Trust estimation of the semantic web using semantic web clustering

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Shirgahi, Hossein; Mohsenzadeh, Mehran; Haj Seyyed Javadi, Hamid

2017-05-01

Development of semantic web and social network is undeniable in the Internet world these days. Widespread nature of semantic web has been very challenging to assess the trust in this field. In recent years, extensive researches have been done to estimate the trust of semantic web. Since trust of semantic web is a multidimensional problem, in this paper, we used parameters of social network authority, the value of pages links authority and semantic authority to assess the trust. Due to the large space of semantic network, we considered the problem scope to the clusters of semantic subnetworks and obtained the trust of each cluster elements as local and calculated the trust of outside resources according to their local trusts and trust of clusters to each other. According to the experimental result, the proposed method shows more than 79% Fscore that is about 11.9% in average more than Eigen, Tidal and centralised trust methods. Mean of error in this proposed method is 12.936, that is 9.75% in average less than Eigen and Tidal trust methods.

A Semantic Analysis Method for Scientific and Engineering Code

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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.

Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD data

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Srivastava Mousami

2012-11-01

Full Text Available Abstract Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal and disease (cancer sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95 identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4. Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1, chemotherapy/drug resistance biomarkers (panel 2, hypoxia regulated biomarkers (panel 3 and lung extra cellular matrix biomarkers (panel 4. Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3, HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1

The semantic structure of gratitude

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Smirnov, Alexander V.

2016-06-01

Full Text Available In the modern social and economic environment of Russia, gratitude might be considered an ambiguous phenomenon. It can have different meaning for a person in different contexts and can manifest itself differently as well (that is, as an expression of sincere feelings or as an element of corruption. In this respect it is topical to investigate the system of meanings and relationships that define the semantic space of gratitude. The goal of the study was the investigation and description of the content and structure of the semantic space of the gratitude phenomenon as well as the determination of male, female, age, and ethnic peculiarities of the expression of gratitude. The objective was achieved by using the semantic differential designed by the authors to investigate attitudes toward gratitude. This investigation was carried out with the participation of 184 respondents (Russians, Tatars, Ukrainians, Jews living in the Russian Federation, Belarus, Kazakhstan, Tajikistan, Israel, Australia, Canada, and the United Kingdom and identifying themselves as representatives of one of these nationalities. The structural components of gratitude were singled out by means of exploratory factor analysis of the empirical data from the designed semantic differential. Gender, age, and ethnic differences were differentiated by means of Student’s t-test. Gratitude can be represented by material and nonmaterial forms as well as by actions in response to help given. The empirical data allowed us to design the ethnically nonspecified semantic structure of gratitude. During the elaboration of the differential, semantic universals of gratitude, which constitute its psychosemantic content, were distinguished. Peculiarities of attitudes toward gratitude by those in different age and gender groups were revealed. Differences in the degree of manifestation of components of the psychosemantic structure of gratitude related to ethnic characteristics were not discovered

Centrality as a Method for the Evaluation of Semantic Resources for Disaster Risk Reduction

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Otakar Čerba

2017-08-01

Full Text Available Clear and straightforward communication is a key aspect of all human activities related to crisis management. Since crisis management activities involve professionals from various disciplines using different terminology, clear and straightforward communication is difficult to achieve. Semantics as a broad science can help to overcome communication difficulties. This research focuses on the evaluation of available semantic resources including ontologies, thesauri, and controlled vocabularies for disaster risk reduction as part of crisis management. The main idea of the study is that the most appropriate source of broadly understandable terminology is such a semantic resource, which is accepted by—or at least connected to the majority of other resources. Important is not only the number of interconnected resources, but also the concrete position of the resource in the complex network of Linked Data resources. Although this is usually done by user experience, objective methods of resource semantic centrality can be applied. This can be described by centrality methods used mainly in graph theory. This article describes the calculation of four types of centrality methods (Outdegree, Indegree, Closeness, and Betweenness applied to 160 geographic concepts published as Linked Data and related to disaster risk reduction. Centralities were calculated for graph structures containing particular semantic resources as nodes and identity links as edges. The results show that (with some discussed exceptions the datasets with high values of centrality serve as important information resources, but they also include more concepts from preselected 160 geographic concepts. Therefore, they could be considered as the most suitable resources of terminology to make communication in the domain easier. The main research goal is to automate the semantic resources evaluation and to apply a well-known theoretical method (centrality to the semantic issues of Linked Data. It

Semantic content-based recommendations using semantic graphs.

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Guo, Weisen; Kraines, Steven B

2010-01-01

Recommender systems (RSs) can be useful for suggesting items that might be of interest to specific users. Most existing content-based recommendation (CBR) systems are designed to recommend items based on text content, and the items in these systems are usually described with keywords. However, similarity evaluations based on keywords suffer from the ambiguity of natural languages. We present a semantic CBR method that uses Semantic Web technologies to recommend items that are more similar semantically with the items that the user prefers. We use semantic graphs to represent the items and we calculate the similarity scores for each pair of semantic graphs using an inverse graph frequency algorithm. The items having higher similarity scores to the items that are known to be preferred by the user are recommended.

Differential cognitive processing of Kanji and Kana words: do orthographic and semantic codes function in parallel in word matching task.

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Kawakami, A; Hatta, T; Kogure, T

2001-12-01

Relative engagements of the orthographic and semantic codes in Kanji and Hiragana word recognition were investigated. In Exp. 1, subjects judged whether the pairs of Kanji words (prime and target) presented sequentially were physically identical to each other in the word condition. In the sentence condition, subjects decided whether the target word was valid for the prime sentence presented in advance. The results showed that the response times to the target swords orthographically similar (to the prime) were significantly slower than to semantically related target words in the word condition and that this was also the case in the sentence condition. In Exp. 2, subjects judged whether the target word written in Hiragana was physically identical to the prime word in the word condition. In the sentence condition, subjects decided if the target word was valid for the previously presented prime sentence. Analysis indicated that response times to orthographically similar words were slower than to semantically related words in the word condition but not in the sentence condition wherein the response times to the semantically and orthographically similar words were largely the same. Based on these results, differential contributions of orthographic and semantic codes in cognitive processing of Japanese Kanji and Hiragana words was discussed.

Semantic relations differentially impact associative recognition memory: electrophysiological evidence.

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Kriukova, Olga; Bridger, Emma; Mecklinger, Axel

2013-10-01

Though associative recognition memory is thought to rely primarily on recollection, recent research indicates that familiarity might also make a substantial contribution when to-be-learned items are integrated into a coherent structure by means of an existing semantic relation. It remains unclear how different types of semantic relations, such as categorical (e.g., dancer-singer) and thematic (e.g., dancer-stage) relations might affect associative recognition, however. Using event-related potentials (ERPs), we addressed this question by manipulating the type of semantic link between paired words in an associative recognition memory experiment. An early midfrontal old/new effect, typically linked to familiarity, was observed across the relation types. In contrast, a robust left parietal old/new effect was found in the categorical condition only, suggesting a clear contribution of recollection to associative recognition for this kind of pairs. One interpretation of this pattern is that familiarity was sufficiently diagnostic for associative recognition of thematic relations, which could result from the integrative nature of the thematic relatedness compared to the similarity-based nature of categorical pairs. The present study suggests that the extent to which recollection and familiarity are involved in associative recognition is at least in part determined by the properties of semantic relations between the paired associates. Copyright © 2013 Elsevier Inc. All rights reserved.

Improving Semantic Updating Method on 3d City Models Using Hybrid Semantic-Geometric 3d Segmentation Technique

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Sharkawi, K.-H.; Abdul-Rahman, A.

2013-09-01

to LoD4. The accuracy and structural complexity of the 3D objects increases with the LoD level where LoD0 is the simplest LoD (2.5D; Digital Terrain Model (DTM) + building or roof print) while LoD4 is the most complex LoD (architectural details with interior structures). Semantic information is one of the main components in CityGML and 3D City Models, and provides important information for any analyses. However, more often than not, the semantic information is not available for the 3D city model due to the unstandardized modelling process. One of the examples is where a building is normally generated as one object (without specific feature layers such as Roof, Ground floor, Level 1, Level 2, Block A, Block B, etc). This research attempts to develop a method to improve the semantic data updating process by segmenting the 3D building into simpler parts which will make it easier for the users to select and update the semantic information. The methodology is implemented for 3D buildings in LoD2 where the buildings are generated without architectural details but with distinct roof structures. This paper also introduces hybrid semantic-geometric 3D segmentation method that deals with hierarchical segmentation of a 3D building based on its semantic value and surface characteristics, fitted by one of the predefined primitives. For future work, the segmentation method will be implemented as part of the change detection module that can detect any changes on the 3D buildings, store and retrieve semantic information of the changed structure, automatically updates the 3D models and visualize the results in a userfriendly graphical user interface (GUI).

Towards the multilingual semantic web principles, methods and applications

CERN Document Server

Buitelaar, Paul

2014-01-01

To date, the relation between multilingualism and the Semantic Web has not yet received enough attention in the research community. One major challenge for the Semantic Web community is to develop architectures, frameworks and systems that can help in overcoming national and language barriers, facilitating equal access to information produced in different cultures and languages. As such, this volume aims at documenting the state-of-the-art with regard to the vision of a Multilingual Semantic Web, in which semantic information will be accessible in and across multiple languages. The Multiling

Semantic processing in deaf and hard-of-hearing children: Large N400 mismatch effects in brain responses, despite poor semantic ability

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Petter Kallioinen

2016-08-01

Full Text Available Difficulties in auditory and phonological processing affect semantic processing in speech comprehension of deaf and hard-of-hearing (DHH children. However, little is known about brain responses of semantic processing in this group. We investigated event-related potentials (ERPs in DHH children with cochlear implants (CI and/or hearing aids (HA, and in normally hearing controls (NH. We used a semantic priming task with spoken word primes followed by picture targets. In both DHH children and controls, response differences between matching and mismatching targets revealed a typical N400-effect associated with semantic processing. Children with CI had the largest mismatch response despite poor semantic abilities overall, children with CI also had the largest ERP differentiation between mismatch types, with small effects of within-category mismatches (target from same category as prime and large effects between-category mismatches (were target is from a different category than prime. NH and HA children had similar responses to both mismatch types. While the large and differentiated ERP responses in the CI group were unexpected and should be interpreted with caution, the results could reflect less precision in semantic processing among children with CI, or a stronger reliance on predictive processing.

Combining Semantic and Lexical Methods for Mapping MedDRA to VCM Icons.

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Lamy, Jean-Baptiste; Tsopra, Rosy

2018-01-01

VCM (Visualization of Concept in Medicine) is an iconic language that represents medical concepts, such as disorders, by icons. VCM has a formal semantics described by an ontology. The icons can be used in medical software for providing a visual summary or enriching texts. However, the use of VCM icons in user interfaces requires to map standard medical terminologies to VCM. Here, we present a method combining semantic and lexical approaches for mapping MedDRA to VCM. The method takes advantage of the hierarchical relations in MedDRA. It also analyzes the groups of lemmas in the term's labels, and relies on a manual mapping of these groups to the concepts in the VCM ontology. We evaluate the method on 50 terms. Finally, we discuss the method and suggest perspectives.

Language networks associated with computerized semantic indices.

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Pakhomov, Serguei V S; Jones, David T; Knopman, David S

2015-01-01

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters. We investigated a computational linguistic approach to measuring the strength of semantic relatedness between words based on latent semantic analysis of word co-occurrences in a subset of a large online encyclopedia. We computed semantic clustering indices and compared them to brain network connectivity measures obtained with task-free fMRI in a sample consisting of healthy participants and those differentially affected by cognitive impairment. We found that semantic clustering indices were associated with brain network connectivity in distinct areas including fronto-temporal, fronto-parietal and fusiform gyrus regions. This study shows that computerized semantic indices complement traditional assessments of verbal fluency to provide a more complete account of the relationship between brain and verbal behavior involved organization and retrieval of lexical information from memory. Copyright © 2014 Elsevier Inc. All rights reserved.

Methods and apparatus for capture and storage of semantic information with sub-files in a parallel computing system

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Faibish, Sorin; Bent, John M; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-02-03

Techniques are provided for storing files in a parallel computing system using sub-files with semantically meaningful boundaries. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a plurality of sub-files. The method comprises the steps of obtaining a user specification of semantic information related to the file; providing the semantic information as a data structure description to a data formatting library write function; and storing the semantic information related to the file with one or more of the sub-files in one or more storage nodes of the parallel computing system. The semantic information provides a description of data in the file. The sub-files can be replicated based on semantically meaningful boundaries.

Contribution of Pretesting to Several Measures of Semantic Desensitization Effectiveness

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Israel, Allen C.; And Others

1977-01-01

Snake- or spider-phobic subjects (N=32) were randomly assigned to one of four groups. Subjects receiving semantic desensitization therapy showed less posttest anxiety on the semantic differential than control subjects regardless of testing condition. (Author)

Semantic word category processing in semantic dementia and posterior cortical atrophy.

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Shebani, Zubaida; Patterson, Karalyn; Nestor, Peter J; Diaz-de-Grenu, Lara Z; Dawson, Kate; Pulvermüller, Friedemann

2017-08-01

There is general agreement that perisylvian language cortex plays a major role in lexical and semantic processing; but the contribution of additional, more widespread, brain areas in the processing of different semantic word categories remains controversial. We investigated word processing in two groups of patients whose neurodegenerative diseases preferentially affect specific parts of the brain, to determine whether their performance would vary as a function of semantic categories proposed to recruit those brain regions. Cohorts with (i) Semantic Dementia (SD), who have anterior temporal-lobe atrophy, and (ii) Posterior Cortical Atrophy (PCA), who have predominantly parieto-occipital atrophy, performed a lexical decision test on words from five different lexico-semantic categories: colour (e.g., yellow), form (oval), number (seven), spatial prepositions (under) and function words (also). Sets of pseudo-word foils matched the target words in length and bi-/tri-gram frequency. Word-frequency was matched between the two visual word categories (colour and form) and across the three other categories (number, prepositions, and function words). Age-matched healthy individuals served as controls. Although broad word processing deficits were apparent in both patient groups, the deficit was strongest for colour words in SD and for spatial prepositions in PCA. The patterns of performance on the lexical decision task demonstrate (a) general lexicosemantic processing deficits in both groups, though more prominent in SD than in PCA, and (b) differential involvement of anterior-temporal and posterior-parietal cortex in the processing of specific semantic categories of words. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

High Performance Descriptive Semantic Analysis of Semantic Graph Databases

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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.

The Image of Political Conflict: Evaluation Semantic Universals in Students’ Individual Mind

OpenAIRE

Virna, Zhanna

2014-01-01

Abstract. The paper is focused on the study of the political conflict image from the perspective of psychosemantics. The integral psychosemantic approach to the political conflict allowed establishing semantic universals viewed as students’ evaluation of the conflict’s image. Among the parameters were active, dangerous, open, rational, moral, close, aggressive, etc. The results of the students’ semantic space study through the semantic differential showed that the semantic constructs of “poli...

Word-embeddings Italian semantic spaces: A semantic model for psycholinguistic research

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Marelli Marco

2017-01-01

Full Text Available Distributional semantics has been for long a source of successful models in psycholinguistics, permitting to obtain semantic estimates for a large number of words in an automatic and fast way. However, resources in this respect remain scarce or limitedly accessible for languages different from English. The present paper describes WEISS (Word-Embeddings Italian Semantic Space, a distributional semantic model based on Italian. WEISS includes models of semantic representations that are trained adopting state-of-the-art word-embeddings methods, applying neural networks to induce distributed representations for lexical meanings. The resource is evaluated against two test sets, demonstrating that WEISS obtains a better performance with respect to a baseline encoding word associations. Moreover, an extensive qualitative analysis of the WEISS output provides examples of the model potentialities in capturing several semantic phenomena. Two variants of WEISS are released and made easily accessible via web through the SNAUT graphic interface.

Development of a Bone-Conducted Ultrasonic Hearing Aid for the Profoundly Deaf: Evaluation of Sound Quality Using a Semantic Differential Method

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Nakagawa, Seiji; Fujiyuki, Chika; Kagomiya, Takayuki

2013-07-01

Bone-conducted ultrasound (BCU) is perceived even by the profoundly sensorineural deaf. A novel hearing aid using the perception of amplitude-modulated BCU (BCU hearing aid: BCUHA) has been developed. However, there is room for improvement particularly in terms of sound quality. BCU speech is accompanied by a strong high-pitched tone and contain some distortion. In this study, the sound quality of BCU speech with several types of amplitude modulation [double-sideband with transmitted carrier (DSB-TC), double-sideband with suppressed carrier (DSB-SC), and transposed modulations] and air-conducted (AC) speech was quantitatively evaluated using semantic differential and factor analysis. The results showed that all the types of BCU speech had higher metallic and lower esthetic factor scores than AC speech. On the other hand, transposed speech was closer than the other types of BCU speech to AC speech generally; the transposed speech showed a higher powerfulness factor score than the other types of BCU speech and a higher esthetic factor score than DSB-SC speech. These results provide useful information for further development of the BCUHA.

Methods for automated semantic definition of manufacturing structures (mBOM) in mechanical engineering companies

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Stekolschik, Alexander, Prof.

2017-10-01

The bill of materials (BOM), which involves all parts and assemblies of the product, is the core of any mechanical or electronic product. The flexible and integrated management of engineering (Engineering Bill of Materials [eBOM]) and manufacturing (Manufacturing Bill of Materials [mBOM]) structures is the key to the creation of modern products in mechanical engineering companies. This paper presents a method framework for the creation and control of e- and, especially, mBOM. The requirements, resulting from the process of differentiation between companies that produce serialized or engineered-to-order products, are considered in the analysis phase. The main part of the paper describes different approaches to fully or partly automated creation of mBOM. The first approach is the definition of part selection rules in the generic mBOM templates. The mBOM can be derived from the eBOM for partly standardized products by using this method. Another approach is the simultaneous use of semantic rules, options, and parameters in both structures. The implementation of the method framework (selection of use cases) in a standard product lifecycle management (PLM) system is part of the research.

Generalized differential transform method to differential-difference equation

International Nuclear Information System (INIS)

Zou Li; Wang Zhen; Zong Zhi

2009-01-01

In this Letter, we generalize the differential transform method to solve differential-difference equation for the first time. Two simple but typical examples are applied to illustrate the validity and the great potential of the generalized differential transform method in solving differential-difference equation. A Pade technique is also introduced and combined with GDTM in aim of extending the convergence area of presented series solutions. Comparisons are made between the results of the proposed method and exact solutions. Then we apply the differential transform method to the discrete KdV equation and the discrete mKdV equation, and successfully obtain solitary wave solutions. The results reveal that the proposed method is very effective and simple. We should point out that generalized differential transform method is also easy to be applied to other nonlinear differential-difference equation.

Semantics and the multisensory brain: how meaning modulates processes of audio-visual integration.

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Doehrmann, Oliver; Naumer, Marcus J

2008-11-25

By using meaningful stimuli, multisensory research has recently started to investigate the impact of stimulus content on crossmodal integration. Variations in this respect have often been termed as "semantic". In this paper we will review work related to the question for which tasks the influence of semantic factors has been found and which cortical networks are most likely to mediate these effects. More specifically, the focus of this paper will be on processing of object stimuli presented in the auditory and visual sensory modalities. Furthermore, we will investigate which cortical regions are particularly responsive to experimental variations of content by comparing semantically matching ("congruent") and mismatching ("incongruent") experimental conditions. In this context, recent neuroimaging studies point toward a possible functional differentiation of temporal and frontal cortical regions, with the former being more responsive to semantically congruent and the latter to semantically incongruent audio-visual (AV) stimulation. To account for these differential effects, we will suggest in the final section of this paper a possible synthesis of these data on semantic modulation of AV integration with findings from neuroimaging studies and theoretical accounts of semantic memory.

Categorizing words through semantic memory navigation

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Borge-Holthoefer, J.; Arenas, A.

2010-03-01

Semantic memory is the cognitive system devoted to storage and retrieval of conceptual knowledge. Empirical data indicate that semantic memory is organized in a network structure. Everyday experience shows that word search and retrieval processes provide fluent and coherent speech, i.e. are efficient. This implies either that semantic memory encodes, besides thousands of words, different kind of links for different relationships (introducing greater complexity and storage costs), or that the structure evolves facilitating the differentiation between long-lasting semantic relations from incidental, phenomenological ones. Assuming the latter possibility, we explore a mechanism to disentangle the underlying semantic backbone which comprises conceptual structure (extraction of categorical relations between pairs of words), from the rest of information present in the structure. To this end, we first present and characterize an empirical data set modeled as a network, then we simulate a stochastic cognitive navigation on this topology. We schematize this latter process as uncorrelated random walks from node to node, which converge to a feature vectors network. By doing so we both introduce a novel mechanism for information retrieval, and point at the problem of category formation in close connection to linguistic and non-linguistic experience.

When the Wedding March becomes sad: Semantic memory impairment for music in the semantic variant of primary progressive aphasia.

Science.gov (United States)

Macoir, Joël; Berubé-Lalancette, Sarah; Wilson, Maximiliano A; Laforce, Robert; Hudon, Carol; Gravel, Pierre; Potvin, Olivier; Duchesne, Simon; Monetta, Laura

2016-12-01

Music can induce particular emotions and activate semantic knowledge. In the semantic variant of primary progressive aphasia (svPPA), semantic memory is impaired as a result of anterior temporal lobe (ATL) atrophy. Semantics is responsible for the encoding and retrieval of factual knowledge about music, including associative and emotional attributes. In the present study, we report the performance of two individuals with svPPA in three experiments. NG with bilateral ATL atrophy and ND with atrophy largely restricted to the left ATL. Experiment 1 assessed the recognition of musical excerpts and both patients were unimpaired. Experiment 2 studied the emotions conveyed by music and only NG showed impaired performance. Experiment 3 tested the association of semantic concepts to musical excerpts and both patients were impaired. These results suggest that the right ATL seems essential for the recognition of emotions conveyed by music and that the left ATL is involved in binding music to semantics. They are in line with the notion that the ATLs are devoted to the binding of different modality-specific properties and suggest that they are also differentially involved in the processing of factual and emotional knowledge associated with music.

Semantic attributes based texture generation

Science.gov (United States)

Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

2018-04-01

Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

Differential Equations as Actions

DEFF Research Database (Denmark)

Ronkko, Mauno; Ravn, Anders P.

1997-01-01

We extend a conventional action system with a primitive action consisting of a differential equation and an evolution invariant. The semantics is given by a predicate transformer. The weakest liberal precondition is chosen, because it is not always desirable that steps corresponding to differential...... actions shall terminate. It is shown that the proposed differential action has a semantics which corresponds to a discrete approximation when the discrete step size goes to zero. The extension gives action systems the power to model real-time clocks and continuous evolutions within hybrid systems....

A THREE-STEP SPATIAL-TEMPORAL-SEMANTIC CLUSTERING METHOD FOR HUMAN ACTIVITY PATTERN ANALYSIS

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W. Huang

2016-06-01

Full Text Available How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time to four dimensions (space, time and semantics. More specifically, not only a location and time that people stay and spend are collected, but also what people “say” for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The

Functional imaging of the semantic system: retrieval of sensory-experienced and verbally learned knowledge.

Science.gov (United States)

Noppeney, Uta; Price, Cathy J

2003-01-01

This paper considers how functional neuro-imaging can be used to investigate the organization of the semantic system and the limitations associated with this technique. The majority of the functional imaging studies of the semantic system have looked for divisions by varying stimulus category. These studies have led to divergent results and no clear anatomical hypotheses have emerged to account for the dissociations seen in behavioral studies. Only a few functional imaging studies have used task as a variable to differentiate the neural correlates of semantic features more directly. We extend these findings by presenting a new study that contrasts tasks that differentially weight sensory (color and taste) and verbally learned (origin) semantic features. Irrespective of the type of semantic feature retrieved, a common semantic system was activated as demonstrated in many previous studies. In addition, the retrieval of verbally learned, but not sensory-experienced, features enhanced activation in medial and lateral posterior parietal areas. We attribute these "verbally learned" effects to differences in retrieval strategy and conclude that evidence for segregation of semantic features at an anatomical level remains weak. We believe that functional imaging has the potential to increase our understanding of the neuronal infrastructure that sustains semantic processing but progress may require multiple experiments until a consistent explanatory framework emerges.

An explicit semantic relatedness measure based on random walk

Directory of Open Access Journals (Sweden)

HU Sihui

2016-10-01

Full Text Available The semantic relatedness calculation of open domain knowledge network is a significant issue.In this paper,pheromone strategy is drawn from the thought of ant colony algorithm and is integrated into the random walk which is taken as the basic framework of calculating the semantic relatedness degree.The pheromone distribution is taken as a criterion of determining the tightness degree of semantic relatedness.A method of calculating semantic relatedness degree based on random walk is proposed and the exploration process of calculating the semantic relatedness degree is presented in a dominant way.The method mainly contains Path Select Model(PSM and Semantic Relatedness Computing Model(SRCM.PSM is used to simulate the path selection of ants and pheromone release.SRCM is used to calculate the semantic relatedness by utilizing the information returned by ants.The result indicates that the method could complete semantic relatedness calculation in linear complexity and extend the feasible strategy of semantic relatedness calculation.

Verbal and non-verbal semantic impairment: From fluent primary progressive aphasia to semantic dementia

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Mirna Lie Hosogi Senaha

Full Text Available Abstract Selective disturbances of semantic memory have attracted the interest of many investigators and the question of the existence of single or multiple semantic systems remains a very controversial theme in the literature. Objectives: To discuss the question of multiple semantic systems based on a longitudinal study of a patient who presented semantic dementia from fluent primary progressive aphasia. Methods: A 66 year-old woman with selective impairment of semantic memory was examined on two occasions, undergoing neuropsychological and language evaluations, the results of which were compared to those of three paired control individuals. Results: In the first evaluation, physical examination was normal and the score on the Mini-Mental State Examination was 26. Language evaluation revealed fluent speech, anomia, disturbance in word comprehension, preservation of the syntactic and phonological aspects of the language, besides surface dyslexia and dysgraphia. Autobiographical and episodic memories were relatively preserved. In semantic memory tests, the following dissociation was found: disturbance of verbal semantic memory with preservation of non-verbal semantic memory. Magnetic resonance of the brain revealed marked atrophy of the left anterior temporal lobe. After 14 months, the difficulties in verbal semantic memory had become more severe and the semantic disturbance, limited initially to the linguistic sphere, had worsened to involve non-verbal domains. Conclusions: Given the dissociation found in the first examination, we believe there is sufficient clinical evidence to refute the existence of a unitary semantic system.

Using test of Colour Semantic Differential for research into organizational culture

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Martina Rešlová

2013-01-01

Full Text Available The aim of this article is to show the possibility of using a combination of the Values Survey Module 1994 (VSM 94 and the Test of Colour Semantic Differential (TCSD for research into organizational culture. The results of the VSM 94 enable the researcher to determine which poles of Hofstede’s cultural dimensions a particular working group is in fact approaching while the data obtained through TCSD make it possible to define how employees consciously rate and unconsciously perceive expressions related to Hofstede’s cultural dimensions, or how they identify themselves with the researched values, respectively. The final values from the VSM 94 are compared with Hofstede’s national values and it is investigated whether it is possible to speak about the impact of national culture on corporate culture. This article also describes advantages and disadvantages of TCSD as well as the possibilities of its more focused use for research into organizational culture. TCSD has not been widely used for research into organizational culture although it has many practical uses thanks to the ability to work with respondents’ unconsciousness in connection with culture.

THE PRINCIPLES AND METHODS OF INFORMATION AND EDUCATIONAL SPACE SEMANTIC STRUCTURING BASED ON ONTOLOGIC APPROACH REALIZATION

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Yurij F. Telnov

2014-01-01

Full Text Available This article reveals principles of semantic structuring of information and educational space of objects of knowledge and scientific and educational services with use of methods of ontologic engineering. Novelty of offered approach is interface of ontology of a content and ontology of scientific and educational services that allows to carry out effective composition of services and objects of knowledge according to models of professional competences and requirements being trained. As a result of application of methods of information and educational space semantic structuring integration of use of the diverse distributed scientific and educational content by educational institutions for carrying out scientific researches, methodical development and training is provided.

Semantic Blogging : Spreading the Semantic Web Meme

OpenAIRE

Cayzer, Steve

2004-01-01

This paper is about semantic blogging, an application of the semantic web to blogging. The semantic web promises to make the web more useful by endowing metadata with machine processable semantics. Blogging is a lightweight web publishing paradigm which provides a very low barrier to entry, useful syndication and aggregation behaviour, a simple to understand structure and decentralized construction of a rich information network. Semantic blogging builds upon the success and clear network valu...

Workspaces in the Semantic Web

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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.

Acoustic and semantic interference effects in words and pictures.

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Dhawan, M; Pellegrino, J W

1977-05-01

Interference effects for pictures and words were investigated using a probe-recall task. Word stimuli showed acoustic interference effects for items at the end of the list and semantic interference effects for items at the beginning of the list, similar to results of Kintsch and Buschke (1969). Picture stimuli showed large semantic interference effects at all list positions with smaller acoustic interference effects. The results were related to latency data on picture-word processing and interpreted in terms of the differential order, probability, and/or speed of access to acoustic and semantic levels of processing. A levels of processing explanation of picture-word retention differences was related to dual coding theory. Both theoretical positions converge on an explanation of picture-word retention differences as a function of the relative capacity for semantic or associative processing.

A semantics-based method for clustering of Chinese web search results

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Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

2014-01-01

Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

Biomedical semantics in the Semantic Web.

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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.

METHODOLOGICAL ISSUES OF THE SOCIOLOGICAL STUDY OF POETRY (the use of semantic differentials in sociopoetics

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A. I. Antonov

2017-01-01

Full Text Available In sociology, literature, along with the study of the content of works of art and social characteristics of characters it is important to study the creative process. Here is an attempt to look at the poetry writing and its results through the prism of the behavioral approach on the basis of the poetry content analysis. Creation of the poem is considered as a behavioral creative process of self-actualization of creative potential, interactions of the system of requirements and social situations verbally expressed by means of language. During the framing actualized thoughts and feelings of the poet translated into poetic form. The main hypothesis is that the emotional dissonance express itself poetically. Semantic differential (SD technique provides a clue to the text. Content analysis of poems (cycles, books of separate poets through SD method could provide the understanding of similarities and differences of successive stages of the creating creative process of the same master, or explain the dissimilarity of poets compared to each other. The analysis of separate poems of Blok, Gumilev, Yesenin, Akhmatova ect. may demonstrate style features, the individual originality of each poets considered in terms of the dialectic opposition. The article discusses the possibilities of the SD method and the antonyms scales search in the author’s text in the study of the creative process, based on the characteristics of the poetry of classical Russian poet Alexander Blok.

Generation Y, wine and alcohol. A semantic differential approach to consumption analysis in Tuscany.

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Marinelli, Nicola; Fabbrizzi, Sara; Alampi Sottini, Veronica; Sacchelli, Sandro; Bernetti, Iacopo; Menghini, Silvio

2014-04-01

The aim of the study is the elicitation of the consumer's semantic perception of different alcoholic beverages in order to provide information for the definition of communication strategies for both the private sector (and specifically the wine industry) and the public decision maker. Such information can be seen as the basis of a wider social marketing construct aimed at the promotion of responsible drinking among young consumers. The semantic differential approach was used in this study. The data collection was based on a survey to 430 consumers between 18 and 35years old in Tuscany, Italy. The database was organized in a three-way structure, indexing the data in a multiway matrix. The data were processed using a Multiple Factor Analysis (MFA). Moreover, homogeneous clusters of consumers were identified using a Hierarchical Clustering on Principal Components (HCPC) approach. The results of the study highlight that beer and spirits are mainly perceived as "Young", "Social", "Euphoric", "Happy", "Appealing" and "Trendy" beverages, while wine is associated mostly with terms such as "Pleasure", "Quality" and "Comfortable". Furthermore, the cluster analysis allowed for the identification of three groups of individuals with different approaches to alcohol drinking. The results of the study supply a useful information framework for the elaboration of specific communication strategies that, based on the drinking habits of young consumers and their perception of different beverages, can use a language that is very close to the consumer typologies. Such information can be helpful for both private and public communication strategies. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

The semantic basis of taste-shape associations

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Carlos Velasco

2016-02-01

Full Text Available Previous research shows that people systematically match tastes with shapes. Here, we assess the extent to which matched taste and shape stimuli share a common semantic space and whether semantically congruent versus incongruent taste/shape associations can influence the speed with which people respond to both shapes and taste words. In Experiment 1, semantic differentiation was used to assess the semantic space of both taste words and shapes. The results suggest a common semantic space containing two principal components (seemingly, intensity and hedonics and two principal clusters, one including round shapes and the taste word “sweet,” and the other including angular shapes and the taste words “salty,” “sour,” and “bitter.” The former cluster appears more positively-valenced whilst less potent than the latter. In Experiment 2, two speeded classification tasks assessed whether congruent versus incongruent mappings of stimuli and responses (e.g., sweet with round versus sweet with angular would influence the speed of participants’ responding, to both shapes and taste words. The results revealed an overall effect of congruence with congruent trials yielding faster responses than their incongruent counterparts. These results are consistent with previous evidence suggesting a close relation (or crossmodal correspondence between tastes and shape curvature that may derive from common semantic coding, perhaps along the intensity and hedonic dimensions.

Preserved musical semantic memory in semantic dementia.

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

2011-02-01

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

Semantisches Differential über Gott

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Benesch, Thomas

2017-11-01

Full Text Available A qualitative research was performed to explore the semantic differential regarding the image of God from young persons. These pairs of contrast were qualified in the field of environment as well as physical and mental characteristics. 27 contrast pairs from a large number of different options had been selected, to reveal through a written survey with adolescents their relationship with God. The semantic differential was evaluated through a factor analysis.

Dynamic switching between semantic and episodic memory systems.

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Kompus, Kristiina; Olsson, Carl-Johan; Larsson, Anne; Nyberg, Lars

2009-09-01

It has been suggested that episodic and semantic long-term memory systems interact during retrieval. Here we examined the flexibility of memory retrieval in an associative task taxing memories of different strength, assumed to differentially engage episodic and semantic memory. Healthy volunteers were pre-trained on a set of 36 face-name pairs over a 6-week period. Another set of 36 items was shown only once during the same time period. About 3 months after the training period all items were presented in a randomly intermixed order in an event-related fMRI study of face-name memory. Once presented items differentially activated anterior cingulate cortex and a right prefrontal region that previously have been associated with episodic retrieval mode. High-familiar items were associated with stronger activation of posterior cortices and a left frontal region. These findings fit a model of memory retrieval by which early processes determine, on a trial-by-trial basis, if the task can be solved by the default semantic system. If not, there is a dynamic shift to cognitive control processes that guide retrieval from episodic memory.

Semantic matchmaking with nonmonotonic description logics

CERN Document Server

Grimm, S

2009-01-01

Semantic web has grown into a mature field of research. Its methods find innovative applications on and off the World Wide Web. Its underlying technologies have significant impact on adjacent fields of research and on industrial applications. This new book series reports on the state-of-the-art in foundations, methods, and applications of semantic web and its underlying technologies. It is a central forum for the communication of recent developments and comprises research monographs, textbooks and edited volumes on all topics related to the semantic web. In this first volume several non-monoto

COTARD SYNDROME IN SEMANTIC DEMENTIA

Science.gov (United States)

Mendez, Mario F.; Ramírez-Bermúdez, Jesús

2011-01-01

Background Semantic dementia is a neurodegenerative disorder characterized by the loss of meaning of words or concepts. semantic dementia can offer potential insights into the mechanisms of content-specific delusions. Objective The authors present a rare case of semantic dementia with Cotard syndrome, a delusion characterized by nihilism or self-negation. Method The semantic deficits and other features of semantic dementia were evaluated in relation to the patient's Cotard syndrome. Results Mrs. A developed the delusional belief that she was wasting and dying. This occurred after she lost knowledge for her somatic discomforts and sensations and for the organs that were the source of these sensations. Her nihilistic beliefs appeared to emerge from her misunderstanding of her somatic sensations. Conclusion This unique patient suggests that a mechanism for Cotard syndrome is difficulty interpreting the nature and source of internal pains and sensations. We propose that loss of semantic knowledge about one's own body may lead to the delusion of nihilism or death. PMID:22054629

Semantic Advertising

OpenAIRE

Zamanzadeh, Ben; Ashish, Naveen; Ramakrishnan, Cartic; Zimmerman, John

2013-01-01

We present the concept of Semantic Advertising which we see as the future of online advertising. Semantic Advertising is online advertising powered by semantic technology which essentially enables us to represent and reason with concepts and the meaning of things. This paper aims to 1) Define semantic advertising, 2) Place it in the context of broader and more widely used concepts such as the Semantic Web and Semantic Search, 3) Provide a survey of work in related areas such as context matchi...

Functional heterogeneity within the default network during semantic processing and speech production.

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Mohamed L Seghier

2012-08-01

Full Text Available This fMRI study investigated the functional heterogeneity of the core nodes of the default mode network (DMN during language processing. The core nodes of the DMN were defined as task-induced deactivations over multiple tasks in 94 healthy subjects. We used a factorial design that manipulated different tasks (semantic matching or speech production and stimuli (familiar words and objects or unfamiliar stimuli, alternating with periods of fixation/rest. Our findings revealed several consistent effects in the DMN, namely less deactivations in the left inferior parietal lobule during semantic than perceptual matching in parallel with greater deactivations during semantic matching in anterior subdivisions of the posterior cingulate cortex and the ventromedial prefrontal cortex. This suggests that, when the brain is engaged in effortful semantic tasks, a part of the DMN in the left angular gyrus was less deactivated as five other nodes of the DMN were more deactivated. These five DMN areas, where deactivation was greater for semantic than perceptual matching, were further differentiated because deactivation was greater in (i posterior ventromedial prefrontal cortex for speech production relative to semantic matching, (ii posterior precuneus and posterior cingulate cortex for perceptual processing relative to speech production and (iii right inferior parietal cortex for pictures of objects relative to written words during both naming and semantic decisions. Our results thus highlight that task difficulty alone cannot fully explain the functional variability in task-induced deactivations. Together these results emphasize that core nodes within the DMN are functionally heterogeneous and differentially sensitive to the type of language processing.

Graph-based Operational Semantics of a Lazy Functional Languages

DEFF Research Database (Denmark)

Rose, Kristoffer Høgsbro

1992-01-01

Presents Graph Operational Semantics (GOS): a semantic specification formalism based on structural operational semantics and term graph rewriting. Demonstrates the method by specifying the dynamic ...

Semantic Business Process Modeling

OpenAIRE

Markovic, Ivan

2010-01-01

This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios.

Using semantic analysis to improve speech recognition performance

OpenAIRE

Erdoğan, Hakan; Erdogan, Hakan; Sarıkaya, Ruhi; Sarikaya, Ruhi; Chen, Stanley F.; Gao, Yuqing; Picheny, Michael

2005-01-01

Although syntactic structure has been used in recent work in language modeling, there has not been much effort in using semantic analysis for language models. In this study, we propose three new language modeling techniques that use semantic analysis for spoken dialog systems. We call these methods concept sequence modeling, two-level semantic-lexical modeling, and joint semantic-lexical modeling. These models combine lexical information with varying amounts of semantic information, using ann...

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2008-01-01

We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i...... actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine...

A Denotational Semantics for Communicating Unstructured Code

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Nils Jähnig

2015-03-01

Full Text Available An important property of programming language semantics is that they should be compositional. However, unstructured low-level code contains goto-like commands making it hard to define a semantics that is compositional. In this paper, we follow the ideas of Saabas and Uustalu to structure low-level code. This gives us the possibility to define a compositional denotational semantics based on least fixed points to allow for the use of inductive verification methods. We capture the semantics of communication using finite traces similar to the denotations of CSP. In addition, we examine properties of this semantics and give an example that demonstrates reasoning about communication and jumps. With this semantics, we lay the foundations for a proof calculus that captures both, the semantics of unstructured low-level code and communication.

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2008-01-01

.e., big-step operational semantics) specified in Abadi and Cardelli's monograph. This abstract machine therefore embodies the soundness of Abadi and Cardelli's reduction semantics and natural semantics relative to each other. To move closer to actual implementations, which use environments rather than......We present a new abstract machine for Abadi and Cardelli's untyped calculus of objects. What is special about this semantic artifact (i.e., man-made construct) is that is mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i...... actual substitutions, we then represent object methods as closures and in the same inter-derivational spirit, we present three new semantic artifacts: a reduction semantics for a version of Abadi and Cardelli's untyped calculus of objects with explicit substitutions, an environment-based abstract machine...

Semantator: annotating clinical narratives with semantic web ontologies.

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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.

LAIR: A Language for Automated Semantics-Aware Text Sanitization based on Frame Semantics

DEFF Research Database (Denmark)

Hedegaard, Steffen; Houen, Søren; Simonsen, Jakob Grue

2009-01-01

We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires on...... with automated redaction of web pages for subjectively undesirable content; initial experiments suggest that using a small language based on semantic recognition of undesirable terms can be highly useful as a supplement to traditional methods of text sanitization.......We present \\lair{}: A domain-specific language that enables users to specify actions to be taken upon meeting specific semantic frames in a text, in particular to rephrase and redact the textual content. While \\lair{} presupposes superficial knowledge of frames and frame semantics, it requires only...... limited prior programming experience. It neither contain scripting or I/O primitives, nor does it contain general loop constructions and is not Turing-complete. We have implemented a \\lair{} compiler and integrated it in a pipeline for automated redaction of web pages. We detail our experience...

Advanced differential quadrature methods

CERN Document Server

Zong, Zhi

2009-01-01

Modern Tools to Perform Numerical DifferentiationThe original direct differential quadrature (DQ) method has been known to fail for problems with strong nonlinearity and material discontinuity as well as for problems involving singularity, irregularity, and multiple scales. But now researchers in applied mathematics, computational mechanics, and engineering have developed a range of innovative DQ-based methods to overcome these shortcomings. Advanced Differential Quadrature Methods explores new DQ methods and uses these methods to solve problems beyond the capabilities of the direct DQ method.After a basic introduction to the direct DQ method, the book presents a number of DQ methods, including complex DQ, triangular DQ, multi-scale DQ, variable order DQ, multi-domain DQ, and localized DQ. It also provides a mathematical compendium that summarizes Gauss elimination, the Runge-Kutta method, complex analysis, and more. The final chapter contains three codes written in the FORTRAN language, enabling readers to q...

Learning semantic and visual similarity for endomicroscopy video retrieval.

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Andre, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2012-06-01

Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them

Episodic and semantic memory impairments in (very early Alzheimer’s disease: The diagnostic accuracy of paired-associate learning formats

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Pauline E.J. Spaan

2016-12-01

Full Text Available Paired-associate learning (PAL paradigms measure memory processes sensitive to the medial temporal lobe, which shows atrophy in early Alzheimer’s disease (AD. PAL tests have not yet been standard clinical procedure, neither are semantic memory tests. In early AD, impairments are more subtle. A literature review indicates that standard neuropsychological tests may not measure these impairments accurately. Therefore, I constructed new episodic and semantic memory tests. I investigated the diagnostic accuracy of these tests in 37 amnestic mild cognitive impairment (aMCI; of whom 21 had converted to AD at 1.3-year-follow-up, 43 early AD patients, and 80 non-demented controls. Main questions: (1 which tests best differentiate aMCI and AD from normal aging: most sensitively, most specifically?; (2 do PAL paradigms and/or semantic memory tests (fluency; naming contribute to this differentiation? A free recall (non-PAL test of unrelated words was most sensitive to aMCI and AD (91%, whereas a PAL-recognition-test (of semantically related word pairs of moderate association strength, including strongly related foils was most specific (96%. Stepwise logistic regression analysis showed that differentiation was improved by a subordinate semantic fluency test. I conclude that a combination of episodic and semantic memory components best predicts AD. Future research should focus on comparing semantic and visuospatial PAL tests.

Differential Medial Temporal Lobe and Parietal Cortical Contributions to Real-world Autobiographical Episodic and Autobiographical Semantic Memory.

Science.gov (United States)

Brown, Thackery I; Rissman, Jesse; Chow, Tiffany E; Uncapher, Melina R; Wagner, Anthony D

2018-04-18

Autobiographical remembering can depend on two forms of memory: episodic (event) memory and autobiographical semantic memory (remembering personally relevant semantic knowledge, independent of recalling a specific experience). There is debate about the degree to which the neural signals that support episodic recollection relate to or build upon autobiographical semantic remembering. Pooling data from two fMRI studies of memory for real-world personal events, we investigated whether medial temporal lobe (MTL) and parietal subregions contribute to autobiographical episodic and semantic remembering. During scanning, participants made memory judgments about photograph sequences depicting past events from their life or from others' lives, and indicated whether memory was based on episodic or semantic knowledge. Results revealed several distinct functional patterns: activity in most MTL subregions was selectively associated with autobiographical episodic memory; the hippocampal tail, superior parietal lobule, and intraparietal sulcus were similarly engaged when memory was based on retrieval of an autobiographical episode or autobiographical semantic knowledge; and angular gyrus demonstrated a graded pattern, with activity declining from autobiographical recollection to autobiographical semantic remembering to correct rejections of novel events. Collectively, our data offer insights into MTL and parietal cortex functional organization, and elucidate circuitry that supports different forms of real-world autobiographical memory.

Compiling Dictionaries Using Semantic Domains*

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Ronald Moe

2011-10-01

Full Text Available

Abstract: The task of providing dictionaries for all the world's languages is prodigious, re-quiring efficient techniques. The text corpus method cannot be used for minority languages lacking texts. To meet the need, the author has constructed a list of 1 600 semantic domains, which he has successfully used to collect words. In a workshop setting, a group of speakers can collect as many as 17 000 words in ten days. This method results in a classified word list that can be efficiently expanded into a full dictionary. The method works because the mental lexicon is a giant web or-ganized around key concepts. A semantic domain can be defined as an important concept together with the words directly related to it by lexical relations. A person can utilize the mental web to quickly jump from word to word within a domain. The author is developing a template for each domain to aid in collecting words and in de-scribing their semantics. Investigating semantics within the context of a domain yields many in-sights. The method permits the production of both alphabetically and semantically organized dic-tionaries. The list of domains is intended to be universal in scope and applicability. Perhaps due to universals of human experience and universals of linguistic competence, there are striking simi-larities in various lists of semantic domains developed for languages around the world. Using a standardized list of domains to classify multiple dictionaries opens up possibilities for cross-lin-guistic research into semantic and lexical universals.

Keywords: SEMANTIC DOMAINS, SEMANTIC FIELDS, SEMANTIC CATEGORIES, LEX-ICAL RELATIONS, SEMANTIC PRIMITIVES, DOMAIN TEMPLATES, MENTAL LEXICON, SEMANTIC UNIVERSALS, MINORITY LANGUAGES, LEXICOGRAPHY

Opsomming: Samestelling van woordeboeke deur gebruikmaking van se-mantiese domeine. Die taak van die voorsiening van woordeboeke aan al die tale van die wêreld is geweldig en vereis doeltreffende tegnieke. Die

A Numerical Method for Partial Differential Algebraic Equations Based on Differential Transform Method

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Murat Osmanoglu

2013-01-01

Full Text Available We have considered linear partial differential algebraic equations (LPDAEs of the form , which has at least one singular matrix of . We have first introduced a uniform differential time index and a differential space index. The initial conditions and boundary conditions of the given system cannot be prescribed for all components of the solution vector here. To overcome this, we introduced these indexes. Furthermore, differential transform method has been given to solve LPDAEs. We have applied this method to a test problem, and numerical solution of the problem has been compared with analytical solution.

Topics in Semantics-based Program Manipulation

DEFF Research Database (Denmark)

Grobauer, Bernt

four articles in the field of semantics-based techniques for program manipulation: three articles are about partial evaluation, a method for program specialization; the fourth article treats an approach to automatic cost analysis. Partial evaluation optimizes programs by specializing them with respect...... article in this dissertation describes how the second Futamura projection can be achieved for type-directed partial evaluation (TDPE), a relatively recent approach to partial evaluation: We derive an ML implementation of the second Futamura projection for TDPE. Due to the differences between ‘traditional...... denotational semantics—allows us to relate various possible semantics to each other both conceptually and formally. We thus are able to explain goal-directed evaluation using an intuitive list-based semantics, while using a continuation semantics for semantics-based compilation through partial evaluation...

Personal semantics: Is it distinct from episodic and semantic memory? An electrophysiological study of memory for autobiographical facts and repeated events in honor of Shlomo Bentin.

Science.gov (United States)

Renoult, Louis; Tanguay, Annick; Beaudry, Myriam; Tavakoli, Paniz; Rabipour, Sheida; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian; Davidson, Patrick S R

2016-03-01

Declarative memory is thought to consist of two independent systems: episodic and semantic. Episodic memory represents personal and contextually unique events, while semantic memory represents culturally-shared, acontextual factual knowledge. Personal semantics refers to aspects of declarative memory that appear to fall somewhere in between the extremes of episodic and semantic. Examples include autobiographical knowledge and memories of repeated personal events. These two aspects of personal semantics have been studied little and rarely compared to both semantic and episodic memory. We recorded the event-related potentials (ERPs) of 27 healthy participants while they verified the veracity of sentences probing four types of questions: general (i.e., semantic) facts, autobiographical facts, repeated events, and unique (i.e., episodic) events. Behavioral results showed equivalent reaction times in all 4 conditions. True sentences were verified faster than false sentences, except for unique events for which no significant difference was observed. Electrophysiological results showed that the N400 (which is classically associated with retrieval from semantic memory) was maximal for general facts and the LPC (which is classically associated with retrieval from episodic memory) was maximal for unique events. For both ERP components, the two personal semantic conditions (i.e., autobiographical facts and repeated events) systematically differed from semantic memory. In addition, N400 amplitudes also differentiated autobiographical facts from unique events. Autobiographical facts and repeated events did not differ significantly from each other but their corresponding scalp distributions differed from those associated with general facts. Our results suggest that the neural correlates of personal semantics can be distinguished from those of semantic and episodic memory, and may provide clues as to how unique events are transformed to semantic memory. Copyright © 2015 Elsevier

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

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

2016-01-01

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

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

Science.gov (United States)

Bonnici, Heidi M; Richter, Franziska R; Yazar, Yasemin; Simons, Jon S

2016-05-18

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

Semantics and expressiveness of ordered SOS

NARCIS (Netherlands)

Mousavi, M.R.; Phillips, I.C.C.; Reniers, M.A.; Ulidowski, I.

2009-01-01

Structured Operational Semantics (SOS) is a popular method for defining semantics by means of transition rules. An important feature of SOS rules is negative premises, which are crucial in the definitions of such phenomena as priority mechanisms and time-outs. However, the inclusion of negative

Scandinavian Semantics and the Human Body

DEFF Research Database (Denmark)

Levisen, Carsten

2015-01-01

, it is demonstrated that Scandinavian and English systems differ significantly in some aspects of the way in which the construe the human body with words. The study ventures an innovative combination of methods, pairing the Natural Semantic Metalanguage (NSM) approach to linguistic and conceptual analysis......This paper presents an ethnolinguistic analysis of how the space between the head and the body is construed in Scandinavian semantic systems vis-a-vis the semantic system of English. With an extensive case study of neck-related meanings in Danish, and with cross-Scandinavian reference...... with empirical evidence from the Evolution of Semantic Systems (EoSS) project. This combination of empirical and interpretative tools helps to integrate evidence from semantics and semiotics, pinning out in great detail the intricacies of the meanings of particular body words. The paper concludes that body words...

Semantic Information Extraction of Lanes Based on Onboard Camera Videos

Science.gov (United States)

Tang, L.; Deng, T.; Ren, C.

2018-04-01

In the field of autonomous driving, semantic information of lanes is very important. This paper proposes a method of automatic detection of lanes and extraction of semantic information from onboard camera videos. The proposed method firstly detects the edges of lanes by the grayscale gradient direction, and improves the Probabilistic Hough transform to fit them; then, it uses the vanishing point principle to calculate the lane geometrical position, and uses lane characteristics to extract lane semantic information by the classification of decision trees. In the experiment, 216 road video images captured by a camera mounted onboard a moving vehicle were used to detect lanes and extract lane semantic information. The results show that the proposed method can accurately identify lane semantics from video images.

SEPHYRES 1: A Symptom Checker based on Semantic Pain Descriptors and Weight Spreading

Directory of Open Access Journals (Sweden)

Ali SANAEIFAR

2016-12-01

Full Text Available Semantic-enabled medical diagnostic systems, which have exploited an ontology in their internal engines, have failed to perfectly describe disease profiles, especially in complex medical terms having a variant generality level or certainty in the medical literature. The main objective of this paper was to present an ontology with a highly matching grade of proeminent medical concepts able to analyze the patient’s descriptive medical condition. Focusing on semantic pain descriptors and weight spreading techniques, we proposed a semantic-pseudo-fuzzy engine entitled SEPHYRES, with which we tried to present an ontology-based solution using not only a generic semantic reasoner but also complementary domain-heuristic reasoning. Having applied the valid evidence-based references along with local experts, we illustrated how the resilient expressive model represents the complex medical term relations. The twenty test cases were extracted from the MEDSCAPE and PubMed databases and the precision and recall were calculated. Finally, the results were compared against the Isabel symptom checker and performed the Wilcoxon signed-rank test. The recall measures indicated that the accuracy was equal to 75%, if the system was adjusted to only ten results as differential diagnoses. Moreover, the Wilcoxon signed-rank test showed that there was significant difference between SEPHYRES and Isabel symptom checker (P= 0.016 so that this method is sufficiently able to improve semantic expressiveness in both professional medical diagnosis and patient decision aid systems.

Evaluation of the Project Management Competences Based on the Semantic Networks

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

Full Text Available The paper presents the testing and evaluation facilities of the SinPers system. The SinPers is a web based learning environment in project management, capable of building and conducting a complete and personalized training cycle, from the definition of the learning objectives to the assessment of the learning results for each learner. The testing and evaluation facilities of SinPers system are based on the ontological approach. The educational ontology is mapped on a semantic network. Further, the semantic network is projected into a concept space graph. The semantic computability of the concept space graph is used to design the tests. The paper focuses on the applicability of the system in the certification, for the knowledge assessment, related to each element of competence. The semantic computability is used for differentiating between different certification levels.

Approximate semantic matching of music classes on the internet

NARCIS (Netherlands)

Aleksovski, Zharko; Kate, Warner Ten; Van Harmelen, Frank

2006-01-01

We address the problem of semantic matching, which concerns the search for semantic agreement between heterogeneous concept hierarchies. We propose a new approximation method to discover and assess the "strength" (preciseness) of a semantic match between concepts from two such concept hierarchies.

Geospatial semantic web

CERN Document Server

Zhang, Chuanrong; Li, Weidong

2015-01-01

This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL, and GeoSPARQL, and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.

Differential diagnosis of neurodegenerative dementias with nuclear medicine methods

International Nuclear Information System (INIS)

Kluge, R.

2015-01-01

Full text: Neurodegenerative dementias (NDD) are characterized by insidious onset and gradual progression of cognitive dysfunction, initially relatively focal with respect to cognitive domains and brain regions involved. Nuclear medicine techniques help to clarify differential diagnoses of syndromes such as Alzheimer’s disease (AD), dementia with Lewy bodies (DlB), posterior cortical atrophy (PCA), logopenic primary progressive aphasia (PPA), agrammatic PPA, semantic dementia (SD), behavioral variant frontotemporal dementia (bvFTD) and progressive supranuclear palsy syndrome (PSPS). The process of pathologic changes in the brain may start decades before first clinical symptoms become evident. An early diagnosis already in the pre-clinical phase of the diseases will be of immense importance when expected effective therapeutic options have been introduced. NDDs are histopathologically characterized by accumulation of pathological proteins in the brain like beta amyloid or protein tau. While radiotracers for labeling of protein tau are in preclinical evaluation, different radiotracers labeling amyloid plaques ([11C]PIB, [18F]Florbetapir (Amyvid, Fa. EliLilly), [18F]Florbetaben (Neuraceq, Fa. Piramal), [18F]Flutemetamol (vVzamyl, Fa. Ge) have already been established in clinical use during the last years. In AD these tracers are intensively accumulated in the whole cortical brain. Even an early disease can be excluded in case of a negative amyloid PET. The method is, however, not highly specific since amyloid plaques may also be present in DlB (70 – 80%), FTD (30%) orlogopenicPPA (100%). Neuronal dysfunction goes along with decreased glucose consumption. Different diseases are characterized by different topographical zones of reduced [18F]FDG uptake. In AD the posterior cingular, temporopariatal and (later) frontal cortex are affected, in DlB the pattern is similar, including the occipital cortex, in FTD the frontal cortex is affected, in nonfluent PPA the

Semantic-based surveillance video retrieval.

Science.gov (United States)

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.

A Method for Transforming Existing Web Service Descriptions into an Enhanced Semantic Web Service Framework

Science.gov (United States)

Du, Xiaofeng; Song, William; Munro, Malcolm

Web Services as a new distributed system technology has been widely adopted by industries in the areas, such as enterprise application integration (EAI), business process management (BPM), and virtual organisation (VO). However, lack of semantics in the current Web Service standards has been a major barrier in service discovery and composition. In this chapter, we propose an enhanced context-based semantic service description framework (CbSSDF+) that tackles the problem and improves the flexibility of service discovery and the correctness of generated composite services. We also provide an agile transformation method to demonstrate how the various formats of Web Service descriptions on the Web can be managed and renovated step by step into CbSSDF+ based service description without large amount of engineering work. At the end of the chapter, we evaluate the applicability of the transformation method and the effectiveness of CbSSDF+ through a series of experiments.

Semantic Multimedia

NARCIS (Netherlands)

S. Staab; A. Scherp; R. Arndt; R. Troncy (Raphael); M. Grzegorzek; C. Saathoff; S. Schenk; L. Hardman (Lynda)

2008-01-01

htmlabstractMultimedia constitutes an interesting field of application for Semantic Web and Semantic Web reasoning, as the access and management of multimedia content and context depends strongly on the semantic descriptions of both. At the same time, multimedia resources constitute complex objects,

Extracting Semantic Information from Visual Data: A Survey

Directory of Open Access Journals (Sweden)

Qiang Liu

2016-03-01

Full Text Available The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.

A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis

OpenAIRE

Okoye, Kingsley; Tawil, Abdel-Rahman; Naeem, Usman; Lamine, Elyes

2015-01-01

Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respo...

Recognition during recall failure: Semantic feature matching as a mechanism for recognition of semantic cues when recall fails.

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Cleary, Anne M; Ryals, Anthony J; Wagner, Samantha R

2016-01-01

Research suggests that a feature-matching process underlies cue familiarity-detection when cued recall with graphemic cues fails. When a test cue (e.g., potchbork) overlaps in graphemic features with multiple unrecalled studied items (e.g., patchwork, pitchfork, pocketbook, pullcork), higher cue familiarity ratings are given during recall failure of all of the targets than when the cue overlaps in graphemic features with only one studied target and that target fails to be recalled (e.g., patchwork). The present study used semantic feature production norms (McRae et al., Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005) to examine whether the same holds true when the cues are semantic in nature (e.g., jaguar is used to cue cheetah). Indeed, test cues (e.g., cedar) that overlapped in semantic features (e.g., a_tree, has_bark, etc.) with four unretrieved studied items (e.g., birch, oak, pine, willow) received higher cue familiarity ratings during recall failure than test cues that overlapped in semantic features with only two (also unretrieved) studied items (e.g., birch, oak), which in turn received higher familiarity ratings during recall failure than cues that did not overlap in semantic features with any studied items. These findings suggest that the feature-matching theory of recognition during recall failure can accommodate recognition of semantic cues during recall failure, providing a potential mechanism for conceptually-based forms of cue recognition during target retrieval failure. They also provide converging evidence for the existence of the semantic features envisaged in feature-based models of semantic knowledge representation and for those more concretely specified by the production norms of McRae et al. (Behavior Research Methods, Instruments, & Computers, 37, 547-559, 2005).

Varieties of semantic 'access' deficit in Wernicke's aphasia and semantic aphasia.

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Thompson, Hannah E; Robson, Holly; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2015-12-01

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 'beneficial' effects of stimulus repetition: cases with

Enhancing biomedical text summarization using semantic relation extraction.

Directory of Open Access Journals (Sweden)

Yue Shang

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

Enhancing biomedical text summarization using semantic relation extraction.

Science.gov (United States)

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

2011-01-01

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

Walking Across Wikipedia: A Scale-Free Network Model of Semantic Memory Retrieval

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Graham William Thompson

2014-02-01

Full Text Available Semantic knowledge has been investigated using both online and offline methods. One common online method is category recall, in which members of a semantic category like animals are retrieved in a given period of time. The order, timing, and number of retrievals are used as assays of semantic memory processes. One common offline method is corpus analysis, in which the structure of semantic knowledge is extracted from texts using co-occurrence or encyclopedic methods. Online measures of semantic processing, as well as offline measures of semantic structure, have yielded data resembling inverse power law distributions. The aim of the present study is to investigate whether these patterns in data might be related. A semantic network model of animal knowledge is formulated on the basis of Wikipedia pages and their overlap in word probability distributions. The network is scale-free, in that node degree is related to node frequency as an inverse power law. A random walk over this network is shown to simulate a number of results from a category recall experiment, including power law-like distributions of inter-response intervals. Results are discussed in terms of theories of semantic structure and processing.

Generative Semantics.

Science.gov (United States)

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…

Neural Substrates of Semantic Prospection – Evidence from the Dementias

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

2016-01-01

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

Neural Substrates of Semantic Prospection – Evidence from the Dementias

Directory of Open Access Journals (Sweden)

Muireann eIrish

2016-05-01

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

Relationship Structures and Semantic Type Assignments of the UMLS Enriched Semantic Network

Science.gov (United States)

Zhang, Li; Halper, Michael; Perl, Yehoshua; Geller, James; Cimino, James J.

2005-01-01

Objective: The Enriched Semantic Network (ESN) was introduced as an extension of the Unified Medical Language System (UMLS) Semantic Network (SN). Its multiple subsumption configuration and concomitant multiple inheritance make the ESN's relationship structures and semantic type assignments different from those of the SN. A technique for deriving the relationship structures of the ESN's semantic types and an automated technique for deriving the ESN's semantic type assignments from those of the SN are presented. Design: The technique to derive the ESN's relationship structures finds all newly inherited relationships in the ESN. All such relationships are audited for semantic validity, and the blocking mechanism is used to block invalid relationships. The mapping technique to derive the ESN's semantic type assignments uses current SN semantic type assignments and preserves nonredundant categorizations, while preventing new redundant categorizations. Results: Among the 426 newly inherited relationships, 326 are deemed valid. Seven blockings are applied to avoid inheritance of the 100 invalid relationships. Sixteen semantic types have different relationship structures in the ESN as compared to those in the SN. The mapping of semantic type assignments from the SN to the ESN avoids the generation of 26,950 redundant categorizations. The resulting ESN contains 138 semantic types, 149 IS-A links, 7,303 relationships, and 1,013,876 semantic type assignments. Conclusion: The ESN's multiple inheritance provides more complete relationship structures than in the SN. The ESN's semantic type assignments avoid the existing redundant categorizations appearing in the SN and prevent new ones that might arise due to multiple parents. Compared to the SN, the ESN provides a more accurate unifying semantic abstraction of the UMLS Metathesaurus. PMID:16049233

Discovering Central Practitioners in a Medical Discussion Forum Using Semantic Web Analytics.

Science.gov (United States)

Rajabi, Enayat; Abidi, Syed Sibte Raza

2017-01-01

The aim of this paper is to investigate semantic web based methods to enrich and transform a medical discussion forum in order to perform semantics-driven social network analysis. We use the centrality measures as well as semantic similarity metrics to identify the most influential practitioners within a discussion forum. The centrality results of our approach are in line with centrality measures produced by traditional SNA methods, thus validating the applicability of semantic web based methods for SNA, particularly for analyzing social networks for specialized discussion forums.

Exploring and linking biomedical resources through multidimensional semantic spaces.

Science.gov (United States)

Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria

2012-01-25

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

SCC: Semantic Context Cascade for Efficient Action Detection

KAUST Repository

Heilbron, Fabian Caba; Barrios, Wayner; Escorcia, Victor; Ghanem, Bernard

2017-01-01

in videos. Existing approaches have mitigated the computational cost, but still, these methods lack rich high-level semantics that helps them to localize the actions quickly. In this paper, we introduce a Semantic Cascade Context (SCC) model that aims

Efficient computation of argumentation semantics

CERN Document Server

Liao, Beishui

2013-01-01

Efficient Computation of Argumentation Semantics addresses argumentation semantics and systems, introducing readers to cutting-edge decomposition methods that drive increasingly efficient logic computation in AI and intelligent systems. Such complex and distributed systems are increasingly used in the automation and transportation systems field, and particularly autonomous systems, as well as more generic intelligent computation research. The Series in Intelligent Systems publishes titles that cover state-of-the-art knowledge and the latest advances in research and development in intelligen

Semantic Desktop

Science.gov (United States)

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.

Semantic reasoning with XML-based biomedical information models.

Science.gov (United States)

O'Connor, Martin J; Das, Amar

2010-01-01

The Extensible Markup Language (XML) is increasingly being used for biomedical data exchange. The parallel growth in the use of ontologies in biomedicine presents opportunities for combining the two technologies to leverage the semantic reasoning services provided by ontology-based tools. There are currently no standardized approaches for taking XML-encoded biomedical information models and representing and reasoning with them using ontologies. To address this shortcoming, we have developed a workflow and a suite of tools for transforming XML-based information models into domain ontologies encoded using OWL. In this study, we applied semantics reasoning methods to these ontologies to automatically generate domain-level inferences. We successfully used these methods to develop semantic reasoning methods for information models in the HIV and radiological image domains.

Semantic Dysfunction in Women With Schizotypal Personality Disorder

OpenAIRE

Niznikiewicz, Margaret A.; Shenton, Martha E.; Voglmaier, Martina; Nestor, Paul G.; Dickey, Chandlee C.; Frumin, Melissa; Seidman, Larry J.; Allen, Christopher G.; McCarley, Robert W.

2002-01-01

Objective: This study examined whether early or late processes in semantic networks were abnormal in women with a diagnosis of schizotypal personality disorder. The N400 component of the EEG event-related potentials was used as a probe of semantic processes. Method: Word pairs were presented with short and long stimulus-onset asynchronies to investigate, respectively, early and late semantic processes in 16 women with schizotypal personality disorder and 15 normal female comparison subjects. ...

Unsure When to Stop? Ask Your Semantic Neighbors

OpenAIRE

Gonçalves, Ivo; Silva, Sara; Fonseca, Carlos M.; Castelli, Mauro

2017-01-01

In iterative supervised learning algorithms it is common to reach a point in the search where no further induction seems to be possible with the available data. If the search is continued beyond this point, the risk of overfitting increases significantly. Following the recent developments in inductive semantic stochastic methods, this paper studies the feasibility of using information gathered from the semantic neighborhood to decide when to stop the search. Two semantic stopping criteria are...

SemFunSim: a new method for measuring disease similarity by integrating semantic and gene functional association.

Directory of Open Access Journals (Sweden)

Liang Cheng

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

Semantic heterogeneity: comparing new semantic web approaches with those of digital libraries

OpenAIRE

Krause, Jürgen

2008-01-01

To demonstrate that newer developments in the semantic web community, particularly those based on ontologies (simple knowledge organization system and others) mitigate common arguments from the digital library (DL) community against participation in the Semantic web. The approach is a semantic web discussion focusing on the weak structure of the Web and the lack of consideration given to the semantic content during indexing. The points criticised by the semantic web and ontology approaches ar...

A Derivational Approach to the Operational Semantics of Functional Languages

DEFF Research Database (Denmark)

Biernacka, Malgorzata

We study the connections between different forms of operational semantics for functional programming languages and we present systematic methods of interderiving reduction semantics, abstract machines and higher-order evaluators. We first consider two methods based on program transformations: a s...

Ontology based heterogeneous materials database integration and semantic query

Science.gov (United States)

Zhao, Shuai; Qian, Quan

2017-10-01

Materials digital data, high throughput experiments and high throughput computations are regarded as three key pillars of materials genome initiatives. With the fast growth of materials data, the integration and sharing of data is very urgent, that has gradually become a hot topic of materials informatics. Due to the lack of semantic description, it is difficult to integrate data deeply in semantic level when adopting the conventional heterogeneous database integration approaches such as federal database or data warehouse. In this paper, a semantic integration method is proposed to create the semantic ontology by extracting the database schema semi-automatically. Other heterogeneous databases are integrated to the ontology by means of relational algebra and the rooted graph. Based on integrated ontology, semantic query can be done using SPARQL. During the experiments, two world famous First Principle Computational databases, OQMD and Materials Project are used as the integration targets, which show the availability and effectiveness of our method.

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

Science.gov (United States)

Ježek, Petr; Mouček, Roman

2015-01-01

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

Methods and apparatus for multi-resolution replication of files in a parallel computing system using semantic information

Science.gov (United States)

Faibish, Sorin; Bent, John M.; Tzelnic, Percy; Grider, Gary; Torres, Aaron

2015-10-20

Techniques are provided for storing files in a parallel computing system using different resolutions. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a sub-file. The method comprises the steps of obtaining semantic information related to the file; generating a plurality of replicas of the file with different resolutions based on the semantic information; and storing the file and the plurality of replicas of the file in one or more storage nodes of the parallel computing system. The different resolutions comprise, for example, a variable number of bits and/or a different sub-set of data elements from the file. A plurality of the sub-files can be merged to reproduce the file.

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

Science.gov (United States)

Ikram, Najmul; Qadir, Muhammad Abdul; Afzal, Muhammad Tanvir

2018-01-01

Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic similarity methods, and in protein function prediction. In this research, we investigate the relationship between the two similarity methods. The results suggest absence of a strong correlation between sequence and semantic similarities. There is a large number of proteins with low sequence similarity and high semantic similarity. We observe that Pearson's correlation coefficient is not sufficient to explain the nature of this relationship. Interestingly, the term semantic similarity values above 0 and below 1 do not seem to play a role in improving the correlation. That is, the correlation coefficient depends only on the number of common GO terms in proteins under comparison, and the semantic similarity measurement method does not influence it. Semantic similarity and sequence similarity have a distinct behavior. These findings are of significant effect for future works on protein comparison, and will help understand the semantic similarity between proteins in a better way.

Programming the semantic web

CERN Document Server

Segaran, Toby; Taylor, Jamie

2009-01-01

With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing

A Similarity-Ranking Method on Semantic Computing for Providing Information-Services in Station-Concierge System

Directory of Open Access Journals (Sweden)

Motoki Yokoyama

2017-07-01

Full Text Available The prevalence of smartphones and wireless broadband networks have been progressing as a new Railway infomration environment.　According to the spread of such devices and information technology, various types of information can be obtained from databases connected to the Internet. One scenario of obtaining such a wide variety of information resources is in the phase of user’s transportation. This paper proposes an information provision system, named the Station Concierge System that matches the situation and intention of passengers. The purpose of this system is to estimate the needs of passengers like station staff or hotel concierge and to provide information resources that satisfy user’s expectations dynamically. The most important module of the system is constructed based on a new information ranking method for passenger intention prediction and service recommendation. This method has three main features, which are (1 projecting a user to semantic vector space by using her current context, (2 predicting the intention of a user based on selecting a semantic vector subspace, and (3 ranking the services by a descending order of relevant scores to the user’ intention. By comparing the predicted results of our method with those of two straightforward computation methods, the experimental studies show the effectiveness and efficiency of the proposed method. Using this system, users can obtain transit information and service map that dynamically matches their context.

GIF Video Sentiment Detection Using Semantic Sequence

Directory of Open Access Journals (Sweden)

Dazhen Lin

2017-01-01

Full Text Available With the development of social media, an increasing number of people use short videos in social media applications to express their opinions and sentiments. However, sentiment detection of short videos is a very challenging task because of the semantic gap problem and sequence based sentiment understanding problem. In this context, we propose a SentiPair Sequence based GIF video sentiment detection approach with two contributions. First, we propose a Synset Forest method to extract sentiment related semantic concepts from WordNet to build a robust SentiPair label set. This approach considers the semantic gap between label words and selects a robust label subset which is related to sentiment. Secondly, we propose a SentiPair Sequence based GIF video sentiment detection approach that learns the semantic sequence to understand the sentiment from GIF videos. Our experiment results on GSO-2016 (GIF Sentiment Ontology data show that our approach not only outperforms four state-of-the-art classification methods but also shows better performance than the state-of-the-art middle level sentiment ontology features, Adjective Noun Pairs (ANPs.

Semantic and episodic memory in children with temporal lobe epilepsy: do they relate to literacy skills?

Science.gov (United States)

Lah, Suncica; Smith, Mary Lou

2014-01-01

Children with temporal lobe epilepsy are at risk for deficits in new learning (episodic memory) and literacy skills. Semantic memory deficits and double dissociations between episodic and semantic memory have recently been found in this patient population. In the current study we investigate whether impairments of these 2 distinct memory systems relate to literacy skills. 57 children with unilateral temporal lobe epilepsy completed tests of verbal memory (episodic and semantic) and literacy skills (reading and spelling accuracy, and reading comprehension). For the entire group, semantic memory explained over 30% of variance in each of the literacy domains. Episodic memory explained a significant, but rather small proportion (memory impairments (intact semantic/impaired episodic, intact episodic/impaired semantic) were compared, significant reductions in literacy skills were evident only in children with semantic memory impairments, but not in children with episodic memory impairments relative to the norms and to children with temporal lobe epilepsy who had intact memory. Our study provides the first evidence for differential relations between episodic and semantic memory impairments and literacy skills in children with temporal lobe epilepsy. As such, it highlights the urgent need to consider semantic memory deficits in management of children with temporal lobe epilepsy and undertake further research into the nature of reading difficulties of children with semantic memory impairments.

Semantic metrics

OpenAIRE

Hu, Bo; Kalfoglou, Yannis; Dupplaw, David; Alani, Harith; Lewis, Paul; Shadbolt, Nigel

2006-01-01

In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and/or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a...

Semantic coherence in English accusative-with-bare-infinitive constructions

DEFF Research Database (Denmark)

Jensen, Kim Ebensgaard

2013-01-01

-with-bare-infinitive construction. The main methodological framework is that of covarying collexeme analysis, which, through statistical corpus analysis, allows for the analyst to address the semantics of a construction. Using this method on data from the BNC, the ultimate purpose of the paper is to address the underlying semantic...... relations of English accusatives-with-bare-infinitives through the relations of semantic coherence between the two VPs....

Inquisitive semantics and pragmatics

NARCIS (Netherlands)

Groenendijk, J.; Roelofsen, F.; Larrazabal, J.M.; Zubeldia, L.

2009-01-01

This paper starts with an informal introduction to inquisitive semantics. After that, we present a formal definition of the semantics, and introduce the basic semantic notions of inquisitiveness and informativeness, in terms of wich we define the semantic categories of questions, assertions, and

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

Science.gov (United States)

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. Copyright © 2012 Elsevier Ltd. All rights reserved.

Perbandingan Hasil Deteksi Plagiarisme Dokumen dengan Metode Jaro-Winkler Distance dan Metode Latent Semantic Analysis

Directory of Open Access Journals (Sweden)

Tinaliah Tinaliah

2018-01-01

Full Text Available Various methods are applied in the application of plagiarism detection to help check the similarity of a document. Jaro-Winkler Distance can measure the distance between two strings. However, this method basically depends on the position of the word. Latent Semantic Analysis emphasizes the words contained in the document regardless of its linguistic character. This study compares the results of plagiarism detection using the Jaro-Winkler Distance and the Latent Semantic Analysis method. From comparing results of  Jaro-Winkler Distance method and Latent Semantic Analysis method, Jaro-Winkler Distance method is better than Latent Semantic Analysis method if using the same test data. Jaro-Winkler Distance method will give plagiarism result 100% and Latent Semantic Analysis method will give plagiarism result 97,14%. Beragam metode diterapkan dalam aplikasi deteksi plagiarisme untuk membantu mengecek tingkat kesamaan sebuah dokumen. Metode Jaro-Winkler Distance dapat mengukur kesamaan antara dua buah string dan sangat bergantung pada urutan atau posisi kata. Latent Semantic Analysis mementingkan kata-kata yang terkandung di dalam dokumen tanpa memperhatikan karakter linguistiknya. Penelitian ini melakukan perbandingan hasil deteksi plagiarisme dengan menggunakan metode Jaro-Winkler Distance dan metode Latent Semantic Analysis. Hasil pendeteksian plagiarisme dokumen menggunakan metode Jaro-Winkler Distance memberikan hasil yang lebih baik daripada metode Latent Semantic Analysis, yaitu jika data yang dibandingkan sama persis maka akan menghasilkan nilai plagiat sebesar 100%, sedangkan metode Latent Semantic Analysis menghasilkan nilai plagiat sebesar 97,14%.

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

Science.gov (United States)

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

2009-09-23

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

Iterative Splitting Methods for Differential Equations

CERN Document Server

Geiser, Juergen

2011-01-01

Iterative Splitting Methods for Differential Equations explains how to solve evolution equations via novel iterative-based splitting methods that efficiently use computational and memory resources. It focuses on systems of parabolic and hyperbolic equations, including convection-diffusion-reaction equations, heat equations, and wave equations. In the theoretical part of the book, the author discusses the main theorems and results of the stability and consistency analysis for ordinary differential equations. He then presents extensions of the iterative splitting methods to partial differential

Determining the semantic similarities among Gene Ontology terms.

Science.gov (United States)

Taha, Kamal

2013-05-01

We present in this paper novel techniques that determine the semantic relationships among GeneOntology (GO) terms. We implemented these techniques in a prototype system called GoSE, which resides between user application and GO database. Given a set S of GO terms, GoSE would return another set S' of GO terms, where each term in S' is semantically related to each term in S. Most current research is focused on determining the semantic similarities among GO ontology terms based solely on their IDs and proximity to one another in the GO graph structure, while overlooking the contexts of the terms, which may lead to erroneous results. The context of a GO term T is the set of other terms, whose existence in the GO graph structure is dependent on T. We propose novel techniques that determine the contexts of terms based on the concept of existence dependency. We present a stack-based sort-merge algorithm employing these techniques for determining the semantic similarities among GO terms.We evaluated GoSE experimentally and compared it with three existing methods. The results of measuring the semantic similarities among genes in KEGG and Pfam pathways retrieved from the DBGET and Sanger Pfam databases, respectively, have shown that our method outperforms the other three methods in recall and precision.

A semantic data dictionary method for database schema integration in CIESIN

Science.gov (United States)

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

1993-08-01

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

Measurement of semantic similarity for land use and land cover classification systems

Science.gov (United States)

Deng, Dongpo

2008-12-01

Land use and land cover (LULC) data is essential to environmental and ecological research. However, semantic heterogeneous of land use and land cover classification are often resulted from different data resources, different cultural contexts, and different utilities. Therefore, there is need to develop a method to measure, compare and integrate between land cover categories. To understand the meaning and the use of terminology from different domains, the common ontology approach is used to acquire information regarding the meaning of terms, and to compare two terms to determine how they might be related. Ontology is a formal specification of a shared conceptualization of a domain of interest. LULC classification system is a ontology. The semantic similarity method is used to compare to entities of three LULC classification systems: CORINE (European Environmental Agency), Oregon State, USA), and Taiwan. The semantic properties and relations firstly have been extracted from their definitions of LULC classification systems. Then semantic properties and relations of categories in three LULC classification systems are mutually compared. The visualization of semantic proximity is finally presented to explore the similarity or dissimilarity of data. This study shows the semantic similarity method efficiently detect semantic distance in three LULC classification systems and find out the semantic similar objects.

Dementias show differential physiological responses to salient sounds.

Science.gov (United States)

Fletcher, Phillip D; Nicholas, Jennifer M; Shakespeare, Timothy J; Downey, Laura E; Golden, Hannah L; Agustus, Jennifer L; Clark, Camilla N; Mummery, Catherine J; Schott, Jonathan M; Crutch, Sebastian J; Warren, Jason D

2015-01-01

Abnormal responsiveness to salient sensory signals is often a prominent feature of dementia diseases, particularly the frontotemporal lobar degenerations, but has been little studied. Here we assessed processing of one important class of salient signals, looming sounds, in canonical dementia syndromes. We manipulated tones using intensity cues to create percepts of salient approaching ("looming") or less salient withdrawing sounds. Pupil dilatation responses and behavioral rating responses to these stimuli were compared in patients fulfilling consensus criteria for dementia syndromes (semantic dementia, n = 10; behavioral variant frontotemporal dementia, n = 16, progressive nonfluent aphasia, n = 12; amnestic Alzheimer's disease, n = 10) and a cohort of 26 healthy age-matched individuals. Approaching sounds were rated as more salient than withdrawing sounds by healthy older individuals but this behavioral response to salience did not differentiate healthy individuals from patients with dementia syndromes. Pupil responses to approaching sounds were greater than responses to withdrawing sounds in healthy older individuals and in patients with semantic dementia: this differential pupil response was reduced in patients with progressive nonfluent aphasia and Alzheimer's disease relative both to the healthy control and semantic dementia groups, and did not correlate with nonverbal auditory semantic function. Autonomic responses to auditory salience are differentially affected by dementias and may constitute a novel biomarker of these diseases.

SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

Science.gov (United States)

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.

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

Science.gov (United States)

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

2011-06-01

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

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

Science.gov (United States)

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 �

Semantics of the VDM Real-Time Dialect

DEFF Research Database (Denmark)

Lausdahl, Kenneth; Coleman, Joey; Larsen, Peter Gorm

All formally defined languages need to be given an unambiguous semantics such that the meaning of all models expressed using the language is clear. In this technical report a semantic model is provided for the Real-Time dialect of the Vienna Development Method (VDM). This builds upon both...... the formal semantics provided for the ISO standard VDM Specification Language, and on other work on the core of the VDM-RT notation. Although none of the VDM dialects are executable in general, the primary focus of the work presented here is on the executable subset. This focus is result of parallel work...

Semantic graphs and associative memories

Science.gov (United States)

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.

Domain XML semantic integration based on extraction rules and ontology mapping

Directory of Open Access Journals (Sweden)

Huayu LI

2016-08-01

Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

Learning Semantic Segmentation with Diverse Supervision

OpenAIRE

Ye, Linwei; Liu, Zhi; Wang, Yang

2018-01-01

Models based on deep convolutional neural networks (CNN) have significantly improved the performance of semantic segmentation. However, learning these models requires a large amount of training images with pixel-level labels, which are very costly and time-consuming to collect. In this paper, we propose a method for learning CNN-based semantic segmentation models from images with several types of annotations that are available for various computer vision tasks, including image-level labels fo...

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

Science.gov (United States)

Wiese, Holger; Schweinberger, Stefan R

2015-01-01

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

Semantically Interoperable XML Data.

Science.gov (United States)

Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

2013-09-01

XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups.

Semantically Interoperable XML Data

Science.gov (United States)

Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

2013-01-01

XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

Semantics of Kinship Terms in Tamil from the Semantic Typology Point of View

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Анна Александровна Смирнитская

2016-12-01

Full Text Available In this article the author examines the lexical-semantic group “kinship terms” in Tamil, applying the attainments of modern semantic typology and the theory of semantic derivation. The kinship terms describing nuclear and extended family are explored. The “semantic shift” relation between two different meanings is established if such relation is realized by synchronous polysemy in one lexeme, semantic derivation, diachronic semantic change, cognates or some other means. The starting point of the study is the typological data from the DatSemShift catalogue of semantic shifts in languages of the world developed by a group of researchers under the guidance of Anna A. Zalizniak in the Institute of Linguistics, RAS. We verify the presence of semantic shifts described in the Database in Tamil. Also, we propose new semantic shifts specific only for this language. We confirm the presence of semantic relation of the studied type among the meanings with English “labels”: father - parents, girl - daughter, to deliver (a child - parents, - child, old woman - wife, owner - wife and others. The data also allows the assumption that the same relation exists between the meanings: old - grandfather, earth - mother, son - courage, unripe - son and others. The meanings of this field are the sources of semantic movements to abstract notions, lexicon of posession, forms of address and others; in addition many inner semantic relations inside this field are revealed. The meanings covering the nuclear part of the kinship system participate in universal semantic shifts described in the DatSemShift catalogue, while the meanings from collateral branches of this bifurcative kinship system (uncle, aunt turn out to be incomparable with kinship terms from indo-european lineal systems. Their meanings can be included in the DatSemShift catalogue only with an indication of system specifics. The information about semantic shifts can be useful for

Semantic Role Labeling

CERN Document Server

Palmer, Martha; Xue, Nianwen

2011-01-01

This book is aimed at providing an overview of several aspects of semantic role labeling. Chapter 1 begins with linguistic background on the definition of semantic roles and the controversies surrounding them. Chapter 2 describes how the theories have led to structured lexicons such as FrameNet, VerbNet and the PropBank Frame Files that in turn provide the basis for large scale semantic annotation of corpora. This data has facilitated the development of automatic semantic role labeling systems based on supervised machine learning techniques. Chapter 3 presents the general principles of applyin

The Use of Semantic Differential in Function of Measuring Image of the Company

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Ines Đokić

2017-06-01

Full Text Available In order to influence consumers to buy products, company has to figure out how and where to present them, i.e., it is necessary to make decisions about which marketing communication instruments to use to refer them. What is needed is to provide consumers sufficient information to identify the brand in a given product category at the moment of purchase decision, because consumers, before opting for a particular product, go through various stages. Company can apply different marketing communication instruments, but needs to co-ordinate them to send consumers a clear and consistent promotional message. Whether company has implemented marketing communications successfully can be seen from different indicators, from economic to communication, that is, from increasing sales to a positive image. It is very important for a company to measure the effects of implemented marketing communication, because it helps in making the right decisions in the future and obtaining as many regular customers. One of the main goals of the company is positive and clear image that can be achieved through the instruments of marketing communication. Company can measure its image by applying semantic differential, which can help in obtaining a picture that consumers have about the company and its products. Its usage can be of the great importance for entrepreneurs, as well.

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

Science.gov (United States)

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…

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

DEFF Research Database (Denmark)

Petersen, Michael Kai

2015-01-01

already in toddlers, this study explores whether articulatory and acoustic parameters may likewise differentiate the latent semantics of action verbs. Selecting 3 X 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...

UML 2 Semantics and Applications

CERN Document Server

Lano, Kevin

2009-01-01

A coherent and integrated account of the leading UML 2 semantics work and the practical applications of UML semantics development With contributions from leading experts in the field, the book begins with an introduction to UML and goes on to offer in-depth and up-to-date coverage of: The role of semantics Considerations and rationale for a UML system model Definition of the UML system model UML descriptive semantics Axiomatic semantics of UML class diagrams The object constraint language Axiomatic semantics of state machines A coalgebraic semantic framework for reasoning about interaction des

Semi-Supervised Learning to Identify UMLS Semantic Relations.

Science.gov (United States)

Luo, Yuan; Uzuner, Ozlem

2014-01-01

The UMLS Semantic Network is constructed by experts and requires periodic expert review to update. We propose and implement a semi-supervised approach for automatically identifying UMLS semantic relations from narrative text in PubMed. Our method analyzes biomedical narrative text to collect semantic entity pairs, and extracts multiple semantic, syntactic and orthographic features for the collected pairs. We experiment with seeded k-means clustering with various distance metrics. We create and annotate a ground truth corpus according to the top two levels of the UMLS semantic relation hierarchy. We evaluate our system on this corpus and characterize the learning curves of different clustering configuration. Using KL divergence consistently performs the best on the held-out test data. With full seeding, we obtain macro-averaged F-measures above 70% for clustering the top level UMLS relations (2-way), and above 50% for clustering the second level relations (7-way).

Semantic search during divergent thinking.

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Hass, Richard W

2017-09-01

Divergent thinking, as a method of examining creative cognition, has not been adequately analyzed in the context of modern cognitive theories. This article casts divergent thinking responding in the context of theories of memory search. First, it was argued that divergent thinking tasks are similar to semantic fluency tasks, but are more constrained, and less well structured. Next, response time distributions from 54 participants were analyzed for temporal and semantic clustering. Participants responded to two prompts from the alternative uses test: uses for a brick and uses for a bottle, for two minutes each. Participants' cumulative response curves were negatively accelerating, in line with theories of search of associative memory. However, results of analyses of semantic and temporal clustering suggested that clustering is less evident in alternative uses responding compared to semantic fluency tasks. This suggests either that divergent thinking responding does not involve an exhaustive search through a clustered memory trace, but rather that the process is more exploratory, yielding fewer overall responses that tend to drift away from close associates of the divergent thinking prompt. Copyright © 2017 Elsevier B.V. All rights reserved.

Semantic memory in object use.

Science.gov (United States)

Silveri, Maria Caterina; Ciccarelli, Nicoletta

2009-10-01

We studied five patients with semantic memory disorders, four with semantic dementia and one with herpes simplex virus encephalitis, to investigate the involvement of semantic conceptual knowledge in object use. Comparisons between patients who had semantic deficits of different severity, as well as the follow-up, showed that the ability to use objects was largely preserved when the deficit was mild but progressively decayed as the deficit became more severe. Naming was generally more impaired than object use. Production tasks (pantomime execution and actual object use) and comprehension tasks (pantomime recognition and action recognition) as well as functional knowledge about objects were impaired when the semantic deficit was severe. Semantic and unrelated errors were produced during object use, but actions were always fluent and patients performed normally on a novel tools task in which the semantic demand was minimal. Patients with severe semantic deficits scored borderline on ideational apraxia tasks. Our data indicate that functional semantic knowledge is crucial for using objects in a conventional way and suggest that non-semantic factors, mainly non-declarative components of memory, might compensate to some extent for semantic disorders and guarantee some residual ability to use very common objects independently of semantic knowledge.

Lexical and semantic representations in the acquisition of L2 cognate and non-cognate words: evidence from two learning methods in children.

Science.gov (United States)

Comesaña, Montserrat; Soares, Ana Paula; Sánchez-Casas, Rosa; Lima, Cátia

2012-08-01

How bilinguals represent words in two languages and which mechanisms are responsible for second language acquisition are important questions in the bilingual and vocabulary acquisition literature. This study aims to analyse the effect of two learning methods (picture- vs. word-based method) and two types of words (cognates and non-cognates) in early stages of children's L2 acquisition. Forty-eight native speakers of European Portuguese, all sixth graders (mean age = 10.87 years; SD= 0.85), participated in the study. None of them had prior knowledge of Basque (the L2 in this study). After a learning phase in which L2 words were learned either by a picture- or a word-based method, children were tested in a backward-word translation recognition task at two times (immediately vs. one week later). Results showed that the participants made more errors when rejecting semantically related than semantically unrelated words as correct translations (semantic interference effect). The magnitude of this effect was higher in the delayed test condition regardless of the learning method. Moreover, the overall performance of participants from the word-based method was better than the performance of participants from the picture-word method. Results were discussed concerning the most significant bilingual lexical processing models. ©2011 The British Psychological Society.

Enabling Semantic Queries Against the Spatial Database

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PENG, X.

2012-02-01

Full Text Available The spatial database based upon the object-relational database management system (ORDBMS has the merits of a clear data model, good operability and high query efficiency. That is why it has been widely used in spatial data organization and management. However, it cannot express the semantic relationships among geospatial objects, making the query results difficult to meet the user's requirement well. Therefore, this paper represents an attempt to combine the Semantic Web technology with the spatial database so as to make up for the traditional database's disadvantages. In this way, on the one hand, users can take advantages of ORDBMS to store and manage spatial data; on the other hand, if the spatial database is released in the form of Semantic Web, the users could describe a query more concisely with the cognitive pattern which is similar to that of daily life. As a consequence, this methodology enables the benefits of both Semantic Web and the object-relational database (ORDB available. The paper discusses systematically the semantic enriched spatial database's architecture, key technologies and implementation. Subsequently, we demonstrate the function of spatial semantic queries via a practical prototype system. The query results indicate that the method used in this study is feasible.

Semantics by analogy for illustrative volume visualization☆

Science.gov (United States)

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

2012-01-01

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

The structure of semantic person memory: evidence from semantic priming in person recognition.

Science.gov (United States)

Wiese, Holger

2011-11-01

This paper reviews research on the structure of semantic person memory as examined with semantic priming. In this experimental paradigm, a familiarity decision on a target face or written name is usually faster when it is preceded by a related as compared to an unrelated prime. This effect has been shown to be relatively short lived and susceptible to interfering items. Moreover, semantic priming can cross stimulus domains, such that a written name can prime a target face and vice versa. However, it remains controversial whether representations of people are stored in associative networks based on co-occurrence, or in more abstract semantic categories. In line with prominent cognitive models of face recognition, which explain semantic priming by shared semantic information between prime and target, recent research demonstrated that priming could be obtained from purely categorically related, non-associated prime/target pairs. Although strategic processes, such as expectancy and retrospective matching likely contribute, there is also evidence for a non-strategic contribution to priming, presumably related to spreading activation. Finally, a semantic priming effect has been demonstrated in the N400 event-related potential (ERP) component, which may reflect facilitated access to semantic information. It is concluded that categorical relatedness is one organizing principle of semantic person memory. ©2011 The British Psychological Society.

A biopsychosocial investigation of changes in self-concept on the Head Injury Semantic Differential Scale.

Science.gov (United States)

Reddy, Avneel; Ownsworth, Tamara; King, Joshua; Shields, Cassandra

2017-12-01

This study aimed to investigate the influence of the "good-old-days" bias, neuropsychological functioning and cued recall of life events on self-concept change. Forty seven adults with TBI (70% male, 1-5 years post-injury) and 47 matched controls rated their past and present self-concept on the Head Injury Semantic Differential Scale (HISD) III. TBI participants also completed a battery of neuropsychological tests. The matched control group of 47 were from a sample of 78 uninjured participants who were randomised to complete either the Social Readjustment Rating Scale-Revised (cued recall) or HISD (non-cued recall) first. Consistent with the good-old-days bias, participants with TBI rated their pre-injury self-concept as more positive than their present self-concept and the present self-concept of controls (p concept ratings were related to lower estimated premorbid IQ and poorer verbal fluency and delayed memory (p concept change (p concept as significantly more negative than the non-cued group (p concept change by affecting retrospective ratings of past self-concept. Further research is needed to investigate the impact of contextual cues on self-concept change after TBI.

Meinongian Semantics and Artificial Intelligence

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William J. Rapaport

2013-12-01

Full Text Available This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks (exemplified by SNePS are discussed; it is argued that only a fully intensional, Meinongian semantics is appropriate for them; and several Meinongian systems are presented.

Geospatial Semantics and the Semantic Web

CERN Document Server

Ashish, Naveen

2011-01-01

The availability of geographic and geospatial information and services, especially on the open Web has become abundant in the last several years with the proliferation of online maps, geo-coding services, geospatial Web services and geospatially enabled applications. The need for geospatial reasoning has significantly increased in many everyday applications including personal digital assistants, Web search applications, local aware mobile services, specialized systems for emergency response, medical triaging, intelligence analysis and more. Geospatial Semantics and the Semantic Web: Foundation

Discovering EEG resting state alterations of semantic dementia.

Science.gov (United States)

Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars-Olof; Dierks, Thomas; Nishida, Keiichiro

2016-05-01

Diagnosis of semantic dementia relies on cost-intensive MRI or PET, although resting EEG markers of other dementias have been reported. Yet the view still holds that resting EEG in patients with semantic dementia is normal. However, studies using increasingly sophisticated EEG analysis methods have demonstrated that slightest alterations of functional brain states can be detected. We analyzed the common four resting EEG microstates (A, B, C, and D) of 8 patients with semantic dementia in comparison with 8 healthy controls and 8 patients with Alzheimer's disease. Topographical differences between the groups were found in microstate classes B and C, while microstate classes A and D were comparable. The data showed that the semantic dementia group had a peculiar microstate E, but the commonly found microstate C was lacking. Furthermore, the presence of microstate E was significantly correlated with lower MMSE and language scores. Alterations in resting EEG can be found in semantic dementia. Topographical shifts in microstate C might be related to semantic memory deficits. This is the first study that discovered resting state EEG abnormality in semantic dementia. The notion that resting EEG in this dementia subtype is normal has to be revised. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Episodic, but not semantic, autobiographical memory is reduced in amnestic mild cognitive impairment.

Science.gov (United States)

Murphy, Kelly J; Troyer, Angela K; Levine, Brian; Moscovitch, Morris

2008-11-01

Amnestic mild cognitive impairment (aMCI) is characterized by decline in anterograde memory as measured by the ability to learn and remember new information. We investigated whether retrograde memory for autobiographical information was affected by aMCI. Eighteen control (age 66-84 years) and 17 aMCI (age 66-84 years) participants described a personal event from each of the five periods across the lifespan. These events were transcribed and scored according to procedures that separate episodic (specific happenings) from semantic (general knowledge) elements of autobiographical memory. Although both groups generated protocols of similar length, the composition of autobiographical recall differentiated the groups. The aMCI group protocols were characterized by reduced episodic and increased semantic information relative to the control group. Both groups showed a similar pattern of recall across time periods, with no evidence that the aMCI group had more difficulty recalling recent, rather than remote, life events. These results indicate that episodic and semantic autobiographical memories are differentially affected by the early brain changes associated with aMCI. Reduced autobiographical episodic memories in aMCI may be the result of medial temporal lobe dysfunction, consistent with multiple trace theory, or alternatively, could be related to dysfunction of a wider related network of neocortical structures. In contrast, the preservation of autobiographical semantic memories in aMCI suggests neural systems, such as lateral temporal cortex, that support these memories, may remain relatively intact.

Annotation and retrieval system of CAD models based on functional semantics

Science.gov (United States)

Wang, Zhansong; Tian, Ling; Duan, Wenrui

2014-11-01

CAD model retrieval based on functional semantics is more significant than content-based 3D model retrieval during the mechanical conceptual design phase. However, relevant research is still not fully discussed. Therefore, a functional semantic-based CAD model annotation and retrieval method is proposed to support mechanical conceptual design and design reuse, inspire designer creativity through existing CAD models, shorten design cycle, and reduce costs. Firstly, the CAD model functional semantic ontology is constructed to formally represent the functional semantics of CAD models and describe the mechanical conceptual design space comprehensively and consistently. Secondly, an approach to represent CAD models as attributed adjacency graphs(AAG) is proposed. In this method, the geometry and topology data are extracted from STEP models. On the basis of AAG, the functional semantics of CAD models are annotated semi-automatically by matching CAD models that contain the partial features of which functional semantics have been annotated manually, thereby constructing CAD Model Repository that supports model retrieval based on functional semantics. Thirdly, a CAD model retrieval algorithm that supports multi-function extended retrieval is proposed to explore more potential creative design knowledge in the semantic level. Finally, a prototype system, called Functional Semantic-based CAD Model Annotation and Retrieval System(FSMARS), is implemented. A case demonstrates that FSMARS can successfully botain multiple potential CAD models that conform to the desired function. The proposed research addresses actual needs and presents a new way to acquire CAD models in the mechanical conceptual design phase.

Problem Solving with General Semantics.

Science.gov (United States)

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)

Dementias show differential physiological responses to salient sounds

Directory of Open Access Journals (Sweden)

Phillip David Fletcher

2015-03-01

Full Text Available Abnormal responsiveness to salient sensory signals is often a prominent feature of dementia diseases, particularly the frontotemporal lobar degenerations, but has been little studied. Here we assessed processing of one important class of salient signals, looming sounds, in canonical dementia syndromes. We manipulated tones using intensity cues to create percepts of salient approaching (‘looming’ or less salient withdrawing sounds. Pupil dilatation responses and behavioural rating responses to these stimuli were compared in patients fulfilling consensus criteria for dementia syndromes (semantic dementia, n=10; behavioural variant frontotemporal dementia, n=16, progressive non-fluent aphasia, n=12; amnestic Alzheimer’s disease, n=10 and a cohort of 26 healthy age-matched individuals. Approaching sounds were rated as more salient than withdrawing sounds by healthy older individuals but this behavioural response to salience did not differentiate healthy individuals from patients with dementia syndromes. Pupil responses to approaching sounds were greater than responses to withdrawing sounds in healthy older individuals and in patients with semantic dementia: this differential pupil response was reduced in patients with progressive nonfluent aphasia and Alzheimer’s disease relative both to the healthy control and semantic dementia groups, and did not correlate with nonverbal auditory semantic function. Autonomic responses to auditory salience are differentially affected by dementias and may constitute a novel biomarker of these diseases.

Dementias show differential physiological responses to salient sounds

Science.gov (United States)

Fletcher, Phillip D.; Nicholas, Jennifer M.; Shakespeare, Timothy J.; Downey, Laura E.; Golden, Hannah L.; Agustus, Jennifer L.; Clark, Camilla N.; Mummery, Catherine J.; Schott, Jonathan M.; Crutch, Sebastian J.; Warren, Jason D.

2015-01-01

Abnormal responsiveness to salient sensory signals is often a prominent feature of dementia diseases, particularly the frontotemporal lobar degenerations, but has been little studied. Here we assessed processing of one important class of salient signals, looming sounds, in canonical dementia syndromes. We manipulated tones using intensity cues to create percepts of salient approaching (“looming”) or less salient withdrawing sounds. Pupil dilatation responses and behavioral rating responses to these stimuli were compared in patients fulfilling consensus criteria for dementia syndromes (semantic dementia, n = 10; behavioral variant frontotemporal dementia, n = 16, progressive nonfluent aphasia, n = 12; amnestic Alzheimer's disease, n = 10) and a cohort of 26 healthy age-matched individuals. Approaching sounds were rated as more salient than withdrawing sounds by healthy older individuals but this behavioral response to salience did not differentiate healthy individuals from patients with dementia syndromes. Pupil responses to approaching sounds were greater than responses to withdrawing sounds in healthy older individuals and in patients with semantic dementia: this differential pupil response was reduced in patients with progressive nonfluent aphasia and Alzheimer's disease relative both to the healthy control and semantic dementia groups, and did not correlate with nonverbal auditory semantic function. Autonomic responses to auditory salience are differentially affected by dementias and may constitute a novel biomarker of these diseases. PMID:25859194

Effects of semantic neighborhood density in abstract and concrete words.

Science.gov (United States)

Reilly, Megan; Desai, Rutvik H

2017-12-01

Concrete and abstract words are thought to differ along several psycholinguistic variables, such as frequency and emotional content. Here, we consider another variable, semantic neighborhood density, which has received much less attention, likely because semantic neighborhoods of abstract words are difficult to measure. Using a corpus-based method that creates representations of words that emphasize featural information, the current investigation explores the relationship between neighborhood density and concreteness in a large set of English nouns. Two important observations emerge. First, semantic neighborhood density is higher for concrete than for abstract words, even when other variables are accounted for, especially for smaller neighborhood sizes. Second, the effects of semantic neighborhood density on behavior are different for concrete and abstract words. Lexical decision reaction times are fastest for words with sparse neighborhoods; however, this effect is stronger for concrete words than for abstract words. These results suggest that semantic neighborhood density plays a role in the cognitive and psycholinguistic differences between concrete and abstract words, and should be taken into account in studies involving lexical semantics. Furthermore, the pattern of results with the current feature-based neighborhood measure is very different from that with associatively defined neighborhoods, suggesting that these two methods should be treated as separate measures rather than two interchangeable measures of semantic neighborhoods. Copyright © 2017 Elsevier B.V. All rights reserved.

Overlap in the functional neural systems involved in semantic and episodic memory retrieval.

Science.gov (United States)

Rajah, M N; McIntosh, A R

2005-03-01

Neuroimaging and neuropsychological data suggest that episodic and semantic memory may be mediated by distinct neural systems. However, an alternative perspective is that episodic and semantic memory represent different modes of processing within a single declarative memory system. To examine whether the multiple or the unitary system view better represents the data we conducted a network analysis using multivariate partial least squares (PLS ) activation analysis followed by covariance structural equation modeling (SEM) of positron emission tomography data obtained while healthy adults performed episodic and semantic verbal retrieval tasks. It is argued that if performance of episodic and semantic retrieval tasks are mediated by different memory systems, then there should differences in both regional activations and interregional correlations related to each type of retrieval task, respectively. The PLS results identified brain regions that were differentially active during episodic retrieval versus semantic retrieval. Regions that showed maximal differences in regional activity between episodic retrieval tasks were used to construct separate functional models for episodic and semantic retrieval. Omnibus tests of these functional models failed to find a significant difference across tasks for both functional models. The pattern of path coefficients for the episodic retrieval model were not different across tasks, nor were the path coefficients for the semantic retrieval model. The SEM results suggest that the same memory network/system was engaged across tasks, given the similarities in path coefficients. Therefore, activation differences between episodic and semantic retrieval may ref lect variation along a continuum of processing during task performance within the context of a single memory system.

Potential role of monkey inferior parietal neurons coding action semantic equivalences as precursors of parts of speech.

Science.gov (United States)

Yamazaki, Yumiko; Yokochi, Hiroko; Tanaka, Michio; Okanoya, Kazuo; Iriki, Atsushi

2010-01-01

The anterior portion of the inferior parietal cortex possesses comprehensive representations of actions embedded in behavioural contexts. Mirror neurons, which respond to both self-executed and observed actions, exist in this brain region in addition to those originally found in the premotor cortex. We found that parietal mirror neurons responded differentially to identical actions embedded in different contexts. Another type of parietal mirror neuron represents an inverse and complementary property of responding equally to dissimilar actions made by itself and others for an identical purpose. Here, we propose a hypothesis that these sets of inferior parietal neurons constitute a neural basis for encoding the semantic equivalence of various actions across different agents and contexts. The neurons have mirror neuron properties, and they encoded generalization of agents, differentiation of outcomes, and categorization of actions that led to common functions. By integrating the activities of these mirror neurons with various codings, we further suggest that in the ancestral primates' brains, these various representations of meaningful action led to the gradual establishment of equivalence relations among the different types of actions, by sharing common action semantics. Such differential codings of the components of actions might represent precursors to the parts of protolanguage, such as gestural communication, which are shared among various members of a society. Finally, we suggest that the inferior parietal cortex serves as an interface between this action semantics system and other higher semantic systems, through common structures of action representation that mimic language syntax.

Montague semantics

NARCIS (Netherlands)

Janssen, T.M.V.

2012-01-01

Montague semantics is a theory of natural language semantics and of its relation with syntax. It was originally developed by the logician Richard Montague (1930-1971) and subsequently modified and extended by linguists, philosophers, and logicians. The most important features of the theory are its

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System

OpenAIRE

Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

2017-01-01

Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships betwe...

From Data to Semantic Information

Directory of Open Access Journals (Sweden)

Luciano Floridi

2003-06-01

Full Text Available Abstract: There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates the important implications of the revised definition for the analysis of the deflationary theories of truth, the standard definition of knowledge and the classic, quantitative theory of semantic information.

Dissociating the effects of semantic grouping and rehearsal strategies on event-related brain potentials.

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Schleepen, T M J; Markus, C R; Jonkman, L M

2014-12-01

The application of elaborative encoding strategies during learning, such as grouping items on similar semantic categories, increases the likelihood of later recall. Previous studies have suggested that stimuli that encourage semantic grouping strategies had modulating effects on specific ERP components. However, these studies did not differentiate between ERP activation patterns evoked by elaborative working memory strategies like semantic grouping and more simple strategies like rote rehearsal. Identification of neurocognitive correlates underlying successful use of elaborative strategies is important to understand better why certain populations, like children or elderly people, have problems applying such strategies. To compare ERP activation during the application of elaborative versus more simple strategies subjects had to encode either four semantically related or unrelated pictures by respectively applying a semantic category grouping or a simple rehearsal strategy. Another goal was to investigate if maintenance of semantically grouped vs. ungrouped pictures modulated ERP-slow waves differently. At the behavioral level there was only a semantic grouping benefit in terms of faster responding on correct rejections (i.e. when the memory probe stimulus was not part of the memory set). At the neural level, during encoding semantic grouping only had a modest specific modulatory effect on a fronto-central Late Positive Component (LPC), emerging around 650 ms. Other ERP components (i.e. P200, N400 and a second Late Positive Component) that had been earlier related to semantic grouping encoding processes now showed stronger modulation by rehearsal than by semantic grouping. During maintenance semantic grouping had specific modulatory effects on left and right frontal slow wave activity. These results stress the importance of careful control of strategy use when investigating the neural correlates of elaborative encoding. Copyright © 2014 Elsevier B.V. All rights

The word processing deficit in semantic dementia: all categories are equal, but some categories are more equal than others.

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Pulvermüller, Friedemann; Cooper-Pye, Elisa; Dine, Clare; Hauk, Olaf; Nestor, Peter J; Patterson, Karalyn

2010-09-01

It has been claimed that semantic dementia (SD), the temporal variant of fronto-temporal dementia, is characterized by an across-the-board deficit affecting all types of conceptual knowledge. We here confirm this generalized deficit but also report differential degrees of impairment in processing specific semantic word categories in a case series of SD patients (N = 11). Within the domain of words with strong visually grounded meaning, the patients' lexical decision accuracy was more impaired for color-related than for form-related words. Likewise, within the domain of action verbs, the patients' performance was worse for words referring to face movements and speech acts than for words semantically linked to actions performed with the hand and arm. Psycholinguistic properties were matched between the stimulus groups entering these contrasts; an explanation for the differential degrees of impairment must therefore involve semantic features of the words in the different conditions. Furthermore, this specific pattern of deficits cannot be captured by classic category distinctions such as nouns versus verbs or living versus nonliving things. Evidence from previous neuroimaging research indicates that color- and face/speech-related words, respectively, draw most heavily on anterior-temporal and inferior-frontal areas, the structures most affected in SD. Our account combines (a) the notion of an anterior-temporal amodal semantic "hub" to explain the profound across-the-board deficit in SD word processing, with (b) a semantic topography model of category-specific circuits whose cortical distributions reflect semantic features of the words and concepts represented.

SEMANTIC SEGMENTATION OF BUILDING ELEMENTS USING POINT CLOUD HASHING

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M. Chizhova

2018-05-01

Full Text Available For the interpretation of point clouds, the semantic definition of extracted segments from point clouds or images is a common problem. Usually, the semantic of geometrical pre-segmented point cloud elements are determined using probabilistic networks and scene databases. The proposed semantic segmentation method is based on the psychological human interpretation of geometric objects, especially on fundamental rules of primary comprehension. Starting from these rules the buildings could be quite well and simply classified by a human operator (e.g. architect into different building types and structural elements (dome, nave, transept etc., including particular building parts which are visually detected. The key part of the procedure is a novel method based on hashing where point cloud projections are transformed into binary pixel representations. A segmentation approach released on the example of classical Orthodox churches is suitable for other buildings and objects characterized through a particular typology in its construction (e.g. industrial objects in standardized enviroments with strict component design allowing clear semantic modelling.

Foundations of semantic web technologies

CERN Document Server

Hitzler, Pascal; Rudolph, Sebastian

2009-01-01

The Quest for Semantics Building Models Calculating with Knowledge Exchanging Information Semanic Web Technologies RESOURCE DESCRIPTION LANGUAGE (RDF)Simple Ontologies in RDF and RDF SchemaIntroduction to RDF Syntax for RDF Advanced Features Simple Ontologies in RDF Schema Encoding of Special Data Structures An ExampleRDF Formal Semantics Why Semantics? Model-Theoretic Semantics for RDF(S) Syntactic Reasoning with Deduction Rules The Semantic Limits of RDF(S)WEB ONTOLOGY LANGUAGE (OWL) Ontologies in OWL OWL Syntax and Intuitive Semantics OWL Species The Forthcoming OWL 2 StandardOWL Formal Sem

Statistical Methods for Stochastic Differential Equations

CERN Document Server

Kessler, Mathieu; Sorensen, Michael

2012-01-01

The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a sp

Categorical model of structural operational semantics for imperative language

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William Steingartner

2016-12-01

Full Text Available Definition of programming languages consists of the formal definition of syntax and semantics. One of the most popular semantic methods used in various stages of software engineering is structural operational semantics. It describes program behavior in the form of state changes after execution of elementary steps of program. This feature makes structural operational semantics useful for implementation of programming languages and also for verification purposes. In our paper we present a new approach to structural operational semantics. We model behavior of programs in category of states, where objects are states, an abstraction of computer memory and morphisms model state changes, execution of a program in elementary steps. The advantage of using categorical model is its exact mathematical structure with many useful proved properties and its graphical illustration of program behavior as a path, i.e. a composition of morphisms. Our approach is able to accentuate dynamics of structural operational semantics. For simplicity, we assume that data are intuitively typed. Visualization and facility of our model is  not only  a  new model of structural operational semantics of imperative programming languages but it can also serve for education purposes.

Towards an Approach of Semantic Access Control for Cloud Computing

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Hu, Luokai; Ying, Shi; Jia, Xiangyang; Zhao, Kai

With the development of cloud computing, the mutual understandability among distributed Access Control Policies (ACPs) has become an important issue in the security field of cloud computing. Semantic Web technology provides the solution to semantic interoperability of heterogeneous applications. In this paper, we analysis existing access control methods and present a new Semantic Access Control Policy Language (SACPL) for describing ACPs in cloud computing environment. Access Control Oriented Ontology System (ACOOS) is designed as the semantic basis of SACPL. Ontology-based SACPL language can effectively solve the interoperability issue of distributed ACPs. This study enriches the research that the semantic web technology is applied in the field of security, and provides a new way of thinking of access control in cloud computing.

Continuous Multistep Methods for Volterra Integro-Differential

African Journals Online (AJOL)

Kamoh et al.

DIFFERENTIAL EQUATIONS OF THE SECOND ORDER. 1Kamoh N.M. ... methods, Volterra integro-differential equation, Convergent, ...... Research of a Multistep Method Applied to Numerical Solution of. Volterra ... Congress on Engineering.

An approach to define semantics for BPM systems interoperability

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Rico, Mariela; Caliusco, María Laura; Chiotti, Omar; Rosa Galli, María

2015-04-01

This article proposes defining semantics for Business Process Management systems interoperability through the ontology of Electronic Business Documents (EBD) used to interchange the information required to perform cross-organizational processes. The semantic model generated allows aligning enterprise's business processes to support cross-organizational processes by matching the business ontology of each business partner with the EBD ontology. The result is a flexible software architecture that allows dynamically defining cross-organizational business processes by reusing the EBD ontology. For developing the semantic model, a method is presented, which is based on a strategy for discovering entity features whose interpretation depends on the context, and representing them for enriching the ontology. The proposed method complements ontology learning techniques that can not infer semantic features not represented in data sources. In order to improve the representation of these entity features, the method proposes using widely accepted ontologies, for representing time entities and relations, physical quantities, measurement units, official country names, and currencies and funds, among others. When the ontologies reuse is not possible, the method proposes identifying whether that feature is simple or complex, and defines a strategy to be followed. An empirical validation of the approach has been performed through a case study.

Retrieval from semantic memory.

NARCIS (Netherlands)

Noordman-Vonk, Wietske

1977-01-01

The present study has been concerned with the retrieval of semantic information. Retrieving semantic information is a fundamental process in almost any kind of cognitive behavior. The introduction presented the main experimental paradigms and results found in the literature on semantic memory as

Towards Universal Semantic Tagging

NARCIS (Netherlands)

Abzianidze, Lasha; Bos, Johan

2017-01-01

The paper proposes the task of universal semantic tagging---tagging word tokens with language-neutral, semantically informative tags. We argue that the task, with its independent nature, contributes to better semantic analysis for wide-coverage multilingual text. We present the initial version of

Process-oriented semantic web search

CERN Document Server

Tran, DT

2011-01-01

The book is composed of two main parts. The first part is a general study of Semantic Web Search. The second part specifically focuses on the use of semantics throughout the search process, compiling a big picture of Process-oriented Semantic Web Search from different pieces of work that target specific aspects of the process.In particular, this book provides a rigorous account of the concepts and technologies proposed for searching resources and semantic data on the Semantic Web. To collate the various approaches and to better understand what the notion of Semantic Web Search entails, this bo

Propagating semantic information in biochemical network models

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Schulz Marvin

2012-01-01

Full Text Available Abstract Background To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation. Results A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements. Conclusions Semantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at http://www.semanticsbml.org.

Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

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

2010-01-01

Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

Applications and methods utilizing the Simple Semantic Web Architecture and Protocol (SSWAP for bioinformatics resource discovery and disparate data and service integration

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Nelson Rex T

2010-06-01

Full Text Available Abstract Background Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of data between information resources difficult and labor intensive. A recently described semantic web protocol, the Simple Semantic Web Architecture and Protocol (SSWAP; pronounced "swap" offers the ability to describe data and services in a semantically meaningful way. We report how three major information resources (Gramene, SoyBase and the Legume Information System [LIS] used SSWAP to semantically describe selected data and web services. Methods We selected high-priority Quantitative Trait Locus (QTL, genomic mapping, trait, phenotypic, and sequence data and associated services such as BLAST for publication, data retrieval, and service invocation via semantic web services. Data and services were mapped to concepts and categories as implemented in legacy and de novo community ontologies. We used SSWAP to express these offerings in OWL Web Ontology Language (OWL, Resource Description Framework (RDF and eXtensible Markup Language (XML documents, which are appropriate for their semantic discovery and retrieval. We implemented SSWAP services to respond to web queries and return data. These services are registered with the SSWAP Discovery Server and are available for semantic discovery at http://sswap.info. Results A total of ten services delivering QTL information from Gramene were created. From SoyBase, we created six services delivering information about soybean QTLs, and seven services delivering genetic locus information. For LIS we constructed three services, two of which allow the retrieval of DNA and RNA FASTA sequences with the third service providing nucleic acid sequence comparison capability (BLAST. Conclusions The need for semantic integration technologies has preceded

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

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

2012-07-01

Semantic dementia is a progressive neurodegenerative condition characterized by the profound and amodal loss of semantic memory in the context of relatively preserved episodic memory. In contrast, patients with Alzheimer's disease typically display impairments in episodic memory, but with semantic deficits of a much lesser magnitude than in semantic dementia. Our understanding of episodic memory retrieval in these cohorts has greatly increased over the last decade, however, we know relatively little regarding the ability of these patients to imagine and describe possible future events, and whether episodic future thinking is mediated by divergent neural substrates contingent on dementia subtype. Here, we explored episodic future thinking in patients with semantic dementia (n=11) and Alzheimer's disease (n=11), in comparison with healthy control participants (n=10). Participants completed a battery of tests designed to probe episodic and semantic thinking across past and future conditions, as well as standardized tests of episodic and semantic memory. Further, all participants underwent magnetic resonance imaging. Despite their relatively intact episodic retrieval for recent past events, the semantic dementia cohort showed significant impairments for episodic future thinking. In contrast, the group with Alzheimer's disease showed parallel deficits across past and future episodic conditions. Voxel-based morphometry analyses confirmed that atrophy in the left inferior temporal gyrus and bilateral temporal poles, regions strongly implicated in semantic memory, correlated significantly with deficits in episodic future thinking in semantic dementia. Conversely, episodic future thinking performance in Alzheimer's disease correlated with atrophy in regions associated with episodic memory, namely the posterior cingulate, parahippocampal gyrus and frontal pole. These distinct neuroanatomical substrates contingent on dementia group were further qualified by correlational

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System

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Zhenyu Wu

2017-02-01

Full Text Available Web of Things (WoT facilitates the discovery and interoperability of Internet of Things (IoT devices in a cyber-physical system (CPS. Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN, it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT framework for CPS (SWoT4CPS. SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System.

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Wu, Zhenyu; Xu, Yuan; Yang, Yunong; Zhang, Chunhong; Zhu, Xinning; Ji, Yang

2017-02-20

Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed.

Modified Chebyshev Collocation Method for Solving Differential Equations

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M Ziaul Arif

2015-05-01

Full Text Available This paper presents derivation of alternative numerical scheme for solving differential equations, which is modified Chebyshev (Vieta-Lucas Polynomial collocation differentiation matrices. The Scheme of modified Chebyshev (Vieta-Lucas Polynomial collocation method is applied to both Ordinary Differential Equations (ODEs and Partial Differential Equations (PDEs cases. Finally, the performance of the proposed method is compared with finite difference method and the exact solution of the example. It is shown that modified Chebyshev collocation method more effective and accurate than FDM for some example given.

Semantic embodiment, disembodiment or misembodiment? In search of meaning in modules and neuron circuits.

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Pulvermüller, Friedemann

2013-10-01

"Embodied" proposals claim that the meaning of at least some words, concepts and constructions is grounded in knowledge about actions and objects. An alternative "disembodied" position locates semantics in a symbolic system functionally detached from sensorimotor modules. This latter view is not tenable theoretically and has been empirically falsified by neuroscience research. A minimally-embodied approach now claims that action-perception systems may "color", but not represent, meaning; however, such minimal embodiment (misembodiment?) still fails to explain why action and perception systems exert causal effects on the processing of symbols from specific semantic classes. Action perception theory (APT) offers neurobiological mechanisms for "embodied" referential, affective and action semantics along with "disembodied" mechanisms of semantic abstraction, generalization and symbol combination, which draw upon multimodal brain systems. In this sense, APT suggests integrative-neuromechanistic explanations of why both sensorimotor and multimodal areas of the human brain differentially contribute to specific facets of meaning and concepts. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Semantic similarity measure in biomedical domain leverage web search engine.

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Chen, Chi-Huang; Hsieh, Sheau-Ling; Weng, Yung-Ching; Chang, Wen-Yung; Lai, Feipei

2010-01-01

Semantic similarity measure plays an essential role in Information Retrieval and Natural Language Processing. In this paper we propose a page-count-based semantic similarity measure and apply it in biomedical domains. Previous researches in semantic web related applications have deployed various semantic similarity measures. Despite the usefulness of the measurements in those applications, measuring semantic similarity between two terms remains a challenge task. The proposed method exploits page counts returned by the Web Search Engine. We define various similarity scores for two given terms P and Q, using the page counts for querying P, Q and P AND Q. Moreover, we propose a novel approach to compute semantic similarity using lexico-syntactic patterns with page counts. These different similarity scores are integrated adapting support vector machines, to leverage the robustness of semantic similarity measures. Experimental results on two datasets achieve correlation coefficients of 0.798 on the dataset provided by A. Hliaoutakis, 0.705 on the dataset provide by T. Pedersen with physician scores and 0.496 on the dataset provided by T. Pedersen et al. with expert scores.

A Patient with Difficulty of Object Recognition: Semantic Amnesia for Manipulable Objects

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A. Yamadori

1992-01-01

Full Text Available We studied a patient who had recognition difficulty for manipulable objects. MRI showed a lesion in the left occipito-parietotemporal area. Differential diagnosis of agnosia, aphasia and apraxia is discussed. We believe this “object meaning amnesia” constitutes a distinct subtype of semantic amnesia.

Text Summarization Using FrameNet-Based Semantic Graph Model

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Xu Han

2016-01-01

Full Text Available Text summarization is to generate a condensed version of the original document. The major issues for text summarization are eliminating redundant information, identifying important difference among documents, and recovering the informative content. This paper proposes a Semantic Graph Model which exploits the semantic information of sentence using FSGM. FSGM treats sentences as vertexes while the semantic relationship as the edges. It uses FrameNet and word embedding to calculate the similarity of sentences. This method assigns weight to both sentence nodes and edges. After all, it proposes an improved method to rank these sentences, considering both internal and external information. The experimental results show that the applicability of the model to summarize text is feasible and effective.

Abstract methods in partial differential equations

CERN Document Server

Carroll, Robert W

2012-01-01

Detailed, self-contained treatment examines modern abstract methods in partial differential equations, especially abstract evolution equations. Suitable for graduate students with some previous exposure to classical partial differential equations. 1969 edition.

A Defense of Semantic Minimalism

Science.gov (United States)

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…

THE COMPLEX ANALYSIS METHOD OF SEMANTIC ASSOCIATIONS IN STUDYING THE STUDENTS’ CREATIVE ETHOS

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P. A. Starikov

2013-01-01

Full Text Available The paper demonstrates the sociological research findings concerning the students’ ideas of creativity based on the questionnaires and testing of the students of the natural science, humanities and technical profiles at Siberian Federal University over the period of 2007-2011.The author suggests a new method of semantic association analysis in order to identify the latent groups of notions related to the concept of creativity. The range of students’ common opinions demonstrate the obvious trend for humanizing the idea of creativity, considering  it as the perfect mode of human existence, which coincide with the ideas of K. Rogers, A. Maslow and other scholars. Today’s students associate creativity primarily with pleasure, self-development, self-expression, inspiration, improvisation, spontaneity; and the resulting semantic complex incorporates such characteristics of creative work as goodness, abundance of energy, integrity, health, freedom and independence, self-development and spirituality.The obtained data prove the importance of the inspiration experience in creative pedagogy; the research outcomes along with the continuing monitoring of students attitude to creativity development can optimize the learning process. The author emphasizes the necessity of introducing some special courses, based on the integral approach (including social, philosophical, psychological, psycho-social and technical aspects, and aimed at developing students’ creative competence. 

Principal semantic components of language and the measurement of meaning.

Science.gov (United States)

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

2010-06-11

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

Principal semantic components of language and the measurement of meaning.

Directory of Open Access Journals (Sweden)

Alexei V Samsonovich

Full Text Available 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

Linguistic expressions and semantic processing a practical approach

CERN Document Server

Butler, Alastair

2015-01-01

This book introduces formal semantics techniques for a natural language processing audience. Methods discussed involve: (i) the denotational techniques used in model-theoretic semantics, which make it possible to determine whether a linguistic expression is true or false with respect to some model of the way things happen to be; and (ii) stages of interpretation, i.e., ways to arrive at meanings by evaluating and converting source linguistic expressions, possibly with respect to contexts, into output (logical) forms that could be used with (i). The book demonstrates that the methods allow w

Subliminal semantic priming in speech.

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Jérôme Daltrozzo

Full Text Available Numerous studies have reported subliminal repetition and semantic priming in the visual modality. We transferred this paradigm to the auditory modality. Prime awareness was manipulated by a reduction of sound intensity level. Uncategorized prime words (according to a post-test were followed by semantically related, unrelated, or repeated target words (presented without intensity reduction and participants performed a lexical decision task (LDT. Participants with slower reaction times in the LDT showed semantic priming (faster reaction times for semantically related compared to unrelated targets and negative repetition priming (slower reaction times for repeated compared to semantically related targets. This is the first report of semantic priming in the auditory modality without conscious categorization of the prime.

Open semantic analysis: The case of word level semantics in Danish

DEFF Research Database (Denmark)

Nielsen, Finn Årup; Hansen, Lars Kai

2017-01-01

The present research is motivated by the need for accessible and efficient tools for automated semantic analysis in Danish. We are interested in tools that are completely open, so they can be used by a critical public, in public administration, non-governmental organizations and businesses. We...... describe data-driven models for Danish semantic relatedness, word intrusion and sentiment prediction. Open Danish corpora were assembled and unsupervised learning implemented for explicit semantic analysis and with Gensim’s Word2vec model. We evaluate the performance of the two models on three different...... annotated word datasets. We test the semantic representations’ alignment with single word sentiment using supervised learning. We find that logistic regression and large random forests perform well with Word2vec features....

Applied Semantic Web Technologies

CERN Document Server

Sugumaran, Vijayan

2011-01-01

The rapid advancement of semantic web technologies, along with the fact that they are at various levels of maturity, has left many practitioners confused about the current state of these technologies. Focusing on the most mature technologies, Applied Semantic Web Technologies integrates theory with case studies to illustrate the history, current state, and future direction of the semantic web. It maintains an emphasis on real-world applications and examines the technical and practical issues related to the use of semantic technologies in intelligent information management. The book starts with

Subclinical naming errors in mild cognitive impairment: A semantic deficit?

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Indra F. Willers

Full Text Available Abstract Mild cognitive impairment (MCI is the transitional stage between normal aging and Alzheimer's disease (AD. Impairments in semantic memory have been demonstrated to be a critical factor in early AD. The Boston Naming Test (BNT is a straightforward method of examining semantic or visuo-perceptual processing and therefore represents a potential diagnostic tool. The objective of this study was to examine naming ability and identify error types in patients with amnestic mild cognitive impairment (aMCI. Methods: Twenty aMCI patients, twenty AD patients and twenty-one normal controls, matched by age, sex and education level were evaluated. As part of a further neuropsychological evaluation, all subjects performed the BNT. A comprehensive classification of error types was devised in order to compare performance and ascertain semantic or perceptual origin of errors. Results: AD patients obtained significantly lower total scores on the BNT than aMCI patients and controls. aMCI patients did not obtain significant differences in total scores, but showed significantly higher semantic errors compared to controls. Conclusion: This study reveals that semantic processing is impaired during confrontation naming in aMCI.

[Electrophysiological bases of semantic processing of objects].

Science.gov (United States)

Kahlaoui, Karima; Baccino, Thierry; Joanette, Yves; Magnié, Marie-Noële

2007-02-01

How pictures and words are stored and processed in the human brain constitute a long-standing question in cognitive psychology. Behavioral studies have yielded a large amount of data addressing this issue. Generally speaking, these data show that there are some interactions between the semantic processing of pictures and words. However, behavioral methods can provide only limited insight into certain findings. Fortunately, Event-Related Potential (ERP) provides on-line cues about the temporal nature of cognitive processes and contributes to the exploration of their neural substrates. ERPs have been used in order to better understand semantic processing of words and pictures. The main objective of this article is to offer an overview of the electrophysiologic bases of semantic processing of words and pictures. Studies presented in this article showed that the processing of words is associated with an N 400 component, whereas pictures elicited both N 300 and N 400 components. Topographical analysis of the N 400 distribution over the scalp is compatible with the idea that both image-mediated concrete words and pictures access an amodal semantic system. However, given the distinctive N 300 patterns, observed only during picture processing, it appears that picture and word processing rely upon distinct neuronal networks, even if they end up activating more or less similar semantic representations.

Knowledge-Base Semantic Gap Analysis for the Vulnerability Detection

Science.gov (United States)

Wu, Raymond; Seki, Keisuke; Sakamoto, Ryusuke; Hisada, Masayuki

Web security became an alert in internet computing. To cope with ever-rising security complexity, semantic analysis is proposed to fill-in the gap that the current approaches fail to commit. Conventional methods limit their focus to the physical source codes instead of the abstraction of semantics. It bypasses new types of vulnerability and causes tremendous business loss.

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

Directory of Open Access Journals (Sweden)

David Shotton

2009-04-01

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

Pascal Semantics by a Combination of Denotational Semantics and High-level Petri Nets

DEFF Research Database (Denmark)

Jensen, Kurt; Schmidt, Erik Meineche

1986-01-01

This paper describes the formal semantics of a subset of PASCAL, by means of a semantic model based on a combination of denotational semantics and high-level Petri nets. It is our intention that the paper can be used as part of the written material for an introductory course in computer science....

Comparison of two methods for customer differentiation

NARCIS (Netherlands)

A.F. Gabor (Adriana); Y. Guang (Yang); S. Axsäter (Sven)

2014-01-01

textabstractIn response to customer specific time guarantee requirements, service providers can offer differentiated ser- vices. However, conventional customer differentiation methods often lead to high holding costs and may have some practical drawbacks. We compare two customer differentiation

Semantic concept-enriched dependence model for medical information retrieval.

Science.gov (United States)

Choi, Sungbin; Choi, Jinwook; Yoo, Sooyoung; Kim, Heechun; Lee, Youngho

2014-02-01

In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance. Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method. We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research. Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query. By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance. Copyright © 2013 Elsevier Inc. All rights reserved.

The Effect of Concurrent Semantic Categorization on Delayed Serial Recall

Science.gov (United States)

Acheson, Daniel J.; MacDonald, Maryellen C.; Postle, Bradley R.

2010-01-01

The influence of semantic processing on the serial ordering of items in short-term memory was explored using a novel dual-task paradigm. Subjects engaged in two picture judgment tasks while simultaneously performing delayed serial recall. List material varied in the presence of phonological overlap (Experiments 1 and 2) and in semantic content (concrete words in Experiment 1 and 3; nonwords in Experiments 2 and 3). Picture judgments varied in the extent to which they required accessing visual semantic information (i.e., semantic categorization and line orientation judgments). Results showed that, relative to line orientation judgments, engaging in semantic categorization judgments increased the proportion of item ordering errors for concrete lists but did not affect error proportions for nonword lists. Furthermore, although more ordering errors were observed for phonologically similar relative to dissimilar lists, no interactions were observed between the phonological overlap and picture judgment task manipulations. These results thus demonstrate that lexical-semantic representations can affect the serial ordering of items in short-term memory. Furthermore, the dual-task paradigm provides a new method for examining when and how semantic representations affect memory performance. PMID:21058880

Does semantic impairment explain surface dyslexia? VLSM evidence for a double dissociation between regularization errors in reading and semantic errors in picture naming

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Sara Pillay

2014-04-01

Full Text Available The correlation between semantic deficits and exception word regularization errors ("surface dyslexia" in semantic dementia has been taken as strong evidence for involvement of semantic codes in exception word pronunciation. Rare cases with semantic deficits but no exception word reading deficit have been explained as due to individual differences in reading strategy, but this account is hotly debated. Semantic dementia is a diffuse process that always includes semantic impairment, making lesion localization difficult and independent assessment of semantic deficits and reading errors impossible. We addressed this problem using voxel-based lesion symptom mapping in 38 patients with left hemisphere stroke. Patients were all right-handed, native English speakers and at least 6 months from stroke onset. Patients performed an oral reading task that included 80 exception words (words with inconsistent orthographic-phonologic correspondence, e.g., pint, plaid, glove. Regularization errors were defined as plausible but incorrect pronunciations based on application of spelling-sound correspondence rules (e.g., 'plaid' pronounced as "played". Two additional tests examined explicit semantic knowledge and retrieval. The first measured semantic substitution errors during naming of 80 standard line drawings of objects. This error type is generally presumed to arise at the level of concept selection. The second test (semantic matching required patients to match a printed sample word (e.g., bus with one of two alternative choice words (e.g., car, taxi on the basis of greater similarity of meaning. Lesions were labeled on high-resolution T1 MRI volumes using a semi-automated segmentation method, followed by diffeomorphic registration to a template. VLSM used an ANCOVA approach to remove variance due to age, education, and total lesion volume. Regularization errors during reading were correlated with damage in the posterior half of the middle temporal gyrus and

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

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He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2017-11-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

Solution of fractional differential equations by using differential transform method

International Nuclear Information System (INIS)

Arikoglu, Aytac; Ozkol, Ibrahim

2007-01-01

In this study, we implement a well known transformation technique, Differential Transform Method (DTM), to the area of fractional differential equations. Theorems that never existed before are introduced with their proofs. Also numerical examples are carried out for various types of problems, including the Bagley-Torvik, Ricatti and composite fractional oscillation equations for the application of the method. The results obtained are in good agreement with the existing ones in open literature and it is shown that the technique introduced here is robust, accurate and easy to apply

Solution of fractional differential equations by using differential transform method

Energy Technology Data Exchange (ETDEWEB)

Arikoglu, Aytac [Istanbul Technical University, Faculty of Aeronautics and Astronautics, Department of Aeronautical Engineering, Maslak, TR-34469 Istanbul (Turkey); Ozkol, Ibrahim [Istanbul Technical University, Faculty of Aeronautics and Astronautics, Department of Aeronautical Engineering, Maslak, TR-34469 Istanbul (Turkey)]. E-mail: ozkol@itu.edu.tr

2007-12-15

In this study, we implement a well known transformation technique, Differential Transform Method (DTM), to the area of fractional differential equations. Theorems that never existed before are introduced with their proofs. Also numerical examples are carried out for various types of problems, including the Bagley-Torvik, Ricatti and composite fractional oscillation equations for the application of the method. The results obtained are in good agreement with the existing ones in open literature and it is shown that the technique introduced here is robust, accurate and easy to apply.

GRAPHIC REALIZATION FOUNDATIONS OF LOGIC-SEMANTIC MODELING IN DIDACTICS

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V. E. Steinberg

2017-01-01

Full Text Available Introduction. Nowadays, there are not a lot of works devoted to a graphic method of logic-semantic modeling of knowledge. Meanwhile, an interest towards this method increases due to the fact of essential increase of the content of visual component in information and educational sources. The present publication is the authors’ contribution into the solution of the problem of search of new forms and means convenient for visual and logic perception of a training material, its assimilation, operating by elements of knowledge and their transformations.The aim of the research is to justify graphical implementation of the method of logic-semantic modeling of knowledge, presented by a natural language (training language and to show the possibilities of application of figurative and conceptual models in student teaching.Methodology and research methods. The research methodology is based on the specified activity-regulatory, system-multi-dimensional and structural-invariant approach and the principle of multidimensionality. The methodology the graphic realization of the logic-semantic models in learning technologies is based on didactic design using computer training programs.Results and scientific novelty. Social and anthropological-cultural adaptation bases of the method of logical-semantic knowledge modeling to the problems of didactics are established and reasoned: coordinate-invariant matrix structure is presented as the basis of logical-semantic models of figurative and conceptual nature; the possibilities of using such models as multifunctional didactic regulators – support schemes, navigation in the content of the educational material, educational activities carried out by navigators, etc., are shown. The characteristics of new teaching tools as objects of semiotics and didactic of regulators are considered; their place and role in the structure of the external and internal training curricula learning activities are pointed out

A SURVEY ON OPTIMIZATION APPROACHES TO SEMANTIC SERVICE DISCOVERY TOWARDS AN INTEGRATED SOLUTION

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Chellammal Surianarayanan

2012-07-01

Full Text Available The process of semantic service discovery using an ontology reasoner such as Pellet is time consuming. This restricts the usage of web services in real time applications having dynamic composition requirements. As performance of semantic service discovery is crucial in service composition, it should be optimized. Various optimization methods are being proposed to improve the performance of semantic discovery. In this work, we investigate the existing optimization methods and broadly classify optimization mechanisms into two categories, namely optimization by efficient reasoning and optimization by efficient matching. Optimization by efficient matching is further classified into subcategories such as optimization by clustering, optimization by inverted indexing, optimization by caching, optimization by hybrid methods, optimization by efficient data structures and optimization by efficient matching algorithms. With a detailed study of different methods, an integrated optimization infrastructure along with matching method has been proposed to improve the performance of semantic matching component. To achieve better optimization the proposed method integrates the effects of caching, clustering and indexing. Theoretical aspects of performance evaluation of the proposed method are discussed.

Reactive Kripke semantics

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Gabbay, Dov M

2013-01-01

This text offers an extension to the traditional Kripke semantics for non-classical logics by adding the notion of reactivity. Reactive Kripke models change their accessibility relation as we progress in the evaluation process of formulas in the model. This feature makes the reactive Kripke semantics strictly stronger and more applicable than the traditional one. Here we investigate the properties and axiomatisations of this new and most effective semantics, and we offer a wide landscape of applications of the idea of reactivity. Applied topics include reactive automata, reactive grammars, rea

Semantic equivalences in Romanian medical terminology

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Corina Lungu

2014-12-01

Full Text Available The present paper aims to underline some aspects concerning the presence of synonymy semantic relationship in specialized medical terminology, having as object of study Romanian medical terms. For this study we use a descriptive, conceptual and lexical semantic research method to provide the understanding of different couples, groups or synonymic series where medical terms have several variations: specialized/common terms, syntagms and patronyms of French or different origin. We propose a classification scheme of synonyms of medical lexicon, terms or synonymic syntagms, total and partial, in order to meet the accessibility needs in scientific communication.

Semantics, contrastive linguistics and parallel corpora

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Violetta Koseska

2014-09-01

Full Text Available Semantics, contrastive linguistics and parallel corpora In view of the ambiguity of the term “semantics”, the author shows the differences between the traditional lexical semantics and the contemporary semantics in the light of various semantic schools. She examines semantics differently in connection with contrastive studies where the description must necessary go from the meaning towards the linguistic form, whereas in traditional contrastive studies the description proceeded from the form towards the meaning. This requirement regarding theoretical contrastive studies necessitates construction of a semantic interlanguage, rather than only singling out universal semantic categories expressed with various language means. Such studies can be strongly supported by parallel corpora. However, in order to make them useful for linguists in manual and computer translations, as well as in the development of dictionaries, including online ones, we need not only formal, often automatic, annotation of texts, but also semantic annotation - which is unfortunately manual. In the article we focus on semantic annotation concerning time, aspect and quantification of names and predicates in the whole semantic structure of the sentence on the example of the “Polish-Bulgarian-Russian parallel corpus”.

Contextually guided very-high-resolution imagery classification with semantic segments

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Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Bio-jETI: a framework for semantics-based service composition

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Margaria Tiziana

2009-10-01

checking and synthesis methods, users may orchestrate complex processes from a wealth of heterogeneous services without worrying about interfaces and (type consistency. The success of this method strongly depends on a careful semantic annotation of the provided services and on its consequent exploitation for analysis, validation, and synthesis. We are convinced that these annotations will become standard, as they will become preconditions for the success and widespread use of (preferred services in the Semantic Web.

Form gene clustering method about pan-ethnic-group products based on emotional semantic

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Chen, Dengkai; Ding, Jingjing; Gao, Minzhuo; Ma, Danping; Liu, Donghui

2016-09-01

The use of pan-ethnic-group products form knowledge primarily depends on a designer's subjective experience without user participation. The majority of studies primarily focus on the detection of the perceptual demands of consumers from the target product category. A pan-ethnic-group products form gene clustering method based on emotional semantic is constructed. Consumers' perceptual images of the pan-ethnic-group products are obtained by means of product form gene extraction and coding and computer aided product form clustering technology. A case of form gene clustering about the typical pan-ethnic-group products is investigated which indicates that the method is feasible. This paper opens up a new direction for the future development of product form design which improves the agility of product design process in the era of Industry 4.0.

Variable-mesh method of solving differential equations

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Van Wyk, R.

1969-01-01

Multistep predictor-corrector method for numerical solution of ordinary differential equations retains high local accuracy and convergence properties. In addition, the method was developed in a form conducive to the generation of effective criteria for the selection of subsequent step sizes in step-by-step solution of differential equations.

Exploring DBpedia and Wikipedia for Portuguese Semantic Relationship Extraction

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David Soares Batista

2013-07-01

Full Text Available The identification of semantic relationships, as expressed between named entities in text, is an important step for extracting knowledge from large document collections, such as the Web. Previous works have addressed this task for the English language through supervised learning techniques for automatic classification. The current state of the art involves the use of learning methods based on string kernels. However, such approaches require manually annotated training data for each type of semantic relationship, and have scalability problems when tens or hundreds of different types of relationships have to be extracted. This article discusses an approach for distantly supervised relation extraction over texts written in the Portuguese language, which uses an efficient technique for measuring similarity between relation instances, based on minwise hashing and on locality sensitive hashing. In the proposed method, the training examples are automatically collected from Wikipedia, corresponding to sentences that express semantic relationships between pairs of entities extracted from DBPedia. These examples are represented as sets of character quadgrams and other representative elements. The sets are indexed in a data structure that implements the idea of locality-sensitive hashing. To check which semantic relationship is expressed between a given pair of entities referenced in a sentence, the most similar training examples are searched, based on an approximation to the Jaccard coefficient, obtained through min-hashing. The relation class is assigned with basis on the weighted votes of the most similar examples. Tests with a dataset from Wikipedia validate the suitability of the proposed method, showing, for instance, that the method is able to extract 10 different types of semantic relations, 8 of them corresponding to asymmetric relations, with an average score of 55.6%, measured in terms of F1.

Field Method for Integrating the First Order Differential Equation

Institute of Scientific and Technical Information of China (English)

JIA Li-qun; ZHENG Shi-wang; ZHANG Yao-yu

2007-01-01

An important modern method in analytical mechanics for finding the integral, which is called the field-method, is used to research the solution of a differential equation of the first order. First, by introducing an intermediate variable, a more complicated differential equation of the first order can be expressed by two simple differential equations of the first order, then the field-method in analytical mechanics is introduced for solving the two differential equations of the first order. The conclusion shows that the field-method in analytical mechanics can be fully used to find the solutions of a differential equation of the first order, thus a new method for finding the solutions of the first order is provided.

Semantic web for dummies

CERN Document Server

Pollock, Jeffrey T

2009-01-01

Semantic Web technology is already changing how we interact with data on the Web. By connecting random information on the Internet in new ways, Web 3.0, as it is sometimes called, represents an exciting online evolution. Whether you're a consumer doing research online, a business owner who wants to offer your customers the most useful Web site, or an IT manager eager to understand Semantic Web solutions, Semantic Web For Dummies is the place to start! It will help you:Know how the typical Internet user will recognize the effects of the Semantic WebExplore all the benefits the data Web offers t

A SEMantic and EPisodic Memory Test (SEMEP) Developed within the Embodied Cognition Framework: Application to Normal Aging, Alzheimer's Disease and Semantic Dementia.

Science.gov (United States)

Vallet, Guillaume T; Hudon, Carol; Bier, Nathalie; Macoir, Joël; Versace, Rémy; Simard, Martine

2017-01-01

Embodiment has highlighted the importance of sensory-motor components in cognition. Perception and memory are thus very tightly bound together, and episodic and semantic memories should rely on the same grounded memory traces. Reduced perception should then directly reduce the ability to encode and retrieve an episodic memory, as in normal aging. Multimodal integration deficits, as in Alzheimer's disease, should lead to more severe episodic memory impairment. The present study introduces a new memory test developed to take into account these assumptions. The SEMEP (SEMantic-Episodic) memory test proposes to assess conjointly semantic and episodic knowledge across multiple tasks: semantic matching, naming, free recall, and recognition. The performance of young adults is compared to healthy elderly adults (HE), patients with Alzheimer's disease (AD), and patients with semantic dementia (SD). The results show specific patterns of performance between the groups. HE commit memory errors only for presented but not to be remembered items. AD patients present the worst episodic memory performance associated with intrusion errors (recall or recognition of items never presented). They were the only group to not benefit from a visual isolation (addition of a yellow background), a method known to increase the distinctiveness of the memory traces. Finally, SD patients suffer from the most severe semantic impairment. To conclude, confusion errors are common across all the elderly groups, whereas AD was the only group to exhibit regular intrusion errors and SD patients to show severe semantic impairment.

A SEMantic and EPisodic Memory Test (SEMEP Developed within the Embodied Cognition Framework: Application to Normal Aging, Alzheimer's Disease and Semantic Dementia

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Guillaume T. Vallet

2017-09-01

Full Text Available Embodiment has highlighted the importance of sensory-motor components in cognition. Perception and memory are thus very tightly bound together, and episodic and semantic memories should rely on the same grounded memory traces. Reduced perception should then directly reduce the ability to encode and retrieve an episodic memory, as in normal aging. Multimodal integration deficits, as in Alzheimer's disease, should lead to more severe episodic memory impairment. The present study introduces a new memory test developed to take into account these assumptions. The SEMEP (SEMantic-Episodic memory test proposes to assess conjointly semantic and episodic knowledge across multiple tasks: semantic matching, naming, free recall, and recognition. The performance of young adults is compared to healthy elderly adults (HE, patients with Alzheimer's disease (AD, and patients with semantic dementia (SD. The results show specific patterns of performance between the groups. HE commit memory errors only for presented but not to be remembered items. AD patients present the worst episodic memory performance associated with intrusion errors (recall or recognition of items never presented. They were the only group to not benefit from a visual isolation (addition of a yellow background, a method known to increase the distinctiveness of the memory traces. Finally, SD patients suffer from the most severe semantic impairment. To conclude, confusion errors are common across all the elderly groups, whereas AD was the only group to exhibit regular intrusion errors and SD patients to show severe semantic impairment.

Age-related vulnerability in the neural systems supporting semantic processing

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Jonathan E Peelle

2013-09-01

Full Text Available Our ability to form abstract representations of objects in semantic memory is crucial to language and thought. The utility of this information relies both on the representations of sensory-motor feature knowledge stored in long-term memory and the executive processes required to retrieve, manipulate, and evaluate this semantic knowledge in a task-relevant manner. These complementary components of semantic memory can be differentially impacted by aging. We investigated semantic processing in normal aging using functional magnetic resonance imaging (fMRI. Young and older adults were asked to judge whether two printed object names match on a particular feature (for example, whether a tomato and strawberry have the same color. The task thus required both retrieval of relevant visual feature knowledge of object concepts and evaluating this information. Objects were drawn from either natural kinds or manufactured objects, and were queried on either color or shape in a factorial design. Behaviorally, all subjects performed well, but older adults could be divided into those whose performance matched that of young adults (better performers and those whose performance was worse (poorer performers. All subjects activated several cortical regions while performing this task, including bilateral inferior and lateral temporal cortex and left frontal and prefrontal cortex. Better performing older adults showed increased overall activity in bilateral premotor cortex and left lateral occipital cortex compared to young adults, and increased activity in these brain regions relative to poorer performing older adults who also showed gray matter atrophy in premotor cortex. These findings highlight the contribution of domain-general executive processing brain regions to semantic memory, and illustrate differences in how these regions are recruited in healthy older adults.

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction.

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Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A; Barak, Ohr; Lambon Ralph, Matthew A; Jefferies, Elizabeth

2018-01-03

Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., , Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal 'hub' in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive-semantic goal representations, largely supported by executive regions such as frontal and parietal cortex, are thought to allow the generation of non-dominant aspects of knowledge when these are appropriate for the task or context. Semantic aphasia (SA) patients have executive-semantic deficits, and these are correlated with general executive impairment. If the CSC proposal is correct, patients with executive impairment should not only exhibit impaired semantic cognition, but should also show characteristics that align with those observed in SA. This possibility remains largely untested, as patients selected on the basis that they show executive impairment (i.e., with 'dysexecutive syndrome') have not been extensively tested on tasks tapping semantic control and have not been previously compared with SA cases. We explored conceptual processing in 12 patients showing symptoms consistent with dysexecutive syndrome (DYS) and 24 SA patients, using a range of multimodal semantic assessments which manipulated control demands. Patients with executive impairments, despite not being selected to show semantic impairments, nevertheless showed parallel patterns to SA cases. They showed strong effects of distractor strength, cues and miscues, and probe-target distance, plus minimal effects of word frequency on comprehension (unlike semantic dementia patients with degradation of conceptual knowledge). This supports a component process account of semantic cognition in which retrieval is shaped by control processes, and confirms that deficits in SA patients reflect

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

Science.gov (United States)

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

2017-07-01

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

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

Science.gov (United States)

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.

GIS Data Modeling of a Regional Geological Structure by Integrating Geometric and Semantic Expressions

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HE Handong

2017-08-01

Full Text Available Using GIS, data models of geology via geometric descriptions and expressions are being developed. However, the role played by these data models in terms of the description and expression of geological structure phenomenon is limited. To improve the semantic information in geological GIS data models, this study adopts an object-oriented method that describes and expresses the geometric and semantic features of the geological structure phenomenon using geological objects and designs a data model of regional geological structures by integrating geometry and semantics. Moreover, the study designs a semantic "vocabulary-explanation-graph" method for describing the geological phenomenon of structures. Based on the semantic features of regional geological structures and a linear classification method, it divides the regional geological structure phenomenon into 3 divisions, 10 groups, 33 classes and defines the element set and element class. Moreover, it builds the basic geometric network for geological elements based on the geometric and semantic relations among geological objects. Using the ArcGIS Diagrammer Geodatabase, it considers the regional geological structure of the Ning-Zhen Mountains to verify the data model, and the results indicate a high practicability.

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2008-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fuse...... its transition function with its driver loop, obtaining the functional implementation of a big-step abstract machine; (2) we adjust this big-step abstract machine so that it is in defunctionalized form, obtaining the functional implementation of a second big-step abstract machine; (3) we...... refunctionalize this adjusted abstract machine, obtaining the functional implementation of a natural semantics in continuation style; and (4) we closure-unconvert this natural semantics, obtaining a compositional continuation-passing evaluation function which we identify as the functional implementation...

Temporal Representation in Semantic Graphs

Energy Technology Data Exchange (ETDEWEB)

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.

Flow Logics and Operational Semantics

DEFF Research Database (Denmark)

Nielson, Flemming; Nielson, Hanne Riis

1998-01-01

Flow logic is a “fast prototyping” approach to program analysis that shows great promise of being able to deal with a wide variety of languages and calculi for computation. However, seemingly innocent choices in the flow logic as well as in the operational semantics may inhibit proving the analys...... correct. Our main conclusion is that environment based semantics is more flexible than either substitution based semantics or semantics making use of structural congruences (like alpha-renaming)....

Semantic Versus Syntactic Cutting Planes

OpenAIRE

Filmus, Yuval; Hrubeš, Pavel; Lauria, Massimo

2016-01-01

In this paper, we compare the strength of the semantic and syntactic version of the cutting planes proof system. First, we show that the lower bound technique of Pudlák applies also to semantic cutting planes: the proof system has feasible interpolation via monotone real circuits, which gives an exponential lower bound on lengths of semantic cutting planes refutations. Second, we show that semantic refutations are stronger than syntactic ones. In particular, we give a formula for whic...

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

Science.gov (United States)

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

2015-11-11

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. The purpose of this study was to assess the usability of SAM by investigating characteristic user behavior of medical students accessing MLOs via SAM. 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. 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. 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.

Semantic web technologies for enterprise 2.0

CERN Document Server

Passant, A

2010-01-01

In this book, we detail different theories, methods and implementations combining Web 2.0 paradigms and Semantic Web technologies in Enterprise environments. After introducing those terms, we present the current shortcomings of tools such as blogs and wikis as well as tagging practices in an Enterprise 2.0 context. We define the SemSLATES methodology and the global vision of a middleware architecture based on Semantic Web technologies and Linked Data principles (languages, models, tools and protocols) to solve these issues. Then, we detail the various ontologies that we build to achieve this g

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

Science.gov (United States)

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

2014-01-01

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

A Line-Tau Collocation Method for Partial Differential Equations ...

African Journals Online (AJOL)

This paper deals with the numerical solution of second order linear partial differential equations with the use of the method of lines coupled with the tau collocation method. The method of lines is used to convert the partial differential equation (PDE) to a sequence of ordinary differential equations (ODEs) which is then ...

Semantic Web Primer

NARCIS (Netherlands)

Antoniou, Grigoris; Harmelen, Frank van

2004-01-01

The development of the Semantic Web, with machine-readable content, has the potential to revolutionize the World Wide Web and its use. A Semantic Web Primer provides an introduction and guide to this still emerging field, describing its key ideas, languages, and technologies. Suitable for use as a

Reduced differential transform method for partial differential equations within local fractional derivative operators

Directory of Open Access Journals (Sweden)

Hossein Jafari

2016-04-01

Full Text Available The non-differentiable solution of the linear and non-linear partial differential equations on Cantor sets is implemented in this article. The reduced differential transform method is considered in the local fractional operator sense. The four illustrative examples are given to show the efficiency and accuracy features of the presented technique to solve local fractional partial differential equations.

Wernicke's Aphasia Reflects a Combination of Acoustic-Phonological and Semantic Control Deficits: A Case-Series Comparison of Wernicke's Aphasia, Semantic Dementia and Semantic Aphasia

Science.gov (United States)

Robson, Holly; Sage, Karen; Lambon Ralph, Matthew A.

2012-01-01

Wernicke's aphasia (WA) is the classical neurological model of comprehension impairment and, as a result, the posterior temporal lobe is assumed to be critical to semantic cognition. This conclusion is potentially confused by (a) the existence of patient groups with semantic impairment following damage to other brain regions (semantic dementia and…

Hierarchical Semantic Model of Geovideo

Directory of Open Access Journals (Sweden)

XIE Xiao

2015-05-01

Full Text Available The public security incidents were getting increasingly challenging with regard to their new features, including multi-scale mobility, multistage dynamic evolution, as well as spatiotemporal concurrency and uncertainty in the complex urban environment. However, the existing video models, which were used/designed for independent archive or local analysis of surveillance video, have seriously inhibited emergency response to the urgent requirements.Aiming at the explicit representation of change mechanism in video, the paper proposed a novel hierarchical geovideo semantic model using UML. This model was characterized by the hierarchical representation of both data structure and semantics based on the change-oriented three domains (feature domain, process domain and event domain instead of overall semantic description of video streaming; combining both geographical semantics and video content semantics, in support of global semantic association between multiple geovideo data. The public security incidents by video surveillance are inspected as an example to illustrate the validity of this model.

Applying homotopy analysis method for solving differential-difference equation

International Nuclear Information System (INIS)

Wang Zhen; Zou Li; Zhang Hongqing

2007-01-01

In this Letter, we apply the homotopy analysis method to solving the differential-difference equations. A simple but typical example is applied to illustrate the validity and the great potential of the generalized homotopy analysis method in solving differential-difference equation. Comparisons are made between the results of the proposed method and exact solutions. The results show that the homotopy analysis method is an attractive method in solving the differential-difference equations

Mapping the Structure of Semantic Memory

Science.gov (United States)

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…

Causality in the semantics of Esterel : revisited

NARCIS (Netherlands)

Mousavi, M.R.; Klin, B.; Sobocinski, P.

2010-01-01

We re-examine the challenges concerning causality in the semantics of Esterel and show that they pertain to the known issues in the semantics of Structured Operational Semantics with negative premises. We show that the solutions offered for the semantics of SOS also provide answers to the semantic

Observer Bias: An Interaction of Temperament Traits with Biases in the Semantic Perception of Lexical Material

Science.gov (United States)

Trofimova, Ira

2014-01-01

The lexical approach is a method in differential psychology that uses people's estimations of verbal descriptors of human behavior in order to derive the structure of human individuality. The validity of the assumptions of this method about the objectivity of people's estimations is rarely questioned. Meanwhile the social nature of language and the presence of emotionality biases in cognition are well-recognized in psychology. A question remains, however, as to whether such an emotionality-capacities bias is strong enough to affect semantic perception of verbal material. For the lexical approach to be valid as a method of scientific investigations, such biases should not exist in semantic perception of the verbal material that is used by this approach. This article reports on two studies investigating differences between groups contrasted by 12 temperament traits (i.e. by energetic and other capacities, as well as emotionality) in the semantic perception of very general verbal material. Both studies contrasted the groups by a variety of capacities: endurance, lability and emotionality separately in physical, social-verbal and mental aspects of activities. Hypotheses of “background emotionality” and a “projection through capacities” were supported. Non-evaluative criteria for categorization (related to complexity, organization, stability and probability of occurrence of objects) followed the polarity of evaluative criteria, and did not show independence from this polarity. Participants with stronger physical or social endurance gave significantly more positive ratings to a variety of concepts, and participants with faster physical tempo gave more positive ratings to timing-related concepts. The results suggest that people's estimations of lexical material related to human behavior have emotionality, language- and dynamical capacities-related biases and therefore are unreliable. This questions the validity of the lexical approach as a method for the objective

Semantic Representatives of the Concept

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Elena N. Tsay

2013-01-01

Full Text Available In the article concept as one of the principle notions of cognitive linguistics is investigated. Considering concept as culture phenomenon, having language realization and ethnocultural peculiarities, the description of the concept “happiness” is presented. Lexical and semantic paradigm of the concept of happiness correlates with a great number of lexical and semantic variants. In the work semantic representatives of the concept of happiness, covering supreme spiritual values are revealed and semantic interpretation of their functioning in the Biblical discourse is given.

System semantics of explanatory dictionaries

Directory of Open Access Journals (Sweden)

Volodymyr Shyrokov

2015-11-01

Full Text Available System semantics of explanatory dictionaries Some semantic properties of the language to be followed from the structure of lexicographical systems of big explanatory dictionaries are considered. The hyperchains and hypercycles are determined as the definite kind of automorphisms of the lexicographical system of explanatory dictionary. Some semantic consequencies following from the principles of lexicographic closure and lexicographic completeness are investigated using the hyperchains and hypercycles formalism. The connection between the hypercyle properties of the lexicographical system semantics and Goedel’s incompleteness theorem is discussed.

A Semantic Approach for Recommendations generation: some Cultural Heritage applications

Directory of Open Access Journals (Sweden)

Maurizio De Tommasi

2011-12-01

Full Text Available EnThe growing availability of data in the information systems has raised the challenging problem of distinguishing between the resources that belong to the same information context. Starting from the hypothesis that the information system is based on Semantic Web technologies, is it possible to use these technologies to make an information system more adaptive to user requirements in order to enable personalization and differentiation mechanisms in the information delivery process?This paper proposes an approach to building recommendations by using Semantic Web technologies, in order to give the users a different access to the information. The outcome is a semantic recommender engine, capable of retrieving and ranking semantically annotated resources, by using a set of domain ontologies and a semantic matching algorithm. We are showing some applications of this model in the Cultural Heritage domain in which the presented approach seems to be particularly effective, due to the richness of semantic structures and models existing for such domain.ItLa crescente quantità di dati disponibili da parte dei sistemi informativi ha sollevato il complesso problema della distinzione tra risorse appartenenti allo stesso contesto informativo. Partendo dall'ipotesi che il sistema informativo si basi sulle tecnologie proprie del Web Semantico, è possibile utilizzare tali tecnologie per rendere il sistema adattivo ai requisiti dell'utente, abilitando, in questo modo, meccanismi di personalizzazione e differenziazione?Questo articolo propone un approccio per la generazione di recommendation,  utilizzando le tecnologie del Web Semantico, al fine di fornire, ai singoli utenti, accessi differenziati alle informazioni. Il risultato è un motore di generazione di recommendation semantiche, in grado di recuperare e classificare risorse annotate semanticamente, avvalendosi di un set di ontologie di dominio e di un algoritmo di matching semantico. Saranno

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

Science.gov (United States)

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

The Semantic Web Revisited

OpenAIRE

Shadbolt, Nigel; Berners-Lee, Tim; Hall, Wendy

2006-01-01

The original Scientific American article on the Semantic Web appeared in 2001. It described the evolution of a Web that consisted largely of documents for humans to read to one that included data and information for computers to manipulate. The Semantic Web is a Web of actionable information--information derived from data through a semantic theory for interpreting the symbols.This simple idea, however, remains largely unrealized. Shopbots and auction bots abound on the Web, but these are esse...

Semantic Search of Web Services

Science.gov (United States)

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…

Semantic technologies in a decision support system

Science.gov (United States)

Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2015-10-01

The aim of our work is to design a decision support system based on ontological representation of domain(s) and semantic technologies. Specifically, we consider the case when Grid / Cloud user describes his/her requirements regarding a "resource" as a class expression from an ontology, while the instances of (the same) ontology represent available resources. The goal is to help the user to find the best option with respect to his/her requirements, while remembering that user's knowledge may be "limited." In this context, we discuss multiple approaches based on semantic data processing, which involve different "forms" of user interaction with the system. Specifically, we consider: (a) ontological matchmaking based on SPARQL queries and class expression, (b) graph-based semantic closeness of instances representing user requirements (constructed from the class expression) and available resources, and (c) multicriterial analysis based on the AHP method, which utilizes expert domain knowledge (also ontologically represented).

Classification with an edge: Improving semantic image segmentation with boundary detection

Science.gov (United States)

Marmanis, D.; Schindler, K.; Wegner, J. D.; Galliani, S.; Datcu, M.; Stilla, U.

2018-01-01

We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art methods rely on DCNNs as their workhorse. A major reason for their success is that deep networks learn to accumulate contextual information over very large receptive fields. However, this success comes at a cost, since the associated loss of effective spatial resolution washes out high-frequency details and leads to blurry object boundaries. Here, we propose to counter this effect by combining semantic segmentation with semantically informed edge detection, thus making class boundaries explicit in the model. First, we construct a comparatively simple, memory-efficient model by adding boundary detection to the SEGNET encoder-decoder architecture. Second, we also include boundary detection in FCN-type models and set up a high-end classifier ensemble. We show that boundary detection significantly improves semantic segmentation with CNNs in an end-to-end training scheme. Our best model achieves >90% overall accuracy on the ISPRS Vaihingen benchmark.

Latent semantic analysis.

Science.gov (United States)

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. © 2013 John Wiley & Sons, Ltd.

SCC: Semantic Context Cascade for Efficient Action Detection

KAUST Repository

Heilbron, Fabian Caba

2017-11-09

Despite the recent advances in large-scale video analysis, action detection remains as one of the most challenging unsolved problems in computer vision. This snag is in part due to the large volume of data that needs to be analyzed to detect actions in videos. Existing approaches have mitigated the computational cost, but still, these methods lack rich high-level semantics that helps them to localize the actions quickly. In this paper, we introduce a Semantic Cascade Context (SCC) model that aims to detect action in long video sequences. By embracing semantic priors associated with human activities, SCC produces high-quality class-specific action proposals and prune unrelated activities in a cascade fashion. Experimental results in ActivityNet unveils that SCC achieves state-of-the-art performance for action detection while operating at real time.

Influence of aging on the neural correlates of autobiographical, episodic, and semantic memory retrieval.

Science.gov (United States)

St-Laurent, Marie; Abdi, Hervé; Burianová, Hana; Grady, Cheryl L

2011-12-01

We used fMRI to assess the neural correlates of autobiographical, semantic, and episodic memory retrieval in healthy young and older adults. Participants were tested with an event-related paradigm in which retrieval demand was the only factor varying between trials. A spatio-temporal partial least square analysis was conducted to identify the main patterns of activity characterizing the groups across conditions. We identified brain regions activated by all three memory conditions relative to a control condition. This pattern was expressed equally in both age groups and replicated previous findings obtained in a separate group of younger adults. We also identified regions whose activity differentiated among the different memory conditions. These patterns of differentiation were expressed less strongly in the older adults than in the young adults, a finding that was further confirmed by a barycentric discriminant analysis. This analysis showed an age-related dedifferentiation in autobiographical and episodic memory tasks but not in the semantic memory task or the control condition. These findings suggest that the activation of a common memory retrieval network is maintained with age, whereas the specific aspects of brain activity that differ with memory content are more vulnerable and less selectively engaged in older adults. Our results provide a potential neural mechanism for the well-known age differences in episodic/autobiographical memory, and preserved semantic memory, observed when older adults are compared with younger adults.

Practical solutions to implementing "Born Semantic" data systems

Science.gov (United States)

Leadbetter, A.; Buck, J. J. H.; Stacey, P.

2015-12-01

The concept of data being "Born Semantic" has been proposed in recent years as a Semantic Web analogue to the idea of data being "born digital"[1], [2]. Within the "Born Semantic" concept, data are captured digitally and at a point close to the time of creation are annotated with markup terms from semantic web resources (controlled vocabularies, thesauri or ontologies). This allows heterogeneous data to be more easily ingested and amalgamated in near real-time due to the standards compliant annotation of the data. In taking the "Born Semantic" proposal from concept to operation, a number of difficulties have been encountered. For example, although there are recognised methods such as Header, Dictionary, Triples [3] for the compression, publication and dissemination of large volumes of triples these systems are not practical to deploy in the field on low-powered (both electrically and computationally) devices. Similarly, it is not practical for instruments to output fully formed semantically annotated data files if they are designed to be plugged into a modular system and the data to be centrally logged in the field as is the case on Argo floats and oceanographic gliders where internal bandwidth becomes an issue [2]. In light of these issues, this presentation will concentrate on pragmatic solutions being developed to the problem of generating Linked Data in near real-time systems. Specific examples from the European Commission SenseOCEAN project where Linked Data systems are being developed for autonomous underwater platforms, and from work being undertaken in the streaming of data from the Irish Galway Bay Cable Observatory initiative will be highlighted. Further, developments of a set of tools for the LogStash-ElasticSearch software ecosystem to allow the storing and retrieval of Linked Data will be introduced. References[1] A. Leadbetter & J. Fredericks, We have "born digital" - now what about "born semantic"?, European Geophysical Union General Assembly, 2014

Graph-Based Methods for Discovery Browsing with Semantic Predications

DEFF Research Database (Denmark)

Wilkowski, Bartlomiej; Fiszman, Marcelo; Miller, Christopher M

2011-01-01

. Poorly understood relationships may be explored through novel points of view, and potentially interesting relationships need not be known ahead of time. In a process of "cooperative reciprocity" the user iteratively focuses system output, thus controlling the large number of relationships often generated...... in literature-based discovery systems. The underlying technology exploits SemRep semantic predications represented as a graph of interconnected nodes (predication arguments) and edges (predicates). The system suggests paths in this graph, which represent chains of relationships. The methodology is illustrated...

Semantic dementia without surface dyslexia in Spanish: unimpaired reading with impaired semantics.

Science.gov (United States)

Wilson, Maximiliano A; Martínez-Cuitiño, Macarena

2012-01-01

Surface dyslexia has been attributed to an overreliance on the sub-lexical route for reading. Typically, surface dyslexic patients commit regularisation errors when reading irregular words. Also, semantic dementia has often been associated with surface dyslexia, leading to some explanations of the reading impairment that stress the role of semantics in irregular word reading. Nevertheless, some patients have been reported with unimpaired ability to read irregular words, even though they show severe comprehension impairment. We present the case of M.B., the first Spanish-speaking semantic dementia patient to be reported who shows unimpaired reading of non-words, regular words, and - most strikingly - irregular loan words. M.B. has severely impaired comprehension of the same words he reads correctly (whether regular or irregular). We argue that M.B.'s pattern of performance shows that irregular words can be correctly read even with impaired semantic knowledge corresponding to those words.

A Semantic Constraint on Syntactic Parsing.

Science.gov (United States)

Crain, Stephen; Coker, Pamela L.

This research examines how semantic information influences syntactic parsing decisions during sentence processing. In the first experiment, subjects were presented lexical strings having syntactically identical surface structures but with two possible underlying structures: "The children taught by the Berlitz method," and "The…

A shortest-path graph kernel for estimating gene product semantic similarity

Directory of Open Access Journals (Sweden)

Alvarez Marco A

2011-07-01

Full Text Available Abstract Background Existing methods for calculating semantic similarity between gene products using the Gene Ontology (GO often rely on external resources, which are not part of the ontology. Consequently, changes in these external resources like biased term distribution caused by shifting of hot research topics, will affect the calculation of semantic similarity. One way to avoid this problem is to use semantic methods that are "intrinsic" to the ontology, i.e. independent of external knowledge. Results We present a shortest-path graph kernel (spgk method that relies exclusively on the GO and its structure. In spgk, a gene product is represented by an induced subgraph of the GO, which consists of all the GO terms annotating it. Then a shortest-path graph kernel is used to compute the similarity between two graphs. In a comprehensive evaluation using a benchmark dataset, spgk compares favorably with other methods that depend on external resources. Compared with simUI, a method that is also intrinsic to GO, spgk achieves slightly better results on the benchmark dataset. Statistical tests show that the improvement is significant when the resolution and EC similarity correlation coefficient are used to measure the performance, but is insignificant when the Pfam similarity correlation coefficient is used. Conclusions Spgk uses a graph kernel method in polynomial time to exploit the structure of the GO to calculate semantic similarity between gene products. It provides an alternative to both methods that use external resources and "intrinsic" methods with comparable performance.

A generalized notion of semantic independence

DEFF Research Database (Denmark)

Fränzle, Martin; Stengel, Bernhard von; Wittmüss, Arne

1995-01-01

For programs represented semantically as relations, a concept of semantic independence is defined that is more general than previously stated notions. It allows for shared input variables and irrelevant interference due to nondeterminism.......For programs represented semantically as relations, a concept of semantic independence is defined that is more general than previously stated notions. It allows for shared input variables and irrelevant interference due to nondeterminism....

The Semantic Web: From Representation to Realization

Science.gov (United States)

Thórisson, Kristinn R.; Spivack, Nova; Wissner, James M.

A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.

Comparing Refinements for Failure and Bisimulation Semantics

NARCIS (Netherlands)

Eshuis, H.; Fokkinga, M.M.

2002-01-01

Refinement in bisimulation semantics is defined differently from refinement in failure semantics: in bisimulation semantics refinement is based on simulations between labelled transition systems, whereas in failure semantics refinement is based on inclusions between failure systems. There exist

Bayesian natural language semantics and pragmatics

CERN Document Server

Zeevat, Henk

2015-01-01

The contributions in this volume focus on the Bayesian interpretation of natural languages, which is widely used in areas of artificial intelligence, cognitive science, and computational linguistics. This is the first volume to take up topics in Bayesian Natural Language Interpretation and make proposals based on information theory, probability theory, and related fields. The methodologies offered here extend to the target semantic and pragmatic analyses of computational natural language interpretation. Bayesian approaches to natural language semantics and pragmatics are based on methods from signal processing and the causal Bayesian models pioneered by especially Pearl. In signal processing, the Bayesian method finds the most probable interpretation by finding the one that maximizes the product of the prior probability and the likelihood of the interpretation. It thus stresses the importance of a production model for interpretation as in Grice's contributions to pragmatics or in interpretation by abduction.

Semantics-based Automated Web Testing

Directory of Open Access Journals (Sweden)

Hai-Feng Guo

2015-08-01

Full Text Available We present TAO, a software testing tool performing automated test and oracle generation based on a semantic approach. TAO entangles grammar-based test generation with automated semantics evaluation using a denotational semantics framework. We show how TAO can be incorporated with the Selenium automation tool for automated web testing, and how TAO can be further extended to support automated delta debugging, where a failing web test script can be systematically reduced based on grammar-directed strategies. A real-life parking website is adopted throughout the paper to demonstrate the effectivity of our semantics-based web testing approach.

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

Science.gov (United States)

Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok

2015-01-01

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

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

Directory of Open Access Journals (Sweden)

Minwoo Ryu

2015-01-01

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

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

Science.gov (United States)

Ryu, Minwoo; Kim, Jaeho; Yun, Jaeseok

2015-01-19

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

Benchmarking semantic web technology

CERN Document Server

García-Castro, R

2009-01-01

This book addresses the problem of benchmarking Semantic Web Technologies; first, from a methodological point of view, proposing a general methodology to follow in benchmarking activities over Semantic Web Technologies and, second, from a practical point of view, presenting two international benchmarking activities that involved benchmarking the interoperability of Semantic Web technologies using RDF(S) as the interchange language in one activity and OWL in the other.The book presents in detail how the different resources needed for these interoperability benchmarking activities were defined:

Numerov iteration method for second order integral-differential equation

International Nuclear Information System (INIS)

Zeng Fanan; Zhang Jiaju; Zhao Xuan

1987-01-01

In this paper, Numerov iterative method for second order integral-differential equation and system of equations are constructed. Numerical examples show that this method is better than direct method (Gauss elimination method) in CPU time and memoy requireing. Therefore, this method is an efficient method for solving integral-differential equation in nuclear physics

Semantic Web and Contextual Information: Semantic Network Analysis of Online Journalistic Texts

Science.gov (United States)

Lim, Yon Soo

This study examines why contextual information is important to actualize the idea of semantic web, based on a case study of a socio-political issue in South Korea. For this study, semantic network analyses were conducted regarding English-language based 62 blog posts and 101 news stories on the web. The results indicated the differences of the meaning structures between blog posts and professional journalism as well as between conservative journalism and progressive journalism. From the results, this study ascertains empirical validity of current concerns about the practical application of the new web technology, and discusses how the semantic web should be developed.

Inducing and assessing differentiated emotion-feeling states in the laboratory.

Science.gov (United States)

Philippot, P

1993-03-01

Two questions are addressed. The first question pertains to the capacity of film segments to induce emotional states that are: (a) as comparable as possible to naturally occurring emotions; (b) similar across individuals; and (c) clearly differentiated across the intended emotions. The second question concerns the discriminant capacity of self-report questionnaires of emotion-feeling states differing in their theoretical assumptions. Subjects viewed six short film segments and rated the strength of their responses on one of three kinds of questionnaires. The questionnaires were: (1) the Differential Emotions Scale that postulates category-based distinctions between emotions; (2) the Semantic Differential that postulates that emotions are distinguished along bipolar dimensions; and (3) free labelling of their feelings by the subjects (control condition with no theoretical a priori). Overall, results indicate that film segments can elicit a diversity of predictable emotions, in the same way, in a majority of individuals. In the present procedure, the Differential Emotions Scale yielded a better discrimination between emotional states than the Semantic Differential. Implications for emotion research and theories of the cognitive structure of emotion are discussed.

Semantic Keys and Reading

Directory of Open Access Journals (Sweden)

Zev bar-Lev

2016-12-01

Full Text Available Semantic Keys are elements (word-parts of written language that give an iconic, general representation of the whole word’s meaning. In written Sino-Japanese the “radical” or semantic components play this role. For example, the character meaning ‘woman, female’ is the Semantic Key of the character for Ma ‘Mama’ (alongside the phonetic component Ma, which means ‘horse’ as a separate character. The theory of semantic Keys in both graphic and phonemic aspects is called qTheory or nanosemantics. The most innovative aspect of the present article is the hypothesis that, in languages using alphabetic writing systems, the role of Semantic Key is played by consonants, more specifically the first consonant. Thus, L meaning ‘LIFT’ is the Semantic Key of English Lift, Ladle, Lofty, aLps, eLevator, oLympus; Spanish Leva, Lecantarse, aLto, Lengua; Arabic aLLah, and Hebrew① ªeL-ºaL ‘upto-above’ (the Israeli airline, Polish Lot ‘flight’ (the Polish airline; Hebrew ªeL, ªeLohim ‘God’, and haLLeluyah ‘praise-ye God’ (using Parallels, ‘Lift up God’. Evidence for the universality of the theory is shown by many examples drawn from various languages, including Indo-European Semitic, Chinese and Japanese. The theory reveals hundreds of relationships within and between languages, related and unrelated, that have been “Hiding in Plain Sight”, to mention just one example: the Parallel between Spanish Pan ‘bread’ and Mandarin Fan ‘rice’.

Interpreting semantic clustering effects in free recall.

Science.gov (United States)

Manning, Jeremy R; Kahana, Michael J

2012-07-01

The order in which participants choose to recall words from a studied list of randomly selected words provides insights into how memories of the words are represented, organised, and retrieved. One pervasive finding is that when a pair of semantically related words (e.g., "cat" and "dog") is embedded in the studied list, the related words are often recalled successively. This tendency to successively recall semantically related words is termed semantic clustering (Bousfield, 1953; Bousfield & Sedgewick, 1944; Cofer, Bruce, & Reicher, 1966). Measuring semantic clustering effects requires making assumptions about which words participants consider to be similar in meaning. However, it is often difficult to gain insights into individual participants' internal semantic models, and for this reason researchers typically rely on standardised semantic similarity metrics. Here we use simulations to gain insights into the expected magnitudes of semantic clustering effects given systematic differences between participants' internal similarity models and the similarity metric used to quantify the degree of semantic clustering. Our results provide a number of useful insights into the interpretation of semantic clustering effects in free recall.

Snapshots for Semantic Maps

National Research Council Canada - National Science Library

Nielsen, Curtis W; Ricks, Bob; Goodrich, Michael A; Bruemmer, David; Few, Doug; Walton, Miles

2004-01-01

.... Semantic maps are a relatively new approach to information presentation. Semantic maps provide more detail about an environment than typical maps because they are augmented by icons or symbols that provide meaning for places or objects of interest...

Towards Compatible and Interderivable Semantic Specifications for the Scheme Programming Language, Part I: Denotational Semantics, Natural Semantics, and Abstract Machines

DEFF Research Database (Denmark)

Danvy, Olivier

2009-01-01

We derive two big-step abstract machines, a natural semantics, and the valuation function of a denotational semantics based on the small-step abstract machine for Core Scheme presented by Clinger at PLDI'98. Starting from a functional implementation of this small-step abstract machine, (1) we fus...

A French Translation of the Pleasure Arousal Dominance (PAD Semantic Differential Scale for the Measure of Affect and Drive

Directory of Open Access Journals (Sweden)

Sandrine Detandt

2017-03-01

Full Text Available Multivariate studies have repeatedly confirmed that three basic dimensions of human emotional behavior, called 'pleasure' (P, 'arousal' (A and 'dominance '(D are persistent in organizing human judgments for a wide range of perceptual and symbolic stimuli. The Mehrabian and Russell’s PAD semantic differential scale is a well-established tool to measure these categories, but no standardized French translation is available for research. The aim of this study was to validate a French version of the PAD. For this purpose, (1 Mehrabian and Russell’s PAD was trans- lated through a process of translations and back-translations and (2 this French PAD was tested in a population of 111 French-speaking adults on 21 images of the International Affective Picture System (IAPS. A confirmatory factor analysis revealed the expected three-factor structure; the French PAD also distributed the images in the affective space according to the expected boomerang-shape. The present version of PAD is thus a valid French translation of Mehrabian and Russell’s original PAD.

Thai Language Sentence Similarity Computation Based on Syntactic Structure and Semantic Vector

Science.gov (United States)

Wang, Hongbin; Feng, Yinhan; Cheng, Liang

2018-03-01

Sentence similarity computation plays an increasingly important role in text mining, Web page retrieval, machine translation, speech recognition and question answering systems. Thai language as a kind of resources scarce language, it is not like Chinese language with HowNet and CiLin resources. So the Thai sentence similarity research faces some challenges. In order to solve this problem of the Thai language sentence similarity computation. This paper proposes a novel method to compute the similarity of Thai language sentence based on syntactic structure and semantic vector. This method firstly uses the Part-of-Speech (POS) dependency to calculate two sentences syntactic structure similarity, and then through the word vector to calculate two sentences semantic similarity. Finally, we combine the two methods to calculate two Thai language sentences similarity. The proposed method not only considers semantic, but also considers the sentence syntactic structure. The experiment result shows that this method in Thai language sentence similarity computation is feasible.

When emotional prosody and semantics dance cheek to cheek: ERP evidence.

Science.gov (United States)

Kotz, Sonja A; Paulmann, Silke

2007-06-02

To communicate emotionally entails that a listener understands a verbal message but also the emotional prosody going along with it. So far the time course and interaction of these emotional 'channels' is still poorly understood. The current set of event-related brain potential (ERP) experiments investigated both the interactive time course of emotional prosody with semantics and of emotional prosody independent of emotional semantics using a cross-splicing method. In a probe verification task (Experiment 1) prosodic expectancy violations elicited a positivity, while a combined prosodic-semantic expectancy violation elicited a negativity. Comparable ERP results were obtained in an emotional prosodic categorization task (Experiment 2). The present data support different ERP responses with distinct time courses and topographies elicited as a function of prosodic expectancy and combined prosodic-semantic expectancy during emotional prosodic processing and combined emotional prosody/emotional semantic processing. These differences suggest that the interaction of more than one emotional channel facilitates subtle transitions in an emotional sentence context.

Examining lateralized semantic access using pictures.

Science.gov (United States)

Lovseth, Kyle; Atchley, Ruth Ann

2010-03-01

A divided visual field (DVF) experiment examined the semantic processing strategies employed by the cerebral hemispheres to determine if strategies observed with written word stimuli generalize to other media for communicating semantic information. We employed picture stimuli and vary the degree of semantic relatedness between the picture pairs. Participants made an on-line semantic relatedness judgment in response to sequentially presented pictures. We found that when pictures are presented to the right hemisphere responses are generally more accurate than the left hemisphere for semantic relatedness judgments for picture pairs. Furthermore, consistent with earlier DVF studies employing words, we conclude that the RH is better at accessing or maintaining access to information that has a weak or more remote semantic relationship. We also found evidence of faster access for pictures presented to the LH in the strongly-related condition. Overall, these results are consistent with earlier DVF word studies that argue that the cerebral hemispheres each play an important and separable role during semantic retrieval. Copyright 2009 Elsevier Inc. All rights reserved.

A Denotational Semantics for Logic Programming

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg

A fully abstract denotational semantics for logic programming has not been constructed yet. In this paper we present a denotational semantics that is almost fully abstract. We take the meaning of a logic program to be an element in a Plotkin power domain of substitutions. In this way our result...... shows that standard domain constructions suffice, when giving a semantics for logic programming. Using the well-known fixpoint semantics of logic programming we have to consider two different fixpoints in order to obtain information about both successful and failed computations. In contrast, our...... semantics is uniform in that the (single) meaning of a logic program contains information about both successful, failed and infinite computations. Finally, based on the full abstractness result, we argue that the detail level of substitutions is needed in any denotational semantics for logic programming....

WEATHER FORECAST DATA SEMANTIC ANALYSIS IN F-LOGIC

Directory of Open Access Journals (Sweden)

Ana Meštrović

2007-06-01

Full Text Available This paper addresses the semantic analysis problem in a spoken dialog system developed for the domain of weather forecasts. The main goal of semantic analysis is to extract the meaning from the spoken utterances and to transform it into a domain database format. In this work a semantic database for the domain of weather forecasts is represented using the F-logic formalism. Semantic knowledge is captured through semantic categories a semantic dictionary using phrases and output templates. Procedures for semantic analysis of Croatian weather data combine parsing techniques for Croatian language and slot filling approach. Semantic analysis is conducted in three phases. In the first phase the main semantic category for the input utterance is determined. The lattices are used for hierarchical semantic relation representation and main category derivation. In the second phase semantic units are analyzed and knowledge slots in the database are filled. Since some slot values of input data are missing in the third phase, incomplete data is updated with missing values. All rules for semantic analysis are defined in the F-logic and implemented using the FLORA-2 system. The results of semantic analysis evaluation in terms of frame and slot error rates are presented.

CASL The Common Algebraic Specification Language Semantics

DEFF Research Database (Denmark)

Haxthausen, Anne

1998-01-01

This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998.......This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the first complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop at Cachan in November 1998....

Semantic Web status model

CSIR Research Space (South Africa)

Gerber, AJ

2006-06-01

Full Text Available Semantic Web application areas are experiencing intensified interest due to the rapid growth in the use of the Web, together with the innovation and renovation of information content technologies. The Semantic Web is regarded as an integrator across...

Autobiographically significant concepts: more episodic than semantic in nature? An electrophysiological investigation of overlapping types of memory.

Science.gov (United States)

Renoult, Louis; Davidson, Patrick S R; Schmitz, Erika; Park, Lillian; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian

2015-01-01

A common assertion is that semantic memory emerges from episodic memory, shedding the distinctive contexts associated with episodes over time and/or repeated instances. Some semantic concepts, however, may retain their episodic origins or acquire episodic information during life experiences. The current study examined this hypothesis by investigating the ERP correlates of autobiographically significant (AS) concepts, that is, semantic concepts that are associated with vivid episodic memories. We inferred the contribution of semantic and episodic memory to AS concepts using the amplitudes of the N400 and late positive component, respectively. We compared famous names that easily brought to mind episodic memories (high AS names) against equally famous names that did not bring such recollections to mind (low AS names) on a semantic task (fame judgment) and an episodic task (recognition memory). Compared with low AS names, high AS names were associated with increased amplitude of the late positive component in both tasks. Moreover, in the recognition task, this effect of AS was highly correlated with recognition confidence. In contrast, the N400 component did not differentiate the high versus low AS names but, instead, was related to the amount of general knowledge participants had regarding each name. These results suggest that semantic concepts high in AS, such as famous names, have an episodic component and are associated with similar brain processes to those that are engaged by episodic memory. Studying AS concepts may provide unique insights into how episodic and semantic memory interact.

A DNA-based semantic fusion model for remote sensing data.

Directory of Open Access Journals (Sweden)

Heng Sun

Full Text Available Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

A DNA-based semantic fusion model for remote sensing data.

Science.gov (United States)

Sun, Heng; Weng, Jian; Yu, Guangchuang; Massawe, Richard H

2013-01-01

Semantic technology plays a key role in various domains, from conversation understanding to algorithm analysis. As the most efficient semantic tool, ontology can represent, process and manage the widespread knowledge. Nowadays, many researchers use ontology to collect and organize data's semantic information in order to maximize research productivity. In this paper, we firstly describe our work on the development of a remote sensing data ontology, with a primary focus on semantic fusion-driven research for big data. Our ontology is made up of 1,264 concepts and 2,030 semantic relationships. However, the growth of big data is straining the capacities of current semantic fusion and reasoning practices. Considering the massive parallelism of DNA strands, we propose a novel DNA-based semantic fusion model. In this model, a parallel strategy is developed to encode the semantic information in DNA for a large volume of remote sensing data. The semantic information is read in a parallel and bit-wise manner and an individual bit is converted to a base. By doing so, a considerable amount of conversion time can be saved, i.e., the cluster-based multi-processes program can reduce the conversion time from 81,536 seconds to 4,937 seconds for 4.34 GB source data files. Moreover, the size of result file recording DNA sequences is 54.51 GB for parallel C program compared with 57.89 GB for sequential Perl. This shows that our parallel method can also reduce the DNA synthesis cost. In addition, data types are encoded in our model, which is a basis for building type system in our future DNA computer. Finally, we describe theoretically an algorithm for DNA-based semantic fusion. This algorithm enables the process of integration of the knowledge from disparate remote sensing data sources into a consistent, accurate, and complete representation. This process depends solely on ligation reaction and screening operations instead of the ontology.

Semantic Memory in the Clinical Progression of Alzheimer Disease.

Science.gov (United States)

Tchakoute, Christophe T; Sainani, Kristin L; Henderson, Victor W

2017-09-01

Semantic memory measures may be useful in tracking and predicting progression of Alzheimer disease. We investigated relationships among semantic memory tasks and their 1-year predictive value in women with Alzheimer disease. We conducted secondary analyses of a randomized clinical trial of raloxifene in 42 women with late-onset mild-to-moderate Alzheimer disease. We assessed semantic memory with tests of oral confrontation naming, category fluency, semantic recognition and semantic naming, and semantic density in written narrative discourse. We measured global cognition (Alzheimer Disease Assessment Scale, cognitive subscale), dementia severity (Clinical Dementia Rating sum of boxes), and daily function (Activities of Daily Living Inventory) at baseline and 1 year. At baseline and 1 year, most semantic memory scores correlated highly or moderately with each other and with global cognition, dementia severity, and daily function. Semantic memory task performance at 1 year had worsened one-third to one-half standard deviation. Factor analysis of baseline test scores distinguished processes in semantic and lexical retrieval (semantic recognition, semantic naming, confrontation naming) from processes in lexical search (semantic density, category fluency). The semantic-lexical retrieval factor predicted global cognition at 1 year. Considered separately, baseline confrontation naming and category fluency predicted dementia severity, while semantic recognition and a composite of semantic recognition and semantic naming predicted global cognition. No individual semantic memory test predicted daily function. Semantic-lexical retrieval and lexical search may represent distinct aspects of semantic memory. Semantic memory processes are sensitive to cognitive decline and dementia severity in Alzheimer disease.

THE USE OF METHODS OF PSYCHOSEMANTICS FOR THE EXAMINATION OF VALUE-SEMANTIC SPHERE OF ADOLESCENTS PRONE TO DRUG-ADDICTED BEHAVIOR

Directory of Open Access Journals (Sweden)

A S Markov

2015-12-01

Full Text Available The article considers the problem of using methods of psychosemantics for the examination of value- semantic sphere of adolescents who are prone to drug-addicted behavior. As a diagnostic tool for this task there was used the psychosemantic approach which gives the opportunity to uncover the subjective picture of the world of the teenager, a member of the risk group, his verbal and graphical constructs.At the first stage of the study, with the help of the proprietary methodology of working scales (motivational- need sphere, emotionally-conative sphere, the sphere of normative and behavioral regulation, the scale of the social risks, value-semantic sphere the personal profiles of adolescents are prone to drug-addicted behavior were identified and described. As part of the description of the personality profiles, the peculiarities of the drug-addicted behavior were also disclosed.The psychosemantic approach applied at the second stage of the empirical research, with the help of the modified role list given to the respondents, allowed to make and characterize the resulting model maps of the subjective semantic space of the teenagers at risk. The above mentioned model maps reflect the subjective value-semantic sphere, the existing correlation between the formed socially approved and also risk-taking role positions, and the internal picture of the world of the adolescents prone to drug-addicted behavior. The study results give the opportunity to improve the preventive and remedial work with adolescents, prone to drug-addicted behavior in the educational environment

A Semantics for Distributed Execution of Statemate

DEFF Research Database (Denmark)

Fränzle, Martin; Niehaus, Jürgen; Metzner, Alexander

2003-01-01

We present a semantics for the statechart variant implemented in the Statemate product of i-Logix. Our semantics enables distributed code generation for Statemate models in the context of rapid prototyping for embedded control applications. We argue that it seems impossible to efficiently generate......, the changes made regarding the interaction of distributed model parts are similar to the interaction between the model and its environment in the original semantics, thus giving designers a familiar execution model. The semantics has been implemented in Grace, a framework for rapid prototyping code generation...... distributed code using the original Statemate semantics. The new, distributed semantics has the advantages that, first, it enables the generation of efficient distributed code, second, it preserves many aspects of the original semantics for those parts of a model that are not distributed, and third...

Numerical methods for differential equations and applications

International Nuclear Information System (INIS)

Ixaru, L.G.

1984-01-01

This book is addressed to persons who, without being professionals in applied mathematics, are often faced with the problem of numerically solving differential equations. In each of the first three chapters a definite class of methods is discussed for the solution of the initial value problem for ordinary differential equations: multistep methods; one-step methods; and piecewise perturbation methods. The fourth chapter is mainly focussed on the boundary value problems for linear second-order equations, with a section devoted to the Schroedinger equation. In the fifth chapter the eigenvalue problem for the radial Schroedinger equation is solved in several ways, with computer programs included. (Auth.)

Quality of semantic standards

NARCIS (Netherlands)

Folmer, Erwin Johan Albert

2012-01-01

Little scientific literature addresses the issue of quality of semantic standards, albeit a problem with high economic and social impact. Our problem survey, including 34 semantic Standard Setting Organizations (SSOs), gives evidence that quality of standards can be improved, but for improvement a

The inferior, anterior temporal lobes and semantic memory clarified: novel evidence from distortion-corrected fMRI.

Science.gov (United States)

Visser, M; Embleton, K V; Jefferies, E; Parker, G J; Ralph, M A Lambon

2010-05-01

The neural basis of semantic memory generates considerable debate. Semantic dementia results from bilateral anterior temporal lobe (ATL) atrophy and gives rise to a highly specific impairment of semantic memory, suggesting that this region is a critical neural substrate for semantic processing. Recent rTMS experiments with neurologically-intact participants also indicate that the ATL are a necessary substrate for semantic memory. Exactly which regions within the ATL are important for semantic memory are difficult to detect from these methods (because the damage in SD covers a large part of the ATL). Functional neuroimaging might provide important clues about which specific areas exhibit activation that correlates with normal semantic performance. Neuroimaging studies, however, have not consistently found anterior temporal lobe activation in semantic tasks. A recent meta-analysis indicates that this inconsistency may be due to a collection of technical limitations associated with previous studies, including a reduced field-of-view and magnetic susceptibility artefacts associated with standard gradient echo fMRI. We conducted an fMRI study of semantic memory using a combination of techniques which improve sensitivity to ATL activations whilst preserving whole-brain coverage. As expected from SD patients and ATL rTMS experiments, this method revealed bilateral temporal activation extending from the inferior temporal lobe along the fusiform gyrus to the anterior temporal regions, bilaterally. We suggest that the inferior, anterior temporal lobe region makes a crucial contribution to semantic cognition and utilising this version of fMRI will enable further research on the semantic role of the ATL. 2010 Elsevier Ltd. All rights reserved.

Morphological Cues for Lexical Semantics

National Research Council Canada - National Science Library

Light, Marc

1996-01-01

Most natural language processing tasks require lexical semantic information such as verbal argument structure and selectional restrictions, corresponding nominal semantic class, verbal aspectual class...

Application of Legendre spectral-collocation method to delay differential and stochastic delay differential equation

Science.gov (United States)

Khan, Sami Ullah; Ali, Ishtiaq

2018-03-01

Explicit solutions to delay differential equation (DDE) and stochastic delay differential equation (SDDE) can rarely be obtained, therefore numerical methods are adopted to solve these DDE and SDDE. While on the other hand due to unstable nature of both DDE and SDDE numerical solutions are also not straight forward and required more attention. In this study, we derive an efficient numerical scheme for DDE and SDDE based on Legendre spectral-collocation method, which proved to be numerical methods that can significantly speed up the computation. The method transforms the given differential equation into a matrix equation by means of Legendre collocation points which correspond to a system of algebraic equations with unknown Legendre coefficients. The efficiency of the proposed method is confirmed by some numerical examples. We found that our numerical technique has a very good agreement with other methods with less computational effort.

On the Existence of Semantic Working Memory: Evidence for Direct Semantic Maintenance

Science.gov (United States)

Shivde, Geeta; Anderson, Michael C.

2011-01-01

Despite widespread acknowledgment of the importance of online semantic maintenance, there has been astonishingly little work that clearly establishes this construct. We review the extant work relevant to short-term retention of meaning and show that, although consistent with semantic working memory, most data can be accommodated in other ways.…

Cognitive semantic networks: emotional verbs throw a tantrum but don't bite

DEFF Research Database (Denmark)

Petersen, Michael Kai; Hansen, Lars Kai

2012-01-01

Neuroimaging studies have over the past decades established that language is grounded in sensorimotor areas of the brain. The same neuronal circuits seem involved whether we literally pick up a ball or in a phrase refer to grasping an idea. However recent findings have demonstrated that not only ...... semantic analysis, multidimensional scaling, hierarchical clustering and network graph analysis to quantify their interaction and identify parameters of force and spatial differentiation which we propose cognitively relate emotions to sensorimotor action schemas....... leg, hand and face related but also emotional action verbs activate premotor systems in the brain. Hypothesizing that the force and spatial parameters which define action based language might also be reflected in the latent semantics of words, we select motor and emotion related verbs and apply latent...

Semantic Coherence Facilitates Distributional Learning.

Science.gov (United States)

Ouyang, Long; Boroditsky, Lera; Frank, Michael C

2017-04-01

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.

Semantic Query Processing : Estimating Relational Purity

NARCIS (Netherlands)

Kalo, Jan-Christoph; Lofi, C.; Maseli, René Pascal; Balke, Wolf-Tilo; Leyer, M.

2017-01-01

The use of semantic information found in structured knowledge bases has become an integral part of the processing pipeline of modern intelligent in-
formation systems. However, such semantic information is frequently insuffi-cient to capture the rich semantics demanded by the applications, and

Pragmatics for formal semantics

DEFF Research Database (Denmark)

Danvy, Olivier

2011-01-01

This tech talk describes how to write and how to inter-derive formal semantics for sequential programming languages. The progress reported here is (1) concrete guidelines to write each formal semantics to alleviate their proof obligations, and (2) simple calculational tools to obtain a formal...

A reasonable Semantic Web

NARCIS (Netherlands)

Hitzler, Pascal; Van Harmelen, Frank

2010-01-01

The realization of Semantic Web reasoning is central to substantiating the Semantic Web vision. However, current mainstream research on this topic faces serious challenges, which forces us to question established lines of research and to rethink the underlying approaches. We argue that reasoning for

Episodic memory, semantic memory, and amnesia.

Science.gov (United States)

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.

Gricean Semantics and Vague Speaker-Meaning

OpenAIRE

Schiffer, Stephen

2017-01-01

Presentations of Gricean semantics, including Stephen Neale’s in “Silent Reference,” totally ignore vagueness, even though virtually every utterance is vague. I ask how Gricean semantics might be adjusted to accommodate vague speaker-meaning. My answer is that it can’t accommodate it: the Gricean program collapses in the face of vague speaker-meaning. The Gricean might, however, fi nd some solace in knowing that every other extant meta-semantic and semantic program is in the same boat.

Modeling the Interaction Between Semantic Agents and Semantic Web Services Using MDA Approach

NARCIS (Netherlands)

Kardas, Geylani; Göknil, Arda; Dikenelli, Oguz; Topaloglu, N. Yasemin

2007-01-01

In this paper, we present our metamodeling approach for integrating semantic web services and semantic web enabled agents under Model Driven Architecture (MDA) view which defines a conceptual framework to realize model driven development. We believe that agents must have well designed environment

Fully convolutional network with cluster for semantic segmentation

Science.gov (United States)

Ma, Xiao; Chen, Zhongbi; Zhang, Jianlin

2018-04-01

At present, image semantic segmentation technology has been an active research topic for scientists in the field of computer vision and artificial intelligence. Especially, the extensive research of deep neural network in image recognition greatly promotes the development of semantic segmentation. This paper puts forward a method based on fully convolutional network, by cluster algorithm k-means. The cluster algorithm using the image's low-level features and initializing the cluster centers by the super-pixel segmentation is proposed to correct the set of points with low reliability, which are mistakenly classified in great probability, by the set of points with high reliability in each clustering regions. This method refines the segmentation of the target contour and improves the accuracy of the image segmentation.

Differential equations methods and applications

CERN Document Server

Said-Houari, Belkacem

2015-01-01

This book presents a variety of techniques for solving ordinary differential equations analytically and features a wealth of examples. Focusing on the modeling of real-world phenomena, it begins with a basic introduction to differential equations, followed by linear and nonlinear first order equations and a detailed treatment of the second order linear equations. After presenting solution methods for the Laplace transform and power series, it lastly presents systems of equations and offers an introduction to the stability theory. To help readers practice the theory covered, two types of exercises are provided: those that illustrate the general theory, and others designed to expand on the text material. Detailed solutions to all the exercises are included. The book is excellently suited for use as a textbook for an undergraduate class (of all disciplines) in ordinary differential equations. .

A Model for Semantic IS Standards

NARCIS (Netherlands)

Folmer, Erwin Johan Albert; Oude Luttighuis, Paul; van Hillegersberg, Jos

2011-01-01

We argue that, in order to suggest improvements of any kind to semantic information system (IS) standards, better understanding of the conceptual structure of semantic IS standard is required. This study develops a model for semantic IS standard, based on literature and expert knowledge. The model

Probabilistic Latent Semantic Analyses (PLSA in Bibliometric Analysis for Technology Forecasting

Directory of Open Access Journals (Sweden)

Wang Zan

2007-03-01

Full Text Available Due to the availability of internet-based abstract services and patent databases, bibliometric analysis has become one of key technology forecasting approaches. Recently, latent semantic analysis (LSA has been applied to improve the accuracy in document clustering. In this paper, a new LSA method, probabilistic latent semantic analysis (PLSA which uses probabilistic methods and algebra to search latent space in the corpus is further applied in document clustering. The results show that PLSA is more accurate than LSA and the improved iteration method proposed by authors can simplify the computing process and improve the computing efficiency

The Effect of Pinyin Input Experience on the Link Between Semantic and Phonology of Chinese Character in Digital Writing.

Science.gov (United States)

Chen, Jingjun; Luo, Rong; Liu, Huashan

2017-08-01

With the development of ICT, digital writing is becoming much more common in people's life. Differently from keyboarding alphabets directly to input English words, keyboarding Chinese character is always through typing phonetic alphabets and then identify the glyph provided by Pinyin input-method software while in this process which do not need users to produce orthography spelling, thus it is different from traditional written language production model based on handwriting process. Much of the research in this domain has found that using Pinyin input method is beneficial to Chinese characters recognition, but only a small part explored the effects of individual's Pinyin input experience on the Chinese characters production process. We ask whether using Pinyin input-method will strengthen the semantic-phonology linkage or semantic-orthography linkage in Chinese character mental lexicon. Through recording the RT and accuracy of participants completing semantic-syllable and semantic-glyph consistency judgments, the results found the accuracy of semantic-syllable consistency judgments in high Pinyin input experienced group was higher than that in low-experienced group, and RT was reversed. There were no significant differences on semantic-glyph consistency judgments between the two groups. We conclude that using Pinyin input method in Chinese digital writing can strengthen the semantic-phonology linkage while do not weakening the semantic-orthography linkage in mental lexicon at the same time, which means that Pinyin input method is beneficial to lexical processing involving Chinese cognition.

The neural basis for simulated drawing and the semantic implications.

Science.gov (United States)

Harrington, Greg S; Farias, Dana; Davis, Christine H

2009-03-01

This functional magnetic resonance imaging (fMRI) study of the mental simulation of drawing (1) investigated the neural substrates of drawing and (2) delineated the semantic aspects of drawing. The goal was to advance our understanding of how drawing a familiar object is linked to lexical semantics and therefore a viable method to use to rehabilitate aphasia. We hypothesized that the semantic aspects of drawing familiar objects compared to drawing non-objects would yield greater activation in the inferior temporal cortex and the inferior frontal cortex of the left hemisphere. To test this hypothesis, eight right-handed subjects performed an fMRI experiment that directly contrasted drawing familiar objects to non-objects using mental imagery. Simulated drawing recruited a large, distributed network of frontal, parietal, and temporal structures. In the contrast comparing drawing familiar objects to non-objects there was stronger activation in the left hemisphere within the inferior temporal, anterior inferior frontal, inferior parietal and superior frontal cortices. The activation within the inferior temporal cortex was associated with visual semantic processing and semantic mediated naming. We suggest that the anterior inferior frontal activation is linked to the inferior temporal cortex and is involved in the selection of specific semantic features of the object as well as retrieval of information regarding the perceptual aspects of the object.

Interdiscursive Character of Semantic Development of Coreferential Metaphors

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Мансур Фарвазович Гайнаншин

2016-12-01

Full Text Available The article is devoted to establishing the character of semantic development involving coreferential metaphors in interdiscursive space. The solution of this problem is aimed at determining semantic relations between different links in chains made up by a number of coreferential metaphors that share the property of variant imagery nomination. The task is implemented within the boundaries of an interdiscourse viewed as a minimum cultural associative context. Empirical data have been drawn from financial and economic texts in electronic and online versions of leading English mass media resources. The meanings of key language units that underlie metaphoric designations of economic notions are clarified with the help of general English language dictionaries and culturological reference books. The analysis of selected examples is carried out based on componential, contextual, discursive, pragmatic analyses and procedures of semantic interpretation supplemented by linguaculturological methods. The investigation allows us to draw the following conclusions: semantic development of coreferential metaphors occurs on two levels: between variant imagery nominations within metaphorical chains M1 + M2 + M3 + ... Мn and between the head metaphor and submetaphors M1 ® ma + mb + mc +... mn; it has proved the role of interdiscursive contextual relations between metaphors having the same type of reference; it has shown the participation of imagery nominations within coreferential chains in the process of sense profiling; it has demonstrated intensification of semantic tension resulting from metaphoric density in coreferential blocks signaling greater synergetic effect produced on the reader.

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

Science.gov (United States)

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.

Semantic models for adaptive interactive systems

CERN Document Server

Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

2013-01-01

Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

Some Novel Techniques in Operational Semantics

DEFF Research Database (Denmark)

Mosses, Peter David

2003-01-01

Several novel techniques for use in operational semantics are presented. They were developed in connection with a modular vatriant of the conventional Structural Operational Semantics framework, but can also be exploited when modularity is of no great concern. Gives a simple introduction to the m......Several novel techniques for use in operational semantics are presented. They were developed in connection with a modular vatriant of the conventional Structural Operational Semantics framework, but can also be exploited when modularity is of no great concern. Gives a simple introduction...

Real-time object detection and semantic segmentation for autonomous driving

Science.gov (United States)

Li, Baojun; Liu, Shun; Xu, Weichao; Qiu, Wei

2018-02-01

In this paper, we proposed a Highly Coupled Network (HCNet) for joint objection detection and semantic segmentation. It follows that our method is faster and performs better than the previous approaches whose decoder networks of different tasks are independent. Besides, we present multi-scale loss architecture to learn better representation for different scale objects, but without extra time in the inference phase. Experiment results show that our method achieves state-of-the-art results on the KITTI datasets. Moreover, it can run at 35 FPS on a GPU and thus is a practical solution to object detection and semantic segmentation for autonomous driving.

The neural substrates of semantic memory deficits in early Alzheimer's disease: Clues from semantic priming effects and FDG-PET

International Nuclear Information System (INIS)

Giffard, B.; Laisney, M.; Mezenge, F.; De la Sayette, V.; Eustache, F.; Desgranges, B.

2008-01-01

The neural substrates responsible for semantic dysfunction during the early stages of AD have yet to be clearly identified. After a brief overview of the literature on normal and pathological semantic memory, we describe a new approach, designed to provide fresh insights into semantic deficits in AD. We mapped the correlations between resting-state brain glucose utilisation measured by FDG-PET and semantic priming scores in a group of 17 AD patients. The priming task, which yields a particularly pure measurement of semantic memory, was composed of related pairs of words sharing an attribute relationship (e.g. tiger-stripe). The priming scores correlated positively with the metabolism of the superior temporal areas on both sides, especially the right side, and this correlation was shown to be specific to the semantic priming effect.This pattern of results is discussed in the light of recent theoretical models of semantic memory, and suggests that a dysfunction of the right superior temporal cortex may contribute to early semantic deficits, characterised by the loss of specific features of concepts in AD. (authors)

Social Semantics for an Effective Enterprise

Science.gov (United States)

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.

SEMANTIC WEB MINING: ISSUES AND CHALLENGES

OpenAIRE

Karan Singh*, Anil kumar, Arun Kumar Yadav

2016-01-01

The combination of the two fast evolving scientific research areas “Semantic Web” and “Web Mining” are well-known as “Semantic Web Mining” in computer science. These two areas cover way for the mining of related and meaningful information from the web, by this means giving growth to the term “Semantic Web Mining”. The “Semantic Web” makes mining easy and “Web Mining” can construct new structure of Web. Web Mining applies Data Mining technique on web content, Structure and Usage. This paper gi...

Semantic role labeling for protein transport predicates

Directory of Open Access Journals (Sweden)

Martin James H

2008-06-01

Full Text Available Abstract Background Automatic semantic role labeling (SRL is a natural language processing (NLP technique that maps sentences to semantic representations. This technique has been widely studied in the recent years, but mostly with data in newswire domains. Here, we report on a SRL model for identifying the semantic roles of biomedical predicates describing protein transport in GeneRIFs – manually curated sentences focusing on gene functions. To avoid the computational cost of syntactic parsing, and because the boundaries of our protein transport roles often did not match up with syntactic phrase boundaries, we approached this problem with a word-chunking paradigm and trained support vector machine classifiers to classify words as being at the beginning, inside or outside of a protein transport role. Results We collected a set of 837 GeneRIFs describing movements of proteins between cellular components, whose predicates were annotated for the semantic roles AGENT, PATIENT, ORIGIN and DESTINATION. We trained these models with the features of previous word-chunking models, features adapted from phrase-chunking models, and features derived from an analysis of our data. Our models were able to label protein transport semantic roles with 87.6% precision and 79.0% recall when using manually annotated protein boundaries, and 87.0% precision and 74.5% recall when using automatically identified ones. Conclusion We successfully adapted the word-chunking classification paradigm to semantic role labeling, applying it to a new domain with predicates completely absent from any previous studies. By combining the traditional word and phrasal role labeling features with biomedical features like protein boundaries and MEDPOST part of speech tags, we were able to address the challenges posed by the new domain data and subsequently build robust models that achieved F-measures as high as 83.1. This system for extracting protein transport information from Gene

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction

OpenAIRE

Thompson, Hannah E; Almaghyuli, Azizah; Noonan, Krist A.; Barak, Ohr; Lambon Ralph, Matthew; Jefferies, Elizabeth

2018-01-01

Semantic cognition, as described by the Controlled Semantic Cognition (CSC) framework (Rogers, Patterson, Jefferies, & Lambon Ralph, 2015), involves two key components: activation of coherent, generalizable concepts within a heteromodal ‘hub’ in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task- appropriate behaviour. Executive-semantic goal representations, largely supported by executive...

Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference

OpenAIRE

Bao, Ruying; Liang, Sihang; Wang, Qingcan

2018-01-01

Deep neural networks have been demonstrated to be vulnerable to adversarial attacks, where small perturbations are intentionally added to the original inputs to fool the classifier. In this paper, we propose a defense method, Featurized Bidirectional Generative Adversarial Networks (FBGAN), to capture the semantic features of the input and filter the non-semantic perturbation. FBGAN is pre-trained on the clean dataset in an unsupervised manner, adversarially learning a bidirectional mapping b...

Interacting Memory Systems—Does EEG Alpha Activity Respond to Semantic Long-Term Memory Access in a Working Memory Task?

Directory of Open Access Journals (Sweden)

Barbara Berger

2014-12-01

Full Text Available Memory consists of various individual processes which form a dynamic system co-ordinated by central (executive functions. The episodic buffer as direct interface between episodic long-term memory (LTM and working memory (WM is fairly well studied but such direct interaction is less clear in semantic LTM. Here, we designed a verbal delayed-match-to-sample task specifically to differentiate between pure information maintenance and mental manipulation of memory traces with and without involvement of access to semantic LTM. Task-related amplitude differences of electroencephalographic (EEG oscillatory brain activity showed a linear increase in frontal-midline theta and linear suppression of parietal beta amplitudes relative to memory operation complexity. Amplitude suppression at upper alpha frequency, which was previously found to indicate access to semantic LTM, was only sensitive to mental manipulation in general, irrespective of LTM involvement. This suggests that suppression of upper EEG alpha activity might rather reflect unspecific distributed cortical activation during complex mental processes than accessing semantic LTM.

Psychologizing the Semantics of Fiction

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John Woods

2010-04-01

Full Text Available Psychologiser la sémantique de la fictionLes théoriciens sémantistes de la fiction cherchent typiquement à expliquer nos relations sémantiques au fictionnel dans le contexte plus général des théories de la référence, privilégiant une explication de la sémantique sur le psychologique. Dans cet article, nous défendons une dépendance inverse. Par l’éclaircissement de nos relations psychologiques au fictionnel, nous trouverons un guide pour savoir comment développer une sémantique de la fiction. S’ensuivra une esquisse de la sémantique.Semantic theorists of fiction typically look for an account of our semantic relations to the fictional within general-purpose theories of reference, privileging an explanation of the semantic over the psychological. In this paper, we counsel a reverse dependency. In sorting out our psychological relations to the fictional, there is useful guidance about how to proceed with the semantics of fiction. A sketch of the semantics follows.

Jigsaw Semantics

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Paul J. E. Dekker

2010-12-01

Full Text Available In the last decade the enterprise of formal semantics has been under attack from several philosophical and linguistic perspectives, and it has certainly suffered from its own scattered state, which hosts quite a variety of paradigms which may seem to be incompatible. It will not do to try and answer the arguments of the critics, because the arguments are often well-taken. The negative conclusions, however, I believe are not. The only adequate reply seems to be a constructive one, which puts several pieces of formal semantics, in particular dynamic semantics, together again. In this paper I will try and sketch an overview of tasks, techniques, and results, which serves to at least suggest that it is possible to develop a coherent overall picture of undeniably important and structural phenomena in the interpretation of natural language. The idea is that the concept of meanings as truth conditions after all provides an excellent start for an integrated study of the meaning and use of natural language, and that an extended notion of goal directed pragmatics naturally complements this picture. None of the results reported here are really new, but we think it is important to re-collect them.ReferencesAsher, Nicholas & Lascarides, Alex. 1998. ‘Questions in Dialogue’. Linguistics and Philosophy 23: 237–309.http://dx.doi.org/10.1023/A:1005364332007Borg, Emma. 2007. ‘Minimalism versus contextualism in semantics’. In Gerhard Preyer & Georg Peter (eds. ‘Context-Sensitivity and Semantic Minimalism’, pp. 339–359. Oxford: Oxford University Press.Cappelen, Herman & Lepore, Ernest. 1997. ‘On an Alleged Connection between Indirect Quotation and Semantic Theory’. Mind and Language 12: pp. 278–296.Cappelen, Herman & Lepore, Ernie. 2005. Insensitive Semantics. Oxford: Blackwell.http://dx.doi.org/10.1002/9780470755792Dekker, Paul. 2002. ‘Meaning and Use of Indefinite Expressions’. Journal of Logic, Language and Information 11: pp. 141–194

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

NARCIS (Netherlands)

Penev, L.; Agosti, D.; Georgiev, T.; Catapano, T.; Miller, J.; Blagoderov, V.; Roberts, D.; Smith, V.S.; Brake, I.; Ryrcroft, S.; Scott, B.; Johnson, N.F.; Morris, R.A.; Sautter, G.; Chavan, V.; Robertson, T.; Remsen, D.; Stoev, P.; Parr, C.; Knapp, S.; Kress, W.J.; Thompson, F.C.; Erwin, T.

2010-01-01

The concept of semantic tagging and its potential for semantic enhancements to taxonomic papers is outlined and illustrated by four exemplar papers published in the present issue of ZooKeys. The four papers were created in different ways: (i) written in Microsoft Word and submitted as non-tagged

The contribution of executive control to semantic cognition: Convergent evidence from semantic aphasia and executive dysfunction

OpenAIRE

Thompson, Hannah; Almaghyuli, Azizah; Noonan, Krist A.; barak, Ohr; Lambon Ralph, Matthew A.; Jefferies, Elizabeth

2018-01-01

Semantic cognition, as described by the controlled semantic cognition (CSC) framework (Rogers et al., 2015, Neuropsychologia, 76, 220), involves two key components: activation of coherent, generalizable concepts within a heteromodal ‘hub’ in combination with modality-specific features (spokes), and a constraining mechanism that manipulates and gates this knowledge to generate time- and task-appropriate behaviour. Executive–semantic goal representations, largely supported by executive regions ...

Survey of semantic modeling techniques

Energy Technology Data Exchange (ETDEWEB)

Smith, C.L.

1975-07-01

The analysis of the semantics of programing languages was attempted with numerous modeling techniques. By providing a brief survey of these techniques together with an analysis of their applicability for answering semantic issues, this report attempts to illuminate the state-of-the-art in this area. The intent is to be illustrative rather than thorough in the coverage of semantic models. A bibliography is included for the reader who is interested in pursuing this area of research in more detail.

Semantic multimedia analysis and processing

CERN Document Server

Spyrou, Evaggelos; Mylonas, Phivos

2014-01-01

Broad in scope, Semantic Multimedia Analysis and Processing provides a complete reference of techniques, algorithms, and solutions for the design and the implementation of contemporary multimedia systems. Offering a balanced, global look at the latest advances in semantic indexing, retrieval, analysis, and processing of multimedia, the book features the contributions of renowned researchers from around the world. Its contents are based on four fundamental thematic pillars: 1) information and content retrieval, 2) semantic knowledge exploitation paradigms, 3) multimedia personalization, and 4)

Distinct loci of lexical and semantic access deficits in aphasia: Evidence from voxel-based lesion-symptom mapping and diffusion tensor imaging.

Science.gov (United States)

Harvey, Denise Y; Schnur, Tatiana T

2015-06-01

comprehension. These neuroanatomical-behavioral findings have implications for models of the lexical-semantic language network by demonstrating that semantic interference in language production and comprehension involves different representations which differentially recruit a cognitive control mechanism for interference resolution. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Novel Method to Identify Differential Pathways in Hippocampus Alzheimer's Disease.

Science.gov (United States)

Liu, Chun-Han; Liu, Lian

2017-05-08

BACKGROUND Alzheimer's disease (AD) is the most common type of dementia. The objective of this paper is to propose a novel method to identify differential pathways in hippocampus AD. MATERIAL AND METHODS We proposed a combined method by merging existed methods. Firstly, pathways were identified by four known methods (DAVID, the neaGUI package, the pathway-based co-expressed method, and the pathway network approach), and differential pathways were evaluated through setting weight thresholds. Subsequently, we combined all pathways by a rank-based algorithm and called the method the combined method. Finally, common differential pathways across two or more of five methods were selected. RESULTS Pathways obtained from different methods were also different. The combined method obtained 1639 pathways and 596 differential pathways, which included all pathways gained from the four existing methods; hence, the novel method solved the problem of inconsistent results. Besides, a total of 13 common pathways were identified, such as metabolism, immune system, and cell cycle. CONCLUSIONS We have proposed a novel method by combining four existing methods based on a rank product algorithm, and identified 13 significant differential pathways based on it. These differential pathways might provide insight into treatment and diagnosis of hippocampus AD.

Neural correlates underlying musical semantic memory.

Science.gov (United States)

Groussard, M; Viader, F; Landeau, B; Desgranges, B; Eustache, F; Platel, H

2009-07-01

Numerous functional imaging studies have examined the neural basis of semantic memory mainly using verbal and visuospatial materials. Musical material also allows an original way to explore semantic memory processes. We used PET imaging to determine the neural substrates that underlie musical semantic memory using different tasks and stimuli. The results of three PET studies revealed a greater involvement of the anterior part of the temporal lobe. Concerning clinical observations and our neuroimaging data, the musical lexicon (and most widely musical semantic memory) appears to be sustained by a temporo-prefrontal cerebral network involving right and left cerebral regions.

Flexible recruitment of semantic richness: Context modulates body-object interaction effects in lexical-semantic processing

Directory of Open Access Journals (Sweden)

Cody eTousignant

2012-03-01

Full Text Available Body-object interaction (BOI is a semantic richness variable that measures the perceived ease with which the human body can physically interact with a word’s referent. Lexical and semantic processing is facilitated when words are associated with relatively more bodily experience (high BOI words, e.g., belt. To date, BOI effects have been examined in only one semantic decision context (is it imageable?. It has been argued that semantic processing is dynamic and can be modulated by context. We examined these influences by testing how task knowledge modulated BOI effects. We presented the same stimuli (high- and low-BOI entity words and a set of action words in each of four action/entity semantic categorization tasks (SCTs. Task framing was manipulated: participants were told about one (actions or entities or both (actions and entities categories of words in the decision task. Facilitatory BOI effects were observed when participants knew that ‘entity’ was part of the decision category, regardless of whether the high- and low-BOI entity words appeared on the affirmative or negative side of the decision. That BOI information was only useful when participants had expectations that object words would be presented suggests a strong role for the decision context in lexical-semantic processing, and supports a dynamic view of conceptual knowledge.

Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products

Directory of Open Access Journals (Sweden)

Mingxin Gan

2014-01-01

Full Text Available Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson’s correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

Semantic Representations in 3D Perceptual Space

Directory of Open Access Journals (Sweden)

Suncica Zdravkovic

2011-05-01

Full Text Available Barsalou's (1999 perceptual theory of knowledge echoes the pre-20th century tradition of conceptualizing all knowledge as inherently perceptual. Hence conceptual space has an infinite number of dimensions and heavily relies on perceptual experience. Osgood's (1952 semantic differential technique was developed as a bridge between perception and semantics. We updated Osgood's methodology in order to investigate current issues in visual cognition by: (1 using a 2D rather than a 1D space to place the concepts, (2 having dimensions that were perceptual while the targets were conceptual, (3 coupling visual experience with another two perceptual domains (audition and touch, (4 analyzing the data using MDS (not factor analysis. In three experiments, subjects (N = 57 judged five concrete and five abstract words on seven bipolar scales in three perceptual modalities. The 2D space led to different patterns of response compared to the classic 1D space. MDS revealed that perceptual modalities are not equally informative for mapping word-meaning distances (Mantel min = −.23; Mantel max = .88. There was no reliable differences due to test administration modality (paper vs. computer, nor scale orientation. The present findings are consistent with multidimensionality of conceptual space, a perceptual basis for knowledge, and dynamic characteristics of concepts discussed in contemporary theories.

Inter-deriving Semantic Artifacts for Object-Oriented Programming

DEFF Research Database (Denmark)

Danvy, Olivier; Johannsen, Jacob

2010-01-01

We present a new abstract machine for Abadi and Cardelli's untyped non-imperative calculus of objects.  This abstract machine mechanically corresponds to both the reduction semantics (i.e., small-step operational semantics) and the natural semantics (i.e., big-step operational semantics) specified...

Fuzzy Emotional Semantic Analysis and Automated Annotation of Scene Images

Directory of Open Access Journals (Sweden)

Jianfang Cao

2015-01-01

Full Text Available With the advances in electronic and imaging techniques, the production of digital images has rapidly increased, and the extraction and automated annotation of emotional semantics implied by images have become issues that must be urgently addressed. To better simulate human subjectivity and ambiguity for understanding scene images, the current study proposes an emotional semantic annotation method for scene images based on fuzzy set theory. A fuzzy membership degree was calculated to describe the emotional degree of a scene image and was implemented using the Adaboost algorithm and a back-propagation (BP neural network. The automated annotation method was trained and tested using scene images from the SUN Database. The annotation results were then compared with those based on artificial annotation. Our method showed an annotation accuracy rate of 91.2% for basic emotional values and 82.4% after extended emotional values were added, which correspond to increases of 5.5% and 8.9%, respectively, compared with the results from using a single BP neural network algorithm. Furthermore, the retrieval accuracy rate based on our method reached approximately 89%. This study attempts to lay a solid foundation for the automated emotional semantic annotation of more types of images and therefore is of practical significance.

CASL - The CoFI Algebraic Specification Language - Semantics

DEFF Research Database (Denmark)

Haxthausen, Anne

1999-01-01

This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the second complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop in Amsterdam in March 1999.......This is version 1.0 of the CASL Language Summary, annotated by the CoFI Semantics Task Group with the semantics of constructs. This is the second complete but possibly imperfect version of the semantics. It was compiled prior to the CoFI workshop in Amsterdam in March 1999....

[Evaluation of temporality semantic knowledge in normal aging and in mild and moderate stages of Alzheimer's disease].

Science.gov (United States)

Rivasseau Jonveaux, T; Batt, M; Empereur, F; Braun, M; Trognon, A

2015-04-01

Episodic and semantic processes are involved in temporality used in daily life. Episodic memory permits one to place an event on the time axis, while semantic memory makes us aware of the time segmentation and its symbolic representation. Memory of the knowledge connected to the passing of time is materialized on the calendar and can be seen symbolically on the dial of a clock. In AD, semantic memory processes are preserved longer than processes related to episodic memory. We wonder whether the specific field of knowledge about time is altered during AD. We validated a specific evaluation with a control group (354 healthy subjects). Then we applied this battery to assess AD patients to appreciate the feasibility of this tool for this population. We then compared 22 AD patients with a control group matched for age, sex and educational level. Our clinical scale of temporal semantic knowledge consists of four parts: (a) hour reading with a.m. and p.m. hours; (b) using a clock: 12 clock faces with the hour numbers already placed: the patient draws hour and minute hands for various hours; (c) temporal segmentation: exploration of the knowledge on daytime scale and of the calendar; (d) time duration estimation: calculate how long the interview has lasted after indicating the time of its beginning and its end, then the time between 10.40 to 12.00. While age and educational level had an influence on all the scores, in the two groups control and patients, gender did not. Temporal segmentation, independent of the cultural level, revealed the best acquired knowledge in our control population. All the scores differentiated patients from control subjects. The temporal semantic knowledge correlated with the AD severity seemed to be correlated with the attention, verbal comprehension, and some components of executive functions, but was not related to the clock drawing test result. Depression did not have any influence on this scale in our AD group. The temporal semantic knowledge

Recommendation of standardized health learning contents using archetypes and semantic web technologies.

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Legaz-García, María del Carmen; Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2012-01-01

Linking Electronic Healthcare Records (EHR) content to educational materials has been considered a key international recommendation to enable clinical engagement and to promote patient safety. This would suggest citizens to access reliable information available on the web and to guide them properly. In this paper, we describe an approach in that direction, based on the use of dual model EHR standards and standardized educational contents. The recommendation method will be based on the semantic coverage of the learning content repository for a particular archetype, which will be calculated by applying semantic web technologies like ontologies and semantic annotations.

Semantic, phonologic, and verb fluency in Huntington's disease

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Mariana Jardim Azambuja

Full Text Available Abstract Verbal fluency tasks have been identified as important indicators of executive functioning impairment in patients with frontal lobe dysfunction. Although the usual evaluation of this ability considers phonologic and semantic criteria, there is some evidence that fluency of verbs would be more sensitive in disclosing frontostriatal physiopathology since frontal regions primarily mediate retrieval of verbs. Huntington's disease usually affects these circuitries. Objective: To compare three types of verbal fluency task in the assessment of frontal-striatal dysfunction in HD subjects. Methods: We studied 26 Huntington's disease subjects, divided into two subgroups: mild (11 and moderate (15 along with 26 normal volunteers matched for age, gender and schooling, for three types of verbal fluency: phonologic fluency (F-A-S, semantic fluency and fluency of verbs. Results: Huntington's disease subjects showed a significant reduction in the number of words correctly generated in the three tasks when compared to the normal group. Both controls and Huntington's disease subjects showed a similar pattern of decreasing task performance with the greatest number of words being generated by semantic elicitation followed by verbs and lastly phonologic criteria. We did not find greater production of verbs compared with F-A-S and semantic conditions. Moreover, the fluency of verbs distinguished only the moderate group from controls. Conclusion: Our results indicated that phonologic and semantic fluency can be used to evaluate executive functioning, proving more sensitive than verb fluency. However, it is important to point out that the diverse presentations of Huntington's disease means that an extended sample is necessary for more consistent analysis of this issue.

Co-clustering for Weblogs in Semantic Space

DEFF Research Database (Denmark)

Zong, Yu; Xu, Guandong; Dolog, Peter

2010-01-01

Web clustering is an approach for aggregating web objects into various groups according to underlying relationships among them. Finding co-clusters of web objects in semantic space is an interesting topic in the context of web usage mining, which is able to capture the underlying user navigational...... interest and content preference simultaneously. In this paper we will present a novel web co-clustering algorithm named Co-Clustering in Semantic space (COCS) to simultaneously partition web users and pages via a latent semantic analysis approach. In COCS, we first, train the latent semantic space...... of weblog data by using Probabilistic Latent Semantic Analysis (PLSA) model, and then, project all weblog data objects into this semantic space with probability distribution to capture the relationship among web pages and web users, at last, propose a clustering algorithm to generate the co...

Discovery and Selection of Semantic Web Services

CERN Document Server

Wang, Xia

2013-01-01

For advanced web search engines to be able not only to search for semantically related information dispersed over different web pages, but also for semantic services providing certain functionalities, discovering semantic services is the key issue. Addressing four problems of current solution, this book presents the following contributions. A novel service model independent of semantic service description models is proposed, which clearly defines all elements necessary for service discovery and selection. It takes service selection as its gist and improves efficiency. Corresponding selection algorithms and their implementation as components of the extended Semantically Enabled Service-oriented Architecture in the Web Service Modeling Environment are detailed. Many applications of semantic web services, e.g. discovery, composition and mediation, can benefit from a general approach for building application ontologies. With application ontologies thus built, services are discovered in the same way as with single...

Action representation: crosstalk between semantics and pragmatics.

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Prinz, Wolfgang

2014-03-01

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

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

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Yuanqing Li

Full Text Available 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.

Learning for Semantic Parsing with Kernels under Various Forms of Supervision

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2007-08-01

natural language sentences to their formal executable meaning representations. This is a challenging problem and is critical for developing computing...sentences are semantically tractable. This indi- cates that Geoquery is more challenging domain for semantic parsing than ATIS. In the past, there have been a...Combining parsers. In Proceedings of the Conference on Em- pirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/ VLC -99), pp. 187–194

The Semantics of Plurals: A Defense of Singularism

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Florio, Salvatore

2010-01-01

In this dissertation, I defend "semantic singularism", which is the view that syntactically plural terms, such as "they" or "Russell and Whitehead", are semantically singular. A semantically singular term is a term that denotes a single entity. Semantic singularism is to be distinguished from "syntactic singularism", according to which…

A methodology for the analysis of differential coexpression across the human lifespan.

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Gillis, Jesse; Pavlidis, Paul

2009-09-22

Differential coexpression is a change in coexpression between genes that may reflect 'rewiring' of transcriptional networks. It has previously been hypothesized that such changes might be occurring over time in the lifespan of an organism. While both coexpression and differential expression of genes have been previously studied in life stage change or aging, differential coexpression has not. Generalizing differential coexpression analysis to many time points presents a methodological challenge. Here we introduce a method for analyzing changes in coexpression across multiple ordered groups (e.g., over time) and extensively test its validity and usefulness. Our method is based on the use of the Haar basis set to efficiently represent changes in coexpression at multiple time scales, and thus represents a principled and generalizable extension of the idea of differential coexpression to life stage data. We used published microarray studies categorized by age to test the methodology. We validated the methodology by testing our ability to reconstruct Gene Ontology (GO) categories using our measure of differential coexpression and compared this result to using coexpression alone. Our method allows significant improvement in characterizing these groups of genes. Further, we examine the statistical properties of our measure of differential coexpression and establish that the results are significant both statistically and by an improvement in semantic similarity. In addition, we found that our method finds more significant changes in gene relationships compared to several other methods of expressing temporal relationships between genes, such as coexpression over time. Differential coexpression over age generates significant and biologically relevant information about the genes producing it. Our Haar basis methodology for determining age-related differential coexpression performs better than other tested methods. The Haar basis set also lends itself to ready interpretation

Control Deficit Subjects are Superior for Man-Made Objects on a Verbal Semantic Task

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Carlos Roncero

2014-04-01

participant—whereas control deficit subjects’ temporal lobe damage was more severe in the left hemisphere and typically unilateral. Therefore, these results suggest our three tasks were sufficient for differentiating anomic subjects with either a control deficit or a storage deficit. Also, considering the worse performance by control deficit subjects for the verbal version of the Camels and Cactus test, the results are consistent with previous arguments that the left temporal lobe is more specialized for verbal knowledge whereas the right temporal lobe is more specialized for visual knowledge (Gainotti, 2014. We also found, however, that this difference on the word version was isolated to living objects only. For manmade objects, control deficit subjects’ answers were similar to normal elderly controls. Therefore, the results suggest that animacy effects may be less related to a loss of visual semantic knowledge, as predicted by the sensory-functional hypothesis, because control deficit subjects performed well on the visual Camels and Cactus Test. Instead, animacy effects may be more related to the location of atrophy within the left temporal lobe.

Towards a Reactive Semantic Execution Environment

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Komazec, Srdjan; Facca, Federico Michele

Managing complex and distributed software systems built on top of the service-oriented paradigm has never been more challenging. While Semantic Web Service technologies offer a promising set of languages and tools as a foundation to resolve the heterogeneity and scalability issues, they are still failing to provide an autonomic execution environment. In this paper we present an approach based on Semantic Web Services to enable the monitoring and self-management of a Semantic Execution Environment (SEE), a brokerage system for Semantic Web Services. Our approach is founded on the event-triggered reactivity paradigm in order to facilitate environment control, thus contributing to its autonomicity, robustness and flexibility.

Semantic Observation Integration

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Werner Kuhn

2012-09-01

Full Text Available Although the integration of sensor-based information into analysis and decision making has been a research topic for many years, semantic interoperability has not yet been reached. The advent of user-generated content for the geospatial domain, Volunteered Geographic Information (VGI, makes it even more difficult to establish semantic integration. This paper proposes a novel approach to integrating conventional sensor information and VGI, which is exploited in the context of detecting forest fires. In contrast to common logic-based semantic descriptions, we present a formal system using algebraic specifications to unambiguously describe the processing steps from natural phenomena to value-added information. A generic ontology of observations is extended and profiled for forest fire detection in order to illustrate how the sensing process, and transformations between heterogeneous sensing systems, can be represented as mathematical functions and grouped into abstract data types. We discuss the required ontological commitments and a possible generalization.

Insensitive Enough Semantics

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Richard Vallée

2006-06-01

Full Text Available According to some philosophers, sentences like (1 “It is raining” and (2 “John is ready” are context sensitive sentences even if they do not contain indexicals or demonstratives. That view initiated a context sensitivity frenzy. Cappelen and Lepore (2005 summarize the frenzy by the slogan “Every sentence is context sensitive” (Insensitive Semantics, p. 6, note 5. They suggest a view they call Minimalism according to which the truth conditions of utterances of sentences like (1/(2 are exactly what Convention T gives you. I will distinguish different propositions, and refocus semantics on sentences. As distinct from what the protagonists in the ongoing debate think, I argue that the content or truth conditions of utterances of both context sensitive sentences and sentences like (1/(2 are not interesting from a semantic point of view, and that the problem sentences like (1/(2 raises is not about context sensitivity or context insensitivity of sentences, but relevance of the content of utterances.

Continuous multistep methods for volterra integro-differential ...

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A new class of numerical methods for Volterra integro-differential equations of the second order is developed. The methods are based on interpolation and collocation of the shifted Legendre polynomial as basis function with Trapezoidal quadrature rules. The convergence analysis revealed that the methods are consistent ...

Semantic description of three-dimensional models of Bologna porches

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Massimo Ballabeni

2015-07-01

Full Text Available The study is part of a broader search coordinated by the Department of Architecture of the University of Bologna, the Cineca and the city of Bologna for the nomination of the city porticoes in the UNESCO World Heritage Site. The study describes, first, the problems and the methods adopted for the survey, the numerical modeling and visualization of the arcades models. In addition, the paper aims to describe a method for the semantic studying of the porticoes architecture and the segmentation of the models. The goal is also to establish an integrated approach to the semantic cataloguing of the Bologna arcades based on historical, material, formal, dimensional and theoretical data, and to make this information easily readable and communicable.

The Problem of Naturalizing Semantics.

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Sullivan, Arthur

2000-01-01

Investigates conceptual barriers prevalent in the works of both proponents and opponents of semantic naturalism. Searches for a tenable definition of naturalism according to which one can be a realist, a non-reductionist, and a naturalist about semantic content. (Author/VWL)

A fusion network for semantic segmentation using RGB-D data

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Yuan, Jiahui; Zhang, Kun; Xia, Yifan; Qi, Lin; Dong, Junyu

2018-04-01

Semantic scene parsing is considerable in many intelligent field, including perceptual robotics. For the past few years, pixel-wise prediction tasks like semantic segmentation with RGB images has been extensively studied and has reached very remarkable parsing levels, thanks to convolutional neural networks (CNNs) and large scene datasets. With the development of stereo cameras and RGBD sensors, it is expected that additional depth information will help improving accuracy. In this paper, we propose a semantic segmentation framework incorporating RGB and complementary depth information. Motivated by the success of fully convolutional networks (FCN) in semantic segmentation field, we design a fully convolutional networks consists of two branches which extract features from both RGB and depth data simultaneously and fuse them as the network goes deeper. Instead of aggregating multiple model, our goal is to utilize RGB data and depth data more effectively in a single model. We evaluate our approach on the NYU-Depth V2 dataset, which consists of 1449 cluttered indoor scenes, and achieve competitive results with the state-of-the-art methods.

Numerical Methods for Partial Differential Equations

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Guo, Ben-yu

1987-01-01

These Proceedings of the first Chinese Conference on Numerical Methods for Partial Differential Equations covers topics such as difference methods, finite element methods, spectral methods, splitting methods, parallel algorithm etc., their theoretical foundation and applications to engineering. Numerical methods both for boundary value problems of elliptic equations and for initial-boundary value problems of evolution equations, such as hyperbolic systems and parabolic equations, are involved. The 16 papers of this volume present recent or new unpublished results and provide a good overview of current research being done in this field in China.

Adaptive semantics visualization

CERN Document Server

Nazemi, Kawa

2016-01-01

This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human’s behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire “SemaVis” system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science.

Semantic annotation in biomedicine: the current landscape.

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Jovanović, Jelena; Bagheri, Ebrahim

2017-09-22

The abundance and unstructured nature of biomedical texts, be it clinical or research content, impose significant challenges for the effective and efficient use of information and knowledge stored in such texts. Annotation of biomedical documents with machine intelligible semantics facilitates advanced, semantics-based text management, curation, indexing, and search. This paper focuses on annotation of biomedical entity mentions with concepts from relevant biomedical knowledge bases such as UMLS. As a result, the meaning of those mentions is unambiguously and explicitly defined, and thus made readily available for automated processing. This process is widely known as semantic annotation, and the tools that perform it are known as semantic annotators.Over the last dozen years, the biomedical research community has invested significant efforts in the development of biomedical semantic annotation technology. Aiming to establish grounds for further developments in this area, we review a selected set of state of the art biomedical semantic annotators, focusing particularly on general purpose annotators, that is, semantic annotation tools that can be customized to work with texts from any area of biomedicine. We also examine potential directions for further improvements of today's annotators which could make them even more capable of meeting the needs of real-world applications. To motivate and encourage further developments in this area, along the suggested and/or related directions, we review existing and potential practical applications and benefits of semantic annotators.

Learning Semantic Tags from Big Data for Clinical Text Representation.

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Li, Yanpeng; Liu, Hongfang

2015-01-01

In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

Semantic distance as a critical factor in icon design for in-car infotainment systems.

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Silvennoinen, Johanna M; Kujala, Tuomo; Jokinen, Jussi P P

2017-11-01

In-car infotainment systems require icons that enable fluent cognitive information processing and safe interaction while driving. An important issue is how to find an optimised set of icons for different functions in terms of semantic distance. In an optimised icon set, every icon needs to be semantically as close as possible to the function it visually represents and semantically as far as possible from the other functions represented concurrently. In three experiments (N = 21 each), semantic distances of 19 icons to four menu functions were studied with preference rankings, verbal protocols, and the primed product comparisons method. The results show that the primed product comparisons method can be efficiently utilised for finding an optimised set of icons for time-critical applications out of a larger set of icons. The findings indicate the benefits of the novel methodological perspective into the icon design for safety-critical contexts in general. Copyright © 2017 Elsevier Ltd. All rights reserved.

Exploiting semantic linkages among multiple sources for semantic information retrieval

Science.gov (United States)

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.

Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD.

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Bullinaria, John A; Levy, Joseph P

2012-09-01

In a previous article, we presented a systematic computational study of the extraction of semantic representations from the word-word co-occurrence statistics of large text corpora. The conclusion was that semantic vectors of pointwise mutual information values from very small co-occurrence windows, together with a cosine distance measure, consistently resulted in the best representations across a range of psychologically relevant semantic tasks. This article extends that study by investigating the use of three further factors--namely, the application of stop-lists, word stemming, and dimensionality reduction using singular value decomposition (SVD)--that have been used to provide improved performance elsewhere. It also introduces an additional semantic task and explores the advantages of using a much larger corpus. This leads to the discovery and analysis of improved SVD-based methods for generating semantic representations (that provide new state-of-the-art performance on a standard TOEFL task) and the identification and discussion of problems and misleading results that can arise without a full systematic study.

Uncovering highly obfuscated plagiarism cases using fuzzy semantic-based similarity model

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Salha M. Alzahrani

2015-07-01

Full Text Available Highly obfuscated plagiarism cases contain unseen and obfuscated texts, which pose difficulties when using existing plagiarism detection methods. A fuzzy semantic-based similarity model for uncovering obfuscated plagiarism is presented and compared with five state-of-the-art baselines. Semantic relatedness between words is studied based on the part-of-speech (POS tags and WordNet-based similarity measures. Fuzzy-based rules are introduced to assess the semantic distance between source and suspicious texts of short lengths, which implement the semantic relatedness between words as a membership function to a fuzzy set. In order to minimize the number of false positives and false negatives, a learning method that combines a permission threshold and a variation threshold is used to decide true plagiarism cases. The proposed model and the baselines are evaluated on 99,033 ground-truth annotated cases extracted from different datasets, including 11,621 (11.7% handmade paraphrases, 54,815 (55.4% artificial plagiarism cases, and 32,578 (32.9% plagiarism-free cases. We conduct extensive experimental verifications, including the study of the effects of different segmentations schemes and parameter settings. Results are assessed using precision, recall, F-measure and granularity on stratified 10-fold cross-validation data. The statistical analysis using paired t-tests shows that the proposed approach is statistically significant in comparison with the baselines, which demonstrates the competence of fuzzy semantic-based model to detect plagiarism cases beyond the literal plagiarism. Additionally, the analysis of variance (ANOVA statistical test shows the effectiveness of different segmentation schemes used with the proposed approach.

Dynamics of Semantic and Word-Formation Subsystems of the Russian Language: Historical Dynamics of the Word Family

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Olga Ivanovna Dmitrieva

2015-09-01

Full Text Available The article provides comprehensive justification of the principles and methods of the synchronic and diachronic research of word-formation subsystems of the Russian language. The authors also study the ways of analyzing historical dynamics of word family as the main macro-unit of word-formation system. In the field of analysis there is a family of words with the stem 'ход-' (the meaning of 'motion', word-formation of which is investigated in different periods of the Russian literary language. Significance of motion-verbs in the process of forming a language picture of the world determined the character and the structure of this word family as one of the biggest in the history of the Russian language. In the article a structural and semantic dynamics of the word family 'ход-' is depicted. The results of the study show that in the ancient period the prefixes of verbal derivatives were formed, which became the apex-branched derivational paradigms existing in modern Russian. The old Russian period of language development is characterized by the appearance of words with connotative meaning (with suffixes -ishk-, -ichn-, as well as the words with possessive semantics (with suffixes –ev-, -sk-. In this period the verbs with the postfix -cz also supplement the analyzed word family. The period of formation of the National Russian language was marked by the loss of a large number of abstract nouns and the appearance of neologisms from some old Russian abstract nouns. The studied family in the modern Russian language is characterized by the following processes: the appearance of terms, the active semantic derivation, the weakening of word-formation variability, the semantic differentiation of duplicate units, the development of subsystem of words with connotative meanings, and the preservation of derivatives in all functional styles.

Modulation of the semantic system by word imageability.

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Sabsevitz, D S; Medler, D A; Seidenberg, M; Binder, J R

2005-08-01

A prevailing neurobiological theory of semantic memory proposes that part of our knowledge about concrete, highly imageable concepts is stored in the form of sensory-motor representations. While this theory predicts differential activation of the semantic system by concrete and abstract words, previous functional imaging studies employing this contrast have provided relatively little supporting evidence. We acquired event-related functional magnetic resonance imaging (fMRI) data while participants performed a semantic similarity judgment task on a large number of concrete and abstract noun triads. Task difficulty was manipulated by varying the degree to which the words in the triad were similar in meaning. Concrete nouns, relative to abstract nouns, produced greater activation in a bilateral network of multimodal and heteromodal association areas, including ventral and medial temporal, posterior-inferior parietal, dorsal prefrontal, and posterior cingulate cortex. In contrast, abstract nouns produced greater activation almost exclusively in the left hemisphere in superior temporal and inferior frontal cortex. Increasing task difficulty modulated activation mainly in attention, working memory, and response monitoring systems, with almost no effect on areas that were modulated by imageability. These data provide critical support for the hypothesis that concrete, imageable concepts activate perceptually based representations not available to abstract concepts. In contrast, processing abstract concepts makes greater demands on left perisylvian phonological and lexical retrieval systems. The findings are compatible with dual coding theory and less consistent with single-code models of conceptual representation. The lack of overlap between imageability and task difficulty effects suggests that once the neural representation of a concept is activated, further maintenance and manipulation of that information in working memory does not further increase neural activation in

Is semantic verbal fluency impairment explained by executive function deficits in schizophrenia?

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Arthur A. Berberian

2016-01-01

Full Text Available Objective: To investigate if verbal fluency impairment in schizophrenia reflects executive function deficits or results from degraded semantic store or inefficient search and retrieval strategies. Method: Two groups were compared: 141 individuals with schizophrenia and 119 healthy age and education-matched controls. Both groups performed semantic and phonetic verbal fluency tasks. Performance was evaluated using three scores, based on 1 number of words generated; 2 number of clustered/related words; and 3 switching score. A fourth performance score based on the number of clusters was also measured. Results: SZ individuals produced fewer words than controls. After controlling for the total number of words produced, a difference was observed between the groups in the number of cluster-related words generated in the semantic task. In both groups, the number of words generated in the semantic task was higher than that generated in the phonemic task, although a significant group vs. fluency type interaction showed that subjects with schizophrenia had disproportionate semantic fluency impairment. Working memory was positively associated with increased production of words within clusters and inversely correlated with switching. Conclusion: Semantic fluency impairment may be attributed to an inability (resulting from reduced cognitive control to distinguish target signal from competing noise and to maintain cues for production of memory probes.

A semantic-based method for extracting concept definitions from scientific publications: evaluation in the autism phenotype domain.

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Hassanpour, Saeed; O'Connor, Martin J; Das, Amar K

2013-08-12

A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based text-mining approach that can automatically identify such definitions within text. Using an existing knowledge base of 156 autism phenotype definitions and an annotated corpus of 26 source articles containing such definitions, we evaluated and compared the average rank of correctly identified rule definition or corresponding rule template using both our semantic-based approach and a standard term-based approach. We examined three separate scenarios: (1) the snippet of text contained a definition already in the knowledge base; (2) the snippet contained an alternative definition for a concept in the knowledge base; and (3) the snippet contained a definition not in the knowledge base. Our semantic-based approach had a higher average rank than the term-based approach for each of the three scenarios (scenario 1: 3.8 vs. 5.0; scenario 2: 2.8 vs. 4.9; and scenario 3: 4.5 vs. 6.2), with each comparison significant at the p-value of 0.05 using the Wilcoxon signed-rank test. Our work shows that leveraging existing domain knowledge in the information extraction of biomedical definitions significantly improves the correct identification of such knowledge within sentences. Our method can thus help researchers rapidly acquire knowledge about biomedical definitions that are specified and evolving within an ever-growing corpus of scientific publications.

Modified Differential Transform Method for Two Singular Boundary Values Problems

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Yinwei Lin

2014-01-01

Full Text Available This paper deals with the two singular boundary values problems of second order. Two singular points are both boundary values points of the differential equation. The numerical solutions are developed by modified differential transform method (DTM for expanded point. Linear and nonlinear models are solved by this method to get more reliable and efficient numerical results. It can also solve ordinary differential equations where the traditional one fails. Besides, we give the convergence of this new method.

The neural substrates of semantic memory deficits in early Alzheimer's disease: Clues from semantic priming effects and FDG-PET

Energy Technology Data Exchange (ETDEWEB)

Giffard, B.; Laisney, M.; Mezenge, F.; De la Sayette, V.; Eustache, F.; Desgranges, B. [Univ Caen Basse Normandie, INSERM, U923, Unite Rech, EPHE, Lab Neuropsychol, CHU Cote Nacre, GIP Cyceron, F-14033 Caen (France)

2008-07-01

The neural substrates responsible for semantic dysfunction during the early stages of AD have yet to be clearly identified. After a brief overview of the literature on normal and pathological semantic memory, we describe a new approach, designed to provide fresh insights into semantic deficits in AD. We mapped the correlations between resting-state brain glucose utilisation measured by FDG-PET and semantic priming scores in a group of 17 AD patients. The priming task, which yields a particularly pure measurement of semantic memory, was composed of related pairs of words sharing an attribute relationship (e.g. tiger-stripe). The priming scores correlated positively with the metabolism of the superior temporal areas on both sides, especially the right side, and this correlation was shown to be specific to the semantic priming effect.This pattern of results is discussed in the light of recent theoretical models of semantic memory, and suggests that a dysfunction of the right superior temporal cortex may contribute to early semantic deficits, characterised by the loss of specific features of concepts in AD. (authors)

Lagrange-Noether method for solving second-order differential equations

Institute of Scientific and Technical Information of China (English)

Wu Hui-Bin; Wu Run-Heng

2009-01-01

The purpose of this paper is to provide a new method called the Lagrange-Noether method for solving second-order differential equations. The method is,firstly,to write the second-order differential equations completely or partially in the form of Lagrange equations,and secondly,to obtain the integrals of the equations by using the Noether theory of the Lagrange system. An example is given to illustrate the application of the result.

A Generalization of Inquisitive Semantics

Czech Academy of Sciences Publication Activity Database

Punčochář, Vít

2016-01-01

Roč. 45, č. 4 (2016), s. 399-428 ISSN 0022-3611 R&D Projects: GA ČR(CZ) GA13-21076S Institutional support: RVO:67985955 Keywords : Intuitionistic logic * Superintuitionistic logics * Inquisitive logic * Topological semantics * Kripke semantics * Disjunction Subject RIV: AA - Philosophy ; Religion

The Role of Executive Function in the Semantic Comprehension Deficits of Stroke Aphasia and Semantic Dementia

Directory of Open Access Journals (Sweden)

Curtiss Chapman

2015-05-01

Results from 5 SD patients and 4 SA patients in our ongoing study suggest similar patterns of impairment on both semantic and executive function tasks for both patient groups. Both showed multi-modal semantic deficits via poor performance on at least 3 out of 5 semantic tasks tapping different modalities. Also, SA and SD patients showed no difference in consistency across semantic tasks (see Fig. 1a & b. Both groups also showed consistently poor performance on trail-making and verbal Stroop tasks compared to controls (see Figs. 1c & 1d. SD patients seem to be less impaired on both span measures (word span range: 2.17 – 4.43; digit span: 3.17 – 5.5 than SA patients (word span range: 1.63 – 3.75; digit span: 1.17 – 4.17, and performance was variable for both groups on non-verbal Stroop and picture-word interference. SD patients found many executive tasks too difficult to understand, which may be the reason for limited prior data for them on EF tasks.. These findings suggest that the use of syndrome categories like semantic dementia and comprehension-impaired stroke aphasia are not useful in distinguishing between storage and access deficits. Patients classified as having SD seem as likely as SA patients to have certain kinds of executive deficits and SA patients may be as likely as SD patients to show consistency across semantic tasks. The results imply that some other behavioral or neuroanatomical basis rather than syndrome classification should be used to address the hypothesized separation of storage vs. control aspects of semantic memory.

Application of the Generalized Differential Quadrature Method in Solving Burgers' Equations

International Nuclear Information System (INIS)

Mokhtari, R.; Toodar, A. Samadi; Chegini, N.G.

2011-01-01

The aim of this paper is to obtain numerical solutions of the one-dimensional, two-dimensional and coupled Burgers' equations through the generalized differential quadrature method (GDQM). The polynomial-based differential quadrature (PDQ) method is employed and the obtained system of ordinary differential equations is solved via the total variation diminishing Runge-Kutta (TVD-RK) method. The numerical solutions are satisfactorily coincident with the exact solutions. The method can compete against the methods applied in the literature. (general)

Semantic e-Learning: Next Generation of e-Learning?

Science.gov (United States)

Konstantinos, Markellos; Penelope, Markellou; Giannis, Koutsonikos; Aglaia, Liopa-Tsakalidi

Semantic e-learning aspires to be the next generation of e-learning, since the understanding of learning materials and knowledge semantics allows their advanced representation, manipulation, sharing, exchange and reuse and ultimately promote efficient online experiences for users. In this context, the paper firstly explores some fundamental Semantic Web technologies and then discusses current and potential applications of these technologies in e-learning domain, namely, Semantic portals, Semantic search, personalization, recommendation systems, social software and Web 2.0 tools. Finally, it highlights future research directions and open issues of the field.

Introduction to numerical methods for time dependent differential equations

CERN Document Server

Kreiss, Heinz-Otto

2014-01-01

Introduces both the fundamentals of time dependent differential equations and their numerical solutions Introduction to Numerical Methods for Time Dependent Differential Equations delves into the underlying mathematical theory needed to solve time dependent differential equations numerically. Written as a self-contained introduction, the book is divided into two parts to emphasize both ordinary differential equations (ODEs) and partial differential equations (PDEs). Beginning with ODEs and their approximations, the authors provide a crucial presentation of fundamental notions, such as the t

Explaining Semantic Short-Term Memory Deficits: Evidence for the Critical Role of Semantic Control

Science.gov (United States)

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…

Intelligent query processing for semantic mediation of information systems

Directory of Open Access Journals (Sweden)

Saber Benharzallah

2011-11-01

Full Text Available We propose an intelligent and an efficient query processing approach for semantic mediation of information systems. We propose also a generic multi agent architecture that supports our approach. Our approach focuses on the exploitation of intelligent agents for query reformulation and the use of a new technology for the semantic representation. The algorithm is self-adapted to the changes of the environment, offers a wide aptitude and solves the various data conflicts in a dynamic way; it also reformulates the query using the schema mediation method for the discovered systems and the context mediation for the other systems.

SM4MQ: A Semantic Model for Multidimensional Queries

DEFF Research Database (Denmark)

Varga, Jovan; Dobrokhotova, Ekaterina; Romero, Oscar

2017-01-01

On-Line Analytical Processing (OLAP) is a data analysis approach to support decision-making. On top of that, Exploratory OLAP is a novel initiative for the convergence of OLAP and the Semantic Web (SW) that enables the use of OLAP techniques on SW data. Moreover, OLAP approaches exploit different......, sharing, and reuse on the SW. As OLAP is based on the underlying multidimensional (MD) data model we denote such queries as MD queries and define SM4MQ: A Semantic Model for Multidimensional Queries. Furthermore, we propose a method to automate the exploitation of queries by means of SPARQL. We apply...

The Semantics of "Violence"

DEFF Research Database (Denmark)

Levisen, Carsten

This paper presents a semantic analysis of “violence” – a word around which Anglo-internationaldiscourses revolve. Many ethnolinguistic communities around the world are currently adapting thisEnglish lexical concept into their linguistic systems, and, presumably also, the view of the worldembodied...... by the “violence” concept.Based on semantic fieldwork in Port Vila, the creolophone capital of Vanuatu in the SouthPacific, the paper investigates the discursive introduction of “violence” into a community which,until recently, lived by other concepts. I compare and contrast the traditional Bislama concepts...... kilimand faetem with the newly imported English word vaeolens (violence). My study provides newevidence for how cognitive and semantic change co-occur in the context of postcolonial linguisticcommunities, and my paper addresses an important, ongoing controversy related to the notion of“Anglocentric bias...

Determining Semantically Related Significant Genes.

Science.gov (United States)

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.

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

OpenAIRE

Hamed Hassanzadeh; MohammadReza Keyvanpour

2011-01-01

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as ...

Auxiliary equation method for solving nonlinear partial differential equations

International Nuclear Information System (INIS)

Sirendaoreji,; Jiong, Sun

2003-01-01

By using the solutions of an auxiliary ordinary differential equation, a direct algebraic method is described to construct several kinds of exact travelling wave solutions for some nonlinear partial differential equations. By this method some physically important nonlinear equations are investigated and new exact travelling wave solutions are explicitly obtained with the aid of symbolic computation

Discrete variational derivative method a structure-preserving numerical method for partial differential equations

CERN Document Server

Furihata, Daisuke

2010-01-01

Nonlinear Partial Differential Equations (PDEs) have become increasingly important in the description of physical phenomena. Unlike Ordinary Differential Equations, PDEs can be used to effectively model multidimensional systems. The methods put forward in Discrete Variational Derivative Method concentrate on a new class of ""structure-preserving numerical equations"" which improves the qualitative behaviour of the PDE solutions and allows for stable computing. The authors have also taken care to present their methods in an accessible manner, which means that the book will be useful to engineer

On Solving the Lorenz System by Differential Transformation Method

International Nuclear Information System (INIS)

Al-Sawalha, M. Mossa; Noorani, M. S. M.

2008-01-01

The differential transformation method (DTM) is employed to solve a nonlinear differential equation, namely the Lorenz system. Numerical results are compared to those obtained by the Runge–Kutta method to illustrate the preciseness and effectiveness of the proposed method. In particular, we examine the accuracy of the (DTM) as the Lorenz system changes from a non-chaotic system to a chaotic one. It is shown that the (DTM) is robust, accurate and easy to apply

Age of Bilingual Exposure Is Related to the Contribution of Phonological and Semantic Knowledge to Successful Reading Development.

Science.gov (United States)

Jasińska, Kaja K; Petitto, Laura-Ann

2018-01-01

Bilingual children's reading as a function of age of first bilingual language exposure (AoE) was examined. Bilingual (varied AoE) and monolingual children (N = 421) were compared in their English language and reading abilities (6-10 years) using phonological awareness, semantic knowledge, and reading tasks. Structural equation modeling was applied to determine how bilingual AoE predicts reading outcomes. Early exposed bilinguals outperformed monolinguals on phonological awareness and word reading. Phonology and semantic (vocabulary) knowledge differentially predicted reading depending on the bilingual experience and AoE. Understanding how bilingual experiences impact phonological awareness and semantic knowledge, and in turn, impact reading outcomes is relevant for our understanding of what language and reading skills are best to focus on, and when, to promote optimal reading success. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

On the Semantics of Focus

Science.gov (United States)

Kess, Joseph F.

1975-01-01

This article discusses the semantics of the notion of focus, insofar as it relates to Filipino languages. The evolution of this notion is reviewed, and an alternative explanation of it is given, stressing the fact that grammar and semantics should be kept separate in a discussion of focus. (CLK)

Semantics of data and service registration to advance interdisciplinary information and data access.

Science.gov (United States)

Fox, P. P.; McGuinness, D. L.; Raskin, R.; Sinha, A. K.

2008-12-01

In developing an application of semantic web methods and technologies to address the integration of heterogeneous and interdisciplinary earth-science datasets, we have developed methodologies for creating rich semantic descriptions (ontologies) of the application domains. We have leveraged and extended where possible existing ontology frameworks such as SWEET. As a result of this semantic approach, we have also utilized ontologic descriptions of key enabling elements of the application, such as the registration of datasets with ontologies at several levels of granularity. This has enabled the location and usage of the data across disciplines. We are also realizing the need to develop similar semantic registration of web service data holdings as well as those provided with community and/or standard markup languages (e.g. GeoSciML). This level of semantic enablement extending beyond domain terms and relations significantly enhances our ability to provide a coherent semantic data framework for data and information systems. Much of this work is on the frontier of technology development and we will present the current and near-future capabilities we are developing. This work arises from the Semantically-Enabled Science Data Integration (SESDI) project, which is an NASA/ESTO/ACCESS-funded project involving the High Altitude Observatory at the National Center for Atmospheric Research (NCAR), McGuinness Associates Consulting, NASA/JPL and Virginia Polytechnic University.

A development framework for semantically interoperable health information systems.

Science.gov (United States)

Lopez, Diego M; Blobel, Bernd G M E

2009-02-01

Semantic interoperability is a basic challenge to be met for new generations of distributed, communicating and co-operating health information systems (HIS) enabling shared care and e-Health. Analysis, design, implementation and maintenance of such systems and intrinsic architectures have to follow a unified development methodology. The Generic Component Model (GCM) is used as a framework for modeling any system to evaluate and harmonize state of the art architecture development approaches and standards for health information systems as well as to derive a coherent architecture development framework for sustainable, semantically interoperable HIS and their components. The proposed methodology is based on the Rational Unified Process (RUP), taking advantage of its flexibility to be configured for integrating other architectural approaches such as Service-Oriented Architecture (SOA), Model-Driven Architecture (MDA), ISO 10746, and HL7 Development Framework (HDF). Existing architectural approaches have been analyzed, compared and finally harmonized towards an architecture development framework for advanced health information systems. Starting with the requirements for semantic interoperability derived from paradigm changes for health information systems, and supported in formal software process engineering methods, an appropriate development framework for semantically interoperable HIS has been provided. The usability of the framework has been exemplified in a public health scenario.

A novel method to solve functional differential equations

International Nuclear Information System (INIS)

Tapia, V.

1990-01-01

A method to solve differential equations containing the variational operator as the derivation operation is presented. They are called variational differential equations (VDE). The solution to a VDE should be a function containing the derivatives, with respect to the base space coordinates, of the fields up to a generic order s: a s-th-order function. The variational operator doubles the order of the function on which it acts. Therefore, in order to make compatible the orders of the different terms appearing in a VDE, the solution should be a function containing the derivatives of the fields at all orders. But this takes us again back to the functional methods. In order to avoid this, one must restrict the considerations, in the case of second-order VDEs, to the space of s-th-order functions on which the variational operator acts transitively. These functions have been characterized for a one-dimensional base space for the first- and second-order cases. These functions turn out to be polynomial in the highest-order derivatives of the fields with functions of the lower-order derivatives as coefficients. Then VDEs reduce to a system of coupled partial differential equations for the coefficients above mentioned. The importance of the method lies on the fact that the solutions to VDEs are in a one-to-one correspondence with the solutions of functional differential equations. The previous method finds direct applications in quantum field theory, where the Schroedinger equation plays a central role. Since the Schroedinger equation is reduced to a system of coupled partial differential equations, this provides a nonperturbative scheme for quantum field theory. As an example, the massless scalar field is considered

Information Interaction as a Mechanism of Semantic Gap Elimination

Directory of Open Access Journals (Sweden)

Victor Y. Tsvetkov

2013-01-01

Full Text Available The article studies semantic gap as an objective phenomenon, shows that semantic gap occurs both in parallel computing and in other areas. Semantic description of the content is revealed as a set of different descriptions. Causes of semantic gap are described. The content of information exchange is explained in the article. Information interaction in the semantic field is interpreted as a mechanism to lessen the gap

On the (un)suitability of semantic categories

DEFF Research Database (Denmark)

Rijkhoff, Jan

2009-01-01

Since Greenberg’s groundbreaking publication on universals of grammar, typologists have used semantic categories to investigate (constraints on) morphological and syntactic variation in the world’s languages and this tradition has been continued in the WALS project. It is argued here that the emp......Since Greenberg’s groundbreaking publication on universals of grammar, typologists have used semantic categories to investigate (constraints on) morphological and syntactic variation in the world’s languages and this tradition has been continued in the WALS project. It is argued here...... that the employment of semantic categories has some serious drawbacks, however, suggesting that semantic categories, just like formal categories, cannot be equated across languages in morphosyntactic typology. Whereas formal categories are too narrow in that they do not cover all structural variants attested across...... languages, semantic categories can be too wide, including too many structural variants. Furthermore, it appears that in some major typological studies semantic categories have been confused with formal categories. A possible solution is pointed out: typologists first need to make sure that the forms...

An Operational Semantics for Trust Policies

DEFF Research Database (Denmark)

Krukow, Karl

2006-01-01

In the trust-structure framework for trust management, principals specify their trusting relationships in terms of trust policies. In their paper on trust structures, Carbone et al. present a language for such policies, and provide a suitable denotational semantics. The semantics ensures that for......In the trust-structure framework for trust management, principals specify their trusting relationships in terms of trust policies. In their paper on trust structures, Carbone et al. present a language for such policies, and provide a suitable denotational semantics. The semantics ensures...... that for any collection of policies, there is always a unique global trust-state, compatible with all the policies, specifying everyone's degree of trust in everyone else. However, as the authors themselves point out, the language lacks an operational model: the global trust-state is a well......-defined mathematical object, but it is not clear how principals can actually compute it. This becomes even more apparent when one considers the intended application environment: vast numbers of autonomous principals, distributed and possibly mobile. We provide a compositional operational semantics for a language...

Application of differential transformation method for solving dengue transmission mathematical model

Science.gov (United States)

Ndii, Meksianis Z.; Anggriani, Nursanti; Supriatna, Asep K.

2018-03-01

The differential transformation method (DTM) is a semi-analytical numerical technique which depends on Taylor series and has application in many areas including Biomathematics. The aim of this paper is to employ the differential transformation method (DTM) to solve system of non-linear differential equations for dengue transmission mathematical model. Analytical and numerical solutions are determined and the results are compared to that of Runge-Kutta method. We found a good agreement between DTM and Runge-Kutta method.

Stochastic Automata for Outdoor Semantic Mapping using Optimised Signal Quantisation

DEFF Research Database (Denmark)

Caponetti, Fabio; Blas, Morten Rufus; Blanke, Mogens

2011-01-01

Autonomous robots require many types of information to obtain intelligent and safe behaviours. For outdoor operations, semantic mapping is essential and this paper proposes a stochastic automaton to localise the robot within the semantic map. For correct modelling and classi¯cation under...... uncertainty, this paper suggests quantising robotic perceptual features, according to a probabilistic description, and then optimising the quantisation. The proposed method is compared with other state-of-the-art techniques that can assess the con¯dence of their classi¯cation. Data recorded on an autonomous...

The semantic similarity ensemble

Directory of Open Access Journals (Sweden)

Andrea Ballatore

2013-12-01

Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

Semantic similarity measures in the biomedical domain by leveraging a web search engine.

Science.gov (United States)

Hsieh, Sheau-Ling; Chang, Wen-Yung; Chen, Chi-Huang; Weng, Yung-Ching

2013-07-01

Various researches in web related semantic similarity measures have been deployed. However, measuring semantic similarity between two terms remains a challenging task. The traditional ontology-based methodologies have a limitation that both concepts must be resided in the same ontology tree(s). Unfortunately, in practice, the assumption is not always applicable. On the other hand, if the corpus is sufficiently adequate, the corpus-based methodologies can overcome the limitation. Now, the web is a continuous and enormous growth corpus. Therefore, a method of estimating semantic similarity is proposed via exploiting the page counts of two biomedical concepts returned by Google AJAX web search engine. The features are extracted as the co-occurrence patterns of two given terms P and Q, by querying P, Q, as well as P AND Q, and the web search hit counts of the defined lexico-syntactic patterns. These similarity scores of different patterns are evaluated, by adapting support vector machines for classification, to leverage the robustness of semantic similarity measures. Experimental results validating against two datasets: dataset 1 provided by A. Hliaoutakis; dataset 2 provided by T. Pedersen, are presented and discussed. In dataset 1, the proposed approach achieves the best correlation coefficient (0.802) under SNOMED-CT. In dataset 2, the proposed method obtains the best correlation coefficient (SNOMED-CT: 0.705; MeSH: 0.723) with physician scores comparing with measures of other methods. However, the correlation coefficients (SNOMED-CT: 0.496; MeSH: 0.539) with coder scores received opposite outcomes. In conclusion, the semantic similarity findings of the proposed method are close to those of physicians' ratings. Furthermore, the study provides a cornerstone investigation for extracting fully relevant information from digitizing, free-text medical records in the National Taiwan University Hospital database.

SEMANTIC3D.NET: a New Large-Scale Point Cloud Classification Benchmark

Science.gov (United States)

Hackel, T.; Savinov, N.; Ladicky, L.; Wegner, J. D.; Schindler, K.; Pollefeys, M.

2017-05-01

This paper presents a new 3D point cloud classification benchmark data set with over four billion manually labelled points, meant as input for data-hungry (deep) learning methods. We also discuss first submissions to the benchmark that use deep convolutional neural networks (CNNs) as a work horse, which already show remarkable performance improvements over state-of-the-art. CNNs have become the de-facto standard for many tasks in computer vision and machine learning like semantic segmentation or object detection in images, but have no yet led to a true breakthrough for 3D point cloud labelling tasks due to lack of training data. With the massive data set presented in this paper, we aim at closing this data gap to help unleash the full potential of deep learning methods for 3D labelling tasks. Our semantic3D.net data set consists of dense point clouds acquired with static terrestrial laser scanners. It contains 8 semantic classes and covers a wide range of urban outdoor scenes: churches, streets, railroad tracks, squares, villages, soccer fields and castles. We describe our labelling interface and show that our data set provides more dense and complete point clouds with much higher overall number of labelled points compared to those already available to the research community. We further provide baseline method descriptions and comparison between methods submitted to our online system. We hope semantic3D.net will pave the way for deep learning methods in 3D point cloud labelling to learn richer, more general 3D representations, and first submissions after only a few months indicate that this might indeed be the case.

ERPs, semantic processing and age.

Science.gov (United States)

Miyamoto, T; Katayama, J; Koyama, T

1998-06-01

ERPs (N400, LPC and CNV) were elicited in two sets of subjects grouped according to age (young vs. elderly) using a word-pair category matching paradigm. Each prime consisted of a Japanese noun (constructed from two to four characters of the Hiragana) followed by one Chinese character (Kanji) as the target, this latter representing one of five semantic categories. There were two equally probable target conditions: match or mismatch. Each target was preceded by a prime, either belonging to, or not belonging to, the same semantic category. The subjects were required to respond with a specified button press to the given target according to the condition. We found RTs to be longer in the elderly subjects and under the mismatch condition. N400 amplitude was reduced in the elderly subjects under the mismatch condition and there was no difference between match and mismatch response, which were similar in amplitude to that under match condition for the young subjects. In addition, the CNV amplitudes were larger in the elderly subjects. These results suggested that functional changes in semantic processing through aging (larger semantic networks and diffuse semantic activation) were the cause of this N400 reduction, attributing a subsidiary role to attentional disturbance. We also discuss the importance of taking age-related changes into consideration in clinical studies.

The semantics of prosody: acoustic and perceptual evidence of prosodic correlates to word meaning.

Science.gov (United States)

Nygaard, Lynne C; Herold, Debora S; Namy, Laura L

2009-01-01

This investigation examined whether speakers produce reliable prosodic correlates to meaning across semantic domains and whether listeners use these cues to derive word meaning from novel words. Speakers were asked to produce phrases in infant-directed speech in which novel words were used to convey one of two meanings from a set of antonym pairs (e.g., big/small). Acoustic analyses revealed that some acoustic features were correlated with overall valence of the meaning. However, each word meaning also displayed a unique acoustic signature, and semantically related meanings elicited similar acoustic profiles. In two perceptual tests, listeners either attempted to identify the novel words with a matching meaning dimension (picture pair) or with mismatched meaning dimensions. Listeners inferred the meaning of the novel words significantly more often when prosody matched the word meaning choices than when prosody mismatched. These findings suggest that speech contains reliable prosodic markers to word meaning and that listeners use these prosodic cues to differentiate meanings. That prosody is semantic suggests a reconceptualization of traditional distinctions between linguistic and nonlinguistic properties of spoken language. Copyright © 2009 Cognitive Science Society, Inc.

Runge-Kutta Methods for Linear Ordinary Differential Equations

Science.gov (United States)

Zingg, David W.; Chisholm, Todd T.

1997-01-01

Three new Runge-Kutta methods are presented for numerical integration of systems of linear inhomogeneous ordinary differential equations (ODES) with constant coefficients. Such ODEs arise in the numerical solution of the partial differential equations governing linear wave phenomena. The restriction to linear ODEs with constant coefficients reduces the number of conditions which the coefficients of the Runge-Kutta method must satisfy. This freedom is used to develop methods which are more efficient than conventional Runge-Kutta methods. A fourth-order method is presented which uses only two memory locations per dependent variable, while the classical fourth-order Runge-Kutta method uses three. This method is an excellent choice for simulations of linear wave phenomena if memory is a primary concern. In addition, fifth- and sixth-order methods are presented which require five and six stages, respectively, one fewer than their conventional counterparts, and are therefore more efficient. These methods are an excellent option for use with high-order spatial discretizations.

Semantic interpretation of search engine resultant

Science.gov (United States)

Nasution, M. K. M.

2018-01-01

In semantic, logical language can be interpreted in various forms, but the certainty of meaning is included in the uncertainty, which directly always influences the role of technology. One results of this uncertainty applies to search engines as user interfaces with information spaces such as the Web. Therefore, the behaviour of search engine results should be interpreted with certainty through semantic formulation as interpretation. Behaviour formulation shows there are various interpretations that can be done semantically either temporary, inclusion, or repeat.

Waveform relaxation methods for implicit differential equations

NARCIS (Netherlands)

P.J. van der Houwen; W.A. van der Veen

1996-01-01

textabstractWe apply a Runge-Kutta-based waveform relaxation method to initial-value problems for implicit differential equations. In the implementation of such methods, a sequence of nonlinear systems has to be solved iteratively in each step of the integration process. The size of these systems

Behavior Modification Through Covert Semantic Desensitization

Science.gov (United States)

Hekmat, Hamid; Vanian, Daniel

1971-01-01

Results support the hypothesized relationship between meaning and phobia. Semantic desensitization techniques based on counter conditioning of meaning were significantly effective in altering the semantic value of the word from unpleasantness to neutrality. (Author)

Semantic processing of EHR data for clinical research.

Science.gov (United States)

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

2015-12-01

There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data. Copyright © 2015 Elsevier Inc. All rights reserved.

Semantic acquisition games harnessing manpower for creating semantics

CERN Document Server

Šimko, Jakub

2014-01-01

A comprehensive and extensive review of state-of-the-art in semantics acquisition game (SAG) design A set of design patterns for SAG designers A set of case studies (real SAG projects) demonstrating the use of SAG design patterns

Semantic transparency affects morphological priming . . . eventually.

Science.gov (United States)

Heyer, Vera; Kornishova, Dana

2018-05-01

Semantic transparency has been in the focus of psycholinguistic research for decades, with the controversy about the time course of the application of morpho-semantic information during the processing of morphologically complex words not yet resolved. This study reports two masked priming studies with English - ness and Russian - ost' nominalisations, investigating how semantic transparency modulates native speakers' morphological priming effects at short and long stimulus onset asynchronies (SOAs). In both languages, we found increased morphological priming for nominalisations at the transparent end of the scale (e.g. paleness - pale) in comparison to items at the opaque end of the scale (e.g. business - busy) but only at longer prime durations. The present findings are in line with models that posit an initial phase of morpho-orthographic (semantically blind) decomposition.

Semantic computing and language knowledge bases

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Wang, Lei; Wang, Houfeng; Yu, Shiwen

2017-09-01

As the proposition of the next-generation Web - semantic Web, semantic computing has been drawing more and more attention within the circle and the industries. A lot of research has been conducted on the theory and methodology of the subject, and potential applications have also been investigated and proposed in many fields. The progress of semantic computing made so far cannot be detached from its supporting pivot - language resources, for instance, language knowledge bases. This paper proposes three perspectives of semantic computing from a macro view and describes the current status of affairs about the construction of language knowledge bases and the related research and applications that have been carried out on the basis of these resources via a case study in the Institute of Computational Linguistics at Peking University.

Semantic web for integrated network analysis in biomedicine.

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

2009-03-01

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

Intuitions and Competence in Formal Semantics

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Martin Stokhof

2010-12-01

Full Text Available In formal semantics intuition plays a key role, in two ways. Intuitions about semantic properties of expressions are the primary data, and intuitions of the semanticists are the main access to these data. The paper investigates how this dual role is related to the concept of competence and the role that this concept plays in semantics. And it inquires whether the self-reflexive role of intuitions has consequences for the methodology of semantics as an empirical discipline.ReferencesBaggio, Giosuè, van Lambalgen, Michiel & Hagoort, Peter. 2008. ‘Computing and recomputing discourse models: an ERP study of the semantics of temporal connectives’. Journal of Memory and Language 59, no. 1: 36–53.http://dx.doi.org/10.1016/j.jml.2008.02.005Chierchia, Gennaro & McConnell-Ginet, Sally. 2000. Meaning and Grammar. second ed. Cambridge, Mass.: MIT Press.Chomsky, Noam. 1965. Aspects of the Theory of Syntax. Cambridge, Mass.: MIT Press.Cresswell, Max J. 1978. ‘Semantic competence’. In F. Guenthner & M. Guenther-Reutter (eds. ‘Meaning and Translation’, 9–27. Duckworth, London. de Swart, Henriëtte. 1998. Introduction to Natural Language Semantics. Stanford: CSLI.Dowty, David, Wall, Robert & Peters, Stanley. 1981. Introduction to Montague Semantics. Dordrecht: Reidel.Heim, Irene & Kratzer, Angelika. 1998. Semantics in Generative Grammar. Oxford: Blackwell.Larson, Richard & Segal, Gabriel. 1995. Knowledge of Meaning. Cambridge, Mass.: MIT Press.Lewis, David K. 1975. ‘Languages and Language’. In Keith Gunderson (ed. ‘Language, Mind and Knowledge’, 3–35. Minneapolis: University of Minnesota Press.Montague, Richard. 1970. ‘Universal Grammar’. Theoria 36: 373–98.http://dx.doi.org/10.1111/j.1755-2567.1970.tb00434.xPartee, Barbara H. 1979. ‘Semantics – Mathematics or Psychology?’ In Rainer Bäuerle, Urs Egli & Arnim von Stechow (eds. ‘Semantics from Different Points of View’, 1–14. Berlin: Springer.Partee, Barbara H. 1980. �

The influence of rTMS over prefrontal and motor areas in a morphological task: grammatical vs. semantic effects.

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Gerfo, Emanuele Lo; Oliveri, Massimiliano; Torriero, Sara; Salerno, Silvia; Koch, Giacomo; Caltagirone, Carlo

2008-01-31

We investigated the differential role of two frontal regions in the processing of grammatical and semantic knowledge. Given the documented specificity of the prefrontal cortex for the grammatical class of verbs, and of the primary motor cortex for the semantic class of action words, we sought to investigate whether the prefrontal cortex is also sensitive to semantic effects, and whether the motor cortex is also sensitive to grammatical class effects. We used repetitive transcranial magnetic stimulation (rTMS) to suppress the excitability of a portion of left prefontal cortex (first experiment) and of the motor area (second experiment). In the first experiment we found that rTMS applied to the left prefrontal cortex delays the processing of action verbs' retrieval, but is not critical for retrieval of state verbs and state nouns. In the second experiment we found that rTMS applied to the left motor cortex delays the processing of action words, both name and verbs, while it is not critical for the processing of state words. These results support the notion that left prefrontal and motor cortex are involved in the process of action word retrieval. Left prefrontal cortex subserves processing of both grammatical and semantic information, whereas motor cortex contributes to the processing of semantic representation of action words without any involvement in the representation of grammatical categories.

Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.

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Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin

2018-04-03

Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.

Semantic transference for enriching multilingual biomedical knowledge resources.

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Pérez, María; Berlanga, Rafael

2015-12-01

Biomedical knowledge resources (KRs) are mainly expressed in English, and many applications using them suffer from the scarcity of knowledge in non-English languages. The goal of the present work is to take maximum profit from existing multilingual biomedical KRs lexicons to enrich their non-English counterparts. We propose to combine different automatic methods to generate pair-wise language alignments. More specifically, we use two well-known translation methods (GIZA++ and Moses), and we propose a new ad hoc method specially devised for multilingual KRs. Then, resulting alignments are used to transfer semantics between KRs across their languages. Transference quality is ensured by checking the semantic coherence of the generated alignments. Experiments have been carried out over the Spanish, French and German UMLS Metathesaurus counterparts. As a result, the enriched Spanish KR can grow up to 1,514,217 concepts (originally 286,659), the French KR up to 1,104,968 concepts (originally 83,119), and the German KR up to 1,136,020 concepts (originally 86,842). Copyright © 2015 Elsevier Inc. All rights reserved.

Semantic relation vs. surprise: the differential effects of related and unrelated co-verbal gestures on neural encoding and subsequent recognition.

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Straube, Benjamin; Meyer, Lea; Green, Antonia; Kircher, Tilo

2014-06-03

Speech-associated gesturing leads to memory advantages for spoken sentences. However, unexpected or surprising events are also likely to be remembered. With this study we test the hypothesis that different neural mechanisms (semantic elaboration and surprise) lead to memory advantages for iconic and unrelated gestures. During fMRI-data acquisition participants were presented with video clips of an actor verbalising concrete sentences accompanied by iconic gestures (IG; e.g., circular gesture; sentence: "The man is sitting at the round table"), unrelated free gestures (FG; e.g., unrelated up down movements; same sentence) and no gestures (NG; same sentence). After scanning, recognition performance for the three conditions was tested. Videos were evaluated regarding semantic relation and surprise by a different group of participants. The semantic relationship between speech and gesture was rated higher for IG (IG>FG), whereas surprise was rated higher for FG (FG>IG). Activation of the hippocampus correlated with subsequent memory performance of both gesture conditions (IG+FG>NG). For the IG condition we found activation in the left temporal pole and middle cingulate cortex (MCC; IG>FG). In contrast, for the FG condition posterior thalamic structures (FG>IG) as well as anterior and posterior cingulate cortices were activated (FG>NG). Our behavioral and fMRI-data suggest different mechanisms for processing related and unrelated co-verbal gestures, both of them leading to enhanced memory performance. Whereas activation in MCC and left temporal pole for iconic co-verbal gestures may reflect semantic memory processes, memory enhancement for unrelated gestures relies on the surprise response, mediated by anterior/posterior cingulate cortex and thalamico-hippocampal structures. Copyright © 2014 Elsevier B.V. All rights reserved.

Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer

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Mauro Castelli

2015-01-01

Full Text Available Energy consumption forecasting (ECF is an important policy issue in today’s economies. An accurate ECF has great benefits for electric utilities and both negative and positive errors lead to increased operating costs. The paper proposes a semantic based genetic programming framework to address the ECF problem. In particular, we propose a system that finds (quasi-perfect solutions with high probability and that generates models able to produce near optimal predictions also on unseen data. The framework blends a recently developed version of genetic programming that integrates semantic genetic operators with a local search method. The main idea in combining semantic genetic programming and a local searcher is to couple the exploration ability of the former with the exploitation ability of the latter. Experimental results confirm the suitability of the proposed method in predicting the energy consumption. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that including a local searcher in the geometric semantic genetic programming system can speed up the search process and can result in fitter models that are able to produce an accurate forecasting also on unseen data.

Ontology Based Resolution of Semantic Conflicts in Information Integration

Institute of Scientific and Technical Information of China (English)

LU Han; LI Qing-zhong

2004-01-01

Semantic conflict is the conflict caused by using different ways in heterogeneous systems to express the same entity in reality.This prevents information integration from accomplishing semantic coherence.Since ontology helps to solve semantic problems, this area has become a hot topic in information integration.In this paper, we introduce semantic conflict into information integration of heterogeneous applications.We discuss the origins and categories of the conflict, and present an ontology-based schema mapping approach to eliminate semantic conflicts.

A logical correspondence between natural semantics and abstract machines

DEFF Research Database (Denmark)

Simmons, Robert J.; Zerny, Ian

2013-01-01

We present a logical correspondence between natural semantics and abstract machines. This correspondence enables the mechanical and fully-correct construction of an abstract machine from a natural semantics. Our logical correspondence mirrors the Reynolds functional correspondence, but we...... manipulate semantic specifications encoded in a logical framework instead of manipulating functional programs. Natural semantics and abstract machines are instances of substructural operational semantics. As a byproduct, using a substructural logical framework, we bring concurrent and stateful models...

Approximate Method for Solving the Linear Fuzzy Delay Differential Equations

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S. Narayanamoorthy

2015-01-01

Full Text Available We propose an algorithm of the approximate method to solve linear fuzzy delay differential equations using Adomian decomposition method. The detailed algorithm of the approach is provided. The approximate solution is compared with the exact solution to confirm the validity and efficiency of the method to handle linear fuzzy delay differential equation. To show this proper features of this proposed method, numerical example is illustrated.

On the universal structure of human lexical semantics.

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Youn, Hyejin; Sutton, Logan; Smith, Eric; Moore, Cristopher; Wilkins, Jon F; Maddieson, Ian; Croft, William; Bhattacharya, Tanmoy

2016-02-16

How universal is human conceptual structure? The way concepts are organized in the human brain may reflect distinct features of cultural, historical, and environmental background in addition to properties universal to human cognition. Semantics, or meaning expressed through language, provides indirect access to the underlying conceptual structure, but meaning is notoriously difficult to measure, let alone parameterize. Here, we provide an empirical measure of semantic proximity between concepts using cross-linguistic dictionaries to translate words to and from languages carefully selected to be representative of worldwide diversity. These translations reveal cases where a particular language uses a single "polysemous" word to express multiple concepts that another language represents using distinct words. We use the frequency of such polysemies linking two concepts as a measure of their semantic proximity and represent the pattern of these linkages by a weighted network. This network is highly structured: Certain concepts are far more prone to polysemy than others, and naturally interpretable clusters of closely related concepts emerge. Statistical analysis of the polysemies observed in a subset of the basic vocabulary shows that these structural properties are consistent across different language groups, and largely independent of geography, environment, and the presence or absence of a literary tradition. The methods developed here can be applied to any semantic domain to reveal the extent to which its conceptual structure is, similarly, a universal attribute of human cognition and language use.

Effects of literacy on semantic verbal fluency in an immigrant population

DEFF Research Database (Denmark)

Nielsen, T. Rune; Waldemar, Gunhild

2016-01-01

OBJECTIVE: A significant impact of limited schooling and illiteracy has been found on numerous neuropsychological tests, which may partly be due to the ecological relevance of the tests in the context of illiteracy. The aims of this study were to compare the performance of illiterate and literate...... and acculturation score did not affect this interaction effect. CONCLUSIONS: Overall, our results are in line with previous studies comparing semantic fluency in illiterate and literate individuals. The results lend further support to the strong associations between literacy, semantic verbal fluency performance...... immigrants on two semantic criteria for the verbal fluency test, and examine the influence of acculturation on test performances. METHOD: Performances of 20 cognitively unimpaired illiterate and 21 literate Turkish immigrants aged ≥50 years were compared on an animal and supermarket criterion...

Semantic Web for Chemical Genomics – need, how to, and hurdles

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Talapady Bhat

2007-08-01

Full Text Available Semantic Web has been often suggested as the information technology solution to the growing problem in managing the millions of data points generated by modern science such as nanotechnology and high through-put screening for drugs. However, the progress towards this vision envisaged by the W3C has been very limited. Here we discuss –some of the obstacles to the realization of this vision and we make some suggestions as to how one may overcome some of these hurdles? Here we discuss some of these issues and present thoughts on an alternative method to Semantic Web that is less drastic in requirements. This method does not require the use of RDF and Protege, and it works in an environment currently used by the chemical and biological database providers. In our method one attempts to use as many components as possible from the tools already used by the database providers and one brings in far fewer new tools and techniques compared to the method that use RDF or Protégé. Our method uses a standard database environment and web tools rather than the RDF and Protégé to manage user interface and the data is held in a database rather than using RDF. This method shifts the task of building Semantic knowledge-base and ontology from RDF and Protégé to a SQL based database environment.

“Pre-semantic” cognition revisited: Critical differences between semantic aphasia and semantic dementia

OpenAIRE

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 atypical of the domain and "regularisation errors" (irregular/atypical items are produced as if they were domain-typical). The emergence of this pattern ...

Hierarchical Matching of Traffic Information Services Using Semantic Similarity

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Zongtao Duan

2018-01-01