Fast Distributed Dynamics of Semantic Networks via Social Media

Directory of Open Access Journals (Sweden)

Facundo Carrillo

2015-01-01

Full Text Available We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS, based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network.

Semantique et psychologie (Semantics and Psychology)

Science.gov (United States)

Le Ny, Jean-Francois

1975-01-01

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

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

Science.gov (United States)

Lim, Yon Soo

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

Semantic network analysis of vaccine sentiment in online social media.

Science.gov (United States)

Kang, Gloria J; Ewing-Nelson, Sinclair R; Mackey, Lauren; Schlitt, James T; Marathe, Achla; Abbas, Kaja M; Swarup, Samarth

2017-06-22

To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage

What is the Value Proposition of Persistent Identifiers?

Science.gov (United States)

Klump, Jens; Huber, Robert

2017-04-01

Persistent identifiers (PID) are widely used today in scientific communication and documentation. Global unique identification plus persistent resolution of links to referenced digital research objects have been strong selling points for PID Systems as enabling technical infrastructures. Novel applications of PID Systems in research now go beyond the identification of file based objects such as literature or data sets and include the identification of dynamically changing datasets accessed through web services, physical objects, persons and organisations. But not only do we see more use cases but also a proliferation of identifier systems. An analysis of PID Systems used by 1381 repositories listed in the Registry of Research Data Repositories (re3data.org, status of 14 Dec 2015) showed that many disciplinary data repositories make use of PID that are not among the systems promoted by the libraries and publishers (DOI, PURL, ARK). This indicates that a number of communities have developed their own PID Systems. This begs the question, do we need more identifier systems? What makes their value proposition more appealing than those of already existing systems? On the other hand, some of these new use cases deal with entities outside the digital domain, the original scope of application for PIDs. It is therefore necessary to critically appraise the value propositions of available PID Systems and compare these against the requirements of new use cases for PID. Undoubtedly, DOI are the most used persistent identifier in scholarly communication. It was originally designed "to link customers with publishers, facilitate electronic commerce, and enable copyright management systems." Today, the DOI system is described as providing "a technical and social infrastructure for the registration and use of persistent interoperable identifiers for use on digital networks". This example shows how value propositions can change over time. Additional value can be gained by cross

A fusion network for semantic segmentation using RGB-D data

Science.gov (United States)

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

2018-04-01

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

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Kalil A. Bispo

2015-10-01

Full Text Available 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.

Natural semantic networks in the Social Representations of Responsibility

Directory of Open Access Journals (Sweden)

Humberto Emilio Aguilera Arévalo

2010-07-01

Full Text Available The study of social representations of responsibility is a fundamental construct of the present democratic societies. Different empirical techniques such as natural semantic networks can significantly improve the approach to the object of study than the traditional associationist techniques. The present study examines natural semantic networks of six stimulus words with respect to responsibility and irresponsibility at the individual, in group and out group level in a sample of Guatemalan students.

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

Directory of Open Access Journals (Sweden)

Graham William Thompson

2014-02-01

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

Musical and verbal semantic memory: two distinct neural networks?

Science.gov (United States)

Groussard, M; Viader, F; Hubert, V; Landeau, B; Abbas, A; Desgranges, B; Eustache, F; Platel, H

2010-02-01

Semantic memory has been investigated in numerous neuroimaging and clinical studies, most of which have used verbal or visual, but only very seldom, musical material. Clinical studies have suggested that there is a relative neural independence between verbal and musical semantic memory. In the present study, "musical semantic memory" is defined as memory for "well-known" melodies without any knowledge of the spatial or temporal circumstances of learning, while "verbal semantic memory" corresponds to general knowledge about concepts, again without any knowledge of the spatial or temporal circumstances of learning. Our aim was to compare the neural substrates of musical and verbal semantic memory by administering the same type of task in each modality. We used high-resolution PET H(2)O(15) to observe 11 young subjects performing two main tasks: (1) a musical semantic memory task, where the subjects heard the first part of familiar melodies and had to decide whether the second part they heard matched the first, and (2) a verbal semantic memory task with the same design, but where the material consisted of well-known expressions or proverbs. The musical semantic memory condition activated the superior temporal area and inferior and middle frontal areas in the left hemisphere and the inferior frontal area in the right hemisphere. The verbal semantic memory condition activated the middle temporal region in the left hemisphere and the cerebellum in the right hemisphere. We found that the verbal and musical semantic processes activated a common network extending throughout the left temporal neocortex. In addition, there was a material-dependent topographical preference within this network, with predominantly anterior activation during musical tasks and predominantly posterior activation during semantic verbal tasks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

The Syntax and Semantics of Russian Non-Sentence Adverbials

DEFF Research Database (Denmark)

Lorentzen, Elena; Durst-Andersen, Per

2015-01-01

For the first time non-sentence adverbials in Russian are analyzed in their totality, i.e., from a lexical, syntactic and propositional-semantic point of view. They are classified, defined and interpreted according to four propositional structures identified in Russian: (1) state descriptions...... and (2) activity descriptions – both created by simplex verbs; (3) event descriptions and (4) process descriptions – both involving complex verbs. All four structures function as statement models and are used to represent semantic paraphrases of utterances in order to be able to show the exact...

Transfer Effects of Semantic Networks on Expert Systems: Mindtools at Work.

Science.gov (United States)

Marra, Rose M.; Jonassen, David H.

2002-01-01

Discussion of computers as mindtools focuses on semantic networks and expert systems that help learners build a representation of what they know by designing their own knowledge bases. Describes a study of undergraduates that examined the effects of building semantic networks on the construction of expert systems. (Author/LRW)

A chemical specialty semantic network for the Unified Medical Language System

Directory of Open Access Journals (Sweden)

Morrey C

2012-05-01

Full Text Available Abstract Background Terms representing chemical concepts found the Unified Medical Language System (UMLS are used to derive an expanded semantic network with mutually exclusive semantic types. The UMLS Semantic Network (SN is composed of a collection of broad categories called semantic types (STs that are assigned to concepts. Within the UMLS’s coverage of the chemical domain, we find a great deal of concepts being assigned more than one ST. This leads to the situation where the extent of a given ST may contain concepts elaborating variegated semantics. A methodology for expanding the chemical subhierarchy of the SN into a finer-grained categorization of mutually exclusive types with semantically uniform extents is presented. We call this network a Chemical Specialty Semantic Network (CSSN. A CSSN is derived automatically from the existing chemical STs and their assignments. The methodology incorporates a threshold value governing the minimum size of a type’s extent needed for inclusion in the CSSN. Thus, different CSSNs can be created by choosing different threshold values based on varying requirements. Results A complete CSSN is derived using a threshold value of 300 and having 68 STs. It is used effectively to provide high-level categorizations for a random sample of compounds from the “Chemical Entities of Biological Interest” (ChEBI ontology. The effect on the size of the CSSN using various threshold parameter values between one and 500 is shown. Conclusions The methodology has several potential applications, including its use to derive a pre-coordinated guide for ST assignments to new UMLS chemical concepts, as a tool for auditing existing concepts, inter-terminology mapping, and to serve as an upper-level network for ChEBI.

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

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

2016-01-01

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

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

Science.gov (United States)

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

2015-11-11

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

Propagating semantic information in biochemical network models

Directory of Open Access Journals (Sweden)

Schulz Marvin

2012-01-01

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

Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia.

Science.gov (United States)

Ding, Junhua; Chen, Keliang; Zhang, Weibin; Li, Ming; Chen, Yan; Yang, Qing; Lv, Yingru; Guo, Qihao; Han, Zaizhu

2017-01-01

Semantic dementia (SD) is characterized by a selective decline in semantic processing. Although the neuropsychological pattern of this disease has been identified, its topological global alterations and symptom-relevant modules in the whole-brain anatomical network have not been fully elucidated. This study aims to explore the topological alteration of anatomical network in SD and reveal the modules associated with semantic deficits in this disease. We first constructed the whole-brain white-matter networks of 20 healthy controls and 19 patients with SD. Then, the network metrics of graph theory were compared between these two groups. Finally, we separated the network of SD patients into different modules and correlated the structural integrity of each module with the severity of the semantic deficits across patients. The network of the SD patients presented a significantly reduced global efficiency, indicating that the long-distance connections were damaged. The network was divided into the following four distinctive modules: the left temporal/occipital/parietal, frontal, right temporal/occipital, and frontal/parietal modules. The first two modules were associated with the semantic deficits of SD. These findings illustrate the skeleton of the neuroanatomical network of SD patients and highlight the key role of the left temporal/occipital/parietal module and the left frontal module in semantic processing.

Semantic Blogging : Spreading the Semantic Web Meme

OpenAIRE

Cayzer, Steve

2004-01-01

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

Calculation of parameters of radial-piston reducer based on the use of functional semantic networks

Directory of Open Access Journals (Sweden)

Pashkevich V.M.

2016-12-01

Full Text Available The questions of сalculation of parameters of radial-piston reducer are considered in this article. It is used the approach which is based technologies of functional semantic networks. It is considered possibility applications of functional se-mantic networks for calculation of parameters of radial-piston reducer. Semantic networks to calculate the mass of the radial piston reducer are given.

Investigating the structure of semantic networks in low and high creative persons

Directory of Open Access Journals (Sweden)

Yoed Nissan Kenett

2014-06-01

Full Text Available According to Mednick’s (1962 theory of individual differences in creativity, creative individuals appear to have a richer and more flexible associative network than less creative individuals. Thus, creative individuals are characterized by flat (broader associations instead of steep (few, common associations associational hierarchies. To study these differences, we implement a novel computational approach to the study of semantic networks, through the analysis of free associations. The core notion of our method is that concepts in the network are related to each other by their association correlations - overlap of similar associative responses (association clouds. We began by collecting a large sample of participants who underwent several creativity measurements and used a decision tree approach to divide the sample into low and high creative groups. Next, each group underwent a free association generation paradigm which allowed us to construct and analyze the semantic networks of both groups. Comparison of the semantic memory networks of persons with low creative ability and persons with high creative ability revealed differences between the two networks. The semantic memory network of persons with low creative ability seems to be more rigid, compared to the network of persons with high creative ability, in the sense that it is more spread out and breaks apart into more sub-parts. We discuss how our findings are in accord and extend Mednick’s (1962 theory and the feasibility of using network science paradigms to investigate high level cognition.

Semantic integration to identify overlapping functional modules in protein interaction networks

Directory of Open Access Journals (Sweden)

Ramanathan Murali

2007-07-01

Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

MATRIX-VECTOR ALGORITHMS OF LOCAL POSTERIORI INFERENCE IN ALGEBRAIC BAYESIAN NETWORKS ON QUANTA PROPOSITIONS

Directory of Open Access Journals (Sweden)

A. A. Zolotin

2015-07-01

Full Text Available Posteriori inference is one of the three kinds of probabilistic-logic inferences in the probabilistic graphical models theory and the base for processing of knowledge patterns with probabilistic uncertainty using Bayesian networks. The paper deals with a task of local posteriori inference description in algebraic Bayesian networks that represent a class of probabilistic graphical models by means of matrix-vector equations. The latter are essentially based on the use of tensor product of matrices, Kronecker degree and Hadamard product. Matrix equations for calculating posteriori probabilities vectors within posteriori inference in knowledge patterns with quanta propositions are obtained. Similar equations of the same type have already been discussed within the confines of the theory of algebraic Bayesian networks, but they were built only for the case of posteriori inference in the knowledge patterns on the ideals of conjuncts. During synthesis and development of matrix-vector equations on quanta propositions probability vectors, a number of earlier results concerning normalizing factors in posteriori inference and assignment of linear projective operator with a selector vector was adapted. We consider all three types of incoming evidences - deterministic, stochastic and inaccurate - combined with scalar and interval estimation of probability truth of propositional formulas in the knowledge patterns. Linear programming problems are formed. Their solution gives the desired interval values of posterior probabilities in the case of inaccurate evidence or interval estimates in a knowledge pattern. That sort of description of a posteriori inference gives the possibility to extend the set of knowledge pattern types that we can use in the local and global posteriori inference, as well as simplify complex software implementation by use of existing third-party libraries, effectively supporting submission and processing of matrices and vectors when

Fully convolutional network with cluster for semantic segmentation

Science.gov (United States)

Ma, Xiao; Chen, Zhongbi; Zhang, Jianlin

2018-04-01

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

Evaluation of the Project Management Competences Based on the Semantic Networks

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

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

Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems

Directory of Open Access Journals (Sweden)

Abdul-Wahid Mohammed

2017-01-01

Full Text Available The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home.

Knowledge represented using RDF semantic network in the concept of semantic web

Energy Technology Data Exchange (ETDEWEB)

Lukasova, A., E-mail: alena.lukasova@osu.cz; Vajgl, M., E-mail: marek.vajgl@osu.cz; Zacek, M., E-mail: martin.zacek@osu.cz [Department of Informatics and Computers, Faculty of Science, University of Ostrava 30. dubna 22, 701 03 Ostrava, Czech Republic http://prf.osu.eu/kip/ (Czech Republic)

2016-06-08

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDF to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.

Knowledge represented using RDF semantic network in the concept of semantic web

International Nuclear Information System (INIS)

Lukasova, A.; Vajgl, M.; Zacek, M.

2016-01-01

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDF to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.

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

Science.gov (United States)

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

Proposition algebra

NARCIS (Netherlands)

Bergstra, J.A.; Ponse, A.

2011-01-01

Sequential propositional logic deviates from conventional propositional logic by taking into account that during the sequential evaluation of a propositional statement, atomic propositions may yield different Boolean values at repeated occurrences. We introduce "free valuations" to capture this

Scientific Knowledge Discovery in Complex Semantic Networks of Geophysical Systems

Science.gov (United States)

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.

A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links

Science.gov (United States)

Türker, Ilker; Sulak, Eyüb Ekmel

2018-02-01

Complex network studies, as an interdisciplinary framework, span a large variety of subjects including social media. In social networks, several mechanisms generate miscellaneous structures like friendship networks, mention networks, tag networks, etc. Focusing on tag networks (namely, hashtags in twitter), we made a two-layer analysis of tag networks from a massive dataset of Twitter entries. The first layer is constructed by converting the co-occurrences of these tags in a single entry (tweet) into links, while the second layer is constructed converting the semantic relations of the tags into links. We observed that the universal properties of the real networks like small-world property, clustering and power-law distributions in various network parameters are also evident in the multilayer network of hashtags. Moreover, we outlined that co-occurrences of hashtags in tweets are mostly coupled with semantic relations, whereas a small number of semantically unrelated, therefore random links reduce node separation and network diameter in the co-occurrence network layer. Together with the degree distributions, the power-law consistencies of degree difference, edge weight and cosine similarity distributions in both layers are also appealing forms of Zipf’s law evident in nature.

Alignment of the UMLS semantic network with BioTop: Methodology and assessment

NARCIS (Netherlands)

S. Schulz; E. Beisswanger (Elena); L. van den Hoek (László); O. Bodenreider (Olivier); E.M. van Mulligen (Erik)

2009-01-01

textabstractMotivation: 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

Semantic computing and language knowledge bases

Science.gov (United States)

Wang, Lei; Wang, Houfeng; Yu, Shiwen

2017-09-01

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

Path Network Recovery Using Remote Sensing Data and Geospatial-Temporal Semantic Graphs

Energy Technology Data Exchange (ETDEWEB)

McLendon, William C.,; Brost, Randolph

2016-05-01

Remote sensing systems produce large volumes of high-resolution images that are difficult to search. The GeoGraphy (pronounced Geo-Graph-y) framework [2, 20] encodes remote sensing imagery into a geospatial-temporal semantic graph representation to enable high level semantic searches to be performed. Typically scene objects such as buildings and trees tend to be shaped like blocks with few holes, but other shapes generated from path networks tend to have a large number of holes and can span a large geographic region due to their connectedness. For example, we have a dataset covering the city of Philadelphia in which there is a single road network node spanning a 6 mile x 8 mile region. Even a simple question such as "find two houses near the same street" might give unexpected results. More generally, nodes arising from networks of paths (roads, sidewalks, trails, etc.) require additional processing to make them useful for searches in GeoGraphy. We have assigned the term Path Network Recovery to this process. Path Network Recovery is a three-step process involving (1) partitioning the network node into segments, (2) repairing broken path segments interrupted by occlusions or sensor noise, and (3) adding path-aware search semantics into GeoQuestions. This report covers the path network recovery process, how it is used, and some example use cases of the current capabilities.

Insensitive Enough Semantics

Directory of Open Access Journals (Sweden)

Richard Vallée

2006-06-01

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

Translation-aware semantic segmentation via conditional least-square generative adversarial networks

Science.gov (United States)

Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

2017-10-01

Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

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

Science.gov (United States)

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.

Trust estimation of the semantic web using semantic web clustering

Science.gov (United States)

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

2017-05-01

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

Spreading Activation in an Attractor Network with Latching Dynamics: Automatic Semantic Priming Revisited

Science.gov (United States)

Lerner, Itamar; Bentin, Shlomo; Shriki, Oren

2012-01-01

Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified…

Social networking sites use and the morphology of a social-semantic brain network.

Science.gov (United States)

Turel, Ofir; He, Qinghua; Brevers, Damien; Bechara, Antoine

2017-09-30

Social lives have shifted, at least in part, for large portions of the population to social networking sites. How such lifestyle changes may be associated with brain structures is still largely unknown. In this manuscript, we describe two preliminary studies aimed at exploring this issue. The first study (n = 276) showed that Facebook users reported on increased social-semantic and mentalizing demands, and that such increases were positively associated with people's level of Facebook use. The second study (n = 33) theorized on and examined likely anatomical correlates of such changes in demands on the brain. Findings indicated that the grey matter volumes of the posterior parts of the bilateral middle and superior temporal, and left fusiform gyri were positively associated with the level of Facebook use. These results provided preliminary evidence that grey matter volumes of brain structures involved in social-semantic and mentalizing tasks may be linked to the extent of social networking sites use.

Semantic diff as the basis for knowledge base versioning

CSIR Research Space (South Africa)

Franconi, E

2010-05-01

Full Text Available to restrict our attention to finitely generated propositional logics, and show that our semantic framework can be represented syntactically in a particular kind of normal form, referred to as ordered complete conjunctive normal form or oc-CNF. This is followed...

Propositional Logics of Dependence

NARCIS (Netherlands)

Yang, F.; Väänänen, J.

2016-01-01

In this paper, we study logics of dependence on the propositional level. We prove that several interesting propositional logics of dependence, including propositional dependence logic, propositional intuitionistic dependence logic as well as propositional inquisitive logic, are expressively complete

Using Semantic Linking to Understand Persons’ Networks Extracted from Text

Directory of Open Access Journals (Sweden)

Alessio Palmero Aprosio

2017-11-01

Full Text Available In this work, we describe a methodology to interpret large persons’ networks extracted from text by classifying cliques using the DBpedia ontology. The approach relies on a combination of NLP, Semantic web technologies, and network analysis. The classification methodology that first starts from single nodes and then generalizes to cliques is effective in terms of performance and is able to deal also with nodes that are not linked to Wikipedia. The gold standard manually developed for evaluation shows that groups of co-occurring entities share in most of the cases a category that can be automatically assigned. This holds for both languages considered in this study. The outcome of this work may be of interest to enhance the readability of large networks and to provide an additional semantic layer on top of cliques. This would greatly help humanities scholars when dealing with large amounts of textual data that need to be interpreted or categorized. Furthermore, it represents an unsupervised approach to automatically extend DBpedia starting from a corpus.

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

Science.gov (United States)

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

2016-01-01

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

Diagnostic and prognostic role of semantic processing in preclinical Alzheimer's disease.

Science.gov (United States)

Venneri, Annalena; Jahn-Carta, Caroline; Marco, Matteo De; Quaranta, Davide; Marra, Camillo

2018-06-13

Relatively spared during most of the timeline of normal aging, semantic memory shows a subtle yet measurable decline even during the pre-clinical stage of Alzheimer's disease. This decline is thought to reflect early neurofibrillary changes and impairment is detectable using tests of language relying on lexical-semantic abilities. A promising approach is the characterization of semantic parameters such as typicality and age of acquisition of words, and propositional density from verbal output. Seminal research like the Nun Study or the analysis of the linguistic decline of famous writers and politicians later diagnosed with Alzheimer's disease supports the early diagnostic value of semantic processing and semantic memory. Moreover, measures of these skills may play an important role for the prognosis of patients with mild cognitive impairment.

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

Science.gov (United States)

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.

A Drone Remote Sensing for Virtual Reality Simulation System for Forest Fires: Semantic Neural Network Approach

Science.gov (United States)

Narasimha Rao, Gudikandhula; Jagadeeswara Rao, Peddada; Duvvuru, Rajesh

2016-09-01

Wild fires have significant impact on atmosphere and lives. The demand of predicting exact fire area in forest may help fire management team by using drone as a robot. These are flexible, inexpensive and elevated-motion remote sensing systems that use drones as platforms are important for substantial data gaps and supplementing the capabilities of manned aircraft and satellite remote sensing systems. In addition, powerful computational tools are essential for predicting certain burned area in the duration of a forest fire. The reason of this study is to built up a smart system based on semantic neural networking for the forecast of burned areas. The usage of virtual reality simulator is used to support the instruction process of fire fighters and all users for saving of surrounded wild lives by using a naive method Semantic Neural Network System (SNNS). Semantics are valuable initially to have a enhanced representation of the burned area prediction and better alteration of simulation situation to the users. In meticulous, consequences obtained with geometric semantic neural networking is extensively superior to other methods. This learning suggests that deeper investigation of neural networking in the field of forest fires prediction could be productive.

A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions.

Science.gov (United States)

Taylor, Duncan; Biedermann, Alex; Hicks, Tacha; Champod, Christophe

2018-03-01

The hierarchy of propositions has been accepted amongst the forensic science community for some time. It is also accepted that the higher up the hierarchy the propositions are, against which the scientist are competent to evaluate their results, the more directly useful the testimony will be to the court. Because each case represents a unique set of circumstances and findings, it is difficult to come up with a standard structure for evaluation. One common tool that assists in this task is Bayesian networks (BNs). There is much diversity in the way that BN can be constructed. In this work, we develop a template for BN construction that allows sufficient flexibility to address most cases, but enough commonality and structure that the flow of information in the BN is readily recognised at a glance. We provide seven steps that can be used to construct BNs within this structure and demonstrate how they can be applied, using a case example. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A Proposition Of Knowledge Management Methodology For The Purpose Of Reasoning With The Use Of An Upper-Ontology

Directory of Open Access Journals (Sweden)

Kamil Szymański

2007-01-01

Full Text Available This article describes a proposition of knowledge organization for the purpose of reasoningusing an upper-ontology. It presents a model of integrated ontologies architecture whichconsists of a domain ontologies layer with instances, a shared upper-ontology layer withadditional rules and a layer of ontologies mapping concrete domain ontologies with the upperontology.Thanks to the upper-ontology, new facts were concluded from domain ontologiesduring the reasoning process. A practical realization proposition is given as well. It is basedon some popular SemanticWeb technologies and tools, such as OWL, SWRL, nRQL, Prot´eg´eand Racer.

Decomposing social and semantic networks in emerging "big data" research

NARCIS (Netherlands)

Park, H.W.; Leydesdorff, L.

2013-01-01

This paper examines the structural patterns of networks of internationally co-authored SCI papers in the domain of research driven by big data and provides an empirical analysis of semantic patterns of paper titles. The results based on data collected from the DVD version of the 2011 SCI database

The Semantic Network Model of Creativity: Analysis of Online Social Media Data

Science.gov (United States)

Yu, Feng; Peng, Theodore; Peng, Kaiping; Zheng, Sam Xianjun; Liu, Zhiyuan

2016-01-01

The central hypothesis of Semantic Network Model of Creativity is that creative people, who are exposed to more information that are both novel and useful, will have more interconnections between event schemas in their associations. The networks of event schemas in creative people's minds were expected to be wider and denser than those in less…

Mapping the Structure of Semantic Memory

Science.gov (United States)

Morais, Ana Sofia; Olsson, Henrik; Schooler, Lael J.

2013-01-01

Aggregating snippets from the semantic memories of many individuals may not yield a good map of an individual's semantic memory. The authors analyze the structure of semantic networks that they sampled from individuals through a new snowball sampling paradigm during approximately 6 weeks of 1-hr daily sessions. The semantic networks of individuals…

Semantic Segmentation of Convolutional Neural Network for Supervised Classification of Multispectral Remote Sensing

Science.gov (United States)

Xue, L.; Liu, C.; Wu, Y.; Li, H.

2018-04-01

Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remote Sensing Imagery is a challenging task. Although the neural network has achieved excellent performance in semantic segmentation in the last years, there are a few of works using CNN for ground object segmentation and the results could be further improved. This paper used convolution neural network named U-Net, its structure has a contracting path and an expansive path to get high resolution output. In the network , We added BN layers, which is more conducive to the reverse pass. Moreover, after upsampling convolution , we add dropout layers to prevent overfitting. They are promoted to get more precise segmentation results. To verify this network architecture, we used a Kaggle dataset. Experimental results show that U-Net achieved good performance compared with other architectures, especially in high-resolution remote sensing imagery.

METHODS OF TEXT INFORMATION CLASSIFICATION ON THE BASIS OF ARTIFICIAL NEURAL AND SEMANTIC NETWORKS

Directory of Open Access Journals (Sweden)

L. V. Serebryanaya

2016-01-01

Full Text Available The article covers the use of perseptron, Hopfild artificial neural network and semantic network for classification of text information. Network training algorithms are studied. An algorithm of inverse mistake spreading for perceptron network and convergence algorithm for Hopfild network are implemented. On the basis of the offered models and algorithms automatic text classification software is developed and its operation results are evaluated.

Deep Neural Network-Based Chinese Semantic Role Labeling

Institute of Scientific and Technical Information of China (English)

ZHENG Xiaoqing; CHEN Jun; SHANG Guoqiang

2017-01-01

A recent trend in machine learning is to use deep architec-tures to discover multiple levels of features from data, which has achieved impressive results on various natural language processing (NLP) tasks. We propose a deep neural network-based solution to Chinese semantic role labeling (SRL) with its application on message analysis. The solution adopts a six-step strategy: text normalization, named entity recognition (NER), Chinese word segmentation and part-of-speech (POS) tagging, theme classification, SRL, and slot filling. For each step, a novel deep neural network - based model is designed and optimized, particularly for smart phone applications. Ex-periment results on all the NLP sub - tasks of the solution show that the proposed neural networks achieve state-of-the-art performance with the minimal computational cost. The speed advantage of deep neural networks makes them more competitive for large-scale applications or applications requir-ing real-time response, highlighting the potential of the pro-posed solution for practical NLP systems.

Automated fault tree synthesis by semantic network modeling, rulebased development and recursive 3-value procedure

International Nuclear Information System (INIS)

Kumamoto, Hiromitsu; Henley, E.J.

1995-01-01

A concept of flow is introduced to represent any material, information, energy, activity, or phenomenon which can move or propagate along flow paths to cause events specific to the system to be analyzed. A graphical equipment library is given to represent typical types of 'generation rate' and 'aperture' controllers. The system is modeled by a semantic network with labeled arrows showing effect to cause (backward) relationships between flow and equipment nodes. A correspondence between the equipment library and the system components is established, and the semantic network is constructed by integrating network fragments in the library. Fixed and/or free boundary conditions can be specified explicitly for flow or equipment nodes. Forward-chaining event development rules locally trace the labeled arrows, while a 3-value procedure guides the FT generation by recursive rule applications. The rules are obtained from tables and equipment definitions. The 3-value logic is used to truncate FTs according to the boundary conditions. Different FTs are generated for different top events and boundary conditions, given a semantic network model. FT modules and their hierarchies can be identified by examining network theoretic properties of flow nodes. The proposed approach is demonstrated for a relay system, a hypothetical swimming pool reactor and a chemical reactor

SEMANTIC NETWORKS: THEORETICAL, TECHNICAL, METHODOLOGIC AND ANALYTICAL ASPECTS

Directory of Open Access Journals (Sweden)

José Ángel Vera Noriega

2005-09-01

Full Text Available This work is a review of the methodological procedures and cares for the measurement of the connotative meanings which will be used in the elaboration of instruments with ethnic validity. Beginning from the techniques originally proposed by Figueroa et al. (1981 and later described by Lagunes (1993, the intention is to offer a didactic panorama to carry out the measurement by semantic networks introducing some recommendations derived from the studies performed with this method.

ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation

OpenAIRE

Visin, Francesco; Ciccone, Marco; Romero, Adriana; Kastner, Kyle; Cho, Kyunghyun; Bengio, Yoshua; Matteucci, Matteo; Courville, Aaron

2015-01-01

We propose a structured prediction architecture, which exploits the local generic features extracted by Convolutional Neural Networks and the capacity of Recurrent Neural Networks (RNN) to retrieve distant dependencies. The proposed architecture, called ReSeg, is based on the recently introduced ReNet model for image classification. We modify and extend it to perform the more challenging task of semantic segmentation. Each ReNet layer is composed of four RNN that sweep the image horizontally ...

Distributed Database Semantic Integration of Wireless Sensor Network to Access the Environmental Monitoring System

Directory of Open Access Journals (Sweden)

Ubaidillah Umar

2018-06-01

Full Text Available A wireless sensor network (WSN works continuously to gather information from sensors that generate large volumes of data to be handled and processed by applications. Current efforts in sensor networks focus more on networking and development services for a variety of applications and less on processing and integrating data from heterogeneous sensors. There is an increased need for information to become shareable across different sensors, database platforms, and applications that are not easily implemented in traditional database systems. To solve the issue of these large amounts of data from different servers and database platforms (including sensor data, a semantic sensor web service platform is needed to enable a machine to extract meaningful information from the sensor’s raw data. This additionally helps to minimize and simplify data processing and to deduce new information from existing data. This paper implements a semantic web data platform (SWDP to manage the distribution of data sensors based on the semantic database system. SWDP uses sensors for temperature, humidity, carbon monoxide, carbon dioxide, luminosity, and noise. The system uses the Sesame semantic web database for data processing and a WSN to distribute, minimize, and simplify information processing. The sensor nodes are distributed in different places to collect sensor data. The SWDP generates context information in the form of a resource description framework. The experiment results demonstrate that the SWDP is more efficient than the traditional database system in terms of memory usage and processing time.

Building a transnational biosurveillance network using semantic web technologies: requirements, design, and preliminary evaluation.

Science.gov (United States)

Teodoro, Douglas; Pasche, Emilie; Gobeill, Julien; Emonet, Stéphane; Ruch, Patrick; Lovis, Christian

2012-05-29

Antimicrobial resistance has reached globally alarming levels and is becoming a major public health threat. Lack of efficacious antimicrobial resistance surveillance systems was identified as one of the causes of increasing resistance, due to the lag time between new resistances and alerts to care providers. Several initiatives to track drug resistance evolution have been developed. However, no effective real-time and source-independent antimicrobial resistance monitoring system is available publicly. To design and implement an architecture that can provide real-time and source-independent antimicrobial resistance monitoring to support transnational resistance surveillance. In particular, we investigated the use of a Semantic Web-based model to foster integration and interoperability of interinstitutional and cross-border microbiology laboratory databases. Following the agile software development methodology, we derived the main requirements needed for effective antimicrobial resistance monitoring, from which we proposed a decentralized monitoring architecture based on the Semantic Web stack. The architecture uses an ontology-driven approach to promote the integration of a network of sentinel hospitals or laboratories. Local databases are wrapped into semantic data repositories that automatically expose local computing-formalized laboratory information in the Web. A central source mediator, based on local reasoning, coordinates the access to the semantic end points. On the user side, a user-friendly Web interface provides access and graphical visualization to the integrated views. We designed and implemented the online Antimicrobial Resistance Trend Monitoring System (ARTEMIS) in a pilot network of seven European health care institutions sharing 70+ million triples of information about drug resistance and consumption. Evaluation of the computing performance of the mediator demonstrated that, on average, query response time was a few seconds (mean 4.3, SD 0.1 × 10

Socio-semantic Networks of Research Publications in the Learning Analytics Community

NARCIS (Netherlands)

Fazeli, Soude; Drachsler, Hendrik; Sloep, Peter

2013-01-01

Fazeli, S., Drachsler, H., & Sloep, P. B. (2013). Socio-semantic Networks of Research Publications in the Learning Analytics Community. In M. d'Aquin, S. Dietze, H. Drachsler, E. Herder, & D. Taibi (Eds.), Linked data challenge, Learning Analytic and Knowledge (LAK13) (pp. 6-10). Vol. 974, Leuven,

Proposition algebra with projective limits

NARCIS (Netherlands)

Bergstra, J.A.; Ponse, A.

2008-01-01

Sequential propositional logic deviates from ordinary propositional logic by taking into account that during the sequential evaluation of a proposition, atomic propositions may yield different Boolean values at repeated occurrences. We introduce `free reactive valuations' to capture this dynamics of

From Logic Programming Semantics to the Consistency of Syntactical Treatments of Knowledge and Belief

DEFF Research Database (Denmark)

Bolander, Thomas

2003-01-01

that we can keep the predicate approach if we make suitable restrictions to our set of epistemic axioms. Their results are proved by careful translations from corresponding modal formalisms. In the present paper we show that their results fit nicely into the framework of logic programming semantics......, in that we show their results to be corollaries of well-known results in this field. This does not only allow us to demonstrate a close connection between consistency problems in the syntactic treatment of propositional attitudes and problems in semantics for logic programs, but it also allows us......This paper concerns formal theories for reasoning about the knowledge and belief of agents. It has seemed attractive to researchers in artificial intelligence to formalise these propositional attitudes as predicates of first-order predicate logic. This allows the agents to express stronger...

Exploring ideation: Knowledge development in science through the lens of semantic and social networks

NARCIS (Netherlands)

Moser, C.; Birkholz, J.M.; Deichmann, D.; Hellsten, I.; Wang, S.

2013-01-01

In this paper, we explore changes in both structural and semantic characteristics of a scientific social network. We trace the emergence of knowledge, what we refer to as ideation, through publication data from two conferences in a sub-field of Computer Science. Social network analysis is used to

Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

Science.gov (United States)

Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

2018-05-01

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

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

Directory of Open Access Journals (Sweden)

Mohamed L Seghier

2012-08-01

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

Squeeze-SegNet: a new fast deep convolutional neural network for semantic segmentation

Science.gov (United States)

Nanfack, Geraldin; Elhassouny, Azeddine; Oulad Haj Thami, Rachid

2018-04-01

The recent researches in Deep Convolutional Neural Network have focused their attention on improving accuracy that provide significant advances. However, if they were limited to classification tasks, nowadays with contributions from Scientific Communities who are embarking in this field, they have become very useful in higher level tasks such as object detection and pixel-wise semantic segmentation. Thus, brilliant ideas in the field of semantic segmentation with deep learning have completed the state of the art of accuracy, however this architectures become very difficult to apply in embedded systems as is the case for autonomous driving. We present a new Deep fully Convolutional Neural Network for pixel-wise semantic segmentation which we call Squeeze-SegNet. The architecture is based on Encoder-Decoder style. We use a SqueezeNet-like encoder and a decoder formed by our proposed squeeze-decoder module and upsample layer using downsample indices like in SegNet and we add a deconvolution layer to provide final multi-channel feature map. On datasets like Camvid or City-states, our net gets SegNet-level accuracy with less than 10 times fewer parameters than SegNet.

Semantic and episodic memory of music are subserved by distinct neural networks.

Science.gov (United States)

Platel, Hervé; Baron, Jean-Claude; Desgranges, Béatrice; Bernard, Frédéric; Eustache, Francis

2003-09-01

Numerous functional imaging studies have shown that retrieval from semantic and episodic memory is subserved by distinct neural networks. However, these results were essentially obtained with verbal and visuospatial material. The aim of this work was to determine the neural substrates underlying the semantic and episodic components of music using familiar and nonfamiliar melodic tunes. To study musical semantic memory, we designed a task in which the instruction was to judge whether or not the musical extract was felt as "familiar." To study musical episodic memory, we constructed two delayed recognition tasks, one containing only familiar and the other only nonfamiliar items. For each recognition task, half of the extracts (targets) were presented in the prior semantic task. The episodic and semantic tasks were to be contrasted by a comparison to two perceptive control tasks and to one another. Cerebral blood flow was assessed by means of the oxygen-15-labeled water injection method, using high-resolution PET. Distinct patterns of activations were found. First, regarding the episodic memory condition, bilateral activations of the middle and superior frontal gyri and precuneus (more prominent on the right side) were observed. Second, the semantic memory condition disclosed extensive activations in the medial and orbital frontal cortex bilaterally, the left angular gyrus, and predominantly the left anterior part of the middle temporal gyri. The findings from this study are discussed in light of the available neuropsychological data obtained in brain-damaged subjects and functional neuroimaging studies.

Alignment of the UMLS semantic network with BioTop: methodology and assessment.

Science.gov (United States)

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/.

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

Science.gov (United States)

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

2014-01-01

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

[Semantic Network Analysis of Online News and Social Media Text Related to Comprehensive Nursing Care Service].

Science.gov (United States)

Kim, Minji; Choi, Mona; Youm, Yoosik

2017-12-01

As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies. © 2017 Korean Society of Nursing Science

Semantic Network and Frame Knowledge Representation Formalisms in Artificial Intelligence

OpenAIRE

Rashid, Pshtiwan Qader

2015-01-01

ABSTRACT: Choosing a suitable method to represent the knowledge concerning the real world is one of the major issues involved in Artificial Intelligence. The purpose of this research is to consider the important beneficial roles of semantic network and frame formalisms for knowledge representation in Artificial Intelligence. The basic properties of the above methods for appropriate structuring and arranging the knowledge are presented. Some types of relationships, the conceptual graph...

Value Proposition Canvas

DEFF Research Database (Denmark)

Kyhnau, Jan Glæsner

2017-01-01

Alexander Osterwalders Value Proposition Canvas hjælper virksomheder med at udvikle produkter og services, som kunderne rent faktisk vil have. Modellen zoomer ind på de to grundlæggende byggesten i Business Model Canvas Customer Segments og Value Propositions og kortlægger, hvilket match der er...... mellem kundernes behov og virksomhedens evne til at opfylde disse. Modellen afslører gaps og dermed hvilke forbedringer eller innovationer der er brug for. "Value Proposition Canvas" er et kapitel i bogen "Marketingmodeller" - en kort og overskuelig håndbog, værktøjskasse og brugervejledning med de...

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

Science.gov (United States)

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

2014-02-01

A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.

The association of personal semantic memory to identity representations: insight into higher-order networks of autobiographical contents.

Science.gov (United States)

Grilli, Matthew D

2017-11-01

Identity representations are higher-order knowledge structures that organise autobiographical memories on the basis of personality and role-based themes of one's self-concept. In two experiments, the extent to which different types of personal semantic content are reflected in these higher-order networks of memories was investigated. Healthy, young adult participants generated identity representations that varied in remoteness of formation and verbally reflected on these themes in an open-ended narrative task. The narrative responses were scored for retrieval of episodic, experience-near personal semantic and experience-far (i.e., abstract) personal semantic contents. Results revealed that to reflect on remotely formed identity representations, experience-far personal semantic contents were retrieved more than experience-near personal semantic contents. In contrast, to reflect on recently formed identity representations, experience-near personal semantic contents were retrieved more than experience-far personal semantic contents. Although episodic memory contents were retrieved less than both personal semantic content types to reflect on remotely formed identity representations, this content type was retrieved at a similar frequency as experience-far personal semantic content to reflect on recently formed identity representations. These findings indicate that the association of personal semantic content to identity representations is robust and related to time since acquisition of these knowledge structures.

Information retrieval system with ability of analogical inference using semantic network and function of fuzzification

Energy Technology Data Exchange (ETDEWEB)

Nakamura, K; Iwai, S

1982-01-01

In information retrieval system, it is necessary to grasp user's subject of interest in order to present appropriate documents to the user. In this paper, the authors propose a model of human ability of analogical inference based on association between key words and, using it, construct an information retrieval system in which the computer with the ability learns its user's subject of interest through question-answering with the user. In this system, the association between key words is represented by a semantic network, and a function of fuzzification of input information is introduced in the semantic network to implement the ability of analogical inference based on the association. Finally, the effect of analogical inference on the learning efficiency of the system is investigated. 5 references.

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

Science.gov (United States)

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.

Relating Sequent Calculi for Bi-intuitionistic Propositional Logic

Directory of Open Access Journals (Sweden)

Luís Pinto

2011-01-01

Full Text Available Bi-intuitionistic logic is the conservative extension of intuitionistic logic with a connective dual to implication. It is sometimes presented as a symmetric constructive subsystem of classical logic. In this paper, we compare three sequent calculi for bi-intuitionistic propositional logic: (1 a basic standard-style sequent calculus that restricts the premises of implication-right and exclusion-left inferences to be single-conclusion resp. single-assumption and is incomplete without the cut rule, (2 the calculus with nested sequents by Gore et al., where a complete class of cuts is encapsulated into special "unnest" rules and (3 a cut-free labelled sequent calculus derived from the Kripke semantics of the logic. We show that these calculi can be translated into each other and discuss the ineliminable cuts of the standard-style sequent calculus.

Evaluating forensic biology results given source level propositions.

Science.gov (United States)

Taylor, Duncan; Abarno, Damien; Hicks, Tacha; Champod, Christophe

2016-03-01

The evaluation of forensic evidence can occur at any level within the hierarchy of propositions depending on the question being asked and the amount and type of information that is taken into account within the evaluation. Commonly DNA evidence is reported given propositions that deal with the sub-source level in the hierarchy, which deals only with the possibility that a nominated individual is a source of DNA in a trace (or contributor to the DNA in the case of a mixed DNA trace). We explore the use of information obtained from examinations, presumptive and discriminating tests for body fluids, DNA concentrations and some case circumstances within a Bayesian network in order to provide assistance to the Courts that have to consider propositions at source level. We use a scenario in which the presence of blood is of interest as an exemplar and consider how DNA profiling results and the potential for laboratory error can be taken into account. We finish with examples of how the results of these reports could be presented in court using either numerical values or verbal descriptions of the results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Strategic framing in the BP crisis: A semantic network analysis of associative frames

NARCIS (Netherlands)

Schultz, F.; Kleinnijenhuis, J.; Oegema, D.; Utz, S.; van Atteveldt, W.H.

2012-01-01

This paper contributes to the analysis of the interplay of public relations and news in crisis situations, and the conceptualization of strategic framing by introducing the idea of associative frames and the method of semantic network analysis to the PR research field. By building on a more advanced

Concept typicality responses in the semantic memory network.

Science.gov (United States)

Santi, Andrea; Raposo, Ana; Frade, Sofia; Marques, J Frederico

2016-12-01

For decades concept typicality has been recognized as critical to structuring conceptual knowledge, but only recently has typicality been applied in better understanding the processes engaged by the neurological network underlying semantic memory. This previous work has focused on one region within the network - the Anterior Temporal Lobe (ATL). The ATL responds negatively to concept typicality (i.e., the more atypical the item, the greater the activation in the ATL). To better understand the role of typicality in the entire network, we ran an fMRI study using a category verification task in which concept typicality was manipulated parametrically. We argue that typicality is relevant to both amodal feature integration centers as well as category-specific regions. Both the Inferior Frontal Gyrus (IFG) and ATL demonstrated a negative correlation with typicality, whereas inferior parietal regions showed positive effects. We interpret this in light of functional theories of these regions. Interactions between category and typicality were not observed in regions classically recognized as category-specific, thus, providing an argument against category specific regions, at least with fMRI. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG

Directory of Open Access Journals (Sweden)

Wenquan Jin

2018-02-01

Full Text Available Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention. Several solutions are proposed in the literature based on manual interpretation through explicit programming. However, programmatically implementing the interpretation of the data sender and data receiver in the e-Health system for the data transmission is counterproductive as modification will be required for each new device added into the system. In this paper, an e-Health system with the Semantic Sensor Network (SSN is proposed to address the device interoperability issue. In the proposed system, we have used IETF YANG for modeling the semantic e-Health data to represent the information of e-Health sensors. This modeling scheme helps in provisioning semantic interoperability between devices and expressing the sensing data in a user-friendly manner. For this purpose, we have developed an ontology for e-Health data that supports different styles of data formats. The ontology is defined in YANG for provisioning semantic interpretation of sensing data in the system by constructing meta-models of e-Health sensors. The proposed approach assists in the auto-configuration of eHealth sensors and querying the sensor network with semantic interoperability support for the e-Health system.

A neural network model of semantic memory linking feature-based object representation and words.

Science.gov (United States)

Cuppini, C; Magosso, E; Ursino, M

2009-06-01

Recent theories in cognitive neuroscience suggest that semantic memory is a distributed process, which involves many cortical areas and is based on a multimodal representation of objects. The aim of this work is to extend a previous model of object representation to realize a semantic memory, in which sensory-motor representations of objects are linked with words. The model assumes that each object is described as a collection of features, coded in different cortical areas via a topological organization. Features in different objects are segmented via gamma-band synchronization of neural oscillators. The feature areas are further connected with a lexical area, devoted to the representation of words. Synapses among the feature areas, and among the lexical area and the feature areas are trained via a time-dependent Hebbian rule, during a period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from acoustic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits).

Construction of coffee transcriptome networks based on gene annotation semantics

Directory of Open Access Journals (Sweden)

Castillo Luis F.

2012-12-01

Full Text Available Gene annotation is a process that encompasses multiple approaches on the analysis of nucleic acids or protein sequences in order to assign structural and functional characteristics to gene models. When thousands of gene models are being described in an organism genome, construction and visualization of gene networks impose novel challenges in the understanding of complex expression patterns and the generation of new knowledge in genomics research. In order to take advantage of accumulated text data after conventional gene sequence analysis, this work applied semantics in combination with visualization tools to build transcriptome networks from a set of coffee gene annotations. A set of selected coffee transcriptome sequences, chosen by the quality of the sequence comparison reported by Basic Local Alignment Search Tool (BLAST and Interproscan, were filtered out by coverage, identity, length of the query, and e-values. Meanwhile, term descriptors for molecular biology and biochemistry were obtained along the Wordnet dictionary in order to construct a Resource Description Framework (RDF using Ruby scripts and Methontology to find associations between concepts. Relationships between sequence annotations and semantic concepts were graphically represented through a total of 6845 oriented vectors, which were reduced to 745 non-redundant associations. A large gene network connecting transcripts by way of relational concepts was created where detailed connections remain to be validated for biological significance based on current biochemical and genetics frameworks. Besides reusing text information in the generation of gene connections and for data mining purposes, this tool development opens the possibility to visualize complex and abundant transcriptome data, and triggers the formulation of new hypotheses in metabolic pathways analysis.

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

DEFF Research Database (Denmark)

Petersen, Michael Kai; Hansen, Lars Kai

2012-01-01

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

Hare and Others on the Proposition

Directory of Open Access Journals (Sweden)

John Corcoran

2011-04-01

Full Text Available History witnesses alternative approaches to “the proposition”. The proposition has been referred to as the object of belief, disbelief, and doubt: generally as the object of propositional attitudes, that which can be said to be believed, disbelieved, understood, etc. It has also been taken to be the object of grasping, judging, assuming, affirming, denying, and inquiring: generally as the object of propositional actions, that which can be said to be grasped, judged true or false, assumed for reasoning purposes, etc. The proposition has also been taken to be the subject of truth and falsity: generally as the subject of propositional properties, that which can be said to be true, false, tautological, informative, inconsistent, etc. It has also been taken as the subject and object of logical relations, e.g. that which can be said to imply, be implied, contradict, be contradicted, etc. Prima facie, such properties and relations are non-mental and objective. It has also been taken to be the resultants or products of propositional operations, usually mental or linguistic; e.g. judging, affirming, and denying have been held to produce propositions called judgments, affirmations, and negations, respectively. Propositions have also been taken to be certain declarative sentences. Finally, propositions have been taken to be meanings of certain declarative sentences. This essay is an informal, selective, and incomplete survey of alternative approaches to “the proposition” with special attention to the views of the late American philosopher Peter Hare (1935–2008 and of those who influenced him.

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

Directory of Open Access Journals (Sweden)

Marelli Marco

2017-01-01

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

Static, Dynamic and Semantic Dimensions: Towards a Multidisciplinary Approach of Social Networks Analysis

Science.gov (United States)

Thovex, Christophe; Trichet, Francky

The objective of our work is to extend static and dynamic models of Social Networks Analysis (SNA), by taking conceptual aspects of enterprises and institutions social graph into account. The originality of our multidisciplinary work is to introduce abstract notions of electro-physic to define new measures in SNA, for new decision-making functions dedicated to Human Resource Management (HRM). This paper introduces a multidimensional system and new measures: (1) a tension measure for social network analysis, (2) an electrodynamic, predictive and semantic system for recommendations on social graphs evolutions and (3) a reactance measure used to evaluate the individual stress at work of the members of a social network.

Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery

Directory of Open Access Journals (Sweden)

Yu Liu

2017-05-01

Full Text Available A new convolution neural network (CNN architecture for semantic segmentation of high resolution aerial imagery is proposed in this paper. The proposed architecture follows an hourglass-shaped network (HSN design being structured into encoding and decoding stages. By taking advantage of recent advances in CNN designs, we use the composed inception module to replace common convolutional layers, providing the network with multi-scale receptive areas with rich context. Additionally, in order to reduce spatial ambiguities in the up-sampling stage, skip connections with residual units are also employed to feed forward encoding-stage information directly to the decoder. Moreover, overlap inference is employed to alleviate boundary effects occurring when high resolution images are inferred from small-sized patches. Finally, we also propose a post-processing method based on weighted belief propagation to visually enhance the classification results. Extensive experiments based on the Vaihingen and Potsdam datasets demonstrate that the proposed architectures outperform three reference state-of-the-art network designs both numerically and visually.

Categorizing words through semantic memory navigation

Science.gov (United States)

Borge-Holthoefer, J.; Arenas, A.

2010-03-01

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

MEANING OF CO-RESIDENCE IN ELDERLY VISION: A STRATEGY FOR COGNITIVE ANALYSIS WITH USE OF SEMANTICS NETWORKS

Directory of Open Access Journals (Sweden)

Claudia Ribeiro Santos Lopes

2015-06-01

Full Text Available This paper presents a pilot study for cognitive analysis of the concept of co-residence from the perspective of a group of elderly based on the analysis of semantic networks. The data were collected in research with elderly people in a city in the state of Bahia, using the free evocation of words technique. The term inducer was co-residence. Each individual participant of the research should say up to five words that came to his/her mind. Data analysis was interpretively carried out and related to the use of semantic networks with the theoretical support the social and complex network analysis. The elderly gave to the concept of coresidence the meanings of love, happiness, goodness, union and peace, which leads us to believe the emphasis on co-residence, since it represents an interaction leading to a better living and health conditions.

MEANING OF CO-RESIDENCE IN ELDERLY VISION: A STRATEGY FOR COGNITIVE ANALYSIS WITH USE OF SEMANTICS NETWORKS

Directory of Open Access Journals (Sweden)

Claudia Ribeiro Santos Lopes

2015-04-01

Full Text Available This paper presents a pilot study for cognitive analysis of the concept of co-residence from the perspective of a group of elderly based on the analysis of semantic networks. The data were collected in research with elderly people in a city in the state of Bahia, using the free evocation of words technique. The term inducer was co-residence. Each individual participant of the research should say up to five words that came to his/her mind. Data analysis was interpretively carried out and related to the use of semantic networks with the theoretical support the social and complex network analysis. The elderly gave to the concept of co-residence the meanings of love, happiness, goodness, union and peace, which leads us to believe the emphasis on co-residence, since it represents an interaction leading to a better living and health conditions.

Semantics and pragmatics.

Science.gov (United States)

McNally, Louise

2013-05-01

The fields of semantics and pragmatics are devoted to the study of conventionalized and context- or use-dependent aspects of natural language meaning, respectively. The complexity of human language as a semiotic system has led to considerable debate about how the semantics/pragmatics distinction should be drawn, if at all. This debate largely reflects contrasting views of meaning as a property of linguistic expressions versus something that speakers do. The fact that both views of meaning are essential to a complete understanding of language has led to a variety of efforts over the last 40 years to develop better integrated and more comprehensive theories of language use and interpretation. The most important advances have included the adaptation of propositional analyses of declarative sentences to interrogative, imperative and exclamative forms; the emergence of dynamic, game theoretic, and multi-dimensional theories of meaning; and the development of various techniques for incorporating context-dependent aspects of content into representations of context-invariant content with the goal of handling phenomena such as vagueness resolution, metaphor, and metonymy. WIREs Cogn Sci 2013, 4:285-297. doi: 10.1002/wcs.1227 For further resources related to this article, please visit the WIREs website. The authors declare no conflict of interest. Copyright © 2013 John Wiley & Sons, Ltd.

Default network activation during episodic and semantic memory retrieval: A selective meta-analytic comparison.

Science.gov (United States)

Kim, Hongkeun

2016-01-08

It remains unclear whether and to what extent the default network subregions involved in episodic memory (EM) and semantic memory (SM) processes overlap or are separated from one another. This study addresses this issue through a controlled meta-analysis of functional neuroimaging studies involving healthy participants. Various EM and SM task paradigms differ widely in the extent of default network involvement. Therefore, the issue at hand cannot be properly addressed without some control for this factor. In this regard, this study employs a two-stage analysis: a preliminary meta-analysis to select EM and SM task paradigms that recruit relatively extensive default network regions and a main analysis to compare the selected task paradigms. Based on a within-EM comparison, the default network contributed more to recollection/familiarity effects than to old/new effects, and based on a within-SM comparison, it contributed more to word/pseudoword effects than to semantic/phonological effects. According to a direct comparison of recollection/familiarity and word/pseudoword effects, each involving a range of default network regions, there were more overlaps than separations in default network subregions involved in these two effects. More specifically, overlaps included the bilateral posterior cingulate/retrosplenial cortex, left inferior parietal lobule, and left anteromedial prefrontal regions, whereas separations included only the hippocampal formation and the parahippocampal cortex region, which was unique to recollection/familiarity effects. These results indicate that EM and SM retrieval processes involving strong memory signals recruit extensive and largely overlapping default network regions and differ mainly in distinct contributions of hippocampus and parahippocampal regions to EM retrieval. Copyright © 2015 Elsevier Ltd. All rights reserved.

Report on the behalf of the economy, sustainable development and land planning commission of the European resolution proposition by Mr Ladislas Poniatowski on the directive proposition by the European Parliament and Council related to energy efficiency

International Nuclear Information System (INIS)

Poniatowski, L.

2011-01-01

In its first part, this report outlines the interest of the directive proposition as energy efficiency and energy savings must be a priority for the European energy policy, that important energy saving fields are still to be explored, and that this directive is an ambitious and multi-sector oriented arrangement. The second part deals with the resolution proposition (the version proposed by M. Poniatowski and that of the commission). These propositions present the general objectives, comment the rules concerning public bodies, discuss obligation mechanisms regarding energy savings, discuss the issue of energy counting and billing, and the development of cogeneration and networks. The discussion of the commission is reported

Semantic graphs and associative memories

Science.gov (United States)

Pomi, Andrés; Mizraji, Eduardo

2004-12-01

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

Crossmodal semantic congruence can affect visuo-spatial processing and activity of the fronto-parietal attention networks

Directory of Open Access Journals (Sweden)

Serena eMastroberardino

2015-07-01

Full Text Available Previous studies have shown that multisensory stimuli can contribute to attention control. Here we investigate whether irrelevant audio-visual stimuli can affect the processing of subsequent visual targets, in the absence of any direct bottom-up signals generated by low-level sensory changes and any goal-related associations between the multisensory stimuli and the visual targets. Each trial included two pictures (cat/dog, one in each visual hemifield, and a central sound that was semantically congruent with one of the two pictures (i.e. either meow or woof sound. These irrelevant audio-visual stimuli were followed by a visual target that appeared either where the congruent or the incongruent picture had been presented (valid/invalid trials. The visual target was a Gabor patch requiring an orientation discrimination judgment, allowing us to uncouple the visual task from the audio-visual stimuli. Behaviourally we found lower performance for invalid than valid trials, but only when the task demands were high (Gabor target presented together with a Gabor distractor vs. Gabor target alone. The fMRI analyses revealed greater activity for invalid than for valid trials in the dorsal and the ventral fronto-parietal attention networks. The dorsal network was recruited irrespective of task demands, while the ventral network was recruited only when task demands were high and target discrimination required additional top-down control. We propose that crossmodal semantic congruence generates a processing bias associated with the location of congruent picture, and that the presentation of the visual target on the opposite side required updating these processing priorities. We relate the activation of the attention networks to these updating operations. We conclude that the fronto-parietal networks mediate the influence of crossmodal semantic congruence on visuo-spatial processing, even in the absence of any low-level sensory cue and any goal-driven task

Automated Understanding of Financial Statements Using Neural Networks and Semantic Grammars

OpenAIRE

Markovitch, J. S.

1995-01-01

This article discusses how neural networks and semantic grammars may be used to locate and understand financial statements embedded in news stories received from on-line news wires. A neural net is used to identify where in the news story a financial statement appears to begin. A grammar then is applied to this text in an effort to extract specific facts from the financial statement. Applying grammars to financial statements presents unique parsing problems since the dollar amounts of financi...

Ontology alignment architecture for semantic sensor Web integration.

Science.gov (United States)

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

2013-09-18

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

Ontology Alignment Architecture for Semantic Sensor Web Integration

Directory of Open Access Journals (Sweden)

Bernardo Alarcos

2013-09-01

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

A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions

OpenAIRE

Taylor, Duncan; Biedermann, Alex; Hicks, Tacha; Champod, Christophe

2018-01-01

The hierarchy of propositions has been accepted amongst the forensic science community for some time. It is also accepted that the higher up the hierarchy the propositions are, against which the scientist are competent to evaluate their results, the more directly useful the testimony will be to the court. Because each case represents a unique set of circumstances and findings, it is difficult to come up with a standard structure for evaluation. One common tool that assists in this task is Bay...

Richness of information about novel words influences how episodic and semantic memory networks interact during lexicalization

NARCIS (Netherlands)

Takashima, A.; Bakker, I.; Hell, J.G. van; Janzen, G.; McQueen, J.M.

2014-01-01

The complementary learning systems account of declarative memory suggests two distinct memory networks, a fast-mapping, episodic system involving the hippocampus, and a slower semantic memory system distributed across the neocortex in which new information is gradually integrated with existing

Mimoza: web-based semantic zooming and navigation in metabolic networks.

Science.gov (United States)

Zhukova, Anna; Sherman, David J

2015-02-26

The complexity of genome-scale metabolic models makes them quite difficult for human users to read, since they contain thousands of reactions that must be included for accurate computer simulation. Interestingly, hidden similarities between groups of reactions can be discovered, and generalized to reveal higher-level patterns. The web-based navigation system Mimoza allows a human expert to explore metabolic network models in a semantically zoomable manner: The most general view represents the compartments of the model; the next view shows the generalized versions of reactions and metabolites in each compartment; and the most detailed view represents the initial network with the generalization-based layout (where similar metabolites and reactions are placed next to each other). It allows a human expert to grasp the general structure of the network and analyze it in a top-down manner Mimoza can be installed standalone, or used on-line at http://mimoza.bordeaux.inria.fr/ , or installed in a Galaxy server for use in workflows. Mimoza views can be embedded in web pages, or downloaded as COMBINE archives.

Secure grid-based computing with social-network based trust management in the semantic web

Czech Academy of Sciences Publication Activity Database

Špánek, Roman; Tůma, Miroslav

2006-01-01

Roč. 16, č. 6 (2006), s. 475-488 ISSN 1210-0552 R&D Projects: GA AV ČR 1ET100300419; GA MŠk 1M0554 Institutional research plan: CEZ:AV0Z10300504 Keywords : semantic web * grid computing * trust management * reconfigurable networks * security * hypergraph model * hypergraph algorithms Subject RIV: IN - Informatics, Computer Science

Optimizing Semantic Pointer Representations for Symbol-Like Processing in Spiking Neural Networks.

Science.gov (United States)

Gosmann, Jan; Eliasmith, Chris

2016-01-01

The Semantic Pointer Architecture (SPA) is a proposal of specifying the computations and architectural elements needed to account for cognitive functions. By means of the Neural Engineering Framework (NEF) this proposal can be realized in a spiking neural network. However, in any such network each SPA transformation will accumulate noise. By increasing the accuracy of common SPA operations, the overall network performance can be increased considerably. As well, the representations in such networks present a trade-off between being able to represent all possible values and being only able to represent the most likely values, but with high accuracy. We derive a heuristic to find the near-optimal point in this trade-off. This allows us to improve the accuracy of common SPA operations by up to 25 times. Ultimately, it allows for a reduction of neuron number and a more efficient use of both traditional and neuromorphic hardware, which we demonstrate here.

On a syntactic-semantic model with the locative case

Directory of Open Access Journals (Sweden)

Antonić Ivana

2008-01-01

Full Text Available The topic of this paper is a syntactic-semantic model whose distinctive element is the locative case with the preposition U (IN and the relevant feature (+ human being. This model is realized in three different variants - with the intransitive (A or transitive verb (B, where the nominative in the function of subject and the locative indicate different (B1 or the same (B2 referents. Furthermore, the verb belongs to a semantic class which denotes emerging, stimulation, duration, fading away, diminishing or change in the intensity, in principle, of any phenomenon, and concretely in this model such verbs appear in the collocational link with the nouns implying man's psychological, physiological or mental states, feelings or mood. With an adequate analytic procedure, all the three variants of this model are approached from the syntactic-semantic and pragmatic perspective. The paper points to the causative semantics of these structures, reduced to the metalinguistic formula 'make that X V', which confirms that the semantics of these verb-noun collocational links, syntactically speaking, condenses a complex two-member sentential structure represented by the semantically deficient verb (= causative component in the basic, matrix structure, and the complement clause with the conjunction DA (THAT and the basic verb. And precisely from this semantic feature there follows that the notion in the locative case semantically, actually, represents the BEARER of a physiological, physiological or mental state, feeling, mood, so that it represents the GRAMMATICAL SUBJECT of the corresponding basic subordinated predication whose exponent, actually, is the grammatical subject in the structure with the intransitive verb (or with the syntactically-semantically intransitive verb structure, that is the object in the structure with the transitive verb. Two possible semantic interpretations of this model are presented: the one related to the referential pointing to the

Episodic Memory, Semantic Memory, and Fluency.

Science.gov (United States)

Schaefer, Carl F.

1980-01-01

Suggests that creating a second-language semantic network can be conceived as developing a plan for retrieving second-language word forms. Characteristics of linguistic performance which will promote fluency are discussed in light of the distinction between episodic and semantic memory. (AMH)

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

Science.gov (United States)

Wiese, Holger

2011-11-01

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

Semantic organization in children with Cochlear Implants: Computational analysis of verbal fluency

Directory of Open Access Journals (Sweden)

Yoed Nissan Kenett

2013-09-01

Full Text Available Purpose: Cochlear implants (CIs enable children with severe and profound hearing impairments to perceive the sensation of sound sufficiently to permit oral language acquisition. So far, studies have focused mainly on technological improvements and general outcomes of implantation for speech perception and spoken language development. This study quantitatively explored the semantic networks of children with CIs in comparison to those of age-matched normal hearing (NH peers.Method: Twenty seven children with CIs and twenty seven age- and IQ-matched NH children ages 7-10 were tested on a timed animal verbal fluency task (Name as many animals as you can. The responses were analyzed using correlation and network methodologies. The structure of the animal category semantic networks for both groups were extracted and compared.Results: Children with CIs appeared to have a less-developed semantic lexicon structure compared to age-matched NH peers. The average shortest path length and the network diameter measures were larger for the NH group compared to the CIs group. This difference was consistent for the analysis of networks derived from animal names generated by each group (sample-matched correlation networks and for the networks derived from the common animal names generated by both groups (word-matched correlation networks.Conclusions: The main difference between the semantic networks of children with CIs and NH children lies in the network structure. The semantic network of children with CIs is under-developed compared to the semantic network of the age-matched NH children. We discuss the practical and clinical implications of our findings.

A Structural-Lexical Measure of Semantic Similarity for Geo-Knowledge Graphs

Directory of Open Access Journals (Sweden)

Andrea Ballatore

2015-04-01

Full Text Available Graphs have become ubiquitous structures to encode geographic knowledge online. The Semantic Web’s linked open data, folksonomies, wiki websites and open gazetteers can be seen as geo-knowledge graphs, that is labeled graphs whose vertices represent geographic concepts and whose edges encode the relations between concepts. To compute the semantic similarity of concepts in such structures, this article defines the network-lexical similarity measure (NLS. This measure estimates similarity by combining two complementary sources of information: the network similarity of vertices and the semantic similarity of the lexical definitions. NLS is evaluated on the OpenStreetMap Semantic Network, a crowdsourced geo-knowledge graph that describes geographic concepts. The hybrid approach outperforms both network and lexical measures, obtaining very strong correlation with the similarity judgments of human subjects.

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

Science.gov (United States)

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

2014-10-22

Research from the previous decade suggests that word meaning is partially stored in distributed modality-specific cortical networks. However, little is known about the mechanisms by which semantic content from multiple modalities is integrated into a coherent multisensory representation. Therefore we aimed to characterize differences between integration of lexical-semantic information from a single modality compared with two sensory modalities. We used magnetoencephalography in humans to investigate changes in oscillatory neuronal activity while participants verified two features for a given target word (e.g., "bus"). Feature pairs consisted of either two features from the same modality (visual: "red," "big") or different modalities (auditory and visual: "red," "loud"). The results suggest that integrating modality-specific features of the target word is associated with enhanced high-frequency power (80-120 Hz), while integrating features from different modalities is associated with a sustained increase in low-frequency power (2-8 Hz). Source reconstruction revealed a peak in the anterior temporal lobe for low-frequency and high-frequency effects. These results suggest that integrating lexical-semantic knowledge at different cortical scales is reflected in frequency-specific oscillatory neuronal activity in unisensory and multisensory association networks. Copyright © 2014 the authors 0270-6474/14/3314318-06$15.00/0.

Neural correlates underlying musical semantic memory.

Science.gov (United States)

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

2009-07-01

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

The Influence of Concreteness of Concepts on the Integration of Novel Words into the Semantic Network.

Science.gov (United States)

Ding, Jinfeng; Liu, Wenjuan; Yang, Yufang

2017-01-01

On the basis of previous studies revealing a processing advantage of concrete words over abstract words, the current study aimed to further explore the influence of concreteness on the integration of novel words into semantic memory with the event related potential (ERP) technique. In the experiment during the learning phase participants read two-sentence contexts and inferred the meaning of novel words. The novel words were two-character non-words in Chinese language. Their meaning was either a concrete or abstract known concept which could be inferred from the contexts. During the testing phase participants performed a lexical decision task in which the learned novel words served as primes for either their corresponding concepts, semantically related or unrelated targets. For the concrete novel words, the semantically related words belonged to the same semantic categories with their corresponding concepts. For the abstract novel words, the semantically related words were synonyms of their corresponding concepts. The unrelated targets were real words which were concrete or abstract for the concrete or abstract novel words respectively. The ERP results showed that the corresponding concepts and the semantically related words elicited smaller N400s than the unrelated words. The N400 effect was not modulated by the concreteness of the concepts. In addition, the concrete corresponding concepts elicited a smaller late positive component (LPC) than the concrete unrelated words. This LPC effect was absent for the abstract words. The results indicate that although both concrete and abstract novel words can be acquired and linked to their related words in the semantic network after a short learning phase, the concrete novel words are learned better. Our findings support the (extended) dual coding theory and broaden our understanding of adult word learning and changes in concept organization.

The Influence of Concreteness of Concepts on the Integration of Novel Words into the Semantic Network

Directory of Open Access Journals (Sweden)

Jinfeng Ding

2017-12-01

Full Text Available On the basis of previous studies revealing a processing advantage of concrete words over abstract words, the current study aimed to further explore the influence of concreteness on the integration of novel words into semantic memory with the event related potential (ERP technique. In the experiment during the learning phase participants read two-sentence contexts and inferred the meaning of novel words. The novel words were two-character non-words in Chinese language. Their meaning was either a concrete or abstract known concept which could be inferred from the contexts. During the testing phase participants performed a lexical decision task in which the learned novel words served as primes for either their corresponding concepts, semantically related or unrelated targets. For the concrete novel words, the semantically related words belonged to the same semantic categories with their corresponding concepts. For the abstract novel words, the semantically related words were synonyms of their corresponding concepts. The unrelated targets were real words which were concrete or abstract for the concrete or abstract novel words respectively. The ERP results showed that the corresponding concepts and the semantically related words elicited smaller N400s than the unrelated words. The N400 effect was not modulated by the concreteness of the concepts. In addition, the concrete corresponding concepts elicited a smaller late positive component (LPC than the concrete unrelated words. This LPC effect was absent for the abstract words. The results indicate that although both concrete and abstract novel words can be acquired and linked to their related words in the semantic network after a short learning phase, the concrete novel words are learned better. Our findings support the (extended dual coding theory and broaden our understanding of adult word learning and changes in concept organization.

A Note on Omitting Types in Propositional Logic

Directory of Open Access Journals (Sweden)

Oren Kolman

2015-05-01

Full Text Available Analogues of the classical omitting types theorems of first-order logic are proved for propositional logic. For an infinite cardinal $\\kappa$, a sufficient criterion is given for the omission of $\\kappa$-many types in a propositional language with $\\kappa$ propositional variables.

Transforming equality logic to propositional logic

NARCIS (Netherlands)

Zantema, H.; Groote, J.F.

2003-01-01

Abstract We investigate and compare various ways of transforming equality formulas to propositional formulas, in order to be able to solve satisfiability in equality logic by means of satisfiability in propositional logic. We propose equality substitution as a new approach combining desirable

Pushing the Quality Level in Networked News Business: Semantic-Based Content Retrieval and Composition in International News Publishing

OpenAIRE

M.W. Schranz

2006-01-01

Electronic publishing exploits numerous possibilities to present or exchange information and to communicate via most current media like the Internet. By utilizing modern Web technologies like Web Services, loosely coupled services, and peer-to-peer networks we describe the integration of an intelligent business news presentation and distribution network. Employing semantics technologies enables the coupling of multinational and multilingual business news data on a scaleable international leve...

Logic without unique readability - a study of semantic and syntactic ambiguity

DEFF Research Database (Denmark)

Bentzen, Martin Mose

One of the main reasons for introducing a formal language is to remove ambiguity, the possibility of assigning several meanings to a linguistic expression. Typically, this is achieved through ensuring unique readability of formulas by using brackets (or another convention, such as Polish notation...... not hold true universally. Whereas e.g. scope ambiguities in natural languages have been studied extensively, ambiguous formal languages have not been the focus of in depth research. Here, we lift the assumption of unique readability by omitting the brackets from propositional logic, making it possible...... to formally distinguish between syntactic and semantic ambiguity. A valuation then amounts to a semantic disambiguation, and rather than a unique valuation (truth value), there is a set of valuations corresponding to ways a formula could have been constructed. We show what happens to familiar concepts...

Trust Networks on the Semantic Web

National Research Council Canada - National Science Library

Golbeck, Jennifer; Parisa, Bijan; Hendler, James

2006-01-01

The so-called "Web of Trust" is one of the ultimate goals of the Semantic Web. Research on the topic of trust in this domain has focused largely on digital signatures, certificates, and authentication...

Semantic Network Analysis on Terms related Mantle in Earth Science 2 Textbooks of Korea

Science.gov (United States)

Chung, Duk Ho; reum Cho, Ah; Park, Seon Ok

2016-04-01

The purpose of this study is to demonstrate if freshmen's cognitive frame about 'Crisis of the Earth' upon taking the Earth science 1 in high school reflects the school curriculum. The data was collected from 67 freshmen who'd graduated high school in formal education. They expressed 'Crisis of the Earth' as a painting with explanation and then we extracted units of meaning from paintings, respectively. We analyzed the words and frame using the Semantic Network Analysis. The result is as follows; First, as every participant forms the cognitive frame for the crisis of the Earth, it is shown that they connect each part which that composes the global environment and realize it as the changing relation with interaction. Secondly, forming a cognitive frame regarding crisis of the Earth, both groups connect it with human endeavor. Especially, it seems that the group of participants who finished Earth Science I fully reflects the course of the formal education. It is necessary to make the students recognize it from a universal point of view, not only from the Earth. Also, much effort is required in order to enlighten about the appropriateness regarding problem-solving of the Earth and expand their mind as time changes. Keywords : Earth ScienceⅠ, cognitive frame, crisis of the earth, semantic network analysis

Semantic Models of Sentences with Verbs of Motion in Standard Language and in Scientific Language Used in Biology

Directory of Open Access Journals (Sweden)

Vita Banionytė

2016-06-01

Full Text Available The semantic models of sentences with verbs of motion in German standard language and in scientific language used in biology are analyzed in the article. In its theoretic part it is affirmed that the article is based on the semantic theory of the sentence. This theory, in its turn, is grounded on the correlation of semantic predicative classes and semantic roles. The combination of semantic predicative classes and semantic roles is expressed by the main semantic formula – proposition. In its practical part the differences between the semantic models of standard and scientific language used in biology are explained. While modelling sentences with verbs of motion, two groups of semantic models of sentences are singled out: that of action (Handlung and process (Vorgang. The analysis shows that the semantic models of sentences with semantic action predicatives dominate in the text of standard language while the semantic models of sentences with semantic process predicatives dominate in the texts of scientific language used in biology. The differences how the doer and direction are expressed in standard and in scientific language are clearly seen and the semantic cases (Agens, Patiens, Direktiv1 help to determine that. It is observed that in scientific texts of high level of specialization (biology science in contrast to popular scientific literature models of sentences with moving verbs are usually seldom found. They are substituted by denominative constructions. In conclusions it is shown that this analysis can be important in methodics, especially planning material for teaching professional-scientific language.

Semantic policy and adversarial modeling for cyber threat identification and avoidance

Science.gov (United States)

DeFrancesco, Anton; McQueary, Bruce

2009-05-01

Today's enterprise networks undergo a relentless barrage of attacks from foreign and domestic adversaries. These attacks may be perpetrated with little to no funding, but may wreck incalculable damage upon the enterprises security, network infrastructure, and services. As more services come online, systems that were once in isolation now provide information that may be combined dynamically with information from other systems to create new meaning on the fly. Security issues are compounded by the potential to aggregate individual pieces of information and infer knowledge at a higher classification than any of its constituent parts. To help alleviate these challenges, in this paper we introduce the notion of semantic policy and discuss how it's use is evolving from a robust approach to access control to preempting and combating attacks in the cyber domain, The introduction of semantic policy and adversarial modeling to network security aims to ask 'where is the network most vulnerable', 'how is the network being attacked', and 'why is the network being attacked'. The first aspect of our approach is integration of semantic policy into enterprise security to augment traditional network security with an overall awareness of policy access and violations. This awareness allows the semantic policy to look at the big picture - analyzing trends and identifying critical relations in system wide data access. The second aspect of our approach is to couple adversarial modeling with semantic policy to move beyond reactive security measures and into a proactive identification of system weaknesses and areas of vulnerability. By utilizing Bayesian-based methodologies, the enterprise wide meaning of data and semantic policy is applied to probability and high-level risk identification. This risk identification will help mitigate potential harm to enterprise networks by enabling resources to proactively isolate, lock-down, and secure systems that are most vulnerable.

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

Science.gov (United States)

Rajabi, Enayat; Abidi, Syed Sibte Raza

2017-01-01

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

Natural Propositions

DEFF Research Database (Denmark)

Stjernfelt, Frederik

Preface -- Introduction -- The generality of signs -- Dicisigns -- Some consequences of the dicisign doctrine -- Dicisigns and cognition -- Natural propositions--the evolution of semiotic self-control -- Dicisigns beyond language -- Operational and optimal iconicity in Peirce's diagrammatology...... -- Cows, red cows, and red herrings -- Corollarial and theorematic experiments with diagrams -- Strategies of research: Peirce's enlightenment maxims -- Perspective -- References -- Index....

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

Science.gov (United States)

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".

Propositions for the implementation and reinforcement of surveillance activities of exposure and risks associated to radon inhalation

International Nuclear Information System (INIS)

2003-10-01

This report treats exclusively of exposure by inhalation. It expresses the propositions relative to the implantation and the development of an information network allowing to characterize the radon exposures by inhalation and associated risks. (N.C.)

A One-System Theory Which is Not Propositional.

Science.gov (United States)

Witnauer, James E; Urcelay, Gonzalo P; Miller, Ralph R

2009-04-01

We argue that the propositional and link-based approaches to human contingency learning represent different levels of analysis because propositional reasoning requires a basis, which is plausibly provided by a link-based architecture. Moreover, in their attempt to compare two general classes of models (link-based and propositional), Mitchell et al. have referred to only two generic models and ignore the large variety of different models within each class.

Propositional systems in local field theories

International Nuclear Information System (INIS)

Banai, M.

1980-07-01

The authors investigate propositional systems for local field theories, which reflect intrinsically the uncertainties of measurements made on the physical system, and satisfy the isotony and local commutativity postulates of Haag and Kastler. The spacetime covariance can be implemented in natural way in these propositional systems. New techniques are introduced to obtain these propositional systems: the lattice-valued logics. The decomposition of the complete orthomodular lattice-valued logics shows that these logics are more general than the usual two-valued ones and that in these logics there is enough structure to characterize the classical and quantum, non relativistic and relativistic local field theories in a natural way. The Hilbert modules give the natural inner product ''spaces'' (modules) for the realization of the lattice-valued logics. (author)

The use of web ontology languages and other semantic web tools in drug discovery.

Science.gov (United States)

Chen, Huajun; Xie, Guotong

2010-05-01

To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

The Semantic Network of Flood Hydrological Data for Kelantan, Malaysia

Science.gov (United States)

Yusoff, Aziyati; Din, Norashidah Md; Yussof, Salman; Ullah Khan, Samee

2016-03-01

Every year, authorities in Malaysia are putting efforts on disaster management mechanisms including the flood incidence that might hit the east coast of Peninsular Malaysia. This includes the state of Kelantan of which it was reported that flood is just a normal event occurred annually. However, the aftermath was always unmanageable and had left the state to struggle for its own recoveries. Though it was expected that flood occurred every year, among the worst were in 1967, 1974, 1982 and recently in December 2014. This study is proposing a semantic network as an approach to the method of utilising big data analytics in analysing the huge data from the state’s flood reading stations. It is expected that by using current computing edge can also facilitate mitigating this particular disaster.

Semantic Dysfunction in Women With Schizotypal Personality Disorder

OpenAIRE

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

2002-01-01

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

Nursing intellectual capital theory: testing selected propositions.

Science.gov (United States)

Covell, Christine L; Sidani, Souraya

2013-11-01

To test the selected propositions of the middle-range theory of nursing intellectual capital. The nursing intellectual capital theory conceptualizes nursing knowledge's influence on patient and organizational outcomes. The theory proposes nursing human capital, nurses' knowledge, skills and experience, is related to the quality of patient care and nurse recruitment and retention of an inpatient care unit. Two factors in the work environment, nurse staffing and employer support for nurse continuing professional development, are proposed to influence nursing human capital's association with patient and organizational outcomes. A cross-sectional survey design. The study took place in 2008 in six Canadian acute care hospitals. Financial, human resource and risk data were collected from hospital departments and unit managers. Clearly specified empirical indicators quantified the study variables. The propositions of the theory were tested with data from 91 inpatient care units using structural equation modelling. The propositions associated with the nursing human capital concept were supported. The propositions associated with the employer support for nurse continuing professional development concept were not. The proposition that nurse staffing's influences on patient outcomes was mediated by the nursing human capital of an inpatient unit, was partially supported. Some of the theory's propositions were empirically validated. Additional theoretical work is needed to refine the operationalization and measurement of some of the theory's concepts. Further research with larger samples of data from different geographical settings and types of hospitals is required to determine if the theory can withstand empirical scrutiny. © 2013 Blackwell Publishing Ltd.

Semantic Segmentation of Aerial Images with AN Ensemble of Cnns

Science.gov (United States)

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

2016-06-01

This paper describes a deep learning approach to semantic segmentation of very high resolution (aerial) images. Deep neural architectures hold the promise of end-to-end learning from raw images, making heuristic feature design obsolete. Over the last decade this idea has seen a revival, and in recent years deep convolutional neural networks (CNNs) have emerged as the method of choice for a range of image interpretation tasks like visual recognition and object detection. Still, standard CNNs do not lend themselves to per-pixel semantic segmentation, mainly because one of their fundamental principles is to gradually aggregate information over larger and larger image regions, making it hard to disentangle contributions from different pixels. Very recently two extensions of the CNN framework have made it possible to trace the semantic information back to a precise pixel position: deconvolutional network layers undo the spatial downsampling, and Fully Convolution Networks (FCNs) modify the fully connected classification layers of the network in such a way that the location of individual activations remains explicit. We design a FCN which takes as input intensity and range data and, with the help of aggressive deconvolution and recycling of early network layers, converts them into a pixelwise classification at full resolution. We discuss design choices and intricacies of such a network, and demonstrate that an ensemble of several networks achieves excellent results on challenging data such as the ISPRS semantic labeling benchmark, using only the raw data as input.

A proposition calculus in quantum mechanisms

International Nuclear Information System (INIS)

Omnes, R.

1987-01-01

In quantum mechanics, to a set of n+1 observables A 0 , A 1 ...A n and a set of time instants, one can associate a probabilized space (X, B, P) where X is the direct product of the spectra of A 1 ...A n . The sigma-field B has a basis that is not a direct product but constructed in a well-defined order using sets in the spectra or equivalently projectors in the Hilbert space. The probability measure P on B satisfies the axioms of probability theory if some compatibility conditions, first found by R. Griffiths, are satisfied. To do so, one must use some quasi-classical Fefferman approximants for A 1 ...A n . Sets in B can be used as predicates in a proposition calculus using P, such that a proposition π 1 implies a proposition π-2, also gives probability 1 for π 2 . This is consistent with the logical axioms about implication. Here E 0 , projector on a set on the spectrum of A 0 is a common first predicate.This formalism is used to analyze the Einstein-Podolsky-Rosen gedankenexperiment and turns out not to contradict the finite-velocity propogation axiom of special relativity. Since only propositions and no measuring apparatus nor external observer have to be introduced, this theory generalizing quantum mechanics satisfies the criteria of objectivity, and remains non-separable. It turns out that, when an actual measuring apparatus is used, wave-packet reduction is the logico-mathematical operation that takes care of the measurement result as a proposition [fr

ANA, automatic natural learning of a semantic network

International Nuclear Information System (INIS)

Enguehard, Chantal

1992-01-01

The objective of this research thesis is the automatic extraction of terminology and the study of its automatic structuring in order to produce a semantic network. Such an operation is applied to text corpus representing knowledge on a specific field in order to select the relevant technical vocabulary regarding this field. Thus, the author developed a method and a software for the automatic acquisition of terminology items. The author first gives an overview of systems and methods of document indexing and of thesaurus elaboration, and a brief presentation of the state-of-the-art of learning. Then, he discusses some drawbacks of computer systems of natural language processing which are using large knowledge sources such as grammars and dictionaries. After a presentation of the adopted approach and of some hypotheses, the author defines objects and operators which are necessary for an easier data handling, presents the knowledge acquisition process, and finally precisely describes the system computerization. Some results are assessed and discussed, and limitations and perspectives are commented [fr

Learning Document Semantic Representation with Hybrid Deep Belief Network

Directory of Open Access Journals (Sweden)

Yan Yan

2015-01-01

it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.

Metric propositional neighborhood logics on natural numbers

DEFF Research Database (Denmark)

Bresolin, Davide; Della Monica, Dario; Goranko, Valentin

2013-01-01

Metric Propositional Neighborhood Logic (MPNL) over natural numbers. MPNL features two modalities referring, respectively, to an interval that is “met by” the current one and to an interval that “meets” the current one, plus an infinite set of length constraints, regarded as atomic propositions...

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

Directory of Open Access Journals (Sweden)

Mengxue eCao

2014-03-01

Full Text Available 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.

Contradiction-tolerant process algebra with propositional signals

NARCIS (Netherlands)

Bergstra, J.A.; Middelburg, C.A.

2017-01-01

In a previous paper, an ACP-style process algebra was proposed in which propositions are used as the visible part of the state of processes and as state conditions under which processes may proceed. This process algebra, called ACPps, is built on classical propositional logic. In this paper, we

Delineating the effect of semantic congruency on episodic memory: the role of integration and relatedness.

Science.gov (United States)

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

2015-01-01

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

Delineating the effect of semantic congruency on episodic memory: the role of integration and relatedness.

Directory of Open Access Journals (Sweden)

Oded Bein

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

Customer value propositions in business markets.

Science.gov (United States)

Anderson, James C; Narus, James A; van Rossum, Wouter

2006-03-01

Examples of consumer value propositions that resonate with customers are exceptionally difficult to find. When properly constructed, value propositions force suppliers to focus on what their offerings are really worth. Once companies become disciplined about understanding their customers, they can make smarter choices about where to allocate scarce resources. The authors illuminate the pitfalls of current approaches, then present a systematic method for developing value propositions that are meaningful to target customers and that focus suppliers' efforts on creating superior value. When managers construct a customer value proposition, they often simply list all the benefits their offering might deliver. But the relative simplicity of this all-benefits approach may have a major drawback: benefit assertion. In other words, managers may claim advantages for features their customers don't care about in the least. Other suppliers try to answer the question, Why should our firm purchase your offering instead of your competitor's? But without a detailed understanding of the customer's requirements and preferences, suppliers can end up stressing points of difference that deliver relatively little value to the target customer. The pitfall with this approach is value presumption: assuming that any favorable points of difference must be valuable for the customer. Drawing on the best practices of a handful of suppliers in business markets, the authors advocate a resonating focus approach. Suppliers can provide simple, yet powerfully captivating, consumer value propositions by making their offerings superior on the few elements that matter most to target customers, demonstrating and documenting the value of this superior performance, and communicating it in a way that conveys a sophisticated understanding of the customer's business priorities.

An explicit semantic relatedness measure based on random walk

Directory of Open Access Journals (Sweden)

HU Sihui

2016-10-01

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

Learning Semantic Segmentation with Diverse Supervision

OpenAIRE

Ye, Linwei; Liu, Zhi; Wang, Yang

2018-01-01

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

Propositions for the implementation and reinforcement of surveillance activities of exposure and risks associated to radon inhalation; Propositions pour la mise en place et le renforcement d'activites de surveillance des expositions et des risques associes a l'inhalation du radon

Energy Technology Data Exchange (ETDEWEB)

NONE

2003-10-01

This report treats exclusively of exposure by inhalation. It expresses the propositions relative to the implantation and the development of an information network allowing to characterize the radon exposures by inhalation and associated risks. (N.C.)

Improving life sciences information retrieval using semantic web technology.

Science.gov (United States)

Quan, Dennis

2007-05-01

The ability to retrieve relevant information is at the heart of every aspect of research and development in the life sciences industry. Information is often distributed across multiple systems and recorded in a way that makes it difficult to piece together the complete picture. Differences in data formats, naming schemes and network protocols amongst information sources, both public and private, must be overcome, and user interfaces not only need to be able to tap into these diverse information sources but must also assist users in filtering out extraneous information and highlighting the key relationships hidden within an aggregated set of information. The Semantic Web community has made great strides in proposing solutions to these problems, and many efforts are underway to apply Semantic Web techniques to the problem of information retrieval in the life sciences space. This article gives an overview of the principles underlying a Semantic Web-enabled information retrieval system: creating a unified abstraction for knowledge using the RDF semantic network model; designing semantic lenses that extract contextually relevant subsets of information; and assembling semantic lenses into powerful information displays. Furthermore, concrete examples of how these principles can be applied to life science problems including a scenario involving a drug discovery dashboard prototype called BioDash are provided.

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

Science.gov (United States)

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

2018-01-01

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

Semantic dysfunction in women with schizotypal personality disorder.

Science.gov (United States)

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

2002-10-01

This study examined whether early or late processes in semantic networks were abnormal in women with a diagnosis of schizotypal personality disorder. The N400 component of the EEG event-related potentials was used as a probe of semantic processes. Word pairs were presented with short and long stimulus-onset asynchronies to investigate, respectively, early and late semantic processes in 16 women with schizotypal personality disorder and 15 normal female comparison subjects. Event-related potentials were recorded in response to the last words in a pair. With the short stimulus-onset asynchrony, the N400 amplitude was less negative in the schizotypal personality disorder group than in the normal comparison group. No group differences were found with the long stimulus-onset asynchrony. The finding of a less negative than normal N400 amplitude with the short stimulus-onset asynchrony in women with schizotypal personality disorder supports the hypothesis that persons with this disorder evince an overactivation of semantic networks. The absence of group differences with the long stimulus-onset asynchrony, which is primarily sensitive to processes involved in context integration, suggests that in this group of schizotypal personality disorder subjects, additional demands on working memory may be necessary to bring out the semantic dysfunction.

Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference

OpenAIRE

Bao, Ruying; Liang, Sihang; Wang, Qingcan

2018-01-01

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

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

Science.gov (United States)

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

Value Proposition: A Common Ground between Company and Customer

OpenAIRE

Zhou, Xinyu

2009-01-01

This is a paper that examines the contribution of the value proposition and the interplay between value creation process and value proposition strategy, between competencies and value proposition in competitive market situation. A literature review was carried out to understand the relevant research already in existence. The origin of value and the two main contemporary theories of customer value were reviewed; some models were covered as well. The two theories are Customer-based value ...

Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network

Directory of Open Access Journals (Sweden)

Hasan Asy’ari Arief

2018-06-01

Full Text Available Inspired by the success of deep learning techniques in dense-label prediction and the increasing availability of high precision airborne light detection and ranging (LiDAR data, we present a research process that compares a collection of well-proven semantic segmentation architectures based on the deep learning approach. Our investigation concludes with the proposition of some novel deep learning architectures for generating detailed land resource maps by employing a semantic segmentation approach. The contribution of our work is threefold. (1 First, we implement the multiclass version of the intersection-over-union (IoU loss function that contributes to handling highly imbalanced datasets and preventing overfitting. (2 Thereafter, we propose a novel deep learning architecture integrating the deep atrous network architecture with the stochastic depth approach for speeding up the learning process, and impose a regularization effect. (3 Finally, we introduce an early fusion deep layer that combines image-based and LiDAR-derived features. In a benchmark study carried out using the Follo 2014 LiDAR data and the NIBIO AR5 land resources dataset, we compare our proposals to other deep learning architectures. A quantitative comparison shows that our best proposal provides more than 5% relative improvement in terms of mean intersection-over-union over the atrous network, providing a basis for a more frequent and improved use of LiDAR data for automatic land cover segmentation.

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

OpenAIRE

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

2017-01-01

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

Semantic Identification Attacks on Web Browsing

OpenAIRE

Guha, Neel

2016-01-01

We introduce a Semantic Identification Attack, in which an adversary uses semantic signals about the pages visited in one browsing session to identify other browsing sessions launched by the same user. This attack allows an adver- sary to determine if two browsing sessions originate from the same user regardless of any measures taken by the user to disguise their browser or network. We use the MSNBC Anonymous Browsing data set, which contains a large set of user visits (labeled by category) t...

Neural changes associated with semantic processing in healthy aging despite intact behavioral performance.

Science.gov (United States)

Lacombe, Jacinthe; Jolicoeur, Pierre; Grimault, Stephan; Pineault, Jessica; Joubert, Sven

2015-10-01

Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level. Copyright © 2015 Elsevier Inc. All rights reserved.

Propositional matrices as alternative representation of truth values ...

African Journals Online (AJOL)

The paper considered the subject of representation of truth values in symbolic logic. An alternative representation was given based on the rows and columns properties of matrices, with the operations involving the logical connectives subjected to the laws of algebra of propositions. Matrices of various propositions detailing ...

Matching Value Propositions with Varied Customer Needs

DEFF Research Database (Denmark)

Heikka, Eija-Liisa; Frandsen, Thomas; Hsuan, Juliana

2018-01-01

Organizations seek to manage varied customer segments using varied value propositions. The ability of a knowledge-intensive business service (KIBS) provider to formulate value propositions into attractive offerings to varied customers becomes a competitive advantage. In this specific business based...... on often highly abstract service offerings, this requires the provider to have a clear overview of its knowledge and resources and how these can be configured to obtain the desired customization of services. Hence, the purpose of this paper is to investigate how a KIBS provider can match value propositions...... with varied customer needs utilizing service modularity. To accomplish this purpose, a qualitative multiple case study is organized around 5 projects allowing within-case and cross-case comparisons. Our findings describe how through the configuration of knowledge and resources a sustainable competitive...

Semantically supporting data discovery, markup and aggregation in the European Marine Observation and Data Network (EMODnet)

Science.gov (United States)

Lowry, Roy; Leadbetter, Adam

2014-05-01

The semantic content of the NERC Vocabulary Server (NVS) has been developed over thirty years. It has been used to mark up metadata and data in a wide range of international projects, including the European Commission (EC) Framework Programme 7 projects SeaDataNet and The Open Service Network for Marine Environmental Data (NETMAR). Within the United States, the National Science Foundation projects Rolling Deck to Repository and Biological & Chemical Data Management Office (BCO-DMO) use concepts from NVS for markup. Further, typed relationships between NVS concepts and terms served by the Marine Metadata Interoperability Ontology Registry and Repository. The vast majority of the concepts publicly served from NVS (35% of ~82,000) form the British Oceanographic Data Centre (BODC) Parameter Usage Vocabulary (PUV). The PUV is instantiated on the NVS as a SKOS concept collection. These terms are used to describe the individual channels in data and metadata served by, for example, BODC, SeaDataNet and BCO-DMO. The PUV terms are designed to be very precise and may contain a high level of detail. Some users have reported that the PUV is difficult to navigate due to its size and complexity (a problem CSIRO have begun to address by deploying a SISSVoc interface to the NVS), and it has been difficult to aggregate data as multiple PUV terms can - with full validity - be used to describe the same data channels. Better approaches to data aggregation are required as a use case for the PUV from the EC European Marine Observation and Data Network (EMODnet) Chemistry project. One solution, proposed and demonstrated during the course of the NETMAR project, is to build new SKOS concept collections which formalise the desired aggregations for given applications, and uses typed relationships to state which PUV concepts contribute to a specific aggregation. Development of these new collections requires input from a group of experts in the application domain who can decide which PUV

Semi-Supervised Learning to Identify UMLS Semantic Relations.

Science.gov (United States)

Luo, Yuan; Uzuner, Ozlem

2014-01-01

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

Context-rich semantic framework for effective data-to-decisions in coalition networks

Science.gov (United States)

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.

Law Grenelle 1 evaluation and propositions; Loi grenelle 1 evaluation et propositions

Energy Technology Data Exchange (ETDEWEB)

Bacher, P

2008-11-15

In spite of many positive points proposed in the law project Grenelle 1, some gaps remain. The author provides recommendations for some articles and details this propositions. Particularly he explains that the law project forgets the electricity part in the fight against the CO{sub 2} emissions. (A.L.B.)

Effective Fusion of Multi-Modal Remote Sensing Data in a Fully Convolutional Network for Semantic Labeling

Directory of Open Access Journals (Sweden)

Wenkai Zhang

2017-12-01

Full Text Available In recent years, Fully Convolutional Networks (FCN have led to a great improvement of semantic labeling for various applications including multi-modal remote sensing data. Although different fusion strategies have been reported for multi-modal data, there is no in-depth study of the reasons of performance limits. For example, it is unclear, why an early fusion of multi-modal data in FCN does not lead to a satisfying result. In this paper, we investigate the contribution of individual layers inside FCN and propose an effective fusion strategy for the semantic labeling of color or infrared imagery together with elevation (e.g., Digital Surface Models. The sensitivity and contribution of layers concerning classes and multi-modal data are quantified by recall and descent rate of recall in a multi-resolution model. The contribution of different modalities to the pixel-wise prediction is analyzed explaining the reason of the poor performance caused by the plain concatenation of different modalities. Finally, based on the analysis an optimized scheme for the fusion of layers with image and elevation information into a single FCN model is derived. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset (infrared and RGB imagery as well as elevation and the Potsdam dataset (RGB imagery and elevation. Comprehensive evaluations demonstrate the potential of the proposed approach.

Syntaxe de l'adverbe de phrase et structure prédicative de la proposition allemande : Eléments pour une description fonctionnelle

Directory of Open Access Journals (Sweden)

Modicom, Pierre-Yves

2016-07-01

Full Text Available The syntax of higher-order adverbials (modal and argumentative adverbials, among others raises several challenges for the topological model of German sentence structure when it comes to its semantic and/or information structural interpretation. It is often assumed that, when used in post-verbal position, in the so-called middle field of the sentence, or in a subordinate clause, they mark the border between a topical or thematic field (defined as « what the proposition is about » and the comment or rheme (« what is said about the topic/theme ». More specifically, researchers such as FOURQUET and ZEMB have given a predicational reading of this theme-rheme opposition; the placement of higher-order adverbials and/or sentence negation is supposed to be the index of the border between the main predicate (corresponding to the « right middle field » and its domain of validity (« left middle field ». Yet, on the basis of authentic data, it appears that the crucial requirement for this claim, namely that there is one and only one slot for such « phematic » adverbials in each proposition, does not fit with reality. More specifically, higher-order adverbials can be realized inside the allegedly thematic part of the middle field. The article proposes to use a framework derived from DIK's Functional Grammar to solve this problem. According to this approach, the proposition is generated through a succession of predications corresponding to a precise number of representational levels. I argue that constituent order in German exhibits some regularities corresponding to this view. Once this finite series of predications is taken for granted, ZEMB's model can be reformulated in such a way that there is a slot for higher-order adverbials at each predicational level. This claim matches the semantic intuitions of both FOURQUET and ZEMB, and the data observed in corpora. Finally, I propose that higher-order adverbials be treated as commending both the domain

Lateralized direct and indirect semantic priming effects in subjects with paranormal experiences and beliefs.

Science.gov (United States)

Pizzagalli, D; Lehmann, D; Brugger, P

2001-01-01

The present investigation tested the hypothesis that, as an aspect of schizotypal thinking, the formation of paranormal beliefs was related to spreading activation characteristics within semantic networks. From a larger student population (n = 117) prescreened for paranormal belief, 12 strong believers and 12 strong disbelievers (all women) were invited for a lateralized semantic priming task with directly and indirectly related prime-target pairs. Believers showed stronger indirect (but not direct) semantic priming effects than disbelievers after left (but not right) visual field stimulation, indicating faster appreciation of distant semantic relations specifically by the right hemisphere, reportedly specialized in coarse rather than focused semantic processing. These results are discussed in the light of recent findings in schizophrenic patients with thought disorders. They suggest that a disinhibition with semantic networks may underlie the formation of paranormal belief. The potential usefulness of work with healthy subjects for neuropsychiatric research is stressed. Copyright 2001 S. Karger AG, Basel

Gender Differences and Informal Networks in a Scandinavian Context

DEFF Research Database (Denmark)

Waldstrøm, Christian

2001-01-01

The informal networks in organizations have been under increasing scrutiny in the past years, and several aspects of those informal structures have been studied, among those the gender differences. In order to go beyond the intuitive and prejudicial characterization, several researchers have...... performed empirical analyses using networks theory. This has resulted in a number of well-founded propositions about how male and female managers develop and use different informal networks. One key finding, among others, is the proposition that female managers seem to develop dual networks (one with other...... important competencies stated by male and female managers in Danish companies. While the results seem to indicate that there are fewer differences between the genders than might be expected, using a factor analysis indicates that there are some structural differences suggesting that the proposition about...

Propositional Calculus in Coq

OpenAIRE

van Doorn, Floris

2015-01-01

I formalize important theorems about classical propositional logic in the proof assistant Coq. The main theorems I prove are (1) the soundness and completeness of natural deduction calculus, (2) the equivalence between natural deduction calculus, Hilbert systems and sequent calculus and (3) cut elimination for sequent calculus.

Mining Predictors of Success in Air Force Flight Training Regiments via Semantic Analysis of Instructor Evaluations

Science.gov (United States)

2018-03-01

the flight-training course. 14. SUBJECT TERMS text mining , feedback analysis, semantic network, binary classification 15. NUMBER OF PAGES 105 16...A. TEXT MINING ..........................................................................................5 B. SEMANTIC WORD NETWORK...13 Figure 2. Text Mining Pre-Processing Techniques. Source: Vijayarani (2015). ............20 Figure 3. From text

Theoretical Propositions for the Citizen Formation Mediated by Technology

Directory of Open Access Journals (Sweden)

Tania Margarita Martínez de Padrón

2018-02-01

Full Text Available The research presented emerges from the connotations concerning the formation of the citizenship by the information technology and communication. Be part of the conception of the current citizen and the influence that has emerged through the utility of the various social networks, as well as Canaima education project and the guidance provided to schoolchildren in this sense. The general objective was to generate propositions theoretical that guide the formation of citizenship mediated by ICT in the primary schools of Santa Teresa del Tuy. The methodology used was the qualitative paradigm, based on the interpretative phenomenological approach of Heidegger, which is interested in discovering and understanding the meanings, habits and practices of the human being. Castle (2000: 5. The researcher approached the field object of study to observe, describe and interpret a reality. As an instrument used the interview in depth. The information obtained was recorded in pictures which allowed to comply with the development of specific objectives through triangulation. On whose findings prevailed deviating from the use of technological tools and how these have formed the formation of citizenship in school children in their behavior and actions. At the same time, allowed know from educational technological approach, that sparing the teacher provides guidance that redirect the formation of citizenship. Also was the stated objective as it was the theoretical propositions that guide the formation of citizens ICT-mediated.

Semantic Web: Metadata, Linked Data, Open Data

Directory of Open Access Journals (Sweden)

Vanessa Russo

2015-12-01

Full Text Available What's the Semantic Web? What's the use? The inventor of the Web Tim Berners-Lee describes it as a research methodology able to take advantage of the network to its maximum capacity. This metadata system represents the innovative element through web 2.0 to web 3.0. In this context will try to understand what are the theoretical and informatic requirements of the Semantic Web. Finally will explain Linked Data applications to develop new tools for active citizenship.

ERPs, semantic processing and age.

Science.gov (United States)

Miyamoto, T; Katayama, J; Koyama, T

1998-06-01

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

The Functional Organisation of the Fronto-Temporal Language System: Evidence from Syntactic and Semantic Ambiguity

Science.gov (United States)

Rodd, Jennifer M.; Longe, Olivia A.; Randall, Billi; Tyler, Lorraine K.

2010-01-01

Spoken language comprehension is known to involve a large left-dominant network of fronto-temporal brain regions, but there is still little consensus about how the syntactic and semantic aspects of language are processed within this network. In an fMRI study, volunteers heard spoken sentences that contained either syntactic or semantic ambiguities…

Exploring the role of the posterior middle temporal gyrus in semantic cognition: Integration of anterior temporal lobe with executive processes.

Science.gov (United States)

Davey, James; Thompson, Hannah E; Hallam, Glyn; Karapanagiotidis, Theodoros; Murphy, Charlotte; De Caso, Irene; Krieger-Redwood, Katya; Bernhardt, Boris C; Smallwood, Jonathan; Jefferies, Elizabeth

2016-08-15

Making sense of the world around us depends upon selectively retrieving information relevant to our current goal or context. However, it is unclear whether selective semantic retrieval relies exclusively on general control mechanisms recruited in demanding non-semantic tasks, or instead on systems specialised for the control of meaning. One hypothesis is that the left posterior middle temporal gyrus (pMTG) is important in the controlled retrieval of semantic (not non-semantic) information; however this view remains controversial since a parallel literature links this site to event and relational semantics. In a functional neuroimaging study, we demonstrated that an area of pMTG implicated in semantic control by a recent meta-analysis was activated in a conjunction of (i) semantic association over size judgements and (ii) action over colour feature matching. Under these circumstances the same region showed functional coupling with the inferior frontal gyrus - another crucial site for semantic control. Structural and functional connectivity analyses demonstrated that this site is at the nexus of networks recruited in automatic semantic processing (the default mode network) and executively demanding tasks (the multiple-demand network). Moreover, in both task and task-free contexts, pMTG exhibited functional properties that were more similar to ventral parts of inferior frontal cortex, implicated in controlled semantic retrieval, than more dorsal inferior frontal sulcus, implicated in domain-general control. Finally, the pMTG region was functionally correlated at rest with other regions implicated in control-demanding semantic tasks, including inferior frontal gyrus and intraparietal sulcus. We suggest that pMTG may play a crucial role within a large-scale network that allows the integration of automatic retrieval in the default mode network with executively-demanding goal-oriented cognition, and that this could support our ability to understand actions and non

Semantic labeling of high-resolution aerial images using an ensemble of fully convolutional networks

Science.gov (United States)

Sun, Xiaofeng; Shen, Shuhan; Lin, Xiangguo; Hu, Zhanyi

2017-10-01

High-resolution remote sensing data classification has been a challenging and promising research topic in the community of remote sensing. In recent years, with the rapid advances of deep learning, remarkable progress has been made in this field, which facilitates a transition from hand-crafted features designing to an automatic end-to-end learning. A deep fully convolutional networks (FCNs) based ensemble learning method is proposed to label the high-resolution aerial images. To fully tap the potentials of FCNs, both the Visual Geometry Group network and a deeper residual network, ResNet, are employed. Furthermore, to enlarge training samples with diversity and gain better generalization, in addition to the commonly used data augmentation methods (e.g., rotation, multiscale, and aspect ratio) in the literature, aerial images from other datasets are also collected for cross-scene learning. Finally, we combine these learned models to form an effective FCN ensemble and refine the results using a fully connected conditional random field graph model. Experiments on the ISPRS 2-D Semantic Labeling Contest dataset show that our proposed end-to-end classification method achieves an overall accuracy of 90.7%, a state-of-the-art in the field.

Architecture for WSN Nodes Integration in Context Aware Systems Using Semantic Messages

Science.gov (United States)

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.

Further evidence for biased semantic networks in obsessive-compulsive disorder (OCD): when knives are no longer associated with buttering bread but only with stabbing people.

Science.gov (United States)

Jelinek, Lena; Hauschildt, Marit; Hottenrott, Birgit; Kellner, Michael; Moritz, Steffen

2014-12-01

Semantic network models suggest that individuals with obsessive-compulsive disorder (OCD) process words with multiple meanings (e.g., "knife") more likely in an OC-related (i.e., "weapon") than in a neutral way (i.e., "cutlery"). Initial evidence was found in an online study. The aim of the current study was to investigate semantic networks in a clinical OCD sample and particularly to identify whether changes in semantic networks following the add-on intervention association splitting (AS) exceeded changes expected through cognitive behavioral therapy (CBT) alone. An association task was presented to 36 healthy controls and 70 OCD patients over a period of eight weeks with OCD patients receiving CBT and an add-on intervention (randomized allocation to either AS or a computerized cognitive training). Participants were asked to generate up to five associations to standardized (OC-relevant, negative, neutral) and individual cue words. Associations were rated with regard to OC-relevance and valence. Analyses revealed that OCD participants produced a) significantly more OC-relevant associations and b) more negative associations than controls for cue words. In the OCD sample, the OC-relevance and valence of associations changed after therapy for personal cue words. This effect was associated with AS at statistical trend level. No clinical control group was recruited; no inter-rater reliability was assessed for the association task. Further evidence for biased associative networks in OCD was found. Associations of individually chosen cue words proved to be modifiable by therapy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Biomedical semantics in the Semantic Web.

Science.gov (United States)

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

2011-03-07

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

Production, Innovation and Service Networks

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Wæhrens, Brian Vejrum; Johansen, John

2012-01-01

Production, innovation and service networks of companies all over the world become increasingly decentralised, specialised and interdependent. These three characteristics combined inevitably lead to the formation of complex configurations of resources, crossing both national and organisational...... borders. The existing studies do not adequately address the complex interplay between co-evolving production, innovation and service networks. The widening geographical and cognitive gaps between these networks mean that coordinating them and managing their interfaces in a global operations context...... are becoming strategically important. The purpose of this paper is to address this issue and to develop a number of propositions about the development and organisation of these networks. The paper highlights the critical importance of engineering operations in this process. The propositions are developed...

Production, Innovation and Service Networks

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Wæhrens, Brian Vejrum; Johansen, John

2011-01-01

is becoming strategically important. The purpose of this paper is to address this issue and to develop a number of propositions about how companies can organize these networks and coordinate between them effectively. The propositions are developed by employing the design science approach based on a literature......Production, innovation and service networks of companies all over the world become increasingly decentralized, specialized and interdependent. The three characteristics combined inevitably lead to the formation of complex configurations of assets and capabilities crossing both national...... and organisational borders. The existing studies do not adequately address the complex interplay between co-evolving production, innovation and service networks. The widening geographical and cognitive gap between these networks means that coordinating them and managing their interfaces in global operations context...

California's tobacco tax initiative: the development and passage of Proposition 99.

Science.gov (United States)

Traynor, M P; Glantz, S A

1996-01-01

In this case study, we describe and analyze the development and passage of California's tobacco tax initiative, Proposition 99, the Tobacco Tax and Health Promotion Act of 1988. We gathered information from published reports, public documents, personal correspondence, internal memorandums, polling data, and interviews with representatives from organizations that participated in the Proposition 99 campaign. Proposition 99 passed as a result of the efforts of a coalition of voluntary health agencies, medical organizations, and environmental groups. They organized a long-term effort by conducting essential polling, planning strategies, gaining media exposure, developing a coalition, and running a successful campaign to enact the tax by shifting the venue from legislative to initiative politics. To build the coalition that was needed to pass Proposition 99, public health proponents enlisted the help of medical organizations in exchange for additional revenue to be allocated to medical services. By shifting the venue from the legislature to the general public, advocates capitalized on public concern about tobacco and for youth and took advantage of the tobacco industry's low credibility. The passage of Proposition 99, despite a massive campaign against it by the tobacco industry, represents a milestone in the tobacco control and public health fields. From its passage in 1988 through 1993, tobacco use in California declined by 27 percent, which is three times faster than the United States average. As a result, Proposition 99 has served as a national model for other states and the federal government. Although allocation of tobacco tax revenues specifically to health education and prevention was a primary goal during the development and passage of Proposition 99, when the venue shifted back to the legislature for implementation, medical organizations successfully advocated illegal diversions of Proposition 99 tobacco control and research funds to medical services

Interests diffusion on a semantic multiplex. Comparing Computer Science and American Physical Society communities

Science.gov (United States)

D'Agostino, Gregorio; De Nicola, Antonio

2016-10-01

Exploiting the information about members of a Social Network (SN) represents one of the most attractive and dwelling subjects for both academic and applied scientists. The community of Complexity Science and especially those researchers working on multiplex social systems are devoting increasing efforts to outline general laws, models, and theories, to the purpose of predicting emergent phenomena in SN's (e.g. success of a product). On the other side the semantic web community aims at engineering a new generation of advanced services tailored to specific people needs. This implies defining constructs, models and methods for handling the semantic layer of SNs. We combined models and techniques from both the former fields to provide a hybrid approach to understand a basic (yet complex) phenomenon: the propagation of individual interests along the social networks. Since information may move along different social networks, one should take into account a multiplex structure. Therefore we introduced the notion of "Semantic Multiplex". In this paper we analyse two different semantic social networks represented by authors publishing in the Computer Science and those in the American Physical Society Journals. The comparison allows to outline common and specific features.

Real-time object detection and semantic segmentation for autonomous driving

Science.gov (United States)

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

2018-02-01

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

Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

Directory of Open Access Journals (Sweden)

Carlos R. Rangel

2016-08-01

Full Text Available In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease, and the main cells in each community. We analyze our approach in two cases: TGF-ß and the Alzheimer Disease.

Semantic Modeling for SNPs Associated with Ethnic Disparities in HapMap Samples

Directory of Open Access Journals (Sweden)

HyoYoung Kim

2014-03-01

Full Text Available Single-nucleotide polymorphisms (SNPs have been emerging out of the efforts to research human diseases and ethnic disparities. A semantic network is needed for in-depth understanding of the impacts of SNPs, because phenotypes are modulated by complex networks, including biochemical and physiological pathways. We identified ethnicity-specific SNPs by eliminating overlapped SNPs from HapMap samples, and the ethnicity-specific SNPs were mapped to the UCSC RefGene lists. Ethnicity-specific genes were identified as follows: 22 genes in the USA (CEU individuals, 25 genes in the Japanese (JPT individuals, and 332 genes in the African (YRI individuals. To analyze the biologically functional implications for ethnicity-specific SNPs, we focused on constructing a semantic network model. Entities for the network represented by "Gene," "Pathway," "Disease," "Chemical," "Drug," "ClinicalTrials," "SNP," and relationships between entity-entity were obtained through curation. Our semantic modeling for ethnicity-specific SNPs showed interesting results in the three categories, including three diseases ("AIDS-associated nephropathy," "Hypertension," and "Pelvic infection", one drug ("Methylphenidate", and five pathways ("Hemostasis," "Systemic lupus erythematosus," "Prostate cancer," "Hepatitis C virus," and "Rheumatoid arthritis". We found ethnicity-specific genes using the semantic modeling, and the majority of our findings was consistent with the previous studies - that an understanding of genetic variability explained ethnicity-specific disparities.

The Semantic Web in Education

Science.gov (United States)

Ohler, Jason

2008-01-01

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

Evaluating the effect of annotation size on measures of semantic similarity

KAUST Repository

Kulmanov, Maxat

2017-02-13

Background: Ontologies are widely used as metadata in biological and biomedical datasets. Measures of semantic similarity utilize ontologies to determine how similar two entities annotated with classes from ontologies are, and semantic similarity is increasingly applied in applications ranging from diagnosis of disease to investigation in gene networks and functions of gene products.

Preserved musical semantic memory in semantic dementia.

Science.gov (United States)

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

2011-02-01

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

A trade-off between local and distributed information processing associated with remote episodic versus semantic memory.

Science.gov (United States)

Heisz, Jennifer J; Vakorin, Vasily; Ross, Bernhard; Levine, Brian; McIntosh, Anthony R

2014-01-01

Episodic memory and semantic memory produce very different subjective experiences yet rely on overlapping networks of brain regions for processing. Traditional approaches for characterizing functional brain networks emphasize static states of function and thus are blind to the dynamic information processing within and across brain regions. This study used information theoretic measures of entropy to quantify changes in the complexity of the brain's response as measured by magnetoencephalography while participants listened to audio recordings describing past personal episodic and general semantic events. Personal episodic recordings evoked richer subjective mnemonic experiences and more complex brain responses than general semantic recordings. Critically, we observed a trade-off between the relative contribution of local versus distributed entropy, such that personal episodic recordings produced relatively more local entropy whereas general semantic recordings produced relatively more distributed entropy. Changes in the relative contributions of local and distributed entropy to the total complexity of the system provides a potential mechanism that allows the same network of brain regions to represent cognitive information as either specific episodes or more general semantic knowledge.

Energy, Economic Growth and Environmental Sustainability: Five Propositions

Directory of Open Access Journals (Sweden)

Steven Sorrell

2010-06-01

Full Text Available This paper advances five linked and controversial propositions that have both deep historical roots and urgent contemporary relevance. These are: (a the rebound effects from energy efficiency improvements are significant and limit the potential for decoupling energy consumption from economic growth; (b the contribution of energy to productivity improvements and economic growth has been greatly underestimated; (c the pursuit of improved efficiency needs to be complemented by an ethic of sufficiency; (d sustainability is incompatible with continued economic growth in rich countries; and (e a zero-growth economy is incompatible with a fractional reserve banking system. These propositions run counter to conventional wisdom and each highlights either a "blind spot" or "taboo subject" that deserves closer scrutiny. While accepting one proposition reinforces the case for accepting the next, the former is neither necessary nor sufficient for the latter.

Reasoning about logical propositions and success in science

Science.gov (United States)

Piburn, Michael D.

1990-12-01

Students display a number of misconceptions when asked to reason about logical propositions. Rather than being random, these misconceptions are stereotypic, and relate to age, ability, and success in science. The grades in science achieved by tenth-grade general science students from two parochial single-sex schools in Australia correlated with their scores on the Propositional Logic Test. The students' ability level was consistently related to the pattern of errors they committed on that measure. Mean scores were lowest on a subtest of ability to use the biconditional and implication, higher on the disjunction, and highest on the conjunction. Success in science was predicted most strongly by the disjunction and biconditional subtests. Knowledge of the way in which a person reasons about logical propositions provides additional insights into the transformations information is subjected to as it is integrated into mental schemata.

Metric Propositional Neighborhood Logics: Expressiveness, Decidability, and Undecidability

DEFF Research Database (Denmark)

Bresolin, Davide; Della Monica, Dario; Goranko, Valentin

2010-01-01

Metric Propositional Neighborhood Logic (MPNL) over natural numbers. MPNL features two modalities referring, respectively, to an interval that is “met by” the current one and to an interval that “meets” the current one, plus an infinite set of length constraints, regarded as atomic propositions...... that MPNL is decidable in double exponential time and expressively complete with respect to a well-defined subfragment of the two-variable fragment FO2[N, =,...

Propositional density and cognitive function in later life: findings from the Precursors Study.

Science.gov (United States)

Engelman, Michal; Agree, Emily M; Meoni, Lucy A; Klag, Michael J

2010-11-01

We used longitudinal data from the Johns Hopkins Precursors Study to test the hypothesis that written propositional density measured early in life is lower for people who develop dementia categorized as Alzheimer's disease (AD). This association was reported in 1996 for the Nun Study, and the Precursors Study offered an unprecedented chance to reexamine it among respondents with different gender, education, and occupation profiles. Eighteen individuals classified as AD patients (average age at diagnosis: 74) were assigned 2 sex-and-age matched controls, and propositional density in medical school admission essays (average age at writing: 22) was assessed via Computerized Propositional Idea Density Rater 3 linguistic analysis software. Adjusted odds ratios (ORs) for the matched case-control study were calculated using conditional (fixed-effects) logistic regression. Mean propositional density is lower for cases than for controls (4.70 vs. 4.99 propositions per 10 words, 1-sided p = .01). Higher propositional density substantially lowers the odds of AD (OR = 0.16, 95% confidence interval = 0.03-0.90, 1-sided p = .02). Propositional density scores in writing samples from early adulthood appear to predict AD in later life for men as well as women. Studies of cognition across the life course might beneficially incorporate propositional density as a potential marker of cognitive reserve.

The role of the left anterior temporal lobe in semantic composition vs. semantic memory.

Science.gov (United States)

Westerlund, Masha; Pylkkänen, Liina

2014-05-01

The left anterior temporal lobe (LATL) is robustly implicated in semantic processing by a growing body of literature. However, these results have emerged from two distinct bodies of work, addressing two different processing levels. On the one hand, the LATL has been characterized as a 'semantic hub׳ that binds features of concepts across a distributed network, based on results from semantic dementia and hemodynamic findings on the categorization of specific compared to basic exemplars. On the other, the LATL has been implicated in combinatorial operations in language, as shown by increased activity in this region associated with the processing of sentences and of basic phrases. The present work aimed to reconcile these two literatures by independently manipulating combination and concept specificity within a minimal MEG paradigm. Participants viewed simple nouns that denoted either low specificity (fish) or high specificity categories (trout) presented in either combinatorial (spotted fish/trout) or non-combinatorial contexts (xhsl fish/trout). By combining these paradigms from the two literatures, we directly compared the engagement of the LATL in semantic memory vs. semantic composition. Our results indicate that although noun specificity subtly modulates the LATL activity elicited by single nouns, it most robustly affects the size of the composition effect when these nouns are adjectivally modified, with low specificity nouns eliciting a much larger effect. We conclude that these findings are compatible with an account in which the specificity and composition effects arise from a shared mechanism of meaning specification. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Novel Approach to Semantic Similarity Measurement Based on a Weighted Concept Lattice: Exemplifying Geo-Information

Directory of Open Access Journals (Sweden)

Jia Xiao

2017-11-01

Full Text Available The measurement of semantic similarity has been widely recognized as having a fundamental and key role in information science and information systems. Although various models have been proposed to measure semantic similarity, these models are not able effectively to quantify the weights of relevant factors that impact on the judgement of semantic similarity, such as the attributes of concepts, application context, and concept hierarchy. In this paper, we propose a novel approach that comprehensively considers the effects of various factors on semantic similarity judgment, which we name semantic similarity measurement based on a weighted concept lattice (SSMWCL. A feature model and network model are integrated together in SSMWCL. Based on the feature model, the combined weight of each attribute of the concepts is calculated by merging its information entropy and inclusion-degree importance in a specific application context. By establishing the weighted concept lattice, the relative hierarchical depths of concepts for comparison are computed according to the principle of the network model. The integration of feature model and network model enables SSMWCL to take account of differences in concepts more comprehensively in semantic similarity measurement. Additionally, a workflow of SSMWCL is designed to demonstrate these procedures and a case study of geo-information is conducted to assess the approach.

Distinctive Structural and Effective Connectivity Changes of Semantic Cognition Network across Left and Right Mesial Temporal Lobe Epilepsy Patients

Directory of Open Access Journals (Sweden)

Xiaotong Fan

2016-01-01

Full Text Available Occurrence of language impairment in mesial temporal lobe epilepsy (mTLE patients is common and left mTLE patients always exhibit a primary problem with access to names. To explore different neuropsychological profiles between left and right mTLE patients, the study investigated both structural and effective functional connectivity changes within the semantic cognition network between these two groups and those from normal controls. We found that gray matter atrophy of left mTLE patients was more severe than that of right mTLE patients in the whole brain and especially within the semantic cognition network in their contralateral hemisphere. It suggested that seizure attacks were rather targeted than random for patients with hippocampal sclerosis (HS in the dominant hemisphere. Functional connectivity analysis during resting state fMRI revealed that subregions of the anterior temporal lobe (ATL in the left HS patients were no longer effectively connected. Further, we found that, unlike in right HS patients, increased causal linking between ipsilateral regions in the left HS epilepsy patients cannot make up for their decreased contralateral interaction. It suggested that weakened contralateral connection and disrupted effective interaction between subregions of the unitary, transmodal hub of the ATL may be the primary cause of anomia in the left HS patients.

Distinctive Structural and Effective Connectivity Changes of Semantic Cognition Network across Left and Right Mesial Temporal Lobe Epilepsy Patients

Science.gov (United States)

Fan, Xiaotong; Shang, Kun; Wang, Xiaocui; Wang, Peipei; Shan, Yongzhi; Lu, Jie

2016-01-01

Occurrence of language impairment in mesial temporal lobe epilepsy (mTLE) patients is common and left mTLE patients always exhibit a primary problem with access to names. To explore different neuropsychological profiles between left and right mTLE patients, the study investigated both structural and effective functional connectivity changes within the semantic cognition network between these two groups and those from normal controls. We found that gray matter atrophy of left mTLE patients was more severe than that of right mTLE patients in the whole brain and especially within the semantic cognition network in their contralateral hemisphere. It suggested that seizure attacks were rather targeted than random for patients with hippocampal sclerosis (HS) in the dominant hemisphere. Functional connectivity analysis during resting state fMRI revealed that subregions of the anterior temporal lobe (ATL) in the left HS patients were no longer effectively connected. Further, we found that, unlike in right HS patients, increased causal linking between ipsilateral regions in the left HS epilepsy patients cannot make up for their decreased contralateral interaction. It suggested that weakened contralateral connection and disrupted effective interaction between subregions of the unitary, transmodal hub of the ATL may be the primary cause of anomia in the left HS patients. PMID:28018680

Beginning Typewriting: A Fifty-Fifty Proposition

Science.gov (United States)

Ivarie, Ted

1976-01-01

Beginning typewriting should be a 50-50 proposition with equal time devoted to machine operation and skill development and to language arts instruction in elementary and secondary education. (Author/LH)

Semantic Advertising

OpenAIRE

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

2013-01-01

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

Increased functional connectivity in the default mode network in mild cognitive impairment: a maladaptive compensatory mechanism associated with poor semantic memory performance.

Science.gov (United States)

Gardini, Simona; Venneri, Annalena; Sambataro, Fabio; Cuetos, Fernando; Fasano, Fabrizio; Marchi, Massimo; Crisi, Girolamo; Caffarra, Paolo

2015-01-01

Semantic memory decline and changes of default mode network (DMN) connectivity have been reported in mild cognitive impairment (MCI). Only a few studies, however, have investigated the role of changes of activity in the DMN on semantic memory in this clinical condition. The present study aimed to investigate more extensively the relationship between semantic memory impairment and DMN intrinsic connectivity in MCI. Twenty-one MCI patients and 21 healthy elderly controls matched for demographic variables took part in this study. All participants underwent a comprehensive semantic battery including tasks of category fluency, visual naming and naming from definition for objects, actions and famous people, word-association for early and late acquired words and reading. A subgroup of the original sample (16 MCI patients and 20 healthy elderly controls) was also scanned with resting state functional magnetic resonance imaging and DMN connectivity was estimated using a seed-based approach. Compared with healthy elderly, patients showed an extensive semantic memory decline in category fluency, visual naming, naming from definition, words-association, and reading tasks. Patients presented increased DMN connectivity between the medial prefrontal regions and the posterior cingulate and between the posterior cingulate and the parahippocampus and anterior hippocampus. MCI patients also showed a significant negative correlation of medial prefrontal gyrus connectivity with parahippocampus and posterior hippocampus and visual naming performance. Our findings suggest that increasing DMN connectivity may contribute to semantic memory deficits in MCI, specifically in visual naming. Increased DMN connectivity with posterior cingulate and medio-temporal regions seems to represent a maladaptive reorganization of brain functions in MCI, which detrimentally contributes to cognitive impairment in this clinical population.

The semantic web in an SMS

NARCIS (Netherlands)

Valkering, Onno; de Boer, Victor; Lô, Gossa; Blankendaal, Romy; Schlobach, Stefan

2016-01-01

Many ICT applications and services, including those from the Semantic Web, rely on the Web for the exchange of data. This includes expensive server and network infrastructures. Most rural areas of developing countries are not reached by the Web and its possibilities, while at the same time the

Varieties of semantic cognition revealed through simultaneous decomposition of intrinsic brain connectivity and behaviour.

Science.gov (United States)

Vatansever, Deniz; Bzdok, Danilo; Wang, Hao-Ting; Mollo, Giovanna; Sormaz, Mladen; Murphy, Charlotte; Karapanagiotidis, Theodoros; Smallwood, Jonathan; Jefferies, Elizabeth

2017-09-01

Contemporary theories assume that semantic cognition emerges from a neural architecture in which different component processes are combined to produce aspects of conceptual thought and behaviour. In addition to the state-level, momentary variation in brain connectivity, individuals may also differ in their propensity to generate particular configurations of such components, and these trait-level differences may relate to individual differences in semantic cognition. We tested this view by exploring how variation in intrinsic brain functional connectivity between semantic nodes in fMRI was related to performance on a battery of semantic tasks in 154 healthy participants. Through simultaneous decomposition of brain functional connectivity and semantic task performance, we identified distinct components of semantic cognition at rest. In a subsequent validation step, these data-driven components demonstrated explanatory power for neural responses in an fMRI-based semantic localiser task and variation in self-generated thoughts during the resting-state scan. Our findings showed that good performance on harder semantic tasks was associated with relative segregation at rest between frontal brain regions implicated in controlled semantic retrieval and the default mode network. Poor performance on easier tasks was linked to greater coupling between the same frontal regions and the anterior temporal lobe; a pattern associated with deliberate, verbal thematic thoughts at rest. We also identified components that related to qualities of semantic cognition: relatively good performance on pictorial semantic tasks was associated with greater separation of angular gyrus from frontal control sites and greater integration with posterior cingulate and anterior temporal cortex. In contrast, good speech production was linked to the separation of angular gyrus, posterior cingulate and temporal lobe regions. Together these data show that quantitative and qualitative variation in semantic

Priming semantic concepts affects the dynamics of aesthetic appreciation.

Science.gov (United States)

Faerber, Stella J; Leder, Helmut; Gerger, Gernot; Carbon, Claus-Christian

2010-10-01

Aesthetic appreciation (AA) plays an important role for purchase decisions, for the appreciation of art and even for the selection of potential mates. It is known that AA is highly reliable in single assessments, but over longer periods of time dynamic changes of AA may occur. We measured AA as a construct derived from the literature through attractiveness, arousal, interestingness, valence, boredom and innovativeness. By means of the semantic network theory we investigated how the priming of AA-relevant semantic concepts impacts the dynamics of AA of unfamiliar product designs (car interiors) that are known to be susceptible to triggering such effects. When participants were primed for innovativeness, strong dynamics were observed, especially when the priming involved additional AA-relevant dimensions. This underlines the relevance of priming of specific semantic networks not only for the cognitive processing of visual material in terms of selective perception or specific representation, but also for the affective-cognitive processing in terms of the dynamics of aesthetic processing. Copyright © 2010 Elsevier B.V. All rights reserved.

Crossmodal Semantic Constraints on Visual Perception of Binocular Rivalry

Directory of Open Access Journals (Sweden)

Yi-Chuan Chen

2011-10-01

Full Text Available Environments typically convey contextual information via several different sensory modalities. Here, we report a study designed to investigate the crossmodal semantic modulation of visual perception using the binocular rivalry paradigm. The participants viewed a dichoptic figure consisting of a bird and a car presented to each eye, while also listening to either a bird singing or car engine revving. Participants' dominant percepts were modulated by the presentation of a soundtrack associated with either bird or car, as compared to the presentation of a soundtrack irrelevant to both visual figures (tableware clattering together in a restaurant. No such crossmodal semantic effect was observed when the participants maintained an abstract semantic cue in memory. We then further demonstrate that crossmodal semantic modulation can be dissociated from the effects of high-level attentional control over the dichoptic figures and of low-level luminance contrast of the figures. In sum, we demonstrate a novel crossmodal effect in terms of crossmodal semantic congruency on binocular rivalry. This effect can be considered a perceptual grouping or contextual constraint on human visual awareness through mid-level crossmodal excitatory connections embedded in the multisensory semantic network.

[Electrophysiological bases of semantic processing of objects].

Science.gov (United States)

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

2007-02-01

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

Structured Semantic Knowledge Can Emerge Automatically from Predicting Word Sequences in Child-Directed Speech

Science.gov (United States)

Huebner, Philip A.; Willits, Jon A.

2018-01-01

Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory) to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM) and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing semantic system. PMID

Structured Semantic Knowledge Can Emerge Automatically from Predicting Word Sequences in Child-Directed Speech

Directory of Open Access Journals (Sweden)

Philip A. Huebner

2018-02-01

Full Text Available Previous research has suggested that distributional learning mechanisms may contribute to the acquisition of semantic knowledge. However, distributional learning mechanisms, statistical learning, and contemporary “deep learning” approaches have been criticized for being incapable of learning the kind of abstract and structured knowledge that many think is required for acquisition of semantic knowledge. In this paper, we show that recurrent neural networks, trained on noisy naturalistic speech to children, do in fact learn what appears to be abstract and structured knowledge. We trained two types of recurrent neural networks (Simple Recurrent Network, and Long Short-Term Memory to predict word sequences in a 5-million-word corpus of speech directed to children ages 0–3 years old, and assessed what semantic knowledge they acquired. We found that learned internal representations are encoding various abstract grammatical and semantic features that are useful for predicting word sequences. Assessing the organization of semantic knowledge in terms of the similarity structure, we found evidence of emergent categorical and hierarchical structure in both models. We found that the Long Short-term Memory (LSTM and SRN are both learning very similar kinds of representations, but the LSTM achieved higher levels of performance on a quantitative evaluation. We also trained a non-recurrent neural network, Skip-gram, on the same input to compare our results to the state-of-the-art in machine learning. We found that Skip-gram achieves relatively similar performance to the LSTM, but is representing words more in terms of thematic compared to taxonomic relations, and we provide reasons why this might be the case. Our findings show that a learning system that derives abstract, distributed representations for the purpose of predicting sequential dependencies in naturalistic language may provide insight into emergence of many properties of the developing

Semantator: annotating clinical narratives with semantic web ontologies.

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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

2011-07-01

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

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

Science.gov (United States)

Rajah, M N; McIntosh, A R

2005-03-01

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

On the universal structure of human lexical semantics.

Science.gov (United States)

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

2016-02-16

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

On the Translation of Semantic Relations: an empirical study

Directory of Open Access Journals (Sweden)

Louise Denver

2002-01-01

Full Text Available In this article, the transfer of semantic relations between propositions is discussed based on a pilot study carried out for didactic purposes at the Copenhagen Business School. The relations studied were unmarked in the source text (ST and the research aimed at investigating to what extent the translation of textual cohesion is the object of mental processing by semi-professional opt for a strategy involving the explicitation in the target text (TT of semantic relations which can be deduced from the ST by means of inferences.Neste artigo, discute-se a transferência de relações semânticas entre proposições com base em um estudo piloto com objetivos didáticos realizado na Copenhagen Business School. As relações analisadas eram não marcadas no texto de partida (TP. Procura-se investigar até que ponto a tradução da coesão textual é objeto de processamento mental por tradutores quase profissionais durante o processo de tradução e até que ponto os tradutores quase profissionais optam por uma estratégia envolvendo explicitação no texto de chegada (TC das relações semânticas que podem ser deduzidas a partir do TP através de inferências.

EVALUATION OF SEMANTIC SIMILARITY FOR SENTENCES IN NATURAL LANGUAGE BY MATHEMATICAL STATISTICS METHODS

Directory of Open Access Journals (Sweden)

A. E. Pismak

2016-03-01

Full Text Available Subject of Research. The paper is focused on Wiktionary articles structural organization in the aspect of its usage as the base for semantic network. Wiktionary community references, article templates and articles markup features are analyzed. The problem of numerical estimation for semantic similarity of structural elements in Wiktionary articles is considered. Analysis of existing software for semantic similarity estimation of such elements is carried out; algorithms of their functioning are studied; their advantages and disadvantages are shown. Methods. Mathematical statistics methods were used to analyze Wiktionary articles markup features. The method of semantic similarity computing based on statistics data for compared structural elements was proposed.Main Results. We have concluded that there is no possibility for direct use of Wiktionary articles as the source for semantic network. We have proposed to find hidden similarity between article elements, and for that purpose we have developed the algorithm for calculation of confidence coefficients proving that each pair of sentences is semantically near. The research of quantitative and qualitative characteristics for the developed algorithm has shown its major performance advantage over the other existing solutions in the presence of insignificantly higher error rate. Practical Relevance. The resulting algorithm may be useful in developing tools for automatic Wiktionary articles parsing. The developed method could be used in computing of semantic similarity for short text fragments in natural language in case of algorithm performance requirements are higher than its accuracy specifications.

A semantic autonomous video surveillance system for dense camera networks in Smart Cities.

Science.gov (United States)

Calavia, Lorena; Baladrón, Carlos; Aguiar, Javier M; Carro, Belén; Sánchez-Esguevillas, Antonio

2012-01-01

This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

A Semantic Autonomous Video Surveillance System for Dense Camera Networks in Smart Cities

Directory of Open Access Journals (Sweden)

Antonio Sánchez-Esguevillas

2012-08-01

Full Text Available This paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network.

Developing A Web-based User Interface for Semantic Information Retrieval

Science.gov (United States)

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.

The semantic web in translational medicine: current applications and future directions.

Science.gov (United States)

Machado, Catia M; Rebholz-Schuhmann, Dietrich; Freitas, Ana T; Couto, Francisco M

2015-01-01

Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice. © The Author 2013. Published by Oxford University Press.

Distinct neural substrates of affective and cognitive theory of mind impairment in semantic dementia.

Science.gov (United States)

Bejanin, Alexandre; Chételat, Gaël; Laisney, Mickael; Pélerin, Alice; Landeau, Brigitte; Merck, Catherine; Belliard, Serge; de La Sayette, Vincent; Eustache, Francis; Desgranges, Béatrice

2017-06-01

Using structural MRI, we investigated the brain substrates of both affective and cognitive theory of mind (ToM) in 19 patients with semantic dementia. We also ran intrinsic connectivity analyses to identify the networks to which the substrates belong and whether they are functionally disturbed in semantic dementia. In line with previous studies, we observed a ToM impairment in patients with semantic dementia even when semantic memory was regressed out. Our results also highlighted different neural bases according to the nature (affective or cognitive) of the representations being inferred. The affective ToM deficit was associated with atrophy in the amygdala, suggesting the involvement of emotion-processing deficits in this impairment. By contrast, cognitive ToM performances were correlated with the volume of medial prefrontal and parietal regions, as well as the right frontal operculum. Intrinsic connectivity analyses revealed decreased functional connectivity, mainly between midline cortical regions and temporal regions. They also showed that left medial temporal regions were functionally isolated, a further possible hindrance to normal social cognitive functioning in semantic dementia. Overall, this study addressed for the first time the neuroanatomical substrates of both cognitive and affective ToM disruption in semantic dementia, highlighting disturbed connectivity within the networks that sustain these abilities.

The Interaction between Semantic Representation and Episodic Memory.

Science.gov (United States)

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.

Semantic content-based recommendations using semantic graphs.

Science.gov (United States)

Guo, Weisen; Kraines, Steven B

2010-01-01

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

Modeling non-monotonic properties under propositional argumentation

Science.gov (United States)

Wang, Geng; Lin, Zuoquan

2013-03-01

In the field of knowledge representation, argumentation is usually considered as an abstract framework for nonclassical logic. In this paper, however, we'd like to present a propositional argumentation framework, which can be used to closer simulate a real-world argumentation. We thereby argue that under a dialectical argumentation game, we can allow non-monotonic reasoning even under classical logic. We introduce two methods together for gaining nonmonotonicity, one by giving plausibility for arguments, the other by adding "exceptions" which is similar to defaults. Furthermore, we will give out an alternative definition for propositional argumentation using argumentative models, which is highly related to the previous reasoning method, but with a simple algorithm for calculation.

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

Science.gov (United States)

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%).

Semantic growth of morphological families in English

Directory of Open Access Journals (Sweden)

Henry Regina

2013-01-01

Full Text Available This paper explores the question of when and how morphological families are formed in one’s mental lexicon, by analyzing age-of-acquisition norms to morphological families (e.g., booking, bookshelf, check book and their shared morphemes (book. We demonstrate that the speed of growth and the size of the family depend on how early the shared morpheme is acquired and how many connections the family has at the time a new concept is incorporated in the family. These findings dovetail perfectly with the Semantic Growth model of connectivity in semantic networks by Steyvers and Tenenbaum (2005. We discuss implications of our findings for theories of vocabulary acquisition.

Biology Question Generation from a Semantic Network

Science.gov (United States)

Zhang, Lishan

Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions. To boost students' learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student's current competence so that a suitable question could be selected based on the student's previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group. To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators. A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from

SEMANTIC SEGMENTATION OF BUILDING ELEMENTS USING POINT CLOUD HASHING

Directory of Open Access Journals (Sweden)

M. Chizhova

2018-05-01

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

Challenges and weaknesses in the use of concept maps as a learning strategy in undergraduate health programs

Directory of Open Access Journals (Sweden)

Enios Carlos Duarte

2017-09-01

Full Text Available This paper considers the analysis of concept maps utilized as a learning tool in disciplines dealing with immunological responses in two undergraduate Health programs. In total, 48 concept maps were assessed regarding their propositions and structure. The clarity of the propositions was analyzed by using the Propositional Clarity Table and they were classified as adequate propositions (AP and inadequate propositions (IP. In 48 concept maps, 648 propositions were analyzed in order to determine semantic clarity and conceptual mistakes. Assessments revealed that 69 % of the propositions were classified as adequate and 31 % as inadequate. All the maps analyzed were categorized as showing a network structure. However, when correlating the connections established among the several types of response by the immune system, it was found that despite being structured as a network, only 31.2 % of the concept maps indicated conceptual relationships between the modes of immune response. 27% of the concept maps were made with a high rate of proficiency. Upon the results of our analysis, we realized that there is still a long way in developing the mapping strategy. For us, this low percentage is related to the way undergraduates assimilate the mapping processes. This is a challenge which also reveals limits and weaknesses that may be addressed in future studies. It was noted that results bring into focus that the undergraduates’ learning of concepts associated with the bases of the immunological responses occurred in a meaningful way.

Evolutionary and Swarm computing for the Semantic Web

NARCIS (Netherlands)

Guéret, C.; Schlobach, S.; Dentler, K.; Schut, M.; Eiben, G.

2012-01-01

The Semantic Web has become a dynamic and enormous network of typed links between data sets stored on different machines. These data sets are machine readable and unambiguously interpretable, thanks to their underlying standard representation languages. The expressiveness and flexibility of the

Evolutionary and Swarm Computing for the Semantic Web

NARCIS (Netherlands)

Guéret, Christophe

2015-01-01

The Semantic Web has become a dynamic and enormous network of typed links between data sets stored on different machines. These data sets are machine readable and unambiguously interpretable, thanks to their underlying standard representation languages. The expressiveness and flexibility of the

A Current Logical Framework: The Propositional Fragment

National Research Council Canada - National Science Library

Watkins, Kevin

2003-01-01

We present the propositional fragment CLF of the Concurrent Logical Framework (CLF). CLF extends the Linear Logical Framework to allow the natural representation of concurrent computations in an object language...

Semantic web in the e-learning

Directory of Open Access Journals (Sweden)

Andrenizia Aquino Eluan

2008-01-01

Full Text Available With the evolution of the technology of information and communication, the Web is adding diversity of resources that can facilitate the development of some areas of the knowledge, because promotes the access and the use of information globalised, accessible and without borders. Discusses the semantic Web as a means of sharing information to adopt standards for interoperability to the communication in network. Among the concerns that surround the education area, are the strategies of search and information retrieval in a relevant and effective for the knowledge of construction and learning. In this context, is the Distance Education, which area can enjoy the resources of the Semantic Web and the advantages of using ontology, which will be presented in this article

Network-Based Visual Analysis of Tabular Data

Science.gov (United States)

Liu, Zhicheng

2012-01-01

Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look…

Risk, innovation and change : design propositions for implementing risk management in organizations

NARCIS (Netherlands)

van Staveren, Martinus Theodorus

2009-01-01

This Ph.D. research generated unique design propositions for implementing existing risk management methodologies in organizations. The resulting design propositions incorporate a synthesis of risk management, innovation management and change management. True implementation of risk management is

Association splitting of the sexual orientation-OCD-relevant semantic network.

Science.gov (United States)

Ching, Terence H W; Williams, Monnica T

2018-05-01

There is little research on treating symptoms of sexual orientation-obsessive-compulsive disorder (SO-OCD). Semantic networks represent a new cognitive approach for understanding cognitive mechanisms of SO-OCD. Specifically, we tested whether the self-help cognitive technique of association splitting (AS) developed from this approach would be efficacious in reducing SO-OCD symptoms and thought suppression. One hundred and twenty heterosexual undergraduates (82 females, 38 males) were randomly assigned to either the AS or waitlist control group. At baseline and four weeks later, participants completed items assessing SO-OCD symptoms, measures of sexual obsessions and thought suppression, and an association task in which they generated associations to different cue words. Generated associations were coded based on SO-OCD relevance and emotional valence. Results indicated reductions in SO-OCD-relevant associations across levels of emotional valence and SO-OCD-irrelevant negative associations, and increases in SO-OCD-irrelevant positive and neutral associations, only in the AS group. Furthermore, there were reductions in SO-OCD symptoms, sexual obsessions, and thought suppression only in the AS group. Importantly, these findings were obtained with overall large effect sizes. AS appears to be an efficacious self-help technique in reducing SO-OCD symptoms, sexual obsessions, and thought suppression. Clinical implications, limitations, and suggestions for future research are discussed.

Geospatial semantic web

CERN Document Server

Zhang, Chuanrong; Li, Weidong

2015-01-01

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

Of Prepositions and Propositions: Sharing Experiences and ...

African Journals Online (AJOL)

Of Prepositions and Propositions: Sharing Experiences and Perspectives on ... and Africanist scholars, written by an African and an Africanist graduate student. ... in the long-standing dispute over FGM (Female Genital Mutilation) research.

Towards IoT platforms’ integration : Semantic Translations between W3C SSN and ETSI SAREF

NARCIS (Netherlands)

Moreira, João Luiz; Daniele, L.M.; Ferreira Pires, Luis; van Sinderen, Marten J.; Wasielewska, Katarzyna; Szmeja, Pawel; Pawlowski, Wieslaw; Ganzha, Maria; Paprzycki, Marcin

2017-01-01

Several IoT ontologies have been developed lately to improve the semantic interoperability of IoT solutions. The most popular of these ontologies, the W3C Semantic Sensor Network (SSN), is considered an ontological foundation for diverse IoT initiatives, particularly OpenIoT. With characteristics

A librarian's guide to graphs, data and the semantic web

CERN Document Server

Powell, James

2015-01-01

Graphs are about connections, and are an important part of our connected and data-driven world. A Librarian's Guide to Graphs, Data and the Semantic Web is geared toward library and information science professionals, including librarians, software developers and information systems architects who want to understand the fundamentals of graph theory, how it is used to represent and explore data, and how it relates to the semantic web. This title provides a firm grounding in the field at a level suitable for a broad audience, with an emphasis on open source solutions and what problems these tools solve at a conceptual level, with minimal emphasis on algorithms or mathematics. The text will also be of special interest to data science librarians and data professionals, since it introduces many graph theory concepts by exploring data-driven networks from various scientific disciplines. The first two chapters consider graphs in theory and the science of networks, before the following chapters cover networks in vario...

Semantic Multimedia

NARCIS (Netherlands)

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

2008-01-01

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

Cross-modal integration of lexical-semantic features during word processing: evidence from oscillatory dynamics during EEG.

Directory of Open Access Journals (Sweden)

Markus J van Ackeren

Full Text Available In recent years, numerous studies have provided converging evidence that word meaning is partially stored in modality-specific cortical networks. However, little is known about the mechanisms supporting the integration of this distributed semantic content into coherent conceptual representations. In the current study we aimed to address this issue by using EEG to look at the spatial and temporal dynamics of feature integration during word comprehension. Specifically, participants were presented with two modality-specific features (i.e., visual or auditory features such as silver and loud and asked to verify whether these two features were compatible with a subsequently presented target word (e.g., WHISTLE. Each pair of features described properties from either the same modality (e.g., silver, tiny  =  visual features or different modalities (e.g., silver, loud  =  visual, auditory. Behavioral and EEG data were collected. The results show that verifying features that are putatively represented in the same modality-specific network is faster than verifying features across modalities. At the neural level, integrating features across modalities induces sustained oscillatory activity around the theta range (4-6 Hz in left anterior temporal lobe (ATL, a putative hub for integrating distributed semantic content. In addition, enhanced long-range network interactions in the theta range were seen between left ATL and a widespread cortical network. These results suggest that oscillatory dynamics in the theta range could be involved in integrating multimodal semantic content by creating transient functional networks linking distributed modality-specific networks and multimodal semantic hubs such as left ATL.

Outline of a Theory of Truth as Correctness for Semantic Information

Directory of Open Access Journals (Sweden)

Luciano Floridi

2009-11-01

Full Text Available The article develops a correctness theory of truth (CTT for semantic information. After the introduction, in section two, semantic information is shown to be translatable into propositional semantic information (i. In section three, i is polarised into a query (Q and a result (R, qualified by a specific context, a level of abstraction and a purpose. This polarization is normalised in section four, where [Q + R] is transformed into a Boolean question and its relative yes/no answer [Q + A]. This completes the reduction of the truth of i to the correctness of A. In sections five and six, it is argued that (1 A is the correct answer to Q if and only if (2 A correctly saturates (in a Fregean sense Q by verifying and validating it (in the computer science’s sense of “verification” and “validation”; that (2 is the case if and only if (3 [Q + A] generates an adequate model (m of the relevant system (s identified by Q; that (3 is the case if and only if (4 m is a proxy of s (in the computer science’s sense of “proxy” and (5 proximal access to m commutes with the distal access to s (in the category theory’s sense of “commutation”; and that (5 is the case if and only if (6 reading/writing (accessing, in the computer science’s technical sense of the term m enables one to read/write (access s. The last section draws a general conclusion about the nature of CTT as a theory for systems designers not just systems users.

Semantic Data Integration and Knowledge Management to Represent Biological Network Associations.

Science.gov (United States)

Losko, Sascha; Heumann, Klaus

2017-01-01

The vast quantities of information generated by academic and industrial research groups are reflected in a rapidly growing body of scientific literature and exponentially expanding resources of formalized data, including experimental data, originating from a multitude of "-omics" platforms, phenotype information, and clinical data. For bioinformatics, the challenge remains to structure this information so that scientists can identify relevant information, to integrate this information as specific "knowledge bases," and to formalize this knowledge across multiple scientific domains to facilitate hypothesis generation and validation. Here we report on progress made in building a generic knowledge management environment capable of representing and mining both explicit and implicit knowledge and, thus, generating new knowledge. Risk management in drug discovery and clinical research is used as a typical example to illustrate this approach. In this chapter we introduce techniques and concepts (such as ontologies, semantic objects, typed relationships, contexts, graphs, and information layers) that are used to represent complex biomedical networks. The BioXM™ Knowledge Management Environment is used as an example to demonstrate how a domain such as oncology is represented and how this representation is utilized for research.

Neural correlates of concreteness in semantic categorization.

Science.gov (United States)

Pexman, Penny M; Hargreaves, Ian S; Edwards, Jodi D; Henry, Luke C; Goodyear, Bradley G

2007-08-01

In some contexts, concrete words (CARROT) are recognized and remembered more readily than abstract words (TRUTH). This concreteness effect has historically been explained by two theories of semantic representation: dual-coding [Paivio, A. Dual coding theory: Retrospect and current status. Canadian Journal of Psychology, 45, 255-287, 1991] and context-availability [Schwanenflugel, P. J. Why are abstract concepts hard to understand? In P. J. Schwanenflugel (Ed.), The psychology of word meanings (pp. 223-250). Hillsdale, NJ: Erlbaum, 1991]. Past efforts to adjudicate between these theories using functional magnetic resonance imaging have produced mixed results. Using event-related functional magnetic resonance imaging, we reexamined this issue with a semantic categorization task that allowed for uniform semantic judgments of concrete and abstract words. The participants were 20 healthy adults. Functional analyses contrasted activation associated with concrete and abstract meanings of ambiguous and unambiguous words. Results showed that for both ambiguous and unambiguous words, abstract meanings were associated with more widespread cortical activation than concrete meanings in numerous regions associated with semantic processing, including temporal, parietal, and frontal cortices. These results are inconsistent with both dual-coding and context-availability theories, as these theories propose that the representations of abstract concepts are relatively impoverished. Our results suggest, instead, that semantic retrieval of abstract concepts involves a network of association areas. We argue that this finding is compatible with a theory of semantic representation such as Barsalou's [Barsalou, L. W. Perceptual symbol systems. Behavioral & Brain Sciences, 22, 577-660, 1999] perceptual symbol systems, whereby concrete and abstract concepts are represented by similar mechanisms but with differences in focal content.

Creating Value Propositions Through Configuration of Knowledge and Resources

DEFF Research Database (Denmark)

Heikka, Eija-Liisa; Frandsen, Thomas; Hsuan, Juliana

Service providers seek to manage different customer segments using different value propositions. In this paper we investigate how configuring knowledge and resources within organizations can facilitate the creation of value propositions for different customers. A qualitative multiple case study...... is organized around two projects allowing within-case and cross-case comparisons. Our findings indicate that, no matter how complex or simple a project is, there is a need for PR person(s) to take care of marketing and sales and to make appointments with the customers, who valued most the KIBS provider...

Creative thinking as orchestrated by semantic processing versus cognitive control brain networks

Directory of Open Access Journals (Sweden)

Anna eAbraham

2014-02-01

Full Text Available Creativity is primarily investigated within the neuroscientific perspective as a unitary construct. While such an approach is beneficial when trying to infer the general picture regarding creativity and brain function, it is insufficient if the objective is to uncover the information processing brain mechanisms by which creativity occurs. As creative thinking emerges through the dynamic interplay between several cognitive processes, assessing the neural correlates of these operations would enable the development and characterization of an information processing framework from which to better understand this complex ability. This article focuses on two aspects of creative cognition that are central to generating original ideas. Conceptual expansion refers to the ability to widen one’s conceptual structures to include unusual or novel associations, while overcoming knowledge constraints refers to our ability to override the constraining influence imposed by salient or pertinent knowledge when trying to be creative. Neuroimaging and neuropsychological evidence is presented to illustrate how semantic processing and cognitive control networks in the brain differentially modulate these critical facets of creative cognition.

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

Science.gov (United States)

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.

The semantic network, lexical access, and reading comprehension in monolingual and bilingual children : An individual differences study

NARCIS (Netherlands)

Spätgens, T.; Schoonen, R.

Using a semantic priming experiment, the influence of lexical access and knowledge of semantic relations on reading comprehension was studied in Dutch monolingual and bilingual minority children. Both context-independent semantic relations in the form of category coordinates and context-dependent

Integrated use of spatial and semantic relationships for extracting road networks from floating car data

Science.gov (United States)

Li, Jun; Qin, Qiming; Xie, Chao; Zhao, Yue

2012-10-01

The update frequency of digital road maps influences the quality of road-dependent services. However, digital road maps surveyed by probe vehicles or extracted from remotely sensed images still have a long updating circle and their cost remain high. With GPS technology and wireless communication technology maturing and their cost decreasing, floating car technology has been used in traffic monitoring and management, and the dynamic positioning data from floating cars become a new data source for updating road maps. In this paper, we aim to update digital road maps using the floating car data from China's National Commercial Vehicle Monitoring Platform, and present an incremental road network extraction method suitable for the platform's GPS data whose sampling frequency is low and which cover a large area. Based on both spatial and semantic relationships between a trajectory point and its associated road segment, the method classifies each trajectory point, and then merges every trajectory point into the candidate road network through the adding or modifying process according to its type. The road network is gradually updated until all trajectories have been processed. Finally, this method is applied in the updating process of major roads in North China and the experimental results reveal that it can accurately derive geometric information of roads under various scenes. This paper provides a highly-efficient, low-cost approach to update digital road maps.

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

Science.gov (United States)

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

2015-12-01

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

Functional neuroimaging of semantic and episodic musical memory.

Science.gov (United States)

Platel, Hervé

2005-12-01

The distinction between episodic and semantic memory has become very popular since it was first proposed by Tulving in 1972. So far, very few neuropsychological, psychophysical, and imaging studies have related to the mnemonic aspects of music, notably on the long-term memory features, and practically nothing is known about the functional anatomy of long-term memory for music. Numerous functional imaging studies have shown that retrieval from semantic and episodic memory is subserved by distinct neural networks. For instance, the HERA model (hemispheric encoding/retrieval asymmetry) ascribes to the left prefrontal cortex a preferential role in the encoding process of episodic material and the recall of semantic information, while the right prefrontal cortex would preferentially operate in the recall of episodic information. However, these results were essentially obtained with verbal and visuo-spatial material. We have done a study to determine the neural substrates underlying the semantic and episodic components of music using familiar and nonfamiliar melodic tunes. Two distinct patterns of activations were found: bilateral activation of the middle and superior frontal areas and precuneus for episodic memory, and activation of the medial and orbital frontal cortex bilaterally, left angular gyrus, and the anterior part of the left middle and superior temporal gyri for semantic memory. We discuss these findings in light of the available neuropsychological data obtained in brain-damaged subjects and functional neuroimaging studies.

Law proposition aiming to organize the sustainable management of radioactive wastes; Proposition de loi tendant a organiser la gestion durable des dechets radioactifs

Energy Technology Data Exchange (ETDEWEB)

Bataille, Ch.; Ayrault, J.M.; Hollande, F.; Dose, F.; Dumont, J.L.; Brottes, F.; Le Deaut, J.Y

2006-02-15

In 1991 the France decided to intensify its researches in the high activity radioactive wastes management domain. The law of the 30 December 1991 relative to the radioactive wastes management, decided that a period of 15 years would be devoted to the research of very long dated solutions. This law proposition takes into account these researches results and aims to define a policy of radioactive wastes management in the framework of a sustainable development. The authors present and discuss the different articles of the law proposition. (A.L.B.)

Combining wireless sensor networks and semantic middleware for an Internet of Things-based sportsman/woman monitoring application.

Science.gov (United States)

Rodríguez-Molina, Jesús; Martínez, José-Fernán; Castillejo, Pedro; López, Lourdes

2013-01-31

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application

Science.gov (United States)

Rodríguez-Molina, Jesús; Martínez, José-Fernán; Castillejo, Pedro; López, Lourdes

2013-01-01

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained. PMID:23385405

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application

Directory of Open Access Journals (Sweden)

Lourdes López

2013-01-01

Full Text Available Wireless Sensor Networks (WSNs are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.

Compiling Relational Bayesian Networks for Exact Inference

DEFF Research Database (Denmark)

Jaeger, Manfred; Chavira, Mark; Darwiche, Adnan

2004-01-01

We describe a system for exact inference with relational Bayesian networks as defined in the publicly available \\primula\\ tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference by evaluating...

Generative Semantics.

Science.gov (United States)

King, Margaret

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

Pengembangan Value Proposition Dalam Penetapan Strategi Pemasaran (Studi Kasus Terhadap Mobil Toyota Agya Di Kota Malang)

OpenAIRE

Andaru, Rizka Kurnia

2015-01-01

This research aims to knowing value proposition that is offered on Toyota Agya, knowing consumer perceptions about value proposition of toyota agya in Malang City, and knowing the development of value proposition in determining the marketing strategy at Toyota Agya in Malang City. The data source of research were informant, documents, places and events. Analysis of the data used interactive data analysis. The results showed that 11 elements of Value proposition according to Alexander Osterwal...

Semantic Web, Reusable Learning Objects, Personal Learning Networks in Health: Key Pieces for Digital Health Literacy.

Science.gov (United States)

Konstantinidis, Stathis Th; Wharrad, Heather; Windle, Richard; Bamidis, Panagiotis D

2017-01-01

The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients "new habits" of learning through their own Personal Learning Networks. In this paper we propose a framework for empowering patients' digital health literacy adjusted to patients' currents needs by utilizing the contemporary way of learning through Personal Learning Networks, existing high quality learning resources and semantics technologies for interconnecting knowledge pieces. The framework based on the concept of knowledge maps for health as defined in this paper. Health Digital Literacy needs definitely further enhancement and the use of the proposed concept might lead to useful tools which enable use of understandable health trusted resources tailored to each person needs.

Anatomy of a value proposition for laboratory medicine.

Science.gov (United States)

Price, Christopher P; St John, Andrew

2014-09-25

Value is now becoming a key driver in the ongoing development of healthcare delivery; key facets include the identification of what is valuable and how that value can be identified, leveraged, and delivered. The concept of a value proposition is widely used in business but can be used in healthcare as a statement of the benefits, costs and value that an organization can deliver to its customers. The foundation of this statement in laboratory medicine is evidence of clinical and cost effectiveness, not only for the patient, but also for other stakeholders involved in the delivery of healthcare, e.g., the carer, service provider, commissioner, purchaser, and the supplier of the test or device, as well as society as a whole. However the value of any laboratory medicine investigation is only achieved if the output (the test result(s)), is acted upon by the initiator of the investigation. Laboratory medicine is one part of a complex intervention, and so the value proposition should encompass the breadth of that intervention - from addressing the unmet need through the generation of clinical, operational and economic outcomes. A value proposition in laboratory medicine is central to successful innovation and quality improvement in healthcare. Copyright © 2014 Elsevier B.V. All rights reserved.

Compiling Relational Bayesian Networks for Exact Inference

DEFF Research Database (Denmark)

Jaeger, Manfred; Darwiche, Adnan; Chavira, Mark

2006-01-01

We describe in this paper a system for exact inference with relational Bayesian networks as defined in the publicly available PRIMULA tool. The system is based on compiling propositional instances of relational Bayesian networks into arithmetic circuits and then performing online inference...

Propositional Optimal Trajectory Programming for Improving Stability ...

African Journals Online (AJOL)

Propositional Optimal Trajectory Programming for Improving Stability of Hermite Definite Control System. ... PROMOTING ACCESS TO AFRICAN RESEARCH. AFRICAN JOURNALS ONLINE (AJOL) ... Knowledge of systems operation subjected to heat diffusion constraints is required of systems analysts. In an instance that ...

Semantic Web based Self-management for a Pervasive Service Middleware

DEFF Research Database (Denmark)

Zhang, Weishan; Hansen, Klaus Marius

2008-01-01

Self-management is one of the challenges for realizing ambient intelligence in pervasive computing. In this paper,we propose and present a semantic Web based self-management approach for a pervasive service middleware where dynamic context information is encoded in a set of self-management context...... ontologies. The proposed approach is justified from the characteristics of pervasive computing and the open world assumption and reasoning potentials of semantic Web and its rule language. To enable real-time self-management, application level and network level state reporting is employed in our approach....... State changes are triggering execution of self-management rules for adaption, monitoring, diagnosis, and so on. Evaluations of self-diagnosis in terms of extensibility, performance,and scalability show that the semantic Web based self-management approach is effective to achieve the self-diagnosis goals...

A COMPARISON OF SEMANTIC SIMILARITY MODELS IN EVALUATING CONCEPT SIMILARITY

Directory of Open Access Journals (Sweden)

Q. X. Xu

2012-08-01

Full Text Available The semantic similarities are important in concept definition, recognition, categorization, interpretation, and integration. Many semantic similarity models have been established to evaluate semantic similarities of objects or/and concepts. To find out the suitability and performance of different models in evaluating concept similarities, we make a comparison of four main types of models in this paper: the geometric model, the feature model, the network model, and the transformational model. Fundamental principles and main characteristics of these models are introduced and compared firstly. Land use and land cover concepts of NLCD92 are employed as examples in the case study. The results demonstrate that correlations between these models are very high for a possible reason that all these models are designed to simulate the similarity judgement of human mind.

Value propositions of mHealth projects.

Science.gov (United States)

Gorski, Irena; Bram, Joshua T; Sutermaster, Staci; Eckman, Molly; Mehta, Khanjan

While mHealth holds great potential for addressing global health disparities, a majority of the initiatives never proceed beyond the pilot stage. One fundamental concern is that mHealth projects are seldom designed from the customer's perspective to address their specific problems and/or create appreciable value. A customer-centric view, where direct tangible benefits of interventions are identified and communicated effectively, can drive customer engagement and advance projects toward self-sustaining business models. This article reviews the business models of 234 mHealth projects to identify nine distinct value propositions that solve specific problems for customers. Each of these value propositions is discussed with real-world examples, analyses of their design approaches and business strategies, and common enablers as well as hurdles to surviving past the pilot stage. Furthermore, a deeper analysis of 42 mHealth ventures that have achieved self-sustainability through project revenue provides a host of practical and poignant insights into the design of systems that can fulfil mHealth's promise to address healthcare challenges in the long term.

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

Science.gov (United States)

Doehrmann, Oliver; Naumer, Marcus J

2008-11-25

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

Dissociating Parieto-Frontal Networks for Phonological and Semantic Word Decisions

DEFF Research Database (Denmark)

Hartwigsen, Gesa; Weigel, Anni; Schuschan, Paul

2016-01-01

Left posterior inferior frontal gyrus (pIFG) and supramarginal gyrus (SMG) are key regions for phonological decisions, whereas angular gyrus (ANG) and anterior IFG (aIFG) are associated with semantics. However, it is less clear whether the functional contribution of one area changes in the presen...

The neural basis for simulated drawing and the semantic implications.

Science.gov (United States)

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

2009-03-01

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

On the structure of quantal proposition systems

Science.gov (United States)

Bub, Jeffrey

1994-09-01

I define sublaltices of quantum propositions that can be taken as having determinate (but perhaps unknown) truth values for a given quantum state, in the sense that sufficiently many two-valued maps satisfying a Boolean homomorphism condition exist on each determinate sublattice to generate a Kolmogorov probability space for the probabilities defined by the slate. I show that these sublattices are maximal, subject to certain constraints, from which it follows easily that they are unique. I discuss the relevance of this result for the measurement problem, relating it to an early proposal by Jauch and Piron for defining a new notion of state for quantum systems, to a recent uniqueness proof by Clifton for the sublattice of propositions specified as determinate by modal interpretations of quantum mechanics that exploit the polar decompostion theorem, and to my own previous suggestions for interpreting quantum mechanics without the projection postulate.

Semantic Desktop

Science.gov (United States)

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

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

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

OpenAIRE

Krause, Jürgen

2008-01-01

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

An examination of a reciprocal relationship between network governance and network structure

DEFF Research Database (Denmark)

Bergenholtz, Carsten; Goduscheit, René Chester

The present article examines the network structure and governance of inter-organisational innovation networks. Network governance refers to the issue of how to manage and coordinate the relational activities and processes in the network while research on network structure deals with the overall...... structural relations between the actors in the network. These streams of research do contain references to each other but mostly rely on a static conception of the relationship between network structure and the applied network governance. The paper is based on a primarily qualitative case study of a loosely...... coupled Danish inter-organisational innovation network. The proposition is that a reciprocal relation between network governance and network structure can be identified....

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

Science.gov (United States)

Ježek, Petr; Mouček, Roman

2015-01-01

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

Semantic mechanisms may be responsible for developing synesthesia

Directory of Open Access Journals (Sweden)

Aleksandra eMroczko-Wąsowicz

2014-08-01

Full Text Available Currently, little is known about how synesthesia develops and which aspects of synesthesia can be acquired through a learning process. We review the increasing evidence for the role of semantic representations in the induction of synesthesia, and argue for the thesis that synesthetic abilities are developed and modified by semantic mechanisms. That is, in certain people semantic mechanisms associate concepts with perception-like experiences—and this association occurs in an extraordinary way. This phenomenon can be referred to as higher synesthesia or ideasthesia. The present analysis suggests that synesthesia develops during childhood and is being enriched further throughout the synesthetes’ lifetime; for example, the already existing concurrents may be adopted by novel inducers or new concurrents may be formed. For a deeper understanding of the origin and nature of synesthesia we propose to focus future research on two aspects: i the similarities between synesthesia and ordinary phenomenal experiences based on concepts, and ii the tight entanglement of perception, cognition and the conceptualization of the world. Most importantly, an explanation of how biological systems get to generate experiences, synesthetic or not, may have to involve an explanation of how we form semantic networks in general and what their role is in our ability to be aware of the surrounding world.

Semantic Web Improved with the Weighted IDF Feature

OpenAIRE

Mrs. Jyoti Gautam; Dr. Ela Kumar

2015-01-01

The development of search engines is taking at a very fast rate. A lot of algorithms have been tried and tested. But, still the people are not getting precise results. Social networking sites are developing at tremendous rate and their growth has given birth to the new interesting problems. The social networking sites use semantic data to enhance the results. This provides us with a new perspective on how to improve the quality of information retrieval. As we are aware, many techniques of tex...

Quality Assurance of UMLS Semantic Type Assignments Using SNOMED CT Hierarchies.

Science.gov (United States)

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.

Richness of information about novel words influences how episodic and semantic memory networks interact during lexicalization.

Science.gov (United States)

Takashima, Atsuko; Bakker, Iske; van Hell, Janet G; Janzen, Gabriele; McQueen, James M

2014-01-01

The complementary learning systems account of declarative memory suggests two distinct memory networks, a fast-mapping, episodic system involving the hippocampus, and a slower semantic memory system distributed across the neocortex in which new information is gradually integrated with existing representations. In this study, we investigated the extent to which these two networks are involved in the integration of novel words into the lexicon after extensive learning, and how the involvement of these networks changes after 24h. In particular, we explored whether having richer information at encoding influences the lexicalization trajectory. We trained participants with two sets of novel words, one where exposure was only to the words' phonological forms (the form-only condition), and one where pictures of unfamiliar objects were associated with the words' phonological forms (the picture-associated condition). A behavioral measure of lexical competition (indexing lexicalization) indicated stronger competition effects for the form-only words. Imaging (fMRI) results revealed greater involvement of phonological lexical processing areas immediately after training in the form-only condition, suggesting that tight connections were formed between novel words and existing lexical entries already at encoding. Retrieval of picture-associated novel words involved the episodic/hippocampal memory system more extensively. Although lexicalization was weaker in the picture-associated condition, overall memory strength was greater when tested after a 24hour delay, probably due to the availability of both episodic and lexical memory networks to aid retrieval. It appears that, during lexicalization of a novel word, the relative involvement of different memory networks differs according to the richness of the information about that word available at encoding. © 2013.

Proposition 13 and the Future of California's Schools

Science.gov (United States)

Guthrie, James W.

1978-01-01

Describes the California legislature's education-related response to Proposition 13 and analyzes the likely long-range effects of that response--including its effect on revenue stability, expenditure equality, and school governance. (Author/IRT)

"Place" as an integrating concept in natural resource politics: propositions for a social science research agenda.

Science.gov (United States)

Antony S. Cheng; Linda E. Kruger; Steven E. Daniels

2003-01-01

This article lays out six propositions centering on a relationship between peopleplace connections and strategic behavior in natural resource politics. The first two propositions suggest a strong and direct connection between self-identity, place, and how individuals perceive and value the environment. The third, fourth, and fifth propositions tie together social group...

Fuzzy Emotional Semantic Analysis and Automated Annotation of Scene Images

Directory of Open Access Journals (Sweden)

Jianfang Cao

2015-01-01

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

MARVIN: Distributed reasoning over large-scale Semantic Web data

NARCIS (Netherlands)

Oren, E.; Kotoulas, S.; Anadiotis, G.; Siebes, R.M.; ten Teije, A.C.M.; van Harmelen, F.A.H.

2009-01-01

Many Semantic Web problems are difficult to solve through common divide-and-conquer strategies, since they are hard to partition. We present Marvin, a parallel and distributed platform for processing large amounts of RDF data, on a network of loosely coupled peers. We present our divide-conquer-swap

Programming the semantic web

CERN Document Server

Segaran, Toby; Taylor, Jamie

2009-01-01

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

New energy technologies. Research program proposition

International Nuclear Information System (INIS)

2005-02-01

This document presents the most promising program propositions of research and development and the public financing needed for their realization. The concerned technologies are: the hydrogen and the fuel cell PAN-H, the separation and the storage of the CO 2 , the photovoltaic solar electricity, the PREBAT program of the building energy recovery and the bio-energies. (A.L.B.)

Semantic metrics

OpenAIRE

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

2006-01-01

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

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

Science.gov (United States)

Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael

2012-01-25

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

On the Predictability of Classical Propositional Logic

Directory of Open Access Journals (Sweden)

Poliana M. Reis

2013-01-01

Full Text Available In this work we provide a statistical form of empirical analysis of classical propositional logic decision methods called SAT solvers. This work is perceived as an empirical counterpart of a theoretical movement, called the enduring scandal of deduction, that opposes considering Boolean Logic as trivial in any sense. For that, we study the predictability of classical logic, which we take to be the distribution of the runtime of its decision process. We present a series of experiments that determines the run distribution of SAT solvers and discover a varying landscape of distributions, following the known existence of a transition of easy-hard-easy cases of propositional formulas. We find clear distributions for the easy areas and the transitions easy-hard and hard-easy. The hard cases are shown to be hard also for the detection of statistical distributions, indicating that several independent processes may be at play in those cases.

Publishing high-quality climate data on the semantic web

Science.gov (United States)

Woolf, Andrew; Haller, Armin; Lefort, Laurent; Taylor, Kerry

2013-04-01

temperature dataset, Australian Climate Observations Reference Network - Surface Air Temperature (ACORN-SAT) [BoM, 2012b]. This dataset contains daily homogenised surface temperature observations for 112 locations around Australia, dating back to 1910. An ontology for the dataset was developed [Lefort et. al., 2012], based on the existing Semantic Sensor Network ontology [Compton et. al., 2012] and the W3C RDF Data Cube vocabulary [W3C, 2012]. Additional vocabularies were developed, e.g. for BoM weather stations and rainfall districts. The dataset was converted to RDF and loaded into an RDF triplestore. The Linked-Data API (http://code.google.com/p/linked-data-api) was used to configure specific URI query patterns (e.g. for observation timeseries slices by station), and a SPARQL endpoint was provided for direct querying. In addition, some demonstration 'mash-ups' were developed, providing an interactive browser-based interface to the temperature timeseries. References [Berners-Lee et. al., 2001] Tim Berners-Lee, James Hendler and Ora Lassila (2001), "The Semantic Web", Scientific American, May 2001. [Berners-Lee, 2006] Tim Berners-Lee (2006), "Linked Data - Design Issues", W3C [http://www.w3.org/DesignIssues/LinkedData.html] [BoM, 2012a] Bureau of Meteorology (2012), "Environmental information" [http://www.bom.gov.au/environment/] [BoM, 2012b] Bureau of Meteorology (2012), "Australian Climate Observations Reference Network - Surface Air Temperature" [http://www.bom.gov.au/climate/change/acorn-sat/] [Compton et. al., 2012] Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit Sheth, Kerry Taylor (2012), "The SSN Ontology of the W3C Semantic Sensor Network Incubator Group", J. Web Semantics, 17 (2012) [http

The importance of distinguishing information from evidence/observations when formulating propositions.

Science.gov (United States)

Hicks, T; Biedermann, A; de Koeijer, J A; Taroni, F; Champod, C; Evett, I W

2015-12-01

The value of forensic results crucially depends on the propositions and the information under which they are evaluated. For example, if a full single DNA profile for a contemporary marker system matching the profile of Mr A is assessed, given the propositions that the DNA came from Mr A and given it came from an unknown person, the strength of evidence can be overwhelming (e.g., in the order of a billion). In contrast, if we assess the same result given that the DNA came from Mr A and given it came from his twin brother (i.e., a person with the same DNA profile), the strength of evidence will be 1, and therefore neutral, unhelpful and irrelevant(1) to the case at hand. While this understanding is probably uncontroversial and obvious to most, if not all practitioners dealing with DNA evidence, the practical precept of not specifying an alternative source with the same characteristics as the one considered under the first proposition may be much less clear in other circumstances. During discussions with colleagues and trainees, cases have come to our attention where forensic scientists have difficulty with the formulation of propositions. It is particularly common to observe that results (e.g., observations) are included in the propositions, whereas-as argued throughout this note-they should not be. A typical example could be a case where a shoe-mark with a logo and the general pattern characteristics of a Nike Air Jordan shoe is found at the scene of a crime. A Nike Air Jordan shoe is then seized at Mr A's house and control prints of this shoe compared to the mark. The results (e.g., a trace with this general pattern and acquired characteristics corresponding to the sole of Mr A's shoe) are then evaluated given the propositions 'The mark was left by Mr A's Nike Air Jordan shoe-sole' and 'The mark was left by an unknown Nike Air Jordan shoe'. As a consequence, the footwear examiner will not evaluate part of the observations (i.e., the mark presents the general

Inquisitive semantics and pragmatics

NARCIS (Netherlands)

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

2009-01-01

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

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

Science.gov (United States)

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

2012-11-01

Declarative memory is usually described as consisting of two systems: semantic and episodic memory. Between these two poles, however, may lie a third entity: personal semantics (PS). PS concerns knowledge of one's past. Although typically assumed to be an aspect of semantic memory, it is essentially absent from existing models of knowledge. Furthermore, like episodic memory (EM), PS is idiosyncratically personal (i.e., not culturally-shared). We show that, depending on how it is operationalized, the neural correlates of PS can look more similar to semantic memory, more similar to EM, or dissimilar to both. We consider three different perspectives to better integrate PS into existing models of declarative memory and suggest experimental strategies for disentangling PS from semantic and episodic memory. Copyright © 2012 Elsevier Ltd. All rights reserved.

Semantic Location Extraction from Crowdsourced Data

Science.gov (United States)

Koswatte, S.; Mcdougall, K.; Liu, X.

2016-06-01

Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

SEMANTIC LOCATION EXTRACTION FROM CROWDSOURCED DATA

Directory of Open Access Journals (Sweden)

S. Koswatte

2016-06-01

Full Text Available Crowdsourced Data (CSD has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network. This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction.

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

Science.gov (United States)

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

2009-09-23

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

Plug-in hybrid electric vehicle value proposition study. Phase 1, task 2, select value proposition/business model for further study

Science.gov (United States)

2008-04-01

The objective of Task 2 is to identify the combination of value propositions that is : believed to be achievable by 2030 and collectively hold promise for a sustainable : PHEV market by 2030. This deliverable outlines what the project team (with inpu...

Distributed coordination of heterogeneous agents using a semantic overlay network and a goal-directed graphplan planner.

Directory of Open Access Journals (Sweden)

António Luís Lopes

Full Text Available In this paper, we describe a distributed coordination system that allows agents to seamlessly cooperate in problem solving by partially contributing to a problem solution and delegating the subproblems for which they do not have the required skills or knowledge to appropriate agents. The coordination mechanism relies on a dynamically built semantic overlay network that allows the agents to efficiently locate, even in very large unstructured networks, the necessary skills for a specific problem. Each agent performs partial contributions to the problem solution using a new distributed goal-directed version of the Graphplan algorithm. This new goal-directed version of the original Graphplan algorithm provides an efficient solution to the problem of "distraction", which most forward-chaining algorithms suffer from. We also discuss a set of heuristics to be used in the backward-search process of the planning algorithm in order to distribute this process amongst idle agents in an attempt to find a solution in less time. The evaluation results show that our approach is effective in building a scalable and efficient agent society capable of solving complex distributable problems.

New energy technologies. Research program proposition; Nouvelles technologies de l'energie. Proposition de programme de recherche

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-02-01

This document presents the most promising program propositions of research and development and the public financing needed for their realization. The concerned technologies are: the hydrogen and the fuel cell PAN-H, the separation and the storage of the CO{sub 2}, the photovoltaic solar electricity, the PREBAT program of the building energy recovery and the bio-energies. (A.L.B.)

Towards an 'inland terminal centred' value proposition

NARCIS (Netherlands)

Van den Berg, R.; de Langen, P.W.

2015-01-01

The two main value propositions in international container transport are ‘port-to-port’ services and ‘door-to-door’ services. In port-to-port services, buyers ‘just’ purchase maritime transport from a shipping line. Door-to-door services comprise the total transport chain and include land-based

SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

Science.gov (United States)

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

2004-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Semantic Fields to Improve Business: the hotels case

Directory of Open Access Journals (Sweden)

Joan-Francesc Fondevila-Gascón

2016-12-01

Full Text Available The decision-making from a tourist depends on the social media experience. For tourists, the importance of qualitative sources (for example, comments in forums of websites, blogs and social networks: Internet technologies is increasing for tourist enterprises. A representative percentage of tourists choose destinations thanks to the opinions of other users. In this article, we use the methodology of sentiment analysis and opinion mining to capture keywords and linking messages with a singular semantic field to find the principal concepts of online comments collected in Booking and TripAdvisor opinion platforms for tourists staying in hotels. We conclude that hotels find in the semantic fields a tool for observing internal strengths and weaknesses and external opportunities and threats.

Historical Fiction and the Allegorical Truth of Colonial Violence in The Proposition

Directory of Open Access Journals (Sweden)

Felicity Collins

2011-04-01

Full Text Available Firing another shot in the history wars, Prime Minister Howard used his 2006 Australia Day speech to berate postmodern approaches to historical truth. At the same time, a UK-Australia co-production, The Proposition (John Hillcoat, 2005 was enjoying critical acclaim as both a violent revisionist Western and an important film about Australia’s frontier history. It would be tempting to include this frontier film in the cycle of ‘post Mabo’ films exemplified by The Tracker (Rolf de Heer, 2002. Yet unlike The Tracker, The Proposition eschews historical reference in favour of baroque allegory. If The Tracker’s moral fable is clearly a left-liberal intervention in the history wars, The Proposition seems to offer no illumination of the present, only the unredeemed violence of retribution as the irrefutable truth of the frontier, aligning it with the 1976 mini-series, Luke’s Kingdom. This article asks in what sense history persists in the allegorical truth of frontier films which cannot be subsumed into historical representation. I argue that The Proposition offers a philosophical view of history as mediated time, rather than a political view of history as traumatic event. I contrast the popular reception of The Proposition as a revisionist, bushranger Western ‘about’ Australian history, with Routt’s counter-claim that The Proposition is an art film ‘about’ violence, revealing Australia as ‘a primal scene of annihilation.’ However, in order not to reinstate the myth of a fatal landscape as the template of Australian identity, I turn to Benjamin’s critique of Baroque allegory as a retrospective mode in which the transience of time finds expression in decay, ruin and debris. The question to be resolved is whether, by giving us multiple horizons of historical time, the revisionist film avoids being drawn into allegory’s melancholy alliance with myth, opening instead into a cinematic revelation of history’s unrealised potential.

Molecular codes in biological and chemical reaction networks.

Directory of Open Access Journals (Sweden)

Dennis Görlich

Full Text Available Shannon's theory of communication has been very successfully applied for the analysis of biological information. However, the theory neglects semantic and pragmatic aspects and thus cannot directly be applied to distinguish between (bio- chemical systems able to process "meaningful" information from those that do not. Here, we present a formal method to assess a system's semantic capacity by analyzing a reaction network's capability to implement molecular codes. We analyzed models of chemical systems (martian atmosphere chemistry and various combustion chemistries, biochemical systems (gene expression, gene translation, and phosphorylation signaling cascades, an artificial chemistry, and random reaction networks. Our study suggests that different chemical systems possess different semantic capacities. No semantic capacity was found in the model of the martian atmosphere chemistry, the studied combustion chemistries, and highly connected random networks, i.e. with these chemistries molecular codes cannot be implemented. High semantic capacity was found in the studied biochemical systems and in random reaction networks where the number of second order reactions is twice the number of species. We conclude that our approach can be applied to evaluate the information processing capabilities of a chemical system and may thus be a useful tool to understand the origin and evolution of meaningful information, e.g. in the context of the origin of life.

Value Creation in Knowledge Networks

DEFF Research Database (Denmark)

Hansen, Magnus Rotvit Perlt; Pries-Heje, Jan

2017-01-01

Knowledge networks enable businesses to enhance their levels of innovation and market competitiveness. In this paper, we propose five principles for designing IT tools that can support the facilitation and improvement of knowledge networks. We also introduce a new value proposition that constitutes...... a nascent design theory in the domain of knowledge network improvement. The design principles are derived from an iterative process applied in three different case settings. In each case, we apply and evaluate the network nexus tool to determine whether the knowledge network provides value to its...

Complexity of Propositional Proofs Under a Promise

Czech Academy of Sciences Publication Activity Database

Dershowitz, N.; Tzameret, Iddo

2010-01-01

Roč. 11, č. 3 (2010), s. 1-29 ISSN 1529-3785 Institutional research plan: CEZ:AV0Z10190503 Keywords : theory * promise problems * propositional proof complexity * random 3CNF * resolution Subject RIV: BA - General Mathematics Impact factor: 1.391, year: 2010 http://dl.acm.org/ citation .cfm?doid=1740582.1740586

Complexity of Propositional Proofs Under a Promise

Czech Academy of Sciences Publication Activity Database

Dershowitz, N.; Tzameret, Iddo

2010-01-01

Roč. 11, č. 3 (2010), s. 1-29 ISSN 1529-3785 Institutional research plan: CEZ:AV0Z10190503 Keywords : theory * promise problems * propositional proof complexity * random 3CNF * resolution Subject RIV: BA - General Mathematics Impact factor: 1.391, year: 2010 http://dl.acm.org/citation.cfm?doid=1740582.1740586

Towards a global quantum network

Science.gov (United States)

Simon, Christoph

2017-11-01

The creation of a global quantum network is now a realistic proposition thanks to developments in satellite and fibre links and quantum memory. Applications will range from secure communication and fundamental physics experiments to a future quantum internet.

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

Science.gov (United States)

Wiese, Holger; Schweinberger, Stefan R

2015-01-01

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

Didactic Networks: A Proposal for e-learning Content Generation

Directory of Open Access Journals (Sweden)

F. Javier Del Alamo

2010-12-01

Full Text Available The Didactic Networks proposed in this paper are based on previous publications in the field of the RSR (Rhetorical-Semantic Relations. The RSR is a set of primitive relations used for building a specific kind of semantic networks for artificial intelligence applications on the web: the RSN (Rhetorical-Semantic Networks. We bring into focus the RSR application in the field of elearning, by defining Didactic Networks as a new set of semantic patterns oriented to the development of elearning applications. The different lines we offer in our research fall mainly into three levels: (1 The most basic one is in the field of computational linguistics and related to Logical Operations on RSR (RSR Inverses and plurals, RSR combinations, etc, once they have been created. The application of Walter Bosma's results regarding rhetorical distance application and treatment as semantic weighted networks is one of the important issues here. (2 In parallel, we have been working on the creation of a knowledge representation and storage model and data architecture capable of supporting the definition of knowledge networks based on RSR. (3 The third strategic line is in the meso-level, the formulation of a molecular structure of knowledge based on the most frequently used patterns. The main contribution at this level is the set of Fundamental Cognitive Networks (FCN as an application of Novak's mental maps proposal. This paper is part of this third intermediate level, and the Fundamental Didactic Networks (FDN are the result of the application of rhetorical theory procedures to the instructional theory. We have formulated a general set of RSR capable of building discourse, making it possible to express any concept, procedure or principle in terms of knowledge nodes and RSRs. The Instructional knowledge can then be elaborated in the same way. This network structure expressing the instructional knowledge in terms of RSR makes the objective of developing web

Semantically Interoperable XML Data.

Science.gov (United States)

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

2013-09-01

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

Semantically Interoperable XML Data

Science.gov (United States)

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

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Анна Александровна Смирнитская

2016-12-01

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

Speaker information affects false recognition of unstudied lexical-semantic associates.

Science.gov (United States)

Luthra, Sahil; Fox, Neal P; Blumstein, Sheila E

2018-05-01

Recognition of and memory for a spoken word can be facilitated by a prior presentation of that word spoken by the same talker. However, it is less clear whether this speaker congruency advantage generalizes to facilitate recognition of unheard related words. The present investigation employed a false memory paradigm to examine whether information about a speaker's identity in items heard by listeners could influence the recognition of novel items (critical intruders) phonologically or semantically related to the studied items. In Experiment 1, false recognition of semantically associated critical intruders was sensitive to speaker information, though only when subjects attended to talker identity during encoding. Results from Experiment 2 also provide some evidence that talker information affects the false recognition of critical intruders. Taken together, the present findings indicate that indexical information is able to contact the lexical-semantic network to affect the processing of unheard words.

Semantic Role Labeling

CERN Document Server

Palmer, Martha; Xue, Nianwen

2011-01-01

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

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

Science.gov (United States)

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

2007-01-01

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

UML 2 Semantics and Applications

CERN Document Server

Lano, Kevin

2009-01-01

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

Jauch-Piron orthomodular posets and propositional systems: A comparison

Science.gov (United States)

Piron, C.

1993-10-01

We compare the structures obtained via orthomodular posets and via propositional systems, discussing some examples of the links between them. Despite some analogies, the two structures are fundamentally different.

Semantic eScience for Ecosystem Understanding and Monitoring: The Jefferson Project Case Study

Science.gov (United States)

McGuinness, D. L.; Pinheiro da Silva, P.; Patton, E. W.; Chastain, K.

2014-12-01

Monitoring and understanding ecosystems such as lakes and their watersheds is becoming increasingly important. Accelerated eutrophication threatens our drinking water sources. Many believe that the use of nutrients (e.g., road salts, fertilizers, etc.) near these sources may have negative impacts on animal and plant populations and water quality although it is unclear how to best balance broad community needs. The Jefferson Project is a joint effort between RPI, IBM and the Fund for Lake George aimed at creating an instrumented water ecosystem along with an appropriate cyberinfrastructure that can serve as a global model for ecosystem monitoring, exploration, understanding, and prediction. One goal is to help communities understand the potential impacts of actions such as road salting strategies so that they can make appropriate informed recommendations that serve broad community needs. Our semantic eScience team is creating a semantic infrastructure to support data integration and analysis to help trained scientists as well as the general public to better understand the lake today, and explore potential future scenarios. We are leveraging our RPI Tetherless World Semantic Web methodology that provides an agile process for describing use cases, identification of appropriate background ontologies and technologies, implementation, and evaluation. IBM is providing a state-of-the-art sensor network infrastructure along with a collection of tools to share, maintain, analyze and visualize the network data. In the context of this sensor infrastructure, we will discuss our semantic approach's contributions in three knowledge representation and reasoning areas: (a) human interventions on the deployment and maintenance of local sensor networks including the scientific knowledge to decide how and where sensors are deployed; (b) integration, interpretation and management of data coming from external sources used to complement the project's models; and (c) knowledge about

Prediction signatures in the brain: Semantic pre-activation during language comprehension

Directory of Open Access Journals (Sweden)

Burkhard Maess

2016-11-01

Full Text Available There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: Highly predictive (that is more informative verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns.

Semantic memory in object use.

Science.gov (United States)

Silveri, Maria Caterina; Ciccarelli, Nicoletta

2009-10-01

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

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

Directory of Open Access Journals (Sweden)

Zhenyu Wu

2017-02-01

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

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

Science.gov (United States)

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

2017-02-20

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

Geospatial Semantics and the Semantic Web

CERN Document Server

Ashish, Naveen

2011-01-01

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

Towards a neural basis of processing musical semantics

Science.gov (United States)

Koelsch, Stefan

2011-06-01

Processing of meaning is critical for language perception, and therefore the majority of research on meaning processing has focused on the semantic, lexical, conceptual, and propositional processing of language. However, music is another a means of communication, and meaning also emerges from the interpretation of musical information. This article provides a framework for the investigation of the processing of musical meaning, and reviews neuroscience studies investigating this issue. These studies reveal two neural correlates of meaning processing, the N400 and the N5 (which are both components of the event-related electric brain potential). Here I argue that the N400 can be elicited by musical stimuli due to the processing of extra-musical meaning, whereas the N5 can be elicited due to the processing of intra-musical meaning. Notably, whereas the N400 can be elicited by both linguistic and musical stimuli, the N5 has so far only been observed for the processing of meaning in music. Thus, knowledge about both the N400 and the N5 can advance our understanding of how the human brain processes meaning information.

DOORS to the semantic web and grid with a PORTAL for biomedical computing.

Science.gov (United States)

Taswell, Carl

2008-03-01

The semantic web remains in the early stages of development. It has not yet achieved the goals envisioned by its founders as a pervasive web of distributed knowledge and intelligence. Success will be attained when a dynamic synergism can be created between people and a sufficient number of infrastructure systems and tools for the semantic web in analogy with those for the original web. The domain name system (DNS), web browsers, and the benefits of publishing web pages motivated many people to register domain names and publish web sites on the original web. An analogous resource label system, semantic search applications, and the benefits of collaborative semantic networks will motivate people to register resource labels and publish resource descriptions on the semantic web. The Domain Ontology Oriented Resource System (DOORS) and Problem Oriented Registry of Tags and Labels (PORTAL) are proposed as infrastructure systems for resource metadata within a paradigm that can serve as a bridge between the original web and the semantic web. The Internet Registry Information Service (IRIS) registers [corrected] domain names while DNS publishes domain addresses with mapping of names to addresses for the original web. Analogously, PORTAL registers resource labels and tags while DOORS publishes resource locations and descriptions with mapping of labels to locations for the semantic web. BioPORT is proposed as a prototype PORTAL registry specific for the problem domain of biomedical computing.

An engineering approach to an integrated value proposition design framework

Directory of Open Access Journals (Sweden)

Van Der Merwe, Carmen

2015-05-01

Full Text Available Numerous problems with product quality and time-to-market launches can be traced back to how the product lifecycle process is managed within the organisation. This article provides insight into how an integrated value proposition design framework shifts product lifecycle management from a product-centric view to a customer-centric view, through the use of good engineering practices as found in the systems engineering discipline. Combining this with methods and tools such as the Refined Kano model, Blue Ocean strategy, and the Generalised Bass model enables the organisation to enhance product and service quality while reducing the time-to-market for new value proposition launches.

Semantic Meaning in Attitudinal Lexemes in the Domain of Kesenangan (Joy in Indonesian: An Analysis of Meaning Components and Lexical Relation

Directory of Open Access Journals (Sweden)

Prima Gusti Yanti

2017-04-01

Full Text Available The attitudinal lexeme on the domain of kesenangan in Indonesia language has not shown such clear meaning relationship, for both the common and diagnostic meaning of the lexemes. Those lexemes have such circular definitions, confusing upon their use. This study is conducted using a qualitative research approach employing content analysis technique. The aim of this study is to find out lexical relation and semantic meaning in attitudinal lexeme in the domain of kesenangan (joy in Indonesian language. Data is collected from seven Indonesian dictionaries, two magazines, five newspapers, and six literary works. All data is analyzed using a component analysis in the semantic theory. The research findings show that fourteen (14 lexemes (senang, nikmat, enak, puas, asyik, sukacita, ria, bangga, lega, bahagia, gembira, girang, riang, and ceria of attitudinal lexemes are related with the domain of kesenangan. The result shows that hyponymy and synonymy lexical relations occur in the domain of kesenangan. Synonymy relation consists of near-synonymy and propositional synonymy. In this case, absolute synonymy is not found.

Handbook of metadata, semantics and ontologies

CERN Document Server

Sicilia, Miguel-Angel

2013-01-01

Metadata research has emerged as a discipline cross-cutting many domains, focused on the provision of distributed descriptions (often called annotations) to Web resources or applications. Such associated descriptions are supposed to serve as a foundation for advanced services in many application areas, including search and location, personalization, federation of repositories and automated delivery of information. Indeed, the Semantic Web is in itself a concrete technological framework for ontology-based metadata. For example, Web-based social networking requires metadata describing people and

Law proposition aiming to organize the sustainable management of radioactive wastes

International Nuclear Information System (INIS)

Bataille, Ch.; Ayrault, J.M.; Hollande, F.; Dose, F.; Dumont, J.L.; Brottes, F.; Le Deaut, J.Y.

2006-02-01

In 1991 the France decided to intensify its researches in the high activity radioactive wastes management domain. The law of the 30 December 1991 relative to the radioactive wastes management, decided that a period of 15 years would be devoted to the research of very long dated solutions. This law proposition takes into account these researches results and aims to define a policy of radioactive wastes management in the framework of a sustainable development. The authors present and discuss the different articles of the law proposition. (A.L.B.)

Quantum aspects of semantic analysis and symbolic artificial intelligence

International Nuclear Information System (INIS)

Aerts, Diederik; Czachor, Marek

2004-01-01

Modern approaches to semantic analysis if reformulated as Hilbert-space problems reveal formal structures known from quantum mechanics. A similar situation is found in distributed representations of cognitive structures developed for the purpose of neural networks. We take a closer look at similarities and differences between the above two fields and quantum information theory. (letter to the editor)

Quantum aspects of semantic analysis and symbolic artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Aerts, Diederik [Centrum Leo Apostel (CLEA) and Foundations of the Exact Sciences (FUND), Vrije Universiteit Brussel, 1050 Brussels (Belgium); Czachor, Marek [Katedra Fizyki Teoretycznej i Metod Matematycznych, Politechnika Gdanska, 80-952 Gdansk (Poland)

2004-03-26

Modern approaches to semantic analysis if reformulated as Hilbert-space problems reveal formal structures known from quantum mechanics. A similar situation is found in distributed representations of cognitive structures developed for the purpose of neural networks. We take a closer look at similarities and differences between the above two fields and quantum information theory. (letter to the editor)

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

Directory of Open Access Journals (Sweden)

HE Handong

2017-08-01

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

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

Directory of Open Access Journals (Sweden)

Mirna Lie Hosogi Senaha

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

If You Don't Have Valence, Ask Your Neighbor: Evaluation of Neutral Words as a Function of Affective Semantic Associates.

Science.gov (United States)

Kuhlmann, Michael; Hofmann, Markus J; Jacobs, Arthur M

2017-01-01

How do humans perform difficult forced-choice evaluations, e.g., of words that have been previously rated as being neutral? Here we tested the hypothesis that in this case, the valence of semantic associates is of significant influence. From corpus based co-occurrence statistics as a measure of association strength we computed individual neighborhoods for single neutral words comprised of the 10 words with the largest association strength. We then selected neutral words according to the valence of the associated words included in the neighborhoods, which were either mostly positive, mostly negative, mostly neutral or mixed positive and negative, and tested them using a valence decision task (VDT). The data showed that the valence of semantic neighbors can predict valence judgments to neutral words. However, all but the positive neighborhood items revealed a high tendency to elicit negative responses. For the positive and negative neighborhood categories responses congruent with the neighborhood's valence were faster than incongruent responses. We interpret this effect as a semantic network process that supports the evaluation of neutral words by assessing the valence of the associative semantic neighborhood. In this perspective, valence is considered a semantic super-feature, at least partially represented in associative activation patterns of semantic networks.

Education Hangs in Balance: Financing after Proposition 13.

Science.gov (United States)

Guthrie, James W.

1979-01-01

In light of the passage of Proposition 13 in California, which requires rethinking of the state's school financing structure, the author assesses the advantages and disadvantages of complete state financing v retaining some proportion of the revenue function at the local level. (Author/SJL)

Provenance-Based Approaches to Semantic Web Service Discovery and Usage

Science.gov (United States)

Narock, Thomas William

2012-01-01

The World Wide Web Consortium defines a Web Service as "a software system designed to support interoperable machine-to-machine interaction over a network." Web Services have become increasingly important both within and across organizational boundaries. With the recent advent of the Semantic Web, web services have evolved into semantic…

Montague semantics

NARCIS (Netherlands)

Janssen, T.M.V.

2012-01-01

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

From Data to Semantic Information

Directory of Open Access Journals (Sweden)

Luciano Floridi

2003-06-01

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

Semantic modeling and structural synthesis of onboard electronics protection means as open information system

Science.gov (United States)

Zhevnerchuk, D. V.; Surkova, A. S.; Lomakina, L. S.; Golubev, A. S.

2018-05-01

The article describes the component representation approach and semantic models of on-board electronics protection from ionizing radiation of various nature. Semantic models are constructed, the feature of which is the representation of electronic elements, protection modules, sources of impact in the form of blocks with interfaces. The rules of logical inference and algorithms for synthesizing the object properties of the semantic network, imitating the interface between the components of the protection system and the sources of radiation, are developed. The results of the algorithm are considered using the example of radiation-resistant microcircuits 1645RU5U, 1645RT2U and the calculation and experimental method for estimating the durability of on-board electronics.

Foundations of semantic web technologies

CERN Document Server

Hitzler, Pascal; Rudolph, Sebastian

2009-01-01

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

A Semantic Sensor Web for Environmental Decision Support Applications

Science.gov (United States)

Gray, Alasdair J. G.; Sadler, Jason; Kit, Oles; Kyzirakos, Kostis; Karpathiotakis, Manos; Calbimonte, Jean-Paul; Page, Kevin; García-Castro, Raúl; Frazer, Alex; Galpin, Ixent; Fernandes, Alvaro A. A.; Paton, Norman W.; Corcho, Oscar; Koubarakis, Manolis; De Roure, David; Martinez, Kirk; Gómez-Pérez, Asunción

2011-01-01

Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England. PMID:22164110

An evidential path logic for multi-relational networks

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, Marko A [Los Alamos National Laboratory; Geldart, Joe [UNIV OF DURHAM

2008-01-01

Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Description Framework (RDF). One of the primary purposes of a knowledge network is to reason; that is, to alter the topology of the network according to an algorithm that uses the existing topological structure as its input. There exist many such reasoning algorithms. With respect to the Semantic Web, the bivalent, axiomatic reasoners of the RDF Schema (RDFS) and the Web Ontology Language (OWL) are the most prevalent. However, nothing prevents other forms of reasoning from existing in the Semantic Web. This article presents a non-bivalent, non-axiomatic, evidential logic and reasoner that is an algebraic ring over a multi-relational network and two binary operations that can be composed to perform various forms of inference. Given its multi-relational grounding, it is possible to use the presented evidential framework as another method for structuring knowledge and reasoning in the Semantic Web. The benefits of this framework are that it works with arbitrary, partial, and contradictory knowledge while, at the same time, supporting a tractable approximate reasoning process.

Leveraging the real value of laboratory medicine with the value proposition.

Science.gov (United States)

Price, Christopher P; John, Andrew St; Christenson, Robert; Scharnhorst, Volker; Oellerich, Michael; Jones, Patricia; Morris, Howard A

2016-11-01

Improving quality and patient safety, containing costs and delivering value-for-money are the key drivers of change in the delivery of healthcare and have stimulated a shift from an activity-based service to a service based on patient-outcomes. The delivery of an outcomes-based healthcare agenda requires that the real value of laboratory medicine to all stakeholders be understood, effectively defined and communicated. The value proposition of any product or service is the link between the provider and the needs of the customer describing the utility of the product or service in terms of benefit to the customer. The framework of a value proposition for laboratory medicine provides the core business case that drives key activities in the evolution and maintenance of high quality healthcare from research through to adoption and quality improvement in an established service. The framework of a value proposition for laboratory medicine is described. The content is endorsed by IFCC and WASPaLM. Copyright © 2016 Elsevier B.V. All rights reserved.

Relating UMLS semantic types and task-based ontology to computer-interpretable clinical practice guidelines.

Science.gov (United States)

Kumar, Anand; Ciccarese, Paolo; Quaglini, Silvana; Stefanelli, Mario; Caffi, Ezio; Boiocchi, Lorenzo

2003-01-01

Medical knowledge in clinical practice guideline (GL) texts is the source of task-based computer-interpretable clinical guideline models (CIGMs). We have used Unified Medical Language System (UMLS) semantic types (STs) to understand the percentage of GL text which belongs to a particular ST. We also use UMLS semantic network together with the CIGM-specific ontology to derive a semantic meaning behind the GL text. In order to achieve this objective, we took nine GL texts from the National Guideline Clearinghouse (NGC) and marked up the text dealing with a particular ST. The STs we took into consideration were restricted taking into account the requirements of a task-based CIGM. We used DARPA Agent Markup Language and Ontology Inference Layer (DAML + OIL) to create the UMLS and CIGM specific semantic network. For the latter, as a bench test, we used the 1999 WHO-International Society of Hypertension Guidelines for the Management of Hypertension. We took into consideration the UMLS STs closest to the clinical tasks. The percentage of the GL text dealing with the ST "Health Care Activity" and subtypes "Laboratory Procedure", "Diagnostic Procedure" and "Therapeutic or Preventive Procedure" were measured. The parts of text belonging to other STs or comments were separated. A mapping of terms belonging to other STs was done to the STs under "HCA" for representation in DAML + OIL. As a result, we found that the three STs under "HCA" were the predominant STs present in the GL text. In cases where the terms of related STs existed, they were mapped into one of the three STs. The DAML + OIL representation was able to describe the hierarchy in task-based CIGMs. To conclude, we understood that the three STs could be used to represent the semantic network of the task-bases CIGMs. We identified some mapping operators which could be used for the mapping of other STs into these.

A semantically rich and standardised approach enhancing discovery of sensor data and metadata

Science.gov (United States)

Kokkinaki, Alexandra; Buck, Justin; Darroch, Louise

2016-04-01

The marine environment plays an essential role in the earth's climate. To enhance the ability to monitor the health of this important system, innovative sensors are being produced and combined with state of the art sensor technology. As the number of sensors deployed is continually increasing,, it is a challenge for data users to find the data that meet their specific needs. Furthermore, users need to integrate diverse ocean datasets originating from the same or even different systems. Standards provide a solution to the above mentioned challenges. The Open Geospatial Consortium (OGC) has created Sensor Web Enablement (SWE) standards that enable different sensor networks to establish syntactic interoperability. When combined with widely accepted controlled vocabularies, they become semantically rich and semantic interoperability is achievable. In addition, Linked Data is the recommended best practice for exposing, sharing and connecting information on the Semantic Web using Uniform Resource Identifiers (URIs), Resource Description Framework (RDF) and RDF Query Language (SPARQL). As part of the EU-funded SenseOCEAN project, the British Oceanographic Data Centre (BODC) is working on the standardisation of sensor metadata enabling 'plug and play' sensor integration. Our approach combines standards, controlled vocabularies and persistent URIs to publish sensor descriptions, their data and associated metadata as 5 star Linked Data and OGC SWE (SensorML, Observations & Measurements) standard. Thus sensors become readily discoverable, accessible and useable via the web. Content and context based searching is also enabled since sensors descriptions are understood by machines. Additionally, sensor data can be combined with other sensor or Linked Data datasets to form knowledge. This presentation will describe the work done in BODC to achieve syntactic and semantic interoperability in the sensor domain. It will illustrate the reuse and extension of the Semantic Sensor

Basic semantics of product sounds

NARCIS (Netherlands)

Özcan Vieira, E.; Van Egmond, R.

2012-01-01

Product experience is a result of sensory and semantic experiences with product properties. In this paper, we focus on the semantic attributes of product sounds and explore the basic components for product sound related semantics using a semantic differential paradigmand factor analysis. With two

Retrieval from semantic memory.

NARCIS (Netherlands)

Noordman-Vonk, Wietske

1977-01-01

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

Towards Universal Semantic Tagging

NARCIS (Netherlands)

Abzianidze, Lasha; Bos, Johan

2017-01-01

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

Process-oriented semantic web search

CERN Document Server

Tran, DT

2011-01-01

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

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

Science.gov (United States)

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

2010-01-01

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

Alternate proof of the Rowe-Rosensteel proposition and seniority conservation

International Nuclear Information System (INIS)

Qi Chong; Wang, X. B.; Xu, F. R.; Xu, Z. X.; Liotta, R. J.; Wyss, R.

2010-01-01

For a system with three identical nucleons in a single-j shell, the states can be written as the angular-momentum coupling of a nucleon pair and the odd nucleon. The overlaps between these nonorthonormal states form a matrix that coincides with the one derived by Rowe and Rosensteel [Phys. Rev. Lett. 87, 172501 (2001)]. The propositions they state are related to the eigenvalue problems of the matrix and dimensions of the associated subspaces. In this work, the propositions are proven from the symmetric properties of the 6j symbols. Algebraic expressions for the dimension of the states, eigenenergies, as well as conditions for conservation of seniority can be derived from the matrix.

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

Science.gov (United States)

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

2012-07-01

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

Disordered semantic representation in schizophrenic temporal cortex revealed by neuromagnetic response patterns

Directory of Open Access Journals (Sweden)

Silberman Yaron

2006-05-01

Full Text Available Abstract Background Loosening of associations and thought disruption are key features of schizophrenic psychopathology. Alterations in neural networks underlying this basic abnormality have not yet been sufficiently identified. Previously, we demonstrated that spatio-temporal clustering of magnetic brain responses to pictorial stimuli map categorical representations in temporal cortex. This result has opened the possibility to quantify associative strength within and across semantic categories in schizophrenic patients. We hypothesized that in contrast to controls, schizophrenic patients exhibit disordered representations of semantic categories. Methods The spatio-temporal clusters of brain magnetic activities elicited by object pictures related to super-ordinate (flowers, animals, furniture, clothes and base-level (e.g. tulip, rose, orchid, sunflower categories were analysed in the source space for the time epochs 170–210 and 210–450 ms following stimulus onset and were compared between 10 schizophrenic patients and 10 control subjects. Results Spatio-temporal correlations of responses elicited by base-level concepts and the difference of within vs. across super-ordinate categories were distinctly lower in patients than in controls. Additionally, in contrast to the well-defined categorical representation in control subjects, unsupervised clustering indicated poorly defined representation of semantic categories in patients. Within the patient group, distinctiveness of categorical representation in the temporal cortex was positively related to negative symptoms and tended to be inversely related to positive symptoms. Conclusion Schizophrenic patients show a less organized representation of semantic categories in clusters of magnetic brain responses than healthy adults. This atypical neural network architecture may be a correlate of loosening of associations, promoting positive symptoms.

High Performance Descriptive Semantic Analysis of Semantic Graph Databases

Energy Technology Data Exchange (ETDEWEB)

Joslyn, Cliff A.; Adolf, Robert D.; al-Saffar, Sinan; Feo, John T.; Haglin, David J.; Mackey, Greg E.; Mizell, David W.

2011-06-02

As semantic graph database technology grows to address components ranging from extant large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly important to be able to understand their inherent semantic structure, whether codified in explicit ontologies or not. Our group is researching novel methods for what we call descriptive semantic analysis of RDF triplestores, to serve purposes of analysis, interpretation, visualization, and optimization. But data size and computational complexity makes it increasingly necessary to bring high performance computational resources to bear on this task. Our research group built a novel high performance hybrid system comprising computational capability for semantic graph database processing utilizing the large multi-threaded architecture of the Cray XMT platform, conventional servers, and large data stores. In this paper we describe that architecture and our methods, and present the results of our analyses of basic properties, connected components, namespace interaction, and typed paths such for the Billion Triple Challenge 2010 dataset.

X-Informatics: Practical Semantic Science

Science.gov (United States)

Borne, K. D.

2009-12-01

The discipline of data science is merging with multiple science disciplines to form new X-informatics research disciplines. They are almost too numerous to name, but they include geoinformatics, bioinformatics, cheminformatics, biodiversity informatics, ecoinformatics, materials informatics, and the emerging discipline of astroinformatics. Within any X-informatics discipline, the information granules are unique to that discipline -- e.g., gene sequences in bio, the sky object in astro, and the spatial object in geo (such as points, lines, and polygons in the vector model, and pixels in the raster model). Nevertheless the goals are similar: transparent data re-use across subdisciplines and within education settings, information and data integration and fusion, personalization of user interactions with the data collection, semantic search and retrieval, and knowledge discovery. The implementation of an X-informatics framework enables these semantic e-science research goals. We describe the concepts, challenges, and new developments associated with the new discipline of astroinformatics, and how geoinformatics provides valuable lessons learned and a model for practical semantic science within a traditional science discipline through the accretion of data science methodologies (such as formal metadata creation, data models, data mining, information retrieval, knowledge engineering, provenance, taxonomies, and ontologies). The emerging concept of data-as-a-service (DaaS) builds upon the concept of smart data (or data DNA) for intelligent data management, automated workflows, and intelligent processing. Smart data, defined through X-informatics, enables several practical semantic science use cases, including self-discovery, data intelligence, automatic recommendations, relevance analysis, dimension reduction, feature selection, constraint-based mining, interdisciplinary data re-use, knowledge-sharing, data use in education, and more. We describe these concepts within the

GESTURE-VERBAL UTTERANCES FROM THE COGNITIVE PERSPECTIVE

OpenAIRE

Martynyuk, Alla

2016-01-01

The article develops the idea of speech and gesture as an integral system of generation of meaning viewing an individual’s cognitive system as a dynamic, evolving semantic lattice organising semantic items of propositional and imagistic modes around a core meaning: linguistic items (propositions) are linked to ideas, concepts and beliefs as well as to specific feelings, mental states, images of gestures and stereotypic patterns of behaviour. Since gesture and speech are equally engaged in gen...

Exploring continuous organisational transformation as a form of network interdependence

OpenAIRE

Stebbings, H; Braganza, A

2008-01-01

In this paper we examine the problematic area of continuous transformation. We conduct our analysis from three theoretical perspectives: the resource based view, social network theory, and stakeholder theory. We found that the continuous transformation can be explained through the concept of Network Interdependence. This paper describes Network Interdependence and develops theoretical propositions from a synthesis of the three theories. Our contribution of Network Interdependence offers f...

Moving Matters of Contemporary Art: Three New Materialist Propositions

Directory of Open Access Journals (Sweden)

Katve-Kaisa Kontturi

2014-04-01

Full Text Available Fashioning a new materialist agenda, this essay calls for sensitivity to subtly moving matters present in the processes of making and encountering art. Otherwise, it claims, we will end up with seriously restricted understandings of art’s capabilities. Indeed, we might even miss art’s most inventive and moving offering: how it can change our thinking-feeling. In this essay, I suggest methods of relating to art in more bodily and material terms, and propose concepts that help to point out the materiality of encountering and making art. To make sense of how a new materialist approach might work in the case of contemporary art, I will offer three propositions that revolve around ontology, ethics and politics. These propositions arise from participation with art and are probed and provoked by a close relation to art.

Harmonising and semantically linking key variables from in-situ observing networks of an Integrated Atlantic Ocean Observing System, AtlantOS

Science.gov (United States)

Darroch, Louise; Buck, Justin

2017-04-01

Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements at regional, national and international scales. The EU Horizon 2020 AtlantOS project aims to deliver an advanced framework for the development of an Integrated Atlantic Ocean Observing System that strengthens the Global Ocean Observing System (GOOS) and contributes to the aims of the Galway Statement on Atlantic Ocean Cooperation. One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to a wider community, including the international ocean science community and other stakeholders in this field. To help achieve this goal, the British Oceanographic Data Centre (BODC) produced a parameter matrix to harmonise data exchange, data flow and data integration for the key variables acquired by multiple in-situ AtlantOS observing networks such as ARGO, Seafloor Mapping and OceanSITES. Our solution used semantic linking of controlled vocabularies and metadata for parameters that were "mappable" to existing EU and international standard vocabularies. An AtlantOS Essential Variables list of terms (aggregated level) based on Global Climate Observing System (GCOS) Essential Climate Variables (ECV), GOOS Essential Ocean Variables (EOV) and other key network variables was defined and published on the Natural Environment Research Council (NERC) Vocabulary Server (version 2.0) as collection A05 (http://vocab.nerc.ac.uk/collection/A05/current/). This new vocabulary was semantically linked to standardised metadata for observed properties and units that had been validated by the AtlantOS community: SeaDataNet parameters (P01), Climate and Forecast (CF) Standard Names (P07) and SeaDataNet units (P06). Observed properties were mapped to biological entities from the internationally assured AphiaID from the WOrld Register of Marine Species (WoRMS), http

Subliminal semantic priming in speech.

Directory of Open Access Journals (Sweden)

Jérôme Daltrozzo

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

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

DEFF Research Database (Denmark)

Nielsen, Finn Årup; Hansen, Lars Kai

2017-01-01

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

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

Science.gov (United States)

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.

Grasping Ideas with the Motor System: Semantic Somatotopy in Idiom Comprehension

Science.gov (United States)

Hauk, Olaf; Pulvermüller, Friedemann

2009-01-01

Single words and sentences referring to bodily actions activate the motor cortex. However, this semantic grounding of concrete language does not address the critical question whether the sensory–motor system contributes to the processing of abstract meaning and thought. We examined functional magnetic resonance imaging activation to idioms and literal sentences including arm- and leg-related action words. A common left fronto-temporal network was engaged in sentence reading, with idioms yielding relatively stronger activity in (pre)frontal and middle temporal cortex. Crucially, somatotopic activation along the motor strip, in central and precentral cortex, was elicited by idiomatic and literal sentences, reflecting the body part reference of the words embedded in the sentences. Semantic somatotopy was most pronounced after sentence ending, thus reflecting sentence-level processing rather than that of single words. These results indicate that semantic representations grounded in the sensory–motor system play a role in the composition of sentence-level meaning, even in the case of idioms. PMID:19068489

Analisis Customer Segment, Channels, Dan Customer Relationship Dalam Pembentukan Value Proposition Di Starbucks Coffee (Studi Kasus Pada Starbucks Coffee Indonesia)

OpenAIRE

Nurmanisa, Aisy; Wilopo,; Sanawiri, Brillyanes

2016-01-01

This research aims to understand and explain; How to Starbucks Coffee create value proposition for their customer? How to Starbucks Coffee segmented the customer, to create the value proposition? How to Starbucks Coffee build and choose the channels to grab the customer and create value proposition? How to Starbucks Coffee build a customer relationship and create value proposition from the process? .This reaserch uses primery data descriptive analysis method with fenomelogy kualitative o...

Applied Semantic Web Technologies

CERN Document Server

Sugumaran, Vijayan

2011-01-01

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

AN APPLICATION FOR EFFICIENT TELECOMMUNICATION NETWORKS PROVISIONING USING LINEAR PROGRAMMING

Directory of Open Access Journals (Sweden)

Maria Augusta Soares Machado

2015-03-01

Full Text Available This paper presents a practical proposition for the application of the Linear Programming quantitative method in order to assist planning and control of customer circuit delivery activities in telecommunications companies working with the corporative market. Based upon data provided for by a telecom company operating in Brazil, the Linear Programming method was employed for one of the classical problems of determining the optimum mix of production quantities for a set of five products of that company: Private Telephone Network, Internet Network, Intranet Network, Low Speed Data Network, and High Speed Data Network, in face of several limitations of the productive resources, seeking to maximize the company’s monthly revenue. By fitting the production data available into a primary model, observation was made as to what number of monthly activations for each product would be mostly optimized in order to achieve maximum revenues in the company. The final delivery of a complete network was not observed but the delivery of the circuits that make it up, and this was a limiting factor for the study herein, which, however, brings an innovative proposition for the planning of private telecommunications network provisioning.

Automated Proposition Density Analysis for Discourse in Aphasia

Science.gov (United States)

Fromm, Davida; Greenhouse, Joel; Hou, Kaiyue; Russell, G. Austin; Cai, Xizhen; Forbes, Margaret; Holland, Audrey; MacWhinney, Brian

2016-01-01

Purpose: This study evaluates how proposition density can differentiate between persons with aphasia (PWA) and individuals in a control group, as well as among subtypes of aphasia, on the basis of procedural discourse and personal narratives collected from large samples of participants. Method: Participants were 195 PWA and 168 individuals in a…

Evaluation of Forensic DNA Traces When Propositions of Interest Relate to Activities

DEFF Research Database (Denmark)

Biedermann, Alex; Champod, Christophe; Jackson, Graham

2016-01-01

When forensic scientists evaluate and report on the probative strength of single DNA traces, they commonly rely on only one number, expressing the rarity of the DNA profile in the population of interest. This is so because the focus is on propositions regarding the source of the recovered trace...... demonstrated in day-to-day forensic practice and is also voiced in specialized literature. Yet many forensic scientists remain reluctant to assess their results given propositions that relate to different activities. Some scientists consider evaluations beyond the issue of source as being overly speculative...

Spatial Relation Predicates in Topographic Feature Semantics

Science.gov (United States)

Varanka, Dalia E.; Caro, Holly K.

2013-01-01

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking

Science.gov (United States)

Ma, Zhanshan (Sam); Krings, Axel W.; Hung, Chih-Cheng

computer science, especially secure and resilient computing, the semantic web, and social networking. One important thread unifying the three aspects is the evolutionary game theory modeling or its extensions with survival analysis and agreement algorithms [19][20], which offer powerful game models for describing time-, space-, and covariate-dependent frailty (uncertainty and vulnerability) and deception (honesty).

Lateral and medial prefrontal contributions to emotion generation by semantic elaboration during episodic encoding.

Science.gov (United States)

Kaneda, Takumi; Shigemune, Yayoi; Tsukiura, Takashi

2017-02-01

Memories for emotion-laden stimuli are remembered more accurately than those for neutral stimuli. Although this enhancement reflects stimulus-driven modulation of memory by emotions, functional neuroimaging evidence of the interacting mechanisms between emotions generated by intentional processes, such as semantic elaboration, and memory is scarce. The present fMRI study investigated how encoding-related activation is modulated by emotions generated during the process of semantic elaboration. During encoding with fMRI, healthy young adults viewed neutral (target) pictures either passively or with semantic elaboration. In semantic elaboration, participants imagined background stories related to the pictures. Encoding trials with semantic elaboration were subdivided into conditions in which participants imagined negative, positive, or neutral stories. One week later, memories for target pictures were tested. In behavioral results, memories for target pictures were significantly enhanced by semantic elaboration, compared to passive viewing, and the memory enhancement was more remarkable when negative or positive stories were imagined. fMRI results demonstrated that activations in the left inferior frontal gyrus and dorsal medial prefrontal cortex (dmPFC) were greater during the encoding of target pictures with semantic elaboration than those with passive viewing, and that these activations further increased during encoding with semantic elaboration of emotional stories than of neutral stories. Functional connectivity between the left inferior frontal gyrus and dmPFC/hippocampus during encoding significantly predicted retrieval accuracies of memories encoded with self-generated emotional stories. These findings suggest that networks including the left inferior frontal region, dmPFC, and hippocampus could contribute to the modulation of memories encoded with the emotion generation.

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

Directory of Open Access Journals (Sweden)

David Shotton

2009-04-01

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

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

DEFF Research Database (Denmark)

Jensen, Kurt; Schmidt, Erik Meineche

1986-01-01

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

The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.

Science.gov (United States)

Tamminen, Jakke; Lambon Ralph, Matthew A; Lewis, Penelope A

2013-09-25

Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.

An fMRI study of semantic processing in men with schizophrenia

Science.gov (United States)

Kubicki, M.; McCarley, R.W.; Nestor, P.G.; Huh, T.; Kikinis, R.; Shenton, M.E.; Wible, C.G.

2009-01-01

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

An fMRI study of semantic processing in men with schizophrenia.

Science.gov (United States)

Kubicki, M; McCarley, R W; Nestor, P G; Huh, T; Kikinis, R; Shenton, M E; Wible, C G

2003-12-01

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.

Gann Limit & Proposition 13: Negative Effects on Local Government Agencies, Inlcuding Schools & Community College Districts.

Science.gov (United States)

Rodda, Albert S.

In fall 1978, Paul Gann, who worked with Howard Jarvis to pass California's Proposition 13 in June 1978, sought to qualify an intitiative placing a constitutional limit on state and local government expenditures. This initiative qualified and was approved by voters in November 1979 as Proposition 4. Gann's solicitation set the limitation's base…

Consumer demand as a driver of improved working conditions: the 'Ergo-Brand' proposition.

Science.gov (United States)

Neumann, W Patrick; Dixon, Shane M; Nordvall, Anna-Carin

2014-01-01

This article develops and explores the 'Ergo-Brand' proposition, which posits that consumers may prefer to buy goods that are made under good working conditions (GWCs). This preference would enhance a differentiation strategy for companies, thereby fostering the application of ergonomics in production. This proposition is developed in the context of a narrative review of the literature on 'ethical consumerism'. This is supplemented with a survey study, conducted in both Canada and Sweden (n = 141) to explore this proposition. Results indicate that consumers would prefer goods made under GWCs, but not unconditionally as quality and price concerns were ranked higher. Access to information on the working conditions in production was seen as a barrier. Nevertheless, the Ergo-Brand concept may be a viable avenue in promoting attention towards ergonomics in companies - particularly if consumer habits are subject to intervention by advertising. Further research on this strategy is warranted.

Gaussian mixture models and semantic gating improve reconstructions from human brain activity

Directory of Open Access Journals (Sweden)

Sanne eSchoenmakers

2015-01-01

Full Text Available Better acquisition protocols and analysis techniques are making it possible to use fMRI to obtain highly detailed visualizations of brain processes. In particular we focus on the reconstruction of natural images from BOLD responses in visual cortex. We expand our linear Gaussian framework for percept decoding with Gaussian mixture models to better represent the prior distribution of natural images. Reconstruction of such images then boils down to probabilistic inference in a hybrid Bayesian network. In our set-up, different mixture components correspond to different character categories. Our framework can automatically infer higher-order semantic categories from lower-level brain areas. Furthermore the framework can gate semantic information from higher-order brain areas to enforce the correct category during reconstruction. When categorical information is not available, we show that automatically learned clusters in the data give a similar improvement in reconstruction. The hybrid Bayesian network leads to highly accurate reconstructions in both supervised and unsupervised settings.

Reactive Kripke semantics

CERN Document Server

Gabbay, Dov M

2013-01-01

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

Market Segmentation, Customers, and Value Propositions Analysis for Polymer Clay Art Business Start-Up

Directory of Open Access Journals (Sweden)

Desman Hidayat

2016-05-01

Full Text Available Polymer clay art is one of the creative businesses that are recently starting to get a lot of attentions. To prepare a startup business in this field, analysis from a lot of aspects is needed. The purpose of this article was to explain the approach of the polymer clay art business startup from the market segmentation, customer, and value proposition side of the business. The method was applied by analyzing those steps in details. The analysis started from brainstorming to choose the market matching to business, the customer side, value proposition, and between both aspects. The result of the analysis shows the business focus of the polymer clay art business, where the value propositions are focusing on unique decorations, and several types of customer segments.

The HPT Value Proposition in the Larger Improvement Arena.

Science.gov (United States)

Wallace, Guy W.

2003-01-01

Discussion of human performance technology (HPT) emphasizes the key variable, which is the human variable. Highlights include the Ishikawa Diagram; human performance as one variable of process performance; collaborating with other improvement approaches; value propositions; and benefits to stakeholders, including real return on investments. (LRW)

Semantics, contrastive linguistics and parallel corpora

Directory of Open Access Journals (Sweden)

Violetta Koseska

2014-09-01

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

Dynamic information processing states revealed through neurocognitive models of object semantics

Science.gov (United States)

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

A semantic web ontology for small molecules and their biological targets.

Science.gov (United States)

Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

2010-05-24

A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

Semantic web for dummies

CERN Document Server

Pollock, Jeffrey T

2009-01-01

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

A constructive logic for services and information flow in computer networks

NARCIS (Netherlands)

Borghuis, V.A.J.; Feijs, L.M.G.

2000-01-01

In this paper we introduce a typed -calculus in which computer networks can be formalized and directed at situations where the services available on the network are stationary, while the information can flow freely. For this calculus, an analogue of the ‘propositions-as-types ’interpretation of

A top-down manner-based DCNN architecture for semantic image segmentation.

Directory of Open Access Journals (Sweden)

Kai Qiao

Full Text Available Given their powerful feature representation for recognition, deep convolutional neural networks (DCNNs have been driving rapid advances in high-level computer vision tasks. However, their performance in semantic image segmentation is still not satisfactory. Based on the analysis of visual mechanism, we conclude that DCNNs in a bottom-up manner are not enough, because semantic image segmentation task requires not only recognition but also visual attention capability. In the study, superpixels containing visual attention information are introduced in a top-down manner, and an extensible architecture is proposed to improve the segmentation results of current DCNN-based methods. We employ the current state-of-the-art fully convolutional network (FCN and FCN with conditional random field (DeepLab-CRF as baselines to validate our architecture. Experimental results of the PASCAL VOC segmentation task qualitatively show that coarse edges and error segmentation results are well improved. We also quantitatively obtain about 2%-3% intersection over union (IOU accuracy improvement on the PASCAL VOC 2011 and 2012 test sets.

Opening the Semantic Space in the Service of Collective Intelligence - DOI: 10.3395/reciis.v1i1.43en

Directory of Open Access Journals (Sweden)

Pierre Lévy

2007-06-01

Full Text Available As the human recorded memory is progressively digitized and posted on line, the need for a common semantic coordinate system independant from natural languages and ontologies is growing. A future universal semantic addressing system, able to index all digital documents, should meet three basic requirements. First, each distinct concept should have a unique address. Second, the semantic coordinate system should be open to any concept and relations between concepts (ontologies, whatever the cultural environments where these concepts are created and transformed, without neither privileges nor exclusions. Third, it should support a group of mathematically defined (automatable operations on semantic addresses, namely : rotations, symmetries and translations in the « semantic space » ; semantic compression and decompression ; set-theory operations like union, intersection and symmetric differences ; ranking on semantic criteria ; semantic pattern recognition ; semantic distances measurement ; logical inferences, etc. Developped by an international research network led by the Canada Research Chair in Collective Intelligence at the University of Ottawa, the Information Economy MetaLanguage (IEML, allows the construction of a semantic coordinate system meeting these three constraints. Website, including the IEML dictionary, since may 2006 : www.ieml.org. In Brasil, BIREME (www.bireme.br is member of the IEML initiative.

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

Science.gov (United States)

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

2018-01-03

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

Formal Women-only Networks

DEFF Research Database (Denmark)

Villesèche, Florence; Josserand, Emmanuel

2017-01-01

/organisations and the wider social group of women in business. Research limitations/implications: The authors focus on the distinction between external and internal formal women-only networks while also acknowledging the broader diversity that can characterise such networks. Their review provides the reader with an insight...... member level, the authors suggest that such networks can be of value for organisations and the wider social group of women in management and leadership positions.......Purpose: The purpose of this paper is to review the emerging literature on formal women-only business networks and outline propositions to develop this under-theorised area of knowledge and stimulate future research. Design/methodology/approach: The authors review the existing literature on formal...

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

Science.gov (United States)

Kazic, Toni

2006-01-01

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

Multimedia Information Networks in Social Media

Science.gov (United States)

Cao, Liangliang; Qi, Guojun; Tsai, Shen-Fu; Tsai, Min-Hsuan; Pozo, Andrey Del; Huang, Thomas S.; Zhang, Xuemei; Lim, Suk Hwan

The popularity of personal digital cameras and online photo/video sharing community has lead to an explosion of multimedia information. Unlike traditional multimedia data, many new multimedia datasets are organized in a structural way, incorporating rich information such as semantic ontology, social interaction, community media, geographical maps, in addition to the multimedia contents by themselves. Studies of such structured multimedia data have resulted in a new research area, which is referred to as Multimedia Information Networks. Multimedia information networks are closely related to social networks, but especially focus on understanding the topics and semantics of the multimedia files in the context of network structure. This chapter reviews different categories of recent systems related to multimedia information networks, summarizes the popular inference methods used in recent works, and discusses the applications related to multimedia information networks. We also discuss a wide range of topics including public datasets, related industrial systems, and potential future research directions in this field.

Bill project related to energy transition for a green growth. ANCCLI's opinion and propositions. Posture note. Synthesis of ANCCLI's opinions and propositions. ANCCLI's amendment propositions

International Nuclear Information System (INIS)

2014-09-01

This document first contains a brief justification of the ANCCLI's posture regarding the debate on energy within the frame of the bill project related to energy transition for a green growth. The next part comments some parts of the bill project, its motivations, the main objectives of the energy policy, citizen safety and information (the document outlines the role of CLIs and of the ANCCLI - the national association of local information committees -, discusses the issue of access to information, those related to definitive shutdown and dismantling of installations, to safety control and assessment, to nuclear materials and radioactive wastes), the nuclear governance within the energetic planning (steering of the installed nuclear production capacity, safety challenges to be taken into account, the 40 year deadline for the lifetime of nuclear reactors). The next part proposes a synthesis of ANCCLI's opinions and propositions for the bill project on the same aspects (general directions, citizen safety and information, nuclear governance). Six amendment propositions are then formulated for the strengthening of CLIs' role and for the access to information and to expertise, and for the implementation of a specific decision procedure for the 40 year deadline, and three others for the continuation of reactor operation

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

DEFF Research Database (Denmark)

Danvy, Olivier

2008-01-01

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

Right Propositional Neighborhood Logic over Natural Numbers with Integer Constraints for Interval Lengths

DEFF Research Database (Denmark)

Bresolin, Davide; Goranko, Valentin; Montanari, Angelo

2009-01-01

Interval temporal logics are based on interval structures over linearly (or partially) ordered domains, where time intervals, rather than time instants, are the primitive ontological entities. In this paper we introduce and study Right Propositional Neighborhood Logic over natural numbers...... with integer constraints for interval lengths, which is a propositional interval temporal logic featuring a modality for the 'right neighborhood' relation between intervals and explicit integer constraints for interval lengths. We prove that it has the bounded model property with respect to ultimately periodic...

Temporal Representation in Semantic Graphs

Energy Technology Data Exchange (ETDEWEB)

Levandoski, J J; Abdulla, G M

2007-08-07

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

Flow Logics and Operational Semantics

DEFF Research Database (Denmark)

Nielson, Flemming; Nielson, Hanne Riis

1998-01-01

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

Semantic Versus Syntactic Cutting Planes

OpenAIRE

Filmus, Yuval; Hrubeš, Pavel; Lauria, Massimo

2016-01-01

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

Only time will tell - why temporal information is essential for our neuroscientific understanding of semantics.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2017-08-01

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

Semantic strategy training increases memory performance and brain activity in patients with prefrontal cortex lesions.

Science.gov (United States)

Miotto, Eliane C; Savage, Cary R; Evans, Jonathan J; Wilson, Barbara A; Martin, Maria G M; Balardin, Joana B; Barros, Fabio G; Garrido, Griselda; Teixeira, Manoel J; Amaro Junior, Edson

2013-03-01

Memory deficit is a frequent cognitive disorder following acquired prefrontal cortex lesions. In the present study, we investigated the brain correlates of a short semantic strategy training and memory performance of patients with distinct prefrontal cortex lesions using fMRI and cognitive tests. Twenty-one adult patients with post-acute prefrontal cortex (PFC) lesions, twelve with left dorsolateral PFC (LPFC) and nine with bilateral orbitofrontal cortex (BOFC) were assessed before and after a short cognitive semantic training using a verbal memory encoding paradigm during scanning and neuropsychological tests outside the scanner. After the semantic strategy training both groups of patients showed significant behavioral improvement in verbal memory recall and use of semantic strategies. In the LPFC group, greater activity in left inferior and medial frontal gyrus, precentral gyrus and insula was found after training. For the BOFC group, a greater activation was found in the left parietal cortex, right cingulated and precuneus after training. The activation of these specific areas in the memory and executive networks following cognitive training was associated to compensatory brain mechanisms and application of the semantic strategy. Copyright © 2012 Elsevier B.V. All rights reserved.

Distinct contributions of the fornix and inferior longitudinal fasciculus to episodic and semantic autobiographical memory.

Science.gov (United States)

Hodgetts, Carl J; Postans, Mark; Warne, Naomi; Varnava, Alice; Lawrence, Andrew D; Graham, Kim S

2017-09-01

Autobiographical memory (AM) is multifaceted, incorporating the vivid retrieval of contextual detail (episodic AM), together with semantic knowledge that infuses meaning and coherence into past events (semantic AM). While neuropsychological evidence highlights a role for the hippocampus and anterior temporal lobe (ATL) in episodic and semantic AM, respectively, it is unclear whether these constitute dissociable large-scale AM networks. We used high angular resolution diffusion-weighted imaging and constrained spherical deconvolution-based tractography to assess white matter microstructure in 27 healthy young adult participants who were asked to recall past experiences using word cues. Inter-individual variation in the microstructure of the fornix (the main hippocampal input/output pathway) related to the amount of episodic, but not semantic, detail in AMs - independent of memory age. Conversely, microstructure of the inferior longitudinal fasciculus, linking occipitotemporal regions with ATL, correlated with semantic, but not episodic, AMs. Further, these significant correlations remained when controlling for hippocampal and ATL grey matter volume, respectively. This striking correlational double dissociation supports the view that distinct, large-scale distributed brain circuits underpin context and concepts in AM. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Mediator infrastructure for information integration and semantic data integration environment for biomedical research.

Science.gov (United States)

Grethe, Jeffrey S; Ross, Edward; Little, David; Sanders, Brian; Gupta, Amarnath; Astakhov, Vadim

2009-01-01

This paper presents current progress in the development of semantic data integration environment which is a part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A goal is the development of a cyberinfrastructure for biomedical research that supports advance data acquisition, data storage, data management, data integration, data mining, data visualization, and other computing and information processing services over the Internet. Each participating institution maintains storage of their experimental or computationally derived data. Mediator-based data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This paper describes recent revision of the system architecture, implementation, and capabilities of the semantically based data integration environment for BIRN.

Diagnosis of Cognitive Impairment Compatible with Early Diagnosis of Alzheimer's Disease. A Bayesian Network Model based on the Analysis of Oral Definitions of Semantic Categories.

Science.gov (United States)

Guerrero, J M; Martínez-Tomás, R; Rincón, M; Peraita, H

2016-01-01

Early detection of Alzheimer's disease (AD) has become one of the principal focuses of research in medicine, particularly when the disease is incipient or even prodromic, because treatments are more effective in these stages. Lexical-semantic-conceptual deficit (LSCD) in the oral definitions of semantic categories for basic objects is an important early indicator in the evaluation of the cognitive state of patients. The objective of this research is to define an economic procedure for cognitive impairment (CI) diagnosis, which may be associated with early stages of AD, by analysing cognitive alterations affecting declarative semantic memory. Because of its low cost, it could be used for routine clinical evaluations or screenings, leading to more expensive and selective tests that confirm or rule out the disease accurately. It should necessarily be an explanatory procedure, which would allow us to study the evolution of the disease in relation to CI, the irregularities in different semantic categories, and other neurodegenerative diseases. On the basis of these requirements, we hypothesise that Bayesian networks (BNs) are the most appropriate tool for this purpose. We have developed a BN for CI diagnosis in mild and moderate AD patients by analysing the oral production of semantic features. The BN causal model represents LSCD in certain semantic categories, both of living things (dog, pine, and apple) and non-living things (chair, car, and trousers), as symptoms of CI. The model structure, the qualitative part of the model, uses domain knowledge obtained from psychology experts and epidemiological studies. Further, the model parameters, the quantitative part of the model, are learnt automatically from epidemiological studies and Peraita and Grasso's linguistic corpus of oral definitions. This corpus was prepared with an incidental sampling and included the analysis of the oral linguistic production of 81 participants (42 cognitively healthy elderly people and 39

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

Science.gov (United States)

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

2014-01-01

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

Semantic Web Primer

NARCIS (Netherlands)

Antoniou, Grigoris; Harmelen, Frank van

2004-01-01

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

The pivotal role of semantic memory in remembering the past and imagining the future

Directory of Open Access Journals (Sweden)

Muireann eIrish

2013-04-01

Full Text Available Episodic memory refers to a complex and multifaceted process which enables the retrieval of richly detailed evocative memories from the past. In contrast, semantic memory is conceptualised as the retrieval of general conceptual knowledge divested of a specific spatiotemporal context. The neural substrates of the episodic and semantic memory systems have been dissociated in healthy individuals during functional imaging studies, and in clinical cohorts, leading to the prevailing view that episodic and semantic memory represent functionally distinct systems subtended by discrete neurobiological substrates. Importantly, however, converging evidence focusing on widespread neural networks now points to significant overlap between those regions essential for retrieval of autobiographical memories, episodic learning, and semantic processing. Here we review recent advances in episodic memory research focusing on neurodegenerative populations which has proved revelatory for our understanding of the complex interplay between episodic and semantic memory. Whereas episodic memory research has traditionally focused on retrieval of autobiographical events from the past, we also include evidence from the recent paradigm shift in which episodic memory is viewed as an adaptive and constructive process which facilitates the imagining of possible events in the future. We examine the available evidence which converges to highlight the pivotal role of semantic memory in providing schemas and meaning whether one is engaged in autobiographical retrieval for the past, or indeed, is endeavouring to construct a plausible scenario of an event in the future. It therefore seems plausible to contend that semantic processing may underlie most, if not all, forms of episodic memory, irrespective of temporal condition.

The Pivotal Role of Semantic Memory in Remembering the Past and Imagining the Future

Science.gov (United States)

Irish, Muireann; Piguet, Olivier

2013-01-01

Episodic memory refers to a complex and multifaceted process which enables the retrieval of richly detailed evocative memories from the past. In contrast, semantic memory is conceptualized as the retrieval of general conceptual knowledge divested of a specific spatiotemporal context. The neural substrates of the episodic and semantic memory systems have been dissociated in healthy individuals during functional imaging studies, and in clinical cohorts, leading to the prevailing view that episodic and semantic memory represent functionally distinct systems subtended by discrete neurobiological substrates. Importantly, however, converging evidence focusing on widespread neural networks now points to significant overlap between those regions essential for retrieval of autobiographical memories, episodic learning, and semantic processing. Here we review recent advances in episodic memory research focusing on neurodegenerative populations which has proved revelatory for our understanding of the complex interplay between episodic and semantic memory. Whereas episodic memory research has traditionally focused on retrieval of autobiographical events from the past, we also include evidence from the recent paradigm shift in which episodic memory is viewed as an adaptive and constructive process which facilitates the imagining of possible events in the future. We examine the available evidence which converges to highlight the pivotal role of semantic memory in providing schemas and meaning whether one is engaged in autobiographical retrieval for the past, or indeed, is endeavoring to construct a plausible scenario of an event in the future. It therefore seems plausible to contend that semantic processing may underlie most, if not all, forms of episodic memory, irrespective of temporal condition. PMID:23565081

Priming the semantic neighbourhood during the attentional blink.

Directory of Open Access Journals (Sweden)

Irina M Harris

2010-09-01

Full Text Available When two targets are presented in close temporal proximity amongst a rapid serial visual stream of distractors, a period of disrupted attention and attenuated awareness lasting 200-500 ms follows identification of the first target (T1. This phenomenon is known as the "attentional blink" (AB and is generally attributed to a failure to consolidate information in visual short-term memory due to depleted or disrupted attentional resources. Previous research has shown that items presented during the AB that fail to reach conscious awareness are still processed to relatively high levels, including the level of meaning. For example, missed word stimuli have been shown to prime later targets that are closely associated words. Although these findings have been interpreted as evidence for semantic processing during the AB, closely associated words (e.g., day-night may also rely on specific, well-worn, lexical associative links which enhance attention to the relevant target.We used a measure of semantic distance to create prime-target pairs that are conceptually close, but have low word associations (e.g., wagon and van and investigated priming from a distractor stimulus presented during the AB to a subsequent target (T2. The stimuli were words (concrete nouns in Experiment 1 and the corresponding pictures of objects in Experiment 2. In both experiments, report of T2 was facilitated when this item was preceded by a semantically-related distractor.This study is the first to show conclusively that conceptual information is extracted from distractor stimuli presented during a period of attenuated awareness and that this information spreads to neighbouring concepts within a semantic network.

On the Predictability of Classical Propositional Logic

OpenAIRE

Finger, Marcelo; Reis, Poliana

2013-01-01

In this work we provide a statistical form of empirical analysis of classical propositional logic decision methods called SAT solvers. This work is perceived as an empirical counterpart of a theoretical movement, called the enduring scandal of deduction, that opposes considering Boolean Logic as trivial in any sense. For that, we study the predictability of classical logic, which we take to be the distribution of the runtime of its decision process. We present a series of experiments that det...

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

Science.gov (United States)

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

2012-01-01

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

COTARD SYNDROME IN SEMANTIC DEMENTIA

Science.gov (United States)

Mendez, Mario F.; Ramírez-Bermúdez, Jesús

2011-01-01

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

Hierarchical Semantic Model of Geovideo

Directory of Open Access Journals (Sweden)

XIE Xiao

2015-05-01

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

Causality in the semantics of Esterel : revisited

NARCIS (Netherlands)

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

2010-01-01

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

Definition of Strong Equality of Tautologies and Universal System for Various Propositional Logics

Directory of Open Access Journals (Sweden)

Anahit Chubaryan

2008-10-01

Full Text Available Earlier we have introduced a definition of strong equality of classical tautologies, according to which two tautologies are equal iff they have the same hardness. The strong equality implies well known equality, but not vice versa. The strong equality is based on the notion of determinitive conjunct, using of which some new deduction system for classical propositional logic were defined. Here the notions of strong equality of tautologies for various logics are suggested and the idea of construction of universal deduction system for various propositional logics is given.

GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

Directory of Open Access Journals (Sweden)

Hengcai Zhang

2017-03-01

Full Text Available Existing data models for moving objects in networks are often limited by flexibly controlling the granularity of representing networks and the cost of location updates and do not encompass semantic information, such as traffic states, traffic restrictions and social relationships. In this paper, we aim to fill the gap of traditional network-constrained models and propose a hierarchical graph model called the Geo-Social-Moving model for moving objects in Networks (GSMNet that adopts four graph structures, RouteGraph, SegmentGraph, ObjectGraph and MoveGraph, to represent the underlying networks, trajectories and semantic information in an integrated manner. The bulk of user-defined data types and corresponding operators is proposed to handle moving objects and answer a new class of queries supporting three kinds of conditions: spatial, temporal and semantic information. Then, we develop a prototype system with the native graph database system Neo4Jto implement the proposed GSMNet model. In the experiment, we conduct the performance evaluation using simulated trajectories generated from the BerlinMOD (Berlin Moving Objects Database benchmark and compare with the mature MOD system Secondo. The results of 17 benchmark queries demonstrate that our proposed GSMNet model has strong potential to reduce time-consuming table join operations an d shows remarkable advantages with regard to representing semantic information and controlling the cost of location updates.

Framework for Evaluating the Total Value Proposition of Clean Energy Technologies

Energy Technology Data Exchange (ETDEWEB)

Pater, J. E.

2006-02-01

Conventional valuation techniques fail to include many of the financial advantages of clean energy technologies. By omitting benefits associated with risk management, emissions reductions, policy incentives, resource use, corporate social responsibility, and societal economic benefits, investors and firms sacrifice opportunities for new revenue streams and avoided costs. In an effort to identify some of these externalities, this analysis develops a total value proposition for clean energy technologies. It incorporates a series of values under each of the above categories, describing the opportunities for recapturing investments throughout the value chain. The framework may be used to create comparable value propositions for clean energy technologies supporting investment decisions, project siting, and marketing strategies. It can also be useful in policy-making decisions.

Semantic Representatives of the Concept

Directory of Open Access Journals (Sweden)

Elena N. Tsay

2013-01-01

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

System semantics of explanatory dictionaries

Directory of Open Access Journals (Sweden)

Volodymyr Shyrokov

2015-11-01

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

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

Science.gov (United States)

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

2016-01-01

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

Presenting results as dynamically generated co-authorship subgraphs in semantic digital library collections

Directory of Open Access Journals (Sweden)

James Powell

2012-02-01

Full Text Available Semantic web representations of data are by definition graphs, and these graphs can be explored using concepts from graph theory. This paper demonstrates how semantically mapped bibliographic metadata, combined with a lightweight software architecture and Web-based graph visualization tools, can be used to generate dynamic authorship graphs in response to typical user queries, as an alternative to more common text-based results presentations. It also shows how centrality measures and path analysis techniques from social network analysis can be used to enhance the visualization of query results. The resulting graphs require modestly more cognitive engagement from the user but offer insights not available from text.

Semantic Feature Analysis Treatment for Anomia of Two Nonfluent Persian-Speaking Aphasic Patients

Directory of Open Access Journals (Sweden)

Mozhgan Asadi

2014-09-01

Full Text Available Objectives: Semantic Feature Analysis was designed to improve lexical retrieval of aphasic patients via activation of semantic networks of the words. In this approach, the anomic patients are cured with semantic information to assist oral naming. The purpose of this study was to examine the effects of Semantic Feature Analysis treatment on anomia of two nonfluent aphasic patients. Methods: A single-subject study with ABA design was applied to two Persian-speaking patients with chronic nonfluent aphasia. Assessment, baseline, ntervention and maintenance phases were carried out respectively during 6 weeks. A picture naming task which was made up of pictures with high name- agreement comprising 12 target, 18 non-treated control and 5 easy words was used for probes and intervention. Intervention was performed in 5 successive days, 60 minutes per session. Descriptive statistics, level, trend & slope analyses, C and d statistics were used for data analysis. Results: Both participants revealed statistically significant improvements in naming target words. Some generalizations to control words was also occured. A minimal decrease in naming of target words was observed in maintenance phase but the naming ability was still above the baseline. The therapy maintenance effect size for both patients were obtained as medium. Discussion: The findings of the current study seems to confirm Semantic Feature Analysis as an effective intervention for improving naming ability of Persian-speaking aphasic patients.

A Semantic Sensor Web for Environmental Decision Support Applications

Directory of Open Access Journals (Sweden)

Raúl García-Castro

2011-09-01

Full Text Available Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.

The Semantic Web Revisited

OpenAIRE

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

2006-01-01

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

Semantic Search of Web Services

Science.gov (United States)

Hao, Ke

2013-01-01

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

Simulating non-prenex cuts in quantified propositional calculus

Czech Academy of Sciences Publication Activity Database

Jeřábek, Emil; Nguyen, P.

2011-01-01

Roč. 57, č. 5 (2011), s. 524-532 ISSN 0942-5616 R&D Projects: GA AV ČR IAA100190902; GA MŠk(CZ) 1M0545 Institutional research plan: CEZ:AV0Z10190503 Keywords : proof complexity * prenex cuts * quantified propositional calculus Subject RIV: BA - General Mathematics Impact factor: 0.496, year: 2011 http://onlinelibrary.wiley.com/doi/10.1002/malq.201020093/abstract

Network diversity structure, closeness and innovation of South African micro-entrepreneurs

OpenAIRE

Eliada Wosu Griffin-EL

2014-01-01

This study qualitatively explores the embeddedness of the innovation process of South African microbusinesses by investigating how small local entrepreneurs in the Greater Johannesburg area utilise their social networks to source entrepreneurial value. A comparative grounded theory analysis enabled the original conceptualisation of Network Diversity Structure and formulates the central proposition that the network dimensions of diversity and closeness enable the innovation process among manuf...

Propositional Attitudes, Intentionality and Lawful Behaviors

Directory of Open Access Journals (Sweden)

Luiz Henrique de A. Dutra

2003-12-01

Full Text Available This paper aims to discuss Quine’s last analysis of propositional attitudes as involving intentionality and as regards human action and the very subject matter of social sciences. As to this problem, Quine acquiesces in both Davidson’s anomalous monism and Dennett’s intentional stance. An alternative analysis is here presented, which is based on Howard Rachlin’s teleological behaviorism. Some problems regarding this approach are also considered. Intentionality and rationality are still to be saved, but they are construed according to a lawful perspective to human behavior and social contexts of action.

Understanding willingness to pay for social network sites

NARCIS (Netherlands)

Vock, M.; van Dolen, W.; de Ruyter, K.

2013-01-01

The authors investigate how perceived customer value can be translated into economic returns for online social network sites (SNS). The (joint) impact of two value propositions, social capital and entitativity, is assessed. Perceived economic and social customer value are investigated as outcomes of

Magnetoencephalography of frontotemporal dementia: spatiotemporally localized changes during semantic decisions

Science.gov (United States)

Nestor, Peter J.; Hodges, John R.; Rowe, James B.

2011-01-01

Behavioural variant frontotemporal dementia is a neurodegenerative disorder with dysfunction and atrophy of the frontal lobes leading to changes in personality, behaviour, empathy, social conduct and insight, with relative preservation of language and memory. As novel treatments begin to emerge, biomarkers of frontotemporal dementia will become increasingly important, including functionally relevant neuroimaging indices of the neurophysiological basis of cognition. We used magnetoencephalography to examine behavioural variant frontotemporal dementia using a semantic decision task that elicits both frontal and temporal activity in healthy people. Twelve patients with behavioural variant frontotemporal dementia (age 50–75) and 16 matched controls made categorical semantic judgements about 400 pictures during continuous magnetoencephalography. Distributed source analysis was used to compare patients and controls. The patients had normal early responses to picture confrontation, indicating intact visual processing. However, a predominantly posterior set of regions including temporoparietal cortex showed reduced source activity 250–310 ms after stimulus onset, in proportion to behavioural measures of semantic association. In contrast, a left frontoparietal network showed reduced source activity at 550–650 ms, proportional to patients’ deficits in attention and orientation. This late deficit probably reflects impairment in the neural substrate of goal-oriented decision making. The results demonstrate behaviourally relevant neural correlates of semantic processing and decision making in behavioural variant frontotemporal dementia, and show for the first time that magnetoencephalography can be used to study cognitive systems in the context of frontotemporal dementia. PMID:21840892

Using ontology-based semantic similarity to facilitate the article screening process for systematic reviews.

Science.gov (United States)

Ji, Xiaonan; Ritter, Alan; Yen, Po-Yin

2017-05-01

Systematic Reviews (SRs) are utilized to summarize evidence from high quality studies and are considered the preferred source of evidence-based practice (EBP). However, conducting SRs can be time and labor intensive due to the high cost of article screening. In previous studies, we demonstrated utilizing established (lexical) article relationships to facilitate the identification of relevant articles in an efficient and effective manner. Here we propose to enhance article relationships with background semantic knowledge derived from Unified Medical Language System (UMLS) concepts and ontologies. We developed a pipelined semantic concepts representation process to represent articles from an SR into an optimized and enriched semantic space of UMLS concepts. Throughout the process, we leveraged concepts and concept relations encoded in biomedical ontologies (SNOMED-CT and MeSH) within the UMLS framework to prompt concept features of each article. Article relationships (similarities) were established and represented as a semantic article network, which was readily applied to assist with the article screening process. We incorporated the concept of active learning to simulate an interactive article recommendation process, and evaluated the performance on 15 completed SRs. We used work saved over sampling at 95% recall (WSS95) as the performance measure. We compared the WSS95 performance of our ontology-based semantic approach to existing lexical feature approaches and corpus-based semantic approaches, and found that we had better WSS95 in most SRs. We also had the highest average WSS95 of 43.81% and the highest total WSS95 of 657.18%. We demonstrated using ontology-based semantics to facilitate the identification of relevant articles for SRs. Effective concepts and concept relations derived from UMLS ontologies can be utilized to establish article semantic relationships. Our approach provided a promising performance and can easily apply to any SR topics in the

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

DEFF Research Database (Denmark)

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

2009-01-01

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

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

Science.gov (United States)

Wilson, Maximiliano A; Martínez-Cuitiño, Macarena

2012-01-01

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

WPS criterion proposition based on experimental data base interpretation

International Nuclear Information System (INIS)

Chapuliot, S.; Izard, J.P.; Moinereau, D.; Marie, S.

2011-01-01

This article gives the background and the methodology developed to define a K J based criterion for brittle fracture of Reactor Pressure Vessel (RPV) submitted to Pressurized Thermal Shock (PTS), and taking into account Warm Pre Stressing effect (WPS). The first step of this methodology is the constitution of an experimental data base. This work was performed through bibliography and partnerships, and allows merging experimental results dealing with: -) Various ferritic steels; -) Various material states (as received, thermally aged, irradiated...); -) Various mode of fracture (cleavage, inter-granular, mixed mode); -) Various specimen geometry and size (CT, SENB, mock-ups); -) Various thermo-mechanical transients. Based on this experimental data base, a simple K J based limit is proposed and compared to experimental results. Parametric studies are performed in order to define the main parameters of the problem. Finally, a simple proposition based on a detailed analysis of tests results is performed. This proposition giving satisfactory results in every cases, it constitutes a good candidate for integration in French RSE-M code for in service assessment. (authors)

A generalized notion of semantic independence

DEFF Research Database (Denmark)

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

1995-01-01

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

Information report on electricity distribution network security and financing

International Nuclear Information System (INIS)

2011-01-01

This report first outlines the degradation of electricity quality, and identifies the lack of investment as the main reason of the network weakness. It notices that the French network is much extended, and that the medium and low voltage networks need to be secured, and outlines that some legal measures have already been implemented to correct these problems. In its second part, the report comments the network manager's point of view, and denies his critics of the conceding authorities. It also discusses the network manager's investments, and finally formulates six propositions for a better future of the distribution network

Comparing Refinements for Failure and Bisimulation Semantics