing speed of English compounds. All experiments revealed that semantically transparent compounds (e.g., "rosebud") were processed more quickly than matched monomorphemic words (e.g., "giraffe"). Opaque compounds (e.g., "hogwash") were also…

  16. Using Eye Tracking to Investigate Semantic and Spatial Representations of Scientific Diagrams during Text-Diagram Integration

    ERIC Educational Resources Information Center

    Jian, Yu-Cin; Wu, Chao-Jung

    2015-01-01

    We investigated strategies used by readers when reading a science article with a diagram and assessed whether semantic and spatial representations were constructed while reading the diagram. Seventy-one undergraduate participants read a scientific article while tracking their eye movements and then completed a reading comprehension test. Our…

  17. SSWAP: A Simple Semantic Web Architecture and Protocol for Semantic Web Services

    Technology Transfer Automated Retrieval System (TEKTRAN)

    SSWAP (Simple Semantic Web Architecture and Protocol) is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP is the driving technology behind the Virtual Plant Information Network, an NSF-funded semantic w...

  18. Individual differences in the joint effects of semantic priming and word frequency: The role of lexical integrity

    PubMed Central

    Yap, Melvin J.; Tse, Chi-Shing; Balota, David A.

    2009-01-01

    Word frequency and semantic priming effects are among the most robust effects in visual word recognition, and it has been generally assumed that these two variables produce interactive effects in lexical decision performance, with larger priming effects for low-frequency targets. The results from four lexical decision experiments indicate that the joint effects of semantic priming and word frequency are critically dependent upon differences in the vocabulary knowledge of the participants. Specifically, across two Universities, additive effects of the two variables were observed in participants with more vocabulary knowledge, while interactive effects were observed in participants with less vocabulary knowledge. These results are discussed with reference to Borowsky and Besner’s (1993) multistage account and Plaut and Booth’s (2000) single-mechanism model. In general, the findings are also consistent with a flexible lexical processing system that optimizes performance based on processing fluency and task demands. PMID:20161653

  19. Automated rule-base creation via CLIPS-Induce

    NASA Technical Reports Server (NTRS)

    Murphy, Patrick M.

    1994-01-01

    Many CLIPS rule-bases contain one or more rule groups that perform classification. In this paper we describe CLIPS-Induce, an automated system for the creation of a CLIPS classification rule-base from a set of test cases. CLIPS-Induce consists of two components, a decision tree induction component and a CLIPS production extraction component. ID3, a popular decision tree induction algorithm, is used to induce a decision tree from the test cases. CLIPS production extraction is accomplished through a top-down traversal of the decision tree. Nodes of the tree are used to construct query rules, and branches of the tree are used to construct classification rules. The learned CLIPS productions may easily be incorporated into a large CLIPS system that perform tasks such as accessing a database or displaying information.

  20. Guidelines for visualizing and annotating rule-based models†

    PubMed Central

    Chylek, Lily A.; Hu, Bin; Blinov, Michael L.; Emonet, Thierry; Faeder, James R.; Goldstein, Byron; Gutenkunst, Ryan N.; Haugh, Jason M.; Lipniacki, Tomasz; Posner, Richard G.; Yang, Jin; Hlavacek, William S.

    2011-01-01

    Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models. PMID:21647530

  1. An approach to articulating expert system rule bases

    NASA Technical Reports Server (NTRS)

    Abernethy, Ken

    1988-01-01

    A rule-base generation procedure is developed for expert systems used to diagnose anomalies in the performance of mechanical plants and similar engineering systems. The method is based on construction of a failure-mode information-propagation model (FIPM). Details of the FIPM procedure are discussed and illustrated with diagrams; reference is made to a sample application involving the turbopump of the high-pressure oxidizer for the Space Shuttle main engine.

  2. Index : A Rule Based Expert System For Computer Network Maintenance

    NASA Astrophysics Data System (ADS)

    Chaganty, Srinivas; Pitchai, Anandhi; Morgan, Thomas W.

    1988-03-01

    Communications is an expert intensive discipline. The application of expert systems for maintenance of large and complex networks, mainly as an aid in trouble shooting, can simplify the task of network management. The important steps involved in troubleshooting are fault detection, fault reporting, fault interpretation and fault isolation. At present, Network Maintenance Facilities are capable of detecting and reporting the faults to network personnel. Fault interpretation refers to the next step in the process, which involves coming up with reasons for the failure. Fault interpretation can be characterized in two ways. First, it involves such a diversity of facts that it is difficult to predict. Secondly, it embodies a wealth of knowledge in the form of network management personnel. The application of expert systems in these interpretive tasks is an important step towards automation of network maintenance. In this paper, INDEX (Intelligent Network Diagnosis Expediter), a rule based production system for computer network alarm interpretation is described. It acts as an intelligent filter for people analyzing network alarms. INDEX analyzes the alarms in the network and identifies proper maintenance action to be taken.The important feature of this production system is that it is data driven. Working memory is the principal data repository of production systems and its contents represent the current state of the problem. Control is based upon which productions match the constantly changing working memory elements. Implementation of the prototype is in OPS83. Major issues in rule based system development such as rule base organization, implementation and efficiency are discussed.

  3. SemanticOrganizer Brings Teams Together

    NASA Technical Reports Server (NTRS)

    Laufenberg, Lawrence

    2003-01-01

    SemanticOrganizer enables researchers in different locations to share, search for, and integrate data. Its customizable semantic links offer fast access to interrelated information. This knowledge management and information integration tool also supports real-time instrument data collection and collaborative image annotation.

  4. Fuzzylot: a novel self-organising fuzzy-neural rule-based pilot system for automated vehicles.

    PubMed

    Pasquier, M; Quek, C; Toh, M

    2001-10-01

    This paper presents part of our research work concerned with the realisation of an Intelligent Vehicle and the technologies required for its routing, navigation, and control. An automated driver prototype has been developed using a self-organising fuzzy rule-based system (POPFNN-CRI(S)) to model and subsequently emulate human driving expertise. The ability of fuzzy logic to represent vague information using linguistic variables makes it a powerful tool to develop rule-based control systems when an exact working model is not available, as is the case of any vehicle-driving task. Designing a fuzzy system, however, is a complex endeavour, due to the need to define the variables and their associated fuzzy sets, and determine a suitable rule base. Many efforts have thus been devoted to automating this process, yielding the development of learning and optimisation techniques. One of them is the family of POP-FNNs, or Pseudo-Outer Product Fuzzy Neural Networks (TVR, AARS(S), AARS(NS), CRI, Yager). These generic self-organising neural networks developed at the Intelligent Systems Laboratory (ISL/NTU) are based on formal fuzzy mathematical theory and are able to objectively extract a fuzzy rule base from training data. In this application, a driving simulator has been developed, that integrates a detailed model of the car dynamics, complete with engine characteristics and environmental parameters, and an OpenGL-based 3D-simulation interface coupled with driving wheel and accelerator/ brake pedals. The simulator has been used on various road scenarios to record from a human pilot driving data consisting of steering and speed control actions associated to road features. Specifically, the POPFNN-CRI(S) system is used to cluster the data and extract a fuzzy rule base modelling the human driving behaviour. Finally, the effectiveness of the generated rule base has been validated using the simulator in autopilot mode.

  5. Generative Semantics

    ERIC Educational Resources Information Center

    Bagha, Karim Nazari

    2011-01-01

    Generative semantics is (or perhaps was) a research program within linguistics, initiated by the work of George Lakoff, John R. Ross, Paul Postal and later McCawley. The approach developed out of transformational generative grammar in the mid 1960s, but stood largely in opposition to work by Noam Chomsky and his students. The nature and genesis of…

  6. Simulation of large-scale rule-based models

    SciTech Connect

    Hlavacek, William S; Monnie, Michael I; Colvin, Joshua; Faseder, James

    2008-01-01

    Interactions of molecules, such as signaling proteins, with multiple binding sites and/or multiple sites of post-translational covalent modification can be modeled using reaction rules. Rules comprehensively, but implicitly, define the individual chemical species and reactions that molecular interactions can potentially generate. Although rules can be automatically processed to define a biochemical reaction network, the network implied by a set of rules is often too large to generate completely or to simulate using conventional procedures. To address this problem, we present DYNSTOC, a general-purpose tool for simulating rule-based models. DYNSTOC implements a null-event algorithm for simulating chemical reactions in a homogenous reaction compartment. The simulation method does not require that a reaction network be specified explicitly in advance, but rather takes advantage of the availability of the reaction rules in a rule-based specification of a network to determine if a randomly selected set of molecular components participates in a reaction during a time step. DYNSTOC reads reaction rules written in the BioNetGen language which is useful for modeling protein-protein interactions involved in signal transduction. The method of DYNSTOC is closely related to that of STOCHSIM. DYNSTOC differs from STOCHSIM by allowing for model specification in terms of BNGL, which extends the range of protein complexes that can be considered in a model. DYNSTOC enables the simulation of rule-based models that cannot be simulated by conventional methods. We demonstrate the ability of DYNSTOC to simulate models accounting for multisite phosphorylation and multivalent binding processes that are characterized by large numbers of reactions. DYNSTOC is free for non-commercial use. The C source code, supporting documentation and example input files are available at .

  7. Connecting clinical and actuarial prediction with rule-based methods.

    PubMed

    Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

    2015-06-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods.

  8. Rule-based navigation control design for autonomous flight

    NASA Astrophysics Data System (ADS)

    Contreras, Hugo; Bassi, Danilo

    2008-04-01

    This article depicts a navigation control system design that is based on a set of rules in order to follow a desired trajectory. The full control of the aircraft considered here comprises: a low level stability control loop, based on classic PID controller and the higher level navigation whose main job is to exercise lateral control (course) and altitude control, trying to follow a desired trajectory. The rules and PID gains were adjusted systematically according to the result of flight simulation. In spite of its simplicity, the rule-based navigation control proved to be robust, even with big perturbation, like crossing winds.

  9. Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines

    PubMed Central

    2010-01-01

    Background Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs. The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase. Methods A framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA). Results The applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows. Conclusions The framework is an

  10. g.infer: A GRASS GIS module for rule-based data-driven classification and workflow control.

    NASA Astrophysics Data System (ADS)

    Löwe, Peter

    2013-04-01

    This poster describes the internal architecture of the new GRASS GIS module g.infer [1] and demonstrates application scenarios . The new module for GRASS GIS Version 6.x and 7.x enables rule-based analysis and workflow management via data-driven inference processes based on the C Language Integrated Production System (CLIPS) [2]. g.infer uses the pyClips module [3] to provide an Python-based environment for CLIPS within the GRASS GIS environment for rule-based knowledge engineering. Application scenarios range from rule-based classification tasks, event-driven workflow-control to complex simulations for tasks such as Soil Erosion Monitoring and Disaster Early Warning [4]. References: [1] Löwe P.: Introducing the new GRASS module g.infer for data-driven rule-based applications, Vol.8 2012-08, Geoinformatics FCE CTU, ISSN 1802-2669 [2] http://clipsrules.sourceforge.net/ [3] http://pyclips.sourceforge.net/web/ [4] Löwe P.: A Spatial Decision Support System for Radar-metereology Data in South Africa, Transactions in GIS 2004, (2): 235-244

  11. Rule Based Category Learning in Patients with Parkinson’s Disease

    PubMed Central

    Price, Amanda; Filoteo, J. Vincent; Maddox, W. Todd

    2009-01-01

    Measures of explicit rule-based category learning are commonly used in neuropsychological evaluation of individuals with Parkinson’s disease (PD) and the pattern of PD performance on these measures tends to be highly varied. We review the neuropsychological literature to clarify the manner in which PD affects the component processes of rule-based category learning and work to identify and resolve discrepancies within this literature. In particular, we address the manner in which PD and its common treatments affect the processes of rule generation, maintenance, shifting and selection. We then integrate the neuropsychological research with relevant neuroimaging and computational modeling evidence to clarify the neurobiological impact of PD on each process. Current evidence indicates that neurochemical changes associated with PD primarily disrupt rule shifting, and may disturb feedback-mediated learning processes that guide rule selection. Although surgical and pharmacological therapies remediate this deficit, it appears that the same treatments may contribute to impaired rule generation, maintenance and selection processes. These data emphasize the importance of distinguishing between the impact of PD and its common treatments when considering the neuropsychological profile of the disease. PMID:19428385

  12. Rule-based topology system for spatial databases to validate complex geographic datasets

    NASA Astrophysics Data System (ADS)

    Martinez-Llario, J.; Coll, E.; Núñez-Andrés, M.; Femenia-Ribera, C.

    2017-06-01

    A rule-based topology software system providing a highly flexible and fast procedure to enforce integrity in spatial relationships among datasets is presented. This improved topology rule system is built over the spatial extension Jaspa. Both projects are open source, freely available software developed by the corresponding author of this paper. Currently, there is no spatial DBMS that implements a rule-based topology engine (considering that the topology rules are designed and performed in the spatial backend). If the topology rules are applied in the frontend (as in many GIS desktop programs), ArcGIS is the most advanced solution. The system presented in this paper has several major advantages over the ArcGIS approach: it can be extended with new topology rules, it has a much wider set of rules, and it can mix feature attributes with topology rules as filters. In addition, the topology rule system can work with various DBMSs, including PostgreSQL, H2 or Oracle, and the logic is performed in the spatial backend. The proposed topology system allows users to check the complex spatial relationships among features (from one or several spatial layers) that require some complex cartographic datasets, such as the data specifications proposed by INSPIRE in Europe and the Land Administration Domain Model (LADM) for Cadastral data.

  13. Assessing flood vulnerability using a rule-based fuzzy system.

    PubMed

    Yazdi, J; Neyshabouri, S A A S

    2012-01-01

    Population growth and urbanization in the last decades have increased the vulnerability of properties and societies in flood-prone areas. Vulnerability analysis is one of the main factors used to determine the necessary measures of flood risk reduction in floodplains. At present, the vulnerability of natural disasters is analyzed by defining the various physical and social indices. This study presents a model based on a fuzzy rule-based system to address various ambiguities and uncertainties from natural variability, and human knowledge and preferences in vulnerability analysis. The proposed method is applied for a small watershed as a case study and the obtained results are compared with one of the index approaches. Both approaches present the same ranking for the sub-basin's vulnerability in the watershed. Finally, using the scores of vulnerability in different sub-basins, a vulnerability map of the watershed is presented.

  14. A high-level language for rule-based modelling.

    PubMed

    Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D

    2015-01-01

    Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

  15. Rule based design of conceptual models for formative evaluation

    NASA Technical Reports Server (NTRS)

    Moore, Loretta A.; Chang, Kai; Hale, Joseph P.; Bester, Terri; Rix, Thomas; Wang, Yaowen

    1994-01-01

    A Human-Computer Interface (HCI) Prototyping Environment with embedded evaluation capability has been investigated. This environment will be valuable in developing and refining HCI standards and evaluating program/project interface development, especially Space Station Freedom on-board displays for payload operations. This environment, which allows for rapid prototyping and evaluation of graphical interfaces, includes the following four components: (1) a HCI development tool; (2) a low fidelity simulator development tool; (3) a dynamic, interactive interface between the HCI and the simulator; and (4) an embedded evaluator that evaluates the adequacy of a HCI based on a user's performance. The embedded evaluation tool collects data while the user is interacting with the system and evaluates the adequacy of an interface based on a user's performance. This paper describes the design of conceptual models for the embedded evaluation system using a rule-based approach.

  16. Approaches to the verification of rule-based expert systems

    NASA Technical Reports Server (NTRS)

    Culbert, Chris; Riley, Gary; Savely, Robert T.

    1987-01-01

    Expert systems are a highly useful spinoff of artificial intelligence research. One major stumbling block to extended use of expert systems is the lack of well-defined verification and validation (V and V) methodologies. Since expert systems are computer programs, the definitions of verification and validation from conventional software are applicable. The primary difficulty with expert systems is the use of development methodologies which do not support effective V and V. If proper techniques are used to document requirements, V and V of rule-based expert systems is possible, and may be easier than with conventional code. For NASA applications, the flight technique panels used in previous programs should provide an excellent way to verify the rules used in expert systems. There are, however, some inherent differences in expert systems that will affect V and V considerations.

  17. Rule-based category learning in Down syndrome.

    PubMed

    Phillips, B Allyson; Conners, Frances A; Merrill, Edward; Klinger, Mark R

    2014-05-01

    Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III ( Woodock, McGrew, & Mather, 2001 ). In regression-based analyses, DS and ID groups performed below the level expected for their nonverbal ability. In cross-sectional developmental trajectory analyses, results depended on the task. On the MCST, the DS and ID groups were similar to the TD group. On the Concept Formation test, the DS group had slower cross-sectional change than the other 2 groups. Category learning may be an area of difficulty for those with ID, but task-related factors may affect trajectories for youths with DS.

  18. A Rule-Based Industrial Boiler Selection System

    NASA Astrophysics Data System (ADS)

    Tan, C. F.; Khalil, S. N.; Karjanto, J.; Tee, B. T.; Wahidin, L. S.; Chen, W.; Rauterberg, G. W. M.; Sivarao, S.; Lim, T. L.

    2015-09-01

    Boiler is a device used for generating the steam for power generation, process use or heating, and hot water for heating purposes. Steam boiler consists of the containing vessel and convection heating surfaces only, whereas a steam generator covers the whole unit, encompassing water wall tubes, super heaters, air heaters and economizers. The selection of the boiler is very important to the industry for conducting the operation system successfully. The selection criteria are based on rule based expert system and multi-criteria weighted average method. The developed system consists of Knowledge Acquisition Module, Boiler Selection Module, User Interface Module and Help Module. The system capable of selecting the suitable boiler based on criteria weighted. The main benefits from using the system is to reduce the complexity in the decision making for selecting the most appropriate boiler to palm oil process plant.

  19. Rule based design of conceptual models for formative evaluation

    NASA Technical Reports Server (NTRS)

    Moore, Loretta A.; Chang, Kai; Hale, Joseph P.; Bester, Terri; Rix, Thomas; Wang, Yaowen

    1994-01-01

    A Human-Computer Interface (HCI) Prototyping Environment with embedded evaluation capability has been investigated. This environment will be valuable in developing and refining HCI standards and evaluating program/project interface development, especially Space Station Freedom on-board displays for payload operations. This environment, which allows for rapid prototyping and evaluation of graphical interfaces, includes the following four components: (1) a HCI development tool, (2) a low fidelity simulator development tool, (3) a dynamic, interactive interface between the HCI and the simulator, and (4) an embedded evaluator that evaluates the adequacy of a HCI based on a user's performance. The embedded evaluation tool collects data while the user is interacting with the system and evaluates the adequacy of an interface based on a user's performance. This paper describes the design of conceptual models for the embedded evaluation system using a rule-based approach.

  20. Genetic learning in rule-based and neural systems

    NASA Technical Reports Server (NTRS)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  1. Fuzzy-rule-based image reconstruction for positron emission tomography

    NASA Astrophysics Data System (ADS)

    Mondal, Partha P.; Rajan, K.

    2005-09-01

    Positron emission tomography (PET) and single-photon emission computed tomography have revolutionized the field of medicine and biology. Penalized iterative algorithms based on maximum a posteriori (MAP) estimation eliminate noisy artifacts by utilizing available prior information in the reconstruction process but often result in a blurring effect. MAP-based algorithms fail to determine the density class in the reconstructed image and hence penalize the pixels irrespective of the density class. Reconstruction with better edge information is often difficult because prior knowledge is not taken into account. The recently introduced median-root-prior (MRP)-based algorithm preserves the edges, but a steplike streaking effect is observed in the reconstructed image, which is undesirable. A fuzzy approach is proposed for modeling the nature of interpixel interaction in order to build an artifact-free edge-preserving reconstruction. The proposed algorithm consists of two elementary steps: (1) edge detection, in which fuzzy-rule-based derivatives are used for the detection of edges in the nearest neighborhood window (which is equivalent to recognizing nearby density classes), and (2) fuzzy smoothing, in which penalization is performed only for those pixels for which no edge is detected in the nearest neighborhood. Both of these operations are carried out iteratively until the image converges. Analysis shows that the proposed fuzzy-rule-based reconstruction algorithm is capable of producing qualitatively better reconstructed images than those reconstructed by MAP and MRP algorithms. The reconstructed images are sharper, with small features being better resolved owing to the nature of the fuzzy potential function.

  2. Rule-Based Orientation Recognition Of A Moving Object

    NASA Astrophysics Data System (ADS)

    Gove, Robert J.

    1989-03-01

    This paper presents a detailed description and a comparative analysis of the algorithms used to determine the position and orientation of an object in real-time. The exemplary object, a freely moving gold-fish in an aquarium, provides "real-world" motion, with definable characteristics of motion (the fish never swims upside-down) and the complexities of a non-rigid body. For simplicity of implementation, and since a restricted and stationary viewing domain exists (fish-tank), we reduced the problem of obtaining 3D correspondence information to trivial alignment calculations by using two cameras orthogonally viewing the object. We applied symbolic processing techniques to recognize the 3-D orientation of a moving object of known identity in real-time. Assuming motion, each new frame (sensed by the two cameras) provides images of the object's profile which has most likely undergone translation, rotation, scaling and/or bending of the non-rigid object since the previous frame. We developed an expert system which uses heuristics of the object's motion behavior in the form of rules and information obtained via low-level image processing (like numerical inertial axis calculations) to dynamically estimate the object's orientation. An inference engine provides these estimates at frame rates of up to 10 per second (which is essentially real-time). The advantages of the rule-based approach to orientation recognition will be compared other pattern recognition techniques. Our results of an investigation of statistical pattern recognition, neural networks, and procedural techniques for orientation recognition will be included. We implemented the algorithms in a rapid-prototyping environment, the TI-Ezplorer, equipped with an Odyssey and custom imaging hardware. A brief overview of the workstation is included to clarify one motivation for our choice of algorithms. These algorithms exploit two facets of the prototype image processing and understanding workstation - both low

  3. Timescale analysis of rule-based biochemical reaction networks

    PubMed Central

    Klinke, David J.; Finley, Stacey D.

    2012-01-01

    The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed upon reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of Interleukin-12 (IL-12) signaling in näive CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based upon the available data. The analysis correctly predicted that reactions associated with JAK2 and TYK2 binding to their corresponding receptor exist at a pseudo-equilibrium. In contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. PMID:21954150

  4. Semantically aided interpretation and querying of Jefferson Project data using the SemantEco framework

    NASA Astrophysics Data System (ADS)

    Patton, E. W.; Pinheiro, P.; McGuinness, D. L.

    2014-12-01

    We will describe the benefits we realized using semantic technologies to address the often challenging and resource intensive task of ontology alignment in service of data integration. Ontology alignment became relatively simple as we reused our existing semantic data integration framework, SemantEco. We work in the context of the Jefferson Project (JP), an effort to monitor and predict the health of Lake George in NY by deploying a large-scale sensor network in the lake, and analyzing the high-resolution sensor data. SemantEco is an open-source framework for building semantically-aware applications to assist users, particularly non-experts, in exploration and interpretation of integrated scientific data. SemantEco applications are composed of a set of modules that incorporate new datasets, extend the semantic capabilities of the system to integrate and reason about data, and provide facets for extending or controlling semantic queries. Whereas earlier SemantEco work focused on integration of water, air, and species data from government sources, we focus on redeploying it to provide a provenance-aware, semantic query and interpretation interface for JP's sensor data. By employing a minor alignment between SemantEco's ontology and the Human-Aware Sensor Network Ontology used to model the JP's sensor deployments, we were able to bring SemantEco's capabilities to bear on the JP sensor data and metadata. This alignment enabled SemantEco to perform the following tasks: (1) select JP datasets related to water quality; (2) understand how the JP's notion of water quality relates to water quality concepts in previous work; and (3) reuse existing SemantEco interactive data facets, e.g. maps and time series visualizations, and modules, e.g. the regulation module that interprets water quality data through the lens of various federal and state regulations. Semantic technologies, both as the engine driving SemantEco and the means of modeling the JP data, enabled us to rapidly

  5. A rule-based expert system for generating control displays at the Advanced Photon Source

    SciTech Connect

    Coulter, K.J.

    1993-11-01

    The integration of a rule-based expert system for generating screen displays for controlling and monitoring instrumentation under the Experimental Physics and Industrial Control System (EPICS) is presented. The expert system is implemented using CLIPS, an expert system shell from the Software Technology Branch at Lyndon B. Johnson Space Center. The user selects the hardware input and output to be displayed and the expert system constructs a graphical control screen appropriate for the data. Such a system provides a method for implementing a common look and feel for displays created by several different users and reduces the amount of time required to create displays for new hardware configurations. Users are able to modify the displays as needed using the EPICS display editor tool.

  6. Preserved Musical Semantic Memory in Semantic Dementia

    PubMed Central

    Weinstein, Jessica; Koenig, Phyllis; Gunawardena, Delani; McMillan, Corey; Bonner, Michael; Grossman, Murray

    2012-01-01

    Objective To understand the scope of semantic impairment in semantic dementia. Design Case study. Setting Academic medical center. Patient A man with semantic dementia, as demonstrated by clinical, neuropsychological, and imaging studies. Main Outcome Measures Music performance and magnetic resonance imaging results. Results Despite profoundly impaired semantic memory for words and objects due to left temporal lobe atrophy, this semiprofessional musician was creative and expressive in demonstrating preserved musical knowledge. Conclusion Long-term representations of words and objects in semantic memory may be dissociated from meaningful knowledge in other domains, such as music. PMID:21320991

  7. On Decision-Making Among Multiple Rule-Bases in Fuzzy Control Systems

    NASA Technical Reports Server (NTRS)

    Tunstel, Edward; Jamshidi, Mo

    1997-01-01

    Intelligent control of complex multi-variable systems can be a challenge for single fuzzy rule-based controllers. This class of problems cam often be managed with less difficulty by distributing intelligent decision-making amongst a collection of rule-bases. Such an approach requires that a mechanism be chosen to ensure goal-oriented interaction between the multiple rule-bases. In this paper, a hierarchical rule-based approach is described. Decision-making mechanisms based on generalized concepts from single-rule-based fuzzy control are described. Finally, the effects of different aggregation operators on multi-rule-base decision-making are examined in a navigation control problem for mobile robots.

  8. The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail

    PubMed Central

    2012-01-01

    Background Signaling systems typically involve large, structured molecules each consisting of a large number of subunits called molecule domains. In modeling such systems these domains can be considered as the main players. In order to handle the resulting combinatorial complexity, rule-based modeling has been established as the tool of choice. In contrast to the detailed quantitative rule-based modeling, qualitative modeling approaches like logical modeling rely solely on the network structure and are particularly useful for analyzing structural and functional properties of signaling systems. Results We introduce the Process-Interaction-Model (PIM) concept. It defines a common representation (or basis) of rule-based models and site-specific logical models, and, furthermore, includes methods to derive models of both types from a given PIM. A PIM is based on directed graphs with nodes representing processes like post-translational modifications or binding processes and edges representing the interactions among processes. The applicability of the concept has been demonstrated by applying it to a model describing EGF insulin crosstalk. A prototypic implementation of the PIM concept has been integrated in the modeling software ProMoT. Conclusions The PIM concept provides a common basis for two modeling formalisms tailored to the study of signaling systems: a quantitative (rule-based) and a qualitative (logical) modeling formalism. Every PIM is a compact specification of a rule-based model and facilitates the systematic set-up of a rule-based model, while at the same time facilitating the automatic generation of a site-specific logical model. Consequently, modifications can be made on the underlying basis and then be propagated into the different model specifications – ensuring consistency of all models, regardless of the modeling formalism. This facilitates the analysis of a system on different levels of detail as it guarantees the application of established

  9. Interleaving Semantic Web Reasoning and Service Discovery to Enforce Context-Sensitive Security and Privacy Policies

    DTIC Science & Technology

    2005-07-01

    Friedman- Hill . Jess in Action: Java Rule-based Systems, Manning Publications Com-pany, June 2003, ISBN 1930110898, http://herzberg.ca.sandia.gov/jess...Semantics Journal, 1(3), 2004. [9] R. Hull, B. Kumar, D. Lieuwen, P. Patel-Schneider, A. Sahuguet, S. Varadarajan, and A. Vyas . Enabling context

  10. A novel rules based approach for estimating software birthmark.

    PubMed

    Nazir, Shah; Shahzad, Sara; Khan, Sher Afzal; Alias, Norma Binti; Anwar, Sajid

    2015-01-01

    Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark.

  11. A Novel Rules Based Approach for Estimating Software Birthmark

    PubMed Central

    Binti Alias, Norma; Anwar, Sajid

    2015-01-01

    Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark. PMID:25945363

  12. A Rules-Based Simulation of Bacterial Turbulence

    NASA Astrophysics Data System (ADS)

    Mikel-Stites, Maxwell; Staples, Anne

    2015-11-01

    In sufficiently dense bacterial populations (>40% bacteria by volume), unusual collective swimming behaviors have been consistently observed, resembling von Karman vortex streets. The source of these collective swimming behavior has yet to be fully determined, and as of yet, no research has been conducted that would define whether or not this behavior is derived predominantly from the properties of the surrounding media, or if it is an emergent behavior as a result of the ``rules'' governing the behavior of individual bacteria. The goal of this research is to ascertain whether or not it is possible to design a simulation that can replicate the qualitative behavior of the densely packed bacterial populations using only behavioral rules to govern the actions of each bacteria, with the physical properties of the media being neglected. The results of the simulation will address whether or not it is possible for the system's overall behavior to be driven exclusively by these rule-based dynamics. In order to examine this, the behavioral simulation was written in MATLAB on a fixed grid, and updated sequentially with the bacterial behavior, including randomized tumbling, gathering and perceptual sub-functions. If the simulation is successful, it will serve as confirmation that it is possible to generate these qualitatively vortex-like behaviors without specific physical media (that the phenomena arises in emergent fashion from behavioral rules), or as evidence that the observed behavior requires some specific set of physical parameters.

  13. Rule-based deduplication of article records from bibliographic databases.

    PubMed

    Jiang, Yu; Lin, Can; Meng, Weiyi; Yu, Clement; Cohen, Aaron M; Smalheiser, Neil R

    2014-01-01

    We recently designed and deployed a metasearch engine, Metta, that sends queries and retrieves search results from five leading biomedical databases: PubMed, EMBASE, CINAHL, PsycINFO and the Cochrane Central Register of Controlled Trials. Because many articles are indexed in more than one of these databases, it is desirable to deduplicate the retrieved article records. This is not a trivial problem because data fields contain a lot of missing and erroneous entries, and because certain types of information are recorded differently (and inconsistently) in the different databases. The present report describes our rule-based method for deduplicating article records across databases and includes an open-source script module that can be deployed freely. Metta was designed to satisfy the particular needs of people who are writing systematic reviews in evidence-based medicine. These users want the highest possible recall in retrieval, so it is important to err on the side of not deduplicating any records that refer to distinct articles, and it is important to perform deduplication online in real time. Our deduplication module is designed with these constraints in mind. Articles that share the same publication year are compared sequentially on parameters including PubMed ID number, digital object identifier, journal name, article title and author list, using text approximation techniques. In a review of Metta searches carried out by public users, we found that the deduplication module was more effective at identifying duplicates than EndNote without making any erroneous assignments.

  14. Rule-based deduplication of article records from bibliographic databases

    PubMed Central

    Jiang, Yu; Lin, Can; Meng, Weiyi; Yu, Clement; Cohen, Aaron M.; Smalheiser, Neil R.

    2014-01-01

    We recently designed and deployed a metasearch engine, Metta, that sends queries and retrieves search results from five leading biomedical databases: PubMed, EMBASE, CINAHL, PsycINFO and the Cochrane Central Register of Controlled Trials. Because many articles are indexed in more than one of these databases, it is desirable to deduplicate the retrieved article records. This is not a trivial problem because data fields contain a lot of missing and erroneous entries, and because certain types of information are recorded differently (and inconsistently) in the different databases. The present report describes our rule-based method for deduplicating article records across databases and includes an open-source script module that can be deployed freely. Metta was designed to satisfy the particular needs of people who are writing systematic reviews in evidence-based medicine. These users want the highest possible recall in retrieval, so it is important to err on the side of not deduplicating any records that refer to distinct articles, and it is important to perform deduplication online in real time. Our deduplication module is designed with these constraints in mind. Articles that share the same publication year are compared sequentially on parameters including PubMed ID number, digital object identifier, journal name, article title and author list, using text approximation techniques. In a review of Metta searches carried out by public users, we found that the deduplication module was more effective at identifying duplicates than EndNote without making any erroneous assignments. PMID:24434031

  15. Linked data scientometrics in semantic e-Science

    NASA Astrophysics Data System (ADS)

    Narock, Tom; Wimmer, Hayden

    2017-03-01

    The Semantic Web is inherently multi-disciplinary and many domains have taken advantage of semantic technologies. Yet, the geosciences are one of the fields leading the way in Semantic Web adoption and validation. Astronomy, Earth science, hydrology, and solar-terrestrial physics have seen a noteworthy amount of semantic integration. The geoscience community has been willing early adopters of semantic technologies and have provided essential feedback to the broader semantic web community. Yet, there has been no systematic study of the community as a whole and there exists no quantitative data on the impact and status of semantic technologies in the geosciences. We explore the applicability of Linked Data to scientometrics in the geosciences. In doing so, we gain an initial understanding of the breadth and depth of the Semantic Web in the geosciences. We identify what appears to be a transitionary period in the applicability of these technologies.

  16. The development of co-speech gesture and its semantic integration with speech in 6- to 12-year-old children with autism spectrum disorders.

    PubMed

    So, Wing-Chee; Wong, Miranda Kit-Yi; Lui, Ming; Yip, Virginia

    2015-11-01

    Previous work leaves open the question of whether children with autism spectrum disorders aged 6-12 years have delay in producing gestures compared to their typically developing peers. This study examined gestural production among school-aged children in a naturalistic context and how their gestures are semantically related to the accompanying speech. Delay in gestural production was found in children with autism spectrum disorders through their middle to late childhood. Compared to their typically developing counterparts, children with autism spectrum disorders gestured less often and used fewer types of gestures, in particular markers, which carry culture-specific meaning. Typically developing children's gestural production was related to language and cognitive skills, but among children with autism spectrum disorders, gestural production was more strongly related to the severity of socio-communicative impairment. Gesture impairment also included the failure to integrate speech with gesture: in particular, supplementary gestures are absent in children with autism spectrum disorders. The findings extend our understanding of gestural production in school-aged children with autism spectrum disorders during spontaneous interaction. The results can help guide new therapies for gestural production for children with autism spectrum disorders in middle and late childhood.

  17. Getting connected: Both associative and semantic links structure semantic memory for newly learned persons.

    PubMed

    Wiese, Holger; Schweinberger, Stefan R

    2015-01-01

    The present study examined whether semantic memory for newly learned people is structured by visual co-occurrence, shared semantics, or both. Participants were trained with pairs of simultaneously presented (i.e., co-occurring) preexperimentally unfamiliar faces, which either did or did not share additionally provided semantic information (occupation, place of living, etc.). Semantic information could also be shared between faces that did not co-occur. A subsequent priming experiment revealed faster responses for both co-occurrence/no shared semantics and no co-occurrence/shared semantics conditions, than for an unrelated condition. Strikingly, priming was strongest in the co-occurrence/shared semantics condition, suggesting additive effects of these factors. Additional analysis of event-related brain potentials yielded priming in the N400 component only for combined effects of visual co-occurrence and shared semantics, with more positive amplitudes in this than in the unrelated condition. Overall, these findings suggest that both semantic relatedness and visual co-occurrence are important when novel information is integrated into person-related semantic memory.

  18. A Semantic Approach with Decision Support for Safety Service in Smart Home Management

    PubMed Central

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-01-01

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate. PMID:27527170

  19. A Semantic Approach with Decision Support for Safety Service in Smart Home Management.

    PubMed

    Huang, Xiaoci; Yi, Jianjun; Zhu, Xiaomin; Chen, Shaoli

    2016-08-03

    Research on smart homes (SHs) has increased significantly in recent years because of the convenience provided by having an assisted living environment. The functions of SHs as mentioned in previous studies, particularly safety services, are seldom discussed or mentioned. Thus, this study proposes a semantic approach with decision support for safety service in SH management. The focus of this contribution is to explore a context awareness and reasoning approach for risk recognition in SH that enables the proper decision support for flexible safety service provision. The framework of SH based on a wireless sensor network is described from the perspective of neighbourhood management. This approach is based on the integration of semantic knowledge in which a reasoner can make decisions about risk recognition and safety service. We present a management ontology for a SH and relevant monitoring contextual information, which considers its suitability in a pervasive computing environment and is service-oriented. We also propose a rule-based reasoning method to provide decision support through reasoning techniques and context-awareness. A system prototype is developed to evaluate the feasibility, time response and extendibility of the approach. The evaluation of our approach shows that it is more effective in daily risk event recognition. The decisions for service provision are shown to be accurate.

  20. Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services

    PubMed Central

    Daniel, Christel; Ouagne, David; Sadou, Eric; Forsberg, Kerstin; Gilchrist, Mark Mc; Zapletal, Eric; Paris, Nicolas; Hussain, Sajjad; Jaulent, Marie-Christine; MD, Dipka Kalra

    2016-01-01

    With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. PMID:27570649

  1. Neural substrates of similarity and rule-based strategies in judgment

    PubMed Central

    von Helversen, Bettina; Karlsson, Linnea; Rasch, Björn; Rieskamp, Jörg

    2014-01-01

    Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI), we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved. PMID:25360099

  2. Rule-based Cross-matching of Very Large Catalogs

    NASA Astrophysics Data System (ADS)

    Ogle, P. M.; Mazzarella, J.; Ebert, R.; Fadda, D.; Lo, T.; Terek, S.; Schmitz, M.; NED Team

    2015-09-01

    The NASA Extragalactic Database (NED) has deployed a new rule-based cross-matching algorithm called Match Expert (MatchEx), capable of cross-matching very large catalogs (VLCs) with >10 million objects. MatchEx goes beyond traditional position-based cross-matching algorithms by using other available data together with expert logic to determine which candidate match is the best. Furthermore, the local background density of sources is used to determine and minimize the false-positive match rate and to estimate match completeness. The logical outcome and statistical probability of each match decision is stored in the database and may be used to tune the algorithm and adjust match parameter thresholds. For our first production run, we cross-matched the GALEX All Sky Survey Catalog (GASC), containing nearly 40 million NUV-detected sources, against a directory of 180 million objects in NED. Candidate matches were identified for each GASC source within a 7''.5 radius. These candidates were filtered on position-based matching probability and on other criteria including object type and object name. We estimate a match completeness of 97.6% and a match accuracy of 99.75%. Over the next year, we will be cross-matching over 2 billion catalog sources to NED, including the Spitzer Source List, the 2MASS point-source catalog, AllWISE, and SDSS DR 10. We expect to add new capabilities to filter candidate matches based on photometry, redshifts, and refined object classifications. We will also extend MatchEx to handle more heterogenous datasets federated from smaller catalogs through NED's literature pipeline.

  3. LORD: a phenotype-genotype semantically integrated biomedical data tool to support rare disease diagnosis coding in health information systems.

    PubMed

    Choquet, Remy; Maaroufi, Meriem; Fonjallaz, Yannick; de Carrara, Albane; Vandenbussche, Pierre-Yves; Dhombres, Ferdinand; Landais, Paul

    Characterizing a rare disease diagnosis for a given patient is often made through expert's networks. It is a complex task that could evolve over time depending on the natural history of the disease and the evolution of the scientific knowledge. Most rare diseases have genetic causes and recent improvements of sequencing techniques contribute to the discovery of many new diseases every year. Diagnosis coding in the rare disease field requires data from multiple knowledge bases to be aggregated in order to offer the clinician a global information space from possible diagnosis to clinical signs (phenotypes) and known genetic mutations (genotype). Nowadays, the major barrier to the coding activity is the lack of consolidation of such information scattered in different thesaurus such as Orphanet, OMIM or HPO. The Linking Open data for Rare Diseases (LORD) web portal we developed stands as the first attempt to fill this gap by offering an integrated view of 8,400 rare diseases linked to more than 14,500 signs and 3,270 genes. The application provides a browsing feature to navigate through the relationships between diseases, signs and genes, and some Application Programming Interfaces to help its integration in health information systems in routine.

  4. LORD: a phenotype-genotype semantically integrated biomedical data tool to support rare disease diagnosis coding in health information systems

    PubMed Central

    Choquet, Remy; Maaroufi, Meriem; Fonjallaz, Yannick; de Carrara, Albane; Vandenbussche, Pierre-Yves; Dhombres, Ferdinand; Landais, Paul

    2015-01-01

    Characterizing a rare disease diagnosis for a given patient is often made through expert’s networks. It is a complex task that could evolve over time depending on the natural history of the disease and the evolution of the scientific knowledge. Most rare diseases have genetic causes and recent improvements of sequencing techniques contribute to the discovery of many new diseases every year. Diagnosis coding in the rare disease field requires data from multiple knowledge bases to be aggregated in order to offer the clinician a global information space from possible diagnosis to clinical signs (phenotypes) and known genetic mutations (genotype). Nowadays, the major barrier to the coding activity is the lack of consolidation of such information scattered in different thesaurus such as Orphanet, OMIM or HPO. The Linking Open data for Rare Diseases (LORD) web portal we developed stands as the first attempt to fill this gap by offering an integrated view of 8,400 rare diseases linked to more than 14,500 signs and 3,270 genes. The application provides a browsing feature to navigate through the relationships between diseases, signs and genes, and some Application Programming Interfaces to help its integration in health information systems in routine. PMID:26958175

  5. Rule-Based Classification of Chemical Structures by Scaffold.

    PubMed

    Schuffenhauer, Ansgar; Varin, Thibault

    2011-08-01

    Databases for small organic chemical molecules usually contain millions of structures. The screening decks of pharmaceutical companies contain more than a million of structures. Nevertheless chemical substructure searching in these databases can be performed interactively in seconds. Because of this nobody has really missed structural classification of these databases for the purpose of finding data for individual chemical substructures. However, a full deck high-throughput screen produces also activity data for more than a million of substances. How can this amount of data be analyzed? Which are the active scaffolds identified by an assays? To answer such questions systematic classifications of molecules by scaffolds are needed. In this review it is described how molecules can be hierarchically classified by their scaffolds. It is explained how such classifications can be used to identify active scaffolds in an HTS data set. Once active classes are identified, they need to be visualized in the context of related scaffolds in order to understand SAR. Consequently such visualizations are another topic of this review. In addition scaffold based diversity measures are discussed and an outlook is given about the potential impact of structural classifications on a chemically aware semantic web.

  6. The Semantic eScience Framework

    NASA Astrophysics Data System (ADS)

    Fox, P. A.; McGuinness, D. L.

    2009-12-01

    The goal of this effort is to design and implement a configurable and extensible semantic eScience framework (SESF). Configuration requires research into accommodating different levels of semantic expressivity and user requirements from use cases. Extensibility is being achieved in a modular approach to the semantic encodings (i.e. ontologies) performed in community settings, i.e. an ontology framework into which specific applications all the way up to communities can extend the semantics for their needs.We report on how we are accommodating the rapid advances in semantic technologies and tools and the sustainable software path for the future (certain) technical advances. In addition to a generalization of the current data science interface, we will present plans for an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.SESF builds upon previous work in the Virtual Solar-Terrestrial Observatory. The VSTO utilizes leading edge knowledge representation, query and reasoning techniques to support knowledge-enhanced search, data access, integration, and manipulation. It encodes term meanings and their inter-relationships in ontologies anduses these ontologies and associated inference engines to semantically enable the data services. The Semantically-Enabled Science Data Integration (SESDI) project implemented data integration capabilities among three sub-disciplines; solar radiation, volcanic outgassing and atmospheric structure using extensions to existingmodular ontolgies and used the VSTO data framework, while adding smart faceted search and semantic data registrationtools. The Semantic Provenance Capture in Data Ingest Systems (SPCDIS) has added explanation provenance capabilities to an observational data ingest pipeline for images of the Sun providing a set of tools to answer diverseend user questions such as ``Why does this image look bad?.

  7. The Semantic eScience Framework

    NASA Astrophysics Data System (ADS)

    McGuinness, Deborah; Fox, Peter; Hendler, James

    2010-05-01

    The goal of this effort is to design and implement a configurable and extensible semantic eScience framework (SESF). Configuration requires research into accommodating different levels of semantic expressivity and user requirements from use cases. Extensibility is being achieved in a modular approach to the semantic encodings (i.e. ontologies) performed in community settings, i.e. an ontology framework into which specific applications all the way up to communities can extend the semantics for their needs.We report on how we are accommodating the rapid advances in semantic technologies and tools and the sustainable software path for the future (certain) technical advances. In addition to a generalization of the current data science interface, we will present plans for an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.SESF builds upon previous work in the Virtual Solar-Terrestrial Observatory. The VSTO utilizes leading edge knowledge representation, query and reasoning techniques to support knowledge-enhanced search, data access, integration, and manipulation. It encodes term meanings and their inter-relationships in ontologies anduses these ontologies and associated inference engines to semantically enable the data services. The Semantically-Enabled Science Data Integration (SESDI) project implemented data integration capabilities among three sub-disciplines; solar radiation, volcanic outgassing and atmospheric structure using extensions to existingmodular ontolgies and used the VSTO data framework, while adding smart faceted search and semantic data registrationtools. The Semantic Provenance Capture in Data Ingest Systems (SPCDIS) has added explanation provenance capabilities to an observational data ingest pipeline for images of the Sun providing a set of tools to answer diverseend user questions such as ``Why does this image look bad?. http://tw.rpi.edu/portal/SESF

  8. Application of a rule-based knowledge system using CLIPS for the taxonomy of selected Opuntia species

    NASA Technical Reports Server (NTRS)

    Heymans, Bart C.; Onema, Joel P.; Kuti, Joseph O.

    1991-01-01

    A rule based knowledge system was developed in CLIPS (C Language Integrated Production System) for identifying Opuntia species in the family Cactaceae, which contains approx. 1500 different species. This botanist expert tool system is capable of identifying selected Opuntia plants from the family level down to the species level when given some basic characteristics of the plants. Many plants are becoming of increasing importance because of their nutrition and human health potential, especially in the treatment of diabetes mellitus. The expert tool system described can be extremely useful in an unequivocal identification of many useful Opuntia species.

  9. An ontology-based hierarchical semantic modeling approach to clinical pathway workflows.

    PubMed

    Ye, Yan; Jiang, Zhibin; Diao, Xiaodi; Yang, Dong; Du, Gang

    2009-08-01

    This paper proposes an ontology-based approach of modeling clinical pathway workflows at the semantic level for facilitating computerized clinical pathway implementation and efficient delivery of high-quality healthcare services. A clinical pathway ontology (CPO) is formally defined in OWL web ontology language (OWL) to provide common semantic foundation for meaningful representation and exchange of pathway-related knowledge. A CPO-based semantic modeling method is then presented to describe clinical pathways as interconnected hierarchical models including the top-level outcome flow and intervention workflow level along a care timeline. Furthermore, relevant temporal knowledge can be fully represented by combing temporal entities in CPO and temporal rules based on semantic web rule language (SWRL). An illustrative example about a clinical pathway for cesarean section shows the applicability of the proposed methodology in enabling structured semantic descriptions of any real clinical pathway.

  10. Semantic-Web Technology: Applications at NASA

    NASA Technical Reports Server (NTRS)

    Ashish, Naveen

    2004-01-01

    We provide a description of work at the National Aeronautics and Space Administration (NASA) on building system based on semantic-web concepts and technologies. NASA has been one of the early adopters of semantic-web technologies for practical applications. Indeed there are several ongoing 0 endeavors on building semantics based systems for use in diverse NASA domains ranging from collaborative scientific activity to accident and mishap investigation to enterprise search to scientific information gathering and integration to aviation safety decision support We provide a brief overview of many applications and ongoing work with the goal of informing the external community of these NASA endeavors.

  11. Semantics via Machine Translation

    ERIC Educational Resources Information Center

    Culhane, P. T.

    1977-01-01

    Recent experiments in machine translation have given the semantic elements of collocation in Russian more objective criteria. Soviet linguists in search of semantic relationships have attempted to devise a semantic synthesis for construction of a basic language for machine translation. One such effort is summarized. (CHK)

  12. SEMANTICS AND CRITICAL READING.

    ERIC Educational Resources Information Center

    FLANIGAN, MICHAEL C.

    PROFICIENCY IN CRITICAL READING CAN BE ACCELERATED BY MAKING STUDENTS AWARE OF VARIOUS SEMANTIC DEVICES THAT HELP CLARIFY MEANINGS AND PURPOSES. EXCERPTS FROM THE ARTICLE "TEEN-AGE CORRUPTION" FROM THE NINTH-GRADE SEMANTICS UNIT WRITTEN BY THE PROJECT ENGLISH DEMONSTRATION CENTER AT EUCLID, OHIO, ARE USED TO ILLUSTRATE HOW SEMANTICS RELATE TO…

  13. Semantic SenseLab: implementing the vision of the Semantic Web in neuroscience

    PubMed Central

    Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

    2011-01-01

    Summary Objective Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Methods Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. Conclusion We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/ PMID:20006477

  14. Increasing Complexity in Rule-Based Clinical Decision Support: The Symptom Assessment and Management Intervention

    PubMed Central

    Johns, Ellis B; Halpenny, Barbara; Saunders, Toni-Ann; Brzozowski, Jane; Del Fiol, Guilherme; Berry, Donna L; Braun, Ilana M; Finn, Kathleen; Wolfe, Joanne; Abrahm, Janet L; Cooley, Mary E

    2016-01-01

    Background Management of uncontrolled symptoms is an important component of quality cancer care. Clinical guidelines are available for optimal symptom management, but are not often integrated into the front lines of care. The use of clinical decision support (CDS) at the point-of-care is an innovative way to incorporate guideline-based symptom management into routine cancer care. Objective The objective of this study was to develop and evaluate a rule-based CDS system to enable management of multiple symptoms in lung cancer patients at the point-of-care. Methods This study was conducted in three phases involving a formative evaluation, a system evaluation, and a contextual evaluation of clinical use. In Phase 1, we conducted iterative usability testing of user interface prototypes with patients and health care providers (HCPs) in two thoracic oncology clinics. In Phase 2, we programmed complex algorithms derived from clinical practice guidelines into a rules engine that used Web services to communicate with the end-user application. Unit testing of algorithms was conducted using a stack-traversal tree-spanning methodology to identify all possible permutations of pathways through each algorithm, to validate accuracy. In Phase 3, we evaluated clinical use of the system among patients and HCPs in the two clinics via observations, structured interviews, and questionnaires. Results In Phase 1, 13 patients and 5 HCPs engaged in two rounds of formative testing, and suggested improvements leading to revisions until overall usability scores met a priori benchmarks. In Phase 2, symptom management algorithms contained between 29 and 1425 decision nodes, resulting in 19 to 3194 unique pathways per algorithm. Unit testing required 240 person-hours, and integration testing required 40 person-hours. In Phase 3, both patients and HCPs found the system usable and acceptable, and offered suggestions for improvements. Conclusions A rule-based CDS system for complex symptom management

  15. Biomedical semantics in the Semantic Web.

    PubMed

    Splendiani, Andrea; Burger, Albert; Paschke, Adrian; Romano, Paolo; Marshall, M Scott

    2011-03-07

    The Semantic Web offers an ideal platform for representing and linking biomedical information, which is a prerequisite for the development and application of analytical tools to address problems in data-intensive areas such as systems biology and translational medicine. As for any new paradigm, the adoption of the Semantic Web offers opportunities and poses questions and challenges to the life sciences scientific community: which technologies in the Semantic Web stack will be more beneficial for the life sciences? Is biomedical information too complex to benefit from simple interlinked representations? What are the implications of adopting a new paradigm for knowledge representation? What are the incentives for the adoption of the Semantic Web, and who are the facilitators? Is there going to be a Semantic Web revolution in the life sciences?We report here a few reflections on these questions, following discussions at the SWAT4LS (Semantic Web Applications and Tools for Life Sciences) workshop series, of which this Journal of Biomedical Semantics special issue presents selected papers from the 2009 edition, held in Amsterdam on November 20th.

  16. Linguistic and Non-Linguistic Semantic Processing in Individuals with Autism Spectrum Disorders: An ERP Study.

    PubMed

    Coderre, Emily L; Chernenok, Mariya; Gordon, Barry; Ledoux, Kerry

    2017-01-12

    Individuals with autism spectrum disorders (ASD) experience difficulties with language, particularly higher-level functions like semantic integration. Yet some studies indicate that semantic processing of non-linguistic stimuli is not impaired, suggesting a language-specific deficit in semantic processing. Using a semantic priming task, we compared event-related potentials (ERPs) in response to lexico-semantic processing (written words) and visuo-semantic processing (pictures) in adults with ASD and adults with typical development (TD). The ASD group showed successful lexico-semantic and visuo-semantic processing, indicated by similar N400 effects between groups for word and picture stimuli. However, differences in N400 latency and topography in word conditions suggested different lexico-semantic processing mechanisms: an expectancy-based strategy for the TD group but a controlled post-lexical integration strategy for the ASD group.

  17. The semantic anatomical network: Evidence from healthy and brain-damaged patient populations.

    PubMed

    Fang, Yuxing; Han, Zaizhu; Zhong, Suyu; Gong, Gaolang; Song, Luping; Liu, Fangsong; Huang, Ruiwang; Du, Xiaoxia; Sun, Rong; Wang, Qiang; He, Yong; Bi, Yanchao

    2015-09-01

    Semantic processing is central to cognition and is supported by widely distributed gray matter (GM) regions and white matter (WM) tracts. The exact manner in which GM regions are anatomically connected to process semantics remains unknown. We mapped the semantic anatomical network (connectome) by conducting diffusion imaging tractography in 48 healthy participants across 90 GM "nodes," and correlating the integrity of each obtained WM edge and semantic performance across 80 brain-damaged patients. Fifty-three WM edges were obtained whose lower integrity associated with semantic deficits and together with their linked GM nodes constitute a semantic WM network. Graph analyses of this network revealed three structurally segregated modules that point to distinct semantic processing components and identified network hubs and connectors that are central in the communication across the subnetworks. Together, our results provide an anatomical framework of human semantic network, advancing the understanding of the structural substrates supporting semantic processing.

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

    PubMed Central

    Ježek, Petr; Mouček, Roman

    2015-01-01

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

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

    PubMed

    Ježek, Petr; Mouček, Roman

    2015-01-01

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

  20. Significance testing of rules in rule-based models of human problem solving

    NASA Technical Reports Server (NTRS)

    Lewis, C. M.; Hammer, J. M.

    1986-01-01

    Rule-based models of human problem solving have typically not been tested for statistical significance. Three methods of testing rules - analysis of variance, randomization, and contingency tables - are presented. Advantages and disadvantages of the methods are also described.

  1. RFID sensor-tags feeding a context-aware rule-based healthcare monitoring system.

    PubMed

    Catarinucci, Luca; Colella, Riccardo; Esposito, Alessandra; Tarricone, Luciano; Zappatore, Marco

    2012-12-01

    Along with the growing of the aging population and the necessity of efficient wellness systems, there is a mounting demand for new technological solutions able to support remote and proactive healthcare. An answer to this need could be provided by the joint use of the emerging Radio Frequency Identification (RFID) technologies and advanced software choices. This paper presents a proposal for a context-aware infrastructure for ubiquitous and pervasive monitoring of heterogeneous healthcare-related scenarios, fed by RFID-based wireless sensors nodes. The software framework is based on a general purpose architecture exploiting three key implementation choices: ontology representation, multi-agent paradigm and rule-based logic. From the hardware point of view, the sensing and gathering of context-data is demanded to a new Enhanced RFID Sensor-Tag. This new device, de facto, makes possible the easy integration between RFID and generic sensors, guaranteeing flexibility and preserving the benefits in terms of simplicity of use and low cost of UHF RFID technology. The system is very efficient and versatile and its customization to new scenarios requires a very reduced effort, substantially limited to the update/extension of the ontology codification. Its effectiveness is demonstrated by reporting both customization effort and performance results obtained from validation in two different healthcare monitoring contexts.

  2. Designing caption production rules based on face, text, and motion detection

    NASA Astrophysics Data System (ADS)

    Chapdelaine, C.; Beaulieu, M.; Gagnon, L.

    2008-02-01

    Producing off-line captions for the deaf and hearing impaired people is a labor-intensive task that can require up to 18 hours of production per hour of film. Captions are placed manually close to the region of interest but it must avoid masking human faces, texts or any moving objects that might be relevant to the story flow. Our goal is to use image processing techniques to reduce the off-line caption production process by automatically placing the captions on the proper consecutive frames. We implemented a computer-assisted captioning software tool which integrates detection of faces, texts and visual motion regions. The near frontal faces are detected using a cascade of weak classifier and tracked through a particle filter. Then, frames are scanned to perform text spotting and build a region map suitable for text recognition. Finally, motion mapping is based on the Lukas-Kanade optical flow algorithm and provides MPEG-7 motion descriptors. The combined detected items are then fed to a rule-based algorithm to determine the best captions localization for the related sequences of frames. This paper focuses on the defined rules to assist the human captioners and the results of a user evaluation for this approach.

  3. A rule-based kinetic model of RNA polymerase II C-terminal domain phosphorylation

    PubMed Central

    Aitken, Stuart; Alexander, Ross D.; Beggs, Jean D.

    2013-01-01

    The complexity of many RNA processing pathways is such that a conventional systems modelling approach is inadequate to represent all the molecular species involved. We demonstrate that rule-based modelling permits a detailed model of a complex RNA signalling pathway to be defined. Phosphorylation of the RNA polymerase II (RNAPII) C-terminal domain (CTD; a flexible tail-like extension of the largest subunit) couples pre-messenger RNA capping, splicing and 3′ end maturation to transcriptional elongation and termination, and plays a central role in integrating these processes. The phosphorylation states of the serine residues of many heptapeptide repeats of the CTD alter along the coding region of genes as a function of distance from the promoter. From a mechanistic perspective, both the changes in phosphorylation and the location at which they take place on the genes are a function of the time spent by RNAPII in elongation as this interval provides the opportunity for the kinases and phosphatases to interact with the CTD. On this basis, we synthesize the available data to create a kinetic model of the action of the known kinases and phosphatases to resolve the phosphorylation pathways and their kinetics. PMID:23804443

  4. The Development of Co-Speech Gesture and Its Semantic Integration with Speech in 6- to 12-Year-Old Children with Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    So, Wing-Chee; Wong, Miranda Kit-Yi; Lui, Ming; Yip, Virginia

    2015-01-01

    Previous work leaves open the question of whether children with autism spectrum disorders aged 6-12?years have delay in producing gestures compared to their typically developing peers. This study examined gestural production among school-aged children in a naturalistic context and how their gestures are semantically related to the accompanying…

  5. Individual Differences in the Joint Effects of Semantic Priming and Word Frequency Revealed by RT Distributional Analyses: The Role of Lexical Integrity

    ERIC Educational Resources Information Center

    Yap, Melvin J.; Tse, Chi-Shing; Balota, David A.

    2009-01-01

    Word frequency and semantic priming effects are among the most robust effects in visual word recognition, and it has been generally assumed that these two variables produce interactive effects in lexical decision performance, with larger priming effects for low-frequency targets. The results from four lexical decision experiments indicate that the…

  6. SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services

    PubMed Central

    Gessler, Damian DG; Schiltz, Gary S; May, Greg D; Avraham, Shulamit; Town, Christopher D; Grant, David; Nelson, Rex T

    2009-01-01

    Background SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. Results There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at , developer tools at , and a portal to third-party ontologies at (a "swap meet"). Conclusion SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the confounding of content, structure, and presentation. SSWAP is novel by establishing

  7. Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis

    SciTech Connect

    Li Qiang; Doi Kunio

    2006-02-15

    Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists detect various lesions in medical images. In CAD schemes, classifiers play a key role in achieving a high lesion detection rate and a low false-positive rate. Although many popular classifiers such as linear discriminant analysis and artificial neural networks have been employed in CAD schemes for reduction of false positives, a rule-based classifier has probably been the simplest and most frequently used one since the early days of development of various CAD schemes. However, with existing rule-based classifiers, there are major disadvantages that significantly reduce their practicality and credibility. The disadvantages include manual design, poor reproducibility, poor evaluation methods such as resubstitution, and a large overtraining effect. An automated rule-based classifier with a minimized overtraining effect can overcome or significantly reduce the extent of the above-mentioned disadvantages. In this study, we developed an 'optimal' method for the selection of cutoff thresholds and a fully automated rule-based classifier. Experimental results performed with Monte Carlo simulation and a real lung nodule CT data set demonstrated that the automated threshold selection method can completely eliminate overtraining effect in the procedure of cutoff threshold selection, and thus can minimize overall overtraining effect in the constructed rule-based classifier. We believe that this threshold selection method is very useful in the construction of automated rule-based classifiers with minimized overtraining effect.

  8. Semantic Networks and Social Networks

    ERIC Educational Resources Information Center

    Downes, Stephen

    2005-01-01

    Purpose: To illustrate the need for social network metadata within semantic metadata. Design/methodology/approach: Surveys properties of social networks and the semantic web, suggests that social network analysis applies to semantic content, argues that semantic content is more searchable if social network metadata is merged with semantic web…

  9. Considering the role of semantic memory in episodic future thinking: evidence from semantic dementia.

    PubMed

    Irish, Muireann; Addis, Donna Rose; Hodges, John R; Piguet, Olivier

    2012-07-01

    analyses that confirmed the relation between semantic memory deficits and episodic future thinking in semantic dementia, in contrast with the role of episodic memory deficits and episodic future thinking in Alzheimer's disease. Our findings demonstrate that semantic knowledge is critical for the construction of novel future events, providing the necessary scaffolding into which episodic details can be integrated. Further research is necessary to elucidate the precise contribution of semantic memory to future thinking, and to explore how deficits in self-projection manifest on behavioural and social levels in different dementia subtypes.

  10. SemanticSCo: A platform to support the semantic composition of services for gene expression analysis.

    PubMed

    Guardia, Gabriela D A; Ferreira Pires, Luís; da Silva, Eduardo G; de Farias, Cléver R G

    2017-02-01

    Gene expression studies often require the combined use of a number of analysis tools. However, manual integration of analysis tools can be cumbersome and error prone. To support a higher level of automation in the integration process, efforts have been made in the biomedical domain towards the development of semantic web services and supporting composition environments. Yet, most environments consider only the execution of simple service behaviours and requires users to focus on technical details of the composition process. We propose a novel approach to the semantic composition of gene expression analysis services that addresses the shortcomings of the existing solutions. Our approach includes an architecture designed to support the service composition process for gene expression analysis, and a flexible strategy for the (semi) automatic composition of semantic web services. Finally, we implement a supporting platform called SemanticSCo to realize the proposed composition approach and demonstrate its functionality by successfully reproducing a microarray study documented in the literature. The SemanticSCo platform provides support for the composition of RESTful web services semantically annotated using SAWSDL. Our platform also supports the definition of constraints/conditions regarding the order in which service operations should be invoked, thus enabling the definition of complex service behaviours. Our proposed solution for semantic web service composition takes into account the requirements of different stakeholders and addresses all phases of the service composition process. It also provides support for the definition of analysis workflows at a high-level of abstraction, thus enabling users to focus on biological research issues rather than on the technical details of the composition process. The SemanticSCo source code is available at https://github.com/usplssb/SemanticSCo.

  11. Anticipating Words and Their Gender: An Event-related Brain Potential Study of Semantic Integration, Gender Expectancy, and Gender Agreement in Spanish Sentence Reading

    PubMed Central

    Wicha, Nicole Y. Y.; Moreno, Eva M.; Kutas, Marta

    2012-01-01

    Recent studies indicate that the human brain attends to and uses grammatical gender cues during sentence comprehension. Here, we examine the nature and time course of the effect of gender on word-by-word sentence reading. Event-related brain potentials were recorded to an article and noun, while native Spanish speakers read medium- to high-constraint Spanish sentences for comprehension. The noun either fit the sentence meaning or not, and matched the preceding article in gender or not; in addition, the preceding article was either expected or unexpected based on prior sentence context. Semantically anomalous nouns elicited an N400. Gender-disagreeing nouns elicited a posterior late positivity (P600), replicating previous findings for words. Gender agreement and semantic congruity interacted in both the N400 window—with a larger negativity frontally for double violations—and the P600 window—with a larger positivity for semantic anomalies, relative to the prestimulus baseline. Finally, unexpected articles elicited an enhanced positivity (500–700 msec post onset) relative to expected articles. Overall, our data indicate that readers anticipate and attend to the gender of both articles and nouns, and use gender in real time to maintain agreement and to build sentence meaning. PMID:15453979

  12. LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

    SciTech Connect

    VERSPOOR, KARIN; LIN, SHOU-DE

    2007-01-29

    An N-gram language model aims at capturing statistical syntactic word order information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can be learned without annotated training examples. Finally, we report on a case study showing how the semantics-enhanced language model can be applied to unsupervised word sense disambiguation with promising results.

  13. Enabling Ontology Based Semantic Queries in Biomedical Database Systems

    PubMed Central

    Zheng, Shuai; Lu, James

    2014-01-01

    There is a lack of tools to ease the integration and ontology based semantic queries in biomedical databases, which are often annotated with ontology concepts. We aim to provide a middle layer between ontology repositories and semantically annotated databases to support semantic queries directly in the databases with expressive standard database query languages. We have developed a semantic query engine that provides semantic reasoning and query processing, and translates the queries into ontology repository operations on NCBO BioPortal. Semantic operators are implemented in the database as user defined functions extended to the database engine, thus semantic queries can be directly specified in standard database query languages such as SQL and XQuery. The system provides caching management to boosts query performance. The system is highly adaptable to support different ontologies through easy customizations. We have implemented the system DBOntoLink as an open source software, which supports major ontologies hosted at BioPortal. DBOntoLink supports a set of common ontology based semantic operations and have them fully integrated with a database management system IBM DB2. The system has been deployed and evaluated with an existing biomedical database for managing and querying image annotations and markups (AIM). Our performance study demonstrates the high expressiveness of semantic queries and the high efficiency of the queries. PMID:25541585

  14. Anomia as a Marker of Distinct Semantic Memory Impairments in Alzheimer’s Disease and Semantic Dementia

    PubMed Central

    Reilly, Jamie; Peelle, Jonathan E.; Antonucci, Sharon M.; Grossman, Murray

    2011-01-01

    Objective Many neurologically-constrained models of semantic memory have been informed by two primary temporal lobe pathologies: Alzheimer’s Disease (AD) and Semantic Dementia (SD). However, controversy persists regarding the nature of the semantic impairment associated with these patient populations. Some argue that AD presents as a disconnection syndrome in which linguistic impairment reflects difficulties in lexical or perceptual means of semantic access. In contrast, there is a wider consensus that SD reflects loss of core knowledge that underlies word and object meaning. Object naming provides a window into the integrity of semantic knowledge in these two populations. Method We examined naming accuracy, errors and the correlation of naming ability with neuropsychological measures (semantic ability, executive functioning, and working memory) in a large sample of patients with AD (n=36) and SD (n=21). Results Naming ability and naming errors differed between groups, as did neuropsychological predictors of naming ability. Despite a similar extent of baseline cognitive impairment, SD patients were more anomic than AD patients. Conclusions These results add to a growing body of literature supporting a dual impairment to semantic content and active semantic processing in AD, and confirm the fundamental deficit in semantic content in SD. We interpret these findings as supporting of a model of semantic memory premised upon dynamic interactivity between the process and content of conceptual knowledge. PMID:21443339

  15. A Metrics Taxonomy and Reporting Strategy for Rule-Based Alerts

    PubMed Central

    Krall, Michael; Gerace, Alexander

    2015-01-01

    Context: Because institutions rely on rule-based alerts as an important component of their safety and quality strategies, they should determine whether the alerts achieve the expected benefit. Objective: To develop and to test a method of reporting outcome metrics for rule-based electronic health record alerts on a large scale. Methods: We empirically developed an action-oriented alerts taxonomy according to structure, actions, and implicit intended process outcomes using a set of 333 rule-based alerts at Kaiser Permanente Northwest. Next we developed a method for producing metrics reports for alert classes. Finally, we applied this method to alert taxa. Main Outcome Measures: Outcome measures were the successful development of a rule-based alerts taxonomy and the demonstration of its application in a reporting strategy. Results: We identified 9 major and 17 overall classes of alerts. We developed a specific metric approach for 5 of these classes, including the 3 most numerous ones in our institution, accounting for 224 (67%) of our alerts. Some alert classes do not readily lend themselves to this approach. Conclusions: We developed a taxonomy for rule-based alerts and demonstrated its application in developing outcome metrics reports on a large scale. This information allows tuning or retiring alerts and may inform the need to develop complementary or alternative approaches to address organizational imperatives. A method that assigns alerts to classes each amenable to a particular reporting strategy could reduce the difficulty of producing metrics reports. PMID:26057684

  16. The Semantic Learning Organization

    ERIC Educational Resources Information Center

    Sicilia, Miguel-Angel; Lytras, Miltiadis D.

    2005-01-01

    Purpose: The aim of this paper is introducing the concept of a "semantic learning organization" (SLO) as an extension of the concept of "learning organization" in the technological domain. Design/methodology/approach: The paper takes existing definitions and conceptualizations of both learning organizations and Semantic Web technology to develop…

  17. Aging and Semantic Activation.

    ERIC Educational Resources Information Center

    Howard, Darlene V.

    Three studies tested the theory that long term memory consists of a semantically organized network of concept nodes interconnected by leveled associations or relations, and that when a stimulus is processed, the corresponding concept node is assumed to be temporarily activated and this activation spreads to nearby semantically related nodes. In…

  18. Ontology Reuse in Geoscience Semantic Applications

    NASA Astrophysics Data System (ADS)

    Mayernik, M. S.; Gross, M. B.; Daniels, M. D.; Rowan, L. R.; Stott, D.; Maull, K. E.; Khan, H.; Corson-Rikert, J.

    2015-12-01

    The tension between local ontology development and wider ontology connections is fundamental to the Semantic web. It is often unclear, however, what the key decision points should be for new semantic web applications in deciding when to reuse existing ontologies and when to develop original ontologies. In addition, with the growth of semantic web ontologies and applications, new semantic web applications can struggle to efficiently and effectively identify and select ontologies to reuse. This presentation will describe the ontology comparison, selection, and consolidation effort within the EarthCollab project. UCAR, Cornell University, and UNAVCO are collaborating on the EarthCollab project to use semantic web technologies to enable the discovery of the research output from a diverse array of projects. The EarthCollab project is using the VIVO Semantic web software suite to increase discoverability of research information and data related to the following two geoscience-based communities: (1) the Bering Sea Project, an interdisciplinary field program whose data archive is hosted by NCAR's Earth Observing Laboratory (EOL), and (2) diverse research projects informed by geodesy through the UNAVCO geodetic facility and consortium. This presentation will outline of EarthCollab use cases, and provide an overview of key ontologies being used, including the VIVO-Integrated Semantic Framework (VIVO-ISF), Global Change Information System (GCIS), and Data Catalog (DCAT) ontologies. We will discuss issues related to bringing these ontologies together to provide a robust ontological structure to support the EarthCollab use cases. It is rare that a single pre-existing ontology meets all of a new application's needs. New projects need to stitch ontologies together in ways that fit into the broader semantic web ecosystem.

  19. Order Theoretical Semantic Recommendation

    SciTech Connect

    Joslyn, Cliff A.; Hogan, Emilie A.; Paulson, Patrick R.; Peterson, Elena S.; Stephan, Eric G.; Thomas, Dennis G.

    2013-07-23

    Mathematical concepts of order and ordering relations play multiple roles in semantic technologies. Discrete totally ordered data characterize both input streams and top-k rank-ordered recommendations and query output, while temporal attributes establish numerical total orders, either over time points or in the more complex case of startend temporal intervals. But also of note are the fully partially ordered data, including both lattices and non-lattices, which actually dominate the semantic strcuture of ontological systems. Scalar semantic similarities over partially-ordered semantic data are traditionally used to return rank-ordered recommendations, but these require complementation with true metrics available over partially ordered sets. In this paper we report on our work in the foundations of partial order measurement in ontologies, with application to top-k semantic recommendation in workflows.

  20. Enhancing medical database semantics.

    PubMed Central

    Leão, B. de F.; Pavan, A.

    1995-01-01

    Medical Databases deal with dynamic, heterogeneous and fuzzy data. The modeling of such complex domain demands powerful semantic data modeling methodologies. This paper describes GSM-Explorer a Case Tool that allows for the creation of relational databases using semantic data modeling techniques. GSM Explorer fully incorporates the Generic Semantic Data Model-GSM enabling knowledge engineers to model the application domain with the abstraction mechanisms of generalization/specialization, association and aggregation. The tool generates a structure that implements persistent database-objects through the automatic generation of customized SQL ANSI scripts that sustain the semantics defined in the higher lever. This paper emphasizes the system architecture and the mapping of the semantic model into relational tables. The present status of the project and its further developments are discussed in the Conclusions. PMID:8563288

  1. Rule-based system for three-dimensional shape recovery from a single perspective view

    NASA Astrophysics Data System (ADS)

    Young, Tzay Y.; Gunasekaran, Seetharaman; Shomar, Wasim J.

    1988-03-01

    A rule based system for 3D shape recovery and orientation estimation from a single perspective view is described. The primary input to our system is a set of line segments extracted from images by a complex segmentation process. In practice, humans are able to interpret 3D shape and orientation from 2D images with very little a priori information. The heuristics behind shape constancy suggest that certain regularity assumptions play an important role. Fifteen rules have been developed for the rule base which can be extended to include additional rules. The current rules deal with parallel lines, perpendicular lines, and right corners in the object space that lead to the given image instance recorded by the camera. Forward chaining methodology is adopted. The implementation is written in the rule base language OPS5 in conjunction with Pascal on a VAX/VMS system. Two examples are presented, and the results are consistent with human perception.

  2. Semantics, Pragmatics, and the Nature of Semantic Theories

    ERIC Educational Resources Information Center

    Spewak, David Charles, Jr.

    2013-01-01

    The primary concern of this dissertation is determining the distinction between semantics and pragmatics and how context sensitivity should be accommodated within a semantic theory. I approach the question over how to distinguish semantics from pragmatics from a new angle by investigating what the objects of a semantic theory are, namely…

  3. Semantic processing of EHR data for clinical research.

    PubMed

    Sun, Hong; Depraetere, Kristof; De Roo, Jos; Mels, Giovanni; De Vloed, Boris; Twagirumukiza, Marc; Colaert, Dirk

    2015-12-01

    There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data.

  4. Hybrid neural network and rule-based pattern recognition system capable of self-modification

    SciTech Connect

    Glover, C.W.; Silliman, M.; Walker, M.; Spelt, P.F. ); Rao, N.S.V. . Dept. of Computer Science)

    1990-01-01

    This paper describes a hybrid neural network and rule-based pattern recognition system architecture which is capable of self-modification or learning. The central research issue to be addressed for a multiclassifier hybrid system is whether such a system can perform better than the two classifiers taken by themselves. The hybrid system employs a hierarchical architecture, and it can be interfaced with one or more sensors. Feature extraction routines operating on raw sensor data produce feature vectors which serve as inputs to neural network classifiers at the next level in the hierarchy. These low-level neural networks are trained to provide further discrimination of the sensor data. A set of feature vectors is formed from a concatenation of information from the feature extraction routines and the low-level neural network results. A rule-based classifier system uses this feature set to determine if certain expected environmental states, conditions, or objects are present in the sensors' current data stream. The rule-based system has been given an a priori set of models of the expected environmental states, conditions, or objects which it is expected to identify. The rule-based system forms many candidate directed graphs of various combinations of incoming features vectors, and it uses a suitably chosen metric to measure the similarity between candidate and model directed graphs. The rule-based system must decide if there is a match between one of the candidate graphs and a model graph. If a match is found, then the rule-based system invokes a routine to create and train a new high-level neural network from the appropriate feature vector data to recognize when this model state is present in future sensor data streams. 12 refs., 3 figs.

  5. A Semantic Graph Query Language

    SciTech Connect

    Kaplan, I L

    2006-10-16

    Semantic graphs can be used to organize large amounts of information from a number of sources into one unified structure. A semantic query language provides a foundation for extracting information from the semantic graph. The graph query language described here provides a simple, powerful method for querying semantic graphs.

  6. A Defense of Semantic Minimalism

    ERIC Educational Resources Information Center

    Kim, Su

    2012-01-01

    Semantic Minimalism is a position about the semantic content of declarative sentences, i.e., the content that is determined entirely by syntax. It is defined by the following two points: "Point 1": The semantic content is a complete/truth-conditional proposition. "Point 2": The semantic content is useful to a theory of…

  7. [Semantic dementia--a multimodal disorder of conceptual knowledge].

    PubMed

    Nishio, Yoshiyuki; Mori, Etsuro

    2009-11-01

    Semantic dementia (SD) is a clinical syndrome characterized by progressive loss of semantic memory/ conceptual knowledge and by bilateral, but usually asymmetric, atrophy of the anterior temporal lobes (ATLS). On the basis of the neuropsychological findings of SD, the two theoretical implications for the organization of semantic memory have been suggested. First, selective impairment of semantic memory in the early stages of SD contrasts with the isolated loss of episodic memory in patients with damage to the medial temporal lobes and other Papez's circuit components. This double dissociation provides empirical evidence for fractionation of explicit memory into the two subsystems with different neural underpinnings. Second, the multimodal nature of semantic deficits in SD leads to a seminal view that semantic memory is organized as an amodal system. The ATLs play a pivotal role as a 'convergence zone' or 'semantic hub' integrating abundant verbal and perceptual attributes that are represented in the posterior temporal and temporo-occipital cortices. To develop further comprehensive theories regarding semantic memory, we should understand differential roles of the left and right ATLs and clarify the clinicoanatomical relationship between verbal, visual, and emotional aspects of semantic memory loss and the detailed anatomical localization of the lesions.

  8. Haunted by a doppelgänger: irrelevant facial similarity affects rule-based judgments.

    PubMed

    von Helversen, Bettina; Herzog, Stefan M; Rieskamp, Jörg

    2014-01-01

    Judging other people is a common and important task. Every day professionals make decisions that affect the lives of other people when they diagnose medical conditions, grant parole, or hire new employees. To prevent discrimination, professional standards require that decision makers render accurate and unbiased judgments solely based on relevant information. Facial similarity to previously encountered persons can be a potential source of bias. Psychological research suggests that people only rely on similarity-based judgment strategies if the provided information does not allow them to make accurate rule-based judgments. Our study shows, however, that facial similarity to previously encountered persons influences judgment even in situations in which relevant information is available for making accurate rule-based judgments and where similarity is irrelevant for the task and relying on similarity is detrimental. In two experiments in an employment context we show that applicants who looked similar to high-performing former employees were judged as more suitable than applicants who looked similar to low-performing former employees. This similarity effect was found despite the fact that the participants used the relevant résumé information about the applicants by following a rule-based judgment strategy. These findings suggest that similarity-based and rule-based processes simultaneously underlie human judgment.

  9. Rule-based approach to operating system selection: RMS vs. UNIX

    SciTech Connect

    Phifer, M.S.; Sadlowe, A.R.; Emrich, M.L.; Gadagkar, H.P.

    1988-10-01

    A rule-based system is under development for choosing computer operating systems. Following a brief historical account, this paper compares and contrasts the essential features of two operating systems highlighting particular applications. ATandT's UNIX System and Datapoint Corporations's Resource Management System (RMS) are used as illustrative examples. 11 refs., 3 figs.

  10. A rule-based expert system for chemical prioritization using effects-based chemical categories

    EPA Science Inventory

    A rule-based expert system (ES) was developed to predict chemical binding to the estrogen receptor (ER) patterned on the research approaches championed by Gilman Veith to whom this article and journal issue are dedicated. The ERES was built to be mechanistically-transparent and m...

  11. Effects of Multimedia on Cognitive Load, Self-Efficacy, and Multiple Rule-Based Problem Solving

    ERIC Educational Resources Information Center

    Zheng, Robert; McAlack, Matthew; Wilmes, Barbara; Kohler-Evans, Patty; Williamson, Jacquee

    2009-01-01

    This study investigates effects of multimedia on cognitive load, self-efficacy and learners' ability to solve multiple rule-based problems. Two hundred twenty-two college students were randomly assigned to interactive and non-interactive multimedia groups. Based on Engelkamp's multimodal theory, the present study investigates the role of…

  12. Application of Rule-Based Computer Models to the Evaluation of Combat Training: A Feasibility Study

    DTIC Science & Technology

    1981-07-01

    Rule-Based Computer Models to Final Technical Report the Evaluation of Combat Training: A Feasi- -August 1979-July 1980 7t. AUHAs for theRAC Beha GRNT2...an ac- ceptable level of performance. For example, when talking of a "move to contact," the expected average speed is 15- 25 mph. This kind of evalua

  13. Effectiveness of Visual Imagery versus Rule-Based Strategies in Teaching Spelling to Learning Disabled Students.

    ERIC Educational Resources Information Center

    Darch, Craig; Simpson, Robert G.

    1990-01-01

    Among 28 upper elementary learning-disabled students in a summer remedial program, those that were taught spelling with explicit rule-based strategies out-performed students presented with a visual imagery mnemonic on unit tests, a posttest, and a standardized spelling test. Contains 20 references. (SV)

  14. Age affects chunk-based, but not rule-based learning in artificial grammar acquisition.

    PubMed

    Kürten, Julia; De Vries, Meinou H; Kowal, Kristina; Zwitserlood, Pienie; Flöel, Agnes

    2012-07-01

    Explicit learning is well known to decline with age, but divergent results have been reported for implicit learning. Here, we assessed the effect of aging on implicit vs. explicit learning within the same task. Fifty-five young (mean 32 years) and 55 elderly (mean 64 years) individuals were exposed to letter strings generated by an artificial grammar. Subsequently, participants classified novel strings as grammatical or nongrammatical. Acquisition of superficial ("chunk-based") and structural ("rule-based") features of the grammar were analyzed separately. We found that overall classification accuracy was diminished in the elderly, driven by decreased performance on items that required chunk-based knowledge. Performance on items requiring rule-based knowledge was comparable between groups. Results indicate that rule-based and chunk-based learning are differentially affected by age: while rule-based learning, reflecting implicit learning, is preserved, chunk-based learning, which contains at least some explicit learning aspects, declines with age. Our findings may explain divergent results on implicit learning tasks in previous studies on aging. They may also help to better understand compensatory mechanisms during the aging process.

  15. Using Rule-Based Computer Programming to Unify Communication Rules Research.

    ERIC Educational Resources Information Center

    Sanford, David L.; Roach, J. W.

    This paper proposes the use of a rule-based computer programming language as a standard for the expression of rules, arguing that the adoption of a standard would enable researchers to communicate about rules in a consistent and significant way. Focusing on the formal equivalence of artificial intelligence (AI) programming to different types of…

  16. Semantic Service Design for Collaborative Business Processes in Internetworked Enterprises

    NASA Astrophysics Data System (ADS)

    Bianchini, Devis; Cappiello, Cinzia; de Antonellis, Valeria; Pernici, Barbara

    Modern collaborating enterprises can be seen as borderless organizations whose processes are dynamically transformed and integrated with the ones of their partners (Internetworked Enterprises, IE), thus enabling the design of collaborative business processes. The adoption of Semantic Web and service-oriented technologies for implementing collaboration in such distributed and heterogeneous environments promises significant benefits. IE can model their own processes independently by using the Software as a Service paradigm (SaaS). Each enterprise maintains a catalog of available services and these can be shared across IE and reused to build up complex collaborative processes. Moreover, each enterprise can adopt its own terminology and concepts to describe business processes and component services. This brings requirements to manage semantic heterogeneity in process descriptions which are distributed across different enterprise systems. To enable effective service-based collaboration, IEs have to standardize their process descriptions and model them through component services using the same approach and principles. For enabling collaborative business processes across IE, services should be designed following an homogeneous approach, possibly maintaining a uniform level of granularity. In the paper we propose an ontology-based semantic modeling approach apt to enrich and reconcile semantics of process descriptions to facilitate process knowledge management and to enable semantic service design (by discovery, reuse and integration of process elements/constructs). The approach brings together Semantic Web technologies, techniques in process modeling, ontology building and semantic matching in order to provide a comprehensive semantic modeling framework.

  17. Overcoming semantic heterogeneity in spatial data infrastructures

    NASA Astrophysics Data System (ADS)

    Lutz, M.; Sprado, J.; Klien, E.; Schubert, C.; Christ, I.

    2009-04-01

    In current spatial data infrastructures (SDIs), it is still often difficult to effectively exchange or re-use geographic data sets. A main reason for this is semantic heterogeneity, which occurs at different levels: at the metadata, the schema and the data content level. It is the goal of the work presented in this paper to overcome the problems caused by semantic heterogeneity on all three levels. We present a method based on ontologies and logical reasoning, which enhances the discovery, retrieval, interpretation and integration of geographic data in SDIs. Its benefits and practical use are illustrated with examples from the domains of geology and hydrology.

  18. Trusting Crowdsourced Geospatial Semantics

    NASA Astrophysics Data System (ADS)

    Goodhue, P.; McNair, H.; Reitsma, F.

    2015-08-01

    The degree of trust one can place in information is one of the foremost limitations of crowdsourced geospatial information. As with the development of web technologies, the increased prevalence of semantics associated with geospatial information has increased accessibility and functionality. Semantics also provides an opportunity to extend indicators of trust for crowdsourced geospatial information that have largely focused on spatio-temporal and social aspects of that information. Comparing a feature's intrinsic and extrinsic properties to associated ontologies provides a means of semantically assessing the trustworthiness of crowdsourced geospatial information. The application of this approach to unconstrained semantic submissions then allows for a detailed assessment of the trust of these features whilst maintaining the descriptive thoroughness this mode of information submission affords. The resulting trust rating then becomes an attribute of the feature, providing not only an indication as to the trustworthiness of a specific feature but is able to be aggregated across multiple features to illustrate the overall trustworthiness of a dataset.

  19. Exact hybrid particle/population simulation of rule-based models of biochemical systems.

    PubMed

    Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R

    2014-04-01

    Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings

  20. Discontinuous Categories Affect Information-Integration but not Rule-Based Category Learning

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Filoteo, J. Vincent; Lauritzen, J. Scott; Connally, Emily; Hejl, Kelli D.

    2005-01-01

    Three experiments were conducted that provide a direct examination of within-category discontinuity manipulations on the implicit, procedural-based learning and the explicit, hypothesis-testing systems proposed in F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, and E. M. Waldron's (1998) competition between verbal and implicit systems model.…

  1. Integrating Rule-Based and Neural-Net Techniques for Spectral Analysis

    DTIC Science & Technology

    1990-06-01

    perceptron, is presented in Figure 6. This neural network is a generalization of the single layer perceptron 18 OUTPMUT (CLASSES) 1 2 3 . P TH IRD LAYER Wkl...ten input nodes and four output nodes and used a single layer perceptron . The output of the neural network merely separated chemicals into four

  2. Enhanced semantic interpretability by healthcare standards profiling.

    PubMed

    Lopez, Diego M; Blobel, Bernd G M E

    2008-01-01

    Several current healthcare standards support semantic interoperability. These standards are far to be completely adopted in health information system development, however. The objective of this paper is to provide a method and necessary tooling for reusing healthcare standards by exploiting the extensibility mechanisms of UML, by that way supporting the development of semantically interoperable systems and components. The method identifies first the models and tasks in the software development process in which health care standards can be reused. Then, the selected standard is formalized as a UML profile. Finally that profile is applied to system models, annotating them with the standard semantics. The supporting tools are Eclipse-based UML modeling tools. The method is integrated into a comprehensive framework for health information systems development. The feasibility of the approach is exemplified by a scenario reusing HL7 RIM and DIMs specifications. The approach presented is also applicable for harmonizing different standard specifications.

  3. Semantic querying of relational data for clinical intelligence: a semantic web services-based approach

    PubMed Central

    2013-01-01

    Background Clinical Intelligence, as a research and engineering discipline, is dedicated to the development of tools for data analysis for the purposes of clinical research, surveillance, and effective health care management. Self-service ad hoc querying of clinical data is one desirable type of functionality. Since most of the data are currently stored in relational or similar form, ad hoc querying is problematic as it requires specialised technical skills and the knowledge of particular data schemas. Results A possible solution is semantic querying where the user formulates queries in terms of domain ontologies that are much easier to navigate and comprehend than data schemas. In this article, we are exploring the possibility of using SADI Semantic Web services for semantic querying of clinical data. We have developed a prototype of a semantic querying infrastructure for the surveillance of, and research on, hospital-acquired infections. Conclusions Our results suggest that SADI can support ad-hoc, self-service, semantic queries of relational data in a Clinical Intelligence context. The use of SADI compares favourably with approaches based on declarative semantic mappings from data schemas to ontologies, such as query rewriting and RDFizing by materialisation, because it can easily cope with situations when (i) some computation is required to turn relational data into RDF or OWL, e.g., to implement temporal reasoning, or (ii) integration with external data sources is necessary. PMID:23497556

  4. Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article

    PubMed Central

    Shotton, David; Portwin, Katie; Klyne, Graham; Miles, Alistair

    2009-01-01

    Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit “Citations in Context”, and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own research

  5. Adventures in semantic publishing: exemplar semantic enhancements of a research article.

    PubMed

    Shotton, David; Portwin, Katie; Klyne, Graham; Miles, Alistair

    2009-04-01

    Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit "Citations in Context", and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own research articles

  6. Semantic Services for Wikipedia

    NASA Astrophysics Data System (ADS)

    Wang, Haofen; Penin, Thomas; Fu, Linyun; Liu, Qiaoling; Xue, Guirong; Yu, Yong

    Wikipedia, a killer application in Web 2.0, has embraced the power of collaborative editing to harness collective intelligence. It features many attractive characteristics, like entity-based link graph, abundant categorization and semi-structured layout, and can serve as an ideal data source to extract high quality and well-structured data. In this chapter, we first propose several solutions to extract knowledge from Wikipedia. We do not only consider information from the relational summaries of articles (infoboxes) but also semi-automatically extract it from the article text using the structured content available. Due to differences with information extraction from the Web, it is necessary to tackle new problems, like the lack of redundancy in Wikipedia that is dealt with by extending traditional machine learning algorithms to work with few labeled data. Furthermore, we also exploit the widespread categories as a complementary way to discover additional knowledge. Benefiting from both structured and textural information, we additionally provide a suggestion service for Wikipedia authoring. With the aim to facilitate semantic reuse, our proposal provides users with facilities such as link, categories and infobox content suggestions. The proposed enhancements can be applied to attract more contributors and lighten the burden of professional editors. Finally, we developed an enhanced search system, which can ease the process of exploiting Wikipedia. To provide a user-friendly interface, it extends the faceted search interface with relation navigation and let the user easily express his complex information needs in an interactive way. In order to achieve efficient query answering, it extends scalable IR engines to index and search both the textual and structured information with an integrated ranking support.

  7. Non-semantic contributions to "semantic" redundancy gain.

    PubMed

    Shepherdson, Peter; Miller, Jeff

    2016-01-01

    Recently, two groups of researchers have reported redundancy gains (enhanced performance with multiple, redundant targets) in tasks requiring semantic categorization. Here we report two experiments aimed at determining whether the gains found by one of these groups resulted from some form of semantic coactivation. We asked undergraduate psychology students to complete choice RT tasks requiring the semantic categorization of visually presented words, and compared performance with redundant targets from the same semantic category to performance with redundant targets from different semantic categories. If the redundancy gains resulted from the combination of information at a semantic level, they should have been greater in the former than the latter situation. However, our results showed no significant differences in redundancy gain (for latency and accuracy) between same-category and different-category conditions, despite gains appearing in both conditions. Thus, we suggest that redundancy gain in the semantic categorization task may result entirely from statistical facilitation or combination of information at non-semantic levels.

  8. User-centered semantic harmonization: a case study.

    PubMed

    Weng, Chunhua; Gennari, John H; Fridsma, Douglas B

    2007-06-01

    Semantic interoperability is one of the great challenges in biomedical informatics. Methods such as ontology alignment or use of metadata neither scale nor fundamentally alleviate semantic heterogeneity among information sources. In the context of the Cancer Biomedical Informatics Grid program, the Biomedical Research Integrated Domain Group (BRIDG) has been making an ambitious effort to harmonize existing information models for clinical research from a variety of sources and modeling agreed-upon semantics shared by the technical harmonization committee and the developers of these models. This paper provides some observations on this user-centered semantic harmonization effort and its inherent technical and social challenges. The authors also compare BRIDG with related efforts to achieve semantic interoperability in healthcare, including UMLS, InterMed, the Semantic Web, and the Ontology for Biomedical Investigations initiative. The BRIDG project demonstrates the feasibility of user-centered collaborative domain modeling as an approach to semantic harmonization, but also highlights a number of technology gaps in support of collaborative semantic harmonization that remain to be filled.

  9. Remote semantic memory is impoverished in hippocampal amnesia.

    PubMed

    Klooster, Nathaniel B; Duff, Melissa C

    2015-12-01

    The necessity of the hippocampus for acquiring new semantic concepts is a topic of considerable debate. However, it is generally accepted that any role the hippocampus plays in semantic memory is time limited and that previously acquired information becomes independent of the hippocampus over time. This view, along with intact naming and word-definition matching performance in amnesia, has led to the notion that remote semantic memory is intact in patients with hippocampal amnesia. Motivated by perspectives of word learning as a protracted process where additional features and senses of a word are added over time, and by recent discoveries about the time course of hippocampal contributions to on-line relational processing, reconsolidation, and the flexible integration of information, we revisit the notion that remote semantic memory is intact in amnesia. Using measures of semantic richness and vocabulary depth from psycholinguistics and first and second language-learning studies, we examined how much information is associated with previously acquired, highly familiar words in a group of patients with bilateral hippocampal damage and amnesia. Relative to healthy demographically matched comparison participants and a group of brain-damaged comparison participants, the patients with hippocampal amnesia performed significantly worse on both productive and receptive measures of vocabulary depth and semantic richness. These findings suggest that remote semantic memory is impoverished in patients with hippocampal amnesia and that the hippocampus may play a role in the maintenance and updating of semantic memory beyond its initial acquisition.

  10. Remote semantic memory is impoverished in hippocampal amnesia

    PubMed Central

    Klooster, Nathaniel B.; Duff, Melissa C.

    2015-01-01

    The necessity of the hippocampus for acquiring new semantic concepts is a topic of considerable debate. However, it is generally accepted that any role the hippocampus plays in semantic memory is time limited and that previously acquired information becomes independent of the hippocampus over time. This view, along with intact naming and word-definition matching performance in amnesia, has led to the notion that remote semantic memory is intact in patients with hippocampal amnesia. Motivated by perspectives of word learning as a protracted process where additional features and senses of a word are added over time, and by recent discoveries about the time course of hippocampal contributions to on-line relational processing, reconsolidation, and the flexible integration of information, we revisit the notion that remote semantic memory is intact in amnesia. Using measures of semantic richness and vocabulary depth from psycholinguistics and first and second language-learning studies, we examined how much information is associated with previously acquired, highly familiar words in a group of patients with bilateral hippocampal damage and amnesia. Relative to healthy demographically matched comparison participants and a group of brain-damaged comparison participants, the patients with hippocampal amnesia performed significantly worse on both productive and receptive measures of vocabulary depth and semantic richness. These findings suggest that remote semantic memory is impoverished in patients with hippocampal amnesia and that the hippocampus may play a role in the maintenance and updating of semantic memory beyond its initial acquisition. PMID:26474741

  11. Rule-based mechanisms of learning for intelligent adaptive flight control

    NASA Technical Reports Server (NTRS)

    Handelman, David A.; Stengel, Robert F.

    1990-01-01

    How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

  12. Spatial Queries Entity Recognition and Disambiguation Using Rule-Based Approach

    NASA Astrophysics Data System (ADS)

    Hamzei, E.; Hakimpour, F.; Forati, A.

    2015-12-01

    In the digital world, search engines have been proposed as one of challenging research areas. One of the main issues in search engines studies is query processing, which its aim is to understand user's needs. If unsuitable spatial query processing approach is employed, the results will be associated with high degree of ambiguity. To evade such degree of ambiguity, in this paper we present a new algorithm which depends on rule-based systems to process queries. Our algorithm is implemented in the three basic steps including: deductively iterative splitting the query; finding candidates for the location names, the location types and spatial relationships; and finally checking the relationships logically and conceptually using a rule based system. As we finally present in the paper using our proposed method have two major advantages: the search engines can provide the capability of spatial analysis based on the specific process and secondly because of its disambiguation technique, user reaches the more desirable result.

  13. A self-learning rule base for command following in dynamical systems

    NASA Technical Reports Server (NTRS)

    Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

    1992-01-01

    In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

  14. Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

    PubMed

    van Ginneken, Bram

    2017-03-01

    Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

  15. Auto-Generated Semantic Processing Services

    NASA Technical Reports Server (NTRS)

    Davis, Rodney; Hupf, Greg

    2009-01-01

    Auto-Generated Semantic Processing (AGSP) Services is a suite of software tools for automated generation of other computer programs, denoted cross-platform semantic adapters, that support interoperability of computer-based communication systems that utilize a variety of both new and legacy communication software running in a variety of operating- system/computer-hardware combinations. AGSP has numerous potential uses in military, space-exploration, and other government applications as well as in commercial telecommunications. The cross-platform semantic adapters take advantage of common features of computer- based communication systems to enforce semantics, messaging protocols, and standards of processing of streams of binary data to ensure integrity of data and consistency of meaning among interoperating systems. The auto-generation aspect of AGSP Services reduces development time and effort by emphasizing specification and minimizing implementation: In effect, the design, building, and debugging of software for effecting conversions among complex communication protocols, custom device mappings, and unique data-manipulation algorithms is replaced with metadata specifications that map to an abstract platform-independent communications model. AGSP Services is modular and has been shown to be easily integrable into new and legacy NASA flight and ground communication systems.

  16. A New Rule-Based System for the Construction and Structural Characterization of Artificial Proteins

    NASA Astrophysics Data System (ADS)

    Štambuk, Nikola; Konjevoda, Paško; Gotovac, Nikola

    In this paper, we present a new rule-based system for an artificial protein design incorporating ternary amino acid polarity (polar, nonpolar, and neutral). It may be used to design de novo α and β protein fold structures and mixed class proteins. The targeted molecules are artificial proteins with important industrial and biomedical applications, related to the development of diagnostic-therapeutic peptide pharmaceuticals, antibody mimetics, peptide vaccines, new nanobiomaterials and engineered protein scaffolds.

  17. Feature- versus rule-based generalization in rats, pigeons and humans.

    PubMed

    Maes, Elisa; De Filippo, Guido; Inkster, Angus B; Lea, Stephen E G; De Houwer, Jan; D'Hooge, Rudi; Beckers, Tom; Wills, Andy J

    2015-11-01

    Humans can spontaneously create rules that allow them to efficiently generalize what they have learned to novel situations. An enduring question is whether rule-based generalization is uniquely human or whether other animals can also abstract rules and apply them to novel situations. In recent years, there have been a number of high-profile claims that animals such as rats can learn rules. Most of those claims are quite weak because it is possible to demonstrate that simple associative systems (which do not learn rules) can account for the behavior in those tasks. Using a procedure that allows us to clearly distinguish feature-based from rule-based generalization (the Shanks-Darby procedure), we demonstrate that adult humans show rule-based generalization in this task, while generalization in rats and pigeons was based on featural overlap between stimuli. In brief, when learning that a stimulus made of two components ("AB") predicts a different outcome than its elements ("A" and "B"), people spontaneously abstract an opposites rule and apply it to new stimuli (e.g., knowing that "C" and "D" predict one outcome, they will predict that "CD" predicts the opposite outcome). Rats and pigeons show the reverse behavior-they generalize what they have learned, but on the basis of similarity (e.g., "CD" is similar to "C" and "D", so the same outcome is predicted for the compound stimulus as for the components). Genuinely rule-based behavior is observed in humans, but not in rats and pigeons, in the current procedure.

  18. Experiments in knowledge refinement for a large rule-based system

    NASA Astrophysics Data System (ADS)

    Harvey, Wilson A., Jr.; Tambe, Milind

    1993-08-01

    Knowledge-refinement is a central problem in the field of expert systems. For rule-based systems, refinement implies the addition, deletion, and modification of rules in the system so as to improve the system's overall performance. The goal of this research effort is to understand the methodology for refining large rule-based systems, as well as to develop tools that will be useful in refining such systems. The vehicle for our investigation is SPAM, a production system (rule-based system) for the interpretation of aerial imagery. Complex and computation-intensive systems like SPAM impose some unique constraints on knowledge refinement. More specifically, the credit/blame assignment problem for locating pieces of knowledge to refine becomes difficult. Given that constraint, we approach the problem in a bottom-up fashion, i.e., begin by refining portions of SPAM's knowledge base and then attempt to understand the interactions between them. We begin by identifying gaps and/or faults in the knowledge base by comparing SPAM's intermediate output to that of an expert, then modifying the knowledge base so that the system's output more accurately matches the expert's output. While this approach leads to some improvements, it also raises some interesting issues concerning the evaluation of refined knowledge at intermediate levels and of interaction between the refinements. This paper presents our initial efforts toward addressing these issues.

  19. A weighted rule based method for predicting malignancy of pulmonary nodules by nodule characteristics.

    PubMed

    Kaya, Aydın; Can, Ahmet Burak

    2015-08-01

    Predicting malignancy of solitary pulmonary nodules from computer tomography scans is a difficult and important problem in the diagnosis of lung cancer. This paper investigates the contribution of nodule characteristics in the prediction of malignancy. Using data from Lung Image Database Consortium (LIDC) database, we propose a weighted rule based classification approach for predicting malignancy of pulmonary nodules. LIDC database contains CT scans of nodules and information about nodule characteristics evaluated by multiple annotators. In the first step of our method, votes for nodule characteristics are obtained from ensemble classifiers by using image features. In the second step, votes and rules obtained from radiologist evaluations are used by a weighted rule based method to predict malignancy. The rule based method is constructed by using radiologist evaluations on previous cases. Correlations between malignancy and other nodule characteristics and agreement ratio of radiologists are considered in rule evaluation. To handle the unbalanced nature of LIDC, ensemble classifiers and data balancing methods are used. The proposed approach is compared with the classification methods trained on image features. Classification accuracy, specificity and sensitivity of classifiers are measured. The experimental results show that using nodule characteristics for malignancy prediction can improve classification results.

  20. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    NASA Technical Reports Server (NTRS)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  1. The Cognitive and Neural Expression of Semantic Memory Impairment in Mild Cognitive Impairment and Early Alzheimer's Disease

    ERIC Educational Resources Information Center

    Joubert, Sven; Brambati, Simona M.; Ansado, Jennyfer; Barbeau, Emmanuel J.; Felician, Olivier; Didic, Mira; Lacombe, Jacinthe; Goldstein, Rachel; Chayer, Celine; Kergoat, Marie-Jeanne

    2010-01-01

    Semantic deficits in Alzheimer's disease have been widely documented, but little is known about the integrity of semantic memory in the prodromal stage of the illness. The aims of the present study were to: (i) investigate naming abilities and semantic memory in amnestic mild cognitive impairment (aMCI), early Alzheimer's disease (AD) compared to…

  2. Semantic web data warehousing for caGrid.

    PubMed

    McCusker, James P; Phillips, Joshua A; González Beltrán, Alejandra; Finkelstein, Anthony; Krauthammer, Michael

    2009-10-01

    The National Cancer Institute (NCI) is developing caGrid as a means for sharing cancer-related data and services. As more data sets become available on caGrid, we need effective ways of accessing and integrating this information. Although the data models exposed on caGrid are semantically well annotated, it is currently up to the caGrid client to infer relationships between the different models and their classes. In this paper, we present a Semantic Web-based data warehouse (Corvus) for creating relationships among caGrid models. This is accomplished through the transformation of semantically-annotated caBIG Unified Modeling Language (UML) information models into Web Ontology Language (OWL) ontologies that preserve those semantics. We demonstrate the validity of the approach by Semantic Extraction, Transformation and Loading (SETL) of data from two caGrid data sources, caTissue and caArray, as well as alignment and query of those sources in Corvus. We argue that semantic integration is necessary for integration of data from distributed web services and that Corvus is a useful way of accomplishing this. Our approach is generalizable and of broad utility to researchers facing similar integration challenges.

  3. Temporal Representation in Semantic Graphs

    SciTech Connect

    Levandoski, J J; Abdulla, G M

    2007-08-07

    A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.

  4. Semantic Search of Web Services

    ERIC Educational Resources Information Center

    Hao, Ke

    2013-01-01

    This dissertation addresses semantic search of Web services using natural language processing. We first survey various existing approaches, focusing on the fact that the expensive costs of current semantic annotation frameworks result in limited use of semantic search for large scale applications. We then propose a vector space model based service…

  5. Semantator: semantic annotator for converting biomedical text to linked data.

    PubMed

    Tao, Cui; Song, Dezhao; Sharma, Deepak; Chute, Christopher G

    2013-10-01

    More than 80% of biomedical data is embedded in plain text. The unstructured nature of these text-based documents makes it challenging to easily browse and query the data of interest in them. One approach to facilitate browsing and querying biomedical text is to convert the plain text to a linked web of data, i.e., converting data originally in free text to structured formats with defined meta-level semantics. In this paper, we introduce Semantator (Semantic Annotator), a semantic-web-based environment for annotating data of interest in biomedical documents, browsing and querying the annotated data, and interactively refining annotation results if needed. Through Semantator, information of interest can be either annotated manually or semi-automatically using plug-in information extraction tools. The annotated results will be stored in RDF and can be queried using the SPARQL query language. In addition, semantic reasoners can be directly applied to the annotated data for consistency checking and knowledge inference. Semantator has been released online and was used by the biomedical ontology community who provided positive feedbacks. Our evaluation results indicated that (1) Semantator can perform the annotation functionalities as designed; (2) Semantator can be adopted in real applications in clinical and transactional research; and (3) the annotated results using Semantator can be easily used in Semantic-web-based reasoning tools for further inference.

  6. THE TWO-LEVEL THEORY OF VERB MEANING: AN APPROACH TO INTEGRATING THE SEMANTICS OF ACTION WITH THE MIRROR NEURON SYSTEM

    PubMed Central

    Kemmerer, David; Castillo, Javier Gonzalez

    2010-01-01

    Verbs have two separate levels of meaning. One level reflects the uniqueness of every verb and is called the “root.” The other level consists of a more austere representation that is shared by all the verbs in a given class and is called the “event structure template.” We explore the following hypotheses about how, with specific reference to the motor features of action verbs, these two distinct levels of semantic representation might correspond to two distinct levels of the mirror neuron system. Hypothesis 1: Root-level motor features of verb meaning are partially subserved by somatotopically mapped mirror neurons in the left primary motor and/or premotor cortices. Hypothesis 2: Template-level motor features of verb meaning are partially subserved by representationally more schematic mirror neurons in Brodmann area 44 of the left inferior frontal gyrus. Evidence has been accumulating in support of the general neuroanatomical claims made by these two hypotheses—namely, that each level of verb meaning is associated with the designated cortical areas. However, as yet no studies have satisfied all the criteria necessary to support the more specific neurobiological claims made by the two hypotheses—namely, that each level of verb meaning is associated with mirror neurons in the pertinent brain regions. This would require demonstrating that within those regions the same neuronal populations are engaged during (a) the linguistic processing of particular motor features of verb meaning, (b) the execution of actions with the corresponding motor features, and (c) the observation of actions with the corresponding motor features. PMID:18996582

  7. Incorporating Semantic Knowledge into Dynamic Data Processing for Smart Power Grids

    SciTech Connect

    Zhou, Qunzhi; Simmhan, Yogesh; Prasanna, Viktor

    2012-11-15

    Semantic Web allows us to model and query time-invariant or slowly evolving knowledge using ontologies. Emerging applications in Cyber Physical Systems such as Smart Power Grids that require continuous information monitoring and integration present novel opportunities and challenges for Semantic Web technologies. Semantic Web is promising to model diverse Smart Grid domain knowledge for enhanced situation awareness and response by multi-disciplinary participants. However, current technology does pose a performance overhead for dynamic analysis of sensor measurements. In this paper, we combine semantic web and complex event processing for stream based semantic querying. We illustrate its adoption in the USC Campus Micro-Grid for detecting and enacting dynamic response strategies to peak power situations by diverse user roles. We also describe the semantic ontology and event query model that supports this. Further, we introduce and evaluate caching techniques to improve the response time for semantic event queries to meet our application needs and enable sustainable energy management.

  8. Embedding of Semantic Predications.

    PubMed

    Cohen, Trevor; Widdows, Dominic

    2017-03-08

    This paper concerns the generation of distributed vector representations of biomedical concepts from structured knowledge, in the form of subject-relation-object triplets known as semantic predications. Specifically, we evaluate the extent to which a representational approach we have developed for this purpose previously, known as Predication-based Semantic Indexing (PSI), might benefit from insights gleaned from neural-probabilistic language models, which have enjoyed a surge in popularity in recent years as a means to generate distributed vector representations of terms from free text. To do so, we develop a novel neural-probabilistic approach to encoding predications, called Embedding of Semantic Predications (ESP), by adapting aspects of the Skipgram with Negative Sampling (SGNS) algorithm to this purpose. We compare ESP and PSI across a number of tasks including recovery of encoded information, estimation of semantic similarity and relatedness, and identification of potentially therapeutic and harmful relationships using both analogical retrieval and supervised learning. We find advantages for ESP in some, but not all of these tasks, revealing the contexts in which the additional computational work of neural-probabilistic modeling is justified.

  9. Environmental Attitudes Semantic Differential.

    ERIC Educational Resources Information Center

    Mehne, Paul R.; Goulard, Cary J.

    This booklet is an evaluation instrument which utilizes semantic differential data to assess environmental attitudes. Twelve concepts are included: regulated access to beaches, urban planning, dune vegetation, wetlands, future cities, reclaiming wetlands for building development, city parks, commercial development of beaches, existing cities,…

  10. Semantically Grounded Briefings

    DTIC Science & Technology

    2005-12-01

    occurring relations. AeroText and consequently AeroDAML can be tailored to particular domains through training sessions with annotated corpuses...the complexities of semantic markup by using mnemonic names for URIs, hiding unnamed intermediate objects (represented by “ GenSym ” identifiers), and

  11. Semantic and Lexical Coherence.

    ERIC Educational Resources Information Center

    Fahnestock, Jeanne

    Helping students understand coherence in terms of the lexical ties and semantic relations possible between clauses and sentences formalizes an area of writing instruction that has been somewhat vague before and makes the process of creating a coherent paragraph less mysterious. Many students do not have the intuitive knowledge base for absorbing…

  12. "Dyslexia": Toward Semantical Clarification.

    ERIC Educational Resources Information Center

    Manzo, Anthony V.; Duffelmeyer, Fred

    A formulated definition of the term dyslexia is proposed in this paper in order to clarify the semantical confusion which exists among both specialists and the general public. Dyslexia is explained as a generic term for severe and puzzling reading disability, found to be both acute (where reading-age lags 25 percent or more below mental age) and…

  13. Latent Semantic Analysis.

    ERIC Educational Resources Information Center

    Dumais, Susan T.

    2004-01-01

    Presents a literature review that covers the following topics related to Latent Semantic Analysis (LSA): (1) LSA overview; (2) applications of LSA, including information retrieval (IR), information filtering, cross-language retrieval, and other IR-related LSA applications; (3) modeling human memory, including the relationship of LSA to other…

  14. Semantic Web Development

    DTIC Science & Technology

    2006-09-01

    many documents are not expressible in logica at all, and many in logic but not in N3. However, we are building a system for which a prime goal is the...demonstrate that conventional logica programming tools are efficent and straightforwradly adapted to semantic web work. • Jena RDF toolkit now accepts N3 as

  15. Applications and Methods Utilizing the Simple Semantic Web Architecture and Protocol (SSWAP) for Bioinformatics Resource Discovery and Disparate Data and Service Integration

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of scientific data between information resources difficu...

  16. Neural Substrates of Semantic Prospection – Evidence from the Dementias

    PubMed Central

    Irish, Muireann; Eyre, Nadine; Dermody, Nadene; O’Callaghan, Claire; Hodges, John R.; Hornberger, Michael; Piguet, Olivier

    2016-01-01

    The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15) and disease-matched behavioral-variant frontotemporal dementia (n = 15), neurodegenerative disorders characterized by significant medial temporal lobe (MTL) and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic) and non-personal (semantic) domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1-weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between gray matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal, and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

  17. Neural Substrates of Semantic Prospection - Evidence from the Dementias.

    PubMed

    Irish, Muireann; Eyre, Nadine; Dermody, Nadene; O'Callaghan, Claire; Hodges, John R; Hornberger, Michael; Piguet, Olivier

    2016-01-01

    The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer's disease (n = 15) and disease-matched behavioral-variant frontotemporal dementia (n = 15), neurodegenerative disorders characterized by significant medial temporal lobe (MTL) and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic) and non-personal (semantic) domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1-weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between gray matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal, and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

  18. Taxonomy, Ontology and Semantics at Johnson Space Center

    NASA Technical Reports Server (NTRS)

    Berndt, Sarah Ann

    2011-01-01

    At NASA Johnson Space Center (JSC), the Chief Knowledge Officer has been developing the JSC Taxonomy to capitalize on the accomplishments of yesterday while maintaining the flexibility needed for the evolving information environment of today. A clear vision and scope for the semantic system is integral to its success. The vision for the JSC Taxonomy is to connect information stovepipes to present a unified view for information and knowledge across the Center, across organizations, and across decades. Semantic search at JSC means seemless integration of disparate information sets into a single interface. Ever increasing use, interest, and organizational participation mark successful integration and provide the framework for future application.

  19. Exploring and linking biomedical resources through multidimensional semantic spaces

    PubMed Central

    2012-01-01

    Background The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). Results This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Conclusions Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations

  20. A fuzzy rule base system for object-based feature extraction and classification

    NASA Astrophysics Data System (ADS)

    Jin, Xiaoying; Paswaters, Scott

    2007-04-01

    In this paper, we present a fuzzy rule base system for object-based feature extraction and classification on remote sensing imagery. First, the object primitives are generated from the segmentation step. Object primitives are defined as individual regions with a set of attributes computed on the regions. The attributes computed include spectral, texture and shape measurements. Crisp rules are very intuitive to the users. They are usually represented as "GT (greater than)", "LT (less than)" and "IB (In Between)" with numerical values. The features can be manually generated by querying on the attributes using these crisp rules and monitoring the resulting selected object primitives. However, the attributes of different features are usually overlapping. The information is inexact and not suitable for traditional digital on/off decisions. Here a fuzzy rule base system is built to better model the uncertainty inherent in the data and vague human knowledge. Rather than representing attributes in linguistic terms like "Small", "Medium", "Large", we proposed a new method for automatic fuzzification of the traditional crisp concepts "GT", "LT" and "IB". Two sets of membership functions are defined to model those concepts. One is based on the piecewise linear functions, the other is based on S-type membership functions. A novel concept "fuzzy tolerance" is proposed to control the degree of fuzziness of each rule. The experimental results on classification and extracting features such as water, buildings, trees, fields and urban areas have shown that this newly designed fuzzy rule base system is intuitive and allows users to easily generate fuzzy rules.

  1. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

    PubMed Central

    Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

    2013-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

  2. Evaluation of a rule base for decision making in general practice.

    PubMed Central

    Essex, B; Healy, M

    1994-01-01

    BACKGROUND. Decision making in general practice relies heavily on judgmental expertise. It should be possible to codify this expertise into rules and principles. AIM. A study was undertaken to evaluate the effectiveness, of rules from a rule base designed to improve students' and trainees' management decisions relating to patients seen in general practice. METHOD. The rule base was developed after studying decisions about and management of thousands of patients seen in one general practice over an eight year period. Vignettes were presented to 93 fourth year medical students and 179 general practitioner trainees. They recorded their perception and management of each case before and after being presented with a selection of relevant rules. Participants also commented on their level of agreement with each of the rules provided with the vignettes. A panel of five independent assessors then rated as good, acceptable or poor, the participants' perception and management of each case before and after seeing the rules. RESULTS. Exposure to a few selected rules of thumb improved the problem perception and management decisions of both undergraduates and trainees. The degree of improvement was not related to previous experience or to the stated level of agreement with the proposed rules. The assessors identified difficulties students and trainees experienced in changing their perceptions and management decisions when the rules suggested options they had not considered. CONCLUSION. The rules developed to improve decision making skills in general practice are effective when used with vignettes. The next phase is to transform the rule base into an expert system to train students and doctors to acquire decision making skills. It could also be used to provide decision support when confronted with difficult management decisions in general practice. PMID:8204334

  3. Compensatory processing during rule-based category learning in older adults.

    PubMed

    Bharani, Krishna L; Paller, Ken A; Reber, Paul J; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G

    2016-01-01

    Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.

  4. Semantic similarity measure in biomedical domain leverage web search engine.

    PubMed

    Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

    2010-01-01

    Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

  5. A conceptual model to empower software requirements conflict detection and resolution with rule-based reasoning

    NASA Astrophysics Data System (ADS)

    Ahmad, Sabrina; Jalil, Intan Ermahani A.; Ahmad, Sharifah Sakinah Syed

    2016-08-01

    It is seldom technical issues which impede the process of eliciting software requirements. The involvement of multiple stakeholders usually leads to conflicts and therefore the need of conflict detection and resolution effort is crucial. This paper presents a conceptual model to further improve current efforts. Hence, this paper forwards an improved conceptual model to assist the conflict detection and resolution effort which extends the model ability and improves overall performance. The significant of the new model is to empower the automation of conflicts detection and its severity level with rule-based reasoning.

  6. A rule-based approach to model checking of UML state machines

    NASA Astrophysics Data System (ADS)

    Grobelna, Iwona; Grobelny, Michał; Stefanowicz, Łukasz

    2016-12-01

    In the paper a new approach to formal verification of control process specification expressed by means of UML state machines in version 2.x is proposed. In contrast to other approaches from the literature, we use the abstract and universal rule-based logical model suitable both for model checking (using the nuXmv model checker), but also for logical synthesis in form of rapid prototyping. Hence, a prototype implementation in hardware description language VHDL can be obtained that fully reflects the primary, already formally verified specification in form of UML state machines. Presented approach allows to increase the assurance that implemented system meets the user-defined requirements.

  7. Traditional Versus Rule-Based Programming Techniques: Application To The Control Of Optional Flight Information

    NASA Astrophysics Data System (ADS)

    Ricks, Wendell R.; Abbott, Kathy H.

    1987-05-01

    To the software design community, the concern over the costs associated with a program's execution time and implementation is great. It is always desirable, and sometimes imperative, that the proper programming technique is chosen which minimizes all costs for a given application or type of application. This paper describes a study that compared the cost-related factors associated with traditional programming techniques to rale-based programming techniques for a specific application. The results of this study favored the traditional approach regarding execution efficiency, but favored the rule-based approach regarding programmer productivity (implementation ease). Although this study examined a specific application, the resuli:s should be widely applicable.

  8. Distinct pathways for rule-based retrieval and spatial mapping of memory representations in hippocampal neurons

    PubMed Central

    Navawongse, Rapeechai; Eichenbaum, Howard

    2013-01-01

    Hippocampal neurons encode events within the context in which they occurred, a fundamental feature of episodic memory. Here we explored the sources of event and context information represented by hippocampal neurons during the retrieval of object associations in rats. Temporary inactivation of the medial prefrontal cortex differentially reduced the selectivity of rule-based object associations represented by hippocampal neuronal firing patterns but did not affect spatial firing patterns. By contrast, inactivation of the medial entorhinal cortex resulted in a pervasive reorganization of hippocampal mappings of spatial context and events. These results suggest distinct and cooperative prefrontal and medial temporal mechanisms in memory representation. PMID:23325238

  9. Predicting the relatiave vulnerability of near-coastal species to climate change using a rule-based ecoinformatics approach

    EPA Science Inventory

    Background/Questions/Methods Near-coastal species are threatened by multiple climate change drivers, including temperature increases, ocean acidification, and sea level rise. To identify vulnerable habitats, geographic regions, and species, we developed a sequential, rule-based...

  10. Semantic interoperability between clinical and public health information systems for improving public health services.

    PubMed

    Lopez, Diego M; Blobel, Bernd G M E

    2007-01-01

    Improving public health services requires comprehensively integrating all services including medical, social, community, and public health ones. Therefore, developing integrated health information services has to start considering business process, rules and information semantics of involved domains. The paper proposes a business and information architecture for the specification of a future-proof national integrated system, concretely the requirements for semantic integration between public health surveillance and clinical information systems. The architecture is a semantically interoperable approach because it describes business process, rules and information semantics based on national policy documents and expressed in a standard language such us the Unified Modeling Language UML. Having the enterprise and information models formalized, semantically interoperable Health IT components/services development is supported.

  11. Parameters of Semantic Multisensory Integration Depend on Timing and Modality Order among People on the Autism Spectrum: Evidence from Event-Related Potentials

    ERIC Educational Resources Information Center

    Russo, N.; Mottron, L.; Burack, J. A.; Jemel, B.

    2012-01-01

    Individuals with autism spectrum disorders (ASD) report difficulty integrating simultaneously presented visual and auditory stimuli (Iarocci & McDonald, 2006), albeit showing enhanced perceptual processing of unisensory stimuli, as well as an enhanced role of perception in higher-order cognitive tasks (Enhanced Perceptual Functioning (EPF) model;…

  12. Meaningful Physical Changes Mediate Lexical-Semantic Integration: Top-Down and Form-Based Bottom-Up Information Sources Interact in the N400

    ERIC Educational Resources Information Center

    Lotze, Netaya; Tune, Sarah; Schlesewsky, Matthias; Bornkessel-Schlesewsky, Ina

    2011-01-01

    Models of how the human brain reconstructs an intended meaning from a linguistic input often draw upon the N400 event-related potential (ERP) component as evidence. Current accounts of the N400 emphasise either the role of contextually induced lexical preactivation of a critical word (Lau, Phillips, & Poeppel, 2008) or the ease of integration into…

  13. From Data to Semantic Information

    NASA Astrophysics Data System (ADS)

    Floridi, Luciano

    2003-06-01

    There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information.

  14. Latent Semantic Indexing of medical diagnoses using UMLS semantic structures.

    PubMed Central

    Chute, C. G.; Yang, Y.; Evans, D. A.

    1991-01-01

    The relational files within the UMLS Metathesaurus contain rich semantic associations to main concepts. We invoked the technique of Latent Semantic Indexing to generate information matrices based on these relationships and created "semantic vectors" using singular value decomposition. Evaluations were made on the complete set and subsets of Metathesaurus main concepts with the semantic type "Disease or Syndrome." Real number matrices were created with main concepts, lexical variants, synonyms, and associated expressions. Ancestors, children, siblings, and related terms were added to alternative matrices, preserving the hierarchical direction of the relation as the imaginary component of a complex number. Preliminary evaluation suggests that this technique is robust. A major advantage is the exploitation of semantic features which derive from a statistical decomposition of UMLS structures, possibly reducing dependence on the tedious construction of semantic frames by humans. PMID:1807584

  15. The value of the Semantic Web in the laboratory.

    PubMed

    Frey, Jeremy G

    2009-06-01

    The Semantic Web is beginning to impact on the wider chemical and physical sciences, beyond the earlier adopted bio-informatics. While useful in large-scale data driven science with automated processing, these technologies can also help integrate the work of smaller scale laboratories producing diverse data. The semantics aid the discovery, reliable re-use of data, provide improved provenance and facilitate automated processing by increased resilience to changes in presentation and reduced ambiguity. The Semantic Web, its tools and collections are not yet competitive with well-established solutions to current problems. It is in the reduced cost of instituting solutions to new problems that the versatility of Semantic Web-enabled data and resources will make their mark once the more general-purpose tools are more available.

  16. Concepts as Semantic Pointers: A Framework and Computational Model.

    PubMed

    Blouw, Peter; Solodkin, Eugene; Thagard, Paul; Eliasmith, Chris

    2016-07-01

    The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts with a more finely grained taxonomy of mental representations. In this paper, we describe an alternative approach involving a single class of mental representations called "semantic pointers." Semantic pointers are symbol-like representations that result from the compression and recursive binding of perceptual, lexical, and motor representations, effectively integrating traditional connectionist and symbolic approaches. We present a computational model using semantic pointers that replicates experimental data from categorization studies involving each prior paradigm. We argue that a framework involving semantic pointers can provide a unified account of conceptual phenomena, and we compare our framework to existing alternatives in accounting for the scope, content, recursive combination, and neural implementation of concepts.

  17. A rule-based approach for the correlation of alarms to support Disaster and Emergency Management

    NASA Astrophysics Data System (ADS)

    Gloria, M.; Minei, G.; Lersi, V.; Pasquariello, D.; Monti, C.; Saitto, A.

    2009-04-01

    Key words: Simple Event Correlator, Agent Platform, Ontology, Semantic Web, Distributed Systems, Emergency Management The importance of recognition of emergency's typology to control the critical situation for security of citizens has been always recognized. It follows this aspect is very important for proper management of a hazardous event. In this work we present a solution for the recognition of emergency's typology adopted by an Italian research project, called CI6 (Centro Integrato per Servizi di Emergenza Innovativi). In our approach, CI6 receives alarms by citizen or people involved in the work (for example: police, operator of 112, and so on). CI6 represents any alarm by a set of information, including a text that describes it and obtained when the user points out the danger, and a pair of coordinates for its location. The system realizes an analysis of text and automatically infers information on the type of emergencies by means a set of parsing rules and rules of inference applied by a independent module: a correlator of events based on their log and called Simple Event Correlator (SEC). SEC, integrated in CI6's platform, is an open source and platform independent event correlation tool. SEC accepts input both files and text derived from standard input, making it flexible because it can be matched to any application that is able to write its output to a file stream. The SEC configuration is stored in text files as rules, each rule specifying an event matching condition, an action list, and optionally a Boolean expression whose truth value decides whether the rule can be applied at a given moment. SEC can produce output events by executing user-specified shell scripts or programs, by writing messages to files, and by various other means. SEC has been successfully applied in various domains like network management, system monitoring, data security, intrusion detection, log file monitoring and analysis, etc; it has been used or integrated with many

  18. A Rule Based Approach to ISS Interior Volume Control and Layout

    NASA Technical Reports Server (NTRS)

    Peacock, Brian; Maida, Jim; Fitts, David; Dory, Jonathan

    2001-01-01

    Traditional human factors design involves the development of human factors requirements based on a desire to accommodate a certain percentage of the intended user population. As the product is developed human factors evaluation involves comparison between the resulting design and the specifications. Sometimes performance metrics are involved that allow leniency in the design requirements given that the human performance result is satisfactory. Clearly such approaches may work but they give rise to uncertainty and negotiation. An alternative approach is to adopt human factors design rules that articulate a range of each design continuum over which there are varying outcome expectations and interactions with other variables, including time. These rules are based on a consensus of human factors specialists, designers, managers and customers. The International Space Station faces exactly this challenge in interior volume control, which is based on anthropometric, performance and subjective preference criteria. This paper describes the traditional approach and then proposes a rule-based alternative. The proposed rules involve spatial, temporal and importance dimensions. If successful this rule-based concept could be applied to many traditional human factors design variables and could lead to a more effective and efficient contribution of human factors input to the design process.

  19. RB-ARD: A proof of concept rule-based abort

    NASA Technical Reports Server (NTRS)

    Smith, Richard; Marinuzzi, John

    1987-01-01

    The Abort Region Determinator (ARD) is a console program in the space shuttle mission control center. During shuttle ascent, the Flight Dynamics Officer (FDO) uses the ARD to determine the possible abort modes and make abort calls for the crew. The goal of the Rule-based Abort region Determinator (RB/ARD) project was to test the concept of providing an onboard ARD for the shuttle or an automated ARD for the mission control center (MCC). A proof of concept rule-based system was developed on a LMI Lambda computer using PICON, a knowdedge-based system shell. Knowdedge derived from documented flight rules and ARD operation procedures was coded in PICON rules. These rules, in conjunction with modules of conventional code, enable the RB-ARD to carry out key parts of the ARD task. Current capabilities of the RB-ARD include: continuous updating of the available abort mode, recognition of a limited number of main engine faults and recommendation of safing actions. Safing actions recommended by the RB-ARD concern the Space Shuttle Main Engine (SSME) limit shutdown system and powerdown of the SSME Ac buses.

  20. The relevance of a rules-based maize marketing policy: an experimental case study of Zambia.

    PubMed

    Abbink, Klaus; Jayne, Thomas S; Moller, Lars C

    2011-01-01

    Strategic interaction between public and private actors is increasingly recognised as an important determinant of agricultural market performance in Africa and elsewhere. Trust and consultation tends to positively affect private activity while uncertainty of government behaviour impedes it. This paper reports on a laboratory experiment based on a stylised model of the Zambian maize market. The experiment facilitates a comparison between discretionary interventionism and a rules-based policy in which the government pre-commits itself to a future course of action. A simple precommitment rule can, in theory, overcome the prevailing strategic dilemma by encouraging private sector participation. Although this result is also borne out in the economic experiment, the improvement in private sector activity is surprisingly small and not statistically significant due to irrationally cautious choices by experimental governments. Encouragingly, a rules-based policy promotes a much more stable market outcome thereby substantially reducing the risk of severe food shortages. These results underscore the importance of predictable and transparent rules for the state's involvement in agricultural markets.

  1. Automated detection of pain from facial expressions: a rule-based approach using AAM

    NASA Astrophysics Data System (ADS)

    Chen, Zhanli; Ansari, Rashid; Wilkie, Diana J.

    2012-02-01

    In this paper, we examine the problem of using video analysis to assess pain, an important problem especially for critically ill, non-communicative patients, and people with dementia. We propose and evaluate an automated method to detect the presence of pain manifested in patient videos using a unique and large collection of cancer patient videos captured in patient homes. The method is based on detecting pain-related facial action units defined in the Facial Action Coding System (FACS) that is widely used for objective assessment in pain analysis. In our research, a person-specific Active Appearance Model (AAM) based on Project-Out Inverse Compositional Method is trained for each patient individually for the modeling purpose. A flexible representation of the shape model is used in a rule-based method that is better suited than the more commonly used classifier-based methods for application to the cancer patient videos in which pain-related facial actions occur infrequently and more subtly. The rule-based method relies on the feature points that provide facial action cues and is extracted from the shape vertices of AAM, which have a natural correspondence to face muscular movement. In this paper, we investigate the detection of a commonly used set of pain-related action units in both the upper and lower face. Our detection results show good agreement with the results obtained by three trained FACS coders who independently reviewed and scored the action units in the cancer patient videos.

  2. Automated Diagnosis of Heart Sounds Using Rule-Based Classification Tree.

    PubMed

    Karar, Mohamed Esmail; El-Khafif, Sahar H; El-Brawany, Mohamed A

    2017-04-01

    In order to assist the diagnosis procedure of heart sound signals, this paper presents a new automated method for classifying the heart status using a rule-based classification tree into normal and three abnormal cases; namely the aortic valve stenosis, aortic insufficient, and ventricular septum defect. The developed method includes three main steps as follows. First, one cycle of the heart sound signals is automatically detected and segmented based on time properties of the heart signals. Second, the segmented cycle is preprocessed with the discrete wavelet transform and then largest Lyapunov exponents are calculated to generate the dynamical features of heart sound time series. Finally, a rule-based classification tree is fed by these Lyapunov exponents to give the final decision of the heart health status. The developed method has been tested successfully on twenty-two datasets of normal heart sounds and murmurs with success rate of 95.5%. The resulting error can be easily corrected by modifying the classification rules; consequently, the accuracy of automated heart sounds diagnosis is further improved.

  3. A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

    NASA Technical Reports Server (NTRS)

    Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.

    1992-01-01

    In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

  4. Mapping Rule-Based And Stochastic Constraints To Connection Architectures: Implication For Hierarchical Image Processing

    NASA Astrophysics Data System (ADS)

    Miller, Michael I.; Roysam, Badrinath; Smith, Kurt R.

    1988-10-01

    Essential to the solution of ill posed problems in vision and image processing is the need to use object constraints in the reconstruction. While Bayesian methods have shown the greatest promise, a fundamental difficulty has persisted in that many of the available constraints are in the form of deterministic rules rather than as probability distributions and are thus not readily incorporated as Bayesian priors. In this paper, we propose a general method for mapping a large class of rule-based constraints to their equivalent stochastic Gibbs' distribution representation. This mapping allows us to solve stochastic estimation problems over rule-generated constraint spaces within a Bayesian framework. As part of this approach we derive a method based on Langevin's stochastic differential equation and a regularization technique based on the classical autologistic transfer function that allows us to update every site simultaneously regardless of the neighbourhood structure. This allows us to implement a completely parallel method for generating the constraint sets corresponding to the regular grammar languages on massively parallel networks. We illustrate these ideas by formulating the image reconstruction problem based on a hierarchy of rule-based and stochastic constraints, and derive a fully parallelestimator structure. We also present results computed on the AMT DAP500 massively parallel digital computer, a mesh-connected 32x32 array of processing elements which are configured in a Single-Instruction, Multiple Data stream architecture.

  5. A fuzzy rule based metamodel for monthly catchment nitrate fate simulations

    NASA Astrophysics Data System (ADS)

    van der Heijden, S.; Haberlandt, U.

    2015-12-01

    The high complexity of nitrate dynamics and corresponding deterministic models make it very appealing to employ easy, fast, and parsimonious modelling alternatives for decision support. This study presents a fuzzy rule based metamodel consisting of eight fuzzy modules, which is able to simulate nitrate fluxes in large watersheds from their diffuse sources via surface runoff, interflow, and base flow to the catchment outlet. The fuzzy rules are trained on a database established with a calibrated SWAT model for an investigation area of 1000 km2. The metamodel performs well on this training area and on two out of three validation areas in different landscapes, with a Nash-Sutcliffe coefficient of around 0.5-0.7 for the monthly nitrate calculations. The fuzzy model proves to be fast, requires only few readily available input data, and the rule based model structure facilitates a common-sense interpretation of the model, which deems the presented approach suitable for the development of decision support tools.

  6. Complex Semantic Networks

    NASA Astrophysics Data System (ADS)

    Teixeira, G. M.; Aguiar, M. S. F.; Carvalho, C. F.; Dantas, D. R.; Cunha, M. V.; Morais, J. H. M.; Pereira, H. B. B.; Miranda, J. G. V.

    Verbal language is a dynamic mental process. Ideas emerge by means of the selection of words from subjective and individual characteristics throughout the oral discourse. The goal of this work is to characterize the complex network of word associations that emerge from an oral discourse from a discourse topic. Because of that, concepts of associative incidence and fidelity have been elaborated and represented the probability of occurrence of pairs of words in the same sentence in the whole oral discourse. Semantic network of words associations were constructed, where the words are represented as nodes and the edges are created when the incidence-fidelity index between pairs of words exceeds a numerical limit (0.001). Twelve oral discourses were studied. The networks generated from these oral discourses present a typical behavior of complex networks and their indices were calculated and their topologies characterized. The indices of these networks obtained from each incidence-fidelity limit exhibit a critical value in which the semantic network has maximum conceptual information and minimum residual associations. Semantic networks generated by this incidence-fidelity limit depict a pattern of hierarchical classes that represent the different contexts used in the oral discourse.

  7. Models of Relevant Cue Integration in Name Retrieval

    ERIC Educational Resources Information Center

    Lombardi, Luigi; Sartori, Giuseppe

    2007-01-01

    Semantic features have different levels of importance in indexing a target concept. The article proposes that semantic relevance, an algorithmically derived measure based on concept descriptions, may efficiently capture the relative importance of different semantic features. Three models of how semantic features are integrated in terms of…

  8. Semantic Enhancement for Enterprise Data Management

    NASA Astrophysics Data System (ADS)

    Ma, Li; Sun, Xingzhi; Cao, Feng; Wang, Chen; Wang, Xiaoyuan; Kanellos, Nick; Wolfson, Dan; Pan, Yue

    Taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise. Existing CDM systems focus on integrating customer data from all customer-facing channels and front and back office systems through multiple interfaces, as well as publishing customer data to different applications. To make the effective use of the CDM system, this paper investigates semantic query and analysis over the integrated and centralized customer data, enabling automatic classification and relationship discovery. We have implemented these features over IBM Websphere Customer Center, and shown the prototype to our clients. We believe that our study and experiences are valuable for both Semantic Web community and data management community.

  9. Mathematical logic in the human brain: semantics.

    PubMed

    Friedrich, Roland M; Friederici, Angela D

    2013-01-01

    As a higher cognitive function in humans, mathematics is supported by parietal and prefrontal brain regions. Here, we give an integrative account of the role of the different brain systems in processing the semantics of mathematical logic from the perspective of macroscopic polysynaptic networks. By comparing algebraic and arithmetic expressions of identical underlying structure, we show how the different subparts of a fronto-parietal network are modulated by the semantic domain, over which the mathematical formulae are interpreted. Within this network, the prefrontal cortex represents a system that hosts three major components, namely, control, arithmetic-logic, and short-term memory. This prefrontal system operates on data fed to it by two other systems: a premotor-parietal top-down system that updates and transforms (external) data into an internal format, and a hippocampal bottom-up system that either detects novel information or serves as an access device to memory for previously acquired knowledge.

  10. Graph Mining Meets the Semantic Web

    SciTech Connect

    Lee, Sangkeun; Sukumar, Sreenivas R; Lim, Seung-Hwan

    2015-01-01

    The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.

  11. Mathematical Logic in the Human Brain: Semantics

    PubMed Central

    Friedrich, Roland M.; Friederici, Angela D.

    2013-01-01

    As a higher cognitive function in humans, mathematics is supported by parietal and prefrontal brain regions. Here, we give an integrative account of the role of the different brain systems in processing the semantics of mathematical logic from the perspective of macroscopic polysynaptic networks. By comparing algebraic and arithmetic expressions of identical underlying structure, we show how the different subparts of a fronto-parietal network are modulated by the semantic domain, over which the mathematical formulae are interpreted. Within this network, the prefrontal cortex represents a system that hosts three major components, namely, control, arithmetic-logic, and short-term memory. This prefrontal system operates on data fed to it by two other systems: a premotor-parietal top-down system that updates and transforms (external) data into an internal format, and a hippocampal bottom-up system that either detects novel information or serves as an access device to memory for previously acquired knowledge. PMID:23301101

  12. Description of a Rule-based System for the i2b2 Challenge in Natural Language Processing for Clinical Data

    PubMed Central

    Childs, Lois C.; Enelow, Robert; Simonsen, Lone; Heintzelman, Norris H.; Kowalski, Kimberly M.; Taylor, Robert J.

    2009-01-01

    The Obesity Challenge, sponsored by Informatics for Integrating Biology and the Bedside (i2b2), a National Center for Biomedical Computing, asked participants to build software systems that could “read” a patient's clinical discharge summary and replicate the judgments of physicians in evaluating presence or absence of obesity and 15 comorbidities. The authors describe their methodology and discuss the results of applying Lockheed Martin's rule-based natural language processing (NLP) capability, ClinREAD. We tailored ClinREAD with medical domain expertise to create assigned default judgments based on the most probable results as defined in the ground truth. It then used rules to collect evidence similar to the evidence that the human judges likely relied upon, and applied a logic module to weigh the strength of all evidence collected to arrive at final judgments. The Challenge results suggest that rule-based systems guided by human medical expertise are capable of solving complex problems in machine processing of medical text. PMID:19390103

  13. Semantic Metadata for Heterogeneous Spatial Planning Documents

    NASA Astrophysics Data System (ADS)

    Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

    2016-09-01

    Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

  14. Using semantic information for processing negation and disjunction in logic programs

    SciTech Connect

    Gaasterland, T.; Lobo, J.

    1993-07-01

    There are many applications in which integrity constraints can play an important role. An example is the semantic query optimization method developed by Chakravarthy, Grant, and Minker for definite deductive databases. They use integrity constraints during query processing to prevent the exploration of search space that is bound to fail. In this paper, the authors generalize the semantic query optimization method to apply to negated atoms. The generalized method is referred to as semantic compilation. They show that semantic compilation provides an alternative search space for negative query literals. They also show how semantic compilation can be used to transform a disjunctive database with or without functions and denial constraints without negation into a new disjunctive database that complies with the integrity constraints.

  15. Using semantic information for processing negation and disjunction in logic programs

    SciTech Connect

    Gaasterland, T. ); Lobo, J. )

    1993-01-01

    There are many applications in which integrity constraints can play an important role. An example is the semantic query optimization method developed by Chakravarthy, Grant, and Minker for definite deductive databases. They use integrity constraints during query processing to prevent the exploration of search space that is bound to fail. In this paper, the authors generalize the semantic query optimization method to apply to negated atoms. The generalized method is referred to as semantic compilation. They show that semantic compilation provides an alternative search space for negative query literals. They also show how semantic compilation can be used to transform a disjunctive database with or without functions and denial constraints without negation into a new disjunctive database that complies with the integrity constraints.

  16. Redundancy in perceptual and linguistic experience: comparing feature-based and distributional models of semantic representation.

    PubMed

    Riordan, Brian; Jones, Michael N

    2011-04-01

    Since their inception, distributional models of semantics have been criticized as inadequate cognitive theories of human semantic learning and representation. A principal challenge is that the representations derived by distributional models are purely symbolic and are not grounded in perception and action; this challenge has led many to favor feature-based models of semantic representation. We argue that the amount of perceptual and other semantic information that can be learned from purely distributional statistics has been underappreciated. We compare the representations of three feature-based and nine distributional models using a semantic clustering task. Several distributional models demonstrated semantic clustering comparable with clustering-based on feature-based representations. Furthermore, when trained on child-directed speech, the same distributional models perform as well as sensorimotor-based feature representations of children's lexical semantic knowledge. These results suggest that, to a large extent, information relevant for extracting semantic categories is redundantly coded in perceptual and linguistic experience. Detailed analyses of the semantic clusters of the feature-based and distributional models also reveal that the models make use of complementary cues to semantic organization from the two data streams. Rather than conceptualizing feature-based and distributional models as competing theories, we argue that future focus should be on understanding the cognitive mechanisms humans use to integrate the two sources.

  17. A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains.

    PubMed

    Sinaci, A Anil; Laleci Erturkmen, Gokce B

    2013-10-01

    In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems.

  18. SAS- Semantic Annotation Service for Geoscience resources on the web

    NASA Astrophysics Data System (ADS)

    Elag, M.; Kumar, P.; Marini, L.; Li, R.; Jiang, P.

    2015-12-01

    There is a growing need for increased integration across the data and model resources that are disseminated on the web to advance their reuse across different earth science applications. Meaningful reuse of resources requires semantic metadata to realize the semantic web vision for allowing pragmatic linkage and integration among resources. Semantic metadata associates standard metadata with resources to turn them into semantically-enabled resources on the web. However, the lack of a common standardized metadata framework as well as the uncoordinated use of metadata fields across different geo-information systems, has led to a situation in which standards and related Standard Names abound. To address this need, we have designed SAS to provide a bridge between the core ontologies required to annotate resources and information systems in order to enable queries and analysis over annotation from a single environment (web). SAS is one of the services that are provided by the Geosematnic framework, which is a decentralized semantic framework to support the integration between models and data and allow semantically heterogeneous to interact with minimum human intervention. Here we present the design of SAS and demonstrate its application for annotating data and models. First we describe how predicates and their attributes are extracted from standards and ingested in the knowledge-base of the Geosemantic framework. Then we illustrate the application of SAS in annotating data managed by SEAD and annotating simulation models that have web interface. SAS is a step in a broader approach to raise the quality of geoscience data and models that are published on the web and allow users to better search, access, and use of the existing resources based on standard vocabularies that are encoded and published using semantic technologies.

  19. The Semantic Mapping of Archival Metadata to the CIDOC CRM Ontology

    ERIC Educational Resources Information Center

    Bountouri, Lina; Gergatsoulis, Manolis

    2011-01-01

    In this article we analyze the main semantics of archival description, expressed through Encoded Archival Description (EAD). Our main target is to map the semantics of EAD to the CIDOC Conceptual Reference Model (CIDOC CRM) ontology as part of a wider integration architecture of cultural heritage metadata. Through this analysis, it is concluded…

  20. EIIS: An Educational Information Intelligent Search Engine Supported by Semantic Services

    ERIC Educational Resources Information Center

    Huang, Chang-Qin; Duan, Ru-Lin; Tang, Yong; Zhu, Zhi-Ting; Yan, Yong-Jian; Guo, Yu-Qing

    2011-01-01

    The semantic web brings a new opportunity for efficient information organization and search. To meet the special requirements of the educational field, this paper proposes an intelligent search engine enabled by educational semantic support service, where three kinds of searches are integrated into Educational Information Intelligent Search (EIIS)…

  1. The diagnosis of microcytic anemia by a rule-based expert system using VP-Expert.

    PubMed

    O'Connor, M L; McKinney, T

    1989-09-01

    We describe our experience in creating a rule-based expert system for the interpretation of microcytic anemia using the expert system development tool, VP-Expert, running on an IBM personal computer. VP-Expert processes data (complete blood cell count results, age, and sex) according to a set of user-written logic rules (our program) to reach conclusions as to the following causes of microcytic anemia: alpha- and beta-thalassemia trait, iron deficiency, and anemia of chronic disease. Our expert system was tested using previously interpreted complete blood cell count data. In most instances, there was good agreement between the expert system and its pathologist-author, but many discrepancies were found in the interpretation of anemia of chronic disease. We conclude that VP-Expert has a useful level of power and flexibility, yet is simple enough that individuals with modest programming experience can create their own expert systems. Limitations of such expert systems are discussed.

  2. Modeling for (physical) biologists: an introduction to the rule-based approach

    NASA Astrophysics Data System (ADS)

    Chylek, Lily A.; Harris, Leonard A.; Faeder, James R.; Hlavacek, William S.

    2015-07-01

    Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions.

  3. Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks

    PubMed Central

    Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

    2016-01-01

    In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles. PMID:27399709

  4. Choosing goals, not rules: deciding among rule-based action plans.

    PubMed

    Klaes, Christian; Westendorff, Stephanie; Chakrabarti, Shubhodeep; Gail, Alexander

    2011-05-12

    In natural situations, movements are often directed toward locations different from that of the evoking sensory stimulus. Movement goals must then be inferred from the sensory cue based on rules. When there is uncertainty about the rule that applies for a given cue, planning a movement involves both choosing the relevant rule and computing the movement goal based on that rule. Under these conditions, it is not clear whether primates compute multiple movement goals based on all possible rules before choosing an action, or whether they first choose a rule and then only represent the movement goal associated with that rule. Supporting the former hypothesis, we show that neurons in the frontoparietal reach areas of monkeys simultaneously represent two different rule-based movement goals, which are biased by the monkeys' choice preferences. Apparently, primates choose between multiple behavioral options by weighing against each other the movement goals associated with each option.

  5. Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks

    NASA Astrophysics Data System (ADS)

    Chiang, Y.-M.; Chang, L.-C.; Tsai, M.-J.; Wang, Y.-F.; Chang, F.-J.

    2010-09-01

    Pumping stations play an important role in flood mitigation in metropolitan areas. The existing sewerage systems, however, are facing a great challenge of fast rising peak flow resulting from urbanization and climate change. It is imperative to construct an efficient and accurate operating prediction model for pumping stations to simulate the drainage mechanism for discharging the rainwater in advance. In this study, we propose two rule-based fuzzy neural networks, adaptive neuro-fuzzy inference system (ANFIS) and counterpropagatiom fuzzy neural network (CFNN) for on-line predicting of the number of open and closed pumps of a pivotal pumping station in Taipei city up to a lead time of 20 min. The performance of ANFIS outperforms that of CFNN in terms of model efficiency, accuracy, and correctness. Furthermore, the results not only show the predictive water levels do contribute to the successfully operating pumping stations but also demonstrate the applicability and reliability of ANFIS in automatically controlling the urban sewerage systems.

  6. Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks

    NASA Astrophysics Data System (ADS)

    Chiang, Y.-M.; Chang, L.-C.; Tsai, M.-J.; Wang, Y.-F.; Chang, F.-J.

    2011-01-01

    Pumping stations play an important role in flood mitigation in metropolitan areas. The existing sewerage systems, however, are facing a great challenge of fast rising peak flow resulting from urbanization and climate change. It is imperative to construct an efficient and accurate operating prediction model for pumping stations to simulate the drainage mechanism for discharging the rainwater in advance. In this study, we propose two rule-based fuzzy neural networks, adaptive neuro-fuzzy inference system (ANFIS) and counterpropagation fuzzy neural network for on-line predicting of the number of open and closed pumps of a pivotal pumping station in Taipei city up to a lead time of 20 min. The performance of ANFIS outperforms that of CFNN in terms of model efficiency, accuracy, and correctness. Furthermore, the results not only show the predictive water levels do contribute to the successfully operating pumping stations but also demonstrate the applicability and reliability of ANFIS in automatically controlling the urban sewerage systems.

  7. Modeling for (physical) biologists: an introduction to the rule-based approach

    PubMed Central

    Chylek, Lily A; Harris, Leonard A; Faeder, James R; Hlavacek, William S

    2015-01-01

    Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions. PMID:26178138

  8. Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks.

    PubMed

    Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

    2016-07-07

    In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles.

  9. Neural changes associated with semantic processing in healthy aging despite intact behavioral performance.

    PubMed

    Lacombe, Jacinthe; Jolicoeur, Pierre; Grimault, Stephan; Pineault, Jessica; Joubert, Sven

    2015-10-01

    Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level.

  10. The UMLS Semantic Network and the Semantic Web.

    PubMed

    Kashyap, Vipul

    2003-01-01

    The Unified Medical Language System is an extensive source of biomedical knowledge developed and maintained by the US National Library of Medicine (NLM) and is being currently used in a wide variety of biomedical applications. The Semantic Network, a component of the UMLS is a structured description of core biomedical knowledge consisting of well defined semantic types and relationships between them. We investigate the expressiveness of DAML+OIL, a markup language proposed for ontologies on the Semantic Web, for representing the knowledge contained in the Semantic Network. Requirements specific to the Semantic Network, such as polymorphic relationships and blocking relationship inheritance are discussed and approaches to represent these in DAML+OIL are presented. Finally, conclusions are presented along with a discussion of ongoing and future work.

  11. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    NASA Astrophysics Data System (ADS)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  12. From science to e-Science to Semantic e-Science: A Heliophysics case study

    NASA Astrophysics Data System (ADS)

    Narock, Thomas; Fox, Peter

    2012-09-01

    The past few years have witnessed unparalleled efforts to make scientific data web accessible. The Semantic Web has proven invaluable in this effort; however, much of the literature is devoted to system design, ontology creation, and trials and tribulations of current technologies. In order to fully develop the nascent field of Semantic e-Science we must also evaluate systems in real-world settings. We describe a case study within the field of Heliophysics and provide a comparison of the evolutionary stages of data discovery, from manual to semantically enable. We describe the socio-technical implications of moving toward automated and intelligent data discovery. In doing so, we highlight how this process enhances what is currently being done manually in various scientific disciplines. Our case study illustrates that Semantic e-Science is more than just semantic search. The integration of search with web services, relational databases, and other cyberinfrastructure is a central tenet of our case study and one that we believe has applicability as a generalized research area within Semantic e-Science. This case study illustrates a specific example of the benefits, and limitations, of semantically replicating data discovery. We show examples of significant reductions in time and effort enable by Semantic e-Science; yet, we argue that a "complete" solution requires integrating semantic search with other research areas such as data provenance and web services.

  13. From Science to e-Science to Semantic e-Science: A Heliosphysics Case Study

    NASA Technical Reports Server (NTRS)

    Narock, Thomas; Fox, Peter

    2011-01-01

    The past few years have witnessed unparalleled efforts to make scientific data web accessible. The Semantic Web has proven invaluable in this effort; however, much of the literature is devoted to system design, ontology creation, and trials and tribulations of current technologies. In order to fully develop the nascent field of Semantic e-Science we must also evaluate systems in real-world settings. We describe a case study within the field of Heliophysics and provide a comparison of the evolutionary stages of data discovery, from manual to semantically enable. We describe the socio-technical implications of moving toward automated and intelligent data discovery. In doing so, we highlight how this process enhances what is currently being done manually in various scientific disciplines. Our case study illustrates that Semantic e-Science is more than just semantic search. The integration of search with web services, relational databases, and other cyberinfrastructure is a central tenet of our case study and one that we believe has applicability as a generalized research area within Semantic e-Science. This case study illustrates a specific example of the benefits, and limitations, of semantically replicating data discovery. We show examples of significant reductions in time and effort enable by Semantic e-Science; yet, we argue that a "complete" solution requires integrating semantic search with other research areas such as data provenance and web services.

  14. Semantic Knowledge for Famous Names in Mild Cognitive Impairment

    PubMed Central

    Seidenberg, Michael; Guidotti, Leslie; Nielson, Kristy A.; Woodard, John L.; Durgerian, Sally; Zhang, Qi; Gander, Amelia; Antuono, Piero; Rao, Stephen M.

    2008-01-01

    Person identification represents a unique category of semantic knowledge that is commonly impaired in Alzheimer's Disease (AD), but has received relatively little investigation in patients with Mild Cognitive Impairment (MCI). The current study examined the retrieval of semantic knowledge for famous names from three time epochs (recent, remote, and enduring) in two participant groups; 23 aMCI patients and 23 healthy elderly controls. The aMCI group was less accurate and produced less semantic knowledge than controls for famous names. Names from the enduring period were recognized faster than both recent and remote names in both groups, and remote names were recognized more quickly than recent names. Episodic memory performance was correlated with greater semantic knowledge particularly for recent names. We suggest that the anterograde memory deficits in the aMCI group interferes with learning of recent famous names and as a result produces difficulties with updating and integrating new semantic information with previously stored information. The implications of these findings for characterizing semantic memory deficits in MCI are discussed. PMID:19128524

  15. A Generic Evaluation Model for Semantic Web Services

    NASA Astrophysics Data System (ADS)

    Shafiq, Omair

    Semantic Web Services research has gained momentum over the last few Years and by now several realizations exist. They are being used in a number of industrial use-cases. Soon software developers will be expected to use this infrastructure to build their B2B applications requiring dynamic integration. However, there is still a lack of guidelines for the evaluation of tools developed to realize Semantic Web Services and applications built on top of them. In normal software engineering practice such guidelines can already be found for traditional component-based systems. Also some efforts are being made to build performance models for servicebased systems. Drawing on these related efforts in component-oriented and servicebased systems, we identified the need for a generic evaluation model for Semantic Web Services applicable to any realization. The generic evaluation model will help users and customers to orient their systems and solutions towards using Semantic Web Services. In this chapter, we have presented the requirements for the generic evaluation model for Semantic Web Services and further discussed the initial steps that we took to sketch such a model. Finally, we discuss related activities for evaluating semantic technologies.

  16. Semantic knowledge for famous names in mild cognitive impairment.

    PubMed

    Seidenberg, Michael; Guidotti, Leslie; Nielson, Kristy A; Woodard, John L; Durgerian, Sally; Zhang, Qi; Gander, Amelia; Antuono, Piero; Rao, Stephen M

    2009-01-01

    Person identification represents a unique category of semantic knowledge that is commonly impaired in Alzheimer's disease (AD), but has received relatively little investigation in patients with mild cognitive impairment (MCI). The current study examined the retrieval of semantic knowledge for famous names from three time epochs (recent, remote, and enduring) in two participant groups: 23 amnestic MCI (aMCI) patients and 23 healthy elderly controls. The aMCI group was less accurate and produced less semantic knowledge than controls for famous names. Names from the enduring period were recognized faster than both recent and remote names in both groups, and remote names were recognized more quickly than recent names. Episodic memory performance was correlated with greater semantic knowledge particularly for recent names. We suggest that the anterograde memory deficits in the aMCI group interferes with learning of recent famous names and as a result produces difficulties with updating and integrating new semantic information with previously stored information. The implications of these findings for characterizing semantic memory deficits in MCI are discussed. (JINS, 2009, 15, 9-18.).

  17. Establishing semantic interoperability of biomedical metadata registries using extended semantic relationships.

    PubMed

    Park, Yu Rang; Yoon, Young Jo; Kim, Hye Hyeon; Kim, Ju Han

    2013-01-01

    Achieving semantic interoperability is critical for biomedical data sharing between individuals, organizations and systems. The ISO/IEC 11179 MetaData Registry (MDR) standard has been recognized as one of the solutions for this purpose. The standard model, however, is limited. Representing concepts consist of two or more values, for instance, are not allowed including blood pressure with systolic and diastolic values. We addressed the structural limitations of ISO/IEC 11179 by an integrated metadata object model in our previous research. In the present study, we introduce semantic extensions for the model by defining three new types of semantic relationships; dependency, composite and variable relationships. To evaluate our extensions in a real world setting, we measured the efficiency of metadata reduction by means of mapping to existing others. We extracted metadata from the College of American Pathologist Cancer Protocols and then evaluated our extensions. With no semantic loss, one third of the extracted metadata could be successfully eliminated, suggesting better strategy for implementing clinical MDRs with improved efficiency and utility.

  18. Semantic Feature Distinctiveness and Frequency

    ERIC Educational Resources Information Center

    Lamb, Katherine M.

    2012-01-01

    Lexical access is the process in which basic components of meaning in language, the lexical entries (words) are activated. This activation is based on the organization and representational structure of the lexical entries. Semantic features of words, which are the prominent semantic characteristics of a word concept, provide important information…

  19. Semantic Research for Digital Libraries.

    ERIC Educational Resources Information Center

    Chen, Hsinchun

    1999-01-01

    Discusses the need for semantic research in digital libraries to help overcome interoperability problems. Highlights include federal initiatives; semantic analysis; knowledge representations; human-computer interactions and information visualization; and the University of Illinois DLI (Digital Libraries Initiative) project through partnership with…

  20. Semantic Tools in Information Retrieval.

    ERIC Educational Resources Information Center

    Rubinoff, Morris; Stone, Don C.

    This report discusses the problem of the meansings of words used in information retrieval systems, and shows how semantic tools can aid in the communication which takes place between indexers and searchers via index terms. After treating the differing use of semantic tools in different types of systems, two tools (classification tables and…

  1. Indexing by Latent Semantic Analysis.

    ERIC Educational Resources Information Center

    Deerwester, Scott; And Others

    1990-01-01

    Describes a new method for automatic indexing and retrieval called latent semantic indexing (LSI). Problems with matching query words with document words in term-based information retrieval systems are discussed, semantic structure is examined, singular value decomposition (SVD) is explained, and the mathematics underlying the SVD model is…

  2. Semantic Processing of Mathematical Gestures

    ERIC Educational Resources Information Center

    Lim, Vanessa K.; Wilson, Anna J.; Hamm, Jeff P.; Phillips, Nicola; Iwabuchi, Sarina J.; Corballis, Michael C.; Arzarello, Ferdinando; Thomas, Michael O. J.

    2009-01-01

    Objective: To examine whether or not university mathematics students semantically process gestures depicting mathematical functions (mathematical gestures) similarly to the way they process action gestures and sentences. Semantic processing was indexed by the N400 effect. Results: The N400 effect elicited by words primed with mathematical gestures…

  3. Information tables with neighborhood semantics

    NASA Astrophysics Data System (ADS)

    Yao, Yiyu

    2000-04-01

    Information tables provide a convenient and useful tool for representing a set of objects using a group of attributes. This notion is enriched by introducing neighborhood systems on attribute values. The neighborhood systems represent the semantics relationships between, and knowledge about, attribute values. With added semantics, neighborhood based information tables may provide a more general framework for knowledge discovery, data mining, and information retrieval.

  4. The semantic planetary data system

    NASA Technical Reports Server (NTRS)

    Hughes, J. Steven; Crichton, Daniel; Kelly, Sean; Mattmann, Chris

    2005-01-01

    This paper will provide a brief overview of the PDS data model and the PDS catalog. It will then describe the implentation of the Semantic PDS including the development of the formal ontology, the generation of RDFS/XML and RDF/XML data sets, and the buiding of the semantic search application.

  5. A Web-Based Multidrug-Resistant Organisms Surveillance and Outbreak Detection System with Rule-Based Classification and Clustering

    PubMed Central

    Tseng, Yi-Ju; Wu, Jung-Hsuan; Ping, Xiao-Ou; Lin, Hui-Chi; Chen, Ying-Yu; Shang, Rung-Ji; Chen, Ming-Yuan; Lai, Feipei

    2012-01-01

    Background The emergence and spread of multidrug-resistant organisms (MDROs) are causing a global crisis. Combating antimicrobial resistance requires prevention of transmission of resistant organisms and improved use of antimicrobials. Objectives To develop a Web-based information system for automatic integration, analysis, and interpretation of the antimicrobial susceptibility of all clinical isolates that incorporates rule-based classification and cluster analysis of MDROs and implements control chart analysis to facilitate outbreak detection. Methods Electronic microbiological data from a 2200-bed teaching hospital in Taiwan were classified according to predefined criteria of MDROs. The numbers of organisms, patients, and incident patients in each MDRO pattern were presented graphically to describe spatial and time information in a Web-based user interface. Hierarchical clustering with 7 upper control limits (UCL) was used to detect suspicious outbreaks. The system’s performance in outbreak detection was evaluated based on vancomycin-resistant enterococcal outbreaks determined by a hospital-wide prospective active surveillance database compiled by infection control personnel. Results The optimal UCL for MDRO outbreak detection was the upper 90% confidence interval (CI) using germ criterion with clustering (area under ROC curve (AUC) 0.93, 95% CI 0.91 to 0.95), upper 85% CI using patient criterion (AUC 0.87, 95% CI 0.80 to 0.93), and one standard deviation using incident patient criterion (AUC 0.84, 95% CI 0.75 to 0.92). The performance indicators of each UCL were statistically significantly higher with clustering than those without clustering in germ criterion (P < .001), patient criterion (P = .04), and incident patient criterion (P < .001). Conclusion This system automatically identifies MDROs and accurately detects suspicious outbreaks of MDROs based on the antimicrobial susceptibility of all clinical isolates. PMID:23195868

  6. Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

    NASA Astrophysics Data System (ADS)

    Shi, Liehang; Ling, Tonghui; Zhang, Jianguo

    2016-03-01

    Radiologists currently use a variety of terminologies and standards in most hospitals in China, and even there are multiple terminologies being used for different sections in one department. In this presentation, we introduce a medical semantic comprehension system (MedSCS) to extract semantic information about clinical findings and conclusion from free text radiology reports so that the reports can be classified correctly based on medical terms indexing standards such as Radlex or SONMED-CT. Our system (MedSCS) is based on both rule-based methods and statistics-based methods which improve the performance and the scalability of MedSCS. In order to evaluate the over all of the system and measure the accuracy of the outcomes, we developed computation methods to calculate the parameters of precision rate, recall rate, F-score and exact confidence interval.

  7. [Semantic information. Internal language. Thinking].

    PubMed

    Azcoaga, J E

    1993-06-01

    Semantic information has reached an objective condition after a lengthy history of semantic inquiries that instrumental neurophysiological devices--such as event-related potentials, electroencephalographic spectral analysis, regional brain circulation, PET scan, deep brain electrodes, and other--have made easier. In turn, internal language, as screened according to Vigotsky's perspective, is considered a product of semantic information circulation understood as neurosemae interconnection. Finally, in normal adults, thinking processes are assumed to be made up by both sensoperceptive information (proprioceptive information included) and semantic information. Thus, an "extraverbal thinking" can be distinguished, whose activity is hardly describable in healthy adults but should be considered as a condition of non-educated deaf persons, and a "verbal thinking", or internal language, made up by semantic information.

  8. Hierarchical abstract semantic model for image classification

    NASA Astrophysics Data System (ADS)

    Ye, Zhipeng; Liu, Peng; Zhao, Wei; Tang, Xianglong

    2015-09-01

    Semantic gap limits the performance of bag-of-visual-words. To deal with this problem, a hierarchical abstract semantics method that builds abstract semantic layers, generates semantic visual vocabularies, measures semantic gap, and constructs classifiers using the Adaboost strategy is proposed. First, abstract semantic layers are proposed to narrow the semantic gap between visual features and their interpretation. Then semantic visual words are extracted as features to train semantic classifiers. One popular form of measurement is used to quantify the semantic gap. The Adaboost training strategy is used to combine weak classifiers into strong ones to further improve performance. For a testing image, the category is estimated layer-by-layer. Corresponding abstract hierarchical structures for popular datasets, including Caltech-101 and MSRC, are proposed for evaluation. The experimental results show that the proposed method is capable of narrowing semantic gaps effectively and performs better than other categorization methods.

  9. A Semantic Grid Oriented to E-Tourism

    NASA Astrophysics Data System (ADS)

    Zhang, Xiao Ming

    With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.

  10. Improving healthcare middleware standards with semantic methods and technologies.

    PubMed

    Román, Isabel; Calvillo, Jorge; Roa, Laura M; Madinabeitia, Germán

    2008-01-01

    A critical issue in healthcare informatics is to facilitate the integration and interoperability of applications. This goal can be achieved through an open architecture based on a middleware independent from specific applications; useful for working with existing systems, as well as for the integration of new systems. Several standard organizations are making efforts toward this target. This work is based on the EN 12967-1,2,3, developed by CEN, that follows the ODP (Open Distributed Processing) methodology, providing a specification of distributed systems based on the definition of five viewpoints. However, only the three upper viewpoints are used to produce EN 12967, the two lower viewpoints should be considered in the implementation context. We are using Semantic Grid for lower views and Semantic Web and Web Services for the definition of the upper views. We analyze benefits of using these methods and technologies and expose methodology for the development of this semantic healthcare middleware observing European Standards.

  11. Management Tool for Semantic Annotations in WSDL

    NASA Astrophysics Data System (ADS)

    Boissel-Dallier, Nicolas; Lorré, Jean-Pierre; Benaben, Frédérick

    Semantic Web Services add features to automate web services discovery and composition. A new standard called SAWSDL emerged recently as a W3C recommendation to add semantic annotations within web service descriptions (WSDL). In order to manipulate such information in Java program we need an XML parser. Two open-source libraries already exist (SAWSDL4J and Woden4SAWSDL) but they don't meet all our specific needs such as support for WSDL 1.1 and 2.0. This paper presents a new tool, called EasyWSDL, which is able to handle semantic annotations as well as to manage the full WSDL description thanks to a plug-in mechanism. This tool allows us to read/edit/create a WSDL description and related annotations thanks to a uniform API, in both 1.1 and 2.0 versions. This document compares these three libraries and presents its integration into Dragon the OW2 open-source SOA governance tool.

  12. Semantic Web for Manufacturing Web Services

    SciTech Connect

    Kulvatunyou, Boonserm; Ivezic, Nenad

    2002-06-01

    As markets become unexpectedly turbulent with a shortened product life cycle and a power shift towards buyers, the need for methods to rapidly and cost-effectively develop products, production facilities and supporting software is becoming urgent. The use of a virtual enterprise plays a vital role in surviving turbulent markets. However, its success requires reliable and large-scale interoperation among trading partners via a semantic web of trading partners' services whose properties, capabilities, and interfaces are encoded in an unambiguous as well as computer-understandable form. This paper demonstrates a promising approach to integration and interoperation between a design house and a manufacturer by developing semantic web services for business and engineering transactions. To this end, detailed activity and information flow diagrams are developed, in which the two trading partners exchange messages and documents. The properties and capabilities of the manufacturer sites are defined using DARPA Agent Markup Language (DAML) ontology definition language. The prototype development of semantic webs shows that enterprises can widely interoperate in an unambiguous and autonomous manner; hence, virtual enterprise is realizable at a low cost.

  13. Distributed Semantic Overlay Networks

    NASA Astrophysics Data System (ADS)

    Doulkeridis, Christos; Vlachou, Akrivi; Nørvåg, Kjetil; Vazirgiannis, Michalis

    Semantic Overlay Networks (SONs) have been recently proposed as a way to organize content in peer-to-peer (P2P) networks. The main objective is to discover peers with similar content and then form thematically focused peer groups. Efficient content retrieval can be performed by having queries selectively forwarded only to relevant groups of peers to the query. As a result, less peers need to be contacted, in order to answer a query. In this context, the challenge is to generate SONs in a decentralized and distributed manner, as the centralized assembly of global information is not feasible. Different approaches for exploiting the generated SONs for content retrieval have been proposed in the literature, which are examined in this chapter, with a particular focus on SON interconnections for efficient search. Several applications, such as P2P document and image retrieval, can be deployed over generated SONs, motivating the need for distributed and truly scalable SON creation. Therefore, recently several research papers focus on SONs as stated in our comprehensive overview of related work in the field of semantic overlay networks. A classification of existing algorithms according to a set of qualitative criteria is also provided. In spite of the rich existing work in the field of SONs, several challenges have not been efficiently addressed yet, therefore, future promising research directions are pointed out and discussed at the end of this chapter.

  14. Semantic Workflows and Provenance

    NASA Astrophysics Data System (ADS)

    Gil, Y.

    2011-12-01

    While sharing and disseminating data is widely practiced across scientific communities, we have yet to recognize the importance of sharing and disseminating the analytic processes that leads to published data. Data retrieved from shared repositories and archives is often hard to interpret because we lack documentation about those processes: what models were used, what assumptions were made, what calibrations were carried out, etc. This process documentation is also key to aggregate data in a meaningful way, whether aggregating shared third party data or aggregating shared data with local sensor data collected by individual investigators. We suggest that augmenting published data with process documentation would greatly enhance our ability to find, reuse, interpret, and aggregate data and therefore have a significant impact in the utility of data repositories and archives. We will show that semantic workflows and provenance provide key technologies for capturing process documentation. Semantic workflows describe the kinds of data transformation and analysis steps used to create new data products, and can include useful constraints about why specific models were selected or parameters chosen. Provenance records can be used to publish workflow descriptions in standard formats that can be reused to enable verification and reproducibility of data products.

  15. "Pre-Semantic" Cognition Revisited: Critical Differences between Semantic Aphasia and Semantic Dementia

    ERIC Educational Resources Information Center

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

    2010-01-01

    Patients with semantic dementia show a specific pattern of impairment on both verbal and non-verbal "pre-semantic" tasks, e.g., reading aloud, past tense generation, spelling to dictation, lexical decision, object decision, colour decision and delayed picture copying. All seven tasks are characterised by poorer performance for items that are…

  16. X-Informatics: Practical Semantic Science

    NASA Astrophysics Data System (ADS)

    Borne, K. D.

    2009-12-01

    The discipline of data science is merging with multiple science disciplines to form new X-informatics research disciplines. They are almost too numerous to name, but they include geoinformatics, bioinformatics, cheminformatics, biodiversity informatics, ecoinformatics, materials informatics, and the emerging discipline of astroinformatics. Within any X-informatics discipline, the information granules are unique to that discipline -- e.g., gene sequences in bio, the sky object in astro, and the spatial object in geo (such as points, lines, and polygons in the vector model, and pixels in the raster model). Nevertheless the goals are similar: transparent data re-use across subdisciplines and within education settings, information and data integration and fusion, personalization of user interactions with the data collection, semantic search and retrieval, and knowledge discovery. The implementation of an X-informatics framework enables these semantic e-science research goals. We describe the concepts, challenges, and new developments associated with the new discipline of astroinformatics, and how geoinformatics provides valuable lessons learned and a model for practical semantic science within a traditional science discipline through the accretion of data science methodologies (such as formal metadata creation, data models, data mining, information retrieval, knowledge engineering, provenance, taxonomies, and ontologies). The emerging concept of data-as-a-service (DaaS) builds upon the concept of smart data (or data DNA) for intelligent data management, automated workflows, and intelligent processing. Smart data, defined through X-informatics, enables several practical semantic science use cases, including self-discovery, data intelligence, automatic recommendations, relevance analysis, dimension reduction, feature selection, constraint-based mining, interdisciplinary data re-use, knowledge-sharing, data use in education, and more. We describe these concepts within the

  17. ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-level Rule-based Models in Cell Biology.

    PubMed

    Bittig, Arne; Uhrmacher, Adelinde

    2016-08-03

    Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

  18. Revisiting intracellular calcium signaling semantics.

    PubMed

    Haiech, Jacques; Audran, Emilie; Fève, Marie; Ranjeva, Raoul; Kilhoffer, Marie-Claude

    2011-12-01

    Cells use intracellular free calcium concentration changes for signaling. Signal encoding occurs through both spatial and temporal modulation of the free calcium concentration. The encoded message is detected by an ensemble of intracellular sensors forming the family of calcium-binding proteins (CaBPs) which must faithfully translate the message using a new syntax that is recognized by the cell. The cell is home to a significant although limited number of genes coding for proteins involved in the signal encoding and decoding processes. In a cell, only a subset of this ensemble of genes is expressed, leading to a genetic regulation of the calcium signal pathways. Calmodulin (CaM), the most ubiquitous expressed intracellular calcium-binding protein, plays a major role in calcium signal translation. Similar to a hub, it is central to a large and finely tuned network, receiving information, integrating it and dispatching the cognate response. In this review, we examine the different steps starting with an external stimulus up to a cellular response, with special emphasis on CaM and the mechanism by which it decodes calcium signals and translates it into exquisitely coordinated cellular events. By this means, we will revisit the calcium signaling semantics, hoping that we will ease communication between scientists dealing with calcium signals in different biological systems and different domains.

  19. Improving protein coreference resolution by simple semantic classification

    PubMed Central

    2012-01-01

    Background Current research has shown that major difficulties in event extraction for the biomedical domain are traceable to coreference. Therefore, coreference resolution is believed to be useful for improving event extraction. To address coreference resolution in molecular biology literature, the Protein Coreference (COREF) task was arranged in the BioNLP Shared Task (BioNLP-ST, hereafter) 2011, as a supporting task. However, the shared task results indicated that transferring coreference resolution methods developed for other domains to the biological domain was not a straight-forward task, due to the domain differences in the coreference phenomena. Results We analyzed the contribution of domain-specific information, including the information that indicates the protein type, in a rule-based protein coreference resolution system. In particular, the domain-specific information is encoded into semantic classification modules for which the output is used in different components of the coreference resolution. We compared our system with the top four systems in the BioNLP-ST 2011; surprisingly, we found that the minimal configuration had outperformed the best system in the BioNLP-ST 2011. Analysis of the experimental results revealed that semantic classification, using protein information, has contributed to an increase in performance by 2.3% on the test data, and 4.0% on the development data, in F-score. Conclusions The use of domain-specific information in semantic classification is important for effective coreference resolution. Since it is difficult to transfer domain-specific information across different domains, we need to continue seek for methods to utilize such information in coreference resolution. PMID:23157272

  20. Semantic Representation and Naming in Young Children.

    ERIC Educational Resources Information Center

    McGregor, Karla K.; Friedman, Rena M.; Reilly, Renee M.; Newman, Robyn M.

    2002-01-01

    Two experiments examined children's semantic representations and semantic naming errors. Results suggested that functional and physical properties are core aspects of object representations in the semantic lexicon and that the degree of semantic knowledge makes words more or less vulnerable to retrieval failure. Discussion focuses on the dynamic…

  1. The Semantic Distance Model of Relevance Assessment.

    ERIC Educational Resources Information Center

    Brooks, Terrence A.

    1998-01-01

    Presents the Semantic Distance Model (SDM) of Relevance Assessment, a cognitive model of the relationship between semantic distance and relevance assessment. Discusses premises of the model such as the subjective nature of information and the metaphor of semantic distance. Empirical results illustrate the effects of semantic distance and semantic…

  2. Mapping the Structure of Semantic Memory

    ERIC Educational Resources Information Center

    Morais, Ana Sofia; Olsson, Henrik; Schooler, Lael J.

    2013-01-01

    Aggregating snippets from the semantic memories of many individuals may not yield a good map of an individual's semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1-hr daily sessions. The semantic networks of individuals…

  3. Automatic construction of rule-based ICD-9-CM coding systems

    PubMed Central

    Farkas, Richárd; Szarvas, György

    2008-01-01

    Background In this paper we focus on the problem of automatically constructing ICD-9-CM coding systems for radiology reports. ICD-9-CM codes are used for billing purposes by health institutes and are assigned to clinical records manually following clinical treatment. Since this labeling task requires expert knowledge in the field of medicine, the process itself is costly and is prone to errors as human annotators have to consider thousands of possible codes when assigning the right ICD-9-CM labels to a document. In this study we use the datasets made available for training and testing automated ICD-9-CM coding systems by the organisers of an International Challenge on Classifying Clinical Free Text Using Natural Language Processing in spring 2007. The challenge itself was dominated by entirely or partly rule-based systems that solve the coding task using a set of hand crafted expert rules. Since the feasibility of the construction of such systems for thousands of ICD codes is indeed questionable, we decided to examine the problem of automatically constructing similar rule sets that turned out to achieve a remarkable accuracy in the shared task challenge. Results Our results are very promising in the sense that we managed to achieve comparable results with purely hand-crafted ICD-9-CM classifiers. Our best model got a 90.26% F measure on the training dataset and an 88.93% F measure on the challenge test dataset, using the micro-averaged Fβ=1 measure, the official evaluation metric of the International Challenge on Classifying Clinical Free Text Using Natural Language Processing. This result would have placed second in the challenge, with a hand-crafted system achieving slightly better results. Conclusions Our results demonstrate that hand-crafted systems – which proved to be successful in ICD-9-CM coding – can be reproduced by replacing several laborious steps in their construction with machine learning models. These hybrid systems preserve the favourable

  4. Using rule-based shot dose assignment in model-based MPC applications

    NASA Astrophysics Data System (ADS)

    Bork, Ingo; Buck, Peter; Wang, Lin; Müller, Uwe

    2014-10-01

    Shrinking feature sizes and the need for tighter CD (Critical Dimension) control require the introduction of new technologies in mask making processes. One of those methods is the dose assignment of individual shots on VSB (Variable Shaped Beam) mask writers to compensate CD non-linearity effects and improve dose edge slope. Using increased dose levels only for most critical features, generally only for the smallest CDs on a mask, the change in mask write time is minimal while the increase in image quality can be significant. This paper describes a method combining rule-based shot dose assignment with model-based shot size correction. This combination proves to be very efficient in correcting mask linearity errors while also improving dose edge slope of small features. Shot dose assignment is based on tables assigning certain dose levels to a range of feature sizes. The dose to feature size assignment is derived from mask measurements in such a way that shape corrections are kept to a minimum. For example, if a 50nm drawn line on mask results in a 45nm chrome line using nominal dose, a dose level is chosen which is closest to getting the line back on target. Since CD non-linearity is different for lines, line-ends and contacts, different tables are generated for the different shape categories. The actual dose assignment is done via DRC rules in a pre-processing step before executing the shape correction in the MPC engine. Dose assignment to line ends can be restricted to critical line/space dimensions since it might not be required for all line ends. In addition, adding dose assignment to a wide range of line ends might increase shot count which is undesirable. The dose assignment algorithm is very flexible and can be adjusted based on the type of layer and the best balance between accuracy and shot count. These methods can be optimized for the number of dose levels available for specific mask writers. The MPC engine now needs to be able to handle different dose

  5. Matching Alternative Addresses: a Semantic Web Approach

    NASA Astrophysics Data System (ADS)

    Ariannamazi, S.; Karimipour, F.; Hakimpour, F.

    2015-12-01

    Rapid development of crowd-sourcing or volunteered geographic information (VGI) provides opportunities for authoritatives that deal with geospatial information. Heterogeneity of multiple data sources and inconsistency of data types is a key characteristics of VGI datasets. The expansion of cities resulted in the growing number of POIs in the OpenStreetMap, a well-known VGI source, which causes the datasets to outdate in short periods of time. These changes made to spatial and aspatial attributes of features such as names and addresses might cause confusion or ambiguity in the processes that require feature's literal information like addressing and geocoding. VGI sources neither will conform specific vocabularies nor will remain in a specific schema for a long period of time. As a result, the integration of VGI sources is crucial and inevitable in order to avoid duplication and the waste of resources. Information integration can be used to match features and qualify different annotation alternatives for disambiguation. This study enhances the search capabilities of geospatial tools with applications able to understand user terminology to pursuit an efficient way for finding desired results. Semantic web is a capable tool for developing technologies that deal with lexical and numerical calculations and estimations. There are a vast amount of literal-spatial data representing the capability of linguistic information in knowledge modeling, but these resources need to be harmonized based on Semantic Web standards. The process of making addresses homogenous generates a helpful tool based on spatial data integration and lexical annotation matching and disambiguating.

  6. Exploiting Recurring Structure in a Semantic Network

    NASA Technical Reports Server (NTRS)

    Wolfe, Shawn R.; Keller, Richard M.

    2004-01-01

    With the growing popularity of the Semantic Web, an increasing amount of information is becoming available in machine interpretable, semantically structured networks. Within these semantic networks are recurring structures that could be mined by existing or novel knowledge discovery methods. The mining of these semantic structures represents an interesting area that focuses on mining both for and from the Semantic Web, with surprising applicability to problems confronting the developers of Semantic Web applications. In this paper, we present representative examples of recurring structures and show how these structures could be used to increase the utility of a semantic repository deployed at NASA.

  7. Receptive vocabulary and semantic knowledge in children with SLI and children with Down syndrome.

    PubMed

    Laws, Glynis; Briscoe, Josie; Ang, Su-Yin; Brown, Heather; Hermena, Ehab; Kapikian, Anna

    2015-01-01

    Receptive vocabulary and associated semantic knowledge were compared within and between groups of children with specific language impairment (SLI), children with Down syndrome (DS), and typically developing children. To overcome the potential confounding effects of speech or language difficulties on verbal tests of semantic knowledge, a novel task was devised based on picture-based semantic association tests used to assess adult patients with semantic dementia. Receptive vocabulary, measured by word-picture matching, of children with SLI was weak relative to chronological age and to nonverbal mental age but their semantic knowledge, probed across the same lexical items, did not differ significantly from that of vocabulary-matched typically developing children. By contrast, although receptive vocabulary of children with DS was a relative strength compared to nonverbal cognitive abilities (p < .0001), DS was associated with a significant deficit in semantic knowledge (p < .0001) indicative of dissociation between word-picture matching vocabulary and depth of semantic knowledge. Overall, these data challenge the integrity of semantic-conceptual development in DS and imply that contemporary theories of semantic cognition should also seek to incorporate evidence from atypical conceptual development.

  8. Workspaces in the Semantic Web

    NASA Technical Reports Server (NTRS)

    Wolfe, Shawn R.; Keller, RIchard M.

    2005-01-01

    Due to the recency and relatively limited adoption of Semantic Web technologies. practical issues related to technology scaling have received less attention than foundational issues. Nonetheless, these issues must be addressed if the Semantic Web is to realize its full potential. In particular, we concentrate on the lack of scoping methods that reduce the size of semantic information spaces so they are more efficient to work with and more relevant to an agent's needs. We provide some intuition to motivate the need for such reduced information spaces, called workspaces, give a formal definition, and suggest possible methods of deriving them.

  9. High Performance Descriptive Semantic Analysis of Semantic Graph Databases

    SciTech Connect

    Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan; Feo, John T.; Haglin, David J.; Mackey, Greg E.; Mizell, David W.

    2011-06-02

    As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.

  10. Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems

    PubMed Central

    Lebar Bajec, Iztok

    2017-01-01

    Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question ‘why,’ however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour. PMID:28045964

  11. Space communications scheduler: A rule-based approach to adaptive deadline scheduling

    NASA Technical Reports Server (NTRS)

    Straguzzi, Nicholas

    1990-01-01

    Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.

  12. Transfer in Rule-Based Category Learning Depends on the Training Task

    PubMed Central

    Kattner, Florian; Cox, Christopher R.; Green, C. Shawn

    2016-01-01

    While learning is often highly specific to the exact stimuli and tasks used during training, there are cases where training results in learning that generalizes more broadly. It has been previously argued that the degree of specificity can be predicted based upon the learning solution(s) dictated by the particular demands of the training task. Here we applied this logic in the domain of rule-based categorization learning. Participants were presented with stimuli corresponding to four different categories and were asked to perform either a category discrimination task (which permits learning specific rule to discriminate two categories) or a category identification task (which does not permit learning a specific discrimination rule). In a subsequent transfer stage, all participants were asked to discriminate stimuli belonging to two of the categories which they had seen, but had never directly discriminated before (i.e., this particular discrimination was omitted from training). As predicted, learning in the category-discrimination tasks tended to be specific, while the category-identification task produced learning that transferred to the transfer discrimination task. These results suggest that the discrimination and identification tasks fostered the acquisition of different category representations which were more or less generalizable. PMID:27764221

  13. A rule-based expert system for chemical prioritization using effects-based chemical categories.

    PubMed

    Schmieder, P K; Kolanczyk, R C; Hornung, M W; Tapper, M A; Denny, J S; Sheedy, B R; Aladjov, H

    2014-01-01

    A rule-based expert system (ES) was developed to predict chemical binding to the estrogen receptor (ER) patterned on the research approaches championed by Gilman Veith to whom this article and journal issue are dedicated. The ERES was built to be mechanistically transparent and meet the needs of a specific application, i.e. predict for all chemicals within two well-defined inventories (industrial chemicals used as pesticide inerts and antimicrobial pesticides). These chemicals all lack structural features associated with high affinity binders and thus any binding should be low affinity. Similar to the high-quality fathead minnow database upon which Veith QSARs were built, the ERES was derived from what has been termed gold standard data, systematically collected in assays optimized to detect even low affinity binding and maximizing confidence in the negatives determinations. The resultant logic-based decision tree ERES, determined to be a robust model, contains seven major nodes with multiple effects-based chemicals categories within each. Predicted results are presented in the context of empirical data within local chemical structural groups facilitating informed decision-making. Even using optimized detection assays, the ERES applied to two inventories of >600 chemicals resulted in only ~5% of the chemicals predicted to bind ER.

  14. Application of a stopping rule based on total treatment failures: the postoperative Crohn's disease trial.

    PubMed

    Steinhart, A H; O'Rourke, K; Wolff, B G; McLeod, R S

    1992-05-01

    The Postoperative Crohn's Disease Trial (PCDT), a placebo-controlled randomized trial of Rowasa I in the prevention of postoperative recurrence of Crohn's disease, is used as an example of how a stopping rule based on total endpoint occurrences can provide considerable advantage over standard fixed sample size methods. It can be used when the primary outcome is occurrence or time to occurrence and does not raise the troublesome issues regarding the unblinding of group differences that other sequential methods create. The main advantage of the total endpoint stopping rule is that it provides set power. Standard fixed sample size designs provide a given power only on average. The power actually achieved in a particular fixed sample size trial is largely determined by the overall observed rate of endpoint occurrences. This claim about the total endpoint stopping rule is well established in the statistical literature and, as well as outlining the mathematical details in an Appendix, we use computer simulation of the PCDT to demonstrate that use of the stopping rule will allow termination of the trial while maintaining power and type I error at a predetermined level.

  15. A rule-based classification from a region-growing segmentation of airborne lidar

    NASA Astrophysics Data System (ADS)

    Martínez, Jorge; Rivera, Francisco F.; Cabaleiro, José C.; Vilariño, David L.; Pena, Tomás. F.; Miranda B., David

    2016-10-01

    Light Detection and Ranging (LiDAR) has attracted the interest of the research community in many fields, including object classification of the earth surface. In this paper we present an object-based classification method for airborne LiDAR that distinguishes three main classes (buildings, vegetation and ground) based only on LiDAR information. The key components of our proposal are the following: First, the LiDAR point cloud is stored in an octree for its efficient processing and the normal vector of each point is estimated using an adaptive neighborhood algorithm. Then, the points are segmented using a two-phase region growing algorithm where planar and non-planar objects are handled differently. The utilization of an epicenter point is introduced to allow regions to expand without losing homogeneity. Finally, a ruled-based procedure is performed to classify the segmented clusters. In order to evaluate our approach, a building detection was carried out, and results were obtained in terms of accuracy and computational time.

  16. Rule-based fuzzy vector median filters for 3D phase contrast MRI segmentation

    NASA Astrophysics Data System (ADS)

    Sundareswaran, Kartik S.; Frakes, David H.; Yoganathan, Ajit P.

    2008-02-01

    Recent technological advances have contributed to the advent of phase contrast magnetic resonance imaging (PCMRI) as standard practice in clinical environments. In particular, decreased scan times have made using the modality more feasible. PCMRI is now a common tool for flow quantification, and for more complex vector field analyses that target the early detection of problematic flow conditions. Segmentation is one component of this type of application that can impact the accuracy of the final product dramatically. Vascular segmentation, in general, is a long-standing problem that has received significant attention. Segmentation in the context of PCMRI data, however, has been explored less and can benefit from object-based image processing techniques that incorporate fluids specific information. Here we present a fuzzy rule-based adaptive vector median filtering (FAVMF) algorithm that in combination with active contour modeling facilitates high-quality PCMRI segmentation while mitigating the effects of noise. The FAVMF technique was tested on 111 synthetically generated PC MRI slices and on 15 patients with congenital heart disease. The results were compared to other multi-dimensional filters namely the adaptive vector median filter, the adaptive vector directional filter, and the scalar low pass filter commonly used in PC MRI applications. FAVMF significantly outperformed the standard filtering methods (p < 0.0001). Two conclusions can be drawn from these results: a) Filtering should be performed after vessel segmentation of PC MRI; b) Vector based filtering methods should be used instead of scalar techniques.

  17. Rule-based learning of regular past tense in children with specific language impairment.

    PubMed

    Smith-Lock, Karen M

    2015-01-01

    The treatment of children with specific language impairment was used as a means to investigate whether a single- or dual-mechanism theory best conceptualizes the acquisition of English past tense. The dual-mechanism theory proposes that regular English past-tense forms are produced via a rule-based process whereas past-tense forms of irregular verbs are stored in the lexicon. Single-mechanism theories propose that both regular and irregular past-tense verbs are stored in the lexicon. Five 5-year-olds with specific language impairment received treatment for regular past tense. The children were tested on regular past-tense production and third-person singular "s" twice before treatment and once after treatment, at eight-week intervals. Treatment consisted of one-hour play-based sessions, once weekly, for eight weeks. Crucially, treatment focused on different lexical items from those in the test. Each child demonstrated significant improvement on the untreated past-tense test items after treatment, but no improvement on the untreated third-person singular "s". Generalization to untreated past-tense verbs could not be attributed to a frequency effect or to phonological similarity of trained and tested items. It is argued that the results are consistent with a dual-mechanism theory of past-tense inflection.

  18. Trainable rule-based network for irradiation field recognition in Agfa's ADC system

    NASA Astrophysics Data System (ADS)

    Dewaele, Piet; Ibison, Michael; Vuylsteke, Pieter

    1996-04-01

    The irradiation field is the diagnostic region of radiograph which has been exposed directly to x rays and has not been shielded from the source by x-ray opaque material. Such material may have been placed to shield vulnerable regions of the patient from unnecessary exposure, and also to partition the radiograph into sub-images, thereby permitting multiple exposures on the same plate. In this paper we describe an image analysis method to automatically detect and locate the irradiation field of a digital radiograph. The aim is to prepare the radiographic image for contrast-enhancement processing which is driven only by exposure data from the diagnostically useful part of the radiograph. The algorithm is broadly edge-based, and comprises four stages: (1) edge detection, culminating in a set of straight-line edge segments as non-iconic data structures; (2) clustering (where possible) these segments into longer lines in accordance with colinearity constraints and the like; (3) model matching by a trainable rule- based network to identify irradiation field boundaries; (4) masking, which acts upon the input image to blank out the regions not in the irradiation field. The network has been trained on a database of 2100 images, and has been tested in clinical use, delivering an accuracy for recognition of the irradiation field of better than 99%.

  19. The study on dynamic cadastral coding rules based on kinship relationship

    NASA Astrophysics Data System (ADS)

    Xu, Huan; Liu, Nan; Liu, Renyi; Lu, Jingfeng

    2007-06-01

    Cadastral coding rules are an important supplement to the existing national and local standard specifications for building cadastral database. After analyzing the course of cadastral change, especially the parcel change with the method of object-oriented analysis, a set of dynamic cadastral coding rules based on kinship relationship corresponding to the cadastral change is put forward and a coding format composed of street code, block code, father parcel code, child parcel code and grandchild parcel code is worked out within the county administrative area. The coding rule has been applied to the development of an urban cadastral information system called "ReGIS", which is not only able to figure out the cadastral code automatically according to both the type of parcel change and the coding rules, but also capable of checking out whether the code is spatiotemporally unique before the parcel is stored in the database. The system has been used in several cities of Zhejiang Province and got a favorable response. This verifies the feasibility and effectiveness of the coding rules to some extent.

  20. Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes

    NASA Astrophysics Data System (ADS)

    Ianni, Giovambattista; Krennwallner, Thomas; Martello, Alessandra; Polleres, Axel

    RDF Schema (RDFS) as a lightweight ontology language is gaining popularity and, consequently, tools for scalable RDFS inference and querying are needed. SPARQL has become recently a W3C standard for querying RDF data, but it mostly provides means for querying simple RDF graphs only, whereas querying with respect to RDFS or other entailment regimes is left outside the current specification. In this paper, we show that SPARQL faces certain unwanted ramifications when querying ontologies in conjunction with RDF datasets that comprise multiple named graphs, and we provide an extension for SPARQL that remedies these effects. Moreover, since RDFS inference has a close relationship with logic rules, we generalize our approach to select a custom ruleset for specifying inferences to be taken into account in a SPARQL query. We show that our extensions are technically feasible by providing benchmark results for RDFS querying in our prototype system GiaBATA, which uses Datalog coupled with a persistent Relational Database as a back-end for implementing SPARQL with dynamic rule-based inference. By employing different optimization techniques like magic set rewriting our system remains competitive with state-of-the-art RDFS querying systems.

  1. Reliability and performance evaluation of systems containing embedded rule-based expert systems

    NASA Technical Reports Server (NTRS)

    Beaton, Robert M.; Adams, Milton B.; Harrison, James V. A.

    1989-01-01

    A method for evaluating the reliability of real-time systems containing embedded rule-based expert systems is proposed and investigated. It is a three stage technique that addresses the impact of knowledge-base uncertainties on the performance of expert systems. In the first stage, a Markov reliability model of the system is developed which identifies the key performance parameters of the expert system. In the second stage, the evaluation method is used to determine the values of the expert system's key performance parameters. The performance parameters can be evaluated directly by using a probabilistic model of uncertainties in the knowledge-base or by using sensitivity analyses. In the third and final state, the performance parameters of the expert system are combined with performance parameters for other system components and subsystems to evaluate the reliability and performance of the complete system. The evaluation method is demonstrated in the context of a simple expert system used to supervise the performances of an FDI algorithm associated with an aircraft longitudinal flight-control system.

  2. Overcoming rule-based rigidity and connectionist limitations through massively-parallel case-based reasoning

    NASA Technical Reports Server (NTRS)

    Barnden, John; Srinivas, Kankanahalli

    1990-01-01

    Symbol manipulation as used in traditional Artificial Intelligence has been criticized by neural net researchers for being excessively inflexible and sequential. On the other hand, the application of neural net techniques to the types of high-level cognitive processing studied in traditional artificial intelligence presents major problems as well. A promising way out of this impasse is to build neural net models that accomplish massively parallel case-based reasoning. Case-based reasoning, which has received much attention recently, is essentially the same as analogy-based reasoning, and avoids many of the problems leveled at traditional artificial intelligence. Further problems are avoided by doing many strands of case-based reasoning in parallel, and by implementing the whole system as a neural net. In addition, such a system provides an approach to some aspects of the problems of noise, uncertainty and novelty in reasoning systems. The current neural net system (Conposit), which performs standard rule-based reasoning, is being modified into a massively parallel case-based reasoning version.

  3. Scalable rule-based modelling of allosteric proteins and biochemical networks.

    PubMed

    Ollivier, Julien F; Shahrezaei, Vahid; Swain, Peter S

    2010-11-04

    Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

  4. An Expert System for Diagnosis of Sleep Disorder Using Fuzzy Rule-Based Classification Systems

    NASA Astrophysics Data System (ADS)

    Septem Riza, Lala; Pradini, Mila; Fitrajaya Rahman, Eka; Rasim

    2017-03-01

    Sleep disorder is an anomaly that could cause problems for someone’ sleeping pattern. Nowadays, it becomes an issue since people are getting busy with their own business and have no time to visit the doctors. Therefore, this research aims to develop a system used for diagnosis of sleep disorder using Fuzzy Rule-Based Classification System (FRBCS). FRBCS is a method based on the fuzzy set concepts. It consists of two steps: (i) constructing a model/knowledge involving rulebase and database, and (ii) prediction over new data. In this case, the knowledge is obtained from experts whereas in the prediction stage, we perform fuzzification, inference, and classification. Then, a platform implementing the method is built with a combination between PHP and the R programming language using the “Shiny” package. To validate the system that has been made, some experiments have been done using data from a psychiatric hospital in West Java, Indonesia. Accuracy of the result and computation time are 84.85% and 0.0133 seconds, respectively.

  5. Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

    PubMed

    Demšar, Jure; Lebar Bajec, Iztok

    2017-01-01

    Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging), group decision-making process, and group behaviour types. The question 'why,' however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

  6. A self-organized, distributed, and adaptive rule-based induction system.

    PubMed

    Rojanavasu, Pornthep; Dam, Hai Huong; Abbass, Hussein A; Lokan, Chris; Pinngern, Ouen

    2009-03-01

    Learning classifier systems (LCSs) are rule-based inductive learning systems that have been widely used in the field of supervised and reinforcement learning over the last few years. This paper employs sUpervised Classifier System (UCS), a supervised learning classifier system, that was introduced in 2003 for classification tasks in data mining. We present an adaptive framework of UCS on top of a self-organized map (SOM) neural network. The overall classification problem is decomposed adaptively and in real time by the SOM into subproblems, each of which is handled by a separate UCS. The framework is also tested with replacing UCS by a feedforward artificial neural network (ANN). Experiments on several synthetic and real data sets, including a very large real data set, show that the accuracy of classifications in the proposed distributed environment is as good or better than in the nondistributed environment, and execution is faster. In general, each UCS attached to a cell in the SOM has a much smaller population size than a single UCS working on the overall problem; since each data instance is exposed to a smaller population size than in the single population approach, the throughput of the overall system increases. The experiments show that the proposed framework can decompose a problem adaptively into subproblems, maintaining or improving accuracy and increasing speed.

  7. Computerized lung nodule detection on thoracic CT images: combined rule-based and statistical classifier for false-positive reduction

    NASA Astrophysics Data System (ADS)

    Gurcan, Metin N.; Petrick, Nicholas; Sahiner, Berkman; Chan, Heang-Ping; Cascade, Philip N.; Kazerooni, Ella A.; Hadjiiski, Lubomir M.

    2001-07-01

    We are developing a computer-aided diagnosis (CAD) system for lung nodule detection on thoracic helical computed tomography (CT) images. In the first stage of this CAD system, lung regions are identified and suspicious structures are segmented. These structures may include true lung nodules or normal structures that consist mainly of vascular structures. We have designed rule-based classifiers to distinguish nodules and normal structures using 2D and 3D features. After rule-based classification, linear discriminant analysis (LDA) is used to further reduce the number of false positive (FP) objects. We have performed a preliminary study using CT images from 17 patients with 31 lung nodules. When only LDA classification was applied to the segmented objects, the sensitivity was 84% (26/31) with 2.53 (1549/612) FP objects per slice. When the LDA followed the rule-based classifier, the number of FP objects per slice decreased to 1.75 (1072/612) at the same sensitivity. These preliminary results demonstrate the feasibility of our approach for nodule detection and FP reduction on CT images. The inclusion of rule-based classification leads to an improvement in detection accuracy for the CAD system.

  8. Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

    ERIC Educational Resources Information Center

    Zhang, Zhidong

    2016-01-01

    This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

  9. Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

    PubMed

    Grouin, Cyril; Zweigenbaum, Pierre

    2013-01-01

    In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

  10. Fault tolerant synchronization of chaotic heavy symmetric gyroscope systems versus external disturbances via Lyapunov rule-based fuzzy control.

    PubMed

    Farivar, Faezeh; Shoorehdeli, Mahdi Aliyari

    2012-01-01

    In this paper, fault tolerant synchronization of chaotic gyroscope systems versus external disturbances via Lyapunov rule-based fuzzy control is investigated. Taking the general nature of faults in the slave system into account, a new synchronization scheme, namely, fault tolerant synchronization, is proposed, by which the synchronization can be achieved no matter whether the faults and disturbances occur or not. By making use of a slave observer and a Lyapunov rule-based fuzzy control, fault tolerant synchronization can be achieved. Two techniques are considered as control methods: classic Lyapunov-based control and Lyapunov rule-based fuzzy control. On the basis of Lyapunov stability theory and fuzzy rules, the nonlinear controller and some generic sufficient conditions for global asymptotic synchronization are obtained. The fuzzy rules are directly constructed subject to a common Lyapunov function such that the error dynamics of two identical chaotic motions of symmetric gyros satisfy stability in the Lyapunov sense. Two proposed methods are compared. The Lyapunov rule-based fuzzy control can compensate for the actuator faults and disturbances occurring in the slave system. Numerical simulation results demonstrate the validity and feasibility of the proposed method for fault tolerant synchronization.

  11. Ability-Grouping and Academic Inequality: Evidence from Rule-Based Student Assignments. NBER Working Paper No. 14911

    ERIC Educational Resources Information Center

    Jackson, C. Kirabo

    2009-01-01

    In Trinidad and Tobago students are assigned to secondary schools after fifth grade based on achievement tests, leading to large differences in the school environments to which students of differing initial levels of achievement are exposed. Using both a regression discontinuity design and rule-based instrumental variables to address…

  12. Deriving a probabilistic syntacto-semantic grammar for biomedicine based on domain-specific terminologies.

    PubMed

    Fan, Jung-Wei; Friedman, Carol

    2011-10-01

    Biomedical natural language processing (BioNLP) is a useful technique that unlocks valuable information stored in textual data for practice and/or research. Syntactic parsing is a critical component of BioNLP applications that rely on correctly determining the sentence and phrase structure of free text. In addition to dealing with the vast amount of domain-specific terms, a robust biomedical parser needs to model the semantic grammar to obtain viable syntactic structures. With either a rule-based or corpus-based approach, the grammar engineering process requires substantial time and knowledge from experts, and does not always yield a semantically transferable grammar. To reduce the human effort and to promote semantic transferability, we propose an automated method for deriving a probabilistic grammar based on a training corpus consisting of concept strings and semantic classes from the Unified Medical Language System (UMLS), a comprehensive terminology resource widely used by the community. The grammar is designed to specify noun phrases only due to the nominal nature of the majority of biomedical terminological concepts. Evaluated on manually parsed clinical notes, the derived grammar achieved a recall of 0.644, precision of 0.737, and average cross-bracketing of 0.61, which demonstrated better performance than a control grammar with the semantic information removed. Error analysis revealed shortcomings that could be addressed to improve performance. The results indicated the feasibility of an approach which automatically incorporates terminology semantics in the building of an operational grammar. Although the current performance of the unsupervised solution does not adequately replace manual engineering, we believe once the performance issues are addressed, it could serve as an aide in a semi-supervised solution.

  13. Does semantic redundancy gain result from multiple semantic priming?

    PubMed

    Schröter, Hannes; Bratzke, Daniel; Fiedler, Anja; Birngruber, Teresa

    2015-10-01

    Fiedler, Schröter, and Ulrich (2013) reported faster responses to a single written word when the semantic content of this word (e.g., "elephant") matched both targets (e.g., "animal", "gray") as compared to a single target (e.g., "animal", "brown"). This semantic redundancy gain was explained by statistical facilitation due to a race of independent memory retrieval processes. The present experiment addresses one alternative explanation, namely that semantic redundancy gain results from multiple pre-activation of words that match both targets. In different blocks of trials, participants performed a redundant-targets task and a lexical decision task. The targets of the redundant-targets task served as primes in the lexical decision task. Replicating the findings of Fiedler et al., a semantic redundancy gain was observed in the redundant-targets task. Crucially, however, there was no evidence of a multiple semantic priming effect in the lexical decision task. This result suggests that semantic redundancy gain cannot be explained by multiple pre-activation of words that match both targets.

  14. Problem Solving with General Semantics.

    ERIC Educational Resources Information Center

    Hewson, David

    1996-01-01

    Discusses how to use general semantics formulations to improve problem solving at home or at work--methods come from the areas of artificial intelligence/computer science, engineering, operations research, and psychology. (PA)

  15. Nine Principles of Semantic Harmonization.

    PubMed

    Cunningham, James A; Van Speybroeck, Michel; Kalra, Dipak; Verbeeck, Rudi

    2016-01-01

    Medical data is routinely collected, stored and recorded across different institutions and in a range of different formats. Semantic harmonization is the process of collating this data into a singular consistent logical view, with many approaches to harmonizing both possible and valid. The broad scope of possibilities for undertaking semantic harmonization do lead however to the development of bespoke and ad-hoc systems; this is particularly the case when it comes to cohort data, the format of which is often specific to a cohort's area of focus. Guided by work we have undertaken in developing the 'EMIF Knowledge Object Library', a semantic harmonization framework underpinning the collation of pan-European Alzheimer's cohort data, we have developed a set of nine generic guiding principles for developing semantic harmonization frameworks, the application of which will establish a solid base for constructing similar frameworks.

  16. Nine Principles of Semantic Harmonization

    PubMed Central

    Cunningham, James A.; Van Speybroeck, Michel; Kalra, Dipak; Verbeeck, Rudi

    2016-01-01

    Medical data is routinely collected, stored and recorded across different institutions and in a range of different formats. Semantic harmonization is the process of collating this data into a singular consistent logical view, with many approaches to harmonizing both possible and valid. The broad scope of possibilities for undertaking semantic harmonization do lead however to the development of bespoke and ad-hoc systems; this is particularly the case when it comes to cohort data, the format of which is often specific to a cohort’s area of focus. Guided by work we have undertaken in developing the ‘EMIF Knowledge Object Library’, a semantic harmonization framework underpinning the collation of pan-European Alzheimer’s cohort data, we have developed a set of nine generic guiding principles for developing semantic harmonization frameworks, the application of which will establish a solid base for constructing similar frameworks. PMID:28269840

  17. At the edge of semantic space: the breakdown of coherent concepts in semantic dementia is constrained by typicality and severity but not modality.

    PubMed

    Mayberry, Emily J; Sage, Karen; Ralph, Matthew A Lambon

    2011-09-01

    Hub-and-spoke models of semantic representation suggest that coherent concepts are formed from the integration of multiple, modality-specific information sources with additional modality-invariant representations-most likely stored in the ventrolateral anterior temporal lobe (vATL). As well as providing the necessary computational mechanisms for the complexities of feature integration, these modality-invariant representations also license a key aspect of semantic memory-semantic-based generalization. Semantic dementia allows us to investigate this aspect of conceptual knowledge because (a) the patients have a selective and progressive semantic degradation and (b) this is associated with profound ventrolateral ATL atrophy. Specifically, the boundaries between concepts become degraded in semantic dementia and, when tested using the appropriate materials, the patients make simultaneous under- and overgeneralization errors. We found that the rate of these errors were a function of typicality and pseudotypicality of the items as well as the severity of the patients' semantic impairment. Following the modality-invariant nature of the vATL hub representation, we also confirmed that the patients were impaired on both verbal- and picture-based versions of the same task.

  18. Semantic Support for Complex Ecosystem Research Environments

    NASA Astrophysics Data System (ADS)

    Klawonn, M.; McGuinness, D. L.; Pinheiro, P.; Santos, H. O.; Chastain, K.

    2015-12-01

    As ecosystems come under increasing stresses from diverse sources, there is growing interest in research efforts aimed at monitoring, modeling, and improving understanding of ecosystems and protection options. We aimed to provide a semantic infrastructure capable of representing data initially related to one large aquatic ecosystem research effort - the Jefferson project at Lake George. This effort includes significant historical observational data, extensive sensor-based monitoring data, experimental data, as well as model and simulation data covering topics including lake circulation, watershed runoff, lake biome food webs, etc. The initial measurement representation has been centered on monitoring data and related provenance. We developed a human-aware sensor network ontology (HASNetO) that leverages existing ontologies (PROV-O, OBOE, VSTO*) in support of measurement annotations. We explicitly support the human-aware aspects of human sensor deployment and collection activity to help capture key provenance that often is lacking. Our foundational ontology has since been generalized into a family of ontologies and used to create our human-aware data collection infrastructure that now supports the integration of measurement data along with simulation data. Interestingly, we have also utilized the same infrastructure to work with partners who have some more specific needs for specifying the environmental conditions where measurements occur, for example, knowing that an air temperature is not an external air temperature, but of the air temperature when windows are shut and curtains are open. We have also leveraged the same infrastructure to work with partners more interested in modeling smart cities with data feeds more related to people, mobility, environment, and living. We will introduce our human-aware data collection infrastructure, and demonstrate how it uses HASNetO and its supporting SOLR-based search platform to support data integration and semantic browsing

  19. NASA and The Semantic Web

    NASA Technical Reports Server (NTRS)

    Ashish, Naveen

    2005-01-01

    We provide an overview of several ongoing NASA endeavors based on concepts, systems, and technology from the Semantic Web arena. Indeed NASA has been one of the early adopters of Semantic Web Technology and we describe ongoing and completed R&D efforts for several applications ranging from collaborative systems to airspace information management to enterprise search to scientific information gathering and discovery systems at NASA.

  20. Semantic Interoperability on the Web

    DTIC Science & Technology

    2000-01-01

    these agents would not be affected by presentation changes if the pages were available in XML, they would still break if the XML representation of the... these semantics into tools that are used to interpret or translate the XML documents, but software tools cannot acquire these semantics independently...mapping differences in naming conventions. As with natural language, XML DTDs have the problems of polysemy and synonymy. For example, the elements

  1. Neural substrates of semantic memory.

    PubMed

    Hart, John; Anand, Raksha; Zoccoli, Sandra; Maguire, Mandy; Gamino, Jacque; Tillman, Gail; King, Richard; Kraut, Michael A

    2007-09-01

    Semantic memory is described as the storage of knowledge, concepts, and information that is common and relatively consistent across individuals (e.g., memory of what is a cup). These memories are stored in multiple sensorimotor modalities and cognitive systems throughout the brain (e.g., how a cup is held and manipulated, the texture of a cup's surface, its shape, its function, that is related to beverages such as coffee, and so on). Our ability to engage in purposeful interactions with our environment is dependent on the ability to understand the meaning and significance of the objects and actions around us that are stored in semantic memory. Theories of the neural basis of the semantic memory of objects have produced sophisticated models that have incorporated to varying degrees the results of cognitive and neural investigations. The models are grouped into those that are (1) cognitive models, where the neural data are used to reveal dissociations in semantic memory after a brain lesion occurs; (2) models that incorporate both cognitive and neuroanatomical information; and (3) models that use cognitive, neuroanatomic, and neurophysiological data. This review highlights the advances and issues that have emerged from these models and points to future directions that provide opportunities to extend these models. The models of object memory generally describe how category and/or feature representations encode for object memory, and the semantic operations engaged in object processing. The incorporation of data derived from multiple modalities of investigation can lead to detailed neural specifications of semantic memory organization. The addition of neurophysiological data can potentially provide further elaboration of models to include semantic neural mechanisms. Future directions should incorporate available and newly developed techniques to better inform the neural underpinning of semantic memory models.

  2. [An effect of semantic satiation in conceptual processing].

    PubMed

    Takashi, Shimokido

    2007-12-01

    This study examined whether semantic satiation effects for a picture exemplar differ from a word exemplar. If massive repetition of the category name leads to an inhibition of conceptual processing, then semantic satiation effects would be found in both the word and picture exemplar conditions. However, if the repetition leads to an inhibition of lexical processing, then effects would be found for the word exemplar but not the picture exemplar. To examine these hypotheses, 48 college students were asked to judge whether a target pair of exemplars belonged to the same named category. The results showed that semantic satiation effects were found equally in both exemplar conditions. Moreover, the picture-superiority effect was intact regardless of the prime repetitions. The possibility was discussed that word and picture exemplars are integrated into an abstract and amodal conceptual unit; hence category judgment was affected by the satiation effect.

  3. Bridging the Gap between Linked Data and the Semantic Desktop

    NASA Astrophysics Data System (ADS)

    Groza, Tudor; Drăgan, Laura; Handschuh, Siegfried; Decker, Stefan

    The exponential growth of the World Wide Web in the last decade brought an explosion in the information space, which has important consequences also in the area of scientific research. Finding relevant work in a particular field and exploring the links between publications is currently a cumbersome task. Similarly, on the desktop, managing the publications acquired over time can represent a real challenge. Extracting semantic metadata, exploring the linked data cloud and using the semantic desktop for managing personal information represent, in part, solutions for different aspects of the above mentioned issues. In this paper, we propose an innovative approach for bridging these three directions with the overall goal of alleviating the information overload problem burdening early stage researchers. Our application combines harmoniously document engineering-oriented automatic metadata extraction with information expansion and visualization based on linked data, while the resulting documents can be seamlessly integrated into the semantic desktop.

  4. Toward Semantic Web Infrastructure for Spatial FEATURES' Information

    NASA Astrophysics Data System (ADS)

    Arabsheibani, R.; Ariannamazi, S.; Hakimpour, F.

    2015-12-01

    The Web and its capabilities can be employed as a tool for data and information integration if comprehensive datasets and appropriate technologies and standards enable the web with interpretation and easy alignment of data and information. Semantic Web along with the spatial functionalities enable the web to deal with the huge amount of data and information. The present study investigate the advantages and limitations of the Spatial Semantic Web and compare its capabilities with relational models in order to build a spatial data infrastructure. An architecture is proposed and a set of criteria is defined for the efficiency evaluation. The result demonstrate that when using the data with special characteristics such as schema dynamicity, sparse data or available relations between the features, the spatial semantic web and graph databases with spatial operations are preferable.

  5. Semantic preview benefit during reading.

    PubMed

    Hohenstein, Sven; Kliegl, Reinhold

    2014-01-01

    Word features in parafoveal vision influence eye movements during reading. The question of whether readers extract semantic information from parafoveal words was studied in 3 experiments by using a gaze-contingent display change technique. Subjects read German sentences containing 1 of several preview words that were replaced by a target word during the saccade to the preview (boundary paradigm). In the 1st experiment the preview word was semantically related or unrelated to the target. Fixation durations on the target were shorter for semantically related than unrelated previews, consistent with a semantic preview benefit. In the 2nd experiment, half the sentences were presented following the rules of German spelling (i.e., previews and targets were printed with an initial capital letter), and the other half were presented completely in lowercase. A semantic preview benefit was obtained under both conditions. In the 3rd experiment, we introduced 2 further preview conditions, an identical word and a pronounceable nonword, while also manipulating the text contrast. Whereas the contrast had negligible effects, fixation durations on the target were reliably different for all 4 types of preview. Semantic preview benefits were greater for pretarget fixations closer to the boundary (large preview space) and, although not as consistently, for long pretarget fixation durations (long preview time). The results constrain theoretical proposals about eye movement control in reading. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  6. A health analytics semantic ETL service for obesity surveillance.

    PubMed

    Poulymenopoulou, M; Papakonstantinou, D; Malamateniou, F; Vassilacopoulos, G

    2015-01-01

    The increasingly large amount of data produced in healthcare (e.g. collected through health information systems such as electronic medical records - EMRs or collected through novel data sources such as personal health records - PHRs, social media, web resources) enable the creation of detailed records about people's health, sentiments and activities (e.g. physical activity, diet, sleep quality) that can be used in the public health area among others. However, despite the transformative potential of big data in public health surveillance there are several challenges in integrating big data. In this paper, the interoperability challenge is tackled and a semantic Extract Transform Load (ETL) service is proposed that seeks to semantically annotate big data to result into valuable data for analysis. This service is considered as part of a health analytics engine on the cloud that interacts with existing healthcare information exchange networks, like the Integrating the Healthcare Enterprise (IHE), PHRs, sensors, mobile applications, and other web resources to retrieve patient health, behavioral and daily activity data. The semantic ETL service aims at semantically integrating big data for use by analytic mechanisms. An illustrative implementation of the service on big data which is potentially relevant to human obesity, enables using appropriate analytic techniques (e.g. machine learning, text mining) that are expected to assist in identifying patterns and contributing factors (e.g. genetic background, social, environmental) for this social phenomenon and, hence, drive health policy changes and promote healthy behaviors where residents live, work, learn, shop and play.

  7. Semantic elaboration: ERPs reveal rapid transition from novel to known.

    PubMed

    Bauer, Patricia J; Jackson, Felicia L

    2015-01-01

    Like language, semantic memory is productive: It extends itself through self-derivation of new information through logical processes such as analogy, deduction, and induction, for example. Though it is clear these productive processes occur, little is known about the time course over which newly self-derived information becomes incorporated into semantic knowledge. In the present research, we used event-related potentials to examine this dynamic process. Subjects were presented with separate but related facts that, when integrated with one another, supported generation of new information (Integration facts). After 2 400-ms presentations, P600 responses to Integration facts differed from responses to Novel facts and did not differ from responses to Well-known facts, suggesting that the newly self-derived information had been incorporated into the knowledge base. The finding of rapid transition from newly self-derived to well known helps explain the richness of semantic memory. By implication, it also may contribute to the absence of episodic information specifying when and where semantic contents were acquired.

  8. Building a Semantic Framework for eScience

    NASA Astrophysics Data System (ADS)

    Movva, S.; Ramachandran, R.; Maskey, M.; Li, X.

    2009-12-01

    The e-Science vision focuses on the use of advanced computing technologies to support scientists. Recent research efforts in this area have focused primarily on “enabling” use of infrastructure resources for both data and computational access especially in Geosciences. One of the existing gaps in the existing e-Science efforts has been the failure to incorporate stable semantic technologies within the design process itself. In this presentation, we describe our effort in designing a framework for e-Science built using Service Oriented Architecture. Our framework provides users capabilities to create science workflows and mine distributed data. Our e-Science framework is being designed around a mass market tool to promote reusability across many projects. Semantics is an integral part of this framework and our design goal is to leverage the latest stable semantic technologies. The use of these stable semantic technologies will provide the users of our framework the useful features such as: allow search engines to find their content with RDFa tags; create RDF triple data store for their content; create RDF end points to share with others; and semantically mash their content with other online content available as RDF end point.

  9. Mapping the semantic structure of cognitive neuroscience.

    PubMed

    Beam, Elizabeth; Appelbaum, L Gregory; Jack, Jordynn; Moody, James; Huettel, Scott A

    2014-09-01

    Cognitive neuroscience, as a discipline, links the biological systems studied by neuroscience to the processing constructs studied by psychology. By mapping these relations throughout the literature of cognitive neuroscience, we visualize the semantic structure of the discipline and point to directions for future research that will advance its integrative goal. For this purpose, network text analyses were applied to an exhaustive corpus of abstracts collected from five major journals over a 30-month period, including every study that used fMRI to investigate psychological processes. From this, we generate network maps that illustrate the relationships among psychological and anatomical terms, along with centrality statistics that guide inferences about network structure. Three terms--prefrontal cortex, amygdala, and anterior cingulate cortex--dominate the network structure with their high frequency in the literature and the density of their connections with other neuroanatomical terms. From network statistics, we identify terms that are understudied compared with their importance in the network (e.g., insula and thalamus), are underspecified in the language of the discipline (e.g., terms associated with executive function), or are imperfectly integrated with other concepts (e.g., subdisciplines like decision neuroscience that are disconnected from the main network). Taking these results as the basis for prescriptive recommendations, we conclude that semantic analyses provide useful guidance for cognitive neuroscience as a discipline, both by illustrating systematic biases in the conduct and presentation of research and by identifying directions that may be most productive for future research.

  10. Rule-Based Modeling of Chronic Disease Epidemiology: Elderly Depression as an Illustration

    PubMed Central

    Chiêm, Jean-Christophe; Macq, Jean; Speybroeck, Niko

    2012-01-01

    Background Rule-based Modeling (RBM) is a computer simulation modeling methodology already used to model infectious diseases. Extending this technique to the assessment of chronic diseases, mixing quantitative and qualitative data appear to be a promising alternative to classical methods. Elderly depression reveals an important source of comorbidities. Yet, the intertwined relationship between late-life events and the social support of the elderly person remains difficult to capture. We illustrate the usefulness of RBM in modeling chronic diseases using the example of elderly depression in Belgium. Methods We defined a conceptual framework of interactions between late-life events and social support impacting elderly depression. This conceptual framework was underpinned by experts' opinions elicited through a questionnaire. Several scenarios were implemented successively to better mimic the real population, and to explore a treatment effect and a socio-economic distinction. The simulated patterns of depression by age were compared with empirical patterns retrieved from the Belgian Health Interview Survey. Results Simulations were run using different groupings of experts' opinions on the parameters. The results indicate that the conceptual framework can reflect a realistic evolution of the prevalence of depression. Indeed, simulations combining the opinions of well-selected experts and a treatment effect showed no significant difference with the empirical pattern. Conclusions Our conceptual framework together with a quantification of parameters through elicited expert opinions improves the insights into possible dynamics driving elderly depression. While RBM does not require high-level skill in mathematics or computer programming, the whole implementation process provides a powerful tool to learn about complex chronic diseases, combining advantages of both quantitative and qualitative approaches. PMID:22952581

  11. Perceptual Learning Improves Adult Amblyopic Vision Through Rule-Based Cognitive Compensation

    PubMed Central

    Zhang, Jun-Yun; Cong, Lin-Juan; Klein, Stanley A.; Levi, Dennis M.; Yu, Cong

    2014-01-01

    Purpose. We investigated whether perceptual learning in adults with amblyopia could be enabled to transfer completely to an orthogonal orientation, which would suggest that amblyopic perceptual learning results mainly from high-level cognitive compensation, rather than plasticity in the amblyopic early visual brain. Methods. Nineteen adults (mean age = 22.5 years) with anisometropic and/or strabismic amblyopia were trained following a training-plus-exposure (TPE) protocol. The amblyopic eyes practiced contrast, orientation, or Vernier discrimination at one orientation for six to eight sessions. Then the amblyopic or nonamblyopic eyes were exposed to an orthogonal orientation via practicing an irrelevant task. Training was first performed at a lower spatial frequency (SF), then at a higher SF near the cutoff frequency of the amblyopic eye. Results. Perceptual learning was initially orientation specific. However, after exposure to the orthogonal orientation, learning transferred to an orthogonal orientation completely. Reversing the exposure and training order failed to produce transfer. Initial lower SF training led to broad improvement of contrast sensitivity, and later higher SF training led to more specific improvement at high SFs. Training improved visual acuity by 1.5 to 1.6 lines (P < 0.001) in the amblyopic eyes with computerized tests and a clinical E acuity chart. It also improved stereoacuity by 53% (P < 0.001). Conclusions. The complete transfer of learning suggests that perceptual learning in amblyopia may reflect high-level learning of rules for performing a visual discrimination task. These rules are applicable to new orientations to enable learning transfer. Therefore, perceptual learning may improve amblyopic vision mainly through rule-based cognitive compensation. PMID:24550359

  12. Frontotemporal neural systems supporting semantic processing in Alzheimer's disease.

    PubMed

    Peelle, Jonathan E; Powers, John; Cook, Philip A; Smith, Edward E; Grossman, Murray

    2014-03-01

    We hypothesized that semantic memory for object concepts involves both representations of visual feature knowledge in modality-specific association cortex and heteromodal regions that are important for integrating and organizing this semantic knowledge so that it can be used in a flexible, contextually appropriate manner. We examined this hypothesis in an fMRI study of mild Alzheimer's disease (AD). Participants were presented with pairs of printed words and asked whether the words matched on a given visual-perceptual feature (e.g., guitar, violin: SHAPE). The stimuli probed natural kinds and manufactured objects, and the judgments involved shape or color. We found activation of bilateral ventral temporal cortex and left dorsolateral prefrontal cortex during semantic judgments, with AD patients showing less activation of these regions than healthy seniors. Moreover, AD patients showed less ventral temporal activation than did healthy seniors for manufactured objects, but not for natural kinds. We also used diffusion-weighted MRI of white matter to examine fractional anisotropy (FA). Patients with AD showed significantly reduced FA in the superior longitudinal fasciculus and inferior frontal-occipital fasciculus, which carry projections linking temporal and frontal regions of this semantic network. Our results are consistent with the hypothesis that semantic memory is supported in part by a large-scale neural network involving modality-specific association cortex, heteromodal association cortex, and projections between these regions. The semantic deficit in AD thus arises from gray matter disease that affects the representation of feature knowledge and processing its content, as well as white matter disease that interrupts the integrated functioning of this large-scale network.

  13. The neural correlates of semantic richness: evidence from an fMRI study of word learning.

    PubMed

    Ferreira, Roberto A; Göbel, Silke M; Hymers, Mark; Ellis, Andrew W

    2015-04-01

    We investigated the neural correlates of concrete nouns with either many or few semantic features. A group of 21 participants underwent two days of training and were then asked to categorize 40 newly learned words and a set of matched familiar words as living or nonliving in an MRI scanner. Our results showed that the most reliable effects of semantic richness were located in the left angular gyrus (AG) and middle temporal gyrus (MTG), where activation was higher for semantically rich than poor words. Other areas showing the same pattern included bilateral precuneus and posterior cingulate gyrus. Our findings support the view that AG and anterior MTG, as part of the multimodal network, play a significant role in representing and integrating semantic features from different input modalities. We propose that activation in bilateral precuneus and posterior cingulate gyrus reflects interplay between AG and episodic memory systems during semantic retrieval.

  14. Using semantic memory to boost 'episodic' recall in a case of developmental amnesia.

    PubMed

    Brandt, Karen R; Gardiner, John M; Vargha-Khadem, Faraneh; Baddeley, Alan D; Mishkin, Mortimer

    2006-07-17

    We report two experiments that investigated factors that might boost 'episodic' recall for Jon, a developmental amnesic whose episodic memory is gravely impaired but whose semantic memory seems relatively normal. Experiment 1 showed that Jon's recall improved following a semantic study task compared with a non-semantic study task, as well as following four repeated study trials compared with only one. Experiment 2 additionally revealed that Jon's recall improved after acting compared with reading action phrases at study, but only if the phrases were well integrated semantically. The results provide some support for the hypothesis that Jon's 'episodic' recall depends on the extent to which he is able to retrieve events using semantic memory.

  15. Distinct functional connectivity of the hippocampus during semantic and phonemic fluency.

    PubMed

    Glikmann-Johnston, Yifat; Oren, Noga; Hendler, Talma; Shapira-Lichter, Irit

    2015-03-01

    Verbal fluency tasks are typically used in neuropsychological practice for assessment of language function in a variety of neurological disorders. Recently, it has been shown that the hippocampus, a region thought to be exclusive to the domain of memory, is also involved in tests of semantic fluency. The present study further explores hippocampal contribution to verbal fluency using functional Magnetic Resonance Imaging (fMRI) and examining mean activity and inter-regional functional connectivity with known task-related brain regions. Given the clear lateralization of brain areas involved in language, lateralization of hippocampal involvement in semantic and phonemic word fluency was also investigated. Different hippocampal recruitment during semantic and phonemic fluency was found: greater change in activity was seen during semantic fluency, as compared with phonemic fluency. This pattern was obtained in the right and the left hippocampus, with no lateralization effects. Functional connectivity analyses corroborate the notion of selective contribution of the hippocampus to semantic fluency. During the semantic fluency task, connectivity levels between the hippocampi and components of the semantic network did not differ from connectivity levels within the semantic network. In contrast, during the phonemic fluency task, the hippocampi were less correlated with components of the phonemic network, as compared to the within phonemic network connectivity. Importantly, hippocampal connectivity with the semantic network was task-dependent and restricted to periods of semantic fluency performance. Altogether, results suggest that the right and the left hippocampus are integral components of the brain network that selectively supports verbal semantic fluency, but not phonemic fluency.

  16. The anatomy and time course of semantic priming investigated by fMRI and ERPs.

    PubMed

    Rossell, Susan L; Price, Cathy J; Nobre, A Christina

    2003-01-01

    We combined complementary non-invasive brain imaging techniques with behavioural measures to investigate the anatomy and time course of brain activity associated with semantic priming in a lexical-decision task. Participants viewed pairs of stimuli, and decided whether the second item was a real word or not. There were two variables, the semantic relationship between the prime and the target (related or unrelated) and the interval between the onset of prime and target (200 or 1000 ms), to vary the degree of semantic expectancy that was possible during task performance. Behavioural results replicated the well-established finding that identification of the target is facilitated by a preceding semantically related prime. Event-related functional magnetic resonance imaging (efMRI) identified two brain areas involved in the semantic-priming effect. Activity in the anterior medial temporal cortex was diminished when target words were primed by semantically related words, suggesting involvement of this brain region during active semantic association or integration. In contrast, activity in the left supramarginal gyrus in the temporal-parietal junction was enhanced for target words primed by semantically related words. Brain areas influenced by the interval between prime and target words, and by the interaction between word interval and semantic priming were also identified. A parallel experiment using event-related potentials (ERPs) unveiled a striking difference in the time course of semantic priming as a function of expectancy. In line with previous reports, the primary effect of semantic priming on ERPs was the attenuation of the N400 component, in both short- and long-interval conditions. However, the priming effect started significantly earlier in the long-interval condition. Activity in the anterior medial temporal cortex has previously been shown to contribute to the N400 component, a finding that links the priming results obtained with efMRI and ERP methods.

  17. Semantically Enriched Tools for the Knowledge Society: Case of Project Management and Presentation

    NASA Astrophysics Data System (ADS)

    Talaš, Jakub; Gregar, Tomáš; Pitner, Tomáš

    Working with semantically rich data is one of the stepping stones to the knowledge society. In recent years, gathering, processing, and using semantic data have made a big progress, particularly in the academic environment. However, the advantages of the semantic description remain commonly undiscovered by a "common user", including people from academia and IT industry that could otherwise profit from capabilities of contemporary semantic systems in the areas of project management and/or technology-enhanced learning. Mostly, the root cause lays in complexity and non-transparency of the mainstream semantic applications. The semantic tool for project management and presentation consists mainly of a module for the semantic annotation of wiki pages integrated into the project management system Trac. It combines the dynamic, easy-of-use nature and applicability of a wiki for project management with the advantages of semantically rich and accurate approach. The system is released as open-source (OS) and is used for management of students' and research projects at the research lab of the authors.

  18. Concept-oriented indexing of video databases: toward semantic sensitive retrieval and browsing.

    PubMed

    Fan, Jianping; Luo, Hangzai; Elmagarmid, Ahmed K

    2004-07-01

    Digital video now plays an important role in medical education, health care, telemedicine and other medical applications. Several content-based video retrieval (CBVR) systems have been proposed in the past, but they still suffer from the following challenging problems: semantic gap, semantic video concept modeling, semantic video classification, and concept-oriented video database indexing and access. In this paper, we propose a novel framework to make some advances toward the final goal to solve these problems. Specifically, the framework includes: 1) a semantic-sensitive video content representation framework by using principal video shots to enhance the quality of features; 2) semantic video concept interpretation by using flexible mixture model to bridge the semantic gap; 3) a novel semantic video-classifier training framework by integrating feature selection, parameter estimation, and model selection seamlessly in a single algorithm; and 4) a concept-oriented video database organization technique through a certain domain-dependent concept hierarchy to enable semantic-sensitive video retrieval and browsing.

  19. GIDL: a rule based expert system for GenBank Intelligent Data Loading into the Molecular Biodiversity database

    PubMed Central

    2012-01-01

    Background In the scientific biodiversity community, it is increasingly perceived the need to build a bridge between molecular and traditional biodiversity studies. We believe that the information technology could have a preeminent role in integrating the information generated by these studies with the large amount of molecular data we can find in bioinformatics public databases. This work is primarily aimed at building a bioinformatic infrastructure for the integration of public and private biodiversity data through the development of GIDL, an Intelligent Data Loader coupled with the Molecular Biodiversity Database. The system presented here organizes in an ontological way and locally stores the sequence and annotation data contained in the GenBank primary database. Methods The GIDL architecture consists of a relational database and of an intelligent data loader software. The relational database schema is designed to manage biodiversity information (Molecular Biodiversity Database) and it is organized in four areas: MolecularData, Experiment, Collection and Taxonomy. The MolecularData area is inspired to an established standard in Generic Model Organism Databases, the Chado relational schema. The peculiarity of Chado, and also its strength, is the adoption of an ontological schema which makes use of the Sequence Ontology. The Intelligent Data Loader (IDL) component of GIDL is an Extract, Transform and Load software able to parse data, to discover hidden information in the GenBank entries and to populate the Molecular Biodiversity Database. The IDL is composed by three main modules: the Parser, able to parse GenBank flat files; the Reasoner, which automatically builds CLIPS facts mapping the biological knowledge expressed by the Sequence Ontology; the DBFiller, which translates the CLIPS facts into ordered SQL statements used to populate the database. In GIDL Semantic Web technologies have been adopted due to their advantages in data representation, integration and

  20. No one way ticket from orthography to semantics in recognition memory: N400 and P200 effects of associations.

    PubMed

    Stuellein, Nicole; Radach, Ralph R; Jacobs, Arthur M; Hofmann, Markus J

    2016-05-15

    Computational models of word recognition already successfully used associative spreading from orthographic to semantic levels to account for false memories. But can they also account for semantic effects on event-related potentials in a recognition memory task? To address this question, target words in the present study had either many or few semantic associates in the stimulus set. We found larger P200 amplitudes and smaller N400 amplitudes for old words in comparison to new words. Words with many semantic associates led to larger P200 amplitudes and a smaller N400 in comparison to words with a smaller number of semantic associations. We also obtained inverted response time and accuracy effects for old and new words: faster response times and fewer errors were found for old words that had many semantic associates, whereas new words with a large number of semantic associates produced slower response times and more errors. Both behavioral and electrophysiological results indicate that semantic associations between words can facilitate top-down driven lexical access and semantic integration in recognition memory. Our results support neurophysiologically plausible predictions of the Associative Read-Out Model, which suggests top-down connections from semantic to orthographic layers.

  1. Architecture For The Optimization Of A Machining Process In Real Time Through Rule-Based Expert System

    NASA Astrophysics Data System (ADS)

    Serrano, Rafael; González, Luis Carlos; Martín, Francisco Jesús

    2009-11-01

    Under the project SENSOR-IA which has had financial funding from the Order of Incentives to the Regional Technology Centers of the Counsil of Innovation, Science and Enterprise of Andalusia, an architecture for the optimization of a machining process in real time through rule-based expert system has been developed. The architecture consists of an acquisition system and sensor data processing engine (SATD) from an expert system (SE) rule-based which communicates with the SATD. The SE has been designed as an inference engine with an algorithm for effective action, using a modus ponens rule model of goal-oriented rules.The pilot test demonstrated that it is possible to govern in real time the machining process based on rules contained in a SE. The tests have been done with approximated rules. Future work includes an exhaustive collection of data with different tool materials and geometries in a database to extract more precise rules.

  2. A Fuzzy Rule-Base Model for Classification of Spirometric FVC Graphs in Chronical Obstructive Pulmonary Diseases

    DTIC Science & Technology

    2007-11-02

    of distinguishing COPD group diseases (chronic bronchitis, emphysema and asthma ) by using fuzzy theory and to put into practice a “fuzzy rule-base...FVC Plots”. Keywords - asthma , chronic bronchitis, COPD (Chronic Obstructive Pulmonary Disease), emphysema , expert systems, FVC (forced vital...the group of chronic bronchitis, emphysema and asthma because of these reasons [4-7]. Additionally, similar symptoms may cause fuzziness in

  3. Computerized nodule detection in thin-slice CT using selective enhancement filter and automated rule-based classifier

    NASA Astrophysics Data System (ADS)

    Li, Qiang; Li, Feng; Doi, Kunio

    2005-04-01

    We have been developing computer-aided diagnostic (CAD) scheme to assist radiologists detect lung nodules in thoracic CT images. In order to improve the sensitivity for nodule detection, we developed a selective nodule enhancement filter for nodule which can simultaneously enhance nodules and suppress other normal anatomic structures such as blood vessels and airway walls. Therefore, as preprocessing steps, this filter is useful for improving the sensitivity of nodule detection and for reducing the number of false positives. Another new technique we employed in this study is an automated rule-based classifier. It can significantly reduce the extent of the disadvantages of existing rule-based classifiers, including manual design, poor reproducibility, poor evaluation methods such as re-substitution, and a large overtraining effect. Experimental results performed with Monte Carlo simulation and a real lung nodule CT dataset demonstrated that the automated method can completely eliminate overtraining effect in the procedure of cutoff threshold selection, and thus can minimize overall overtraining effect in the rule-based classifier.

  4. Enhanced high-level Petri nets with multiple colors for knowledge verification/validation of rule-based expert systems.

    PubMed

    Wu, C H; Lee, S J

    1997-01-01

    Exploring the properties of rule-based expert systems through Petri net models has received a lot of attention. Traditional Petri nets provide a straightforward but inadequate method for knowledge verification/validation of rule-based expert systems. We propose an enhanced high-level Petri net model in which variables and negative information can be represented and processed properly. Rule inference is modeled exactly and some important aspects in rule-based systems (RBSs), such as conservation of facts, refraction, and closed-world assumption, are considered in this model. With the coloring scheme proposed in this paper, the tasks involved in checking the logic structure and output correctness of an RES are formally investigated. We focus on the detection of redundancy, conflicts, cycles, unnecessary conditions, dead ends, and unreachable goals in an RES. These knowledge verification/validation (KVV) tasks are formulated as the reachability problem and improper knowledge can be detected by solving a set of equations with respect to multiple colors. The complexity of our method is discussed and a comparison of our model with other Petri net models is presented.

  5. Context-dependent semantic processing in the human brain: evidence from idiom comprehension.

    PubMed

    Rommers, Joost; Dijkstra, Ton; Bastiaansen, Marcel

    2013-05-01

    Language comprehension involves activating word meanings and integrating them with the sentence context. This study examined whether these routines are carried out even when they are theoretically unnecessary, namely, in the case of opaque idiomatic expressions, for which the literal word meanings are unrelated to the overall meaning of the expression. Predictable words in sentences were replaced by a semantically related or unrelated word. In literal sentences, this yielded previously established behavioral and electrophysiological signatures of semantic processing: semantic facilitation in lexical decision, a reduced N400 for semantically related relative to unrelated words, and a power increase in the gamma frequency band that was disrupted by semantic violations. However, the same manipulations in idioms yielded none of these effects. Instead, semantic violations elicited a late positivity in idioms. Moreover, gamma band power was lower in correct idioms than in correct literal sentences. It is argued that the brain's semantic expectancy and literal word meaning integration operations can, to some extent, be "switched off" when the context renders them unnecessary. Furthermore, the results lend support to models of idiom comprehension that involve unitary idiom representations.

  6. Action semantics modulate action prediction.

    PubMed

    Springer, Anne; Prinz, Wolfgang

    2010-11-01

    Previous studies have demonstrated that action prediction involves an internal action simulation that runs time-locked to the real action. The present study replicates and extends these findings by indicating a real-time simulation process (Graf et al., 2007), which can be differentiated from a similarity-based evaluation of internal action representations. Moreover, results showed that action semantics modulate action prediction accuracy. The semantic effect was specified by the processing of action verbs and concrete nouns (Experiment 1) and, more specifically, by the dynamics described by action verbs (Experiment 2) and the speed described by the verbs (e.g., "to catch" vs. "to grasp" vs. "to stretch"; Experiment 3). These results propose a linkage between action simulation and action semantics as two yet unrelated domains, a view that coincides with a recent notion of a close link between motor processes and the understanding of action language.

  7. Semantic processing of crowded stimuli?

    PubMed

    Huckauf, Anke; Knops, Andre; Nuerk, Hans-Christoph; Willmes, Klaus

    2008-11-01

    Effects of semantic processing of crowded characters were investigated using numbers as stimuli. In an identification task, typical spacing effects in crowding were replicated. Using the same stimuli in a magnitude comparison task, a smaller effect of spacing was observed as well as an effect of response congruency. These effects were replicated in a second experiment with varying stimulus-onset asynchronies. In addition, decreasing performance with increasing onset-asynchrony (so-called type-B masking) for incongruent flankers indicates semantic processing of target and flankers. The data show that semantic processing takes place even in crowded stimuli. This argues strongly against common accounts of crowding in terms of early stimulus-driven impairments of processing.

  8. Ontology Matching with Semantic Verification

    PubMed Central

    Jean-Mary, Yves R.; Shironoshita, E. Patrick; Kabuka, Mansur R.

    2009-01-01

    ASMOV (Automated Semantic Matching of Ontologies with Verification) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies. PMID:20186256

  9. The semantic web in translational medicine: current applications and future directions.

    PubMed

    Machado, Catia M; Rebholz-Schuhmann, Dietrich; Freitas, Ana T; Couto, Francisco M

    2015-01-01

    Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice.

  10. Semantic, factual, and social language comprehension in adolescents with autism: an FMRI study.

    PubMed

    Groen, W B; Tesink, C; Petersson, K M; van Berkum, J; van der Gaag, R J; Hagoort, P; Buitelaar, J K

    2010-08-01

    Language in high-functioning autism is characterized by pragmatic and semantic deficits, and people with autism have a reduced tendency to integrate information. Because the left and right inferior frontal (LIF and RIF) regions are implicated with integration of speaker information, world knowledge, and semantic knowledge, we hypothesized that abnormal functioning of the LIF and RIF regions might contribute to pragmatic and semantic language deficits in autism. Brain activation of sixteen 12- to 18-year-old, high-functioning autistic participants was measured with functional magnetic resonance imaging during sentence comprehension and compared with that of twenty-six matched controls. The content of the pragmatic sentence was congruent or incongruent with respect to the speaker characteristics (male/female, child/adult, and upper class/lower class). The semantic- and world-knowledge sentences were congruent or incongruent with respect to semantic expectancies and factual expectancies about the world, respectively. In the semantic-knowledge and world-knowledge condition, activation of the LIF region did not differ between groups. In sentences that required integration of speaker information, the autism group showed abnormally reduced activation of the LIF region. The results suggest that people with autism may recruit the LIF region in a different manner in tasks that demand integration of social information.

  11. Towards Automatic Semantic Labelling of 3D City Models

    NASA Astrophysics Data System (ADS)

    Rook, M.; Biljecki, F.; Diakité, A. A.

    2016-10-01

    The lack of semantic information in many 3D city models is a considerable limiting factor in their use, as a lot of applications rely on semantics. Such information is not always available, since it is not collected at all times, it might be lost due to data transformation, or its lack may be caused by non-interoperability in data integration from other sources. This research is a first step in creating an automatic workflow that semantically labels plain 3D city model represented by a soup of polygons, with semantic and thematic information, as defined in the CityGML standard. The first step involves the reconstruction of the topology, which is used in a region growing algorithm that clusters upward facing adjacent triangles. Heuristic rules, embedded in a decision tree, are used to compute a likeliness score for these regions that either represent the ground (terrain) or a RoofSurface. Regions with a high likeliness score, to one of the two classes, are used to create a decision space, which is used in a support vector machine (SVM). Next, topological relations are utilised to select seeds that function as a start in a region growing algorithm, to create regions of triangles of other semantic classes. The topological relationships of the regions are used in the aggregation of the thematic building features. Finally, the level of detail is detected to generate the correct output in CityGML. The results show an accuracy between 85 % and 99 % in the automatic semantic labelling on four different test datasets. The paper is concluded by indicating problems and difficulties implying the next steps in the research.

  12. Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

    NASA Astrophysics Data System (ADS)

    Fox, P.

    2012-04-01

    The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

  13. Metadata management and semantics in microarray repositories.

    PubMed

    Kocabaş, F; Can, T; Baykal, N

    2011-12-01

    The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework.

  14. NCBO Technology: Powering semantically aware applications.

    PubMed

    Whetzel, Patricia L

    2013-04-15

    As new biomedical technologies are developed, the amount of publically available biomedical data continues to increase. To help manage these vast and disparate data sources, researchers have turned to the Semantic Web. Specifically, ontologies are used in data annotation, natural language processing, information retrieval, clinical decision support, and data integration tasks. The development of software applications to perform these tasks requires the integration of Web services to incorporate the wide variety of ontologies used in the health care and life sciences. The National Center for Biomedical Ontology, a National Center for Biomedical Computing created under the NIH Roadmap, developed BioPortal, which provides access to one of the largest repositories of biomedical ontologies. The NCBO Web services provide programmtic access to these ontologies and can be grouped into four categories; Ontology, Mapping, Annotation, and Data Access. The Ontology Web services provide access to ontologies, their metadata, ontology versions, downloads, navigation of the class hierarchy (parents, children, siblings) and details of each term. The Mapping Web services provide access to the millions of ontology mappings published in BioPortal. The NCBO Annotator Web service "tags" text automatically with terms from ontologies in BioPortal, and the NCBO Resource Index Web services provides access to an ontology-based index of public, online data resources. The NCBO Widgets package the Ontology Web services for use directly in Web sites. The functionality of the NCBO Web services and widgets are incorporated into semantically aware applications for ontology development and visualization, data annotation, and data integration. This overview will describe these classes of applications, discuss a few examples of each type, and which NCBO Web services are used by these applications.

  15. Neural bases of syntax-semantics interface processing.

    PubMed

    Malaia, Evguenia; Newman, Sharlene

    2015-06-01

    The binding problem-question of how information between the modules of the linguistic system is integrated during language processing-is as yet unresolved. The remarkable speed of language processing and comprehension (Pulvermüller et al. 2009) suggests that at least coarse semantic information (e.g. noun animacy) and syntactically-relevant information (e.g. verbal template) are integrated rapidly to allow for coarse comprehension. This EEG study investigated syntax-semantics interface processing during word-by-word sentence reading. As alpha-band neural activity serves as an inhibition mechanism for local networks, we used topographical distribution of alpha power to help identify the timecourse of the binding process. We manipulated the syntactic parameter of verbal event structure, and semantic parameter of noun animacy in reduced relative clauses (RRCs, e.g. "The witness/mansion seized/protected by the agent was in danger"), to investigate the neural bases of interaction between syntactic and semantic networks during sentence processing. The word-by-word stimulus presentation method in the present experiment required manipulation of both syntactic structure and semantic features in the working memory. The results demonstrated a gradient distribution of early components (biphasic posterior P1-N2 and anterior N1-P2) over function words "by" and "the", and the verb, corresponding to facilitation or conflict resulting from the syntactic (telicity) and semantic (animacy) cues in the preceding portion of the sentence. This was followed by assimilation of power distribution in the α band at the second noun. The flattened distribution of α power during the mental manipulation with high demand on working memory-thematic role re-assignment-demonstrates a state of α equilibrium with strong functional coupling between posterior and anterior regions. These results demonstrate that the processing of semantic and syntactic features during sentence comprehension proceeds

  16. Semantic processing in information retrieval.

    PubMed Central

    Rindflesch, T. C.; Aronson, A. R.

    1993-01-01

    Intuition suggests that one way to enhance the information retrieval process would be the use of phrases to characterize the contents of text. A number of researchers, however, have noted that phrases alone do not improve retrieval effectiveness. In this paper we briefly review the use of phrases in information retrieval and then suggest extensions to this paradigm using semantic information. We claim that semantic processing, which can be viewed as expressing relations between the concepts represented by phrases, will in fact enhance retrieval effectiveness. The availability of the UMLS domain model, which we exploit extensively, significantly contributes to the feasibility of this processing. PMID:8130547

  17. Bootstrapping to a Semantic Grid

    SciTech Connect

    Schwidder, Jens; Talbott, Tara; Myers, James D.

    2005-02-28

    The Scientific Annotation Middleware (SAM) is a set of components and services that enable researchers, applications, problem solving environments (PSE) and software agents to create metadata and annotations about data objects and document the semantic relationships between them. Developed starting in 2001, SAM allows applications to encode metadata within files or to manage metadata at the level of individual relationships as desired. SAM then provides mechanisms to expose metadata and relation¬ships encoded either way as WebDAV properties. In this paper, we report on work to further map this metadata into RDF and discuss the role of middleware such as SAM in bridging between traditional and semantic grid applications.

  18. Language networks in semantic dementia.

    PubMed

    Agosta, Federica; Henry, Roland G; Migliaccio, Raffaella; Neuhaus, John; Miller, Bruce L; Dronkers, Nina F; Brambati, Simona M; Filippi, Massimo; Ogar, Jennifer M; Wilson, Stephen M; Gorno-Tempini, Maria Luisa

    2010-01-01

    Cognitive deficits in semantic dementia have been attributed to anterior temporal lobe grey matter damage; however, key aspects of the syndrome could be due to altered anatomical connectivity between language pathways involving the temporal lobe. The aim of this study was to investigate the left language-related cerebral pathways in semantic dementia using diffusion tensor imaging-based tractography and to combine the findings with cortical anatomical and functional magnetic resonance imaging data obtained during a reading activation task. The left inferior longitudinal fasciculus, arcuate fasciculus and fronto-parietal superior longitudinal fasciculus were tracked in five semantic dementia patients and eight healthy controls. The left uncinate fasciculus and the genu and splenium of the corpus callosum were also obtained for comparison with previous studies. From each tract, mean diffusivity, fractional anisotropy, as well as parallel and transverse diffusivities were obtained. Diffusion tensor imaging results were related to grey and white matter atrophy volume assessed by voxel-based morphometry and functional magnetic resonance imaging activations during a reading task. Semantic dementia patients had significantly higher mean diffusivity, parallel and transverse in the inferior longitudinal fasciculus. The arcuate and uncinate fasciculi demonstrated significantly higher mean diffusivity, parallel and transverse and significantly lower fractional anisotropy. The fronto-parietal superior longitudinal fasciculus was relatively spared, with a significant difference observed for transverse diffusivity and fractional anisotropy, only. In the corpus callosum, the genu showed lower fractional anisotropy compared with controls, while no difference was found in the splenium. The left parietal cortex did not show significant volume changes on voxel-based morphometry and demonstrated normal functional magnetic resonance imaging activation in response to reading items that

  19. Language networks in semantic dementia

    PubMed Central

    Agosta, Federica; Henry, Roland G.; Migliaccio, Raffaella; Neuhaus, John; Miller, Bruce L.; Dronkers, Nina F.; Brambati, Simona M.; Filippi, Massimo; Ogar, Jennifer M.; Wilson, Stephen M.

    2010-01-01

    Cognitive deficits in semantic dementia have been attributed to anterior temporal lobe grey matter damage; however, key aspects of the syndrome could be due to altered anatomical connectivity between language pathways involving the temporal lobe. The aim of this study was to investigate the left language-related cerebral pathways in semantic dementia using diffusion tensor imaging-based tractography and to combine the findings with cortical anatomical and functional magnetic resonance imaging data obtained during a reading activation task. The left inferior longitudinal fasciculus, arcuate fasciculus and fronto-parietal superior longitudinal fasciculus were tracked in five semantic dementia patients and eight healthy controls. The left uncinate fasciculus and the genu and splenium of the corpus callosum were also obtained for comparison with previous studies. From each tract, mean diffusivity, fractional anisotropy, as well as parallel and transverse diffusivities were obtained. Diffusion tensor imaging results were related to grey and white matter atrophy volume assessed by voxel-based morphometry and functional magnetic resonance imaging activations during a reading task. Semantic dementia patients had significantly higher mean diffusivity, parallel and transverse in the inferior longitudinal fasciculus. The arcuate and uncinate fasciculi demonstrated significantly higher mean diffusivity, parallel and transverse and significantly lower fractional anisotropy. The fronto-parietal superior longitudinal fasciculus was relatively spared, with a significant difference observed for transverse diffusivity and fractional anisotropy, only. In the corpus callosum, the genu showed lower fractional anisotropy compared with controls, while no difference was found in the splenium. The left parietal cortex did not show significant volume changes on voxel-based morphometry and demonstrated normal functional magnetic resonance imaging activation in response to reading items that

  20. Abstraction and natural language semantics.

    PubMed Central

    Kayser, Daniel

    2003-01-01

    According to the traditional view, a word prototypically denotes a class of objects sharing similar features, i.e. it results from an abstraction based on the detection of common properties in perceived entities. I explore here another idea: words result from abstraction of common premises in the rules governing our actions. I first argue that taking 'inference', instead of 'reference', as the basic issue in semantics does matter. I then discuss two phenomena that are, in my opinion, particularly difficult to analyse within the scope of traditional semantic theories: systematic polysemy and plurals. I conclude by a discussion of my approach, and by a summary of its main features. PMID:12903662