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Sample records for latent semantic indexing

  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. On updating problems in latent semantic indexing

    SciTech Connect

    Zha, H.; Simon, H.D.

    1999-10-01

    The authors develop new SVD-updating algorithms for three types of updating problems arising from latent semantic indexing (LSI) for information retrieval to deal with rapidly changing text document collections. They also provide theoretical justification for using a reduced-dimension representation of the original document collection in the updating process. Numerical experiments using several standard text document collections show that the new algorithms give higher (interpolated) average precisions that the existing algorithms, and the retrieval accuracy is comparable to that obtained using the complete document collection.

  3. On updating problems in latent semantic indexing

    SciTech Connect

    Simon, H.D.; Zha, H.

    1997-11-01

    The authors develop new SVD-updating algorithms for three types of updating problems arising from Latent Semantic Indexing (LSI) for information retrieval to deal with rapidly changing text document collections. They also provide theoretical justification for using a reduced-dimension representation of the original document collection in the updating process. Numerical experiments using several standard text document collections show that the new algorithms give higher (interpolated) average precisions than the existing algorithms and the retrieval accuracy is comparable to that obtained using the complete document collection.

  4. Asymmetric latent semantic indexing for gene expression experiments visualization.

    PubMed

    González, Javier; Muñoz, Alberto; Martos, Gabriel

    2016-08-01

    We propose a new method to visualize gene expression experiments inspired by the latent semantic indexing technique originally proposed in the textual analysis context. By using the correspondence word-gene document-experiment, we define an asymmetric similarity measure of association for genes that accounts for potential hierarchies in the data, the key to obtain meaningful gene mappings. We use the polar decomposition to obtain the sources of asymmetry of the similarity matrix, which are later combined with previous knowledge. Genetic classes of genes are identified by means of a mixture model applied in the genes latent space. We describe the steps of the procedure and we show its utility in the Human Cancer dataset. PMID:27427382

  5. An Explanation of the Effectiveness of Latent Semantic Indexing by Means of a Bayesian Regression Model.

    ERIC Educational Resources Information Center

    Story, Roger E.

    1996-01-01

    Discussion of the use of Latent Semantic Indexing to determine relevancy in information retrieval focuses on statistical regression and Bayesian methods. Topics include keyword searching; a multiple regression model; how the regression model can aid search methods; and limitations of this approach, including complexity, linearity, and…

  6. A Comparison of SVD, SVR, ADE and IRR for Latent Semantic Indexing

    NASA Astrophysics Data System (ADS)

    Zhang, Wen; Tang, Xijin; Yoshida, Taketoshi

    Recently, singular value decomposition (SVD) and its variants, which are singular value rescaling (SVR), approximation dimension equalization (ADE) and iterative residual rescaling (IRR), were proposed to conduct the job of latent semantic indexing (LSI). Although they are all based on linear algebraic method for tem-document matrix computation, which is SVD, the basic motivations behind them concerning LSI are different from each other. In this paper, a series of experiments are conducted to examine their effectiveness of LSI for the practical application of text mining, including information retrieval, text categorization and similarity measure. The experimental results demonstrate that SVD and SVR have better performances than other proposed LSI methods in the above mentioned applications. Meanwhile, ADE and IRR, because of the too much difference between their approximation matrix and original term-document matrix in Frobenius norm, can not derive good performances for text mining applications using LSI.

  7. Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications.

    PubMed

    Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M; Maudsley, Stuart

    2013-01-01

    Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

  8. Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications

    PubMed Central

    Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M.; Maudsley, Stuart

    2012-01-01

    Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data. PMID:23386833

  9. 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…

  10. Latent semantic analysis.

    PubMed

    Evangelopoulos, Nicholas E

    2013-11-01

    This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. PMID:26304272

  11. Latent semantic analysis.

    PubMed

    Evangelopoulos, Nicholas E

    2013-11-01

    This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

  12. Prediction of nuclear proteins using nuclear translocation signals proposed by probabilistic latent semantic indexing

    PubMed Central

    2012-01-01

    Background Identification of subcellular localization in proteins is crucial to elucidate cellular processes and molecular functions in a cell. However, given a tremendous amount of sequence data generated in the post-genomic era, determining protein localization based on biological experiments can be expensive and time-consuming. Therefore, developing prediction systems to analyze uncharacterised proteins efficiently has played an important role in high-throughput protein analyses. In a eukaryotic cell, many essential biological processes take place in the nucleus. Nuclear proteins shuttle between nucleus and cytoplasm based on recognition of nuclear translocation signals, including nuclear localization signals (NLSs) and nuclear export signals (NESs). Currently, only a few approaches have been developed specifically to predict nuclear localization using sequence features, such as putative NLSs. However, it has been shown that prediction coverage based on the NLSs is very low. In addition, most existing approaches only attained prediction accuracy and Matthew's correlation coefficient (MCC) around 54%~70% and 0.250~0.380 on independent test set, respectively. Moreover, no predictor can generate sequence motifs to characterize features of potential NESs, in which biological properties are not well understood from existing experimental studies. Results In this study, first we propose PSLNuc (Protein Subcellular Localization prediction for Nucleus) for predicting nuclear localization in proteins. First, for feature representation, a protein is represented by gapped-dipeptides and the feature values are weighted by homology information from a smoothed position-specific scoring matrix. After that, we incorporate probabilistic latent semantic indexing (PLSI) for feature reduction. Finally, the reduced features are used as input for a support vector machine (SVM) classifier. In addition to PSLNuc, we further identify gapped-dipeptide signatures for putative NLSs and NESs

  13. Comparing and Combining the Effectiveness of Latent Semantic Indexing and the Ordinary Vector Space Model for Information Retrieval.

    ERIC Educational Resources Information Center

    Lochbaum, Karen E.; Streeter, Lynn A.

    1989-01-01

    Describes experiments that compared a new method for automatically analyzing semantic structures in text by statistical means with the standard vector space model. Findings indicate that combining both methods improved performance over either alone. The effects of other experimental variables on retrieval performance (term weighting, suffix…

  14. From paragraph to graph: Latent semantic analysis for information visualization

    PubMed Central

    Landauer, Thomas K.; Laham, Darrell; Derr, Marcia

    2004-01-01

    Most techniques for relating textual information rely on intellectually created links such as author-chosen keywords and titles, authority indexing terms, or bibliographic citations. Similarity of the semantic content of whole documents, rather than just titles, abstracts, or overlap of keywords, offers an attractive alternative. Latent semantic analysis provides an effective dimension reduction method for the purpose that reflects synonymy and the sense of arbitrary word combinations. However, latent semantic analysis correlations with human text-to-text similarity judgments are often empirically highest at ≈300 dimensions. Thus, two- or three-dimensional visualizations are severely limited in what they can show, and the first and/or second automatically discovered principal component, or any three such for that matter, rarely capture all of the relations that might be of interest. It is our conjecture that linguistic meaning is intrinsically and irreducibly very high dimensional. Thus, some method to explore a high dimensional similarity space is needed. But the 2.7 × 107 projections and infinite rotations of, for example, a 300-dimensional pattern are impossible to examine. We suggest, however, that the use of a high dimensional dynamic viewer with an effective projection pursuit routine and user control, coupled with the exquisite abilities of the human visual system to extract information about objects and from moving patterns, can often succeed in discovering multiple revealing views that are missed by current computational algorithms. We show some examples of the use of latent semantic analysis to support such visualizations and offer views on future needs. PMID:15037748

  15. From paragraph to graph: latent semantic analysis for information visualization.

    PubMed

    Landauer, Thomas K; Laham, Darrell; Derr, Marcia

    2004-04-01

    Most techniques for relating textual information rely on intellectually created links such as author-chosen keywords and titles, authority indexing terms, or bibliographic citations. Similarity of the semantic content of whole documents, rather than just titles, abstracts, or overlap of keywords, offers an attractive alternative. Latent semantic analysis provides an effective dimension reduction method for the purpose that reflects synonymy and the sense of arbitrary word combinations. However, latent semantic analysis correlations with human text-to-text similarity judgments are often empirically highest at approximately 300 dimensions. Thus, two- or three-dimensional visualizations are severely limited in what they can show, and the first and/or second automatically discovered principal component, or any three such for that matter, rarely capture all of the relations that might be of interest. It is our conjecture that linguistic meaning is intrinsically and irreducibly very high dimensional. Thus, some method to explore a high dimensional similarity space is needed. But the 2.7 x 10(7) projections and infinite rotations of, for example, a 300-dimensional pattern are impossible to examine. We suggest, however, that the use of a high dimensional dynamic viewer with an effective projection pursuit routine and user control, coupled with the exquisite abilities of the human visual system to extract information about objects and from moving patterns, can often succeed in discovering multiple revealing views that are missed by current computational algorithms. We show some examples of the use of latent semantic analysis to support such visualizations and offer views on future needs.

  16. Transforming Selected Concepts into Dimensions in Latent Semantic Analysis

    ERIC Educational Resources Information Center

    Olmos, Ricardo; Jorge-Botana, Guillermo; León, José Antonio; Escudero, Inmaculada

    2014-01-01

    This study presents a new approach for transforming the latent representation derived from a Latent Semantic Analysis (LSA) space into one where dimensions have nonlatent meanings. These meanings are based on lexical descriptors, which are selected by the LSA user. The authors present three analyses that provide examples of the utility of this…

  17. Effectiveness of Automated Chinese Sentence Scoring with Latent Semantic Analysis

    ERIC Educational Resources Information Center

    Liao, Chen-Huei; Kuo, Bor-Chen; Pai, Kai-Chih

    2012-01-01

    Automated scoring by means of Latent Semantic Analysis (LSA) has been introduced lately to improve the traditional human scoring system. The purposes of the present study were to develop a LSA-based assessment system to evaluate children's Chinese sentence construction skills and to examine the effectiveness of LSA-based automated scoring function…

  18. Modeling semantic aspects for cross-media image indexing.

    PubMed

    Monay, Florent; Gatica-Perez, Daniel

    2007-10-01

    To go beyond the query-by-example paradigm in image retrieval, there is a need for semantic indexing of large image collections for intuitive text-based image search. Different models have been proposed to learn the dependencies between the visual content of an image set and the associated text captions, then allowing for the automatic creation of semantic indices for unannotated images. The task, however, remains unsolved. In this paper, we present three alternatives to learn a Probabilistic Latent Semantic Analysis model (PLSA) for annotated images, and evaluate their respective performance for automatic image indexing. Under the PLSA assumptions, an image is modeled as a mixture of latent aspects that generates both image features and text captions, and we investigate three ways to learn the mixture of aspects. We also propose a more discriminative image representation than the traditional Blob histogram, concatenating quantized local color information and quantized local texture descriptors. The first learning procedure of a PLSA model for annotated images is a standard EM algorithm, which implicitly assumes that the visual and the textual modalities can be treated equivalently. The other two models are based on an asymmetric PLSA learning, allowing to constrain the definition of the latent space on the visual or on the textual modality. We demonstrate that the textual modality is more appropriate to learn a semantically meaningful latent space, which translates into improved annotation performance. A comparison of our learning algorithms with respect to recent methods on a standard dataset is presented, and a detailed evaluation of the performance shows the validity of our framework. PMID:17699924

  19. Modeling semantic aspects for cross-media image indexing.

    PubMed

    Monay, Florent; Gatica-Perez, Daniel

    2007-10-01

    To go beyond the query-by-example paradigm in image retrieval, there is a need for semantic indexing of large image collections for intuitive text-based image search. Different models have been proposed to learn the dependencies between the visual content of an image set and the associated text captions, then allowing for the automatic creation of semantic indices for unannotated images. The task, however, remains unsolved. In this paper, we present three alternatives to learn a Probabilistic Latent Semantic Analysis model (PLSA) for annotated images, and evaluate their respective performance for automatic image indexing. Under the PLSA assumptions, an image is modeled as a mixture of latent aspects that generates both image features and text captions, and we investigate three ways to learn the mixture of aspects. We also propose a more discriminative image representation than the traditional Blob histogram, concatenating quantized local color information and quantized local texture descriptors. The first learning procedure of a PLSA model for annotated images is a standard EM algorithm, which implicitly assumes that the visual and the textual modalities can be treated equivalently. The other two models are based on an asymmetric PLSA learning, allowing to constrain the definition of the latent space on the visual or on the textual modality. We demonstrate that the textual modality is more appropriate to learn a semantically meaningful latent space, which translates into improved annotation performance. A comparison of our learning algorithms with respect to recent methods on a standard dataset is presented, and a detailed evaluation of the performance shows the validity of our framework.

  20. Massively Parallel Latent Semantic Analyzes using a Graphics Processing Unit

    SciTech Connect

    Cavanagh, Joseph M; Cui, Xiaohui

    2009-01-01

    Latent Semantic Indexing (LSA) aims to reduce the dimensions of large Term-Document datasets using Singular Value Decomposition. However, with the ever expanding size of data sets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. The Graphics Processing Unit (GPU) can solve some highly parallel problems much faster than the traditional sequential processor (CPU). Thus, a deployable system using a GPU to speedup large-scale LSA processes would be a much more effective choice (in terms of cost/performance ratio) than using a computer cluster. Due to the GPU s application-specific architecture, harnessing the GPU s computational prowess for LSA is a great challenge. We present a parallel LSA implementation on the GPU, using NVIDIA Compute Unified Device Architecture and Compute Unified Basic Linear Algebra Subprograms. The performance of this implementation is compared to traditional LSA implementation on CPU using an optimized Basic Linear Algebra Subprograms library. After implementation, we discovered that the GPU version of the algorithm was twice as fast for large matrices (1000x1000 and above) that had dimensions not divisible by 16. For large matrices that did have dimensions divisible by 16, the GPU algorithm ran five to six times faster than the CPU version. The large variation is due to architectural benefits the GPU has for matrices divisible by 16. It should be noted that the overall speeds for the CPU version did not vary from relative normal when the matrix dimensions were divisible by 16. Further research is needed in order to produce a fully implementable version of LSA. With that in mind, the research we presented shows that the GPU is a viable option for increasing the speed of LSA, in terms of cost/performance ratio.

  1. Probabilistic latent semantic analysis applied to whole bacterial genomes identifies common genomic features.

    PubMed

    Rusakovica, Julija; Hallinan, Jennifer; Wipat, Anil; Zuliani, Paolo

    2014-01-01

    The spread of drug resistance amongst clinically-important bacteria is a serious, and growing, problem [1]. However, the analysis of entire genomes requires considerable computational effort, usually including the assembly of the genome and subsequent identification of genes known to be important in pathology. An alternative approach is to use computational algorithms to identify genomic differences between pathogenic and non-pathogenic bacteria, even without knowing the biological meaning of those differences. To overcome this problem, a range of techniques for dimensionality reduction have been developed. One such approach is known as latent-variable models [2]. In latent-variable models dimensionality reduction is achieved by representing a high-dimensional data by a few hidden or latent variables, which are not directly observed but inferred from the observed variables present in the model. Probabilistic Latent Semantic Indexing (PLSA) is an extention of LSA [3]. PLSA is based on a mixture decomposition derived from a latent class model. The main objective of the algorithm, as in LSA, is to represent high-dimensional co-occurrence information in a lower-dimensional way in order to discover the hidden semantic structure of the data using a probabilistic framework. In this work we applied the PLSA approach to analyse the common genomic features in methicillin resistant Staphylococcus aureus, using tokens derived from amino acid sequences rather than DNA. We characterised genome-scale amino acid sequences in terms of their components, and then investigated the relationships between genomes and tokens and the phenotypes they generated. As a control we used the non-pathogenic model Gram-positive bacterium Bacillus subtilis. PMID:24980693

  2. Probabilistic latent semantic analysis applied to whole bacterial genomes identifies common genomic features.

    PubMed

    Rusakovica, Julija; Hallinan, Jennifer; Wipat, Anil; Zuliani, Paolo

    2014-06-30

    The spread of drug resistance amongst clinically-important bacteria is a serious, and growing, problem [1]. However, the analysis of entire genomes requires considerable computational effort, usually including the assembly of the genome and subsequent identification of genes known to be important in pathology. An alternative approach is to use computational algorithms to identify genomic differences between pathogenic and non-pathogenic bacteria, even without knowing the biological meaning of those differences. To overcome this problem, a range of techniques for dimensionality reduction have been developed. One such approach is known as latent-variable models [2]. In latent-variable models dimensionality reduction is achieved by representing a high-dimensional data by a few hidden or latent variables, which are not directly observed but inferred from the observed variables present in the model. Probabilistic Latent Semantic Indexing (PLSA) is an extention of LSA [3]. PLSA is based on a mixture decomposition derived from a latent class model. The main objective of the algorithm, as in LSA, is to represent high-dimensional co-occurrence information in a lower-dimensional way in order to discover the hidden semantic structure of the data using a probabilistic framework. In this work we applied the PLSA approach to analyse the common genomic features in methicillin resistant Staphylococcus aureus, using tokens derived from amino acid sequences rather than DNA. We characterised genome-scale amino acid sequences in terms of their components, and then investigated the relationships between genomes and tokens and the phenotypes they generated. As a control we used the non-pathogenic model Gram-positive bacterium Bacillus subtilis.

  3. Parallel Latent Semantic Analysis using a Graphics Processing Unit

    SciTech Connect

    Cui, Xiaohui; Potok, Thomas E; Cavanagh, Joseph M

    2009-01-01

    Latent Semantic Analysis (LSA) can be used to reduce the dimensions of large Term-Document datasets using Singular Value Decomposition. However, with the ever expanding size of data sets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. The Graphics Processing Unit (GPU) can solve some highly parallel problems much faster than the traditional sequential processor (CPU). Thus, a deployable system using a GPU to speedup large-scale LSA processes would be a much more effective choice (in terms of cost/performance ratio) than using a computer cluster. In this paper, we presented a parallel LSA implementation on the GPU, using NVIDIA Compute Unified Device Architecture (CUDA) and Compute Unified Basic Linear Algebra Subprograms (CUBLAS). The performance of this implementation is compared to traditional LSA implementation on CPU using an optimized Basic Linear Algebra Subprograms library. For large matrices that have dimensions divisible by 16, the GPU algorithm ran five to six times faster than the CPU version.

  4. MASSIVELY PARALLEL LATENT SEMANTIC ANALYSES USING A GRAPHICS PROCESSING UNIT

    SciTech Connect

    Cavanagh, J.; Cui, S.

    2009-01-01

    Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using Singular Value Decomposition. However, with the ever-expanding size of datasets, current implementations are not fast enough to quickly and easily compute the results on a standard PC. A graphics processing unit (GPU) can solve some highly parallel problems much faster than a traditional sequential processor or central processing unit (CPU). Thus, a deployable system using a GPU to speed up large-scale LSA processes would be a much more effective choice (in terms of cost/performance ratio) than using a PC cluster. Due to the GPU’s application-specifi c architecture, harnessing the GPU’s computational prowess for LSA is a great challenge. We presented a parallel LSA implementation on the GPU, using NVIDIA® Compute Unifi ed Device Architecture and Compute Unifi ed Basic Linear Algebra Subprograms software. The performance of this implementation is compared to traditional LSA implementation on a CPU using an optimized Basic Linear Algebra Subprograms library. After implementation, we discovered that the GPU version of the algorithm was twice as fast for large matrices (1 000x1 000 and above) that had dimensions not divisible by 16. For large matrices that did have dimensions divisible by 16, the GPU algorithm ran fi ve to six times faster than the CPU version. The large variation is due to architectural benefi ts of the GPU for matrices divisible by 16. It should be noted that the overall speeds for the CPU version did not vary from relative normal when the matrix dimensions were divisible by 16. Further research is needed in order to produce a fully implementable version of LSA. With that in mind, the research we presented shows that the GPU is a viable option for increasing the speed of LSA, in terms of cost/performance ratio.

  5. A computational modeling of semantic knowledge in reading comprehension: Integrating the landscape model with latent semantic analysis.

    PubMed

    Yeari, Menahem; van den Broek, Paul

    2016-09-01

    It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena.

  6. A computational modeling of semantic knowledge in reading comprehension: Integrating the landscape model with latent semantic analysis.

    PubMed

    Yeari, Menahem; van den Broek, Paul

    2016-09-01

    It is a well-accepted view that the prior semantic (general) knowledge that readers possess plays a central role in reading comprehension. Nevertheless, computational models of reading comprehension have not integrated the simulation of semantic knowledge and online comprehension processes under a unified mathematical algorithm. The present article introduces a computational model that integrates the landscape model of comprehension processes with latent semantic analysis representation of semantic knowledge. In three sets of simulations of previous behavioral findings, the integrated model successfully simulated the activation and attenuation of predictive and bridging inferences during reading, as well as centrality estimations and recall of textual information after reading. Analyses of the computational results revealed new theoretical insights regarding the underlying mechanisms of the various comprehension phenomena. PMID:27383752

  7. Latent Semantic Analysis as a Method of Content-Based Image Retrieval in Medical Applications

    ERIC Educational Resources Information Center

    Makovoz, Gennadiy

    2010-01-01

    The research investigated whether a Latent Semantic Analysis (LSA)-based approach to image retrieval can map pixel intensity into a smaller concept space with good accuracy and reasonable computational cost. From a large set of M computed tomography (CT) images, a retrieval query found all images for a particular patient based on semantic…

  8. Semantic-Aware Co-Indexing for Image Retrieval.

    PubMed

    Zhang, Shiliang; Yang, Ming; Wang, Xiaoyu; Lin, Yuanqing; Tian, Qi

    2015-12-01

    In content-based image retrieval, inverted indexes allow fast access to database images and summarize all knowledge about the database. Indexing multiple clues of image contents allows retrieval algorithms search for relevant images from different perspectives, which is appealing to deliver satisfactory user experiences. However, when incorporating diverse image features during online retrieval, it is challenging to ensure retrieval efficiency and scalability. In this paper, for large-scale image retrieval, we propose a semantic-aware co-indexing algorithm to jointly embed two strong cues into the inverted indexes: 1) local invariant features that are robust to delineate low-level image contents, and 2) semantic attributes from large-scale object recognition that may reveal image semantic meanings. Specifically, for an initial set of inverted indexes of local features, we utilize semantic attributes to filter out isolated images and insert semantically similar images to this initial set. Encoding these two distinct and complementary cues together effectively enhances the discriminative capability of inverted indexes. Such co-indexing operations are totally off-line and introduce small computation overhead to online retrieval, because only local features but no semantic attributes are employed for the query. Hence, this co-indexing is different from existing image retrieval methods fusing multiple features or retrieval results. Extensive experiments and comparisons with recent retrieval methods manifest the competitive performance of our method. PMID:26539859

  9. Semantic-Aware Co-Indexing for Image Retrieval.

    PubMed

    Zhang, Shiliang; Yang, Ming; Wang, Xiaoyu; Lin, Yuanqing; Tian, Qi

    2015-12-01

    In content-based image retrieval, inverted indexes allow fast access to database images and summarize all knowledge about the database. Indexing multiple clues of image contents allows retrieval algorithms search for relevant images from different perspectives, which is appealing to deliver satisfactory user experiences. However, when incorporating diverse image features during online retrieval, it is challenging to ensure retrieval efficiency and scalability. In this paper, for large-scale image retrieval, we propose a semantic-aware co-indexing algorithm to jointly embed two strong cues into the inverted indexes: 1) local invariant features that are robust to delineate low-level image contents, and 2) semantic attributes from large-scale object recognition that may reveal image semantic meanings. Specifically, for an initial set of inverted indexes of local features, we utilize semantic attributes to filter out isolated images and insert semantically similar images to this initial set. Encoding these two distinct and complementary cues together effectively enhances the discriminative capability of inverted indexes. Such co-indexing operations are totally off-line and introduce small computation overhead to online retrieval, because only local features but no semantic attributes are employed for the query. Hence, this co-indexing is different from existing image retrieval methods fusing multiple features or retrieval results. Extensive experiments and comparisons with recent retrieval methods manifest the competitive performance of our method.

  10. Latent morpho-semantic analysis : multilingual information retrieval with character n-grams and mutual information.

    SciTech Connect

    Bader, Brett William; Chew, Peter A.; Abdelali, Ahmed

    2008-08-01

    We describe an entirely statistics-based, unsupervised, and language-independent approach to multilingual information retrieval, which we call Latent Morpho-Semantic Analysis (LMSA). LMSA overcomes some of the shortcomings of related previous approaches such as Latent Semantic Analysis (LSA). LMSA has an important theoretical advantage over LSA: it combines well-known techniques in a novel way to break the terms of LSA down into units which correspond more closely to morphemes. Thus, it has a particular appeal for use with morphologically complex languages such as Arabic. We show through empirical results that the theoretical advantages of LMSA can translate into significant gains in precision in multilingual information retrieval tests. These gains are not matched either when a standard stemmer is used with LSA, or when terms are indiscriminately broken down into n-grams.

  11. Latent Semantics of Action Verbs Reflect Phonetic Parameters of Intensity and Emotional Content

    PubMed Central

    Petersen, Michael Kai

    2015-01-01

    Conjuring up our thoughts, language reflects statistical patterns of word co-occurrences which in turn come to describe how we perceive the world. Whether counting how frequently nouns and verbs combine in Google search queries, or extracting eigenvectors from term document matrices made up of Wikipedia lines and Shakespeare plots, the resulting latent semantics capture not only the associative links which form concepts, but also spatial dimensions embedded within the surface structure of language. As both the shape and movements of objects have been found to be associated with phonetic contrasts already in toddlers, this study explores whether articulatory and acoustic parameters may likewise differentiate the latent semantics of action verbs. Selecting 3 × 20 emotion-, face-, and hand-related verbs known to activate premotor areas in the brain, their mutual cosine similarities were computed using latent semantic analysis LSA, and the resulting adjacency matrices were compared based on two different large scale text corpora: HAWIK and TASA. Applying hierarchical clustering to identify common structures across the two text corpora, the verbs largely divide into combined mouth and hand movements versus emotional expressions. Transforming the verbs into their constituent phonemes, and projecting them into an articulatory space framed by tongue height and formant frequencies, the clustered small and large size movements appear differentiated by front versus back vowels corresponding to increasing levels of arousal. Whereas the clustered emotional verbs seem characterized by sequences of close versus open jaw produced phonemes, generating up- or downwards shifts in formant frequencies that may influence their perceived valence. Suggesting, that the latent semantics of action verbs reflect parameters of intensity and emotional polarity that appear correlated with the articulatory contrasts and acoustic characteristics of phonemes. PMID:25849977

  12. Latent semantics of action verbs reflect phonetic parameters of intensity and emotional content.

    PubMed

    Petersen, Michael Kai

    2015-01-01

    Conjuring up our thoughts, language reflects statistical patterns of word co-occurrences which in turn come to describe how we perceive the world. Whether counting how frequently nouns and verbs combine in Google search queries, or extracting eigenvectors from term document matrices made up of Wikipedia lines and Shakespeare plots, the resulting latent semantics capture not only the associative links which form concepts, but also spatial dimensions embedded within the surface structure of language. As both the shape and movements of objects have been found to be associated with phonetic contrasts already in toddlers, this study explores whether articulatory and acoustic parameters may likewise differentiate the latent semantics of action verbs. Selecting 3 × 20 emotion-, face-, and hand-related verbs known to activate premotor areas in the brain, their mutual cosine similarities were computed using latent semantic analysis LSA, and the resulting adjacency matrices were compared based on two different large scale text corpora: HAWIK and TASA. Applying hierarchical clustering to identify common structures across the two text corpora, the verbs largely divide into combined mouth and hand movements versus emotional expressions. Transforming the verbs into their constituent phonemes, and projecting them into an articulatory space framed by tongue height and formant frequencies, the clustered small and large size movements appear differentiated by front versus back vowels corresponding to increasing levels of arousal. Whereas the clustered emotional verbs seem characterized by sequences of close versus open jaw produced phonemes, generating up- or downwards shifts in formant frequencies that may influence their perceived valence. Suggesting, that the latent semantics of action verbs reflect parameters of intensity and emotional polarity that appear correlated with the articulatory contrasts and acoustic characteristics of phonemes.

  13. Simulating Expert Clinical Comprehension: Adapting Latent Semantic Analysis to Accurately Extract Clinical Concepts from Psychiatric Narrative

    PubMed Central

    Cohen, Trevor; Blatter, Brett; Patel, Vimla

    2008-01-01

    Cognitive studies reveal that less-than-expert clinicians are less able to recognize meaningful patterns of data in clinical narratives. Accordingly, psychiatric residents early in training fail to attend to information that is relevant to diagnosis and the assessment of dangerousness. This manuscript presents cognitively motivated methodology for the simulation of expert ability to organize relevant findings supporting intermediate diagnostic hypotheses. Latent Semantic Analysis is used to generate a semantic space from which meaningful associations between psychiatric terms are derived. Diagnostically meaningful clusters are modeled as geometric structures within this space and compared to elements of psychiatric narrative text using semantic distance measures. A learning algorithm is defined that alters components of these geometric structures in response to labeled training data. Extraction and classification of relevant text segments is evaluated against expert annotation, with system-rater agreement approximating rater-rater agreement. A range of biomedical informatics applications for these methods are suggested. PMID:18455483

  14. Semantic Indexing of Medical Learning Objects: Medical Students' Usage of a Semantic Network

    PubMed Central

    Gießler, Paul; Ohnesorge-Radtke, Ursula; Spreckelsen, Cord

    2015-01-01

    Background The Semantically Annotated Media (SAM) project aims to provide a flexible platform for searching, browsing, and indexing medical learning objects (MLOs) based on a semantic network derived from established classification systems. Primarily, SAM supports the Aachen emedia skills lab, but SAM is ready for indexing distributed content and the Simple Knowledge Organizing System standard provides a means for easily upgrading or even exchanging SAM’s semantic network. There is a lack of research addressing the usability of MLO indexes or search portals like SAM and the user behavior with such platforms. Objective The purpose of this study was to assess the usability of SAM by investigating characteristic user behavior of medical students accessing MLOs via SAM. Methods In this study, we chose a mixed-methods approach. Lean usability testing was combined with usability inspection by having the participants complete four typical usage scenarios before filling out a questionnaire. The questionnaire was based on the IsoMetrics usability inventory. Direct user interaction with SAM (mouse clicks and pages accessed) was logged. Results The study analyzed the typical usage patterns and habits of students using a semantic network for accessing MLOs. Four scenarios capturing characteristics of typical tasks to be solved by using SAM yielded high ratings of usability items and showed good results concerning the consistency of indexing by different users. Long-tail phenomena emerge as they are typical for a collaborative Web 2.0 platform. Suitable but nonetheless rarely used keywords were assigned to MLOs by some users. Conclusions It is possible to develop a Web-based tool with high usability and acceptance for indexing and retrieval of MLOs. SAM can be applied to indexing multicentered repositories of MLOs collaboratively. PMID:27731860

  15. Predicting Raters’ Transparency Judgments of English and Chinese Morphological Constituents using Latent Semantic Analysis

    PubMed Central

    Wang, Hsueh-Cheng; Hsu, Li-Chuan; Tien, Yi-Min; Pomplun, Marc

    2013-01-01

    The morphological constituents of English compounds (e.g., “butter” and “fly” for “butterfly”) and two-character Chinese compounds may differ in meaning from the whole word. Subjective differences and ambiguity of transparency make the judgments difficult, and a computational alternative based on a general model may be a way to average across subjective differences. The current study proposes two approaches based on Latent Semantic Analysis (Landauer & Dumais, 1997): Model 1 compares the semantic similarity between a compound word and each of its constituents, and Model 2 derives the dominant meaning of a constituent based on a clustering analysis of morphological family members (e.g., “butterfingers” or “buttermilk” for “butter”). The proposed models successfully predicted participants’ transparency ratings, and we recommend that experimenters use Model 1 for English compounds and Model 2 for Chinese compounds, due to raters’ morphological processing in different writing systems. The dominance of lexical meaning, semantic transparency, and the average similarity between all pairs within a morphological family are provided, and practical applications for future studies are discussed. PMID:23784009

  16. Validating Quantitative Measurement Using Qualitative Data: Combining Rasch Scaling and Latent Semantic Analysis in Psychiatry

    NASA Astrophysics Data System (ADS)

    Lange, Rense

    2015-02-01

    An extension of concurrent validity is proposed that uses qualitative data for the purpose of validating quantitative measures. The approach relies on Latent Semantic Analysis (LSA) which places verbal (written) statements in a high dimensional semantic space. Using data from a medical / psychiatric domain as a case study - Near Death Experiences, or NDE - we established concurrent validity by connecting NDErs qualitative (written) experiential accounts with their locations on a Rasch scalable measure of NDE intensity. Concurrent validity received strong empirical support since the variance in the Rasch measures could be predicted reliably from the coordinates of their accounts in the LSA derived semantic space (R2 = 0.33). These coordinates also predicted NDErs age with considerable precision (R2 = 0.25). Both estimates are probably artificially low due to the small available data samples (n = 588). It appears that Rasch scalability of NDE intensity is a prerequisite for these findings, as each intensity level is associated (at least probabilistically) with a well- defined pattern of item endorsements.

  17. Applying latent semantic analysis to large-scale medical image databases.

    PubMed

    Stathopoulos, Spyridon; Kalamboukis, Theodore

    2015-01-01

    Latent Semantic Analysis (LSA) although has been used successfully in text retrieval when applied to CBIR induces scalability issues with large image collections. The method so far has been used with small collections due to the high cost of storage and computational time for solving the SVD problem for a large and dense feature matrix. Here we present an effective and efficient approach of applying LSA skipping the SVD solution of the feature matrix and overcoming in this way the deficiencies of the method with large scale datasets. Early and late fusion techniques are tested and their performance is calculated. The study demonstrates that early fusion of several composite descriptors with visual words increase retrieval effectiveness. It also combines well in a late fusion for mixed (textual and visual) ad hoc and modality classification. The results reported are comparable to state of the art algorithms without including additional knowledge from the medical domain. PMID:24934416

  18. Towards a typology of business process management professionals: identifying patterns of competences through latent semantic analysis

    NASA Astrophysics Data System (ADS)

    Müller, Oliver; Schmiedel, Theresa; Gorbacheva, Elena; vom Brocke, Jan

    2016-01-01

    While researchers have analysed the organisational competences that are required for successful Business Process Management (BPM) initiatives, individual BPM competences have not yet been studied in detail. In this study, latent semantic analysis is used to examine a collection of 1507 BPM-related job advertisements in order to develop a typology of BPM professionals. This empirical analysis reveals distinct ideal types and profiles of BPM professionals on several levels of abstraction. A closer look at these ideal types and profiles confirms that BPM is a boundary-spanning field that requires interdisciplinary sets of competence that range from technical competences to business and systems competences. Based on the study's findings, it is posited that individual and organisational alignment with the identified ideal types and profiles is likely to result in high employability and organisational BPM success.

  19. Latent semantic analysis cosines as a cognitive similarity measure: Evidence from priming studies.

    PubMed

    Günther, Fritz; Dudschig, Carolin; Kaup, Barbara

    2016-01-01

    In distributional semantics models (DSMs) such as latent semantic analysis (LSA), words are represented as vectors in a high-dimensional vector space. This allows for computing word similarities as the cosine of the angle between two such vectors. In two experiments, we investigated whether LSA cosine similarities predict priming effects, in that higher cosine similarities are associated with shorter reaction times (RTs). Critically, we applied a pseudo-random procedure in generating the item material to ensure that we directly manipulated LSA cosines as an independent variable. We employed two lexical priming experiments with lexical decision tasks (LDTs). In Experiment 1 we presented participants with 200 different prime words, each paired with one unique target. We found a significant effect of cosine similarities on RTs. The same was true for Experiment 2, where we reversed the prime-target order (primes of Experiment 1 were targets in Experiment 2, and vice versa). The results of these experiments confirm that LSA cosine similarities can predict priming effects, supporting the view that they are psychologically relevant. The present study thereby provides evidence for qualifying LSA cosine similarities not only as a linguistic measure, but also as a cognitive similarity measure. However, it is also shown that other DSMs can outperform LSA as a predictor of priming effects.

  20. Assessing short summaries with human judgments procedure and latent semantic analysis in narrative and expository texts.

    PubMed

    León, José A; Olmos, Ricardo; Escudero, Inmaculada; Cañas, José J; Salmerón, Lalo

    2006-11-01

    In the present study, we tested a computer-based procedure for assessing very concise summaries (50 words long) of two types of text (narrative and expository) using latent semantic analysis (LSA) in comparison with the judgments of four human experts. LSA was used to estimate semantic similarity using six different methods: four holistic (summary-text, summary-summaries, summary-expert summaries, and pregraded-ungraded summary) and two componential (summary-sentence text and summary-main sentence text). A total of 390 Spanish middle and high school students (14-16 years old) and six experts read a narrative or expository text and later summarized it. The results support the viability of developing a computerized assessment tool using human judgments and LSA, although the correlation between human judgments and LSA was higher in the narrative text than in the expository, and LSA correlated more with human content ratings thanwith hu mancoherence ratings. Finally, theholistic methods were found to be more reliable than the componential methods analyzed in this study.

  1. Transmembrane helix prediction using amino acid property features and latent semantic analysis

    PubMed Central

    Ganapathiraju, Madhavi; Balakrishnan, N; Reddy, Raj; Klein-Seetharaman, Judith

    2008-01-01

    Background Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of free parameters in their models which are tuned to fit the little data available for training. Further, they are often restricted to the generally accepted topology "cytoplasmic-transmembrane-extracellular" and cannot adapt to membrane proteins that do not conform to this topology. Recent crystal structures of channel proteins have revealed novel architectures showing that the above topology may not be as universal as previously believed. Thus, there is a need for methods that can better predict TM helices even in novel topologies and families. Results Here, we describe a new method "TMpro" to predict TM helices with high accuracy. To avoid overfitting to existing topologies, we have collapsed cytoplasmic and extracellular labels to a single state, non-TM. TMpro is a binary classifier which predicts TM or non-TM using multiple amino acid properties (charge, polarity, aromaticity, size and electronic properties) as features. The features are extracted from sequence information by applying the framework used for latent semantic analysis of text documents and are input to neural networks that learn the distinction between TM and non-TM segments. The model uses only 25 free parameters. In benchmark analysis TMpro achieves 95% segment F-score corresponding to 50% reduction in error rate compared to the best methods not requiring an evolutionary profile of a protein to be known. Performance is also improved when applied to more recent and larger high resolution datasets PDBTM and MPtopo. TMpro predictions in membrane proteins with unusual or disputed TM structure (K+ channel, aquaporin and HIV envelope glycoprotein) are discussed. Conclusion TMpro uses very few free parameters in modeling TM segments as opposed to the very large number of free parameters used in state-of-the-art membrane

  2. Exploring dangerous neighborhoods: Latent Semantic Analysis and computing beyond the bounds of the familiar

    PubMed Central

    Cohen, Trevor; Blatter, Brett; Patel, Vimla

    2005-01-01

    Certain applications require computer systems to approximate intended human meaning. This is achievable in constrained domains with a finite number of concepts. Areas such as psychiatry, however, draw on concepts from the world-at-large. A knowledge structure with broad scope is required to comprehend such domains. Latent Semantic Analysis (LSA) is an unsupervised corpus-based statistical method that derives quantitative estimates of the similarity between words and documents from their contextual usage statistics. The aim of this research was to evaluate the ability of LSA to derive meaningful associations between concepts relevant to the assessment of dangerousness in psychiatry. An expert reference model of dangerousness was used to guide the construction of a relevant corpus. Derived associations between words in the corpus were evaluated qualitatively. A similarity-based scoring function was used to assign dangerousness categories to discharge summaries. LSA was shown to derive intuitive relationships between concepts and correlated significantly better than random with human categorization of psychiatric discharge summaries according to dangerousness. The use of LSA to derive a simulated knowledge structure can extend the scope of computer systems beyond the boundaries of constrained conceptual domains. PMID:16779020

  3. Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

    PubMed

    Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

    2014-11-01

    Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management.

  4. A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides.

    PubMed

    Cruz-Roa, Angel; González, Fabio; Galaro, Joseph; Judkins, Alexander R; Ellison, David; Baccon, Jennifer; Madabhushi, Anant; Romero, Eduardo

    2012-01-01

    A method for automatic analysis and interpretation of histopathology images is presented. The method uses a representation of the image data set based on bag of features histograms built from visual dictionary of Haar-based patches and a novel visual latent semantic strategy for characterizing the visual content of a set of images. One important contribution of the method is the provision of an interpretability layer, which is able to explain a particular classification by visually mapping the most important visual patterns associated with such classification. The method was evaluated on a challenging problem involving automated discrimination of medulloblastoma tumors based on image derived attributes from whole slide images as anaplastic or non-anaplastic. The data set comprised 10 labeled histopathological patient studies, 5 for anaplastic and 5 for non-anaplastic, where 750 square images cropped randomly from cancerous region from whole slide per study. The experimental results show that the new method is competitive in terms of classification accuracy achieving 0.87 in average.

  5. Annotations of Mexican bullfighting videos for semantic index

    NASA Astrophysics Data System (ADS)

    Montoya Obeso, Abraham; Oropesa Morales, Lester Arturo; Fernando Vázquez, Luis; Cocolán Almeda, Sara Ivonne; Stoian, Andrei; García Vázquez, Mireya Saraí; Zamudio Fuentes, Luis Miguel; Montiel Perez, Jesús Yalja; de la O Torres, Saul; Ramírez Acosta, Alejandro Alvaro

    2015-09-01

    The video annotation is important for web indexing and browsing systems. Indeed, in order to evaluate the performance of video query and mining techniques, databases with concept annotations are required. Therefore, it is necessary generate a database with a semantic indexing that represents the digital content of the Mexican bullfighting atmosphere. This paper proposes a scheme to make complex annotations in a video in the frame of multimedia search engine project. Each video is partitioned using our segmentation algorithm that creates shots of different length and different number of frames. In order to make complex annotations about the video, we use ELAN software. The annotations are done in two steps: First, we take note about the whole content in each shot. Second, we describe the actions as parameters of the camera like direction, position and deepness. As a consequence, we obtain a more complete descriptor of every action. In both cases we use the concepts of the TRECVid 2014 dataset. We also propose new concepts. This methodology allows to generate a database with the necessary information to create descriptors and algorithms capable to detect actions to automatically index and classify new bullfighting multimedia content.

  6. Concept-Based Retrieval of Hypermedia Information: From Term Indexing to Semantic Hyperindexing.

    ERIC Educational Resources Information Center

    Arents, Hans C.; Bogaerts, Walter F. L.

    1993-01-01

    Discusses and examines two approaches to concept-based retrieval of hypermedia information that improve a user's ability to navigate large systems--term indexing with semantically coupled thesauri and semantic hyperindexing. Visualization of index structures is discussed, and an example, the Cube of Contents retrieval model for the "Active Library…

  7. The semantic pathfinder: using an authoring metaphor for generic multimedia indexing.

    PubMed

    Snoek, Cees G M; Worring, Marcel; Geusebroek, Jan-Mark; Koelma, Dennis C; Seinstra, Frank J; Smeulders, Arnold W M

    2006-10-01

    This paper presents the semantic pathfinder architecture for generic indexing of multimedia archives. The semantic pathfinder extracts semantic concepts from video by exploring different paths through three consecutive analysis steps, which we derive from the observation that produced video is the result of an authoring-driven process. We exploit this authoring metaphor for machine-driven understanding. The pathfinder starts with the content analysis step. In this analysis step, we follow a data-driven approach of indexing semantics. The style analysis step is the second analysis step. Here, we tackle the indexing problem by viewing a video from the perspective of production. Finally, in the context analysis step, we view semantics in context. The virtue of the semantic pathfinder is its ability to learn the best path of analysis steps on a per-concept basis. To show the generality of this novel indexing approach, we develop detectors for a lexicon of 32 concepts and we evaluate the semantic pathfinder against the 2004 NIST TRECVID video retrieval benchmark, using a news archive of 64 hours. Top ranking performance in the semantic concept detection task indicates the merit of the semantic pathfinder for generic indexing of multimedia archives. PMID:16986547

  8. The semantic pathfinder: using an authoring metaphor for generic multimedia indexing.

    PubMed

    Snoek, Cees G M; Worring, Marcel; Geusebroek, Jan-Mark; Koelma, Dennis C; Seinstra, Frank J; Smeulders, Arnold W M

    2006-10-01

    This paper presents the semantic pathfinder architecture for generic indexing of multimedia archives. The semantic pathfinder extracts semantic concepts from video by exploring different paths through three consecutive analysis steps, which we derive from the observation that produced video is the result of an authoring-driven process. We exploit this authoring metaphor for machine-driven understanding. The pathfinder starts with the content analysis step. In this analysis step, we follow a data-driven approach of indexing semantics. The style analysis step is the second analysis step. Here, we tackle the indexing problem by viewing a video from the perspective of production. Finally, in the context analysis step, we view semantics in context. The virtue of the semantic pathfinder is its ability to learn the best path of analysis steps on a per-concept basis. To show the generality of this novel indexing approach, we develop detectors for a lexicon of 32 concepts and we evaluate the semantic pathfinder against the 2004 NIST TRECVID video retrieval benchmark, using a news archive of 64 hours. Top ranking performance in the semantic concept detection task indicates the merit of the semantic pathfinder for generic indexing of multimedia archives.

  9. Discovering discovery patterns with predication-based Semantic Indexing

    PubMed Central

    Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W.; Davies, Peter; Rindflesch, Thomas C.

    2012-01-01

    In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as “discovery patterns”, such as “drug x INHIBITS substance y, substance y CAUSES disease z” that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues. PMID:22841748

  10. Discovering discovery patterns with Predication-based Semantic Indexing.

    PubMed

    Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W; Davies, Peter; Rindflesch, Thomas C

    2012-12-01

    In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as "discovery patterns", such as "drug x INHIBITS substance y, substance y CAUSES disease z" that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues.

  11. Detecting Growth Shape Misspecifications in Latent Growth Models: An Evaluation of Fit Indexes

    ERIC Educational Resources Information Center

    Leite, Walter L.; Stapleton, Laura M.

    2011-01-01

    In this study, the authors compared the likelihood ratio test and fit indexes for detection of misspecifications of growth shape in latent growth models through a simulation study and a graphical analysis. They found that the likelihood ratio test, MFI, and root mean square error of approximation performed best for detecting model misspecification…

  12. N400-like Potentials and Reaction Times Index Semantic Relations between Highly Repeated Individual Words

    ERIC Educational Resources Information Center

    Renoult, Louis; Debruille, J. Bruno

    2011-01-01

    The N400 ERP is an electrophysiological index of semantic processing. Its amplitude varies with the semantic category of words, their concreteness, or whether their meaning matches that of a preceding context. The results of a number of studies suggest that these effects could be markedly reduced or suppressed for stimuli that are repeated.…

  13. 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.

  14. Identification of latent variables in a semantic odor profile database using principal component analysis.

    PubMed

    Zarzo, Manuel; Stanton, David T

    2006-10-01

    Many classifications of odors have been proposed, but none of them have yet gained wide acceptance. Odor sensation is usually described by means of odor character descriptors. If these semantic profiles are obtained for a large diversity of compounds, the resulting database can be considered representative of odor perception space. Few of these comprehensive databases are publicly available, being a valuable source of information for fragrance research. Their statistical analysis has revealed that the underlying structure of odor space is high dimensional and not governed by a few primary odors. In a new effort to study the underlying sensory dimensions of the multivariate olfactory perception space, we have applied principal component analysis to a database of 881 perfume materials with semantic profiles comprising 82 odor descriptors. The relationships identified between the descriptors are consistent with those reported in similar studies and have allowed their classification into 17 odor classes.

  15. DeepMeSH: deep semantic representation for improving large-scale MeSH indexing

    PubMed Central

    Peng, Shengwen; You, Ronghui; Wang, Hongning; Zhai, Chengxiang; Mamitsuka, Hiroshi; Zhu, Shanfeng

    2016-01-01

    Motivation: Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. Methods: We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the ‘learning to rank’ framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. Results: DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. Availability and Implementation: The software is available upon request. Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307646

  16. Semantic extraction and processing of medical records for patient-oriented visual index

    NASA Astrophysics Data System (ADS)

    Zheng, Weilin; Dong, Wenjie; Chen, Xiangjiao; Zhang, Jianguo

    2012-02-01

    To have comprehensive and completed understanding healthcare status of a patient, doctors need to search patient medical records from different healthcare information systems, such as PACS, RIS, HIS, USIS, as a reference of diagnosis and treatment decisions for the patient. However, it is time-consuming and tedious to do these procedures. In order to solve this kind of problems, we developed a patient-oriented visual index system (VIS) to use the visual technology to show health status and to retrieve the patients' examination information stored in each system with a 3D human model. In this presentation, we present a new approach about how to extract the semantic and characteristic information from the medical record systems such as RIS/USIS to create the 3D Visual Index. This approach includes following steps: (1) Building a medical characteristic semantic knowledge base; (2) Developing natural language processing (NLP) engine to perform semantic analysis and logical judgment on text-based medical records; (3) Applying the knowledge base and NLP engine on medical records to extract medical characteristics (e.g., the positive focus information), and then mapping extracted information to related organ/parts of 3D human model to create the visual index. We performed the testing procedures on 559 samples of radiological reports which include 853 focuses, and achieved 828 focuses' information. The successful rate of focus extraction is about 97.1%.

  17. TRANSMISSION AND RISK FACTORS FOR LATENT TUBERCULOSIS INFECTIONS AMONG INDEX CASE-MATCHED HOUSEHOLD CONTACTS.

    PubMed

    Faksri, Kiatichai; Reechaipichitkul, Wipa; Pimrin, Wilailuk; Bourpoern, Janpen; Prompinij, Supapim

    2015-05-01

    An understanding of the risk factors associated with acquiring and transmitting Mycobacterium tuberculosis (MTB) is required for controlling tuberculosis (TB). We aimed to determine the risk factors and transmission factors for latent tuberculosis infection (LTBI) in northeastern Thailand. Household contact persons (n = 70) and matched index patients with pulmonary TB (n = 42) who presented to Srinagarind Hospital, Khon Kaen, Thailand were interviewed from September 1, 2012 to March 31, 2014. LTBI was determined by positive results on both a tuberculin skin test and the QuantiFERON-TB Gold In-Tube test. Multivariate analysis of host and environmental risk factors was performed. Among contact persons, being aged 20 years (adjusted OR=14.0; 95% CI: 1.2-159.5), having a family relationship with a TB subject such as being a spouse or parent (adjusted OR=24.9; 95% CI: 2.4-263.9) and exposure to a TB subject for 5 hours/day (adjusted OR=9.2; 95% CI: 1.4-58.1) were risk factors for LTBI. Having a high bacillary load (adjusted OR=2; 95% CI: 1.26-3.17) or a moderate bacillary load (adjusted OR=1.39; 95% CI: 1.04-1.84) among TB subjects correlated with increased transmissibility compared to having a low bacillary load. The type of dwelling and density of household members were not found to be risk factors for LTBI in our study. We conclude being aged 20 years and having a relationship with a TB patient as a spouse or parent were risk factors for acquiring LTBI, and having a higher bacillary load was a risk factor for transmitting TB. Keywords: latent tuberculosis infection, transmission factor, risk factor, Mycobacterium tuberculosis, interferon-gamma release assay, Thailand PMID:26521523

  18. Concept indexing and expansion for social multimedia websites based on semantic processing and graph analysis

    NASA Astrophysics Data System (ADS)

    Lin, Po-Chuan; Chen, Bo-Wei; Chang, Hangbae

    2016-07-01

    This study presents a human-centric technique for social video expansion based on semantic processing and graph analysis. The objective is to increase metadata of an online video and to explore related information, thereby facilitating user browsing activities. To analyze the semantic meaning of a video, shots and scenes are firstly extracted from the video on the server side. Subsequently, this study uses annotations along with ConceptNet to establish the underlying framework. Detailed metadata, including visual objects and audio events among the predefined categories, are indexed by using the proposed method. Furthermore, relevant online media associated with each category are also analyzed to enrich the existing content. With the above-mentioned information, users can easily browse and search the content according to the link analysis and its complementary knowledge. Experiments on a video dataset are conducted for evaluation. The results show that our system can achieve satisfactory performance, thereby demonstrating the feasibility of the proposed idea.

  19. Inferring the semantic relationships of words within an ontology using random indexing: applications to pharmacogenomics.

    PubMed

    Percha, Bethany; Altman, Russ B

    2013-01-01

    The biomedical literature presents a uniquely challenging text mining problem. Sentences are long and complex, the subject matter is highly specialized with a distinct vocabulary, and producing annotated training data for this domain is time consuming and expensive. In this environment, unsupervised text mining methods that do not rely on annotated training data are valuable. Here we investigate the use of random indexing, an automated method for producing vector-space semantic representations of words from large, unlabeled corpora, to address the problem of term normalization in sentences describing drugs and genes. We show that random indexing produces similarity scores that capture some of the structure of PHARE, a manually curated ontology of pharmacogenomics concepts. We further show that random indexing can be used to identify likely word candidates for inclusion in the ontology, and can help localize these new labels among classes and roles within the ontology.

  20. The Nature of Indexing: How Humans and Machines Analyze Messages and Texts for Retrieval. Part II: Machine Indexing, and the Allocation of Human versus Machine Effort.

    ERIC Educational Resources Information Center

    Anderson, James D.; Perez-Carballo, Jose

    2001-01-01

    Discussion of human intellectual indexing versus automatic indexing focuses on automatic indexing. Topics include keyword indexing; negative vocabulary control; counting words; comparative counting and weighting; stemming; words versus phrases; clustering; latent semantic indexing; citation indexes; bibliographic coupling; co-citation; relevance…

  1. A semantic based video indexing and retrieval system for maritime surveillance

    NASA Astrophysics Data System (ADS)

    Nguyen, Hieu T.; Ramu, Prakash; Liu, Xiaoqing; Wei, Hai; Yadegar, Jacob

    2009-05-01

    Content-based video retrieval from archived image/video is a very attractive capability of modern intelligent video surveillance systems. This paper presents an innovative Semantic-Based Video Indexing and Retrieval (SBVIR) software toolkit to help users of intelligent video surveillance to easily and rapidly search the content of large video archives to conduct video-based forensic and image intelligence. Tailored for maritime environment, SBVIR is suited for surveillance applications in harbor, sea shores, or around ships. The system comprises two major modules: a video analytic module that performs automatic target detection, tracking, classification, activities recognition, and a retrieval module that performs data indexing, and information retrieval. SBVIR is capable of detecting and tracking objects from multiple cameras robustly in condition of dynamic water background and illumination changes. The system provides hierarchical target classification among a large ontology of watercraft classes, and is capable of recognizing a variety of boat activities. Video retrieval is achieved with both query-by-keyword and query-by-example. Users can query video content using semantic concepts selected from a large dictionary of objects and activities, display the history linked to a given target/activity, and search for anomalies. The user can interact with the system and provide feedbacks to tune the system for improved accuracy and relevance of retrieved data. SBVIR has been tested for real maritime surveillance scenarios and shown to be able to generate highly-semantic metadata tags that can be used during the retrieval to provide user with relevant and accurate data in real-time.

  2. BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature

    PubMed Central

    Sen Sarma, Moushumi; Arcoleo, David; Khetani, Radhika S.; Chee, Brant; Ling, Xu; He, Xin; Jiang, Jing; Mei, Qiaozhu; Zhai, ChengXiang; Schatz, Bruce

    2011-01-01

    With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php. PMID:21558175

  3. BeeSpace Navigator: exploratory analysis of gene function using semantic indexing of biological literature.

    PubMed

    Sen Sarma, Moushumi; Arcoleo, David; Khetani, Radhika S; Chee, Brant; Ling, Xu; He, Xin; Jiang, Jing; Mei, Qiaozhu; Zhai, ChengXiang; Schatz, Bruce

    2011-07-01

    With the rapid decrease in cost of genome sequencing, the classification of gene function is becoming a primary problem. Such classification has been performed by human curators who read biological literature to extract evidence. BeeSpace Navigator is a prototype software for exploratory analysis of gene function using biological literature. The software supports an automatic analogue of the curator process to extract functions, with a simple interface intended for all biologists. Since extraction is done on selected collections that are semantically indexed into conceptual spaces, the curation can be task specific. Biological literature containing references to gene lists from expression experiments can be analyzed to extract concepts that are computational equivalents of a classification such as Gene Ontology, yielding discriminating concepts that differentiate gene mentions from other mentions. The functions of individual genes can be summarized from sentences in biological literature, to produce results resembling a model organism database entry that is automatically computed. Statistical frequency analysis based on literature phrase extraction generates offline semantic indexes to support these gene function services. The website with BeeSpace Navigator is free and open to all; there is no login requirement at www.beespace.illinois.edu for version 4. Materials from the 2010 BeeSpace Software Training Workshop are available at www.beespace.illinois.edu/bstwmaterials.php.

  4. Visualizing Semantic Spaces and Author Co-citation Networks in Digital Libraries.

    ERIC Educational Resources Information Center

    Chen, Chaomei

    1999-01-01

    Describes the development and application of visualization techniques for users to access and explore information in digital libraries effectively and intuitively. Salient semantic structures and citation patterns are extracted from several collections of documents using Latent Semantic Indexing and Pathfinder Network Scaling. Author cocitation…

  5. Targeted Echocardiographic Screening for Latent Rheumatic Heart Disease in Northern Uganda: Evaluating Familial Risk Following Identification of an Index Case

    PubMed Central

    Aliku, Twalib; Sable, Craig; Scheel, Amy; Tompsett, Alison; Lwabi, Peter; Okello, Emmy; McCarter, Robert; Summar, Marshall; Beaton, Andrea

    2016-01-01

    Background Echocardiographic screening for detection of latent RHD has shown potential as a strategy to decrease the burden of disease. However, further research is needed to determine optimal implementation strategies. RHD results from a complex interplay between environment and host susceptibility. Family members share both and relatives of children with latent RHD may represent a high-risk group. The objective of this study was to use echocardiographic family screening to determine the relative risk of RHD among first-degree relatives of children with latent RHD compared to the risk in first-degree relatives of healthy peers. Methodology/Principal Findings Previous school-based screening data were used to identify RHD positive children and RHD negative peers. All first-degree relatives ≥ 5 years were invited for echocardiography screening (2012 World Heart Federation Criteria). Sixty RHD positive cases (30 borderline/30 definite RHD) and 67 RHD negative cases were recruited. A total of 455/667 (68%) family members were screened. Definite RHD was more common in childhood siblings of RHD positive compared to RHD negative (p = 0.05). Children with any RHD were 4.5 times as likely to have a sibling with definite RHD, a risk that increased to 5.6 times when considering only cases with definite RHD. Mothers of RHD positive and RHD negative cases had an unexpectedly high rate of latent RHD (9.3%). Conclusions/Significance Siblings of RHD positive cases with RHD are more likely to have definite RHD and the relative risk is highest if the index case has definite RHD. Future screening programs should consider implementation of sibling screening following detection of an RHD positive child. Larger screening studies of adults are needed, as data on prevalence of latent RHD outside of childhood are sparse. Future studies should prioritize implementation research to answer questions of how RHD screening can best be integrated into existing healthcare structures, ensuring

  6. Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study

    NASA Astrophysics Data System (ADS)

    Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

    The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they typically rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this chapter we present a semantically enabled image annotation and retrieval engine that is designed to satisfy the requirements of commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as presenting our initial thoughts on exploiting lexical databases for explicit semantic-based query expansion.

  7. A Semantic Analysis of Abstracts Around an Experiment in Mechanized Indexing.

    ERIC Educational Resources Information Center

    Noel, Jacques

    The first part of this dissertation is a metatheoretical discussion of the needs and means of semantic analysis. This discussion includes sections on metalanguage, deep and surface structure and structural semantics, and procedures for relating the English of abstracts to a classification concordance in the same language. The second part describes…

  8. Word Sense Disambiguation by Selecting the Best Semantic Type Based on Journal Descriptor Indexing: Preliminary Experiment

    PubMed Central

    Humphrey, Susanne M.; Rogers, Willie J.; Kilicoglu, Halil; Demner-Fushman, Dina; Rindflesch, Thomas C.

    2008-01-01

    An experiment was performed at the National Library of Medicine® (NLM®) in word sense disambiguation (WSD) using the Journal Descriptor Indexing (JDI) methodology. The motivation is the need to solve the ambiguity problem confronting NLM’s MetaMap system, which maps free text to terms corresponding to concepts in NLM’s Unified Medical Language System® (UMLS®) Metathesaurus®. If the text maps to more than one Metathesaurus concept at the same high confidence score, MetaMap has no way of knowing which concept is the correct mapping. We describe the JDI methodology, which is ultimately based on statistical associations between words in a training set of MEDLINE® citations and a small set of journal descriptors (assigned by humans to journals per se) assumed to be inherited by the citations. JDI is the basis for selecting the best meaning that is correlated to UMLS semantic types (STs) assigned to ambiguous concepts in the Metathesaurus. For example, the ambiguity transport has two meanings: “Biological Transport” assigned the ST Cell Function and “Patient transport” assigned the ST Health Care Activity. A JDI-based methodology can analyze text containing transport and determine which ST receives a higher score for that text, which then returns the associated meaning, presumed to apply to the ambiguity itself. We then present an experiment in which a baseline disambiguation method was compared to four versions of JDI in disambiguating 45 ambiguous strings from NLM’s WSD Test Collection. Overall average precision for the highest-scoring JDI version was 0.7873 compared to 0.2492 for the baseline method, and average precision for individual ambiguities was greater than 0.90 for 23 of them (51%), greater than 0.85 for 24 (53%), and greater than 0.65 for 35 (79%). On the basis of these results, we hope to improve performance of JDI and test its use in applications. PMID:19890434

  9. Nouns, verbs, objects, actions, and abstractions: Local fMRI activity indexes semantics, not lexical categories

    PubMed Central

    Moseley, Rachel L.; Pulvermüller, Friedemann

    2014-01-01

    Noun/verb dissociations in the literature defy interpretation due to the confound between lexical category and semantic meaning; nouns and verbs typically describe concrete objects and actions. Abstract words, pertaining to neither, are a critical test case: dissociations along lexical-grammatical lines would support models purporting lexical category as the principle governing brain organisation, whilst semantic models predict dissociation between concrete words but not abstract items. During fMRI scanning, participants read orthogonalised word categories of nouns and verbs, with or without concrete, sensorimotor meaning. Analysis of inferior frontal/insula, precentral and central areas revealed an interaction between lexical class and semantic factors with clear category differences between concrete nouns and verbs but not abstract ones. Though the brain stores the combinatorial and lexical-grammatical properties of words, our data show that topographical differences in brain activation, especially in the motor system and inferior frontal cortex, are driven by semantics and not by lexical class. PMID:24727103

  10. Nouns, verbs, objects, actions, and abstractions: local fMRI activity indexes semantics, not lexical categories.

    PubMed

    Moseley, Rachel L; Pulvermüller, Friedemann

    2014-05-01

    Noun/verb dissociations in the literature defy interpretation due to the confound between lexical category and semantic meaning; nouns and verbs typically describe concrete objects and actions. Abstract words, pertaining to neither, are a critical test case: dissociations along lexical-grammatical lines would support models purporting lexical category as the principle governing brain organisation, whilst semantic models predict dissociation between concrete words but not abstract items. During fMRI scanning, participants read orthogonalised word categories of nouns and verbs, with or without concrete, sensorimotor meaning. Analysis of inferior frontal/insula, precentral and central areas revealed an interaction between lexical class and semantic factors with clear category differences between concrete nouns and verbs but not abstract ones. Though the brain stores the combinatorial and lexical-grammatical properties of words, our data show that topographical differences in brain activation, especially in the motor system and inferior frontal cortex, are driven by semantics and not by lexical class.

  11. Model-based assessment of estuary ecosystem health using the latent health factor index, with application to the richibucto estuary.

    PubMed

    Chiu, Grace S; Wu, Margaret A; Lu, Lin

    2013-01-01

    The ability to quantitatively assess ecological health is of great interest to those tasked with monitoring and conserving ecosystems. For decades, biomonitoring research and policies have relied on multimetric health indices of various forms. Although indices are numbers, many are constructed based on qualitative procedures, thus limiting the quantitative rigor of the practical interpretations of such indices. The statistical modeling approach to construct the latent health factor index (LHFI) was recently developed. With ecological data that otherwise are used to construct conventional multimetric indices, the LHFI framework expresses such data in a rigorous quantitative model, integrating qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modeling approach allows unified statistical inference of health for observed sites (along with prediction of health for partially observed sites, if desired) and of the relevance of ecological drivers, all accompanied by formal uncertainty statements from a single, integrated analysis. Thus far, the LHFI approach has been demonstrated and validated in a freshwater context. We adapt this approach to modeling estuarine health, and illustrate it on the previously unassessed system in Richibucto in New Brunswick, Canada, where active oyster farming is a potential stressor through its effects on sediment properties. Field data correspond to health metrics that constitute the popular AZTI marine biotic index and the infaunal trophic index, as well as abiotic predictors preconceived to influence biota. Our paper is the first to construct a scientifically sensible model that rigorously identifies the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content-all regarded a priori as qualitatively important abiotic drivers-towards site health in the Richibucto ecosystem. This suggests the potential effectiveness of the

  12. Model-Based Assessment of Estuary Ecosystem Health Using the Latent Health Factor Index, with Application to the Richibucto Estuary

    PubMed Central

    Chiu, Grace S.; Wu, Margaret A.; Lu, Lin

    2013-01-01

    The ability to quantitatively assess ecological health is of great interest to those tasked with monitoring and conserving ecosystems. For decades, biomonitoring research and policies have relied on multimetric health indices of various forms. Although indices are numbers, many are constructed based on qualitative procedures, thus limiting the quantitative rigor of the practical interpretations of such indices. The statistical modeling approach to construct the latent health factor index (LHFI) was recently developed. With ecological data that otherwise are used to construct conventional multimetric indices, the LHFI framework expresses such data in a rigorous quantitative model, integrating qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modeling approach allows unified statistical inference of health for observed sites (along with prediction of health for partially observed sites, if desired) and of the relevance of ecological drivers, all accompanied by formal uncertainty statements from a single, integrated analysis. Thus far, the LHFI approach has been demonstrated and validated in a freshwater context. We adapt this approach to modeling estuarine health, and illustrate it on the previously unassessed system in Richibucto in New Brunswick, Canada, where active oyster farming is a potential stressor through its effects on sediment properties. Field data correspond to health metrics that constitute the popular AZTI marine biotic index and the infaunal trophic index, as well as abiotic predictors preconceived to influence biota. Our paper is the first to construct a scientifically sensible model that rigorously identifies the collective explanatory capacity of salinity, distance downstream, channel depth, and silt–clay content–all regarded a priori as qualitatively important abiotic drivers–towards site health in the Richibucto ecosystem. This suggests the potential effectiveness of

  13. Model-based assessment of estuary ecosystem health using the latent health factor index, with application to the richibucto estuary.

    PubMed

    Chiu, Grace S; Wu, Margaret A; Lu, Lin

    2013-01-01

    The ability to quantitatively assess ecological health is of great interest to those tasked with monitoring and conserving ecosystems. For decades, biomonitoring research and policies have relied on multimetric health indices of various forms. Although indices are numbers, many are constructed based on qualitative procedures, thus limiting the quantitative rigor of the practical interpretations of such indices. The statistical modeling approach to construct the latent health factor index (LHFI) was recently developed. With ecological data that otherwise are used to construct conventional multimetric indices, the LHFI framework expresses such data in a rigorous quantitative model, integrating qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modeling approach allows unified statistical inference of health for observed sites (along with prediction of health for partially observed sites, if desired) and of the relevance of ecological drivers, all accompanied by formal uncertainty statements from a single, integrated analysis. Thus far, the LHFI approach has been demonstrated and validated in a freshwater context. We adapt this approach to modeling estuarine health, and illustrate it on the previously unassessed system in Richibucto in New Brunswick, Canada, where active oyster farming is a potential stressor through its effects on sediment properties. Field data correspond to health metrics that constitute the popular AZTI marine biotic index and the infaunal trophic index, as well as abiotic predictors preconceived to influence biota. Our paper is the first to construct a scientifically sensible model that rigorously identifies the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content-all regarded a priori as qualitatively important abiotic drivers-towards site health in the Richibucto ecosystem. This suggests the potential effectiveness of the

  14. Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System

    PubMed Central

    Uthayan, K. R.; Anandha Mala, G. S.

    2015-01-01

    Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology. PMID:25922851

  15. Hybrid ontology for semantic information retrieval model using keyword matching indexing system.

    PubMed

    Uthayan, K R; Mala, G S Anandha

    2015-01-01

    Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.

  16. Hybrid ontology for semantic information retrieval model using keyword matching indexing system.

    PubMed

    Uthayan, K R; Mala, G S Anandha

    2015-01-01

    Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology. PMID:25922851

  17. Analysis of semantic search within the domains of uncertainty: using Keyword Effectiveness Indexing as an evaluation tool.

    PubMed

    Lorence, Daniel; Abraham, Joanna

    2006-01-01

    Medical and health-related searches pose a special case of risk when using the web as an information resource. Uninsured consumers, lacking access to a trained provider, will often rely on information from the internet for self-diagnosis and treatment. In areas where treatments are uncertain or controversial, most consumers lack the knowledge to make an informed decision. This exploratory technology assessment examines the use of Keyword Effectiveness Indexing (KEI) analysis as a potential tool for profiling information search and keyword retrieval patterns. Results demonstrate that the KEI methodology can be useful in identifying e-health search patterns, but is limited by semantic or text-based web environments.

  18. Dissociation of Event-Related Potentials Indexing Arousal and Semantic Cohesion During Emotional Word Encoding

    ERIC Educational Resources Information Center

    Dillon, Daniel G.; Cooper, Julie J.; Grent-'t-Jong, Tineke; Woldorff, Marty G.; LaBar, Kevin S.

    2006-01-01

    Event-related potential (ERP) studies have shown that emotional stimuli elicit greater amplitude late positive-polarity potentials (LPPs) than neutral stimuli. This effect has been attributed to arousal, but emotional stimuli are also more semantically coherent than uncategorized neutral stimuli. ERPs were recorded during encoding of positive,…

  19. VastMM-Tag: Semantic Indexing and Browsing of Videos for E-Learning

    ERIC Educational Resources Information Center

    Morris, Mitchell J.

    2012-01-01

    Quickly accessing the contents of a video is challenging for users, particularly for unstructured video, which contains no intentional shot boundaries, no chapters, and no apparent edited format. We approach this problem in the domain of lecture videos though the use of machine learning, to gather semantic information about the videos; and through…

  20. Automated semantic indexing of imaging reports to support retrieval of medical images in the multimedia electronic medical record.

    PubMed

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A; Mailhot, M

    1999-12-01

    This paper describes preliminary work evaluating automated semantic indexing of radiology imaging reports to represent images stored in the Image Engine multimedia medical record system at the University of Pittsburgh Medical Center. The authors used the SAPHIRE indexing system to automatically identify important biomedical concepts within radiology reports and represent these concepts with terms from the 1998 edition of the U.S. National Library of Medicine's Unified Medical Language System (UMLS) Metathesaurus. This automated UMLS indexing was then compared with manual UMLS indexing of the same reports. Human indexing identified appropriate UMLS Metathesaurus descriptors for 81% of the important biomedical concepts contained in the report set. SAPHIRE automatically identified UMLS Metathesaurus descriptors for 64% of the important biomedical concepts contained in the report set. The overall conclusions of this pilot study were that the UMLS metathesaurus provided adequate coverage of the majority of the important concepts contained within the radiology report test set and that SAPHIRE could automatically identify and translate almost two thirds of these concepts into appropriate UMLS descriptors. Further work is required to improve both the recall and precision of this automated concept extraction process. PMID:10805018

  1. Automated semantic indexing of imaging reports to support retrieval of medical images in the multimedia electronic medical record.

    PubMed

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A; Mailhot, M

    1999-12-01

    This paper describes preliminary work evaluating automated semantic indexing of radiology imaging reports to represent images stored in the Image Engine multimedia medical record system at the University of Pittsburgh Medical Center. The authors used the SAPHIRE indexing system to automatically identify important biomedical concepts within radiology reports and represent these concepts with terms from the 1998 edition of the U.S. National Library of Medicine's Unified Medical Language System (UMLS) Metathesaurus. This automated UMLS indexing was then compared with manual UMLS indexing of the same reports. Human indexing identified appropriate UMLS Metathesaurus descriptors for 81% of the important biomedical concepts contained in the report set. SAPHIRE automatically identified UMLS Metathesaurus descriptors for 64% of the important biomedical concepts contained in the report set. The overall conclusions of this pilot study were that the UMLS metathesaurus provided adequate coverage of the majority of the important concepts contained within the radiology report test set and that SAPHIRE could automatically identify and translate almost two thirds of these concepts into appropriate UMLS descriptors. Further work is required to improve both the recall and precision of this automated concept extraction process.

  2. Indexing method of digital audiovisual medical resources with semantic Web integration.

    PubMed

    Cuggia, Marc; Mougin, Fleur; Le Beux, Pierre

    2005-03-01

    Digitalization of audiovisual resources and network capability offer many possibilities which are the subject of intensive work in scientific and industrial sectors. Indexing such resources is a major challenge. Recently, the Motion Pictures Expert Group (MPEG) has developed MPEG-7, a standard for describing multimedia content. The goal of this standard is to develop a rich set of standardized tools to enable efficient retrieval from digital archives or the filtering of audiovisual broadcasts on the Internet. How could this kind of technology be used in the medical context? In this paper, we propose a simpler indexing system, based on the Dublin Core standard and compliant to MPEG-7. We use MeSH and the UMLS to introduce conceptual navigation. We also present a video-platform which enables encoding and gives access to audiovisual resources in streaming mode. PMID:15694622

  3. Indexing method of digital audiovisual medical resources with semantic Web integration.

    PubMed

    Cuggia, Marc; Mougin, Fleur; Le Beux, Pierre

    2003-01-01

    Digitalization of audio-visual resources combined with the performances of the networks offer many possibilities which are the subject of intensive work in the scientific and industrial sectors. Indexing such resources is a major challenge. Recently, the Motion Pictures Expert Group (MPEG) has been developing MPEG-7, a standard for describing multimedia content. The good of this standard is to develop a rich set of standardized tools to enable fast efficient retrieval from digital archives or filtering audiovisual broadcasts on the internet. How this kind of technologies could be used in the medical context? In this paper, we propose a simpler indexing system, based on Dublin Core standard and complaint to MPEG-7. We use MeSH and UMLS to introduce conceptual navigation. We also present a video-platform with enables to encode and give access to audio-visual resources in streaming mode. PMID:14664072

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

    PubMed Central

    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 known and unknown word sentence endings served as primes for semantically related, unrelated, and synonym/identical target words. As expected, N400 amplitudes to target words preceded by known word primes were reduced by prime-target relatedness. Critically, N400 amplitudes to targets preceded by novel primes also varied with prime-target relatedness, but only when they had initially appeared in highly constraining sentences. This demonstrates for the first time that fast-mapped word representations can develop strong associations with semantically related word meanings and reveals a rapid neural process that can integrate information about word meanings into the mental lexicon of young adults. PMID:23125559

  5. 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…

  6. Analysis of leaf area index in the ECMWF land surface model and impact on latent heat and carbon fluxes: Application to West Africa

    NASA Astrophysics Data System (ADS)

    Jarlan, L.; Balsamo, G.; Lafont, S.; Beljaars, A.; Calvet, J. C.; Mougin, E.

    2008-12-01

    A new version of the land surface model of the European Centre for Medium-Range Weather Forecasts (Carbon-TESSEL, or CTESSEL) includes a vegetation growth model. This study describes a leaf area index (LAI) data assimilation system (LDAS) based on CTESSEL and satellite LAI for operational Net Ecosystem Exchange (NEE) predictions. The LDAS is evaluated over West Africa. A preliminary experiment shows a significant impact of the LAI on the CTESSEL NEE. The LAI is compared to two satellite products: the predicted annual cycle is delayed over the Sahel and savannah, and the LAI values differ from the satellite products. Preliminary to their use in the LDAS, the LAI products are rescaled to the CTESSEL predictions. The LDAS simulations are confronted to measurements of biomass and LAI for a site in Mali. The LAI analysis is shown to improve the predicted biomass and the annual cycles of the water (latent heat flux, or LE) and carbon (NEE) fluxes. Afterward, the LDAS is run over West Africa with the Moderate-Resolution Imaging Spectroradiometer products (2001-2005). The analysis of LAI shows a limited impact on LE, but it impacts strongly on NEE. Finally, the CTESSEL NEE are compared to two other models' outputs (simple biosphere (SIB) and Carnegie-Ames-Stanford (CASA)). The order of magnitude of the three data sets agrees well, and the shift in annual cycle of CTESSEL is reduced by the LDAS. It is concluded that a LAI data assimilation system is essential for NEE prediction at seasonal and interannual timescales, while a LAI satellite-based climatology may be sufficient for accurate LE predictions.

  7. Comparing Latent Dirichlet Allocation and Latent Semantic Analysis as Classifiers

    ERIC Educational Resources Information Center

    Anaya, Leticia H.

    2011-01-01

    In the Information Age, a proliferation of unstructured text electronic documents exists. Processing these documents by humans is a daunting task as humans have limited cognitive abilities for processing large volumes of documents that can often be extremely lengthy. To address this problem, text data computer algorithms are being developed.…

  8. 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…

  9. The semantic priming project.

    PubMed

    Hutchison, Keith A; Balota, David A; Neely, James H; Cortese, Michael J; Cohen-Shikora, Emily R; Tse, Chi-Shing; Yap, Melvin J; Bengson, Jesse J; Niemeyer, Dale; Buchanan, Erin

    2013-12-01

    Speeded naming and lexical decision data for 1,661 target words following related and unrelated primes were collected from 768 subjects across four different universities. These behavioral measures have been integrated with demographic information for each subject and descriptive characteristics for every item. Subjects also completed portions of the Woodcock-Johnson reading battery, three attentional control tasks, and a circadian rhythm measure. These data are available at a user-friendly Internet-based repository ( http://spp.montana.edu ). This Web site includes a search engine designed to generate lists of prime-target pairs with specific characteristics (e.g., length, frequency, associative strength, latent semantic similarity, priming effect in standardized and raw reaction times). We illustrate the types of questions that can be addressed via the Semantic Priming Project. These data represent the largest behavioral database on semantic priming and are available to researchers to aid in selecting stimuli, testing theories, and reducing potential confounds in their studies.

  10. Semantic Data Matching: Principles and Performance

    NASA Astrophysics Data System (ADS)

    Deaton, Russell; Doan, Thao; Schweiger, Tom

    Automated and real-time management of customer relationships requires robust and intelligent data matching across widespread and diverse data sources. Simple string matching algorithms, such as dynamic programming, can handle typographical errors in the data, but are less able to match records that require contextual and experiential knowledge. Latent Semantic Indexing (LSI) (Berry et al. ; Deerwester et al. is a machine intelligence technique that can match data based upon higher order structure, and is able to handle difficult problems, such as words that have different meanings but the same spelling, are synonymous, or have multiple meanings. Essentially, the technique matches records based upon context, or mathematically quantifying when terms occur in the same record.

  11. Towards knowledge-based retrieval of medical images. The role of semantic indexing, image content representation and knowledge-based retrieval.

    PubMed

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A

    1998-01-01

    Medicine is increasingly image-intensive. The central importance of imaging technologies such as computerized tomography and magnetic resonance imaging in clinical decision making, combined with the trend to store many "traditional" clinical images such as conventional radiographs, microscopic pathology and dermatology images in digital format present both challenges and an opportunities for the designers of clinical information systems. The emergence of Multimedia Electronic Medical Record Systems (MEMRS), architectures that integrate medical images with text-based clinical data, will further hasten this trend. The development of these systems, storing a large and diverse set of medical images, suggests that in the future MEMRS will become important digital libraries supporting patient care, research and education. The representation and retrieval of clinical images within these systems is problematic as conventional database architectures and information retrieval models have, until recently, focused largely on text-based data. Medical imaging data differs in many ways from text-based medical data but perhaps the most important difference is that the information contained within imaging data is fundamentally knowledge-based. New representational and retrieval models for clinical images will be required to address this issue. Within the Image Engine multimedia medical record system project at the University of Pittsburgh we are evolving an approach to representation and retrieval of medical images which combines semantic indexing using the UMLS Metathesuarus, image content-based representation and knowledge-based image analysis. PMID:9929345

  12. Towards knowledge-based retrieval of medical images. The role of semantic indexing, image content representation and knowledge-based retrieval.

    PubMed

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A

    1998-01-01

    Medicine is increasingly image-intensive. The central importance of imaging technologies such as computerized tomography and magnetic resonance imaging in clinical decision making, combined with the trend to store many "traditional" clinical images such as conventional radiographs, microscopic pathology and dermatology images in digital format present both challenges and an opportunities for the designers of clinical information systems. The emergence of Multimedia Electronic Medical Record Systems (MEMRS), architectures that integrate medical images with text-based clinical data, will further hasten this trend. The development of these systems, storing a large and diverse set of medical images, suggests that in the future MEMRS will become important digital libraries supporting patient care, research and education. The representation and retrieval of clinical images within these systems is problematic as conventional database architectures and information retrieval models have, until recently, focused largely on text-based data. Medical imaging data differs in many ways from text-based medical data but perhaps the most important difference is that the information contained within imaging data is fundamentally knowledge-based. New representational and retrieval models for clinical images will be required to address this issue. Within the Image Engine multimedia medical record system project at the University of Pittsburgh we are evolving an approach to representation and retrieval of medical images which combines semantic indexing using the UMLS Metathesuarus, image content-based representation and knowledge-based image analysis.

  13. 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…

  14. Generative Semantics.

    ERIC Educational Resources Information Center

    King, Margaret

    The first section of this paper deals with the attempts within the framework of transformational grammar to make semantics a systematic part of linguistic description, and outlines the characteristics of the generative semantics position. The second section takes a critical look at generative semantics in its later manifestations, and makes a case…

  15. Graph-Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory

    ERIC Educational Resources Information Center

    Gruenenfelder, Thomas M.; Recchia, Gabriel; Rubin, Tim; Jones, Michael N.

    2016-01-01

    We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…

  16. Automatic Indexing of Full Texts.

    ERIC Educational Resources Information Center

    Jonak, Zdenek

    1984-01-01

    Demonstrates efficiency of preparation of query description using semantic analyser method based on analysis of semantic structure of documents in field of automatic indexing. Results obtained are compared with automatic indexing results performed by traditional methods and results of indexing done by human indexers. Sample terms and codes are…

  17. Semantic Desktop

    NASA Astrophysics Data System (ADS)

    Sauermann, Leo; Kiesel, Malte; Schumacher, Kinga; Bernardi, Ansgar

    In diesem Beitrag wird gezeigt, wie der Arbeitsplatz der Zukunft aussehen könnte und wo das Semantic Web neue Möglichkeiten eröffnet. Dazu werden Ansätze aus dem Bereich Semantic Web, Knowledge Representation, Desktop-Anwendungen und Visualisierung vorgestellt, die es uns ermöglichen, die bestehenden Daten eines Benutzers neu zu interpretieren und zu verwenden. Dabei bringt die Kombination von Semantic Web und Desktop Computern besondere Vorteile - ein Paradigma, das unter dem Titel Semantic Desktop bekannt ist. Die beschriebenen Möglichkeiten der Applikationsintegration sind aber nicht auf den Desktop beschränkt, sondern können genauso in Web-Anwendungen Verwendung finden.

  18. Generalized Latent Trait Models.

    ERIC Educational Resources Information Center

    Moustaki, Irini; Knott, Martin

    2000-01-01

    Discusses a general model framework within which manifest variables with different distributions in the exponential family can be analyzed with a latent trait model. Presents a unified maximum likelihood method for estimating the parameters of the generalized latent trait model and discusses the scoring of individuals on the latent dimensions.…

  19. Latent Regression Analysis.

    PubMed

    Tarpey, Thaddeus; Petkova, Eva

    2010-07-01

    Finite mixture models have come to play a very prominent role in modelling data. The finite mixture model is predicated on the assumption that distinct latent groups exist in the population. The finite mixture model therefore is based on a categorical latent variable that distinguishes the different groups. Often in practice distinct sub-populations do not actually exist. For example, disease severity (e.g. depression) may vary continuously and therefore, a distinction of diseased and not-diseased may not be based on the existence of distinct sub-populations. Thus, what is needed is a generalization of the finite mixture's discrete latent predictor to a continuous latent predictor. We cast the finite mixture model as a regression model with a latent Bernoulli predictor. A latent regression model is proposed by replacing the discrete Bernoulli predictor by a continuous latent predictor with a beta distribution. Motivation for the latent regression model arises from applications where distinct latent classes do not exist, but instead individuals vary according to a continuous latent variable. The shapes of the beta density are very flexible and can approximate the discrete Bernoulli distribution. Examples and a simulation are provided to illustrate the latent regression model. In particular, the latent regression model is used to model placebo effect among drug treated subjects in a depression study. PMID:20625443

  20. Capturing the Semantics of User Interaction: A Review and Case Study

    NASA Astrophysics Data System (ADS)

    Morrison, Donn; Marchand-Maillet, Stéphane; Bruno, Eric

    In many retrieval domains there exists a problematic gap between what computers can describe and what humans are capable of perceiving. This gap is most evident in the indexing of multimedia data such as images, video and sound where the low-level features are too semantically deficient to be of use from a typical users' perspective. On the other hand, users possess the ability to quickly examine and summarise these documents, even subconsciously. Examples include specifying relevance between a query and results, rating preferences in film databases, purchasing items from online retailers, and even browsing web sites. Data from these interactions, captured and stored in log files, can be interpreted to have semantic meaning, which proves indispensable when used in a collaborative setting where users share similar preferences or goals. In this chapter we summarise techniques for efficiently exploiting user interaction in its many forms for the generation and augmentation of semantic data in large databases. This user interaction can be applied to improve performance in recommender and information retrieval systems. A case study is presented which applies a popular technique, latent semantic analysis, to improve retrieval on an image database.

  1. Principal semantic components of language and the measurement of meaning.

    PubMed

    Samsonovich, Alexei V; Samsonovic, Alexei V; Ascoli, Giorgio A

    2010-01-01

    Metric systems for semantics, or semantic cognitive maps, are allocations of words or other representations in a metric space based on their meaning. Existing methods for semantic mapping, such as Latent Semantic Analysis and Latent Dirichlet Allocation, are based on paradigms involving dissimilarity metrics. They typically do not take into account relations of antonymy and yield a large number of domain-specific semantic dimensions. Here, using a novel self-organization approach, we construct a low-dimensional, context-independent semantic map of natural language that represents simultaneously synonymy and antonymy. Emergent semantics of the map principal components are clearly identifiable: the first three correspond to the meanings of "good/bad" (valence), "calm/excited" (arousal), and "open/closed" (freedom), respectively. The semantic map is sufficiently robust to allow the automated extraction of synonyms and antonyms not originally in the dictionaries used to construct the map and to predict connotation from their coordinates. The map geometric characteristics include a limited number ( approximately 4) of statistically significant dimensions, a bimodal distribution of the first component, increasing kurtosis of subsequent (unimodal) components, and a U-shaped maximum-spread planar projection. Both the semantic content and the main geometric features of the map are consistent between dictionaries (Microsoft Word and Princeton's WordNet), among Western languages (English, French, German, and Spanish), and with previously established psychometric measures. By defining the semantics of its dimensions, the constructed map provides a foundational metric system for the quantitative analysis of word meaning. Language can be viewed as a cumulative product of human experiences. Therefore, the extracted principal semantic dimensions may be useful to characterize the general semantic dimensions of the content of mental states. This is a fundamental step toward a

  2. Principal Semantic Components of Language and the Measurement of Meaning

    PubMed Central

    Samsonovic, Alexei V.; Ascoli, Giorgio A.

    2010-01-01

    Metric systems for semantics, or semantic cognitive maps, are allocations of words or other representations in a metric space based on their meaning. Existing methods for semantic mapping, such as Latent Semantic Analysis and Latent Dirichlet Allocation, are based on paradigms involving dissimilarity metrics. They typically do not take into account relations of antonymy and yield a large number of domain-specific semantic dimensions. Here, using a novel self-organization approach, we construct a low-dimensional, context-independent semantic map of natural language that represents simultaneously synonymy and antonymy. Emergent semantics of the map principal components are clearly identifiable: the first three correspond to the meanings of “good/bad” (valence), “calm/excited” (arousal), and “open/closed” (freedom), respectively. The semantic map is sufficiently robust to allow the automated extraction of synonyms and antonyms not originally in the dictionaries used to construct the map and to predict connotation from their coordinates. The map geometric characteristics include a limited number (∼4) of statistically significant dimensions, a bimodal distribution of the first component, increasing kurtosis of subsequent (unimodal) components, and a U-shaped maximum-spread planar projection. Both the semantic content and the main geometric features of the map are consistent between dictionaries (Microsoft Word and Princeton's WordNet), among Western languages (English, French, German, and Spanish), and with previously established psychometric measures. By defining the semantics of its dimensions, the constructed map provides a foundational metric system for the quantitative analysis of word meaning. Language can be viewed as a cumulative product of human experiences. Therefore, the extracted principal semantic dimensions may be useful to characterize the general semantic dimensions of the content of mental states. This is a fundamental step toward a

  3. The Use of Semantic Links in Hypertext Information Retrieval.

    ERIC Educational Resources Information Center

    Frei, H. P.; Stieger, D.

    1995-01-01

    Highlights semantic links and shows how the semantic content of hypertext links can be used for information retrieval. Discussion includes indexing and retrieval algorithms that exploit link content and node content; retrieval strategies exploiting semantic links, including conventional retrieval and constrained spreading activation techniques;…

  4. 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…

  5. Latent Variable Theory

    ERIC Educational Resources Information Center

    Borsboom, Denny

    2008-01-01

    This paper formulates a metatheoretical framework for latent variable modeling. It does so by spelling out the difference between observed and latent variables. This difference is argued to be purely epistemic in nature: We treat a variable as "observed" when the inference from data structure to variable structure can be made with certainty and as…

  6. Latent myofascial trigger points.

    PubMed

    Ge, Hong-You; Arendt-Nielsen, Lars

    2011-10-01

    A latent myofascial trigger point (MTP) is defined as a focus of hyperirritability in a muscle taut band that is clinically associated with local twitch response and tenderness and/or referred pain upon manual examination. Current evidence suggests that the temporal profile of the spontaneous electrical activity at an MTP is similar to focal muscle fiber contraction and/or muscle cramp potentials, which contribute significantly to the induction of local tenderness and pain and motor dysfunctions. This review highlights the potential mechanisms underlying the sensory-motor dysfunctions associated with latent MTPs and discusses the contribution of central sensitization associated with latent MTPs and the MTP network to the spatial propagation of pain and motor dysfunctions. Treating latent MTPs in patients with musculoskeletal pain may not only decrease pain sensitivity and improve motor functions, but also prevent latent MTPs from transforming into active MTPs, and hence, prevent the development of myofascial pain syndrome.

  7. 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.

  8. Textrous!: extracting semantic textual meaning from gene sets.

    PubMed

    Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M; Siddiqui, Sana; Luttrell, Louis M; Maudsley, Stuart

    2013-01-01

    The un-biased and reproducible interpretation of high-content gene sets from large-scale genomic experiments is crucial to the understanding of biological themes, validation of experimental data, and the eventual development of plans for future experimentation. To derive biomedically-relevant information from simple gene lists, a mathematical association to scientific language and meaningful words or sentences is crucial. Unfortunately, existing software for deriving meaningful and easily-appreciable scientific textual 'tokens' from large gene sets either rely on controlled vocabularies (Medical Subject Headings, Gene Ontology, BioCarta) or employ Boolean text searching and co-occurrence models that are incapable of detecting indirect links in the literature. As an improvement to existing web-based informatic tools, we have developed Textrous!, a web-based framework for the extraction of biomedical semantic meaning from a given input gene set of arbitrary length. Textrous! employs natural language processing techniques, including latent semantic indexing (LSI), sentence splitting, word tokenization, parts-of-speech tagging, and noun-phrase chunking, to mine MEDLINE abstracts, PubMed Central articles, articles from the Online Mendelian Inheritance in Man (OMIM), and Mammalian Phenotype annotation obtained from Jackson Laboratories. Textrous! has the ability to generate meaningful output data with even very small input datasets, using two different text extraction methodologies (collective and individual) for the selecting, ranking, clustering, and visualization of English words obtained from the user data. Textrous!, therefore, is able to facilitate the output of quantitatively significant and easily appreciable semantic words and phrases linked to both individual gene and batch genomic data.

  9. A Programme for Semantics; Semantics and Its Critics; Semantics Shamantics.

    ERIC Educational Resources Information Center

    Goldstein, Laurence; Harris, Roy

    1990-01-01

    In a statement-response-reply format, a proposition concerning the study of semantics is made and debated in three papers by two authors. In the first paper, it is proposed that semantics is not the study of the concept of meaning, but rather a neurolinguistic issue, despite the fact that semantics is linked to context. It is argued that semantic…

  10. Multimethod latent class analysis

    PubMed Central

    Nussbeck, Fridtjof W.; Eid, Michael

    2015-01-01

    Correct and, hence, valid classifications of individuals are of high importance in the social sciences as these classifications are the basis for diagnoses and/or the assignment to a treatment. The via regia to inspect the validity of psychological ratings is the multitrait-multimethod (MTMM) approach. First, a latent variable model for the analysis of rater agreement (latent rater agreement model) will be presented that allows for the analysis of convergent validity between different measurement approaches (e.g., raters). Models of rater agreement are transferred to the level of latent variables. Second, the latent rater agreement model will be extended to a more informative MTMM latent class model. This model allows for estimating (i) the convergence of ratings, (ii) method biases in terms of differential latent distributions of raters and differential associations of categorizations within raters (specific rater bias), and (iii) the distinguishability of categories indicating if categories are satisfyingly distinct from each other. Finally, an empirical application is presented to exemplify the interpretation of the MTMM latent class model. PMID:26441714

  11. Latent fingerprint matching.

    PubMed

    Jain, Anil K; Feng, Jianjiang

    2011-01-01

    Latent fingerprint identification is of critical importance to law enforcement agencies in identifying suspects: Latent fingerprints are inadvertent impressions left by fingers on surfaces of objects. While tremendous progress has been made in plain and rolled fingerprint matching, latent fingerprint matching continues to be a difficult problem. Poor quality of ridge impressions, small finger area, and large nonlinear distortion are the main difficulties in latent fingerprint matching compared to plain or rolled fingerprint matching. We propose a system for matching latent fingerprints found at crime scenes to rolled fingerprints enrolled in law enforcement databases. In addition to minutiae, we also use extended features, including singularity, ridge quality map, ridge flow map, ridge wavelength map, and skeleton. We tested our system by matching 258 latents in the NIST SD27 database against a background database of 29,257 rolled fingerprints obtained by combining the NIST SD4, SD14, and SD27 databases. The minutiae-based baseline rank-1 identification rate of 34.9 percent was improved to 74 percent when extended features were used. In order to evaluate the relative importance of each extended feature, these features were incrementally used in the order of their cost in marking by latent experts. The experimental results indicate that singularity, ridge quality map, and ridge flow map are the most effective features in improving the matching accuracy.

  12. Latent palmprint matching.

    PubMed

    Jain, Anil K; Feng, Jianjiang

    2009-06-01

    The evidential value of palmprints in forensic applications is clear as about 30 percent of the latents recovered from crime scenes are from palms. While biometric systems for palmprint-based personal authentication in access control type of applications have been developed, they mostly deal with low-resolution (about 100 ppi) palmprints and only perform full-to-full palmprint matching. We propose a latent-to-full palmprint matching system that is needed in forensic applications. Our system deals with palmprints captured at 500 ppi (the current standard in forensic applications) or higher resolution and uses minutiae as features to be compatible with the methodology used by latent experts. Latent palmprint matching is a challenging problem because latent prints lifted at crime scenes are of poor image quality, cover only a small area of the palm, and have a complex background. Other difficulties include a large number of minutiae in full prints (about 10 times as many as fingerprints), and the presence of many creases in latents and full prints. A robust algorithm to reliably estimate the local ridge direction and frequency in palmprints is developed. This facilitates the extraction of ridge and minutiae features even in poor quality palmprints. A fixed-length minutia descriptor, MinutiaCode, is utilized to capture distinctive information around each minutia and an alignment-based minutiae matching algorithm is used to match two palmprints. Two sets of partial palmprints (150 live-scan partial palmprints and 100 latent palmprints) are matched to a background database of 10,200 full palmprints to test the proposed system. Despite the inherent difficulty of latent-to-full palmprint matching, rank-1 recognition rates of 78.7 and 69 percent, respectively, were achieved in searching live-scan partial palmprints and latent palmprints against the background database.

  13. Formal semantic and computer text processing, 1982

    SciTech Connect

    Meunier, J.G.; Lepage, F.

    1983-01-01

    Computer processing of large nonpreedited natural language texts has often been limited either to managing and editing or to analysing basic levels of content (indexes, concordances, clusters, etc.). Few systems approach syntactic information, even less semantic information. Because of the complexity and the originality of the underlying semantic information of any text it is not possible to import directly the AI and computational semantic concepts. It is necessary to explore news paths. The research presented here is oriented toward the understanding of certain semantic aspects in computer text processing (words and meaning representation and inference patterns). This is done through a model theoretic approach embedded in an algebraic language. The hypothesis which governs the concepts and the distinctions is the following: discourse in a text constitutes a semantic space built of an ordered set of sentences which are of different logical types and which present a specific pattern of coherence expressible in a syntactic manner. 47 references.

  14. Semantic guidance of eye movements in real-world scenes

    PubMed Central

    Hwang, Alex D.; Wang, Hsueh-Cheng; Pomplun, Marc

    2011-01-01

    The perception of objects in our visual world is influenced by not only their low-level visual features such as shape and color, but also their high-level features such as meaning and semantic relations among them. While it has been shown that low-level features in real-world scenes guide eye movements during scene inspection and search, the influence of semantic similarity among scene objects on eye movements in such situations has not been investigated. Here we study guidance of eye movements by semantic similarity among objects during real-world scene inspection and search. By selecting scenes from the LabelMe object-annotated image database and applying Latent Semantic Analysis (LSA) to the object labels, we generated semantic saliency maps of real-world scenes based on the semantic similarity of scene objects to the currently fixated object or the search target. An ROC analysis of these maps as predictors of subjects’ gaze transitions between objects during scene inspection revealed a preference for transitions to objects that were semantically similar to the currently inspected one. Furthermore, during the course of a scene search, subjects’ eye movements were progressively guided toward objects that were semantically similar to the search target. These findings demonstrate substantial semantic guidance of eye movements in real-world scenes and show its importance for understanding real-world attentional control. PMID:21426914

  15. Latent Toxoplasmosis and Human

    PubMed Central

    Dalimi, A; Abdoli, A

    2012-01-01

    Toxoplasmosis is one of the most common parasitic diseases worldwide. Although estimated that one third of the world's population are infected with Toxoplasma gondii, but the most common form of the disease is latent (asymptomatic). On the other hand, recent findings indicated that latent toxoplasmosis is not only unsafe for human, but also may play various roles in the etiology of different mental disorders. This paper reviews new findings about importance of latent toxoplasmosis (except in immunocompromised patients) in alterations of behavioral parameters and also its role in the etiology of schizophrenia and depressive disorders, obsessive–compulsive disorder, Alzheimer's diseases and Parkinson's disease, epilepsy, headache and or migraine, mental retardation and intelligence quotients, suicide attempt, risk of traffic accidents, sex ratio and some possible mechanisms of T. gondii that could contribute in the etiology of these alterations. PMID:23133466

  16. Latent toxoplasmosis and human.

    PubMed

    Dalimi, A; Abdoli, A

    2012-01-01

    Toxoplasmosis is one of the most common parasitic diseases worldwide. Although estimated that one third of the world's population are infected with Toxoplasma gondii, but the most common form of the disease is latent (asymptomatic). On the other hand, recent findings indicated that latent toxoplasmosis is not only unsafe for human, but also may play various roles in the etiology of different mental disorders. This paper reviews new findings about importance of latent toxoplasmosis (except in immunocompromised patients) in alterations of behavioral parameters and also its role in the etiology of schizophrenia and depressive disorders, obsessive-compulsive disorder, Alzheimer's diseases and Parkinson's disease, epilepsy, headache and or migraine, mental retardation and intelligence quotients, suicide attempt, risk of traffic accidents, sex ratio and some possible mechanisms of T. gondii that could contribute in the etiology of these alterations.

  17. Impact of latent infection treatment in indigenous populations.

    PubMed

    Yuhara, Lucia Suemi; Sacchi, Flávia Patussi Correia; Croda, Julio

    2013-01-01

    The aims of the present study were to identify risk factors associated with latent tuberculosis (TB), examine the development of active disease among contacts, and assess the effectiveness of treating latent infection in indigenous Brazilians from January 2006 to December 2011. This was a retrospective study consisting of 1,371 tuberculosis contacts, 392 of whom underwent treatment for latent infection. Morbidity-from-TB data were obtained from the Information System for Disease Notification (SINAN) database, and the contacts' data were collected from the clinical records using forms employed by Special Department of Indigenous Health (SESAI) multidisciplinary teams, according to SESAI's instructions. The variables that were associated with latent infection among the contacts were age (odds ratio [OR]: 1.03; 95% confidence interval [CI]: 1.02-1.04) and close contact with a smear-positive index case (OR: 2.26, 95% CI: 1.59-3.22). The variables associated with the development of active TB among the contacts were a tuberculin skin test (TST) ≥10 mm (relative risk [RR]: 1.12, 95% CI: 1.07-1.17), age (RR: 1.01, 95% CI: 1.00-1.03), and treatment of latent infection (RR: 0.03, 95% CI: 0.01-0.27). The estimated number of latent infection treatments needed to prevent one case of active TB among the contacts was 51 treatments (95% CI: 33-182). In contacts with TST ≥10 mm, 10 (95% CI: 6-19) latent infection treatments were necessary to prevent one case of active TB. Age and close contact with a smear-positive index case were associated with latent TB. Screening with TST is a high priority among individuals contacting smear-positive index cases. Age and TST are associated with the development of active TB among contacts, and treatment of latent infection is an effective measure to control TB in indigenous communities. PMID:23936264

  18. Latent Variable Interaction Modeling.

    ERIC Educational Resources Information Center

    Schumacker, Randall E.

    2002-01-01

    Used simulation to study two different approaches to latent variable interaction modeling with continuous observed variables: (1) a LISREL 8.30 program and (2) data analysis through PRELIS2 and SIMPLIS programs. Results show that parameter estimation was similar but standard errors were different. Discusses differences in ease of implementation.…

  19. Measuring Latent Quantities

    ERIC Educational Resources Information Center

    McDonald, Roderick P.

    2011-01-01

    A distinction is proposed between measures and predictors of latent variables. The discussion addresses the consequences of the distinction for the true-score model, the linear factor model, Structural Equation Models, longitudinal and multilevel models, and item-response models. A distribution-free treatment of calibration and…

  20. Facilitating Image Search With a Scalable and Compact Semantic Mapping.

    PubMed

    Wang, Meng; Li, Weisheng; Liu, Dong; Ni, Bingbing; Shen, Jialie; Yan, Shuicheng

    2015-08-01

    This paper introduces a novel approach to facilitating image search based on a compact semantic embedding. A novel method is developed to explicitly map concepts and image contents into a unified latent semantic space for the representation of semantic concept prototypes. Then, a linear embedding matrix is learned that maps images into the semantic space, such that each image is closer to its relevant concept prototype than other prototypes. In our approach, the semantic concepts equated with query keywords and the images mapped into the vicinity of the prototype are retrieved by our scheme. In addition, a computationally efficient method is introduced to incorporate new semantic concept prototypes into the semantic space by updating the embedding matrix. This novelty improves the scalability of the method and allows it to be applied to dynamic image repositories. Therefore, the proposed approach not only narrows semantic gap but also supports an efficient image search process. We have carried out extensive experiments on various cross-modality image search tasks over three widely-used benchmark image datasets. Results demonstrate the superior effectiveness, efficiency, and scalability of our proposed approach.

  1. Indexing and Automatic Significance Analysis

    ERIC Educational Resources Information Center

    Steinacker, Ivo

    1974-01-01

    An algorithm is proposed to solve the problem of sequential indexing which does not use any grammatical or semantic analysis, but follows the principle of emulating human judgement by evaluation of machine-recognizable attributes of structured word assemblies. (Author)

  2. Semantic-based surveillance video retrieval.

    PubMed

    Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

    2007-04-01

    Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene. PMID:17405446

  3. Exploring MEDLINE Space with Random Indexing and Pathfinder Networks

    PubMed Central

    Cohen, Trevor

    2008-01-01

    The integration of disparate research domains is a prerequisite for the success of the translational science initiative. MEDLINE abstracts contain content from a broad range of disciplines, presenting an opportunity for the development of methods able to integrate the knowledge they contain. Latent Semantic Analysis (LSA) and related methods learn human-like associations between terms from unannotated text. However, their computational and memory demands limits their ability to address a corpus of this size. Furthermore, visualization methods previously used in conjunction with LSA have limited ability to define the local structure of the associative networks LSA learns. This paper explores these issues by (1) processing the entire MEDLINE corpus using Random Indexing, a variant of LSA, and (2) exploring learned associations using Pathfinder Networks. Meaningful associations are inferred from MEDLINE, including a drug-disease association undetected by PUBMED search. PMID:18999236

  4. 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)

  5. 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…

  6. Latent effects decision analysis

    DOEpatents

    Cooper, J. Arlin; Werner, Paul W.

    2004-08-24

    Latent effects on a system are broken down into components ranging from those far removed in time from the system under study (latent) to those which closely effect changes in the system. Each component is provided with weighted inputs either by a user or from outputs of other components. A non-linear mathematical process known as `soft aggregation` is performed on the inputs to each component to provide information relating to the component. This information is combined in decreasing order of latency to the system to provide a quantifiable measure of an attribute of a system (e.g., safety) or to test hypotheses (e.g., for forensic deduction or decisions about various system design options).

  7. Reactivation of latent melioidosis.

    PubMed

    Johnson, A B; Ali, N

    1990-09-01

    Reports of melioidosis in residents of European countries are rare. We describe a case of reactivation of latent melioidosis in a United Kingdom resident. The case demonstrates the lack of clinical response to chemotherapy despite proven in vitro sensitivity of the organism to the drugs used. It is important to consider melioidosis as a cause of septicaemic illness in patients who have travelled to, or been resident in South-East Asia.

  8. Reactivation of latent melioidosis.

    PubMed Central

    Johnson, A. B.; Ali, N.

    1990-01-01

    Reports of melioidosis in residents of European countries are rare. We describe a case of reactivation of latent melioidosis in a United Kingdom resident. The case demonstrates the lack of clinical response to chemotherapy despite proven in vitro sensitivity of the organism to the drugs used. It is important to consider melioidosis as a cause of septicaemic illness in patients who have travelled to, or been resident in South-East Asia. PMID:2235805

  9. Semantic networks of English.

    PubMed

    Miller, G A; Fellbaum, C

    1991-12-01

    Principles of lexical semantics developed in the course of building an on-line lexical database are discussed. The approach is relational rather than componential. The fundamental semantic relation is synonymy, which is required in order to define the lexicalized concepts that words can be used to express. Other semantic relations between these concepts are then described. No single set of semantic relations or organizational structure is adequate for the entire lexicon: nouns, adjectives, and verbs each have their own semantic relations and their own organization determined by the role they must play in the construction of linguistic messages.

  10. Biomedical semantics in the Semantic Web

    PubMed Central

    2011-01-01

    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. PMID:21388570

  11. 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.

  12. Peach latent mosaic viroid: not so latent.

    PubMed

    Flores, Ricardo; Delgado, Sonia; Rodio, María-Elena; Ambrós, Silvia; Hernández, Carmen; Serio, Francesco D I

    2006-07-01

    SUMMARY Taxonomy: Peach latent mosaic viroid (PLMVd) is the type species of the genus Pelamoviroid within the family Avsunviroidae of chloroplastic viroids with hammerhead ribozymes. Physical properties: A small circular RNA of 336-351 nt (differences in size result from the absence or presence of certain insertions) adopting a branched conformation stabilized by a pseudoknot between two kissing loops. This particular conformation is most likely responsible for the insolubility of PLMVd in highly saline conditions (in which other viroids adopting a rod-like conformation are soluble). Both polarity strands are able to form hammerhead structures and to self-cleave during replication as predicted by these ribozymes. Biological properties: Although most infections occur without conspicuous symptoms, certain PLMVd isolates induce leaf mosaics, blotches and in the most extreme cases albinism (peach calico, PC), flower streaking, delays in foliation, flowering and ripening, deformations and decolorations of fruits, which usually present cracked sutures and enlarged roundish stones, bud necrosis, stem pitting and premature ageing of the trees, which also adopt a characteristic growing pattern (open habit). The molecular determinant for PC has been mapped at a 12-14-nt insertion that folds into a hairpin capped by a U-rich loop present only in certain variants. PLMVd is horizontally transmitted by the propagation of infected buds and to a lesser extent by pruning tools and aphids, but not by pollen; the viroid is not vertically transmitted through seed. Interesting features: This provides a suitable system for studying how a minimal non-protein-coding catalytic RNA replicates (subverting a DNA-dependent RNA polymerase to transcribe an RNA template), moves, interferes with the metabolism of its host (inciting specific symptoms and a defensive RNA silencing response) and evolves following a quasi-species model characterized by a complex spectrum of variants.

  13. Somatotopic Semantic Priming and Prediction in the Motor System

    PubMed Central

    Grisoni, Luigi; Dreyer, Felix R.; Pulvermüller, Friedemann

    2016-01-01

    The recognition of action-related sounds and words activates motor regions, reflecting the semantic grounding of these symbols in action information; in addition, motor cortex exerts causal influences on sound perception and language comprehension. However, proponents of classic symbolic theories still dispute the role of modality-preferential systems such as the motor cortex in the semantic processing of meaningful stimuli. To clarify whether the motor system carries semantic processes, we investigated neurophysiological indexes of semantic relationships between action-related sounds and words. Event-related potentials revealed that action-related words produced significantly larger stimulus-evoked (Mismatch Negativity-like) and predictive brain responses (Readiness Potentials) when presented in body-part-incongruent sound contexts (e.g., “kiss” in footstep sound context; “kick” in whistle context) than in body-part-congruent contexts, a pattern reminiscent of neurophysiological correlates of semantic priming. Cortical generators of the semantic relatedness effect were localized in areas traditionally associated with semantic memory, including left inferior frontal cortex and temporal pole, and, crucially, in motor areas, where body-part congruency of action sound–word relationships was indexed by a somatotopic pattern of activation. As our results show neurophysiological manifestations of action-semantic priming in the motor cortex, they prove semantic processing in the motor system and thus in a modality-preferential system of the human brain. PMID:26908635

  14. An enhanced feature set for pattern recognition based contrast enhancement of contact-less captured latent fingerprints in digitized crime scene forensics

    NASA Astrophysics Data System (ADS)

    Hildebrandt, Mario; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

    2014-02-01

    In crime scene forensics latent fingerprints are found on various substrates. Nowadays primarily physical or chemical preprocessing techniques are applied for enhancing the visibility of the fingerprint trace. In order to avoid altering the trace it has been shown that contact-less sensors offer a non-destructive acquisition approach. Here, the exploitation of fingerprint or substrate properties and the utilization of signal processing techniques are an essential requirement to enhance the fingerprint visibility. However, especially the optimal sensory is often substrate-dependent. An enhanced generic pattern recognition based contrast enhancement approach for scans of a chromatic white light sensor is introduced in Hildebrandt et al.1 using statistical, structural and Benford's law2 features for blocks of 50 micron. This approach achieves very good results for latent fingerprints on cooperative, non-textured, smooth substrates. However, on textured and structured substrates the error rates are very high and the approach thus unsuitable for forensic use cases. We propose the extension of the feature set with semantic features derived from known Gabor filter based exemplar fingerprint enhancement techniques by suggesting an Epsilon-neighborhood of each block in order to achieve an improved accuracy (called fingerprint ridge orientation semantics). Furthermore, we use rotation invariant Hu moments as an extension of the structural features and two additional preprocessing methods (separate X- and Y Sobel operators). This results in a 408-dimensional feature space. In our experiments we investigate and report the recognition accuracy for eight substrates, each with ten latent fingerprints: white furniture surface, veneered plywood, brushed stainless steel, aluminum foil, "Golden-Oak" veneer, non-metallic matte car body finish, metallic car body finish and blued metal. In comparison to Hildebrandt et al.,1 our evaluation shows a significant reduction of the error rates

  15. Is There Semantic Interference in Delayed Naming?

    ERIC Educational Resources Information Center

    Madebach, Andreas; Oppermann, Frank; Hantsch, Ansgar; Curda, Christian; Jescheniak, Jorg D.

    2011-01-01

    The semantic interference effect in the picture-word interference task is interpreted as an index of lexical competition in prominent speech production models. Janssen, Schirm, Mahon, and Caramazza (2008) challenged this interpretation on the basis of experiments with a novel version of this task, which introduced a task-switching component.…

  16. 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…

  17. A Comparison of Latent Growth Models for Constructs Measured by Multiple Items

    ERIC Educational Resources Information Center

    Leite, Walter L.

    2007-01-01

    Univariate latent growth modeling (LGM) of composites of multiple items (e.g., item means or sums) has been frequently used to analyze the growth of latent constructs. This study evaluated whether LGM of composites yields unbiased parameter estimates, standard errors, chi-square statistics, and adequate fit indexes. Furthermore, LGM was compared…

  18. CINDI: A Virtual Library Indexing and Discovery System.

    ERIC Educational Resources Information Center

    Desai, Bipin C.; Shinghal, Raijan; Shayan, Nader R.; Zhou, Youquan

    1999-01-01

    Describes a system called CINDI (Concordia INdexing and DIscovery System) for cataloging and searching documents in a distributed virtual library. The document author registers metadata in the form of a semantic header that contains information on syntactic and semantic content, and an expert system fills the semantic header according to accepted…

  19. Latent Supervised Learning

    PubMed Central

    Wei, Susan; Kosorok, Michael R.

    2013-01-01

    A new machine learning task is introduced, called latent supervised learning, where the goal is to learn a binary classifier from continuous training labels which serve as surrogates for the unobserved class labels. A specific model is investigated where the surrogate variable arises from a two-component Gaussian mixture with unknown means and variances, and the component membership is determined by a hyperplane in the covariate space. The estimation of the separating hyperplane and the Gaussian mixture parameters forms what shall be referred to as the change-line classification problem. A data-driven sieve maximum likelihood estimator for the hyperplane is proposed, which in turn can be used to estimate the parameters of the Gaussian mixture. The estimator is shown to be consistent. Simulations as well as empirical data show the estimator has high classification accuracy. PMID:24319303

  20. Semantic diversity: a measure of semantic ambiguity based on variability in the contextual usage of words.

    PubMed

    Hoffman, Paul; Lambon Ralph, Matthew A; Rogers, Timothy T

    2013-09-01

    Semantic ambiguity is typically measured by summing the number of senses or dictionary definitions that a word has. Such measures are somewhat subjective and may not adequately capture the full extent of variation in word meaning, particularly for polysemous words that can be used in many different ways, with subtle shifts in meaning. Here, we describe an alternative, computationally derived measure of ambiguity based on the proposal that the meanings of words vary continuously as a function of their contexts. On this view, words that appear in a wide range of contexts on diverse topics are more variable in meaning than those that appear in a restricted set of similar contexts. To quantify this variation, we performed latent semantic analysis on a large text corpus to estimate the semantic similarities of different linguistic contexts. From these estimates, we calculated the degree to which the different contexts associated with a given word vary in their meanings. We term this quantity a word's semantic diversity (SemD). We suggest that this approach provides an objective way of quantifying the subtle, context-dependent variations in word meaning that are often present in language. We demonstrate that SemD is correlated with other measures of ambiguity and contextual variability, as well as with frequency and imageability. We also show that SemD is a strong predictor of performance in semantic judgments in healthy individuals and in patients with semantic deficits, accounting for unique variance beyond that of other predictors. SemD values for over 30,000 English words are provided as supplementary materials. PMID:23239067

  1. Semantic diversity: a measure of semantic ambiguity based on variability in the contextual usage of words.

    PubMed

    Hoffman, Paul; Lambon Ralph, Matthew A; Rogers, Timothy T

    2013-09-01

    Semantic ambiguity is typically measured by summing the number of senses or dictionary definitions that a word has. Such measures are somewhat subjective and may not adequately capture the full extent of variation in word meaning, particularly for polysemous words that can be used in many different ways, with subtle shifts in meaning. Here, we describe an alternative, computationally derived measure of ambiguity based on the proposal that the meanings of words vary continuously as a function of their contexts. On this view, words that appear in a wide range of contexts on diverse topics are more variable in meaning than those that appear in a restricted set of similar contexts. To quantify this variation, we performed latent semantic analysis on a large text corpus to estimate the semantic similarities of different linguistic contexts. From these estimates, we calculated the degree to which the different contexts associated with a given word vary in their meanings. We term this quantity a word's semantic diversity (SemD). We suggest that this approach provides an objective way of quantifying the subtle, context-dependent variations in word meaning that are often present in language. We demonstrate that SemD is correlated with other measures of ambiguity and contextual variability, as well as with frequency and imageability. We also show that SemD is a strong predictor of performance in semantic judgments in healthy individuals and in patients with semantic deficits, accounting for unique variance beyond that of other predictors. SemD values for over 30,000 English words are provided as supplementary materials.

  2. 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…

  3. Communication: General Semantics Perspectives.

    ERIC Educational Resources Information Center

    Thayer, Lee, Ed.

    This book contains the edited papers from the eleventh International Conference on General Semantics, titled "A Search for Relevance." The conference questioned, as a central theme, the relevance of general semantics in a world of wars and human misery. Reacting to a fundamental Korzybski-ian principle that man's view of reality is distorted by…

  4. 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

  5. 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.

  6. Large-scale weakly supervised object localization via latent category learning.

    PubMed

    Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

    2015-04-01

    Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets. PMID:25643405

  7. Impact of Latent Infection Treatment in Indigenous Populations

    PubMed Central

    Yuhara, Lucia Suemi; Sacchi, Flávia Patussi Correia; Croda, Julio

    2013-01-01

    The aims of the present study were to identify risk factors associated with latent tuberculosis (TB), examine the development of active disease among contacts, and assess the effectiveness of treating latent infection in indigenous Brazilians from January 2006 to December 2011. This was a retrospective study consisting of 1,371 tuberculosis contacts, 392 of whom underwent treatment for latent infection. Morbidity-from-TB data were obtained from the Information System for Disease Notification (SINAN) database, and the contacts’ data were collected from the clinical records using forms employed by Special Department of Indigenous Health (SESAI) multidisciplinary teams, according to SESAI’s instructions. The variables that were associated with latent infection among the contacts were age (odds ratio [OR]: 1.03; 95% confidence interval [CI]: 1.02–1.04) and close contact with a smear-positive index case (OR: 2.26, 95% CI: 1.59–3.22). The variables associated with the development of active TB among the contacts were a tuberculin skin test (TST) ≥10 mm (relative risk [RR]: 1.12, 95% CI: 1.07–1.17), age (RR: 1.01, 95% CI: 1.00–1.03), and treatment of latent infection (RR: 0.03, 95% CI: 0.01–0.27). The estimated number of latent infection treatments needed to prevent one case of active TB among the contacts was 51 treatments (95% CI: 33–182). In contacts with TST ≥10 mm, 10 (95% CI: 6–19) latent infection treatments were necessary to prevent one case of active TB. Age and close contact with a smear-positive index case were associated with latent TB. Screening with TST is a high priority among individuals contacting smear-positive index cases. Age and TST are associated with the development of active TB among contacts, and treatment of latent infection is an effective measure to control TB in indigenous communities. PMID:23936264

  8. 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…

  9. LATENT LIFE OF ARTERIES.

    PubMed

    Carrel, A

    1910-07-23

    When a segment of artery, killed by heat, formalin or glycerin is transplanted, it undergoes a rapid degeneration. Its muscle fibers disappear while the tissue of the host reacts by building a new wall of connective tissue. When the transplanted vessel has been preserved in a condition of latent life, no degeneration of the wall occurs, or the wall undergoes only partial degeneration. The muscle fibers can keep their normal appearance, even for a long time after the operation. It is, therefore, demonstrated that arteries can be preserved outside of the body in a condition of unmanifested actual life. The best method of preservation consists of placing the vessels, immersed in vaselin, in an ice box, the temperature of which is slightly above the freezing point. From a surgical standpoint, the transplantation of preserved vessels can be used with some safety. When the arteries were kept in defibrinated blood or vaselin and in cold storage, the proportion of positive results was 75 and 80 per cent., and this can probably be increased. PMID:19867337

  10. 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…

  11. 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.

  12. Semantic Theory: A Linguistic Perspective.

    ERIC Educational Resources Information Center

    Nilsen, Don L. F.; Nilsen, Alleen Pace

    This book attempts to bring linguists and language teachers up to date on the latest developments in semantics. A survey of the role of semantics in linguistics and other academic areas is followed by a historical perspective of semantics in American linguistics. Various semantic models are discussed. Anomaly, ambiguity, and discourse are…

  13. Semantic Options in the Transitivity System: An Example of Textual Analysis.

    ERIC Educational Resources Information Center

    Lavid, Julia

    This article aims to discover the latent organization of a text by revealing a semantically motivated pattern of language functions that inform the theme of a story. it is shown how this pattern of linguistic features in the text provides insights into the literary effects of a description of a scene of a novel. The analysis proposed follows the…

  14. Understanding Latent Heat of Vaporization.

    ERIC Educational Resources Information Center

    Linz, Ed

    1995-01-01

    Presents a simple exercise for students to do in the kitchen at home to determine the latent heat of vaporization of water using typical household materials. Designed to stress understanding by sacrificing precision for simplicity. (JRH)

  15. Predicting Latent Class Scores for Subsequent Analysis

    ERIC Educational Resources Information Center

    Petersen, Janne; Bandeen-Roche, Karen; Budtz-Jorgensen, Esben; Larsen, Klaus Groes

    2012-01-01

    Latent class regression models relate covariates and latent constructs such as psychiatric disorders. Though full maximum likelihood estimation is available, estimation is often in three steps: (i) a latent class model is fitted without covariates; (ii) latent class scores are predicted; and (iii) the scores are regressed on covariates. We propose…

  16. The role of textual semantic constraints in knowledge-based inference generation during reading comprehension: A computational approach.

    PubMed

    Yeari, Menahem; van den Broek, Paul

    2015-01-01

    The present research adopted a computational approach to explore the extent to which the semantic content of texts constrains the activation of knowledge-based inferences. Specifically, we examined whether textual semantic constraints (TSC) can explain (1) the activation of predictive inferences, (2) the activation of bridging inferences and (3) the higher prevalence of the activation of bridging inferences compared to predictive inferences. To examine these hypotheses, we computed the strength of semantic associations between texts and probe items as presented to human readers in previous behavioural studies, using the Latent Semantic Analysis (LSA) algorithm. We tested whether stronger semantic associations are observed for inferred items compared to control items. Our results show that in 15 out of 17 planned comparisons, the computed strength of semantic associations successfully simulated the activation of inferences. These findings suggest that TSC play a central role in the activation of knowledge-based inferences.

  17. A presentation of latent tropical sprue in a Canadian hospital.

    PubMed

    Dargavel, Callum; Kassam, Zain; Hunt, Richard; Greenwald, Eric

    2013-08-01

    Tropical sprue (TS) is a chronic diarrheal disease of unknown etiology characterized by malabsorption and small bowel mucosal abnormalities. TS affects residents of, and visitors to, endemic tropical regions. Rarely the disease may remain latent for several years, and to date, few cases of latent TS have been reported in Europe or North America. However, in our increasingly multicultural communities and in a 'global village' where travel is common, clinicians must maintain a high index of suspicion for TS in patients presenting with diarrhea and malabsorption who have traveled to endemic regions. TS may mimic common diarrheal diseases that are seen in developed nations, including celiac disease, Crohn's disease, bacterial overgrowth, and other infectious etiologies. Accordingly, once these more common etiologies have been ruled out, TS must be considered in patients presenting with diarrhea after travel to endemic regions. We present a unique Canadian case of latent TS, with a brief review of the diagnostic approach and treatment.

  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. Algebraic Semantics for Narrative

    ERIC Educational Resources Information Center

    Kahn, E.

    1974-01-01

    This paper uses discussion of Edmund Spenser's "The Faerie Queene" to present a theoretical framework for explaining the semantics of narrative discourse. The algebraic theory of finite automata is used. (CK)

  20. Arabic Literature: Uniterm Indexing System for Storage and Retrieval.

    ERIC Educational Resources Information Center

    Ghani, Abdul

    1987-01-01

    Describes the uniterm system of coordinate indexing and examines its applicability to the indexing of Arabic literature. Unresolved problems in semantics, thesauri development, and standardization are identified and discussed. (CLB)

  1. Reproducibility and discriminability of brain patterns of semantic categories enhanced by congruent audiovisual stimuli.

    PubMed

    Li, Yuanqing; Wang, Guangyi; Long, Jinyi; Yu, Zhuliang; Huang, Biao; Li, Xiaojian; Yu, Tianyou; Liang, Changhong; Li, Zheng; Sun, Pei

    2011-01-01

    One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or semantic categories through a functional magnetic resonance imaging (fMRI) experiment. We used a pattern search method to extract brain patterns corresponding to two semantic categories: "old people" and "young people." These brain patterns were elicited by semantically congruent audiovisual, semantically incongruent audiovisual, unimodal visual, and unimodal auditory stimuli belonging to the two semantic categories. We calculated the reproducibility index, which measures the similarity of the patterns within the same category. We also decoded the semantic categories from these brain patterns. The decoding accuracy reflects the discriminability of the brain patterns between two categories. The results showed that both the reproducibility index of brain patterns and the decoding accuracy were significantly higher for semantically congruent audiovisual stimuli than for unimodal visual and unimodal auditory stimuli, while the semantically incongruent stimuli did not elicit brain patterns with significantly higher reproducibility index or decoding accuracy. Thus, the semantically congruent audiovisual stimuli enhanced the within-class reproducibility of brain patterns and the between-class discriminability of brain patterns, and facilitate neural representations of semantic categories or concepts. Furthermore, we analyzed the brain activity in superior temporal sulcus and middle temporal gyrus (STS/MTG). The strength of the fMRI signal and the reproducibility index were enhanced by the semantically congruent audiovisual stimuli. Our results support the use of the reproducibility index as a potential tool to supplement the fMRI signal amplitude for evaluating multimodal integration.

  2. Latent variable models with nonparametric interaction effects of latent variables.

    PubMed

    Song, Xinyuan; Lu, Zhaohua; Feng, Xiangnan

    2014-05-10

    Renal disease is one of the common complications of diabetes, especially for Asian populations. Moreover, cardiovascular and renal diseases share common risk factors. This paper proposes a latent variable model with nonparametric interaction effects of latent variables for a study based on the Hong Kong Diabetes Registry, which was established in 1995 as part of a continuous quality improvement program at the Prince of Wales Hospital in Hong Kong. Renal outcome (outcome latent variable) is regressed in terms of cardiac function and diabetes (explanatory latent variables) through an additive structural equation formulated using a series of unspecified univariate and bivariate smooth functions. The Bayesian P-splines approach, along with a Markov chain Monte Carlo algorithm, is proposed to estimate smooth functions, unknown parameters, and latent variables in the model. The performance of the developed methodology is demonstrated via a simulation study. The effect of the nonparametric interaction of cardiac function and diabetes on renal outcome is investigated using the proposed methodology. PMID:24338916

  3. "Pre-semantic" cognition revisited: critical differences between semantic aphasia and semantic dementia.

    PubMed

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

    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 atypical of the domain and "regularization errors" (irregular/atypical items are produced as if they were domain-typical). The emergence of this pattern across diverse tasks in the same patients indicates that semantic memory plays a key role in all of these types of "pre-semantic" processing. However, this claim remains controversial because semantically impaired patients sometimes fail to show an influence of regularity. This study demonstrates that (a) the location of brain damage and (b) the underlying nature of the semantic deficit affect the likelihood of observing the expected relationship between poor comprehension and regularity effects. We compared the effect of multimodal semantic impairment in the context of semantic dementia and stroke aphasia on the seven "pre-semantic" tasks listed above. In all of these tasks, the semantic aphasia patients were less sensitive to typicality than the semantic dementia patients, even though the two groups obtained comparable scores on semantic tests. The semantic aphasia group also made fewer regularization errors and many more unrelated and perseverative responses. We propose that these group differences reflect the different locus for the semantic impairment in the two conditions: patients with semantic dementia have degraded semantic representations, whereas semantic aphasia patients show deregulated semantic cognition with concomitant executive deficits. These findings suggest a reinterpretation of single-case studies of comprehension-impaired aphasic patients who fail to show the expected effect of regularity on "pre-semantic" tasks. Consequently, such cases do not demonstrate

  4. Effects of speed of word processing on semantic access: the case of bilingualism.

    PubMed

    Martin, Clara D; Costa, Albert; Dering, Benjamin; Hoshino, Noriko; Wu, Yan Jing; Thierry, Guillaume

    2012-01-01

    Bilingual speakers generally manifest slower word recognition than monolinguals. We investigated the consequences of the word processing speed on semantic access in bilinguals. The paradigm involved a stream of English words and pseudowords presented in succession at a constant rate. English-Welsh bilinguals and English monolinguals were asked to count the number of letters in pseudowords and actively disregard words. They were not explicitly told that pairs of words in immediate succession were embedded and could either be semantically related or not. We expected that slower word processing in bilinguals would result in semantic access indexed by semantic priming. As expected, bilinguals showed significant semantic priming, indexed by an N400 modulation, whilst monolinguals did not. Moreover, bilinguals were slower in performing the task. The results suggest that bilinguals cannot discriminate between pseudowords and words without accessing semantic information whereas monolinguals can dismiss English words on the basis of subsemantic information.

  5. Auditory semantic networks for words and natural sounds.

    PubMed

    Cummings, A; Ceponiene, R; Koyama, A; Saygin, A P; Townsend, J; Dick, F

    2006-10-18

    Does lexical processing rely on a specialized semantic network in the brain, or does it draw on more general semantic resources? The primary goal of this study was to compare behavioral and electrophysiological responses evoked during the processing of words, environmental sounds, and non-meaningful sounds in semantically matching or mismatching visual contexts. A secondary goal was to characterize the dynamic relationship between the behavioral and neural activities related to semantic integration using a novel analysis technique, ERP imaging. In matching trials, meaningful-sound ERPs were characterized by an extended positivity (200-600 ms) that in mismatching trials partly overlapped with centro-parietal N400 and frontal N600 negativities. The mismatch word-N400 peaked later than the environmental sound-N400 and was only slightly more posterior in scalp distribution. Single-trial ERP imaging revealed that for meaningful stimuli, the match-positivity consisted of a sensory P2 (200 ms), a semantic positivity (PS, 300 ms), and a parietal response-related positivity (PR, 500-800 ms). The magnitudes (but not the timing) of the N400 and PS activities correlated with subjects' reaction times, whereas both the latency and magnitude of the PR was correlated with subjects' reaction times. These results suggest that largely overlapping neural networks process verbal and non-verbal semantic information. In addition, it appears that semantic integration operates across different time scales: earlier processes (indexed by the PS and N400) utilize the established meaningful, but not necessarily lexical, semantic representations, whereas later processes (indexed by the PR and N600) are involved in the explicit interpretation of stimulus semantics and possibly of the required response. PMID:16962567

  6. Class-specific Gaussian-multinomial latent Dirichlet allocation for image annotation

    NASA Astrophysics Data System (ADS)

    Qian, Zhiming; Zhong, Ping; Wang, Runsheng

    2015-12-01

    Image annotation has been a challenging problem due to the well-known semantic gap between two heterogeneous information modalities, i.e., the visual modality referring to low-level visual features and the semantic modality referring to high-level human concepts. To bridge the semantic gap, we present an extension of latent Dirichlet allocation (LDA), denoted as class-specific Gaussian-multinomial latent Dirichlet allocation (csGM-LDA), in an effort to simulate the human's visual perception system. An analysis of previous supervised LDA models shows that the topics discovered by generative LDA models are driven by general image regularities rather than the semantic regularities for image annotation. To address this, csGM-LDA is introduced by using class supervision at the level of visual features for multimodal topic modeling. The csGM-LDA model combines the labeling strength of topic supervision with the flexibility of topic discovery, and the modeling problem can be effectively solved by a variational expectation-maximization (EM) algorithm. Moreover, as natural images usually generate an enormous size of high-dimensional data in annotation applications, an efficient descriptor based on Laplacian regularized uncorrelated tensor representation is proposed for explicitly exploiting the manifold structures in the high-order image space. Experimental results on two standard annotation datasets have shown the effectiveness of the proposed method by comparing with several state-of-the-art annotation methods.

  7. Spontaneously reactivated patterns in frontal and temporal lobe predict semantic clustering during memory search.

    PubMed

    Manning, Jeremy R; Sperling, Michael R; Sharan, Ashwini; Rosenberg, Emily A; Kahana, Michael J

    2012-06-27

    Although it is well established that remembering an item will bring to mind memories of other semantically related items (Bousfield, 1953), the neural basis of this phenomenon is poorly understood. We studied how the similarity relations among items influence their retrieval by analyzing electrocorticographic recordings taken as 46 human neurosurgical patients studied and freely recalled lists of words. We first identified semantic components of neural activity that varied systematically with the meanings of each studied word, as defined by latent semantic analysis (Landauer and Dumais, 1997). We then examined the dynamics of these semantic components as participants attempted to recall the previously studied words. Our analyses revealed that the semantic components of neural activity were spontaneously reactivated during memory search, just before recall of the studied words. Further, the degree to which neural activity correlated with semantic similarity during recall predicted participants' tendencies to organize the sequences of their responses on the basis of semantic similarity. Thus, our work shows that differences in the neural correlates of semantic information, and how they are reactivated before recall, reveal how individuals organize and retrieve memories of words.

  8. The Semantic SPASE

    NASA Astrophysics Data System (ADS)

    Hughes, S.; Crichton, D.; Thieman, J.; Ramirez, P.; King, T.; Weiss, M.

    2005-12-01

    The Semantic SPASE (Space Physics Archive Search and Extract) prototype demonstrates the use of semantic web technologies to capture, document, and manage the SPASE data model, support facet- and text-based search, and provide flexible and intuitive user interfaces. The SPASE data model, under development since late 2003 by a consortium of space physics domain experts, is intended to serve as the basis for interoperability between independent data systems. To develop the Semantic SPASE prototype, the data model was first analyzed to determine the inherit object classes and their attributes. These were entered into Stanford Medical Informatics' Protege ontology tool and annotated using definitions from the SPASE documentation. Further analysis of the data model resulted in the addition of class relationships. Finally attributes and relationships that support broad-scope interoperability were added from research associated with the Object-Oriented Data Technology task. To validate the ontology and produce a knowledge base, example data products were ingested. The capture of the data model as an ontology results in a more formal specification of the model. The Protege software is also a powerful management tool and supports plug-ins that produce several graphical notations as output. The stated purpose of the semantic web is to support machine understanding of web-based information. Protege provides an export capability to RDF/XML and RDFS/XML for this purpose. Several research efforts use RDF/XML knowledge bases to provide semantic search. MIT's Simile/Longwell project provides both facet- and text-based search using a suite of metadata browsers and the text-based search engine Lucene. Using the Protege generated RDF knowledge-base a semantic search application was easily built and deployed to run as a web application. Configuration files specify the object attributes and values to be designated as facets (i.e. search) constraints. Semantic web technologies provide

  9. Latent fingermark pore area reproducibility.

    PubMed

    Gupta, A; Buckley, K; Sutton, R

    2008-08-01

    The study of the reproducibility of friction ridge pore detail in fingermarks is a measure of their usefulness in personal identification. Pore area in latent prints developed using cyanoacrylate and ninhydrin were examined and measured by photomicrography using appropriate software tools. The data were analysed statistically and the results showed that pore area is not reproducible in developed latent prints, using either of the development techniques. The results add further support to the lack of reliability of pore area in personal identification. PMID:18617339

  10. Joint modeling of repeated multivariate cognitive measures and competing risks of dementia and death: a latent process and latent class approach.

    PubMed

    Proust-Lima, Cécile; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

    2016-02-10

    Joint models initially dedicated to a single longitudinal marker and a single time-to-event need to be extended to account for the rich longitudinal data of cohort studies. Multiple causes of clinical progression are indeed usually observed, and multiple longitudinal markers are collected when the true latent trait of interest is hard to capture (e.g., quality of life, functional dependency, and cognitive level). These multivariate and longitudinal data also usually have nonstandard distributions (discrete, asymmetric, bounded, etc.). We propose a joint model based on a latent process and latent classes to analyze simultaneously such multiple longitudinal markers of different natures, and multiple causes of progression. A latent process model describes the latent trait of interest and links it to the observed longitudinal outcomes using flexible measurement models adapted to different types of data, and a latent class structure links the longitudinal and cause-specific survival models. The joint model is estimated in the maximum likelihood framework. A score test is developed to evaluate the assumption of conditional independence of the longitudinal markers and each cause of progression given the latent classes. In addition, individual dynamic cumulative incidences of each cause of progression based on the repeated marker data are derived. The methodology is validated in a simulation study and applied on real data about cognitive aging obtained from a large population-based study. The aim is to predict the risk of dementia by accounting for the competing death according to the profiles of semantic memory measured by two asymmetric psychometric tests.

  11. Semantic home video categorization

    NASA Astrophysics Data System (ADS)

    Min, Hyun-Seok; Lee, Young Bok; De Neve, Wesley; Ro, Yong Man

    2009-02-01

    Nowadays, a strong need exists for the efficient organization of an increasing amount of home video content. To create an efficient system for the management of home video content, it is required to categorize home video content in a semantic way. So far, a significant amount of research has already been dedicated to semantic video categorization. However, conventional categorization approaches often rely on unnecessary concepts and complicated algorithms that are not suited in the context of home video categorization. To overcome the aforementioned problem, this paper proposes a novel home video categorization method that adopts semantic home photo categorization. To use home photo categorization in the context of home video, we segment video content into shots and extract key frames that represent each shot. To extract the semantics from key frames, we divide each key frame into ten local regions and extract lowlevel features. Based on the low level features extracted for each local region, we can predict the semantics of a particular key frame. To verify the usefulness of the proposed home video categorization method, experiments were performed with home video sequences, labeled by concepts part of the MPEG-7 VCE2 dataset. To verify the usefulness of the proposed home video categorization method, experiments were performed with 70 home video sequences. For the home video sequences used, the proposed system produced a recall of 77% and an accuracy of 78%.

  12. Bridging the semantic gap in sports

    NASA Astrophysics Data System (ADS)

    Li, Baoxin; Errico, James; Pan, Hao; Sezan, M. Ibrahim

    2003-01-01

    One of the major challenges facing current media management systems and the related applications is the so-called "semantic gap" between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs. The framework is based on a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.

  13. Semantic Parameters of Split Intransitivity.

    ERIC Educational Resources Information Center

    Van Valin, Jr., Robert D.

    1990-01-01

    This paper argues that split-intransitive phenomena are better explained in semantic terms. A semantic analysis is carried out in Role and Reference Grammar, which assumes the theory of verb classification proposed in Dowty 1979. (49 references) (JL)

  14. Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation

    PubMed Central

    Huang, Chung-Chi; Lu, Zhiyong

    2016-01-01

    Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as ‘CHEMICAL-1 compared to CHEMICAL-2.’ With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical–disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked

  15. Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

    PubMed

    Huang, Chung-Chi; Lu, Zhiyong

    2016-01-01

    Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

  16. 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.

  17. Effects of Latent Toxoplasmosis on Autoimmune Thyroid Diseases in Pregnancy

    PubMed Central

    Kaňková, Šárka; Procházková, Lucie; Flegr, Jaroslav; Calda, Pavel; Springer, Drahomíra; Potluková, Eliška

    2014-01-01

    Background Toxoplasmosis, one of the most common zoonotic diseases worldwide, can induce various hormonal and behavioural alterations in infected hosts, and its most common form, latent toxoplasmosis, influences the course of pregnancy. Autoimmune thyroid diseases (AITD) belong to the well-defined risk factors for adverse pregnancy outcomes. The aim of this study was to investigate whether there is a link between latent toxoplasmosis and maternal AITD in pregnancy. Methods Cross-sectional study in 1248 consecutive pregnant women in the 9–12th gestational weeks. Serum thyroid-stimulating hormone (TSH), thyroperoxidase antibodies (TPOAb), and free thyroxine (FT4) were assessed by chemiluminescence; the Toxoplasma status was detected by the complement fixation test (CFT) and anti-Toxoplasma IgG enzyme-linked immunosorbent assay (ELISA). Results Overall, 22.5% of the women were positive for latent toxoplasmosis and 14.7% were screened positive for AITD. Women with latent toxoplasmosis had more often highly elevated TPOAb than the Toxoplasma-negative ones (p = 0.004), and latent toxoplasmosis was associated with decrease in serum TSH levels (p = 0.049). Moreover, we found a positive correlation between FT4 and the index of positivity for anti-Toxoplasma IgG antibodies (p = 0.033), which was even stronger in the TPOAb-positive Toxoplasma-positive women, (p = 0.014), as well as a positive correlation between FT4 and log2 CFT (p = 0.009). Conclusions Latent toxoplasmosis was associated with a mild increase in thyroid hormone production in pregnancy. The observed Toxoplasma-associated changes in the parameters of AITD are mild and do not seem to be clinically relevant; however, they could provide new clues to the complex pathogenesis of autoimmune thyroid diseases. PMID:25350671

  18. Causal premise semantics.

    PubMed

    Kaufmann, Stefan

    2013-08-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal semantic analysis of conditionals, Kratzer-style premise semantics, allows for a straightforward implementation of the crucial ideas and insights of Pearl-style causal networks. I spell out the details of such an implementation, focusing especially on the notions of intervention on a network and backtracking interpretations of counterfactuals.

  19. A Revised Semantic Differential Scale Distinguishing between Negative and Positive God Images

    ERIC Educational Resources Information Center

    Francis, Leslie J.; Robbins, Mandy; Gibson, Harry M.

    2006-01-01

    A sample of 755 school pupils between the ages of 11 and 18 years completed the Benson and Spilka semantic differential measure of God images. Factor analysis indicated the advantages of re-scoring the measure as an eight item unidimensional index, defining semantic space relating to God images ranging from negative affect to positive affect.…

  20. Semantic Processing in Children and Adults: Incongruity and the N400

    ERIC Educational Resources Information Center

    Benau, Erik M.; Morris, Joanna; Couperus, J. W.

    2011-01-01

    Semantic processing in 10-year-old children and adults was examined using event related potentials (ERPs). The N400 component, an index of semantic processing, was studied in relation to sentences that ended with congruent, moderately incongruent, or strongly incongruent words. N400 amplitude in adults corresponded to levels of semantic…

  1. Semantic Webs and Study Skills.

    ERIC Educational Resources Information Center

    Hoover, John J.; Rabideau, Debra K.

    1995-01-01

    Principles for ensuring effective use of semantic webbing in meeting study skill needs of students with learning problems are noted. Important study skills are listed, along with suggested semantic web topics for which subordinate ideas may be developed. Two semantic webs are presented, illustrating the study skills of multiple choice test-taking…

  2. 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…

  3. Taxometric and Factor Analytic Models of Anxiety Sensitivity: Integrating Approaches to Latent Structural Research

    ERIC Educational Resources Information Center

    Bernstein, Amit; Zvolensky, Michael J.; Norton, Peter J.; Schmidt, Norman B.; Taylor, Steven; Forsyth, John P.; Lewis, Sarah F.; Feldner, Matthew T.; Leen-Feldner, Ellen W.; Stewart, Sherry H.; Cox, Brian

    2007-01-01

    This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), as indexed by the 16-item Anxiety Sensitivity Index (ASI; S. Reiss, R. A. Peterson, M. Gursky, & R. J. McNally, 1986), by using taxometric and factor-analytic approaches in an integrative manner. Taxometric analyses indicated that AS has a…

  4. GOOSE: semantic search on internet connected sensors

    NASA Astrophysics Data System (ADS)

    Schutte, Klamer; Bomhof, Freek; Burghouts, Gertjan; van Diggelen, Jurriaan; Hiemstra, Peter; van't Hof, Jaap; Kraaij, Wessel; Pasman, Huib; Smith, Arthur; Versloot, Corne; de Wit, Joost

    2013-05-01

    More and more sensors are getting Internet connected. Examples are cameras on cell phones, CCTV cameras for traffic control as well as dedicated security and defense sensor systems. Due to the steadily increasing data volume, human exploitation of all this sensor data is impossible for effective mission execution. Smart access to all sensor data acts as enabler for questions such as "Is there a person behind this building" or "Alert me when a vehicle approaches". The GOOSE concept has the ambition to provide the capability to search semantically for any relevant information within "all" (including imaging) sensor streams in the entire Internet of sensors. This is similar to the capability provided by presently available Internet search engines which enable the retrieval of information on "all" web pages on the Internet. In line with current Internet search engines any indexing services shall be utilized cross-domain. The two main challenge for GOOSE is the Semantic Gap and Scalability. The GOOSE architecture consists of five elements: (1) an online extraction of primitives on each sensor stream; (2) an indexing and search mechanism for these primitives; (3) a ontology based semantic matching module; (4) a top-down hypothesis verification mechanism and (5) a controlling man-machine interface. This paper reports on the initial GOOSE demonstrator, which consists of the MES multimedia analysis platform and the CORTEX action recognition module. It also provides an outlook into future GOOSE development.

  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. Semantator: annotating clinical narratives with semantic web ontologies.

    PubMed

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

    2012-01-01

    To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. With a loaded free text document and an ontology, Semantator supports the creation/deletion of ontology instances for any document fragment, linking/disconnecting instances with the properties in the ontology, and also enables automatic annotation by connecting to the NCBO annotator and cTAKES. By representing annotations in Semantic Web standards, Semantator supports reasoning based upon the underlying semantics of the owl:disjointWith and owl:equivalentClass predicates. We present discussions based on user experiences of using Semantator.

  7. Latent Growth Modeling for Logistic Response Functions

    ERIC Educational Resources Information Center

    Choi, Jaehwa; Harring, Jeffrey R.; Hancock, Gregory R.

    2009-01-01

    Throughout much of the social and behavioral sciences, latent growth modeling (latent curve analysis) has become an important tool for understanding individuals' longitudinal change. Although nonlinear variations of latent growth models appear in the methodological and applied literature, a notable exclusion is the treatment of growth following…

  8. A Multicomponent Latent Trait Model for Diagnosis

    ERIC Educational Resources Information Center

    Embretson, Susan E.; Yang, Xiangdong

    2013-01-01

    This paper presents a noncompensatory latent trait model, the multicomponent latent trait model for diagnosis (MLTM-D), for cognitive diagnosis. In MLTM-D, a hierarchical relationship between components and attributes is specified to be applicable to permit diagnosis at two levels. MLTM-D is a generalization of the multicomponent latent trait…

  9. Multiply-constrained semantic search in the Remote Associates Test.

    PubMed

    Smith, Kevin A; Huber, David E; Vul, Edward

    2013-07-01

    Many important problems require consideration of multiple constraints, such as choosing a job based on salary, location, and responsibilities. We used the Remote Associates Test to study how people solve such multiply-constrained problems by asking participants to make guesses as they came to mind. We evaluated how people generated these guesses by using Latent Semantic Analysis to measure the similarity between the guesses, cues, and answers. We found that people use two systematic strategies to solve multiply-constrained problems: (a) people produce guesses primarily on the basis of just one of the three cues at a time; and (b) people adopt a local search strategy--they make new guesses based in part on their previous guesses. These results inform how people combine constraints to search through and retrieve semantic information from memory.

  10. 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,…

  11. Assertiveness through Semantics.

    ERIC Educational Resources Information Center

    Zuercher, Nancy T.

    1983-01-01

    Suggests that connotations of assertiveness do not convey all of its meanings, particularly the components of positive feelings, communication, and cooperation. The application of semantics can help restore the balance. Presents a model for differentiating assertive behavior and clarifying the definition. (JAC)

  12. Are Terminologies Semantically Uninteresting?

    ERIC Educational Resources Information Center

    Jacobson, Sven

    Some semanticists have argued that technical vocabulary or terminology is extralinguistic and therefore semantically uninteresting. However, no boundary exists in linguistic reality between terminology and ordinary vocabulary. Rather, terminologies and ordinary language exist on a continuum, and terminology is therefore a legitimate field for…

  13. Semantic Space Analyst

    2004-04-15

    The Semantic Space Analyst (SSA) is software for analyzing a text corpus, discovering relationships among terms, and allowing the user to explore that information in different ways. It includes features for displaying and laying out terms and relationships visually, for generating such maps from manual queries, for discovering differences between corpora. Data can also be exported to Microsoft Excel.

  14. Semantic physical science

    PubMed Central

    2012-01-01

    The articles in this special issue arise from a workshop and symposium held in January 2012 (Semantic Physical Science’). We invited people who shared our vision for the potential of the web to support chemical and related subjects. Other than the initial invitations, we have not exercised any control over the content of the contributed articles. PMID:22856527

  15. Universal Semantics in Translation

    ERIC Educational Resources Information Center

    Wang, Zhenying

    2009-01-01

    What and how we translate are questions often argued about. No matter what kind of answers one may give, priority in translation should be granted to meaning, especially those meanings that exist in all concerned languages. In this paper the author defines them as universal sememes, and the study of them as universal semantics, of which…

  16. Video summarization and semantics editing tools

    NASA Astrophysics Data System (ADS)

    Xu, Li-Qun; Zhu, Jian; Stentiford, Fred

    2001-01-01

    This paper describes a video summarization and semantics editing tool that is suited for content-based video indexing and retrieval with appropriate human operator assistance. The whole system has been designed with a clear focus on the extraction and exploitation of motion information inherent in the dynamic video scene. The dominant motion information has ben used explicitly for shot boundary detection, camera motion characterization, visual content variations description, and for key frame extraction. Various contributions have been made to ensure that the system works robustly with complex scenes and across different media types. A window-based graphical user interface has been designed to make the task very easy for interactive analysis and editing of semantic events and episode where appropriate.

  17. Video summarization and semantics editing tools

    NASA Astrophysics Data System (ADS)

    Xu, Li-Qun; Zhu, Jian; Stentiford, Fred

    2000-12-01

    This paper describes a video summarization and semantics editing tool that is suited for content-based video indexing and retrieval with appropriate human operator assistance. The whole system has been designed with a clear focus on the extraction and exploitation of motion information inherent in the dynamic video scene. The dominant motion information has ben used explicitly for shot boundary detection, camera motion characterization, visual content variations description, and for key frame extraction. Various contributions have been made to ensure that the system works robustly with complex scenes and across different media types. A window-based graphical user interface has been designed to make the task very easy for interactive analysis and editing of semantic events and episode where appropriate.

  18. Tuberculosis Infection and Latent Tuberculosis

    PubMed Central

    2016-01-01

    Active tuberculosis (TB) has a greater burden of TB bacilli than latent TB and acts as an infection source for contacts. Latent tuberculosis infection (LTBI) is the state in which humans are infected with Mycobacterium tuberculosis without any clinical symptoms, radiological abnormality, or microbiological evidence. TB is transmissible by respiratory droplet nucleus of 1–5 µm in diameter, containing 1–10 TB bacilli. TB transmission is affected by the strength of the infectious source, infectiousness of TB bacilli, immunoresistance of the host, environmental stresses, and biosocial factors. Infection controls to reduce TB transmission consist of managerial activities, administrative control, engineering control, environmental control, and personal protective equipment provision. However, diagnosis and treatment for LTBI as a national TB control program is an important strategy on the precondition that active TB is not missed. Therefore, more concrete evidences for LTBI management based on clinical and public perspectives are needed. PMID:27790271

  19. Effects of semantic predictability and regional dialect on vowel space reduction.

    PubMed

    Clopper, Cynthia G; Pierrehumbert, Janet B

    2008-09-01

    This study explored the interaction between semantic predictability and regional dialect variation in an analysis of speech produced by college-aged female talkers from the Northern, Midland, and Southern dialects of American English. Previous research on the effects of semantic predictability has shown that vowels in high semantic predictability contexts are temporally and spectrally reduced compared to vowels in low semantic predictability contexts. In the current study, an analysis of vowel duration confirmed temporal reduction in the high predictability condition. An analysis of vowel formant structure and vowel space dispersion revealed overall spectral reduction for the Southern talkers. For the Northern talkers, more extreme Northern Cities shifting occurred in the high predictability condition than in the low predictability condition. No effects of semantic predictability were observed for the Midland talkers. These findings suggest an interaction between semantic and indexical factors in vowel reduction processes.

  20. [Latent autoimmune diabetes in adults].

    PubMed

    Maioli, M; Puddu, L; Pes, G M

    2006-01-01

    Latent autoimmune diabetes in adults (LADA) is a disorder with onset after age 30, insulin independence for at least 6 months after diagnosis, and the presence of circulating pancreatic islet autoantibodies. The prevalence of LADA varies substantially across ethnic groups and ranges approximately from 1% to 10% among patients with type 2 diabetes. In this review we discuss the nomenclature, diagnostic criteria, immunologic and genetic markers, metabolic alterations and therapy of this form of diabetes.

  1. Emergent latent symbol systems in recurrent neural networks

    NASA Astrophysics Data System (ADS)

    Monner, Derek; Reggia, James A.

    2012-12-01

    Fodor and Pylyshyn [(1988). Connectionism and cognitive architecture: A critical analysis. Cognition, 28(1-2), 3-71] famously argued that neural networks cannot behave systematically short of implementing a combinatorial symbol system. A recent response from Frank et al. [(2009). Connectionist semantic systematicity. Cognition, 110(3), 358-379] claimed to have trained a neural network to behave systematically without implementing a symbol system and without any in-built predisposition towards combinatorial representations. We believe systems like theirs may in fact implement a symbol system on a deeper and more interesting level: one where the symbols are latent - not visible at the level of network structure. In order to illustrate this possibility, we demonstrate our own recurrent neural network that learns to understand sentence-level language in terms of a scene. We demonstrate our model's learned understanding by testing it on novel sentences and scenes. By paring down our model into an architecturally minimal version, we demonstrate how it supports combinatorial computation over distributed representations by using the associative memory operations of Vector Symbolic Architectures. Knowledge of the model's memory scheme gives us tools to explain its errors and construct superior future models. We show how the model designs and manipulates a latent symbol system in which the combinatorial symbols are patterns of activation distributed across the layers of a neural network, instantiating a hybrid of classical symbolic and connectionist representations that combines advantages of both.

  2. Semantic interpretation of nominalizations

    SciTech Connect

    Hull, R.D.; Gomez, F.

    1996-12-31

    A computational approach to the semantic interpretation of nominalizations is described. Interpretation of normalizations involves three tasks: deciding whether the normalization is being used in a verbal or non-verbal sense; disambiguating the normalized verb when a verbal sense is used; and determining the fillers of the thematic roles of the verbal concept or predicate of the nominalization. A verbal sense can be recognized by the presence of modifiers that represent the arguments of the verbal concept. It is these same modifiers which provide the semantic clues to disambiguate the normalized verb. In the absence of explicit modifiers, heuristics are used to discriminate between verbal and non-verbal senses. A correspondence between verbs and their nominalizations is exploited so that only a small amount of additional knowledge is needed to handle the nominal form. These methods are tested in the domain of encyclopedic texts and the results are shown.

  3. Living With Semantic Dementia

    PubMed Central

    Sage, Karen; Wilkinson, Ray; Keady, John

    2014-01-01

    Semantic dementia is a variant of frontotemporal dementia and is a recently recognized diagnostic condition. There has been some research quantitatively examining care partner stress and burden in frontotemporal dementia. There are, however, few studies exploring the subjective experiences of family members caring for those with frontotemporal dementia. Increased knowledge of such experiences would allow service providers to tailor intervention, support, and information better. We used a case study design, with thematic narrative analysis applied to interview data, to describe the experiences of a wife and son caring for a husband/father with semantic dementia. Using this approach, we identified four themes: (a) living with routines, (b) policing and protecting, (c) making connections, and (d) being adaptive and flexible. Each of these themes were shared and extended, with the importance of routines in everyday life highlighted. The implications for policy, practice, and research are discussed. PMID:24532121

  4. Practical Semantic Astronomy

    NASA Astrophysics Data System (ADS)

    Graham, Matthew; Gray, N.; Burke, D.

    2010-01-01

    Many activities in the era of data-intensive astronomy are predicated upon some transference of domain knowledge and expertise from human to machine. The semantic infrastructure required to support this is no longer a pipe dream of computer science but a set of practical engineering challenges, more concerned with deployment and performance details than AI abstractions. The application of such ideas promises to help in such areas as contextual data access, exploiting distributed annotation and heterogeneous sources, and intelligent data dissemination and discovery. In this talk, we will review the status and use of semantic technologies in astronomy, particularly to address current problems in astroinformatics, with such projects as SKUA and AstroCollation.

  5. Live Social Semantics

    NASA Astrophysics Data System (ADS)

    Alani, Harith; Szomszor, Martin; Cattuto, Ciro; van den Broeck, Wouter; Correndo, Gianluca; Barrat, Alain

    Social interactions are one of the key factors to the success of conferences and similar community gatherings. This paper describes a novel application that integrates data from the semantic web, online social networks, and a real-world contact sensing platform. This application was successfully deployed at ESWC09, and actively used by 139 people. Personal profiles of the participants were automatically generated using several Web 2.0 systems and semantic academic data sources, and integrated in real-time with face-to-face contact networks derived from wearable sensors. Integration of all these heterogeneous data layers made it possible to offer various services to conference attendees to enhance their social experience such as visualisation of contact data, and a site to explore and connect with other participants. This paper describes the architecture of the application, the services we provided, and the results we achieved in this deployment.

  6. Structural Similarities between Brain and Linguistic Data Provide Evidence of Semantic Relations in the Brain

    PubMed Central

    Crangle, Colleen E.; Perreau-Guimaraes, Marcos; Suppes, Patrick

    2013-01-01

    This paper presents a new method of analysis by which structural similarities between brain data and linguistic data can be assessed at the semantic level. It shows how to measure the strength of these structural similarities and so determine the relatively better fit of the brain data with one semantic model over another. The first model is derived from WordNet, a lexical database of English compiled by language experts. The second is given by the corpus-based statistical technique of latent semantic analysis (LSA), which detects relations between words that are latent or hidden in text. The brain data are drawn from experiments in which statements about the geography of Europe were presented auditorily to participants who were asked to determine their truth or falsity while electroencephalographic (EEG) recordings were made. The theoretical framework for the analysis of the brain and semantic data derives from axiomatizations of theories such as the theory of differences in utility preference. Using brain-data samples from individual trials time-locked to the presentation of each word, ordinal relations of similarity differences are computed for the brain data and for the linguistic data. In each case those relations that are invariant with respect to the brain and linguistic data, and are correlated with sufficient statistical strength, amount to structural similarities between the brain and linguistic data. Results show that many more statistically significant structural similarities can be found between the brain data and the WordNet-derived data than the LSA-derived data. The work reported here is placed within the context of other recent studies of semantics and the brain. The main contribution of this paper is the new method it presents for the study of semantics and the brain and the focus it permits on networks of relations detected in brain data and represented by a semantic model. PMID:23799009

  7. Semantic Annotation for Biological Information Retrieval System

    PubMed Central

    Oshaiba, Mohamed Marouf Z.; El Houby, Enas M. F.; Salah, Akram

    2015-01-01

    Online literatures are increasing in a tremendous rate. Biological domain is one of the fast growing domains. Biological researchers face a problem finding what they are searching for effectively and efficiently. The aim of this research is to find documents that contain any combination of biological process and/or molecular function and/or cellular component. This research proposes a framework that helps researchers to retrieve meaningful documents related to their asserted terms based on gene ontology (GO). The system utilizes GO by semantically decomposing it into three subontologies (cellular component, biological process, and molecular function). Researcher has the flexibility to choose searching terms from any combination of the three subontologies. Document annotation is taking a place in this research to create an index of biological terms in documents to speed the searching process. Query expansion is used to infer semantically related terms to asserted terms. It increases the search meaningful results using the term synonyms and term relationships. The system uses a ranking method to order the retrieved documents based on the ranking weights. The proposed system achieves researchers' needs to find documents that fit the asserted terms semantically. PMID:25737720

  8. Semantic annotation for biological information retrieval system.

    PubMed

    Oshaiba, Mohamed Marouf Z; El Houby, Enas M F; Salah, Akram

    2015-01-01

    Online literatures are increasing in a tremendous rate. Biological domain is one of the fast growing domains. Biological researchers face a problem finding what they are searching for effectively and efficiently. The aim of this research is to find documents that contain any combination of biological process and/or molecular function and/or cellular component. This research proposes a framework that helps researchers to retrieve meaningful documents related to their asserted terms based on gene ontology (GO). The system utilizes GO by semantically decomposing it into three subontologies (cellular component, biological process, and molecular function). Researcher has the flexibility to choose searching terms from any combination of the three subontologies. Document annotation is taking a place in this research to create an index of biological terms in documents to speed the searching process. Query expansion is used to infer semantically related terms to asserted terms. It increases the search meaningful results using the term synonyms and term relationships. The system uses a ranking method to order the retrieved documents based on the ranking weights. The proposed system achieves researchers' needs to find documents that fit the asserted terms semantically.

  9. Inspection technique of latent flaws on fine polished glass substrates using stress-induced light scattering method

    NASA Astrophysics Data System (ADS)

    Sakata, Yoshitaro; Sakai, Kazufumi; Nonaka, Kazuhiro

    2014-05-01

    The fine polishing technique, e.g. Chemical Mechanical Polishing treatment (CMP), is one of the most important techniques in the glass substrate manufacturing. However, mechanical interaction, e.g. friction, occurs between the abrasive and the surface of substrates. Therefore, latent flaws are formed in the surfaces of glass substrates depending on the polishing condition. In the case of the cleaning process of the glass substrate in which the latent flaws existed, latent flaws become obvious because glass surfaces were eaten away by chemical interaction of cleaning liquid. Therefore, latent flaws are the cause of decrease the yield of products. In general, non-destructive inspection techniques, e.g. light scattering method, foreign matter on the surface of glass substrates. Though, it is difficult to detect the latent flaws by these method, because these are closed. The present authors propose a novel inspection technique of latent flaws which occurred by the fine polishing technique, using light scattering method with stress concentration (Stress-Induced Light scattering Method; SILSM). SILSM is possible to classify and separately detect latent flaws and particles on the surfaces. Samples are deformed by the actuator and stress concentrations are occurred around the tip of latent flaws. By photo-elastic effect, the refractive index of around the tip of latent flaws is changed. And then, changed refractive index is detected by cooled CCD camera as the light scattering intensity. In this report, applying SILSM to glass substrates, latent flaws on the surface of glass substrates are detected non-destructively, and the usefulness of SILSM is evaluated as novel inspection technique of latent flaws.

  10. The semantic structure of the UMLS Metathesaurus.

    PubMed

    Nelson, S J; Fuller, L F; Erlbaum, M S; Tuttle, M S; Sherertz, D D; Olson, N E

    1992-01-01

    Meta-1.1, the UMLS metathesaurus, represents medical knowledge in the forms of names of concepts and links between those concepts. The representations of the semantic neighborhood of a concept can be thought of as dimensions of the property of semantic locality and include term information (broader, narrower, or otherwise related), the contextual information (parent-child, siblings in a hierarchy), the semantic types, and the co-occurrence data (links discovered empirically from concepts used to index the medical literature.) The degree of redundancy of each of these dimensions was investigated by reviewing the extent of multiple presentations of concepts which appear as related to a given concept. The degree of overlap was surprisingly small. While the co-occurrence data finds some of the links represented by other dimensions, those links are but minute fractions of the vast amount of co-occurrence derived links. Because parent-child relationships are often subsumptive (or categorical) in nature, it might be expected that siblings usually share the same semantic types. While true in the aggregate, the wide variance in percent of types shared may reflect the intended usages of the source vocabularies. Noun phrases were extracted from the definitions of 40 concepts in Meta-1 in order to assess systematically the coverage of important concepts by Meta-1, and to assess whether the links between these definitional concepts, which may have special value, and the concept being defined were indeed present. Out of 161 of these definitional concepts, 29 were not represented in Meta-1, and 37 of those represented in Meta-1 had no direct link to the concept they were defining.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:1482952

  11. Personal semantics: at the crossroads of semantic and episodic memory.

    PubMed

    Renoult, Louis; Davidson, Patrick S R; Palombo, Daniela J; Moscovitch, Morris; Levine, Brian

    2012-11-01

    Declarative memory is usually described as consisting of two systems: semantic and episodic memory. Between these two poles, however, may lie a third entity: personal semantics (PS). PS concerns knowledge of one's past. Although typically assumed to be an aspect of semantic memory, it is essentially absent from existing models of knowledge. Furthermore, like episodic memory (EM), PS is idiosyncratically personal (i.e., not culturally-shared). We show that, depending on how it is operationalized, the neural correlates of PS can look more similar to semantic memory, more similar to EM, or dissimilar to both. We consider three different perspectives to better integrate PS into existing models of declarative memory and suggest experimental strategies for disentangling PS from semantic and episodic memory.

  12. Latent IBP Compound Dirichlet Allocation.

    PubMed

    Archambeau, Cedric; Lakshminarayanan, Balaji; Bouchard, Guillaume

    2015-02-01

    We introduce the four-parameter IBP compound Dirichlet process (ICDP), a stochastic process that generates sparse non-negative vectors with potentially an unbounded number of entries. If we repeatedly sample from the ICDP we can generate sparse matrices with an infinite number of columns and power-law characteristics. We apply the four-parameter ICDP to sparse nonparametric topic modelling to account for the very large number of topics present in large text corpora and the power-law distribution of the vocabulary of natural languages. The model, which we call latent IBP compound Dirichlet allocation (LIDA), allows for power-law distributions, both, in the number of topics summarising the documents and in the number of words defining each topic. It can be interpreted as a sparse variant of the hierarchical Pitman-Yor process when applied to topic modelling. We derive an efficient and simple collapsed Gibbs sampler closely related to the collapsed Gibbs sampler of latent Dirichlet allocation (LDA), making the model applicable in a wide range of domains. Our nonparametric Bayesian topic model compares favourably to the widely used hierarchical Dirichlet process and its heavy tailed version, the hierarchical Pitman-Yor process, on benchmark corpora. Experiments demonstrate that accounting for the power-distribution of real data is beneficial and that sparsity provides more interpretable results. PMID:26353244

  13. Information-Theoretic Latent Distribution Modeling: Distinguishing Discrete and Continuous Latent Variable Models

    ERIC Educational Resources Information Center

    Markon, Kristian E.; Krueger, Robert F.

    2006-01-01

    Distinguishing between discrete and continuous latent variable distributions has become increasingly important in numerous domains of behavioral science. Here, the authors explore an information-theoretic approach to latent distribution modeling, in which the ability of latent distribution models to represent statistical information in observed…

  14. Optimization-Based Model Fitting for Latent Class and Latent Profile Analyses

    ERIC Educational Resources Information Center

    Huang, Guan-Hua; Wang, Su-Mei; Hsu, Chung-Chu

    2011-01-01

    Statisticians typically estimate the parameters of latent class and latent profile models using the Expectation-Maximization algorithm. This paper proposes an alternative two-stage approach to model fitting. The first stage uses the modified k-means and hierarchical clustering algorithms to identify the latent classes that best satisfy the…

  15. Semi-Nonparametric Methods for Detecting Latent Non-Normality: A Fusion of Latent Trait and Ordered Latent Class Modeling

    ERIC Educational Resources Information Center

    Schmitt, J. Eric; Mehta, Paras D.; Aggen, Steven H.; Kubarych, Thomas S.; Neale, Michael C.

    2006-01-01

    Ordered latent class analysis (OLCA) can be used to approximate unidimensional latent distributions. The main objective of this study is to evaluate the method of OLCA in detecting non-normality of an unobserved continuous variable (i.e., a common factor) used to explain the covariation between dichotomous item-level responses. Using simulation,…

  16. Semantic Roles and Grammatical Relations.

    ERIC Educational Resources Information Center

    Van Valin, Robert D., Jr.

    The nature of semantic roles and grammatical relations are explored from the perspective of Role and Reference Grammar (RRG). It is proposed that unraveling the relational aspects of grammar involves the recognition that semantic roles fall into two types, thematic relations and macroroles, and that grammatical relations are not universal and are…

  17. Semantic Focus and Sentence Comprehension.

    ERIC Educational Resources Information Center

    Cutler, Anne; Fodor, Jerry A.

    1979-01-01

    Reaction time to detect a phoneme target in a sentence was faster when the target-containing word formed part of the semantic focus of the sentence. Sentence understanding was facilitated by rapid identification of focused information. Active search for accented words can be interpreted as a search for semantic focus. (Author/RD)

  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. 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.

  20. Semantic Analysis in Machine Translation.

    ERIC Educational Resources Information Center

    Skorokhodko, E. F.

    1970-01-01

    In many cases machine-translation does not produce satisfactory results within the framework of purely formal (morphological and syntaxic) analysis, particularly, in the case of syntaxic and lexical homonomy. An algorithm for syntaxic-semantic analysis is proposed, and its principles of operation are described. The syntaxico-semantic structure is…

  1. A semantically-aided approach for online annotation and retrieval of medical images.

    PubMed

    Kyriazos, George K; Gerostathopoulos, Ilias Th; Kolias, Vassileios D; Stoitsis, John S; Nikita, Konstantina S

    2011-01-01

    The need for annotating the continuously increasing volume of medical image data is recognized from medical experts for a variety of purposes, regardless if this is medical practice, research or education. The rich information content latent in medical images can be made explicit and formal with the use of well-defined ontologies. Evolution of the Semantic Web now offers a unique opportunity of a web-based, service-oriented approach. Remote access to FMA and ICD-10 reference ontologies provides the ontological annotation framework. The proposed system utilizes this infrastructure to provide a customizable and robust annotation procedure. It also provides an intelligent search mechanism indicating the advantages of semantic over keyword search. The common representation layer discussed facilitates interoperability between institutions and systems, while semantic content enables inference and knowledge integration.

  2. 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.

  3. The Ontological Perspectives of the Semantic Web and the Metadata Harvesting Protocol: Applications of Metadata for Improving Web Search.

    ERIC Educational Resources Information Center

    Fast, Karl V.; Campbell, D. Grant

    2001-01-01

    Compares the implied ontological frameworks of the Open Archives Initiative Protocol for Metadata Harvesting and the World Wide Web Consortium's Semantic Web. Discusses current search engine technology, semantic markup, indexing principles of special libraries and online databases, and componentization and the distinction between data and…

  4. Latent Information in Fluency Lists Predicts Functional Decline in Persons at Risk for Alzheimer Disease

    PubMed Central

    Clark, D.G.; Kapur, P.; Geldmacher, D.S.; Brockington, J.C.; Harrell, L.; DeRamus, T.P.; Blanton, P.D.; Lokken, K.; Nicholas, A.P.; Marson, D.C.

    2014-01-01

    Objective We constructed random forest classifiers employing either the traditional method of scoring semantic fluency word lists or new methods. These classifiers were then compared in terms of their ability to diagnose Alzheimer disease (AD) or to prognosticate among individuals along the continuum from cognitively normal (CN) through mild cognitive impairment (MCI) to AD. Method Semantic fluency lists from 44 cognitively normal elderly individuals, 80 MCI patients, and 41 AD patients were transcribed into electronic text files and scored by four methods: traditional raw scores, clustering and switching scores, “generalized” versions of clustering and switching, and a method based on independent components analysis (ICA). Random forest classifiers based on raw scores were compared to “augmented” classifiers that incorporated newer scoring methods. Outcome variables included AD diagnosis at baseline, MCI conversion, increase in Clinical Dementia Rating-Sum of Boxes (CDR-SOB) score, or decrease in Financial Capacity Instrument (FCI) score. ROC curves were constructed for each classifier and the area under the curve (AUC) was calculated. We compared AUC between raw and augmented classifiers using Delong’s test and assessed validity and reliability of the augmented classifier. Results Augmented classifiers outperformed classifiers based on raw scores for the outcome measures AD diagnosis (AUC 0.97 vs. 0.95), MCI conversion (AUC 0.91 vs. 0.77), CDR-SOB increase (AUC 0.90 vs. 0.79), and FCI decrease (AUC 0.89 vs. 0.72). Measures of validity and stability over time support the use of the method. Conclusion Latent information in semantic fluency word lists is useful for predicting cognitive and functional decline among elderly individuals at increased risk for developing AD. Modern machine learning methods may incorporate latent information to enhance the diagnostic value of semantic fluency raw scores. These methods could yield information valuable for patient

  5. Indexing Learning Objects: Vocabularies and Empirical Investigation of Consistency

    ERIC Educational Resources Information Center

    Kabel, Suzanne; De Hoog, Robert; Wielinga, Bob; Anjewierden, Anjo

    2004-01-01

    In addition to the LOM standard and instructional design specifications, as well as domain specific indexing vocabularies, a structured indexing vocabulary for the more elementary learning objects is advisable in order to support retrieval tasks of developers. Furthermore, because semantic indexing is seen as a difficult task, three issues…

  6. Socioeconomic gradients in immune response to latent infection.

    PubMed

    Dowd, Jennifer Beam; Haan, Mary N; Blythe, Lynn; Moore, Kari; Aiello, Allison E

    2008-01-01

    There is a strong relation between socioeconomic position and health outcomes, although the mechanisms are poorly understood. The authors used data from 1,503 California participants in the 1998-1999 Sacramento Area Latino Study on Aging aged 60-100 years to ask whether socioeconomic position is related to immune function as measured by the body's ability to keep latent herpesvirus antibody levels in a quiescent state. Individuals with lower educational levels had significantly higher levels of immunoglobulin G antibodies to cytomegalovirus and herpes simplex virus type 1. The odds ratio for being in a higher tertile of cytomegalovirus antibodies was 1.54 (95% confidence interval: 1.18, 2.01) for those in the lowest educational group, and the odds ratio for being in a higher tertile of herpes simplex virus type 1 was 1.63 (95% confidence interval: 1.25, 2.13). The relation between education and cytomegalovirus and herpes simplex virus type 1 antibody levels remained strong after controlling for baseline health conditions, smoking status, and body mass index. This is the first study known to show a relation between socioeconomic position and immune response to latent infection. It provides suggestive evidence that modulation of the immune system via latent infections may play a role in the observed associations between socioeconomic position and disease.

  7. A Vernacular for Linear Latent Growth Models

    ERIC Educational Resources Information Center

    Hancock, Gregory R.; Choi, Jaehwa

    2006-01-01

    In its most basic form, latent growth modeling (latent curve analysis) allows an assessment of individuals' change in a measured variable X over time. For simple linear models, as with other growth models, parameter estimates associated with the a construct (amount of X at a chosen temporal reference point) and b construct (growth in X per unit…

  8. Insidious Structural Errors in Latent Variable Models.

    ERIC Educational Resources Information Center

    Pohlmann, John T.

    1993-01-01

    Nonlinear relationships and latent variable assumptions can lead to serious specification errors in structural models. A quadratic relationship, described by a linear structural model with a latent variable, is shown to have less predictive validity than a simple manifest variable regression model. Advocates the use of simpler preliminary…

  9. Latent Memory for Sensitization in "Aplysia"

    ERIC Educational Resources Information Center

    Philips, Gary T.; Tzvetkova, Ekaterina I.; Marinesco, Stephane; Carew, Thomas J.

    2006-01-01

    In the analysis of memory it is commonly observed that, even after a memory is apparently forgotten, its latent presence can still be revealed in a subsequent learning task. Although well established on a behavioral level, the mechanisms underlying latent memory are not well understood. To begin to explore these mechanisms, we have used "Aplysia,"…

  10. Latent Heating Structures Derived from TRMM

    NASA Technical Reports Server (NTRS)

    Tao, W.-K.; Smith, E. A.; Adler, R.; Hou, A.; Kakar, R.; Krishnamurti, T.; Kummerow, C.; Lang, S.; Olson, W.; Satoh, S.

    2004-01-01

    Rainfall is the fundamental variable within the Earth's hydrological cycle because it is both the main forcing term leading to variations in continental and oceanic surface water budgets. The vertical distribution of latent heat release, which is accompanied with rain, modulates large-scale meridional and zonal circulations within the tropics as well as modifying the energetic efficiency of mid-latitude weather systems. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water.This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission 0. The TRMM observatory, whose development was a joint US-Japan space endeavor, was launched in November 1997. TRMM measurements provide an accurate account of rainfall over the global tropics, information which can be .used to estimate the four-dimensional structure of latent heating across the entire tropical and sub-tropical regions. Various algorithm methodologies for estimating latent heating based on rain rate measurements from TRMM observations are described. The strengths and weaknesses of these algorithms, as well as the latent heating products generated by these algorithms, are also discussed along with validation analyses of the products. The investigation paper provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, and concludes with remarks designed to stimulate further research on latent heating retrieval

  11. Consequences of Fitting Nonidentified Latent Class Models

    ERIC Educational Resources Information Center

    Abar, Beau; Loken, Eric

    2012-01-01

    Latent class models are becoming more popular in behavioral research. When models with a large number of latent classes relative to the number of manifest indicators are estimated, researchers must consider the possibility that the model is not identified. It is not enough to determine that the model has positive degrees of freedom. A well-known…

  12. "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…

  13. Epstein–Barr virus latent genes

    PubMed Central

    Kang, Myung-Soo; Kieff, Elliott

    2015-01-01

    Latent Epstein–Barr virus (EBV) infection has a substantial role in causing many human disorders. The persistence of these viral genomes in all malignant cells, yet with the expression of limited latent genes, is consistent with the notion that EBV latent genes are important for malignant cell growth. While the EBV-encoded nuclear antigen-1 (EBNA-1) and latent membrane protein-2A (LMP-2A) are critical, the EBNA-leader proteins, EBNA-2, EBNA-3A, EBNA-3C and LMP-1, are individually essential for in vitro transformation of primary B cells to lymphoblastoid cell lines. EBV-encoded RNAs and EBNA-3Bs are dispensable. In this review, the roles of EBV latent genes are summarized. PMID:25613728

  14. Latent classiness and other mixtures.

    PubMed

    Neale, Michael C

    2014-05-01

    The aim of this article is to laud Lindon Eaves' role in the development of mixture modeling in genetic studies. The specification of models for mixture distributions was very much in its infancy when Professor Eaves implemented it in his own FORTRAN programs, and extended it to data collected from relatives such as twins. It was his collaboration with the author of this article which led to the first implementation of mixture distribution modeling in a general-purpose structural equation modeling program, Mx, resulting in a 1996 article on linkage analysis in Behavior Genetics. Today, the popularity of these methods continues to grow, encompassing methods for genetic association, latent class analysis, growth curve mixture modeling, factor mixture modeling, regime switching, marginal maximum likelihood, genotype by environment interaction, variance component twin modeling in the absence of zygosity information, and many others. This primarily historical article concludes with some consideration of some possible future developments. PMID:24477932

  15. Body-part-specific representations of semantic noun categories.

    PubMed

    Carota, Francesca; Moseley, Rachel; Pulvermüller, Friedemann

    2012-06-01

    Word meaning processing in the brain involves ventrolateral temporal cortex, but a semantic contribution of the dorsal stream, especially frontocentral sensorimotor areas, has been controversial. We here examine brain activation during passive reading of object-related nouns from different semantic categories, notably animal, food, and tool words, matched for a range of psycholinguistic features. Results show ventral stream activation in temporal cortex along with category-specific activation patterns in both ventral and dorsal streams, including sensorimotor systems and adjacent pFC. Precentral activation reflected action-related semantic features of the word categories. Cortical regions implicated in mouth and face movements were sparked by food words, and hand area activation was seen for tool words, consistent with the actions implicated by the objects the words are used to speak about. Furthermore, tool words specifically activated the right cerebellum, and food words activated the left orbito-frontal and fusiform areas. We discuss our results in the context of category-specific semantic deficits in the processing of words and concepts, along with previous neuroimaging research, and conclude that specific dorsal and ventral areas in frontocentral and temporal cortex index visual and affective-emotional semantic attributes of object-related nouns and action-related affordances of their referent objects.

  16. Body-part-specific representations of semantic noun categories.

    PubMed

    Carota, Francesca; Moseley, Rachel; Pulvermüller, Friedemann

    2012-06-01

    Word meaning processing in the brain involves ventrolateral temporal cortex, but a semantic contribution of the dorsal stream, especially frontocentral sensorimotor areas, has been controversial. We here examine brain activation during passive reading of object-related nouns from different semantic categories, notably animal, food, and tool words, matched for a range of psycholinguistic features. Results show ventral stream activation in temporal cortex along with category-specific activation patterns in both ventral and dorsal streams, including sensorimotor systems and adjacent pFC. Precentral activation reflected action-related semantic features of the word categories. Cortical regions implicated in mouth and face movements were sparked by food words, and hand area activation was seen for tool words, consistent with the actions implicated by the objects the words are used to speak about. Furthermore, tool words specifically activated the right cerebellum, and food words activated the left orbito-frontal and fusiform areas. We discuss our results in the context of category-specific semantic deficits in the processing of words and concepts, along with previous neuroimaging research, and conclude that specific dorsal and ventral areas in frontocentral and temporal cortex index visual and affective-emotional semantic attributes of object-related nouns and action-related affordances of their referent objects. PMID:22390464

  17. Enhancing clinical concept extraction with distributional semantics

    PubMed Central

    Cohen, Trevor; Wu, Stephen; Gonzalez, Graciela

    2011-01-01

    Extracting concepts (such as drugs, symptoms, and diagnoses) from clinical narratives constitutes a basic enabling technology to unlock the knowledge within and support more advanced reasoning applications such as diagnosis explanation, disease progression modeling, and intelligent analysis of the effectiveness of treatment. The recent release of annotated training sets of de-identified clinical narratives has contributed to the development and refinement of concept extraction methods. However, as the annotation process is labor-intensive, training data are necessarily limited in the concepts and concept patterns covered, which impacts the performance of supervised machine learning applications trained with these data. This paper proposes an approach to minimize this limitation by combining supervised machine learning with empirical learning of semantic relatedness from the distribution of the relevant words in additional unannotated text. The approach uses a sequential discriminative classifier (Conditional Random Fields) to extract the mentions of medical problems, treatments and tests from clinical narratives. It takes advantage of all Medline abstracts indexed as being of the publication type “clinical trials” to estimate the relatedness between words in the i2b2/VA training and testing corpora. In addition to the traditional features such as dictionary matching, pattern matching and part-of-speech tags, we also used as a feature words that appear in similar contexts to the word in question (that is, words that have a similar vector representation measured with the commonly used cosine metric, where vector representations are derived using methods of distributional semantics). To the best of our knowledge, this is the first effort exploring the use of distributional semantics, the semantics derived empirically from unannotated text often using vector space models, for a sequence classification task such as concept extraction. Therefore, we first

  18. Enhancing clinical concept extraction with distributional semantics.

    PubMed

    Jonnalagadda, Siddhartha; Cohen, Trevor; Wu, Stephen; Gonzalez, Graciela

    2012-02-01

    Extracting concepts (such as drugs, symptoms, and diagnoses) from clinical narratives constitutes a basic enabling technology to unlock the knowledge within and support more advanced reasoning applications such as diagnosis explanation, disease progression modeling, and intelligent analysis of the effectiveness of treatment. The recent release of annotated training sets of de-identified clinical narratives has contributed to the development and refinement of concept extraction methods. However, as the annotation process is labor-intensive, training data are necessarily limited in the concepts and concept patterns covered, which impacts the performance of supervised machine learning applications trained with these data. This paper proposes an approach to minimize this limitation by combining supervised machine learning with empirical learning of semantic relatedness from the distribution of the relevant words in additional unannotated text. The approach uses a sequential discriminative classifier (Conditional Random Fields) to extract the mentions of medical problems, treatments and tests from clinical narratives. It takes advantage of all Medline abstracts indexed as being of the publication type "clinical trials" to estimate the relatedness between words in the i2b2/VA training and testing corpora. In addition to the traditional features such as dictionary matching, pattern matching and part-of-speech tags, we also used as a feature words that appear in similar contexts to the word in question (that is, words that have a similar vector representation measured with the commonly used cosine metric, where vector representations are derived using methods of distributional semantics). To the best of our knowledge, this is the first effort exploring the use of distributional semantics, the semantics derived empirically from unannotated text often using vector space models, for a sequence classification task such as concept extraction. Therefore, we first experimented

  19. Enhancing clinical concept extraction with distributional semantics.

    PubMed

    Jonnalagadda, Siddhartha; Cohen, Trevor; Wu, Stephen; Gonzalez, Graciela

    2012-02-01

    Extracting concepts (such as drugs, symptoms, and diagnoses) from clinical narratives constitutes a basic enabling technology to unlock the knowledge within and support more advanced reasoning applications such as diagnosis explanation, disease progression modeling, and intelligent analysis of the effectiveness of treatment. The recent release of annotated training sets of de-identified clinical narratives has contributed to the development and refinement of concept extraction methods. However, as the annotation process is labor-intensive, training data are necessarily limited in the concepts and concept patterns covered, which impacts the performance of supervised machine learning applications trained with these data. This paper proposes an approach to minimize this limitation by combining supervised machine learning with empirical learning of semantic relatedness from the distribution of the relevant words in additional unannotated text. The approach uses a sequential discriminative classifier (Conditional Random Fields) to extract the mentions of medical problems, treatments and tests from clinical narratives. It takes advantage of all Medline abstracts indexed as being of the publication type "clinical trials" to estimate the relatedness between words in the i2b2/VA training and testing corpora. In addition to the traditional features such as dictionary matching, pattern matching and part-of-speech tags, we also used as a feature words that appear in similar contexts to the word in question (that is, words that have a similar vector representation measured with the commonly used cosine metric, where vector representations are derived using methods of distributional semantics). To the best of our knowledge, this is the first effort exploring the use of distributional semantics, the semantics derived empirically from unannotated text often using vector space models, for a sequence classification task such as concept extraction. Therefore, we first experimented

  20. Latent Heating from TRMM Satellite Measurements

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Smith, E. A.; Adler, R.; Haddad, Z.; Hou, A.; Iguchi, T.; Kakar, R.; Krishnamurti, T.; Kummerow, C.; Lang, S.

    2004-01-01

    Rainfall production is the fundamental variable within the Earth's hydrological cycle because it is both the principal forcing term in surface water budgets and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the tropics - as well as modifying the energetic efficiencies of midlatitude weather systems. This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) satellite observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional account of rainfall over the global tropics and sub-tropics, information which can be used to estimate the space-time structure of latent heating across the Earth's low latitudes. The paper examines how the observed TRMM distribution of rainfall has advanced an understanding of the global water and energy cycle and its consequent relationship to the atmospheric general circulation and climate via latent heat release. A set of algorithm methodologies that are being used to estimate latent heating based on rain rate retrievals from the TRMM observations are described. The characteristics of these algorithms and the latent heating products that can be generated from them are also described, along with validation analyses of the heating products themselves. Finally, the investigation provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

  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. 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.

  4. Semantic perception for ground robotics

    NASA Astrophysics Data System (ADS)

    Hebert, M.; Bagnell, J. A.; Bajracharya, M.; Daniilidis, K.; Matthies, L. H.; Mianzo, L.; Navarro-Serment, L.; Shi, J.; Wellfare, M.

    2012-06-01

    Semantic perception involves naming objects and features in the scene, understanding the relations between them, and understanding the behaviors of agents, e.g., people, and their intent from sensor data. Semantic perception is a central component of future UGVs to provide representations which 1) can be used for higher-level reasoning and tactical behaviors, beyond the immediate needs of autonomous mobility, and 2) provide an intuitive description of the robot's environment in terms of semantic elements that can shared effectively with a human operator. In this paper, we summarize the main approaches that we are investigating in the RCTA as initial steps toward the development of perception systems for UGVs.

  5. 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.

  6. 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.

  7. Scalable Medical Image Understanding by Fusing Cross-Modal Object Recognition with Formal Domain Semantics

    NASA Astrophysics Data System (ADS)

    Möller, Manuel; Sintek, Michael; Buitelaar, Paul; Mukherjee, Saikat; Zhou, Xiang Sean; Freund, Jörg

    Recent advances in medical imaging technology have dramatically increased the amount of clinical image data. In contrast, techniques for efficiently exploiting the rich semantic information in medical images have evolved much slower. Despite the research outcomes in image understanding, current image databases are still indexed by manually assigned subjective keywords instead of the semantics of the images. Indeed, most current content-based image search applications index image features that do not generalize well and use inflexible queries. This slow progress is due to the lack of scalable and generic information representation systems which can abstract over the high dimensional nature of medical images as well as semantically model the results of object recognition techniques. We propose a system combining medical imaging information with ontological formalized semantic knowledge that provides a basis for building universal knowledge repositories and gives clinicians fully cross-lingual and cross-modal access to biomedical information.

  8. WORD STATISTICS IN THE GENERATION OF SEMANTIC TOOLS FOR INFORMATION SYSTEMS.

    ERIC Educational Resources Information Center

    STONE, DON C.

    ONE OF THE PROBLEMS IN INFORMATION STORAGE AND RETRIEVAL SYSTEMS OF TECHNICAL DOCUMENTS IS THE INTERPRETATION OF WORDS USED TO INDEX DOCUMENTS. SEMANTIC TOOLS, DEFINED AS CHANNELS FOR THE COMMUNICATION OF WORD MEANINGS BETWEEN TECHNICAL EXPERTS, DOCUMENT INDEXERS, AND SEARCHERS, PROVIDE ONE METHOD OF DEALING WITH THE PROBLEM OF MULTIPLE…

  9. Orientation field estimation for latent fingerprint enhancement.

    PubMed

    Feng, Jianjiang; Zhou, Jie; Jain, Anil K

    2013-04-01

    Identifying latent fingerprints is of vital importance for law enforcement agencies to apprehend criminals and terrorists. Compared to live-scan and inked fingerprints, the image quality of latent fingerprints is much lower, with complex image background, unclear ridge structure, and even overlapping patterns. A robust orientation field estimation algorithm is indispensable for enhancing and recognizing poor quality latents. However, conventional orientation field estimation algorithms, which can satisfactorily process most live-scan and inked fingerprints, do not provide acceptable results for most latents. We believe that a major limitation of conventional algorithms is that they do not utilize prior knowledge of the ridge structure in fingerprints. Inspired by spelling correction techniques in natural language processing, we propose a novel fingerprint orientation field estimation algorithm based on prior knowledge of fingerprint structure. We represent prior knowledge of fingerprints using a dictionary of reference orientation patches. which is constructed using a set of true orientation fields, and the compatibility constraint between neighboring orientation patches. Orientation field estimation for latents is posed as an energy minimization problem, which is solved by loopy belief propagation. Experimental results on the challenging NIST SD27 latent fingerprint database and an overlapped latent fingerprint database demonstrate the advantages of the proposed orientation field estimation algorithm over conventional algorithms.

  10. Attentional sensitization of unconscious cognition: task sets modulate subsequent masked semantic priming.

    PubMed

    Kiefer, Markus; Martens, Ulla

    2010-08-01

    According to classical theories, automatic processes are autonomous and independent of higher level cognitive influence. In contrast, the authors propose that automatic processing depends on attentional sensitization of task-congruent processing pathways. In 3 experiments, the authors tested this hypothesis with a modified masked semantic priming paradigm during a lexical decision task by measuring event-related potentials (ERPs): Before masked prime presentation, participants attended an induction task either to semantic or perceptual stimulus features designed to activate a semantic or perceptual task set, respectively. Semantic priming effects on the N400 ERP component, an electrophysiological index of semantic processing, were obtained when a semantic task set was induced immediately before subliminal prime presentation, whereas a previously induced perceptual task set attenuated N400 priming. Across experiments, comparable results were obtained regardless of the difficulty level and the verbal or nonverbal nature of the induction tasks. In line with the proposed attentional sensitization model, unconscious semantic processing is enhanced by a semantic and attenuated by a perceptual task set. Hence, automatic processing of unconscious stimuli is susceptible to top-down control for optimizing goal-related information processing. PMID:20677895

  11. Predictive Inference Using Latent Variables with Covariates*

    PubMed Central

    Schofield, Lynne Steuerle; Junker, Brian; Taylor, Lowell J.; Black, Dan A.

    2014-01-01

    Plausible Values (PVs) are a standard multiple imputation tool for analysis of large education survey data that measures latent proficiency variables. When latent proficiency is the dependent variable, we reconsider the standard institutionally-generated PV methodology and find it applies with greater generality than shown previously. When latent proficiency is an independent variable, we show that the standard institutional PV methodology produces biased inference because the institutional conditioning model places restrictions on the form of the secondary analysts’ model. We offer an alternative approach that avoids these biases based on the mixed effects structural equations (MESE) model of Schofield (2008). PMID:25231627

  12. 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)

  13. 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.

  14. Semantic priming from crowded words.

    PubMed

    Yeh, Su-Ling; He, Sheng; Cavanagh, Patrick

    2012-06-01

    Vision in a cluttered scene is extremely inefficient. This damaging effect of clutter, known as crowding, affects many aspects of visual processing (e.g., reading speed). We examined observers' processing of crowded targets in a lexical decision task, using single-character Chinese words that are compact but carry semantic meaning. Despite being unrecognizable and indistinguishable from matched nonwords, crowded prime words still generated robust semantic-priming effects on lexical decisions for test words presented in isolation. Indeed, the semantic-priming effect of crowded primes was similar to that of uncrowded primes. These findings show that the meanings of words survive crowding even when the identities of the words do not, suggesting that crowding does not prevent semantic activation, a process that may have evolved in the context of a cluttered visual environment.

  15. Semantic Similarities between a Keyword Database and a Controlled Vocabulary Database: An Investigation in the Antibiotic Resistance Literature.

    ERIC Educational Resources Information Center

    Qin, Jian

    2000-01-01

    Explores similarities or dissimilarities between citation-semantic and analytic indexing based on a study of records in the Science Citation Index and MEDLINE databases on antibiotic resistance in pneumonia. Concludes that disparate indexing terms may be an advantage for better recall and precision in information retrieval. (Contains 42…

  16. 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.

  17. Stress-induced light scattering method for the detection of latent flaws on fine polished glass substrates.

    PubMed

    Sakata, Y; Sakai, K; Nonaka, K

    2014-08-01

    Fine polishing techniques, such as the chemical mechanical polishing treatment, are one of the most important technique to glass substrate manufacturing. Mechanical interaction in the form of friction occurs between the abrasive and the substrate surface during polishing, which may cause formation of latent flaws on the glass substrate surface. Fine polishing-induced latent flaws may become obvious during a subsequent cleaning process if glass surfaces are corroded away by chemical interaction with the cleaning liquid. Latent flaws thus reduce product yield. In general, non-destructive inspection techniques, such as the light-scattering methods, used to detect foreign matters on the glass substrate surface. However, it is difficult to detect latent flaws by these methods because the flaws remain closed. Authors propose a novel inspection technique for fine polishing-induced latent flaws by combining the light scattering method with stress effects, referred to as the stress-induced light scattering method (SILSM). SILSM is able to distinguish between latent flaws and particles on the surface. In this method, samples are deformed by an actuator and stress effects are induced around the tips of latent flaws. Due to the photoelastic effect, the refractive index of the material around the tip of a latent flaw is changed. This changed refractive index is in turn detected by a cooled charge-coupled device camera as variations in light scattering intensity. In this report, surface latent flaws are detected non-destructively by applying SILSM to glass substrates, and the utility of SILSM evaluated as a novel inspection technique.

  18. Stress-induced light scattering method for the detection of latent flaws on fine polished glass substrates

    NASA Astrophysics Data System (ADS)

    Sakata, Y.; Sakai, K.; Nonaka, K.

    2014-08-01

    Fine polishing techniques, such as the chemical mechanical polishing treatment, are one of the most important technique to glass substrate manufacturing. Mechanical interaction in the form of friction occurs between the abrasive and the substrate surface during polishing, which may cause formation of latent flaws on the glass substrate surface. Fine polishing-induced latent flaws may become obvious during a subsequent cleaning process if glass surfaces are corroded away by chemical interaction with the cleaning liquid. Latent flaws thus reduce product yield. In general, non-destructive inspection techniques, such as the light-scattering methods, used to detect foreign matters on the glass substrate surface. However, it is difficult to detect latent flaws by these methods because the flaws remain closed. Authors propose a novel inspection technique for fine polishing-induced latent flaws by combining the light scattering method with stress effects, referred to as the stress-induced light scattering method (SILSM). SILSM is able to distinguish between latent flaws and particles on the surface. In this method, samples are deformed by an actuator and stress effects are induced around the tips of latent flaws. Due to the photoelastic effect, the refractive index of the material around the tip of a latent flaw is changed. This changed refractive index is in turn detected by a cooled charge-coupled device camera as variations in light scattering intensity. In this report, surface latent flaws are detected non-destructively by applying SILSM to glass substrates, and the utility of SILSM evaluated as a novel inspection technique.

  19. Semplore: An IR Approach to Scalable Hybrid Query of Semantic Web Data

    NASA Astrophysics Data System (ADS)

    Zhang, Lei; Liu, Qiaoling; Zhang, Jie; Wang, Haofen; Pan, Yue; Yu, Yong

    As an extension to the current Web, Semantic Web will not only contain structured data with machine understandable semantics but also textual information. While structured queries can be used to find information more precisely on the Semantic Web, keyword searches are still needed to help exploit textual information. It thus becomes very important that we can combine precise structured queries with imprecise keyword searches to have a hybrid query capability. In addition, due to the huge volume of information on the Semantic Web, the hybrid query must be processed in a very scalable way. In this paper, we define such a hybrid query capability that combines unary tree-shaped structured queries with keyword searches. We show how existing information retrieval (IR) index structures and functions can be reused to index semantic web data and its textual information, and how the hybrid query is evaluated on the index structure using IR engines in an efficient and scalable manner. We implemented this IR approach in an engine called Semplore. Comprehensive experiments on its performance show that it is a promising approach. It leads us to believe that it may be possible to evolve current web search engines to query and search the Semantic Web. Finally, we breifly describe how Semplore is used for searching Wikipedia and an IBM customer's product information.

  20. Retrieved Latent Heating from TRMM

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Smith, Eric A.; Houze Jr, Robert

    2008-01-01

    The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of precipitation formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the tropics with the associated latent heating (LH) accounting for three-fourths of the total heat energy available to the Earth's atmosphere. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. In the last decade, it has been established that standard products of LH from satellite measurements, particularly TRMM measurements, would be a valuable resource for scientific research and applications. Such products would enable new insights and investigations concerning the complexities of convection system life cycles, the diabatic heating controls and feedbacks related to meso-synoptic circulations and their forecasting, the relationship of tropical patterns of LH to the global circulation and climate, and strategies for improving cloud parameterizations in environmental prediction models. The status of retrieved TRMM LH products, TRMM LH inter-comparison and validation project, current TRMM LH applications and critic issues/action items (based on previous five TRMM LH workshops) is presented in this article.

  1. 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).

  2. Reactivation of Latent Viruses in Space

    NASA Technical Reports Server (NTRS)

    Pierson, D. L.; Mehta, S. K.; Tyring, S. K.; Lugg, D. J.

    1999-01-01

    Reactivation of latent viruses is an important health risk for people working and living in physically isolated extreme environments such as Antarctica and space. Preflight quarantine does not significantly reduce the risk associated with latent viruses, however, pharmaceutical countermeasures are available for some viruses. The molecular basis of latency is not fully understood, but physical and psychosocial stresses are known to initiate the reactivation of latent viruses. Presumably, stress induced changes in selected hormones lead to alterations in the cell- mediated immune (CMI) response resulting in increased shedding of latent viruses. Limited access to space makes the use of ground-based analogs essential. The Australian Antarctic stations serve as a good stress model and simulate many aspects of space flight. Closed environmental chambers have been used to simulate space flight since the Skylab missions and have also proven to be a valuable analog of selected aspects of space flight.

  3. Indexing Images.

    ERIC Educational Resources Information Center

    Rasmussen, Edie M.

    1997-01-01

    Focuses on access to digital image collections by means of manual and automatic indexing. Contains six sections: (1) Studies of Image Systems and their Use; (2) Approaches to Indexing Images; (3) Image Attributes; (4) Concept-Based Indexing; (5) Content-Based Indexing; and (6) Browsing in Image Retrieval. Contains 105 references. (AEF)

  4. Greedy learning of binary latent trees.

    PubMed

    Harmeling, Stefan; Williams, Christopher K I

    2011-06-01

    Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures is the latent trees, i.e., tree-structured distributions involving latent variables where the visible variables are leaves. These are also called hierarchical latent class (HLC) models. Zhang and Kocka proposed a search algorithm for learning such models in the spirit of Bayesian network structure learning. While such an approach can find good solutions, it can be computationally expensive. As an alternative, we investigate two greedy procedures: the BIN-G algorithm determines both the structure of the tree and the cardinality of the latent variables in a bottom-up fashion. The BIN-A algorithm first determines the tree structure using agglomerative hierarchical clustering, and then determines the cardinality of the latent variables as for BIN-G. We show that even with restricting ourselves to binary trees, we obtain HLC models of comparable quality to Zhang's solutions (in terms of cross-validated log-likelihood), while being generally faster to compute. This claim is validated by a comprehensive comparison on several data sets. Furthermore, we demonstrate that our methods are able to estimate interpretable latent structures on real-world data with a large number of variables. By applying our method to a restricted version of the 20 newsgroups data, these models turn out to be related to topic models, and on data from the PASCAL Visual Object Classes (VOC) 2007 challenge, we show how such treestructured models help us understand how objects co-occur in images. For reproducibility of all experiments in this paper, all code and data sets (or links to data) are available at http://people.kyb.tuebingen.mpg.de/harmeling/code/ltt-1.4.tar.

  5. Latent phenotypes pervade gene regulatory circuits

    PubMed Central

    2014-01-01

    Background Latent phenotypes are non-adaptive byproducts of adaptive phenotypes. They exist in biological systems as different as promiscuous enzymes and genome-scale metabolic reaction networks, and can give rise to evolutionary adaptations and innovations. We know little about their prevalence in the gene expression phenotypes of regulatory circuits, important sources of evolutionary innovations. Results Here, we study a space of more than sixteen million three-gene model regulatory circuits, where each circuit is represented by a genotype, and has one or more functions embodied in one or more gene expression phenotypes. We find that the majority of circuits with single functions have latent expression phenotypes. Moreover, the set of circuits with a given spectrum of functions has a repertoire of latent phenotypes that is much larger than that of any one circuit. Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit’s main functions. Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes. Conclusions Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation. PMID:24884746

  6. Semantic photo synthesis

    NASA Astrophysics Data System (ADS)

    Johnson, Matthew; Brostow, G. J.; Shotton, J.; Kwatra, V.; Cipolla, R.

    2007-02-01

    Composite images are synthesized from existing photographs by artists who make concept art, e.g. storyboards for movies or architectural planning. Current techniques allow an artist to fabricate such an image by digitally splicing parts of stock photographs. While these images serve mainly to "quickly" convey how a scene should look, their production is laborious. We propose a technique that allows a person to design a new photograph with substantially less effort. This paper presents a method that generates a composite image when a user types in nouns, such as "boat" and "sand." The artist can optionally design an intended image by specifying other constraints. Our algorithm formulates the constraints as queries to search an automatically annotated image database. The desired photograph, not a collage, is then synthesized using graph-cut optimization, optionally allowing for further user interaction to edit or choose among alternative generated photos. Our results demonstrate our contributions of (1) a method of creating specific images with minimal human effort, and (2) a combined algorithm for automatically building an image library with semantic annotations from any photo collection.

  7. The Latent Structure of Dictionaries.

    PubMed

    Vincent-Lamarre, Philippe; Massé, Alexandre Blondin; Lopes, Marcos; Lord, Mélanie; Marcotte, Odile; Harnad, Stevan

    2016-07-01

    How many words-and which ones-are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns out to be its Core, a "Strongly Connected Subset" of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the rest-the graph's "minimum feedback vertex set" or MinSet-is about 1% of the dictionary, about 15% of the Kernel, and part-Core/part-Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual-code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition. PMID:27424842

  8. Imprint of the ENSO on rainfall and latent heating variability over the Southern South China Sea from TRMM observations

    NASA Astrophysics Data System (ADS)

    Wang, Lei; Huang, Ke

    2016-04-01

    Analyses of the Tropical Rainfall Measuring Mission (TRMM) datasets revealed a prominent interannual variation in the convective-stratiform rainfall and latent heating over the southern South China Sea (SCS) during the winter monsoon between 1998 and 2010. Although the height of maximum latent heating remained nearly constant at around 7 km in all of the years, the year-to-year changes in the magnitudes of maximum latent heating over the region were noticeable. The interannual variations of the convective- stratiform rainfall and latent heating over the southern SCS were highly anti-correlated with the Niño-3 index, with more (less) rainfall and latent heating during La Niña (El Niño) years. Analysis of the large-scale environment revealed that years of active rainfall and latent heating corresponded to years of large deep convergence and relative humidity at 600 hPa. The moisture budget diagnosis indicated that the interannual variation of humidity at 600 hPa was largely modulated by the vertical moisture advection. The year-to-year changes in rainfall over the southern SCS were mainly caused by the interannual variations of the dynamic component associated with anomalous upward motions in the middle troposphere, while the interannual variations of the thermodynamic component associated with changes in surface specific humidity played a minor role. Larger latent heating over the southern SCS during La Niña years may possibly further enhance the local Hadley circulation over the SCS in the wintertime.

  9. From N400 to N300: variations in the timing of semantic processing with repetition.

    PubMed

    Renoult, Louis; Wang, Xiaoxiao; Calcagno, Vincent; Prévost, Marie; Debruille, J Bruno

    2012-05-15

    The present study aimed to explore the variations of semantic processing according to the number of target words (i.e., 4, 12 and 24) and according to the number of repetitions (i.e, 1 to 15). The number of targets had no impact on the N400 brain potential, the index of semantic processing, nor on the late positive component (LPC), an index of episodic encoding and retrieval. Analyses of the effects of the number of repetitions showed that the duration of semantic processes--assessed by measuring N400 latency--was linearly shortened along repetitions while their extent--as indexed by N400 amplitude--remained constant after the second presentation. In contrast, the extent of episodic processes--as indexed by LPC amplitude--was found to increase linearly with repetition. By showing that N400 latency may be much less stable than previously thought, these results bring new constraints on the functional correlates of this key stage in the processing of semantic information. They also suggest that semantic processes can be studied at high repetition rates whatever the number of target stimuli. Finally, our findings show that each episode of prior presentation has an impact on the late processing of a stimulus despite the absence of an explicit memory task.

  10. 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.

  11. Effective Web and Desktop Retrieval with Enhanced Semantic Spaces

    NASA Astrophysics Data System (ADS)

    Daoud, Amjad M.

    We describe the design and implementation of the NETBOOK prototype system for collecting, structuring and efficiently creating semantic vectors for concepts, noun phrases, and documents from a corpus of free full text ebooks available on the World Wide Web. Automatic generation of concept maps from correlated index terms and extracted noun phrases are used to build a powerful conceptual index of individual pages. To ensure scalabilty of our system, dimension reduction is performed using Random Projection [13]. Furthermore, we present a complete evaluation of the relative effectiveness of the NETBOOK system versus the Google Desktop [8].

  12. Semantic graphs and associative memories.

    PubMed

    Pomi, Andrés; Mizraji, Eduardo

    2004-12-01

    Graphs have been increasingly utilized in the characterization of complex networks from diverse origins, including different kinds of semantic networks. Human memories are associative and are known to support complex semantic nets; these nets are represented by graphs. However, it is not known how the brain can sustain these semantic graphs. The vision of cognitive brain activities, shown by modern functional imaging techniques, assigns renewed value to classical distributed associative memory models. Here we show that these neural network models, also known as correlation matrix memories, naturally support a graph representation of the stored semantic structure. We demonstrate that the adjacency matrix of this graph of associations is just the memory coded with the standard basis of the concept vector space, and that the spectrum of the graph is a code invariant of the memory. As long as the assumptions of the model remain valid this result provides a practical method to predict and modify the evolution of the cognitive dynamics. Also, it could provide us with a way to comprehend how individual brains that map the external reality, almost surely with different particular vector representations, are nevertheless able to communicate and share a common knowledge of the world. We finish presenting adaptive association graphs, an extension of the model that makes use of the tensor product, which provides a solution to the known problem of branching in semantic nets.

  13. Semantic graphs and associative memories

    NASA Astrophysics Data System (ADS)

    Pomi, Andrés; Mizraji, Eduardo

    2004-12-01

    Graphs have been increasingly utilized in the characterization of complex networks from diverse origins, including different kinds of semantic networks. Human memories are associative and are known to support complex semantic nets; these nets are represented by graphs. However, it is not known how the brain can sustain these semantic graphs. The vision of cognitive brain activities, shown by modern functional imaging techniques, assigns renewed value to classical distributed associative memory models. Here we show that these neural network models, also known as correlation matrix memories, naturally support a graph representation of the stored semantic structure. We demonstrate that the adjacency matrix of this graph of associations is just the memory coded with the standard basis of the concept vector space, and that the spectrum of the graph is a code invariant of the memory. As long as the assumptions of the model remain valid this result provides a practical method to predict and modify the evolution of the cognitive dynamics. Also, it could provide us with a way to comprehend how individual brains that map the external reality, almost surely with different particular vector representations, are nevertheless able to communicate and share a common knowledge of the world. We finish presenting adaptive association graphs, an extension of the model that makes use of the tensor product, which provides a solution to the known problem of branching in semantic nets.

  14. Latent Curve Models and Latent Change Score Models Estimated in R

    ERIC Educational Resources Information Center

    Ghisletta, Paolo; McArdle, John J.

    2012-01-01

    In recent years the use of the latent curve model (LCM) among researchers in social sciences has increased noticeably, probably thanks to contemporary software developments and the availability of specialized literature. Extensions of the LCM, like the the latent change score model (LCSM), have also increased in popularity. At the same time, the R…

  15. Unsupervised mining of frequent tags for clinical eligibility text indexing.

    PubMed

    Miotto, Riccardo; Weng, Chunhua

    2013-12-01

    Clinical text, such as clinical trial eligibility criteria, is largely underused in state-of-the-art medical search engines due to difficulties of accurate parsing. This paper proposes a novel methodology to derive a semantic index for clinical eligibility documents based on a controlled vocabulary of frequent tags, which are automatically mined from the text. We applied this method to eligibility criteria on ClinicalTrials.gov and report that frequent tags (1) define an effective and efficient index of clinical trials and (2) are unlikely to grow radically when the repository increases. We proposed to apply the semantic index to filter clinical trial search results and we concluded that frequent tags reduce the result space more efficiently than an uncontrolled set of UMLS concepts. Overall, unsupervised mining of frequent tags from clinical text leads to an effective semantic index for the clinical eligibility documents and promotes their computational reuse.

  16. Practical life log video indexing based on content and context

    NASA Astrophysics Data System (ADS)

    Tancharoen, Datchakorn; Yamasaki, Toshihiko; Aizawa, Kiyoharu

    2006-01-01

    Today, multimedia information has gained an important role in daily life and people can use imaging devices to capture their visual experiences. In this paper, we present our personal Life Log system to record personal experiences in form of wearable video and environmental data; in addition, an efficient retrieval system is demonstrated to recall the desirable media. We summarize the practical video indexing techniques based on Life Log content and context to detect talking scenes by using audio/visual cues and semantic key frames from GPS data. Voice annotation is also demonstrated as a practical indexing method. Moreover, we apply body media sensors to record continuous life style and use body media data to index the semantic key frames. In the experiments, we demonstrated various video indexing results which provided their semantic contents and showed Life Log visualizations to examine personal life effectively.

  17. Scene Classfication Based on the Semantic-Feature Fusion Fully Sparse Topic Model for High Spatial Resolution Remote Sensing Imagery

    NASA Astrophysics Data System (ADS)

    Zhu, Qiqi; Zhong, Yanfei; Zhang, Liangpei

    2016-06-01

    Topic modeling has been an increasingly mature method to bridge the semantic gap between the low-level features and high-level semantic information. However, with more and more high spatial resolution (HSR) images to deal with, conventional probabilistic topic model (PTM) usually presents the images with a dense semantic representation. This consumes more time and requires more storage space. In addition, due to the complex spectral and spatial information, a combination of multiple complementary features is proved to be an effective strategy to improve the performance for HSR image scene classification. But it should be noticed that how the distinct features are fused to fully describe the challenging HSR images, which is a critical factor for scene classification. In this paper, a semantic-feature fusion fully sparse topic model (SFF-FSTM) is proposed for HSR imagery scene classification. In SFF-FSTM, three heterogeneous features - the mean and standard deviation based spectral feature, wavelet based texture feature, and dense scale-invariant feature transform (SIFT) based structural feature are effectively fused at the latent semantic level. The combination of multiple semantic-feature fusion strategy and sparse based FSTM is able to provide adequate feature representations, and can achieve comparable performance with limited training samples. Experimental results on the UC Merced dataset and Google dataset of SIRI-WHU demonstrate that the proposed method can improve the performance of scene classification compared with other scene classification methods for HSR imagery.

  18. Latent Semantic Analysis As a Tool for Learner Positioning in Learning Networks for Lifelong Learning

    ERIC Educational Resources Information Center

    van Bruggen, Jan; Sloep, Peter; van Rosmalen, Peter; Brouns, Francis; Vogten, Hubert; Koper, Rob; Tattersall, Colin

    2004-01-01

    As we move towards distributed, self-organised learning networks for lifelong learning to which multiple providers contribute content, there is a need to develop new techniques to determine where learners can be positioned in these networks. Positioning requires us to map characteristics of the learner onto characteristics of learning materials…

  19. Automatic Evaluation for E-Learning Using Latent Semantic Analysis: A Use Case

    ERIC Educational Resources Information Center

    Farrus, Mireia; Costa-jussa, Marta R.

    2013-01-01

    Assessment in education allows for obtaining, organizing, and presenting information about how much and how well the student is learning. The current paper aims at analysing and discussing some of the most state-of-the-art assessment systems in education. Later, this work presents a specific use case developed for the Universitat Oberta de…

  20. A Semantic Web Blackboard System

    NASA Astrophysics Data System (ADS)

    McKenzie, Craig; Preece, Alun; Gray, Peter

    In this paper, we propose a Blackboard Architecture as a means for coordinating hybrid reasoning over the Semantic Web. We describe the components of traditional blackboard systems (Knowledge Sources, Blackboard, Controller) and then explain how we have enhanced these by incorporating some of the principles of the Semantic Web to pro- duce our Semantic Web Blackboard. Much of the framework is already in place to facilitate our research: the communication protocol (HTTP); the data representation medium (RDF); a rich expressive description language (OWL); and a method of writing rules (SWRL). We further enhance this by adding our own constraint based formalism (CIF/SWRL) into the mix. We provide an example walk-though of our test-bed system, the AKTive Workgroup Builder and Blackboard(AWB+B), illustrating the interaction and cooperation of the Knowledge Sources and providing some context as to how the solution is achieved. We conclude with the strengths and weaknesses of the architecture.

  1. Neurocybernetic basis of semantic processes.

    PubMed

    Restian, A

    1984-11-01

    Although semantics cannot be reduced to neurophysiology, it must have however a certain neurophysiologic basis and this paper deals with, that neurophysiologic basis which, in fact, has a neurocybernetic basis. The paper first approaches the relations between information and signification and their part within the nervous system's work. Then, it analyses semantic function discoverying neurocybernetic mechanisms which can be proper not only to the conventional signs but also to the objects and phenomena which in turn can play the sign's part. Finally, semantic levels of the nervous system, beginning with the most elementary level of unity, as letters are, and up to the level of the highest ideas and concepts the brain is working with, are described.

  2. 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.

  3. The semantics of biological forms.

    PubMed

    Albertazzi, Liliana; Canal, Luisa; Dadam, James; Micciolo, Rocco

    2014-01-01

    This study analyses how certain qualitative perceptual appearances of biological forms are correlated with expressions of natural language. Making use of the Osgood semantic differential, we presented the subjects with 32 drawings of biological forms and a list of 10 pairs of connotative adjectives to be put in correlations with them merely by subjective judgments. The principal components analysis made it possible to group the semantics of forms according to two distinct axes of variability: harmony and dynamicity. Specifically, the nonspiculed, nonholed, and flat forms were perceived as harmonic and static; the rounded ones were harmonic and dynamic. The elongated forms were somewhat disharmonious and somewhat static. The results suggest the existence in the general population of a correspondence between perceptual and semantic processes, and of a nonsymbolic relation between visual forms and their adjectival expressions in natural language.

  4. 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

  5. Ontology Matching with Semantic Verification.

    PubMed

    Jean-Mary, Yves R; Shironoshita, E Patrick; Kabuka, Mansur R

    2009-09-01

    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.

  6. 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.

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

    PubMed Central

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

    2011-01-01

    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. PMID:21632604

  8. Taxometrics, Polytomous Constructs, and the Comparison Curve Fit Index: A Monte Carlo Analysis

    ERIC Educational Resources Information Center

    Walters, Glenn D.; McGrath, Robert E.; Knight, Raymond A.

    2010-01-01

    The taxometric method effectively distinguishes between dimensional (1-class) and taxonic (2-class) latent structure, but there is virtually no information on how it responds to polytomous (3-class) latent structure. A Monte Carlo analysis showed that the mean comparison curve fit index (CCFI; Ruscio, Haslam, & Ruscio, 2006) obtained with 3…

  9. 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

  10. 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.

  11. 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

  12. Order effects in dynamic semantics.

    PubMed

    Graben, Peter Beim

    2014-01-01

    In their target article, Wang and Busemeyer (2013) discuss question order effects in terms of incompatible projectors on a Hilbert space. In a similar vein, Blutner recently presented an orthoalgebraic query language essentially relying on dynamic update semantics. Here, I shall comment on some interesting analogies between the different variants of dynamic semantics and generalized quantum theory to illustrate other kinds of order effects in human cognition, such as belief revision, the resolution of anaphors, and default reasoning that result from the crucial non-commutativity of mental operations upon the belief state of a cognitive agent.

  13. Metasemantics: On the Limits of Semantic Theory

    ERIC Educational Resources Information Center

    Parent, T.

    2009-01-01

    METASEMANTICS is a wake-up call for semantic theory: It reveals that some semantic questions have no adequate answer. (This is meant to be the "epistemic" point that certain semantic questions cannot be "settled"--not a metaphysical point about whether there is a fact-of-the-matter.) METASEMANTICS thus checks our default "optimism" that any…

  14. Chinese Character Decoding: A Semantic Bias?

    ERIC Educational Resources Information Center

    Williams, Clay; Bever, Thomas

    2010-01-01

    The effects of semantic and phonetic radicals on Chinese character decoding were examined. Our results suggest that semantic and phonetic radicals are each available for access when a corresponding task emphasizes one or the other kind of radical. But in a more neutral lexical recognition task, the semantic radical is more informative. Semantic…

  15. Semantic Weight and Verb Retrieval in Aphasia

    ERIC Educational Resources Information Center

    Barde, Laura H. F.; Schwartz, Myrna F.; Boronat, Consuelo B.

    2006-01-01

    Individuals with agrammatic aphasia may have difficulty with verb production in comparison to nouns. Additionally, they may have greater difficulty producing verbs that have fewer semantic components (i.e., are semantically "light") compared to verbs that have greater semantic weight. A connectionist verb-production model proposed by Gordon and…

  16. Semantic Relatedness for Evaluation of Course Equivalencies

    ERIC Educational Resources Information Center

    Yang, Beibei

    2012-01-01

    Semantic relatedness, or its inverse, semantic distance, measures the degree of closeness between two pieces of text determined by their meaning. Related work typically measures semantics based on a sparse knowledge base such as WordNet or Cyc that requires intensive manual efforts to build and maintain. Other work is based on a corpus such as the…

  17. Semantic memory retrieval circuit: role of pre-SMA, caudate, and thalamus.

    PubMed

    Hart, John; Maguire, Mandy J; Motes, Michael; Mudar, Raksha Anand; Chiang, Hsueh-Sheng; Womack, Kyle B; Kraut, Michael A

    2013-07-01

    We propose that pre-supplementary motor area (pre-SMA)-thalamic interactions govern processes fundamental to semantic retrieval of an integrated object memory. At the onset of semantic retrieval, pre-SMA initiates electrical interactions between multiple cortical regions associated with semantic memory subsystems encodings as indexed by an increase in theta-band EEG power. This starts between 100-150 ms after stimulus presentation and is sustained throughout the task. We posit that this activity represents initiation of the object memory search, which continues in searching for an object memory. When the correct memory is retrieved, there is a high beta-band EEG power increase, which reflects communication between pre-SMA and thalamus, designates the end of the search process and resultant in object retrieval from multiple semantic memory subsystems. This high beta signal is also detected in cortical regions. This circuit is modulated by the caudate nuclei to facilitate correct and suppress incorrect target memories.

  18. Intractable diarrhoea of infancy and latent otomastoiditis.

    PubMed Central

    Salazar de Sousa, J; da Silva, A; da Costa Ribeiro, V

    1980-01-01

    In 16 infants with intractable diarrhoea, latent otomastoiditis was found in 9 (3 at necropsy and 6 at myringotomy-antrotomy). In 5 of the 6 operated group, surgery was followed by a striking cessation of the diarrhoea and with weight gain. It is concluded that (1) latent otomastoiditis may be a perpetuating factor in intractable diarrhoea; (2) myringotomy-antrotomy should be considered if other forms of treatment have failed, and especially if there is leucocytosis; (3) mastoiditis with diffuse osteitis seems to be associated with a poor prognosis. PMID:7458392

  19. Learning Minimal Latent Directed Information Polytrees.

    PubMed

    Etesami, Jalal; Kiyavash, Negar; Coleman, Todd

    2016-09-01

    We propose an approach for learning latent directed polytrees as long as there exists an appropriately defined discrepancy measure between the observed nodes. Specifically, we use our approach for learning directed information polytrees where samples are available from only a subset of processes. Directed information trees are a new type of probabilistic graphical models that represent the causal dynamics among a set of random processes in a stochastic system. We prove that the approach is consistent for learning minimal latent directed trees. We analyze the sample complexity of the learning task when the empirical estimator of mutual information is used as the discrepancy measure. PMID:27391682

  20. An Efficient Web Page Ranking for Semantic Web

    NASA Astrophysics Data System (ADS)

    Chahal, P.; Singh, M.; Kumar, S.

    2014-01-01

    With the enormous amount of information presented on the web, the retrieval of relevant information has become a serious problem and is also the topic of research for last few years. The most common tools to retrieve information from web are search engines like Google. The Search engines are usually based on keyword searching and indexing of web pages. This approach is not very efficient as the result-set of web pages obtained include large irrelevant pages. Sometimes even the entire result-set may contain lot of irrelevant pages for the user. The next generation of search engines must address this problem. Recently, many semantic web search engines have been developed like Ontolook, Swoogle, which help in searching meaningful documents presented on semantic web. In this process the ranking of the retrieved web pages is very crucial. Some attempts have been made in ranking of semantic web pages but still the ranking of these semantic web documents is neither satisfactory and nor up to the user's expectations. In this paper we have proposed a semantic web based document ranking scheme that relies not only on the keywords but also on the conceptual instances present between the keywords. As a result only the relevant page will be on the top of the result-set of searched web pages. We explore all relevant relations between the keywords exploring the user's intention and then calculate the fraction of these relations on each web page to determine their relevance. We have found that this ranking technique gives better results than those by the prevailing methods.

  1. Action representation: crosstalk between semantics and pragmatics.

    PubMed

    Prinz, Wolfgang

    2014-03-01

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

  2. Semantic bifurcated importance field visualization

    NASA Astrophysics Data System (ADS)

    Lindahl, Eric; Petrov, Plamen

    2007-04-01

    While there are many good ways to map sensual reality to two dimensional displays, mapping non-physical and possibilistic information can be challenging. The advent of faster-than-real-time systems allow the predictive and possibilistic exploration of important factors that can affect the decision maker. Visualizing a compressed picture of the past and possible factors can assist the decision maker summarizing information in a cognitive based model thereby reducing clutter and perhaps related decision times. Our proposed semantic bifurcated importance field visualization uses saccadic eye motion models to partition the display into a possibilistic and sensed data vertically and spatial and semantic data horizontally. Saccadic eye movement precedes and prepares decision makers before nearly every directed action. Cognitive models for saccadic eye movement show that people prefer lateral to vertical saccadic movement. Studies have suggested that saccades may be coupled to momentary problem solving strategies. Also, the central 1.5 degrees of the visual field represents 100 times greater resolution that then peripheral field so concentrating factors can reduce unnecessary saccades. By packing information according to saccadic models, we can relate important decision factors reduce factor dimensionality and present the dense summary dimensions of semantic and importance. Inter and intra ballistics of the SBIFV provide important clues on how semantic packing assists in decision making. Future directions of SBIFV are to make the visualization reactive and conformal to saccades specializing targets to ballistics, such as dynamically filtering and highlighting verbal targets for left saccades and spatial targets for right saccades.

  3. Semantic Systems of Minority Groups.

    ERIC Educational Resources Information Center

    Entwisle, Doris R.

    Because socialization in terms of language behavior is the pivot for all other socialization, great emphasis is being placed in the linguistic determinants of cognition, and the influence of parents' language on child language and cognition. The same life conditions that foster dialect differences may be presumed to lead to semantic differences.…

  4. Colourful Semantics: A Clinical Investigation

    ERIC Educational Resources Information Center

    Bolderson, Sarah; Dosanjh, Christine; Milligan, Claudine; Pring, Tim; Chiat, Shula

    2011-01-01

    Children with language difficulties often omit verbs and grammatical elements and fail to complete sentences. Bryan (1997) described "colourful semantics", a therapy she used to treat a 5-year-old boy. The therapy uses colour coding to highlight the predicate argument structure of sentences. This study further tested the therapy's effectiveness by…

  5. Semantic Fission through Dialect Fusion.

    ERIC Educational Resources Information Center

    Linn, Michael D.

    The linguistic atlas projects have provided much information on the regional distribution of pronunciation, vocabulary, and syntax and have given important evidence for a greater understanding of problems involved in semantic change, particularly in pointing out transition areas where dialects become fused. In a study supplementary to that…

  6. Semantic Borders and Incomplete Understanding.

    PubMed

    Silva-Filho, Waldomiro J; Dazzani, Maria Virgínia

    2016-03-01

    In this article, we explore a fundamental issue of Cultural Psychology, that is our "capacity to make meaning", by investigating a thesis from contemporary philosophical semantics, namely, that there is a decisive relationship between language and rationality. Many philosophers think that for a person to be described as a rational agent he must understand the semantic content and meaning of the words he uses to express his intentional mental states, e.g., his beliefs and thoughts. Our argument seeks to investigate the thesis developed by Tyler Burge, according to which our mastery or understanding of the semantic content of the terms which form our beliefs and thoughts is an "incomplete understanding". To do this, we discuss, on the one hand, the general lines of anti-individualism or semantic externalism and, on the other, criticisms of the Burgean notion of incomplete understanding - one radical and the other moderate. We defend our understanding that the content of our beliefs must be described in the light of the limits and natural contingencies of our cognitive capacities and the normative nature of our rationality. At heart, anti-individualism leads us to think about the fact that we are social creatures, living in contingent situations, with important, but limited, cognitive capacities, and that we receive the main, and most important, portion of our knowledge simply from what others tell us. Finally, we conclude that this discussion may contribute to the current debate about the notion of borders.

  7. A Note on Semantic Selection.

    ERIC Educational Resources Information Center

    Endo, Yoshio

    1989-01-01

    The notions of categorical selection (c-selection) and semantic selection (s-selection) as outlined in recent research on generative grammar are discussed. The first section addresses the type of selectional constraint imposed on English small clauses (e.g., "John considers [Mary smart]"). In the second section, it is suggested that the constraint…

  8. Genres, Semantics, and Classroom Education.

    ERIC Educational Resources Information Center

    Lemke, Jay

    1988-01-01

    Argues that competence in academic subjects depends on mastery of their specialized patterns of language use. These patterns are described in terms of: 1) the semantics underlying Halliday's functional linguistics and 2) the structural analysis of communication genres. A sample classroom episode illustrates relationships among semantic…

  9. Semantic Borders and Incomplete Understanding.

    PubMed

    Silva-Filho, Waldomiro J; Dazzani, Maria Virgínia

    2016-03-01

    In this article, we explore a fundamental issue of Cultural Psychology, that is our "capacity to make meaning", by investigating a thesis from contemporary philosophical semantics, namely, that there is a decisive relationship between language and rationality. Many philosophers think that for a person to be described as a rational agent he must understand the semantic content and meaning of the words he uses to express his intentional mental states, e.g., his beliefs and thoughts. Our argument seeks to investigate the thesis developed by Tyler Burge, according to which our mastery or understanding of the semantic content of the terms which form our beliefs and thoughts is an "incomplete understanding". To do this, we discuss, on the one hand, the general lines of anti-individualism or semantic externalism and, on the other, criticisms of the Burgean notion of incomplete understanding - one radical and the other moderate. We defend our understanding that the content of our beliefs must be described in the light of the limits and natural contingencies of our cognitive capacities and the normative nature of our rationality. At heart, anti-individualism leads us to think about the fact that we are social creatures, living in contingent situations, with important, but limited, cognitive capacities, and that we receive the main, and most important, portion of our knowledge simply from what others tell us. Finally, we conclude that this discussion may contribute to the current debate about the notion of borders. PMID:26111737

  10. Handbook of Semantic Word Norms.

    ERIC Educational Resources Information Center

    Toglia, Michael P.; Battig, William F.

    This volume contains information derived from college student ratings of a large number and variety of individual words (along with some nonwords) for seven basic semantic characteristics. The primary data are rating values for over 2800 words for seven dimensions of special significance for current research on verbal behavior and related topics.…

  11. Incrementally Dissociating Syntax and Semantics

    ERIC Educational Resources Information Center

    Brennan, Jonathan R.

    2010-01-01

    A basic challenge for research into the neurobiology of language is understanding how the brain combines words to make complex representations. Linguistic theory divides this task into several computations including syntactic structure building and semantic composition. The close relationship between these computations, however, poses a strong…

  12. Generative Semantics and Dialect Geography.

    ERIC Educational Resources Information Center

    Ney, James W.

    An extrinsic relationship between generative semantics and dialect geography should be exploited because contemporary transformational grammarians have too easily ignored the work of the dialectologist and have been too readily satisfied with what might be called armchair evidence. The work of the dialect geographers needs to be taken into…

  13. Semantic Annotation of Computational Components

    NASA Technical Reports Server (NTRS)

    Vanderbilt, Peter; Mehrotra, Piyush

    2004-01-01

    This paper describes a methodology to specify machine-processable semantic descriptions of computational components to enable them to be shared and reused. A particular focus of this scheme is to enable automatic compositon of such components into simple work-flows.

  14. The Semantic Web in Education

    ERIC Educational Resources Information Center

    Ohler, Jason

    2008-01-01

    The semantic web or Web 3.0 makes information more meaningful to people by making it more understandable to machines. In this article, the author examines the implications of Web 3.0 for education. The author considers three areas of impact: knowledge construction, personal learning network maintenance, and personal educational administration.…

  15. Semantic Activation in Action Planning

    ERIC Educational Resources Information Center

    Lindemann, Oliver; Stenneken, Prisca; van Schie, Hein T.; Bekkering, Harold

    2006-01-01

    Four experiments investigated activation of semantic information in action preparation. Participants either prepared to grasp and use an object (e.g., to drink from a cup) or to lift a finger in association with the object's position following a go/no-go lexical-decision task. Word stimuli were consistent to the action goals of the object use…

  16. Quest for a Computerised Semantics.

    ERIC Educational Resources Information Center

    Leslie, Adrian R.

    The objective of this thesis was to colligate the various strands of research in the literature of computational linguistics that have to do with the computational treatment of semantic content so as to encode it into a computerized dictionary. In chapter 1 the course of mechanical translation (1947-1960) and quantitative linguistics is traced to…

  17. Semantic Preview Benefit during Reading

    ERIC Educational Resources Information Center

    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…

  18. Entanglement as a Semantic Resource

    NASA Astrophysics Data System (ADS)

    Dalla Chiara, Maria Luisa; Giuntini, Roberto; Ledda, Antonio; Leporini, Roberto; Sergioli, Giuseppe

    2010-10-01

    The characteristic holistic features of the quantum theoretic formalism and the intriguing notion of entanglement can be applied to a field that is far from microphysics: logical semantics. Quantum computational logics are new forms of quantum logic that have been suggested by the theory of quantum logical gates in quantum computation. In the standard semantics of these logics, sentences denote quantum information quantities: systems of qubits ( quregisters) or, more generally, mixtures of quregisters ( qumixes), while logical connectives are interpreted as special quantum logical gates (which have a characteristic reversible and dynamic behavior). In this framework, states of knowledge may be entangled, in such a way that our information about the whole determines our information about the parts; and the procedure cannot be, generally, inverted. In spite of its appealing properties, the standard version of the quantum computational semantics is strongly “Hilbert-space dependent”. This certainly represents a shortcoming for all applications, where real and complex numbers do not generally play any significant role (as happens, for instance, in the case of natural and of artistic languages). We propose an abstract version of quantum computational semantics, where abstract qumixes, quregisters and registers are identified with some special objects (not necessarily living in a Hilbert space), while gates are reversible functions that transform qumixes into qumixes. In this framework, one can give an abstract definition of the notions of superposition and of entangled pieces of information, quite independently of any numerical values. We investigate three different forms of abstract holistic quantum computational logic.

  19. The effect of semantic categorisation on recall memory in amnesia.

    PubMed

    Channon, S; Daum, I

    2000-01-01

    Amnesic patients were compared to a healthy control group on recall of word lists containing semantically-related or unrelated words. As expected on the basis of previous literature, the amnesic group performed below the control group on all measures of recall. When total recall scores for each list were used as the index of performance, their scores were not significantly affected by the type of list, unlike those of the control group. Comparison of serial position effects for different parts of the lists revealed that the control group derived greater benefit from semantic relatedness in recall of items from the middle positions. This effect was not shown by the amnesic group, who showed similar U-shaped serial position curves for recall of all three lists, and appeared to use a more passive recall strategy than the control group. The findings are discussed in relation to our current understanding of amnesic deficits.

  20. Knowledge networks in the age of the Semantic Web.

    PubMed

    Neumann, Eric; Prusak, Larry

    2007-05-01

    The Web has become the major medium for various communities to share their knowledge. To this end, it provides an optimal environment for knowledge networks. The web offers global connectivity that is virtually instantaneous, and whose resources and documents can easily be indexed for easy searching. In the coupled realms of biomedical research and healthcare, this has become especially important where today many thousands of communities already exist that connect across academia, hospitals and industry. These communities also rely on several forms of knowledge assets, including publications, experimental data, domain-specific vocabularies and policies. Web-based communities will be one of the earlier beneficiaries of the emerging Semantic Web. With the new standards and technologies of the Semantic Web, effective utilization of knowledge networks will expand profoundly, fostering new levels of innovation and knowledge.

  1. Latent Fingerprint Matching: Performance Gain via Feedback from Exemplar Prints.

    PubMed

    Arora, Sunpreet S; Liu, Eryun; Cao, Kai; Jain, Anil K

    2014-12-01

    Latent fingerprints serve as an important source of forensic evidence in a court of law. Automatic matching of latent fingerprints to rolled/plain (exemplar) fingerprints with high accuracy is quite vital for such applications. However, latent impressions are typically of poor quality with complex background noise which makes feature extraction and matching of latents a significantly challenging problem. We propose incorporating top-down information or feedback from an exemplar to refine the features extracted from a latent for improving latent matching accuracy. The refined latent features (e.g. ridge orientation and frequency), after feedback, are used to re-match the latent to the top K candidate exemplars returned by the baseline matcher and resort the candidate list. The contributions of this research include: (i) devising systemic ways to use information in exemplars for latent feature refinement, (ii) developing a feedback paradigm which can be wrapped around any latent matcher for improving its matching performance, and (iii) determining when feedback is actually necessary to improve latent matching accuracy. Experimental results show that integrating the proposed feedback paradigm with a state-of-the-art latent matcher improves its identification accuracy by 0.5-3.5 percent for NIST SD27 and WVU latent databases against a background database of 100k exemplars.

  2. Latent Fingerprint Matching: Performance Gain via Feedback from Exemplar Prints.

    PubMed

    Arora, Sunpreet S; Liu, Eryun; Cao, Kai; Jain, Anil K

    2014-12-01

    Latent fingerprints serve as an important source of forensic evidence in a court of law. Automatic matching of latent fingerprints to rolled/plain (exemplar) fingerprints with high accuracy is quite vital for such applications. However, latent impressions are typically of poor quality with complex background noise which makes feature extraction and matching of latents a significantly challenging problem. We propose incorporating top-down information or feedback from an exemplar to refine the features extracted from a latent for improving latent matching accuracy. The refined latent features (e.g. ridge orientation and frequency), after feedback, are used to re-match the latent to the top K candidate exemplars returned by the baseline matcher and resort the candidate list. The contributions of this research include: (i) devising systemic ways to use information in exemplars for latent feature refinement, (ii) developing a feedback paradigm which can be wrapped around any latent matcher for improving its matching performance, and (iii) determining when feedback is actually necessary to improve latent matching accuracy. Experimental results show that integrating the proposed feedback paradigm with a state-of-the-art latent matcher improves its identification accuracy by 0.5-3.5 percent for NIST SD27 and WVU latent databases against a background database of 100k exemplars. PMID:26353151

  3. Synonym extraction and abbreviation expansion with ensembles of semantic spaces

    PubMed Central

    2014-01-01

    Background Terminologies that account for variation in language use by linking synonyms and abbreviations to their corresponding concept are important enablers of high-quality information extraction from medical texts. Due to the use of specialized sub-languages in the medical domain, manual construction of semantic resources that accurately reflect language use is both costly and challenging, often resulting in low coverage. Although models of distributional semantics applied to large corpora provide a potential means of supporting development of such resources, their ability to isolate synonymy from other semantic relations is limited. Their application in the clinical domain has also only recently begun to be explored. Combining distributional models and applying them to different types of corpora may lead to enhanced performance on the tasks of automatically extracting synonyms and abbreviation-expansion pairs. Results A combination of two distributional models – Random Indexing and Random Permutation – employed in conjunction with a single corpus outperforms using either of the models in isolation. Furthermore, combining semantic spaces induced from different types of corpora – a corpus of clinical text and a corpus of medical journal articles – further improves results, outperforming a combination of semantic spaces induced from a single source, as well as a single semantic space induced from the conjoint corpus. A combination strategy that simply sums the cosine similarity scores of candidate terms is generally the most profitable out of the ones explored. Finally, applying simple post-processing filtering rules yields substantial performance gains on the tasks of extracting abbreviation-expansion pairs, but not synonyms. The best results, measured as recall in a list of ten candidate terms, for the three tasks are: 0.39 for abbreviations to long forms, 0.33 for long forms to abbreviations, and 0.47 for synonyms. Conclusions This study demonstrates

  4. An Experiment in Scientific Code Semantic Analysis

    NASA Technical Reports Server (NTRS)

    Stewart, Mark E. M.

    1998-01-01

    This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, distributed expert parsers. These semantic parser are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. The parsers will automatically recognize and document some static, semantic concepts and locate some program semantic errors. Results are shown for a subroutine test case and a collection of combustion code routines. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

  5. Lexical Semantics and Irregular Inflection

    PubMed Central

    Huang, Yi Ting; Pinker, Steven

    2010-01-01

    Whether a word has an irregular inflection does not depend on its sound alone: compare lie-lay (recline) and lie-lied (prevaricate). Theories of morphology, particularly connectionist and symbolic models, disagree on which nonphonological factors are responsible. We test four possibilities: (1) Lexical effects, in which two lemmas differ in whether they specify an irregular form; (2) Semantic effects, in which the semantic features of a word become associated with regular or irregular forms; (3) Morphological structure effects, in which a word with a headless structure (e.g., a verb derived from a noun) blocks access to a stored irregular form; (4) Compositionality effects, in which the stored combination of an irregular word’s meaning (e.g., the verb’s inherent aspect) with the meaning of the inflection (e.g., pastness) doesn’t readily transfer to new senses with different combinations of such meanings. In four experiments, speakers were presented with existing and novel verbs and asked to rate their past-tense forms, semantic similarities, grammatical structure, and aspectual similarities. We found (1) an interaction between semantic and phonological similarity, coinciding with reported strategies of analogizing to known verbs and implicating lexical effects; (2) weak and inconsistent effects of semantic similarity; (3) robust effects of morphological structure, and (4) robust effects of aspectual compositionality. Results are consistent with theories of language that invoke lexical entries and morphological structure, and which differentiate the mode of storage of regular and irregular verbs. They also suggest how psycholinguistic processes have shaped vocabulary structure over history. PMID:21151703

  6. Category-specific semantic deficits in Alzheimer's disease: a semantic priming study.

    PubMed

    Hernández, Mireia; Costa, Albert; Juncadella, Montserrat; Sebastián-Gallés, Núria; Reñé, Ramón

    2008-03-01

    Category-specific semantic deficits in individuals suffering brain damage after relatively focal lesions provide an important source of evidence about the organization of semantic knowledge. However, whether Alzheimer's disease (AD), in which the brain damage is more widespread, affects semantic categories to a different extent is still controversial. In the present study, we assess this issue by means of the semantic priming technique. AD patients with a mild impairment of their semantic knowledge showed comparable priming effects to that of controls for the categories of animals and artifacts. Interestingly, however, patients with a moderate impairment of their semantic knowledge showed a normal priming effect for animals but a very reduced priming effect (if any) for artifacts. These results reveal that AD may affect the semantic knowledge of different semantic categories to a different extent. The implications of this observation for current theoretical accounts of semantic representation in the brain are discussed.

  7. Latent TGF-β-binding proteins

    PubMed Central

    Robertson, Ian B.; Horiguchi, Masahito; Zilberberg, Lior; Dabovic, Branka; Hadjiolova, Krassimira; Rifkin, Daniel B.

    2016-01-01

    The LTBPs (or latent transforming growth factor β binding proteins) are important components of the extracellular matrix (ECM) that interact with fibrillin microfibrils and have a number of different roles in microfibril biology. There are four LTBPs isoforms in the human genome (LTBP-1, -2, -3, and -4), all of which appear to associate with fibrillin and the biology of each isoform is reviewed here. The LTBPs were first identified as forming latent complexes with TGFβ by covalently binding the TGFβ propeptide (LAP) via disulfide bonds in the endoplasmic reticulum. LAP in turn is cleaved from the mature TGFβ precursor in the trans golgi network but LAP and TGFβ remain strongly bound through non-covalent interactions. LAP, TGFβ, and LTBP together form the large latent complex (LLC). LTBPs were originally thought to primarily play a role in maintaining TGFβ latency and targeting the latent growth factor to the extracellular matrix (ECM), but it has also been shown that LTBP-1 participates in TGFβ activation by integrins and may also regulate activation by proteases and other factors. LTBP-3 appears to have a role in skeletal formation including tooth development. As well as having important functions in TGFβ regulation, TGFβ-independent activities have recently been identified for LTBP-2 and LTBP-4 in stabilizing microfibril bundles and regulating elastic fiber assembly. PMID:25960419

  8. Generalized Structured Component Analysis with Latent Interactions

    ERIC Educational Resources Information Center

    Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

    2010-01-01

    Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

  9. Confirmatory Measurement Model Comparisons Using Latent Means.

    ERIC Educational Resources Information Center

    Millsap, Roger E.; Everson, Howard

    1991-01-01

    Use of confirmatory factor analysis (CFA) with nonzero latent means in testing six different measurement models from classical test theory is discussed. Implications of the six models for observed mean and covariance structures are described, and three examples of the use of CFA in testing the models are presented. (SLD)

  10. The Trait in Latent Trait Theory.

    ERIC Educational Resources Information Center

    Levine, Michael V.

    Significant to a latent trait or item response theory analysis of a mental test is the determination of exactly what is being quantified. The following are practical problems to be considered in the formulation of a good theory: (1) deciding whether two tests measure the same trait or traits; (2) analyzing the relative contributions of a pair of…

  11. Dish-mounted latent heat buffer storage

    NASA Technical Reports Server (NTRS)

    Manvi, R.

    1981-01-01

    Dish-mounted latent heat storage subsystems for Rankine, Brayton, and Stirling engines operating at 427 C, 816 C, and 816 C respectively are discussed. Storage requirements definition, conceptual design, media stability and compatibility tests, and thermal performance analyses are considered.

  12. Thermally Stable, Latent Olefin Metathesis Catalysts

    PubMed Central

    Thomas, Renee M.; Fedorov, Alexey; Keitz, Benjamin K.

    2011-01-01

    Highly thermally stable N-aryl,N-alkyl N-heterocyclic carbene (NHC) ruthenium catalysts were designed and synthesized for latent olefin metathesis. These catalysts showed excellent latent behavior toward metathesis reactions, whereby the complexes were inactive at ambient temperature and initiated at elevated temperatures, a challenging property to achieve with second generation catalysts. A sterically hindered N-tert-butyl substituent on the NHC ligand of the ruthenium complex was found to induce latent behavior toward cross-metathesis reactions, and exchange of the chloride ligands for iodide ligands was necessary to attain latent behavior during ring-opening metathesis polymerization (ROMP). Iodide-based catalysts showed no reactivity toward ROMP of norbornene-derived monomers at 25 °C, and upon heating to 85 °C gave complete conversion of monomer to polymer in less than 2 hours. All of the complexes were very stable to air, moisture, and elevated temperatures up to at least 90 °C, and exhibited a long catalyst lifetime in solution at elevated temperatures. PMID:22282652

  13. Immune Function and Reactivation of Latent Viruses

    NASA Technical Reports Server (NTRS)

    Butel, Janet S.

    1999-01-01

    A major concern associated with long-duration space flight is the possibility of infectious diseases posing an unacceptable medical risk to crew members. One major hypothesis addressed in this project is that space flight will cause alterations in the immune system that will allow latent viruses that are endogenous in the human population to reactivate and shed to higher levels than normal, which may affect the health of crew members. The second major hypothesis being examined is that the effects of space flight will alter the mucosal immune system, the first line of defense against many microbial infections, including herpesviruses, polyomaviruses, and gastroenteritis viruses, rendering crew members more susceptible to virus infections across the mucosa. We are focusing the virus studies on the human herpesviruses and polyomaviruses, important pathogens known to establish latent infections in most of the human population. Both primary infection and reactivation from latent infection with these groups of viruses (especially certain herpesviruses) can cause a variety of illnesses that result in morbidity and, occasionally, mortality. Both herpesviruses and polyomaviruses have been associated with human cancer, as well. Effective vaccines exist for only one of the eight known human herpesviruses and available antivirals are of limited use. Whereas normal individuals display minimal consequences from latent viral infections, events which alter immune function (such as immunosuppressive therapy following solid organ transplantation) are known to increase the risk of complications as a result of viral reactivations.

  14. Extended Generalized Linear Latent and Mixed Model

    ERIC Educational Resources Information Center

    Segawa, Eisuke; Emery, Sherry; Curry, Susan J.

    2008-01-01

    The generalized linear latent and mixed modeling (GLLAMM framework) includes many models such as hierarchical and structural equation models. However, GLLAMM cannot currently accommodate some models because it does not allow some parameters to be random. GLLAMM is extended to overcome the limitation by adding a submodel that specifies a…

  15. Forensic Chemistry: The Revelation of Latent Fingerprints

    ERIC Educational Resources Information Center

    Friesen, J. Brent

    2015-01-01

    The visualization of latent fingerprints often involves the use of a chemical substance that creates a contrast between the fingerprint residues and the surface on which the print was deposited. The chemical-aided visualization techniques can be divided into two main categories: those that chemically react with the fingerprint residue and those…

  16. Detection of latent prints by Raman imaging

    DOEpatents

    Lewis, Linda Anne; Connatser, Raynella Magdalene; Lewis, Sr., Samuel Arthur

    2011-01-11

    The present invention relates to a method for detecting a print on a surface, the method comprising: (a) contacting the print with a Raman surface-enhancing agent to produce a Raman-enhanced print; and (b) detecting the Raman-enhanced print using a Raman spectroscopic method. The invention is particularly directed to the imaging of latent fingerprints.

  17. Taxometric and Factor Analytic Models of Anxiety Sensitivity among Youth: Exploring the Latent Structure of Anxiety Psychopathology Vulnerability

    ERIC Educational Resources Information Center

    Bernstein, Amit; Zvolensky, Michael J.; Stewart, Sherry; Comeau, Nancy

    2007-01-01

    This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), a well-established affect-sensitivity individual difference factor, among youth by employing taxometric and factor analytic approaches in an integrative manner. Taxometric analyses indicated that AS, as indexed by the Child Anxiety Sensitivity…

  18. Learning to Read Changes Children's Phonological Skills: Evidence from a Latent Variable Longitudinal Study of Reading and Nonword Repetition

    ERIC Educational Resources Information Center

    Nation, Kate; Hulme, Charles

    2011-01-01

    Individual differences in nonword repetition are associated with language and literacy development, but few studies have considered the extent to which learning to read influences phonological skills as indexed by nonword repetition performance. We explored this question using a latent variable longitudinal design. Reading, oral language and…

  19. Latent Heating Processes within Tropical Deep Convection

    NASA Astrophysics Data System (ADS)

    van den Heever, S. C.; Mcgee, C. J.

    2013-12-01

    It has been suggested that latent heating above the freezing level plays an important role in reconciling Riehl and Malkus' Hot Tower Hypothesis (HTH) with observational evidence of diluted tropical deep convective cores. In this study, recent modifications to the HTH have been evaluated through the use of Lagrangian trajectory analysis of deep convective cores simulated using the Regional Atmospheric Modeling System (RAMS), a cloud-resolving model (CRM) with sophisticated microphysical, surface and radiation parameterization schemes. Idealized, high-resolution simulations of a line of tropical convective cells have been conducted. A two-moment microphysical scheme was utilized, and the initial and lateral boundary grid conditions were obtained from a large-domain CRM simulation approaching radiative convective equilibrium. As the tropics are never too far from radiative convective equilibrium, such a framework is useful for investigating the relationships between radiation, thermodynamics and microphysics in tropical convection. Microphysical impacts on latent heating and equivalent potential temperature (θe) have been analyzed along trajectories ascending within convective regions. Changes in θe along backward trajectories are partitioned into contributions from latent heating due to ice processes and a residual term that is shown to be an approximate representation of mixing. It is apparent from the CRM simulations that mixing with dry environmental air decreases θe along ascending trajectories below the freezing level, while latent heating due to freezing and vapor deposition increase θe above the freezing level. The along-trajectory contributions to latent heating from cloud nucleation, condensation, evaporation, freezing, deposition, and sublimation have also been quantified. Finally, the source regions of trajectories reaching the upper troposphere have been identified. The analysis indicates that while much of the air ascending within convective

  20. Exploiting semantic linkages among multiple sources for semantic information retrieval

    NASA Astrophysics Data System (ADS)

    Li, JianQiang; Yang, Ji-Jiang; Liu, Chunchen; Zhao, Yu; Liu, Bo; Shi, Yuliang

    2014-07-01

    The vision of the Semantic Web is to build a global Web of machine-readable data to be consumed by intelligent applications. As the first step to make this vision come true, the initiative of linked open data has fostered many novel applications aimed at improving data accessibility in the public Web. Comparably, the enterprise environment is so different from the public Web that most potentially usable business information originates in an unstructured form (typically in free text), which poses a challenge for the adoption of semantic technologies in the enterprise environment. Considering that the business information in a company is highly specific and centred around a set of commonly used concepts, this paper describes a pilot study to migrate the concept of linked data into the development of a domain-specific application, i.e. the vehicle repair support system. The set of commonly used concepts, including the part name of a car and the phenomenon term on the car repairing, are employed to build the linkage between data and documents distributed among different sources, leading to the fusion of documents and data across source boundaries. Then, we describe the approaches of semantic information retrieval to consume these linkages for value creation for companies. The experiments on two real-world data sets show that the proposed approaches outperform the best baseline 6.3-10.8% and 6.4-11.1% in terms of top five and top 10 precisions, respectively. We believe that our pilot study can serve as an important reference for the development of similar semantic applications in an enterprise environment.

  1. A Note on Cluster Effects in Latent Class Analysis

    ERIC Educational Resources Information Center

    Kaplan, David; Keller, Bryan

    2011-01-01

    This article examines the effects of clustering in latent class analysis. A comprehensive simulation study is conducted, which begins by specifying a true multilevel latent class model with varying within- and between-cluster sample sizes, varying latent class proportions, and varying intraclass correlations. These models are then estimated under…

  2. Stochastic Approximation Methods for Latent Regression Item Response Models

    ERIC Educational Resources Information Center

    von Davier, Matthias; Sinharay, Sandip

    2010-01-01

    This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response theory (IRT) to a latent variable model with covariates…

  3. A General Approach to Defining Latent Growth Components

    ERIC Educational Resources Information Center

    Mayer, Axel; Steyer, Rolf; Mueller, Horst

    2012-01-01

    We present a 3-step approach to defining latent growth components. In the first step, a measurement model with at least 2 indicators for each time point is formulated to identify measurement error variances and obtain latent variables that are purged from measurement error. In the second step, we use contrast matrices to define the latent growth…

  4. Fingerprint Minutiae from Latent and Matching Tenprint Images

    National Institute of Standards and Technology Data Gateway

    NIST Fingerprint Minutiae from Latent and Matching Tenprint Images (PC database for purchase)   NIST Special Database 27 contains latent fingerprints from crime scenes and their matching rolled fingerprint mates. This database can be used to develop and test new fingerprint algorithms, test commercial and research AFIS systems, train latent examiners, and promote the ANSI/NIST file format standard.

  5. Bayesian Semiparametric Structural Equation Models with Latent Variables

    ERIC Educational Resources Information Center

    Yang, Mingan; Dunson, David B.

    2010-01-01

    Structural equation models (SEMs) with latent variables are widely useful for sparse covariance structure modeling and for inferring relationships among latent variables. Bayesian SEMs are appealing in allowing for the incorporation of prior information and in providing exact posterior distributions of unknowns, including the latent variables. In…

  6. Adopting Abstract Images for Semantic Scene Understanding.

    PubMed

    Zitnick, C Lawrence; Vedantam, Ramakrishna; Parikh, Devi

    2016-04-01

    Relating visual information to its linguistic semantic meaning remains an open and challenging area of research. The semantic meaning of images depends on the presence of objects, their attributes and their relations to other objects. But precisely characterizing this dependence requires extracting complex visual information from an image, which is in general a difficult and yet unsolved problem. In this paper, we propose studying semantic information in abstract images created from collections of clip art. Abstract images provide several advantages over real images. They allow for the direct study of how to infer high-level semantic information, since they remove the reliance on noisy low-level object, attribute and relation detectors, or the tedious hand-labeling of real images. Importantly, abstract images also allow the ability to generate sets of semantically similar scenes. Finding analogous sets of real images that are semantically similar would be nearly impossible. We create 1,002 sets of 10 semantically similar abstract images with corresponding written descriptions. We thoroughly analyze this dataset to discover semantically important features, the relations of words to visual features and methods for measuring semantic similarity. Finally, we study the relation between the saliency and memorability of objects and their semantic importance.

  7. A Semantic-Oriented Approach for Organizing and Developing Annotation for E-Learning

    ERIC Educational Resources Information Center

    Brut, Mihaela M.; Sedes, Florence; Dumitrescu, Stefan D.

    2011-01-01

    This paper presents a solution to extend the IEEE LOM standard with ontology-based semantic annotations for efficient use of learning objects outside Learning Management Systems. The data model corresponding to this approach is first presented. The proposed indexing technique for this model development in order to acquire a better annotation of…

  8. Brain Responses to Lexical-Semantic Priming in Children At-Risk for Dyslexia

    ERIC Educational Resources Information Center

    Torkildsen, Janne von Koss; Syversen, Gro; Simonsen, Hanne Gram; Moen, Inger; Lindgren, Magnus

    2007-01-01

    Deviances in early event-related potential (ERP) components reflecting auditory and phonological processing are well-documented in children at familial risk for dyslexia. However, little is known about brain responses which index processing in other linguistic domains such as lexicon, semantics and syntax in this group. The present study…

  9. Semantic Memory and Verbal Working Memory Correlates of N400 to Subordinate Homographs

    ERIC Educational Resources Information Center

    Salisbury, Dean F.

    2004-01-01

    N400 is an event-related brain potential that indexes operations in semantic memory conceptual space, whether elicited by language or some other representation (e.g., drawings). Language models typically propose three stages: lexical access or orthographic- and phonological-level analysis; lexical selection or word-level meaning and associate…

  10. Variation in verbal fluency: a latent variable analysis of clustering, switching, and overall performance.

    PubMed

    Unsworth, Nash; Spillers, Gregory J; Brewer, Gene A

    2011-03-01

    Verbal fluency tasks have long been used to assess and estimate group and individual differences in executive functioning in both cognitive and neuropsychological research domains. Despite their ubiquity, however, the specific component processes important for success in these tasks have remained elusive. The current work sought to reveal these various components and their respective roles in determining performance in fluency tasks using latent variable analysis. Two types of verbal fluency (semantic and letter) were compared along with several cognitive constructs of interest (working memory capacity, inhibition, vocabulary size, and processing speed) in order to determine which constructs are necessary for performance in these tasks. The results are discussed within the context of a two-stage cyclical search process in which participants first search for higher order categories and then search for specific items within these categories.

  11. Variation in verbal fluency: a latent variable analysis of clustering, switching, and overall performance.

    PubMed

    Unsworth, Nash; Spillers, Gregory J; Brewer, Gene A

    2011-03-01

    Verbal fluency tasks have long been used to assess and estimate group and individual differences in executive functioning in both cognitive and neuropsychological research domains. Despite their ubiquity, however, the specific component processes important for success in these tasks have remained elusive. The current work sought to reveal these various components and their respective roles in determining performance in fluency tasks using latent variable analysis. Two types of verbal fluency (semantic and letter) were compared along with several cognitive constructs of interest (working memory capacity, inhibition, vocabulary size, and processing speed) in order to determine which constructs are necessary for performance in these tasks. The results are discussed within the context of a two-stage cyclical search process in which participants first search for higher order categories and then search for specific items within these categories. PMID:20839136

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

    PubMed Central

    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. PMID:26418230

  13. A neotropical Miocene pollen database employing image-based search and semantic modeling1

    PubMed Central

    Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W.; Jaramillo, Carlos; Shyu, Chi-Ren

    2014-01-01

    • Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. PMID:25202648

  14. A first look at HealthCyberMap medical semantic subject search engine.

    PubMed

    Boulos, Maged N Kamel

    2004-01-01

    HealthCyberMap (http://healthcybermap.semanticweb.org) is a Semantic Web project that aims at mapping selected parts of health information resources in cyberspace in novel semantic ways to improve their retrieval and navigation. This paper describes HealthCyberMap semantic subject search engine methodology and early prototype which attempt to overcome the limitations of conventional free text search engines. Explicit concepts in resource metadata map onto a brokering domain ontology (a clinical terminology or classification) allowing a Semantic Web search engine to infer implicit meanings (synonyms and semantic relationships) not directly mentioned in either the resource or its metadata. Similarly, user queries would map to the same ontology allowing the search engine to infer the implicit semantics of user queries and use them to optimise retrieval. Related issues of metadata, clinical terminologies and automatic vs. manual indexing of medical Web resources are also discussed, together with future methodological directions, which include the use of a true terminology server as an intelligent broker between user queries and HealthCyberMap pool of resource metadata. A comparative evaluation of the new engine based on relevance metrics is also proposed. PMID:15096685

  15. A first look at HealthCyberMap medical semantic subject search engine.

    PubMed

    Boulos, Maged N Kamel

    2004-01-01

    HealthCyberMap (http://healthcybermap.semanticweb.org) is a Semantic Web project that aims at mapping selected parts of health information resources in cyberspace in novel semantic ways to improve their retrieval and navigation. This paper describes HealthCyberMap semantic subject search engine methodology and early prototype which attempt to overcome the limitations of conventional free text search engines. Explicit concepts in resource metadata map onto a brokering domain ontology (a clinical terminology or classification) allowing a Semantic Web search engine to infer implicit meanings (synonyms and semantic relationships) not directly mentioned in either the resource or its metadata. Similarly, user queries would map to the same ontology allowing the search engine to infer the implicit semantics of user queries and use them to optimise retrieval. Related issues of metadata, clinical terminologies and automatic vs. manual indexing of medical Web resources are also discussed, together with future methodological directions, which include the use of a true terminology server as an intelligent broker between user queries and HealthCyberMap pool of resource metadata. A comparative evaluation of the new engine based on relevance metrics is also proposed.

  16. Electrophysiology reveals semantic priming at a short SOA irrespective of depth of prime processing.

    PubMed

    Küper, Kristina; Heil, Martin

    2009-04-01

    The otherwise robust behavioral semantic priming effect is reduced to the point of being absent when a letter search has to be performed on the prime word. As a result the automaticity of semantic activation has been called into question. It is unclear, however, in how far automatic processes are even measurable in the letter search priming paradigm as the prime task necessitates a long prime-probe stimulus-onset asynchrony (SOA). In a modified procedure, a short SOA can be realized by delaying the prime task response until after participants have made a lexical decision on the probe. While the absence of lexical decision priming has already been demonstrated in this design it seems premature to draw any definite conclusions from this purely behavioral result since event related potential (ERP) measures have been shown to be a more sensitive index of semantic activation. Using the modified paradigm we thus recorded ERP in addition to lexical decision times. Stimuli were presented at two different SOAs (240 ms vs. 840 ms) and participants performed either a grammatical discrimination (Experiment 1) or a letter search (Experiment 2) on the prime. Irrespective of prime task, the modulation of the N400, the ERP correlate of semantic activation, provided clear-cut evidence of semantic processing at the short SOA. Implications for theories of semantic activation as well as the constraints of the delayed prime task procedure are discussed.

  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. The evolution of semantic systems.

    PubMed

    Bainbridge, William Sims

    2004-05-01

    Semantic or cultural systems are sets of concepts connected by meaningful relationships, and they exhibit properties similar to those of populations of biological organisms. Drawing upon ideas from evolutionary biology and methods from information technology, this article explores the potential for research and engineering on the evolution of semantic systems. Such work in cultural genetics requires two things: (1) a rigorous but evolving taxonomic system to categorize cultural artifacts, elements, and clusters, and (2) a set of hypotheses about the processes that cause evolutionary change. This article illustrates systematic approaches to cultural taxonomy with data on the popular ideology of the space program, science fiction motion pictures, nanotechnology books, and nanotechnology research grants. It offers hypotheses derived from evolutionary and population biology that might be useful in explaining cultural evolution. PMID:15194612

  19. The Formal Semantics of PVS

    NASA Technical Reports Server (NTRS)

    Owre, Sam; Shankar, Natarajan

    1999-01-01

    A specification language is a medium for expressing what is computed rather than how it is computed. Specification languages share some features with programming languages but are also different in several important ways. For our purpose, a specification language is a logic within which the behavior of computational systems can be formalized. Although a specification can be used to simulate the behavior of such systems, we mainly use specifications to state and prove system properties with mechanical assistance. We present the formal semantics of the specification language of SRI's Prototype Verification System (PVS). This specification language is based on the simply typed lambda calculus. The novelty in PVS is that it contains very expressive language features whose static analysis (e.g., typechecking) requires the assistance of a theorem prover. The formal semantics illuminates several of the design considerations underlying PVS, the interaction between theorem proving and typechecking.

  20. Semantic priming of familiar songs.

    PubMed

    Johnson, Sarah K; Halpern, Andrea R

    2012-05-01

    We explored the functional organization of semantic memory for music by comparing priming across familiar songs both within modalities (Experiment 1, tune to tune; Experiment 3, category label to lyrics) and across modalities (Experiment 2, category label to tune; Experiment 4, tune to lyrics). Participants judged whether or not the target tune or lyrics were real (akin to lexical decision tasks). We found significant priming, analogous to linguistic associative-priming effects, in reaction times for related primes as compared to unrelated primes, but primarily for within-modality comparisons. Reaction times to tunes (e.g., "Silent Night") were faster following related tunes ("Deck the Hall") than following unrelated tunes ("God Bless America"). However, a category label (e.g., Christmas) did not prime tunes from within that category. Lyrics were primed by a related category label, but not by a related tune. These results support the conceptual organization of music in semantic memory, but with potentially weaker associations across modalities.

  1. Modeling Nonlinear Change via Latent Change and Latent Acceleration Frameworks: Examining Velocity and Acceleration of Growth Trajectories

    ERIC Educational Resources Information Center

    Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele

    2013-01-01

    We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth curve models when change…

  2. Two Studies of Specification Error in Models for Categorical Latent Variables

    ERIC Educational Resources Information Center

    Kaplan, David; Depaoli, Sarah

    2011-01-01

    This article examines the problem of specification error in 2 models for categorical latent variables; the latent class model and the latent Markov model. Specification error in the latent class model focuses on the impact of incorrectly specifying the number of latent classes of the categorical latent variable on measures of model adequacy as…

  3. Semantic integration during metaphor comprehension in Asperger syndrome.

    PubMed

    Gold, Rinat; Faust, Miriam; Goldstein, Abraham

    2010-06-01

    Previous research indicates severe disabilities in processing figurative language in people diagnosed on the autism spectrum disorders. However, this aspect of language comprehension in Asperger syndrome (AS) specifically has rarely been the subject of formal study. The present study aimed to examine the possibility that in addition to their pragmatic deficits, the difficulties in the comprehension of metaphors in AS may be explained by deficient linguistic information processing. Specifically, we aimed to examine whether a deficient semantic integration process underlies the difficulties in metaphor comprehension frequently experienced by persons with AS. The semantic integration process of sixteen AS participants and sixteen matched controls was examined using event related potentials (ERPs). N400 amplitude served as an index for degree of effort invested in the semantic integration process of two-word expressions denoting literal, conventional metaphoric, and novel metaphoric meaning, as well as unrelated word pairs. Large N400 amplitudes for both novel and conventional metaphors demonstrated the greater difficulties in metaphor comprehension in the AS participants as compared to controls. Findings suggest that differences in linguistic information processing cause difficulties in metaphor comprehension in AS.

  4. Blocking of potentiation of latent inhibition.

    PubMed

    Hall, Geoffrey; Rodriguez, Gabriel

    2011-01-01

    We present a theory of latent inhibition based on the Pearce-Hall (Pearce & Hall, 1980) model for classical conditioning. Its central features are (1) that the associability of a stimulus declines as it comes to predict its consequences and (2) that nonreinforced exposure to a stimulus engages an associative learning process that makes the stimulus an accurate predictor of its consequences (in this case, the occurrence of no event). A formalization of this theory is shown to accommodate the finding that preexposure in compound with another cue can potentiate latent inhibition to the target cue. It further predicts that preexposure to the added cue will eliminate the potentiation effect. An experiment using rats and the flavor-aversion procedure confirmed this prediction.

  5. Medical linguistics: automated indexing into SNOMED.

    PubMed

    Wingert, F

    1988-01-01

    This paper reviews the state of the art in processing medical language data. The area is divided into the topics: (1) morphologic analysis, (2) syntactic analysis, (3) semantic analysis, and (4) pragmatics. Additional attention is given to medical nomenclatures and classifications as the bases of (automated) indexing procedures which are required whenever medical information is formalized. These topics are completed by an evaluation of related data structures and methods used to organize language-based medical knowledge.

  6. Explaining semantic short-term memory deficits: Evidence for the critical role of semantic control

    PubMed Central

    Hoffman, Paul; Jefferies, Elizabeth; Lambon Ralph, Matthew A.

    2011-01-01

    Patients with apparently selective short-term memory (STM) deficits for semantic information have played an important role in developing multi-store theories of STM and challenge the idea that verbal STM is supported by maintaining activation in the language system. We propose that semantic STM deficits are not as selective as previously thought and can occur as a result of mild disruption to semantic control processes, i.e., mechanisms that bias semantic processing towards task-relevant aspects of knowledge and away from irrelevant information. We tested three semantic STM patients with tasks that tapped four aspects of semantic control: (i) resolving ambiguity between word meanings, (ii) sensitivity to cues, (iii) ignoring irrelevant information and (iv) detecting weak semantic associations. All were impaired in conditions requiring more semantic control, irrespective of the STM demands of the task, suggesting a mild, but task-general, deficit in regulating semantic knowledge. This mild deficit has a disproportionate effect on STM tasks because they have high intrinsic control demands: in STM tasks, control is required to keep information active when it is no longer available in the environment and to manage competition between items held in memory simultaneously. By re-interpreting the core deficit in semantic STM patients in this way, we are able to explain their apparently selective impairment without the need for a specialised STM store. Instead, we argue that semantic STM patients occupy the mildest end of spectrum of semantic control disorders. PMID:21195105

  7. Representations for Semantic Learning Webs: Semantic Web Technology in Learning Support

    ERIC Educational Resources Information Center

    Dzbor, M.; Stutt, A.; Motta, E.; Collins, T.

    2007-01-01

    Recent work on applying semantic technologies to learning has concentrated on providing novel means of accessing and making use of learning objects. However, this is unnecessarily limiting: semantic technologies will make it possible to develop a range of educational Semantic Web services, such as interpretation, structure-visualization, support…

  8. 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...

  9. Semantic deficits in amyotrophic lateral sclerosis.

    PubMed

    Leslie, Felicity V C; Hsieh, Sharpley; Caga, Jashelle; Savage, Sharon A; Mioshi, Eneida; Hornberger, Michael; Kiernan, Matthew C; Hodges, John R; Burrell, James R

    2015-03-01

    Our objective was to investigate, and establish neuroanatomical correlates of, semantic deficits in amyotrophic lateral sclerosis (ALS) and amyotrophic lateral sclerosis-frontotemporal dementia (ALS-FTD), compared to semantic dementia (SD) and controls. Semantic deficits were evaluated using a naming and semantic knowledge composite score, comprising verbal and non-verbal neuropsychological measures of single-word processing (confrontational naming, comprehension, and semantic association) from the Sydney Language Battery (SYDBAT) and Addenbrooke's Cognitive Examination - Revised (ACE-R). Voxel based morphometry (VBM) analysis was conducted using the region of interest approach. In total, 84 participants were recruited from a multidisciplinary research clinic in Sydney. Participants included 17 patients with ALS, 19 with ALS-FTD, 22 with SD and 26 age- and education-matched healthy controls. Significant semantic deficits were observed in ALS and ALS-FTD compared to controls. The severity of semantic deficits varied across the clinical phenotypes: ALS patients were less impaired than ALS-FTD patients, who in turn were not as impaired as SD patients. Anterior temporal lobe atrophy significantly correlated with semantic deficits. In conclusion, semantic impairment is a feature of ALS and ALS-FTD, and reflects the severity of temporal lobe pathology.

  10. Semantic Clustering of Search Engine Results.

    PubMed

    Soliman, Sara Saad; El-Sayed, Maged F; Hassan, Yasser F

    2015-01-01

    This paper presents a novel approach for search engine results clustering that relies on the semantics of the retrieved documents rather than the terms in those documents. The proposed approach takes into consideration both lexical and semantics similarities among documents and applies activation spreading technique in order to generate semantically meaningful clusters. This approach allows documents that are semantically similar to be clustered together rather than clustering documents based on similar terms. A prototype is implemented and several experiments are conducted to test the prospered solution. The result of the experiment confirmed that the proposed solution achieves remarkable results in terms of precision.

  11. Synonyms Provide Semantic Preview Benefit in English

    PubMed Central

    Schotter, Elizabeth R.

    2013-01-01

    While orthographic and phonological preview benefits in reading are uncontroversial (see Schotter, Angele, & Rayner, 2012 for a review), researchers have debated the existence of semantic preview benefit with positive evidence in Chinese and German, but no support in English. Two experiments, using the gazecontingent boundary paradigm (Rayner, 1975), show that semantic preview benefit can be observed in English when the preview and target are synonyms (share the same or highly similar meaning, e.g., curlers-rollers). However, no semantic preview benefit was observed for semantic associates (e.g., curlers-styling). These different preview conditions represent different degrees to which the meaning of the sentence changes when the preview is replaced by the target. When this continuous variable (determined by a norming procedure) was used as the predictor in the analyses, there was a significant relationship between it and all reading time measures, suggesting that similarity in meaning between what is accessed parafoveally and what is processed foveally may be an important influence on the presence of semantic preview benefit. Why synonyms provide semantic preview benefit in reading English is discussed in relation to (1) previous failures to find semantic preview benefit in English and (2) the fact that semantic preview benefit is observed in other languages even for non-synonymous words. Semantic preview benefit is argued to depend on several factors—attentional resources, depth of orthography, and degree of similarity between preview and target. PMID:24347813

  12. Similarity Based Semantic Web Service Match

    NASA Astrophysics Data System (ADS)

    Peng, Hui; Niu, Wenjia; Huang, Ronghuai

    Semantic web service discovery aims at returning the most matching advertised services to the service requester by comparing the semantic of the request service with an advertised service. The semantic of a web service are described in terms of inputs, outputs, preconditions and results in Ontology Web Language for Service (OWL-S) which formalized by W3C. In this paper we proposed an algorithm to calculate the semantic similarity of two services by weighted averaging their inputs and outputs similarities. Case study and applications show the effectiveness of our algorithm in service match.

  13. Semantic Clustering of Search Engine Results

    PubMed Central

    Soliman, Sara Saad; El-Sayed, Maged F.; Hassan, Yasser F.

    2015-01-01

    This paper presents a novel approach for search engine results clustering that relies on the semantics of the retrieved documents rather than the terms in those documents. The proposed approach takes into consideration both lexical and semantics similarities among documents and applies activation spreading technique in order to generate semantically meaningful clusters. This approach allows documents that are semantically similar to be clustered together rather than clustering documents based on similar terms. A prototype is implemented and several experiments are conducted to test the prospered solution. The result of the experiment confirmed that the proposed solution achieves remarkable results in terms of precision. PMID:26933673

  14. Multistage sampling for latent variable models.

    PubMed

    Thomas, Duncan C

    2007-12-01

    I consider the design of multistage sampling schemes for epidemiologic studies involving latent variable models, with surrogate measurements of the latent variables on a subset of subjects. Such models arise in various situations: when detailed exposure measurements are combined with variables that can be used to assign exposures to unmeasured subjects; when biomarkers are obtained to assess an unobserved pathophysiologic process; or when additional information is to be obtained on confounding or modifying variables. In such situations, it may be possible to stratify the subsample on data available for all subjects in the main study, such as outcomes, exposure predictors, or geographic locations. Three circumstances where analytic calculations of the optimal design are possible are considered: (i) when all variables are binary; (ii) when all are normally distributed; and (iii) when the latent variable and its measurement are normally distributed, but the outcome is binary. In each of these cases, it is often possible to considerably improve the cost efficiency of the design by appropriate selection of the sampling fractions. More complex situations arise when the data are spatially distributed: the spatial correlation can be exploited to improve exposure assignment for unmeasured locations using available measurements on neighboring locations; some approaches for informative selection of the measurement sample using location and/or exposure predictor data are considered.

  15. Clinical implication of latent myofascial trigger point.

    PubMed

    Celik, Derya; Mutlu, Ebru Kaya

    2013-08-01

    Myofascial trigger points (MTrPs) are hyperirritable points located within a taut band of skeletal muscle or fascia, which cause referred pain, local tenderness and autonomic changes when compressed. There are fundamental differences between the effects produced by the two basic types of MTrPs (active and latent). Active trigger points (ATrPs) usually produce referred pain and tenderness. In contrast, latent trigger points (LTrPs) are foci of hyperirritability in a taut band of muscle, which are clinically associated with a local twitch response, tenderness and/or referred pain upon manual examination. LTrPs may be found in many pain-free skeletal muscles and may be "activated" and converted to ATrPs by continuous detrimental stimuli. ATrPs can be inactivated by different treatment strategies; however, they never fully disappear but rather convert to the latent form. Therefore, the diagnosis and treatment of LTrPs is important. This review highlights the clinical implication of LTrPs.

  16. Parameter Estimation and Energy Minimization for Region-Based Semantic Segmentation.

    PubMed

    Kumar, M Pawan; Turki, Haithem; Preston, Dan; Koller, Daphne

    2015-07-01

    We consider the problem of parameter estimation and energy minimization for a region-based semantic segmentation model. The model divides the pixels of an image into non-overlapping connected regions, each of which is to a semantic class. In the context of energy minimization, the main problem we face is the large number of putative pixel-to-region assignments. We address this problem by designing an accurate linear programming based approach for selecting the best set of regions from a large dictionary. The dictionary is constructed by merging and intersecting segments obtained from multiple bottom-up over-segmentations. The linear program is solved efficiently using dual decomposition. In the context of parameter estimation, the main problem we face is the lack of fully supervised data. We address this issue by developing a principled framework for parameter estimation using diverse data. More precisely, we propose a latent structural support vector machine formulation, where the latent variables model any missing information in the human annotation. Of particular interest to us are three types of annotations: (i) images segmented using generic foreground or background classes; (ii) images with bounding boxes specified for objects; and (iii) images labeled to indicate the presence of a class. Using large, publicly available datasets we show that our methods are able to significantly improve the accuracy of the region-based model. PMID:26352446

  17. Using a high-dimensional graph of semantic space to model relationships among words

    PubMed Central

    Jackson, Alice F.; Bolger, Donald J.

    2014-01-01

    The GOLD model (Graph Of Language Distribution) is a network model constructed based on co-occurrence in a large corpus of natural language that may be used to explore what information may be present in a graph-structured model of language, and what information may be extracted through theoretically-driven algorithms as well as standard graph analysis methods. The present study will employ GOLD to examine two types of relationship between words: semantic similarity and associative relatedness. Semantic similarity refers to the degree of overlap in meaning between words, while associative relatedness refers to the degree to which two words occur in the same schematic context. It is expected that a graph structured model of language constructed based on co-occurrence should easily capture associative relatedness, because this type of relationship is thought to be present directly in lexical co-occurrence. However, it is hypothesized that semantic similarity may be extracted from the intersection of the set of first-order connections, because two words that are semantically similar may occupy similar thematic or syntactic roles across contexts and thus would co-occur lexically with the same set of nodes. Two versions the GOLD model that differed in terms of the co-occurence window, bigGOLD at the paragraph level and smallGOLD at the adjacent word level, were directly compared to the performance of a well-established distributional model, Latent Semantic Analysis (LSA). The superior performance of the GOLD models (big and small) suggest that a single acquisition and storage mechanism, namely co-occurrence, can account for associative and conceptual relationships between words and is more psychologically plausible than models using singular value decomposition (SVD). PMID:24860525

  18. Semantics-based information modeling for the health-care administration sector: the citation platform.

    PubMed

    Anagnostakis, Aristidis G; Tzima, Maria; Sakellaris, George C; Fotiadis, Dimitrios I; Likas, Aristidis C

    2005-06-01

    An information brokerage environment for effective information structuring, indexing, and retrieval in the health-care administration sector is presented. The system is based on ontology modeling, natural language processing, extensible markup language, semantics analysis, and behavioral description. Semantics-based information acquisition is achieved through the uniform modeling, representation, and handling of domain-specific knowledge, both content-based and procedural. The system has been validated using information located on several repositories in the web and its performance is reported in terms of precision and recall.

  19. Design and implementation of semantics-based image retrieval system

    NASA Astrophysics Data System (ADS)

    Ni, Chundi; Liu, Shenkui; Pan, Ligong; Yin, Xiaowei

    2015-07-01

    Through the study of the existing image retrieval technology, in this paper, a new design scheme of semantics-based image retrieval system is presented. Based on the establishment of mapping relationship between the low-level image features and the low layer of semantic image, this scheme associates the low layer of semantic image with high-level semantics, thus realizing hierarchical semantics description structure, to improve the high-level semantic image recognition accuracy rate.

  20. Semantic tagging of and semantic enhancements to systematics papers: ZooKeys working examples

    PubMed Central

    Penev, Lyubomir; Agosti, Donat; Georgiev, Teodor; Catapano, Terry; Miller, Jeremy; Blagoderov, Vladimir; Roberts, David; Smith, Vincent S.; Brake, Irina; Ryrcroft, Simon; Scott, Ben; Johnson, Norman F.; Morris, Robert A.; Sautter, Guido; Chavan, Vishwas; Robertson, Tim; Remsen, David; Stoev, Pavel; Parr, Cynthia; Knapp, Sandra; Kress, W. John; Thompson, Chris F.; Erwin, Terry

    2010-01-01

    (PTP) to large international database services and indexers such as Global Biodiversity Information Facility (GBIF), National Center for Biotechnology Information (NCBI), Barcode of Life (BOLD), Encyclopedia of Life (EOL), ZooBank, Wikipedia, Wikispecies, Wikimedia, and others; (vi) GenBank accession numbers autotagged and linked to NCBI; (vii) external links of taxon names to references in PubMed, Google Scholar, Biodiversity Heritage Library and other sources. With the launching of the working example, ZooKeys becomes the first taxonomic journal to provide a complete XML-based editorial, publication and dissemination workflow implemented as a routine and cost-efficient practice. It is anticipated that XML-based workflow will also soon be implemented in botany through PhytoKeys, a forthcoming partner journal of ZooKeys. The semantic markup and enhancements are expected to greatly extend and accelerate the way taxonomic information is published, disseminated and used. PMID:21594113

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

    PubMed

    Racoceanu, Daniel; Capron, Frédérique

    2016-01-01

    be devoted to morphological microsemiology (microscopic morphology semantics). Besides insuring the traceability of the results (second opinion) and supporting the orchestration of high-content image analysis modules, the role of semantics will be crucial for the correlation between digital pathology and noninvasive medical imaging modalities. In addition, semantics has an important role in modelling the links between traditional microscopy and recent label-free technologies. The massive amount of visual data is challenging and represents a characteristic intrinsic to digital pathology. The design of an operational integrative microscopy framework needs to focus on scalable multiscale imaging formalism. In this sense, we prospectively consider some of the most recent scalable methodologies adapted to digital pathology as marked point processes for nuclear atypia and point-set mathematical morphology for architecture grading. To orchestrate this scalable framework, semantics-based WSI management (analysis, exploration, indexing, retrieval and report generation support) represents an important means towards approaches to integrating big data into biomedicine. This insight reflects our vision through an instantiation of essential bricks of this type of architecture. The generic approach introduced here is applicable to a number of challenges related to molecular imaging, high-content image management and, more generally, bioinformatics. PMID:27100713

  2. Semantic tagging of and semantic enhancements to systematics papers: ZooKeys working examples.

    PubMed

    Penev, Lyubomir; Agosti, Donat; Georgiev, Teodor; Catapano, Terry; Miller, Jeremy; Blagoderov, Vladimir; Roberts, David; Smith, Vincent S; Brake, Irina; Ryrcroft, Simon; Scott, Ben; Johnson, Norman F; Morris, Robert A; Sautter, Guido; Chavan, Vishwas; Robertson, Tim; Remsen, David; Stoev, Pavel; Parr, Cynthia; Knapp, Sandra; Kress, W John; Thompson, Chris F; Erwin, Terry

    2010-01-01

    large international database services and indexers such as Global Biodiversity Information Facility (GBIF), National Center for Biotechnology Information (NCBI), Barcode of Life (BOLD), Encyclopedia of Life (EOL), ZooBank, Wikipedia, Wikispecies, Wikimedia, and others; (vi) GenBank accession numbers autotagged and linked to NCBI; (vii) external links of taxon names to references in PubMed, Google Scholar, Biodiversity Heritage Library and other sources. With the launching of the working example, ZooKeys becomes the first taxonomic journal to provide a complete XML-based editorial, publication and dissemination workflow implemented as a routine and cost-efficient practice. It is anticipated that XML-based workflow will also soon be implemented in botany through PhytoKeys, a forthcoming partner journal of ZooKeys. The semantic markup and enhancements are expected to greatly extend and accelerate the way taxonomic information is published, disseminated and used. PMID:21594113

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

    PubMed

    Racoceanu, Daniel; Capron, Frédérique

    2016-01-01

    be devoted to morphological microsemiology (microscopic morphology semantics). Besides insuring the traceability of the results (second opinion) and supporting the orchestration of high-content image analysis modules, the role of semantics will be crucial for the correlation between digital pathology and noninvasive medical imaging modalities. In addition, semantics has an important role in modelling the links between traditional microscopy and recent label-free technologies. The massive amount of visual data is challenging and represents a characteristic intrinsic to digital pathology. The design of an operational integrative microscopy framework needs to focus on scalable multiscale imaging formalism. In this sense, we prospectively consider some of the most recent scalable methodologies adapted to digital pathology as marked point processes for nuclear atypia and point-set mathematical morphology for architecture grading. To orchestrate this scalable framework, semantics-based WSI management (analysis, exploration, indexing, retrieval and report generation support) represents an important means towards approaches to integrating big data into biomedicine. This insight reflects our vision through an instantiation of essential bricks of this type of architecture. The generic approach introduced here is applicable to a number of challenges related to molecular imaging, high-content image management and, more generally, bioinformatics.

  4. Allergen databases and allergen semantics.

    PubMed

    Gendel, Steven M

    2009-08-01

    The efficacy of any specific bioinformatic analysis of the potential allergenicity of new food proteins depends directly on the nature and content of the databases that are used in the analysis. A number of different allergen-related databases have been developed, each designed to meet a different need. These databases differ in content, organization, and accessibility. These differences create barriers for users and prevent data sharing and integration. The development and application of appropriate semantic web technologies, (for example, a food allergen ontology) could help to overcome these barriers and promote the development of more advanced analytic capabilities.

  5. Gazetteer Brokering through Semantic Mediation

    NASA Astrophysics Data System (ADS)

    Hobona, G.; Bermudez, L. E.; Brackin, R.

    2013-12-01

    A gazetteer is a geographical directory containing some information regarding places. It provides names, location and other attributes for places which may include points of interest (e.g. buildings, oilfields and boreholes), and other features. These features can be published via web services conforming to the Gazetteer Application Profile of the Web Feature Service (WFS) standard of the Open Geospatial Consortium (OGC). Against the backdrop of advances in geophysical surveys, there has been a significant increase in the amount of data referenced to locations. Gazetteers services have played a significant role in facilitating access to such data, including through provision of specialized queries such as text, spatial and fuzzy search. Recent developments in the OGC have led to advances in gazetteers such as support for multilingualism, diacritics, and querying via advanced spatial constraints (e.g. search by radial search and nearest neighbor). A challenge remaining however, is that gazetteers produced by different organizations have typically been modeled differently. Inconsistencies from gazetteers produced by different organizations may include naming the same feature in a different way, naming the attributes differently, locating the feature in a different location, and providing fewer or more attributes than the other services. The Gazetteer application profile of the WFS is a starting point to address such inconsistencies by providing a standardized interface based on rules specified in ISO 19112, the international standard for spatial referencing by geographic identifiers. The profile, however, does not provide rules to deal with semantic inconsistencies. The USGS and NGA commissioned research into the potential for a Single Point of Entry Global Gazetteer (SPEGG). The research was conducted by the Cross Community Interoperability thread of the OGC testbed, referenced OWS-9. The testbed prototyped approaches for brokering gazetteers through use of semantic

  6. The Semantic Web and Educational Technology

    ERIC Educational Resources Information Center

    Maddux, Cleborne D., Ed.

    2008-01-01

    The "Semantic Web" is an idea proposed by Tim Berners-Lee, the inventor of the "World Wide Web." The topic has been generating a great deal of interest and enthusiasm, and there is a rapidly growing body of literature dealing with it. This article attempts to explain how the Semantic Web would work, and explores short-term and long-term…

  7. Spatial information semantic query based on SPARQL

    NASA Astrophysics Data System (ADS)

    Xiao, Zhifeng; Huang, Lei; Zhai, Xiaofang

    2009-10-01

    How can the efficiency of spatial information inquiries be enhanced in today's fast-growing information age? We are rich in geospatial data but poor in up-to-date geospatial information and knowledge that are ready to be accessed by public users. This paper adopts an approach for querying spatial semantic by building an Web Ontology language(OWL) format ontology and introducing SPARQL Protocol and RDF Query Language(SPARQL) to search spatial semantic relations. It is important to establish spatial semantics that support for effective spatial reasoning for performing semantic query. Compared to earlier keyword-based and information retrieval techniques that rely on syntax, we use semantic approaches in our spatial queries system. Semantic approaches need to be developed by ontology, so we use OWL to describe spatial information extracted by the large-scale map of Wuhan. Spatial information expressed by ontology with formal semantics is available to machines for processing and to people for understanding. The approach is illustrated by introducing a case study for using SPARQL to query geo-spatial ontology instances of Wuhan. The paper shows that making use of SPARQL to search OWL ontology instances can ensure the result's accuracy and applicability. The result also indicates constructing a geo-spatial semantic query system has positive efforts on forming spatial query and retrieval.

  8. Semantics vs Pragmatics of a Compound Word

    ERIC Educational Resources Information Center

    Smirnova, Elena A.; Biktemirova, Ella I.; Davletbaeva, Diana N.

    2016-01-01

    This paper is devoted to the study of correlation between semantic and pragmatic potential of a compound word, which functions in informal speech, and the mechanisms of secondary nomination, which realizes the potential of semantic-pragmatic features of colloquial compounds. The relevance and the choice of the research question is based on the…

  9. Analyticity and Features of Semantic Interaction.

    ERIC Educational Resources Information Center

    Steinberg, Danny D.

    The findings reported in this paper are the result of an experiment to determine the empirical validity of such semantic concepts as analytic, synthetic, and contradictory. Twenty-eight university students were presented with 156 sentences to assign to one of four semantic categories: (1) synthetic ("The dog is a poodle"), (2) analytic ("The tulip…

  10. Computation of Semantic Number from Morphological Information

    ERIC Educational Resources Information Center

    Berent, Iris; Pinker, Steven; Tzelgov, Joseph; Bibi, Uri; Goldfarb, Liat

    2005-01-01

    The distinction between singular and plural enters into linguistic phenomena such as morphology, lexical semantics, and agreement and also must interface with perceptual and conceptual systems that assess numerosity in the world. Three experiments examine the computation of semantic number for singulars and plurals from the morphological…

  11. 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

  12. Semantic and Phonemic Verbal Fluency in Blinds

    ERIC Educational Resources Information Center

    Nejati, Vahid; Asadi, Anoosh

    2010-01-01

    A person who has suffered the total loss of a sensory system has, indirectly, suffered a brain lesion. Semantic and phonologic verbal fluency are used for evaluation of executive function and language. The aim of this study is evaluation and comparison of phonemic and semantic verbal fluency in acquired blinds. We compare 137 blinds and 124…

  13. Aspects of Semantic Theory and Reading Comprehension.

    ERIC Educational Resources Information Center

    Jeremiah, Milford A.

    This paper investigates the ways readers use two semantic tools, synonymy and entailment, when responding to reading-comprehension questions. After a brief overview of semantic theory, two reading passages and their attendant multiple-choice questions are analyzed, demonstrating how readers might choose the correct answer by analyzing the way it…

  14. Neuronal Activation for Semantically Reversible Sentences

    ERIC Educational Resources Information Center

    Richardson, Fiona M.; Thomas, Michael S. C.; Price, Cathy J.

    2010-01-01

    Semantically reversible sentences are prone to misinterpretation and take longer for typically developing children and adults to comprehend; they are also particularly problematic for those with language difficulties such as aphasia or Specific Language Impairment. In our study, we used fMRI to compare the processing of semantically reversible and…

  15. Orthographic and Semantic Processing in Young Readers

    ERIC Educational Resources Information Center

    Polse, Lara R.; Reilly, Judy S.

    2015-01-01

    This investigation examined orthographic and semantic processing during reading acquisition. Children in first to fourth grade were presented with a target word and two response alternatives, and were asked to identify the semantic match. Words were presented in four conditions: an exact match and unrelated foil (STONE-STONE-EARS), an exact match…

  16. The Semantic Web in Teacher Education

    ERIC Educational Resources Information Center

    Czerkawski, Betül Özkan

    2014-01-01

    The Semantic Web enables increased collaboration among computers and people by organizing unstructured data on the World Wide Web. Rather than a separate body, the Semantic Web is a functional extension of the current Web made possible by defining relationships among websites and other online content. When explicitly defined, these relationships…

  17. Social Semantics for an Effective Enterprise

    NASA Technical Reports Server (NTRS)

    Berndt, Sarah; Doane, Mike

    2012-01-01

    An evolution of the Semantic Web, the Social Semantic Web (s2w), facilitates knowledge sharing with "useful information based on human contributions, which gets better as more people participate." The s2w reaches beyond the search box to move us from a collection of hyperlinked facts, to meaningful, real time context. When focused through the lens of Enterprise Search, the Social Semantic Web facilitates the fluid transition of meaningful business information from the source to the user. It is the confluence of human thought and computer processing structured with the iterative application of taxonomies, folksonomies, ontologies, and metadata schemas. The importance and nuances of human interaction are often deemphasized when focusing on automatic generation of semantic markup, which results in dissatisfied users and unrealized return on investment. Users consistently qualify the value of information sets through the act of selection, making them the de facto stakeholders of the Social Semantic Web. Employers are the ultimate beneficiaries of s2w utilization with a better informed, more decisive workforce; one not achieved with an IT miracle technology, but by improved human-computer interactions. Johnson Space Center Taxonomist Sarah Berndt and Mike Doane, principal owner of Term Management, LLC discuss the planning, development, and maintenance stages for components of a semantic system while emphasizing the necessity of a Social Semantic Web for the Enterprise. Identification of risks and variables associated with layering the successful implementation of a semantic system are also modeled.

  18. Learning the Semantics of Structured Data Sources

    ERIC Educational Resources Information Center

    Taheriyan, Mohsen

    2015-01-01

    Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data, however, they rarely provide a semantic model to describe their contents. Semantic models of data sources capture the intended meaning of data sources by mapping them to the concepts and relationships defined by a…

  19. Should We Teach Semantic Prosody Awareness?

    ERIC Educational Resources Information Center

    McGee, Iain

    2012-01-01

    While considerable attention has been paid to collocation, and the development of the collocational competence of L2 learners in recent years, very little has been said about a related concept in teaching journals, namely semantic prosody, and L2 learner awareness of this phenomenon. In this paper the concept of semantic prosody is introduced, and…

  20. Quantifying Semantic Linguistic Maturity in Children

    ERIC Educational Resources Information Center

    Hansson, Kristina; Bååth, Rasmus; Löhndorf, Simone; Sahlén, Birgitta; Sikström, Sverker

    2016-01-01

    We propose a method to quantify "semantic linguistic maturity" (SELMA) based on a high dimensional semantic representation of words created from the co-occurrence of words in a large text corpus. The method was applied to oral narratives from 108 children aged 4;0-12;10. By comparing the SELMA measure with maturity ratings made by human…

  1. Implicit Learning of Semantic Preferences of Verbs

    ERIC Educational Resources Information Center

    Paciorek, Albertyna; Williams, John N.

    2015-01-01

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

  2. Social Networking on the Semantic Web

    ERIC Educational Resources Information Center

    Finin, Tim; Ding, Li; Zhou, Lina; Joshi, Anupam

    2005-01-01

    Purpose: Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach: The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents with social network information that were encoded using the…

  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. Phasic Affective Modulation of Semantic Priming

    ERIC Educational Resources Information Center

    Topolinski, Sascha; Deutsch, Roland

    2013-01-01

    The present research demonstrates that very brief variations in affect, being around 1 s in length and changing from trial to trial independently from semantic relatedness of primes and targets, modulate the amount of semantic priming. Implementing consonant and dissonant chords (Experiments 1 and 5), naturalistic sounds (Experiment 2), and visual…

  5. Is There a Critical Period for Semantics?

    ERIC Educational Resources Information Center

    Slabakova, Roumyana

    2006-01-01

    This article reviews recent research on the second language acquisition of meaning with a view of establishing whether there is a critical period for the acquisition of compositional semantics. It is claimed that the functional lexicon presents the most formidable challenge, while syntax and phrasal semantics pose less difficulty to learners.…

  6. Elaborative Retrieval: Do Semantic Mediators Improve Memory?

    ERIC Educational Resources Information Center

    Lehman, Melissa; Karpicke, Jeffrey D.

    2016-01-01

    The elaborative retrieval account of retrieval-based learning proposes that retrieval enhances retention because the retrieval process produces the generation of semantic mediators that link cues to target information. We tested 2 assumptions that form the basis of this account: that semantic mediators are more likely to be generated during…

  7. Semantique et psychologie (Semantics and Psychology)

    ERIC Educational Resources Information Center

    Le Ny, Jean-Francois

    1975-01-01

    Semantic activities constitute a sub-class of psychological activities; from this point of departure the article discusses such topics as: idiosyncrasies, meaning and causality, internal determinants, neo-associationism, componential theories, noun- and verb-formation, sentences and propositions, semantics and cognition, mnemesic compontents, and…

  8. Priming Addition Facts with Semantic Relations

    ERIC Educational Resources Information Center

    Bassok, Miriam; Pedigo, Samuel F.; Oskarsson, An T.

    2008-01-01

    Results from 2 relational-priming experiments suggest the existence of an automatic analogical coordination between semantic and arithmetic relations. Word pairs denoting object sets served as primes in a task that elicits "obligatory" activation of addition facts (5 + 3 activates 8; J. LeFevre, J. Bisanz, & L. Mrkonjic, 1988). Semantic relations…

  9. An Approach to the Semantics of Verbs.

    ERIC Educational Resources Information Center

    von Glasersfeld, Ernst

    This paper explains a method of semantic analysis developed in the course of a natural-language research project that led to the computer implementation of the Multistore Parser. Positing an interlinguistic substratum of semantic particles of several different types (e.g. substantive, attributive, developmental, relational), a method is…

  10. INDEXING MECHANISM

    DOEpatents

    Kock, L.J.

    1959-09-22

    A device is presented for loading and unloading fuel elements containing material fissionable by neutrons of thermal energy. The device comprises a combination of mechanical features Including a base, a lever pivotally attached to the base, an Indexing plate on the base parallel to the plane of lever rotation and having a plurality of apertures, the apertures being disposed In rows, each aperture having a keyway, an Index pin movably disposed to the plane of lever rotation and having a plurality of apertures, the apertures being disposed in rows, each aperture having a keyway, an index pin movably disposed on the lever normal to the plane rotation, a key on the pin, a sleeve on the lever spaced from and parallel to the index pin, a pair of pulleys and a cable disposed between them, an open collar rotatably attached to the sleeve and linked to one of the pulleys, a pin extending from the collar, and a bearing movably mounted in the sleeve and having at least two longitudinal grooves in the outside surface.

  11. An Analysis of Semantic Aware Crossover

    NASA Astrophysics Data System (ADS)

    Uy, Nguyen Quang; Hoai, Nguyen Xuan; O'Neill, Michael; McKay, Bob; Galván-López, Edgar

    It is well-known that the crossover operator plays an important role in Genetic Programming (GP). In Standard Crossover (SC), semantics are not used to guide the selection of the crossover points, which are generated randomly. This lack of semantic information is the main cause of destructive effects from SC (e.g., children having lower fitness than their parents). Recently, we proposed a new semantic based crossover known GP called Semantic Aware Crossover (SAC) [25]. We show that SAC outperforms SC in solving a class of real-value symbolic regression problems. We clarify the effect of SAC on GP search in increasing the semantic diversity of the population, thus helping to reduce the destructive effects of crossover in GP.

  12. Semantic Context Detection Using Audio Event Fusion

    NASA Astrophysics Data System (ADS)

    Chu, Wei-Ta; Cheng, Wen-Huang; Wu, Ja-Ling

    2006-12-01

    Semantic-level content analysis is a crucial issue in achieving efficient content retrieval and management. We propose a hierarchical approach that models audio events over a time series in order to accomplish semantic context detection. Two levels of modeling, audio event and semantic context modeling, are devised to bridge the gap between physical audio features and semantic concepts. In this work, hidden Markov models (HMMs) are used to model four representative audio events, that is, gunshot, explosion, engine, and car braking, in action movies. At the semantic context level, generative (ergodic hidden Markov model) and discriminative (support vector machine (SVM)) approaches are investigated to fuse the characteristics and correlations among audio events, which provide cues for detecting gunplay and car-chasing scenes. The experimental results demonstrate the effectiveness of the proposed approaches and provide a preliminary framework for information mining by using audio characteristics.

  13. Minding the PS, queues, and PXQs: Uniformity of semantic processing across multiple stimulus types

    PubMed Central

    Laszlo, Sarah; Federmeier, Kara D.

    2009-01-01

    An assumption in the reading literature is that access to semantics is gated by stimulus properties such as orthographic regularity or familiarity. In the electrophysiological domain, this assumption has led to a debate about the features necessary to initiate semantic processing as indexed by theN400 event-related potential (ERP) component. To examine this, we recorded ERPs to sentences with endings that were familiar and legal (words), familiar and illegal (acronyms), or unfamiliar and illegal (consonant or vowel strings). N400 congruency effects (reduced negativity to expected relative to unexpected endings) were observed for words and acronyms; these were identical in size, timing, and scalp distribution. Notably, clear N400 potentials were also elicited by unfamiliar, illegal strings, suggesting that, at least in a verbal context, semantic access may be attempted for any letter string, regardless of familiarity or regularity. PMID:18221447

  14. Latent Viruses: A Space Travel Hazard??

    NASA Technical Reports Server (NTRS)

    Ling, P. D.; Peng, R. S.; Pierson, D.; Lednicky, J.; Butel, J. S.

    1999-01-01

    A major issue associated with long-duration space flight is the possibility of infectious disease causing an unacceptable medical risk to crew members. Our proposal is designed to gain information that addresses several issues outlined in the Immunology/Infectious disease critical path. The major hypothesis addressed is that space flight causes alterations in the immune system that may allow latent viruses which are endogenous in the human population to reactivate and shed to higher levels than normal which can affect the health of crew members during a long term space-flight mission. We will initially focus our studies on the human herpesviruses and human polyomaviruses which are important pathogens known to establish latent infections in the human population. Both primary infection and reactivation from latent infection with this group of viruses can cause a variety of illnesses that result in morbidity and occasionally mortality of infected individuals. Effective vaccines exist for only one of the eight known human herpesviruses and the vaccine itself can still reactivate from latent infection. Available antivirals are of limited use and are effective against only a few of the human herpesviruses. Although most individuals display little if any clinical consequences from latent infection, events which alter immune function such as immunosuppressive therapy following solid organ transplantation are known to increase the risk of developing complications as a result of latent virus reactivation. This proposal will measure both the frequency and magnitude of viral shedding and genome loads in the blood from humans participating in activities that serve as ground based models of space flight conditions. Our initial goal is to develop sensitive quantitative competitive PCR- based assays (QC-PCR) to detect the herpesvirus Epstein-Barr virus (EBV), and the polyomaviruses SV40, BKV, and JCV. Using these assays we will establish baseline patterns of viral genome load in

  15. Targeting the latent reservoir to achieve functional HIV cure

    PubMed Central

    Cary, Daniele C.; Peterlin, B. Matija

    2016-01-01

    While highly active anti-retroviral therapy has greatly improved the lives of HIV-infected individuals, current treatments are unable to completely eradicate the virus. This is due to the presence of HIV latently infected cells which harbor transcriptionally silent HIV. Latent HIV does not replicate or produce viral proteins, thereby preventing efficient targeting by anti-retroviral drugs. Strategies to target the HIV latent reservoir include viral reactivation, enhancing host defense mechanisms, keeping latent HIV silent, and using gene therapy techniques to knock out or reactivate latent HIV. While research into each of these areas has yielded promising results, currently no one mechanism eradicates latent HIV. Instead, combinations of these approaches should be considered for a potential HIV functional cure. PMID:27303638

  16. Determining Semantically Related Significant Genes.

    PubMed

    Taha, Kamal

    2014-01-01

    GO relation embodies some aspects of existence dependency. If GO term xis existence-dependent on GO term y, the presence of y implies the presence of x. Therefore, the genes annotated with the function of the GO term y are usually functionally and semantically related to the genes annotated with the function of the GO term x. A large number of gene set enrichment analysis methods have been developed in recent years for analyzing gene sets enrichment. However, most of these methods overlook the structural dependencies between GO terms in GO graph by not considering the concept of existence dependency. We propose in this paper a biological search engine called RSGSearch that identifies enriched sets of genes annotated with different functions using the concept of existence dependency. We observe that GO term xcannot be existence-dependent on GO term y, if x- and y- have the same specificity (biological characteristics). After encoding into a numeric format the contributions of GO terms annotating target genes to the semantics of their lowest common ancestors (LCAs), RSGSearch uses microarray experiment to identify the most significant LCA that annotates the result genes. We evaluated RSGSearch experimentally and compared it with five gene set enrichment systems. Results showed marked improvement.

  17. Solar desalination with latent heat recovery

    SciTech Connect

    Assouad, Y.; Lavan, Z.

    1988-02-01

    Unlike conventional solar stills, the present system utilizes the latent heat of condensation and the sensible heat of the discarded seawater. The performance was optimized analytically and the system is presently under construction in Egypt. The system consists of a humidifier, a solar still or channel, a condenser, and a pond. In the humidifier, ambient air is humidified and heated by a warm brine from the pond. If the brine outlet temperature is higher than the ambient temperature, it goes back to the pond, if not, it is discarded. The solar still is a long glass-covered channel, about 200 meters long.

  18. Argumentation-Based Indexing for Information Retrieval from Learned Articles.

    ERIC Educational Resources Information Center

    Sillince, J. A. A.

    1992-01-01

    Proposes an argumentation-based method for information retrieval that involves representing a scholarly article by means of rhetorical structure rather than by a semantic representation of content. Topics addressed include problems with indexing practices, the argumentative nature of articles, rhetoric as an information categorizing schema, and…

  19. On Automatic Support to Indexing a Life Sciences Data Base.

    ERIC Educational Resources Information Center

    Vleduts-Stokolov, N.

    1982-01-01

    Describes technique developed as automatic support to subject heading indexing at BIOSIS based on use of formalized language for semantic representation of biological texts and subject headings. Language structures, experimental results, and analysis of journal/subject heading and author/subject heading correlation data are discussed. References…

  20. Research on Automatic Indexing, Classification, and Abstracting Techniques. Final Report.

    ERIC Educational Resources Information Center

    Williams, John H., Jr.

    The report very briefly summarizes the research performed during the contract period March 1, 1964, to February 28, 1971. The emphasis of the research was on the discovery and development of techniques for automatically indexing and classifying documents. The research was limited to statistical techniques rather than semantic or syntactic. A…

  1. The Identification of Index Terms in Natural Language Object Descriptions.

    ERIC Educational Resources Information Center

    Heidorn, P. Bryan

    1999-01-01

    Examines the vocabulary and communication constructs that are used by novices and domain experts to describe objects in an object identification task. Results suggest that indexing and retrieval systems should provide semantic level similarity mechanisms to allow for whole-object as well as part-wise visual analogy. The systems should also provide…

  2. A hierarchical knowledge-based approach for retrieving similar medical images described with semantic annotations

    PubMed Central

    Kurtz, Camille; Beaulieu, Christopher F.; Napel, Sandy; Rubin, Daniel L.

    2014-01-01

    Computer-assisted image retrieval applications could assist radiologist interpretations by identifying similar images in large archives as a means to providing decision support. However, the semantic gap between low-level image features and their high level semantics may impair the system performances. Indeed, it can be challenging to comprehensively characterize the images using low-level imaging features to fully capture the visual appearance of diseases on images, and recently the use of semantic terms has been advocated to provide semantic descriptions of the visual contents of images. However, most of the existing image retrieval strategies do not consider the intrinsic properties of these terms during the comparison of the images beyond treating them as simple binary (presence/absence) features. We propose a new framework that includes semantic features in images and that enables retrieval of similar images in large databases based on their semantic relations. It is based on two main steps: (1) annotation of the images with semantic terms extracted from an ontology, and (2) evaluation of the similarity of image pairs by computing the similarity between the terms using the Hierarchical Semantic-Based Distance (HSBD) coupled to an ontological measure. The combination of these two steps provides a means of capturing the semantic correlations among the terms used to characterize the images that can be considered as a potential solution to deal with the semantic gap problem. We validate this approach in the context of the retrieval and the classification of 2D regions of interest (ROIs) extracted from computed tomographic (CT) images of the liver. Under this framework, retrieval accuracy of more than 0.96 was obtained on a 30-images dataset using the Normalized Discounted Cumulative Gain (NDCG) index that is a standard technique used to measure the effectiveness of information retrieval algorithms when a separate reference standard is available. Classification

  3. Bayesian Analysis of Multivariate Latent Curve Models with Nonlinear Longitudinal Latent Effects

    ERIC Educational Resources Information Center

    Song, Xin-Yuan; Lee, Sik-Yum; Hser, Yih-Ing

    2009-01-01

    In longitudinal studies, investigators often measure multiple variables at multiple time points and are interested in investigating individual differences in patterns of change on those variables. Furthermore, in behavioral, social, psychological, and medical research, investigators often deal with latent variables that cannot be observed directly…

  4. Dimensionality of the Latent Structure and Item Selection via Latent Class Multidimensional IRT Models

    ERIC Educational Resources Information Center

    Bartolucci, F.; Montanari, G. E.; Pandolfi, S.

    2012-01-01

    With reference to a questionnaire aimed at assessing the performance of Italian nursing homes on the basis of the health conditions of their patients, we investigate two relevant issues: dimensionality of the latent structure and discriminating power of the items composing the questionnaire. The approach is based on a multidimensional item…

  5. Functional networks underlying latent inhibition learning in the mouse brain.

    PubMed

    Puga, Frank; Barrett, Douglas W; Bastida, Christel C; Gonzalez-Lima, F

    2007-10-15

    The present study reports the first comprehensive map of brain networks underlying latent inhibition learning and the first application of structural equation modeling to cytochrome oxidase data. In latent inhibition, repeated exposure to a stimulus results in a latent form of learning that inhibits subsequent associations with that stimulus. As neuronal energy demands to form learned associations changes, so does the induction of the respiratory enzyme cytochrome oxidase. Therefore, cytochrome oxidase can be used as an endpoint metabolic marker of the effects of experience on regional brain metabolic capacity. Quantitative cytochrome oxidase histochemistry was used to map brain regions in mice trained on a tone-footshock fear conditioning paradigm with either tone preexposure (latent inhibition), conditioning only (acquisition), conditioning followed by tone alone (extinction), or no handling or conditioning (naive). The ventral cochlear nucleus, medial geniculate, CA1 hippocampus, and perirhinal cortex showed modified metabolic capacity due to latent inhibition. Structural equation modeling was used to determine the causal influences in an anatomical network of these regions and others thought to mediate latent inhibition, including the accumbens and entorhinal cortex. An uncoupling of ascending influences between auditory regions was observed in latent inhibition. There was also a reduced influence on the accumbens from the perirhinal cortex in both latent inhibition and extinction. The results suggest a specific network with a neural mechanism of latent inhibition that appears to involve sensory gating, as evidenced by modifications in metabolic capacity and effective connectivity between auditory regions and reduced perirhinal cortex influence on the accumbens.

  6. Determination of the Latent Heats and Triple Point of Perfluorocyclobutane

    ERIC Educational Resources Information Center

    Briggs, A. G.; Strachan, A. N.

    1977-01-01

    Proposes the use of Perfluorocyclobutane in physical chemistry courses to conduct experiments on latent heat, triple point temperatures and pressures, boiling points, and entropy of vaporization. (SL)

  7. A brain electrical signature of left-lateralized semantic activation from single words.

    PubMed

    Koppehele-Gossel, Judith; Schnuerch, Robert; Gibbons, Henning

    2016-01-01

    Lesion and imaging studies consistently indicate a left-lateralization of semantic language processing in human temporo-parietal cortex. Surprisingly, electrocortical measures, which allow a direct assessment of brain activity and the tracking of cognitive functions with millisecond precision, have not yet been used to capture this hemispheric lateralization, at least with respect to posterior portions of this effect. Using event-related potentials, we employed a simple single-word reading paradigm to compare neural activity during three tasks requiring different degrees of semantic processing. As expected, we were able to derive a simple temporo-parietal left-right asymmetry index peaking around 300ms into word processing that neatly tracks the degree of semantic activation. The validity of this measure in specifically capturing verbal semantic activation was further supported by a significant relation to verbal intelligence. We thus posit that it represents a promising tool to monitor verbal semantic processing in the brain with little technological effort and in a minimal experimental setup. PMID:27156035

  8. A Framework for Reproducible Latent Fingerprint Enhancements

    PubMed Central

    Carasso, Alfred S.

    2014-01-01

    Photoshop processing1 of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology. PMID:26601028

  9. A Framework for Reproducible Latent Fingerprint Enhancements.

    PubMed

    Carasso, Alfred S

    2014-01-01

    Photoshop processing of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology.

  10. Latent TGF-[beta] structure and activation

    SciTech Connect

    Shi, Minlong; Zhu, Jianghai; Wang, Rui; Chen, Xing; Mi, Lizhi; Walz, Thomas; Springer, Timothy A.

    2011-09-16

    Transforming growth factor (TGF)-{beta} is stored in the extracellular matrix as a latent complex with its prodomain. Activation of TGF-{beta}1 requires the binding of {alpha}v integrin to an RGD sequence in the prodomain and exertion of force on this domain, which is held in the extracellular matrix by latent TGF-{beta} binding proteins. Crystals of dimeric porcine proTGF-{beta}1 reveal a ring-shaped complex, a novel fold for the prodomain, and show how the prodomain shields the growth factor from recognition by receptors and alters its conformation. Complex formation between {alpha}v{beta}6 integrin and the prodomain is insufficient for TGF-{beta}1 release. Force-dependent activation requires unfastening of a 'straitjacket' that encircles each growth-factor monomer at a position that can be locked by a disulphide bond. Sequences of all 33 TGF-{beta} family members indicate a similar prodomain fold. The structure provides insights into the regulation of a family of growth and differentiation factors of fundamental importance in morphogenesis and homeostasis.

  11. Visualization of latent fingerprint corrosion of brass.

    PubMed

    Bond, John W

    2009-09-01

    Visualization of latent fingerprint deposits on metals by enhancing the fingerprint-induced corrosion is now an established technique. However, the corrosion mechanism itself is less well understood. Here, we describe the apparatus constructed to measure the spatial variation (DeltaV) in applied potential (V) over the surface of brass disks corroded by latent fingerprint deposits. Measurement of DeltaV for potential of 1400 V has enabled visualization of fingerprint ridges and characteristics in terms of this potential difference with DeltaV typically of a few volts. This visualization is consistent with the formation of a Schottky barrier at the brass-corrosion product junction. Measurement of the work function of the corroded brass of up to 4.87 +/- 0.03 eV supports previous results that suggested that the corrosion product is composed of p-type copper oxides. A model for the galvanic corrosion of brass by ionic salts present in fingerprint deposits is proposed that is consistent with these experimental results.

  12. A Framework for Reproducible Latent Fingerprint Enhancements.

    PubMed

    Carasso, Alfred S

    2014-01-01

    Photoshop processing of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology. PMID:26601028

  13. Shared Features Dominate Semantic Richness Effects for Concrete Concepts

    ERIC Educational Resources Information Center

    Grondin, Ray; Lupker, Stephen J.; McRae, Ken

    2009-01-01

    When asked to list semantic features for concrete concepts, participants list many features for some concepts and few for others. Concepts with many semantic features are processed faster in lexical and semantic decision tasks [Pexman, P. M., Lupker, S. J., & Hino, Y. (2002). "The impact of feedback semantics in visual word recognition:…

  14. Proof-Theoretic Semantics for a Natural Language Fragment

    NASA Astrophysics Data System (ADS)

    Francez, Nissim; Dyckhoff, Roy

    We propose a Proof - Theoretic Semantics (PTS) for a (positive) fragment E+0 of Natural Language (NL) (English in this case). The semantics is intended [7] to be incorporated into actual grammars, within the framework of Type - Logical Grammar (TLG) [12]. Thereby, this semantics constitutes an alternative to the traditional model - theoretic semantics (MTS), originating in Montague's seminal work [11], used in TLG.

  15. The Influence of Semantic Neighbours on Visual Word Recognition

    ERIC Educational Resources Information Center

    Yates, Mark

    2012-01-01

    Although it is assumed that semantics is a critical component of visual word recognition, there is still much that we do not understand. One recent way of studying semantic processing has been in terms of semantic neighbourhood (SN) density, and this research has shown that semantic neighbours facilitate lexical decisions. However, it is not clear…

  16. Semantic Priming for Coordinate Distant Concepts in Alzheimer's Disease Patients

    ERIC Educational Resources Information Center

    Perri, R.; Zannino, G. D.; Caltagirone, C.; Carlesimo, G. A.

    2011-01-01

    Semantic priming paradigms have been used to investigate semantic knowledge in patients with Alzheimer's disease (AD). While priming effects produced by prime-target pairs with associative relatedness reflect processes at both lexical and semantic levels, priming effects produced by words that are semantically related but not associated should…

  17. Verb Production during Action Naming in Semantic Dementia

    ERIC Educational Resources Information Center

    Meligne, D.; Fossard, M.; Belliard, S.; Moreaud, O.; Duvignau, K.; Demonet, J.-F.

    2011-01-01

    In contrast with widely documented deficits of semantic knowledge relating to object concepts and the corresponding nouns in semantic dementia (SD), little is known about action semantics and verb production in SD. The degradation of action semantic knowledge was studied in 5 patients with SD compared with 17 matched control participants in an…

  18. Uncovering the Architecture of Action Semantics

    PubMed Central

    Watson, Christine E.; Buxbaum, Laurel J.

    2014-01-01

    Despite research suggesting that stored sensorimotor information about tool use is a component of the semantic representations of tools, little is known about the action features or organizing principles that underlie this knowledge. We used methods similar to those applied in other semantic domains to examine the “architecture” of action semantic knowledge. In Experiment 1, participants sorted photographs of tools into groups according to the similarity of their associated “use” actions and rated tools on dimensions related to action. The results suggest that the magnitude of arm movement, configuration of the hand, and manner of motion during tool use play a role in determining how tools cluster in action “semantic space”. In Experiment 2, we validated the architecture uncovered in Experiment 1 using an implicit semantic task for which tool use knowledge was not ostensibly relevant (blocked cyclic word-picture matching). Using stimuli from Experiment 1, we found that participants performed more poorly during blocks of trials containing tools used with similar versus unrelated actions, and the amount of semantic interference depended on the magnitude of action similarity among tools. Thus, the degree of featural overlap between tool use actions plays a role in determining the overall semantic similarity of tools. PMID:25045905

  19. Episodic memory, semantic memory, and amnesia.

    PubMed

    Squire, L R; Zola, S M

    1998-01-01

    Episodic memory and semantic memory are two types of declarative memory. There have been two principal views about how this distinction might be reflected in the organization of memory functions in the brain. One view, that episodic memory and semantic memory are both dependent on the integrity of medial temporal lobe and midline diencephalic structures, predicts that amnesic patients with medial temporal lobe/diencephalic damage should be proportionately impaired in both episodic and semantic memory. An alternative view is that the capacity for semantic memory is spared, or partially spared, in amnesia relative to episodic memory ability. This article reviews two kinds of relevant data: 1) case studies where amnesia has occurred early in childhood, before much of an individual's semantic knowledge has been acquired, and 2) experimental studies with amnesic patients of fact and event learning, remembering and knowing, and remote memory. The data provide no compelling support for the view that episodic and semantic memory are affected differently in medial temporal lobe/diencephalic amnesia. However, episodic and semantic memory may be dissociable in those amnesic patients who additionally have severe frontal lobe damage.

  20. Uncovering the architecture of action semantics.

    PubMed

    Watson, Christine E; Buxbaum, Laurel J

    2014-10-01

    Despite research suggesting that stored sensorimotor information about tool use is a component of the semantic representations of tools, little is known about the action features or organizing principles that underlie this knowledge. We used methods similar to those applied in other semantic domains to examine the "architecture" of action semantic knowledge. In Experiment 1, participants sorted photographs of tools into groups according to the similarity of their associated "use" actions and rated tools on dimensions related to action. The results suggest that the magnitude of arm movement, configuration of the hand, and manner of motion during tool use play a role in determining how tools cluster in action "semantic space." In Experiment 2, we validated the architecture uncovered in Experiment 1 using an implicit semantic task for which tool use knowledge was not ostensibly relevant (blocked cyclic word-picture matching). Using stimuli from Experiment 1, we found that participants performed more poorly during blocks of trials containing tools used with similar versus unrelated actions, and the amount of semantic interference depended on the magnitude of action similarity among tools. Thus, the degree of featural overlap between tool use actions plays a role in determining the overall semantic similarity of tools.

  1. Preserved semantic access in neglect dyslexia.

    PubMed

    Làdavas, E; Shallice, T; Zanella, M T

    1997-03-01

    The aim of this study was to investigate the preservation of semantic access in patients with severe neglect dyslexia for words and non-words. Patients were given the following tasks: (1) reading aloud letter strings (first basic reading task), (2) making semantic decisions (categorial and inferential judgements), (3) making semantic decisions and reading the letter strings immediately afterwards (semantic-reading tasks), (4) reading letter strings again (final basic reading tasks) and (5) auditory control tasks. Of 23 patients with visual neglect, four showed neglect dyslexia for both words and non-words. Of these four patients, three showed a performance in the semantic tasks that was as good as in the auditory condition. Moreover, the reading of the patients improved dramatically in the semantic-reading tasks but this was not maintained in the final basic reading task. Non-words showed only a minor improvement. Findings are discussed in terms of an interaction between the attentional system and the different reading routes, and provide evidence that semantic routes are less affected by neglect.

  2. Semantic classification of pictures and words.

    PubMed

    Taikh, Alex; Hargreaves, Ian S; Yap, Melvin J; Pexman, Penny M

    2015-01-01

    We provide new behavioural norms for semantic classification of pictures and words. The picture stimuli are 288 black and white line drawings from the International Picture Naming Project ([Székely, A., Jacobsen, T., D'Amico, S., Devescovi, A., Andonova, E., Herron, D., et al. (2004). A new on-line resource for psycholinguistic studies. Journal of Memory & Language, 51, 247-250]). We presented these pictures for classification in a living/nonliving decision, and in a separate version of the task presented the corresponding word labels for classification. We analyzed behavioural responses to a subset of the stimuli in order to explore questions about semantic processing. We found multiple semantic richness effects for both picture and word classification. Further, while lexical-level factors were related to semantic classification of words, they were not related to semantic classification of pictures. We argue that these results are consistent with privileged semantic access for pictures, and point to ways in which these data could be used to address other questions about picture processing and semantic memory. PMID:25403693

  3. Varieties of semantic ‘access’ deficit in Wernicke’s aphasia and semantic aphasia

    PubMed Central

    Robson, Holly; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

    2015-01-01

    Comprehension deficits are common in stroke aphasia, including in cases with (i) semantic aphasia, characterized by poor executive control of semantic processing across verbal and non-verbal modalities; and (ii) Wernicke’s aphasia, associated with poor auditory–verbal comprehension and repetition, plus fluent speech with jargon. However, the varieties of these comprehension problems, and their underlying causes, are not well understood. Both patient groups exhibit some type of semantic ‘access’ deficit, as opposed to the ‘storage’ deficits observed in semantic dementia. Nevertheless, existing descriptions suggest that these patients might have different varieties of ‘access’ impairment—related to difficulty resolving competition (in semantic aphasia) versus initial activation of concepts from sensory inputs (in Wernicke’s aphasia). We used a case series design to compare patients with Wernicke’s aphasia and those with semantic aphasia on Warrington’s paradigmatic assessment of semantic ‘access’ deficits. In these verbal and non-verbal matching tasks, a small set of semantically-related items are repeatedly presented over several cycles so that the target on one trial becomes a distractor on another (building up interference and eliciting semantic ‘blocking’ effects). Patients with Wernicke’s aphasia and semantic aphasia were distinguished according to lesion location in the temporal cortex, but in each group, some individuals had additional prefrontal damage. Both of these aspects of lesion variability—one that mapped onto classical ‘syndromes’ and one that did not—predicted aspects of the semantic ‘access’ deficit. Both semantic aphasia and Wernicke’s aphasia cases showed multimodal semantic impairment, although as expected, the Wernicke’s aphasia group showed greater deficits on auditory-verbal than picture judgements. Distribution of damage in the temporal lobe was crucial for predicting the initially

  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. 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?.

  6. 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

  7. Introduction to geospatial semantics and technology workshop handbook

    USGS Publications Warehouse

    Varanka, Dalia E.

    2012-01-01

    The workshop is a tutorial on introductory geospatial semantics with hands-on exercises using standard Web browsers. The workshop is divided into two sections, general semantics on the Web and specific examples of geospatial semantics using data from The National Map of the U.S. Geological Survey and the Open Ontology Repository. The general semantics section includes information and access to publicly available semantic archives. The specific session includes information on geospatial semantics with access to semantically enhanced data for hydrography, transportation, boundaries, and names. The Open Ontology Repository offers open-source ontologies for public use.

  8. On the roles of distinctiveness and semantic expectancies in episodic encoding of emotional words.

    PubMed

    Kamp, Siri-Maria; Potts, Geoffrey F; Donchin, Emanuel

    2015-12-01

    We examined the factors that contribute to enhanced recall for emotionally arousing words by analyzing behavioral performance, the P300 as an index of distinctiveness, and the N400 as an index of semantic expectancy violation in a modified Von Restorff paradigm. While their EEG was recorded, participants studied three list types (1) neutral words including one emotionally arousing isolate (either positive or negative), (2) arousing, negative words including one neutral isolate, or (3) arousing, positive words including one neutral isolate. Immediately after each list, free recall was tested. Negative, but not positive, words exhibited enhanced recall when presented as isolates in lists of neutral words and elicited a larger P300 for subsequently recalled than not-recalled words. This suggests that arousing, negative words stand out and that their distinctiveness contributes to their superior recall. Positive valence had an enhancing effect on recall only when the list contained mostly other positive words. Neutral isolates placed in either positive or negative lists elicited an N400, suggesting that semantic expectations developed in emotional word lists regardless of valence. However, semantic relatedness appeared to more strongly contribute to recall for positive than negative words. Our results suggest that distinctiveness and semantic relatedness contribute to episodic encoding of arousing words, but the impact of each factor depends on both a word's valence and its context.

  9. Clustering and semantically filtering web images to create a large-scale image ontology

    NASA Astrophysics Data System (ADS)

    Zinger, S.; Millet, C.; Mathieu, B.; Grefenstette, G.; Hède, P.; Moëllic, P.-A.

    2006-01-01

    In our effort to contribute to the closing of the "semantic gap" between images and their semantic description, we are building a large-scale ontology of images of objects. This visual catalog will contain a large number of images of objects, structured in a hierarchical catalog, allowing image processing researchers to derive signatures for wide classes of objects. We are building this ontology using images found on the web. We describe in this article our initial approach for finding coherent sets of object images. We first perform two semantic filtering steps: the first involves deciding which words correspond to objects and using these words to access databases which index text found associated with an image (e.g. Google Image search) to find a set of candidate images; the second semantic filtering step involves using face recognition technology to remove images of people from the candidate set (we have found that often requests for objects return images of people). After these two steps, we have a cleaner set of candidate images for each object. We then index and cluster the remaining images using our system VIKA (VIsual KAtaloguer) to find coherent sets of objects.

  10. A Semantic Analysis Method for Scientific and Engineering Code

    NASA Technical Reports Server (NTRS)

    Stewart, Mark E. M.

    1998-01-01

    This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

  11. [A medical image semantic modeling based on hierarchical Bayesian networks].

    PubMed

    Lin, Chunyi; Ma, Lihong; Yin, Junxun; Chen, Jianyu

    2009-04-01

    A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in allusion to characters of medical images. It used GMM (Gaussian mixture models) to map low-level image features into object semantics with probabilities, then it captured high-level semantics through fusing these object semantics using a Bayesian network, so that it built a multi-layer medical image semantic model, aiming to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. As for the validity of this method, we have built a multi-level semantic model from a small set of astrocytoma MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytoma in malignant degree. Experiment results show that this is a superior approach.

  12. Semantics of color in chromatism

    NASA Astrophysics Data System (ADS)

    Serov, Nikolai V.

    2002-06-01

    The aim of this investigation is to describe the semantics of color in chromatism (from the ancient Greek triune notion of <>: (1) color as ideal (Id- plan), psychic; (2) tint as physical, verbal; material (M- plan), physiological, syntonic (S-plan), and (3) emotion as their informative-energetic correlation). Being a new field of science, chromatism links humanitarian and natural subjects by means of interdiscipline investigation of a real (f-m) man living in a real (color) surrounding environment. According to the definition for <>, color may be considered to be the most universal notion, permitting to assume the unity of both a man and an environment. Due to this assumption, we may give models of human intellect.

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

    PubMed

    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

  14. 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

  15. SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

    NASA Technical Reports Server (NTRS)

    Keller, Richard M.; Berrios, Daniel C.; Carvalho, Robert E.; Hall, David R.; Rich, Stephen J.; Sturken, Ian B.; Swanson, Keith J.; Wolfe, Shawn R.

    2004-01-01

    SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.

  16. Semantic Metrics for Analysis of Software

    NASA Technical Reports Server (NTRS)

    Etzkorn, Letha H.; Cox, Glenn W.; Farrington, Phil; Utley, Dawn R.; Ghalston, Sampson; Stein, Cara

    2005-01-01

    A recently conceived suite of object-oriented software metrics focus is on semantic aspects of software, in contradistinction to traditional software metrics, which focus on syntactic aspects of software. Semantic metrics represent a more human-oriented view of software than do syntactic metrics. The semantic metrics of a given computer program are calculated by use of the output of a knowledge-based analysis of the program, and are substantially more representative of software quality and more readily comprehensible from a human perspective than are the syntactic metrics.

  17. 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.

  18. Attention trees and semantic paths

    NASA Astrophysics Data System (ADS)

    Giusti, Christian; Pieroni, Goffredo G.; Pieroni, Laura

    2007-02-01

    In the last few decades several techniques for image content extraction, often based on segmentation, have been proposed. It has been suggested that under the assumption of very general image content, segmentation becomes unstable and classification becomes unreliable. According to recent psychological theories, certain image regions attract the attention of human observers more than others and, generally, the image main meaning appears concentrated in those regions. Initially, regions attracting our attention are perceived as a whole and hypotheses on their content are formulated; successively the components of those regions are carefully analyzed and a more precise interpretation is reached. It is interesting to observe that an image decomposition process performed according to these psychological visual attention theories might present advantages with respect to a traditional segmentation approach. In this paper we propose an automatic procedure generating image decomposition based on the detection of visual attention regions. A new clustering algorithm taking advantage of the Delaunay- Voronoi diagrams for achieving the decomposition target is proposed. By applying that algorithm recursively, starting from the whole image, a transformation of the image into a tree of related meaningful regions is obtained (Attention Tree). Successively, a semantic interpretation of the leaf nodes is carried out by using a structure of Neural Networks (Neural Tree) assisted by a knowledge base (Ontology Net). Starting from leaf nodes, paths toward the root node across the Attention Tree are attempted. The task of the path consists in relating the semantics of each child-parent node pair and, consequently, in merging the corresponding image regions. The relationship detected in this way between two tree nodes generates, as a result, the extension of the interpreted image area through each step of the path. The construction of several Attention Trees has been performed and partial

  19. Semantic Facilitation and Semantic Interference in Language Production: Further Evidence for the Conceptual Selection Model of Lexical Access

    ERIC Educational Resources Information Center

    Bloem, Ineke; van den Boogaard, Sylvia; Heij, Wido La

    2004-01-01

    Bloem and La Heij (2003) reported that in a word-translation task context words induce semantic interference whereas context pictures induce semantic facilitation. This finding was accounted for by a model of lexical access in which: (a) semantic facilitation is localized at the conceptual level, (b) semantic interference is localized at the…

  20. Putting semantics into the semantic web: how well can it capture biology?

    PubMed

    Kazic, Toni

    2006-01-01

    Could the Semantic Web work for computations of biological interest in the way it's intended to work for movie reviews and commercial transactions? It would be wonderful if it could, so it's worth looking to see if its infrastructure is adequate to the job. The technologies of the Semantic Web make several crucial assumptions. I examine those assumptions; argue that they create significant problems; and suggest some alternative ways of achieving the Semantic Web's goals for biology.

  1. Synergistic Activation of Latent HIV-1 Expression by Novel Histone Deacetylase Inhibitors and Bryostatin-1

    PubMed Central

    Martínez-Bonet, Marta; Isabel Clemente, Maria; Jesús Serramía, Maria; Muñoz, Eduardo; Moreno, Santiago; Ángeles Muñoz-Fernández, Maria

    2015-01-01

    Viral reactivation from latently infected cells has become a promising therapeutic approach to eradicate HIV. Due to the complexity of the viral latency, combinations of efficient and available drugs targeting different pathways of latency are needed. In this work, we evaluated the effect of various combinations of bryostatin-1 (BRY) and novel histone deacetylase inhibitors (HDACIs) on HIV-reactivation and on cellular phenotype. The lymphocyte (J89GFP) or monocyte/macrophage (THP89GFP) latently infected cell lines were treated with BRY, panobinostat (PNB) and romidepsin (RMD) either alone or in combination. Thus, the effect on the viral reactivation was evaluated. We calculated the combination index for each drug combination; the BRY/HDACIs showed a synergistic HIV-reactivation profile in the majority of the combinations tested, whereas non-synergistic effects were observed when PNB was mixed with RMD. Indeed, the 75% effective concentrations of BRY, PNB and RMD were reduced in these combinations. Moreover, primary CD4 T cells treated with such drug combinations presented similar activation and proliferation profiles in comparison with single drug treated cells. Summing up, combinations between BRY, PNB and/or RMD presented a synergistic profile by inducing virus expression in HIV-latently infected cells, rendering these combinations an attractive novel and safe option for future clinical trials. PMID:26563568

  2. Synergistic Activation of Latent HIV-1 Expression by Novel Histone Deacetylase Inhibitors and Bryostatin-1.

    PubMed

    Martínez-Bonet, Marta; Clemente, Maria Isabel; Serramía, Maria Jesús; Muñoz, Eduardo; Moreno, Santiago; Muñoz-Fernández, Maria Ángeles

    2015-11-13

    Viral reactivation from latently infected cells has become a promising therapeutic approach to eradicate HIV. Due to the complexity of the viral latency, combinations of efficient and available drugs targeting different pathways of latency are needed. In this work, we evaluated the effect of various combinations of bryostatin-1 (BRY) and novel histone deacetylase inhibitors (HDACIs) on HIV-reactivation and on cellular phenotype. The lymphocyte (J89GFP) or monocyte/macrophage (THP89GFP) latently infected cell lines were treated with BRY, panobinostat (PNB) and romidepsin (RMD) either alone or in combination. Thus, the effect on the viral reactivation was evaluated. We calculated the combination index for each drug combination; the BRY/HDACIs showed a synergistic HIV-reactivation profile in the majority of the combinations tested, whereas non-synergistic effects were observed when PNB was mixed with RMD. Indeed, the 75% effective concentrations of BRY, PNB and RMD were reduced in these combinations. Moreover, primary CD4 T cells treated with such drug combinations presented similar activation and proliferation profiles in comparison with single drug treated cells. Summing up, combinations between BRY, PNB and/or RMD presented a synergistic profile by inducing virus expression in HIV-latently infected cells, rendering these combinations an attractive novel and safe option for future clinical trials.

  3. A Bayesian Semiparametric Latent Variable Model for Mixed Responses

    ERIC Educational Resources Information Center

    Fahrmeir, Ludwig; Raach, Alexander

    2007-01-01

    In this paper we introduce a latent variable model (LVM) for mixed ordinal and continuous responses, where covariate effects on the continuous latent variables are modelled through a flexible semiparametric Gaussian regression model. We extend existing LVMs with the usual linear covariate effects by including nonparametric components for nonlinear…

  4. A Latent Class Approach to Estimating Test-Score Reliability

    ERIC Educational Resources Information Center

    van der Ark, L. Andries; van der Palm, Daniel W.; Sijtsma, Klaas

    2011-01-01

    This study presents a general framework for single-administration reliability methods, such as Cronbach's alpha, Guttman's lambda-2, and method MS. This general framework was used to derive a new approach to estimating test-score reliability by means of the unrestricted latent class model. This new approach is the latent class reliability…

  5. Nonlinear Latent Curve Models for Multivariate Longitudinal Data

    ERIC Educational Resources Information Center

    Blozis, Shelley A.; Conger, Katherine J.; Harring, Jeffrey R.

    2007-01-01

    Latent curve models have become a useful approach to analyzing longitudinal data, due in part to their allowance of and emphasis on individual differences in features that describe change. Common applications of latent curve models in developmental studies rely on polynomial functions, such as linear or quadratic functions. Although useful for…

  6. An Importance Sampling EM Algorithm for Latent Regression Models

    ERIC Educational Resources Information Center

    von Davier, Matthias; Sinharay, Sandip

    2007-01-01

    Reporting methods used in large-scale assessments such as the National Assessment of Educational Progress (NAEP) rely on latent regression models. To fit the latent regression model using the maximum likelihood estimation technique, multivariate integrals must be evaluated. In the computer program MGROUP used by the Educational Testing Service for…

  7. Higher-Order Item Response Models for Hierarchical Latent Traits

    ERIC Educational Resources Information Center

    Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming

    2013-01-01

    Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…

  8. Modeling Heterogeneity of Latent Growth Depending on Initial Status

    ERIC Educational Resources Information Center

    Klein, Andreas G.; Muthen, Bengt O.

    2006-01-01

    In this article, a heterogeneous latent growth curve model for modeling heterogeneity of growth rates is proposed. The suggested model is an extension of a conventional growth curve model and a complementary tool to mixed growth modeling. It allows the modeling of heterogeneity of growth rates as a continuous function of latent initial status and…

  9. A Simplified Estimation of Latent State--Trait Parameters

    ERIC Educational Resources Information Center

    Hagemann, Dirk; Meyerhoff, David

    2008-01-01

    The latent state-trait (LST) theory is an extension of the classical test theory that allows one to decompose a test score into a true trait, a true state residual, and an error component. For practical applications, the variances of these latent variables may be estimated with standard methods of structural equation modeling (SEM). These…

  10. Nonlinear and Quasi-Simplex Patterns in Latent Growth Models

    ERIC Educational Resources Information Center

    Bianconcini, Silvia

    2012-01-01

    In the SEM literature, simplex and latent growth models have always been considered competing approaches for the analysis of longitudinal data, even if they are strongly connected and both of specific importance. General dynamic models, which simultaneously estimate autoregressive structures and latent curves, have been recently proposed in the…

  11. Latent Structure of Motor Abilities in Pre-School Children

    ERIC Educational Resources Information Center

    Vatroslav, Horvat

    2011-01-01

    The theoretical and practical knowledge which have so far been acquired through work with pre-school children pointed to the conclusion that the structures of the latent dimensions of the motor abilities differ greatly from such a structure, in pre-school children and adults alike. Establishing the latent structure of the motor abilities in…

  12. A Review of the Latent and Manifest Benefits (LAMB) Scale

    ERIC Educational Resources Information Center

    Muller, Juanita; Waters, Lea

    2012-01-01

    The latent and manifest benefits (LAMB) scale (Muller, Creed, Waters & Machin, 2005) was designed to measure the latent and manifest benefits of employment and provide a single scale to test Jahoda's (1981) and Fryer's (1986) theories of unemployment. Since its publication in 2005 there have been 13 studies that have used the scale with 5692…

  13. On the Utilization of Sample Weights in Latent Variable Models.

    ERIC Educational Resources Information Center

    Kaplan, David; Ferguson, Aaron J.

    1999-01-01

    Examines the use of sample weights in latent variable models in the case where a simple random sample is drawn from a population containing a mixture of strata through a bootstrap simulation study. Results show that ignoring weights can lead to serious bias in latent variable model parameters and reveal the advantages of using sample weights. (SLD)

  14. Use of Latent Profile Analysis in Studies of Gifted Students

    ERIC Educational Resources Information Center

    Mammadov, Sakhavat; Ward, Thomas J.; Cross, Jennifer Riedl; Cross, Tracy L.

    2016-01-01

    To date, in gifted education and related fields various conventional factor analytic and clustering techniques have been used extensively for investigation of the underlying structure of data. Latent profile analysis is a relatively new method in the field. In this article, we provide an introduction to latent profile analysis for gifted education…

  15. Evaluating Intercept-Slope Interactions in Latent Growth Modeling

    ERIC Educational Resources Information Center

    Sun, Ronghua; Willson, Victor L.

    2009-01-01

    The effects of misspecifying intercept-covariate interactions in a 4 time-point latent growth model were the focus of this investigation. The investigation was motivated by school growth studies in which students' entry-level skills may affect their rate of growth. We studied the latent interaction of intercept and a covariate in predicting growth…

  16. The Latent Variable Approach as Applied to Transitive Reasoning

    ERIC Educational Resources Information Center

    Bouwmeester, Samantha; Vermunt, Jeroen K.; Sijtsma, Klaas

    2012-01-01

    We discuss the limitations of hypothesis testing using (quasi-) experiments in the study of cognitive development and suggest latent variable modeling as a viable alternative to experimentation. Latent variable models allow testing a theory as a whole, incorporating individual differences with respect to developmental processes or abilities in the…

  17. Gene Variants Associated with Antisocial Behaviour: A Latent Variable Approach

    ERIC Educational Resources Information Center

    Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

    2013-01-01

    Objective: The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods: Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a…

  18. Spurious Latent Classes in the Mixture Rasch Model

    ERIC Educational Resources Information Center

    Alexeev, Natalia; Templin, Jonathan; Cohen, Allan S.

    2011-01-01

    Mixture Rasch models have been used to study a number of psychometric issues such as goodness of fit, response strategy differences, strategy shifts, and multidimensionality. Although these models offer the potential for improving understanding of the latent variables being measured, under some conditions overextraction of latent classes may…

  19. Semantic preview benefit in English: Individual differences in the extraction and use of parafoveal semantic information.

    PubMed

    Veldre, Aaron; Andrews, Sally

    2016-06-01

    Although there is robust evidence that skilled readers of English extract and use orthographic and phonological information from the parafovea to facilitate word identification, semantic preview benefits have been elusive. We sought to establish whether individual differences in the extraction and/or use of parafoveal semantic information could account for this discrepancy. Ninety-nine adult readers who were assessed on measures of reading and spelling ability read sentences while their eye movements were recorded. The gaze-contingent boundary paradigm was used to manipulate the availability of relevant semantic and orthographic information in the parafovea. On average, readers showed a benefit from previews high in semantic feature overlap with the target. However, reading and spelling ability yielded opposite effects on semantic preview benefit. High reading ability was associated with a semantic preview benefit that was equivalent to an identical preview on first-pass reading. High spelling ability was associated with a reduced semantic preview benefit despite an overall higher rate of skipping. These results suggest that differences in the magnitude of semantic preview benefits in English reflect constraints on extracting semantic information from the parafovea and competition between the orthographic features of the preview and the target. (PsycINFO Database Record PMID:26595070

  20. Latent autoimmune diabetes of the adult: current knowledge and uncertainty

    PubMed Central

    Laugesen, E; Østergaard, J A; Leslie, R D G

    2015-01-01

    Patients with adult-onset autoimmune diabetes have less Human Leucocyte Antigen (HLA)-associated genetic risk and fewer diabetes-associated autoantibodies compared with patients with childhood-onset Type 1 diabetes. Metabolic changes at diagnosis reflect a broad clinical phenotype ranging from diabetic ketoacidosis to mild non-insulin-requiring diabetes, also known as latent autoimmune diabetes of the adult (LADA). This latter phenotype is the most prevalent form of adult-onset autoimmune diabetes and probably the most prevalent form of autoimmune diabetes in general. Although LADA is associated with the same genetic and immunological features as childhood-onset Type 1 diabetes, it also shares some genetic features with Type 2 diabetes, which raises the question of genetic heterogeneity predisposing to this form of the disease. The potential value of screening patients with adult-onset diabetes for diabetes-associated autoantibodies to identify those with LADA is emphasized by their lack of clinically distinct features, their different natural history compared with Type 2 diabetes and their potential need for a dedicated management strategy. The fact that, in some studies, patients with LADA show worse glucose control than patients with Type 2 diabetes, highlights the need for further therapeutic studies. Challenges regarding classification, epidemiology, genetics, metabolism, immunology, clinical presentation and treatment of LADA were discussed at a 2014 workshop arranged by the Danish Diabetes Academy. The presentations and discussions are summarized in this review, which sets out the current ideas and controversies surrounding this form of diabetes. What’s new? Latent autoimmune diabetes of the adult (LADA) is an autoimmune diabetes defined by adult-onset, presence of diabetes associated autoantibodies, and no insulin treatment requirement for a period after diagnosis. Immunologically, glutamic acid decarboxylase 65 autoantibodies are by far the most

  1. A latent classification of male batterers.

    PubMed

    Mauricio, Anne M; Lopez, Frederick G

    2009-01-01

    Regression latent class analysis was used to identify batterer subgroups with distinct violence patterns and to examine associations between class membership and adult attachment orientations as well as antisocial and borderline personality disorders. Results supported three batterer subgroups, with classes varying on frequency and severity of violence. The high-level violence class represented 40% of batterers, and both anxious and avoidant adult attachment orientations as well as borderline personality characteristics predicted membership in this class. The moderate-level violence class represented 35% of the batterers, and adult anxious attachment orientation was associated with membership in this class. The low-level violence class represented 25% of the sample and reported significantly less violence than other classes. Neither adult attachment orientations nor personality disorders predicted membership in this class.

  2. Diagnosis of latent forms of labyrinthine affections

    NASA Technical Reports Server (NTRS)

    Vaslilyeva, V. P.

    1980-01-01

    Features and significance of individual vestibular symptoms for the diagnosis of latent labyrinthitis and limited forms of labyrinthine affections offering considerable difficulties are discussed. Vestibular symptoms are indistinct. In case of the negative fistular symptom the greatest significance is acquired by the study of posture nystagmus according to the results of electronystagmograms, changes of tonic reactions and statics, as well as data of experimental vestibular tests. The necessity of evaluation of all the vestibular symptoms from the point of view of their vector characteristics and in a complex of evidence obtained by otoneurological examination of the patient is emphasized. Delicate topic and differential diagnosis of vestibular disturbances is of great importance and significance in the choice of the conservative or surgical method of treatment.

  3. Latent laser-induced graphitization of diamond

    NASA Astrophysics Data System (ADS)

    Kononenko, V. V.; Gololobov, V. M.; Konov, V. I.

    2016-03-01

    Basic features and mechanism of femtosecond laser graphitization of diamond surface were studied in the two regimes of irradiation: (1) by an intensive (>10 J/cm2) single shot and (2) by a train of pulses with near-threshold intensity (~1-10 J/cm2). Special attention was paid to the so-called accumulative regime, when multipulse laser treatment results in prolonged delay of an appearance of crystal modification of the crystal. The light absorption mechanisms dominating in each regime are discussed. The experiments with fundamental (800 nm), second (400 nm) and third (266 nm) harmonics of Ti-sapphire laser (100 fs) have revealed that thermally stimulated processes play an essential role in latent diamond graphitization.

  4. Targeting latent TGFβ release in muscular dystrophy.

    PubMed

    Ceco, Ermelinda; Bogdanovich, Sasha; Gardner, Brandon; Miller, Tamari; DeJesus, Adam; Earley, Judy U; Hadhazy, Michele; Smith, Lucas R; Barton, Elisabeth R; Molkentin, Jeffery D; McNally, Elizabeth M

    2014-10-22

    Latent transforming growth factor-β (TGFβ) binding proteins (LTBPs) bind to inactive TGFβ in the extracellular matrix. In mice, muscular dystrophy symptoms are intensified by a genetic polymorphism that changes the hinge region of LTBP, leading to increased proteolytic susceptibility and TGFβ release. We have found that the hinge region of human LTBP4 was also readily proteolysed and that proteolysis could be blocked by an antibody to the hinge region. Transgenic mice were generated to carry a bacterial artificial chromosome encoding the human LTBP4 gene. These transgenic mice displayed larger myofibers, increased damage after muscle injury, and enhanced TGFβ signaling. In the mdx mouse model of Duchenne muscular dystrophy, the human LTBP4 transgene exacerbated muscular dystrophy symptoms and resulted in weaker muscles with an increased inflammatory infiltrate and greater LTBP4 cleavage in vivo. Blocking LTBP4 cleavage may be a therapeutic strategy to reduce TGFβ release and activity and decrease inflammation and muscle damage in muscular dystrophy.

  5. Semantic Antinomies and Deep Structure Analysis

    ERIC Educational Resources Information Center

    Zuber, Ryszard

    1975-01-01

    This article discusses constructions known as semantic antinomies, that is, the paradoxical results of false presuppositions, and how they can be dealt with by means of deep structure analysis. See FL 508 186 for availability. (CLK)

  6. Semantic Mapping: A Study Skills Strategy.

    ERIC Educational Resources Information Center

    Schewel, Rosel

    1989-01-01

    A discussion of semantic mapping, a strategy to enhance comprehension and memory based on schema theory, describes the origins of the technique, research in the past decade, and procedures used to teach it. (MSE)

  7. A Collection of Features for Semantic Graphs

    SciTech Connect

    Eliassi-Rad, T; Fodor, I K; Gallagher, B

    2007-05-02

    Semantic graphs are commonly used to represent data from one or more data sources. Such graphs extend traditional graphs by imposing types on both nodes and links. This type information defines permissible links among specified nodes and can be represented as a graph commonly referred to as an ontology or schema graph. Figure 1 depicts an ontology graph for data from National Association of Securities Dealers. Each node type and link type may also have a list of attributes. To capture the increased complexity of semantic graphs, concepts derived for standard graphs have to be extended. This document explains briefly features commonly used to characterize graphs, and their extensions to semantic graphs. This document is divided into two sections. Section 2 contains the feature descriptions for static graphs. Section 3 extends the features for semantic graphs that vary over time.

  8. Semantic information influences race categorization from faces.

    PubMed

    Tskhay, Konstantin O; Rule, Nicholas O

    2015-06-01

    It is well established that low-level visual features affect person categorization in a bottom-up fashion. Few studies have examined top-down influences, however, and have largely focused on how information recalled from memory or from motivation influences categorization. Here, we investigated how race categorizations are affected by the context in which targets are perceived by manipulating semantic information associated with the faces being categorized. We found that presenting faces that systematically varied in racial ambiguity with race-congruent (vs. incongruent) semantic labels shifted the threshold at which perceivers distinguished between racial groups. The semantic information offered by the labels therefore appeared to influence the categorization of race. These findings suggest that semantic information creates a context for the interpretation of perceptual cues during social categorization, highlighting an active role of top-down information in race perception. PMID:25810414

  9. Semantic information influences race categorization from faces.

    PubMed

    Tskhay, Konstantin O; Rule, Nicholas O

    2015-06-01

    It is well established that low-level visual features affect person categorization in a bottom-up fashion. Few studies have examined top-down influences, however, and have largely focused on how information recalled from memory or from motivation influences categorization. Here, we investigated how race categorizations are affected by the context in which targets are perceived by manipulating semantic information associated with the faces being categorized. We found that presenting faces that systematically varied in racial ambiguity with race-congruent (vs. incongruent) semantic labels shifted the threshold at which perceivers distinguished between racial groups. The semantic information offered by the labels therefore appeared to influence the categorization of race. These findings suggest that semantic information creates a context for the interpretation of perceptual cues during social categorization, highlighting an active role of top-down information in race perception.

  10. Software analysis in the semantic web

    NASA Astrophysics Data System (ADS)

    Taylor, Joshua; Hall, Robert T.

    2013-05-01

    Many approaches in software analysis, particularly dynamic malware analyis, benefit greatly from the use of linked data and other Semantic Web technology. In this paper, we describe AIS, Inc.'s Semantic Extractor (SemEx) component from the Malware Analysis and Attribution through Genetic Information (MAAGI) effort, funded under DARPA's Cyber Genome program. The SemEx generates OWL-based semantic models of high and low level behaviors in malware samples from system call traces generated by AIS's introspective hypervisor, IntroVirtTM. Within MAAGI, these semantic models were used by modules that cluster malware samples by functionality, and construct "genealogical" malware lineages. Herein, we describe the design, implementation, and use of the SemEx, as well as the C2DB, an OWL ontology used for representing software behavior and cyber-environments.

  11. Teacher’s Corner: Latent Curve Models and Latent Change Score Models Estimated in R

    PubMed Central

    Ghisletta, Paolo; McArdle, John J.

    2014-01-01

    In recent years the use of the Latent Curve Model (LCM) among researchers in social sciences has increased noticeably, probably thanks to contemporary software developments and to the availability of specialized literature. Extensions of the LCM, like the the Latent Change Score Model (LCSM), have also increased in popularity. At the same time, the R statistical language and environment, which is open source and runs on several operating systems, is becoming a leading software for applied statistics. We show how to estimate both the LCM and LCSM with the sem, lavaan, and OpenMx packages of the R software. We also illustrate how to read in, summarize, and plot data prior to analyses. Examples are provided on data previously illustrated by Ferrer, Hamagami, & McArdle, 2004. The data and all scripts used here are available on the first author’s website. PMID:25505366

  12. ENDOGENOUS ANALGESIA, DEPENDENCE, AND LATENT PAIN SENSITIZATION

    PubMed Central

    Taylor, Bradley K; Corder, Gregory

    2015-01-01

    Endogenous activation of μ-opioid receptors (MORs) provides relief from acute pain. Recent studies have established that tissue inflammation produces latent pain sensitization (LS) that is masked by spinal MOR signaling for months, even after complete recovery from injury and re-establishment of normal pain thresholds. Disruption with MOR inverse agonists reinstates pain and precipitates cellular, somatic and aversive signs of physical withdrawal; this phenomenon requires N-methyl-D-aspartate receptor-mediated activation of calcium-sensitive adenylyl cyclase type 1 (AC1). In this review, we present a new conceptual model of the transition from acute to chronic pain, based on the delicate balance between LS and endogenous analgesia that develops after painful tissue injury. First, injury activates pain pathways. Second, the spinal cord establishes MOR constitutive activity (MORCA) as it attempts to control pain. Third, over time, the body becomes dependent on MORCA, which paradoxically sensitizes pain pathways. Stress or injury escalates opposing inhibitory and excitatory influences on nociceptive processing as a pathological consequence of increased endogenous opioid tone. Pain begets MORCA begets pain vulnerability in a vicious cycle. The final result is a silent insidious state characterized by the escalation of two opposing excitatory and inhibitory influences on pain transmission: LS mediated by AC1 (which maintains accelerator), and pain inhibition mediated by MORCA (which maintains the brake). This raises the prospect that opposing homeostatic interactions between MORCA analgesia and latent NMDAR–AC1-mediated pain sensitization create a lasting vulnerability to develop chronic pain. Thus, chronic pain syndromes may result from a failure in constitutive signaling of spinal MORs and a loss of endogenous analgesic control. An overarching long-term therapeutic goal of future research is to alleviate chronic pain by either: a) facilitating endogenous opioid

  13. Latent Herpes Viral Reactivation in Astronauts

    NASA Technical Reports Server (NTRS)

    Pierson, D. L.; Mehta, S. K.; Stowe, R.

    2008-01-01

    Latent viruses are ubiquitous and reactivate during stressful periods with and without symptoms. Latent herpes virus reactivation is used as a tool to predict changes in the immune status in astronauts and to evaluate associated health risks. Methods: Viral DNA was detected by real time polymerase chain reaction in saliva and urine from astronauts before, during and after short and long-duration space flights. Results and Discussion: EpsteinBarr virus (EBV), cytomegalovirus (CMV), and varicella zoster virus (VZV) reactivated, and viral DNA was shed in saliva (EBV and VZV) or urine (CMV). EBV levels in saliva during flight were 10fold higher than baseline levels. Elevations in EBV specific CD8+ T-cells, viral antibody titers, and specific cytokines were consistent with viral reactivation. Intracellular levels of cytokines were reduced in EBVspecific Tcells. CMV, rarely present in urine of healthy individuals, was shed in urine of 27% of astronauts during all phases of spaceflight. VZV, not found in saliva of asymptomatic individuals, was found in saliva of 50% of astronauts during spaceflight and 35 days after flight. VZV recovered from astronaut saliva was found to be live, infectious virus. DNA sequencing demonstrated that the VZV recovered from astronauts was from the common European strain of VZV. Elevation of stress hormones accompanied viral reactivation indicating involvement of the hypothalmic-pituitary-adrenal and sympathetic adrenal-medullary axes in the mechanism of viral reactivation in astronauts. A study of 53 shingles patients found that all shingles patients shed VZV DNA in their saliva and the VZV levels correlated with the severity of the disease. Lower VZV levels in shingles patients were similar to those observed in astronauts. We proposed a rapid, simple, and cost-effective assay to detect VZV in saliva of patients with suspected shingles. Early detection of VZV infection allows early medical intervention.

  14. Latent Virus Reactivation in Space Shuttle Astronauts

    NASA Technical Reports Server (NTRS)

    Mehta, S. K.; Crucian, B. E.; Stowe, R. P.; Sams, C.; Castro, V. A.; Pierson, D. L.

    2011-01-01

    Latent virus reactivation was measured in 17 astronauts (16 male and 1 female) before, during, and after short-duration Space Shuttle missions. Blood, urine, and saliva samples were collected 2-4 months before launch, 10 days before launch (L-10), 2-3 hours after landing (R+0), 3 days after landing (R+14), and 120 days after landing (R+120). Epstein-Barr virus (EBV) DNA was measured in these samples by quantitative polymerase chain reaction. Varicella-zoster virus (VZV) DNA was measured in the 381 saliva samples and cytomegalovirus (CMV) DNA in the 66 urine samples collected from these subjects. Fourteen astronauts shed EBV DNA in 21% of their saliva samples before, during, and after flight, and 7 astronauts shed VZV in 7.4% of their samples during and after flight. It was interesting that shedding of both EBV and VZV increased during the flight phase relative to before or after flight. In the case of CMV, 32% of urine samples from 8 subjects contained DNA of this virus. In normal healthy control subjects, EBV shedding was found in 3% and VZV and CMV were found in less than 1% of the samples. The circadian rhythm of salivary cortisol measured before, during, and after space flight did not show any significant difference between flight phases. These data show that increased reactivation of latent herpes viruses may be associated with decreased immune system function, which has been reported in earlier studies as well as in these same subjects (data not reported here).

  15. Laser interrogation of latent vehicle registration number

    SciTech Connect

    Russo, R.E. |; Pelkey, G.E.; Grant, P.; Whipple, R.E.; Andresen, B.D.

    1994-09-01

    A recent investigation involved automobile registration numbers as important evidentiary specimens. In California, as in most states, small, thin metallic decals are issued to owners of vehicles each year as the registration is renewed. The decals are applied directly to the license plate of the vehicle and typically on top of the previous year`s expired decal. To afford some degree of security, the individual registration decals have been designed to tear easily; they cannot be separated from each other, but can be carefully removed intact from the metal license plate by using a razor blade. In September 1993, the City of Livermore Police Department obtained a blue 1993 California decal that had been placed over an orange 1992 decal. The two decals were being investigated as possible evidence in a case involving vehicle registration fraud. To confirm the suspicion and implicate a suspect, the department needed to known the registration number on the bottom (completely covered) 1992 decal. The authors attempted to use intense and directed light to interrogate the colored stickers. Optical illumination using a filtered white-light source partially identified the latent number. However, the most successful technique used a tunable dye laser pumped by a pulsed Nd:YAG laser. By selectively tuning the wavelength and intensity of the dye laser, backlit illumination of the decals permitted visualization of the underlying registration number through the surface of the top sticker. With optimally-tuned wavelength and intensity, 100% accuracy was obtained in identifying the sequence of latent characters. The advantage of optical techniques is their completely nondestructive nature, thus preserving the evidence for further interrogation or courtroom presentation.

  16. Estimating Generalizability to a Latent Variable Common to All of a Scale's Indicators: A Comparison of Estimators for Omega[subscript h

    ERIC Educational Resources Information Center

    Zinbarg, Richard E.; Yovel, Iftah; Revelle, William; McDonald, Roderick P.

    2006-01-01

    The extent to which a scale score generalizes to a latent variable common to all of the scale's indicators is indexed by the scale's general factor saturation. Seven techniques for estimating this parameter--omega[hierarchical] (omega[subscript h])--are compared in a series of simulated data sets. Primary comparisons were based on 160 artificial…

  17. Semantic dementia: aspects of the early diagnosis.

    PubMed

    Belliard, S; Merck, C; Jonin, P Y; Vérin, M

    2013-10-01

    Semantic dementia is a lobar atrophy syndrome, related to a degeneration of anterior temporal regions, and characterized by a very predominant impairment of semantic memory. Whereas the diagnosis is relatively easy to establish in the typical form and if the patient is seen early, the emergence of possible additional cognitive or psycho-behavioural disorders can lead to a misdiagnosis in favour of a frontotemporal dementia syndrome or even probable Alzheimer's disease.

  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. 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.

  20. Evaluating word semantic properties using Sketch Engine

    NASA Astrophysics Data System (ADS)

    Stoykova, Velislava; Simkova, Maria

    2015-02-01

    The paper describes approach to use statistically-based tools incorporated into Sketch Engine system for electronic text corpora processing to mining big textual data for search and extract word semantic properties. It presents and compares series of word search experiments using different statistical approaches and evaluates results for Bulgarian language EUROPARL 7 Corpus search to extract word semantic properties. Finally, the methodology is extended for multilingual application using Slovak language EUROPARL 7 Corpus.