Is it advisable to include negative attributes to assess the stereotype content? Yes, but only in the morality dimension.

PubMed

Sayans-Jiménez, Pablo; Rojas Tejada, Antonio José; Cuadrado Guirado, Isabel

2017-04-01

Competence, morality and sociability dimensions have shown to be essential to measure stereotypes. Theoretically, the attributes associated with the negative pole of morality are more reliable and have shown to have higher evaluative weight. However, the current research usually employs only positive attributes to measure each dimension. Since the advantages of the inclusion of negative morality are clear it would be interesting to know about the effects of the inclusion of such type of attributes (i.e., it is good or bad for the measurement). The purpose of this study is to examine if the addition of negative items makes possible to improve the stereotype content measures. This study compares the differences between scales with various compositions of positive and negative items of stereotypes to predict three related variables: anger, fear and a semantic differential of evaluation. The study was carried out with a sample of 550 Spaniards. The data found highlights the importance of using attributes of the negative pole of morality in studying stereotypes. Their use was able to explain the intergroup emotional responses and the semantic differential more efficiently. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Selective sex differences in declarative memory.

PubMed

Maitland, Scott B; Herlitz, Agneta; Nyberg, Lars; Bäckman, Lars; Nilsson, Lars-Göran

2004-10-01

Sex invariance of a six-factor, higher order model of declarative memory (two second-order factors: episodic and semantic memory; and four first-order factors: recall, recognition, fluency, and knowledge) was established for 1,796 participants (35-85 years). Metric invariance of first- and second-order factor loadings across sex was demonstrated. At the second-order level, a female advantage was observed for both episodic and semantic memory. At the first-order level, sex differences in episodic memory were apparent for both recall and recognition, whereas the differences in semantic memory were driven by a female superiority in fluency. Additional tests of sex differences in three age groups (35-50, 55-65, and 70-85 years of age) indicated that the female superiority in declarative memory diminished with advancing age. The factor-specific sex differences are discussed in relation to sex differences in hippocampal function.

Lexicality Effects in Word and Nonword Recall of Semantic Dementia and Progressive Nonfluent Aphasia

PubMed Central

Reilly, Jamie; Troche, Joshua; Chatel, Alison; Park, Hyejin; Kalinyak-Fliszar, Michelene; Antonucci, Sharon M.; Martin, Nadine

2012-01-01

Background Verbal working memory is an essential component of many language functions, including sentence comprehension and word learning. As such, working memory has emerged as a domain of intense research interest both in aphasiology and in the broader field of cognitive neuroscience. The integrity of verbal working memory encoding relies on a fluid interaction between semantic and phonological processes. That is, we encode verbal detail using many cues related to both the sound and meaning of words. Lesion models can provide an effective means of parsing the contributions of phonological or semantic impairment to recall performance. Methods and Procedures We employed the lesion model approach here by contrasting the nature of lexicality errors incurred during recall of word and nonword sequences by 3individuals with progressive nonfluent aphasia (a phonological dominant impairment) compared to that of 2 individuals with semantic dementia (a semantic dominant impairment). We focused on psycholinguistic attributes of correctly recalled stimuli relative to those that elicited a lexicality error (i.e., nonword → word OR word → nonword). Outcomes and results Patients with semantic dementia showed greater sensitivity to phonological attributes (e.g., phoneme length, wordlikeness) of the target items relative to semantic attributes (e.g., familiarity). Patients with PNFA showed the opposite pattern, marked by sensitivity to word frequency, age of acquisition, familiarity, and imageability. Conclusions We interpret these results in favor of a processing strategy such that in the context of a focal phonological impairment patients revert to an over-reliance on preserved semantic processing abilities. In contrast, a focal semantic impairment forces both reliance upon and hypersensitivity to phonological attributes of target words. We relate this interpretation to previous hypotheses about the nature of verbal short-term memory in progressive aphasia. PMID:23486736

Semantics by analogy for illustrative volume visualization☆

PubMed Central

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

2012-01-01

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

Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

NASA Astrophysics Data System (ADS)

Bhattacharjee, S.; Ghosh, S. K.

2015-07-01

Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

Integrated Japanese Dependency Analysis Using a Dialog Context

NASA Astrophysics Data System (ADS)

Ikegaya, Yuki; Noguchi, Yasuhiro; Kogure, Satoru; Itoh, Toshihiko; Konishi, Tatsuhiro; Kondo, Makoto; Asoh, Hideki; Takagi, Akira; Itoh, Yukihiro

This paper describes how to perform syntactic parsing and semantic analysis in a dialog system. The paper especially deals with how to disambiguate potentially ambiguous sentences using the contextual information. Although syntactic parsing and semantic analysis are often studied independently of each other, correct parsing of a sentence often requires the semantic information on the input and/or the contextual information prior to the input. Accordingly, we merge syntactic parsing with semantic analysis, which enables syntactic parsing taking advantage of the semantic content of an input and its context. One of the biggest problems of semantic analysis is how to interpret dependency structures. We employ a framework for semantic representations that circumvents the problem. Within the framework, the meaning of any predicate is converted into a semantic representation which only permits a single type of predicate: an identifying predicate "aru". The semantic representations are expressed as sets of "attribute-value" pairs, and those semantic representations are stored in the context information. Our system disambiguates syntactic/semantic ambiguities of inputs referring to the attribute-value pairs in the context information. We have experimentally confirmed the effectiveness of our approach; specifically, the experiment confirmed high accuracy of parsing and correctness of generated semantic representations.

Semantic representation in the white matter pathway

PubMed Central

Fang, Yuxing; Wang, Xiaosha; Zhong, Suyu; Song, Luping; Han, Zaizhu; Gong, Gaolang

2018-01-01

Object conceptual processing has been localized to distributed cortical regions that represent specific attributes. A challenging question is how object semantic space is formed. We tested a novel framework of representing semantic space in the pattern of white matter (WM) connections by extending the representational similarity analysis (RSA) to structural lesion pattern and behavioral data in 80 brain-damaged patients. For each WM connection, a neural representational dissimilarity matrix (RDM) was computed by first building machine-learning models with the voxel-wise WM lesion patterns as features to predict naming performance of a particular item and then computing the correlation between the predicted naming score and the actual naming score of another item in the testing patients. This correlation was used to build the neural RDM based on the assumption that if the connection pattern contains certain aspects of information shared by the naming processes of these two items, models trained with one item should also predict naming accuracy of the other. Correlating the neural RDM with various cognitive RDMs revealed that neural patterns in several WM connections that connect left occipital/middle temporal regions and anterior temporal regions associated with the object semantic space. Such associations were not attributable to modality-specific attributes (shape, manipulation, color, and motion), to peripheral picture-naming processes (picture visual similarity, phonological similarity), to broad semantic categories, or to the properties of the cortical regions that they connected, which tended to represent multiple modality-specific attributes. That is, the semantic space could be represented through WM connection patterns across cortical regions representing modality-specific attributes. PMID:29624578

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

PubMed

Berberian, Arthur A; Moraes, Giovanna V; Gadelha, Ary; Brietzke, Elisa; Fonseca, Ana O; Scarpato, Bruno S; Vicente, Marcella O; Seabra, Alessandra G; Bressan, Rodrigo A; Lacerda, Acioly L

2016-04-19

To investigate if verbal fluency impairment in schizophrenia reflects executive function deficits or results from degraded semantic store or inefficient search and retrieval strategies. 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. 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. 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.

The organization and dissolution of semantic-conceptual knowledge: is the 'amodal hub' the only plausible model?

PubMed

Gainotti, Guido

2011-04-01

In recent years, the anatomical and functional bases of conceptual activity have attracted a growing interest. In particular, Patterson and Lambon-Ralph have proposed the existence, in the anterior parts of the temporal lobes, of a mechanism (the 'amodal semantic hub') supporting the interactive activation of semantic representations in all modalities and for all semantic categories. The aim of then present paper is to discuss this model, arguing against the notion of an 'amodal' semantic hub, because we maintain, in agreement with the Damasio's construct of 'higher-order convergence zone', that a continuum exists between perceptual information and conceptual representations, whereas the 'amodal' account views perceptual informations only as a channel through which abstract semantic knowledge can be activated. According to our model, semantic organization can be better explained by two orthogonal higher-order convergence systems, concerning, on one hand, the right vs. left hemisphere and, on the other hand, the ventral vs. dorsal processing pathways. This model posits that conceptual representations may be mainly based upon perceptual activities in the right hemisphere and upon verbal mediation in the left side of the brain. It also assumes that conceptual knowledge based on the convergence of highly processed visual information with other perceptual data (and mainly concerning living categories) may be bilaterally represented in the anterior parts of the temporal lobes, whereas knowledge based on the integration of visual data with action schemata (namely knowledge of actions, body parts and artefacts) may be more represented in the left fronto-temporo-parietal areas. Copyright © 2010 Elsevier Inc. All rights reserved.

Over-Distribution in Source Memory

PubMed Central

Brainerd, C. J.; Reyna, V. F.; Holliday, R. E.; Nakamura, K.

2012-01-01

Semantic false memories are confounded with a second type of error, over-distribution, in which items are attributed to contradictory episodic states. Over-distribution errors have proved to be more common than false memories when the two are disentangled. We investigated whether over-distribution is prevalent in another classic false memory paradigm: source monitoring. It is. Conventional false memory responses (source misattributions) were predominantly over-distribution errors, but unlike semantic false memory, over-distribution also accounted for more than half of true memory responses (correct source attributions). Experimental control of over-distribution was achieved via a series of manipulations that affected either recollection of contextual details or item memory (concreteness, frequency, list-order, number of presentation contexts, and individual differences in verbatim memory). A theoretical model was used to analyze the data (conjoint process dissociation) that predicts that predicts that (a) over-distribution is directly proportional to item memory but inversely proportional to recollection and (b) item memory is not a necessary precondition for recollection of contextual details. The results were consistent with both predictions. PMID:21942494

Are Cortical Motor Maps Based on Body Parts or Coordinated Actions? Implications for Embodied Semantics

ERIC Educational Resources Information Center

Fernandino, Leonardo; Iacoboni, Marco

2010-01-01

The embodied cognition approach to the study of the mind proposes that higher order mental processes such as concept formation and language are essentially based on perceptual and motor processes. Contrary to the classical approach in cognitive science, in which concepts are viewed as amodal, arbitrary symbols, embodied semantics argues that…

The Local Geometry of Multiattribute Tradeoff Preferences

PubMed Central

McGeachie, Michael; Doyle, Jon

2011-01-01

Existing representations for multiattribute ceteris paribus preference statements have provided useful treatments and clear semantics for qualitative comparisons, but have not provided similarly clear representations or semantics for comparisons involving quantitative tradeoffs. We use directional derivatives and other concepts from elementary differential geometry to interpret conditional multiattribute ceteris paribus preference comparisons that state bounds on quantitative tradeoff ratios. This semantics extends the familiar economic notion of marginal rate of substitution to multiple continuous or discrete attributes. The same geometric concepts also provide means for interpreting statements about the relative importance of different attributes. PMID:21528018

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

PubMed

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

2017-08-04

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

Neural basis for generalized quantifier comprehension.

PubMed

McMillan, Corey T; Clark, Robin; Moore, Peachie; Devita, Christian; Grossman, Murray

2005-01-01

Generalized quantifiers like "all cars" are semantically well understood, yet we know little about their neural representation. Our model of quantifier processing includes a numerosity device, operations that combine number elements and working memory. Semantic theory posits two types of quantifiers: first-order quantifiers identify a number state (e.g. "at least 3") and higher-order quantifiers additionally require maintaining a number state actively in working memory for comparison with another state (e.g. "less than half"). We used BOLD fMRI to test the hypothesis that all quantifiers recruit inferior parietal cortex associated with numerosity, while only higher-order quantifiers recruit prefrontal cortex associated with executive resources like working memory. Our findings showed that first-order and higher-order quantifiers both recruit right inferior parietal cortex, suggesting that a numerosity component contributes to quantifier comprehension. Moreover, only probes of higher-order quantifiers recruited right dorsolateral prefrontal cortex, suggesting involvement of executive resources like working memory. We also observed activation of thalamus and anterior cingulate that may be associated with selective attention. Our findings are consistent with a large-scale neural network centered in frontal and parietal cortex that supports comprehension of generalized quantifiers.

Seeing red primes tomato: evidence for comparable priming from colour and colour name primes to semantically related word targets.

PubMed

Nijboer, Tanja C W; van Zandvoort, Martine J E; de Haan, Edward H F

2006-12-01

There is ample evidence that an independent processing stream exists that subserves the perception and appreciation of colour. Neurophysiological research has identified separate brain mechanisms for the processing of wavelength and colour, and neuropsychological studies have revealed selective colour disorders, such as achromatopsia, colour agnosia, and colour anomia. The aim of the present study is to investigate whether the perception of colour may, despite its independent processing, influence other cognitive functions. Specifically, we investigate the possibility that the perception of a colour influences higher order processes such as the activation of semantically related concepts. We designed an associative priming task involving a colour prime (e.g. a red patch or the word RED) and a lexical decision response to a semantically related ('tomato' vs. 'timato') or unrelated ('grass' vs. 'griss') word target. The results of this experiment indicate that there is comparable facilitation of accessing colour-related semantics through the perception of a colour or the reading of a colour name. This suggests that colour has a direct effect on higher order level, cognitive processing. These results are discussed in terms of current models of colour processing.

The Role of Context in Remembering Familiar Persons: Insights from Semantic Dementia

ERIC Educational Resources Information Center

Joubert, Sven; Mauries, Sandrine; Barbeau, Emmanuel; Ceccaldi, Mathieu; Poncet, Michel

2004-01-01

Semantic dementia (SD) is a progressive condition characterized by an insidious and gradual breakdown in semantic knowledge. Patients suffering from this condition gradually lose their knowledge of objects and their attributes, concepts, famous persons, and public events. In contrast, these patients maintain a striking preservation of…

Ontological Standardization for Historical Map Collections: Studying the Greek Borderlines of 1881

NASA Astrophysics Data System (ADS)

Gkadolou, E.; Tomai, E.; Stefanakis, E.; Kritikos, G.

2012-07-01

Historical maps deliver valuable historical information which is applicable in several domains while they document the spatiotemporal evolution of the geographical entities that are depicted therein. In order to use the historical cartographic information effectively, the maps' semantic documentation becomes a necessity for restoring any semantic ambiguities and structuring the relationship between historical and current geographical space. This paper examines cartographic ontologies as a proposed methodology and presents the first outcomes of the methodology applied for the historical map series «Carte de la nouvelle frontière Turco-Grecque» that sets the borderlines between Greece and Ottoman Empire in 1881. The map entities were modelled and compared to the current ones so as to record the changes in their spatial and thematic attributes and an ontology was developed in Protégé OWL Editor 3.4.4 for the attributes that thoroughly define a historical map and the digitised spatial entities. Special focus was given on the Greek borderline and the changes that it caused to other geographic entities.

A semantic framework to protect the privacy of electronic health records with non-numerical attributes.

PubMed

Martínez, Sergio; Sánchez, David; Valls, Aida

2013-04-01

Structured patient data like Electronic Health Records (EHRs) are a valuable source for clinical research. However, the sensitive nature of such information requires some anonymisation procedure to be applied before releasing the data to third parties. Several studies have shown that the removal of identifying attributes, like the Social Security Number, is not enough to obtain an anonymous data file, since unique combinations of other attributes as for example, rare diagnoses and personalised treatments, may lead to patient's identity disclosure. To tackle this problem, Statistical Disclosure Control (SDC) methods have been proposed to mask sensitive attributes while preserving, up to a certain degree, the utility of anonymised data. Most of these methods focus on continuous-scale numerical data. Considering that part of the clinical data found in EHRs is expressed with non-numerical attributes as for example, diagnoses, symptoms, procedures, etc., their application to EHRs produces far from optimal results. In this paper, we propose a general framework to enable the accurate application of SDC methods to non-numerical clinical data, with a focus on the preservation of semantics. To do so, we exploit structured medical knowledge bases like SNOMED CT to propose semantically-grounded operators to compare, aggregate and sort non-numerical terms. Our framework has been applied to several well-known SDC methods and evaluated using a real clinical dataset with non-numerical attributes. Results show that the exploitation of medical semantics produces anonymised datasets that better preserve the utility of EHRs. Copyright © 2012 Elsevier Inc. All rights reserved.

Enabling Energy-Awareness in the Semantic 3d City Model of Vienna

NASA Astrophysics Data System (ADS)

Agugiaro, G.

2016-09-01

This paper presents and discusses the first results regarding selection, analysis, preparation and eventual integration of a number of energy-related datasets, chosen in order to enrich a CityGML-based semantic 3D city model of Vienna. CityGML is an international standard conceived specifically as information and data model for semantic city models at urban and territorial scale. The still-in-development Energy Application Domain Extension (ADE) is a CityGML extension conceived to specifically model, manage and store energy-related features and attributes for buildings. The work presented in this paper is embedded within the European Marie-Curie ITN project "CINERGY, Smart cities with sustainable energy systems", which aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. Given the scope and scale of the project, it is therefore vital to set up a common, unique and spatio-semantically coherent urban data model to be used as information hub for all applications being developed. This paper reports about the experiences done so far, it describes the test area in Vienna, Austria, and the available data sources, it shows and exemplifies the main data integration issues, the strategies developed to solve them in order to obtain the enriched 3D city model. The first results as well as some comments about their quality and limitations are presented, together with the discussion regarding the next steps and some planned improvements.

SAS- Semantic Annotation Service for Geoscience resources on the web

NASA Astrophysics Data System (ADS)

Elag, M.; Kumar, P.; Marini, L.; Li, R.; Jiang, P.

2015-12-01

There is a growing need for increased integration across the data and model resources that are disseminated on the web to advance their reuse across different earth science applications. Meaningful reuse of resources requires semantic metadata to realize the semantic web vision for allowing pragmatic linkage and integration among resources. Semantic metadata associates standard metadata with resources to turn them into semantically-enabled resources on the web. However, the lack of a common standardized metadata framework as well as the uncoordinated use of metadata fields across different geo-information systems, has led to a situation in which standards and related Standard Names abound. To address this need, we have designed SAS to provide a bridge between the core ontologies required to annotate resources and information systems in order to enable queries and analysis over annotation from a single environment (web). SAS is one of the services that are provided by the Geosematnic framework, which is a decentralized semantic framework to support the integration between models and data and allow semantically heterogeneous to interact with minimum human intervention. Here we present the design of SAS and demonstrate its application for annotating data and models. First we describe how predicates and their attributes are extracted from standards and ingested in the knowledge-base of the Geosemantic framework. Then we illustrate the application of SAS in annotating data managed by SEAD and annotating simulation models that have web interface. SAS is a step in a broader approach to raise the quality of geoscience data and models that are published on the web and allow users to better search, access, and use of the existing resources based on standard vocabularies that are encoded and published using semantic technologies.

Semantic processing and response inhibition.

PubMed

Chiang, Hsueh-Sheng; Motes, Michael A; Mudar, Raksha A; Rao, Neena K; Mansinghani, Sethesh; Brier, Matthew R; Maguire, Mandy J; Kraut, Michael A; Hart, John

2013-11-13

The present study examined functional MRI (fMRI) BOLD signal changes in response to object categorization during response selection and inhibition. Young adults (N=16) completed a Go/NoGo task with varying object categorization requirements while fMRI data were recorded. Response inhibition elicited increased signal change in various brain regions, including medial frontal areas, compared with response selection. BOLD signal in an area within the right angular gyrus was increased when higher-order categorization was mandated. In addition, signal change during response inhibition varied with categorization requirements in the left inferior temporal gyrus (lIT). lIT-mediated response inhibition when inhibiting the response only required lower-order categorization, but lIT mediated both response selection and inhibition when selecting and inhibiting the response required higher-order categorization. The findings characterized mechanisms mediating response inhibition associated with semantic object categorization in the 'what' visual object memory system.

Right anterior temporal lobe dysfunction underlies theory of mind impairments in semantic dementia.

PubMed

Irish, Muireann; Hodges, John R; Piguet, Olivier

2014-04-01

Semantic dementia is a progressive neurodegenerative disorder characterized by the amodal and profound loss of semantic knowledge attributable to the degeneration of the left anterior temporal lobe. Although traditionally conceptualized as a language disorder, patients with semantic dementia display significant alterations in behaviour and socioemotional functioning. Recent evidence points to an impaired capacity for theory of mind in predominantly left-lateralized cases of semantic dementia; however, it remains unclear to what extent semantic impairments contribute to these deficits. Further the neuroanatomical signature of such disturbance remains unknown. Here, we sought to determine the neural correlates of theory of mind performance in patients with left predominant semantic dementia (n=11), in contrast with disease-matched cases with behavioural-variant frontotemporal dementia (n=10) and Alzheimer's disease (n=10), and healthy older individuals (n=14) as control participants. Participants completed a simple cartoons task, in which they were required to describe physical and theory of mind scenarios. Irrespective of subscale, patients with semantic dementia exhibited marked impairments relative to control subjects; however, only theory of mind deficits persisted when we covaried for semantic comprehension. Voxel-based morphometry analyses revealed that atrophy in right anterior temporal lobe structures, including the right temporal fusiform cortex, right inferior temporal gyrus, bilateral temporal poles and amygdalae, correlated significantly with theory of mind impairments in the semantic dementia group. Our results point to the marked disruption of cognitive functions beyond the language domain in semantic dementia, not exclusively attributable to semantic processing impairments. The significant involvement of right anterior temporal structures suggests that with disease evolution, the encroachment of pathology into the contralateral hemisphere heralds the onset of social cognitive deficits in this syndrome.

When gentlemen are first and ladies are last: effects of gender stereotypes on the order of romantic partners' names.

PubMed

Hegarty, Peter; Watson, Nila; Fletcher, Laura; McQueen, Grant

2011-03-01

A preference to name stereotypically masculine before stereotypically feminine individuals explains why men are typically named before women, as on the Internet, for example (Study 1). Heterosexual couples are named with men's names first more often when such couples are imagined to conform to gender stereotypes (Studies 2 and 3). First-named partners of imaginary same-sex couples are attributed more stereotypically masculine attributes (Study 4). Familiarity bounds these effects of stereotypes on name order. People name couples they know well with closer people first (Study 5), and consequently name familiar heterosexual couples with members of their own gender first (Study 6). These studies evidence a previously unknown effect of the semantics of gender stereotypes on sentence structure in the everyday use of English. ©2010 The British Psychological Society.

Sensory and semantic activations evoked by action attributes of manipulable objects: Evidence from ERPs

PubMed Central

Lee, Chia-lin; Huang, Hsu-Wen; Federmeier, Kara D.; Buxbaum, Laurel J.

2018-01-01

“Two route” theories of object-related action processing posit different temporal activation profiles of grasp-to-move actions (rapidly evoked based on object structure) versus skilled use actions (more slowly activated based on semantic knowledge). We capitalized on the exquisite temporal resolution and multidimensionality of Event-Related Potentials (ERPs) to directly test this hypothesis. Participants viewed manipulable objects (e.g., calculator) preceded by objects sharing either “grasp”, “use”, or no action attributes (e.g., bar of soap, keyboard, earring, respectively), as well as by action-unrelated but taxonomically-related objects (e.g., abacus); participants judged whether the two objects were related. The results showed more positive responses to “grasp-to-move” primed objects than “skilled use” primed objects or unprimed objects starting in the P1 (0–150 ms) time window and continuing onto the subsequent N1 and P2 components (150–300 ms), suggesting that only “grasp-to-move”, but not “skilled use”, actions may facilitate visual attention to object attributes. Furthermore, reliably reduced N400s (300–500 ms), an index of semantic processing, were observed to taxonomically primed and “skilled use” primed objects relative to unprimed objects, suggesting that “skilled use” action attributes are a component of distributed, multimodal semantic representations of objects. Together, our findings provide evidence supporting two-route theories by demonstrating that “grasp-to-move” and “skilled use” actions impact different aspects of object processing and highlight the relationship of “skilled use” information to other aspects of semantic memory. PMID:29183777

What's Unique about Unique Entities? An fMRI Investigation of the Semantics of Famous Faces and Landmarks

PubMed Central

Olson, Ingrid R.

2012-01-01

Famous people and artifacts are referred to as “unique entities” (UEs) due to the unique nature of the knowledge we have about them. Past imaging and lesion experiments have indicated that the anterior temporal lobes (ATLs) as having a special role in the processing of UEs. It has remained unclear which attributes of UEs were responsible for the observed effects in imaging experiments. In this study, we investigated what factors of UEs influence brain activity. In a training paradigm, we systematically varied the uniqueness of semantic associations, the presence/absence of a proper name, and the number of semantic associations to determine factors modulating activity in regions subserving the processing of UEs. We found that a conjunction of unique semantic information and proper names modulated activity within a section of the left ATL. Overall, the processing of UEs involved a wider left-hemispheric cortical network. Within these regions, brain activity was significantly affected by the unique semantic attributes especially in the presence of a proper name, but we could not find evidence for an effect of the number of semantic associations. Findings are discussed in regard to current models of ATL function, the neurophysiology of semantics, and social cognitive processing. PMID:22021913

Divergent Human Cortical Regions for Processing Distinct Acoustic-Semantic Categories of Natural Sounds: Animal Action Sounds vs. Vocalizations

PubMed Central

Webster, Paula J.; Skipper-Kallal, Laura M.; Frum, Chris A.; Still, Hayley N.; Ward, B. Douglas; Lewis, James W.

2017-01-01

A major gap in our understanding of natural sound processing is knowledge of where or how in a cortical hierarchy differential processing leads to categorical perception at a semantic level. Here, using functional magnetic resonance imaging (fMRI) we sought to determine if and where cortical pathways in humans might diverge for processing action sounds vs. vocalizations as distinct acoustic-semantic categories of real-world sound when matched for duration and intensity. This was tested by using relatively less semantically complex natural sounds produced by non-conspecific animals rather than humans. Our results revealed a striking double-dissociation of activated networks bilaterally. This included a previously well described pathway preferential for processing vocalization signals directed laterally from functionally defined primary auditory cortices to the anterior superior temporal gyri, and a less well-described pathway preferential for processing animal action sounds directed medially to the posterior insulae. We additionally found that some of these regions and associated cortical networks showed parametric sensitivity to high-order quantifiable acoustic signal attributes and/or to perceptual features of the natural stimuli, such as the degree of perceived recognition or intentional understanding. Overall, these results supported a neurobiological theoretical framework for how the mammalian brain may be fundamentally organized to process acoustically and acoustic-semantically distinct categories of ethologically valid, real-world sounds. PMID:28111538

Identification and correction of road courses by merging successive segments and using improved attributes

NASA Astrophysics Data System (ADS)

Bulatov, Dimitri; Häufel, Gisela; Pohl, Melanie

2016-10-01

Both in military and civil applications, there is an urgent need for a highly up-to-date road data, which should be ideally semantically structured (into main roads, walking paths, escape ways, etc.) with application-driven attributes, such as road width, road type, surface condition and many others. A vectorization algorithm processing aerial images recently acquired yields an up-to-date road vector data, which are, however, often represented by wriggly, noisy polylines without semantics. The reasons for zigzagged street courses are insufficiencies in the intermediate results of sensor data processing (orthophotos, elevation maps) and occlusions caused by trees, buildings, and others. In the current contribution, an improved computation of geometric attributes will be explained which makes a difference between straight and circular (or elliptic) polylines. Using improved attributes, the candidates for polylines having identical course and sharing a junction are determined. From such candidates, we form chains of polylines. These chains correspond better to the intuitive perception of the term street than the previously used road polylines, because, even after being interrupted by narrower side roads, a chain maintains its label. The generalization of chains with simultaneously adjusting positions of junctions is evidently performed. We apply a generalization with the purpose-based modification of a well-known polyline simplification algorithm once chain-wise and once polyline-wise in order to show - by means of qualitative results - the advantages of the chain-wise generalization.

Factors Influencing Students' Propensity for Semantic and Syntactic Reasoning in Proof Writing: A Case Study

ERIC Educational Resources Information Center

Mejía-Ramos, Juan Pablo; Weber, Keith; Fuller, Evan

2015-01-01

In this paper we present a case study of an individual student who consistently used semantic reasoning to construct proofs in calculus but infrequently used semantic reasoning to produce proofs in linear algebra. We hypothesize that the differences in these reasoning styles can be partially attributed to this student's familiarity with the…

International Workshop on Principles of Program Analysis

DTIC Science & Technology

1999-01-01

with respect to a semantics of the programming language. It is a sad fact that new program analyses often contain subtle bugs, and a formal ... It defines a higher-order function f with formal parameter x and body x 1; then it defines two functions g and h that are given as actual parameters...begin by presenting a formal semantics for WHILE. The material of this section may be skimmed through on a first reading; however, it is frequently

Relearning in Semantic Dementia Reflects Contributions from Both Medial Temporal Lobe Episodic and Degraded Neocortical Semantic Systems: Evidence in Support of the Complementary Learning Systems Theory

ERIC Educational Resources Information Center

Mayberry, Emily J.; Sage, Karen; Ehsan, Sheeba; Ralph, Matthew A. Lambon

2011-01-01

When relearning words, patients with semantic dementia (SD) exhibit a characteristic rigidity, including a failure to generalise names to untrained exemplars of trained concepts. This has been attributed to an over-reliance on the medial temporal region which captures information in sparse, non-overlapping and therefore rigid representations. The…

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection.

PubMed

Lin, Hui; Wang, Zhou-Jing

2017-09-17

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice.

Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection

PubMed Central

Lin, Hui; Wang, Zhou-Jing

2017-01-01

Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice. PMID:28926985

Identifying image preferences based on demographic attributes

NASA Astrophysics Data System (ADS)

Fedorovskaya, Elena A.; Lawrence, Daniel R.

2014-02-01

The intent of this study is to determine what sorts of images are considered more interesting by which demographic groups. Specifically, we attempt to identify images whose interestingness ratings are influenced by the demographic attribute of the viewer's gender. To that end, we use the data from an experiment where 18 participants (9 women and 9 men) rated several hundred images based on "visual interest" or preferences in viewing images. The images were selected to represent the consumer "photo-space" - typical categories of subject matter found in consumer photo collections. They were annotated using perceptual and semantic descriptors. In analyzing the image interestingness ratings, we apply a multivariate procedure known as forced classification, a feature of dual scaling, a discrete analogue of principal components analysis (similar to correspondence analysis). This particular analysis of ratings (i.e., ordered-choice or Likert) data enables the investigator to emphasize the effect of a specific item or collection of items. We focus on the influence of the demographic item of gender on the analysis, so that the solutions are essentially confined to subspaces spanned by the emphasized item. Using this technique, we can know definitively which images' ratings have been influenced by the demographic item of choice. Subsequently, images can be evaluated and linked, on one hand, to their perceptual and semantic descriptors, and, on the other hand, to the preferences associated with viewers' demographic attributes.

The OceanLink Project

NASA Astrophysics Data System (ADS)

Narock, T.; Arko, R. A.; Carbotte, S. M.; Chandler, C. L.; Cheatham, M.; Finin, T.; Hitzler, P.; Krisnadhi, A.; Raymond, L. M.; Shepherd, A.; Wiebe, P. H.

2014-12-01

A wide spectrum of maturing methods and tools, collectively characterized as the Semantic Web, is helping to vastly improve the dissemination of scientific research. Creating semantic integration requires input from both domain and cyberinfrastructure scientists. OceanLink, an NSF EarthCube Building Block, is demonstrating semantic technologies through the integration of geoscience data repositories, library holdings, conference abstracts, and funded research awards. Meeting project objectives involves applying semantic technologies to support data representation, discovery, sharing and integration. Our semantic cyberinfrastructure components include ontology design patterns, Linked Data collections, semantic provenance, and associated services to enhance data and knowledge discovery, interoperation, and integration. We discuss how these components are integrated, the continued automated and semi-automated creation of semantic metadata, and techniques we have developed to integrate ontologies, link resources, and preserve provenance and attribution.

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

PubMed

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

2012-10-01

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

False memory for orthographically versus semantically similar words in adolescents with dyslexia: a fuzzy-trace theory perspective.

PubMed

Obidziński, Michał; Nieznański, Marek

2017-10-01

The presented research was conducted in order to investigate the connections between developmental dyslexia and the functioning of verbatim and gist memory traces-assumed in the fuzzy-trace theory. The participants were 71 high school students (33 with dyslexia and 38 without learning difficulties). The modified procedure and multinomial model of Stahl and Klauer (simplified conjoint recognition model) was used to collect and analyze data. Results showed statistically significant differences in four of the model parameters: (a) the probability of verbatim trace recollection upon presentation of orthographically similar stimulus was higher in the control than dyslexia group, (b) the probability of verbatim trace recollection upon presentation of semantically similar stimulus was higher in the control than dyslexia group, (c) the probability of gist trace retrieval upon presentation of semantically similar stimulus was higher in the dyslexia than control group, and (d) the probability of gist trace retrieval upon target stimulus presentation (in the semantic condition) was higher in the control than dyslexia group. The obtained results suggest differences of memory functioning in terms of verbatim and gist trace retrieval between people with and without dyslexia on specific, elementary cognitive processes postulated by the fuzzy-trace theory. These can indicate new approaches in the education of persons with developmental dyslexia, focused on specific impairments and the strengths of their memory functioning.

Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.

PubMed

Sihong Chen; Jing Qin; Xing Ji; Baiying Lei; Tianfu Wang; Dong Ni; Jie-Zhi Cheng

2017-03-01

The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images. We regard that there may exist relations among the semantic features of "spiculation", "texture", "margin", etc., that can be explored with the MTL. The Lung Image Database Consortium (LIDC) data is adopted in this study for the rich annotation resources. The LIDC nodules were quantitatively scored w.r.t. 9 semantic features from 12 radiologists of several institutes in U.S.A. By treating each semantic feature as an individual task, the MTL schemes select and map the heterogeneous computational features toward the radiologists' ratings with cross validation evaluation schemes on the randomly selected 2400 nodules from the LIDC dataset. The experimental results suggest that the predicted semantic scores from the three MTL schemes are closer to the radiologists' ratings than the scores from single-task LASSO and elastic net regression methods. The proposed semantic attribute scoring scheme may provide richer quantitative assessments of nodules for better support of diagnostic decision and management. Meanwhile, the capability of the automatic association of medical image contents with the clinical semantic terms by our method may also assist the development of medical search engine.

Attention to Distinct Goal-relevant Features Differentially Guides Semantic Knowledge Retrieval.

PubMed

Hanson, Gavin K; Chrysikou, Evangelia G

2017-07-01

A critical aspect of conceptual knowledge is the selective activation of goal-relevant aspects of meaning. Although the contributions of ventrolateral prefrontal and posterior temporal areas to semantic cognition are well established, the precise role of posterior parietal cortex in semantic control remains unknown. Here, we examined whether this region modulates attention to goal-relevant features within semantic memory according to the same principles that determine the salience of task-relevant object properties during visual attention. Using multivoxel pattern analysis, we decoded attentional referents during a semantic judgment task, in which participants matched an object cue to a target according to concrete (i.e., color, shape) or abstract (i.e., function, thematic context) semantic features. The goal-relevant semantic feature participants attended to (e.g., color or shape, function or theme) could be decoded from task-associated cortical activity with above-chance accuracy, a pattern that held for both concrete and abstract semantic features. A Bayesian confusion matrix analysis further identified differential contributions to representing attentional demands toward specific object properties across lateral prefrontal, posterior temporal, and inferior parietal regions, with the dorsolateral pFC supporting distinctions between higher-order properties and the left intraparietal sulcus being the only region supporting distinctions across all semantic features. These results are the first to demonstrate that patterns of neural activity in the parietal cortex are sensitive to which features of a concept are attended to, thus supporting the contributions of posterior parietal cortex to semantic control.

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

NASA Astrophysics Data System (ADS)

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%).

The effect of concurrent semantic categorization on delayed serial recall.

PubMed

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

2011-01-01

The influence of semantic processing on the serial ordering of items in short-term memory was explored using a novel dual-task paradigm. Participants engaged in 2 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 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.

The Effect of Concurrent Semantic Categorization on Delayed Serial Recall

PubMed Central

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

Dissociative Contributions of Semantic and Lexical-Phonological Information to Immediate Recognition

ERIC Educational Resources Information Center

Nishiyama, Ryoji

2013-01-01

Several neuropsychological studies have reported that patients with memory deficits exhibit a dissociation of effects attributed to semantic and lexical-phonological information in verbal working memory (e.g., Reilly, Martin, & Grossman, 2005; Romani & Martin, 1999). The present study reports on 3 experiments conducted with individuals without…

The perception of emotion-free faces in schizophrenia: a magneto-encephalography study.

PubMed

López-Ibor, Juan J; López-Ibor, María-Inés; Méndez, María-Andreína; Morón, María-Dolores; Ortiz-Terán, Laura; Fernandez, Alberto; Diaz-Marsá, Marina; Ortiz, Tomás

2008-01-01

To analyze how patients suffering from schizophrenia perceive faces of unknown individuals that show no actual emotions in order to investigate the attribution of meanings to a relatively non-significant but complex sensory experience. Analysis of baseline and poststimulation magneto-encephalographic recordings. The stimuli consisted of four pictures with neutral emotional expression of male and female faces of Spanish individuals unknown to research subjects. Twelve right-handed patients suffering from schizophrenia (DSM IV-TR criteria), age 18-65, with active delusional activity (SAPS score in delusions above 39) and 15 right-handed sex- and age-matched control subjects. Compared to controls patients have a significant higher activity of both hemispheres (0-700 ms) being the activity in the right hemisphere (RH) higher than in the left hemisphere (LH). Patients also have a higher activity on the middle fusiform gyrus (BA 37) in the LH (200-300 ms), on the superior temporal areas (BA 22, 41 and 42) in both hemispheres (100-700 ms) and on the temporal pole (BA 38) in the RH (300-400 ms) and a lower activity in the LH of the latter. The areas that are more activated in our study are those involved in the process of thinking, in attributing meanings to perceptions and in activities such as theory of mind, which are essential for social interaction. The anterior temporal areas less activated indicate a reduced semantic memory for faces that could explain the social withdrawal of schizophrenia. These alterations are suggestive of a dysfunction of left hemisphere neuronal networks.

Heteromodal Cortical Areas Encode Sensory-Motor Features of Word Meaning.

PubMed

Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Seidenberg, Mark S; Binder, Jeffrey R

2016-09-21

The capacity to process information in conceptual form is a fundamental aspect of human cognition, yet little is known about how this type of information is encoded in the brain. Although the role of sensory and motor cortical areas has been a focus of recent debate, neuroimaging studies of concept representation consistently implicate a network of heteromodal areas that seem to support concept retrieval in general rather than knowledge related to any particular sensory-motor content. We used predictive machine learning on fMRI data to investigate the hypothesis that cortical areas in this "general semantic network" (GSN) encode multimodal information derived from basic sensory-motor processes, possibly functioning as convergence-divergence zones for distributed concept representation. An encoding model based on five conceptual attributes directly related to sensory-motor experience (sound, color, shape, manipulability, and visual motion) was used to predict brain activation patterns associated with individual lexical concepts in a semantic decision task. When the analysis was restricted to voxels in the GSN, the model was able to identify the activation patterns corresponding to individual concrete concepts significantly above chance. In contrast, a model based on five perceptual attributes of the word form performed at chance level. This pattern was reversed when the analysis was restricted to areas involved in the perceptual analysis of written word forms. These results indicate that heteromodal areas involved in semantic processing encode information about the relative importance of different sensory-motor attributes of concepts, possibly by storing particular combinations of sensory and motor features. The present study used a predictive encoding model of word semantics to decode conceptual information from neural activity in heteromodal cortical areas. The model is based on five sensory-motor attributes of word meaning (color, shape, sound, visual motion, and manipulability) and encodes the relative importance of each attribute to the meaning of a word. This is the first demonstration that heteromodal areas involved in semantic processing can discriminate between different concepts based on sensory-motor information alone. This finding indicates that the brain represents concepts as multimodal combinations of sensory and motor representations. Copyright © 2016 the authors 0270-6474/16/369763-07$15.00/0.

Design and Application of Strategies/Tactics in Higher Order Logics

NASA Technical Reports Server (NTRS)

Archer, Myla (Editor); diVito, Ben (Editor); Munoz, Cesar (Editor)

2003-01-01

This Proceedings includes both a paper from the implementors of PVS providing guidance for PVS strategy writers and a tutorial on PVS strategy writing distilled from the experience of three PVS users who have written extensive sets of PVS user strategies. Following these are three full papers from the higher-order logic theorem proving community that discuss PVS strategies to enhance arithmetic and other interactive reasoning in PVS; implementing first-order tactics in higher-order provers; and a proposed technique for specifying small step semantics that can be used in multiple higher order logic theorem provers, with illustrations from both Coq and PVS. The Proceedings concludes with three position papers for a panel session that discuss three settings in which development of PVS strategies is worth while.

Lessons learned in detailed clinical modeling at Intermountain Healthcare

PubMed Central

Oniki, Thomas A; Coyle, Joseph F; Parker, Craig G; Huff, Stanley M

2014-01-01

Background and objective Intermountain Healthcare has a long history of using coded terminology and detailed clinical models (DCMs) to govern storage of clinical data to facilitate decision support and semantic interoperability. The latest iteration of DCMs at Intermountain is called the clinical element model (CEM). We describe the lessons learned from our CEM efforts with regard to subjective decisions a modeler frequently needs to make in creating a CEM. We present insights and guidelines, but also describe situations in which use cases conflict with the guidelines. We propose strategies that can help reconcile the conflicts. The hope is that these lessons will be helpful to others who are developing and maintaining DCMs in order to promote sharing and interoperability. Methods We have used the Clinical Element Modeling Language (CEML) to author approximately 5000 CEMs. Results Based on our experience, we have formulated guidelines to lead our modelers through the subjective decisions they need to make when authoring models. Reported here are guidelines regarding precoordination/postcoordination, dividing content between the model and the terminology, modeling logical attributes, and creating iso-semantic models. We place our lessons in context, exploring the potential benefits of an implementation layer, an iso-semantic modeling framework, and ontologic technologies. Conclusions We assert that detailed clinical models can advance interoperability and sharing, and that our guidelines, an implementation layer, and an iso-semantic framework will support our progress toward that goal. PMID:24993546

From Sensory Perception to Lexical-Semantic Processing: An ERP Study in Non-Verbal Children with Autism.

PubMed

Cantiani, Chiara; Choudhury, Naseem A; Yu, Yan H; Shafer, Valerie L; Schwartz, Richard G; Benasich, April A

2016-01-01

This study examines electrocortical activity associated with visual and auditory sensory perception and lexical-semantic processing in nonverbal (NV) or minimally-verbal (MV) children with Autism Spectrum Disorder (ASD). Currently, there is no agreement on whether these children comprehend incoming linguistic information and whether their perception is comparable to that of typically developing children. Event-related potentials (ERPs) of 10 NV/MV children with ASD and 10 neurotypical children were recorded during a picture-word matching paradigm. Atypical ERP responses were evident at all levels of processing in children with ASD. Basic perceptual processing was delayed in both visual and auditory domains but overall was similar in amplitude to typically-developing children. However, significant differences between groups were found at the lexical-semantic level, suggesting more atypical higher-order processes. The results suggest that although basic perception is relatively preserved in NV/MV children with ASD, higher levels of processing, including lexical- semantic functions, are impaired. The use of passive ERP paradigms that do not require active participant response shows significant potential for assessment of non-compliant populations such as NV/MV children with ASD.

From Sensory Perception to Lexical-Semantic Processing: An ERP Study in Non-Verbal Children with Autism

PubMed Central

Cantiani, Chiara; Choudhury, Naseem A.; Yu, Yan H.; Shafer, Valerie L.; Schwartz, Richard G.; Benasich, April A.

2016-01-01

This study examines electrocortical activity associated with visual and auditory sensory perception and lexical-semantic processing in nonverbal (NV) or minimally-verbal (MV) children with Autism Spectrum Disorder (ASD). Currently, there is no agreement on whether these children comprehend incoming linguistic information and whether their perception is comparable to that of typically developing children. Event-related potentials (ERPs) of 10 NV/MV children with ASD and 10 neurotypical children were recorded during a picture-word matching paradigm. Atypical ERP responses were evident at all levels of processing in children with ASD. Basic perceptual processing was delayed in both visual and auditory domains but overall was similar in amplitude to typically-developing children. However, significant differences between groups were found at the lexical-semantic level, suggesting more atypical higher-order processes. The results suggest that although basic perception is relatively preserved in NV/MV children with ASD, higher levels of processing, including lexical- semantic functions, are impaired. The use of passive ERP paradigms that do not require active participant response shows significant potential for assessment of non-compliant populations such as NV/MV children with ASD. PMID:27560378

Neural correlates of the object-recall process in semantic memory.

PubMed

Assaf, Michal; Calhoun, Vince D; Kuzu, Cheedem H; Kraut, Michael A; Rivkin, Paul R; Hart, John; Pearlson, Godfrey D

2006-10-30

The recall of an object from features is a specific operation in semantic memory in which the thalamus and pre-supplementary motor area (pre-SMA) are integrally involved. Other higher-order semantic cortices are also likely to be involved. We used the object-recall-from-features paradigm, with more sensitive scanning techniques and larger sample size, to replicate and extend our previous results. Eighteen right-handed healthy participants performed an object-recall task and an association semantic task, while undergoing functional magnetic resonance imaging. During object-recall, subjects determined whether words pairs describing object features combined to recall an object; during the association task they decided if two words were related. Of brain areas specifically involved in object recall, in addition to the thalamus and pre-SMA, other regions included the left dorsolateral prefrontal cortex, inferior parietal lobule, and middle temporal gyrus, and bilateral rostral anterior cingulate and inferior frontal gyri. These regions are involved in semantic processing, verbal working memory and response-conflict detection and monitoring. The thalamus likely helps to coordinate activity of these different brain areas. Understanding the circuit that normally mediates this process is relevant for schizophrenia, where many regions in this circuit are functionally abnormal and semantic memory is impaired.

Higher-Order Containers

NASA Astrophysics Data System (ADS)

Altenkirch, Thorsten; Levy, Paul; Staton, Sam

Containers are a semantic way to talk about strictly positive types. In previous work it was shown that containers are closed under various constructions including products, coproducts, initial algebras and terminal coalgebras. In the present paper we show that, surprisingly, the category of containers is cartesian closed, giving rise to a full cartesian closed subcategory of endofunctors. The result has interesting applications in generic programming and representation of higher order abstract syntax. We also show that the category of containers has finite limits, but it is not locally cartesian closed.

Semantic Memory Recognition Is Supported by Intrinsic Recollection-Like Processes: "The Butcher on the Bus" Revisited

ERIC Educational Resources Information Center

Waidergoren, Shani; Segalowicz, Judith; Gilboa, Asaf

2012-01-01

Dual-process models suggest that recognition memory is independently supported by recollection and familiarity. Current theories attribute recollection solely to hippocampally mediated episodic memory (EM), and familiarity to both episodic and semantic memory (SM) supported by medial temporal lobe cortex (MTLC) and prefrontal cortex. We tested…

Perspective: Semantic Data Management for the Home

DTIC Science & Technology

2009-02-01

stored. For example, one view might be “all files with type=music and artist= Beatles stored on Liz’s iPod” and another “all files with owner=Liz...semantic naming structures and search tech- niques from a rich history of previous work. The Seman- tic Filesystem [12] proposed the use of attribute

Parameters of Semantic Multisensory Integration Depend on Timing and Modality Order among People on the Autism Spectrum: Evidence from Event-Related Potentials

ERIC Educational Resources Information Center

Russo, N.; Mottron, L.; Burack, J. A.; Jemel, B.

2012-01-01

Individuals with autism spectrum disorders (ASD) report difficulty integrating simultaneously presented visual and auditory stimuli (Iarocci & McDonald, 2006), albeit showing enhanced perceptual processing of unisensory stimuli, as well as an enhanced role of perception in higher-order cognitive tasks (Enhanced Perceptual Functioning (EPF) model;…

A keyword searchable attribute-based encryption scheme with attribute update for cloud storage.

PubMed

Wang, Shangping; Ye, Jian; Zhang, Yaling

2018-01-01

Ciphertext-policy attribute-based encryption (CP-ABE) scheme is a new type of data encryption primitive, which is very suitable for data cloud storage for its fine-grained access control. Keyword-based searchable encryption scheme enables users to quickly find interesting data stored in the cloud server without revealing any information of the searched keywords. In this work, we provide a keyword searchable attribute-based encryption scheme with attribute update for cloud storage, which is a combination of attribute-based encryption scheme and keyword searchable encryption scheme. The new scheme supports the user's attribute update, especially in our new scheme when a user's attribute need to be updated, only the user's secret key related with the attribute need to be updated, while other user's secret key and the ciphertexts related with this attribute need not to be updated with the help of the cloud server. In addition, we outsource the operation with high computation cost to cloud server to reduce the user's computational burden. Moreover, our scheme is proven to be semantic security against chosen ciphertext-policy and chosen plaintext attack in the general bilinear group model. And our scheme is also proven to be semantic security against chosen keyword attack under bilinear Diffie-Hellman (BDH) assumption.

A keyword searchable attribute-based encryption scheme with attribute update for cloud storage

PubMed Central

Wang, Shangping; Zhang, Yaling

2018-01-01

Ciphertext-policy attribute-based encryption (CP-ABE) scheme is a new type of data encryption primitive, which is very suitable for data cloud storage for its fine-grained access control. Keyword-based searchable encryption scheme enables users to quickly find interesting data stored in the cloud server without revealing any information of the searched keywords. In this work, we provide a keyword searchable attribute-based encryption scheme with attribute update for cloud storage, which is a combination of attribute-based encryption scheme and keyword searchable encryption scheme. The new scheme supports the user's attribute update, especially in our new scheme when a user's attribute need to be updated, only the user's secret key related with the attribute need to be updated, while other user's secret key and the ciphertexts related with this attribute need not to be updated with the help of the cloud server. In addition, we outsource the operation with high computation cost to cloud server to reduce the user's computational burden. Moreover, our scheme is proven to be semantic security against chosen ciphertext-policy and chosen plaintext attack in the general bilinear group model. And our scheme is also proven to be semantic security against chosen keyword attack under bilinear Diffie-Hellman (BDH) assumption. PMID:29795577

Stimulus Value Signals in Ventromedial PFC Reflect the Integration of Attribute Value Signals Computed in Fusiform Gyrus and Posterior Superior Temporal Gyrus

PubMed Central

Lim, Seung-Lark; O'Doherty, John P.

2013-01-01

We often have to make choices among multiattribute stimuli (e.g., a food that differs on its taste and health). Behavioral data suggest that choices are made by computing the value of the different attributes and then integrating them into an overall stimulus value signal. However, it is not known whether this theory describes the way the brain computes the stimulus value signals, or how the underlying computations might be implemented. We investigated these questions using a human fMRI task in which individuals had to evaluate T-shirts that varied in their visual esthetic (e.g., color) and semantic (e.g., meaning of logo printed in T-shirt) components. We found that activity in the fusiform gyrus, an area associated with the processing of visual features, correlated with the value of the visual esthetic attributes, but not with the value of the semantic attributes. In contrast, activity in posterior superior temporal gyrus, an area associated with the processing of semantic meaning, exhibited the opposite pattern. Furthermore, both areas exhibited functional connectivity with an area of ventromedial prefrontal cortex that reflects the computation of overall stimulus values at the time of decision. The results provide supporting evidence for the hypothesis that some attribute values are computed in cortical areas specialized in the processing of such features, and that those attribute-specific values are then passed to the vmPFC to be integrated into an overall stimulus value signal to guide the decision. PMID:23678116

Stimulus value signals in ventromedial PFC reflect the integration of attribute value signals computed in fusiform gyrus and posterior superior temporal gyrus.

PubMed

Lim, Seung-Lark; O'Doherty, John P; Rangel, Antonio

2013-05-15

We often have to make choices among multiattribute stimuli (e.g., a food that differs on its taste and health). Behavioral data suggest that choices are made by computing the value of the different attributes and then integrating them into an overall stimulus value signal. However, it is not known whether this theory describes the way the brain computes the stimulus value signals, or how the underlying computations might be implemented. We investigated these questions using a human fMRI task in which individuals had to evaluate T-shirts that varied in their visual esthetic (e.g., color) and semantic (e.g., meaning of logo printed in T-shirt) components. We found that activity in the fusiform gyrus, an area associated with the processing of visual features, correlated with the value of the visual esthetic attributes, but not with the value of the semantic attributes. In contrast, activity in posterior superior temporal gyrus, an area associated with the processing of semantic meaning, exhibited the opposite pattern. Furthermore, both areas exhibited functional connectivity with an area of ventromedial prefrontal cortex that reflects the computation of overall stimulus values at the time of decision. The results provide supporting evidence for the hypothesis that some attribute values are computed in cortical areas specialized in the processing of such features, and that those attribute-specific values are then passed to the vmPFC to be integrated into an overall stimulus value signal to guide the decision.

Semantic Differential Comparisons of Attributions and Dimensions among Seven Nations.

ERIC Educational Resources Information Center

Chandler, Theodore A.; Spies, Carl J.

The classifications of 11 attributions according to dimensions of locus, stability, controllability, predictability, and globality by participants in 7 countries (China, France, Germany, Hong Kong, Israel, Spain, and the United States) were compared in a cross-cultural study. The attributions were: (1) bias; (2) help; (3) luck; (4) ability; (5)…

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

PubMed

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

2017-02-01

Gene expression studies often require the combined use of a number of analysis tools. However, manual integration of analysis tools can be cumbersome and error prone. To support a higher level of automation in the integration process, efforts have been made in the biomedical domain towards the development of semantic web services and supporting composition environments. Yet, most environments consider only the execution of simple service behaviours and requires users to focus on technical details of the composition process. We propose a novel approach to the semantic composition of gene expression analysis services that addresses the shortcomings of the existing solutions. Our approach includes an architecture designed to support the service composition process for gene expression analysis, and a flexible strategy for the (semi) automatic composition of semantic web services. Finally, we implement a supporting platform called SemanticSCo to realize the proposed composition approach and demonstrate its functionality by successfully reproducing a microarray study documented in the literature. The SemanticSCo platform provides support for the composition of RESTful web services semantically annotated using SAWSDL. Our platform also supports the definition of constraints/conditions regarding the order in which service operations should be invoked, thus enabling the definition of complex service behaviours. Our proposed solution for semantic web service composition takes into account the requirements of different stakeholders and addresses all phases of the service composition process. It also provides support for the definition of analysis workflows at a high-level of abstraction, thus enabling users to focus on biological research issues rather than on the technical details of the composition process. The SemanticSCo source code is available at https://github.com/usplssb/SemanticSCo. Copyright © 2017 Elsevier Inc. All rights reserved.

Long-lasting perceptual priming and semantic learning in amnesia: a case experiment.

PubMed

Tulving, E; Hayman, C A; Macdonald, C A

1991-07-01

An investigation of perceptual priming and semantic learning in the severely amnesic subject K.C. is reported. He was taught 64 three-word sentences and tested for his ability to produce the final word of each sentence. Despite a total lack of episodic memory, he exhibited (a) strong perceptual priming effects in word-fragment completion, which were retained essentially in full strength for 12 months, and (b) independent of perceptual priming, learning of new semantic facts, many of which were also retained for 12 months. K.C.'s semantic learning may be at least partly attributable to repeated study trials and minimal interference during learning. The findings suggest that perceptual priming and semantic learning are subserved by two memory systems different from episodic memory and that both systems (perceptual representation and semantic memory) are at least partially preserved in some amnesic subjects.

Semantic, Lexical, and Phonological Influences on the Production of Verb Inflections in Agrammatic Aphasia

ERIC Educational Resources Information Center

Faroqi-Shah, Yasmeen; Thompson, Cynthia K.

2004-01-01

Verb inflection errors, often seen in agrammatic aphasic speech, have been attributed to either impaired encoding of diacritical features that specify tense and aspect, or to impaired affixation during phonological encoding. In this study we examined the effect of semantic markedness, word form frequency and affix frequency, as well as accuracy…

An Attribute-Treatment Interaction Study: Lexical-Set versus Semantically-Unrelated Vocabulary Instruction

ERIC Educational Resources Information Center

Hashemi, Mohammad Reza; Gowdasiaei, Farah

2005-01-01

The purpose of the current study was (a) to assess the effectiveness of the lexical-set (LS) and the semantically-unrelated (SU) vocabulary instruction, separately and relative to each other, and (b) to assess the differential effects of the two methods for students of lower and upper English proficiency levels. Two intact EFL classes were…

Impaired Semantic Knowledge Underlies the Reduced Verbal Short-Term Storage Capacity in Alzheimer's Disease

ERIC Educational Resources Information Center

Peters, Frederic; Majerus, Steve; De Baerdemaeker, Julie; Salmon, Eric; Collette, Fabienne

2009-01-01

A decrease in verbal short-term memory (STM) capacity is consistently observed in patients with Alzheimer's disease (AD). Although this impairment has been mainly attributed to attentional deficits during encoding and maintenance, the progressive deterioration of semantic knowledge in early stages of AD may also be an important determinant of poor…

Software analysis in the semantic web

NASA Astrophysics Data System (ADS)

Taylor, Joshua; Hall, Robert T.

2013-05-01

Many approaches in software analysis, particularly dynamic malware analyis, benefit greatly from the use of linked data and other Semantic Web technology. In this paper, we describe AIS, Inc.'s Semantic Extractor (SemEx) component from the Malware Analysis and Attribution through Genetic Information (MAAGI) effort, funded under DARPA's Cyber Genome program. The SemEx generates OWL-based semantic models of high and low level behaviors in malware samples from system call traces generated by AIS's introspective hypervisor, IntroVirtTM. Within MAAGI, these semantic models were used by modules that cluster malware samples by functionality, and construct "genealogical" malware lineages. Herein, we describe the design, implementation, and use of the SemEx, as well as the C2DB, an OWL ontology used for representing software behavior and cyber-environments.

Citation and Recognition of contributions using Semantic Provenance Knowledge Captured in the OPeNDAP Software Framework

NASA Astrophysics Data System (ADS)

West, P.; Michaelis, J.; Lebot, T.; McGuinness, D. L.; Fox, P. A.

2014-12-01

Providing proper citation and attribution for published data, derived data products, and the software tools used to generate them, has always been an important aspect of scientific research. However, It is often the case that this type of detailed citation and attribution is lacking. This is in part because it often requires manual markup since dynamic generation of this type of provenance information is not typically done by the tools used to access, manipulate, transform, and visualize data. In addition, the tools themselves lack the information needed to be properly cited themselves. The OPeNDAP Hyrax Software Framework is a tool that provides access to and the ability to constrain, manipulate, and transform, different types of data from different data formats, into a common format, the DAP (Data Access Protocol), in order to derive new data products. A user, or another software client, specifies an HTTP URL in order to access a particular piece of data, and appropriately transform it to suit a specific purpose of use. The resulting data products, however, do not contain any information about what data was used to create it, or the software process used to generate it, let alone information that would allow the proper citing and attribution to down stream researchers and tool developers. We will present our approach to provenance capture in Hyrax including a mechanism that can be used to report back to the hosting site any derived products, such as publications and reports, using the W3C PROV recommendation pingback service. We will demonstrate our utilization of Semantic Web and Web standards, the development of an information model that extends the PROV model for provenance capture, and the development of the pingback service. We will present our findings, as well as our practices for providing provenance information, visualization of the provenance information, and the development of pingback services, to better enable scientists and tool developers to be recognized and properly cited for their contributions.

Revealing the Dynamic Modulations That Underpin a Resilient Neural Network for Semantic Cognition: An fMRI Investigation in Patients With Anterior Temporal Lobe Resection.

PubMed

Rice, Grace E; Caswell, Helen; Moore, Perry; Lambon Ralph, Matthew A; Hoffman, Paul

2018-06-06

One critical feature of any well-engineered system is its resilience to perturbation and minor damage. The purpose of the current study was to investigate how resilience is achieved in higher cognitive systems, which we explored through the domain of semantic cognition. Convergent evidence implicates the bilateral anterior temporal lobes (ATLs) as a conceptual knowledge hub. While bilateral damage to this region produces profound semantic impairment, unilateral atrophy/resection or transient perturbation has a limited effect. Two neural mechanisms might underpin this resilience to unilateral ATL damage: 1) the undamaged ATL upregulates its activation in order to compensate; and/or 2) prefrontal regions involved in control of semantic retrieval upregulate to compensate for the impoverished semantic representations that follow from ATL damage. To test these possibilities, 34 postsurgical temporal lobe epilepsy patients and 20 age-matched controls were scanned whilst completing semantic tasks. Pictorial tasks, which produced bilateral frontal and temporal activation, showed few activation differences between patients and control participants. Written word tasks, however, produced a left-lateralized activation pattern and greater differences between the groups. Patients with right ATL resection increased activation in left inferior frontal gyrus (IFG). Patients with left ATL resection upregulated both the right ATL and right IFG. Consistent with recent computational models, these results indicate that 1) written word semantic processing in patients with ATL resection is supported by upregulation of semantic knowledge and control regions, principally in the undamaged hemisphere, and 2) pictorial semantic processing is less affected, presumably because it draws on a more bilateral network.

Why are background telephone conversations distracting?

PubMed

Marsh, John E; Ljung, Robert; Jahncke, Helena; MacCutcheon, Douglas; Pausch, Florian; Ball, Linden J; Vachon, François

2018-06-01

Telephone conversation is ubiquitous within the office setting. Overhearing a telephone conversation-whereby only one of the two speakers is heard-is subjectively more annoying and objectively more distracting than overhearing a full conversation. The present study sought to determine whether this "halfalogue" effect is attributable to unexpected offsets and onsets within the background speech (acoustic unexpectedness) or to the tendency to predict the unheard part of the conversation (semantic [un]predictability), and whether these effects can be shielded against through top-down cognitive control. In Experiment 1, participants performed an office-related task in quiet or in the presence of halfalogue and dialogue background speech. Irrelevant speech was either meaningful or meaningless speech. The halfalogue effect was only present for the meaningful speech condition. Experiment 2 addressed whether higher task-engagement could shield against the halfalogue effect by manipulating the font of the to-be-read material. Although the halfalogue effect was found with an easy-to-read font (fluent text), the use of a difficult-to-read font (disfluent text) eliminated the effect. The halfalogue effect is thus attributable to the semantic (un)predictability, not the acoustic unexpectedness, of background telephone conversation and can be prevented by simple means such as increasing the level of engagement required by the focal task. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Attribute-based classification for zero-shot visual object categorization.

PubMed

Lampert, Christoph H; Nickisch, Hannes; Harmeling, Stefan

2014-03-01

We study the problem of object recognition for categories for which we have no training examples, a task also called zero--data or zero-shot learning. This situation has hardly been studied in computer vision research, even though it occurs frequently; the world contains tens of thousands of different object classes, and image collections have been formed and suitably annotated for only a few of them. To tackle the problem, we introduce attribute-based classification: Objects are identified based on a high-level description that is phrased in terms of semantic attributes, such as the object's color or shape. Because the identification of each such property transcends the specific learning task at hand, the attribute classifiers can be prelearned independently, for example, from existing image data sets unrelated to the current task. Afterward, new classes can be detected based on their attribute representation, without the need for a new training phase. In this paper, we also introduce a new data set, Animals with Attributes, of over 30,000 images of 50 animal classes, annotated with 85 semantic attributes. Extensive experiments on this and two more data sets show that attribute-based classification indeed is able to categorize images without access to any training images of the target classes.

Semantic Ambiguity and the Process of Generating Meaning From Print

ERIC Educational Resources Information Center

Pexman, Penny M.; Hino, Yasushi; Lupker, Stephen J.

2004-01-01

An ambiguity disadvantage (slower responses for ambiguous words, e.g., bank, than for unambiguous words) has been reported in semantic tasks (L. R. Gottlob, S. D. Goldinger, G. O. Stone, & G. C. Van Orden, 1999; Y. Hino, S. J. Lupker, & P. M. Pexman, 2002; C. D. Piercey & S. Joordens, 2000) and has been attributed to the meaning activation…

Order recall in verbal short-term memory: The role of semantic networks.

PubMed

Poirier, Marie; Saint-Aubin, Jean; Mair, Ali; Tehan, Gerry; Tolan, Anne

2015-04-01

In their recent article, Acheson, MacDonald, and Postle (Journal of Experimental Psychology: Learning, Memory, and Cognition 37:44-59, 2011) made an important but controversial suggestion: They hypothesized that (a) semantic information has an effect on order information in short-term memory (STM) and (b) order recall in STM is based on the level of activation of items within the relevant lexico-semantic long-term memory (LTM) network. However, verbal STM research has typically led to the conclusion that factors such as semantic category have a large effect on the number of correctly recalled items, but little or no impact on order recall (Poirier & Saint-Aubin, Quarterly Journal of Experimental Psychology 48A:384-404, 1995; Saint-Aubin, Ouellette, & Poirier, Psychonomic Bulletin & Review 12:171-177, 2005; Tse, Memory 17:874-891, 2009). Moreover, most formal models of short-term order memory currently suggest a separate mechanism for order coding-that is, one that is separate from item representation and not associated with LTM lexico-semantic networks. Both of the experiments reported here tested the predictions that we derived from Acheson et al. The findings show that, as predicted, manipulations aiming to affect the activation of item representations significantly impacted order memory.

Variable-Length Computerized Adaptive Testing Using the Higher Order DINA Model

ERIC Educational Resources Information Center

Hsu, Chia-Ling; Wang, Wen-Chung

2015-01-01

Cognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent…

Neural Basis of Semantic and Syntactic Interference in Sentence Comprehension

PubMed Central

Glaser, Yi G.; Martin, Randi C.; Van Dyke, Julie A.; Hamilton, A. Cris; Tan, Yingying

2013-01-01

According to the cue-based parsing approach (Lewis, Vasishth, & Van Dyke, 2006), sentence comprehension difficulty derives from interference from material that partially matches syntactic and semantic retrieval cues. In a 2 (low vs. high semantic interference) × 2 (low vs. high syntactic interference) fMRI study, greater activation was observed in left BA 44/45 for high versus low syntactic interference conditions following sentences and in BA 45/47 for high versus low semantic interference following comprehension questions. A conjunction analysis showed BA45 associated with both types of interference, while BA47 was associated with only semantic interference. Greater activation was also observed in the left STG in the high interference conditions. Importantly, the results for the LIFG could not be attributed to greater working memory capacity demands for high interference conditions. The results favor a fractionation of LIFG wherein BA45 is associated with post-retrieval selection and BA47 with controlled retrieval of semantic information. PMID:23933471

Semantic size of abstract concepts: it gets emotional when you can't see it.

PubMed

Yao, Bo; Vasiljevic, Milica; Weick, Mario; Sereno, Margaret E; O'Donnell, Patrick J; Sereno, Sara C

2013-01-01

Size is an important visuo-spatial characteristic of the physical world. In language processing, previous research has demonstrated a processing advantage for words denoting semantically "big" (e.g., jungle) versus "small" (e.g., needle) concrete objects. We investigated whether semantic size plays a role in the recognition of words expressing abstract concepts (e.g., truth). Semantically "big" and "small" concrete and abstract words were presented in a lexical decision task. Responses to "big" words, regardless of their concreteness, were faster than those to "small" words. Critically, we explored the relationship between semantic size and affective characteristics of words as well as their influence on lexical access. Although a word's semantic size was correlated with its emotional arousal, the temporal locus of arousal effects may depend on the level of concreteness. That is, arousal seemed to have an earlier (lexical) effect on abstract words, but a later (post-lexical) effect on concrete words. Our findings provide novel insights into the semantic representations of size in abstract concepts and highlight that affective attributes of words may not always index lexical access.

Usage of semantic representations in recognition memory.

PubMed

Nishiyama, Ryoji; Hirano, Tetsuji; Ukita, Jun

2017-11-01

Meanings of words facilitate false acceptance as well as correct rejection of lures in recognition memory tests, depending on the experimental context. This suggests that semantic representations are both directly and indirectly (i.e., mediated by perceptual representations) used in remembering. Studies using memory conjunction errors (MCEs) paradigms, in which the lures consist of component parts of studied words, have reported semantic facilitation of rejection of the lures. However, attending to components of the lures could potentially cause this. Therefore, we investigated whether semantic overlap of lures facilitates MCEs using Japanese Kanji words in which a whole-word image is more concerned in reading. Experiments demonstrated semantic facilitation of MCEs in a delayed recognition test (Experiment 1), and in immediate recognition tests in which participants were prevented from using phonological or orthographic representations (Experiment 2), and the salient effect on individuals with high semantic memory capacities (Experiment 3). Additionally, analysis of the receiver operating characteristic suggested that this effect is attributed to familiarity-based memory judgement and phantom recollection. These findings indicate that semantic representations can be directly used in remembering, even when perceptual representations of studied words are available.

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

PubMed

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.

Building validation tools for knowledge-based systems

NASA Technical Reports Server (NTRS)

Stachowitz, R. A.; Chang, C. L.; Stock, T. S.; Combs, J. B.

1987-01-01

The Expert Systems Validation Associate (EVA), a validation system under development at the Lockheed Artificial Intelligence Center for more than a year, provides a wide range of validation tools to check the correctness, consistency and completeness of a knowledge-based system. A declarative meta-language (higher-order language), is used to create a generic version of EVA to validate applications written in arbitrary expert system shells. The architecture and functionality of EVA are presented. The functionality includes Structure Check, Logic Check, Extended Structure Check (using semantic information), Extended Logic Check, Semantic Check, Omission Check, Rule Refinement, Control Check, Test Case Generation, Error Localization, and Behavior Verification.

Different Loci of Semantic Interference in Picture Naming vs. Word-Picture Matching Tasks.

PubMed

Harvey, Denise Y; Schnur, Tatiana T

2016-01-01

Naming pictures and matching words to pictures belonging to the same semantic category impairs performance relative to when stimuli come from different semantic categories (i.e., semantic interference). Despite similar semantic interference phenomena in both picture naming and word-picture matching tasks, the locus of interference has been attributed to different levels of the language system - lexical in naming and semantic in word-picture matching. Although both tasks involve access to shared semantic representations, the extent to which interference originates and/or has its locus at a shared level remains unclear, as these effects are often investigated in isolation. We manipulated semantic context in cyclical picture naming and word-picture matching tasks, and tested whether factors tapping semantic-level (generalization of interference to novel category items) and lexical-level processes (interactions with lexical frequency) affected the magnitude of interference, while also assessing whether interference occurs at a shared processing level(s) (transfer of interference across tasks). We found that semantic interference in naming was sensitive to both semantic- and lexical-level processes (i.e., larger interference for novel vs. old and low- vs. high-frequency stimuli), consistent with a semantically mediated lexical locus. Interference in word-picture matching exhibited stable interference for old and novel stimuli and did not interact with lexical frequency. Further, interference transferred from word-picture matching to naming. Together, these experiments provide evidence to suggest that semantic interference in both tasks originates at a shared processing stage (presumably at the semantic level), but that it exerts its effect at different loci when naming pictures vs. matching words to pictures.

Different Loci of Semantic Interference in Picture Naming vs. Word-Picture Matching Tasks

PubMed Central

Harvey, Denise Y.; Schnur, Tatiana T.

2016-01-01

Naming pictures and matching words to pictures belonging to the same semantic category impairs performance relative to when stimuli come from different semantic categories (i.e., semantic interference). Despite similar semantic interference phenomena in both picture naming and word-picture matching tasks, the locus of interference has been attributed to different levels of the language system – lexical in naming and semantic in word-picture matching. Although both tasks involve access to shared semantic representations, the extent to which interference originates and/or has its locus at a shared level remains unclear, as these effects are often investigated in isolation. We manipulated semantic context in cyclical picture naming and word-picture matching tasks, and tested whether factors tapping semantic-level (generalization of interference to novel category items) and lexical-level processes (interactions with lexical frequency) affected the magnitude of interference, while also assessing whether interference occurs at a shared processing level(s) (transfer of interference across tasks). We found that semantic interference in naming was sensitive to both semantic- and lexical-level processes (i.e., larger interference for novel vs. old and low- vs. high-frequency stimuli), consistent with a semantically mediated lexical locus. Interference in word-picture matching exhibited stable interference for old and novel stimuli and did not interact with lexical frequency. Further, interference transferred from word-picture matching to naming. Together, these experiments provide evidence to suggest that semantic interference in both tasks originates at a shared processing stage (presumably at the semantic level), but that it exerts its effect at different loci when naming pictures vs. matching words to pictures. PMID:27242621

A Collection of Features for Semantic Graphs

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

Eliassi-Rad, T; Fodor, I K; Gallagher, B

2007-05-02

Semantic graphs are commonly used to represent data from one or more data sources. Such graphs extend traditional graphs by imposing types on both nodes and links. This type information defines permissible links among specified nodes and can be represented as a graph commonly referred to as an ontology or schema graph. Figure 1 depicts an ontology graph for data from National Association of Securities Dealers. Each node type and link type may also have a list of attributes. To capture the increased complexity of semantic graphs, concepts derived for standard graphs have to be extended. This document explains brieflymore » features commonly used to characterize graphs, and their extensions to semantic graphs. This document is divided into two sections. Section 2 contains the feature descriptions for static graphs. Section 3 extends the features for semantic graphs that vary over time.« less

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

PubMed

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.

Semantic networks for odors and colors in Alzheimer's disease.

PubMed

Razani, Jill; Chan, Agnes; Nordin, Steven; Murphy, Claire

2010-05-01

Impairment in odor-naming ability and in verbal and visual semantic networks raised the hypothesis of a breakdown in the semantic network for odors in Alzheimer's disease (AD). The current study addressed this hypothesis. Twenty-four individuals, half patients with probable AD and half control participants, performed triadic-similarity judgments for odors and colors, separately, which, utilizing the multidimensional scaling (MDS) technique of individual difference scaling analysis (INDSCAL), generated two-dimensional configurations of similarity. The abilities to match odors and colors with written name labels were assessed to investigate disease-related differences in ability to identify and conceptualize the stimuli. In addition, responses on attribute-sorting tasks, requiring the odor and color perceptions to be categorized as one polarity of a certain dimension, were obtained to allow for objective interpretation of the MDS spatial maps. Whereas comparison subjects generated spatial maps based predominantly on relatively abstract characteristics, patients with AD classified odors on perceptual characteristics. The maps for patients with AD also showed disorganized groupings and loose associations between odors. Their normal configurations for colors imply that the patients were able to comprehend the task per se. The data for label matching and for attribute sorting provide further evidence for a disturbance in semantic odor memory in AD. The patients performed poorer than controls on both these odor tasks, implying that the ability to identify and/or conceptualize odors is impaired in AD. The results provide clear evidence for deterioration of the structure of semantic knowledge for odors in AD.

Event-related potentials to event-related words: grammatical class and semantic attributes in the representation of knowledge.

PubMed

Barber, Horacio A; Kousta, Stavroula-Thaleia; Otten, Leun J; Vigliocco, Gabriella

2010-05-21

A number of recent studies have provided contradictory evidence on the question of whether grammatical class plays a role in the neural representation of lexical knowledge. Most of the previous studies comparing the processing of nouns and verbs, however, confounded word meaning and grammatical class by comparing verbs referring to actions with nouns referring to objects. Here, we recorded electrical brain activity from native Italian speakers reading single words all referring to events (e.g., corsa [the run]; correre [to run]), thus avoiding confounding nouns and verbs with objects and actions. We manipulated grammatical class (noun versus verb) as well as semantic attributes (motor versus sensory events). Activity between 300 and 450ms was more negative for nouns than verbs, and for sensory than motor words, over posterior scalp sites. These grammatical class and semantic effects were not dissociable in terms of latency, duration, or scalp distribution. In a later time window (450-110ms) and at frontal regions, grammatical class and semantic effects interacted; motor verbs were more positive than the other three word categories. We suggest that the lack of a temporal and topographical dissociation between grammatical class and semantic effects in the time range of the N400 component is compatible with an account in which both effects reflect the same underlying process related to meaning retrieval, and we link the later effect with working memory operations associated to the experimental task. Copyright 2010 Elsevier B.V. All rights reserved.

The semantic component of the evoked potential of differentiation.

PubMed

Izmailov, Chingis A; Korshunova, Svetlana G; Sokolov, Yevgeniy N

2008-05-01

This work analyzes data from recordings of (occipital and temporal) cortical evoked potentials (called evoked potentials of differentiation (EPD) occurring in humans in response to an abrupt substitution of stimuli. As stimuli we used three groups of words: the names of the ten basic colors taken from Newton's color circle; the names of seven basic emotions forming Shlossberg's circle of emotions; and seven nonsense words comprised of random combinations of letters. Within each group of word stimuli we constructed a matrix of the differences between the amplitudes of mid-latency components of EPD for each pair of words. This matrix was analyzed using the method of multidimensional scaling. As a result of this analysis we were able to distinguish the semantic and configurational components of EPD amplitude. The semantic component of EPD amplitude was evaluated by comparing structure of the data obtained to the circular structures of emotion and color names. The configurational component was evaluated on the basis of the attribute of word length (number of letters). It was demonstrated that the semantic component of the EPD can only be detected in the left occipital lead at an interpeak amplitude of P120-N180. The configurational component is reflected in the occipital and temporal leads to an identical extent, but only in the amplitude of a later (N180-P230) component of the EPD. The results obtained are discussed in terms of the coding of categorized, configurational, and semantic attributes of a visual stimulus.

Evidence for degraded low frequency verbal concepts in left resected temporal lobe epilepsy patients.

PubMed

Visser, M; Forn, C; Lambon Ralph, M A; Hoffman, P; Gómez Ibáñez, A; Sunajuán, Ana; Rosell Negre, P; Villanueva, V; Ávila, C

2018-06-01

According to a large neuropsychological and neuroimaging literature, the bilateral anterior temporal lobe (ATL) is a core region for semantic processing. It seems therefore surprising that semantic memory appears to be preserved in temporal lobe epilepsy (TLE) patients with unilateral ATL resection. However, recent work suggests that the bilateral semantic system is relatively robust against unilateral damage and semantic impairments under these circumstances only become apparent with low frequency specific concepts. In addition, neuroimaging studies have shown that the function of the left and right ATLs differ and therefore left or right ATL resection should lead to a different pattern of impairment. The current study investigated hemispheric differences in the bilateral semantic system by comparing left and right resected TLE patients during verbal semantic processing of low frequency concepts. Picture naming and semantic comprehension tasks with varying word frequencies were included to investigate the pattern of impairment. Left but not right TLE patients showed impaired semantic processing, which was particularly apparent on low frequency items. This indicates that, for verbal information, the bilateral semantic system is more sensitive to damage in the left compared to the right ATL, which is in line with theories that attribute a more prominent role to the left ATL due to connections with pre-semantic verbal regions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Chemical markup, XML, and the world wide web. 6. CMLReact, an XML vocabulary for chemical reactions.

PubMed

Holliday, Gemma L; Murray-Rust, Peter; Rzepa, Henry S

2006-01-01

A set of components (CMLReact) for managing chemical and biochemical reactions has been added to CML. These can be combined to support most of the strategies for the formal representation of reactions. The elements, attributes, and types are formally defined as XMLSchema components, and their semantics are developed. New syntax and semantics in CML are reported and illustrated with 10 examples.

High-performance analysis of filtered semantic graphs

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

Buluc, Aydin; Fox, Armando; Gilbert, John R.

2012-01-01

High performance is a crucial consideration when executing a complex analytic query on a massive semantic graph. In a semantic graph, vertices and edges carry "attributes" of various types. Analytic queries on semantic graphs typically depend on the values of these attributes; thus, the computation must either view the graph through a filter that passes only those individual vertices and edges of interest, or else must first materialize a subgraph or subgraphs consisting of only the vertices and edges of interest. The filtered approach is superior due to its generality, ease of use, and memory efficiency, but may carry amore » performance cost. In the Knowledge Discovery Toolbox (KDT), a Python library for parallel graph computations, the user writes filters in a high-level language, but those filters result in relatively low performance due to the bottleneck of having to call into the Python interpreter for each edge. In this work, we use the Selective Embedded JIT Specialization (SEJITS) approach to automatically translate filters defined by programmers into a lower-level efficiency language, bypassing the upcall into Python. We evaluate our approach by comparing it with the high-performance C++ /MPI Combinatorial BLAS engine, and show that the productivity gained by using a high-level filtering language comes without sacrificing performance.« less

Fuzzy logic system able to detect interesting areas of a video sequence

NASA Astrophysics Data System (ADS)

De Vleeschouwer, Christophe; Marichal, Xavier; Delmot, Thierry; Macq, Benoit M. M.

1997-06-01

This paper introduces an automatic tool able to analyze the picture according to the semantic interest an observer attributes to its content. Its aim is to give a 'level of interest' to the distinct areas of the picture extracted by any segmentation tool. For the purpose of dealing with semantic interpretation of images, a single criterion is clearly insufficient because the human brain, due to its a priori knowledge and its huge memory of real-world concrete scenes, combines different subjective criteria in order to assess its final decision. The developed method permits such combination through a model using assumptions to express some general subjective criteria. Fuzzy logic enables the user to encode knowledge in a form that is very close the way experts think about the decision process. This fuzzy modeling is also well suited to represent multiple collaborating or even conflicting experts opinions. Actually, the assumptions are verified through a non-hierarchical strategy that considers them in a random order, each partial result contributing to the final one. Presented results prove that the tool is effective for a wide range of natural pictures. It is versatile and flexible in that it can be used stand-alone or can take into account any a priori knowledge about the scene.

A higher order conditional random field model for simultaneous classification of land cover and land use

NASA Astrophysics Data System (ADS)

Albert, Lena; Rottensteiner, Franz; Heipke, Christian

2017-08-01

We propose a new approach for the simultaneous classification of land cover and land use considering spatial as well as semantic context. We apply a Conditional Random Fields (CRF) consisting of a land cover and a land use layer. In the land cover layer of the CRF, the nodes represent super-pixels; in the land use layer, the nodes correspond to objects from a geospatial database. Intra-layer edges of the CRF model spatial dependencies between neighbouring image sites. All spatially overlapping sites in both layers are connected by inter-layer edges, which leads to higher order cliques modelling the semantic relation between all land cover and land use sites in the clique. A generic formulation of the higher order potential is proposed. In order to enable efficient inference in the two-layer higher order CRF, we propose an iterative inference procedure in which the two classification tasks mutually influence each other. We integrate contextual relations between land cover and land use in the classification process by using contextual features describing the complex dependencies of all nodes in a higher order clique. These features are incorporated in a discriminative classifier, which approximates the higher order potentials during the inference procedure. The approach is designed for input data based on aerial images. Experiments are carried out on two test sites to evaluate the performance of the proposed method. The experiments show that the classification results are improved compared to the results of a non-contextual classifier. For land cover classification, the result is much more homogeneous and the delineation of land cover segments is improved. For the land use classification, an improvement is mainly achieved for land use objects showing non-typical characteristics or similarities to other land use classes. Furthermore, we have shown that the size of the super-pixels has an influence on the level of detail of the classification result, but also on the degree of smoothing induced by the segmentation method, which is especially beneficial for land cover classes covering large, homogeneous areas.

Model-based document categorization employing semantic pattern analysis and local structure clustering

NASA Astrophysics Data System (ADS)

Fume, Kosei; Ishitani, Yasuto

2008-01-01

We propose a document categorization method based on a document model that can be defined externally for each task and that categorizes Web content or business documents into a target category in accordance with the similarity of the model. The main feature of the proposed method consists of two aspects of semantics extraction from an input document. The semantics of terms are extracted by the semantic pattern analysis and implicit meanings of document substructure are specified by a bottom-up text clustering technique focusing on the similarity of text line attributes. We have constructed a system based on the proposed method for trial purposes. The experimental results show that the system achieves more than 80% classification accuracy in categorizing Web content and business documents into 15 or 70 categories.

Flexible goal attribution in early mindreading.

PubMed

Michael, John; Christensen, Wayne

2016-03-01

The 2-systems theory developed by Apperly and Butterfill (2009; Butterfill & Apperly, 2013) is an influential approach to explaining the success of infants and young children on implicit false-belief tasks. There is extensive empirical and theoretical work examining many aspects of this theory, but little attention has been paid to the way in which it characterizes goal attribution. We argue here that this aspect of the theory is inadequate. Butterfill and Apperly's characterization of goal attribution is designed to show how goals could be ascribed by infants without representing them as related to other psychological states, and the minimal mindreading system is supposed to operate without employing flexible semantic-executive cognitive processes. But research on infant goal attribution reveals that infants exhibit a high degree of situational awareness that is strongly suggestive of flexible semantic-executive cognitive processing, and infants appear moreover to be sensitive to interrelations between goals, preferences, and beliefs. Further, close attention to the structure of implicit mindreading tasks--for which the theory was specifically designed--indicates that flexible goal attribution is required to succeed. We conclude by suggesting 2 approaches to resolving these problems. (c) 2016 APA, all rights reserved).

The neural mechanisms of semantic and response conflicts: an fMRI study of practice-related effects in the Stroop task.

PubMed

Chen, Zhencai; Lei, Xu; Ding, Cody; Li, Hong; Chen, Antao

2013-02-01

Previous studies have demonstrated that there are separate neural mechanisms underlying semantic and response conflicts in the Stroop task. However, the practice effects of these conflicts need to be elucidated and the possible involvements of common neural mechanisms are yet to be established. We employed functional magnetic resonance imaging (fMRI) in a 4-2 mapping practice-related Stroop task to determine the neural substrates under these conflicts. Results showed that different patterns of brain activations are associated with practice in the attentional networks (e.g., dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and posterior parietal cortex (PPC)) for both conflicts, response control regions (e.g., inferior frontal junction (IFJ), inferior frontal gyrus (IFG)/insula, and pre-supplementary motor areas (pre-SMA)) for semantic conflict, and posterior cortex for response conflict. We also found areas of common activation in the left hemisphere within the attentional networks, for the early practice stage in semantic conflict and the late stage in "pure" response conflict using conjunction analysis. The different practice effects indicate that there are distinct mechanisms underlying these two conflict types: semantic conflict practice effects are attributable to the automation of stimulus processing, conflict and response control; response conflict practice effects are attributable to the proportional increase of conflict-related cognitive resources. In addition, the areas of common activation suggest that the semantic conflict effect may contain a partial response conflict effect, particularly at the beginning of the task. These findings indicate that there are two kinds of response conflicts contained in the key-pressing Stroop task: the vocal-level (mainly in the early stage) and key-pressing (mainly in the late stage) response conflicts; thus, the use of the subtraction method for the exploration of semantic and response conflicts may need to be further examined. Copyright © 2012 Elsevier Inc. All rights reserved.

Multidatabase Query Processing with Uncertainty in Global Keys and Attribute Values.

ERIC Educational Resources Information Center

Scheuermann, Peter; Li, Wen-Syan; Clifton, Chris

1998-01-01

Presents an approach for dynamic database integration and query processing in the absence of information about attribute correspondences and global IDs. Defines different types of equivalence conditions for the construction of global IDs. Proposes a strategy based on ranked role-sets that makes use of an automated semantic integration procedure…

Research of three level match method about semantic web service based on ontology

NASA Astrophysics Data System (ADS)

Xiao, Jie; Cai, Fang

2011-10-01

An important step of Web service Application is the discovery of useful services. Keywords are used in service discovery in traditional technology like UDDI and WSDL, with the disadvantage of user intervention, lack of semantic description and low accuracy. To cope with these problems, OWL-S is introduced and extended with QoS attributes to describe the attribute and functions of Web Services. A three-level service matching algorithm based on ontology and QOS in proposed in this paper. Our algorithm can match web service by utilizing the service profile, QoS parameters together with input and output of the service. Simulation results shows that it greatly enhanced the speed of service matching while high accuracy is also guaranteed.

Linking Somatic and Symbolic Representation in Semantic Memory: The Dynamic Multilevel Reactivation Framework

PubMed Central

Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J

2016-01-01

Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: 1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? 2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework, an integrative model premised upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the Dynamic Multilevel Reactivation Framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of ‘abstract conceptual features’ does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the material on which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation. PMID:27294419

Linking somatic and symbolic representation in semantic memory: the dynamic multilevel reactivation framework.

PubMed

Reilly, Jamie; Peelle, Jonathan E; Garcia, Amanda; Crutch, Sebastian J

2016-08-01

Biological plausibility is an essential constraint for any viable model of semantic memory. Yet, we have only the most rudimentary understanding of how the human brain conducts abstract symbolic transformations that underlie word and object meaning. Neuroscience has evolved a sophisticated arsenal of techniques for elucidating the architecture of conceptual representation. Nevertheless, theoretical convergence remains elusive. Here we describe several contrastive approaches to the organization of semantic knowledge, and in turn we offer our own perspective on two recurring questions in semantic memory research: (1) to what extent are conceptual representations mediated by sensorimotor knowledge (i.e., to what degree is semantic memory embodied)? (2) How might an embodied semantic system represent abstract concepts such as modularity, symbol, or proposition? To address these questions, we review the merits of sensorimotor (i.e., embodied) and amodal (i.e., disembodied) semantic theories and address the neurobiological constraints underlying each. We conclude that the shortcomings of both perspectives in their extreme forms necessitate a hybrid middle ground. We accordingly propose the Dynamic Multilevel Reactivation Framework-an integrative model predicated upon flexible interplay between sensorimotor and amodal symbolic representations mediated by multiple cortical hubs. We discuss applications of the dynamic multilevel reactivation framework to abstract and concrete concept representation and describe how a multidimensional conceptual topography based on emotion, sensation, and magnitude can successfully frame a semantic space containing meanings for both abstract and concrete words. The consideration of 'abstract conceptual features' does not diminish the role of logical and/or executive processing in activating, manipulating and using information stored in conceptual representations. Rather, it proposes that the materials upon which these processes operate necessarily combine pure sensorimotor information and higher-order cognitive dimensions involved in symbolic representation.

What role does the anterior temporal lobe play in sentence-level processing? Neural correlates of syntactic processing in semantic PPA

PubMed Central

Wilson, Stephen M.; DeMarco, Andrew T.; Henry, Maya L.; Gesierich, Benno; Babiak, Miranda; Mandelli, Maria Luisa; Miller, Bruce L.; Gorno-Tempini, Maria Luisa

2014-01-01

Neuroimaging and neuropsychological studies have implicated the anterior temporal lobe (ATL) in sentence-level processing, with syntactic structure-building and/or combinatorial semantic processing suggested as possible roles. A potential challenge to the view that the ATL is involved in syntactic aspects of sentence processing comes from the clinical syndrome of semantic variant primary progressive aphasia (semantic PPA, also known as semantic dementia). In semantic PPA, bilateral neurodegeneration of the anterior temporal lobes is associated with profound lexical semantic deficits, yet syntax is strikingly spared. The goal of this study was to investigate the neural correlates of syntactic processing in semantic PPA, in order to determine which regions normally involved in syntactic processing are damaged in semantic PPA, and whether spared syntactic processing depends on preserved functionality of intact regions, preserved functionality of atrophic regions, or compensatory functional reorganization. We scanned 20 individuals with semantic PPA and 24 age-matched controls using structural and functional MRI. Participants performed a sentence comprehension task that emphasized syntactic processing and minimized lexical semantic demands. We found that in controls, left inferior frontal and left posterior temporal regions were modulated by syntactic processing, while anterior temporal regions were not significantly modulated. In the semantic PPA group, atrophy was most severe in the anterior temporal lobes, but extended to the posterior temporal regions involved in syntactic processing. Functional activity for syntactic processing was broadly similar in patients and controls; in particular, whole-brain analyses revealed no significant differences between patients and controls in the regions modulated by syntactic processing. The atrophic left anterior temporal lobe did show abnormal functionality in semantic PPA patients, however this took the unexpected form of a failure to deactivate. Taken together, our findings indicate that spared syntactic processing in semantic PPA depends on preserved functionality of structurally intact left frontal regions and moderately atrophic left posterior temporal regions, but no functional reorganization was apparent as a consequence of anterior temporal atrophy and dysfunction. These results suggest that the role of the anterior temporal lobe in sentence processing is less likely to relate to syntactic structure-building, and more likely to relate to higher level processes such as combinatorial semantic processing. PMID:24345172

Semantic Size of Abstract Concepts: It Gets Emotional When You Can’t See It

PubMed Central

Yao, Bo; Vasiljevic, Milica; Weick, Mario; Sereno, Margaret E.; O’Donnell, Patrick J.; Sereno, Sara C.

2013-01-01

Size is an important visuo-spatial characteristic of the physical world. In language processing, previous research has demonstrated a processing advantage for words denoting semantically “big” (e.g., jungle) versus “small” (e.g., needle) concrete objects. We investigated whether semantic size plays a role in the recognition of words expressing abstract concepts (e.g., truth). Semantically “big” and “small” concrete and abstract words were presented in a lexical decision task. Responses to “big” words, regardless of their concreteness, were faster than those to “small” words. Critically, we explored the relationship between semantic size and affective characteristics of words as well as their influence on lexical access. Although a word’s semantic size was correlated with its emotional arousal, the temporal locus of arousal effects may depend on the level of concreteness. That is, arousal seemed to have an earlier (lexical) effect on abstract words, but a later (post-lexical) effect on concrete words. Our findings provide novel insights into the semantic representations of size in abstract concepts and highlight that affective attributes of words may not always index lexical access. PMID:24086421

Song Perception by Professional Singers and Actors: An MEG Study

PubMed Central

Rosslau, Ken; Herholz, Sibylle C.; Knief, Arne; Ortmann, Magdalene; Deuster, Dirk; Schmidt, Claus-Michael; Zehnhoff-Dinnesen, Antoinetteam; Pantev, Christo; Dobel, Christian

2016-01-01

The cortical correlates of speech and music perception are essentially overlapping, and the specific effects of different types of training on these networks remain unknown. We compared two groups of vocally trained professionals for music and speech, singers and actors, using recited and sung rhyme sequences from German art songs with semantic and/ or prosodic/melodic violations (i.e. violations of pitch) of the last word, in order to measure the evoked activation in a magnetoencephalographic (MEG) experiment. MEG data confirmed the existence of intertwined networks for the sung and spoken modality in an early time window after word violation. In essence for this early response, higher activity was measured after melodic/prosodic than semantic violations in predominantly right temporal areas. For singers as well as for actors, modality-specific effects were evident in predominantly left-temporal lateralized activity after semantic expectancy violations in the spoken modality, and right-dominant temporal activity in response to melodic violations in the sung modality. As an indication of a special group-dependent audiation process, higher neuronal activity for singers appeared in a late time window in right temporal and left parietal areas, both after the recited and the sung sequences. PMID:26863437

Analysing the lack of Demand Organisation

NASA Astrophysics Data System (ADS)

Boxer, Philip; Cohen, Bernard

1998-07-01

We seek to develop means of intervention in Enterprises that will enable them to react in an effective, sustainable and timely fashion to changes in the ways that markets and demand are organized; that is, to act strategically. We take an enterprise to be some entity that seeks to provide its clients with services that they value while maintaining its ability to do so in the face of changes in the demands of its clients and in the resources at its disposal. The services that clients value form around what the organization of their demands lack. The concept of strategy therefore rests on critically evaluating the ontology and semantics of the Enterprise in relation to these holes in demand organization. We access ontology and semantics by constructing and manipulating hypothetical, first-order, mathematical models of the Enterprise's services and of its value-adding processes. Because an enterprise is an anticipatory system, its semantic domain must include representations of the enterprise's model of itself and of the market and demand organizations within which it competes. First-order (set) theory provides adequate expressive power here, but alternative, higher order, mathematical frameworks, such as Dubois' hyperincursion, provide inadequate power, particularly in relation to the analysis of the properties of emergence. Knowing exactly why and where this mathematical lack manifests in the analysis process enables effective collaboration between systems analysts and psychoanalysts, and suggest directions for mathematical research.

What is in a contour map? A region-based logical formalization of contour semantics

USGS Publications Warehouse

Usery, E. Lynn; Hahmann, Torsten

2015-01-01

This paper analyses and formalizes contour semantics in a first-order logic ontology that forms the basis for enabling computational common sense reasoning about contour information. The elicited contour semantics comprises four key concepts – contour regions, contour lines, contour values, and contour sets – and their subclasses and associated relations, which are grounded in an existing qualitative spatial ontology. All concepts and relations are illustrated and motivated by physical-geographic features identifiable on topographic contour maps. The encoding of the semantics of contour concepts in first-order logic and a derived conceptual model as basis for an OWL ontology lay the foundation for fully automated, semantically-aware qualitative and quantitative reasoning about contours.

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

ERIC Educational Resources Information Center

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

2017-01-01

Individuals with autism spectrum disorders (ASD) experience difficulties with language, particularly higher-level functions like semantic integration. Yet some studies indicate that semantic processing of non-linguistic stimuli is not impaired, suggesting a language-specific deficit in semantic processing. Using a semantic priming task, we…

Morphometric information to reduce the semantic gap in the characterization of microscopic images of thyroid nodules.

PubMed

Macedo, Alessandra A; Pessotti, Hugo C; Almansa, Luciana F; Felipe, Joaquim C; Kimura, Edna T

2016-07-01

The analyses of several systems for medical-imaging processing typically support the extraction of image attributes, but do not comprise some information that characterizes images. For example, morphometry can be applied to find new information about the visual content of an image. The extension of information may result in knowledge. Subsequently, results of mappings can be applied to recognize exam patterns, thus improving the accuracy of image retrieval and allowing a better interpretation of exam results. Although successfully applied in breast lesion images, the morphometric approach is still poorly explored in thyroid lesions due to the high subjectivity thyroid examinations. This paper presents a theoretical-practical study, considering Computer Aided Diagnosis (CAD) and Morphometry, to reduce the semantic discontinuity between medical image features and human interpretation of image content. The proposed method aggregates the content of microscopic images characterized by morphometric information and other image attributes extracted by traditional object extraction algorithms. This method carries out segmentation, feature extraction, image labeling and classification. Morphometric analysis was included as an object extraction method in order to verify the improvement of its accuracy for automatic classification of microscopic images. To validate this proposal and verify the utility of morphometric information to characterize thyroid images, a CAD system was created to classify real thyroid image-exams into Papillary Cancer, Goiter and Non-Cancer. Results showed that morphometric information can improve the accuracy and precision of image retrieval and the interpretation of results in computer-aided diagnosis. For example, in the scenario where all the extractors are combined with the morphometric information, the CAD system had its best performance (70% of precision in Papillary cases). Results signalized a positive use of morphometric information from images to reduce semantic discontinuity between human interpretation and image characterization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

From structure from motion to historical building information modeling: populating a semantic-aware library of architectural elements

NASA Astrophysics Data System (ADS)

Santagati, Cettina; Lo Turco, Massimiliano

2017-01-01

In recent years, we have witnessed a huge diffusion of building information modeling (BIM) approaches in the field of architectural design, although very little research has been undertaken to explore the value, criticalities, and advantages attributable to the application of these methodologies in the cultural heritage domain. Furthermore, the last developments in digital photogrammetry lead to the easy generation of reliable low-cost three-dimensional textured models that could be used in BIM platforms to create semantic-aware objects that could compose a specific library of historical architectural elements. In this case, the transfer between the point cloud and its corresponding parametric model is not so trivial and the level of geometrical abstraction could not be suitable with the scope of the BIM. The aim of this paper is to explore and retrace the milestone works on this crucial topic in order to identify the unsolved issues and to propose and test a unique and simple workflow practitioner centered and based on the use of the latest available solutions for point cloud managing into commercial BIM platforms.

Cooking "shrimp à la créole": a pilot study of an ecological rehabilitation in semantic dementia.

PubMed

Bier, Nathalie; Macoir, Joël; Joubert, Sven; Bottari, Carolina; Chayer, Céline; Pigot, Hélène; Giroux, Sylvain

2011-08-01

New learning in semantic dementia (SD) seems to be tied to a specific temporal and spatial context. Thus, cognitive rehabilitation could capitalise upon preserved episodic memory and focus on everyday activities which, once learned, will have an impact in everyday life. This pilot study thus explores the effectiveness of an ecological approach in one patient suffering from SD. EC, a 68-year-old woman with SD, stopped cooking complex meals due to a substantial loss of knowledge related to all food types. The therapy consisted of preparing a target recipe. She was asked to generate semantic attributes of ingredients found in one target, one control and two no-therapy recipes. The number of recipes cooked by EC between therapy sessions was computed. She was also asked to prepare a generalisation recipe combining ingredients from the target and control recipes. EC's generated semantic attributes (GSA) of ingredients pertaining to the target and control recipes increased significantly (p < .001), compared to the no-therapy recipes (ps > .79). The proportion of meals cooked also increased significantly (p = .021). For the generalisation recipe, she could not succeed without assistance. Frequent food preparation may have provided EC with new memories about the context, usage and appearance of some concepts. These memories seem very context-bound, but EC nonetheless re-introduced some recipes into her day-to-day life. The impact of these results on the relationship between semantic, episodic and procedural memory is discussed, as well as the relevance of an ecological approach in SD.

FN400 potentials are functionally identical to N400 potentials and reflect semantic processing during recognition testing

PubMed Central

Voss, Joel L.; Federmeier, Kara D.

2010-01-01

The “F” in FN400 denotes a more frontal scalp distribution relative to the morphologically similar N400 component—a distinction consistent with the hypothesized distinct roles of FN400 in familiarity memory versus N400 in language. However, no direct comparisons have substantiated these assumed dissimilarities. To this end, we manipulated short-term semantic priming during a recognition test. Semantic priming effects on N400 were indistinguishable from memory effects at the same latency, and semantic priming strongly modulated the “FN400,” despite having no influence on familiarity memory. Thus, no evidence suggested either electrophysiological or functional differences between the N400 and FN400, and findings were contrary to the linking of the “FN400” to familiarity. Instead, it appears that semantic/conceptual priming (reflected in the N400) occurs during recognition tests, and is frequently (mis)labeled as FN400 and attributed to familiarity. PMID:20701709

Integrating the automatic and the controlled: Strategies in Semantic Priming in an Attractor Network with Latching Dynamics

PubMed Central

Lerner, Itamar; Bentin, Shlomo; Shriki, Oren

2014-01-01

Semantic priming has long been recognized to reflect, along with automatic semantic mechanisms, the contribution of controlled strategies. However, previous theories of controlled priming were mostly qualitative, lacking common grounds with modern mathematical models of automatic priming based on neural networks. Recently, we have introduced a novel attractor network model of automatic semantic priming with latching dynamics. Here, we extend this work to show how the same model can also account for important findings regarding controlled processes. Assuming the rate of semantic transitions in the network can be adapted using simple reinforcement learning, we show how basic findings attributed to controlled processes in priming can be achieved, including their dependency on stimulus onset asynchrony and relatedness proportion and their unique effect on associative, category-exemplar, mediated and backward prime-target relations. We discuss how our mechanism relates to the classic expectancy theory and how it can be further extended in future developments of the model. PMID:24890261

First- and Second-Order Metacognitive Judgments of Semantic Memory Reports: The Influence of Personality Traits and Cognitive Styles

ERIC Educational Resources Information Center

Buratti, Sandra; Allwood, Carl Martin; Kleitman, Sabina

2013-01-01

In learning contexts, people need to make realistic confidence judgments about their memory performance. The present study investigated whether second-order judgments of first-order confidence judgments could help people improve their confidence judgments of semantic memory information. Furthermore, we assessed whether different personality and…

Constituent order and semantic parallelism in online comprehension: eye-tracking evidence from German.

PubMed

Knoeferle, Pia; Crocker, Matthew W

2009-12-01

Reading times for the second conjunct of and-coordinated clauses are faster when the second conjunct parallels the first conjunct in its syntactic or semantic (animacy) structure than when its structure differs (Frazier, Munn, & Clifton, 2000; Frazier, Taft, Roeper, & Clifton, 1984). What remains unclear, however, is the time course of parallelism effects, their scope, and the kinds of linguistic information to which they are sensitive. Findings from the first two eye-tracking experiments revealed incremental constituent order parallelism across the board-both during structural disambiguation (Experiment 1) and in sentences with unambiguously case-marked constituent order (Experiment 2), as well as for both marked and unmarked constituent orders (Experiments 1 and 2). Findings from Experiment 3 revealed effects of both constituent order and subtle semantic (noun phrase similarity) parallelism. Together our findings provide evidence for an across-the-board account of parallelism for processing and-coordinated clauses, in which both constituent order and semantic aspects of representations contribute towards incremental parallelism effects. We discuss our findings in the context of existing findings on parallelism and priming, as well as mechanisms of sentence processing.

A Fine-Grained API Link Prediction Approach Supporting CMDA Mashup Recommendation

NASA Astrophysics Data System (ADS)

Zhang, J.; Bao, Q.; Lee, T. J.; Ramachandran, R.; Lee, S.; Pan, L.; Gatlin, P. N.; Maskey, M.

2017-12-01

Service (API) discovery and recommendation is key to the wide spread of service oriented architecture and service oriented software engineering. Service recommendation typically relies on service linkage prediction calculated by the semantic distances (or similarities) among services based on their collection of inherent attributes. Given a specific context (mashup goal), however, different attributes may contribute differently to a service linkage. In this work, instead of training a model for all attributes as a whole, a novel approach is presented to simultaneously train separate models for individual attributes. Our contributions are summarized in three-fold. First is that we have developed a scalable attribute-level data model, featuring scalability and extensibility. We have extended Multiplicative Attribute Graph (MAG) model to represent node profiles featuring rich categorical attributes, while relaxing its constraint of requiring a priori knowledge of predefined attributes. LDA is leveraged to dynamically identify attributes based on attribute modeling, and multiple Gaussian fit is applied to find global optimal values. The second contribution is that we have seamlessly integrated the latent relationships between API attributes as well as observed network structure based on historical API usage data. Such a layered information model enables us to predict the probability of a link between two APIs based on their attribute link affinities carrying a variety of information including meta data, semantic data, historical usage data, as well as crowdsourcing user comments and annotations. The third contribution is that we have developed a finegrained context-aware mashup-API recommendation technique. On top of individual models trained for separate attributes, a dedicated layer is trained to represent the latent attribute distribution regarding mashup purpose, i.e., sensitivity of attributes to context. Thus, given the description of an intended mashup, the attributes sensitive to the goal will be identified, and corresponding attribute models will be exploited to compute the possibility of API linkages under the context. Such a layered model increases search accuracy.

Mental health symptoms and verbal fluency in elderly people: Evidence from the Spanish longitudinal study of aging.

PubMed

Simpson, Ian Craig; Dumitrache, Cristina Gabriela; Calet, Nuria

2018-04-10

Depression and loneliness are highly prevalent in old age. Moreover these mental health symptoms adversely affect the verbal fluency of the elderly. We examined the relationship between depression and loneliness with verbal fluency in people aged 50 years or older. Research data were collected during the pilot study of the Longitudinal Aging Study in Spain (ELES) in which a representative sample of non-institutionalized Spanish older people was assessed. Here, the cross-sectional data for 962 participants were analysed using hierarchical regressions, controlling for age, education level, overall cognitive functioning, social networks and satisfaction with family. Higher levels of cognitive functioning were associated with higher verbal fluency. Females showed higher levels of phonological fluency. Neither depression nor loneliness were significant predictors of phonological fluency but loneliness was a significant predictor of semantic fluency. For mild levels of loneliness, the rate of decline in semantic fluency slows in the oldest ages. In contrast, for severe loneliness the rate of decline in semantic fluency increases in the oldest ages. Depressive symptoms, loneliness and cognitive impairment are all prominent in ageing and therefore their impact on ageing needs to be better understood. Early detection of loneliness, along with the implementation of intervention for individuals diagnosed with loneliness is advisable in order to avoid negative repercussions for the verbal fluency of these individuals.

Integrating semantic dimension into openEHR archetypes for the management of cerebral palsy electronic medical records.

PubMed

Ellouze, Afef Samet; Bouaziz, Rafik; Ghorbel, Hanen

2016-10-01

Integrating semantic dimension into clinical archetypes is necessary once modeling medical records. First, it enables semantic interoperability and, it offers applying semantic activities on clinical data and provides a higher design quality of Electronic Medical Record (EMR) systems. However, to obtain these advantages, designers need to use archetypes that cover semantic features of clinical concepts involved in their specific applications. In fact, most of archetypes filed within open repositories are expressed in the Archetype Definition Language (ALD) which allows defining only the syntactic structure of clinical concepts weakening semantic activities on the EMR content in the semantic web environment. This paper focuses on the modeling of an EMR prototype for infants affected by Cerebral Palsy (CP), using the dual model approach and integrating semantic web technologies. Such a modeling provides a better delivery of quality of care and ensures semantic interoperability between all involved therapies' information systems. First, data to be documented are identified and collected from the involved therapies. Subsequently, data are analyzed and arranged into archetypes expressed in accordance of ADL. During this step, open archetype repositories are explored, in order to find the suitable archetypes. Then, ADL archetypes are transformed into archetypes expressed in OWL-DL (Ontology Web Language - Description Language). Finally, we construct an ontological source related to these archetypes enabling hence their annotation to facilitate data extraction and providing possibility to exercise semantic activities on such archetypes. Semantic dimension integration into EMR modeled in accordance to the archetype approach. The feasibility of our solution is shown through the development of a prototype, baptized "CP-SMS", which ensures semantic exploitation of CP EMR. This prototype provides the following features: (i) creation of CP EMR instances and their checking by using a knowledge base which we have constructed by interviews with domain experts, (ii) translation of initially CP ADL archetypes into CP OWL-DL archetypes, (iii) creation of an ontological source which we can use to annotate obtained archetypes and (vi) enrichment and supply of the ontological source and integration of semantic relations by providing hence fueling the ontology with new concepts, ensuring consistency and eliminating ambiguity between concepts. The degree of semantic interoperability that could be reached between EMR systems depends strongly on the quality of the used archetypes. Thus, the integration of semantic dimension in archetypes modeling process is crucial. By creating an ontological source and annotating archetypes, we create a supportive platform ensuring semantic interoperability between archetypes-based EMR-systems. Copyright © 2016. Published by Elsevier Inc.

Comparing different types of source memory attributes in dementia of Alzheimer's type.

PubMed

Mammarella, Nicola; Fairfield, Beth; Di Domenico, Alberto

2012-04-01

Source monitoring (SM) refers to our ability to discriminate between memories from different sources. Twenty healthy high-cognitive functioning older adults, 20 healthy low-cognitive functioning older adults, and 20 older adults with dementia of Alzheimer's type (DAT) were asked to perform a series of SM tasks that varied in terms of the to-be-remembered source attribute (perceptual, spatial, temporal, semantic, social, and affective details). Results indicated that older DAT adults had greater difficulty in SM compared to the healthy control groups, especially with spatial and semantic details. Data are discussed in terms of the SM framework and suggest that poor memory for some types of source information may be considered as an important indicator of clinical memory function when assessing for the presence and severity of dementia.

The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery

PubMed Central

2014-01-01

The Semanticscience Integrated Ontology (SIO) is an ontology to facilitate biomedical knowledge discovery. SIO features a simple upper level comprised of essential types and relations for the rich description of arbitrary (real, hypothesized, virtual, fictional) objects, processes and their attributes. SIO specifies simple design patterns to describe and associate qualities, capabilities, functions, quantities, and informational entities including textual, geometrical, and mathematical entities, and provides specific extensions in the domains of chemistry, biology, biochemistry, and bioinformatics. SIO provides an ontological foundation for the Bio2RDF linked data for the life sciences project and is used for semantic integration and discovery for SADI-based semantic web services. SIO is freely available to all users under a creative commons by attribution license. See website for further information: http://sio.semanticscience.org. PMID:24602174

Developing A Web-based User Interface for Semantic Information Retrieval

NASA Technical Reports Server (NTRS)

Berrios, Daniel C.; Keller, Richard M.

2003-01-01

While there are now a number of languages and frameworks that enable computer-based systems to search stored data semantically, the optimal design for effective user interfaces for such systems is still uncle ar. Such interfaces should mask unnecessary query detail from users, yet still allow them to build queries of arbitrary complexity without significant restrictions. We developed a user interface supporting s emantic query generation for Semanticorganizer, a tool used by scient ists and engineers at NASA to construct networks of knowledge and dat a. Through this interface users can select node types, node attribute s and node links to build ad-hoc semantic queries for searching the S emanticOrganizer network.

Mimicking Aphasic Semantic Errors in Normal Speech Production: Evidence from a Novel Experimental Paradigm

ERIC Educational Resources Information Center

Hodgson, Catherine; Lambon Ralph, Matthew A.

2008-01-01

Semantic errors are commonly found in semantic dementia (SD) and some forms of stroke aphasia and provide insights into semantic processing and speech production. Low error rates are found in standard picture naming tasks in normal controls. In order to increase error rates and thus provide an experimental model of aphasic performance, this study…

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

PubMed

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

2015-06-01

We propose a Bayesian framework for the attribution of knowledge, and apply this framework to generate novel predictions about knowledge attribution for different types of "Gettier cases", in which an agent is led to a justified true belief yet has made erroneous assumptions. We tested these predictions using a paradigm based on semantic integration. We coded the frequencies with which participants falsely recalled the word "thought" as "knew" (or a near synonym), yielding an implicit measure of conceptual activation. Our experiments confirmed the predictions of our Bayesian account of knowledge attribution across three experiments. We found that Gettier cases due to counterfeit objects were not treated as knowledge (Experiment 1), but those due to intentionally-replaced evidence were (Experiment 2). Our findings are not well explained by an alternative account focused only on luck, because accidentally-replaced evidence activated the knowledge concept more strongly than did similar false belief cases (Experiment 3). We observed a consistent pattern of results across a number of different vignettes that varied the quality and type of evidence available to agents, the relative stakes involved, and surface details of content. Accordingly, the present findings establish basic phenomena surrounding people's knowledge attributions in Gettier cases, and provide explanations of these phenomena within a Bayesian framework. Copyright © 2015 Elsevier B.V. All rights reserved.

How Semantic Categorization Influences Inhibitory Processing in Middle-Childhood: An Event Related Potentials study

ERIC Educational Resources Information Center

Maguire, Mandy J.; White, Joshua; Brier, Matthew R.

2011-01-01

Throughout middle-childhood, inhibitory processes, which underlie many higher order cognitive tasks, are developing. Little is known about how inhibitory processes change as a task becomes conceptually more difficult during these important years. In adults, as Go/NoGo tasks become more difficult there is a systematic decrease in the P3 NoGo…

Distinct functional contributions of primary sensory and association areas to audiovisual integration in object categorization.

PubMed

Werner, Sebastian; Noppeney, Uta

2010-02-17

Multisensory interactions have been demonstrated in a distributed neural system encompassing primary sensory and higher-order association areas. However, their distinct functional roles in multisensory integration remain unclear. This functional magnetic resonance imaging study dissociated the functional contributions of three cortical levels to multisensory integration in object categorization. Subjects actively categorized or passively perceived noisy auditory and visual signals emanating from everyday actions with objects. The experiment included two 2 x 2 factorial designs that manipulated either (1) the presence/absence or (2) the informativeness of the sensory inputs. These experimental manipulations revealed three patterns of audiovisual interactions. (1) In primary auditory cortices (PACs), a concurrent visual input increased the stimulus salience by amplifying the auditory response regardless of task-context. Effective connectivity analyses demonstrated that this automatic response amplification is mediated via both direct and indirect [via superior temporal sulcus (STS)] connectivity to visual cortices. (2) In STS and intraparietal sulcus (IPS), audiovisual interactions sustained the integration of higher-order object features and predicted subjects' audiovisual benefits in object categorization. (3) In the left ventrolateral prefrontal cortex (vlPFC), explicit semantic categorization resulted in suppressive audiovisual interactions as an index for multisensory facilitation of semantic retrieval and response selection. In conclusion, multisensory integration emerges at multiple processing stages within the cortical hierarchy. The distinct profiles of audiovisual interactions dissociate audiovisual salience effects in PACs, formation of object representations in STS/IPS and audiovisual facilitation of semantic categorization in vlPFC. Furthermore, in STS/IPS, the profiles of audiovisual interactions were behaviorally relevant and predicted subjects' multisensory benefits in performance accuracy.

Semantic representations in the temporal pole predict false memories

PubMed Central

Chadwick, Martin J.; Anjum, Raeesa S.; Kumaran, Dharshan; Schacter, Daniel L.; Spiers, Hugo J.; Hassabis, Demis

2016-01-01

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the “semantic hub” of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories. PMID:27551087

Semantic representations in the temporal pole predict false memories.

PubMed

Chadwick, Martin J; Anjum, Raeesa S; Kumaran, Dharshan; Schacter, Daniel L; Spiers, Hugo J; Hassabis, Demis

2016-09-06

Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the "semantic hub" of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.

Weighted Description Logics Preference Formulas for Multiattribute Negotiation

NASA Astrophysics Data System (ADS)

Ragone, Azzurra; di Noia, Tommaso; Donini, Francesco M.; di Sciascio, Eugenio; Wellman, Michael P.

We propose a framework to compute the utility of an agreement w.r.t a preference set in a negotiation process. In particular, we refer to preferences expressed as weighted formulas in a decidable fragment of First-order Logic and agreements expressed as a formula. We ground our framework in Description Logics (DL) endowed with disjunction, to be compliant with Semantic Web technologies. A logic based approach to preference representation allows, when a background knowledge base is exploited, to relax the often unrealistic assumption of additive independence among attributes. We provide suitable definitions of the problem and present algorithms to compute utility in our setting. We also validate our approach through an experimental evaluation.

Desire or Disease? Framing Obesity to Influence Attributions of Responsibility and Policy Support.

PubMed

McGlynn, Joseph; McGlone, Matthew S

2018-02-01

The way we describe health threats affects perceptions of severity and preferred solutions to reduce risk. Most people agree obesity is a problem, but differ in how they attribute responsibility for development and decline of the disease. We explored effects of message framing on attributions of responsibility and support for public obesity policies using a 3 × 2 factorial design. Participants read one of six versions of a health message describing the negative effects of obesity. Message frames influenced respondent attributions and their support for policies to reduce obesity. Those who read a message that assigned agency to the disease (e.g., Obesity causes health problems) endorsed genetics as the cause to a greater degree than those who read a semantically equivalent message that instead assigned agency to people (e.g., Obese people develop health problems). In contrast, assigning agency to people rather than to the disease prompted higher attributions of individual responsibility and support for public policies. Explicit message frames that directly connected responsibility for obesity to either individual or societal factors had no effect on respondent perceptions. Findings suggest explicit arguments may be less effective in shifting perceptions of health threats than arguments embedded in agentic message frames. The results demonstrate specific message features that influence how people attribute responsibility for the onset and solution of obesity.

Body-part-specific representations of semantic noun categories.

PubMed

Carota, Francesca; Moseley, Rachel; Pulvermüller, Friedemann

2012-06-01

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

Further differentiating item and order information in semantic memory: students' recall of words from the "CU Fight Song", Harry Potter book titles, and Scooby Doo theme song.

PubMed

Overstreet, Michael F; Healy, Alice F; Neath, Ian

2017-01-01

University of Colorado (CU) students were tested for both order and item information in their semantic memory for the "CU Fight Song". Following an earlier study by Overstreet and Healy [(2011). Item and order information in semantic memory: Students' retention of the "CU fight song" lyrics. Memory & Cognition, 39, 251-259. doi: 10.3758/s13421-010-0018-3 ], a symmetrical bow-shaped serial position function (with both primacy and recency advantages) was found for reconstructing the order of the nine lines in the song, whereas a function with no primacy advantage was found for recalling a missing word from each line. This difference between order and item information was found even though students filled in missing words without any alternatives provided and missing words came from the beginning, middle, or end of each line. Similar results were found for CU students' recall of the sequence of Harry Potter book titles and the lyrics of the Scooby Doo theme song. These findings strengthen the claim that the pronounced serial position function in semantic memory occurs largely because of the retention of order, rather than item, information.

Medial temporal and neocortical contributions to remote memory for semantic narratives: evidence from amnesia.

PubMed

Verfaellie, Mieke; Bousquet, Kathryn; Keane, Margaret M

2014-08-01

Studies of remote memory for semantic facts and concepts suggest that hippocampal lesions lead to a temporally graded impairment that extends no more than ten years prior to the onset of amnesia. Such findings have led to the notion that once consolidated, semantic memories are represented neocortically and are no longer dependent on the hippocampus. Here, we examined the fate of well-established semantic narratives following medial temporal lobe (MTL) lesions. Seven amnesic patients, five with lesions restricted to the MTL and two with lesions extending into lateral temporal cortex (MTL+), were asked to recount fairy tales and bible stories that they rated as familiar. Narratives were scored for number and type of details, number of main thematic elements, and order in which the main thematic elements were recounted. In comparison to controls, patients with MTL lesions produced fewer details, but the number and order of main thematic elements generated was intact. By contrast, patients with MTL+ lesions showed a pervasive impairment, affecting not only the generation of details, but also the generation and ordering of main steps. These findings challenge the notion that, once consolidated, semantic memories are no longer dependent on the hippocampus for retrieval. Possible hippocampal contributions to the retrieval of detailed semantic narratives are discussed. Published by Elsevier Ltd.

Semantic Differential Scale Method Can Reveal Multi-Dimensional Aspects of Mind Perception.

PubMed

Takahashi, Hideyuki; Ban, Midori; Asada, Minoru

2016-01-01

As humans, we tend to perceive minds in both living and non-living entities, such as robots. From a questionnaire developed in a previous mind perception study, authors found that perceived minds could be located on two dimensions "experience" and "agency." This questionnaire allowed the assessment of how we perceive minds of various entities from a multi-dimensional point of view. In this questionnaire, subjects had to evaluate explicit mental capacities of target characters (e.g., capacity to feel hunger). However, we sometimes perceive minds in non-living entities, even though we cannot attribute these evidently biological capacities to the entity. In this study, we performed a large-scale web survey to assess mind perception by using the semantic differential scale method. We revealed that two mind dimensions "emotion" and "intelligence," respectively, corresponded to the two mind dimensions (experience and agency) proposed in a previous mind perception study. We did this without having to ask about specific mental capacities. We believe that the semantic differential scale is a useful method to assess the dimensions of mind perception especially for non-living entities that are hard to be attributed to biological capacities.

Knowledge representation and management: benefits and challenges of the semantic web for the fields of KRM and NLP.

PubMed

Rassinoux, A-M

2011-01-01

To summarize excellent current research in the field of knowledge representation and management (KRM). A synopsis of the articles selected for the IMIA Yearbook 2011 is provided and an attempt to highlight the current trends in the field is sketched. This last decade, with the extension of the text-based web towards a semantic-structured web, NLP techniques have experienced a renewed interest in knowledge extraction. This trend is corroborated through the five papers selected for the KRM section of the Yearbook 2011. They all depict outstanding studies that exploit NLP technologies whenever possible in order to accurately extract meaningful information from various biomedical textual sources. Bringing semantic structure to the meaningful content of textual web pages affords the user with cooperative sharing and intelligent finding of electronic data. As exemplified by the best paper selection, more and more advanced biomedical applications aim at exploiting the meaningful richness of free-text documents in order to generate semantic metadata and recently to learn and populate domain ontologies. These later are becoming a key piece as they allow portraying the semantics of the Semantic Web content. Maintaining their consistency with documents and semantic annotations that refer to them is a crucial challenge of the Semantic Web for the coming years.

Matching Alternative Addresses: a Semantic Web Approach

NASA Astrophysics Data System (ADS)

Ariannamazi, S.; Karimipour, F.; Hakimpour, F.

2015-12-01

Rapid development of crowd-sourcing or volunteered geographic information (VGI) provides opportunities for authoritatives that deal with geospatial information. Heterogeneity of multiple data sources and inconsistency of data types is a key characteristics of VGI datasets. The expansion of cities resulted in the growing number of POIs in the OpenStreetMap, a well-known VGI source, which causes the datasets to outdate in short periods of time. These changes made to spatial and aspatial attributes of features such as names and addresses might cause confusion or ambiguity in the processes that require feature's literal information like addressing and geocoding. VGI sources neither will conform specific vocabularies nor will remain in a specific schema for a long period of time. As a result, the integration of VGI sources is crucial and inevitable in order to avoid duplication and the waste of resources. Information integration can be used to match features and qualify different annotation alternatives for disambiguation. This study enhances the search capabilities of geospatial tools with applications able to understand user terminology to pursuit an efficient way for finding desired results. Semantic web is a capable tool for developing technologies that deal with lexical and numerical calculations and estimations. There are a vast amount of literal-spatial data representing the capability of linguistic information in knowledge modeling, but these resources need to be harmonized based on Semantic Web standards. The process of making addresses homogenous generates a helpful tool based on spatial data integration and lexical annotation matching and disambiguating.

Long-term semantic representations moderate the effect of attentional refreshing on episodic memory.

PubMed

Loaiza, Vanessa M; Duperreault, Kayla A; Rhodes, Matthew G; McCabe, David P

2015-02-01

The McCabe effect (McCabe, Journal of Memory and Language 58:480-494, 2008) refers to an advantage in episodic memory (EM) retrieval for memoranda studied in complex span versus simple span tasks, particularly for memoranda presented in earlier serial positions. This finding has been attributed to the necessity to refresh memoranda during complex span tasks that, in turn, promotes content-context binding in working memory (WM). Several frameworks have conceptualized WM as being embedded in long-term memory. Thus, refreshing may be less efficient when memoranda are not well-established in long-term semantic memory (SM). To investigate this, we presented words and nonwords in simple and complex span trials in order to manipulate the long-term semantic representations of the memoranda with the requirement to refresh the memoranda during WM. A recognition test was administered that required participants to make a remember-know decision for each memorandum recognized as old. The results replicated the McCabe effect, but only for words, and the beneficial effect of refreshing opportunities was exclusive to recollection. These results extend previous research by indicating that the predictive relationship between WM refreshing and long-term EM is specific to recollection and, furthermore, moderated by representations in long-term SM. This supports the predictions of WM frameworks that espouse the importance of refreshing in content-context binding, but also those that view WM as being an activated subset of and, therefore, constrained by the contents of long-term memory.

Specific default mode subnetworks support mentalizing as revealed through opposing network recruitment by social and semantic FMRI tasks.

PubMed

Hyatt, Christopher J; Calhoun, Vince D; Pearlson, Godfrey D; Assaf, Michal

2015-08-01

The ability to attribute mental states to others, or "mentalizing," is posited to involve specific subnetworks within the overall default mode network (DMN), but this question needs clarification. To determine which default mode (DM) subnetworks are engaged by mentalizing processes, we assessed task-related recruitment of DM subnetworks. Spatial independent component analysis (sICA) applied to fMRI data using relatively high-order model (75 components). Healthy participants (n = 53, ages 17-60) performed two fMRI tasks: an interactive game involving mentalizing (Domino), a semantic memory task (SORT), and a resting state fMRI scan. sICA of the two tasks split the DMN into 10 subnetworks located in three core regions: medial prefrontal cortex (mPFC; five subnetworks), posterior cingulate/precuneus (PCC/PrC; three subnetworks), and bilateral temporoparietal junction (TPJ). Mentalizing events increased recruitment in five of 10 DM subnetworks, located in all three core DMN regions. In addition, three of these five DM subnetworks, one dmPFC subnetwork, one PCC/PrC subnetwork, and the right TPJ subnetwork, showed reduced recruitment by semantic memory task events. The opposing modulation by the two tasks suggests that these three DM subnetworks are specifically engaged in mentalizing. Our findings, therefore, suggest the unique involvement of mentalizing processes in only three of 10 DM subnetworks, and support the importance of the dmPFC, PCC/PrC, and right TPJ in mentalizing as described in prior studies. © 2015 Wiley Periodicals, Inc.

Semantically transparent fingerprinting for right protection of digital cinema

NASA Astrophysics Data System (ADS)

Wu, Xiaolin

2003-06-01

Digital cinema, a new frontier and crown jewel of digital multimedia, has the potential of revolutionizing the science, engineering and business of movie production and distribution. The advantages of digital cinema technology over traditional analog technology are numerous and profound. But without effective and enforceable copyright protection measures, digital cinema can be more susceptible to widespread piracy, which can dampen or even prevent the commercial deployment of digital cinema. In this paper we propose a novel approach of fingerprinting each individual distribution copy of a digital movie for the purpose of tracing pirated copies back to their source. The proposed fingerprinting technique presents a fundamental departure from the traditional digital watermarking/fingerprinting techniques. Its novelty and uniqueness lie in a so-called semantic or subjective transparency property. The fingerprints are created by editing those visual and audio attributes that can be modified with semantic and subjective transparency to the audience. Semantically-transparent fingerprinting or watermarking is the most robust kind among all existing watermarking techniques, because it is content-based not sample-based, and semantically-recoverable not statistically-recoverable.

Reflecting on Learner Assessments and Their Validity in the Presence of Emerging Evidence from Neuroscience

ERIC Educational Resources Information Center

Watagodakumbura, Chandana

2015-01-01

We can now get purposefully directed in the way we assess our learners in light of the emergence of evidence from the field of neuroscience. Why higher-order learning or abstract concepts need to be the focus in assessment is elaborated using the knowledge of semantic and episodic memories. With most of our learning identified to be implicit, why…

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

PubMed

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).

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

PubMed

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.

Integrating a Hypernymic Proposition Interpreter into a Semantic Processor for Biomedical Texts

PubMed Central

Fiszman, Marcelo; Rindflesch, Thomas C.; Kilicoglu, Halil

2003-01-01

Semantic processing provides the potential for producing high quality results in natural language processing (NLP) applications in the biomedical domain. In this paper, we address a specific semantic phenomenon, the hypernymic proposition, and concentrate on integrating the interpretation of such predications into a more general semantic processor in order to improve overall accuracy. A preliminary evaluation assesses the contribution of hypernymic propositions in providing more specific semantic predications and thus improving effectiveness in retrieving treatment propositions in MEDLINE abstracts. Finally, we discuss the generalization of this methodology to additional semantic propositions as well as other types of biomedical texts. PMID:14728170

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases.

PubMed

Wollbrett, Julien; Larmande, Pierre; de Lamotte, Frédéric; Ruiz, Manuel

2013-04-15

In recent years, a large amount of "-omics" data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic.

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases

PubMed Central

2013-01-01

Background In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers. Results We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases. Conclusions BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic. PMID:23586394

Classification deficits in Alzheimer's disease with special reference to living and nonliving things.

PubMed

Montanes, P; Goldblum, M C; Boller, F

1996-08-01

The present study was conducted to assess the hypothesis that visual similarity between exemplars within a semantic category may affect differentially the recognition process of living and nonliving things, according to task demands, in patients with semantic memory disorders. Thirty-nine Alzheimer's patients and 39 normal elderly subjects were presented with a task in which they had to classify pictures and words, depicting either living or nonliving things, at two levels of classification: subordinate (e.g., mammals versus birds or tools versus vehicles) and attribute (e.g., wild versus domestic animals or fast versus slow vehicles). Contrary to previous results (Montañes, Goldblum, & Boller, 1995) in a naming task, but as expected, living things were better classified than nonliving ones by both controls and patients. As expected, classifications at the subordinate level also gave rise to better performance than classifications at the attribute level. Although (and somewhat unexpectedly) no advantage of picture over word classification emerged, some effects consistent with the hypothesis that visual similarity affects picture classification emerged, in particular within a subgroup of patients with predominant verbal deficits and the most severe semantic memory disorders. This subgroup obtained a better score on classification of pictures than of words depicting living items (that share many visual features) when classification is at the subordinate level (for which visual similarity is a reliable clue to classification), but met with major difficulties when classifying those pictures at the attribute level (for which shared visual features are not reliable clues to classification). These results emphasize the fact that some "normal" effects specific to items in living and nonliving categories have to be considered among the factors causing selective category-specific deficits in patients, as well as their relevance in achieving tasks which require either differentiation between competing exemplars in the same semantic category (naming) or detection of resemblance between those exemplars (categorization).

kACTUS 2: Privacy Preserving in Classification Tasks Using k-Anonymity

NASA Astrophysics Data System (ADS)

Kisilevich, Slava; Elovici, Yuval; Shapira, Bracha; Rokach, Lior

k-anonymity is the method used for masking sensitive data which successfully solves the problem of re-linking of data with an external source and makes it difficult to re-identify the individual. Thus k-anonymity works on a set of quasi-identifiers (public sensitive attributes), whose possible availability and linking is anticipated from external dataset, and demands that the released dataset will contain at least k records for every possible quasi-identifier value. Another aspect of k is its capability of maintaining the truthfulness of the released data (unlike other existing methods). This is achieved by generalization, a primary technique in k-anonymity. Generalization consists of generalizing attribute values and substituting them with semantically consistent but less precise values. When the substituted value doesn’t preserve semantic validity the technique is called suppression which is a private case of generalization. We present a hybrid approach called compensation which is based on suppression and swapping for achieving privacy. Since swapping decreases the truthfulness of attribute values there is a tradeoff between level of swapping (information truthfulness) and suppression (information loss) incorporated in our algorithm.

Learning multiple relative attributes with humans in the loop.

PubMed

Qian, Buyue; Wang, Xiang; Cao, Nan; Jiang, Yu-Gang; Davidson, Ian

2014-12-01

Semantic attributes have been recognized as a more spontaneous manner to describe and annotate image content. It is widely accepted that image annotation using semantic attributes is a significant improvement to the traditional binary or multiclass annotation due to its naturally continuous and relative properties. Though useful, existing approaches rely on an abundant supervision and high-quality training data, which limit their applicability. Two standard methods to overcome small amounts of guidance and low-quality training data are transfer and active learning. In the context of relative attributes, this would entail learning multiple relative attributes simultaneously and actively querying a human for additional information. This paper addresses the two main limitations in existing work: 1) it actively adds humans to the learning loop so that minimal additional guidance can be given and 2) it learns multiple relative attributes simultaneously and thereby leverages dependence amongst them. In this paper, we formulate a joint active learning to rank framework with pairwise supervision to achieve these two aims, which also has other benefits such as the ability to be kernelized. The proposed framework optimizes over a set of ranking functions (measuring the strength of the presence of attributes) simultaneously and dependently on each other. The proposed pairwise queries take the form of which one of these two pictures is more natural? These queries can be easily answered by humans. Extensive empirical study on real image data sets shows that our proposed method, compared with several state-of-the-art methods, achieves superior retrieval performance while requires significantly less human inputs.

Modelling Metamorphism by Abstract Interpretation

NASA Astrophysics Data System (ADS)

Dalla Preda, Mila; Giacobazzi, Roberto; Debray, Saumya; Coogan, Kevin; Townsend, Gregg M.

Metamorphic malware apply semantics-preserving transformations to their own code in order to foil detection systems based on signature matching. In this paper we consider the problem of automatically extract metamorphic signatures from these malware. We introduce a semantics for self-modifying code, later called phase semantics, and prove its correctness by showing that it is an abstract interpretation of the standard trace semantics. Phase semantics precisely models the metamorphic code behavior by providing a set of traces of programs which correspond to the possible evolutions of the metamorphic code during execution. We show that metamorphic signatures can be automatically extracted by abstract interpretation of the phase semantics, and that regular metamorphism can be modelled as finite state automata abstraction of the phase semantics.

Part-set cueing impairment & facilitation in semantic memory.

PubMed

Kelley, Matthew R; Parihar, Sushmeena A

2018-01-19

The present study explored the influence of part-set cues in semantic memory using tests of "free" recall, reconstruction of order, and serial recall. Nine distinct categories of information were used (e.g., Zodiac signs, Harry Potter books, Star Wars films, planets). The results showed part-set cueing impairment for all three "free" recall sets, whereas part-set cueing facilitation was evident for five of the six ordered sets. Generally, the present results parallel those often observed across episodic tasks, which could indicate that similar mechanisms contribute to part-set cueing effects in both episodic and semantic memory. A novel anchoring explanation of part-set cueing facilitation in order and spatial tasks is provided.

Abnormal dynamics of language in schizophrenia.

PubMed

Stephane, Massoud; Kuskowski, Michael; Gundel, Jeanette

2014-05-30

Language could be conceptualized as a dynamic system that includes multiple interactive levels (sub-lexical, lexical, sentence, and discourse) and components (phonology, semantics, and syntax). In schizophrenia, abnormalities are observed at all language elements (levels and components) but the dynamic between these elements remains unclear. We hypothesize that the dynamics between language elements in schizophrenia is abnormal and explore how this dynamic is altered. We, first, investigated language elements with comparable procedures in patients and healthy controls. Second, using measures of reaction time, we performed multiple linear regression analyses to evaluate the inter-relationships among language elements and the effect of group on these relationships. Patients significantly differed from controls with respect to sub-lexical/lexical, lexical/sentence, and sentence/discourse regression coefficients. The intercepts of the regression slopes increased in the same order above (from lower to higher levels) in patients but not in controls. Regression coefficients between syntax and both sentence level and discourse level semantics did not differentiate patients from controls. This study indicates that the dynamics between language elements is abnormal in schizophrenia. In patients, top-down flow of linguistic information might be reduced, and the relationship between phonology and semantics but not between syntax and semantics appears to be altered. Published by Elsevier Ireland Ltd.

Kokkos GPU Compiler

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

Moss, Nicholas

The Kokkos Clang compiler is a version of the Clang C++ compiler that has been modified to perform targeted code generation for Kokkos constructs in the goal of generating highly optimized code and to provide semantic (domain) awareness throughout the compilation toolchain of these constructs such as parallel for and parallel reduce. This approach is taken to explore the possibilities of exposing the developer’s intentions to the underlying compiler infrastructure (e.g. optimization and analysis passes within the middle stages of the compiler) instead of relying solely on the restricted capabilities of C++ template metaprogramming. To date our current activities havemore » focused on correct GPU code generation and thus we have not yet focused on improving overall performance. The compiler is implemented by recognizing specific (syntactic) Kokkos constructs in order to bypass normal template expansion mechanisms and instead use the semantic knowledge of Kokkos to directly generate code in the compiler’s intermediate representation (IR); which is then translated into an NVIDIA-centric GPU program and supporting runtime calls. In addition, by capturing and maintaining the higher-level semantics of Kokkos directly within the lower levels of the compiler has the potential for significantly improving the ability of the compiler to communicate with the developer in the terms of their original programming model/semantics.« less

Individual differences in automatic semantic priming.

PubMed

Andrews, Sally; Lo, Steson; Xia, Violet

2017-05-01

This research investigated whether masked semantic priming in a semantic categorization task that required classification of words as animals or nonanimals was modulated by individual differences in lexical proficiency. A sample of 89 skilled readers, assessed on reading comprehension, vocabulary and spelling ability, classified target words preceded by brief (50 ms) masked primes that were either congruent or incongruent with the category of the target. Congruent primes were also selected to be either high (e.g., hawk EAGLE, pistol RIFLE) or low (e.g., mole EAGLE, boots RIFLE) in semantic feature overlap with the target. "Overall proficiency," indexed by high performance on both a "semantic composite" measure of reading comprehension and vocabulary and a "spelling composite," was associated with stronger congruence priming from both high and low feature overlap primes for animal exemplars, but only predicted priming from low overlap primes for nonexemplars. Classification of high frequency nonexemplars was also significantly modulated by an independent "spelling-meaning" factor, indexed by the discrepancy between the semantic and spelling composites, because relatively higher scores on the semantic than the spelling composite were associated with stronger semantic priming. These findings show that higher lexical proficiency is associated with stronger evidence of automatic semantic priming and suggest that individual differences in lexical quality modulate the division of labor between orthographic and semantic processing in early lexical retrieval. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Effect of Concurrent Semantic Categorization on Delayed Serial Recall

ERIC Educational Resources Information Center

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

2011-01-01

The influence of semantic processing on the serial ordering of items in short-term memory was explored using a novel dual-task paradigm. Participants engaged in 2 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…

Episodic but not semantic order memory difficulties in autism spectrum disorder: evidence from the Historical Figures Task.

PubMed

Gaigg, Sebastian B; Bowler, Dermot M; Gardiner, John M

2014-01-01

Considerable evidence suggests that the episodic memory system operates abnormally in autism spectrum disorder (ASD) whereas the functions of the semantic memory system are relatively preserved. Here we show that the same dissociation also applies to the domain of order memory. We asked adult participants to order the names of famous historical figures either according to their chronological order in history (probing semantic memory) or according to a random sequence shown once on a screen (probing episodic memory). As predicted, adults with ASD performed less well than age- and IQ-matched comparison individuals only on the episodic task. This observation is of considerable importance in the context of developmental theory because semantic and episodic order memory abilities can be dissociated in typically developing infants before they reach the age at which the behavioural markers associated with ASD are first apparent. This raises the possibility that early emerging memory abnormalities play a role in shaping the developmental trajectory of the disorder. We discuss the broader implications of this possibility and highlight the urgent need for greater scrutiny of memory competences in ASD early in development.

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

PubMed

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

2017-03-01

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

The modulatory influence of the functional COMT Val158Met polymorphism on lexical decisions and semantic priming.

PubMed

Reuter, Martin; Montag, Christian; Peters, Kristina; Kocher, Anne; Kiefer, Markus

2009-01-01

The role of the prefrontal Cortex (PFC) in higher cognitive functions - including working memory, conflict resolution, set shifting and semantic processing - has been demonstrated unequivocally. Despite the great heterogeneity among tasks measuring these phenotypes, due in part to the different cognitive sub-processes implied and the specificity of the stimulus material used, there is agreement that all of these tasks recruit an executive control system located in the PFC. On a biochemical level it is known that the dopaminergic system plays an important role in executive control functions. Evidence comes from molecular genetics relating the functional COMT Val158Met polymorphism to working memory and set shifting. In order determine whether this pattern of findings generalises to linguistic and semantic processing, we investigated the effects of the COMT Val158Met polymorphism in lexical decision making using masked and unmasked versions of the semantic priming paradigm on N = 104 healthy subjects. Although we observed strong priming effects in all conditions (masked priming, unmasked priming with short/long stimulus asynchronies (SOAs), direct and indirect priming), COMT was not significantly related to priming, suggesting no reliable influence on semantic processing. However, COMT Val158Met was strongly associated with lexical decision latencies in all priming conditions if considered separately, explaining between 9 and 14.5% of the variance. Therefore, the findings indicate that COMT mainly influences more general executive control functions in the PFC supporting the speed of lexical decisions.

The thematic hierarchy in sentence comprehension: A study on the interaction between verb class and word order in Spanish.

PubMed

Gattei, Carolina A; Dickey, Michael W; Wainselboim, Alejandro J; París, Luis

2015-01-01

Linking is the theory that captures the mapping of the semantic roles of lexical arguments to the syntactic functions of the phrases that realize them. At the sentence level, linking allows us to understand "who did what to whom" in an event. In Spanish, linking has been shown to interact with word order, verb class, and case marking. The current study aims to provide the first piece of experimental evidence about the interplay between word order and verb type in Spanish. We achieve this by adopting role and reference grammar and the extended argument dependency model. Two different types of clauses were examined in a self-paced reading task: clauses with object-experiencer psychological verbs and activity verbs. These types of verbs differ in the way that their syntactic and semantic structures are linked, and thus they provide interesting evidence on how information that belongs to the syntax-semantics interface might influence the predictive and integrative processes of sentence comprehension with alternative word orders. Results indicate that in Spanish, comprehension and processing speed is enhanced when the order of the constituents in the sentence mirrors their ranking on a semantic hierarchy that encodes a verb's lexical semantics. Moreover, results show that during online comprehension, predictive mechanisms based on argument hierarchization are used rapidly to inform the processing system. Our findings corroborate already existing cross-linguistic evidence on the issue and are briefly discussed in the light of other sentence-processing models.

FRED: a program development tool

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

Shilling, J.

1985-09-01

The structured, screen-based editor FRED is introduced. FRED provides incremental parsing and semantic analysis. The parsing is based on an LL(1) top-down algorithm which has been modified to provide follow-the-cursor parsing and soft templates. The languages accepted by the editor are LL(1) languages with the addition of the Unknown and preferred production non-terminal classes. The semantic analysis is based on the incremental update of attribute grammar equations. We briefly describe the interface between FRED and an automated reference librarian system that is under development.

ERPs, semantic processing and age.

PubMed

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.

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

PubMed

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

2011-01-01

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

Reproducibility and Discriminability of Brain Patterns of Semantic Categories Enhanced by Congruent Audiovisual Stimuli

PubMed Central

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

2011-01-01

One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or semantic categories through a functional magnetic resonance imaging (fMRI) experiment. We used a pattern search method to extract brain patterns corresponding to two semantic categories: “old people” and “young people.” These brain patterns were elicited by semantically congruent audiovisual, semantically incongruent audiovisual, unimodal visual, and unimodal auditory stimuli belonging to the two semantic categories. We calculated the reproducibility index, which measures the similarity of the patterns within the same category. We also decoded the semantic categories from these brain patterns. The decoding accuracy reflects the discriminability of the brain patterns between two categories. The results showed that both the reproducibility index of brain patterns and the decoding accuracy were significantly higher for semantically congruent audiovisual stimuli than for unimodal visual and unimodal auditory stimuli, while the semantically incongruent stimuli did not elicit brain patterns with significantly higher reproducibility index or decoding accuracy. Thus, the semantically congruent audiovisual stimuli enhanced the within-class reproducibility of brain patterns and the between-class discriminability of brain patterns, and facilitate neural representations of semantic categories or concepts. Furthermore, we analyzed the brain activity in superior temporal sulcus and middle temporal gyrus (STS/MTG). The strength of the fMRI signal and the reproducibility index were enhanced by the semantically congruent audiovisual stimuli. Our results support the use of the reproducibility index as a potential tool to supplement the fMRI signal amplitude for evaluating multimodal integration. PMID:21750692

Usage and applications of Semantic Web techniques and technologies to support chemistry research

PubMed Central

2014-01-01

Background The drug discovery process is now highly dependent on the management, curation and integration of large amounts of potentially useful data. Semantics are necessary in order to interpret the information and derive knowledge. Advances in recent years have mitigated concerns that the lack of robust, usable tools has inhibited the adoption of methodologies based on semantics. Results This paper presents three examples of how Semantic Web techniques and technologies can be used in order to support chemistry research: a controlled vocabulary for quantities, units and symbols in physical chemistry; a controlled vocabulary for the classification and labelling of chemical substances and mixtures; and, a database of chemical identifiers. This paper also presents a Web-based service that uses the datasets in order to assist with the completion of risk assessment forms, along with a discussion of the legal implications and value-proposition for the use of such a service. Conclusions We have introduced the Semantic Web concepts, technologies, and methodologies that can be used to support chemistry research, and have demonstrated the application of those techniques in three areas very relevant to modern chemistry research, generating three new datasets that we offer as exemplars of an extensible portfolio of advanced data integration facilities. We have thereby established the importance of Semantic Web techniques and technologies for meeting Wild’s fourth “grand challenge”. PMID:24855494

Usage and applications of Semantic Web techniques and technologies to support chemistry research.

PubMed

Borkum, Mark I; Frey, Jeremy G

2014-01-01

The drug discovery process is now highly dependent on the management, curation and integration of large amounts of potentially useful data. Semantics are necessary in order to interpret the information and derive knowledge. Advances in recent years have mitigated concerns that the lack of robust, usable tools has inhibited the adoption of methodologies based on semantics. THIS PAPER PRESENTS THREE EXAMPLES OF HOW SEMANTIC WEB TECHNIQUES AND TECHNOLOGIES CAN BE USED IN ORDER TO SUPPORT CHEMISTRY RESEARCH: a controlled vocabulary for quantities, units and symbols in physical chemistry; a controlled vocabulary for the classification and labelling of chemical substances and mixtures; and, a database of chemical identifiers. This paper also presents a Web-based service that uses the datasets in order to assist with the completion of risk assessment forms, along with a discussion of the legal implications and value-proposition for the use of such a service. We have introduced the Semantic Web concepts, technologies, and methodologies that can be used to support chemistry research, and have demonstrated the application of those techniques in three areas very relevant to modern chemistry research, generating three new datasets that we offer as exemplars of an extensible portfolio of advanced data integration facilities. We have thereby established the importance of Semantic Web techniques and technologies for meeting Wild's fourth "grand challenge".

Neural Representations of Belief Concepts: A Representational Similarity Approach to Social Semantics

PubMed Central

Leshinskaya, Anna; Contreras, Juan Manuel; Caramazza, Alfonso; Mitchell, Jason P.

2017-01-01

Abstract The present experiment identified neural regions that represent a class of concepts that are independent of perceptual or sensory attributes. During functional magnetic resonance imaging scanning, participants viewed names of social groups (e.g. Atheists, Evangelicals, and Economists) and performed a one-back similarity judgment according to 1 of 2 dimensions of belief attributes: political orientation (Liberal to Conservative) or spiritualism (Spiritualist to Materialist). By generalizing across a wide variety of social groups that possess these beliefs, these attribute concepts did not coincide with any specific sensory quality, allowing us to target conceptual, rather than perceptual, representations. Multi-voxel pattern searchlight analysis was used to identify regions in which activation patterns distinguished the 2 ends of both dimensions: Conservative from Liberal social groups when participants focused on the political orientation dimension, and spiritual from Materialist groups when participants focused on the spiritualism dimension. A cluster in right precuneus exhibited such a pattern, indicating that it carries information about belief-attribute concepts and forms part of semantic memory—perhaps a component particularly concerned with psychological traits. This region did not overlap with the theory of mind network, which engaged nearby, but distinct, parts of precuneus. These findings have implications for the neural organization of conceptual knowledge, especially the understanding of social groups. PMID:28108495

Weakly supervised visual dictionary learning by harnessing image attributes.

PubMed

Gao, Yue; Ji, Rongrong; Liu, Wei; Dai, Qionghai; Hua, Gang

2014-12-01

Bag-of-features (BoFs) representation has been extensively applied to deal with various computer vision applications. To extract discriminative and descriptive BoF, one important step is to learn a good dictionary to minimize the quantization loss between local features and codewords. While most existing visual dictionary learning approaches are engaged with unsupervised feature quantization, the latest trend has turned to supervised learning by harnessing the semantic labels of images or regions. However, such labels are typically too expensive to acquire, which restricts the scalability of supervised dictionary learning approaches. In this paper, we propose to leverage image attributes to weakly supervise the dictionary learning procedure without requiring any actual labels. As a key contribution, our approach establishes a generative hidden Markov random field (HMRF), which models the quantized codewords as the observed states and the image attributes as the hidden states, respectively. Dictionary learning is then performed by supervised grouping the observed states, where the supervised information is stemmed from the hidden states of the HMRF. In such a way, the proposed dictionary learning approach incorporates the image attributes to learn a semantic-preserving BoF representation without any genuine supervision. Experiments in large-scale image retrieval and classification tasks corroborate that our approach significantly outperforms the state-of-the-art unsupervised dictionary learning approaches.

Semantic Advertising for Web 3.0

NASA Astrophysics Data System (ADS)

Thomas, Edward; Pan, Jeff Z.; Taylor, Stuart; Ren, Yuan; Jekjantuk, Nophadol; Zhao, Yuting

Advertising on the World Wide Web is based around automatically matching web pages with appropriate advertisements, in the form of banner ads, interactive adverts, or text links. Traditionally this has been done by manual classification of pages, or more recently using information retrieval techniques to find the most important keywords from the page, and match these to keywords being used by adverts. In this paper, we propose a new model for online advertising, based around lightweight embedded semantics. This will improve the relevancy of adverts on the World Wide Web and help to kick-start the use of RDFa as a mechanism for adding lightweight semantic attributes to the Web. Furthermore, we propose a system architecture for the proposed new model, based on our scalable ontology reasoning infrastructure TrOWL.

Semantic Clustering of Search Engine Results

PubMed Central

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

2015-01-01

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

Atmosphere-based image classification through luminance and hue

NASA Astrophysics Data System (ADS)

Xu, Feng; Zhang, Yujin

2005-07-01

In this paper a novel image classification system is proposed. Atmosphere serves an important role in generating the scene"s topic or in conveying the message behind the scene"s story, which belongs to abstract attribute level in semantic levels. At first, five atmosphere semantic categories are defined according to rules of photo and film grammar, followed by global luminance and hue features. Then the hierarchical SVM classifiers are applied. In each classification stage, corresponding features are extracted and the trained linear SVM is implemented, resulting in two classes. After three stages of classification, five atmosphere categories are obtained. At last, the text annotation of the atmosphere semantics and the corresponding features by Extensible Markup Language (XML) in MPEG-7 is defined, which can be integrated into more multimedia applications (such as searching, indexing and accessing of multimedia content). The experiment is performed on Corel images and film frames. The classification results prove the effectiveness of the definition of atmosphere semantic classes and the corresponding features.

Semantic memory: a feature-based analysis and new norms for Italian.

PubMed

Montefinese, Maria; Ambrosini, Ettore; Fairfield, Beth; Mammarella, Nicola

2013-06-01

Semantic norms for properties produced by native speakers are valuable tools for researchers interested in the structure of semantic memory and in category-specific semantic deficits in individuals following brain damage. The aims of this study were threefold. First, we sought to extend existing semantic norms by adopting an empirical approach to category (Exp. 1) and concept (Exp. 2) selection, in order to obtain a more representative set of semantic memory features. Second, we extensively outlined a new set of semantic production norms collected from Italian native speakers for 120 artifactual and natural basic-level concepts, using numerous measures and statistics following a feature-listing task (Exp. 3b). Finally, we aimed to create a new publicly accessible database, since only a few existing databases are publicly available online.

EEG Theta and Alpha Responses Reveal Qualitative Differences in Processing Taxonomic versus Thematic Semantic Relationships

ERIC Educational Resources Information Center

Maguire, Mandy J.; Brier, Matthew R.; Ferree, Thomas C.

2010-01-01

Despite the importance of semantic relationships to our understanding of semantic knowledge, the nature of the neural processes underlying these abilities are not well understood. In order to investigate these processes, 20 healthy adults listened to thematically related (e.g., leash-dog), taxonomically related (e.g., horse-dog), or unrelated…

"Big Brown Dog" or "Brown Big Dog?" An Electrophysiological Study of Semantic Constraints on Prenominal Adjective Order

ERIC Educational Resources Information Center

Kemmerer, David; Weber-Fox, Christine; Price, Karen; Zdanczyk, Cynthia; Way, Heather

2007-01-01

Event-related brain potentials (ERPs) were recorded while participants read and made acceptability judgments about sentences containing three types of adjective sequences: (1) normal sequences--e.g., "Jennifer rode a huge gray elephant"; (2) reversed sequences that violate grammatical-semantic constraints on linear order--e.g., *"Jennifer rode a…

Linguistic generalization on the basis of function and constraints on the basis of statistical preemption.

PubMed

Perek, Florent; Goldberg, Adele E

2017-11-01

How do people learn to use language in creative but constrained ways? Experiment 1 investigates linguistic creativity by exposing adult participants to two novel word order constructions that differ in terms of their semantics: One construction exclusively describes actions that have a strong effect; the other construction describes actions with a weaker but otherwise similar effect. One group of participants witnessed novel verbs only appearing in one construction or the other, while another group witnessed a minority of verbs alternating between constructions. Subsequent production and judgment results demonstrate that participants in both conditions extended and accepted verbs in whichever construction best described the intended message. Unlike related previous work, this finding is not naturally attributable to prior knowledge of the likely division of labor between verbs and constructions or to a difference in cue validity. In order to investigate how speakers learn to constrain generalizations, Experiment 2 includes one verb (out of 6) that was witnessed in a single construction to describe both strong and weak effects, essentially statistically preempting the use of the other construction. In this case, participants were much more lexically conservative with this verb and other verbs, while they nonetheless displayed an appreciation of the distinct semantics of the constructions with new novel verbs. Results indicate that the need to better express an intended message encourages generalization, while statistical preemption constrains generalization by providing evidence that verbs are restricted in their distribution. Copyright © 2017 Elsevier B.V. All rights reserved.

The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing

PubMed Central

Weber, Kirsten; Lau, Ellen F.; Stillerman, Benjamin; Kuperberg, Gina R.

2016-01-01

Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions—a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the statistical structure of the wider environmental context. Together, these findings highlight close links between the networks mediating semantic prediction, executive function and learning, giving new insights into how our brains are able to flexibly adapt to our environment. PMID:27010386

The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing.

PubMed

Weber, Kirsten; Lau, Ellen F; Stillerman, Benjamin; Kuperberg, Gina R

2016-01-01

Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the statistical structure of the wider environmental context. Together, these findings highlight close links between the networks mediating semantic prediction, executive function and learning, giving new insights into how our brains are able to flexibly adapt to our environment.

Reduced short-term memory capacity in Alzheimer's disease: the role of phonological, lexical, and semantic processing.

PubMed

Caza, Nicole; Belleville, Sylvie

2008-05-01

Individuals with Alzheimer's disease (AD) are often reported to have reduced verbal short-term memory capacity, typically attributed to their attention/executive deficits. However, these individuals also tend to show progressive impairment of semantic, lexical, and phonological processing which may underlie their low short-term memory capacity. The goals of this study were to assess the contribution of each level of representation (phonological, lexical, and semantic) to immediate serial recall performance in 18 individuals with AD, and to examine how these linguistic effects on short-term memory were modulated by their reduced capacity to manipulate information in short-term memory associated with executive dysfunction. Results showed that individuals with AD had difficulty recalling items that relied on phonological representations, which led to increased lexicality effects relative to the control group. This finding suggests that patients have a greater reliance on lexical/semantic information than controls, possibly to make up for deficits in retention and processing of phonological material. This lexical/semantic effect was not found to be significantly correlated with patients' capacity to manipulate verbal material in short-term memory, indicating that language processing and executive deficits may independently contribute to reducing verbal short-term memory capacity in AD.

LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

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

VERSPOOR, KARIN; LIN, SHOU-DE

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

Interpreting semantic clustering effects in free recall.

PubMed

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.

Richer concepts are better remembered: number of features effects in free recall

PubMed Central

Hargreaves, Ian S.; Pexman, Penny M.; Johnson, Jeremy C.; Zdrazilova, Lenka

2012-01-01

Many models of memory build in a term for encoding variability, the observation that there can be variability in the richness or extensiveness of processing at encoding, and that this variability has consequences for retrieval. In four experiments, we tested the expectation that encoding variability could be driven by the properties of the to-be-remembered item. Specifically, that concepts associated with more semantic features would be better remembered than concepts associated with fewer semantic features. Using feature listing norms we selected sets of items for which people tend to list higher numbers of features (high NoF) and items for which people tend to list lower numbers of features (low NoF). Results showed more accurate free recall for high NoF concepts than for low NoF concepts in expected memory tasks (Experiments 1–3) and also in an unexpected memory task (Experiment 4). This effect was not the result of associative chaining between study items (Experiment 3), and can be attributed to the amount of item-specific processing that occurs at study (Experiment 4). These results provide evidence that stimulus-specific differences in processing at encoding have consequences for explicit memory retrieval. PMID:22514526

Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications

PubMed Central

Masanz, James J; Ogren, Philip V; Zheng, Jiaping; Sohn, Sunghwan; Kipper-Schuler, Karin C; Chute, Christopher G

2010-01-01

We aim to build and evaluate an open-source natural language processing system for information extraction from electronic medical record clinical free-text. We describe and evaluate our system, the clinical Text Analysis and Knowledge Extraction System (cTAKES), released open-source at http://www.ohnlp.org. The cTAKES builds on existing open-source technologies—the Unstructured Information Management Architecture framework and OpenNLP natural language processing toolkit. Its components, specifically trained for the clinical domain, create rich linguistic and semantic annotations. Performance of individual components: sentence boundary detector accuracy=0.949; tokenizer accuracy=0.949; part-of-speech tagger accuracy=0.936; shallow parser F-score=0.924; named entity recognizer and system-level evaluation F-score=0.715 for exact and 0.824 for overlapping spans, and accuracy for concept mapping, negation, and status attributes for exact and overlapping spans of 0.957, 0.943, 0.859, and 0.580, 0.939, and 0.839, respectively. Overall performance is discussed against five applications. The cTAKES annotations are the foundation for methods and modules for higher-level semantic processing of clinical free-text. PMID:20819853

Serial position effects in semantic memory: reconstructing the order of verses of hymns.

PubMed

Maylor, Elizabeth A

2002-12-01

Serial position effects (primacy and recency) have been consistently demonstrated in both short- and long-term episodic memory tasks. The search for corresponding effects in semantic memory tasks (e.g., reconstructing the order of U.S. presidents) has been confounded by factors such as differential exposure to stimuli. In the present study, the stimuli were six-verse hymns that would have been sung from the first to the last verse by churchgoers on numerous occasions. Participants were presented with the verses of each hymn in random order and were required to reconstruct the correct order. Primacy and recency effects were significantly more evident for churchgoers than for nonchurchgoers. Moreover, error gradients were steeper than chance for churchgoers but not for nonchurchgoers; in other words, churchgoers' errors were more likely to be close to the correct position than further away. These findings provide the first unequivocal demonstration of serial position effects in semantic memory.

Thematic relatedness production norms for 100 object concepts.

PubMed

Jouravlev, Olessia; McRae, Ken

2016-12-01

Knowledge of thematic relations is an area of increased interest in semantic memory research because it is crucial to many cognitive processes. One methodological issue that researchers face is how to identify pairs of thematically related concepts that are well-established in semantic memory for most people. In this article, we review existing methods of assessing thematic relatedness and provide thematic relatedness production norming data for 100 object concepts. In addition, 1,174 related concept pairs obtained from the production norms were classified as reflecting one of the five subtypes of relations: attributive, argument, coordinate, locative, and temporal. The database and methodology will be useful for researchers interested in the effects of thematic knowledge on language processing, analogical reasoning, similarity judgments, and memory. These data will also benefit researchers interested in investigating potential processing differences among the five types of semantic relations.

A Graph-Based Recovery and Decomposition of Swanson’s Hypothesis using Semantic Predications

PubMed Central

Cameron, Delroy; Bodenreider, Olivier; Yalamanchili, Hima; Danh, Tu; Vallabhaneni, Sreeram; Thirunarayan, Krishnaprasad; Sheth, Amit P.; Rindflesch, Thomas C.

2014-01-01

Objectives This paper presents a methodology for recovering and decomposing Swanson’s Raynaud Syndrome–Fish Oil Hypothesis semi-automatically. The methodology leverages the semantics of assertions extracted from biomedical literature (called semantic predications) along with structured background knowledge and graph-based algorithms to semi-automatically capture the informative associations originally discovered manually by Swanson. Demonstrating that Swanson’s manually intensive techniques can be undertaken semi-automatically, paves the way for fully automatic semantics-based hypothesis generation from scientific literature. Methods Semantic predications obtained from biomedical literature allow the construction of labeled directed graphs which contain various associations among concepts from the literature. By aggregating such associations into informative subgraphs, some of the relevant details originally articulated by Swanson has been uncovered. However, by leveraging background knowledge to bridge important knowledge gaps in the literature, a methodology for semi-automatically capturing the detailed associations originally explicated in natural language by Swanson has been developed. Results Our methodology not only recovered the 3 associations commonly recognized as Swanson’s Hypothesis, but also decomposed them into an additional 16 detailed associations, formulated as chains of semantic predications. Altogether, 14 out of the 19 associations that can be attributed to Swanson were retrieved using our approach. To the best of our knowledge, such an in-depth recovery and decomposition of Swanson’s Hypothesis has never been attempted. Conclusion In this work therefore, we presented a methodology for semi- automatically recovering and decomposing Swanson’s RS-DFO Hypothesis using semantic representations and graph algorithms. Our methodology provides new insights into potential prerequisites for semantics-driven Literature-Based Discovery (LBD). These suggest that three critical aspects of LBD include: 1) the need for more expressive representations beyond Swanson’s ABC model; 2) an ability to accurately extract semantic information from text; and 3) the semantic integration of scientific literature with structured background knowledge. PMID:23026233

Mimicking aphasic semantic errors in normal speech production: evidence from a novel experimental paradigm.

PubMed

Hodgson, Catherine; Lambon Ralph, Matthew A

2008-01-01

Semantic errors are commonly found in semantic dementia (SD) and some forms of stroke aphasia and provide insights into semantic processing and speech production. Low error rates are found in standard picture naming tasks in normal controls. In order to increase error rates and thus provide an experimental model of aphasic performance, this study utilised a novel method- tempo picture naming. Experiment 1 showed that, compared to standard deadline naming tasks, participants made more errors on the tempo picture naming tasks. Further, RTs were longer and more errors were produced to living items than non-living items a pattern seen in both semantic dementia and semantically-impaired stroke aphasic patients. Experiment 2 showed that providing the initial phoneme as a cue enhanced performance whereas providing an incorrect phonemic cue further reduced performance. These results support the contention that the tempo picture naming paradigm reduces the time allowed for controlled semantic processing causing increased error rates. This experimental procedure would, therefore, appear to mimic the performance of aphasic patients with multi-modal semantic impairment that results from poor semantic control rather than the degradation of semantic representations observed in semantic dementia [Jefferies, E. A., & Lambon Ralph, M. A. (2006). Semantic impairment in stoke aphasia vs. semantic dementia: A case-series comparison. Brain, 129, 2132-2147]. Further implications for theories of semantic cognition and models of speech processing are discussed.

The contribution of timbre attributes to musical tension.

PubMed

Farbood, Morwaread M; Price, Khen C

2017-01-01

Timbre is an auditory feature that has received relatively little attention in empirical work examining musical tension. In order to address this gap, an experiment was conducted to explore the contribution of several specific timbre attributes-inharmonicity, roughness, spectral centroid, spectral deviation, and spectral flatness-to the perception of tension. Listeners compared pairs of sounds representing low and high degrees of each attribute and indicated which sound was more tense. Although the response profiles showed that the high states corresponded with increased tension for all attributes, further analysis revealed that some attributes were strongly correlated with others. When qualitative factors, attribute correlations, and listener responses were all taken into account, there was fairly strong evidence that higher degrees of roughness, inharmonicity, and spectral flatness elicited higher tension. On the other hand, evidence that higher spectral centroid and spectral deviation corresponded to increases in tension was ambiguous.

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

PubMed Central

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

2016-01-01

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

Top-down and bottom-up modulation of language related areas – An fMRI Study

PubMed Central

Noesselt, Tömme; Shah, Nadim Jon; Jäncke, Lutz

2003-01-01

Background One major problem for cognitive neuroscience is to describe the interaction between stimulus and task driven neural modulation. We used fMRI to investigate this interaction in the human brain. Ten male subjects performed a passive listening and a semantic categorization task in a factorial design. In both tasks, words were presented auditorily at three different rates. Results We found: (i) as word presentation rate increased hemodynamic responses increased bilaterally in the superior temporal gyrus including Heschl's gyrus (HG), the planum temporale (PT), and the planum polare (PP); (ii) compared to passive listening, semantic categorization produced increased bilateral activations in the ventral inferior frontal gyrus (IFG) and middle frontal gyrus (MFG); (iii) hemodynamic responses in the left dorsal IFG increased linearly with increasing word presentation rate only during the semantic categorization task; (iv) in the semantic task hemodynamic responses decreased bilaterally in the insula with increasing word presentation rates; and (v) in parts of the HG the hemodynamic response increased with increasing word presentation rates during passive listening more strongly. Conclusion The observed "rate effect" in primary and secondary auditory cortex is in accord with previous findings and suggests that these areas are driven by low-level stimulus attributes. The bilateral effect of semantic categorization is also in accord with previous studies and emphasizes the role of these areas in semantic operations. The interaction between semantic categorization and word presentation in the left IFG indicates that this area has linguistic functions not present in the right IFG. Finally, we speculate that the interaction between semantic categorization and word presentation rates in HG and the insula might reflect an inhibition of the transfer of unnecessary information from the temporal to frontal regions of the brain. PMID:12828789

Semantics of Inheritance and Attributions in the Description System Omega. Revision.

DTIC Science & Technology

1982-01-01

criticized either for being too general or too inflexible. General deductive procedures for predicate logic easily go out of control. There have been a...6 and 7. Section 8 is concerned with a discussion of attributions: the language is extended by introducing syntactic notations for four different...for valid formulas of the theory. The models prorided earlier are usefulL in this stage for providing a guideline and a criterion for suitability of

Evidence of a metacognitive benefit to memory?

PubMed

Hollins, Timothy J; Weber, Nathan

2017-03-01

Studies of the memory-control framework have contrasted free-report and forced-report recall, with little regard to the order of these two tests. The present experiment sought to demonstrate that test order is crucial, and that this suggests a potential role for metacognitive monitoring on memory retrieval. Participants undertook tests of episodic and semantic memory in both free- and forced-report format, in one of the two potential response orders. This showed that free-report performance was more accurate if conducted prior to forced-report, rather than after it, with no cost to memory quantity. Additionally, there was a trend towards higher forced-report performance if it was preceded by an initial free-report test, a pattern revealed by a meta-analysis to be consistent with previous studies in the literature. These findings suggest a reciprocal relationship between metacognitive monitoring and early retrieval processes in memory that results in higher memory performance when monitoring is encouraged.

Personal and Work-Related Predictors of Organizational Commitment and Life Satisfaction of Slovak Women in Higher Education

ERIC Educational Resources Information Center

Brandt, Joanne; Krawczyk, Rosemary; Kalinowski, Jon

2008-01-01

Two samples of Slovak women in higher education were surveyed in order to determine the extent to which organizational commitment and life satisfaction are related to personal and work-related attributes. Organizational commitment was found to be related to the work-related attributes of role conflict and role ambiguity. These work-related…

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

PubMed Central

Bispo, Kalil A.; Rosa, Nelson S.; Cunha, Paulo R. F.

2015-01-01

Wireless sensor networks (WSNs) are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to maximize its lifetime. In this context, this paper presents SITRUS (semantic infrastructure for wireless sensor networks), which aims to reduce the power consumption of WSN nodes using ontologies. SITRUS consists of two major parts: a message-oriented middleware responsible for both an oriented message communication service and a reconfiguration service; and a semantic information processing module whose purpose is to generate a semantic database that provides the basis to decide whether a WSN node needs to be reconfigurated or not. In order to evaluate the proposed solution, we carried out an experimental evaluation to assess the power consumption and memory usage of WSN applications built atop SITRUS. PMID:26528974

Parameters of semantic multisensory integration depend on timing and modality order among people on the autism spectrum: evidence from event-related potentials.

PubMed

Russo, N; Mottron, L; Burack, J A; Jemel, B

2012-07-01

Individuals with autism spectrum disorders (ASD) report difficulty integrating simultaneously presented visual and auditory stimuli (Iarocci & McDonald, 2006), albeit showing enhanced perceptual processing of unisensory stimuli, as well as an enhanced role of perception in higher-order cognitive tasks (Enhanced Perceptual Functioning (EPF) model; Mottron, Dawson, Soulières, Hubert, & Burack, 2006). Individuals with an ASD also integrate auditory-visual inputs over longer periods of time than matched typically developing (TD) peers (Kwakye, Foss-Feig, Cascio, Stone & Wallace, 2011). To tease apart the dichotomy of both extended multisensory processing and enhanced perceptual processing, we used behavioral and electrophysiological measurements of audio-visual integration among persons with ASD. 13 TD and 14 autistics matched on IQ completed a forced choice multisensory semantic congruence task requiring speeded responses regarding the congruence or incongruence of animal sounds and pictures. Stimuli were presented simultaneously or sequentially at various stimulus onset asynchronies in both auditory first and visual first presentations. No group differences were noted in reaction time (RT) or accuracy. The latency at which congruent and incongruent waveforms diverged was the component of interest. In simultaneous presentations, congruent and incongruent waveforms diverged earlier (circa 150 ms) among persons with ASD than among TD individuals (around 350 ms). In sequential presentations, asymmetries in the timing of neuronal processing were noted in ASD which depended on stimulus order, but these were consistent with the nature of specific perceptual strengths in this group. These findings extend the Enhanced Perceptual Functioning Model to the multisensory domain, and provide a more nuanced context for interpreting ERP findings of impaired semantic processing in ASD. Copyright © 2012 Elsevier Ltd. All rights reserved.

An Implicit Measure of Associations with Mental Illness versus Physical Illness: Response Latency Decomposition and Stimuli Differential Functioning in Relation to IAT Order of Associative Conditions and Accuracy

PubMed Central

Mannarini, Stefania; Boffo, Marilisa

2014-01-01

The present study aimed at the definition of a latent measurement dimension underlying an implicit measure of automatic associations between the concept of mental illness and the psychosocial and biogenetic causal explanatory attributes. To this end, an Implicit Association Test (IAT) assessing the association between the Mental Illness and Physical Illness target categories to the Psychological and Biologic attribute categories, representative of the causal explanation domains, was developed. The IAT presented 22 stimuli (words and pictures) to be categorized into the four categories. After 360 university students completed the IAT, a Many-Facet Rasch Measurement (MFRM) modelling approach was applied. The model specified a person latency parameter and a stimulus latency parameter. Two additional parameters were introduced to denote the order of presentation of the task associative conditions and the general response accuracy. Beyond the overall definition of the latent measurement dimension, the MFRM was also applied to disentangle the effect of the task block order and the general response accuracy on the stimuli response latency. Further, the MFRM allowed detecting any differential functioning of each stimulus in relation to both block ordering and accuracy. The results evidenced: a) the existence of a latency measurement dimension underlying the Mental Illness versus Physical Illness - Implicit Association Test; b) significant effects of block order and accuracy on the overall latency; c) a differential functioning of specific stimuli. The results of the present study can contribute to a better understanding of the functioning of an implicit measure of semantic associations with mental illness and give a first blueprint for the examination of relevant issues in the development of an IAT. PMID:25000406

An implicit measure of associations with mental illness versus physical illness: response latency decomposition and stimuli differential functioning in relation to IAT order of associative conditions and accuracy.

PubMed

Mannarini, Stefania; Boffo, Marilisa

2014-01-01

The present study aimed at the definition of a latent measurement dimension underlying an implicit measure of automatic associations between the concept of mental illness and the psychosocial and biogenetic causal explanatory attributes. To this end, an Implicit Association Test (IAT) assessing the association between the Mental Illness and Physical Illness target categories to the Psychological and Biologic attribute categories, representative of the causal explanation domains, was developed. The IAT presented 22 stimuli (words and pictures) to be categorized into the four categories. After 360 university students completed the IAT, a Many-Facet Rasch Measurement (MFRM) modelling approach was applied. The model specified a person latency parameter and a stimulus latency parameter. Two additional parameters were introduced to denote the order of presentation of the task associative conditions and the general response accuracy. Beyond the overall definition of the latent measurement dimension, the MFRM was also applied to disentangle the effect of the task block order and the general response accuracy on the stimuli response latency. Further, the MFRM allowed detecting any differential functioning of each stimulus in relation to both block ordering and accuracy. The results evidenced: a) the existence of a latency measurement dimension underlying the Mental Illness versus Physical Illness - Implicit Association Test; b) significant effects of block order and accuracy on the overall latency; c) a differential functioning of specific stimuli. The results of the present study can contribute to a better understanding of the functioning of an implicit measure of semantic associations with mental illness and give a first blueprint for the examination of relevant issues in the development of an IAT.

Co-occurrence frequency evaluated with large language corpora boosts semantic priming effects.

PubMed

Brunellière, Angèle; Perre, Laetitia; Tran, ThiMai; Bonnotte, Isabelle

2017-09-01

In recent decades, many computational techniques have been developed to analyse the contextual usage of words in large language corpora. The present study examined whether the co-occurrence frequency obtained from large language corpora might boost purely semantic priming effects. Two experiments were conducted: one with conscious semantic priming, the other with subliminal semantic priming. Both experiments contrasted three semantic priming contexts: an unrelated priming context and two related priming contexts with word pairs that are semantically related and that co-occur either frequently or infrequently. In the conscious priming presentation (166-ms stimulus-onset asynchrony, SOA), a semantic priming effect was recorded in both related priming contexts, which was greater with higher co-occurrence frequency. In the subliminal priming presentation (66-ms SOA), no significant priming effect was shown, regardless of the related priming context. These results show that co-occurrence frequency boosts pure semantic priming effects and are discussed with reference to models of semantic network.

Dissociating the semantic function of two neighbouring subregions in the left lateral anterior temporal lobe

PubMed Central

Sanjuán, Ana; Hope, Thomas M.H.; Parker Jones, 'Ōiwi; Prejawa, Susan; Oberhuber, Marion; Guerin, Julie; Seghier, Mohamed L.; Green, David W.; Price, Cathy J.

2015-01-01

We used fMRI in 35 healthy participants to investigate how two neighbouring subregions in the lateral anterior temporal lobe (LATL) contribute to semantic matching and object naming. Four different levels of processing were considered: (A) recognition of the object concepts; (B) search for semantic associations related to object stimuli; (C) retrieval of semantic concepts of interest; and (D) retrieval of stimulus specific concepts as required for naming. During semantic association matching on picture stimuli or heard object names, we found that activation in both subregions was higher when the objects were semantically related (mug–kettle) than unrelated (car–teapot). This is consistent with both LATL subregions playing a role in (C), the successful retrieval of amodal semantic concepts. In addition, one subregion was more activated for object naming than matching semantically related objects, consistent with (D), the retrieval of a specific concept for naming. We discuss the implications of these novel findings for cognitive models of semantic processing and left anterior temporal lobe function. PMID:25496810

Typicality as a Dimension of Encoding

ERIC Educational Resources Information Center

Keller, Dennis; Kellas, George

1978-01-01

The salience of encoding attributes in instances of differing levels of category membership was examined using the release from proactive interference (PI) task with college students. Results are discussed in terms of providing converging evidence for Rosch's (1973,1975) theory of semantic category structure. (Editor/RK)

User Authentication from Web Browsing Behavior

DTIC Science & Technology

2013-05-01

ourselves with a cognitive personal fingerprint. Attribution is broadly defined as the assignment of an ef- fect to a cause. We differentiate between...reusable patterns of behavior. We encode the semantic and stylistic content Figure 4: Burstiness profile below 1 min aggregated across all sessions for

Semantic Shot Classification in Sports Video

NASA Astrophysics Data System (ADS)

Duan, Ling-Yu; Xu, Min; Tian, Qi

2003-01-01

In this paper, we present a unified framework for semantic shot classification in sports videos. Unlike previous approaches, which focus on clustering by aggregating shots with similar low-level features, the proposed scheme makes use of domain knowledge of a specific sport to perform a top-down video shot classification, including identification of video shot classes for each sport, and supervised learning and classification of the given sports video with low-level and middle-level features extracted from the sports video. It is observed that for each sport we can predefine a small number of semantic shot classes, about 5~10, which covers 90~95% of sports broadcasting video. With the supervised learning method, we can map the low-level features to middle-level semantic video shot attributes such as dominant object motion (a player), camera motion patterns, and court shape, etc. On the basis of the appropriate fusion of those middle-level shot classes, we classify video shots into the predefined video shot classes, each of which has a clear semantic meaning. The proposed method has been tested over 4 types of sports videos: tennis, basketball, volleyball and soccer. Good classification accuracy of 85~95% has been achieved. With correctly classified sports video shots, further structural and temporal analysis, such as event detection, video skimming, table of content, etc, will be greatly facilitated.

Abstract Interpreters for Free

NASA Astrophysics Data System (ADS)

Might, Matthew

In small-step abstract interpretations, the concrete and abstract semantics bear an uncanny resemblance. In this work, we present an analysis-design methodology that both explains and exploits that resemblance. Specifically, we present a two-step method to convert a small-step concrete semantics into a family of sound, computable abstract interpretations. The first step re-factors the concrete state-space to eliminate recursive structure; this refactoring of the state-space simultaneously determines a store-passing-style transformation on the underlying concrete semantics. The second step uses inference rules to generate an abstract state-space and a Galois connection simultaneously. The Galois connection allows the calculation of the "optimal" abstract interpretation. The two-step process is unambiguous, but nondeterministic: at each step, analysis designers face choices. Some of these choices ultimately influence properties such as flow-, field- and context-sensitivity. Thus, under the method, we can give the emergence of these properties a graph-theoretic characterization. To illustrate the method, we systematically abstract the continuation-passing style lambda calculus to arrive at two distinct families of analyses. The first is the well-known k-CFA family of analyses. The second consists of novel "environment-centric" abstract interpretations, none of which appear in the literature on static analysis of higher-order programs.

Expressing Intervals in Automated Service Negotiation

NASA Astrophysics Data System (ADS)

Clark, Kassidy P.; Warnier, Martijn; van Splunter, Sander; Brazier, Frances M. T.

During automated negotiation of services between autonomous agents, utility functions are used to evaluate the terms of negotiation. These terms often include intervals of values which are prone to misinterpretation. It is often unclear if an interval embodies a continuum of real numbers or a subset of natural numbers. Furthermore, it is often unclear if an agent is expected to choose only one value, multiple values, a sub-interval or even multiple sub-intervals. Additional semantics are needed to clarify these issues. Normally, these semantics are stored in a domain ontology. However, ontologies are typically domain specific and static in nature. For dynamic environments, in which autonomous agents negotiate resources whose attributes and relationships change rapidly, semantics should be made explicit in the service negotiation. This paper identifies issues that are prone to misinterpretation and proposes a notation for expressing intervals. This notation is illustrated using an example in WS-Agreement.

Semantic Context Detection Using Audio Event Fusion

NASA Astrophysics Data System (ADS)

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

2006-12-01

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

About Edible Restaurants: Conflicts between Syntax and Semantics as Revealed by ERPs

PubMed Central

Kos, Miriam; Vosse, Theo; van den Brink, Daniëlle; Hagoort, Peter

2010-01-01

In order to investigate conflicts between semantics and syntax, we recorded ERPs, while participants read Dutch sentences. Sentences containing conflicts between syntax and semantics (Fred eats in a sandwich…/Fred eats a restaurant…) elicited an N400. These results show that conflicts between syntax and semantics not necessarily lead to P600 effects and are in line with the processing competition account. According to this parallel account the syntactic and semantic processing streams are fully interactive and information from one level can influence the processing at another level. The relative strength of the cues of the processing streams determines which level is affected most strongly by the conflict. The processing competition account maintains the distinction between the N400 as index for semantic processing and the P600 as index for structural processing. PMID:21833277

Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

PubMed

Urbain, Jay

2015-12-01

We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic patients over time. The system was originally developed for the 2014 i2b2 Challenges in Natural Language in Clinical Data. The system's strengths included a high level of accuracy for identifying named entities associated with heart disease risk factor events. The system's primary weakness was due to inaccuracies when characterizing the attributes of some events. For example, determining the relative time of an event with respect to the record date, whether an event is attributable to the patient's history or the patient's family history, and differentiating between current and prior smoking status. We believe these inaccuracies were due in large part to the lack of an effective approach for integrating context into our event detection model. To address these inaccuracies, we explore the addition of a distributional semantic model for characterizing contextual evidence of heart disease risk factor events. Using this semantic model, we raise our initial 2014 i2b2 Challenges in Natural Language of Clinical data F1 score of 0.838 to 0.890 and increased precision by 10.3% without use of any lexicons that might bias our results. Copyright © 2015 Elsevier Inc. All rights reserved.

Gazetteer Brokering through Semantic Mediation

NASA Astrophysics Data System (ADS)

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

2013-12-01

A gazetteer is a geographical directory containing some information regarding places. It provides names, location and other attributes for places which may include points of interest (e.g. buildings, oilfields and boreholes), and other features. These features can be published via web services conforming to the Gazetteer Application Profile of the Web Feature Service (WFS) standard of the Open Geospatial Consortium (OGC). Against the backdrop of advances in geophysical surveys, there has been a significant increase in the amount of data referenced to locations. Gazetteers services have played a significant role in facilitating access to such data, including through provision of specialized queries such as text, spatial and fuzzy search. Recent developments in the OGC have led to advances in gazetteers such as support for multilingualism, diacritics, and querying via advanced spatial constraints (e.g. search by radial search and nearest neighbor). A challenge remaining however, is that gazetteers produced by different organizations have typically been modeled differently. Inconsistencies from gazetteers produced by different organizations may include naming the same feature in a different way, naming the attributes differently, locating the feature in a different location, and providing fewer or more attributes than the other services. The Gazetteer application profile of the WFS is a starting point to address such inconsistencies by providing a standardized interface based on rules specified in ISO 19112, the international standard for spatial referencing by geographic identifiers. The profile, however, does not provide rules to deal with semantic inconsistencies. The USGS and NGA commissioned research into the potential for a Single Point of Entry Global Gazetteer (SPEGG). The research was conducted by the Cross Community Interoperability thread of the OGC testbed, referenced OWS-9. The testbed prototyped approaches for brokering gazetteers through use of semantic web technologies, including ontologies and a semantic mediator. The semantically-enhanced SPEGG allowed a client to submit a single query (e.g. ';hills') and to retrieve data from two separate gazetteers with different vocabularies (e.g. where one refers to ';summits' another refers to ';hills'). Supporting the SPEGG was a SPARQL server that held the ontologies and processed queries on them. Earth Science surveys and forecast always have a place on Earth. Being able to share the information about a place and solve inconsistencies about that place from different sources will enable geoscientists to better do their research. In the advent of mobile geo computing and location based services (LBS), brokering gazetteers will provide geoscientists with access to gazetteer services rich with information and functionality beyond that offered by current generic gazetteers.

Why Can You "Have a Drink" When You Can't "*Have an Eat?"

ERIC Educational Resources Information Center

Wierzbicka, Anna

1982-01-01

Argues that sentences in the "have a V" frame are not idiosyncratic, but exhibit orderly and systematic behavior and are governed by strict semantic rules. Discusses 10 subtypes, each with a slightly different semantic formula. (EKN)

Message passing with parallel queue traversal

DOEpatents

Underwood, Keith D [Albuquerque, NM; Brightwell, Ronald B [Albuquerque, NM; Hemmert, K Scott [Albuquerque, NM

2012-05-01

In message passing implementations, associative matching structures are used to permit list entries to be searched in parallel fashion, thereby avoiding the delay of linear list traversal. List management capabilities are provided to support list entry turnover semantics and priority ordering semantics.

Understanding Freshness Perception from the Cognitive Mechanisms of Flavor: The Case of Beverages

PubMed Central

Roque, Jérémy; Auvray, Malika; Lafraire, Jérémie

2018-01-01

Freshness perception has received recent consideration in the field of consumer science mainly because of its hedonic dimension, which is assumed to influence consumers’ preference and behavior. However, most studies have considered freshness as a multisensory attribute of food and beverage products without investigating the cognitive mechanisms at hand. In the present review, we endorse a slightly different perspective on freshness. We focus on (i) the multisensory integration processes that underpin freshness perception, and (ii) the top–down factors that influence the explicit attribution of freshness to a product by consumers. To do so, we exploit the recent literature on the cognitive underpinnings of flavor perception as a heuristic to better characterize the mechanisms of freshness perception in the particular case of beverages. We argue that the lack of consideration of particular instances of flavor, such as freshness, has resulted in a lack of consensus about the content and structure of different types of flavor representations. We then enrich these theoretical analyses, with a review of the cognitive mechanisms of flavor perception: from multisensory integration processes to the influence of top–down factors (e.g., attentional and semantic). We conclude that similarly to flavor, freshness perception is characterized by hybrid content, both perceptual and semantic, but that freshness has a higher-degree of specificity than flavor. In particular, contrary to flavor, freshness is characterized by specific functions (e.g., alleviation of oropharyngeal symptoms) and likely differs from flavor with respect to the weighting of each sensory contributor, as well as to its subjective location. Finally, we provide a comprehensive model of the cognitive mechanisms that underlie freshness perception. This model paves the way for further empirical research on particular instances of flavor, and will enable advances in the field of food and beverage cognition. PMID:29375453

Understanding Freshness Perception from the Cognitive Mechanisms of Flavor: The Case of Beverages.

PubMed

Roque, Jérémy; Auvray, Malika; Lafraire, Jérémie

2017-01-01

Freshness perception has received recent consideration in the field of consumer science mainly because of its hedonic dimension, which is assumed to influence consumers' preference and behavior. However, most studies have considered freshness as a multisensory attribute of food and beverage products without investigating the cognitive mechanisms at hand. In the present review, we endorse a slightly different perspective on freshness. We focus on (i) the multisensory integration processes that underpin freshness perception, and (ii) the top-down factors that influence the explicit attribution of freshness to a product by consumers. To do so, we exploit the recent literature on the cognitive underpinnings of flavor perception as a heuristic to better characterize the mechanisms of freshness perception in the particular case of beverages. We argue that the lack of consideration of particular instances of flavor, such as freshness, has resulted in a lack of consensus about the content and structure of different types of flavor representations. We then enrich these theoretical analyses, with a review of the cognitive mechanisms of flavor perception: from multisensory integration processes to the influence of top-down factors (e.g., attentional and semantic). We conclude that similarly to flavor, freshness perception is characterized by hybrid content, both perceptual and semantic, but that freshness has a higher-degree of specificity than flavor . In particular, contrary to flavor, freshness is characterized by specific functions (e.g., alleviation of oropharyngeal symptoms) and likely differs from flavor with respect to the weighting of each sensory contributor, as well as to its subjective location. Finally, we provide a comprehensive model of the cognitive mechanisms that underlie freshness perception. This model paves the way for further empirical research on particular instances of flavor, and will enable advances in the field of food and beverage cognition.

Towards Infusing Giovanni with a Semantic and Provenance Aware Visualization System

NASA Astrophysics Data System (ADS)

Del Rio, N.; Pinheiro da Silva, P.; Leptoukh, G. G.; Lynnes, C.

2011-12-01

Giovanni is a Web-based application developed by GES DISC that provides simple and intuitive ways to visualize, analyze, and access vast amounts of Earth science remote sensed data. Currently, the Giovanni visualization module is only aware of the physical links (i.e., hard-coded) between data and services and consequently cannot be easily adapted to new visualization scenarios. VisKo, a semantically enabled visualization framework, can be leveraged by Giovanni as a semantic bridge between data and visualization. VisKo relates data and visualization services at conceptual (i.e., ontological) levels and relies on reasoning systems to leverage the conceptual relationships to automatically infer physical links, facilitating an adaptable environment for new visualization scenarios. This is particularly useful for Giovanni, which has been constantly retrofitted with new visualization software packages to keep up with advancement in visualization capabilities. During our prototype integration of Giovanni with VisKo, a number of future steps were identified that if implemented could cement the integration and promote our prototype to operational status. A number of integration issues arose including the mediation of different languages used by each system to characterize datasets; VisKo relies on semantic data characterization to "match-up" data with visualization processes. It was necessary to identify mappings between Giovanni XML provenance and Proof Markup Language, which is understood by VisKo. Although a translator was implemented based on identified mappings, a more elegant solution is to develop a domain data ontology specific to Giovanni and to "align" this ontology with PML, enabling VisKo to directly ingest the semantic descriptions of Giovanni data. Additionally, the relationship between dataset components (e.g., variables and attributes) and visualization plot components (e.g., geometries, axes, titles) should also be modeled. In Giovanni, meta-data descriptions are used to configure the different properties of the plots such as titles, color-tables, and variable-to-axis bindings. Giovanni services rely on a set of custom attributes and naming conventions that help identify the relationships between dataset components and plot properties. VisKo visualization services however are generic modules that do not rely on any domain specific conventions for identifying relationships between dataset attributes and plot configuration. Rather, VisKo services rely on parameters to configure specific behaviors of the generic services. The relationship between VisKo parameters and plot properties however has yet to formally documented, partly because VisKo regards plots as holistic entities without any internal structure from which to relate parameters. We understand the need for a visualization plot ontology that defines plot components, their retinal properties, such as position and color, and the relationship between the plot properties to controlling service parameter sets. The plot ontology would also be linked to our domain data ontology, providing VisKo with the comprehensive understanding about how data attributes can cue the configuration of plots, and how a specific plot configuration relates to service parameters.

Delta, theta, beta, and gamma brain oscillations index levels of auditory sentence processing.

PubMed

Mai, Guangting; Minett, James W; Wang, William S-Y

2016-06-01

A growing number of studies indicate that multiple ranges of brain oscillations, especially the delta (δ, <4Hz), theta (θ, 4-8Hz), beta (β, 13-30Hz), and gamma (γ, 30-50Hz) bands, are engaged in speech and language processing. It is not clear, however, how these oscillations relate to functional processing at different linguistic hierarchical levels. Using scalp electroencephalography (EEG), the current study tested the hypothesis that phonological and the higher-level linguistic (semantic/syntactic) organizations during auditory sentence processing are indexed by distinct EEG signatures derived from the δ, θ, β, and γ oscillations. We analyzed specific EEG signatures while subjects listened to Mandarin speech stimuli in three different conditions in order to dissociate phonological and semantic/syntactic processing: (1) sentences comprising valid disyllabic words assembled in a valid syntactic structure (real-word condition); (2) utterances with morphologically valid syllables, but not constituting valid disyllabic words (pseudo-word condition); and (3) backward versions of the real-word and pseudo-word conditions. We tested four signatures: band power, EEG-acoustic entrainment (EAE), cross-frequency coupling (CFC), and inter-electrode renormalized partial directed coherence (rPDC). The results show significant effects of band power and EAE of δ and θ oscillations for phonological, rather than semantic/syntactic processing, indicating the importance of tracking δ- and θ-rate phonetic patterns during phonological analysis. We also found significant β-related effects, suggesting tracking of EEG to the acoustic stimulus (high-β EAE), memory processing (θ-low-β CFC), and auditory-motor interactions (20-Hz rPDC) during phonological analysis. For semantic/syntactic processing, we obtained a significant effect of γ power, suggesting lexical memory retrieval or processing grammatical word categories. Based on these findings, we confirm that scalp EEG signatures relevant to δ, θ, β, and γ oscillations can index phonological and semantic/syntactic organizations separately in auditory sentence processing, compatible with the view that phonological and higher-level linguistic processing engage distinct neural networks. Copyright © 2016 Elsevier Inc. All rights reserved.

The Analysis of RDF Semantic Data Storage Optimization in Large Data Era

NASA Astrophysics Data System (ADS)

He, Dandan; Wang, Lijuan; Wang, Can

2018-03-01

With the continuous development of information technology and network technology in China, the Internet has also ushered in the era of large data. In order to obtain the effective acquisition of information in the era of large data, it is necessary to optimize the existing RDF semantic data storage and realize the effective query of various data. This paper discusses the storage optimization of RDF semantic data under large data.

Procedural Semantics as a Theory of Meaning.

DTIC Science & Technology

1981-03-01

Aaron Sloman (none of whom can be held responsible, of course, fcor the opinions expressed herein). Special thanks are also due to John Lyons for valuable...Meanings 12 7 Parametric Ambiguity 14 8 The Economic Necessity of Ambiguity 16 9 Semantic Interpretation 19 10 Semantics of the Internal Language 21 11...sufficiently low order organisms, the behavioral characteristics of that organism in response to stimuli are essentially "wired in" by their genes

Combined use of semantics and metadata to manage Research Data Life Cycle in Environmental Sciences

NASA Astrophysics Data System (ADS)

Aguilar Gómez, Fernando; de Lucas, Jesús Marco; Pertinez, Esther; Palacio, Aida

2017-04-01

The use of metadata to contextualize datasets is quite extended in Earth System Sciences. There are some initiatives and available tools to help data managers to choose the best metadata standard that fit their use cases, like the DCC Metadata Directory (http://www.dcc.ac.uk/resources/metadata-standards). In our use case, we have been gathering physical, chemical and biological data from a water reservoir since 2010. A well metadata definition is crucial not only to contextualize our own data but also to integrate datasets from other sources like satellites or meteorological agencies. That is why we have chosen EML (Ecological Metadata Language), which integrates many different elements to define a dataset, including the project context, instrumentation and parameters definition, and the software used to process, provide quality controls and include the publication details. Those metadata elements can contribute to help both human and machines to understand and process the dataset. However, the use of metadata is not enough to fully support the data life cycle, from the Data Management Plan definition to the Publication and Re-use. To do so, we need to define not only metadata and attributes but also the relationships between them, so semantics are needed. Ontologies, being a knowledge representation, can contribute to define the elements of a research data life cycle, including DMP, datasets, software, etc. They also can define how the different elements are related between them and how they interact. The first advantage of developing an ontology of a knowledge domain is that they provide a common vocabulary hierarchy (i.e. a conceptual schema) that can be used and standardized by all the agents interested in the domain (either humans or machines). This way of using ontologies is one of the basis of the Semantic Web, where ontologies are set to play a key role in establishing a common terminology between agents. To develop an ontology we are using a graphical tool Protégé, which is a graphical ontology-development tool that supports a rich knowledge model and it is open-source and freely available. To process and manage the ontology, we are using Semantic MediaWiki, which is able to process queries. Semantic MediaWiki is an extension of MediaWiki where we can do semantic search and export data in RDF. Our final goal is integrating our data repository portal and semantic processing engine in order to have a complete system to manage the data life cycle stages and their relationships, including machine-actionable DMP solution, datasets and software management, computing resources for processing and analysis and publication features (DOI mint). This way we will be able to reproduce the full data life cycle chain warranting the FAIR+R principles.

Semantic preview benefit in reading English: The effect of initial letter capitalization.

PubMed

Rayner, Keith; Schotter, Elizabeth R

2014-08-01

A major controversy in reading research is whether semantic information is obtained from the word to the right of the currently fixated word (word n + 1). Although most evidence has been negative in English, semantic preview benefit has been observed for readers of Chinese and German. In the present experiment, we investigated whether the discrepancy between English and German may be attributable to a difference in visual properties of the orthography: the first letter of a noun is always capitalized in German, but is only occasionally capitalized in English. This visually salient property may draw greater attention to the word during parafoveal preview and thus increase preview benefit generally (and lead to a greater opportunity for semantic preview benefit). We used English target nouns that can either be capitalized (e.g., We went to the critically acclaimed Ballet of Paris while on vacation.) or not (e.g., We went to the critically acclaimed ballet that was showing in Paris.) and manipulated the capitalization of the preview accordingly, to determine whether capitalization modulates preview benefit in English. The gaze-contingent boundary paradigm was used with identical, semantically related, and unrelated previews. Consistent with our hypothesis, we found numerically larger preview benefits when the preview/target was capitalized than when it was lowercase. Crucially, semantic preview benefit was not observed when the preview/target word was not capitalized, but was observed when the preview/target word was capitalized.

Semantic Development in Spanish-English Bilingual Children: Effects of Age and Language Experience

ERIC Educational Resources Information Center

Sheng, Li; Bedore, Lisa M.; Pena, Elizabeth D.; Fiestas, Christine

2013-01-01

This study examines semantic development in 60 Spanish-English bilingual children, ages 7 years 3 months to 9 years 11 months, who differed orthogonally in age (younger, older) and language experience (higher English experience [HEE], higher Spanish experience [HSE]). Children produced 3 associations to 12 pairs of translation equivalents. Older…

Size matters: bigger is faster.

PubMed

Sereno, Sara C; O'Donnell, Patrick J; Sereno, Margaret E

2009-06-01

A largely unexplored aspect of lexical access in visual word recognition is "semantic size"--namely, the real-world size of an object to which a word refers. A total of 42 participants performed a lexical decision task on concrete nouns denoting either big or small objects (e.g., bookcase or teaspoon). Items were matched pairwise on relevant lexical dimensions. Participants' reaction times were reliably faster to semantically "big" versus "small" words. The results are discussed in terms of possible mechanisms, including more active representations for "big" words, due to the ecological importance attributed to large objects in the environment and the relative speed of neural responses to large objects.

Visuospatial working memory in children with autism: the effect of a semantic global organization.

PubMed

Mammarella, Irene C; Giofrè, David; Caviola, Sara; Cornoldi, Cesare; Hamilton, Colin

2014-06-01

It has been reported that individuals with Autism Spectrum Disorders (ASD) perceive visual scenes as a sparse set of details rather than as a congruent and meaningful unit, failing in the extraction of the global configuration of the scene. In the present study, children with ASD were compared with typically developing (TD) children, in a visuospatial working memory task, the Visual Patterns Test (VPT). The VPT array was manipulated to vary the semantic affordance of the pattern, high semantic (global) vs. low semantic; temporal parameters were also manipulated within the change detection protocol. Overall, there was no main effect associated with Group, however there was a significant effect associated with Semantics, which was further qualified by an interaction between the Group and Semantic factors; there was only a significant effect of semantics in the TD group. The findings are discussed in light of the weak central coherence theory where the ASD group are unable to make use of long term memory semantics in order to construct global representations of the array. Copyright © 2014 Elsevier Ltd. All rights reserved.

Individual differences in white matter microstructure predict semantic control.

PubMed

Nugiel, Tehila; Alm, Kylie H; Olson, Ingrid R

2016-12-01

In everyday conversation, we make many rapid choices between competing concepts and words in order to convey our intent. This process is termed semantic control, and it is thought to rely on information transmission between a distributed semantic store in the temporal lobes and a more discrete region, optimized for retrieval and selection, in the left inferior frontal gyrus. Here, we used diffusion tensor imaging in a group of neurologically normal young adults to investigate the relationship between semantic control and white matter tracts that have been implicated in semantic memory retrieval. Participants completed a verb generation task that taps semantic control (Snyder & Munakata, 2008; Snyder et al., 2010) and underwent a diffusion imaging scan. Deterministic tractography was performed to compute indices representing the microstructural properties of the inferior fronto-occipital fasciculus (IFOF), the uncinate fasciculus (UF), and the inferior longitudinal fasciculus (ILF). Microstructural measures of the UF failed to predict semantic control performance. However, there was a significant relationship between microstructure of the left IFOF and ILF and individual differences in semantic control. Our findings support the view put forth by Duffau (2013) that the IFOF is a key structural pathway in semantic retrieval.

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

PubMed Central

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

2018-01-01

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. PMID:29375930

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

PubMed

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.

What does a patient with semantic dementia remember in verbal short-term memory? Order and sound but not words.

PubMed

Majerus, Steve; Norris, Dennis; Patterson, Karalyn

2007-03-01

In this study, we explored capacities for three different aspects of short-term verbal memory in patients with semantic dementia. As expected, the two patients had poor recall for lexico-semantic item information, as assessed by immediate serial recall of word lists. In contrast, their short-term memory for phonological information was preserved, as evidenced by normal performance for immediate serial recall of nonword lists, with normal or increased nonword phonotactic-frequency effects, and increased sensitivity to phonological lures in a delayed probe recognition task. Furthermore, the patients appeared to have excellent memory for the serial order of the words in a list. These data provide further support for the proposal that language knowledge is a major determining factor of verbal STM capacity, but they also highlight the necessary distinction of processes involved in item and order recall, as proposed by recent models of STM.

E-Government Goes Semantic Web: How Administrations Can Transform Their Information Processes

NASA Astrophysics Data System (ADS)

Klischewski, Ralf; Ukena, Stefan

E-government applications and services are built mainly on access to, retrieval of, integration of, and delivery of relevant information to citizens, businesses, and administrative users. In order to perform such information processing automatically through the Semantic Web,1 machine-readable2 enhancements of web resources are needed, based on the understanding of the content and context of the information in focus. While these enhancements are far from trivial to produce, administrations in their role of information and service providers so far find little guidance on how to migrate their web resources and enable a new quality of information processing; even research is still seeking best practices. Therefore, the underlying research question of this chapter is: what are the appropriate approaches which guide administrations in transforming their information processes toward the Semantic Web? In search for answers, this chapter analyzes the challenges and possible solutions from the perspective of administrations: (a) the reconstruction of the information processing in the e-government in terms of how semantic technologies must be employed to support information provision and consumption through the Semantic Web; (b) the required contribution to the transformation is compared to the capabilities and expectations of administrations; and (c) available experience with the steps of transformation are reviewed and discussed as to what extent they can be expected to successfully drive the e-government to the Semantic Web. This research builds on studying the case of Schleswig-Holstein, Germany, where semantic technologies have been used within the frame of the Access-eGov3 project in order to semantically enhance electronic service interfaces with the aim of providing a new way of accessing and combining e-government services.

Concepts Within Reach: Action Performance Predicts Action Language Processing in Stroke

PubMed Central

Desai, Rutvik H.; Herter, Troy; Riccardi, Nicholas; Rorden, Chris; Fridriksson, Julius

2015-01-01

The relationship between the brain’s conceptual or semantic and sensory-motor systems remains controversial. Here, we tested manual and conceptual abilities of 41 chronic stroke patients in order to examine their relationship. Manual abilities were assed through a reaching task using an exoskeleton robot. Semantic abilities were assessed with implicit as well as explicit semantic tasks, for both verbs and nouns. The results show that that the degree of selective impairment for action word processing was predicted by the degree of impairment in reaching performance. Moreover, the implicit semantic measures showed a correlation with a global reaching parameter, while the explicit semantic similarity judgment task predicted performance in action initiation. These results indicate that action concepts are dynamically grounded through motoric simulations, and that more details are simulated for more explicit semantic tasks. This is evidence for a close and causal relationship between sensory-motor and conceptual systems of the brain. PMID:25858602

The Effect of Signal-to-Noise Ratio on Linguistic Processing in a Semantic Judgment Task: An Aging Study.

PubMed

Stanley, Nicholas; Davis, Tara; Estis, Julie

2017-03-01

Aging effects on speech understanding in noise have primarily been assessed through speech recognition tasks. Recognition tasks, which focus on bottom-up, perceptual aspects of speech understanding, intentionally limit linguistic and cognitive factors by asking participants to only repeat what they have heard. On the other hand, linguistic processing tasks require bottom-up and top-down (linguistic, cognitive) processing skills and are, therefore, more reflective of speech understanding abilities used in everyday communication. The effect of signal-to-noise ratio (SNR) on linguistic processing ability is relatively unknown for either young (YAs) or older adults (OAs). To determine if reduced SNRs would be more deleterious to the linguistic processing of OAs than YAs, as measured by accuracy and reaction time in a semantic judgment task in competing speech. In the semantic judgment task, participants indicated via button press whether word pairs were a semantic Match or No Match. This task was performed in quiet, as well as, +3, 0, -3, and -6 dB SNR with two-talker speech competition. Seventeen YAs (20-30 yr) with normal hearing sensitivity and 17 OAs (60-68 yr) with normal hearing sensitivity or mild-to-moderate sensorineural hearing loss within age-appropriate norms. Accuracy, reaction time, and false alarm rate were measured and analyzed using a mixed design analysis of variance. A decrease in SNR level significantly reduced accuracy and increased reaction time in both YAs and OAs. However, poor SNRs affected accuracy and reaction time of Match and No Match word pairs differently. Accuracy for Match pairs declined at a steeper rate than No Match pairs in both groups as SNR decreased. In addition, reaction time for No Match pairs increased at a greater rate than Match pairs in more difficult SNRs, particularly at -3 and -6 dB SNR. False-alarm rates indicated that participants had a response bias to No Match pairs as the SNR decreased. Age-related differences were limited to No Match pair accuracies at -6 dB SNR. The ability to correctly identify semantically matched word pairs was more susceptible to disruption by a poor SNR than semantically unrelated words in both YAs and OAs. The effect of SNR on this semantic judgment task implies that speech competition differentially affected the facilitation of semantically related words and the inhibition of semantically incompatible words, although processing speed, as measured by reaction time, remained faster for semantically matched pairs. Overall, the semantic judgment task in competing speech elucidated the effect of a poor listening environment on the higher order processing of words. American Academy of Audiology

Phonological Constraints on Children's Production of English Third Person Singular -S

ERIC Educational Resources Information Center

Song, Jae Yung; Sundara, Megha; Demuth, Katherine

2009-01-01

Purpose: Children variably produce grammatical morphemes at early stages of development, often omitting inflectional morphemes in obligatory contexts. This has typically been attributed to immature syntactic or semantic representations. In this study, the authors investigated the hypothesis that children's variable production of the 3rd person…

Proper Names: Reference and Attribution

ERIC Educational Resources Information Center

Maumus, Michael Fletcher

2012-01-01

In the wake of Saul Kripke's landmark "Naming and Necessity," the claim that proper names are directly referential expressions devoid of descriptive content has come to verge on philosophical commonplace. Nevertheless, the return to a purely referential semantics for proper names has coincided with the resurgence of the very puzzles…

Expert Knowledge, Distinctiveness, and Levels of Processing in Language Learning

ERIC Educational Resources Information Center

Bird, Steve

2012-01-01

The foreign language vocabulary learning research literature often attributes strong mnemonic potency to the cognitive processing of meaning when learning words. Routinely cited as support for this idea are experiments by Craik and Tulving (C&T) demonstrating superior recognition and recall of studied words following semantic tasks ("deep"…

The Composition of Episodic Memory.

ERIC Educational Resources Information Center

Underwood, Benton J.; And Others

This study examined the interrelationships among a number of episodic memory tasks and among various attributes of memory. A sample of 200 college students was tested for ten sessions; 28 different measures of episodic memory were obtained. In addition, five measures of semantic memory were available. Results indicated that episodic and semantic…

Verbal Stimulus Control and the Intraverbal Relation

ERIC Educational Resources Information Center

Sundberg, Mark L.

2016-01-01

The importance of the intraverbal relation is missed in most theories of language. Skinner (1957) attributes this to traditional semantic theories of meaning that focus on the nonverbal referents of words and neglect verbal stimuli as separate sources of control for linguistic behavior. An analysis of verbal stimulus control is presented, along…

Nonbibliographic Applications of Z39.50.

ERIC Educational Resources Information Center

Kunze, John A.

1992-01-01

Describes the use of the Z39.50 information retrieval protocol as the basis for Infocal, a read-only, client/server-based campus information system. Technical considerations in adapting the protocol to nonbibliographic data, including semantic modules, dynamic attribute sets, and dynamic record syntax, are described in detail. (Contains 11…

The Nature of Perceived and Imagined Environments

ERIC Educational Resources Information Center

Lowenthal, David; Riel, Marquita

1972-01-01

The environment has a definite structure, made up of discrete clusters of attributes. The shape and composition of these mental pictures depends on the nature and context of environmental experience. While language (semantic response) at times reinforces experiences, at others the two are opposed. These differences are discussed and analyzed based…

Effects of Grammatical Categories on Children's Visual Language Processing: Evidence from Event-Related Brain Potentials

ERIC Educational Resources Information Center

Weber-Fox, Christine; Hart, Laura J.; Spruill, John E., III

2006-01-01

This study examined how school-aged children process different grammatical categories. Event-related brain potentials elicited by words in visually presented sentences were analyzed according to seven grammatical categories with naturally varying characteristics of linguistic functions, semantic features, and quantitative attributes of length and…

Embodied Simulations Are Modulated by Sentential Perspective

ERIC Educational Resources Information Center

van Dam, Wessel O.; Desai, Rutvik H.

2017-01-01

There is considerable evidence that language comprehenders derive lexical-semantic meaning by mentally simulating perceptual and motor attributes of described events. However, the nature of these simulations--including the level of detail that is incorporated and contexts under which simulations occur--is not well understood. Here, we examine the…

Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

NASA Astrophysics Data System (ADS)

Wang, M.; Hu, N. Q.; Qin, G. J.

2011-07-01

In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

Science and students with mental retardation: An analysis of curriculum features and learner characteristics

NASA Astrophysics Data System (ADS)

Scruggs, Thomas E.; Mastropieri, Margo A.

Although much research has been conducted on the learning characteristics of individuals with mental retardation, science learning of such individuals has received far less attention. In this investigation, students with mental retardation were observed over a 2-year period, in order to determine how the characteristics of mental retardation manifested themselves in the context of inquiry-oriented, hands-on science curriculum. Analysis of all relevant data sources, including observations and field notes, videotape and audiotape recordings, student products, and interviews, suggested that several characteristics commonly attributed to students with mild mental retardation were observed to interact with the science curriculum. These characteristics included attention, semantic memory, logical reasoning, and outerdirectedness. However, teachers were skilled at adapting instruction to meet the special needs of these learners. Implications for teaching science to students with mental retardation are provided.

Remembering the Important Things: Semantic Importance in Stream Reasoning

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

Yan, Rui; Greaves, Mark T.; Smith, William P.

Reasoning and querying over data streams rely on the abil- ity to deliver a sequence of stream snapshots to the processing algo- rithms. These snapshots are typically provided using windows as views into streams and associated window management strategies. Generally, the goal of any window management strategy is to preserve the most im- portant data in the current window and preferentially evict the rest, so that the retained data can continue to be exploited. A simple timestamp- based strategy is rst-in-rst-out (FIFO), in which items are replaced in strict order of arrival. All timestamp-based strategies implicitly assume that a temporalmore » ordering reliably re ects importance to the processing task at hand, and thus that window management using timestamps will maximize the ability of the processing algorithms to deliver accurate interpretations of the stream. In this work, we explore a general no- tion of semantic importance that can be used for window management for streams of RDF data using semantically-aware processing algorithms like deduction or semantic query. Semantic importance exploits the infor- mation carried in RDF and surrounding ontologies for ranking window data in terms of its likely contribution to the processing algorithms. We explore the general semantic categories of query contribution, prove- nance, and trustworthiness, as well as the contribution of domain-specic ontologies. We describe how these categories behave using several con- crete examples. Finally, we consider how a stream window management strategy based on semantic importance could improve overall processing performance, especially as available window sizes decrease.« less

Is there a positive bias in false recognition? Evidence from confabulating amnesia patients.

PubMed

Alkathiri, Nura H; Morris, Robin G; Kopelman, Michael D

2015-10-01

Although there is some evidence for a positive emotional bias in the content of confabulations in brain damaged patients, findings have been inconsistent. The present study used the semantic-associates procedure to induce false recall and false recognition in order to examine whether a positive bias would be found in confabulating amnesic patients, relative to non-confabulating amnesic patients and healthy controls. Lists of positive, negative and neutral words were presented in order to induce false recall or false recognition of non-presented (but semantically associated) words. The latter were termed 'critical intrusions'. Thirteen confabulating amnesic patients, 13 non-confabulating amnesic patients and 13 healthy controls were investigated. Confabulating patients falsely recognised a higher proportion of positive (but unrelated) words, compared with non-confabulating patients and healthy controls. No differences were found for recall memory. Signal detection analysis, however, indicated that the positive bias for false recognition memory might reflect weaker memory in the confabulating amnesic group. This suggested that amnesia patients with weaker memory are more likely to confabulate and the content of these confabulations are more likely to be positive. Copyright © 2015 Elsevier Ltd. All rights reserved.

On the universal structure of human lexical semantics

PubMed Central

Sutton, Logan; Smith, Eric; Moore, Cristopher; Wilkins, Jon F.; Maddieson, Ian; Croft, William

2016-01-01

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. PMID:26831113

Phonological and semantic processing during comprehension in Wernicke's aphasia: An N400 and Phonological Mapping Negativity Study.

PubMed

Robson, Holly; Pilkington, Emma; Evans, Louise; DeLuca, Vincent; Keidel, James L

2017-06-01

Comprehension impairments in Wernicke's aphasia are thought to result from a combination of impaired phonological and semantic processes. However, the relationship between these cognitive processes and language comprehension has only been inferred through offline neuropsychological tasks. This study used ERPs to investigate phonological and semantic processing during online single word comprehension. EEG was recorded in a group of Wernicke's aphasia n=8 and control participants n=10 while performing a word-picture verification task. The N400 and Phonological Mapping Negativity/Phonological Mismatch Negativity (PMN) event-related potential components were investigated as an index of semantic and phonological processing, respectively. Individuals with Wernicke's aphasia displayed reduced and inconsistent N400 and PMN effects in comparison to control participants. Reduced N400 effects in the WA group were simulated in the control group by artificially degrading speech perception. Correlation analyses in the Wernicke's aphasia group found that PMN but not N400 amplitude was associated with behavioural word-picture verification performance. The results confirm impairments at both phonological and semantic stages of comprehension in Wernicke's aphasia. However, reduced N400 responses in Wernicke's aphasia are at least partially attributable to earlier phonological processing impairments. The results provide further support for the traditional model of Wernicke's aphasia which claims a causative link between phonological processing and language comprehension impairments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Qualitative features of semantic fluency performance in mesial and lateral frontal patients.

PubMed

Reverberi, Carlo; Laiacona, Marcella; Capitani, Erminio

2006-01-01

Semantic verbal fluency is widely used in clinical and experimental studies. This task is highly sensitive to the presence of brain pathology and is frequently impaired after frontal lesions. Besides the total number of words generated, a qualitative analysis of their sequence can add valuable information about the impaired cognitive components. Thirty-four frontal patients and a group of matched controls were examined. Besides the number of words and subcategories retrieved by each group, we analysed two distinct aspects of the word sequence: the search strategy through a semantically organised store and the ability to switch from one subcategory to another. We checked whether the pattern of impairment changed according to the lesion site within the frontal lobe. Overall, patients produced fewer words than controls. However, only lateral frontal patients presented a reduced semantic relatedness between contiguously produced words and a specifically increased proportion of switches to different subcategories. The performance of lateral frontal patients was in line with the hypothesis of a search strategy impairment and cannot be attributed to a switching deficit. The performance of mesial frontal patients could be ascribed to a general deficit of activation.

Deriving semantic structure from category fluency: clustering techniques and their pitfalls

PubMed Central

Voorspoels, Wouter; Storms, Gert; Longenecker, Julia; Verheyen, Steven; Weinberger, Daniel R.; Elvevåg, Brita

2013-01-01

Assessing verbal output in category fluency tasks provides a sensitive indicator of cortical dysfunction. The most common metrics are the overall number of words produced and the number of errors. Two main observations have been made about the structure of the output, first that there is a temporal component to it with words being generated in spurts, and second that the clustering pattern may reflect a search for meanings such that the ‘clustering’ is attributable to the activation of a specific semantic field in memory. A number of sophisticated approaches to examining the structure of this clustering have been developed, and a core theme is that the similarity relations between category members will reveal the mental semantic structure of the category underlying an individual’s responses, which can then be visualized by a number of algorithms, such as MDS, hierarchical clustering, ADDTREE, ADCLUS or SVD. Such approaches have been applied to a variety of neurological and psychiatric populations, and the general conclusion has been that the clinical condition systematically distorts the semantic structure in the patients, as compared to the healthy controls. In the present paper we explore this approach to understanding semantic structure using category fluency data. On the basis of a large pool of patients with schizophrenia (n=204) and healthy control participants (n=204), we find that the methods are problematic and unreliable to the extent that it is not possible to conclude that any putative difference reflects a systematic difference between the semantic representations in patients and controls. Moreover, taking into account the unreliability of the methods, we find that the most probable conclusion to be made is that no difference in underlying semantic representation exists. The consequences of these findings to understanding semantic structure, and the use of category fluency data, in cortical dysfunction are discussed. PMID:24275165

Adult and Child Semantic Neighbors of the Kroll and Potter (1984) Nonobjects

PubMed Central

Storkel, Holly L.; Adlof, Suzanne M.

2008-01-01

Purpose The purpose was to determine the number of semantic neighbors, namely semantic set size, for 88 nonobjects (Kroll & Potter, 1984) and determine how semantic set size related to other measures and age. Method Data were collected from 82 adults and 92 preschool children in a discrete association task. The nonobjects were presented via computer, and participants reported the first word that came to mind that was meaningfully related to the nonobject. Words reported by two or more participants were considered semantic neighbors. The strength of each neighbor was computed as the proportion of participants who reported the neighbor. Results Results showed that semantic set size was not significantly correlated with objectlikeness ratings or object decision reaction times from Kroll and Potter (1984). However, semantic set size was significantly negatively correlated with the strength of the strongest neighbor(s). In terms of age effects, adult and child semantic set sizes were significantly positively correlated and the majority of numeric differences were on the order of 0–3 neighbors. Comparison of actual neighbors showed greater discrepancies; however, this varied by neighbor strength. Conclusions Semantic set size can be determined for nonobjects. Specific guidelines are suggested for using these nonobjects in future research. PMID:19252127

Semantic Document Model to Enhance Data and Knowledge Interoperability

NASA Astrophysics Data System (ADS)

Nešić, Saša

To enable document data and knowledge to be efficiently shared and reused across application, enterprise, and community boundaries, desktop documents should be completely open and queryable resources, whose data and knowledge are represented in a form understandable to both humans and machines. At the same time, these are the requirements that desktop documents need to satisfy in order to contribute to the visions of the Semantic Web. With the aim of achieving this goal, we have developed the Semantic Document Model (SDM), which turns desktop documents into Semantic Documents as uniquely identified and semantically annotated composite resources, that can be instantiated into human-readable (HR) and machine-processable (MP) forms. In this paper, we present the SDM along with an RDF and ontology-based solution for the MP document instance. Moreover, on top of the proposed model, we have built the Semantic Document Management System (SDMS), which provides a set of services that exploit the model. As an application example that takes advantage of SDMS services, we have extended MS Office with a set of tools that enables users to transform MS Office documents (e.g., MS Word and MS PowerPoint) into Semantic Documents, and to search local and distant semantic document repositories for document content units (CUs) over Semantic Web protocols.

The effects of bilingual language proficiency on recall accuracy and semantic clustering in free recall output: evidence for shared semantic associations across languages.

PubMed

Francis, Wendy S; Taylor, Randolph S; Gutiérrez, Marisela; Liaño, Mary K; Manzanera, Diana G; Penalver, Renee M

2018-05-19

Two experiments investigated how well bilinguals utilise long-standing semantic associations to encode and retrieve semantic clusters in verbal episodic memory. In Experiment 1, Spanish-English bilinguals (N = 128) studied and recalled word and picture sets. Word recall was equivalent in L1 and L2, picture recall was better in L1 than in L2, and the picture superiority effect was stronger in L1 than in L2. Semantic clustering in word and picture recall was equivalent in L1 and L2. In Experiment 2, Spanish-English bilinguals (N = 128) and English-speaking monolinguals (N = 128) studied and recalled word sequences that contained semantically related pairs. Data were analyzed using a multinomial processing tree approach, the pair-clustering model. Cluster formation was more likely for semantically organised than for randomly ordered word sequences. Probabilities of cluster formation, cluster retrieval, and retrieval of unclustered items did not differ across languages or language groups. Language proficiency has little if any impact on the utilisation of long-standing semantic associations, which are language-general.

Retrieval and Monitoring Processes during Visual Working Memory: An ERP Study of the Benefit of Visual Semantics

PubMed Central

Orme, Elizabeth; Brown, Louise A.; Riby, Leigh M.

2017-01-01

In this study, we examined electrophysiological indices of episodic remembering whilst participants recalled novel shapes, with and without semantic content, within a visual working memory paradigm. The components of interest were the parietal episodic (PE; 400–800 ms) and late posterior negativity (LPN; 500–900 ms), as these have previously been identified as reliable markers of recollection and post-retrieval monitoring, respectively. Fifteen young adults completed a visual matrix patterns task, assessing memory for low and high semantic visual representations. Matrices with either low semantic or high semantic content (containing familiar visual forms) were briefly presented to participants for study (1500 ms), followed by a retention interval (6000 ms) and finally a same/different recognition phase. The event-related potentials of interest were tracked from the onset of the recognition test stimuli. Analyses revealed equivalent amplitude for the earlier PE effect for the processing of both low and high semantic stimulus types. However, the LPN was more negative-going for the processing of the low semantic stimuli. These data are discussed in terms of relatively ‘pure’ and complete retrieval of high semantic items, where support can readily be recruited from semantic memory. However, for the low semantic items additional executive resources, as indexed by the LPN, are recruited when memory monitoring and uncertainty exist in order to recall previously studied items more effectively. PMID:28725203

Retrieval and Monitoring Processes during Visual Working Memory: An ERP Study of the Benefit of Visual Semantics.

PubMed

Orme, Elizabeth; Brown, Louise A; Riby, Leigh M

2017-01-01

In this study, we examined electrophysiological indices of episodic remembering whilst participants recalled novel shapes, with and without semantic content, within a visual working memory paradigm. The components of interest were the parietal episodic (PE; 400-800 ms) and late posterior negativity (LPN; 500-900 ms), as these have previously been identified as reliable markers of recollection and post-retrieval monitoring, respectively. Fifteen young adults completed a visual matrix patterns task, assessing memory for low and high semantic visual representations. Matrices with either low semantic or high semantic content (containing familiar visual forms) were briefly presented to participants for study (1500 ms), followed by a retention interval (6000 ms) and finally a same/different recognition phase. The event-related potentials of interest were tracked from the onset of the recognition test stimuli. Analyses revealed equivalent amplitude for the earlier PE effect for the processing of both low and high semantic stimulus types. However, the LPN was more negative-going for the processing of the low semantic stimuli. These data are discussed in terms of relatively 'pure' and complete retrieval of high semantic items, where support can readily be recruited from semantic memory. However, for the low semantic items additional executive resources, as indexed by the LPN, are recruited when memory monitoring and uncertainty exist in order to recall previously studied items more effectively.

From Science to e-Science to Semantic e-Science: A Heliosphysics Case Study

NASA Technical Reports Server (NTRS)

Narock, Thomas; Fox, Peter

2011-01-01

The past few years have witnessed unparalleled efforts to make scientific data web accessible. The Semantic Web has proven invaluable in this effort; however, much of the literature is devoted to system design, ontology creation, and trials and tribulations of current technologies. In order to fully develop the nascent field of Semantic e-Science we must also evaluate systems in real-world settings. We describe a case study within the field of Heliophysics and provide a comparison of the evolutionary stages of data discovery, from manual to semantically enable. We describe the socio-technical implications of moving toward automated and intelligent data discovery. In doing so, we highlight how this process enhances what is currently being done manually in various scientific disciplines. Our case study illustrates that Semantic e-Science is more than just semantic search. The integration of search with web services, relational databases, and other cyberinfrastructure is a central tenet of our case study and one that we believe has applicability as a generalized research area within Semantic e-Science. This case study illustrates a specific example of the benefits, and limitations, of semantically replicating data discovery. We show examples of significant reductions in time and effort enable by Semantic e-Science; yet, we argue that a "complete" solution requires integrating semantic search with other research areas such as data provenance and web services.

The semantic origin of unconscious priming: Behavioral and event-related potential evidence during category congruency priming from strongly and weakly related masked words.

PubMed

Ortells, Juan J; Kiefer, Markus; Castillo, Alejandro; Megías, Montserrat; Morillas, Alejandro

2016-01-01

The mechanisms underlying masked congruency priming, semantic mechanisms such as semantic activation or non-semantic mechanisms, for example response activation, remain a matter of debate. In order to decide between these alternatives, reaction times (RTs) and event-related potentials (ERPs) were recorded in the present study, while participants performed a semantic categorization task on visible word targets that were preceded either 167 ms (Experiment 1) or 34 ms before (Experiment 2) by briefly presented (33 ms) novel (unpracticed) masked prime words. The primes and targets belonged to different categories (unrelated), or they were either strongly or weakly semantically related category co-exemplars. Behavioral (RT) and electrophysiological masked congruency priming effects were significantly greater for strongly related pairs than for weakly related pairs, indicating a semantic origin of effects. Priming in the latter condition was not statistically reliable. Furthermore, priming effects modulated the N400 event-related potential (ERP) component, an electrophysiological index of semantic processing, but not ERPs in the time range of the N200 component, associated with response conflict and visuo-motor response priming. The present results demonstrate that masked congruency priming from novel prime words also depends on semantic processing of the primes and is not exclusively driven by non-semantic mechanisms such as response activation. Copyright © 2015 Elsevier B.V. All rights reserved.

Revisiting the picture-superiority effect in symbolic comparisons: do pictures provide privileged access?

PubMed

Amrhein, Paul C; McDaniel, Mark A; Waddill, Paula

2002-09-01

In 4 experiments, symbolic comparisons were investigated to test semantic-memory retrieval accounts espousing processing advantages for picture over word stimuli. In Experiment 1, participants judged pairs of animal names or pictures by responding to questions probing concrete or abstract attributes (texture or size, ferocity or intelligence). Per pair, attributes were salient or nonsalient concerning their prerated relevance to animals being compared. Distance (near or far) between attribute magnitudes was also varied. Pictures did not significantly speed responding relative to words across all other variables. Advantages were found forfar attribute magnitudes (i.e., the distance effect) and salient attributes. The distance effect was much less for salient than nonsalient concrete-attribute comparisons. These results were consistently found in additional experiments with increased statistical power to detect modality effects. Our findings argue against dual-coding and some common-code accounts of conceptual attribute processing, urging reexamination of the assumption that pictures confer privileged access to long-term knowledge.

Context in Generalized Conversational Implicatures: The Case of Some

PubMed Central

Dupuy, Ludivine E.; Van der Henst, Jean-Baptiste; Cheylus, Anne; Reboul, Anne C.

2016-01-01

There is now general agreement about the optionality of scalar implicatures: the pragmatic interpretation will be accessed depending on the context relative to which the utterance is interpreted. The question, then, is what makes a context upper- (vs. lower-) bounding. Neo-Gricean accounts should predict that contexts including factual information will enhance the rate of pragmatic interpretations. Post-Gricean accounts should predict that contexts including psychological attributions will enhance the rate of pragmatic interpretations. We tested two factors using the quantifier scale : (1) the existence of factual information that facilitates the computation of pragmatic interpretations in the context (here, the cardinality of the domain of quantification) and (2) the fact that the context makes the difference between the semantic and the pragmatic interpretations of the target sentence relevant, involving psychological attributions to the speaker (here a question using all). We did three experiments, all of which suggest that while cardinality information may be necessary to the computation of the pragmatic interpretation, it plays a minor role in triggering it; highlighting the contrast between the pragmatic and the semantic interpretations, while it is not necessary to the computation of the pragmatic interpretation, strongly mandates a pragmatic interpretation. These results favor Sperber and Wilson's (1995) post-Gricean account over Chierchia's (2013) neo-Gricean account. Overall, this suggests that highlighting the relevance of the pragmatic vs. semantic interpretations of the target sentence makes a context upper-bounding. Additionally, the results give a small advantage to the post-Gricean account. PMID:27047413

The semantic specificity of gestures when verbal communication is not possible: the case of emergency evacuation.

PubMed

Prati, Gabriele; Pietrantoni, Luca

2013-01-01

The aim of the present study was to examine the comprehension of gesture in a situation in which the communicator cannot (or can only with difficulty) use verbal communication. Based on theoretical considerations, we expected to obtain higher semantic comprehension for emblems (gestures with a direct verbal definition or translation that is well known by all members of a group, or culture) compared to illustrators (gestures regarded as spontaneous and idiosyncratic and that do not have a conventional definition). Based on the extant literature, we predicted higher semantic specificity associated with arbitrarily coded and iconically coded emblems compared to intrinsically coded illustrators. Using a scenario of emergency evacuation, we tested the difference in semantic specificity between different categories of gestures. 138 participants saw 10 videos each illustrating a gesture performed by a firefighter. They were requested to imagine themselves in a dangerous situation and to report the meaning associated with each gesture. The results showed that intrinsically coded illustrators were more successfully understood than arbitrarily coded emblems, probably because the meaning of intrinsically coded illustrators is immediately comprehensible without recourse to symbolic interpretation. Furthermore, there was no significant difference between the comprehension of iconically coded emblems and that of both arbitrarily coded emblems and intrinsically coded illustrators. It seems that the difference between the latter two types of gestures was supported by their difference in semantic specificity, although in a direction opposite to that predicted. These results are in line with those of Hadar and Pinchas-Zamir (2004), which showed that iconic gestures have higher semantic specificity than conventional gestures.

Morphological Decomposition and Semantic Integration in Word Processing

ERIC Educational Resources Information Center

Meunier, Fanny; Longtin, Catherine-Marie

2007-01-01

In the present study, we looked at cross-modal priming effects produced by auditory presentation of morphologically complex pseudowords in order to investigate semantic integration during the processing of French morphologically complex items. In Experiment 1, we used as primes pseudowords consisting of a non-interpretable combination of roots and…

The Role of Semantics in Sentence-Processing.

ERIC Educational Resources Information Center

Dell, Gary S.

In order to explore the effect of semantic organization on the comprehension of sentences, this research, based on the hypothesis that fully grammatical sentences would be processed more easily than anomalous sentences, depended on data provided by 20 paid college students serving in individual sessions. Each student listened to 30 tape-recorded…

A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains.

PubMed

Sinaci, A Anil; Laleci Erturkmen, Gokce B

2013-10-01

In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems. Copyright © 2013 Elsevier Inc. All rights reserved.

Towards BioDBcore: a community-defined information specification for biological databases

PubMed Central

Gaudet, Pascale; Bairoch, Amos; Field, Dawn; Sansone, Susanna-Assunta; Taylor, Chris; Attwood, Teresa K.; Bateman, Alex; Blake, Judith A.; Bult, Carol J.; Cherry, J. Michael; Chisholm, Rex L.; Cochrane, Guy; Cook, Charles E.; Eppig, Janan T.; Galperin, Michael Y.; Gentleman, Robert; Goble, Carole A.; Gojobori, Takashi; Hancock, John M.; Howe, Douglas G.; Imanishi, Tadashi; Kelso, Janet; Landsman, David; Lewis, Suzanna E.; Mizrachi, Ilene Karsch; Orchard, Sandra; Ouellette, B. F. Francis; Ranganathan, Shoba; Richardson, Lorna; Rocca-Serra, Philippe; Schofield, Paul N.; Smedley, Damian; Southan, Christopher; Tan, Tin Wee; Tatusova, Tatiana; Whetzel, Patricia L.; White, Owen; Yamasaki, Chisato

2011-01-01

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases. PMID:21097465

Towards BioDBcore: a community-defined information specification for biological databases

PubMed Central

Gaudet, Pascale; Bairoch, Amos; Field, Dawn; Sansone, Susanna-Assunta; Taylor, Chris; Attwood, Teresa K.; Bateman, Alex; Blake, Judith A.; Bult, Carol J.; Cherry, J. Michael; Chisholm, Rex L.; Cochrane, Guy; Cook, Charles E.; Eppig, Janan T.; Galperin, Michael Y.; Gentleman, Robert; Goble, Carole A.; Gojobori, Takashi; Hancock, John M.; Howe, Douglas G.; Imanishi, Tadashi; Kelso, Janet; Landsman, David; Lewis, Suzanna E.; Karsch Mizrachi, Ilene; Orchard, Sandra; Ouellette, B.F. Francis; Ranganathan, Shoba; Richardson, Lorna; Rocca-Serra, Philippe; Schofield, Paul N.; Smedley, Damian; Southan, Christopher; Tan, Tin W.; Tatusova, Tatiana; Whetzel, Patricia L.; White, Owen; Yamasaki, Chisato

2011-01-01

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases. PMID:21205783

More than skin deep: body representation beyond primary somatosensory cortex.

PubMed

Longo, Matthew R; Azañón, Elena; Haggard, Patrick

2010-02-01

The neural circuits underlying initial sensory processing of somatic information are relatively well understood. In contrast, the processes that go beyond primary somatosensation to create more abstract representations related to the body are less clear. In this review, we focus on two classes of higher-order processing beyond somatosensation. Somatoperception refers to the process of perceiving the body itself, and particularly of ensuring somatic perceptual constancy. We review three key elements of somatoperception: (a) remapping information from the body surface into an egocentric reference frame, (b) exteroceptive perception of objects in the external world through their contact with the body, and (c) interoceptive percepts about the nature and state of the body itself. Somatorepresentation, in contrast, refers to the essentially cognitive process of constructing semantic knowledge and attitudes about the body, including: (d) lexical-semantic knowledge about bodies generally and one's own body specifically, (e) configural knowledge about the structure of bodies, (f) emotions and attitudes directed towards one's own body, and (g) the link between physical body and psychological self. We review a wide range of neuropsychological, neuroimaging and neurophysiological data to explore the dissociation between these different aspects of higher somatosensory function. 2009 Elsevier Ltd. All rights reserved.

Social distance and stigma toward individuals with schizophrenia: findings in an urban, African-American community sample.

PubMed

Broussard, Beth; Goulding, Sandra M; Talley, Colin L; Compton, Michael T

2012-11-01

Because schizophrenia is arguably among the most stigmatized health conditions, research assessing correlates of stigma is essential. This study examined factors associated with stigma in predominantly Protestant, low-income, urban African Americans in the Southeastern United States. A survey was distributed to 282 patrons of an inner-city food court/farmers' market. Associations were assessed between two measures of stigma--an adapted version of the Social Distance Scale (SDS) and a Semantic Differential Measure (SDM) of attributes such as dangerousness, dirtiness, and worthlessness--and several key variables addressing sociodemographic characteristics and exposure to/familiarity with mental illnesses. Independent predictors of scores on the two measures were identified using linear regression modeling. Higher stigma (as measured by the SDM) was predicted by a family history of psychiatric treatment, whereas lower stigma (as indicated by the SDS) was predicted by personal psychiatric treatment history and higher annual income. The results suggest special considerations when working with disenfranchised populations, especially family members of individuals with mental illnesses, in treatment settings.

Lack of semantic priming effects in famous person recognition in Mild Cognitive Impairment.

PubMed

Brambati, Simona M; Peters, Frédéric; Belleville, Sylvie; Joubert, Sven

2012-04-01

Growing evidence indicates that individuals with Mild Cognitive Impairment (MCI) manifest semantic deficits that are often more severe for items that are characterized by a unique semantic and lexical association, such as famous people and famous buildings, than common concepts, such as objects. However, it is still controversial whether the semantic deficits observed in MCI are determined by a degradation of semantic information or by a deficit in intentional access to semantic knowledge. Here we used a semantic priming task in order to assess the integrity of the semantic system without requiring explicit access to this system. This paradigm may provide new insights in clarifying the nature of the semantic deficits in MCI. We assessed the semantic and repetition priming effect in 13 individuals with MCI and 13 age-matched controls who engaged in a familiarity judgment task of famous names. In the semantic priming condition, the prime was the name of a member of the same occupation category as the target (Tom Cruise-Brad Pitt), while in the repetition priming condition the prime was the same name as the target (Charlie Chaplin-Charlie Chaplin). The results showed a defective priming effect in MCI in the semantic but not in the repetition priming condition. Specifically, when compared to controls, MCI patients did not show a facilitation effect in responding to the same occupation prime-target pairs, but they showed an equivalent facilitation effect when the target was the same name as the prime. The present results provide support to the hypothesis that the semantic impairments observed in MCI cannot be uniquely ascribed to a deficit in intentional access to semantic information. Instead, these findings point to the semantic nature of these deficits and, in particular, to a degraded representation of semantic information concerning famous people. Copyright © 2011 Elsevier Srl. All rights reserved.

Analysis of student attitudes towards e-learning using Fishbein Multiattribute approach

NASA Astrophysics Data System (ADS)

Jasuli

2018-01-01

This research aimed to know students’ attitudes toward e-learning and to determine what attributes were considered to be dominant by students toward the use of e-learning. The research population was all postgraduate students in the 2016 academic year at Universitas Negeri Surabaya. The sampling technique is using nonprobability sampling and purposive sampling with the sample totaled 100 respondents. The research instrument is using questionnaire with semantic differential scale. The models used to analyze is multi-attribute Fishbein model. The findings indicated that student attitudes toward e-learning are positive and easy accessibility which is considered as the most important attribute by students toward the use of e-learning.

When fruits lose to animals: Disorganized search of semantic memory in Parkinson's disease.

PubMed

Tagini, Sofia; Seyed-Allaei, Shima; Scarpina, Federica; Toraldo, Alessio; Mauro, Alessandro; Cherubini, Paolo; Reverberi, Carlo

2018-04-16

The semantic fluency task is widely used in both clinical and research settings to assess both the integrity of the semantic store and the effectiveness of the search through it. Our aim was to investigate whether nondemented Parkinson's disease (PD) patients show an impairment in the strategic exploration of the semantic store and whether the tested semantic category has an impact on multiple measures of performance. We compared 74 nondemented PD patients with 254 healthy subjects in a semantic fluency test using relatively small (fruits) and large (animals) semantic categories. Number of words produced, number of explored semantic subcategories, and degree of order in the produced sequences were computed as dependent variables. PD patients produced fewer words than healthy subjects did, regardless of the category. Number of subcategories was also lower in PD patients than in healthy subjects, without a significant difference between categories. Critically, PD patients' sequences were less semantically organized than were those of controls, but this effect appeared in only the smaller category (fruits), thus pointing to a lack of strategy in exploring the semantic store. Our results show that the semantic fluency deficit in PD patients has a strategic component, even though that may not be the only cause of the impaired performance. Furthermore, our evidence suggests that the semantic category used in the test influences performance, hence providing an explanation for the failure by previous studies, which often used large categories such as animals, to detect strategy deficits in PD. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Acoustic and semantic interference effects in words and pictures.

PubMed

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.

Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

NASA Astrophysics Data System (ADS)

Fox, P.

2012-04-01

The vast majority of explorations of the Earth's systems are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level. Recent successes in the application of complex network theory and algorithms to climate data, raise expectations that more general graph-based approaches offer the opportunity for new discoveries. In the past ~ 5 years in the natural sciences there has substantial progress in providing both specialists and non-specialists the ability to describe in machine readable form, geophysical quantities and relations among them in meaningful and natural ways, effectively breaking the prior syntax barrier. The corresponding open-world semantics and reasoning provide higher-level interconnections. That is, semantics provided around the data structures, using semantically-equipped tools, and semantically aware interfaces between science application components allowing for discovery at the knowledge level. More recently, formal semantic approaches to continuous and aggregate physical processes are beginning to show promise and are soon likely to be ready to apply to geoscientific systems. To illustrate these opportunities, this presentation presents two application examples featuring domain vocabulary (ontology) and property relations (named and typed edges in the graphs). First, a climate knowledge discovery pilot encoding and exploration of CMIP5 catalog information with the eventual goal to encode and explore CMIP5 data. Second, a multi-stakeholder knowledge network for integrated assessments in marine ecosystems, where the data is highly inter-disciplinary.

Direct Exploration of the Role of the Ventral Anterior Temporal Lobe in Semantic Memory: Cortical Stimulation and Local Field Potential Evidence From Subdural Grid Electrodes

PubMed Central

Shimotake, Akihiro; Matsumoto, Riki; Ueno, Taiji; Kunieda, Takeharu; Saito, Satoru; Hoffman, Paul; Kikuchi, Takayuki; Fukuyama, Hidenao; Miyamoto, Susumu; Takahashi, Ryosuke; Ikeda, Akio; Lambon Ralph, Matthew A.

2015-01-01

Semantic memory is a crucial higher cortical function that codes the meaning of objects and words, and when impaired after neurological damage, patients are left with significant disability. Investigations of semantic dementia have implicated the anterior temporal lobe (ATL) region, in general, as crucial for multimodal semantic memory. The potentially crucial role of the ventral ATL subregion has been emphasized by recent functional neuroimaging studies, but the necessity of this precise area has not been selectively tested. The implantation of subdural electrode grids over this subregion, for the presurgical assessment of patients with partial epilepsy or brain tumor, offers the dual yet rare opportunities to record cortical local field potentials while participants complete semantic tasks and to stimulate the functionally identified regions in the same participants to evaluate the necessity of these areas in semantic processing. Across 6 patients, and utilizing a variety of semantic assessments, we evaluated and confirmed that the anterior fusiform/inferior temporal gyrus is crucial in multimodal, receptive, and expressive, semantic processing. PMID:25491206

There Is Something about Grammatical Category in Chinese Visual Word Recognition

ERIC Educational Resources Information Center

Kwong, Oi Yee

2016-01-01

The differential processing of nouns and verbs has been attributed to a combination of morphological, syntactic and semantic factors which are often intertwined with other general lexical properties. This study tested the noun-verb difference with Chinese disyllabic words controlled on various lexical parameters. As Chinese words are free from…

Linguistic multi-criteria decision-making with representing semantics by programming

NASA Astrophysics Data System (ADS)

Yang, Wu-E.; Ma, Chao-Qun; Han, Zhi-Qiu

2017-01-01

A linguistic multi-criteria decision-making method is introduced. In this method, a maximising discrimination programming assigns the semanteme values to linguistic variables to represent their semantics. Incomplete preferences from using linguistic information are expressed by the constraints of the model. Such assignment can amplify the difference between alternatives. Thus, the discrimination of the decision model is increased, which facilitates the decision-maker to rank or order the alternatives for making a decision. We also discuss the parameter setting and its influence, and use an application example to illustrate the proposed method. Further, the results with three types of semantic structure highlight the ability of the method in handling different semantic structures.

How should neuroscience study emotions? by distinguishing emotion states, concepts, and experiences.

PubMed

Adolphs, Ralph

2017-01-01

In this debate with Lisa Feldman Barrett, I defend a view of emotions as biological functional states. Affective neuroscience studies emotions in this sense, but it also studies the conscious experience of emotion ('feelings'), our ability to attribute emotions to others and to animals ('attribution', 'anthropomorphizing'), our ability to think and talk about emotion ('concepts of emotion', 'semantic knowledge of emotion') and the behaviors caused by an emotion ('expression of emotions', 'emotional reactions'). I think that the most pressing challenge facing affective neuroscience is the need to carefully distinguish between these distinct aspects of 'emotion'. I view emotion states as evolved functional states that regulate complex behavior, in both people and animals, in response to challenges that instantiate recurrent environmental themes. These functional states, in turn, can also cause conscious experiences (feelings), and their effects and our memories for those effects also contribute to our semantic knowledge of emotions (concepts). Cross-species studies, dissociations in neurological and psychiatric patients, and more ecologically valid neuroimaging designs should be used to partly separate these different phenomena. © The Author (2016). Published by Oxford University Press.

Test of a potential link between analytic and nonanalytic category learning and automatic, effortful processing.

PubMed

Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J

2001-08-01

The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.

Application of a methodology for categorizing and differentiating urban soundscapes using acoustical descriptors and semantic-differential attributes.

PubMed

Torija, Antonio J; Ruiz, Diego P; Ramos-Ridao, A F

2013-07-01

A subjective and physical categorization of an ambient sound is the first step to evaluate the soundscape and provides a basis for designing or adapting this ambient sound to match people's expectations. For this reason, the main goal of this work is to develop a categorization and differentiation analysis of soundscapes on the basis of acoustical and perceptual variables. A hierarchical cluster analysis, using 15 semantic-differential attributes and acoustical descriptors to include an equivalent sound-pressure level, maximum-minimum sound-pressure level, impulsiveness of the sound-pressure level, sound-pressure level time course, and spectral composition, was conducted to classify soundscapes into different typologies. This analysis identified 15 different soundscape typologies. Furthermore, based on a discriminant analysis the acoustical descriptors, the crest factor (impulsiveness of the sound-pressure level), and the sound level at 125 Hz were found to be the acoustical variables with the highest impact in the differentiation of the recognized types of soundscapes. Finally, to determine how the different soundscape typologies differed from each other, both subjectively and acoustically, a study was performed.

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

PubMed

Günther, Fritz; Dudschig, Carolin; Kaup, Barbara

2016-01-01

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

[False recognition of faces associated with fronto-temporal dementia with prosopagnosia].

PubMed

Verstichel, P

2005-09-01

The association of prosopagnosia and false recognition of faces is unusual and contributes to our understanding of the generation of facial familiarity. A 67-year-old man with a left prefrontal traumatic lesion, developed a temporal variety of fronto-temporal dementia (semantic dementia) with amyotrophic lateral sclerosis. Cerebral imagery demonstrated a bilateral, temporal anterior atrophy predominating in the right hemisphere. The main cognitive signs consisted in severe difficulties to recognize faces of familiar people (prosopagnosia), associated with systematic false recognition of unfamiliar people. Neuropsychological testing indicated that the prosopagnosia probably resulted from the association of an associative/mnemonic mechanism (inability to activate the Face Recognition Units (FRU) from the visual input) and a semantic mechanism (degradation of semantic/biographical information or deconnexion between FRU and this information). At the early stage of the disease, the patient could activate residual semantic information about individuals from their names, but after a 4-year course, he failed to do so. This worsening could be attributed to the extension of the degenerative lesions to the left temporal lobe. Familiar and unfamiliar faces triggered a marked feeling of knowing. False recognition concerned all the unfamiliar faces, and the patient claimed spontaneously that they corresponded to actors, but he could not provide any additional information about their specific identities. The coexistence of prosopagnosia and false recognition suggests the existence of different interconnected systems processing face recognition, one intended to identification of individuals, and the other producing the sense of familiarity. Dysfunctions at different stages of one or the other of these two processes could result in distortions in the feeling of knowing. From this case and others reported in literature, we propose to complete the classical model of face processing by adding a pathway linked to limbic system and frontal structures. This later pathway could normally emit signals for familiarity, essentially autonomic, in response to the familiar faces. These signals, primitively unconscious, secondly reach consciousness and are then integrated by a central supervisor system which evaluates and verifies identity-specific biographical information in order to make a decision about the sense of familiarity.

The role of semantic complexity in treatment of naming deficits: training semantic categories in fluent aphasia by controlling exemplar typicality.

PubMed

Kiran, Swathi; Thompson, Cynthia K

2003-06-01

The effect of typicality of category exemplars on naming was investigated using a single subject experimental design across participants and behaviors in 4 patients with fluent aphasia. Participants received a semantic feature treatment to improve naming of either typical or atypical items within semantic categories, while generalization was tested to untrained items of the category. The order of typicality and category trained was counterbalanced across participants. Results indicated that patients trained on naming of atypical exemplars demonstrated generalization to naming of intermediate and typical items. However, patients trained on typical items demonstrated no generalized naming effect to intermediate or atypical examples. Furthermore, analysis of errors indicated an evolution of errors throughout training, from those with no apparent relationship to the target to primarily semantic and phonemic paraphasias. Performance on standardized language tests also showed changes as a function of treatment. Theoretical and clinical implications regarding the impact of considering semantic complexity on rehabilitation of naming deficits in aphasia are discussed.

The role of semantic complexity in treatment of naming deficits: training semantic categories in fluent aphasia by controlling exemplar typicality.

PubMed

Kiran, Swathi; Thompson, Cynthia K

2003-08-01

The effect of typicality of category exemplars on naming was investigated using a single subject experimental design across participants and behaviors in 4 patients with fluent aphasia. Participants received a semantic feature treatment to improve naming of either typical or atypical items within semantic categories, while generalization was tested to untrained items of the category. The order of typicality and category trained was counterbalanced across participants. Results indicated that patients trained on naming of atypical exemplars demonstrated generalization to naming of intermediate and typical items. However, patients trained on typical items demonstrated no generalized naming effect to intermediate or atypical examples. Furthermore, analysis of errors indicated an evolution of errors throughout training, from those with no apparent relationship to the target to primarily semantic and phonemic paraphasias. Performance on standardized language tests also showed changes as a function of treatment. Theoretical and clinical implications regarding the impact of considering semantic complexity on rehabilitation of naming deficits in aphasia are discussed.

Facial and semantic emotional interference: A pilot study on the behavioral and cortical responses to the dual valence association task

PubMed Central

2011-01-01

Background Integration of compatible or incompatible emotional valence and semantic information is an essential aspect of complex social interactions. A modified version of the Implicit Association Test (IAT) called Dual Valence Association Task (DVAT) was designed in order to measure conflict resolution processing from compatibility/incompatibly of semantic and facial valence. The DVAT involves two emotional valence evaluative tasks which elicits two forms of emotional compatible/incompatible associations (facial and semantic). Methods Behavioural measures and Event Related Potentials were recorded while participants performed the DVAT. Results Behavioural data showed a robust effect that distinguished compatible/incompatible tasks. The effects of valence and contextual association (between facial and semantic stimuli) showed early discrimination in N170 of faces. The LPP component was modulated by the compatibility of the DVAT. Conclusions Results suggest that DVAT is a robust paradigm for studying the emotional interference effect in the processing of simultaneous information from semantic and facial stimuli. PMID:21489277

The Fusion Model of Intelligent Transportation Systems Based on the Urban Traffic Ontology

NASA Astrophysics Data System (ADS)

Yang, Wang-Dong; Wang, Tao

On these issues unified representation of urban transport information using urban transport ontology, it defines the statute and the algebraic operations of semantic fusion in ontology level in order to achieve the fusion of urban traffic information in the semantic completeness and consistency. Thus this paper takes advantage of the semantic completeness of the ontology to build urban traffic ontology model with which we resolve the problems as ontology mergence and equivalence verification in semantic fusion of traffic information integration. Information integration in urban transport can increase the function of semantic fusion, and reduce the amount of data integration of urban traffic information as well enhance the efficiency and integrity of traffic information query for the help, through the practical application of intelligent traffic information integration platform of Changde city, the paper has practically proved that the semantic fusion based on ontology increases the effect and efficiency of the urban traffic information integration, reduces the storage quantity, and improve query efficiency and information completeness.

Mathematical values in the processing of Chinese numeral classifiers and measure words.

PubMed

Her, One-Soon; Chen, Ying-Chun; Yen, Nai-Shing

2017-01-01

A numeral classifier is required between a numeral and a noun in Chinese, which comes in two varieties, sortal classifer (C) and measural classifier (M), also known as 'classifier' and 'measure word', respectively. Cs categorize objects based on semantic attributes and Cs and Ms both denote quantity in terms of mathematical values. The aim of this study was to conduct a psycholinguistic experiment to examine whether participants process C/Ms based on their mathematical values with a semantic distance comparison task, where participants judged which of the two C/M phrases was semantically closer to the target C/M. Results showed that participants performed more accurately and faster for C/Ms with fixed values than the ones with variable values. These results demonstrated that mathematical values do play an important role in the processing of C/Ms. This study may thus shed light on the influence of the linguistic system of C/Ms on magnitude cognition.

Semantic information mediates visual attention during spoken word recognition in Chinese: Evidence from the printed-word version of the visual-world paradigm.

PubMed

Shen, Wei; Qu, Qingqing; Li, Xingshan

2016-07-01

In the present study, we investigated whether the activation of semantic information during spoken word recognition can mediate visual attention's deployment to printed Chinese words. We used a visual-world paradigm with printed words, in which participants listened to a spoken target word embedded in a neutral spoken sentence while looking at a visual display of printed words. We examined whether a semantic competitor effect could be observed in the printed-word version of the visual-world paradigm. In Experiment 1, the relationship between the spoken target words and the printed words was manipulated so that they were semantically related (a semantic competitor), phonologically related (a phonological competitor), or unrelated (distractors). We found that the probability of fixations on semantic competitors was significantly higher than that of fixations on the distractors. In Experiment 2, the orthographic similarity between the spoken target words and their semantic competitors was manipulated to further examine whether the semantic competitor effect was modulated by orthographic similarity. We found significant semantic competitor effects regardless of orthographic similarity. Our study not only reveals that semantic information can affect visual attention, it also provides important new insights into the methodology employed to investigate the semantic processing of spoken words during spoken word recognition using the printed-word version of the visual-world paradigm.

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis

PubMed Central

Guardia, Gabriela D. A.; Pires, Luís Ferreira; Vêncio, Ricardo Z. N.; Malmegrim, Kelen C. R.; de Farias, Cléver R. G.

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis. PMID:26207740

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

PubMed

Guardia, Gabriela D A; Pires, Luís Ferreira; Vêncio, Ricardo Z N; Malmegrim, Kelen C R; de Farias, Cléver R G

2015-01-01

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis.

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

Effect of hearing loss on semantic access by auditory and audiovisual speech in children.

PubMed

Jerger, Susan; Tye-Murray, Nancy; Damian, Markus F; Abdi, Hervé

2013-01-01

This research studied whether the mode of input (auditory versus audiovisual) influenced semantic access by speech in children with sensorineural hearing impairment (HI). Participants, 31 children with HI and 62 children with normal hearing (NH), were tested with the authors' new multimodal picture word task. Children were instructed to name pictures displayed on a monitor and ignore auditory or audiovisual speech distractors. The semantic content of the distractors was varied to be related versus unrelated to the pictures (e.g., picture distractor of dog-bear versus dog-cheese, respectively). In children with NH, picture-naming times were slower in the presence of semantically related distractors. This slowing, called semantic interference, is attributed to the meaning-related picture-distractor entries competing for selection and control of the response (the lexical selection by competition hypothesis). Recently, a modification of the lexical selection by competition hypothesis, called the competition threshold (CT) hypothesis, proposed that (1) the competition between the picture-distractor entries is determined by a threshold, and (2) distractors with experimentally reduced fidelity cannot reach the CT. Thus, semantically related distractors with reduced fidelity do not produce the normal interference effect, but instead no effect or semantic facilitation (faster picture naming times for semantically related versus unrelated distractors). Facilitation occurs because the activation level of the semantically related distractor with reduced fidelity (1) is not sufficient to exceed the CT and produce interference but (2) is sufficient to activate its concept, which then strengthens the activation of the picture and facilitates naming. This research investigated whether the proposals of the CT hypothesis generalize to the auditory domain, to the natural degradation of speech due to HI, and to participants who are children. Our multimodal picture word task allowed us to (1) quantify picture naming results in the presence of auditory speech distractors and (2) probe whether the addition of visual speech enriched the fidelity of the auditory input sufficiently to influence results. In the HI group, the auditory distractors produced no effect or a facilitative effect, in agreement with proposals of the CT hypothesis. In contrast, the audiovisual distractors produced the normal semantic interference effect. Results in the HI versus NH groups differed significantly for the auditory mode, but not for the audiovisual mode. This research indicates that the lower fidelity auditory speech associated with HI affects the normalcy of semantic access by children. Further, adding visual speech enriches the lower fidelity auditory input sufficiently to produce the semantic interference effect typical of children with NH.

A neural signature of food semantics is associated with body-mass index.

PubMed

Pergola, Giulio; Foroni, Francesco; Mengotti, Paola; Argiris, Georgette; Rumiati, Raffaella Ida

2017-10-01

Visual recognition of objects may rely on different features depending on the category to which they belong. Recognizing natural objects, such as fruits and plants, weighs more on their perceptual attributes, whereas recognizing man-made objects, such as tools or vehicles, weighs more upon the functions and actions they enable. Edible objects are perceptually rich but also prepared for specific functions, therefore it is unclear how perceptual and functional attributes affect their recognition. Two event-related potentials experiments investigated: (i) whether food categorization in the brain is differentially modulated by sensory and functional attributes, depending on whether the food is natural or transformed; (ii) whether these processes are modulated by participants' body mass index. In experiment 1, healthy normal-weight participants were presented with a sentence (prime) and a photograph of a food. Primes described either a sensory feature ('It tastes sweet') or a functional feature ('It is suitable for a wedding party') of the food, while photographs depicted either a natural (e.g., cherry) or a transformed food (e.g., pizza). Prime-feature pairs were either congruent or incongruent. This design aimed at modulating N400-like components elicited by semantic processing. In experiment 1, N400-like amplitude was significantly larger for transformed food than for natural food with sensory primes, and vice versa with functional primes. In experiment 2, underweight and obese women performed the same semantic task. We found that, while the N400-like component in obese participants was modulated by sensory-functional primes only for transformed food, the same modulation was found in underweight participants only for natural food. These findings suggest that the level of food transformation interacts with participants' body mass index in modulating food perception and the underlying brain processing. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

When Meaning Is Not Enough: Distributional and Semantic Cues to Word Categorization in Child Directed Speech.

PubMed

Feijoo, Sara; Muñoz, Carmen; Amadó, Anna; Serrat, Elisabet

2017-01-01

One of the most important tasks in first language development is assigning words to their grammatical category. The Semantic Bootstrapping Hypothesis postulates that, in order to accomplish this task, children are guided by a neat correspondence between semantic and grammatical categories, since nouns typically refer to objects and verbs to actions. It is this correspondence that guides children's initial word categorization. Other approaches, on the other hand, suggest that children might make use of distributional cues and word contexts to accomplish the word categorization task. According to such approaches, the Semantic Bootstrapping assumption offers an important limitation, as it might not be true that all the nouns that children hear refer to specific objects or people. In order to explore that, we carried out two studies based on analyses of children's linguistic input. We analyzed child-directed speech addressed to four children under the age of 2;6, taken from the CHILDES database. The corpora were selected from the Manchester corpus. The corpora from the four selected children contained a total of 10,681 word types and 364,196 word tokens. In our first study, discriminant analyses were performed using semantic cues alone. The results show that many of the nouns found in parents' speech do not relate to specific objects and that semantic information alone might not be sufficient for successful word categorization. Given that there must be an additional source of information which, alongside with semantics, might assist young learners in word categorization, our second study explores the availability of both distributional and semantic cues in child-directed speech. Our results confirm that this combination might yield better results for word categorization. These results are in line with theories that suggest the need for an integration of multiple cues from different sources in language development.

The Language Environment and Syntactic Word-Class Acquisition.

ERIC Educational Resources Information Center

Zavrel, Jakub; Veenstra, Jorn

A study analyzed the distribution of words in a three-million-word corpus of text from the "Wall Street Journal," in order to test a theory of the acquisition of word categories. The theory, an alternative to the semantic bootstrapping hypothesis, proposes that the child exploits multiple sources of cues (distributional, semantic, or…

Cue Conflicts in Context: Interplay between Morphosyntax and Discourse Context in Danish Preschoolers' Semantic Role Assignment

ERIC Educational Resources Information Center

Thomsen, Ditte Boeg; Poulsen, Mads

2015-01-01

When learning their first language, children develop strategies for assigning semantic roles to sentence structures, depending on morphosyntactic cues such as case and word order. Traditionally, comprehension experiments have presented transitive clauses in isolation, and cross-linguistically children have been found to misinterpret object-first…

"Dyslexia": Toward Semantical Clarification.

ERIC Educational Resources Information Center

Manzo, Anthony V.; Duffelmeyer, Fred

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

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

PubMed

Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

2017-08-25

We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

A Computational Linguistic Measure of Clustering Behavior on Semantic Verbal Fluency Task Predicts Risk of Future Dementia in the Nun Study

PubMed Central

Pakhomov, Serguei V.S.; Hemmy, Laura S.

2014-01-01

Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer’s disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters. We evaluated a novel automated computational linguistic approach for quantifying clustering behavior. Our approach is based on Latent Semantic Analysis (LSA) for computing strength of semantic relatedness between pairs of words produced in response to SVF test. The mean size of semantic clusters (MCS) and semantic chains (MChS) are calculated based on pairwise relatedness values between words. We evaluated the predictive validity of these measures on a set of 239 participants in the Nun Study, a longitudinal study of aging. All were cognitively intact at baseline assessment, measured with the CERAD battery, and were followed in 18 month waves for up to 20 years. The onset of either dementia or memory impairment were used as outcomes in Cox proportional hazards models adjusted for age and education and censored at follow up waves 5 (6.3 years) and 13 (16.96 years). Higher MCS was associated with 38% reduction in dementia risk at wave 5 and 26% reduction at wave 13, but not with the onset of memory impairment. Higher (+1 SD) MChS was associated with 39% dementia risk reduction at wave 5 but not wave 13, and association with memory impairment was not significant. Higher traditional SVF scores were associated with 22–29% memory impairment and 35–40% dementia risk reduction. SVF scores were not correlated with either MCS or MChS. Our study suggests that an automated approach to measuring clustering behavior can be used to estimate dementia risk in cognitively normal individuals. PMID:23845236

A computational linguistic measure of clustering behavior on semantic verbal fluency task predicts risk of future dementia in the nun study.

PubMed

Pakhomov, Serguei V S; Hemmy, Laura S

2014-06-01

Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer's disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters. We evaluated a novel automated computational linguistic approach for quantifying clustering behavior. Our approach is based on Latent Semantic Analysis (LSA) for computing strength of semantic relatedness between pairs of words produced in response to SVF test. The mean size of semantic clusters (MCS) and semantic chains (MChS) are calculated based on pairwise relatedness values between words. We evaluated the predictive validity of these measures on a set of 239 participants in the Nun Study, a longitudinal study of aging. All were cognitively intact at baseline assessment, measured with the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery, and were followed in 18-month waves for up to 20 years. The onset of either dementia or memory impairment were used as outcomes in Cox proportional hazards models adjusted for age and education and censored at follow-up waves 5 (6.3 years) and 13 (16.96 years). Higher MCS was associated with 38% reduction in dementia risk at wave 5 and 26% reduction at wave 13, but not with the onset of memory impairment. Higher [+1 standard deviation (SD)] MChS was associated with 39% dementia risk reduction at wave 5 but not wave 13, and association with memory impairment was not significant. Higher traditional SVF scores were associated with 22-29% memory impairment and 35-40% dementia risk reduction. SVF scores were not correlated with either MCS or MChS. Our study suggests that an automated approach to measuring clustering behavior can be used to estimate dementia risk in cognitively normal individuals. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cultural Capital in Business Higher Education: Reconsidering the Graduate Attributes Movement and the Focus on Employability

ERIC Educational Resources Information Center

Kalfa, Senia; Taksa, Lucy

2015-01-01

This article examines the increased interest being shown by Australian business faculties in the development of students' employability skills. Many universities have demonstrated their commitment to translating such interest into practice by elaborating lists of "graduate attributes" in order to enable the development of generic skills…

Neural correlates of lexical-semantic memory: A voxel-based morphometry study in mild AD, aMCI and normal aging

PubMed Central

Balthazar, Marcio L.F.; Yasuda, Clarissa L.; Lopes, Tátila M.; Pereira, Fabrício R.S.; Damasceno, Benito Pereira; Cendes, Fernando

2011-01-01

Neuroanatomical correlations of naming and lexical-semantic memory are not yet fully understood. The most influential approaches share the view that semantic representations reflect the manner in which information has been acquired through perception and action, and that each brain area processes different modalities of semantic representations. Despite these anatomical differences in semantic processing, generalization across different features that have similar semantic significance is one of the main characteristics of human cognition. Methods We evaluated the brain regions related to naming, and to the semantic generalization, of visually presented drawings of objects from the Boston Naming Test (BNT), which comprises different categories, such as animals, vegetables, tools, food, and furniture. In order to create a model of lesion method, a sample of 48 subjects presenting with a continuous decline both in cognitive functions, including naming skills, and in grey matter density (GMD) was compared to normal young adults with normal aging, amnestic mild cognitive impairment (aMCI) and mild Alzheimer’s disease (AD). Semantic errors on the BNT, as well as naming performance, were correlated with whole brain GMD as measured by voxel-based morphometry (VBM). Results The areas most strongly related to naming and to semantic errors were the medial temporal structures, thalami, superior and inferior temporal gyri, especially their anterior parts, as well as prefrontal cortices (inferior and superior frontal gyri). Conclusion The possible role of each of these areas in the lexical-semantic networks was discussed, along with their contribution to the models of semantic memory organization. PMID:29213726

An Italian battery for the assessment of semantic memory disorders.

PubMed

Catricalà, Eleonora; Della Rosa, Pasquale A; Ginex, Valeria; Mussetti, Zoe; Plebani, Valentina; Cappa, Stefano F

2013-06-01

We report the construction and standardization of a new comprehensive battery of tests for the assessment of semantic memory disorders. The battery is constructed on a common set of 48 stimuli, belonging to both living and non-living categories, rigidly controlled for several confounding variables, and is based on an empirically derived corpus of semantic features. It includes six tasks, in order to assess semantic memory through different modalities of input and output: two naming tasks, one with colored pictures and the other in response to an oral description, a word-picture matching task, a picture sorting task, a free generation of features task and a sentence verification task. Normative data on 106 Italian subjects pooled across homogenous subgroups for age, sex and education are reported. The new battery allows an in-depth investigation of category-specific disorders and of progressive semantic memory deficits at features level, overcoming some of the limitations of existing tests.

Semantic Encoding Enhances the Pictorial Superiority Effect in the Oldest-Old

PubMed Central

Cherry, Katie E.; Brown, Jennifer Silva; Walker, Erin Jackson; Smitherman, Emily A.; Boudreaux, Emily O.; Volaufova, Julia; Jazwinski, S. Michal

2011-01-01

We examined the effect of a semantic orienting task during encoding on free recall and recognition of simple line drawings and matching words in middle-aged (44 to 59 years), older (60 to 89 years), and oldest-old (90 + years) adults. Participants studied line drawings and matching words presented in blocked order. Half of the participants were given a semantic orienting task and the other half received standard intentional learning instructions. Results confirmed that the pictorial superiority effect was greater in magnitude following semantic encoding compared to the control condition. Analyses of clustering in free recall revealed that oldest-old adults’ encoding and retrieval strategies were generally similar to the two younger groups. Self-reported strategy use was less frequent among the oldest-old adults. These data strongly suggest that semantic elaboration is an effective compensatory mechanism underlying preserved episodic memory performance that persists well into the ninth decade of life. PMID:22053814

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

PubMed

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

2016-06-15

Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval. Large-scale MeSH indexing has two challenging aspects: the citation side and MeSH side. For the citation side, all existing methods, including Medical Text Indexer (MTI) by National Library of Medicine and the state-of-the-art method, MeSHLabeler, deal with text by bag-of-words, which cannot capture semantic and context-dependent information well. We propose DeepMeSH that incorporates deep semantic information for large-scale MeSH indexing. It addresses the two challenges in both citation and MeSH sides. The citation side challenge is solved by a new deep semantic representation, D2V-TFIDF, which concatenates both sparse and dense semantic representations. The MeSH side challenge is solved by using the 'learning to rank' framework of MeSHLabeler, which integrates various types of evidence generated from the new semantic representation. DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations. The software is available upon request. zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Hemispheric asymmetry in the hierarchical perception of music and speech.

PubMed

Rosenthal, Matthew A

2016-11-01

The perception of music and speech involves a higher level, cognitive mechanism that allows listeners to form expectations for future music and speech events. This article comprehensively reviews studies on hemispheric differences in the formation of melodic and harmonic expectations in music and selectively reviews studies on hemispheric differences in the formation of syntactic and semantic expectations in speech. On the basis of this review, it is concluded that the higher level mechanism flexibly lateralizes music processing to either hemisphere depending on the expectation generated by a given musical context. When a context generates in the listener an expectation whose elements are sequentially ordered over time, higher level processing is dominant in the left hemisphere. When a context generates in the listener an expectation whose elements are not sequentially ordered over time, higher level processing is dominant in the right hemisphere. This article concludes with a spreading activation model that describes expectations for music and speech in terms of shared temporal and nontemporal representations. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Knowledge-base browsing: an application of hybrid distributed/local connectionist networks

NASA Astrophysics Data System (ADS)

Samad, Tariq; Israel, Peggy

1990-08-01

We describe a knowledge base browser based on a connectionist (or neural network) architecture that employs both distributed and local representations. The distributed representations are used for input and output thereby enabling associative noise-tolerant interaction with the environment. Internally all representations are fully local. This simplifies weight assignment and facilitates network configuration for specific applications. In our browser concepts and relations in a knowledge base are represented using " microfeatures. " The microfeatures can encode semantic attributes structural features contextual information etc. Desired portions of the knowledge base can then be associatively retrieved based on a structured cue. An ordered list of partial matches is presented to the user for selection. Microfeatures can also be used as " bookmarks" they can be placed dynamically at appropriate points in the knowledge base and subsequently used as retrieval cues. A proof-of-concept system has been implemented for an internally developed Honeywell-proprietary knowledge acquisition tool. 1.

Cerebellar theta-burst stimulation selectively enhances lexical associative priming.

PubMed

Argyropoulos, Giorgos P

2011-09-01

Recent research in cerebellar cognitive and linguistic functions makes plausible the idea that the cerebellum is involved in processing temporally contiguous linguistic input. In order to assess this hypothesis, a simple lexical decision task was constructed to study whether the effect of transcranial magnetic stimulation on two different cerebellar sites would have a selective impact on associative as opposed to semantic priming. This is the first experiment applying transcranial magnetic stimulation of the cerebellum to a linguistic task. The results show a selective drop in lexical decision accuracy after stimulation of a medial cerebellar site in the first session of participation. Most importantly, they also demonstrate a selective increase of associative priming sizes after stimulation of the same site that cannot be attributed to changes in sensorimotor performance or in accuracy rates. The finding is discussed within the context of domain-general associative cerebellar computations.

Apraxia, mechanical problem solving and semantic knowledge: contributions to object usage in corticobasal degeneration.

PubMed

Spatt, Josef; Bak, Thomas; Bozeat, Sasha; Patterson, Karalyn; Hodges, John R

2002-05-01

To investigate the nature of the apraxia in corticobasal degeneration (CBD) five patients with CBD and five matched controls were compared on tests of: i) meaningless and symbolic gesture production, ii) a battery of semantic tasks based on 20 everyday items (involving naming and picture-picture matching according to semantic attributes, matching gestures-to-objects, object usage from name and with the real object) and iii) a novel tool test of mechanical problem solving. All five patients showed severe impairment in the production of meaningless and symbolic gestures from command, and by imitation, and were also impaired when using real objects. Deficits were not, however, restricted to action production: four were unable to match gestures to objects and all five showed impairment in the selection and usage of novel tools in the mechanical problem solving task. Surprising was the finding of an additional semantic knowledge breakdown in three cases, two of whom were markedly anomic. The apraxia in CBD is, therefore, multifactorial. There is profound breakdown in the organisation and co-ordination of motor programming. In addition, patients show central deficits in action knowledge and mechanical problem solving, which has been linked to parietal lobe pathology. General semantic memory may also be affected in CBD in some cases and this may then contribute to impaired object usage. This combination of more than one deficit relevant for object use may explain why CBD patients are far more disabled by their dyspraxia in everyday life than any other patient group.

On the universal structure of human lexical semantics

DOE PAGES

Youn, Hyejin; Sutton, Logan; Smith, Eric; ...

2016-02-01

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 tomore » 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. As a result, 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.« less

Impaired semantic knowledge underlies the reduced verbal short-term storage capacity in Alzheimer's disease.

PubMed

Peters, Frédéric; Majerus, Steve; De Baerdemaeker, Julie; Salmon, Eric; Collette, Fabienne

2009-12-01

A decrease in verbal short-term memory (STM) capacity is consistently observed in patients with Alzheimer's disease (AD). Although this impairment has been mainly attributed to attentional deficits during encoding and maintenance, the progressive deterioration of semantic knowledge in early stages of AD may also be an important determinant of poor STM performance. The aim of this study was to examine the influence of semantic knowledge on verbal short-term memory storage capacity in normal aging and in AD by exploring the impact of word imageability on STM performance. Sixteen patients suffering from mild AD, 16 healthy elderly subjects and 16 young subjects performed an immediate serial recall task using word lists containing high or low imageability words. All participant groups recalled more high imageability words than low imageability words, but the effect of word imageability on verbal STM was greater in AD patients than in both the young and the elderly control groups. More precisely, AD patients showed a marked decrease in STM performance when presented with lists of low imageability words, whereas recall of high imageability words was relatively well preserved. Furthermore, AD patients displayed an abnormal proportion of phonological errors in the low imageability condition. Overall, these results indicate that the support of semantic knowledge on STM performance was impaired for lists of low imageability words in AD patients. More generally, these findings suggest that the deterioration of semantic knowledge is partly responsible for the poor verbal short-term storage capacity observed in AD.

On the universal structure of human lexical semantics

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

Youn, Hyejin; Sutton, Logan; Smith, Eric

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 tomore » 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. As a result, 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.« less

Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision.

PubMed

Maravall, Darío; de Lope, Javier; Fuentes, Juan P

2017-01-01

We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks.

Navigation and Self-Semantic Location of Drones in Indoor Environments by Combining the Visual Bug Algorithm and Entropy-Based Vision

PubMed Central

Maravall, Darío; de Lope, Javier; Fuentes, Juan P.

2017-01-01

We introduce a hybrid algorithm for the self-semantic location and autonomous navigation of robots using entropy-based vision and visual topological maps. In visual topological maps the visual landmarks are considered as leave points for guiding the robot to reach a target point (robot homing) in indoor environments. These visual landmarks are defined from images of relevant objects or characteristic scenes in the environment. The entropy of an image is directly related to the presence of a unique object or the presence of several different objects inside it: the lower the entropy the higher the probability of containing a single object inside it and, conversely, the higher the entropy the higher the probability of containing several objects inside it. Consequently, we propose the use of the entropy of images captured by the robot not only for the landmark searching and detection but also for obstacle avoidance. If the detected object corresponds to a landmark, the robot uses the suggestions stored in the visual topological map to reach the next landmark or to finish the mission. Otherwise, the robot considers the object as an obstacle and starts a collision avoidance maneuver. In order to validate the proposal we have defined an experimental framework in which the visual bug algorithm is used by an Unmanned Aerial Vehicle (UAV) in typical indoor navigation tasks. PMID:28900394

Semantic deficits in Spanish-English bilingual children with language impairment.

PubMed

Sheng, Li; Peña, Elizabeth D; Bedore, Lisa M; Fiestas, Christine E

2012-02-01

To examine the nature and extent of semantic deficits in bilingual children with language impairment (LI). Thirty-seven Spanish-English bilingual children with LI (ranging from age 7;0 [years;months] to 9;10) and 37 typically developing (TD) age-matched peers generated 3 associations to 12 pairs of translation equivalents in English and Spanish. Responses were coded as paradigmatic (e.g., dinner-lunch, cena-desayuno [dinner-breakfast]), syntagmatic (e.g., delicious-pizza, delicioso-frijoles [delicious-beans]), and errors (e.g., wearing-where, vestirse-mal [to get dressed-bad]). A semantic depth score was derived in each language and conceptually by combining children's performance in both languages. The LI group achieved significantly lower semantic depth scores than the TD group after controlling for group differences in vocabulary size. Children showed higher conceptual scores than single-language scores. Both groups showed decreases in semantic depth scores across multiple elicitations. Analyses of individual performances indicated that semantic deficits (1 SD below the TD mean semantic depth score) were manifested in 65% of the children with LI and in 14% of the TD children. School-age bilingual children with and without LI demonstrated spreading activation of semantic networks. Consistent with the literature on monolingual children with LI, sparsely linked semantic networks characterize a considerable proportion of bilingual children with LI.

Right fusiform response patterns reflect visual object identity rather than semantic similarity.

PubMed

Bruffaerts, Rose; Dupont, Patrick; De Grauwe, Sophie; Peeters, Ronald; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik

2013-12-01

We previously reported the neuropsychological consequences of a lesion confined to the middle and posterior part of the right fusiform gyrus (case JA) causing a partial loss of knowledge of visual attributes of concrete entities in the absence of category-selectivity (animate versus inanimate). We interpreted this in the context of a two-step model that distinguishes structural description knowledge from associative-semantic processing and implicated the lesioned area in the former process. To test this hypothesis in the intact brain, multi-voxel pattern analysis was used in a series of event-related fMRI studies in a total of 46 healthy subjects. We predicted that activity patterns in this region would be determined by the identity of rather than the conceptual similarity between concrete entities. In a prior behavioral experiment features were generated for each entity by more than 1000 subjects. Based on a hierarchical clustering analysis the entities were organised into 3 semantic clusters (musical instruments, vehicles, tools). Entities were presented as words or pictures. With foveal presentation of pictures, cosine similarity between fMRI response patterns in right fusiform cortex appeared to reflect both the identity of and the semantic similarity between the entities. No such effects were found for words in this region. The effect of object identity was invariant for location, scaling, orientation axis and color (grayscale versus color). It also persisted for different exemplars referring to a same concrete entity. The apparent semantic similarity effect however was not invariant. This study provides further support for a neurobiological distinction between structural description knowledge and processing of semantic relationships and confirms the role of right mid-posterior fusiform cortex in the former process, in accordance with previous lesion evidence. © 2013.

Cases, Simulacra, and Semantic Web Technologies

ERIC Educational Resources Information Center

Carmichael, P.; Tscholl, M.

2013-01-01

"Ensemble" is an interdisciplinary research and development project exploring the potential role of emerging Semantic Web technologies in case-based learning across learning environments in higher education. Empirical findings have challenged the claim that cases "bring reality into the classroom" and that this, in turn, might…

Semantic-based surveillance video retrieval.

PubMed

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

2007-04-01

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

Research on designing ontologies for location-based services

NASA Astrophysics Data System (ADS)

Cheng, Gang; Du, Qingyun; Cai, Zhongliang; Huang, Maojun; Zhao, Haiyun

2007-06-01

With the far and wide applications of Location-Based Services (LBS), the call for more semantic and accurate services is emerging. From a semantic viewpoint, the major characteristic of, and challenge for, LBS is the fact that they serve as mediator between a possibly unknown user and possibly a priori unknown services. While some geographic information technology standards provide the basis for syntactic interoperability, they do not yet provide methods for dealing with problems of semantic heterogeneity. In this paper we design ontologies for LBS which are used for the identification and association of semantically corresponding concepts to overcome the semantic problems. In order to better understand the semantic content of the data in LBS, we analyze several elements both data and services involved. Then, we model these data and services in a way that captures their peculiarities and allows their sharing between users and services and exchange among different LBS, when desired. For this, we use the Protégé-OWL plug-in for creating hybrid hierarchy of ontologies to enhance the semantic content both the user information and the services have. To argue about the design choices and show their applicability, we present a simple example from a characteristic real world application.

English Learners' Knowledge of Prepositions: Collocational Knowledge or Knowledge Based on Meaning?

ERIC Educational Resources Information Center

Mueller, Charles M.

2011-01-01

Second language (L2) learners' successful performance in an L2 can be partly attributed to their knowledge of collocations. In some cases, this knowledge is accompanied by knowledge of the semantic and/or grammatical patterns that motivate the collocation. At other times, collocational knowledge may serve a compensatory role. To determine the…

The Systems Approach to School Administration: Some Perceptions on the State of the Art in 1967.

ERIC Educational Resources Information Center

Knezevich, S. J.

Concepts which are salient features of the systems approach do not appear to have permeated school administration beyond the threshold of awareness. Confusion among administrators as to the meaning and potential of the systems approach can be partly attributed to its overzealous adherents, semantic difficulties among experts, and its application…

Categorical Priming of Famous Person Recognition: A Hitherto Overlooked Methodological Factor Can Resolve a Long-Standing Debate

ERIC Educational Resources Information Center

Stone, Anna

2008-01-01

The Burton, Bruce and Johnston [Burton, A. M., Bruce, V., & Johnston, R. A. (1990). Understanding face recognition with an interactive activation model. "British Journal of Psychology," 81, 361-380] model of person recognition proposes that representations of known persons are connected by shared semantic attributes. This predicts that priming…

A Synchronization Account of False Recognition

ERIC Educational Resources Information Center

Johns, Brendan T.; Jones, Michael N.; Mewhort, Douglas J. K.

2012-01-01

We describe a computational model to explain a variety of results in both standard and false recognition. A key attribute of the model is that it uses plausible semantic representations for words, built through exposure to a linguistic corpus. A study list is encoded in the model as a gist trace, similar to the proposal of fuzzy trace theory…

Modulation of alpha oscillations is required for the suppression of semantic interference.

PubMed

Melnik, Natalia; Mapelli, Igor; Özkurt, Tolga Esat

2017-10-01

Recent findings on alpha band oscillations suggest their important role in memory consolidation and suppression of external distractors such as environmental noise. However, less attention was given to the phenomenon of internal distracting information being solely inherent to the stimuli content. Human memory may be prone to internal distractions caused by semantic relatedness between the meaning of words (e.g., atom, neutron, nucleus, etc.) to be encoded, i.e., semantic interference. Our study investigates the brain oscillatory dynamics behind the semantic interference phenomenon, whose possible outcome is known as false memories. In this direction, Deese-Roediger-McDermott word lists were appropriated for a modified Sternberg paradigm in auditory modality. Participants received semantically related and unrelated word lists via headphones while EEG data were acquired. Semantic interference triggered the false memory rates to be higher than those of other types of memory errors. Analysis demonstrated that the upper part of alpha band (∼10-12Hz) power decreases on parieto-occipital channels in the retention interval, prior to the probe item for semantically related condition. Our study elucidates the oscillatory mechanisms behind semantic interference by relying on alpha functional inhibition theory. Copyright © 2017 Elsevier Inc. All rights reserved.

Direct Exploration of the Role of the Ventral Anterior Temporal Lobe in Semantic Memory: Cortical Stimulation and Local Field Potential Evidence From Subdural Grid Electrodes.

PubMed

Shimotake, Akihiro; Matsumoto, Riki; Ueno, Taiji; Kunieda, Takeharu; Saito, Satoru; Hoffman, Paul; Kikuchi, Takayuki; Fukuyama, Hidenao; Miyamoto, Susumu; Takahashi, Ryosuke; Ikeda, Akio; Lambon Ralph, Matthew A

2015-10-01

Semantic memory is a crucial higher cortical function that codes the meaning of objects and words, and when impaired after neurological damage, patients are left with significant disability. Investigations of semantic dementia have implicated the anterior temporal lobe (ATL) region, in general, as crucial for multimodal semantic memory. The potentially crucial role of the ventral ATL subregion has been emphasized by recent functional neuroimaging studies, but the necessity of this precise area has not been selectively tested. The implantation of subdural electrode grids over this subregion, for the presurgical assessment of patients with partial epilepsy or brain tumor, offers the dual yet rare opportunities to record cortical local field potentials while participants complete semantic tasks and to stimulate the functionally identified regions in the same participants to evaluate the necessity of these areas in semantic processing. Across 6 patients, and utilizing a variety of semantic assessments, we evaluated and confirmed that the anterior fusiform/inferior temporal gyrus is crucial in multimodal, receptive, and expressive, semantic processing. © The Author 2014. Published by Oxford University Press.

Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans

PubMed Central

Si, Guangsen; Xu, Zeshui

2018-01-01

Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers’ subjective cognition. In general, different decision-makers’ sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method. PMID:29614019

Treatment for Anomia in Semantic Dementia

PubMed Central

Henry, Maya L.; Beeson, Pélagie M.; Rapcsak, Steven Z.

2009-01-01

Anomia is a striking and consistent clinical feature of semantic dementia (SD), a progressive aphasia syndrome associated with focal cortical atrophy of the anterior temporal lobes. Word retrieval deficits in patients with SD have been attributed to the loss of conceptual knowledge, resulting in an impairment referred to as semantic anomia. Whereas an abundance of research has been dedicated to treatment for anomia in individuals with focal brain damage due to stroke, considerably less work has been done regarding treatment for patients with progressive language decline. The purpose of this article is to review the available literature concerning the nature and treatment of anomia in individuals with SD. Several studies have shown that new lexical learning remains possible in these patients. However, newly learned information is likely to be constrained by the learning context, and increased reliance on perceptual and autobiographical contextual information may be necessary to provide critical support for new vocabulary acquisition. There is also evidence suggesting that treatment may slow the progression of anomia over time, even affording some protective benefit to lexical items that are not yet lost. However, treatment efforts are likely to be most beneficial at early stages of the disease, when residual semantic knowledge as. well as relatively spared episodic memory may support new learning. PMID:18348092

Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans.

PubMed

Liao, Huchang; Si, Guangsen; Xu, Zeshui; Fujita, Hamido

2018-04-03

Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers' subjective cognition. In general, different decision-makers' sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method.

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

PubMed Central

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

2009-01-01

Background SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. Results There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at , developer tools at , and a portal to third-party ontologies at (a "swap meet"). Conclusion SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the confounding of content, structure, and presentation. SSWAP is novel by establishing the concept of a canonical yet mutable OWL DL graph that allows data and service providers to describe their resources, to allow discovery servers to offer semantically rich search engines, to allow clients to discover and invoke those resources, and to allow providers to respond with semantically tagged data. SSWAP allows for a mix-and-match of terms from both new and legacy third-party ontologies in these graphs. PMID:19775460

Influence of prime-target relationship on semantic priming effects from words in a lexical-decision task.

PubMed

Abad, María J F; Noguera, Carmen; Ortells, Juan J

2003-07-01

The present research examines the influence of prime-target relationship (associative and categorical versus categorical only) on priming effects from attended and ignored parafoveal words. Participants performed a lexical-decision task on a single central target, which was preceded by two parafoveal prime words, one of which (the attended prime) was spatially precued. The results showed reliable positive and negative priming effects from attended and ignored words, respectively. However, this priming pattern was observed only for the "associative and categorical", but not for the "categorical only" relationship condition. These results suggest that the lack of semantic priming effects from words in some prior studies may be attributed to the kind of material used (i.e. weakly-associated word pairs).

Medical Image Databases

PubMed Central

Tagare, Hemant D.; Jaffe, C. Carl; Duncan, James

1997-01-01

Abstract Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema. PMID:9147338

Attribution and social cognitive neuroscience: a new approach for the "online-assessment" of causality ascriptions and their emotional consequences.

PubMed

Terbeck, Sylvia; Chesterman, Paul; Fischmeister, Florian Ph S; Leodolter, Ulrich; Bauer, Herbert

2008-08-15

Attribution theory plays a central role in understanding cognitive processes that have emotional consequences; however, there has been very limited attention to its neural basis. After reviewing classical studies in social psychology in which attribution has been experimentally manipulated we developed a new approach that allows the investigation of state attributions and emotional consequences using neuroscience methodologies. Participants responded to the Erikson Flanker Task, but, in order to maintain the participant's beliefs about the nature of the task and to produce a significant number of error responses, an adaptive algorithm tuned the available time to respond such that, dependent on the subject's current performance, the negative feedback rate was held at chance level. In order to initiate variation in attribution participants were informed that one and the same task was either easy or difficult. As a result of these two different instructions the two groups differed significantly in error attribution only on the locus of causality dimension. Additionally, attributions were found to be stable over a large number of trials, while accuracy and reaction time remained the same. Thus, the new paradigm is particularly suitable for cognitive neuroscience research that evaluates brain behaviour relationships of higher order processes in 'simulated achievement settings'.

Building English Vocabulary through Roots, Prefixes and Suffixes

ERIC Educational Resources Information Center

Yurtbasi, Metin

2015-01-01

Semantics, the study of the meaning of words, is the sum of the basic elements of four skills, namely, reading, writing, speaking and listening effectively. The knowledge of vocabulary words in lexico-semantics, on the other hand, is essential in every grade level, subject area and assessment for every student. In order to improve students'…

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

ERIC Educational Resources Information Center

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

2011-01-01

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

Using RDF to Model the Structure and Process of Systems

NASA Astrophysics Data System (ADS)

Rodriguez, Marko A.; Watkins, Jennifer H.; Bollen, Johan; Gershenson, Carlos

Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of entities connected by a heterogeneous set of relationships. Semantic networks serve as a promising general-purpose modeling substrate for complex systems. Various standardized formats and tools are now available to support practical, large-scale semantic network models. First, the Resource Description Framework (RDF) offers a standardized semantic network data model that can be further formalized by ontology modeling languages such as RDF Schema (RDFS) and the Web Ontology Language (OWL). Second, the recent introduction of highly performant triple-stores (i.e. semantic network databases) allows semantic network models on the order of 109 edges to be efficiently stored and manipulated. RDF and its related technologies are currently used extensively in the domains of computer science, digital library science, and the biological sciences. This article will provide an introduction to RDF/RDFS/OWL and an examination of its suitability to model discrete element complex systems.

Semantic Structure in Vocabulary Knowledge Interacts With Lexical and Sentence Processing in Infancy.

PubMed

Borovsky, Arielle; Ellis, Erica M; Evans, Julia L; Elman, Jeffrey L

2016-11-01

Although the size of a child's vocabulary associates with language-processing skills, little is understood regarding how this relation emerges. This investigation asks whether and how the structure of vocabulary knowledge affects language processing in English-learning 24-month-old children (N = 32; 18 F, 14 M). Parental vocabulary report was used to calculate semantic density in several early-acquired semantic categories. Performance on two language-processing tasks (lexical recognition and sentence processing) was compared as a function of semantic density. In both tasks, real-time comprehension was facilitated for higher density items, whereas lower density items experienced more interference. The findings indicate that language-processing skills develop heterogeneously and are influenced by the semantic network surrounding a known word. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Interconnected growing self-organizing maps for auditory and semantic acquisition modeling.

PubMed

Cao, Mengxue; Li, Aijun; Fang, Qiang; Kaufmann, Emily; Kröger, Bernd J

2014-01-01

Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM) algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic-semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners. A reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1) I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2) clear auditory and semantic boundaries can be found in the network representation; (3) cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4) reinforcing-by-link training leads to well-perceived auditory-semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.

Efficiently Multi-User Searchable Encryption Scheme with Attribute Revocation and Grant for Cloud Storage

PubMed Central

Wang, Shangping; Zhang, Xiaoxue; Zhang, Yaling

2016-01-01

Cipher-policy attribute-based encryption (CP-ABE) focus on the problem of access control, and keyword-based searchable encryption scheme focus on the problem of finding the files that the user interested in the cloud storage quickly. To design a searchable and attribute-based encryption scheme is a new challenge. In this paper, we propose an efficiently multi-user searchable attribute-based encryption scheme with attribute revocation and grant for cloud storage. In the new scheme the attribute revocation and grant processes of users are delegated to proxy server. Our scheme supports multi attribute are revoked and granted simultaneously. Moreover, the keyword searchable function is achieved in our proposed scheme. The security of our proposed scheme is reduced to the bilinear Diffie-Hellman (BDH) assumption. Furthermore, the scheme is proven to be secure under the security model of indistinguishability against selective ciphertext-policy and chosen plaintext attack (IND-sCP-CPA). And our scheme is also of semantic security under indistinguishability against chosen keyword attack (IND-CKA) in the random oracle model. PMID:27898703

Efficiently Multi-User Searchable Encryption Scheme with Attribute Revocation and Grant for Cloud Storage.

PubMed

Wang, Shangping; Zhang, Xiaoxue; Zhang, Yaling

2016-01-01

Cipher-policy attribute-based encryption (CP-ABE) focus on the problem of access control, and keyword-based searchable encryption scheme focus on the problem of finding the files that the user interested in the cloud storage quickly. To design a searchable and attribute-based encryption scheme is a new challenge. In this paper, we propose an efficiently multi-user searchable attribute-based encryption scheme with attribute revocation and grant for cloud storage. In the new scheme the attribute revocation and grant processes of users are delegated to proxy server. Our scheme supports multi attribute are revoked and granted simultaneously. Moreover, the keyword searchable function is achieved in our proposed scheme. The security of our proposed scheme is reduced to the bilinear Diffie-Hellman (BDH) assumption. Furthermore, the scheme is proven to be secure under the security model of indistinguishability against selective ciphertext-policy and chosen plaintext attack (IND-sCP-CPA). And our scheme is also of semantic security under indistinguishability against chosen keyword attack (IND-CKA) in the random oracle model.

Failing to get the gist of what's being said: background noise impairs higher-order cognitive processing

PubMed Central

Marsh, John E.; Ljung, Robert; Nöstl, Anatole; Threadgold, Emma; Campbell, Tom A.

2015-01-01

A dynamic interplay is known to exist between auditory processing and human cognition. For example, prior investigations of speech-in-noise have revealed there is more to learning than just listening: Even if all words within a spoken list are correctly heard in noise, later memory for those words is typically impoverished. These investigations supported a view that there is a “gap” between the intelligibility of speech and memory for that speech. Here, the notion was that this gap between speech intelligibility and memorability is a function of the extent to which the spoken message seizes limited immediate memory resources (e.g., Kjellberg et al., 2008). Accordingly, the more difficult the processing of the spoken message, the less resources are available for elaboration, storage, and recall of that spoken material. However, it was not previously known how increasing that difficulty affected the memory processing of semantically rich spoken material. This investigation showed that noise impairs higher levels of cognitive analysis. A variant of the Deese-Roediger-McDermott procedure that encourages semantic elaborative processes was deployed. On each trial, participants listened to a 36-item list comprising 12 words blocked by each of 3 different themes. Each of those 12 words (e.g., bed, tired, snore…) was associated with a “critical” lure theme word that was not presented (e.g., sleep). Word lists were either presented without noise or at a signal-to-noise ratio of 5 decibels upon an A-weighting. Noise reduced false recall of the critical words, and decreased the semantic clustering of recall. Theoretical and practical implications are discussed. PMID:26052289

Families of Graph Algorithms: SSSP Case Study

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

Kanewala Appuhamilage, Thejaka Amila Jay; Zalewski, Marcin J.; Lumsdaine, Andrew

2017-08-28

Single-Source Shortest Paths (SSSP) is a well-studied graph problem. Examples of SSSP algorithms include the original Dijkstra’s algorithm and the parallel Δ-stepping and KLA-SSSP algorithms. In this paper, we use a novel Abstract Graph Machine (AGM) model to show that all these algorithms share a common logic and differ from one another by the order in which they perform work. We use the AGM model to thoroughly analyze the family of algorithms that arises from the common logic. We start with the basic algorithm without any ordering (Chaotic), and then we derive the existing and new algorithms by methodically exploringmore » semantic and spatial ordering of work. Our experimental results show that new derived algorithms show better performance than the existing distributed memory parallel algorithms, especially at higher scales.« less

The neural correlates of semantic richness: evidence from an fMRI study of word learning.

PubMed

Ferreira, Roberto A; Göbel, Silke M; Hymers, Mark; Ellis, Andrew W

2015-04-01

We investigated the neural correlates of concrete nouns with either many or few semantic features. A group of 21 participants underwent two days of training and were then asked to categorize 40 newly learned words and a set of matched familiar words as living or nonliving in an MRI scanner. Our results showed that the most reliable effects of semantic richness were located in the left angular gyrus (AG) and middle temporal gyrus (MTG), where activation was higher for semantically rich than poor words. Other areas showing the same pattern included bilateral precuneus and posterior cingulate gyrus. Our findings support the view that AG and anterior MTG, as part of the multimodal network, play a significant role in representing and integrating semantic features from different input modalities. We propose that activation in bilateral precuneus and posterior cingulate gyrus reflects interplay between AG and episodic memory systems during semantic retrieval. Copyright © 2015 Elsevier Inc. All rights reserved.

What can Written-Words Tell us About Lexical Retrieval in Speech Production?

PubMed Central

Navarrete, Eduardo; Mahon, Bradford Z.; Lorenzoni, Anna; Peressotti, Francesca

2016-01-01

In recent decades, researchers have exploited semantic context effects in picture naming tasks in order to investigate the mechanisms involved in the retrieval of words from the mental lexicon. In the blocked naming paradigm, participants name target pictures that are either blocked or not blocked by semantic category. In the continuous naming task, participants name a sequence of target pictures that are drawn from multiple semantic categories. Semantic context effects in both tasks are a highly reliable phenomenon. The empirical evidence is, however, sparse and inconsistent when the target stimuli are printed-words instead of pictures. In the first part of the present study we review the empirical evidence regarding semantic context effects with written-word stimuli in the blocked and continuous naming tasks. In the second part, we empirically test whether semantic context effects are transferred from picture naming trials to word reading trials, and from word reading trials to picture naming trials. The results indicate a transfer of semantic context effects from picture naming to subsequently read within-category words. There is no transfer of semantic effects from target words that were read to subsequently named within-category pictures. These results replicate previous findings (Navarrete et al., 2010) and are contrary to predictions from a recent theoretical analysis by Belke (2013). The empirical evidence reported in the literature together with the present results, are discussed in relation to current accounts of semantic context effects in speech production. PMID:26779090

Semantic Service Design for Collaborative Business Processes in Internetworked Enterprises

NASA Astrophysics Data System (ADS)

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

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

Sculpting the UMLS Refined Semantic Network.

PubMed

He, Zhe; Morrey, C Paul; Perl, Yehoshua; Elhanan, Gai; Chen, Ling; Chen, Yan; Geller, James

2014-01-01

The Refined Semantic Network (RSN) for the UMLS was previously introduced to complement the UMLS Semantic Network (SN). The RSN partitions the UMLS Metathesaurus (META) into disjoint groups of concepts. Each such group is semantically uniform. However, the RSN was initially an order of magnitude larger than the SN, which is undesirable since to be useful, a semantic network should be compact. Most semantic types in the RSN represent combinations of semantic types in the UMLS SN. Such a "combination semantic type" is called Intersection Semantic Type (IST). Many ISTs are assigned to very few concepts. Moreover, when reviewing those concepts, many semantic type assignment inconsistencies were found. After correcting those inconsistencies many ISTs, among them some that contradicted UMLS rules, disappeared, which made the RSN smaller. The authors performed a longitudinal study with the goal of reducing the size of the RSN to become compact. This goal was achieved by correcting inconsistencies and errors in the IST assignments in the UMLS, which additionally helped identify and correct ambiguities, inconsistencies, and errors in source terminologies widely used in the realm of public health. In this paper, we discuss the process and steps employed in this longitudinal study and the intermediate results for different stages. The sculpting process includes removing redundant semantic type assignments, expanding semantic type assignments, and removing illegitimate ISTs by auditing ISTs of small extents. However, the emphasis of this paper is not on the auditing methodologies employed during the process, since they were introduced in earlier publications, but on the strategy of employing them in order to transform the RSN into a compact network. For this paper we also performed a comprehensive audit of 168 "small ISTs" in the 2013AA version of the UMLS to finalize the longitudinal study. Over the years it was found that the editors of the UMLS introduced some new inconsistencies that resulted in the reintroduction of unwarranted ISTs that had already been eliminated as a result of their previous corrections. Because of that, the transformation of the RSN into a compact network covering all necessary categories for the UMLS was slowed down. The corrections suggested by an audit of the 2013AA version of the UMLS achieve a compact RSN of equal magnitude as the UMLS SN. The number of ISTs has been reduced to 336. We also demonstrate how auditing the semantic type assignments of UMLS concepts can expose other modeling errors in the UMLS source terminologies, e.g., SNOMED CT, LOINC, and RxNORM that are important for health informatics. Such errors would otherwise stay hidden. It is hoped that the UMLS curators will implement all required corrections and use the RSN along with the SN when maintaining and extending the UMLS. When used correctly, the RSN will support the prevention of the accidental introduction of inconsistent semantic type assignments into the UMLS. Furthermore, this way the RSN will support the exposure of other hidden errors and inconsistencies in health informatics terminologies, which are sources of the UMLS. Notably, the development of the RSN materializes the deeper, more refined Semantic Network for the UMLS that its designers envisioned originally but had not implemented.

Attentional Sensitization of Unconscious Cognition: Task Sets Modulate Subsequent Masked Semantic Priming

ERIC Educational Resources Information Center

Kiefer, Markus; Martens, Ulla

2010-01-01

According to classical theories, automatic processes are autonomous and independent of higher level cognitive influence. In contrast, the authors propose that automatic processing depends on attentional sensitization of task-congruent processing pathways. In 3 experiments, the authors tested this hypothesis with a modified masked semantic priming…

Children and adolescents' performance on a medium-length/nonsemantic word-list test.

PubMed

Flores-Lázaro, Julio César; Salgado Soruco, María Alejandra; Stepanov, Igor I

2017-01-01

Word-list learning tasks are among the most important and frequently used tests for declarative memory evaluation. For example, the California Verbal Learning Test-Children's Version (CVLT-C) and Rey Auditory Verbal Learning Test provide important information about different cognitive-neuropsychological processes. However, the impact of test length (i.e., number of words) and semantic organization (i.e., type of words) on children's and adolescents' memory performance remains to be clarified, especially during this developmental stage. To explore whether a medium-length non-semantically organized test can produce the typical curvilinear performance that semantically organized tests produce, reflecting executive control, we studied and compared the cognitive performance of normal children and adolescents by utilizing mathematical modeling. The model is based on the first-order system transfer function and has been successfully applied to learning curves for the CVLT-C (15 words, semantically organized paradigm). Results indicate that learning nine semantically unrelated words produces typical curvilinear (executive function) performance in children and younger adolescents and that performance could be effectively analyzed with the mathematical model. This indicates that the exponential increase (curvilinear performance) of correctly learned words does not solely depend on semantic and/or length features. This type of test controls semantic and length effects and may represent complementary tools for executive function evaluation in clinical populations in which semantic and/or length processing are affected.

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

PubMed Central

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

2016-01-01

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

Semantic processes leading to true and false memory formation in schizophrenia.

PubMed

Paz-Alonso, Pedro M; Ghetti, Simona; Ramsay, Ian; Solomon, Marjorie; Yoon, Jong; Carter, Cameron S; Ragland, J Daniel

2013-07-01

Encoding semantic relationships between items on word lists (semantic processing) enhances true memories, but also increases memory distortions. Episodic memory impairments in schizophrenia (SZ) are strongly driven by failures to process semantic relations, but the exact nature of these relational semantic processing deficits is not well understood. Here, we used a false memory paradigm to investigate the impact of implicit and explicit semantic processing manipulations on episodic memory in SZ. Thirty SZ and 30 demographically matched healthy controls (HC) studied Deese/Roediger-McDermott (DRM) lists of semantically associated words. Half of the lists had strong implicit semantic associations and the remainder had low strength associations. Similarly, half of the lists were presented under "standard" instructions and the other half under explicit "relational processing" instructions. After study, participants performed recall and old/new recognition tests composed of targets, critical lures, and unrelated lures. HC exhibited higher true memories and better discriminability between true and false memory compared to SZ. High, versus low, associative strength increased false memory rates in both groups. However, explicit "relational processing" instructions positively improved true memory rates only in HC. Finally, true and false memory rates were associated with severity of disorganized and negative symptoms in SZ. These results suggest that reduced processing of semantic relationships during encoding in SZ may stem from an inability to implement explicit relational processing strategies rather than a fundamental deficit in the implicit activation and retrieval of word meanings from patients' semantic lexicon. Copyright © 2013 Elsevier B.V. All rights reserved.

Modulation of the N400 component in relation to hypomanic personality traits in a word meaning ambiguity resolution task.

PubMed

Raucher-Chéné, Delphine; Terrien, Sarah; Gobin, Pamela; Gierski, Fabien; Kaladjian, Arthur; Besche-Richard, Chrystel

2017-09-01

High levels of hypomanic personality traits have been associated with an increased risk of developing bipolar disorder (BD). Changes in semantic content, impaired verbal associations, abnormal prosody, and abnormal speed of language are core features of BD, and are thought to be related to semantic processing abnormalities. In the present study, we used event-related potentials to investigate the relation between semantic processing (N400 component) and hypomanic personality traits. We assessed 65 healthy young adults on the Hypomanic Personality Scale (HPS). Event-related potentials were recorded during a semantic ambiguity resolution task exploring semantic ambiguity (polysemous word ending a sentence) and congruency (target word semantically related to the sentence). As expected, semantic ambiguity and congruency both elicited an N400 effect across our sample. Correlation analyses showed a significant positive relationship between the Social Vitality subscore of the HPS and N400 modulation in the frontal region of interest in the incongruent unambiguous condition, and in the frontocentral region of interest in the incongruent ambiguous condition. We found differences in semantic processing (i.e., detection of incongruence and semantic inhibition) in individuals with higher Social Vitality subscores. In the light of the literature, we discuss the notion that a semantic processing impairment could be a potential marker of vulnerability to BD, and one that needs to be explored further in this clinical population. © 2017 The Authors. Psychiatry and Clinical Neurosciences © 2017 Japanese Society of Psychiatry and Neurology.

What lies beneath: A comparison of reading aloud in pure alexia and semantic dementia

PubMed Central

Hoffman, Paul; Roberts, Daniel J.; Ralph, Matthew A. Lambon; Patterson, Karalyn E.

2014-01-01

Exaggerated effects of word length upon reading-aloud performance define pure alexia, but have also been observed in semantic dementia. Some researchers have proposed a reading-specific account, whereby performance in these two disorders reflects the same cause: impaired orthographic processing. In contrast, according to the primary systems view of acquired reading disorders, pure alexia results from a basic visual processing deficit, whereas degraded semantic knowledge undermines reading performance in semantic dementia. To explore the source of reading deficits in these two disorders, we compared the reading performance of 10 pure alexic and 10 semantic dementia patients, matched in terms of overall severity of reading deficit. The results revealed comparable frequency effects on reading accuracy, but weaker effects of regularity in pure alexia than in semantic dementia. Analysis of error types revealed a higher rate of letter-based errors and a lower rate of regularization responses in pure alexia than in semantic dementia. Error responses were most often words in pure alexia but most often nonwords in semantic dementia. Although all patients made some letter substitution errors, these were characterized by visual similarity in pure alexia and phonological similarity in semantic dementia. Overall, the data indicate that the reading deficits in pure alexia and semantic dementia arise from impairments of visual processing and knowledge of word meaning, respectively. The locus and mechanisms of these impairments are placed within the context of current connectionist models of reading. PMID:24702272

Affective Priming in a Lexical Decision Task: Is There an Effect of Words' Concreteness?

ERIC Educational Resources Information Center

Ferré, Pilar; Sánchez-Casas, Rosa

2014-01-01

Affective priming occurs when responses to a target are facilitated when it is preceded by a prime congruent in valence. We conducted two experiments in order to test whether this is a genuine emotional effect or rather it can be accounted for by semantic relatedness between primes and targets. With this aim, semantic relatedness and emotional…

Enacting the Semantic Web: Ontological Orderings, Negotiated Standards, and Human-Machine Translations

ERIC Educational Resources Information Center

McCarthy, Matthew T.

2017-01-01

Artificial intelligence (AI) that is based upon semantic search has become one of the dominant means for accessing information in recent years. This is particularly the case in mobile contexts, as search-based AI are embedded in each of the major mobile operating systems. The implications are such that information is becoming less a matter of…

A Metadata Model for E-Learning Coordination through Semantic Web Languages

ERIC Educational Resources Information Center

Elci, Atilla

2005-01-01

This paper reports on a study aiming to develop a metadata model for e-learning coordination based on semantic web languages. A survey of e-learning modes are done initially in order to identify content such as phases, activities, data schema, rules and relations, etc. relevant for a coordination model. In this respect, the study looks into the…

Basic level scene understanding: categories, attributes and structures

PubMed Central

Xiao, Jianxiong; Hays, James; Russell, Bryan C.; Patterson, Genevieve; Ehinger, Krista A.; Torralba, Antonio; Oliva, Aude

2013-01-01

A longstanding goal of computer vision is to build a system that can automatically understand a 3D scene from a single image. This requires extracting semantic concepts and 3D information from 2D images which can depict an enormous variety of environments that comprise our visual world. This paper summarizes our recent efforts toward these goals. First, we describe the richly annotated SUN database which is a collection of annotated images spanning 908 different scene categories with object, attribute, and geometric labels for many scenes. This database allows us to systematically study the space of scenes and to establish a benchmark for scene and object recognition. We augment the categorical SUN database with 102 scene attributes for every image and explore attribute recognition. Finally, we present an integrated system to extract the 3D structure of the scene and objects depicted in an image. PMID:24009590

Attention to Semantic versus Phonetic Verbal Attributes as a Function of Individual Differences in Arousal and Learning Strategy.

ERIC Educational Resources Information Center

Schmeck, Ronald R; Spofford, Mark

1982-01-01

An investigation was undertaken to determine whether highly aroused (e.g. highly anxious) students are handicapped with regard to their ability to learn through deep processing and elaboration. The hypothesis that well-developed deep and elaborative habits of thought might counteract the disruptive effects that excessive arousal has upon students…

Does Truth Exist? Insights from Applied Linguistics for the Rationalism/Postmodern Debate

ERIC Educational Resources Information Center

Ross, David A.

2008-01-01

The question of whether or not truth exists is at the center of the rationalism versus postmodern debate. Noting the difficulty of defining truth, the author uses the principles of linguistics to show that semantic skewing has resulted in the concept of truth being encoded as a noun, while it is really an attribute (true). The introduction of a…

Generation and context memory.

PubMed

Mulligan, Neil W; Lozito, Jeffrey P; Rosner, Zachary A

2006-07-01

Generation enhances memory for occurrence but may not enhance other aspects of memory. The present study further delineates the negative generation effect in context memory reported in N. W. Mulligan (2004). First, the negative generation effect occurred for perceptual attributes of the target item (its color and font) but not for extratarget aspects of context (location and background color). Second, nonvisual generation tasks with either semantic or nonsemantic generation rules (antonym and rhyme generation, respectively) produced the same pattern of results. In contrast, a visual (or data-driven) generation task (letter transposition) did not disrupt context memory for color. Third, generating nonwords produced no effect on item memory but persisted in producing a negative effect on context memory for target attributes, implying that (a) the negative generation effect in context memory is not mediated by semantic encoding, and (b) the negative effect on context memory can be dissociated from the positive effect on item memory. The results are interpreted in terms of the processing account of generation. The original, perceptual-conceptual version of this account is too narrow, but a modified processing account, based on a more generic visual versus nonvisual processing distinction, accommodates the results. Copyright 2006 APA, all rights reserved.

Terminological aspects of data elements

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

Strehlow, R.A.; Kenworthey, W.H. Jr.; Schuldt, R.E.

1991-01-01

The creation and display of data comprise a process that involves a sequence of steps requiring both semantic and systems analysis. An essential early step in this process is the choice, definition, and naming of data element concepts and is followed by the specification of other needed data element concept attributes. The attributes and the values of data element concept remain associated with them from their birth as a concept to a generic data element that serves as a template for final application. Terminology is, therefore, centrally important to the entire data creation process. Smooth mapping from natural language tomore » a database is a critical aspect of database, and consequently, it requires terminology standardization from the outset of database work. In this paper the semantic aspects of data elements are analyzed and discussed. Seven kinds of data element concept information are considered and those that require terminological development and standardization are identified. The four terminological components of a data element are the hierarchical type of a concept, functional dependencies, schematas showing conceptual structures, and definition statements. These constitute the conventional role of terminology in database design. 12 refs., 8 figs., 1 tab.« less

Disruption of Semantic Network in Mild Alzheimer’s Disease Revealed by Resting-State fMRI

PubMed Central

Mascali, Daniele; DiNuzzo, Mauro; Serra, Laura; Mangia, Silvia; Maraviglia, Bruno; Bozzali, Marco; Giove, Federico

2018-01-01

Subtle semantic deficits can be observed in Alzheimer’s disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke’s area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing. PMID:29197559

Differentiation of perceptual and semantic subsequent memory effects using an orthographic paradigm.

PubMed

Kuo, Michael C C; Liu, Karen P Y; Ting, Kin Hung; Chan, Chetwyn C H

2012-11-27

This study aimed to differentiate perceptual and semantic encoding processes using subsequent memory effects (SMEs) elicited by the recognition of orthographs of single Chinese characters. Participants studied a series of Chinese characters perceptually (by inspecting orthographic components) or semantically (by determining the object making sounds), and then made studied or unstudied judgments during the recognition phase. Recognition performance in terms of d-prime measure in the semantic condition was higher, though not significant, than that of the perceptual condition. The between perceptual-semantic condition differences in SMEs at P550 and late positive component latencies (700-1000ms) were not significant in the frontal area. An additional analysis identified larger SME in the semantic condition during 600-1000ms in the frontal pole regions. These results indicate that coordination and incorporation of orthographic information into mental representation is essential to both task conditions. The differentiation was also revealed in earlier SMEs (perceptual>semantic) at N3 (240-360ms) latency, which is a novel finding. The left-distributed N3 was interpreted as more efficient processing of meaning with semantically learned characters. Frontal pole SMEs indicated strategic processing by executive functions, which would further enhance memory. Copyright © 2012 Elsevier B.V. All rights reserved.

Effect of perceptual load on semantic access by speech in children.

PubMed

Jerger, Susan; Damian, Markus F; Mills, Candice; Bartlett, James; Tye-Murray, Nancy; Abdi, Hervé

2013-04-01

To examine whether semantic access by speech requires attention in children. Children (N = 200) named pictures and ignored distractors on a cross-modal (distractors: auditory-no face) or multimodal (distractors: auditory-static face and audiovisual-dynamic face) picture word task. The cross-modal task had a low load, and the multimodal task had a high load (i.e., respectively naming pictures displayed on a blank screen vs. below the talker's face on his T-shirt). Semantic content of distractors was manipulated to be related vs. unrelated to the picture (e.g., picture "dog" with distractors "bear" vs. "cheese"). If irrelevant semantic content manipulation influences naming times on both tasks despite variations in loads, Lavie's (2005) perceptual load model proposes that semantic access is independent of capacity-limited attentional resources; if, however, irrelevant content influences naming only on the cross-modal task (low load), the perceptual load model proposes that semantic access is dependent on attentional resources exhausted by the higher load task. Irrelevant semantic content affected performance for both tasks in 6- to 9-year-olds but only on the cross-modal task in 4- to 5-year-olds. The addition of visual speech did not influence results on the multimodal task. Younger and older children differ in dependence on attentional resources for semantic access by speech.

Does semantic preactivation reduce inattentional blindness?

PubMed

Kreitz, Carina; Schnuerch, Robert; Furley, Philip A; Gibbons, Henning; Memmert, Daniel

2015-04-01

We are susceptible to failures of awareness if a stimulus occurs unexpectedly and our attention is focused elsewhere. Such inattentional blindness is modulated by various parameters, including stimulus attributes, the observer's cognitive resources, and the observer's attentional set regarding the primary task. In three behavioral experiments with a total of 360 participants, we investigated whether mere semantic preactivation of the color of an unexpected object can reduce inattentional blindness. Neither explicitly mentioning the color several times before the occurrence of the unexpected stimulus nor priming the color more implicitly via color-related concepts could significantly reduce the susceptibility to inattentional blindness. Even putting the specific color concept in the main focus of the primary task did not lead to reduced inattentional blindness. Thus, we have shown that the failure to consciously perceive unexpected objects was not moderated by semantic preactivation of the objects' most prominent feature: its color. We suggest that this finding reflects the rather general principle that preactivations that are not motivationally relevant for one's current selection goals do not suffice to make an unexpected object overcome the threshold of awareness.

Levels-Of-Processing Effect on Word Recognition in Schizophrenia

PubMed Central

Ragland, J. Daniel; Moelter, Stephen T.; McGrath, Claire; Hill, S. Kristian; Gur, Raquel E.; Bilker, Warren B.; Siegel, Steven J.; Gur, Ruben C.

2015-01-01

Background Individuals with schizophrenia have difficulty organizing words semantically to facilitate encoding. This is commonly attributed to organizational rather than semantic processing limitations. By requiring participants to classify and encode words on either a shallow (e.g., uppercase/lowercase) or deep level (e.g., concrete/abstract), the levels-of-processing paradigm eliminates the need to generate organizational strategies. Methods This paradigm was administered to 30 patients with schizophrenia and 30 healthy comparison subjects to test whether providing a strategy would improve patient performance. Results Word classification during shallow and deep encoding was slower and less accurate in patients. Patients also responded slowly during recognition testing and maintained a more conservative response bias following deep encoding; however, both groups showed a robust levels-of-processing effect on recognition accuracy, with unimpaired patient performance following both shallow and deep encoding. Conclusions This normal levels-of-processing effect in the patient sample suggests that semantic processing is sufficiently intact for patients to benefit from organizational cues. Memory remediation efforts may therefore be most successful if they focus on teaching patients to form organizational strategies during initial encoding. PMID:14643082

Ontology patterns for complex topographic feature yypes

USGS Publications Warehouse

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Levels-of-processing effect on word recognition in schizophrenia.

PubMed

Ragland, J Daniel; Moelter, Stephen T; McGrath, Claire; Hill, S Kristian; Gur, Raquel E; Bilker, Warren B; Siegel, Steven J; Gur, Ruben C

2003-12-01

Individuals with schizophrenia have difficulty organizing words semantically to facilitate encoding. This is commonly attributed to organizational rather than semantic processing limitations. By requiring participants to classify and encode words on either a shallow (e.g., uppercase/lowercase) or deep level (e.g., concrete/abstract), the levels-of-processing paradigm eliminates the need to generate organizational strategies. This paradigm was administered to 30 patients with schizophrenia and 30 healthy comparison subjects to test whether providing a strategy would improve patient performance. Word classification during shallow and deep encoding was slower and less accurate in patients. Patients also responded slowly during recognition testing and maintained a more conservative response bias following deep encoding; however, both groups showed a robust levels-of-processing effect on recognition accuracy, with unimpaired patient performance following both shallow and deep encoding. This normal levels-of-processing effect in the patient sample suggests that semantic processing is sufficiently intact for patients to benefit from organizational cues. Memory remediation efforts may therefore be most successful if they focus on teaching patients to form organizational strategies during initial encoding.

A Semantic Transformation Methodology for the Secondary Use of Observational Healthcare Data in Postmarketing Safety Studies.

PubMed

Pacaci, Anil; Gonul, Suat; Sinaci, A Anil; Yuksel, Mustafa; Laleci Erturkmen, Gokce B

2018-01-01

Background: Utilization of the available observational healthcare datasets is key to complement and strengthen the postmarketing safety studies. Use of common data models (CDM) is the predominant approach in order to enable large scale systematic analyses on disparate data models and vocabularies. Current CDM transformation practices depend on proprietarily developed Extract-Transform-Load (ETL) procedures, which require knowledge both on the semantics and technical characteristics of the source datasets and target CDM. Purpose: In this study, our aim is to develop a modular but coordinated transformation approach in order to separate semantic and technical steps of transformation processes, which do not have a strict separation in traditional ETL approaches. Such an approach would discretize the operations to extract data from source electronic health record systems, alignment of the source, and target models on the semantic level and the operations to populate target common data repositories. Approach: In order to separate the activities that are required to transform heterogeneous data sources to a target CDM, we introduce a semantic transformation approach composed of three steps: (1) transformation of source datasets to Resource Description Framework (RDF) format, (2) application of semantic conversion rules to get the data as instances of ontological model of the target CDM, and (3) population of repositories, which comply with the specifications of the CDM, by processing the RDF instances from step 2. The proposed approach has been implemented on real healthcare settings where Observational Medical Outcomes Partnership (OMOP) CDM has been chosen as the common data model and a comprehensive comparative analysis between the native and transformed data has been conducted. Results: Health records of ~1 million patients have been successfully transformed to an OMOP CDM based database from the source database. Descriptive statistics obtained from the source and target databases present analogous and consistent results. Discussion and Conclusion: Our method goes beyond the traditional ETL approaches by being more declarative and rigorous. Declarative because the use of RDF based mapping rules makes each mapping more transparent and understandable to humans while retaining logic-based computability. Rigorous because the mappings would be based on computer readable semantics which are amenable to validation through logic-based inference methods.

When does word meaning affect immediate serial recall in semantic dementia?

PubMed

Jefferies, Elizabeth; Jones, Roy; Bateman, David; Ralph, Matthew A Lambon

2004-03-01

Patients with semantic dementia can show superior immediate recall of words that they still understand relatively well, as compared with more semantically degraded words, suggesting that conceptual knowledge makes a major contribution to phonological short-term memory. However, a number of studies have failed to show such a recall difference, challenging this view. We examined the effect of several methodological factors on the recall of known and degraded words in 4 patients with semantic dementia, in order to investigate possible reasons for this discrepancy. In general, our patients did exhibit poorer recall of the degraded words and made more phonological errors on these items. In addition, set size affected the magnitude of the recall advantage for known words. This finding suggests that semantic degradation influenced the rate of learning in the immediate recall task when the same items were presented repeatedly. The methods used to select known and degraded items also impacted on the recall difference. List length, however, did not affect the advantage for known words. The coherence of items in phonological short-term memory was affected by their semantic status, but not by the length of the material to be retained. The implications of these findings for the role of semantic and phonological representations in verbal short-term memory are discussed.

Lifting Events in RDF from Interactions with Annotated Web Pages

NASA Astrophysics Data System (ADS)

Stühmer, Roland; Anicic, Darko; Sen, Sinan; Ma, Jun; Schmidt, Kay-Uwe; Stojanovic, Nenad

In this paper we present a method and an implementation for creating and processing semantic events from interaction with Web pages which opens possibilities to build event-driven applications for the (Semantic) Web. Events, simple or complex, are models for things that happen e.g., when a user interacts with a Web page. Events are consumed in some meaningful way e.g., for monitoring reasons or to trigger actions such as responses. In order for receiving parties to understand events e.g., comprehend what has led to an event, we propose a general event schema using RDFS. In this schema we cover the composition of complex events and event-to-event relationships. These events can then be used to route semantic information about an occurrence to different recipients helping in making the Semantic Web active. Additionally, we present an architecture for detecting and composing events in Web clients. For the contents of events we show a way of how they are enriched with semantic information about the context in which they occurred. The paper is presented in conjunction with the use case of Semantic Advertising, which extends traditional clickstream analysis by introducing semantic short-term profiling, enabling discovery of the current interest of a Web user and therefore supporting advertisement providers in responding with more relevant advertisements.

Semantic Segmentation of Indoor Point Clouds Using Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Babacan, K.; Chen, L.; Sohn, G.

2017-11-01

As Building Information Modelling (BIM) thrives, geometry becomes no longer sufficient; an ever increasing variety of semantic information is needed to express an indoor model adequately. On the other hand, for the existing buildings, automatically generating semantically enriched BIM from point cloud data is in its infancy. The previous research to enhance the semantic content rely on frameworks in which some specific rules and/or features that are hand coded by specialists. These methods immanently lack generalization and easily break in different circumstances. On this account, a generalized framework is urgently needed to automatically and accurately generate semantic information. Therefore we propose to employ deep learning techniques for the semantic segmentation of point clouds into meaningful parts. More specifically, we build a volumetric data representation in order to efficiently generate the high number of training samples needed to initiate a convolutional neural network architecture. The feedforward propagation is used in such a way to perform the classification in voxel level for achieving semantic segmentation. The method is tested both for a mobile laser scanner point cloud, and a larger scale synthetically generated data. We also demonstrate a case study, in which our method can be effectively used to leverage the extraction of planar surfaces in challenging cluttered indoor environments.

UltiMatch-NL: A Web Service Matchmaker Based on Multiple Semantic Filters

PubMed Central

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters. PMID:25157872

UltiMatch-NL: a Web service matchmaker based on multiple semantic filters.

PubMed

Mohebbi, Keyvan; Ibrahim, Suhaimi; Zamani, Mazdak; Khezrian, Mojtaba

2014-01-01

In this paper, a Semantic Web service matchmaker called UltiMatch-NL is presented. UltiMatch-NL applies two filters namely Signature-based and Description-based on different abstraction levels of a service profile to achieve more accurate results. More specifically, the proposed filters rely on semantic knowledge to extract the similarity between a given pair of service descriptions. Thus it is a further step towards fully automated Web service discovery via making this process more semantic-aware. In addition, a new technique is proposed to weight and combine the results of different filters of UltiMatch-NL, automatically. Moreover, an innovative approach is introduced to predict the relevance of requests and Web services and eliminate the need for setting a threshold value of similarity. In order to evaluate UltiMatch-NL, the repository of OWLS-TC is used. The performance evaluation based on standard measures from the information retrieval field shows that semantic matching of OWL-S services can be significantly improved by incorporating designed matching filters.

The general/specific breakdown of semantic memory and the nature of superordinate knowledge: insights from superordinate and basic-level feature norms.

PubMed

Marques, J Frederico

2007-12-01

The deterioration of semantic memory usually proceeds from more specific to more general superordinate categories, although rarer cases of superordinate knowledge impairment have also been reported. The nature of superordinate knowledge and the explanation of these two semantic impairments were evaluated from the analysis of superordinate and basic-level feature norms. The results show that, in comparison to basic-level concepts, superordinate concepts are not generally less informative and have similar feature distinctiveness and proportion of individual sensory features, but their features are less shared by their members. Results are in accord with explanations based on feature connection weights and/or concept confusability for the superordinate advantage cases. Results especially support an explanation for superordinate impairments in terms of higher semantic control requirements as related to features being less shared between concept members. Implications for patients with semantic impairments are also discussed.

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

PubMed Central

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as ‘CHEMICAL-1 compared to CHEMICAL-2.’ With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical–disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order covering diverse bio-entity relations. To assess the potential utility of our automated top-ranked patterns of a given relation in semantic search, we performed a pilot study on frequently sought semantic relations in PubMed and observed improved literature retrieval effectiveness based on post-hoc human relevance evaluation. Further investigation in larger tests and in real-world scenarios is warranted. PMID:27016698

False memories in children and adults: age, distinctiveness, and subjective experience.

PubMed

Ghetti, Simona; Qin, Jianjian; Goodman, Gail S

2002-09-01

This study investigated developmental trends associated with the Deese/Roediger-McDermott false-memory effect, the role of distinctive information in false-memory formation, and participants' subjective experience of true and false memories. Children (5- and 7-year-olds) and adults studied lists of semantically associated words. Half of the participants studied words alone, and half studied words accompanied by pictures. There were significant age differences in recall (5-year-olds evinced more false memories than did adults) but not in recognition of critical lures. Distinctive information reduced false memory for all age groups. Younger children provided with distinctive information, and older children and adults regardless of whether they viewed distinctive information, expressed higher levels of confidence in true than in false memories. Source attributions did not significantly differ between true and false memories. Implications for theories of false memory and memory development are discussed.

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

PubMed

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 confounding of content, structure, and presentation. SSWAP is novel by establishing the concept of a canonical yet mutable OWL DL graph that allows data and service providers to describe their resources, to allow discovery servers to offer semantically rich search engines, to allow clients to discover and invoke those resources, and to allow providers to respond with semantically tagged data. SSWAP allows for a mix-and-match of terms from both new and legacy third-party ontologies in these graphs.

Interconnected growing self-organizing maps for auditory and semantic acquisition modeling

PubMed Central

Cao, Mengxue; Li, Aijun; Fang, Qiang; Kaufmann, Emily; Kröger, Bernd J.

2014-01-01

Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM) algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic–semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners. A reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1) I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2) clear auditory and semantic boundaries can be found in the network representation; (3) cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4) reinforcing-by-link training leads to well-perceived auditory–semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model. PMID:24688478

Supporting Student Research with Semantic Technologies and Digital Archives

ERIC Educational Resources Information Center

Martinez-Garcia, Agustina; Corti, Louise

2012-01-01

This article discusses how the idea of higher education students as producers of knowledge rather than consumers can be operationalised by means of student research projects, in which processes of research archiving and analysis are enabled through the use of semantic technologies. It discusses how existing digital repository frameworks can be…

Semantic-syntactic partial word knowledge growth through reading.

PubMed

Wagovich, Stacy A; Hill, Margaret S; Petroski, Gregory F

2015-02-01

Incidental reading provides a powerful opportunity for partial word knowledge growth in the school-age years. The extent to which children of differing language abilities can use reading experiences to glean partial knowledge of words is not well understood. The purpose of this study was to compare semantic-syntactic partial word knowledge growth of children with higher language skills (HL group; overall language standard scores of 85 or higher) to that of children with relatively lower language skills (LL group; overall receptive or expressive standard score below 85). Thirty-two children, 16 per group, silently read stories containing unfamiliar nouns and verbs 3 times over a 1-week period. Semantic-syntactic partial word knowledge growth was assessed after each reading and 2-3 days later to assess retention. Over time, both groups showed significant partial word knowledge growth, with the HL group showing significantly more growth. In addition, both groups retained knowledge several days later. Regardless of language skill level, children benefit from multiple exposures to unfamiliar words in reading in their development and retention of semantic-syntactic partial word knowledge growth.

Lower- and higher-level models of right hemisphere language. A selective survey.

PubMed

Gainotti, Guido

2016-01-01

The models advanced to explain right hemisphere (RH) language function can be divided into two main types. According to the older (lower-level) models, RH language reflects the ontogenesis of conceptual and semantic-lexical development; the more recent models, on the other hand, suggest that the RH plays an important role in the use of higher-level language functions, such as metaphors, to convey complex, abstract concepts. The hypothesis that the RH may be preferentially involved in processing the semantic-lexical components of language was advanced by Zaidel in splitbrain patients and his model was confirmed by neuropsychological investigations, proving that right brain-damaged patients show selective semanticlexical disorders. The possible links between lower and higher levels of RH language are discussed, as is the hypothesis that the RH may have privileged access to the figurative aspects of novel metaphorical expressions, whereas conventionalization of metaphorical meaning could be a bilaterally-mediated process involving abstract semantic-lexical codes.

Only time will tell - why temporal information is essential for our neuroscientific understanding of semantics.

PubMed

Hauk, Olaf

2016-08-01

Theoretical developments about the nature of semantic representations and processes should be accompanied by a discussion of how these theories can be validated on the basis of empirical data. Here, I elaborate on the link between theory and empirical research, highlighting the need for temporal information in order to distinguish fundamental aspects of semantics. The generic point that fast cognitive processes demand fast measurement techniques has been made many times before, although arguably more often in the psychophysiological community than in the metabolic neuroimaging community. Many reviews on the neuroscience of semantics mostly or even exclusively focus on metabolic neuroimaging data. Following an analysis of semantics in terms of the representations and processes involved, I argue that fundamental theoretical debates about the neuroscience of semantics can only be concluded on the basis of data with sufficient temporal resolution. Any "semantic effect" may result from a conflation of long-term memory representations, retrieval and working memory processes, mental imagery, and episodic memory. This poses challenges for all neuroimaging modalities, but especially for those with low temporal resolution. It also throws doubt on the usefulness of contrasts between meaningful and meaningless stimuli, which may differ on a number of semantic and non-semantic dimensions. I will discuss the consequences of this analysis for research on the role of convergence zones or hubs and distributed modal brain networks, top-down modulation of task and context as well as interactivity between levels of the processing hierarchy, for example in the framework of predictive coding.

The New Challenges for E-learning: The Educational Semantic Web

ERIC Educational Resources Information Center

Aroyo, Lora; Dicheva, Darina

2004-01-01

The big question for many researchers in the area of educational systems now is what is the next step in the evolution of e-learning? Are we finally moving from a scattered intelligence to a coherent space of collaborative intelligence? How close we are to the vision of the Educational Semantic Web and what do we need to do in order to realize it?…

Are Historic Years Understood as Numbers or Events? An fMRI Study of Numbers with Semantic Associations

ERIC Educational Resources Information Center

Gullick, Margaret M.; Temple, Elise

2011-01-01

While numbers generally cue processing of quantity or order, they can also contain semantic information, as in the case of historic years (e.g., "1492" calls forth associations of Columbus sailing the ocean blue). Whether these dates are processed as quantities or events may depend on the context in which they occur. We examined such "ambiguous…

Verbal Semantics Drives Early Anticipatory Eye Movements during the Comprehension of Verb-Initial Sentences.

PubMed

Sauppe, Sebastian

2016-01-01

Studies on anticipatory processes during sentence comprehension often focus on the prediction of postverbal direct objects. In subject-initial languages (the target of most studies so far), however, the position in the sentence, the syntactic function, and the semantic role of arguments are often conflated. For example, in the sentence "The frog will eat the fly" the syntactic object ("fly") is at the same time also the last word and the patient argument of the verb. It is therefore not apparent which kind of information listeners orient to for predictive processing during sentence comprehension. A visual world eye tracking study on the verb-initial language Tagalog (Austronesian) tested what kind of information listeners use to anticipate upcoming postverbal linguistic input. The grammatical structure of Tagalog allows to test whether listeners' anticipatory gaze behavior is guided by predictions of the linear order of words, by syntactic functions (e.g., subject/object), or by semantic roles (agent/patient). Participants heard sentences of the type "Eat frog fly" or "Eat fly frog" (both meaning "The frog will eat the fly") while looking at displays containing an agent referent ("frog"), a patient referent ("fly") and a distractor. The verb carried morphological marking that allowed the order and syntactic function of agent and patient to be inferred. After having heard the verb, listeners fixated on the agent irrespective of its syntactic function or position in the sentence. While hearing the first-mentioned argument, listeners fixated on the corresponding referent in the display accordingly and then initiated saccades to the last-mentioned referent before it was encountered. The results indicate that listeners used verbal semantics to identify referents and their semantic roles early; information about word order or syntactic functions did not influence anticipatory gaze behavior directly after the verb was heard. In this verb-initial language, event semantics takes early precedence during the comprehension of sentences, while arguments are anticipated temporally more local to when they are encountered. The current experiment thus helps to better understand anticipation during language processing by employing linguistic structures not available in previously studied subject-initial languages.

Free-Form Region Description with Second-Order Pooling.

PubMed

Carreira, João; Caseiro, Rui; Batista, Jorge; Sminchisescu, Cristian

2015-06-01

Semantic segmentation and object detection are nowadays dominated by methods operating on regions obtained as a result of a bottom-up grouping process (segmentation) but use feature extractors developed for recognition on fixed-form (e.g. rectangular) patches, with full images as a special case. This is most likely suboptimal. In this paper we focus on feature extraction and description over free-form regions and study the relationship with their fixed-form counterparts. Our main contributions are novel pooling techniques that capture the second-order statistics of local descriptors inside such free-form regions. We introduce second-order generalizations of average and max-pooling that together with appropriate non-linearities, derived from the mathematical structure of their embedding space, lead to state-of-the-art recognition performance in semantic segmentation experiments without any type of local feature coding. In contrast, we show that codebook-based local feature coding is more important when feature extraction is constrained to operate over regions that include both foreground and large portions of the background, as typical in image classification settings, whereas for high-accuracy localization setups, second-order pooling over free-form regions produces results superior to those of the winning systems in the contemporary semantic segmentation challenges, with models that are much faster in both training and testing.

SCALEUS: Semantic Web Services Integration for Biomedical Applications.

PubMed

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

2017-04-01

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

What role does the anterior temporal lobe play in sentence-level processing? Neural correlates of syntactic processing in semantic variant primary progressive aphasia.

PubMed

Wilson, Stephen M; DeMarco, Andrew T; Henry, Maya L; Gesierich, Benno; Babiak, Miranda; Mandelli, Maria Luisa; Miller, Bruce L; Gorno-Tempini, Maria Luisa

2014-05-01

Neuroimaging and neuropsychological studies have implicated the anterior temporal lobe (ATL) in sentence-level processing, with syntactic structure-building and/or combinatorial semantic processing suggested as possible roles. A potential challenge to the view that the ATL is involved in syntactic aspects of sentence processing comes from the clinical syndrome of semantic variant primary progressive aphasia (semantic PPA; also known as semantic dementia). In semantic PPA, bilateral neurodegeneration of the ATLs is associated with profound lexical semantic deficits, yet syntax is strikingly spared. The goal of this study was to investigate the neural correlates of syntactic processing in semantic PPA to determine which regions normally involved in syntactic processing are damaged in semantic PPA and whether spared syntactic processing depends on preserved functionality of intact regions, preserved functionality of atrophic regions, or compensatory functional reorganization. We scanned 20 individuals with semantic PPA and 24 age-matched controls using structural MRI and fMRI. Participants performed a sentence comprehension task that emphasized syntactic processing and minimized lexical semantic demands. We found that, in controls, left inferior frontal and left posterior temporal regions were modulated by syntactic processing, whereas anterior temporal regions were not significantly modulated. In the semantic PPA group, atrophy was most severe in the ATLs but extended to the posterior temporal regions involved in syntactic processing. Functional activity for syntactic processing was broadly similar in patients and controls; in particular, whole-brain analyses revealed no significant differences between patients and controls in the regions modulated by syntactic processing. The atrophic left ATL did show abnormal functionality in semantic PPA patients; however, this took the unexpected form of a failure to deactivate. Taken together, our findings indicate that spared syntactic processing in semantic PPA depends on preserved functionality of structurally intact left frontal regions and moderately atrophic left posterior temporal regions, but no functional reorganization was apparent as a consequence of anterior temporal atrophy and dysfunction. These results suggest that the role of the ATL in sentence processing is less likely to relate to syntactic structure-building and more likely to relate to higher-level processes such as combinatorial semantic processing.

Semantic Feature Training in Combination with Transcranial Direct Current Stimulation (tDCS) for Progressive Anomia

PubMed Central

Hung, Jinyi; Bauer, Ashley; Grossman, Murray; Hamilton, Roy H.; Coslett, H. B.; Reilly, Jamie

2017-01-01

We examined the effectiveness of a 2-week regimen of a semantic feature training in combination with transcranial direct current stimulation (tDCS) for progressive naming impairment associated with primary progressive aphasia (N = 4) or early onset Alzheimer’s Disease (N = 1). Patients received a 2-week regimen (10 sessions) of anodal tDCS delivered over the left temporoparietal cortex while completing a language therapy that consisted of repeated naming and semantic feature generation. Therapy targets consisted of familiar people, household items, clothes, foods, places, hygiene implements, and activities. Untrained items from each semantic category provided item level controls. We analyzed naming accuracies at multiple timepoints (i.e., pre-, post-, 6-month follow-up) via a mixed effects logistic regression and individual differences in treatment responsiveness using a series of non-parametric McNemar tests. Patients showed advantages for naming trained over untrained items. These gains were evident immediately post tDCS. Trained items also showed a shallower rate of decline over 6-months relative to untrained items that showed continued progressive decline. Patients tolerated stimulation well, and sustained improvements in naming accuracy suggest that the current intervention approach is viable. Future implementation of a sham control condition will be crucial toward ascertaining whether neurostimulation and behavioral treatment act synergistically or alternatively whether treatment gains are exclusively attributable to either tDCS or the behavioral intervention. PMID:28559805

A Critical Review on the Use of Support Values in Tree Viewers and Bioinformatics Toolkits.

PubMed

Czech, Lucas; Huerta-Cepas, Jaime; Stamatakis, Alexandros

2017-06-01

Phylogenetic trees are routinely visualized to present and interpret the evolutionary relationships of species. Most empirical evolutionary data studies contain a visualization of the inferred tree with branch support values. Ambiguous semantics in tree file formats can lead to erroneous tree visualizations and therefore to incorrect interpretations of phylogenetic analyses. Here, we discuss problems that arise when displaying branch values on trees after rerooting. Branch values are typically stored as node labels in the widely-used Newick tree format. However, such values are attributes of branches. Storing them as node labels can therefore yield errors when rerooting trees. This depends on the mostly implicit semantics that tools deploy to interpret node labels. We reviewed ten tree viewers and ten bioinformatics toolkits that can display and reroot trees. We found that 14 out of 20 of these tools do not permit users to select the semantics of node labels. Thus, unaware users might obtain incorrect results when rooting trees. We illustrate such incorrect mappings for several test cases and real examples taken from the literature. This review has already led to improvements in eight tools. We suggest tools should provide options that explicitly force users to define the semantics of node labels. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Spicy Adjectives and Nominal Donkeys: Capturing Semantic Deviance Using Compositionality in Distributional Spaces.

PubMed

Vecchi, Eva M; Marelli, Marco; Zamparelli, Roberto; Baroni, Marco

2017-01-01

Sophisticated senator and legislative onion. Whether or not you have ever heard of these things, we all have some intuition that one of them makes much less sense than the other. In this paper, we introduce a large dataset of human judgments about novel adjective-noun phrases. We use these data to test an approach to semantic deviance based on phrase representations derived with compositional distributional semantic methods, that is, methods that derive word meanings from contextual information, and approximate phrase meanings by combining word meanings. We present several simple measures extracted from distributional representations of words and phrases, and we show that they have a significant impact on predicting the acceptability of novel adjective-noun phrases even when a number of alternative measures classically employed in studies of compound processing and bigram plausibility are taken into account. Our results show that the extent to which an attributive adjective alters the distributional representation of the noun is the most significant factor in modeling the distinction between acceptable and deviant phrases. Our study extends current applications of compositional distributional semantic methods to linguistically and cognitively interesting problems, and it offers a new, quantitatively precise approach to the challenge of predicting when humans will find novel linguistic expressions acceptable and when they will not. Copyright © 2016 Cognitive Science Society, Inc.

Sculpting the UMLS Refined Semantic Network

PubMed Central

Morrey, C. Paul; Perl, Yehoshua; Elhanan, Gai; Chen, Ling; Chen, Yan; Geller, James

2014-01-01

Background The Refined Semantic Network (RSN) for the UMLS was previously introduced to complement the UMLS Semantic Network (SN). The RSN partitions the UMLS Metathesaurus (META) into disjoint groups of concepts. Each such group is semantically uniform. However, the RSN was initially an order of magnitude larger than the SN, which is undesirable since to be useful, a semantic network should be compact. Most semantic types in the RSN represent combinations of semantic types in the UMLS SN. Such a “combination semantic type” is called Intersection Semantic Type (IST). Many ISTs are assigned to very few concepts. Moreover, when reviewing those concepts, many semantic type assignment inconsistencies were found. After correcting those inconsistencies many ISTs, among them some that contradicted UMLS rules, disappeared, which made the RSN smaller. Objective The authors performed a longitudinal study with the goal of reducing the size of the RSN to become compact. This goal was achieved by correcting inconsistencies and errors in the IST assignments in the UMLS, which additionally helped identify and correct ambiguities, inconsistencies, and errors in source terminologies widely used in the realm of public health. Methods In this paper, we discuss the process and steps employed in this longitudinal study and the intermediate results for different stages. The sculpting process includes removing redundant semantic type assignments, expanding semantic type assignments, and removing illegitimate ISTs by auditing ISTs of small extents. However, the emphasis of this paper is not on the auditing methodologies employed during the process, since they were introduced in earlier publications, but on the strategy of employing them in order to transform the RSN into a compact network. For this paper we also performed a comprehensive audit of 168 “small ISTs” in the 2013AA version of the UMLS to finalize the longitudinal study. Results Over the years it was found that the editors of the UMLS introduced some new inconsistencies that resulted in the reintroduction of unwarranted ISTs that had already been eliminated as a result of their previous corrections. Because of that, the transformation of the RSN into a compact network covering all necessary categories for the UMLS was slowed down. The corrections suggested by an audit of the 2013AA version of the UMLS achieve a compact RSN of equal magnitude as the UMLS SN. The number of ISTs has been reduced to 336. We also demonstrate how auditing the semantic type assignments of UMLS concepts can expose other modeling errors in the UMLS source terminologies, e.g., SNOMED CT, LOINC, and RxNORM that are important for health informatics. Such errors would otherwise stay hidden. Conclusions It is hoped that the UMLS curators will implement all required corrections and use the RSN along with the SN when maintaining and extending the UMLS. When used correctly, the RSN will support the prevention of the accidental introduction of inconsistent semantic type assignments into the UMLS. Furthermore, this way the RSN will support the exposure of other hidden errors and inconsistencies in health informatics terminologies, which are sources of the UMLS. Notably, the development of the RSN materializes the deeper, more refined Semantic Network for the UMLS that its designers envisioned originally but had not implemented. PMID:25422719

Age-related differences in resolving semantic and phonological competition during receptive language tasks.

PubMed

Zhuang, Jie; Johnson, Micah A; Madden, David J; Burke, Deborah M; Diaz, Michele T

2016-12-01

Receptive language (e.g., reading) is largely preserved in the aging brain, and semantic processes in particular may continue to develop throughout the lifespan. We investigated the neural underpinnings of phonological and semantic retrieval in older and younger adults during receptive language tasks (rhyme and semantic similarity judgments). In particular, we were interested in the role of competition on language retrieval and varied the similarities between a cue, target, and distractor that were hypothesized to affect the mental process of competition. Behaviorally, all participants responded faster and more accurately during the rhyme task compared to the semantic task. Moreover, older adults demonstrated higher response accuracy than younger adults during the semantic task. Although there were no overall age-related differences in the neuroimaging results, an Age×Task interaction was found in left inferior frontal gyrus (IFG), with older adults producing greater activation than younger adults during the semantic condition. These results suggest that at lower levels of task difficulty, older and younger adults engaged similar neural networks that benefited behavioral performance. As task difficulty increased during the semantic task, older adults relied more heavily on largely left hemisphere language regions, as well as regions involved in perception and internal monitoring. Our results are consistent with the stability of language comprehension across the adult lifespan and illustrate how the preservation of semantic representations with aging may influence performance under conditions of increased task difficulty. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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.

Semantic similarity between old and new items produces false alarms in recognition memory.

PubMed

Montefinese, Maria; Zannino, Gian Daniele; Ambrosini, Ettore

2015-09-01

In everyday life, human beings can report memories of past events that did not occur or that occurred differently from the way they remember them because memory is an imperfect process of reconstruction and is prone to distortion and errors. In this recognition study using word stimuli, we investigated whether a specific operationalization of semantic similarity among concepts can modulate false memories while controlling for the possible effect of associative strength and word co-occurrence in an old-new recognition task. The semantic similarity value of each new concept was calculated as the mean cosine similarity between pairs of vectors representing that new concept and each old concept belonging to the same semantic category. Results showed that, compared with (new) low-similarity concepts, (new) high-similarity concepts had significantly higher probability of being falsely recognized as old, even after partialling out the effect of confounding variables, including associative relatedness and lexical co-occurrence. This finding supports the feature-based view of semantic memory, suggesting that meaning overlap and sharing of semantic features (which are greater when more similar semantic concepts are being processed) have an influence on recognition performance, resulting in more false alarms for new high-similarity concepts. We propose that the associative strength and word co-occurrence among concepts are not sufficient to explain illusory memories but is important to take into account also the effects of feature-based semantic relations, and, in particular, the semantic similarity among concepts.

Differential pattern of semantic memory organization between bipolar I and II disorders.

PubMed

Chang, Jae Seung; Choi, Sungwon; Ha, Kyooseob; Ha, Tae Hyon; Cho, Hyun Sang; Choi, Jung Eun; Cha, Boseok; Moon, Eunsoo

2011-06-01

Semantic cognition is one of the key factors in psychosocial functioning. The aim of this study was to explore the differences in pattern of semantic memory organization between euthymic patients with bipolar I and II disorders using the category fluency task. Study participants included 23 euthymic subjects with bipolar I disorder, 23 matched euthymic subjects with bipolar II disorder and 23 matched control subjects. All participants were assessed for verbal learning, recall, learning strategies, and fluency. The combined methods of hierarchical clustering and multidimensional scaling were used to compare the pattern of semantic memory organization among the three groups. Quantitative measures of verbal learning, recall, learning strategies, and fluency did not differ between the three groups. A two-cluster structure of semantic memory organization was identified for the three groups. Semantic structure was more disorganized in the bipolar I disorder group compared to the bipolar II disorder. In addition, patients with bipolar II disorder used less elaborate strategies of semantic memory organization than those of controls. Compared to healthy controls, strategies for categorization in semantic memory appear to be less knowledge-based in patients with bipolar disorders. A differential pattern of semantic memory organization between bipolar I and II disorders indicates a higher risk of cognitive abnormalities in patients with bipolar I disorder compared to patients with bipolar II disorder. Exploring qualitative nature of neuropsychological domains may provide an explanatory insight into the characteristic behaviors of patients with bipolar disorders. Copyright © 2011 Elsevier Inc. All rights reserved.

Neural Substrates for Judgment of Self-Agency in Ambiguous Situations

PubMed Central

Fukushima, Hirokata; Goto, Yurie; Maeda, Takaki; Kato, Motoichiro; Umeda, Satoshi

2013-01-01

The sense of agency is the attribution of oneself as the cause of one’s own actions and their effects. Accurate agency judgments are essential for adaptive behaviors in dynamic environments, especially in conditions of uncertainty. However, it is unclear how agency judgments are made in ambiguous situations where self-agency and non-self-agency are both possible. Agency attribution is thus thought to require higher-order neurocognitive processes that integrate several possibilities. Furthermore, neural activity specific to self-attribution, as compared with non-self-attribution, may reflect higher-order critical operations that contribute to constructions of self-consciousness. Based on these assumptions, the present study focused on agency judgments under ambiguous conditions and examined the neural correlates of this operation with functional magnetic resonance imaging. Participants performed a simple but demanding agency-judgment task, which required them to report on whether they attributed their own action as the cause of a visual stimulus change. The temporal discrepancy between the participant’s action and the visual events was adaptively set to be maximally ambiguous for each individual on a trial-by-trial basis. Comparison with results for a control condition revealed that the judgment of agency was associated with activity in lateral temporo-parietal areas, medial frontal areas, the dorsolateral prefrontal area, and frontal operculum/insula regions. However, most of these areas did not differentiate between self- and non-self-attribution. Instead, self-attribution was associated with activity in posterior midline areas, including the precuneus and posterior cingulate cortex. These results suggest that deliberate self-attribution of an external event is principally associated with activity in posterior midline structures, which is imperative for self-consciousness. PMID:23977268

Effect of second-order exchange in electron-hydrogen scattering

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

Madison, D.H.; Bray, I.; McCarthy, I.

1990-05-07

The electron-hydrogen scattering problem has been a nemesis to theoretical atomic physicists due to the fact that even the most sophisticated of theoretical calculations, both perturbative and nonperturbative, do not agree with experiment. The current opinion is that the perturbative approach cannot be used for this problem since recent second-order calculations are not in agreement with the experimental data and higher-order calculations are deemed impractical. However, these second-order calculations neglected second-order exchange. We have now added exchange to the second-order calculation and have found that the primary source of disagreement between experiment and theory for intermediate energies is attributable notmore » to higher-order terms but to second-order exchange.« less

NEREC, an effective brain mapping protocol for combined language and long-term memory functions.

PubMed

Perrone-Bertolotti, Marcela; Girard, Cléa; Cousin, Emilie; Vidal, Juan Ricardo; Pichat, Cédric; Kahane, Philippe; Baciu, Monica

2015-12-01

Temporal lobe epilepsy can induce functional plasticity in temporoparietal networks involved in language and long-term memory processing. Previous studies in healthy subjects have revealed the relative difficulty for this network to respond effectively across different experimental designs, as compared to more reactive regions such as frontal lobes. For a protocol to be optimal for clinical use, it has to first show robust effects in a healthy cohort. In this study, we developed a novel experimental paradigm entitled NEREC, which is able to reveal the robust participation of temporoparietal networks in a uniquely combined language and memory task, validated in an fMRI study with healthy subjects. Concretely, NEREC is composed of two runs: (a) an intermixed language-memory task (confrontation naming associated with encoding in nonverbal items, NE) to map language (i.e., word retrieval and lexico-semantic processes) combined with simultaneous long-term verbal memory encoding (NE items named but also explicitly memorized) and (b) a memory retrieval task of items encoded during NE (word recognition, REC) intermixed with new items. Word recognition is based on both perceptual-semantic familiarity (feeling of 'know') and accessing stored memory representations (remembering). In order to maximize the remembering and recruitment of medial temporal lobe structures, we increased REC difficulty by changing the modality of stimulus presentation (from nonverbal during NE to verbal during REC). We report that (a) temporoparietal activation during NE was attributable to both lexico-semantic (language) and memory (episodic encoding and semantic retrieval) processes; that (b) encoding activated the left hippocampus, bilateral fusiform, and bilateral inferior temporal gyri; and that (c) task recognition (recollection) activated the right hippocampus and bilateral but predominant left fusiform gyrus. The novelty of this protocol consists of (a) combining two tasks in one (language and long-term memory encoding/recall) instead of applying isolated tasks to map temporoparietal regions, (b) analyzing NE data based on performances recorded during REC, (c) double-mapping networks involved in naming and in long-term memory encoding and retrieval, (d) focusing on remembering with hippocampal activation and familiarity judgment with lateral temporal cortices activation, and (e) short duration of examination and feasibility. These aspects are of particular interest in patients with TLE, who frequently show impairment of these cognitive functions. Here, we show that the novel protocol is suited for this clinical evaluation. Copyright © 2015 Elsevier Inc. All rights reserved.

Optics and Symbolic Computing

DTIC Science & Technology

1987-03-01

applicatior for AI are in variation of classification parameters for knowledge acquisition ( changing of classes into which objects are placed), and...computation. The well-structured data formats of vectors, matrices, etc. used in numeric computing give way to data structures that can change their shapes...by "flexible data structures. The semantic meanings of objects are readily changed by adding and deleting the variable lists of attributes. Another

Case retrieval in medical databases by fusing heterogeneous information.

PubMed

Quellec, Gwénolé; Lamard, Mathieu; Cazuguel, Guy; Roux, Christian; Cochener, Béatrice

2011-01-01

A novel content-based heterogeneous information retrieval framework, particularly well suited to browse medical databases and support new generation computer aided diagnosis (CADx) systems, is presented in this paper. It was designed to retrieve possibly incomplete documents, consisting of several images and semantic information, from a database; more complex data types such as videos can also be included in the framework. The proposed retrieval method relies on image processing, in order to characterize each individual image in a document by their digital content, and information fusion. Once the available images in a query document are characterized, a degree of match, between the query document and each reference document stored in the database, is defined for each attribute (an image feature or a metadata). A Bayesian network is used to recover missing information if need be. Finally, two novel information fusion methods are proposed to combine these degrees of match, in order to rank the reference documents by decreasing relevance for the query. In the first method, the degrees of match are fused by the Bayesian network itself. In the second method, they are fused by the Dezert-Smarandache theory: the second approach lets us model our confidence in each source of information (i.e., each attribute) and take it into account in the fusion process for a better retrieval performance. The proposed methods were applied to two heterogeneous medical databases, a diabetic retinopathy database and a mammography screening database, for computer aided diagnosis. Precisions at five of 0.809 ± 0.158 and 0.821 ± 0.177, respectively, were obtained for these two databases, which is very promising.

Interplay between Narrative and Bodily Self in Access to Consciousness: No Difference between Self- and Non-self Attributes.

PubMed

Noel, Jean-Paul; Blanke, Olaf; Serino, Andrea; Salomon, Roy

2017-01-01

The construct of the "self" is conceived as being fundamental in promoting survival. As such, extensive studies have documented preferential processing of self-relevant stimuli. For example, attributes that relate to the self are better encoded and retrieved, and are more readily consciously perceived. The preferential processing of self-relevant information, however, appears to be especially true for physical (e.g., faces), as opposed to psychological (e.g., traits), conceptions of the self. Here, we test whether semantic attributes that participants judge as self-relevant are further processed unconsciously than attributes that were not judged as self-relevant. In Experiment 1, a continuous flash suppression paradigm was employed with "self" and "non-self" attribute words being presented subliminally, and we asked participants to categorize unseen words as either self-related or not. In a second experiment, we attempted to boost putative preferential self-processing by relation to its physical conception, that is, one's own body. To this aim, we repeated Experiment 1 while administrating acoustic stimuli either close or far from the body, i.e., within or outside peripersonal space. Results of both Experiment 1 and 2 demonstrate no difference in breaking suppression for self and non-self words. Additionally, we found that while participants were able to process the physical location of the unseen words (above or below fixation) they were not able to categorize these as self-relevant or not. Finally, results showed that sounds presented in the extra-personal space elicited a more stringent response criterion for "self" in the process of categorizing unseen visual stimuli. This shift in criterion as a consequence of sound location was restricted to the self, as no such effect was observed in the categorization of attributes occurring above or below fixation. Overall, our findings seem to indicate that subliminally presented stimuli are not semantically processed, at least inasmuch as to be categorized as self-relevant or not. However, we do demonstrate that the distance at which acoustic stimuli are presented may alter the balance between self- and non-self biases.

Interplay between Narrative and Bodily Self in Access to Consciousness: No Difference between Self- and Non-self Attributes

PubMed Central

Noel, Jean-Paul; Blanke, Olaf; Serino, Andrea; Salomon, Roy

2017-01-01

The construct of the “self” is conceived as being fundamental in promoting survival. As such, extensive studies have documented preferential processing of self-relevant stimuli. For example, attributes that relate to the self are better encoded and retrieved, and are more readily consciously perceived. The preferential processing of self-relevant information, however, appears to be especially true for physical (e.g., faces), as opposed to psychological (e.g., traits), conceptions of the self. Here, we test whether semantic attributes that participants judge as self-relevant are further processed unconsciously than attributes that were not judged as self-relevant. In Experiment 1, a continuous flash suppression paradigm was employed with “self” and “non-self” attribute words being presented subliminally, and we asked participants to categorize unseen words as either self-related or not. In a second experiment, we attempted to boost putative preferential self-processing by relation to its physical conception, that is, one’s own body. To this aim, we repeated Experiment 1 while administrating acoustic stimuli either close or far from the body, i.e., within or outside peripersonal space. Results of both Experiment 1 and 2 demonstrate no difference in breaking suppression for self and non-self words. Additionally, we found that while participants were able to process the physical location of the unseen words (above or below fixation) they were not able to categorize these as self-relevant or not. Finally, results showed that sounds presented in the extra-personal space elicited a more stringent response criterion for “self” in the process of categorizing unseen visual stimuli. This shift in criterion as a consequence of sound location was restricted to the self, as no such effect was observed in the categorization of attributes occurring above or below fixation. Overall, our findings seem to indicate that subliminally presented stimuli are not semantically processed, at least inasmuch as to be categorized as self-relevant or not. However, we do demonstrate that the distance at which acoustic stimuli are presented may alter the balance between self- and non-self biases. PMID:28197110

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

PubMed

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.

A DNA-Based Semantic Fusion Model for Remote Sensing Data

PubMed Central

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. PMID:24116207

(Pea)nuts and bolts of visual narrative: Structure and meaning in sequential image comprehension

PubMed Central

Cohn, Neil; Paczynski, Martin; Jackendoff, Ray; Holcomb, Phillip J.; Kuperberg, Gina R.

2012-01-01

Just as syntax differentiates coherent sentences from scrambled word strings, the comprehension of sequential images must also use a cognitive system to distinguish coherent narrative sequences from random strings of images. We conducted experiments analogous to two classic studies of language processing to examine the contributions of narrative structure and semantic relatedness to processing sequential images. We compared four types of comic strips: 1) Normal sequences with both structure and meaning, 2) Semantic Only sequences (in which the panels were related to a common semantic theme, but had no narrative structure), 3) Structural Only sequences (narrative structure but no semantic relatedness), and 4) Scrambled sequences of randomly-ordered panels. In Experiment 1, participants monitored for target panels in sequences presented panel-by-panel. Reaction times were slowest to panels in Scrambled sequences, intermediate in both Structural Only and Semantic Only sequences, and fastest in Normal sequences. This suggests that both semantic relatedness and narrative structure offer advantages to processing. Experiment 2 measured ERPs to all panels across the whole sequence. The N300/N400 was largest to panels in both the Scrambled and Structural Only sequences, intermediate in Semantic Only sequences and smallest in the Normal sequences. This implies that a combination of narrative structure and semantic relatedness can facilitate semantic processing of upcoming panels (as reflected by the N300/N400). Also, panels in the Scrambled sequences evoked a larger left-lateralized anterior negativity than panels in the Structural Only sequences. This localized effect was distinct from the N300/N400, and appeared despite the fact that these two sequence types were matched on local semantic relatedness between individual panels. These findings suggest that sequential image comprehension uses a narrative structure that may be independent of semantic relatedness. Altogether, we argue that the comprehension of visual narrative is guided by an interaction between structure and meaning. PMID:22387723

The mental representation of living and nonliving things: differential weighting and interactivity of sensorial and non-sensorial features.

PubMed

Ventura, Paulo; Morais, José; Brito-Mendes, Carlos; Kolinsky, Régine

2005-02-01

Warrington and colleagues (Warrington & McCarthy, 1983, 1987; Warrington & Shallice, 1984) claimed that sensorial and functional-associative (FA) features are differentially important in determining the meaning of living things (LT) and nonliving things (NLT). The first aim of the present study was to evaluate this hypothesis through two different access tasks: feature generation (Experiment 1) and cued recall (Experiment 2). The results of both experiments provided consistent empirical support for Warrington and colleagues' assumption. The second aim of the present study was to test a new differential interactivity hypothesis that combines Warrington and colleagueS' assumption with the notion of a higher number of intercorrelations and hence of a stronger connectivity between sensorial and non-sensorial features for LTs than for NLTs. This hypothesis was motivated by previoUs reports of an uncrossed interaction between domain (LTs vs NLTs) and attribute type (sensorial vs FA) in, for example, a feature verification task (Laws, Humber, Ramsey, & McCarthy, 1995): while FA attributes are verified faster than sensorial attributes for NLTs, no difference is observed for LTs. We replicated and generalised this finding using several feature verification tasks on both written words and pictures (Experiment 3), including in conditions aimed at minimising the intervention of priming biases and strategic or mnemonic processes (Experiment 4). The whole set of results suggests that both privileged relations between features and categories, and the differential importance of intercorrelations between features as a function of category, modulate access to semantic features.

Effects of semantic neighborhood density in abstract and concrete words.

PubMed

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.

Disruption of Semantic Network in Mild Alzheimer's Disease Revealed by Resting-State fMRI.

PubMed

Mascali, Daniele; DiNuzzo, Mauro; Serra, Laura; Mangia, Silvia; Maraviglia, Bruno; Bozzali, Marco; Giove, Federico

2018-02-10

Subtle semantic deficits can be observed in Alzheimer's disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke's area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Case-Based Learning, Pedagogical Innovation, and Semantic Web Technologies

ERIC Educational Resources Information Center

Martinez-Garcia, A.; Morris, S.; Tscholl, M.; Tracy, F.; Carmichael, P.

2012-01-01

This paper explores the potential of Semantic Web technologies to support teaching and learning in a variety of higher education settings in which some form of case-based learning is the pedagogy of choice. It draws on the empirical work of a major three year research and development project in the United Kingdom: "Ensemble: Semantic…

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

PubMed

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

2015-12-01

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

A remember-know analysis of the semantic serial position function.

PubMed

Kelley, Matthew R; Neath, Ian; Surprenant, Aimée M

2014-01-01

Did the serial position functions observed in certain semantic memory tasks (e.g., remembering the order of books or films) arise because they really tapped episodic memory? To address this issue, participants were asked to make "remember-know" judgments as they reconstructed the release order of the 7 Harry Potter books and 2 sets of movies. For both classes of stimuli, the "remember" and "know" serial position functions were indistinguishable, and all showed the characteristic U-shape with marked primacy and recency effects. These results are inconsistent with a multiple memory systems view, which predicts recency effects only for "remember" responses and no recency effects for "know" responses. However, the data were consistent with a general memory principle account: the relative distinctiveness principle. According to this view, performance on both episodic and semantic memory tasks arises from the same type of processing: Items that are more separated from their close neighbors in psychological space at the time of recall will be better remembered.

Incremental Query Rewriting with Resolution

NASA Astrophysics Data System (ADS)

Riazanov, Alexandre; Aragão, Marcelo A. T.

We address the problem of semantic querying of relational databases (RDB) modulo knowledge bases using very expressive knowledge representation formalisms, such as full first-order logic or its various fragments. We propose to use a resolution-based first-order logic (FOL) reasoner for computing schematic answers to deductive queries, with the subsequent translation of these schematic answers to SQL queries which are evaluated using a conventional relational DBMS. We call our method incremental query rewriting, because an original semantic query is rewritten into a (potentially infinite) series of SQL queries. In this chapter, we outline the main idea of our technique - using abstractions of databases and constrained clauses for deriving schematic answers, and provide completeness and soundness proofs to justify the applicability of this technique to the case of resolution for FOL without equality. The proposed method can be directly used with regular RDBs, including legacy databases. Moreover, we propose it as a potential basis for an efficient Web-scale semantic search technology.

Analyzing Hidden Semantics in Social Bookmarking of Open Educational Resources

NASA Astrophysics Data System (ADS)

Minguillón, Julià

Web 2.0 services such as social bookmarking allow users to manage and share the links they find interesting, adding their own tags for describing them. This is especially interesting in the field of open educational resources, as delicious is a simple way to bridge the institutional point of view (i.e. learning object repositories) with the individual one (i.e. personal collections), thus promoting the discovering and sharing of such resources by other users. In this paper we propose a methodology for analyzing such tags in order to discover hidden semantics (i.e. taxonomies and vocabularies) that can be used to improve descriptions of learning objects and make learning object repositories more visible and discoverable. We propose the use of a simple statistical analysis tool such as principal component analysis to discover which tags create clusters that can be semantically interpreted. We will compare the obtained results with a collection of resources related to open educational resources, in order to better understand the real needs of people searching for open educational resources.

Combining infobuttons and semantic web rules for identifying patterns and delivering highly-personalized education materials.

PubMed

Hulse, Nathan C; Long, Jie; Tao, Cui

2013-01-01

Infobuttons have been established to be an effective resource for addressing information needs at the point of care, as evidenced by recent research and their inclusion in government-based electronic health record incentive programs in the United States. Yet their utility has been limited to wide success for only a specific set of domains (lab data, medication orders, and problem lists) and only for discrete, singular concepts that are already documented in the electronic medical record. In this manuscript, we present an effort to broaden their utility by connecting a semantic web-based phenotyping engine with an infobutton framework in order to identify and address broader issues in patient data, derived from multiple data sources. We have tested these patterns by defining and testing semantic definitions of pre-diabetes and metabolic syndrome. We intend to carry forward relevant information to the infobutton framework to present timely, relevant education resources to patients and providers.

Problems of teaching students to use the featured technologies in the area of semantic web

NASA Astrophysics Data System (ADS)

Klimov, V. V.; Chernyshov, A. A.; Balandina, A. I.; Kostkina, A. D.

2017-01-01

The following paper contains the description of up-to-date technologies in the area of web-services development, service-oriented architecture and the Semantic Web. The paper contains the analysis of the most popular and widespread technologies and methods in the semantic web area which are used in the developed educational course. In the paper, we also describe the problem of teaching students to use these technologies and specify conditions for the creation of the learning and development course. We also describe the main exercise for personal work and skills, which all the students learning this course have to gain. Moreover, in the paper we specify the problem with software which students are going to use while learning this course. In order to solve this problem, we introduce the developing system which will be used to support the laboratory works. For this moment this system supports only the fourth work execution, but our following plans contain the expansion of the system in order to support the leftover works.

Semantic Differential as One of the Research Tools Suitable for Establishing the Attitudes of Pupils to Old Age and Seniors

ERIC Educational Resources Information Center

Divilová, Sona

2016-01-01

The paper presents the results of the pre-research conducted under the project entitled "Seniors in the Eyes of Children". The main objective of the project was to create and test a research tool in order to establish what the attitudes of pupils to old age and seniors were. Semantic differential was chosen for these purposes. Semantic…

Optimizing a Query by Transformation and Expansion.

PubMed

Glocker, Katrin; Knurr, Alexander; Dieter, Julia; Dominick, Friederike; Forche, Melanie; Koch, Christian; Pascoe Pérez, Analie; Roth, Benjamin; Ückert, Frank

2017-01-01

In the biomedical sector not only the amount of information produced and uploaded into the web is enormous, but also the number of sources where these data can be found. Clinicians and researchers spend huge amounts of time on trying to access this information and to filter the most important answers to a given question. As the formulation of these queries is crucial, automated query expansion is an effective tool to optimize a query and receive the best possible results. In this paper we introduce the concept of a workflow for an optimization of queries in the medical and biological sector by using a series of tools for expansion and transformation of the query. After the definition of attributes by the user, the query string is compared to previous queries in order to add semantic co-occurring terms to the query. Additionally, the query is enlarged by an inclusion of synonyms. The translation into database specific ontologies ensures the optimal query formulation for the chosen database(s). As this process can be performed in various databases at once, the results are ranked and normalized in order to achieve a comparable list of answers for a question.

Predicting visual semantic descriptive terms from radiological image data: preliminary results with liver lesions in CT.

PubMed

Depeursinge, Adrien; Kurtz, Camille; Beaulieu, Christopher; Napel, Sandy; Rubin, Daniel

2014-08-01

We describe a framework to model visual semantics of liver lesions in CT images in order to predict the visual semantic terms (VST) reported by radiologists in describing these lesions. Computational models of VST are learned from image data using linear combinations of high-order steerable Riesz wavelets and support vector machines (SVM). In a first step, these models are used to predict the presence of each semantic term that describes liver lesions. In a second step, the distances between all VST models are calculated to establish a nonhierarchical computationally-derived ontology of VST containing inter-term synonymy and complementarity. A preliminary evaluation of the proposed framework was carried out using 74 liver lesions annotated with a set of 18 VSTs from the RadLex ontology. A leave-one-patient-out cross-validation resulted in an average area under the ROC curve of 0.853 for predicting the presence of each VST. The proposed framework is expected to foster human-computer synergies for the interpretation of radiological images while using rotation-covariant computational models of VSTs to 1) quantify their local likelihood and 2) explicitly link them with pixel-based image content in the context of a given imaging domain.

Autism, Context/Noncontext Information Processing, and Atypical Development

PubMed Central

Skoyles, John R.

2011-01-01

Autism has been attributed to a deficit in contextual information processing. Attempts to understand autism in terms of such a defect, however, do not include more recent computational work upon context. This work has identified that context information processing depends upon the extraction and use of the information hidden in higher-order (or indirect) associations. Higher-order associations underlie the cognition of context rather than that of situations. This paper starts by examining the differences between higher-order and first-order (or direct) associations. Higher-order associations link entities not directly (as with first-order ones) but indirectly through all the connections they have via other entities. Extracting this information requires the processing of past episodes as a totality. As a result, this extraction depends upon specialised extraction processes separate from cognition. This information is then consolidated. Due to this difference, the extraction/consolidation of higher-order information can be impaired whilst cognition remains intact. Although not directly impaired, cognition will be indirectly impaired by knock on effects such as cognition compensating for absent higher-order information with information extracted from first-order associations. This paper discusses the implications of this for the inflexible, literal/immediate, and inappropriate information processing of autistic individuals. PMID:22937255

Newly-acquired words are more phonologically robust in verbal short-term memory when they have associated semantic representations.

PubMed

Savill, Nicola; Ellis, Andrew W; Jefferies, Elizabeth

2017-04-01

Verbal short-term memory (STM) is a crucial cognitive function central to language learning, comprehension and reasoning, yet the processes that underlie this capacity are not fully understood. In particular, although STM primarily draws on a phonological code, interactions between long-term phonological and semantic representations might help to stabilise the phonological trace for words ("semantic binding hypothesis"). This idea was first proposed to explain the frequent phoneme recombination errors made by patients with semantic dementia when recalling words that are no longer fully understood. However, converging evidence in support of semantic binding is scant: it is unusual for studies of healthy participants to examine serial recall at the phoneme level and also it is difficult to separate the contribution of phonological-lexical knowledge from effects of word meaning. We used a new method to disentangle these influences in healthy individuals by training new 'words' with or without associated semantic information. We examined phonological coherence in immediate serial recall (ISR), both immediately and the day after training. Trained items were more likely to be recalled than novel nonwords, confirming the importance of phonological-lexical knowledge, and items with semantic associations were also produced more accurately than those with no meaning, at both time points. For semantically-trained items, there were fewer phoneme ordering and identity errors, and consequently more complete target items were produced in both correct and incorrect list positions. These data show that lexical-semantic knowledge improves the robustness of verbal STM at the sub-item level, even when the effect of phonological familiarity is taken into account. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Architecture for Semantically Interoperable Electronic Health Records.

PubMed

Toffanello, André; Gonçalves, Ricardo; Kitajima, Adriana; Puttini, Ricardo; Aguiar, Atualpa

2017-01-01

Despite the increasing adhesion of electronic health records, the challenge of semantic interoperability remains unsolved. The fact that different parties can exchange messages does not mean they can understand the underlying clinical meaning, therefore, it cannot be assumed or treated as a requirement. This work introduces an architecture designed to achieve semantic interoperability, in a way which organizations that follow different policies may still share medical information through a common infrastructure comparable to an ecosystem, whose organisms are exemplified within the Brazilian scenario. Nonetheless, the proposed approach describes a service-oriented design with modules adaptable to different contexts. We also discuss the establishment of an enterprise service bus to mediate a health infrastructure defined on top of international standards, such as openEHR and IHE. Moreover, we argue that, in order to achieve truly semantic interoperability in a wide sense, a proper profile must be published and maintained.

The Interaction between Semantic Representation and Episodic Memory.

PubMed

Fang, Jing; Rüther, Naima; Bellebaum, Christian; Wiskott, Laurenz; Cheng, Sen

2018-02-01

The experimental evidence on the interrelation between episodic memory and semantic memory is inconclusive. Are they independent systems, different aspects of a single system, or separate but strongly interacting systems? Here, we propose a computational role for the interaction between the semantic and episodic systems that might help resolve this debate. We hypothesize that episodic memories are represented as sequences of activation patterns. These patterns are the output of a semantic representational network that compresses the high-dimensional sensory input. We show quantitatively that the accuracy of episodic memory crucially depends on the quality of the semantic representation. We compare two types of semantic representations: appropriate representations, which means that the representation is used to store input sequences that are of the same type as those that it was trained on, and inappropriate representations, which means that stored inputs differ from the training data. Retrieval accuracy is higher for appropriate representations because the encoded sequences are less divergent than those encoded with inappropriate representations. Consistent with our model prediction, we found that human subjects remember some aspects of episodes significantly more accurately if they had previously been familiarized with the objects occurring in the episode, as compared to episodes involving unfamiliar objects. We thus conclude that the interaction with the semantic system plays an important role for episodic memory.

Effect of perceptual load on semantic access by speech in children

PubMed Central

Jerger, Susan; Damian, Markus F.; Mills, Candice; Bartlett, James; Tye-Murray, Nancy; Abdi, Hervè

2013-01-01

Purpose To examine whether semantic access by speech requires attention in children. Method Children (N=200) named pictures and ignored distractors on a cross-modal (distractors: auditory-no face) or multi-modal (distractors: auditory-static face and audiovisual-dynamic face) picture word task. The cross-modal had a low load, and the multi-modal had a high load [i.e., respectively naming pictures displayed 1) on a blank screen vs 2) below the talker’s face on his T-shirt]. Semantic content of distractors was manipulated to be related vs unrelated to picture (e.g., picture dog with distractors bear vs cheese). Lavie's (2005) perceptual load model proposes that semantic access is independent of capacity limited attentional resources if irrelevant semantic-content manipulation influences naming times on both tasks despite variations in loads but dependent on attentional resources exhausted by higher load task if irrelevant content influences naming only on cross-modal (low load). Results Irrelevant semantic content affected performance for both tasks in 6- to 9-year-olds, but only on cross-modal in 4–5-year-olds. The addition of visual speech did not influence results on the multi-modal task. Conclusion Younger and older children differ in dependence on attentional resources for semantic access by speech. PMID:22896045

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

PubMed

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order covering diverse bio-entity relations. To assess the potential utility of our automated top-ranked patterns of a given relation in semantic search, we performed a pilot study on frequently sought semantic relations in PubMed and observed improved literature retrieval effectiveness based on post-hoc human relevance evaluation. Further investigation in larger tests and in real-world scenarios is warranted. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.

Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies.

PubMed

Gu, H; Chen, Y; He, Z; Halper, M; Chen, L

2016-01-01

The Unified Medical Language System (UMLS) is one of the largest biomedical terminological systems, with over 2.5 million concepts in its Metathesaurus repository. The UMLS's Semantic Network (SN) with its collection of 133 high-level semantic types serves as an abstraction layer on top of the Metathesaurus. In particular, the SN elaborates an aspect of the Metathesaurus's concepts via the assignment of one or more types to each concept. Due to the scope and complexity of the Metathesaurus, errors are all but inevitable in this semantic-type assignment process. To develop a semi-automated methodology to help assure the quality of semantic-type assignments within the UMLS. The methodology uses a cross-validation strategy involving SNOMED CT's hierarchies in combination with UMLS semantic types. Semantically uniform, disjoint concept groups are generated programmatically by partitioning the collection of all concepts in the same SNOMED CT hierarchy according to their respective semantic-type assignments in the UMLS. Domain experts are then called upon to review the concepts in any group having a small number of concepts. It is our hypothesis that a semantic-type assignment combination applicable only to a very small number of concepts in a SNOMED CT hierarchy is an indicator of potential problems. The methodology was applied to the UMLS 2013AA release along with the SNOMED CT from January 2013. An overall error rate of 33% was found for concepts proposed by the quality-assurance methodology. Supporting our hypothesis, that number was four times higher than the error rate found in control samples. The results show that the quality-assurance methodology can aid in effective and efficient identification of UMLS semantic-type assignment errors.

An Evaluation of One-Sided and Two-Sided Communication Paradigms on Relaxed-Ordering Interconnect

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

Ibrahim, Khaled Z.; Hargrove, Paul H.; Iancu, Costin

The Cray Gemini interconnect hardware provides multiple transfer mechanisms and out-of-order message delivery to improve communication throughput. In this paper we quantify the performance of one-sided and two-sided communication paradigms with respect to: 1) the optimal available hardware transfer mechanism, 2) message ordering constraints, 3) per node and per core message concurrency. In addition to using Cray native communication APIs, we use UPC and MPI micro-benchmarks to capture one- and two-sided semantics respectively. Our results indicate that relaxing the message delivery order can improve performance up to 4.6x when compared with strict ordering. When hardware allows it, high-level one-sided programmingmore » models can already take advantage of message reordering. Enforcing the ordering semantics of two-sided communication comes with a performance penalty. Furthermore, we argue that exposing out-of-order delivery at the application level is required for the next-generation programming models. Any ordering constraints in the language specifications reduce communication performance for small messages and increase the number of active cores required for peak throughput.« less

A Practical Approach to Implementing Real-Time Semantics

NASA Technical Reports Server (NTRS)

Luettgen, Gerald; Bhat, Girish; Cleaveland, Rance

1999-01-01

This paper investigates implementations of process algebras which are suitable for modeling concurrent real-time systems. It suggests an approach for efficiently implementing real-time semantics using dynamic priorities. For this purpose a proces algebra with dynamic priority is defined, whose semantics corresponds one-to-one to traditional real-time semantics. The advantage of the dynamic-priority approach is that it drastically reduces the state-space sizes of the systems in question while preserving all properties of their functional and real-time behavior. The utility of the technique is demonstrated by a case study which deals with the formal modeling and verification of the SCSI-2 bus-protocol. The case study is carried out in the Concurrency Workbench of North Carolina, an automated verification tool in which the process algebra with dynamic priority is implemented. It turns out that the state space of the bus-protocol model is about an order of magnitude smaller than the one resulting from real-time semantics. The accuracy of the model is proved by applying model checking for verifying several mandatory properties of the bus protocol.

Semantic Metadata for Heterogeneous Spatial Planning Documents

NASA Astrophysics Data System (ADS)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Learning semantic and visual similarity for endomicroscopy video retrieval.

PubMed

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. In our resulting retrieval system, we decide to use visual signatures for perceived similarity learning and retrieval, and semantic signatures for the output of an additional information, expressed in the endoscopist own language, which provides a relevant semantic translation of the visual retrieval outputs.

Integration of nonthematic details in pictures and passages.

PubMed

Viera, C L; Homa, D L

1991-01-01

Nonthematic details in naturalistic scenes were manipulated to produce four stimulus versions: color photos, black-white copies, and elaborated and unelaborated line drawings (Experiment 1); analogous verbal descriptions of each visual version were produced for Experiment 2. In Experiment 1, two or three different versions of a scene were presented in the mixed condition; the same version of the scene was repeated either two or three times in the same condition, and a 1-presentation control condition was also included. In Experiment 2, the same presentation conditions were used across different groups of subjects who either viewed the pictures or heard the descriptions. An old/new recognition test was given in which the nonstudied versions of the studied items were used as foils. Higher false recognition performances for the mixed condition were found for the visual materials in both experiments, and in the second experiment the verbal materials produced equivalently high levels of false recognition for both same and mixed conditions. Additionally, in Experiment 2 the patterns of performances across material conditions were differentially affected by the manipulation of detail in the four stimulus versions. These differences across materials suggest that the integration of semantically consistent details across temporally separable presentations is facilitated when the stimuli do not provide visual/physical attributes to enhance discrimination of different presentations. Further, the evidence derived from the visual scenes in both experiments indicates that the semantic schema abstracted from a picture is not the sole mediator of recognition performance.

Automatic generation of nursing narratives from entity-attribute-value triplet for electronic nursing records system.

PubMed

Min, Yul Ha; Park, Hyeoun-Ae; Lee, Joo Yun; Jo, Soo Jung; Jeon, Eunjoo; Byeon, Namsoo; Choi, Seung Yong; Chung, Eunja

2014-01-01

The aim of this study is to develop and evaluate a natural language generation system to populate nursing narratives using detailed clinical models. Semantic, contextual, and syntactical knowledges were extracted. A natural language generation system linking these knowledges was developed. The quality of generated nursing narratives was evaluated by the three nurse experts using a five-point rating scale. With 82 detailed clinical models, in total 66,888 nursing narratives in four different types of statement were generated. The mean scores for overall quality was 4.66, for content 4.60, for grammaticality 4.40, for writing style 4.13, and for correctness 4.60. The system developed in this study generated nursing narratives with different levels of granularity. The generated nursing narratives can improve semantic interoperability of nursing data documented in nursing records.

Exploiting Semantic Web Technologies to Develop OWL-Based Clinical Practice Guideline Execution Engines.

PubMed

Jafarpour, Borna; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2016-01-01

Computerizing paper-based CPG and then executing them can provide evidence-informed decision support to physicians at the point of care. Semantic web technologies especially web ontology language (OWL) ontologies have been profusely used to represent computerized CPG. Using semantic web reasoning capabilities to execute OWL-based computerized CPG unties them from a specific custom-built CPG execution engine and increases their shareability as any OWL reasoner and triple store can be utilized for CPG execution. However, existing semantic web reasoning-based CPG execution engines suffer from lack of ability to execute CPG with high levels of expressivity, high cognitive load of computerization of paper-based CPG and updating their computerized versions. In order to address these limitations, we have developed three CPG execution engines based on OWL 1 DL, OWL 2 DL and OWL 2 DL + semantic web rule language (SWRL). OWL 1 DL serves as the base execution engine capable of executing a wide range of CPG constructs, however for executing highly complex CPG the OWL 2 DL and OWL 2 DL + SWRL offer additional executional capabilities. We evaluated the technical performance and medical correctness of our execution engines using a range of CPG. Technical evaluations show the efficiency of our CPG execution engines in terms of CPU time and validity of the generated recommendation in comparison to existing CPG execution engines. Medical evaluations by domain experts show the validity of the CPG-mediated therapy plans in terms of relevance, safety, and ordering for a wide range of patient scenarios.

The effects of semantic congruency: a research of audiovisual P300-speller.

PubMed

Cao, Yong; An, Xingwei; Ke, Yufeng; Jiang, Jin; Yang, Hanjun; Chen, Yuqian; Jiao, Xuejun; Qi, Hongzhi; Ming, Dong

2017-07-25

Over the past few decades, there have been many studies of aspects of brain-computer interface (BCI). Of particular interests are event-related potential (ERP)-based BCI spellers that aim at helping mental typewriting. Nowadays, audiovisual unimodal stimuli based BCI systems have attracted much attention from researchers, and most of the existing studies of audiovisual BCIs were based on semantic incongruent stimuli paradigm. However, no related studies had reported that whether there is difference of system performance or participant comfort between BCI based on semantic congruent paradigm and that based on semantic incongruent paradigm. The goal of this study was to investigate the effects of semantic congruency in system performance and participant comfort in audiovisual BCI. Two audiovisual paradigms (semantic congruent and incongruent) were adopted, and 11 healthy subjects participated in the experiment. High-density electrical mapping of ERPs and behavioral data were measured for the two stimuli paradigms. The behavioral data indicated no significant difference between congruent and incongruent paradigms for offline classification accuracy. Nevertheless, eight of the 11 participants reported their priority to semantic congruent experiment, two reported no difference between the two conditions, and only one preferred the semantic incongruent paradigm. Besides, the result indicted that higher amplitude of ERP was found in incongruent stimuli based paradigm. In a word, semantic congruent paradigm had a better participant comfort, and maintained the same recognition rate as incongruent paradigm. Furthermore, our study suggested that the paradigm design of spellers must take both system performance and user experience into consideration rather than merely pursuing a larger ERP response.

Recursion in aphasia.

PubMed

Bánréti, Zoltán

2010-11-01

This study investigates how aphasic impairment impinges on syntactic and/or semantic recursivity of human language. A series of tests has been conducted with the participation of five Hungarian speaking aphasic subjects and 10 control subjects. Photographs representing simple situations were presented to subjects and questions were asked about them. The responses are supposed to involve formal structural recursion, but they contain semantic-pragmatic operations instead, with 'theory of mind' type embeddings. Aphasic individuals tend to exploit the parallel between 'theory of mind' embeddings and syntactic-structural embeddings in order to avoid formal structural recursion. Formal structural recursion may be more impaired in Broca's aphasia and semantic recursivity may remain selectively unimpaired in this type of aphasia.

Context-rich semantic framework for effective data-to-decisions in coalition networks

NASA Astrophysics Data System (ADS)

Grueneberg, Keith; de Mel, Geeth; Braines, Dave; Wang, Xiping; Calo, Seraphin; Pham, Tien

2013-05-01

In a coalition context, data fusion involves combining of soft (e.g., field reports, intelligence reports) and hard (e.g., acoustic, imagery) sensory data such that the resulting output is better than what it would have been if the data are taken individually. However, due to the lack of explicit semantics attached with such data, it is difficult to automatically disseminate and put the right contextual data in the hands of the decision makers. In order to understand the data, explicit meaning needs to be added by means of categorizing and/or classifying the data in relationship to each other from base reference sources. In this paper, we present a semantic framework that provides automated mechanisms to expose real-time raw data effectively by presenting appropriate information needed for a given situation so that an informed decision could be made effectively. The system utilizes controlled natural language capabilities provided by the ITA (International Technology Alliance) Controlled English (CE) toolkit to provide a human-friendly semantic representation of messages so that the messages can be directly processed in human/machine hybrid environments. The Real-time Semantic Enrichment (RTSE) service adds relevant contextual information to raw data streams from domain knowledge bases using declarative rules. The rules define how the added semantics and context information are derived and stored in a semantic knowledge base. The software framework exposes contextual information from a variety of hard and soft data sources in a fast, reliable manner so that an informed decision can be made using semantic queries in intelligent software systems.

GeneYenta: a phenotype-based rare disease case matching tool based on online dating algorithms for the acceleration of exome interpretation.

PubMed

Gottlieb, Michael M; Arenillas, David J; Maithripala, Savanie; Maurer, Zachary D; Tarailo Graovac, Maja; Armstrong, Linlea; Patel, Millan; van Karnebeek, Clara; Wasserman, Wyeth W

2015-04-01

Advances in next-generation sequencing (NGS) technologies have helped reveal causal variants for genetic diseases. In order to establish causality, it is often necessary to compare genomes of unrelated individuals with similar disease phenotypes to identify common disrupted genes. When working with cases of rare genetic disorders, finding similar individuals can be extremely difficult. We introduce a web tool, GeneYenta, which facilitates the matchmaking process, allowing clinicians to coordinate detailed comparisons for phenotypically similar cases. Importantly, the system is focused on phenotype annotation, with explicit limitations on highly confidential data that create barriers to participation. The procedure for matching of patient phenotypes, inspired by online dating services, uses an ontology-based semantic case matching algorithm with attribute weighting. We evaluate the capacity of the system using a curated reference data set and 19 clinician entered cases comparing four matching algorithms. We find that the inclusion of clinician weights can augment phenotype matching. © 2015 WILEY PERIODICALS, INC.

MANCaLog: A Logic for Multi-Attribute Network Cascades

DTIC Science & Technology

2013-01-01

influence function , whose precise effects will be described later on when we discuss the semantics. As a result, a rule consists of four major parts...i) an influence function , (ii) neighbor criteria, (iii) target criteria, and (iv) a target. Intuitively, (i) specifies how the neighbors influence the...in terms of these elements. First, we define influence functions and neighbor criteria. Definition 2.6 ( Influence Function ). An influence function is a

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

PubMed

Uthayan, K R; Mala, G S Anandha

2015-01-01

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

[Electrophysiological bases of semantic processing of objects].

PubMed

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.

The elephant in the room: Inconsistency in scene viewing and representation.

PubMed

Spotorno, Sara; Tatler, Benjamin W

2017-10-01

We examined the extent to which semantic informativeness, consistency with expectations and perceptual salience contribute to object prioritization in scene viewing and representation. In scene viewing (Experiments 1-2), semantic guidance overshadowed perceptual guidance in determining fixation order, with the greatest prioritization for objects that were diagnostic of the scene's depicted event. Perceptual properties affected selection of consistent objects (regardless of their informativeness) but not of inconsistent objects. Semantic and perceptual properties also interacted in influencing foveal inspection, as inconsistent objects were fixated longer than low but not high salience diagnostic objects. While not studied in direct competition with each other (each studied in competition with diagnostic objects), we found that inconsistent objects were fixated earlier and for longer than consistent but marginally informative objects. In change detection (Experiment 3), perceptual guidance overshadowed semantic guidance, promoting detection of highly salient changes. A residual advantage for diagnosticity over inconsistency emerged only when selection prioritization could not be based on low-level features. Overall these findings show that semantic inconsistency is not prioritized within a scene when competing with other relevant information that is essential to scene understanding and respects observers' expectations. Moreover, they reveal that the relative dominance of semantic or perceptual properties during selection depends on ongoing task requirements. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

PubMed Central

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

2015-01-01

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

Early Parallel Activation of Semantics and Phonology in Picture Naming: Evidence from a Multiple Linear Regression MEG Study

PubMed Central

Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf

2015-01-01

The time course of brain activation during word production has become an area of increasingly intense investigation in cognitive neuroscience. The predominant view has been that semantic and phonological processes are activated sequentially, at about 150 and 200–400 ms after picture onset. Although evidence from prior studies has been interpreted as supporting this view, these studies were arguably not ideally suited to detect early brain activation of semantic and phonological processes. We here used a multiple linear regression approach to magnetoencephalography (MEG) analysis of picture naming in order to investigate early effects of variables specifically related to visual, semantic, and phonological processing. This was combined with distributed minimum-norm source estimation and region-of-interest analysis. Brain activation associated with visual image complexity appeared in occipital cortex at about 100 ms after picture presentation onset. At about 150 ms, semantic variables became physiologically manifest in left frontotemporal regions. In the same latency range, we found an effect of phonological variables in the left middle temporal gyrus. Our results demonstrate that multiple linear regression analysis is sensitive to early effects of multiple psycholinguistic variables in picture naming. Crucially, our results suggest that access to phonological information might begin in parallel with semantic processing around 150 ms after picture onset. PMID:25005037

Architecture for WSN Nodes Integration in Context Aware Systems Using Semantic Messages

NASA Astrophysics Data System (ADS)

Larizgoitia, Iker; Muguira, Leire; Vazquez, Juan Ignacio

Wireless sensor networks (WSN) are becoming extremely popular in the development of context aware systems. Traditionally WSN have been focused on capturing data, which was later analyzed and interpreted in a server with more computational power. In this kind of scenario the problem of representing the sensor information needs to be addressed. Every node in the network might have different sensors attached; therefore their correspondent packet structures will be different. The server has to be aware of the meaning of every single structure and data in order to be able to interpret them. Multiple sensors, multiple nodes, multiple packet structures (and not following a standard format) is neither scalable nor interoperable. Context aware systems have solved this problem with the use of semantic technologies. They provide a common framework to achieve a standard definition of any domain. Nevertheless, these representations are computationally expensive, so a WSN cannot afford them. The work presented in this paper tries to bridge the gap between the sensor information and its semantic representation, by defining a simple architecture that enables the definition of this information natively in a semantic way, achieving the integration of the semantic information in the network packets. This will have several benefits, the most important being the possibility of promoting every WSN node to a real semantic information source.

Disentangling Genuine Semantic Stroop Effects in Reading from Contingency Effects: On the Need for Two Neutral Baselines

PubMed Central

Lorentz, Eric; McKibben, Tessa; Ekstrand, Chelsea; Gould, Layla; Anton, Kathryn; Borowsky, Ron

2016-01-01

The automaticity of reading is often explored through the Stroop effect, whereby color-naming is affected by color words. Color associates (e.g., “sky”) also produce a Stroop effect, suggesting that automatic reading occurs through to the level of semantics, even when reading sub-lexically (e.g., the pseudohomophone “skigh”). However, several previous experiments have confounded congruency with contingency learning, whereby faster responding occurs for more frequent stimuli. Contingency effects reflect a higher frequency-pairing of the word with a font color in the congruent condition than in the incongruent condition due to the limited set of congruent pairings. To determine the extent to which the Stroop effect can be attributed to contingency learning of font colors paired with lexical (word-level) and sub-lexical (phonetically decoded) letter strings, as well as assess facilitation and interference relative to contingency effects, we developed two neutral baselines: each one matched on pair-frequency for congruent and incongruent color words. In Experiments 1 and 3, color words (e.g., “blue”) and their pseudohomophones (e.g., “bloo”) produced significant facilitation and interference relative to neutral baselines, regardless of whether the onset (i.e., first phoneme) was matched to the color words. Color associates (e.g., “ocean”) and their pseudohomophones (e.g., “oshin”), however, showed no significant facilitation or interference relative to onset matched neutral baselines (Experiment 2). When onsets were unmatched, color associate words produced consistent facilitation on RT (e.g., “ocean” vs. “dozen”), but pseudohomophones (e.g., “oshin” vs. “duhzen”) failed to produce facilitation or interference. Our findings suggest that the Stroop effects for color and associated stimuli are sensitive to the type of neutral baseline used, as well as stimulus type (word vs. pseudohomophone). In general, contingency learning plays a large role when repeating congruent items more than incongruent items, but appropriate pair-frequency matched neutral baselines allow for the assessment of genuine facilitation and interference. Using such baselines, we found reading processes proceed to a semantic level for familiar words, but not pseudohomophones (i.e., phonetic decoding). Such assessment is critical for separating the effects of genuine congruency from contingency during automatic word reading in the Stroop task, and when used with color associates, isolates the semantic contribution. PMID:27014177

Disentangling Genuine Semantic Stroop Effects in Reading from Contingency Effects: On the Need for Two Neutral Baselines.

PubMed

Lorentz, Eric; McKibben, Tessa; Ekstrand, Chelsea; Gould, Layla; Anton, Kathryn; Borowsky, Ron

2016-01-01

The automaticity of reading is often explored through the Stroop effect, whereby color-naming is affected by color words. Color associates (e.g., "sky") also produce a Stroop effect, suggesting that automatic reading occurs through to the level of semantics, even when reading sub-lexically (e.g., the pseudohomophone "skigh"). However, several previous experiments have confounded congruency with contingency learning, whereby faster responding occurs for more frequent stimuli. Contingency effects reflect a higher frequency-pairing of the word with a font color in the congruent condition than in the incongruent condition due to the limited set of congruent pairings. To determine the extent to which the Stroop effect can be attributed to contingency learning of font colors paired with lexical (word-level) and sub-lexical (phonetically decoded) letter strings, as well as assess facilitation and interference relative to contingency effects, we developed two neutral baselines: each one matched on pair-frequency for congruent and incongruent color words. In Experiments 1 and 3, color words (e.g., "blue") and their pseudohomophones (e.g., "bloo") produced significant facilitation and interference relative to neutral baselines, regardless of whether the onset (i.e., first phoneme) was matched to the color words. Color associates (e.g., "ocean") and their pseudohomophones (e.g., "oshin"), however, showed no significant facilitation or interference relative to onset matched neutral baselines (Experiment 2). When onsets were unmatched, color associate words produced consistent facilitation on RT (e.g., "ocean" vs. "dozen"), but pseudohomophones (e.g., "oshin" vs. "duhzen") failed to produce facilitation or interference. Our findings suggest that the Stroop effects for color and associated stimuli are sensitive to the type of neutral baseline used, as well as stimulus type (word vs. pseudohomophone). In general, contingency learning plays a large role when repeating congruent items more than incongruent items, but appropriate pair-frequency matched neutral baselines allow for the assessment of genuine facilitation and interference. Using such baselines, we found reading processes proceed to a semantic level for familiar words, but not pseudohomophones (i.e., phonetic decoding). Such assessment is critical for separating the effects of genuine congruency from contingency during automatic word reading in the Stroop task, and when used with color associates, isolates the semantic contribution.

Folksonomies and clustering in the collaborative system CiteULike

NASA Astrophysics Data System (ADS)

Capocci, Andrea; Caldarelli, Guido

2008-06-01

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags.

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

PubMed Central

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

2009-01-01

Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit “Citations in Context”, and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own research articles, and thereby break down present barriers to the discovery and re-use of information within traditional modes of scholarly communication. PMID:19381256

Brain connections of words, perceptions and actions: A neurobiological model of spatio-temporal semantic activation in the human cortex.

PubMed

Tomasello, Rosario; Garagnani, Max; Wennekers, Thomas; Pulvermüller, Friedemann

2017-04-01

Neuroimaging and patient studies show that different areas of cortex respectively specialize for general and selective, or category-specific, semantic processing. Why are there both semantic hubs and category-specificity, and how come that they emerge in different cortical regions? Can the activation time-course of these areas be predicted and explained by brain-like network models? In this present work, we extend a neurocomputational model of human cortical function to simulate the time-course of cortical processes of understanding meaningful concrete words. The model implements frontal and temporal cortical areas for language, perception, and action along with their connectivity. It uses Hebbian learning to semantically ground words in aspects of their referential object- and action-related meaning. Compared with earlier proposals, the present model incorporates additional neuroanatomical links supported by connectivity studies and downscaled synaptic weights in order to control for functional between-area differences purely due to the number of in- or output links of an area. We show that learning of semantic relationships between words and the objects and actions these symbols are used to speak about, leads to the formation of distributed circuits, which all include neuronal material in connector hub areas bridging between sensory and motor cortical systems. Therefore, these connector hub areas acquire a role as semantic hubs. By differentially reaching into motor or visual areas, the cortical distributions of the emergent 'semantic circuits' reflect aspects of the represented symbols' meaning, thus explaining category-specificity. The improved connectivity structure of our model entails a degree of category-specificity even in the 'semantic hubs' of the model. The relative time-course of activation of these areas is typically fast and near-simultaneous, with semantic hubs central to the network structure activating before modality-preferential areas carrying semantic information. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference.

PubMed

Widdows, Dominic; Cohen, Trevor

2015-10-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.

[Translation and cultural adaptation of the questionnaire on the reason for food choices (Food Choice Questionnaire - FCQ) into Portuguese].

PubMed

Heitor, Sara Franco Diniz; Estima, Camilla Chermont Prochnik; das Neves, Fabricia Junqueira; de Aguiar, Aline Silva; Castro, Sybelle de Souza; Ferreira, Julia Elba de Souza

2015-08-01

The Food Choice Questionnaire (FCQ) assesses the importance that subjects attribute to nine factors related to food choices: health, mood, convenience, sensory appeal, natural content, price, weight control, familiarity and ethical concern. This study sought to assess the applicability of the FCQ in Brazil; it describes the translation and cultural adaptation from English into Portuguese of the FCQ via the following steps: independent translations, consensus, back-translation, evaluation by a committee of experts, semantic validation and pre-test. The pre-test was run with a randomly sampled group of 86 male and female college students from different courses with a median age of 19. Slight differences between the versions were observed and adjustments were made. After minor changes in the translation process, the committee of experts considered that the Brazilian Portuguese version was semantically and conceptually equivalent to the English original. Semantic validation showed that the questionnaire is easily understood. The instrument presented a high degree of internal consistency. The study is the first stage in the process of validating an instrument, which consists of face and content validity. Further stages, already underway, are needed before other researchers can use it.

On fuzzy semantic similarity measure for DNA coding.

PubMed

Ahmad, Muneer; Jung, Low Tang; Bhuiyan, Md Al-Amin

2016-02-01

A coding measure scheme numerically translates the DNA sequence to a time domain signal for protein coding regions identification. A number of coding measure schemes based on numerology, geometry, fixed mapping, statistical characteristics and chemical attributes of nucleotides have been proposed in recent decades. Such coding measure schemes lack the biologically meaningful aspects of nucleotide data and hence do not significantly discriminate coding regions from non-coding regions. This paper presents a novel fuzzy semantic similarity measure (FSSM) coding scheme centering on FSSM codons׳ clustering and genetic code context of nucleotides. Certain natural characteristics of nucleotides i.e. appearance as a unique combination of triplets, preserving special structure and occurrence, and ability to own and share density distributions in codons have been exploited in FSSM. The nucleotides׳ fuzzy behaviors, semantic similarities and defuzzification based on the center of gravity of nucleotides revealed a strong correlation between nucleotides in codons. The proposed FSSM coding scheme attains a significant enhancement in coding regions identification i.e. 36-133% as compared to other existing coding measure schemes tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference

PubMed Central

Widdows, Dominic; Cohen, Trevor

2015-01-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.1 PMID:26582967

The perirhinal cortex and conceptual processing: Effects of feature-based statistics following damage to the anterior temporal lobes.

PubMed

Wright, Paul; Randall, Billi; Clarke, Alex; Tyler, Lorraine K

2015-09-01

The anterior temporal lobe (ATL) plays a prominent role in models of semantic knowledge, although it remains unclear how the specific subregions within the ATL contribute to semantic memory. Patients with neurodegenerative diseases, like semantic dementia, have widespread damage to the ATL thus making inferences about the relationship between anatomy and cognition problematic. Here we take a detailed anatomical approach to ask which substructures within the ATL contribute to conceptual processing, with the prediction that the perirhinal cortex (PRc) will play a critical role for concepts that are more semantically confusable. We tested two patient groups, those with and without damage to the PRc, across two behavioural experiments - picture naming and word-picture matching. For both tasks, we manipulated the degree of semantic confusability of the concepts. By contrasting the performance of the two groups, along with healthy controls, we show that damage to the PRc results in worse performance in processing concepts with higher semantic confusability across both experiments. Further by correlating the degree of damage across anatomically defined regions of interest with performance, we find that PRc damage is related to performance for concepts with increased semantic confusability. Our results show that the PRc supports a necessary and crucial neurocognitve function that enables fine-grained conceptual processes to take place through the resolution of semantic confusability. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Exploiting semantics for sensor re-calibration in event detection systems

NASA Astrophysics Data System (ADS)

Vaisenberg, Ronen; Ji, Shengyue; Hore, Bijit; Mehrotra, Sharad; Venkatasubramanian, Nalini

2008-01-01

Event detection from a video stream is becoming an important and challenging task in surveillance and sentient systems. While computer vision has been extensively studied to solve different kinds of detection problems over time, it is still a hard problem and even in a controlled environment only simple events can be detected with a high degree of accuracy. Instead of struggling to improve event detection using image processing only, we bring in semantics to direct traditional image processing. Semantics are the underlying facts that hide beneath video frames, which can not be "seen" directly by image processing. In this work we demonstrate that time sequence semantics can be exploited to guide unsupervised re-calibration of the event detection system. We present an instantiation of our ideas by using an appliance as an example--Coffee Pot level detection based on video data--to show that semantics can guide the re-calibration of the detection model. This work exploits time sequence semantics to detect when re-calibration is required to automatically relearn a new detection model for the newly evolved system state and to resume monitoring with a higher rate of accuracy.

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

PubMed

Gainotti, Guido

2015-04-01

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

New methods for analyzing semantic graph based assessments in science education

NASA Astrophysics Data System (ADS)

Vikaros, Lance Steven

This research investigated how the scoring of semantic graphs (known by many as concept maps) could be improved and automated in order to address issues of inter-rater reliability and scalability. As part of the NSF funded SENSE-IT project to introduce secondary school science students to sensor networks (NSF Grant No. 0833440), semantic graphs illustrating how temperature change affects water ecology were collected from 221 students across 16 schools. The graphing task did not constrain students' use of terms, as is often done with semantic graph based assessment due to coding and scoring concerns. The graphing software used provided real-time feedback to help students learn how to construct graphs, stay on topic and effectively communicate ideas. The collected graphs were scored by human raters using assessment methods expected to boost reliability, which included adaptations of traditional holistic and propositional scoring methods, use of expert raters, topical rubrics, and criterion graphs. High levels of inter-rater reliability were achieved, demonstrating that vocabulary constraints may not be necessary after all. To investigate a new approach to automating the scoring of graphs, thirty-two different graph features characterizing graphs' structure, semantics, configuration and process of construction were then used to predict human raters' scoring of graphs in order to identify feature patterns correlated to raters' evaluations of graphs' topical accuracy and complexity. Results led to the development of a regression model able to predict raters' scoring with 77% accuracy, with 46% accuracy expected when used to score new sets of graphs, as estimated via cross-validation tests. Although such performance is comparable to other graph and essay based scoring systems, cross-context testing of the model and methods used to develop it would be needed before it could be recommended for widespread use. Still, the findings suggest techniques for improving the reliability and scalability of semantic graph based assessments without requiring constraint of how ideas are expressed.

A critical evaluation of monkey models of amnesia and dementia.

PubMed

Ridley, R M; Baker, H F

1991-01-01

In this review we consider various models of amnesia and dementia in monkeys and examine the validity of such models. In Section 2 we describe the various types of memory tests (tasks) available for use with monkeys and discuss the extent to which these tasks assess different facets of memory according to present theories of human memory. We argue that the rules which govern correct task performance are best regarded as a form of semantic rather than procedural memory, and that when information about stimulus attributes or reward associations is stored long-term then that knowledge is semantic. The demonstration of episodic memory in monkeys is problematic and the term recognition memory has been used too loosely. In particular, it is difficult to dissociate episodic memory for stimulus events from the use of semantic memory for the rule of the task, since dysfunction of either can produce impairment on performance of the same task. Tasks can also be divided into those which assess memory for stimulus-reward associations (evaluative memory) and those which tax stimulus-response associations including spatial and conditional responding (non-evaluative memory). This dissociation cuts across the distinction between semantic and episodic memory. In Section 3 we examine the usefulness of the classification of tasks described in Section 2 in clarifying our understanding of the contribution of the temporal lobes and the cholinergic system to memory. We conclude that evaluative and non-evaluative memory are mediated by separate parallel systems involving the amygdala and hippocampus, respectively.

Ontology-Driven Knowledge-Based Health-Care System, An Emerging Area - Challenges And Opportunities - Indian Scenario

NASA Astrophysics Data System (ADS)

Sunitha, A.; Babu, G. Suresh

2014-11-01

Recent studies in the decision making efforts in the area of public healthcare systems have been tremendously inspired and influenced by the entry of ontology. Ontology driven systems results in the effective implementation of healthcare strategies for the policy makers. The central source of knowledge is the ontology containing all the relevant domain concepts such as locations, diseases, environments and their domain sensitive inter-relationships which is the prime objective, concern and the motivation behind this paper. The paper further focuses on the development of a semantic knowledge-base for public healthcare system. This paper describes the approach and methodologies in bringing out a novel conceptual theme in establishing a firm linkage between three different ontologies related to diseases, places and environments in one integrated platform. This platform correlates the real-time mechanisms prevailing within the semantic knowledgebase and establishing their inter-relationships for the first time in India. This is hoped to formulate a strong foundation for establishing a much awaited basic need for a meaningful healthcare decision making system in the country. Introduction through a wide range of best practices facilitate the adoption of this approach for better appreciation, understanding and long term outcomes in the area. The methods and approach illustrated in the paper relate to health mapping methods, reusability of health applications, and interoperability issues based on mapping of the data attributes with ontology concepts in generating semantic integrated data driving an inference engine for user-interfaced semantic queries.

Ontology Based Quality Evaluation for Spatial Data

NASA Astrophysics Data System (ADS)

Yılmaz, C.; Cömert, Ç.

2015-08-01

Many institutions will be providing data to the National Spatial Data Infrastructure (NSDI). Current technical background of the NSDI is based on syntactic web services. It is expected that this will be replaced by semantic web services. The quality of the data provided is important in terms of the decision-making process and the accuracy of transactions. Therefore, the data quality needs to be tested. This topic has been neglected in Turkey. Data quality control for NSDI may be done by private or public "data accreditation" institutions. A methodology is required for data quality evaluation. There are studies for data quality including ISO standards, academic studies and software to evaluate spatial data quality. ISO 19157 standard defines the data quality elements. Proprietary software such as, 1Spatial's 1Validate and ESRI's Data Reviewer offers quality evaluation based on their own classification of rules. Commonly, rule based approaches are used for geospatial data quality check. In this study, we look for the technical components to devise and implement a rule based approach with ontologies using free and open source software in semantic web context. Semantic web uses ontologies to deliver well-defined web resources and make them accessible to end-users and processes. We have created an ontology conforming to the geospatial data and defined some sample rules to show how to test data with respect to data quality elements including; attribute, topo-semantic and geometrical consistency using free and open source software. To test data against rules, sample GeoSPARQL queries are created, associated with specifications.

Individual differences in verbal working memory underlie a tradeoff between semantic and structural processing difficulty during language comprehension: An ERP investigation.

PubMed

Kim, Albert E; Oines, Leif; Miyake, Akira

2018-03-01

This study investigated the processes reflected in the widely observed N400 and P600 event-related potential (ERP) effects and tested the hypothesis that the N400 and P600 effects are functionally linked in a tradeoff relationship, constrained in part by individual differences in cognitive ability. Sixty participants read sentences, and ERP effects of semantic anomaly, relative to plausible words, were calculated for each participant. Results suggested qualitatively different ERP patterns across participants: Some individuals generated N400-dominated effects, whereas others generated P600-dominated effects, for the same stimuli. To specify the sources of individual differences in brain responses, we also derived aggregate scores for verbal working memory (WM), nonverbal WM, and language experience/knowledge, based on 6 behavioral measures administered to each participant. Multiple regression analysis pitting these 3 constructs against each other showed that a larger verbal WM capacity was significantly associated with larger P600 and smaller N400 effect amplitudes across individuals, whereas the other constructs did not predict the ERP effects. The results suggest that N400 and P600 brain responses, which may be attributable to semantic integration difficulty and structural processing, respectively, vie for expression when comprehenders encounter semantically unexpected words and that which option wins out is constrained in part by each comprehender's verbal WM capacity. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

PubMed Central

Waagmeester, Andra; Pico, Alexander R.

2016-01-01

The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web. PMID:27336457

Alignment of the UMLS semantic network with BioTop: methodology and assessment.

PubMed

Schulz, Stefan; Beisswanger, Elena; van den Hoek, László; Bodenreider, Olivier; van Mulligen, Erik M

2009-06-15

For many years, the Unified Medical Language System (UMLS) semantic network (SN) has been used as an upper-level semantic framework for the categorization of terms from terminological resources in biomedicine. BioTop has recently been developed as an upper-level ontology for the biomedical domain. In contrast to the SN, it is founded upon strict ontological principles, using OWL DL as a formal representation language, which has become standard in the semantic Web. In order to make logic-based reasoning available for the resources annotated or categorized with the SN, a mapping ontology was developed aligning the SN with BioTop. The theoretical foundations and the practical realization of the alignment are being described, with a focus on the design decisions taken, the problems encountered and the adaptations of BioTop that became necessary. For evaluation purposes, UMLS concept pairs obtained from MEDLINE abstracts by a named entity recognition system were tested for possible semantic relationships. Furthermore, all semantic-type combinations that occur in the UMLS Metathesaurus were checked for satisfiability. The effort-intensive alignment process required major design changes and enhancements of BioTop and brought up several design errors that could be fixed. A comparison between a human curator and the ontology yielded only a low agreement. Ontology reasoning was also used to successfully identify 133 inconsistent semantic-type combinations. BioTop, the OWL DL representation of the UMLS SN, and the mapping ontology are available at http://www.purl.org/biotop/.

Hemispheric differences in the recruitment of semantic processing mechanisms

PubMed Central

Kandhadai, Padmapriya; Federmeier, Kara D.

2010-01-01

This study examined how the two cerebral hemispheres recruit semantic processing mechanisms by combining event-related potential measures and visual half-field methods in a word priming paradigm in which semantic strength and predictability were manipulated using lexically associated word pairs. Activation patterns on the Late Positive Complex (LPC), linked to controlled aspects of processing, showed that previously documented left hemisphere (LH) processing benefits for word pairs with a weak forward but strong backward association stem from the ability to appreciate meaning relations in an order-independent fashion and/or strategically reorder them. Whereas there is a LH benefit for such strategic processing during comprehension in passive tasks, the present study further showed that the RH is also able to make use of these mechanisms when explicit semantic judgments are required. In both hemispheres, N400 responses, linked to initial semantic activation, were largely graded by association strength, with more amplitude reduction for forward associates and strong, symmetrically associated pairs compared to backward associates and matched weak, symmetrically associated pairs. However, responses to moderately associated pairs were more facilitated after initial presentation to the LH than to the RH. This pattern converges with sentence processing findings that point to LH advantages for using context information to predict features of likely upcoming words. Together, the results suggest that an important basis for hemispheric asymmetries in language comprehension arises from when and how each uses top-down semantic mechanisms to shape initial semantic activation over time. PMID:20638397

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

PubMed

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

2016-06-01

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

A user-centred evaluation framework for the Sealife semantic web browsers

PubMed Central

Oliver, Helen; Diallo, Gayo; de Quincey, Ed; Alexopoulou, Dimitra; Habermann, Bianca; Kostkova, Patty; Schroeder, Michael; Jupp, Simon; Khelif, Khaled; Stevens, Robert; Jawaheer, Gawesh; Madle, Gemma

2009-01-01

Background Semantically-enriched browsing has enhanced the browsing experience by providing contextualised dynamically generated Web content, and quicker access to searched-for information. However, adoption of Semantic Web technologies is limited and user perception from the non-IT domain sceptical. Furthermore, little attention has been given to evaluating semantic browsers with real users to demonstrate the enhancements and obtain valuable feedback. The Sealife project investigates semantic browsing and its application to the life science domain. Sealife's main objective is to develop the notion of context-based information integration by extending three existing Semantic Web browsers (SWBs) to link the existing Web to the eScience infrastructure. Methods This paper describes a user-centred evaluation framework that was developed to evaluate the Sealife SWBs that elicited feedback on users' perceptions on ease of use and information findability. Three sources of data: i) web server logs; ii) user questionnaires; and iii) semi-structured interviews were analysed and comparisons made between each browser and a control system. Results It was found that the evaluation framework used successfully elicited users' perceptions of the three distinct SWBs. The results indicate that the browser with the most mature and polished interface was rated higher for usability, and semantic links were used by the users of all three browsers. Conclusion Confirmation or contradiction of our original hypotheses with relation to SWBs is detailed along with observations of implementation issues. PMID:19796398

A user-centred evaluation framework for the Sealife semantic web browsers.

PubMed

Oliver, Helen; Diallo, Gayo; de Quincey, Ed; Alexopoulou, Dimitra; Habermann, Bianca; Kostkova, Patty; Schroeder, Michael; Jupp, Simon; Khelif, Khaled; Stevens, Robert; Jawaheer, Gawesh; Madle, Gemma

2009-10-01

Semantically-enriched browsing has enhanced the browsing experience by providing contextualized dynamically generated Web content, and quicker access to searched-for information. However, adoption of Semantic Web technologies is limited and user perception from the non-IT domain sceptical. Furthermore, little attention has been given to evaluating semantic browsers with real users to demonstrate the enhancements and obtain valuable feedback. The Sealife project investigates semantic browsing and its application to the life science domain. Sealife's main objective is to develop the notion of context-based information integration by extending three existing Semantic Web browsers (SWBs) to link the existing Web to the eScience infrastructure. This paper describes a user-centred evaluation framework that was developed to evaluate the Sealife SWBs that elicited feedback on users' perceptions on ease of use and information findability. Three sources of data: i) web server logs; ii) user questionnaires; and iii) semi-structured interviews were analysed and comparisons made between each browser and a control system. It was found that the evaluation framework used successfully elicited users' perceptions of the three distinct SWBs. The results indicate that the browser with the most mature and polished interface was rated higher for usability, and semantic links were used by the users of all three browsers. Confirmation or contradiction of our original hypotheses with relation to SWBs is detailed along with observations of implementation issues.

Review of the "AS-BUILT BIM" Approaches

NASA Astrophysics Data System (ADS)

Hichri, N.; Stefani, C.; De Luca, L.; Veron, P.

2013-02-01

Today, we need 3D models of heritage buildings in order to handle more efficiently projects of restoration, documentation and maintenance. In this context, developing a performing approach, based on a first phase of building survey, is a necessary step in order to build a semantically enriched digital model. For this purpose, the Building Information Modeling is an efficient tool for storing and exchanging knowledge about buildings. In order to create such a model, there are three fundamental steps: acquisition, segmentation and modeling. For these reasons, it is essential to understand and analyze this entire chain that leads to a well- structured and enriched 3D digital model. This paper proposes a survey and an analysis of the existing approaches on these topics and tries to define a new approach of semantic structuring taking into account the complexity of this chain.

Towards A Topological Framework for Integrating Semantic Information Sources

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

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

2014-09-07

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

A distributed reasoning engine ecosystem for semantic context-management in smart environments.

PubMed

Almeida, Aitor; López-de-Ipiña, Diego

2012-01-01

To be able to react adequately a smart environment must be aware of the context and its changes. Modeling the context allows applications to better understand it and to adapt to its changes. In order to do this an appropriate formal representation method is needed. Ontologies have proven themselves to be one of the best tools to do it. Semantic inference provides a powerful framework to reason over the context data. But there are some problems with this approach. The inference over semantic context information can be cumbersome when working with a large amount of data. This situation has become more common in modern smart environments where there are a lot sensors and devices available. In order to tackle this problem we have developed a mechanism to distribute the context reasoning problem into smaller parts in order to reduce the inference time. In this paper we describe a distributed peer-to-peer agent architecture of context consumers and context providers. We explain how this inference sharing process works, partitioning the context information according to the interests of the agents, location and a certainty factor. We also discuss the system architecture, analyzing the negotiation process between the agents. Finally we compare the distributed reasoning with the centralized one, analyzing in which situations is more suitable each approach.

Feature relevance assessment for the semantic interpretation of 3D point cloud data

NASA Astrophysics Data System (ADS)

Weinmann, M.; Jutzi, B.; Mallet, C.

2013-10-01

The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1.3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data. For the example of semantically interpreting 3D point cloud data, we demonstrate the great potential of smaller subsets consisting of only the most relevant features with 4 different state-of-the-art classifiers. The results reveal that, instead of including as many features as possible in order to compensate for lack of knowledge, a crucial task such as scene interpretation can be carried out with only few versatile features and even improved accuracy.

Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations

NASA Astrophysics Data System (ADS)

Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian

2018-04-01

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

Actively learning human gaze shifting paths for semantics-aware photo cropping.

PubMed

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

An image understanding system using attributed symbolic representation and inexact graph-matching

NASA Astrophysics Data System (ADS)

Eshera, M. A.; Fu, K.-S.

1986-09-01

A powerful image understanding system using a semantic-syntactic representation scheme consisting of attributed relational graphs (ARGs) is proposed for the analysis of the global information content of images. A multilayer graph transducer scheme performs the extraction of ARG representations from images, with ARG nodes representing the global image features, and the relations between features represented by the attributed branches between corresponding nodes. An efficient dynamic programming technique is employed to derive the distance between two ARGs and the inexact matching of their respective components. Noise, distortion and ambiguity in real-world images are handled through modeling in the transducer mapping rules and through the appropriate cost of error-transformation for the inexact matching of the representation. The system is demonstrated for the case of locating objects in a scene composed of complex overlapped objects, and the case of target detection in noisy and distorted synthetic aperture radar image.

The effects of self-instruction training on a deaf child's semantic and pragmatic production.

PubMed

Swanson, H L

1987-10-01

Effects of self-instruction training on the communication skills of a profoundly hearing-impaired child were studied. Self-instruction training included modeling a series of problem-solving steps in order to direct communication production. Communication production was operationalized as signed semantic and pragmatic functions. A multiple baseline was used to assess treatment and generalization (treatment variations of person and setting) effects. There was evidence to suggest that self-instruction was immediately effective on pragmatic behaviors but such behaviors were reduced when another person administered treatment. In contrast, self-instruction training had a gradual influence on semantic behaviors and those effects were maintained when treatment included a different person and setting. Implications of the clinical study were discussed.

Combined semantic and similarity search in medical image databases

NASA Astrophysics Data System (ADS)

Seifert, Sascha; Thoma, Marisa; Stegmaier, Florian; Hammon, Matthias; Kramer, Martin; Huber, Martin; Kriegel, Hans-Peter; Cavallaro, Alexander; Comaniciu, Dorin

2011-03-01

The current diagnostic process at hospitals is mainly based on reviewing and comparing images coming from multiple time points and modalities in order to monitor disease progression over a period of time. However, for ambiguous cases the radiologist deeply relies on reference literature or second opinion. Although there is a vast amount of acquired images stored in PACS systems which could be reused for decision support, these data sets suffer from weak search capabilities. Thus, we present a search methodology which enables the physician to fulfill intelligent search scenarios on medical image databases combining ontology-based semantic and appearance-based similarity search. It enabled the elimination of 12% of the top ten hits which would arise without taking the semantic context into account.

Recommendations for a Retargetable Compiler.

DTIC Science & Technology

1980-03-01

register transfer or switchin circuit level of description. AHPL 4HPL was developed for use in teaching design . Descriptions in AHPL are non -redundant...ment sytex and semantics have bean oefined. 7he language is be- sicly non -procedural, with event conditions controlling groups of actions. There is...handling temporary variables and its lack of high level control constructs can be attributed to this. B-4 TCOLada [Cat78, SLN791 TCOL was designed by R

KaBOB: ontology-based semantic integration of biomedical databases.

PubMed

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

2015-04-23

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

Fuzzy ontologies for semantic interpretation of remotely sensed images

NASA Astrophysics Data System (ADS)

Djerriri, Khelifa; Malki, Mimoun

2015-10-01

Object-based image classification consists in the assignment of object that share similar attributes to object categories. To perform such a task the remote sensing expert uses its personal knowledge, which is rarely formalized. Ontologies have been proposed as solution to represent domain knowledge agreed by domain experts in a formal and machine readable language. Classical ontology languages are not appropriate to deal with imprecision or vagueness in knowledge. Fortunately, Description Logics for the semantic web has been enhanced by various approaches to handle such knowledge. This paper presents the extension of the traditional ontology-based interpretation with fuzzy ontology of main land-cover classes in Landsat8-OLI scenes (vegetation, built-up areas, water bodies, shadow, clouds, forests) objects. A good classification of image objects was obtained and the results highlight the potential of the method to be replicated over time and space in the perspective of transferability of the procedure.

A Model for Semantic Equivalence Discovery for Harmonizing Master Data

NASA Astrophysics Data System (ADS)

Piprani, Baba

IT projects often face the challenge of harmonizing metadata and data so as to have a "single" version of the truth. Determining equivalency of multiple data instances against the given type, or set of types, is mandatory in establishing master data legitimacy in a data set that contains multiple incarnations of instances belonging to the same semantic data record . The results of a real-life application define how measuring criteria and equivalence path determination were established via a set of "probes" in conjunction with a score-card approach. There is a need for a suite of supporting models to help determine master data equivalency towards entity resolution—including mapping models, transform models, selection models, match models, an audit and control model, a scorecard model, a rating model. An ORM schema defines the set of supporting models along with their incarnation into an attribute based model as implemented in an RDBMS.

A cloud-based approach for interoperable electronic health records (EHRs).

PubMed

Bahga, Arshdeep; Madisetti, Vijay K

2013-09-01

We present a cloud-based approach for the design of interoperable electronic health record (EHR) systems. Cloud computing environments provide several benefits to all the stakeholders in the healthcare ecosystem (patients, providers, payers, etc.). Lack of data interoperability standards and solutions has been a major obstacle in the exchange of healthcare data between different stakeholders. We propose an EHR system - cloud health information systems technology architecture (CHISTAR) that achieves semantic interoperability through the use of a generic design methodology which uses a reference model that defines a general purpose set of data structures and an archetype model that defines the clinical data attributes. CHISTAR application components are designed using the cloud component model approach that comprises of loosely coupled components that communicate asynchronously. In this paper, we describe the high-level design of CHISTAR and the approaches for semantic interoperability, data integration, and security.

Design and development of linked data from the National Map

USGS Publications Warehouse

Usery, E. Lynn; Varanka, Dalia E.

2012-01-01

The development of linked data on the World-Wide Web provides the opportunity for the U.S. Geological Survey (USGS) to supply its extensive volumes of geospatial data, information, and knowledge in a machine interpretable form and reach users and applications that heretofore have been unavailable. To pilot a process to take advantage of this opportunity, the USGS is developing an ontology for The National Map and converting selected data from nine research test areas to a Semantic Web format to support machine processing and linked data access. In a case study, the USGS has developed initial methods for legacy vector and raster formatted geometry, attributes, and spatial relationships to be accessed in a linked data environment maintaining the capability to generate graphic or image output from semantic queries. The description of an initial USGS approach to developing ontology, linked data, and initial query capability from The National Map databases is presented.

An approach to define semantics for BPM systems interoperability

NASA Astrophysics Data System (ADS)

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.

The association between job stress and leisure-time physical inactivity adjusted for individual attributes: evidence from a Japanese occupational cohort survey.

PubMed

Oshio, Takashi; Tsutsumi, Akizumi; Inoue, Akiomi

2016-05-01

We examined the association between job stress and leisure-time physical inactivity, adjusting for individual time-invariant attributes. We used data from a Japanese occupational cohort survey, which included 31 025 observations of 9871 individuals. Focusing on the evolution of job stress and leisure-time physical inactivity within the same individual over time, we employed fixed-effects logistic models to examine the association between job stress and leisure-time physical inactivity. We compared the results with those in pooled cross-sectional models and fixed-effects ordered logistic models. Fixed-effects models showed that the odds ratio (OR) of physical inactivity were 22% higher for those with high strain jobs [high demands/low control; OR 1.22, 95% confidence interval (95% CI) 1.03-1.43] and 17% higher for those with active jobs (high demands/high control; OR 1.17, 95% CI 1.02-1.34) than those with low strain jobs (low demands/high control). The models also showed that the odds of physical inactivity were 28% higher for those with high effort/low reward jobs (OR 1.28, 95% CI 1.10-1.50) and 24% higher for those with high effort/high reward jobs (OR 1.24, 95% CI 1.07-1.43) than those with low effort/high reward jobs. Fixed-effects ordered logistic models led to similar results. Job stress, especially high job strain and effort-reward imbalance, was modestly associated with higher risks of physical inactivity, even after controlling for individual time-invariant attributes.

Word Naming in the L1 and L2: A Dynamic Perspective on Automatization and the Degree of Semantic Involvement in Naming.

PubMed

Plat, Rika; Lowie, Wander; de Bot, Kees

2017-01-01

Reaction time data have long been collected in order to gain insight into the underlying mechanisms involved in language processing. Means analyses often attempt to break down what factors relate to what portion of the total reaction time. From a dynamic systems theory perspective or an interaction dominant view of language processing, it is impossible to isolate discrete factors contributing to language processing, since these continually and interactively play a role. Non-linear analyses offer the tools to investigate the underlying process of language use in time, without having to isolate discrete factors. Patterns of variability in reaction time data may disclose the relative contribution of automatic (grapheme-to-phoneme conversion) processing and attention-demanding (semantic) processing. The presence of a fractal structure in the variability of a reaction time series indicates automaticity in the mental structures contributing to a task. A decorrelated pattern of variability will indicate a higher degree of attention-demanding processing. A focus on variability patterns allows us to examine the relative contribution of automatic and attention-demanding processing when a speaker is using the mother tongue (L1) or a second language (L2). A word naming task conducted in the L1 (Dutch) and L2 (English) shows L1 word processing to rely more on automatic spelling-to-sound conversion than L2 word processing. A word naming task with a semantic categorization subtask showed more reliance on attention-demanding semantic processing when using the L2. A comparison to L1 English data shows this was not only due to the amount of language use or language dominance, but also to the difference in orthographic depth between Dutch and English. An important implication of this finding is that when the same task is used to test and compare different languages, one cannot straightforwardly assume the same cognitive sub processes are involved to an equal degree using the same task in different languages.

Autobiographical memory and well-being in aging: The central role of semantic self-images.

PubMed

Rathbone, Clare J; Holmes, Emily A; Murphy, Susannah E; Ellis, Judi A

2015-05-01

Higher levels of well-being are associated with longer life expectancies and better physical health. Previous studies suggest that processes involving the self and autobiographical memory are related to well-being, yet these relationships are poorly understood. The present study tested 32 older and 32 younger adults using scales measuring well-being and the affective valence of two types of autobiographical memory: episodic autobiographical memories and semantic self-images. Results showed that valence of semantic self-images, but not episodic autobiographical memories, was highly correlated with well-being, particularly in older adults. In contrast, well-being in older adults was unrelated to performance across a range of standardised memory tasks. These results highlight the role of semantic self-images in well-being, and have implications for the development of therapeutic interventions for well-being in aging. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Encoding Sequential Information in Semantic Space Models: Comparing Holographic Reduced Representation and Random Permutation

PubMed Central

Recchia, Gabriel; Sahlgren, Magnus; Kanerva, Pentti; Jones, Michael N.

2015-01-01

Circular convolution and random permutation have each been proposed as neurally plausible binding operators capable of encoding sequential information in semantic memory. We perform several controlled comparisons of circular convolution and random permutation as means of encoding paired associates as well as encoding sequential information. Random permutations outperformed convolution with respect to the number of paired associates that can be reliably stored in a single memory trace. Performance was equal on semantic tasks when using a small corpus, but random permutations were ultimately capable of achieving superior performance due to their higher scalability to large corpora. Finally, “noisy” permutations in which units are mapped to other units arbitrarily (no one-to-one mapping) perform nearly as well as true permutations. These findings increase the neurological plausibility of random permutations and highlight their utility in vector space models of semantics. PMID:25954306

Measuring content overlap during handoff communication using distributional semantics: An exploratory study.

PubMed

Abraham, Joanna; Kannampallil, Thomas G; Srinivasan, Vignesh; Galanter, William L; Tagney, Gail; Cohen, Trevor

2017-01-01

We develop and evaluate a methodological approach to measure the degree and nature of overlap in handoff communication content within and across clinical professions. This extensible, exploratory approach relies on combining techniques from conversational analysis and distributional semantics. We audio-recorded handoff communication of residents and nurses on the General Medicine floor of a large academic hospital (n=120 resident and n=120 nurse handoffs). We measured semantic similarity, a proxy for content overlap, between resident-resident and nurse-nurse communication using multiple steps: a qualitative conversational content analysis; an automated semantic similarity analysis using Reflective Random Indexing (RRI); and comparing semantic similarity generated by RRI analysis with human ratings of semantic similarity. There was significant association between the semantic similarity as computed by the RRI method and human rating (ρ=0.88). Based on the semantic similarity scores, content overlap was relatively higher for content related to patient active problems, assessment of active problems, patient-identifying information, past medical history, and medications/treatments. In contrast, content overlap was limited on content related to allergies, family-related information, code status, and anticipatory guidance. Our approach using RRI analysis provides new opportunities for characterizing the nature and degree of overlap in handoff communication. Although exploratory, this method provides a basis for identifying content that can be used for determining shared understanding across clinical professions. Additionally, this approach can inform the development of flexibly standardized handoff tools that reflect clinical content that are most appropriate for fostering shared understanding during transitions of care. Copyright © 2016 Elsevier Inc. All rights reserved.

The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text.

PubMed

Altszyler, Edgar; Ribeiro, Sidarta; Sigman, Mariano; Fernández Slezak, Diego

2017-11-01

Computer-based dreams content analysis relies on word frequencies within predefined categories in order to identify different elements in text. As a complementary approach, we explored the capabilities and limitations of word-embedding techniques to identify word usage patterns among dream reports. These tools allow us to quantify words associations in text and to identify the meaning of target words. Word-embeddings have been extensively studied in large datasets, but only a few studies analyze semantic representations in small corpora. To fill this gap, we compared Skip-gram and Latent Semantic Analysis (LSA) capabilities to extract semantic associations from dream reports. LSA showed better performance than Skip-gram in small size corpora in two tests. Furthermore, LSA captured relevant word associations in dream collection, even in cases with low-frequency words or small numbers of dreams. Word associations in dreams reports can thus be quantified by LSA, which opens new avenues for dream interpretation and decoding. Copyright © 2017 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

The semantic representation of prejudice and stereotypes.

PubMed

Bhatia, Sudeep

2017-07-01

We use a theory of semantic representation to study prejudice and stereotyping. Particularly, we consider large datasets of newspaper articles published in the United States, and apply latent semantic analysis (LSA), a prominent model of human semantic memory, to these datasets to learn representations for common male and female, White, African American, and Latino names. LSA performs a singular value decomposition on word distribution statistics in order to recover word vector representations, and we find that our recovered representations display the types of biases observed in human participants using tasks such as the implicit association test. Importantly, these biases are strongest for vector representations with moderate dimensionality, and weaken or disappear for representations with very high or very low dimensionality. Moderate dimensional LSA models are also the best at learning race, ethnicity, and gender-based categories, suggesting that social category knowledge, acquired through dimensionality reduction on word distribution statistics, can facilitate prejudiced and stereotyped associations. Copyright © 2017 Elsevier B.V. All rights reserved.

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2001-01-01

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

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

PubMed Central

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

2001-01-01

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

BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

PubMed Central

2014-01-01

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed. PMID:24495517

Neural correlates of implicit and explicit combinatorial semantic processing

PubMed Central

Graves, William W.; Binder, Jeffrey R.; Desai, Rutvik H.; Conant, Lisa L.; Seidenberg, Mark S.

2010-01-01

Language consists of sequences of words, but comprehending phrases involves more than concatenating meanings: A boat house is a shelter for boats, whereas a summer house is a house used during summer, and a ghost house is typically uninhabited. Little is known about the brain bases of combinatorial semantic processes. We performed two fMRI experiments using familiar, highly meaningful phrases (LAKE HOUSE) and unfamiliar phrases with minimal meaning created by reversing the word order of the familiar items (HOUSE LAKE). The first experiment used a 1-back matching task to assess implicit semantic processing, and the second used a classification task to engage explicit semantic processing. These conditions required processing of the same words, but with more effective combinatorial processing in the meaningful condition. The contrast of meaningful versus reversed phrases revealed activation primarily during the classification task, to a greater extent in the right hemisphere, including right angular gyrus, dorsomedial prefrontal cortex, and bilateral posterior cingulate/precuneus, areas previously implicated in semantic processing. Positive correlations of fMRI signal with lexical (word-level) frequency occurred exclusively with the 1-back task and to a greater spatial extent on the left, including left posterior middle temporal gyrus and bilateral parahippocampus. These results reveal strong effects of task demands on engagement of lexical versus combinatorial processing and suggest a hemispheric dissociation between these levels of semantic representation. PMID:20600969

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing.

PubMed

Grisoni, Luigi; Miller, Tally McCormick; Pulvermüller, Friedemann

2017-05-03

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system-in dorsolateral hand motor areas for expected hand-related words (e.g., "write"), but in ventral motor cortex for face-related words ("talk"). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they appear. The granularity of the semantic predictions was so fine grained that the cortical sources in sensorimotor and medial prefrontal cortex even distinguished between predicted face- or hand-related action words (e.g., the words "lick" or "pick") and between affirmative and negated sentence meanings. Copyright © 2017 Grisoni et al.

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing

PubMed Central

2017-01-01

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system—in dorsolateral hand motor areas for expected hand-related words (e.g., “write”), but in ventral motor cortex for face-related words (“talk”). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they appear. The granularity of the semantic predictions was so fine grained that the cortical sources in sensorimotor and medial prefrontal cortex even distinguished between predicted face- or hand-related action words (e.g., the words “lick” or “pick”) and between affirmative and negated sentence meanings. PMID:28411271

An fMRI study of semantic processing in men with schizophrenia

PubMed Central

Kubicki, M.; McCarley, R.W.; Nestor, P.G.; Huh, T.; Kikinis, R.; Shenton, M.E.; Wible, C.G.

2009-01-01

As a means toward understanding the neural bases of schizophrenic thought disturbance, we examined brain activation patterns in response to semantically and superficially encoded words in patients with schizophrenia. Nine male schizophrenic and 9 male control subjects were tested in a visual levels of processing (LOP) task first outside the magnet and then during the fMRI scanning procedures (using a different set of words). During the experiments visual words were presented under two conditions. Under the deep, semantic encoding condition, subjects made semantic judgments as to whether the words were abstract or concrete. Under the shallow, nonsemantic encoding condition, subjects made perceptual judgments of the font size (uppercase/lowercase) of the presented words. After performance of the behavioral task, a recognition test was used to assess the depth of processing effect, defined as better performance for semantically encoded words than for perceptually encoded words. For the scanned version only, the words for both conditions were repeated in order to assess repetition-priming effects. Reaction times were assessed in both testing scenarios. Both groups showed the expected depth of processing effect for recognition, and control subjects showed the expected increased activation of the left inferior prefrontal cortex (LIPC) under semantic encoding relative to perceptual encoding conditions as well as repetition priming for semantic conditions only. In contrast, schizophrenics showed similar patterns of fMRI activation regardless of condition. Most striking in relation to controls, patients showed decreased LIFC activation concurrent with increased left superior temporal gyrus activation for semantic encoding versus shallow encoding. Furthermore, schizophrenia subjects did not show the repetition priming effect, either behaviorally or as a decrease in LIPC activity. In patients with schizophrenia, LIFC underactivation and left superior temporal gyrus overactivation for semantically encoded words may reflect a disease-related disruption of a distributed frontal temporal network that is engaged in the representation and processing of meaning of words, text, and discourse and which may underlie schizophrenic thought disturbance. PMID:14683698