Named Entity Recognition for Spanish language and applications in technology forecasting

Directory of Open Access Journals (Sweden)

Raúl Gutiérrez

2015-12-01

Full Text Available Named Entity Recognition (NER is a main task into Natural Language Processing. On the one hand, supporting the extraction of the information on unstructured data. On the other hand, The NER is a probabilistic graphical model that allows us to represent the conditional independency assumptions into the sequential labelling. In this paper, we propose a discriminative graphical model by using linear-chain Conditional Random Fields (CRFs. We present the experiments based on the Conll-2002 shared task and Ancora corpus according to the following criteria: recall, precision and F-score. Our contributions in this work are the following: first, we tested our baseline on the CoNLL-2002 shared task obtaining 80% F1-measure, and 59% F1-measure on AnCora corpus respectively. Finally, the application Vigtech allow us to identify information and patterns in the cancer topic, we discuss the results according to the model performance and the useful information to support the forecasting process

Anatomical entity recognition with a hierarchical framework augmented by external resources.

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Yan Xu

Full Text Available References to anatomical entities in medical records consist not only of explicit references to anatomical locations, but also other diverse types of expressions, such as specific diseases, clinical tests, clinical treatments, which constitute implicit references to anatomical entities. In order to identify these implicit anatomical entities, we propose a hierarchical framework, in which two layers of named entity recognizers (NERs work in a cooperative manner. Each of the NERs is implemented using the Conditional Random Fields (CRF model, which use a range of external resources to generate features. We constructed a dictionary of anatomical entity expressions by exploiting four existing resources, i.e., UMLS, MeSH, RadLex and BodyPart3D, and supplemented information from two external knowledge bases, i.e., Wikipedia and WordNet, to improve inference of anatomical entities from implicit expressions. Experiments conducted on 300 discharge summaries showed a micro-averaged performance of 0.8509 Precision, 0.7796 Recall and 0.8137 F1 for explicit anatomical entity recognition, and 0.8695 Precision, 0.6893 Recall and 0.7690 F1 for implicit anatomical entity recognition. The use of the hierarchical framework, which combines the recognition of named entities of various types (diseases, clinical tests, treatments with information embedded in external knowledge bases, resulted in a 5.08% increment in F1. The resources constructed for this research will be made publicly available.

ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering

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Ren, Xiang; El-Kishky, Ahmed; Wang, Chi; Tao, Fangbo; Voss, Clare R.; Ji, Heng; Han, Jiawei

2015-01-01

Entity recognition is an important but challenging research problem. In reality, many text collections are from specific, dynamic, or emerging domains, which poses significant new challenges for entity recognition with increase in name ambiguity and context sparsity, requiring entity detection without domain restriction. In this paper, we investigate entity recognition (ER) with distant-supervision and propose a novel relation phrase-based ER framework, called ClusType, that runs data-driven phrase mining to generate entity mention candidates and relation phrases, and enforces the principle that relation phrases should be softly clustered when propagating type information between their argument entities. Then we predict the type of each entity mention based on the type signatures of its co-occurring relation phrases and the type indicators of its surface name, as computed over the corpus. Specifically, we formulate a joint optimization problem for two tasks, type propagation with relation phrases and multi-view relation phrase clustering. Our experiments on multiple genres—news, Yelp reviews and tweets—demonstrate the effectiveness and robustness of ClusType, with an average of 37% improvement in F1 score over the best compared method. PMID:26705503

Named Entity Recognition in a Hungarian NL Based QA System

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Tikkl, Domonkos; Szidarovszky, P. Ferenc; Kardkovacs, Zsolt T.; Magyar, Gábor

In WoW project our purpose is to create a complex search interface with the following features: search in the deep web content of contracted partners' databases, processing Hungarian natural language (NL) questions and transforming them to SQL queries for database access, image search supported by a visual thesaurus that describes in a structural form the visual content of images (also in Hungarian). This paper primarily focuses on a particular problem of question processing task: the entity recognition. Before going into details we give a short overview of the project's aims.

Entity recognition from clinical texts via recurrent neural network.

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Liu, Zengjian; Yang, Ming; Wang, Xiaolong; Chen, Qingcai; Tang, Buzhou; Wang, Zhe; Xu, Hua

2017-07-05

Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities and protected health information (PHI), widely exist in clinical texts. Recognizing these entities has become a hot topic in clinical natural language processing (NLP), and a large number of traditional machine learning methods, such as support vector machine and conditional random field, have been deployed to recognize entities from clinical texts in the past few years. In recent years, recurrent neural network (RNN), one of deep learning methods that has shown great potential on many problems including named entity recognition, also has been gradually used for entity recognition from clinical texts. In this paper, we comprehensively investigate the performance of LSTM (long-short term memory), a representative variant of RNN, on clinical entity recognition and protected health information recognition. The LSTM model consists of three layers: input layer - generates representation of each word of a sentence; LSTM layer - outputs another word representation sequence that captures the context information of each word in this sentence; Inference layer - makes tagging decisions according to the output of LSTM layer, that is, outputting a label sequence. Experiments conducted on corpora of the 2010, 2012 and 2014 i2b2 NLP challenges show that LSTM achieves highest micro-average F1-scores of 85.81% on the 2010 i2b2 medical concept extraction, 92.29% on the 2012 i2b2 clinical event detection, and 94.37% on the 2014 i2b2 de-identification, which is considerably competitive with other state-of-the-art systems. LSTM that requires no hand-crafted feature has great potential on entity recognition from clinical texts. It outperforms traditional machine learning methods that suffer from fussy feature engineering. A possible future direction is how to integrate knowledge

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

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Urbain, Jay

2015-12-01

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

Named-Entity Tagging a Very Large Unbalanced Corpus. Training and Evaluating NE classifiers

DEFF Research Database (Denmark)

Bingel, Joachim; Haider, Thomas

2014-01-01

We describe a systematic and application-oriented approach to training and evaluating named entity recognition and classification (NERC) systems, the purpose of which is to identify an optimal system and to train an optimal model for named entity tagging DeReKo, a very large general-purpose corpus...... when evaluated on more uniform and less diverse data. We create and manually annotate such a representative sample as evaluation data for three different NERC systems, for each of which various models are learnt on multiple training data. The proposed sampling method can be viewed as a generally...

Indexing concepts and/or named entities Indicizzare concetti e/o named entities

Directory of Open Access Journals (Sweden)

Pino Buizza

2011-12-01

Full Text Available

A partire da un punto di vista semantico più che morfologico, l'articolo è focalizzato il problema del significato dei nomi propri, con contributi della filosofia del linguaggio e della linguistica semantica. Sono indagate le entità individuali: il loro isolamento all’interno della rete di soggetti e la relazione esemplificativa, il trattamento nelle classificazioni. Le profonde diversità rilevate fra concetti e entità denominate suggeriscono di dichiararle esplicitamente da un punto di vista teorico e di adottare dispositivi che diano risultati unitari ma chiaramente distinguibili nei sistemi di recupero dell’informazione.  
Questo contributo è stato presentato col titolo Indexing concepts and/or named entities all'11th ISKO Conference, Paradigms and conceptual systems in knowledge organization, Roma, 23-26 febbraio 2010, non pubblicato negli atti, e qui leggermente ampliato.

Named Entity Linking Algorithm

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M. F. Panteleev

2017-01-01

Full Text Available In the tasks of processing text in natural language, Named Entity Linking (NEL represents the task to define and link some entity, which is found in the text, with some entity in the knowledge base (for example, Dbpedia. Currently, there is a diversity of approaches to solve this problem, but two main classes can be identified: graph-based approaches and machine learning-based ones. Graph and Machine Learning approaches-based algorithm is proposed accordingly to the stated assumptions about the interrelations of named entities in a sentence and in general.In the case of graph-based approaches, it is necessary to solve the problem of identifying an optimal set of the related entities according to some metric that characterizes the distance between these entities in a graph built on some knowledge base. Due to limitations in processing power, to solve this task directly is impossible. Therefore, its modification is proposed. Based on the algorithms of machine learning, an independent solution cannot be built due to small volumes of training datasets relevant to NEL task. However, their use can contribute to improving the quality of the algorithm. The adaptation of the Latent Dirichlet Allocation model is proposed in order to obtain a measure of the compatibility of attributes of various entities encountered in one context.The efficiency of the proposed algorithm was experimentally tested. A test dataset was independently generated. On its basis the performance of the model was compared using the proposed algorithm with the open source product DBpedia Spotlight, which solves the NEL problem.The mockup, based on the proposed algorithm, showed a low speed as compared to DBpedia Spotlight. However, the fact that it has shown higher accuracy, stipulates the prospects for work in this direction.The main directions of development were proposed in order to increase the accuracy of the system and its productivity.

Entity recognition in the biomedical domain using a hybrid approach.

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Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

LeadMine: a grammar and dictionary driven approach to entity recognition

Science.gov (United States)

2015-01-01

Background Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Results Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Conclusions Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution. PMID:25810776

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition.

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Tsai, Richard Tzong-Han; Sung, Cheng-Lung; Dai, Hong-Jie; Hung, Hsieh-Chuan; Sung, Ting-Yi; Hsu, Wen-Lian

2006-12-18

Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. To develop our ML-based Bio-NER system, we employ conditional

Disease named entity recognition from biomedical literature using a novel convolutional neural network.

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Zhao, Zhehuan; Yang, Zhihao; Luo, Ling; Wang, Lei; Zhang, Yin; Lin, Hongfei; Wang, Jian

2017-12-28

Automatic disease named entity recognition (DNER) is of utmost importance for development of more sophisticated BioNLP tools. However, most conventional CRF based DNER systems rely on well-designed features whose selection is labor intensive and time-consuming. Though most deep learning methods can solve NER problems with little feature engineering, they employ additional CRF layer to capture the correlation information between labels in neighborhoods which makes them much complicated. In this paper, we propose a novel multiple label convolutional neural network (MCNN) based disease NER approach. In this approach, instead of the CRF layer, a multiple label strategy (MLS) first introduced by us, is employed. First, the character-level embedding, word-level embedding and lexicon feature embedding are concatenated. Then several convolutional layers are stacked over the concatenated embedding. Finally, MLS strategy is applied to the output layer to capture the correlation information between neighboring labels. As shown by the experimental results, MCNN can achieve the state-of-the-art performance on both NCBI and CDR corpora. The proposed MCNN based disease NER method achieves the state-of-the-art performance with little feature engineering. And the experimental results show the MLS strategy's effectiveness of capturing the correlation information between labels in the neighborhood.

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition

Directory of Open Access Journals (Sweden)

Hung Hsieh-Chuan

2006-12-01

Full Text Available Abstract Background Biomedical named entity recognition (Bio-NER is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized and at least one class tag (e.g., B-protein, the beginning of a protein name. However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2 cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words. We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. Results To develop our ML

Developing a hybrid dictionary-based bio-entity recognition technique

Science.gov (United States)

2015-01-01

Background Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. Methods This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. Results The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. Conclusions The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall. PMID:26043907

Developing a hybrid dictionary-based bio-entity recognition technique.

Science.gov (United States)

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2015-01-01

Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall.

Recognition of chemical entities: combining dictionary-based and grammar-based approaches

Science.gov (United States)

2015-01-01

Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named

Recognition of chemical entities: combining dictionary-based and grammar-based approaches.

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Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A

2015-01-01

The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming

A method for named entity normalization in biomedical articles: application to diseases and plants.

Science.gov (United States)

Cho, Hyejin; Choi, Wonjun; Lee, Hyunju

2017-10-13

In biomedical articles, a named entity recognition (NER) technique that identifies entity names from texts is an important element for extracting biological knowledge from articles. After NER is applied to articles, the next step is to normalize the identified names into standard concepts (i.e., disease names are mapped to the National Library of Medicine's Medical Subject Headings disease terms). In biomedical articles, many entity normalization methods rely on domain-specific dictionaries for resolving synonyms and abbreviations. However, the dictionaries are not comprehensive except for some entities such as genes. In recent years, biomedical articles have accumulated rapidly, and neural network-based algorithms that incorporate a large amount of unlabeled data have shown considerable success in several natural language processing problems. In this study, we propose an approach for normalizing biological entities, such as disease names and plant names, by using word embeddings to represent semantic spaces. For diseases, training data from the National Center for Biotechnology Information (NCBI) disease corpus and unlabeled data from PubMed abstracts were used to construct word representations. For plants, a training corpus that we manually constructed and unlabeled PubMed abstracts were used to represent word vectors. We showed that the proposed approach performed better than the use of only the training corpus or only the unlabeled data and showed that the normalization accuracy was improved by using our model even when the dictionaries were not comprehensive. We obtained F-scores of 0.808 and 0.690 for normalizing the NCBI disease corpus and manually constructed plant corpus, respectively. We further evaluated our approach using a data set in the disease normalization task of the BioCreative V challenge. When only the disease corpus was used as a dictionary, our approach significantly outperformed the best system of the task. The proposed approach shows robust

Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization.

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Dai, Hong-Jie; Lai, Po-Ting; Chang, Yung-Chun; Tsai, Richard Tzong-Han

2015-01-01

The functions of chemical compounds and drugs that affect biological processes and their particular effect on the onset and treatment of diseases have attracted increasing interest with the advancement of research in the life sciences. To extract knowledge from the extensive literatures on such compounds and drugs, the organizers of BioCreative IV administered the CHEMical Compound and Drug Named Entity Recognition (CHEMDNER) task to establish a standard dataset for evaluating state-of-the-art chemical entity recognition methods. This study introduces the approach of our CHEMDNER system. Instead of emphasizing the development of novel feature sets for machine learning, this study investigates the effect of various tag schemes on the recognition of the names of chemicals and drugs by using conditional random fields. Experiments were conducted using combinations of different tokenization strategies and tag schemes to investigate the effects of tag set selection and tokenization method on the CHEMDNER task. This study presents the performance of CHEMDNER of three more representative tag schemes-IOBE, IOBES, and IOB12E-when applied to a widely utilized IOB tag set and combined with the coarse-/fine-grained tokenization methods. The experimental results thus reveal that the fine-grained tokenization strategy performance best in terms of precision, recall and F-scores when the IOBES tag set was utilized. The IOBES model with fine-grained tokenization yielded the best-F-scores in the six chemical entity categories other than the "Multiple" entity category. Nonetheless, no significant improvement was observed when a more representative tag schemes was used with the coarse or fine-grained tokenization rules. The best F-scores that were achieved using the developed system on the test dataset of the CHEMDNER task were 0.833 and 0.815 for the chemical documents indexing and the chemical entity mention recognition tasks, respectively. The results herein highlight the importance

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text.

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Zhu, Qile; Li, Xiaolin; Conesa, Ana; Pereira, Cécile

2018-05-01

Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networks achieve state-of-the-art performance without hand-crafted features and task-specific knowledge in non-biomedical NER tasks. However, in the biomedical domain, using the same architecture does not yield competitive performance compared with conventional machine learning models. We propose a novel end-to-end deep learning approach for biomedical NER tasks that leverages the local contexts based on n-gram character and word embeddings via Convolutional Neural Network (CNN). We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not require any specific knowledge or feature engineering and can be theoretically applied to a wide range of existing NER problems. The GRAM-CNN approach was evaluated on three well-known biomedical datasets containing different BioNER entities. It obtained an F1-score of 87.26% on the Biocreative II dataset, 87.26% on the NCBI dataset and 72.57% on the JNLPBA dataset. Those results put GRAM-CNN in the lead of the biological NER methods. To the best of our knowledge, we are the first to apply CNN based structures to BioNER problems. The GRAM-CNN source code, datasets and pre-trained model are available online at: https://github.com/valdersoul/GRAM-CNN. andyli@ece.ufl.edu or aconesa@ufl.edu. Supplementary data are available at Bioinformatics online.

Network analysis of named entity co-occurrences in written texts

Science.gov (United States)

Amancio, Diego Raphael

2016-06-01

The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical and semantical networks, only a few works have probed the relevance of investigating the structure arising from the relationship between relevant entities such as characters, locations and organizations. In this study, we represent entities appearing in the same context as a co-occurrence network, where links are established according to a null model based on random, shuffled texts. Computational simulations performed in novels revealed that the proposed model displays interesting topological features, such as the small world feature, characterized by high values of clustering coefficient. The effectiveness of our model was verified in a practical pattern recognition task in real networks. When compared with traditional word adjacency networks, our model displayed optimized results in identifying unknown references in texts. Because the proposed representation plays a complementary role in characterizing unstructured documents via topological analysis of named entities, we believe that it could be useful to improve the characterization of written texts (and related systems), specially if combined with traditional approaches based on statistical and deeper paradigms.

A generic open world named entity disambiguation approach for tweets

NARCIS (Netherlands)

Habib, Mena Badieh; van Keulen, Maurice

Social media is a rich source of information. To make use of this information, it is sometimes required to extract and disambiguate named entities. In this paper we focus on named entity disambiguation (NED) in twitter messages. NED in tweets is challenging in two ways. First, the limited length of

Enhanced Named Entity Extraction via Error-Driven Aggregation

Energy Technology Data Exchange (ETDEWEB)

Lemmond, T D; Perry, N C; Guensche, J W; Nitao, J J; Glaser, R E; Kidwell, P; Hanley, W G

2010-02-22

Despite recent advances in named entity extraction technologies, state-of-the-art extraction tools achieve insufficient accuracy rates for practical use in many operational settings. However, they are not generally prone to the same types of error, suggesting that substantial improvements may be achieved via appropriate combinations of existing tools, provided their behavior can be accurately characterized and quantified. In this paper, we present an inference methodology for the aggregation of named entity extraction technologies that is founded upon a black-box analysis of their respective error processes. This method has been shown to produce statistically significant improvements in extraction relative to standard performance metrics and to mitigate the weak performance of entity extractors operating under suboptimal conditions. Moreover, this approach provides a framework for quantifying uncertainty and has demonstrated the ability to reconstruct the truth when majority voting fails.

Concrete Security for Entity Recognition: The Jane Doe Protocol

DEFF Research Database (Denmark)

Lucks, Stefan; Zenner, Erik; Weimerskirch, Andre

2008-01-01

Entity recognition does not ask whether the message is from some entity X, just whether a message is from the same entity as a previous message. This turns turns out to be very useful for low-end devices. The current paper proposes a new protocol – the “Jane Doe Protocol” –, and provides a formal...

Untangling the brand name from the branded entity

OpenAIRE

Round, Griff; Roper, Stuart

2015-01-01

Purpose\\ud – The purpose of this study is to investigate the value to consumers of the brand name element for established brands, given that the focus in the literature has been on new brands. To accomplish this, conceptual development was initially undertaken to illuminate the links between the brand name element and the brand entity and to provide a theoretical framework for looking at changes in value of the brand name element to consumers over time.\\ud \\ud Design/methodology/approach\\ud –...

Named entity extraction and disambiguation: the missing link

NARCIS (Netherlands)

Habib, Mena Badieh; van Keulen, Maurice

2013-01-01

Named entity extraction (NEE) and disambiguation (NED) are two areas of research that are well covered in literature. Typical fields addressing these topics are information retrieval, natural language processing, and semantic web. Although these topics are highly dependent, almost no existing works

TwitterNEED: a hybrid approach for named entity extraction and disambiguation for tweets

NARCIS (Netherlands)

Habib, Mena Badieh; van Keulen, Maurice

Twitter is a rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing tasks. In this paper, we present TwitterNEED, a hybrid approach for Named Entity Extraction and Named Entity Disambiguation for tweets. We

A study of active learning methods for named entity recognition in clinical text.

Science.gov (United States)

Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

2015-12-01

Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random

Use of global context for handling noisy names in discussion texts of a homeopathy discussion forum

Directory of Open Access Journals (Sweden)

Mukta Majumder

2014-03-01

Full Text Available The task of identifying named entities from the discussion texts in Web forums faces the challenge of noisy names. As the names are often misspelled or abbreviated, the conventional techniques have failed to detect the noisy names properly. In this paper we propose a global context based framework for handling the noisy names. The framework is tested on a named entity recognition system designed to identify the names from the discussion texts in a homeopathy diagnosis discussion forum. The proposed global context-based framework is found to be effective in improving the accuracy of the named entity recognition system.

FamPlex: a resource for entity recognition and relationship resolution of human protein families and complexes in biomedical text mining.

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Bachman, John A; Gyori, Benjamin M; Sorger, Peter K

2018-06-28

For automated reading of scientific publications to extract useful information about molecular mechanisms it is critical that genes, proteins and other entities be correctly associated with uniform identifiers, a process known as named entity linking or "grounding." Correct grounding is essential for resolving relationships among mined information, curated interaction databases, and biological datasets. The accuracy of this process is largely dependent on the availability of machine-readable resources associating synonyms and abbreviations commonly found in biomedical literature with uniform identifiers. In a task involving automated reading of ∼215,000 articles using the REACH event extraction software we found that grounding was disproportionately inaccurate for multi-protein families (e.g., "AKT") and complexes with multiple subunits (e.g."NF- κB"). To address this problem we constructed FamPlex, a manually curated resource defining protein families and complexes as they are commonly encountered in biomedical text. In FamPlex the gene-level constituents of families and complexes are defined in a flexible format allowing for multi-level, hierarchical membership. To create FamPlex, text strings corresponding to entities were identified empirically from literature and linked manually to uniform identifiers; these identifiers were also mapped to equivalent entries in multiple related databases. FamPlex also includes curated prefix and suffix patterns that improve named entity recognition and event extraction. Evaluation of REACH extractions on a test corpus of ∼54,000 articles showed that FamPlex significantly increased grounding accuracy for families and complexes (from 15 to 71%). The hierarchical organization of entities in FamPlex also made it possible to integrate otherwise unconnected mechanistic information across families, subfamilies, and individual proteins. Applications of FamPlex to the TRIPS/DRUM reading system and the Biocreative VI Bioentity

Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition.

Science.gov (United States)

Jauregi Unanue, Iñigo; Zare Borzeshi, Ehsan; Piccardi, Massimo

2017-12-01

Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word "embeddings". (i) To create a highly accurate DNR and CCE system that avoids conventional, time-consuming feature engineering. (ii) To create richer, more specialized word embeddings by using health domain datasets such as MIMIC-III. (iii) To evaluate our systems over three contemporary datasets. Two deep learning methods, namely the Bidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF model is set as the baseline to compare the deep learning systems to a traditional machine learning approach. The same features are used for all the models. We have obtained the best results with the Bidirectional LSTM-CRF model, which has outperformed all previously proposed systems. The specialized embeddings have helped to cover unusual words in DrugBank and MedLine, but not in the i2b2/VA dataset. We present a state-of-the-art system for DNR and CCE. Automated word embeddings has allowed us to avoid costly feature engineering and achieve higher accuracy. Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary. Copyright © 2017 Elsevier Inc. All rights reserved.

Recognition of names of eminent psychologists.

Science.gov (United States)

Duncan, C P

1976-10-01

Faculty members, graduate students, undergraduate majors, and introductory psychology students checked those names they recognized in the list of 228 deceased psychologists, rated for eminence, provided by Annin, Boring, and Watson. Mean percentage recognition was less than 50% for the 128 American psychologists, and less than 25% for the 100 foreign psychologists, by the faculty subjects. The other three groups of subjects gave even lower recognition scores. Recognition was probably also influenced by recency; median year of death of the American psychologists was 1955, of the foreign psychologists, 1943. High recognition (defined as recognition by 80% or more of the faculty group) was achieved by only 34 psychologists, almost all of them American. These highly recognized psychologists also had high eminence ratings, but there was an equal number of psychologists with high eminence ratings that were poorly recognized.

Network and Ensemble Enabled Entity Extraction in Informal Text (NEEEEIT) final report

Energy Technology Data Exchange (ETDEWEB)

Kegelmeyer, Philip W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Shead, Timothy M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dunlavy, Daniel M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2013-09-01

This SAND report summarizes the activities and outcomes of the Network and Ensemble Enabled Entity Extraction in Information Text (NEEEEIT) LDRD project, which addressed improving the accuracy of conditional random fields for named entity recognition through the use of ensemble methods.

Recognition of Famous Names in Psychology by Students and Staff.

Science.gov (United States)

Bunnell, Julie K.

1992-01-01

Presents results of a name recognition questionnaire testing the historical awareness of psychology majors and faculty members. Reports that students showed a low level of name recognition prior to taking a course in the history of psychology. Concludes that explicit instruction is required to impart knowledge of the history of the discipline. (DK)

NEED4Tweet: A Twitterbot for Tweets Named Entity Extraction and Disambiguation

NARCIS (Netherlands)

Habib, Mena Badieh; van Keulen, Maurice

In this demo paper, we present NEED4Tweet, a Twitterbot for named entity extraction (NEE) and disambiguation (NED) for Tweets. The straightforward application of state-of-the-art extraction and disambiguation approaches on informal text widely used in Tweets, typically results in significantly

Named Entity Extraction and Linking Challenge: University of Twente at #Microposts2014

NARCIS (Netherlands)

Habib, Mena Badieh; van Keulen, Maurice; Zhu, Zhemin; Rowe, Matthew; Stankovic, Milan; Dadzie, Aba-Sah

Twitter is a potentially rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing (NLP) tasks. In this paper, we present a hybrid approach for Named Entity Extraction (NEE)and Linking (NEL) for tweets. Although

The Claim Tool Kit for ad hoc recognition of peer entities

DEFF Research Database (Denmark)

Seigneur, Jean-Marc; Jensen, Christian D.

2005-01-01

In ubiquitous/pervasive computing environments, it is envisaged that computing elements—entities—will start interacting in an ad hoc fashion. The peer-to-peer (p2p) paradigm is appealing for such types of interaction especially with JXTA, which supports the development of reusable p2p building...... blocks, which facilitate implementation on any smart device. However, the inability to rely on a centralised authentication infrastructure, the openness of the environment and the absence of an administrator (it is assumed to be too expensive to have a skilled administrator at hand due to the large...... number of peers) challenge the use of legacy authentication mechanisms. Supporting spontaneous interactions among previously unknown entities requires dynamic enrolment of strangers and unknown entities. Entity recognition (ER) is a process that is carried out each time an interaction happens between...

Fluency Effects on Brand Name Recognition and Preference

DEFF Research Database (Denmark)

Erz, Antonia; Christensen, Bo

2014-01-01

Existing research has not provided a clear understanding of processing fluency effects on memory. In a laboratory experiment with novel non-words, we found a recognition advantage of fluent non-words over moderately fluent and disfluent non-words. This advantage diminished when non-words were...... presented as novel brand names in different product contexts. We further tested a preference reversal in favor of disfluency and found that disfluent brand names (non-words) were equally disliked across different products contexts. A preference reversal could be observed when fluent names were preferred...

Does humor in radio advertising affect recognition of novel product brand names?

Science.gov (United States)

Berg, E M; Lippman, L G

2001-04-01

The authors proposed that item selection during shopping is based on brand name recognition rather than recall. College students rated advertisements and news stories of a simulated radio program for level of amusement (orienting activity) before participating in a surprise recognition test. Humor level of the advertisements was varied systematically, and content was controlled. According to signal detection analysis, humor did not affect the strength of recognition memory for brand names (nonsense units). However, brand names and product types were significantly more likely to be associated when appearing in humorous advertisements than in nonhumorous advertisements. The results are compared with prior findings concerning humor and recall.

Semantic representation of scientific literature: bringing claims, contributions and named entities onto the Linked Open Data cloud

Directory of Open Access Journals (Sweden)

Bahar Sateli

2015-12-01

Full Text Available Motivation. Finding relevant scientific literature is one of the essential tasks researchers are facing on a daily basis. Digital libraries and web information retrieval techniques provide rapid access to a vast amount of scientific literature. However, no further automated support is available that would enable fine-grained access to the knowledge ‘stored’ in these documents. The emerging domain of Semantic Publishing aims at making scientific knowledge accessible to both humans and machines, by adding semantic annotations to content, such as a publication’s contributions, methods, or application domains. However, despite the promises of better knowledge access, the manual annotation of existing research literature is prohibitively expensive for wide-spread adoption. We argue that a novel combination of three distinct methods can significantly advance this vision in a fully-automated way: (i Natural Language Processing (NLP for Rhetorical Entity (RE detection; (ii Named Entity (NE recognition based on the Linked Open Data (LOD cloud; and (iii automatic knowledge base construction for both NEs and REs using semantic web ontologies that interconnect entities in documents with the machine-readable LOD cloud.Results. We present a complete workflow to transform scientific literature into a semantic knowledge base, based on the W3C standards RDF and RDFS. A text mining pipeline, implemented based on the GATE framework, automatically extracts rhetorical entities of type Claims and Contributions from full-text scientific literature. These REs are further enriched with named entities, represented as URIs to the linked open data cloud, by integrating the DBpedia Spotlight tool into our workflow. Text mining results are stored in a knowledge base through a flexible export process that provides for a dynamic mapping of semantic annotations to LOD vocabularies through rules stored in the knowledge base. We created a gold standard corpus from computer

Recognition of cigarette brand names and logos by primary schoolchildren in Ankara, Turkey.

Science.gov (United States)

Emri, S; Bağci, T; Karakoca, Y; Bariş, E

1998-01-01

To assess the smoking behaviour of primary schoolchildren and their ability to recognise brand names and logos of widely advertised cigarettes, compared with other commercial products intended for children. Cross-sectional survey in classroom settings using a questionnaire designed to measure attitudes towards smoking and the recognition of brand names and logos for 16 food, beverage, cigarette, and toothpaste products. Ankara, Turkey. 1093 children (54.6% boys, 44.4% girls) aged 7-13 years (mean = 10, SD = 1), from grades 2-5. The student sample was taken from three primary schools--one school in each of three residential districts representing high, middle, and low income populations. Prevalence of ever-smoking, recognition of brand names and logos. Prevalence of ever-smoking was 11.7% overall (13.9% among boys and 9.1% among girls; p Brand recognition rates ranged from 58.1% for Chee-tos (a food product) to 95.2% for Samsun (a Turkish cigarette brand). Recognition rates for cigarette brand names and logos were 95.2% and 80.8%, respectively, for Samsun; 84.0% and 90.5%, respectively, for Camel; and 92.1% and 69.5%, respectively, for Marlboro. The Camel logo and the Samsun and Marlboro brand names were the most highly recognised of all product logos and brand names tested. The high recognition of cigarette brand names and logos is most likely the result of tobacco advertising and promotion. Our results indicate the need to implement comprehensive tobacco control measures in Turkey.

Automatic Recognition of Chinese Personal Name Using Conditional Random Fields and Knowledge Base

Directory of Open Access Journals (Sweden)

Chuan Gu

2015-01-01

Full Text Available According to the features of Chinese personal name, we present an approach for Chinese personal name recognition based on conditional random fields (CRF and knowledge base in this paper. The method builds multiple features of CRF model by adopting Chinese character as processing unit, selects useful features based on selection algorithm of knowledge base and incremental feature template, and finally implements the automatic recognition of Chinese personal name from Chinese document. The experimental results on open real corpus demonstrated the effectiveness of our method and obtained high accuracy rate and high recall rate of recognition.

Phonological Awareness and Naming Speed in the Prediction of Dutch Children's Word Recognition

Science.gov (United States)

Verhagen, W.; Aarnoutse, C.; van Leeuwe, J.

2008-01-01

Influences of phonological awareness and naming speed on the speed and accuracy of Dutch children's word recognition were investigated in a longitudinal study. The speed and accuracy of word recognition at the ends of Grades 1 and 2 were predicted by naming speed from both the beginning and end of Grade 1, after control for autoregressive…

False recall and recognition of brand names increases over time.

Science.gov (United States)

Sherman, Susan M

2013-01-01

Using the Deese-Roediger-McDermott (DRM) paradigm, participants are presented with lists of associated words (e.g., bed, awake, night). Subsequently, they reliably have false memories for related but nonpresented words (e.g., SLEEP). Previous research has found that false memories can be created for brand names (e.g., Morrisons, Sainsbury's, Waitrose, and TESCO). The present study investigates the effect of a week's delay on false memories for brand names. Participants were presented with lists of brand names followed by a distractor task. In two between-subjects experiments, participants completed a free recall task or a recognition task either immediately or a week later. In two within-subjects experiments, participants completed a free recall task or a recognition task both immediately and a week later. Correct recall for presented list items decreased over time, whereas false recall for nonpresented lure items increased. For recognition, raw scores revealed an increase in false memory across time reflected in an increase in Remember responses. Analysis of Pr scores revealed that false memory for lures stayed constant over a week, but with an increase in Remember responses in the between-subjects experiment and a trend in the same direction in the within-subjects experiment. Implications for theories of false memory are discussed.

Gene name ambiguity of eukaryotic nomenclatures.

Science.gov (United States)

Chen, Lifeng; Liu, Hongfang; Friedman, Carol

2005-01-15

With more and more scientific literature published online, the effective management and reuse of this knowledge has become problematic. Natural language processing (NLP) may be a potential solution by extracting, structuring and organizing biomedical information in online literature in a timely manner. One essential task is to recognize and identify genomic entities in text. 'Recognition' can be accomplished using pattern matching and machine learning. But for 'identification' these techniques are not adequate. In order to identify genomic entities, NLP needs a comprehensive resource that specifies and classifies genomic entities as they occur in text and that associates them with normalized terms and also unique identifiers so that the extracted entities are well defined. Online organism databases are an excellent resource to create such a lexical resource. However, gene name ambiguity is a serious problem because it affects the appropriate identification of gene entities. In this paper, we explore the extent of the problem and suggest ways to address it. We obtained gene information from 21 organisms and quantified naming ambiguities within species, across species, with English words and with medical terms. When the case (of letters) was retained, official symbols displayed negligible intra-species ambiguity (0.02%) and modest ambiguities with general English words (0.57%) and medical terms (1.01%). In contrast, the across-species ambiguity was high (14.20%). The inclusion of gene synonyms increased intra-species ambiguity substantially and full names contributed greatly to gene-medical-term ambiguity. A comprehensive lexical resource that covers gene information for the 21 organisms was then created and used to identify gene names by using a straightforward string matching program to process 45,000 abstracts associated with the mouse model organism while ignoring case and gene names that were also English words. We found that 85.1% of correctly retrieved mouse

The SPECIES and ORGANISMS Resources for Fast and Accurate Identification of Taxonomic Names in Text

DEFF Research Database (Denmark)

Pafilis, Evangelos; Pletscher-Frankild, Sune; Fanini, Lucia

2013-01-01

The exponential growth of the biomedical literature is making the need for efficient, accurate text-mining tools increasingly clear. The identification of named biological entities in text is a central and difficult task. We have developed an efficient algorithm and implementation of a dictionary......-based approach to named entity recognition, which we here use to identify names of species and other taxa in text. The tool, SPECIES, is more than an order of magnitude faster and as accurate as existing tools. The precision and recall was assessed both on an existing gold-standard corpus and on a new corpus...

The Predictive Power of Phonemic Awareness and Naming Speed for Early Dutch Word Recognition

Science.gov (United States)

Verhagen, Wim G. M.; Aarnoutse, Cor A. J.; van Leeuwe, Jan F. J.

2009-01-01

Effects of phonemic awareness and naming speed on the speed and accuracy of Dutch children's word recognition were investigated in a longitudinal study. Both the speed and accuracy of word recognition at the end of Grade 2 were predicted by naming speed from both kindergarten and Grade 1, after control for autoregressive relations, kindergarten…

Chemical entity recognition in patents by combining dictionary-based and statistical approaches

Science.gov (United States)

Akhondi, Saber A.; Pons, Ewoud; Afzal, Zubair; van Haagen, Herman; Becker, Benedikt F.H.; Hettne, Kristina M.; van Mulligen, Erik M.; Kors, Jan A.

2016-01-01

We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Passage Detection (CPD) classification task. We addressed both tasks by an ensemble system that combines a dictionary-based approach with a statistical one. For this purpose the performance of several lexical resources was assessed using Peregrine, our open-source indexing engine. We combined our dictionary-based results on the patent corpus with the results of tmChem, a chemical recognizer using a conditional random field classifier. To improve the performance of tmChem, we utilized three additional features, viz. part-of-speech tags, lemmas and word-vector clusters. When evaluated on the training data, our final system obtained an F-score of 85.21% for the CEMP task, and an accuracy of 91.53% for the CPD task. On the test set, the best system ranked sixth among 21 teams for CEMP with an F-score of 86.82%, and second among nine teams for CPD with an accuracy of 94.23%. The differences in performance between the best ensemble system and the statistical system separately were small. Database URL: http://biosemantics.org/chemdner-patents PMID:27141091

REDEN: Named Entity Linking in Digital Literary Editions Using Linked Data Sets

Directory of Open Access Journals (Sweden)

Carmen Brando

2016-07-01

Full Text Available This paper proposes a graph-based Named Entity Linking (NEL algorithm named REDEN for the disambiguation of authors’ names in French literary criticism texts and scientific essays from the 19th and early 20th centuries. The algorithm is described and evaluated according to the two phases of NEL as reported in current state of the art, namely, candidate retrieval and candidate selection. REDEN leverages knowledge from different Linked Data sources in order to select candidates for each author mention, subsequently crawls data from other Linked Data sets using equivalence links (e.g., owl:sameAs, and, finally, fuses graphs of homologous individuals into a non-redundant graph well-suited for graph centrality calculation; the resulting graph is used for choosing the best referent. The REDEN algorithm is distributed in open-source and follows current standards in digital editions (TEI and semantic Web (RDF. Its integration into an editorial workflow of digital editions in Digital humanities and cultural heritage projects is entirely plausible. Experiments are conducted along with the corresponding error analysis in order to test our approach and to help us to study the weaknesses and strengths of our algorithm, thereby to further improvements of REDEN.

Chemical entity recognition in patents by combining dictionary-based and statistical approaches.

Science.gov (United States)

Akhondi, Saber A; Pons, Ewoud; Afzal, Zubair; van Haagen, Herman; Becker, Benedikt F H; Hettne, Kristina M; van Mulligen, Erik M; Kors, Jan A

2016-01-01

We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Passage Detection (CPD) classification task. We addressed both tasks by an ensemble system that combines a dictionary-based approach with a statistical one. For this purpose the performance of several lexical resources was assessed using Peregrine, our open-source indexing engine. We combined our dictionary-based results on the patent corpus with the results of tmChem, a chemical recognizer using a conditional random field classifier. To improve the performance of tmChem, we utilized three additional features, viz. part-of-speech tags, lemmas and word-vector clusters. When evaluated on the training data, our final system obtained an F-score of 85.21% for the CEMP task, and an accuracy of 91.53% for the CPD task. On the test set, the best system ranked sixth among 21 teams for CEMP with an F-score of 86.82%, and second among nine teams for CPD with an accuracy of 94.23%. The differences in performance between the best ensemble system and the statistical system separately were small.Database URL: http://biosemantics.org/chemdner-patents. © The Author(s) 2016. Published by Oxford University Press.

A document processing pipeline for annotating chemical entities in scientific documents.

Science.gov (United States)

Campos, David; Matos, Sérgio; Oliveira, José L

2015-01-01

The recognition of drugs and chemical entities in text is a very important task within the field of biomedical information extraction, given the rapid growth in the amount of published texts (scientific papers, patents, patient records) and the relevance of these and other related concepts. If done effectively, this could allow exploiting such textual resources to automatically extract or infer relevant information, such as drug profiles, relations and similarities between drugs, or associations between drugs and potential drug targets. The objective of this work was to develop and validate a document processing and information extraction pipeline for the identification of chemical entity mentions in text. We used the BioCreative IV CHEMDNER task data to train and evaluate a machine-learning based entity recognition system. Using a combination of two conditional random field models, a selected set of features, and a post-processing stage, we achieved F-measure results of 87.48% in the chemical entity mention recognition task and 87.75% in the chemical document indexing task. We present a machine learning-based solution for automatic recognition of chemical and drug names in scientific documents. The proposed approach applies a rich feature set, including linguistic, orthographic, morphological, dictionary matching and local context features. Post-processing modules are also integrated, performing parentheses correction, abbreviation resolution and filtering erroneous mentions using an exclusion list derived from the training data. The developed methods were implemented as a document annotation tool and web service, freely available at http://bioinformatics.ua.pt/becas-chemicals/.

Building a protein name dictionary from full text: a machine learning term extraction approach

Directory of Open Access Journals (Sweden)

Campagne Fabien

2005-04-01

Full Text Available Abstract Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. Results We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. Conclusion This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt.

Is it about the self or the significance? An fMRI study of self-name recognition.

Science.gov (United States)

Tacikowski, P; Brechmann, A; Marchewka, A; Jednoróg, K; Dobrowolny, M; Nowicka, A

2011-01-01

Our own name, due to its high social relevance, is supposed to have a unique status in our information processing. However, demonstrating this phenomenon empirically proves difficult as famous and unknown names, to which self-name is often compared in the studies, may differ from self-name not only in terms of the 'me vs. not-me' distinction, but also as regards their emotional content and frequency of occurrence in everyday life. In this fMRI study, apart from famous and unknown names we used the names of the most important persons in our subjects' lives. When compared to famous or unknown names recognition, self-name recognition was associated with robust activations in widely distributed bilateral network including fronto-temporal, limbic and subcortical structures, however, when compared to significant other's name, the activations were present specifically in the right inferior frontal gyrus. In addition, the significant other's name produced a similar pattern of activations to the one activated by self-name. These results suggest that the differences between own and other's name processing may rather be quantitative than qualitative in nature.

The Role of Sensory-Motor Information in Object Recognition: Evidence from Category-Specific Visual Agnosia

Science.gov (United States)

Wolk, D.A.; Coslett, H.B.; Glosser, G.

2005-01-01

The role of sensory-motor representations in object recognition was investigated in experiments involving AD, a patient with mild visual agnosia who was impaired in the recognition of visually presented living as compared to non-living entities. AD named visually presented items for which sensory-motor information was available significantly more…

Crowded and Sparse Domains in Object Recognition: Consequences for Categorization and Naming

Science.gov (United States)

Gale, Tim M.; Laws, Keith R.; Foley, Kerry

2006-01-01

Some models of object recognition propose that items from structurally crowded categories (e.g., living things) permit faster access to superordinate semantic information than structurally dissimilar categories (e.g., nonliving things), but slower access to individual object information when naming items. We present four experiments that utilize…

Recognition of faces and names: multimodal physiological correlates of memory and executive function.

Science.gov (United States)

Mitchell, Meghan B; Shirk, Steven D; McLaren, Donald G; Dodd, Jessica S; Ezzati, Ali; Ally, Brandon A; Atri, Alireza

2016-06-01

We sought to characterize electrophysiological, eye-tracking and behavioral correlates of face-name recognition memory in healthy younger adults using high-density electroencephalography (EEG), infrared eye-tracking (ET), and neuropsychological measures. Twenty-one participants first studied 40 face-name (FN) pairs; 20 were presented four times (4R) and 20 were shown once (1R). Recognition memory was assessed by asking participants to make old/new judgments for 80 FN pairs, of which half were previously studied items and half were novel FN pairs (N). Simultaneous EEG and ET recording were collected during recognition trials. Comparisons of event-related potentials (ERPs) for correctly identified FN pairs were compared across the three item types revealing classic ERP old/new effects including 1) relative positivity (1R > N) bi-frontally from 300 to 500 ms, reflecting enhanced familiarity, 2) relative positivity (4R > 1R and 4R > N) in parietal areas from 500 to 800 ms, reflecting enhanced recollection, and 3) late frontal effects (1R > N) from 1000 to 1800 ms in right frontal areas, reflecting post-retrieval monitoring. ET analysis also revealed significant differences in eye movements across conditions. Exploration of cross-modality relationships suggested associations between memory and executive function measures and the three ERP effects. Executive function measures were associated with several indicators of saccadic eye movements and fixations, which were also associated with all three ERP effects. This novel characterization of face-name recognition memory performance using simultaneous EEG and ET reproduced classic ERP and ET effects, supports the construct validity of the multimodal FN paradigm, and holds promise as an integrative tool to probe brain networks supporting memory and executive functioning.

ANOVA Based Approch for Efficient Customer Recognition: Dealing with Common Names

OpenAIRE

Saberi , Morteza; Saberi , Zahra

2015-01-01

Part 2: Artificial Intelligence for Knowledge Management; International audience; This study proposes an Analysis of Variance (ANOVA) technique that focuses on the efficient recognition of customers with common names. The continuous improvement of Information and communications technologies (ICT) has led customers to have new expectations and concerns from their related organization. These new expectations bring various difficulties for organizations’ help desk to meet their customers’ needs....

PKDE4J: Entity and relation extraction for public knowledge discovery.

Science.gov (United States)

Song, Min; Kim, Won Chul; Lee, Dahee; Heo, Go Eun; Kang, Keun Young

2015-10-01

Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means of information search, knowledge discovery, and hypothesis generation. Most previous studies have primarily focused on the design and performance improvement of either named entity recognition or relation extraction. In this paper, we present PKDE4J, a comprehensive text-mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Starting with the Stanford CoreNLP, we developed the system to cope with multiple types of entities and relations. The system also has fairly good performance in terms of accuracy as well as the ability to configure text-processing components. We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction. Copyright © 2015 Elsevier Inc. All rights reserved.

High-recall protein entity recognition using a dictionary

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Kou, Zhenzhen; Cohen, William W.; Murphy, Robert F.

2010-01-01

Protein name extraction is an important step in mining biological literature. We describe two new methods for this task: semiCRFs and dictionary HMMs. SemiCRFs are a recently-proposed extension to conditional random fields that enables more effective use of dictionary information as features. Dictionary HMMs are a technique in which a dictionary is converted to a large HMM that recognizes phrases from the dictionary, as well as variations of these phrases. Standard training methods for HMMs can be used to learn which variants should be recognized. We compared the performance of our new approaches to that of Maximum Entropy (Max-Ent) and normal CRFs on three datasets, and improvement was obtained for all four methods over the best published results for two of the datasets. CRFs and semiCRFs achieved the highest overall performance according to the widely-used F-measure, while the dictionary HMMs performed the best at finding entities that actually appear in the dictionary—the measure of most interest in our intended application. PMID:15961466

Automatic recognition of disorders, findings, pharmaceuticals and body structures from clinical text: an annotation and machine learning study.

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Skeppstedt, Maria; Kvist, Maria; Nilsson, Gunnar H; Dalianis, Hercules

2014-06-01

Automatic recognition of clinical entities in the narrative text of health records is useful for constructing applications for documentation of patient care, as well as for secondary usage in the form of medical knowledge extraction. There are a number of named entity recognition studies on English clinical text, but less work has been carried out on clinical text in other languages. This study was performed on Swedish health records, and focused on four entities that are highly relevant for constructing a patient overview and for medical hypothesis generation, namely the entities: Disorder, Finding, Pharmaceutical Drug and Body Structure. The study had two aims: to explore how well named entity recognition methods previously applied to English clinical text perform on similar texts written in Swedish; and to evaluate whether it is meaningful to divide the more general category Medical Problem, which has been used in a number of previous studies, into the two more granular entities, Disorder and Finding. Clinical notes from a Swedish internal medicine emergency unit were annotated for the four selected entity categories, and the inter-annotator agreement between two pairs of annotators was measured, resulting in an average F-score of 0.79 for Disorder, 0.66 for Finding, 0.90 for Pharmaceutical Drug and 0.80 for Body Structure. A subset of the developed corpus was thereafter used for finding suitable features for training a conditional random fields model. Finally, a new model was trained on this subset, using the best features and settings, and its ability to generalise to held-out data was evaluated. This final model obtained an F-score of 0.81 for Disorder, 0.69 for Finding, 0.88 for Pharmaceutical Drug, 0.85 for Body Structure and 0.78 for the combined category Disorder+Finding. The obtained results, which are in line with or slightly lower than those for similar studies on English clinical text, many of them conducted using a larger training data set, show that

Cell line name recognition in support of the identification of synthetic lethality in cancer from text

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Kaewphan, Suwisa; Van Landeghem, Sofie; Ohta, Tomoko; Van de Peer, Yves; Ginter, Filip; Pyysalo, Sampo

2016-01-01

Motivation: The recognition and normalization of cell line names in text is an important task in biomedical text mining research, facilitating for instance the identification of synthetically lethal genes from the literature. While several tools have previously been developed to address cell line recognition, it is unclear whether available systems can perform sufficiently well in realistic and broad-coverage applications such as extracting synthetically lethal genes from the cancer literature. In this study, we revisit the cell line name recognition task, evaluating both available systems and newly introduced methods on various resources to obtain a reliable tagger not tied to any specific subdomain. In support of this task, we introduce two text collections manually annotated for cell line names: the broad-coverage corpus Gellus and CLL, a focused target domain corpus. Results: We find that the best performance is achieved using NERsuite, a machine learning system based on Conditional Random Fields, trained on the Gellus corpus and supported with a dictionary of cell line names. The system achieves an F-score of 88.46% on the test set of Gellus and 85.98% on the independently annotated CLL corpus. It was further applied at large scale to 24 302 102 unannotated articles, resulting in the identification of 5 181 342 cell line mentions, normalized to 11 755 unique cell line database identifiers. Availability and implementation: The manually annotated datasets, the cell line dictionary, derived corpora, NERsuite models and the results of the large-scale run on unannotated texts are available under open licenses at http://turkunlp.github.io/Cell-line-recognition/. Contact: sukaew@utu.fi PMID:26428294

Annotating patient clinical records with syntactic chunks and named entities: the Harvey Corpus.

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Savkov, Aleksandar; Carroll, John; Koeling, Rob; Cassell, Jackie

The free text notes typed by physicians during patient consultations contain valuable information for the study of disease and treatment. These notes are difficult to process by existing natural language analysis tools since they are highly telegraphic (omitting many words), and contain many spelling mistakes, inconsistencies in punctuation, and non-standard word order. To support information extraction and classification tasks over such text, we describe a de-identified corpus of free text notes, a shallow syntactic and named entity annotation scheme for this kind of text, and an approach to training domain specialists with no linguistic background to annotate the text. Finally, we present a statistical chunking system for such clinical text with a stable learning rate and good accuracy, indicating that the manual annotation is consistent and that the annotation scheme is tractable for machine learning.

Neural correlates of own and close-other’s name recognition: ERP evidence

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Pawel eTacikowski

2014-04-01

Full Text Available One’s own name seems to have a special status in the processing of incoming information. In event-related potential (ERP studies this preferential status has mainly been associated with higher P300 to one’s own name than to other names. Some studies showed preferential responses to own name even for earlier ERP components. However, instead of just being self-specific, these effects could be related to the processing of any highly relevant and/or frequently encountered stimuli. If this is the case: (1 processing of other highly relevant and highly familiar names (e.g., names of friends, partners, siblings, etc. should be associated with similar ERP responses as processing of one's own name; and (2 processing of own and close others' names should result in larger amplitudes of early and late ERP components than processing of less relevant and less familiar names (e.g., names of famous people, names of strangers, etc.. To test this hypothesis we measured and analyzed ERPs from 62 scalp electrodes in 22 subjects. Subjects performed a speeded two-choice recognition task - familiar vs. unfamiliar - with one’s own name being treated as one of the familiar names. All stimuli were presented visually. We found that amplitudes of P200, N250 and P300 did not differ between one’s own and close-other’s names. Crucially, they were significantly larger to own and close-other’s names than to other names (unknown and famous for P300 and unknown for P200 and N250. Our findings suggest that preferential processing of one’s own name is due to its personal-relevance and/or familiarity factors. This pattern of results speaks for a common preference in processing of different kinds of socially relevant stimuli.

Face shape and face identity processing in behavioral variant fronto-temporal dementia: A specific deficit for familiarity and name recognition of famous faces.

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De Winter, François-Laurent; Timmers, Dorien; de Gelder, Beatrice; Van Orshoven, Marc; Vieren, Marleen; Bouckaert, Miriam; Cypers, Gert; Caekebeke, Jo; Van de Vliet, Laura; Goffin, Karolien; Van Laere, Koen; Sunaert, Stefan; Vandenberghe, Rik; Vandenbulcke, Mathieu; Van den Stock, Jan

2016-01-01

Deficits in face processing have been described in the behavioral variant of fronto-temporal dementia (bvFTD), primarily regarding the recognition of facial expressions. Less is known about face shape and face identity processing. Here we used a hierarchical strategy targeting face shape and face identity recognition in bvFTD and matched healthy controls. Participants performed 3 psychophysical experiments targeting face shape detection (Experiment 1), unfamiliar face identity matching (Experiment 2), familiarity categorization and famous face-name matching (Experiment 3). The results revealed group differences only in Experiment 3, with a deficit in the bvFTD group for both familiarity categorization and famous face-name matching. Voxel-based morphometry regression analyses in the bvFTD group revealed an association between grey matter volume of the left ventral anterior temporal lobe and familiarity recognition, while face-name matching correlated with grey matter volume of the bilateral ventral anterior temporal lobes. Subsequently, we quantified familiarity-specific and name-specific recognition deficits as the sum of the celebrities of which respectively only the name or only the familiarity was accurately recognized. Both indices were associated with grey matter volume of the bilateral anterior temporal cortices. These findings extent previous results by documenting the involvement of the left anterior temporal lobe (ATL) in familiarity detection and the right ATL in name recognition deficits in fronto-temporal lobar degeneration.

Neural correlates of recognition and naming of musical instruments.

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Belfi, Amy M; Bruss, Joel; Karlan, Brett; Abel, Taylor J; Tranel, Daniel

2016-10-01

Retrieval of lexical (names) and conceptual (semantic) information is frequently impaired in individuals with neurological damage. One category of items that is often affected is musical instruments. However, distinct neuroanatomical correlates underlying lexical and conceptual knowledge for musical instruments have not been identified. We used a neuropsychological approach to explore the neural correlates of knowledge retrieval for musical instruments. A large sample of individuals with focal brain damage (N = 298), viewed pictures of 16 musical instruments and were asked to name and identify each instrument. Neuroanatomical data were analyzed with a proportional MAP-3 method to create voxelwise lesion proportion difference maps. Impaired naming (lexical retrieval) of musical instruments was associated with damage to the left temporal pole and inferior pre- and postcentral gyri. Impaired recognition (conceptual knowledge retrieval) of musical instruments was associated with a more broadly and bilaterally distributed network of regions, including ventromedial prefrontal cortices, occipital cortices, and superior temporal gyrus. The findings extend our understanding of how musical instruments are processed at neural system level, and elucidate factors that may explain why brain damage may or may not produce anomia or agnosia for musical instruments. Our findings also help inform broader understanding of category-related knowledge mapping in the brain, as musical instruments possess several characteristics that are similar to various other categories of items: They are inanimate and highly manipulable (similar to tools), produce characteristic sounds (similar to animals), and require fine-grained visual differentiation between each other (similar to people). (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Bibliographic Entity Automatic Recognition and Disambiguation

CERN Document Server

AUTHOR|(SzGeCERN)766022

This master thesis reports an applied machine learning research internship done at digital library of the European Organization for Nuclear Research (CERN). The way an author’s name may vary in its representation across scientific publications creates ambiguity when it comes to uniquely identifying an author; In the database of any scientific digital library, the same full name variation can be used by more than one author. This may occur even between authors from the same research affiliation. In this work, we built a machine learning based author name disambiguation solution. The approach consists in learning a distance function from a ground-truth data, blocking publications of broadly similar author names, and clustering the publications using a semi-supervised strategy within each of the blocks. The main contributions of this work are twofold; first, improving the distance model by taking into account the (estimated) ethnicity of the author’s full name. Indeed, names from different ethnicities, for e...

Moving beyond the Name: Defining Corporate Entities to Support Provenance-Based Access

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Light, Michelle

2007-01-01

The second edition of the "International Standard Archival Authority Records for Corporate Bodies, Persons, and Families (ISAAR(CPF)2)" focuses on describing entities as they exist in reality, rather than on establishing authorized terms. This change allows authority records to include multiple authorized terms representing an entity as it changed…

Cortical mechanisms of person representation: recognition of famous and personally familiar names.

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Sugiura, Motoaki; Sassa, Yuko; Watanabe, Jobu; Akitsuki, Yuko; Maeda, Yasuhiro; Matsue, Yoshihiko; Fukuda, Hiroshi; Kawashima, Ryuta

2006-06-01

Personally familiar people are likely to be represented more richly in episodic, emotional, and behavioral contexts than famous people, who are usually represented predominantly in semantic context. To reveal cortical mechanisms supporting this differential person representation, we compared cortical activation during name recognition tasks between personally familiar and famous names, using an event-related functional magnetic resonance imaging (fMRI). Normal subjects performed familiar- or unfamiliar-name detection tasks during visual presentation of personally familiar (Personal), famous (Famous), and unfamiliar (Unfamiliar) names. The bilateral temporal poles and anterolateral temporal cortices, as well as the left temporoparietal junction, were activated in the contrasts Personal-Unfamiliar and Famous-Unfamiliar to a similar extent. The bilateral occipitotemporoparietal junctions, precuneus, and posterior cingulate cortex showed activation in the contrasts Personal-Unfamiliar and Personal-Famous. Together with previous findings, differential activation in the occipitotemporoparietal junction, precuneus, and posterior cingulate cortex between personally familiar and famous names is considered to reflect differential person representation. The similar extent of activation for personally familiar and famous names in the temporal pole and anterolateral temporal cortex is consistent with the associative role of the anterior temporal cortex in person identification, which has been conceptualized as a person identity node in many models of person identification. The left temporoparietal junction was considered to process familiar written names. The results illustrated the neural correlates of the person representation as a network of discrete regions in the bilateral posterior cortices, with the anterior temporal cortices having a unique associative role.

A new face of sleep: The impact of post-learning sleep on recognition memory for face-name associations.

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Maurer, Leonie; Zitting, Kirsi-Marja; Elliott, Kieran; Czeisler, Charles A; Ronda, Joseph M; Duffy, Jeanne F

2015-12-01

Sleep has been demonstrated to improve consolidation of many types of new memories. However, few prior studies have examined how sleep impacts learning of face-name associations. The recognition of a new face along with the associated name is an important human cognitive skill. Here we investigated whether post-presentation sleep impacts recognition memory of new face-name associations in healthy adults. Fourteen participants were tested twice. Each time, they were presented 20 photos of faces with a corresponding name. Twelve hours later, they were shown each face twice, once with the correct and once with an incorrect name, and asked if each face-name combination was correct and to rate their confidence. In one condition the 12-h interval between presentation and recall included an 8-h nighttime sleep opportunity ("Sleep"), while in the other condition they remained awake ("Wake"). There were more correct and highly confident correct responses when the interval between presentation and recall included a sleep opportunity, although improvement between the "Wake" and "Sleep" conditions was not related to duration of sleep or any sleep stage. These data suggest that a nighttime sleep opportunity improves the ability to correctly recognize face-name associations. Further studies investigating the mechanism of this improvement are important, as this finding has implications for individuals with sleep disturbances and/or memory impairments. Copyright © 2015 Elsevier Inc. All rights reserved.

The contribution of discrete-trial naming and visual recognition to rapid automatized naming deficits of dyslexic children with and without a history of language delay

Directory of Open Access Journals (Sweden)

Filippo eGasperini

2014-09-01

Full Text Available Children with Developmental Dyslexia (DD are impaired in Rapid Automatized Naming (RAN tasks, where subjects are asked to name arrays of high frequency items as quickly as possible. However the reasons why RAN speed discriminates DD from typical readers are not yet fully understood. Our study was aimed to identify some of the cognitive mechanisms underlying RAN-reading relationship by comparing one group of 32 children with DD with an age-matched control group of typical readers on a naming and a visual recognition task both using a discrete-trial methodology , in addition to a serial RAN task, all using the same stimuli (digits and colors. Results showed a significant slowness of DD children in both serial and discrete-trial naming tasks regardless of type of stimulus, but no difference between the two groups on the discrete-trial recognition task. Significant differences between DD and control participants in the RAN task disappeared when performance in the discrete-trial naming task was partialled out by covariance analysis for colors, but not for digits. The same pattern held in a subgroup of DD subjects with a history of early language delay (LD. By contrast, in a subsample of DD children without LD the RAN deficit was specific for digits and disappeared after slowness in discrete-trial naming was partialled out. Slowness in discrete-trial naming was more evident for LD than for noLD DD children. Overall, our results confirm previous evidence indicating a name-retrieval deficit as a cognitive impairment underlying RAN slowness in DD children. This deficit seems to be more marked in DD children with previous LD. Moreover, additional cognitive deficits specifically associated with serial RAN tasks have to be taken into account when explaining deficient RAN speed of these latter children. We suggest that partially different cognitive dysfunctions underpin superficially similar RAN impairments in different subgroups of DD subjects.

Encoding of Fundamental Chemical Entities of Organic Reactivity Interest using chemical ontology and XML.

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Durairaj, Vijayasarathi; Punnaivanam, Sankar

2015-09-01

Fundamental chemical entities are identified in the context of organic reactivity and classified as appropriate concept classes namely ElectronEntity, AtomEntity, AtomGroupEntity, FunctionalGroupEntity and MolecularEntity. The entity classes and their subclasses are organized into a chemical ontology named "ChemEnt" for the purpose of assertion, restriction and modification of properties through entity relations. Individual instances of entity classes are defined and encoded as a library of chemical entities in XML. The instances of entity classes are distinguished with a unique notation and identification values in order to map them with the ontology definitions. A model GUI named Entity Table is created to view graphical representations of all the entity instances. The detection of chemical entities in chemical structures is achieved through suitable algorithms. The possibility of asserting properties to the entities at different levels and the mechanism of property flow within the hierarchical entity levels is outlined. Copyright © 2015 Elsevier Inc. All rights reserved.

Combining Open-domain and Biomedical Knowledge for Topic Recognition in Consumer Health Questions.

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Mrabet, Yassine; Kilicoglu, Halil; Roberts, Kirk; Demner-Fushman, Dina

2016-01-01

Determining the main topics in consumer health questions is a crucial step in their processing as it allows narrowing the search space to a specific semantic context. In this paper we propose a topic recognition approach based on biomedical and open-domain knowledge bases. In the first step of our method, we recognize named entities in consumer health questions using an unsupervised method that relies on a biomedical knowledge base, UMLS, and an open-domain knowledge base, DBpedia. In the next step, we cast topic recognition as a binary classification problem of deciding whether a named entity is the question topic or not. We evaluated our approach on a dataset from the National Library of Medicine (NLM), introduced in this paper, and another from the Genetic and Rare Disease Information Center (GARD). The combination of knowledge bases outperformed the results obtained by individual knowledge bases by up to 16.5% F1 and achieved state-of-the-art performance. Our results demonstrate that combining open-domain knowledge bases with biomedical knowledge bases can lead to a substantial improvement in understanding user-generated health content.

Context and Domain Knowledge Enhanced Entity Spotting in Informal Text

Science.gov (United States)

Gruhl, Daniel; Nagarajan, Meena; Pieper, Jan; Robson, Christine; Sheth, Amit

This paper explores the application of restricted relationship graphs (RDF) and statistical NLP techniques to improve named entity annotation in challenging Informal English domains. We validate our approach using on-line forums discussing popular music. Named entity annotation is particularly difficult in this domain because it is characterized by a large number of ambiguous entities, such as the Madonna album "Music" or Lilly Allen's pop hit "Smile".

A controlled vocabulary for pathway entities and events.

Science.gov (United States)

Jupe, Steve; Jassal, Bijay; Williams, Mark; Wu, Guanming

2014-01-01

Entities involved in pathways and the events they participate in require descriptive and unambiguous names that are often not available in the literature or elsewhere. Reactome is a manually curated open-source resource of human pathways. It is accessible via a website, available as downloads in standard reusable formats and via Representational State Transfer (REST)-ful and Simple Object Access Protocol (SOAP) application programming interfaces (APIs). We have devised a controlled vocabulary (CV) that creates concise, unambiguous and unique names for reactions (pathway events) and all the molecular entities they involve. The CV could be reapplied in any situation where names are used for pathway entities and events. Adoption of this CV would significantly improve naming consistency and readability, with consequent benefits for searching and data mining within and between databases. Database URL: http://www.reactome.org. © The Author(s) 2014. Published by Oxford University Press.

Validation of the Face-Name Pairs Task in Major Depression: Impaired recall but not recognition.

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Kimberley J Smith

2014-02-01

Full Text Available Major depression can be associated with neurocognitive deficits which are believed in part to be related to medial temporal lobe pathology. The purpose of this study was to investigate this impairment using a hippocampal-dependent neuropsychological task. The Face-Name pairs task was used to assess associative memory functioning in 19 patients with major depression. When compared to age-sex-and-education matched controls, patients with depression showed impaired learning, delayed cued-recall and delayed free-recall. However, they also showed preserved recognition of the verbal and nonverbal components of this task. Results indicate that the face-name pairs task is sensitive to neurocognitive deficits in major depression.

Adapting Web content for low-literacy readers by using lexical elaboration and named entities labeling

Science.gov (United States)

Watanabe, W. M.; Candido, A.; Amâncio, M. A.; De Oliveira, M.; Pardo, T. A. S.; Fortes, R. P. M.; Aluísio, S. M.

2010-12-01

This paper presents an approach for assisting low-literacy readers in accessing Web online information. The "Educational FACILITA" tool is a Web content adaptation tool that provides innovative features and follows more intuitive interaction models regarding accessibility concerns. Especially, we propose an interaction model and a Web application that explore the natural language processing tasks of lexical elaboration and named entity labeling for improving Web accessibility. We report on the results obtained from a pilot study on usability analysis carried out with low-literacy users. The preliminary results show that "Educational FACILITA" improves the comprehension of text elements, although the assistance mechanisms might also confuse users when word sense ambiguity is introduced, by gathering, for a complex word, a list of synonyms with multiple meanings. This fact evokes a future solution in which the correct sense for a complex word in a sentence is identified, solving this pervasive characteristic of natural languages. The pilot study also identified that experienced computer users find the tool to be more useful than novice computer users do.

Perceptual and Action Routines in Diagrammatic Reasoning for Entity-Reidentification

National Research Council Canada - National Science Library

Banerjee, Bonny; Chandrasekaran, B

2004-01-01

.... In earlier papers, we described a diagrammatic reasoning architecture, and demonstrated the approach for instances of maneuver recognition and information fusion for entity-reidentification problems...

A scalable machine-learning approach to recognize chemical names within large text databases

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Wren Jonathan D

2006-09-01

Full Text Available Abstract Motivation The use or study of chemical compounds permeates almost every scientific field and in each of them, the amount of textual information is growing rapidly. There is a need to accurately identify chemical names within text for a number of informatics efforts such as database curation, report summarization, tagging of named entities and keywords, or the development/curation of reference databases. Results A first-order Markov Model (MM was evaluated for its ability to distinguish chemical names from words, yielding ~93% recall in recognizing chemical terms and ~99% precision in rejecting non-chemical terms on smaller test sets. However, because total false-positive events increase with the number of words analyzed, the scalability of name recognition was measured by processing 13.1 million MEDLINE records. The method yielded precision ranges from 54.7% to 100%, depending upon the cutoff score used, averaging 82.7% for approximately 1.05 million putative chemical terms extracted. Extracted chemical terms were analyzed to estimate the number of spelling variants per term, which correlated with the total number of times the chemical name appeared in MEDLINE. This variability in term construction was found to affect both information retrieval and term mapping when using PubMed and Ovid.

Automatic Recognition of Object Names in Literature

Science.gov (United States)

Bonnin, C.; Lesteven, S.; Derriere, S.; Oberto, A.

2008-08-01

SIMBAD is a database of astronomical objects that provides (among other things) their bibliographic references in a large number of journals. Currently, these references have to be entered manually by librarians who read each paper. To cope with the increasing number of papers, CDS develops a tool to assist the librarians in their work, taking advantage of the Dictionary of Nomenclature of Celestial Objects, which keeps track of object acronyms and of their origin. The program searches for object names directly in PDF documents by comparing the words with all the formats stored in the Dictionary of Nomenclature. It also searches for variable star names based on constellation names and for a large list of usual names such as Aldebaran or the Crab. Object names found in the documents often correspond to several astronomical objects. The system retrieves all possible matches, displays them with their object type given by SIMBAD, and lets the librarian make the final choice. The bibliographic reference can then be automatically added to the object identifiers in the database. Besides, the systematic usage of the Dictionary of Nomenclature, which is updated manually, permitted to automatically check it and to detect errors and inconsistencies. Last but not least, the program collects some additional information such as the position of the object names in the document (in the title, subtitle, abstract, table, figure caption...) and their number of occurrences. In the future, this will permit to calculate the 'weight' of an object in a reference and to provide SIMBAD users with an important new information, which will help them to find the most relevant papers in the object reference list.

Using co-occurrence network structure to extract synonymous gene and protein names from MEDLINE abstracts

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Spackman K

2005-04-01

Full Text Available Abstract Background Text-mining can assist biomedical researchers in reducing information overload by extracting useful knowledge from large collections of text. We developed a novel text-mining method based on analyzing the network structure created by symbol co-occurrences as a way to extend the capabilities of knowledge extraction. The method was applied to the task of automatic gene and protein name synonym extraction. Results Performance was measured on a test set consisting of about 50,000 abstracts from one year of MEDLINE. Synonyms retrieved from curated genomics databases were used as a gold standard. The system obtained a maximum F-score of 22.21% (23.18% precision and 21.36% recall, with high efficiency in the use of seed pairs. Conclusion The method performs comparably with other studied methods, does not rely on sophisticated named-entity recognition, and requires little initial seed knowledge.

Integrating Naming and Addressing of Persistent data in Programming Language and Operating System Contexts

NARCIS (Netherlands)

van der Valk, M.; van der Valk, M.

1993-01-01

There exist a number of desirable transparencies in distributed computing, viz., name transparency: having a uniform way of naming entities in the system, regardless of their type or physical make up; location transparency: having a uniform way of addressing entities, regardless of their physical

Using Local Grammar for Entity Extraction from Clinical Reports

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Aicha Ghoulam

2015-06-01

Full Text Available Information Extraction (IE is a natural language processing (NLP task whose aim is to analyze texts written in natural language to extract structured and useful information such as named entities and semantic relations linking these entities. Information extraction is an important task for many applications such as bio-medical literature mining, customer care, community websites, and personal information management. The increasing information available in patient clinical reports is difficult to access. As it is often in an unstructured text form, doctors need tools to enable them access to this information and the ability to search it. Hence, a system for extracting this information in a structured form can benefits healthcare professionals. The work presented in this paper uses a local grammar approach to extract medical named entities from French patient clinical reports. Experimental results show that the proposed approach achieved an F-Measure of 90. 06%.

NOMINAL MARKING SYSTEM OF BAHASA MANGGARAI AND ITS INTERRELATION TO NAMING SYSTEM OF ENTITIES: A CULTURAL LINGUISTIC STUDY

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Kletus Erom

2012-11-01

Full Text Available This study analyzes the cultural imagery of the Manggaraian SpeechCommunities (MSC in “Nominal Marking System (NMS of Bahasa Manggaraiand Its Interrelation with Naming Systems of Entity (NSE: A CulturalLinguistic Study”. The result of the analysis is useful for both the academic worldand the life of the society, especially the MSC.The study conducted in Manggarai Regency, Flores, East Nusa TenggaraProvince, is qualitative. The data were obtained through observation, elicitation,interview, documentation study, listening, and note taking. For this reason, a numberof questions were prepared in a written form. The data obtained were analyzedthrough steps of selection, listing, translation, and interpretation of the formallinguistic meaning and cultural imagery of the MSC. The result of the data analysisis informally reported and verbally described.To analyze the data, the Cultural Linguistic Theory was applied andsupported by the structural and the dynamic theories. To know the chance and toinspire the study, a number of previous studies were reviewed. To easily understand,direct, and limit the discussion of the study, a number of basic concepts weredefined.Syntactically and semantically, there are four kinds of nominal markers(NMs of BM. NMs in the forms of personal pronouns (PP: hau ‘you SG’, hia/hi‘he/she’, meu ‘you-PLUR’, and ise ‘they’ mark proper nouns (PN as theSubject/Agent or Object/Patient in a clause bearing the meaning of subject or objectposition of a clause and not common nouns (CN. NMs in the forms of de/ di/ disemark the noun (CN/pronoun or PN as the possessor of the possessed noun in aclause bearing the meaning of possession. NMs in the forms of le/ li/ lise mark thenoun (CN/pronoun or PN as the agent diathesis of an action targeted to a noun asthe patient diathesis in a clause bearing the meaning of addition or the target/localityof an action. And NMs in the forms of ge/ gi/ gise mark the noun (CN/pronoun or

Laos Organization Name Using Cascaded Model Based on SVM and CRF

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Duan Shaopeng

2017-01-01

Full Text Available According to the characteristics of Laos organization name, this paper proposes a two layer model based on conditional random field (CRF and support vector machine (SVM for Laos organization name recognition. A layer of model uses CRF to recognition simple organization name, and the result is used to support the decision of the second level. Based on the driving method, the second layer uses SVM and CRF to recognition the complicated organization name. Finally, the results of the two levels are combined, And by a subsequent treatment to correct results of low confidence recognition. The results show that this approach based on SVM and CRF is efficient in recognizing organization name through open test for real linguistics, and the recalling rate achieve 80. 83％and the precision rate achieves 82. 75％.

Robust hybrid name disambiguation framework for large databases

KAUST Repository

Zhu, Jia

2013-10-26

In many databases, science bibliography database for example, name attribute is the most commonly chosen identifier to identify entities. However, names are often ambiguous and not always unique which cause problems in many fields. Name disambiguation is a non-trivial task in data management that aims to properly distinguish different entities which share the same name, particularly for large databases like digital libraries, as only limited information can be used to identify authors\\' name. In digital libraries, ambiguous author names occur due to the existence of multiple authors with the same name or different name variations for the same person. Also known as name disambiguation, most of the previous works to solve this issue often employ hierarchical clustering approaches based on information inside the citation records, e.g. co-authors and publication titles. In this paper, we focus on proposing a robust hybrid name disambiguation framework that is not only applicable for digital libraries but also can be easily extended to other application based on different data sources. We propose a web pages genre identification component to identify the genre of a web page, e.g. whether the page is a personal homepage. In addition, we propose a re-clustering model based on multidimensional scaling that can further improve the performance of name disambiguation. We evaluated our approach on known corpora, and the favorable experiment results indicated that our proposed framework is feasible. © 2013 Akadémiai Kiadó, Budapest, Hungary.

Robust hybrid name disambiguation framework for large databases

KAUST Repository

Zhu, Jia; Yang, Yi; Xie, Qing; Wang, Liwei; Hassan, Saeed-Ul

2013-01-01

In many databases, science bibliography database for example, name attribute is the most commonly chosen identifier to identify entities. However, names are often ambiguous and not always unique which cause problems in many fields. Name disambiguation is a non-trivial task in data management that aims to properly distinguish different entities which share the same name, particularly for large databases like digital libraries, as only limited information can be used to identify authors' name. In digital libraries, ambiguous author names occur due to the existence of multiple authors with the same name or different name variations for the same person. Also known as name disambiguation, most of the previous works to solve this issue often employ hierarchical clustering approaches based on information inside the citation records, e.g. co-authors and publication titles. In this paper, we focus on proposing a robust hybrid name disambiguation framework that is not only applicable for digital libraries but also can be easily extended to other application based on different data sources. We propose a web pages genre identification component to identify the genre of a web page, e.g. whether the page is a personal homepage. In addition, we propose a re-clustering model based on multidimensional scaling that can further improve the performance of name disambiguation. We evaluated our approach on known corpora, and the favorable experiment results indicated that our proposed framework is feasible. © 2013 Akadémiai Kiadó, Budapest, Hungary.

Face-name association learning and brain structural substrates in alcoholism.

Science.gov (United States)

Pitel, Anne-Lise; Chanraud, Sandra; Rohlfing, Torsten; Pfefferbaum, Adolf; Sullivan, Edith V

2012-07-01

Associative learning is required for face-name association and is impaired in alcoholism, but the cognitive processes and brain structural components underlying this deficit remain unclear. It is also unknown whether prompting alcoholics to implement a deep level of processing during face-name encoding would enhance performance. Abstinent alcoholics and controls performed a levels-of-processing face-name learning task. Participants indicated whether the face was that of an honest person (deep encoding) or that of a man (shallow encoding). Retrieval was examined using an associative (face-name) recognition task and a single-item (face or name only) recognition task. Participants also underwent 3T structural MRI. Compared with controls, alcoholics had poorer associative and single-item learning and performed at similar levels. Level of processing at encoding had little effect on recognition performance but affected reaction time (RT). Correlations with brain volumes were generally modest and based primarily on RT in alcoholics, where the deeper the processing at encoding, the more restricted the correlations with brain volumes. In alcoholics, longer control task RTs correlated modestly with smaller tissue volumes across several anterior to posterior brain regions; shallow encoding correlated with calcarine and striatal volumes; deep encoding correlated with precuneus and parietal volumes; and associative recognition RT correlated with cerebellar volumes. In controls, poorer associative recognition with deep encoding correlated significantly with smaller volumes of frontal and striatal structures. Despite prompting, alcoholics did not take advantage of encoding memoranda at a deep level to enhance face-name recognition accuracy. Nonetheless, conditions of deeper encoding resulted in faster RTs and more specific relations with regional brain volumes than did shallow encoding. The normal relation between associative recognition and corticostriatal volumes was not

How Does Using Object Names Influence Visual Recognition Memory?

Science.gov (United States)

Richler, Jennifer J.; Palmeri, Thomas J.; Gauthier, Isabel

2013-01-01

Two recent lines of research suggest that explicitly naming objects at study influences subsequent memory for those objects at test. Lupyan (2008) suggested that naming "impairs" memory by a representational shift of stored representations of named objects toward the prototype (labeling effect). MacLeod, Gopie, Hourihan, Neary, and Ozubko (2010)…

Entity Recognition Via Multimodal Sensor Fusion With Smart Phones

Science.gov (United States)

2015-03-26

sensor’s data. In the research Preprocessing Techniques for Context Recognition from Accelerom- eter Data, Figo, Diniz , Ferreira, and Cardoso provide...International Conference on, pages 13–24. IEEE, 2011. 13. Davide Figo, Pedro C. Diniz , Diogo R. Ferreira, and João M. P. Cardoso. Pre- processing

A NEW RECOGNITION TECHNIQUE NAMED SOMP BASED ON PALMPRINT USING NEURAL NETWORK BASED SELF ORGANIZING MAPS

Directory of Open Access Journals (Sweden)

A. S. Raja

2012-08-01

Full Text Available The word biometrics refers to the use of physiological or biological characteristics of human to recognize and verify the identity of an individual. Palmprint has become a new class of human biometrics for passive identification with uniqueness and stability. This is considered to be reliable due to the lack of expressions and the lesser effect of aging. In this manuscript a new Palmprint based biometric system based on neural networks self organizing maps (SOM is presented. The method is named as SOMP. The paper shows that the proposed SOMP method improves the performance and robustness of recognition. The proposed method is applied to a variety of datasets and the results are shown.

Review Of The Revenue Recognition In Accordance With Statement Of Financial Accounting Standard PSAK No.23 2010 At Damri Corporation

Directory of Open Access Journals (Sweden)

Debbie Christine

2015-08-01

Full Text Available ABSTRACT One of the components of financial statements that are considered useful to look at the condition of the company namely the income statement. One component of the income statement are income the main problems in accounting revenue is determining when revenue recognition. Activities of the company will be deemed ineffective and inefficient when revenue recognition is not done properly. Therefore the recognition of revenue have been set in PSAK No.232010. According to PSAK 232010 revenue is the gross inflow of economic benefits arising from the normal activities of an entity during a period when those inflows result in increases in equity that is not derived from the contribution of investors. The main income earned Damri Corporation is selling the economic city bus bus with air conditioner and Trans Metro Bandung to society or passengers. Damri Corporation is a State-Owned Enterprises SOEs engaged in the provision of transport services one of them a city bus. Final assignment method used is descriptive method descriptive observational methods that analyze about the condition of the company. Damri Corp. apply accrual basis as for recognizing revenue. Application of revenue recognition is done by Damri Corporation in accordance with PSAK No. 232010 in which revenue is recognized on the basis of PSAK No. 232010. The possibility that the economic benefits associated with the transaction will be obtained by the entity and the amount of revenue can be measured reliably. Revenue Recognition In accordance with PSAK No.232010 at Damri Corporation can be concluded that the basic recording of revenue recognition is used Damri Corporation accrual basis accrual basis of revenue recognition is where the income from the sale of goods or services is recognized in the period of the transaction although cash has not been received by the company the transaction has been recorded and recognized as revenue.

Dynamic collective entity representations for entity ranking

NARCIS (Netherlands)

Graus, D.; Tsagkias, M.; Weerkamp, W.; Meij, E.; de Rijke, M.

2016-01-01

Entity ranking, i.e., successfully positioning a relevant entity at the top of the ranking for a given query, is inherently difficult due to the potential mismatch between the entity's description in a knowledge base, and the way people refer to the entity when searching for it. To counter this

The National Geographic Names Data Base: Phase II instructions

Science.gov (United States)

Orth, Donald J.; Payne, Roger L.

1987-01-01

The Geographic Names Information System is a computer-based information system developed to meet major national needs by providing information for named entities in the United States, its territories, and outlying areas. The National Geographic Names Data Base, a component of the Geographic Names Information System, currently contains most names and associated information recorded on the 1:24,000-scale (or largest scale available) topographic maps of the U.S. Geological Survey. The work involved in this initial compilation of names shown on the topographic-map series, and the development and editing of the National Geographic Names Data Base, is referred to as Phase I. Optimal use and effectiveness of an automated names system require that the names of features

Neighbourhood frequency effects in visual word recognition and naming

NARCIS (Netherlands)

Grainger, I.J.

1988-01-01

Two experiments are reported that examine the influence of a given word's ortllographic neighbours (orthographically similar words) on the recognition and pronunciation of that word. In Experiment 1 (lexical decision) neighbourhood frequency as opposed to stimulus-word frequency was shown to have a

By which name should I call thee? The consequences of having multiple names.

Science.gov (United States)

Stevenage, Sarah V; Lewis, Hugh G

2005-11-01

The nominal competitor effect suggests that, when a person has two names associated with them, recall of either name is more difficult than if they just had one name. Drawing on a connectionist framework, this effect could arise either if multiple names were represented as being connected to a single person identity node (PIN), or if multiple names were represented as being connected via one-to-one links to multiple PINs. Whilst the latter has intuitive appeal, results from two experiments support the former architecture. Having two names connected to a single PIN not only gives rise to a nominal competitor effect (Experiment 1), but also gives rise to a familiarity enhancement effect (Experiment 2). These empirical results are simulated using an extension of Brédart, Valentine, Calder, and Gassi's (1995) connectionist architecture, which reveals that both effects hold even when the association of both names to the PIN is unequal. These results are presented in terms of a more complete model for person recognition, and the representation of semantic information within such a model is examined.

Invention and validation of an automated camera system that uses optical character recognition to identify patient name mislabeled samples.

Science.gov (United States)

Hawker, Charles D; McCarthy, William; Cleveland, David; Messinger, Bonnie L

2014-03-01

Mislabeled samples are a serious problem in most clinical laboratories. Published error rates range from 0.39/1000 to as high as 1.12%. Standardization of bar codes and label formats has not yet achieved the needed improvement. The mislabel rate in our laboratory, although low compared with published rates, prompted us to seek a solution to achieve zero errors. To reduce or eliminate our mislabeled samples, we invented an automated device using 4 cameras to photograph the outside of a sample tube. The system uses optical character recognition (OCR) to look for discrepancies between the patient name in our laboratory information system (LIS) vs the patient name on the customer label. All discrepancies detected by the system's software then require human inspection. The system was installed on our automated track and validated with production samples. We obtained 1 009 830 images during the validation period, and every image was reviewed. OCR passed approximately 75% of the samples, and no mislabeled samples were passed. The 25% failed by the system included 121 samples actually mislabeled by patient name and 148 samples with spelling discrepancies between the patient name on the customer label and the patient name in our LIS. Only 71 of the 121 mislabeled samples detected by OCR were found through our normal quality assurance process. We have invented an automated camera system that uses OCR technology to identify potential mislabeled samples. We have validated this system using samples transported on our automated track. Full implementation of this technology offers the possibility of zero mislabeled samples in the preanalytic stage.

Identificação e classificação de entidades mencionadas em galego

Directory of Open Access Journals (Sweden)

Marcos Garcia

2012-01-01

Full Text Available Automatic named entity recognition and classification are important tasks for many natural language processing applications, such as machine translation, information extraction or question-answering systems. This paper describes the adaptation and implementation of several open-source systems for the identification and classification of the following named entities in Galician: (i dates, (ii numerals, (iii quantities and (iv proper nouns. Analysis of the first three types of named entities is performed with the software FreeLing, using finite-state automata. For the proper noun recognition task, two methods were compared: (i finite-state automata and (ii machine learning models. Finally, the semantic classification of proper nouns was carried out with a rulebased system that takes advantage of automatically obtained resources. This paper shows some evaluations for each tool, all available under free licenses.

What's in a Name: The Place of Recognition in a Hospitable Classroom

Science.gov (United States)

Stratman, Jacob

2015-01-01

In this brief article, I argue that recognition is the key virtue of a hospitable classroom. Whether we are discussing the relationship between the teacher and the student, the student and other students, the student and the subject of study, or the teacher and the subject of study, recognition is the building block to a classroom that welcomes…

Can You Say My Name?

DEFF Research Database (Denmark)

Erz, Antonia; Christensen, Bo T.

affect their judgments of people and objects. We extend this research by investigating the effect of phonological fluency on recognition and recall of novel non-word brand names in three laboratory experiments. The results provide us with a more fine-grained idea of fluency effects on memory of non...

Brand name changes help health care providers win market recognition.

Science.gov (United States)

Keesling, G

1993-01-01

As the healthcare industry continues to recognize the strategic implications of branding, more providers will undertake an identity change to better position themselves in competitive markets. The paper examines specific healthcare branding decisions, the reasons prompting brand name decisions and the marketing implications for a change in brand name.

10 CFR 300.3 - Guidance for defining and naming the reporting entity.

Science.gov (United States)

2010-01-01

... agency or departmental level, but distinct organizational units (such as a Department of the Interior... flexibility in defining themselves at an appropriate level of aggregation, it is essential that the name...

Naming names: the first women taxonomists in mycology

Directory of Open Access Journals (Sweden)

Sara Maroske

2018-03-01

Full Text Available The transition from amateur to professional in natural history is generally regarded as having taken place in the nineteenth century, but landmark events such as the 1917 appointment of mycologist Johanna Westerdijk (1883–1961 as the first female professor in the Netherlands indicate that the pattern of change for women was more varied and delayed than for men. We investigate this transition in mycology, and identify only 43 women in the Western World who published scientific mycological literature pre-1900, of whom twelve published new fungal taxa. By charting the emergence of these women over time, and comparing the output of self-taught amateurs and university graduates, we establish the key role of access to higher education in female participation in mycology. Using a suite of strategies, six of the self-taught amateurs managed to overcome their educational disadvantages and name names — Catharina Dörrien (the first to name a fungal taxon, Marie-Anne Libert, Mary Elizabeth Banning, Élise-Caroline Bommer, Mariette Rousseau, and Annie Lorrain Smith. By 1900, the professional era for women in mycology was underway, and increasing numbers published new taxa. Parity with male colleagues in recognition and promotion, however, remains an ongoing issue. Key words: Amateurs, Fungi, Gender studies, History of science, Plant pathology

End-Stop Exemplar Based Recognition

DEFF Research Database (Denmark)

Olsen, Søren I.

2003-01-01

An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring int...... interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion....

Paradigms in object recognition

International Nuclear Information System (INIS)

Mutihac, R.; Mutihac, R.C.

1999-09-01

A broad range of approaches has been proposed and applied for the complex and rather difficult task of object recognition that involves the determination of object characteristics and object classification into one of many a priori object types. Our paper revises briefly the three main different paradigms in pattern recognition, namely Bayesian statistics, neural networks, and expert systems. (author)

Ultra advanced projects. ; Naming hyper-hightech projects. (Cho) no tsuku project. ; Naming no shikumi

Energy Technology Data Exchange (ETDEWEB)

Goto, Y. (Ministry of International Trade and Industry, Tokyo (Japan))

1992-10-05

Significance of using 'super' for naming a project of technological development is discussed. Functions of naming are classified into (1) recognition, (2) display and (3) sales-promotion, whereby mechanism of naming of merchandise that is developed through the technique of 3 is considered. Further, the mechanism of naming is discussed in relation to marketing. It is pointed out that naming of merchandise is determined on the basis of (1) concept of planned goods and (2) marketing-mixes composed of goods, price, sales-roots and sales-promotion. The same mechanism works also in a project for technological development. Technical trends are caught and projects are targetted by taking supposed regimes into account, thereby the most suitable mix is formed. The mix in the technological development is assumed to be composed of purpose, specification, regime and sales-promotion. Two examples of the governmental projects by Ministry of International Trade and Industry, 'the big regime for research and development on industrial technologies' and 'the regime for development of the fundamental technologies in the next generation' are introduced and the significance of their naming is described. 2 tabs.

Perceptual Plasticity for Auditory Object Recognition

Science.gov (United States)

Heald, Shannon L. M.; Van Hedger, Stephen C.; Nusbaum, Howard C.

2017-01-01

In our auditory environment, we rarely experience the exact acoustic waveform twice. This is especially true for communicative signals that have meaning for listeners. In speech and music, the acoustic signal changes as a function of the talker (or instrument), speaking (or playing) rate, and room acoustics, to name a few factors. Yet, despite this acoustic variability, we are able to recognize a sentence or melody as the same across various kinds of acoustic inputs and determine meaning based on listening goals, expectations, context, and experience. The recognition process relates acoustic signals to prior experience despite variability in signal-relevant and signal-irrelevant acoustic properties, some of which could be considered as “noise” in service of a recognition goal. However, some acoustic variability, if systematic, is lawful and can be exploited by listeners to aid in recognition. Perceivable changes in systematic variability can herald a need for listeners to reorganize perception and reorient their attention to more immediately signal-relevant cues. This view is not incorporated currently in many extant theories of auditory perception, which traditionally reduce psychological or neural representations of perceptual objects and the processes that act on them to static entities. While this reduction is likely done for the sake of empirical tractability, such a reduction may seriously distort the perceptual process to be modeled. We argue that perceptual representations, as well as the processes underlying perception, are dynamically determined by an interaction between the uncertainty of the auditory signal and constraints of context. This suggests that the process of auditory recognition is highly context-dependent in that the identity of a given auditory object may be intrinsically tied to its preceding context. To argue for the flexible neural and psychological updating of sound-to-meaning mappings across speech and music, we draw upon examples

Entity associations for search

NARCIS (Netherlands)

Reinanda, R.

2017-01-01

In this thesis, we investigate the broad problem of computing entity associations for search. Specifically, we consider three types of entity association: entity-entity, entity-document, and entity-aspect associations. We touch upon various domains, starting with specific domains such as the

THE IMPORTANCE OF BRAND NAME AND QUALITY IN THE RETAIL FOOD INDUSTRY

OpenAIRE

Apelbaum, Eidan

1999-01-01

This paper analyzes the role of brand name recognition and product quality on the competition between national brands and private labels in the retail food industry. Theoretical and empirical evidence is provided to show that both marketing tools play a significant role, but in quite different ways. Quality improvements by one firm will intensify the competition; one firm will gain at the expense of its competitor. Whereas, increasing brand name recognition relaxes the competition, and both f...

Letter-case information and the identification of brand names.

Science.gov (United States)

Perea, Manuel; Jiménez, María; Talero, Fernanda; López-Cañada, Soraya

2015-02-01

A central tenet of most current models of visual-word recognition is that lexical units are activated on the basis of case-invariant abstract letter representations. Here, we examined this assumption by using a unique type of words: brand names. The rationale of the experiments is that brand names are archetypically printed either in lowercase (e.g., adidas) or uppercase (e.g., IKEA). This allows us to present the brand names in their standard or non-standard case configuration (e.g., adidas, IKEA vs. ADIDAS, ikea, respectively). We conducted two experiments with a brand-decision task ('is it a brand name?'): a single-presentation experiment and a masked priming experiment. Results in the single-presentation experiment revealed faster identification times of brand names in their standard case configuration than in their non-standard case configuration (i.e., adidas faster than ADIDAS; IKEA faster than ikea). In the masked priming experiment, we found faster identification times of brand names when they were preceded by an identity prime that matched its standard case configuration than when it did not (i.e., faster response times to adidas-adidas than to ADIDAS-adidas). Taken together, the present findings strongly suggest that letter-case information forms part of a brand name's graphemic information, thus posing some limits to current models of visual-word recognition. © 2014 The British Psychological Society.

Nomenclatural availability of the names applied to “varieties” of the green toad (Bufo viridis subgroup in the Italian territory, with emphasis on the variety lineata of Ninni (Anura: Bufonidae

Directory of Open Access Journals (Sweden)

Nicola Novarini

2010-07-01

Full Text Available Recent molecular investigations on Eurasian green toads led to the recognition of distinct lineages and to the establishment of new taxa within the former Bufo viridis; as a consequence, significant range-wide nomenclatural changes have been proposed, although some uncertainties remained on the available names applicable within the Italian territory. In order to contribute to clarify the matter, we evaluated, under the provisions of the International Code of Zoological Nomenclature, the nomenclatural availability of all the names that have been applied to infrasubspecific entities of the Bufo viridis subgroup within the Italian territory. We also provided a historical overview of the usage of all these names, as well as detailed information on the original material upon which the variety lineata of A.P. Ninni was established. Our analysis supports the view that only the names crucigera Eichwald, 1831 and balearica Boettger, 1880 are available, the former being however junior synonym of B. viridis Laurenti, 1768, whereas the names acutirostris and obtusirostris of Lessona, lineata of Ninni, concolor and maculata of Camerano, and nardoi of Paolucci, Fuhn and Bruno are all not available.

Financial Management of Economic Entity from the Perspective of Alternative Approach

Directory of Open Access Journals (Sweden)

Victor Munteanu

2016-12-01

Full Text Available Throughout the study the financial management presented is divided into three directions, namely financial analysis, financial planning and financial strategy, focusing on increasing the quality of financial management conducted at the economic entity by identifying an easier possible use for a system of alternative decisions in order to increase the profitability. The study also aims to identify new meanings of financial accounting information system in performing the managerial act through alternative decisions, trying to highlight the need to create a management tool generator of variants possible to be adopted with an impact on their application in the economic entity as a whole. Based on qualitative research on the financial management act, it is revealed the importance of the financial management act manifested in the economic entity and also its quality improvement through simulations targeting the management through budget system.

NCBI disease corpus: a resource for disease name recognition and concept normalization.

Science.gov (United States)

Doğan, Rezarta Islamaj; Leaman, Robert; Lu, Zhiyong

2014-02-01

knowledge-based disease normalization methods with a best performance in F-measure of 63.7%. These results show that the NCBI disease corpus has the potential to significantly improve the state-of-the-art in disease name recognition and normalization research, by providing a high-quality gold standard thus enabling the development of machine-learning based approaches for such tasks. The NCBI disease corpus, guidelines and other associated resources are available at: http://www.ncbi.nlm.nih.gov/CBBresearch/Dogan/DISEASE/. Published by Elsevier Inc.

Programming Entity Framework

CERN Document Server

Lerman, Julia

2009-01-01

Programming Entity Framework is a thorough introduction to Microsoft's new core framework for modeling and interacting with data in .NET applications. This highly-acclaimed book not only gives experienced developers a hands-on tour of the Entity Framework and explains its use in a variety of applications, it also provides a deep understanding of its architecture and APIs -- knowledge that will be extremely valuable as you shift to the Entity Framework version in .NET Framework 4.0 and Visual Studio 2010. From the Entity Data Model (EDM) and Object Services to EntityClient and the Metadata Work

EUPHORBIA SINCLAIRIANA, AN OLDER NAME FOR THE WIDESPREAD EUPHORBIA ELATA

Directory of Open Access Journals (Sweden)

BERNAL RODRIGO

2006-12-01

Full Text Available A comparison of collections of Euphorbia elata from accross its range withspecimens of E. sinclairiana from its only known locality, the island of Gorgona,off the Pacific coast of Colombia, shows that the two entities are better treated asconspecific, under the older name E. sinclairiana.

Eye movements during object recognition in visual agnosia.

Science.gov (United States)

Charles Leek, E; Patterson, Candy; Paul, Matthew A; Rafal, Robert; Cristino, Filipe

2012-07-01

This paper reports the first ever detailed study about eye movement patterns during single object recognition in visual agnosia. Eye movements were recorded in a patient with an integrative agnosic deficit during two recognition tasks: common object naming and novel object recognition memory. The patient showed normal directional biases in saccades and fixation dwell times in both tasks and was as likely as controls to fixate within object bounding contour regardless of recognition accuracy. In contrast, following initial saccades of similar amplitude to controls, the patient showed a bias for short saccades. In object naming, but not in recognition memory, the similarity of the spatial distributions of patient and control fixations was modulated by recognition accuracy. The study provides new evidence about how eye movements can be used to elucidate the functional impairments underlying object recognition deficits. We argue that the results reflect a breakdown in normal functional processes involved in the integration of shape information across object structure during the visual perception of shape. Copyright © 2012 Elsevier Ltd. All rights reserved.

Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls

Directory of Open Access Journals (Sweden)

Wolfgang Gaissmeier

2011-02-01

Full Text Available We investigated the extent to which the human capacity for recognition helps to forecast political elections: We compared naive recognition-based election forecasts computed from convenience samples of citizens' recognition of party names to (i standard polling forecasts computed from representative samples of citizens' voting intentions, and to (ii simple---and typically very accurate---wisdom-of-crowds-forecasts computed from the same convenience samples of citizens' aggregated hunches about election results. Results from four major German elections show that mere recognition of party names forecast the parties' electoral success fairly well. Recognition-based forecasts were most competitive with the other models when forecasting the smaller parties' success and for small sample sizes. However, wisdom-of-crowds-forecasts outperformed recognition-based forecasts in most cases. It seems that wisdom-of-crowds-forecasts are able to draw on the benefits of recognition while at the same time avoiding its downsides, such as lack of discrimination among very famous parties or recognition caused by factors unrelated to electoral success. Yet it seems that a simple extension of the recognition-based forecasts---asking people what proportion of the population would recognize a party instead of whether they themselves recognize it---is also able to eliminate these downsides.

Music recognition in frontotemporal lobar degeneration and Alzheimer disease.

Science.gov (United States)

Johnson, Julene K; Chang, Chiung-Chih; Brambati, Simona M; Migliaccio, Raffaella; Gorno-Tempini, Maria Luisa; Miller, Bruce L; Janata, Petr

2011-06-01

To compare music recognition in patients with frontotemporal dementia, semantic dementia, Alzheimer disease, and controls and to evaluate the relationship between music recognition and brain volume. Recognition of familiar music depends on several levels of processing. There are few studies about how patients with dementia recognize familiar music. Subjects were administered tasks that assess pitch and melody discrimination, detection of pitch errors in familiar melodies, and naming of familiar melodies. There were no group differences on pitch and melody discrimination tasks. However, patients with semantic dementia had considerable difficulty naming familiar melodies and also scored the lowest when asked to identify pitch errors in the same melodies. Naming familiar melodies, but not other music tasks, was strongly related to measures of semantic memory. Voxel-based morphometry analysis of brain magnetic resonance imaging showed that difficulty in naming songs was associated with the bilateral temporal lobes and inferior frontal gyrus, whereas difficulty in identifying pitch errors in familiar melodies correlated with primarily the right temporal lobe. The results support a view that the anterior temporal lobes play a role in familiar melody recognition, and that musical functions are affected differentially across forms of dementia.

Music Recognition in Frontotemporal Lobar Degeneration and Alzheimer Disease

Science.gov (United States)

Johnson, Julene K; Chang, Chiung-Chih; Brambati, Simona M; Migliaccio, Raffaella; Gorno-Tempini, Maria Luisa; Miller, Bruce L; Janata, Petr

2013-01-01

Objective To compare music recognition in patients with frontotemporal dementia, semantic dementia, Alzheimer disease, and controls and to evaluate the relationship between music recognition and brain volume. Background Recognition of familiar music depends on several levels of processing. There are few studies about how patients with dementia recognize familiar music. Methods Subjects were administered tasks that assess pitch and melody discrimination, detection of pitch errors in familiar melodies, and naming of familiar melodies. Results There were no group differences on pitch and melody discrimination tasks. However, patients with semantic dementia had considerable difficulty naming familiar melodies and also scored the lowest when asked to identify pitch errors in the same melodies. Naming familiar melodies, but not other music tasks, was strongly related to measures of semantic memory. Voxel-based morphometry analysis of brain MRI showed that difficulty in naming songs was associated with the bilateral temporal lobes and inferior frontal gyrus, whereas difficulty in identifying pitch errors in familiar melodies correlated with primarily the right temporal lobe. Conclusions The results support a view that the anterior temporal lobes play a role in familiar melody recognition, and that musical functions are affected differentially across forms of dementia. PMID:21617528

Human-machine interaction to disambiguate entities in unstructured text and structured datasets

Science.gov (United States)

Ward, Kevin; Davenport, Jack

2017-05-01

Creating entity network graphs is a manual, time consuming process for an intelligence analyst. Beyond the traditional big data problems of information overload, individuals are often referred to by multiple names and shifting titles as they advance in their organizations over time which quickly makes simple string or phonetic alignment methods for entities insufficient. Conversely, automated methods for relationship extraction and entity disambiguation typically produce questionable results with no way for users to vet results, correct mistakes or influence the algorithm's future results. We present an entity disambiguation tool, DRADIS, which aims to bridge the gap between human-centric and machinecentric methods. DRADIS automatically extracts entities from multi-source datasets and models them as a complex set of attributes and relationships. Entities are disambiguated across the corpus using a hierarchical model executed in Spark allowing it to scale to operational sized data. Resolution results are presented to the analyst complete with sourcing information for each mention and relationship allowing analysts to quickly vet the correctness of results as well as correct mistakes. Corrected results are used by the system to refine the underlying model allowing analysts to optimize the general model to better deal with their operational data. Providing analysts with the ability to validate and correct the model to produce a system they can trust enables them to better focus their time on producing higher quality analysis products.

LINNAEUS: A species name identification system for biomedical literature

Directory of Open Access Journals (Sweden)

Nenadic Goran

2010-02-01

Full Text Available Abstract Background The task of recognizing and identifying species names in biomedical literature has recently been regarded as critical for a number of applications in text and data mining, including gene name recognition, species-specific document retrieval, and semantic enrichment of biomedical articles. Results In this paper we describe an open-source species name recognition and normalization software system, LINNAEUS, and evaluate its performance relative to several automatically generated biomedical corpora, as well as a novel corpus of full-text documents manually annotated for species mentions. LINNAEUS uses a dictionary-based approach (implemented as an efficient deterministic finite-state automaton to identify species names and a set of heuristics to resolve ambiguous mentions. When compared against our manually annotated corpus, LINNAEUS performs with 94% recall and 97% precision at the mention level, and 98% recall and 90% precision at the document level. Our system successfully solves the problem of disambiguating uncertain species mentions, with 97% of all mentions in PubMed Central full-text documents resolved to unambiguous NCBI taxonomy identifiers. Conclusions LINNAEUS is an open source, stand-alone software system capable of recognizing and normalizing species name mentions with speed and accuracy, and can therefore be integrated into a range of bioinformatics and text-mining applications. The software and manually annotated corpus can be downloaded freely at http://linnaeus.sourceforge.net/.

Enhancing spoken connected-digit recognition accuracy by error ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

nition systems have gained acceptable accuracy levels, the accuracy of recognition of current connected ... bar code and ISBN1 library code to name a few. ..... Kopec G, Bush M 1985 Network-based connected-digit recognition. IEEE Trans.

The roles of perceptual and conceptual information in face recognition.

Science.gov (United States)

Schwartz, Linoy; Yovel, Galit

2016-11-01

The representation of familiar objects is comprised of perceptual information about their visual properties as well as the conceptual knowledge that we have about them. What is the relative contribution of perceptual and conceptual information to object recognition? Here, we examined this question by designing a face familiarization protocol during which participants were either exposed to rich perceptual information (viewing each face in different angles and illuminations) or with conceptual information (associating each face with a different name). Both conditions were compared with single-view faces presented with no labels. Recognition was tested on new images of the same identities to assess whether learning generated a view-invariant representation. Results showed better recognition of novel images of the learned identities following association of a face with a name label, but no enhancement following exposure to multiple face views. Whereas these findings may be consistent with the role of category learning in object recognition, face recognition was better for labeled faces only when faces were associated with person-related labels (name, occupation), but not with person-unrelated labels (object names or symbols). These findings suggest that association of meaningful conceptual information with an image shifts its representation from an image-based percept to a view-invariant concept. They further indicate that the role of conceptual information should be considered to account for the superior recognition that we have for familiar faces and objects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Consistency of cross-lingual pronunciation of South African personal names

CSIR Research Space (South Africa)

Kgampe, M

2010-11-01

Full Text Available electronic pronunciation dictionaries (used in spoken dialogue systems) with the most important variants that occur in practice, in order to increase the accuracy of name recognition....

Challenges with the financial reporting of biological assets by public entities in South Africa

Directory of Open Access Journals (Sweden)

Deon Scott

2016-03-01

Full Text Available Fair value accounting of biological assets in the public sector was introduced with the adoption of the public-sector-specific accounting standard: Generally Recognised Accounting Practice (GRAP 101. The public sector currently reports on various bases of accounting. Public entities and municipalities report in terms of accrual accounting, and government departments report on the modified cash basis. The lack of a uniform basis of accounting impedes the comparability of financial information. The implementation of GRAP 101 in the public sector is important in facilitating comparability of financial information regarding biological assets. This paper is based on a content analysis of the annual reports of 10 relevant public entities in South Africa and specifically details the challenges that public entities encounter with the application of GRAP 101. These challenges, and how they were addressed by a public entity that adopted and applied GRAP 101, namely the Accelerated and Shared Growth Initiative South Africa – Eastern Cape (AsgiSA-EC, are documented in this research.

OBJECTIVES AND FUNCTIONS OF FINANCIAL STATEMENTS UNDER ACCOUNTING INFORMATION SYSTEM AT TRADE ENTITIES

Directory of Open Access Journals (Sweden)

CARAIMAN ADRIAN-COSMIN

2015-12-01

Full Text Available As Radu said (2009, pag. 91 [6] logical approach developed by accounting, presentation of an exact image of the heritage, the financial situation and financial results, based on a rational thought, a gradual knowledge domain investigated, concepts, tools and processes that allow a better understanding of the essence of economic phenomena and processes. Theoretical framework brings together a number of concepts that are considered fundamental to regulatory or accounting systems applied at the level of the entity to have clearly specified the coordinates of the base and are able to achieve cohesion between the objective of financial statements as true and fair view, financial information and policy characteristics and estimation techniques as a form of expression towards the recognition and presentation of economic reality. The author considers, in the context of the defined system applied within the accounting entities in general, that principles, presents not only a crucial premise, as well as needed necessity in order to show an exact image of the performance and financial position of the entity.

Solidarity liability of federative entities and “side effects” for the right to health

Directory of Open Access Journals (Sweden)

Felipe Asensi

2016-02-01

Full Text Available The judicial enforcement of the right to health in Brazil raises advances and challenges for public policies. This article analyzes two judicial decisions from the 4th Region’s Federal Court in 2014 admitting the concurrent and solidary responsibility of federative entities in the supply of medicines. In both decisions, the appeal was allowed and the idea that federative entities have concurrent competence and solidarity in health was reinforced. On the one hand, a common example of interaction between the law and the health is observed in these decisions; on the other, a production of tensions and contradictions is identified. At first glance, the recognition of the solidary responsibility of federative entities may seem strongly positive from the user’s perspective, and this will lead to having more users going to courts to claim their right to health. However, from a management perspective, it brings challenges as there will be overpayment of some entities of the federation at the expense of others. In this sense, and based on cases, the main rules of competence currently used in health public policies will be presented. Major advances, limits and challenges of recognizing the solidary responsibility of federative entities as well as some “side effects” that some court decisions may bring will also be discussed.

An Agent Framework for Recognition of Graphic Units in Drawings

NARCIS (Netherlands)

Achten, H.H.; Jessurun, A.J.; Koszewski, K.; Wrona, S.

2002-01-01

Architects use graphic conventions in their drawings that have meaningful content to the design task. In previous work, such well-defined sets of graphic entities have been identified and defined. These sets are called graphic units. In this paper, we discuss how graphic unit recognition in drawings

New FASB standard addresses revenue recognition considerations.

Science.gov (United States)

McKee, Thomas E

2015-12-01

Healthcare organizations are expected to apply the following steps in revenue recognition under the new standard issued in May 2014 by the Financial Accounting Standards Board: Identify the customer contract. Identify the performance obligations in the contract. Determine the transaction price. Allocate the transaction price to the performance obligations in the contract. Recognize revenue when--or in some circumstances, as--the entity satisfies the performance obligation.

A graph-search framework for associating gene identifiers with documents

Directory of Open Access Journals (Sweden)

Cohen William W

2006-10-01

Full Text Available Abstract Background One step in the model organism database curation process is to find, for each article, the identifier of every gene discussed in the article. We consider a relaxation of this problem suitable for semi-automated systems, in which each article is associated with a ranked list of possible gene identifiers, and experimentally compare methods for solving this geneId ranking problem. In addition to baseline approaches based on combining named entity recognition (NER systems with a "soft dictionary" of gene synonyms, we evaluate a graph-based method which combines the outputs of multiple NER systems, as well as other sources of information, and a learning method for reranking the output of the graph-based method. Results We show that named entity recognition (NER systems with similar F-measure performance can have significantly different performance when used with a soft dictionary for geneId-ranking. The graph-based approach can outperform any of its component NER systems, even without learning, and learning can further improve the performance of the graph-based ranking approach. Conclusion The utility of a named entity recognition (NER system for geneId-finding may not be accurately predicted by its entity-level F1 performance, the most common performance measure. GeneId-ranking systems are best implemented by combining several NER systems. With appropriate combination methods, usefully accurate geneId-ranking systems can be constructed based on easily-available resources, without resorting to problem-specific, engineered components.

The Economic Risks Arising from the Analysis of the Balance Sheet of an Economic Entity

Directory of Open Access Journals (Sweden)

Andreea Mihaela Marin

2016-01-01

Full Text Available Any economic entity operates under probability and risk. In a general acceptation, risk means the validity of the result obtained under pressure of the economic environment; in other words, the risk is the potential damage posed to heritage, interests and affect the entity. In this paper we want to capture, the calculation in terms of the balance sheet analysis of the three risks, which can be measured on the basis of the balance sheet data and indicators, namely: the operational risk, financial risk, and the risk of bankruptcy.

Face-Name Associative Recognition Deficits in Subjective Cognitive Decline and Mild Cognitive Impairment.

Science.gov (United States)

Polcher, Alexandra; Frommann, Ingo; Koppara, Alexander; Wolfsgruber, Steffen; Jessen, Frank; Wagner, Michael

2017-01-01

There is a need for more sensitive neuropsychological tests to detect subtle cognitive deficits emerging in the preclinical stage of Alzheimer's disease (AD). Associative memory is a cognitive function supported by the hippocampus and affected early in the process of AD. We developed a short computerized face-name associative recognition test (FNART) and tested whether it would detect memory impairment in memory clinic patients with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). We recruited 61 elderly patients with either SCD (n = 32) or MCI (n = 29) and 28 healthy controls (HC) and compared performance on FNART, self-reported cognitive deterioration in different domains (ECog-39), and, in a reduced sample (n = 46), performance on the visual Paired Associates Learning of the CANTAB battery. A significant effect of group on FNART test performance in the total sample was found (p < 0.001). Planned contrasts indicated a significantly lower associative memory performance in the SCD (p = 0.001, d = 0.82) and MCI group (p < 0.001, d = 1.54), as compared to HCs, respectively. The CANTAB-PAL discriminated only between HC and MCI, possibly because of reduced statistical power. Adjusted for depression, performance on FNART was significantly related to ECog-39 Memory in SCD patients (p = 0.024) but not in MCI patients. Associative memory is substantially impaired in memory clinic patients with SCD and correlates specifically with memory complaints at this putative preclinical stage of AD. Further studies will need to examine the predictive validity of the FNART in SCD patients with regard to longitudinal (i.e., conversion to MCI/AD) and biomarker outcomes.

Spatial distribution and influence factors of interprovincial terrestrial physical geographical names in China

Science.gov (United States)

Zhang, S.; Wang, Y.; Ju, H.

2017-12-01

The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. Based on toponomy dictionaries and different thematic maps, the attributes and the spatial extent of the interprovincial terrestrial physical geographical names (ITPGN, including terrain ITPGN and water ITPGN) were extracted. The coefficient of variation and Moran's I were combined together to measure the spatial variation and spatial association of ITPGN. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. The results showed that 11325 ITPGN were extracted, including 7082 terrain ITPGN and 4243 water ITPGN. Hunan Province had the largest number of ITPGN in China, and Shanghai had the smallest number. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. Further analysis showed that the number of ITPGN was positively related with the relative elevation and the population where the relative elevation was lower than 2000m and the population was less than 50 million. But the number of ITPGN showed a negative relationship with the two factors when their values became larger, indicating a large number of unnamed entities existed in complex terrain areas and a decreasing number of terrestrial physical geographical entities in densely populated area. Based on these analysis, we suggest the government take the ITPGN as management units to realize a balance development between different parts of the entities and strengthen the geographical names census and the nomination of unnamed interprovincial physical geographical entities. This study also demonstrated that the methods of literature survey, coefficient of variation and Moran's I can be combined to enhance the understanding of the spatial pattern of ITPGN.

Fikční jména, fikční entity a role předstírání: chvála abstinence

Czech Academy of Sciences Publication Activity Database

Koťátko, Petr

2016-01-01

Roč. 26, č. 53 (2016), s. 93-101 ISSN 0862-8440 Institutional support: RVO:67985955 Keywords : fictional names * fictional entities * fictional discourse * abstract entities * pretense Subject RIV: AA - Philosophy ; Religion http://hdl.handle.net/11104/0259936

Age invariance in semantic and episodic metamemory: both younger and older adults provide accurate feeling-of-knowing for names of faces.

Science.gov (United States)

Eakin, Deborah K; Hertzog, Christopher; Harris, William

2014-01-01

Age differences in feeling-of-knowing (FOK) accuracy were examined for both episodic memory and semantic memory. Younger and older adults either viewed pictures of famous faces (semantic memory) or associated non-famous faces and names (episodic memory) and were tested on their memory for the name of the presented face. Participants viewed the faces again and made a FOK prediction about future recognition of the name associated with the presented face. Finally, four-alternative forced-choice recognition memory for the name, cued by the face, was tested and confidence judgments (CJs) were collected for each recognition response. Age differences were not obtained in semantic memory or the resolution of semantic FOKs, defined by within-person correlations of FOKs with recognition memory performance. Although age differences were obtained in level of episodic memory, there were no age differences in the resolution of episodic FOKs. FOKs for correctly recognized items correlated reliably with CJs for both types of materials, and did not differ by age group. The results indicate age invariance in monitoring of retrieval processes for name-face associations.

Age Invariance in Semantic and Episodic Metamemory: Both Younger and Older Adults Provide Accurate Feeling of Knowing For Names of Faces

Science.gov (United States)

Eakin, Deborah K.; Hertzog, Christopher; Harris, William

2013-01-01

Age differences in feeling-of-knowing (FOK) accuracy were examined for both episodic memory and semantic memory. Younger and older adults either viewed pictures of famous faces (semantic memory) or associated nonfamous faces and names (episodic memory) and were tested on their memory for the name of the presented face. Participants viewed the faces again and made a FOK prediction about future recognition of the name associated with the presented face. Finally, four-alternative forced-choice recognition memory for the name, cued by the face, was tested and confidence judgments (CJs) were collected for each recognition response. Age differences were not obtained in semantic memory or the resolution of semantic FOKs, defined by within-person correlations of FOKs with recognition memory performance. Although age differences were obtained in level of episodic memory, there were no age differences in the resolution of episodic FOKs. FOKs for correctly recognized items correlated reliably with CJs for both types of materials, and did not differ by age group. The results indicate age invariance in monitoring of retrieval processes for name-face associations. PMID:23537379

A Hybrid Approach for NER System for Scarce Resourced Language-URDU: Integrating n-gram with Rules and Gazetteers

Directory of Open Access Journals (Sweden)

Saeeda Naz

2015-10-01

Full Text Available We present a hybrid NER (Name Entity Recognition system for Urdu script by integration of n-gram model (unigram and bigram, rules and gazetteers. We used prefix and suffix characters for rule construction instead of first name and last name lists or potential terms on the output list that is produced by n-gram model. Evaluation of the system is performed on two corpora, the IJCNLP NE (Named Entity corpus and CRL NE corpus in Urdu text. The system achieved 92.65 and 87.6% using hybrid unigram and 92.47 and 86.83% using hybrid bigram on IJCNLP NE corpus and CRL NE corpus, respectively.

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems.

Science.gov (United States)

Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A

2017-03-01

The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework.

PRIVATE LAW EFFECTS OF THE NON-RECOGNITION OF STATES' EXISTENCE AND TERRITORIAL CHANGES

Directory of Open Access Journals (Sweden)

Ioan-Luca VLAD

2015-07-01

Full Text Available The study presents an outline of the effects in private law (including private international law of the non-recognition of a state or a change of territory. Specifically, it addresses the question of what measures can another state take, in the field of private law, in order to give effect to its policy of not recognizing a state or a territorial annexation, and, in parallel, what are the means available to private parties with links to the unrecognized state or territory. The study is structured in two parts, namely 1 the effects in private law of the non-recognition of a state; and 2 the effect in private law of the non-recognition of an annexation of territory. I will make specific references in particular to the situation in Transnistria and Crimea, as examples of the two issues being addressed. The study intends to be a guide of past and present state practice at the legislative and judicial level, as well as presenting the connections between instruments of public international law, such as Sanctions Resolutions of the UN Security Council, and normative instruments of private law, such as rules of civil procedure, which must adapt to the policy of non-recognition adopted by (or imposed on states. The study also presents specific examples of situations or administrative practices which create practical problems, and result from the existence of a non-recognized entity or change of territory: issues like air traffic coordination, postal traffic, the change in the official currency of a territory, questions of citizenship etc., the aim being to present the reader with a full picture of the issues and intricacies resulting from irregularities existing at the level of the international community of states.

Influences on Facial Emotion Recognition in Deaf Children

Science.gov (United States)

Sidera, Francesc; Amadó, Anna; Martínez, Laura

2017-01-01

This exploratory research is aimed at studying facial emotion recognition abilities in deaf children and how they relate to linguistic skills and the characteristics of deafness. A total of 166 participants (75 deaf) aged 3-8 years were administered the following tasks: facial emotion recognition, naming vocabulary and cognitive ability. The…

Left posterior BA37 is involved in object recognition: a TMS study

DEFF Research Database (Denmark)

Stewart, Lauren; Meyer, Bernd-Ulrich; Frith, Uta

2001-01-01

Functional imaging studies have proposed a role for left BA37 in phonological retrieval, semantic processing, face processing and object recognition. The present study targeted the posterior aspect of BA37 to see whether a deficit, specific to one of the above types of processing could be induced...... to name pictures when TMS was given over lBA37 compared to vertex or rBA37. rTMS over lBA37 had no significant effect on word reading, nonword reading or colour naming. The picture naming deficit is suggested to result from a disruption to object recognition processes. This study corroborates the finding...... from a recent imaging study, that the most posterior part of left hemispheric BA37 has a necessary role in object recognition....

Discriminative learning for speech recognition

CERN Document Server

He, Xiadong

2008-01-01

In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-functio

Programming Entity Framework

CERN Document Server

Lerman, Julia

2010-01-01

Get a thorough introduction to ADO.NET Entity Framework 4 -- Microsoft's core framework for modeling and interacting with data in .NET applications. The second edition of this acclaimed guide provides a hands-on tour of the framework latest version in Visual Studio 2010 and .NET Framework 4. Not only will you learn how to use EF4 in a variety of applications, you'll also gain a deep understanding of its architecture and APIs. Written by Julia Lerman, the leading independent authority on the framework, Programming Entity Framework covers it all -- from the Entity Data Model and Object Service

The "Decorative" Female Model: Sexual Stimuli and the Recognition of Advertisements

Science.gov (United States)

LaChance, Charles C.; And Others

1977-01-01

Examines the impact of the decorative or functionless female models in print advertising and indicates that models facilitate recognition of model/related information but do little to increase the recognition of brand names.

Vitamin K deficiency bleeding presenting as nodular purpura in infancy: A rare and life-threatening entity

Directory of Open Access Journals (Sweden)

Pratik Gahalaut

2013-01-01

Full Text Available Vitamin K deficiency bleeding (VKDB disorder is an uncommon entity, which occurs due to inadequate activity of vitamin K-dependant coagulation factors. An 8-months-old exclusively breast-fed male infant presented with multiple, purpuric and nodular non-collapsible swellings on trunk of 4 days duration. Investigations revealed raised activated partial thromboplastin time and prothrombintime. Fibrinogen level and platelet counts were normal. Late VKDB usually presents as intra-cranial or mucosal hemorrhages. [1] Though skin and mucosal bleeding may occur in 1/3 rd of infants with VKDB, ′nodular purpura′ is not the common presenting feature. Earlier recognition of VKDB and immediate investigation/treatment helps prevent the potentially fatal outcome of the disease. Very little is mentioned about this entity in dermatology literature.

Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion

Science.gov (United States)

Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

2016-01-01

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13. Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract PMID:27504009

22 CFR 96.5 - Requirement that accrediting entity be a nonprofit or public entity.

Science.gov (United States)

2010-04-01

... administering standards for entities providing child welfare services; or (b) A public entity (other than a... political subdivision, agency, or instrumentality thereof, that is responsible for licensing adoption agencies in a State and that has expertise in developing and administering standards for entities providing...

Competition in prescription drug markets: the roles of trademarks, advertising, and generic names.

Science.gov (United States)

Feldman, Roger; Lobo, Félix

2013-08-01

We take on two subjects of controversy among economists-advertising and trademarks-in the context of the market for generic drugs. We outline a model in which trademarks for drug names reduce search costs but increase product differentiation. In this particular framework, trademarks may not benefit consumers. In contrast, the generic names of drugs or "International Nonproprietary Names" (INN) have unquestionable benefits in both economic theory and empirical studies. We offer a second model where advertising of a brand-name drug creates recognition for the generic name. The monopoly patent-holder advertises less than in the absence of a competitive spillover.

Song Recognition without Identification: When People Cannot "Name that Tune" but Can Recognize It as Familiar

Science.gov (United States)

Kostic, Bogdan; Cleary, Anne M.

2009-01-01

Recognition without identification (RWI) is a common day-to-day experience (as when recognizing a face or a tune as familiar without being able to identify the person or the song). It is also a well-established laboratory-based empirical phenomenon: When identification of recognition test items is prevented, participants can discriminate between…

One tagger, many uses

DEFF Research Database (Denmark)

Jensen, Lars Juhl

2016-01-01

Automatic annotation of text is an important complement to manual annotation, because the latter is highly labour intensive. We have developed a fast dictionary-based named entity recognition (NER) system and addressed a wide variety of biomedical problems by applied it to text from many differen....... Despite the simplicity of the approach, it typically achieves 80-90% precision and 70-80% recall. Many of the underlying dictionaries were built from open biomedical ontologies, which further facilitate integration of the text-mining results with evidence from other sources.......Automatic annotation of text is an important complement to manual annotation, because the latter is highly labour intensive. We have developed a fast dictionary-based named entity recognition (NER) system and addressed a wide variety of biomedical problems by applied it to text from many different...

Evaluating Stream Filtering for Entity Profile Updates in TREC 2012, 2013, and 2014 (KBA Track Overview, Notebook Paper)

Science.gov (United States)

2014-11-01

possible future directions that build on the KBA experience.   Data Assets   In addition to the three hundred run submissions from diverse systems...form name of an entity and assigning a confidence score based on the number of matches of tokens in the name. See code in github [6]. macro-P...131 64 GENDER 4 2 FoundedBy     56 30 NAME 2 2 DateOfDeath     54 12 TOP_MEMBERS_EMPLOYEES 2 1 EmployeeOf     44 19 WON_AWARD 1 1

Obligatory and facultative brain regions for voice-identity recognition

Science.gov (United States)

Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

2018-01-01

Abstract Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal

EPONYMY BASED ON NAMES OF COMPANIES

Directory of Open Access Journals (Sweden)

Éva Kovács

2016-03-01

Full Text Available As is generally defined, eponymy, one of the word-formation processes refers to the derivation of a name of a city, country, era, institution, or other place or thing from that of a person such as sandwich, wellington, mackintosh or cardigan. Eponymy can be classified in several ways, some refer to foods (Pizza Margaritha, diseases (Alzheimer disease, places (Washington, scientific laws (Archimedes’s principle and sport terms (Axel jump, whereas others indicate trademarks, brand names (aspirin, prizes, awards (Nobel Prize, inventions (Rubic’s Cube, ideologies (Darwinism, colleges, universities (Stanford University and companies (Ford. The present paper discusses eponyms which denote companies based on the name of their founder(s (e.g. Porsche, Siemens, Gucci, Campari, Cadbury, McDonald’s and Walt Disney, etc. by revealing what kind of a metonymic relationship is manifested in them. Cognitive linguists, such as Lakoff and Johnson (1980, Radden and Kövecses (1999 and Kövecses (2002 state that metonymy is essentially a conceptual phenomenon, in which one conceptual entity, the vehicle, provides mental access to another conceptual entity, the target, within the same idealized cognitive model. In fact, metonymy is part of our everyday way of thinking, and is grounded in experience. Common metonymies include PRODUCER FOR PRODUCT (Pass me the Shakespeare on the top shelf., PLACE FOR EVENT (Iraq nearly cost Tony Blair the premiership, PLACE FOR INSTITUTION (Downing Street refused comment., PART FOR THE WHOLE (She’s not just a pretty face., WHOLE FOR THE PART (England beat Australia in the 2003 Rugby World Cup final. and EFFECT FOR CAUSE (He has a long face.. Following the cognitive approach to metonyms, I tentatively suggest that the metonymy PRODUCER FOR THE PRODUCT can be observed in the case of car makes, products of famous fashion houses, cosmetics and drinks as is illustrated by examples like He’s bought a Ferrari. I ate a McDonald or

Programming Drupal 7 entities

CERN Document Server

Michael, Sammy

2013-01-01

The book follows a standard tutorial-based approach to create, retrieve, update, and delete Drupal 7 entities, their properties and fields.Programming Drupal 7 Entities is perfect for intermediate or advanced developers new to Drupal entity development who are looking to get a good grounding in how to code using the new paradigm. It's assumed that you will have some experience in PHP development already, and being vaguely familiar with Drupal, GIT, and Drush will also help.

Neighborhood Frequency Effect in Chinese Word Recognition: Evidence from Naming and Lexical Decision

Science.gov (United States)

Li, Meng-Feng; Gao, Xin-Yu; Chou, Tai-Li; Wu, Jei-Tun

2017-01-01

Neighborhood frequency is a crucial variable to know the nature of word recognition. Different from alphabetic scripts, neighborhood frequency in Chinese is usually confounded by component character frequency and neighborhood size. Three experiments were designed to explore the role of the neighborhood frequency effect in Chinese and the stimuli…

Brand name logo recognition of fast food and healthy food among children.

Science.gov (United States)

Arredondo, Elva; Castaneda, Diego; Elder, John P; Slymen, Donald; Dozier, David

2009-02-01

The fast food industry has been increasingly criticized for creating brand loyalty in young consumers. Food marketers are well versed in reaching children and youth given the importance of brand loyalty on future food purchasing behavior. In addition, food marketers are increasingly targeting the Hispanic population given their growing spending power. The fast food industry is among the leaders in reaching youth and ethnic minorities through their marketing efforts. The primary objective of this study was to determine if young children recognized fast food restaurant logos at a higher rate than other food brands. Methods Children (n = 155; 53% male; 87% Hispanic) ages 4-8 years were recruited from elementary schools and asked to match 10 logo cards to products depicted on a game board. Parents completed a survey assessing demographic and psychosocial characteristics associated with a healthy lifestyle in the home. Results Older children and children who were overweight were significantly more likely to recognize fast food restaurant logos than other food logos. Moreover, parents' psychosocial and socio-demographic characteristics were associated with the type of food logo recognized by the children. Conclusions Children's high recognition of fast food restaurant logos may reflect greater exposure to fast food advertisements. Families' socio-demographic characteristics play a role in children's recognition of food logos.

Transfer between Pose and Illumination Training in Face Recognition

Science.gov (United States)

Liu, Chang Hong; Bhuiyan, Md. Al-Amin; Ward, James; Sui, Jie

2009-01-01

The relationship between pose and illumination learning in face recognition was examined in a yes-no recognition paradigm. The authors assessed whether pose training can transfer to a new illumination or vice versa. Results show that an extensive level of pose training through a face-name association task was able to generalize to a new…

Public relations violated by unlawful use of documents to form a legal entity

Directory of Open Access Journals (Sweden)

Petukhov E.V.

2014-12-01

Full Text Available The problems of determining the direct object of crime under article 173.2 of the RF Criminal Code are investigated. It’s noted that the article contains two independent corpus delicti. The characteristic that unites them is the direct object of crime, which is broken in two ways: by person providing the relevant documents and by person receiving these documents and information. Scientific points of view concerning the understanding of crime object are estimated. Understanding the object as a legal order of carrying out business activities doesn’t allow to outline the scope of the corresponding relations. Many crimes under chapter 22 of the RF Criminal Code impinge these relations. The author disagrees with the recognition of public relations, ensuring the use of necessary documents for registration of only those organizations that are engaged in lawful activities, as direct object of unlawful use of documents to form (establish, reorganize a legal entity. It’s emphasized that documents submission to the registering authority for registration of legal entities and individual entrepreneurs can be carried out by the applicant or his representative acting on the basis of a notarized power of attorney. The fact of forming legal entity should be connected with certain individuals. Then the organization will have certain responsible persons. The act provided by the analyzed corpus delicti, contributes to this rule violation. It’s summarized that the direct object of crime under considered article is public relations arising due to ensuring the statutory procedure for personalization and identification of responsible individual forming (establishing, reorganizing a legal entity.

Using Serial and Discrete Digit Naming to Unravel Word Reading Processes.

Science.gov (United States)

Altani, Angeliki; Protopapas, Athanassios; Georgiou, George K

2018-01-01

During reading acquisition, word recognition is assumed to undergo a developmental shift from slow serial/sublexical processing of letter strings to fast parallel processing of whole word forms. This shift has been proposed to be detected by examining the size of the relationship between serial- and discrete-trial versions of word reading and rapid naming tasks. Specifically, a strong association between serial naming of symbols and single word reading suggests that words are processed serially, whereas a strong association between discrete naming of symbols and single word reading suggests that words are processed in parallel as wholes. In this study, 429 Grade 1, 3, and 5 English-speaking Canadian children were tested on serial and discrete digit naming and word reading. Across grades, single word reading was more strongly associated with discrete naming than with serial naming of digits, indicating that short high-frequency words are processed as whole units early in the development of reading ability in English. In contrast, serial naming was not a unique predictor of single word reading across grades, suggesting that within-word sequential processing was not required for the successful recognition for this set of words. Factor mixture analysis revealed that our participants could be clustered into two classes, namely beginning and more advanced readers. Serial naming uniquely predicted single word reading only among the first class of readers, indicating that novice readers rely on a serial strategy to decode words. Yet, a considerable proportion of Grade 1 students were assigned to the second class, evidently being able to process short high-frequency words as unitized symbols. We consider these findings together with those from previous studies to challenge the hypothesis of a binary distinction between serial/sublexical and parallel/lexical processing in word reading. We argue instead that sequential processing in word reading operates on a continuum

Reading component skills in dyslexia: word recognition, comprehension and processing speed.

Science.gov (United States)

de Oliveira, Darlene G; da Silva, Patrícia B; Dias, Natália M; Seabra, Alessandra G; Macedo, Elizeu C

2014-01-01

The cognitive model of reading comprehension (RC) posits that RC is a result of the interaction between decoding and linguistic comprehension. Recently, the notion of decoding skill was expanded to include word recognition. In addition, some studies suggest that other skills could be integrated into this model, like processing speed, and have consistently indicated that this skill influences and is an important predictor of the main components of the model, such as vocabulary for comprehension and phonological awareness of word recognition. The following study evaluated the components of the RC model and predictive skills in children and adolescents with dyslexia. 40 children and adolescents (8-13 years) were divided in a Dyslexic Group (DG; 18 children, MA = 10.78, SD = 1.66) and control group (CG 22 children, MA = 10.59, SD = 1.86). All were students from the 2nd to 8th grade of elementary school and groups were equivalent in school grade, age, gender, and IQ. Oral and RC, word recognition, processing speed, picture naming, receptive vocabulary, and phonological awareness were assessed. There were no group differences regarding the accuracy in oral and RC, phonological awareness, naming, and vocabulary scores. DG performed worse than the CG in word recognition (general score and orthographic confusion items) and were slower in naming. Results corroborated the literature regarding word recognition and processing speed deficits in dyslexia. However, dyslexics can achieve normal scores on RC test. Data supports the importance of delimitation of different reading strategies embedded in the word recognition component. The role of processing speed in reading problems remain unclear.

Verifying visual properties in sentence verification facilitates picture recognition memory.

Science.gov (United States)

Pecher, Diane; Zanolie, Kiki; Zeelenberg, René

2007-01-01

According to the perceptual symbols theory (Barsalou, 1999), sensorimotor simulations underlie the representation of concepts. We investigated whether recognition memory for pictures of concepts was facilitated by earlier representation of visual properties of those concepts. During study, concept names (e.g., apple) were presented in a property verification task with a visual property (e.g., shiny) or with a nonvisual property (e.g., tart). Delayed picture recognition memory was better if the concept name had been presented with a visual property than if it had been presented with a nonvisual property. These results indicate that modality-specific simulations are used for concept representation.

[Nonspecific interstitial pneumonitis: a clinicopathologic entity, histologic pattern or unclassified group of heterogeneous interstitial pneumonitis?].

Science.gov (United States)

Morais, António; Moura, M Conceição Souto; Cruz, M Rosa; Gomes, Isabel

2004-01-01

Nonspecific interstitial pneumonitis (NSIP) initially described by Katzenstein and Fiorelli in 1994, seems to be a distinct clinicopathologic entity among idiopathic interstitial pneumonitis (IIP). Besides different histologic features from other IIP, NSIP is characterized by a better long-term outcome, associated with a better steroids responsiveness than idiopathic pulmonar fibrosis (IPF), where usually were included. Thus, differentiating NSIP from other IIP, namely IPF is very significant, since it has important therapeutic and prognostic implications. NSIP encloses different pathologies, namely those with inflammatory predominance (cellular subtype) or fibrous predominance (fibrosing subtype). NSIP is reviewed and discussed by the authors, after two clinical cases description.

The 2016 NIST Speaker Recognition Evaluation

Science.gov (United States)

2017-08-20

impact on system performance. Index Terms: NIST evaluation, NIST SRE, speaker detection, speaker recognition, speaker verification 1. Introduction NIST... self -reported. Second, there were two training conditions in SRE16, namely fixed and open. In the fixed training condition, par- ticipants were only

Obligatory and facultative brain regions for voice-identity recognition.

Science.gov (United States)

Roswandowitz, Claudia; Kappes, Claudia; Obrig, Hellmuth; von Kriegstein, Katharina

2018-01-01

Recognizing the identity of others by their voice is an important skill for social interactions. To date, it remains controversial which parts of the brain are critical structures for this skill. Based on neuroimaging findings, standard models of person-identity recognition suggest that the right temporal lobe is the hub for voice-identity recognition. Neuropsychological case studies, however, reported selective deficits of voice-identity recognition in patients predominantly with right inferior parietal lobe lesions. Here, our aim was to work towards resolving the discrepancy between neuroimaging studies and neuropsychological case studies to find out which brain structures are critical for voice-identity recognition in humans. We performed a voxel-based lesion-behaviour mapping study in a cohort of patients (n = 58) with unilateral focal brain lesions. The study included a comprehensive behavioural test battery on voice-identity recognition of newly learned (voice-name, voice-face association learning) and familiar voices (famous voice recognition) as well as visual (face-identity recognition) and acoustic control tests (vocal-pitch and vocal-timbre discrimination). The study also comprised clinically established tests (neuropsychological assessment, audiometry) and high-resolution structural brain images. The three key findings were: (i) a strong association between voice-identity recognition performance and right posterior/mid temporal and right inferior parietal lobe lesions; (ii) a selective association between right posterior/mid temporal lobe lesions and voice-identity recognition performance when face-identity recognition performance was factored out; and (iii) an association of right inferior parietal lobe lesions with tasks requiring the association between voices and faces but not voices and names. The results imply that the right posterior/mid temporal lobe is an obligatory structure for voice-identity recognition, while the inferior parietal lobe is

Erasmus MC at CLEF eHealth 2016: Concept recognition and coding in French texts

NARCIS (Netherlands)

E.M. Van Mulligen (Erik M.); Z. Afzal (Zubair); S.A. Akhondi (Saber); D. Vo (Dang); J.A. Kors (Jan)

2016-01-01

textabstractWe participated in task 2 of the CLEF eHealth 2016 chal-lenge. Two subtasks were addressed: entity recognition and normalization in a corpus of French drug labels and Medline titles, and ICD-10 coding of French death certificates. For both subtasks we used a dictionary-based approach.

Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion.

Science.gov (United States)

Jonnagaddala, Jitendra; Jue, Toni Rose; Chang, Nai-Wen; Dai, Hong-Jie

2016-01-01

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13.Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract. © The Author(s) 2016. Published by Oxford University Press.

Voice congruency facilitates word recognition.

Science.gov (United States)

Campeanu, Sandra; Craik, Fergus I M; Alain, Claude

2013-01-01

Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs) while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent) varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

Voice congruency facilitates word recognition.

Directory of Open Access Journals (Sweden)

Sandra Campeanu

Full Text Available Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

Wolf in Sheep's Clothing: Primary Lung Cancer Mimicking Benign Entities.

Science.gov (United States)

Snoeckx, Annemie; Dendooven, Amélie; Carp, Laurens; Desbuquoit, Damien; Spinhoven, Maarten J; Lauwers, Patrick; Van Schil, Paul E; van Meerbeeck, Jan P; Parizel, Paul M

2017-10-01

Lung cancer is the most common cancer worldwide. On imaging, it typically presents as mass or nodule. Recognition of these typical cases is often straightforward, whereas diagnosis of uncommon manifestations of primary lung cancer is far more challenging. Lung cancer can mimic a variety of benign entities, including pneumonia, lung abscess, postinfectious scarring, atelectasis, a mediastinal mass, emphysema and granulomatous diseases. Correlation with previous history, clinical and biochemical parameters is necessary in the assessment of these cases, but often aspecific and inconclusive. Whereas 18 F-fluorodeoxyglucose ( 18 F-FDG) Positron Emission Tomography is the cornerstone in staging of lung cancer, its role in diagnosis of these uncommon manifestations is less straightforward since benign entities can present with increased 18 F-FDG-uptake and, on the other hand, a number of these uncommon lung cancer manifestations do not exhibit increased uptake. Chest Computed Tomography (CT) is the imaging modality of choice for both lesion detection and characterization. In this pictorial review we present the wide imaging spectrum of CT-findings as well as radiologic-pathologic correlation of these uncommon lung cancer manifestations. Knowledge of the many faces of lung cancer is crucial for early diagnosis and subsequent treatment. A multidisciplinary approach in these cases is mandatory. Copyright © 2017 Elsevier B.V. All rights reserved.

Gabor Weber Local Descriptor for Bovine Iris Recognition

OpenAIRE

Sun, Shengnan; Zhao, Lindu; Yang, Shicai

2013-01-01

Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD). We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersectio...

Gliding and Saccadic Gaze Gesture Recognition in Real Time

DEFF Research Database (Denmark)

Rozado, David; San Agustin, Javier; Rodriguez, Francisco

2012-01-01

, and their corresponding real-time recognition algorithms, Hierarchical Temporal Memory networks and the Needleman-Wunsch algorithm for sequence alignment. Our results show how a specific combination of gaze gesture modality, namely saccadic gaze gestures, and recognition algorithm, Needleman-Wunsch, allows for reliable...... usage of intentional gaze gestures to interact with a computer with accuracy rates of up to 98% and acceptable completion speed. Furthermore, the gesture recognition engine does not interfere with otherwise standard human-machine gaze interaction generating therefore, very low false positive rates...

Evidence for a Limited-Cascading Account of Written Word Naming

Science.gov (United States)

Bonin, Patrick; Roux, Sebastien; Barry, Christopher; Canell, Laura

2012-01-01

We address the issue of how information flows within the written word production system by examining written object-naming latencies. We report 4 experiments in which we manipulate variables assumed to have their primary impact at the level of object recognition (e.g., quality of visual presentation of pictured objects), at the level of semantic…

tagtog: interactive and text-mining-assisted annotation of gene mentions in PLOS full-text articles.

Science.gov (United States)

Cejuela, Juan Miguel; McQuilton, Peter; Ponting, Laura; Marygold, Steven J; Stefancsik, Raymund; Millburn, Gillian H; Rost, Burkhard

2014-01-01

The breadth and depth of biomedical literature are increasing year upon year. To keep abreast of these increases, FlyBase, a database for Drosophila genomic and genetic information, is constantly exploring new ways to mine the published literature to increase the efficiency and accuracy of manual curation and to automate some aspects, such as triaging and entity extraction. Toward this end, we present the 'tagtog' system, a web-based annotation framework that can be used to mark up biological entities (such as genes) and concepts (such as Gene Ontology terms) in full-text articles. tagtog leverages manual user annotation in combination with automatic machine-learned annotation to provide accurate identification of gene symbols and gene names. As part of the BioCreative IV Interactive Annotation Task, FlyBase has used tagtog to identify and extract mentions of Drosophila melanogaster gene symbols and names in full-text biomedical articles from the PLOS stable of journals. We show here the results of three experiments with different sized corpora and assess gene recognition performance and curation speed. We conclude that tagtog-named entity recognition improves with a larger corpus and that tagtog-assisted curation is quicker than manual curation. DATABASE URL: www.tagtog.net, www.flybase.org.

Chemical name extraction based on automatic training data generation and rich feature set.

Science.gov (United States)

Yan, Su; Spangler, W Scott; Chen, Ying

2013-01-01

The automation of extracting chemical names from text has significant value to biomedical and life science research. A major barrier in this task is the difficulty of getting a sizable and good quality data to train a reliable entity extraction model. Another difficulty is the selection of informative features of chemical names, since comprehensive domain knowledge on chemistry nomenclature is required. Leveraging random text generation techniques, we explore the idea of automatically creating training sets for the task of chemical name extraction. Assuming the availability of an incomplete list of chemical names, called a dictionary, we are able to generate well-controlled, random, yet realistic chemical-like training documents. We statistically analyze the construction of chemical names based on the incomplete dictionary, and propose a series of new features, without relying on any domain knowledge. Compared to state-of-the-art models learned from manually labeled data and domain knowledge, our solution shows better or comparable results in annotating real-world data with less human effort. Moreover, we report an interesting observation about the language for chemical names. That is, both the structural and semantic components of chemical names follow a Zipfian distribution, which resembles many natural languages.

Reading component skills in dyslexia: word recognition, comprehension and processing speed

Directory of Open Access Journals (Sweden)

Darlene Godoy Oliveira

2014-11-01

Full Text Available The cognitive model of reading comprehension posits that reading comprehension is a result of the interaction between decoding and linguistic comprehension. Recently, the notion of decoding skill was expanded to include word recognition. In addition, some studies suggest that other skills could be integrated into this model, like processing speed, and have consistently indicated that this skill influences and is an important predictor of the main components of the model, such as vocabulary for comprehension and phonological awareness of word recognition. The following study evaluated the components of the reading comprehension model and predictive skills in children and adolescents with dyslexia. 40 children and adolescents (8-13 years were divided in a Dyslexic Group (DG, 18 children, MA = 10.78, SD = 1.66 and Control Group (CG 22 children, MA = 10.59, SD = 1.86. All were students from the 2nd to 8th grade of elementary school and groups were equivalent in school grade, age, gender, and IQ. Oral and reading comprehension, word recognition, processing speed, picture naming, receptive vocabulary and phonological awareness were assessed. There were no group differences regarding the accuracy in oral and reading comprehension, phonological awareness, naming, and vocabulary scores. DG performed worse than the CG in word recognition (general score and orthographic confusion items and were slower in naming. Results corroborated the literature regarding word recognition and processing speed deficits in dyslexia. However, dyslexics can achieve normal scores on reading comprehension test. Data supports the importance of delimitation of different reading strategies embedded in the word recognition component. The role of processing speed in reading problems remain unclear.

Priming picture naming with a semantic task: an fMRI investigation.

Directory of Open Access Journals (Sweden)

Shiree Heath

Full Text Available Prior semantic processing can enhance subsequent picture naming performance, yet the neurocognitive mechanisms underlying this effect and its longevity are unknown. This functional magnetic resonance imaging study examined whether different neurological mechanisms underlie short-term (within minutes and long-term (within days facilitation effects from a semantic task in healthy older adults. Both short- and long-term facilitated items were named significantly faster than unfacilitated items, with short-term items significantly faster than long-term items. Region of interest results identified decreased activity for long-term facilitated items compared to unfacilitated and short-term facilitated items in the mid-portion of the middle temporal gyrus, indicating lexical-semantic priming. Additionally, in the whole brain results, increased activity for short-term facilitated items was identified in regions previously linked to episodic memory and object recognition, including the right lingual gyrus (extending to the precuneus region and the left inferior occipital gyrus (extending to the left fusiform region. These findings suggest that distinct neurocognitive mechanisms underlie short- and long-term facilitation of picture naming by a semantic task, with long-term effects driven by lexical-semantic priming and short-term effects by episodic memory and visual object recognition mechanisms.

Testing the Application for Analyzing Structured Entities

OpenAIRE

Ion IVAN; Bogdan VINTILA

2011-01-01

The paper presents the testing process of the application for the analysis of structured text entities. The structured entities are presented. Quality characteristics of structured entities are identified and analyzed. The design and building processes are presented. Rules for building structured entities are described. The steps of building the application for the analysis of structured text entities are presented. The objective of the testing process is defined. Ways of testing the applicat...

Fast cat-eye effect target recognition based on saliency extraction

Science.gov (United States)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

Entity ranking using Wikipedia as a pivot

NARCIS (Netherlands)

Kaptein, R.; Serdyukov, P.; de Vries, A.; Kamps, J.; Huang, X.J.; Jones, G.; Koudas, N.; Wu, X.; Collins-Thompson, K.

2010-01-01

In this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about these entities. Since

Query containment in entity SQL

OpenAIRE

Rull Fort, Guillem; Bernstein, Philip A.; Garcia dos Santos, Ivo; Katsis, Yannis; Melnik, Sergey; Teniente López, Ernest

2013-01-01

We describe a software architecture we have developed for a constructive containment checker of Entity SQL queries defined over extended ER schemas expressed in Microsoft's Entity Data Model. Our application of interest is compilation of object-to-relational mappings for Microsoft's ADO.NET Entity Framework, which has been shipping since 2007. The supported language includes several features which have been individually addressed in the past but, to the best of our knowledge, they have not be...

ACOUSTIC SPEECH RECOGNITION FOR MARATHI LANGUAGE USING SPHINX

Directory of Open Access Journals (Sweden)

Aman Ankit

2016-09-01

Full Text Available Speech recognition or speech to text processing, is a process of recognizing human speech by the computer and converting into text. In speech recognition, transcripts are created by taking recordings of speech as audio and their text transcriptions. Speech based applications which include Natural Language Processing (NLP techniques are popular and an active area of research. Input to such applications is in natural language and output is obtained in natural language. Speech recognition mostly revolves around three approaches namely Acoustic phonetic approach, Pattern recognition approach and Artificial intelligence approach. Creation of acoustic model requires a large database of speech and training algorithms. The output of an ASR system is recognition and translation of spoken language into text by computers and computerized devices. ASR today finds enormous application in tasks that require human machine interfaces like, voice dialing, and etc. Our key contribution in this paper is to create corpora for Marathi language and explore the use of Sphinx engine for automatic speech recognition

Semantic and visual determinants of face recognition in a prosopagnosic patient.

Science.gov (United States)

Dixon, M J; Bub, D N; Arguin, M

1998-05-01

Prosopagnosia is the neuropathological inability to recognize familiar people by their faces. It can occur in isolation or can coincide with recognition deficits for other nonface objects. Often, patients whose prosopagnosia is accompanied by object recognition difficulties have more trouble identifying certain categories of objects relative to others. In previous research, we demonstrated that objects that shared multiple visual features and were semantically close posed severe recognition difficulties for a patient with temporal lobe damage. We now demonstrate that this patient's face recognition is constrained by these same parameters. The prosopagnosic patient ELM had difficulties pairing faces to names when the faces shared visual features and the names were semantically related (e.g., Tonya Harding, Nancy Kerrigan, and Josee Chouinard -three ice skaters). He made tenfold fewer errors when the exact same faces were associated with semantically unrelated people (e.g., singer Celine Dion, actress Betty Grable, and First Lady Hillary Clinton). We conclude that prosopagnosia and co-occurring category-specific recognition problems both stem from difficulties disambiguating the stored representations of objects that share multiple visual features and refer to semantically close identities or concepts.

Ranking related entities: components and analyses

NARCIS (Netherlands)

Bron, M.; Balog, K.; de Rijke, M.

2010-01-01

Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given source entity. We propose a framework for addressing this task and perform a detailed analysis of four core components;

Institutional Choice and Recognition in Development

DEFF Research Database (Denmark)

Rutt, Rebecca Leigh

Abstract This thesis concerns the role of local institutions in fostering development including natural resource management, and how this role is shaped by relations with higher scale institutions such as development agencies and national governments. Specifically, it examines the choice of local...... objective of this thesis was to contribute to understanding processes and outcomes of institutional choice and recognition. It employed mixed methods but primarily semi structured interviews in multiple sites across Nepal. In responding to specific objectives, namely to better understand: i) the rationales...... behind choices of local institutional counterparts, ii) the belonging and citizenship available with local institutions, iii) the dynamics and mutuality of recognition between higher and lower scale institutions, and iv) the social outcomes of choice and recognition, this thesis shows that the way choice...

Enriched vascularity in ameloblastomas, an indeterminate entity: Report of two cases

Directory of Open Access Journals (Sweden)

Usha Hegde

2015-01-01

Full Text Available Vascularity is a highly essential element that is required for the growth, development, and functioning of the body and variations in it can cause pathologies. It is one of the prime features of a proliferating lesion, where it aids in the growth of the lesion through its nutrition supply. Highly increased vascularity in a disease can itself affect the prognosis of the lesion, and in malignancies, it can induce tumor seeding and secondaries. Most of the pathologies including tumors, related to blood vessels, and vascularity are well established. There are some conditions, wherein altered vascularity is one of the prime components along with other diagnostic components of an established disease. In such cases, these lesions are diagnosed with special names, with varying biological behavior and prognosis in comparison to that of established entity. However, there still are few similar conditions whose nature is uncertain due to the rarity of the lesion and the insufficient scientific evidence which eludes the diagnostician. Here is the report of two cases of ameloblastoma, an established entity, with significant vascularity whose nature is indeterminate.

CNN-based ranking for biomedical entity normalization.

Science.gov (United States)

Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

2017-10-03

Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

Training Letter and Orthographic Pattern Recognition in Children with Slow Naming Speed

Science.gov (United States)

Conrad, Nicole J.; Levy, Betty Ann

2011-01-01

Although research has established that performance on a rapid automatized naming (RAN) task is related to reading, the nature of this relationship is unclear. Bowers (2001) proposed that processes underlying performance on the RAN task and orthographic knowledge make independent and additive contributions to reading performance. We examined the…

Efficient Interaction Recognition through Positive Action Representation

Directory of Open Access Journals (Sweden)

Tao Hu

2013-01-01

Full Text Available This paper proposes a novel approach to decompose two-person interaction into a Positive Action and a Negative Action for more efficient behavior recognition. A Positive Action plays the decisive role in a two-person exchange. Thus, interaction recognition can be simplified to Positive Action-based recognition, focusing on an action representation of just one person. Recently, a new depth sensor has become widely available, the Microsoft Kinect camera, which provides RGB-D data with 3D spatial information for quantitative analysis. However, there are few publicly accessible test datasets using this camera, to assess two-person interaction recognition approaches. Therefore, we created a new dataset with six types of complex human interactions (i.e., named K3HI, including kicking, pointing, punching, pushing, exchanging an object, and shaking hands. Three types of features were extracted for each Positive Action: joint, plane, and velocity features. We used continuous Hidden Markov Models (HMMs to evaluate the Positive Action-based interaction recognition method and the traditional two-person interaction recognition approach with our test dataset. Experimental results showed that the proposed recognition technique is more accurate than the traditional method, shortens the sample training time, and therefore achieves comprehensive superiority.

A structural view of microRNA–target recognition

KAUST Repository

Leoni, Guido; Tramontano, Anna

2016-01-01

of the pairing should take into account the effect of the Argonaute protein (AGO), an essential catalyst of the recognition process. Therefore, we developed a strategy named MiREN for building and scoring three-dimensional models of the ternary complex formed

Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi

NARCIS (Netherlands)

Schoch, C.L.; Robbertse, B.; Robert, V.; Vu, D.; Cardinali, G.; Irinyi, L.; Meyer, W.; Nilsson, R.H.; Hughes, K.; Miller, A.N.; Kirk, P.M.; Abarenkov, K.; Aime, M.C.; Ariyawansa, H.A.; Bidartondo, M.; Boekhout, T.; Buyck, B.; Cai, Q.; Chen, J.; Crespo, A.; Crous, P.W.; Damm, U.; Beer, de Z.W.; Dentinger, B.T.M.; Divakar, P.K.; Duenas, M.; Feau, N.; Fliegerova, K.; Garcia, M.A.; Ge, Z.W.; Griffith, G.W.; Groenewald, J.Z.; Groenewald, M.; Grube, M.; Gryzenhout, M.; Gueidan, C.; Guo, L.; Hambleton, S.; Hamelin, R.; Hansen, K.; Hofstetter, V.; Hong, S.B.; Houbraken, J.; Hyde, K.D.; Inderbitzin, P.; Johnston, P.A.; Karunarathna, S.C.; Koljalg, U.; Kovacs, G.M.; Kraichak, E.; Krizsan, K.; Kurtzman, C.P.; Larsson, K.H.; Leavitt, S.; Letcher, P.M.; Liimatainen, K.; Liu, J.K.; Lodge, D.J.; Luangsa-ard, J.J.; Lumbsch, H.T.; Maharachchikumbura, S.S.N.; Manamgoda, D.; Martin, M.P.; Minnis, A.M.; Moncalvo, J.M.; Mule, G.; Nakasone, K.K.; Niskanen, T.; Olariaga, I.; Papp, T.; Petkovits, T.; Pino-Bodas, R.; Powell, M.J.; Raja, H.A.; Redecker, D.; Sarmiento-Ramirez, J.M.; Seifert, K.A.; Shrestha, B.; Stenroos, S.; Stielow, B.; Suh, S.O.; Tanaka, K.; Tedersoo, L.; Telleria, M.T.; Udayanga, D.; Untereiner, W.A.; Dieguez Uribeondo, J.; Subbarao, K.V.; Vagvolgyi, C.; Visagie, C.; Voigt, K.; Walker, D.M.; Weir, B.S.; Weiss, M.; Wijayawardene, N.N.; Wingfield, M.J.; Xu, J.P.; Yang, Z.L.; Zhang, N.; Zhuang, W.Y.; Federhen, S.

2014-01-01

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing

Enhancements for a Dynamic Data Warehousing and Mining System for Large-scale HSCB Data

Science.gov (United States)

2016-07-20

Development of YouTube Analytics and UI ................................................... 2 1.1.1 YouTube Top K Statistics Computation and View...2 1.1.2 YouTube Timeline View ............................................................................... 3...1.1.3 YouTube Media Gallery View ..................................................................... 3 1.1.4 YouTube Named Entity Recognition (NER

Implicit multisensory associations influence voice recognition.

Directory of Open Access Journals (Sweden)

Katharina von Kriegstein

2006-10-01

Full Text Available Natural objects provide partially redundant information to the brain through different sensory modalities. For example, voices and faces both give information about the speech content, age, and gender of a person. Thanks to this redundancy, multimodal recognition is fast, robust, and automatic. In unimodal perception, however, only part of the information about an object is available. Here, we addressed whether, even under conditions of unimodal sensory input, crossmodal neural circuits that have been shaped by previous associative learning become activated and underpin a performance benefit. We measured brain activity with functional magnetic resonance imaging before, while, and after participants learned to associate either sensory redundant stimuli, i.e. voices and faces, or arbitrary multimodal combinations, i.e. voices and written names, ring tones, and cell phones or brand names of these cell phones. After learning, participants were better at recognizing unimodal auditory voices that had been paired with faces than those paired with written names, and association of voices with faces resulted in an increased functional coupling between voice and face areas. No such effects were observed for ring tones that had been paired with cell phones or names. These findings demonstrate that brief exposure to ecologically valid and sensory redundant stimulus pairs, such as voices and faces, induces specific multisensory associations. Consistent with predictive coding theories, associative representations become thereafter available for unimodal perception and facilitate object recognition. These data suggest that for natural objects effective predictive signals can be generated across sensory systems and proceed by optimization of functional connectivity between specialized cortical sensory modules.

Awareness of Entities, Activities and Contexts in Ambient Systems

DEFF Research Database (Denmark)

Kristensen, Bent Bruun

2013-01-01

Ambient systems are modeled by entities, activities and contexts, where entities exist in contexts and engage in activities. A context supports a dynamic collection of entities by services and offers awareness information about the entities. Activities also exist in contexts and model ongoing...... collaborations between entities. Activities and local contexts also obtain awareness information from the context about the dynamic collection of entities. Similarly activities, local contexts and entities are offered awareness information about activities and local contexts....

SAR Target Recognition Using the Multi-aspect-aware Bidirectional LSTM Recurrent Neural Networks

OpenAIRE

Zhang, Fan; Hu, Chen; Yin, Qiang; Li, Wei; Li, Hengchao; Hong, Wen

2017-01-01

The outstanding pattern recognition performance of deep learning brings new vitality to the synthetic aperture radar (SAR) automatic target recognition (ATR). However, there is a limitation in current deep learning based ATR solution that each learning process only handle one SAR image, namely learning the static scattering information, while missing the space-varying information. It is obvious that multi-aspect joint recognition introduced space-varying scattering information should improve ...

Long-term effect of a name change for schizophrenia on reducing stigma.

Science.gov (United States)

Koike, Shinsuke; Yamaguchi, Sosei; Ojio, Yasutaka; Shimada, Takafumi; Watanabe, Kei-ichiro; Ando, Shuntaro

2015-10-01

A name change for schizophrenia was first implemented in Japan for reducing stigma in 2002; however, little is known of its long-term impact. Total 259 students from 20 universities answered an anonymous self-administered questionnaire about their mental health-related experiences, and stigma scales including feasible knowledge and negative stereotypes for four specific diseases, including schizophrenia (old and new names), depression, and diabetes mellitus. We also asked to choose the old and new names of schizophrenia and dementia among ten names for mental and physical illnesses and conditions. The participants had more feasible knowledge and fewer negative stereotypes for the new name of schizophrenia than the old name, but were still significantly worse than for depression and diabetes mellitus (p stereotypes (β = 0.13, p = 0.020). The rate of correct responses for the old and new names of schizophrenia was significantly lower than that of dementia (41 vs. 87%, p media was associated with the recognition of name change for schizophrenia (p = 0.008), which was associated with less feasible knowledge for new name of schizophrenia. The name change of schizophrenia has reduced stigma since 12 years have passed. More effective campaigns, educational curricula, and policy making are needed to reduce stigma toward schizophrenia.

Testing the Application for Analyzing Structured Entities

Directory of Open Access Journals (Sweden)

Ion IVAN

2011-01-01

Full Text Available The paper presents the testing process of the application for the analysis of structured text entities. The structured entities are presented. Quality characteristics of structured entities are identified and analyzed. The design and building processes are presented. Rules for building structured entities are described. The steps of building the application for the analysis of structured text entities are presented. The objective of the testing process is defined. Ways of testing the application on components and as a whole are established. A testing strategy for different objectives is proposed. The behavior of users during the testing period is analyzed. Statistical analysis regarding the behavior of users in processes of infinite resources access are realized.

Arabic medical entity tagging using distant learning

Directory of Open Access Journals (Sweden)

Viviana Cotik

2017-04-01

Full Text Available A semantic tagger aiming to detect relevant entities in Arabic medical documents and tagging them with their appropriate semantic class is presented. The system takes profit of a Multilingual Framework covering four languages (Arabic, English, French, and Spanish, in a way that resources available for each language can be used to improve the results of the others, this is specially important for less resourced languages as Arabic. The approach has been evaluated against Wikipedia pages of the four languages belonging to the medical domain. The core of the system is the definition of a base tagset consisting of the three most represented classes in SNOMED-CT taxonomy and the learning of a binary classifier for each semantic category in the tagset and each language, using a distant learning approach over three widely used knowledge resources, namely Wikipedia, Dbpedia, and SNOMED-CT.

Entity Ranking using Wikipedia as a Pivot

NARCIS (Netherlands)

R. Kaptein; P. Serdyukov; A.P. de Vries (Arjen); J. Kamps

2010-01-01

htmlabstractIn this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about

How reading differs from object naming at the neuronal level.

Science.gov (United States)

Price, C J; McCrory, E; Noppeney, U; Mechelli, A; Moore, C J; Biggio, N; Devlin, J T

2006-01-15

This paper uses whole brain functional neuroimaging in neurologically normal participants to explore how reading aloud differs from object naming in terms of neuronal implementation. In the first experiment, we directly compared brain activation during reading aloud and object naming. This revealed greater activation for reading in bilateral premotor, left posterior superior temporal and precuneus regions. In a second experiment, we segregated the object-naming system into object recognition and speech production areas by factorially manipulating the presence or absence of objects (pictures of objects or their meaningless scrambled counterparts) with the presence or absence of speech production (vocal vs. finger press responses). This demonstrated that the areas associated with speech production (object naming and repetitively saying "OK" to meaningless scrambled pictures) corresponded exactly to the areas where responses were higher for reading aloud than object naming in Experiment 1. Collectively the results suggest that, relative to object naming, reading increases the demands on shared speech production processes. At a cognitive level, enhanced activation for reading in speech production areas may reflect the multiple and competing phonological codes that are generated from the sublexical parts of written words. At a neuronal level, it may reflect differences in the speed with which different areas are activated and integrate with one another.

Entity resolution for uncertain data

NARCIS (Netherlands)

Ayat, N.; Akbarinia, R.; Afsarmanesh, H.; Valduriez, P.

2012-01-01

Entity resolution (ER), also known as duplicate detection or record matching, is the problem of identifying the tuples that represent the same real world entity. In this paper, we address the problem of ER for uncertain data, which we call ERUD. We propose two different approaches for the ERUD

31 CFR 595.303 - Entity.

Science.gov (United States)

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 595.303 Section 595.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY TERRORISM SANCTIONS REGULATIONS General Definitions § 595.303 Entity...

26 CFR 301.7701-2 - Business entities; definitions.

Science.gov (United States)

2010-04-01

... 26 Internal Revenue 18 2010-04-01 2010-04-01 false Business entities; definitions. 301.7701-2...) PROCEDURE AND ADMINISTRATION PROCEDURE AND ADMINISTRATION Definitions § 301.7701-2 Business entities; definitions. (a) Business entities. For purposes of this section and § 301.7701-3, a business entity is any...

7 CFR 1738.16 - Eligible entities.

Science.gov (United States)

2010-01-01

... cooperative, nonprofit, limited dividend or mutual associations, limited liability companies, commercial... or partnerships of individuals are not eligible entities. (2) An entity is not eligible if it serves...

Mountain names in the geographical dictionary of Camagüey Province, environmental studies, and environmental education

Directory of Open Access Journals (Sweden)

Alfonso, L. F.

2014-01-01

Full Text Available The research contributes to the project intended to provide the province of Camagüey with a geographical dictionary, a reference book for economic entities and academic institutions. The article is aimed at standardizing the use of geographical names in education and scientific research in Camagüey. Several methods of geographical research were used, cartographic methods, observing geographic objects in place and field research included. The findings were assessed by means of consulting experts on the topic and computer data processing. The methodology employed follows the guidelines of the national group of advisors for geographical names and the group of advisor of Camagüey province. The most widely used geographical names in the regions were listed in the dictionary.

Bilingual Language Switching: Production vs. Recognition

Science.gov (United States)

Mosca, Michela; de Bot, Kees

2017-01-01

This study aims at assessing how bilinguals select words in the appropriate language in production and recognition while minimizing interference from the non-appropriate language. Two prominent models are considered which assume that when one language is in use, the other is suppressed. The Inhibitory Control (IC) model suggests that, in both production and recognition, the amount of inhibition on the non-target language is greater for the stronger compared to the weaker language. In contrast, the Bilingual Interactive Activation (BIA) model proposes that, in language recognition, the amount of inhibition on the weaker language is stronger than otherwise. To investigate whether bilingual language production and recognition can be accounted for by a single model of bilingual processing, we tested a group of native speakers of Dutch (L1), advanced speakers of English (L2) in a bilingual recognition and production task. Specifically, language switching costs were measured while participants performed a lexical decision (recognition) and a picture naming (production) task involving language switching. Results suggest that while in language recognition the amount of inhibition applied to the non-appropriate language increases along with its dominance as predicted by the IC model, in production the amount of inhibition applied to the non-relevant language is not related to language dominance, but rather it may be modulated by speakers' unconscious strategies to foster the weaker language. This difference indicates that bilingual language recognition and production might rely on different processing mechanisms and cannot be accounted within one of the existing models of bilingual language processing. PMID:28638361

An integrated architecture for shallow and deep processing

OpenAIRE

Crysmann, Berthold; Frank, Anette; Kiefer, Bernd; Müller, Stefan; Neumann, Günter; Piskorski, Jakub; Schäfer, Ulrich; Siegel, Melanie; Uszkoreit, Hans; Xu, Feiyu; Becker, Markus; Krieger, Hans-Ulrich

2011-01-01

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language te...

Recognition properties of receptors consisting of imidazole and indole recognition units towards carbohydrates

Directory of Open Access Journals (Sweden)

Monika Mazik

2010-02-01

Full Text Available Compounds 4 and 5, including both 4(5-substituted imidazole or 3-substituted indole units as the entities used in nature, and 2-aminopyridine group as a heterocyclic analogue of the asparagine/glutamine primary amide side chain, were prepared and their binding properties towards carbohydrates were studied. The design of these receptors was inspired by the binding motifs observed in the crystal structures of protein–carbohydrate complexes. 1H NMR spectroscopic titrations in competitive and non-competitive media as well as binding studies in two-phase systems, such as dissolution of solid carbohydrates in apolar media, revealed both highly effective recognition of neutral carbohydrates and interesting binding preferences of these acyclic compounds. Compared to the previously described acyclic receptors, compounds 4 and 5 showed significantly increased binding affinity towards β-galactoside. Both receptors display high β- vs. α-anomer binding preferences in the recognition of glycosides. It has been shown that both hydrogen bonding and interactions of the carbohydrate CH units with the aromatic rings of the receptors contribute to the stabilization of the receptor–carbohydrate complexes. The molecular modeling calculations, synthesis and binding properties of 4 and 5 towards selected carbohydrates are described and compared with those of the previously described receptors.

31 CFR 800.211 - Entity.

Science.gov (United States)

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 800.211 Section 800.211 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF INVESTMENT... separate legal entity) operated by any one of the foregoing as a business undertaking in a particular...

31 CFR 596.308 - Person; entity.

Science.gov (United States)

2010-07-01

... FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY TERRORISM LIST GOVERNMENTS SANCTIONS REGULATIONS General Definitions § 596.308 Person; entity. (a) The term person means an individual or entity. (b) The...

Handwritten Word Recognition Using Multi-view Analysis

Science.gov (United States)

de Oliveira, J. J.; de A. Freitas, C. O.; de Carvalho, J. M.; Sabourin, R.

This paper brings a contribution to the problem of efficiently recognizing handwritten words from a limited size lexicon. For that, a multiple classifier system has been developed that analyzes the words from three different approximation levels, in order to get a computational approach inspired on the human reading process. For each approximation level a three-module architecture composed of a zoning mechanism (pseudo-segmenter), a feature extractor and a classifier is defined. The proposed application is the recognition of the Portuguese handwritten names of the months, for which a best recognition rate of 97.7% was obtained, using classifier combination.

WCP-RNN : a novel RNN-based approach for Bio-NER in Chinese EMRs: Paper ID: FC_17_25

NARCIS (Netherlands)

Li, Jianqiang; Zhao, Shenhe; Yang, Jijiang; Huang, Zhisheng; Liu, Bo; Chen, Shi; Pan, Hui; Wang, Qing

2018-01-01

Deep learning has achieved remarkable success in a wide range of domains. However, it has not been comprehensively evaluated as a solution for the task of Chinese biomedical named entity recognition (Bio-NER). The traditional deep-learning approach for the Bio-NER task is usually based on the

Entity resolution in the web of data

CERN Document Server

Christophides, Vassilis; Stefanidis, Kostas

2015-01-01

In recent years, several knowledge bases have been built to enable large-scale knowledge sharing, but also an entity-centric Web search, mixing both structured data and text querying. These knowledge bases offer machine-readable descriptions of real-world entities, e.g., persons, places, published on the Web as Linked Data. However, due to the different information extraction tools and curation policies employed by knowledge bases, multiple, complementary and sometimes conflicting descriptions of the same real-world entities may be provided. Entity resolution aims to identify different descrip

[Face recognition in patients with autism spectrum disorders].

Science.gov (United States)

Kita, Yosuke; Inagaki, Masumi

2012-07-01

The present study aimed to review previous research conducted on face recognition in patients with autism spectrum disorders (ASD). Face recognition is a key question in the ASD research field because it can provide clues for elucidating the neural substrates responsible for the social impairment of these patients. Historically, behavioral studies have reported low performance and/or unique strategies of face recognition among ASD patients. However, the performance and strategy of ASD patients is comparable to those of the control group, depending on the experimental situation or developmental stage, suggesting that face recognition of ASD patients is not entirely impaired. Recent brain function studies, including event-related potential and functional magnetic resonance imaging studies, have investigated the cognitive process of face recognition in ASD patients, and revealed impaired function in the brain's neural network comprising the fusiform gyrus and amygdala. This impaired function is potentially involved in the diminished preference for faces, and in the atypical development of face recognition, eliciting symptoms of unstable behavioral characteristics in these patients. Additionally, face recognition in ASD patients is examined from a different perspective, namely self-face recognition, and facial emotion recognition. While the former topic is intimately linked to basic social abilities such as self-other discrimination, the latter is closely associated with mentalizing. Further research on face recognition in ASD patients should investigate the connection between behavioral and neurological specifics in these patients, by considering developmental changes and the spectrum clinical condition of ASD.

A Study of Moment Based Features on Handwritten Digit Recognition

Directory of Open Access Journals (Sweden)

Pawan Kumar Singh

2016-01-01

Full Text Available Handwritten digit recognition plays a significant role in many user authentication applications in the modern world. As the handwritten digits are not of the same size, thickness, style, and orientation, therefore, these challenges are to be faced to resolve this problem. A lot of work has been done for various non-Indic scripts particularly, in case of Roman, but, in case of Indic scripts, the research is limited. This paper presents a script invariant handwritten digit recognition system for identifying digits written in five popular scripts of Indian subcontinent, namely, Indo-Arabic, Bangla, Devanagari, Roman, and Telugu. A 130-element feature set which is basically a combination of six different types of moments, namely, geometric moment, moment invariant, affine moment invariant, Legendre moment, Zernike moment, and complex moment, has been estimated for each digit sample. Finally, the technique is evaluated on CMATER and MNIST databases using multiple classifiers and, after performing statistical significance tests, it is observed that Multilayer Perceptron (MLP classifier outperforms the others. Satisfactory recognition accuracies are attained for all the five mentioned scripts.

Name Recognition to Identify Patients of South Asian Ethnicity within the Cancer Registry

Directory of Open Access Journals (Sweden)

Savitri Singh-Carlson

2016-01-01

Full Text Available Objective: The goal of this project was to develop a list of forenames and surnames of South Asian (SA women that could be used to identify SA breast cancer patients within the cancer registry. This list was compiled, evaluated, and validated to ensure comprehensiveness, accuracy, and applicability of SA names. Methods: This project was conducted by Canadian researchers who are immersed in conducting behavioral studies with SA women diagnosed with cancer in the province of British Columbia. Recruiting SA cancer patients for research can be a difficult task due to social and cultural factors. Methods used by other researchers to identify ethnicity related unique names were employed to filter surnames and forenames that were not common to this ethnic group. Co-author (Gurpreet Oshan of SA ethnicity rigorously identified and deleted multiple lists and redundant entries along with common English forenames which resulted in a list of 16,888 SA forenames. All co-authors of Indian ethnicity (Gurpreet Oshan, Savitri Singh-Carlson, Harajit Lail were involved in critiquing and manually reviewing the names list throughout this process. Comprehensive lists of SA surnames and women′s forenames were reviewed to identify those that were unique to SA ethnicity. Accuracy was ensured by constantly filtering the redundancy by using an Excel program which helped to illustrate the number of times each name was spelled in different ways. Results: The final lists included 9112 surnames and 16,888 forenames of SA ethnicity. On the basis of the surname linkage only, the sensitivity of the list was 76.6%, specificity was 62.9%, and the positive predictive value was 58.5%. On the basis of both the surname and forename linkage, the specificity of the list was 88.6%. These lists include variations in spelling forenames and surnames as well. Conclusions: The list of surnames and forenames can be useful tools to identify SA ethnic groups from large population database in

A COMPARISON OF THE CAPITAL STRUCTURES OF THE TOP 40MULTINATIONAL ENTITIES AND THE TOP 40 JSE-LISTED ENTITIES

Directory of Open Access Journals (Sweden)

Lana H. Harmse

2017-01-01

Full Text Available The strategies and policies of multinational entities (MNEscentre onthe focalgoal of any company, which isto maximise profits and shareholder wealth.Management aims for an optimum ownership structure by implementing variousstrategies. One of these strategies is the debt-to-equity ratio (the capital structure.Previous studiesconductedonvariouscountries’locally-listed entities confirmthat the capital structure of an entity has an impact on the value ofthat entity.Thisthen raisesan interesting question as to whetherthecapital structures ofthetop 40Johannesburg Stock Exchange (JSE-listedentitiesare similar to those ofthe top40 global MNEs.Based on market capitalisation on 31December2014, this studysought to compare the capital structures,using the debt-to-equity ratio,ofthe top40JSE-listed entitieswith those ofthe top 40globalMNEs on the Fortune 500list.Independent t-testswere performed on thedebt-to-equity ratios of thetop 40JSE-listed entities and the top 40globalMNEsas a group.Both independent t-tests and the Mann-Whitney testswereperformedonthedebt-to-equity ratiosofapplicable entities of the group divided into threeselectedindustries. The resultsof theindependent t-testindicateastatistical andpractically significant differencebetween the top 40 JSE-listed entities and the top 40 global MNEs’ capitalstructures.The resultsof the Mann-Whitney testsindicatethat if the financialindustry is excluded,there isnostatistical orpractically significant differencebetween the capital structures of the top 40 JSE-listed entities and the top 40MNEs.However, based on the effect size there is a practical visible difference.

Online recognition of Chinese characters: the state-of-the-art.

Science.gov (United States)

Liu, Cheng-Lin; Jaeger, Stefan; Nakagawa, Masaki

2004-02-01

Online handwriting recognition is gaining renewed interest owing to the increase of pen computing applications and new pen input devices. The recognition of Chinese characters is different from western handwriting recognition and poses a special challenge. To provide an overview of the technical status and inspire future research, this paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s. Compared to the research in the 1980s, the research efforts in the 1990s aimed to further relax the constraints of handwriting, namely, the adherence to standard stroke orders and stroke numbers and the restriction of recognition to isolated characters only. The target of recognition has shifted from regular script to fluent script in order to better meet the requirements of practical applications. The research works are reviewed in terms of pattern representation, character classification, learning/adaptation, and contextual processing. We compare important results and discuss possible directions of future research.

Recognition of handwritten characters using local gradient feature descriptors

NARCIS (Netherlands)

Surinta, Olarik; Karaaba, Mahir F.; Schomaker, Lambert R.B.; Wiering, Marco A.

2015-01-01

Abstract In this paper we propose to use local gradient feature descriptors, namely the scale invariant feature transform keypoint descriptor and the histogram of oriented gradients, for handwritten character recognition. The local gradient feature descriptors are used to extract feature vectors

SOCIAL EFFECTIVENESS OF BUSINESS ENTITIES

Directory of Open Access Journals (Sweden)

Iryna Perevozova

2016-06-01

Full Text Available The article is aimed at investigation of social effectiveness of business entities. Social aspect of business is becoming a necessary component of success, increase of profitability and competitiveness as well as minimization of risks. Social effectiveness is referred to as correspondence between economic activity and main social needs and aims of society, interests of the staff and interests of a certain person. Investigation of social effectiveness of business entities is suggested to analyze with the help of social factors. Social factors are characterized by variability of expectations, relations and interests of society, staff and individuals. We suggest generalized classification of factors which have an impact on social effectiveness of business, we single out external and internal factors. To external factors belong: income of the population, differentiation of population according to income, migration, level of salaries, level of legality of income of population, family status of  population, employment rate, age structure of population etc. As for internal factors we single out the following: low level of basic professional training, use of unskilled workers, absence of conditions for creativity, imperfection of system of motivation of professional growth, absence of specialized centers for certification training etc. Quantity and quality analysis of the above mentioned factors will enable to determine the level of social effectiveness of business entities. For analyses of degree of influence of factors on effectiveness we worked out a questionnaire of expert assessment which is represented in the form of assessment scale. We conducted a questionnaire and analyzed expert results and determined degree of influence of factors on social effectiveness of business. Assessment of level of social effectiveness of business entities was carried out by expert method of certain factor and was represented by a formula. The scale of assessment of

78 FR 31822 - Unincorporated Business Entities

Science.gov (United States)

2013-05-28

... framework for Farm Credit System (System) institutions' use of unincorporated business entities (UBEs) organized under State law for certain business activities. A UBE includes limited partnerships (LPs...-AC65 Unincorporated Business Entities AGENCY: Farm Credit Administration. ACTION: Final rule. SUMMARY...

The wisdom of ignorant crowds: Predicting sport outcomes by mere recognition

Directory of Open Access Journals (Sweden)

Stefan M. Herzog

2011-02-01

Full Text Available that bets on the fact that people's recognition knowledge of names is a proxy for their competitiveness: In sports, it predicts that the better-known team or player wins a game. We present two studies on the predictive power of recognition in forecasting soccer games (World Cup 2006 and UEFA Euro 2008 and analyze previously published results. The performance of the collective recognition heuristic is compared to two benchmarks: predictions based on official rankings and aggregated betting odds. Across three soccer and two tennis tournaments, the predictions based on recognition performed similar to those based on rankings; when compared with betting odds, the heuristic fared reasonably well. Forecasts based on rankings---but not on betting odds---were improved by incorporating collective recognition information. We discuss the use of recognition for forecasting in sports and conclude that aggregating across individual ignorance spawns collective wisdom.

Package Design Affects Accuracy Recognition for Medications.

Science.gov (United States)

Endestad, Tor; Wortinger, Laura A; Madsen, Steinar; Hortemo, Sigurd

2016-12-01

Our aim was to test if highlighting and placement of substance name on medication package have the potential to reduce patient errors. An unintentional overdose of medication is a large health issue that might be linked to medication package design. In two experiments, placement, background color, and the active ingredient of generic medication packages were manipulated according to best human factors guidelines to reduce causes of labeling-related patient errors. In two experiments, we compared the original packaging with packages where we varied placement of the name, dose, and background of the active ingredient. Age-relevant differences and the effect of color on medication recognition error were tested. In Experiment 1, 59 volunteers (30 elderly and 29 young students), participated. In Experiment 2, 25 volunteers participated. The most common error was the inability to identify that two different packages contained the same active ingredient (young, 41%, and elderly, 68%). This kind of error decreased with the redesigned packages (young, 8%, and elderly, 16%). Confusion errors related to color design were reduced by two thirds in the redesigned packages compared with original generic medications. Prominent placement of substance name and dose with a band of high-contrast color support recognition of the active substance in medications. A simple modification including highlighting and placing the name of the active ingredient in the upper right-hand corner of the package helps users realize that two different packages can contain the same active substance, thus reducing the risk of inadvertent medication overdose. © 2016, Human Factors and Ergonomics Society.

Face recognition using slow feature analysis and contourlet transform

Science.gov (United States)

Wang, Yuehao; Peng, Lingling; Zhe, Fuchuan

2018-04-01

In this paper we propose a novel face recognition approach based on slow feature analysis (SFA) in contourlet transform domain. This method firstly use contourlet transform to decompose the face image into low frequency and high frequency part, and then takes technological advantages of slow feature analysis for facial feature extraction. We named the new method combining the slow feature analysis and contourlet transform as CT-SFA. The experimental results on international standard face database demonstrate that the new face recognition method is effective and competitive.

Name agreement in picture naming : An ERP study

NARCIS (Netherlands)

Cheng, Xiaorong; Schafer, Graham; Akyürek, Elkan G.

Name agreement is the extent to which different people agree on a name for a particular picture. Previous studies have found that it takes longer to name low name agreement pictures than high name agreement pictures. To examine the effect of name agreement in the online process of picture naming, we

A family of names : rune-names and ogam-names and their relation to alphabet letter-names

NARCIS (Netherlands)

Griffiths, Alan

2013-01-01

The current consensus is that vernacular names assigned to the runes of the Germanic fuþark and to Irish ogam characters are indigenous creations independent of Mediterranean alphabet traditions. I propose, however, that ogam-names are based on interpretations of Hebrew, Greek or Latin letter-names

Investigation of efficient features for image recognition by neural networks.

Science.gov (United States)

Goltsev, Alexander; Gritsenko, Vladimir

2012-04-01

In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. Copyright © 2011 Elsevier Ltd. All rights reserved.

A GPU-paralleled implementation of an enhanced face recognition algorithm

Science.gov (United States)

Chen, Hao; Liu, Xiyang; Shao, Shuai; Zan, Jiguo

2013-03-01

Face recognition algorithm based on compressed sensing and sparse representation is hotly argued in these years. The scheme of this algorithm increases recognition rate as well as anti-noise capability. However, the computational cost is expensive and has become a main restricting factor for real world applications. In this paper, we introduce a GPU-accelerated hybrid variant of face recognition algorithm named parallel face recognition algorithm (pFRA). We describe here how to carry out parallel optimization design to take full advantage of many-core structure of a GPU. The pFRA is tested and compared with several other implementations under different data sample size. Finally, Our pFRA, implemented with NVIDIA GPU and Computer Unified Device Architecture (CUDA) programming model, achieves a significant speedup over the traditional CPU implementations.

Gabor Weber Local Descriptor for Bovine Iris Recognition

Directory of Open Access Journals (Sweden)

Shengnan Sun

2013-01-01

Full Text Available Iris recognition is a robust biometric technology. This paper proposes a novel local descriptor for bovine iris recognition, named Gabor Weber local descriptor (GWLD. We first compute the Gabor magnitude maps for the input bovine iris image, and then calculate the differential excitation and orientation for each pixel over each Gabor magnitude map. After that, we use these differential excitations and orientations to construct the GWLD histogram representation. Finally, histogram intersection is adopted to measure the similarity between different GWLD histograms. The experimental results on the SEU bovine iris database verify the representation power of our proposed local descriptor.

Age effects on visual-perceptual processing and confrontation naming.

Science.gov (United States)

Gutherie, Audrey H; Seely, Peter W; Beacham, Lauren A; Schuchard, Ronald A; De l'Aune, William A; Moore, Anna Bacon

2010-03-01

The impact of age-related changes in visual-perceptual processing on naming ability has not been reported. The present study investigated the effects of 6 levels of spatial frequency and 6 levels of contrast on accuracy and latency to name objects in 14 young and 13 older neurologically normal adults with intact lexical-semantic functioning. Spatial frequency and contrast manipulations were made independently. Consistent with the hypotheses, variations in these two visual parameters impact naming ability in young and older subjects differently. The results from the spatial frequency-manipulations revealed that, in general, young vs. older subjects are faster and more accurate to name. However, this age-related difference is dependent on the spatial frequency on the image; differences were only seen for images presented at low (e.g., 0.25-1 c/deg) or high (e.g., 8-16 c/deg) spatial frequencies. Contrary to predictions, the results from the contrast manipulations revealed that overall older vs. young adults are more accurate to name. Again, however, differences were only seen for images presented at the lower levels of contrast (i.e., 1.25%). Both age groups had shorter latencies on the second exposure of the contrast-manipulated images, but this possible advantage of exposure was not seen for spatial frequency. Category analyses conducted on the data from this study indicate that older vs. young adults exhibit a stronger nonliving-object advantage for naming spatial frequency-manipulated images. Moreover, the findings suggest that bottom-up visual-perceptual variables integrate with top-down category information in different ways. Potential implications on the aging and naming (and recognition) literature are discussed.

Citizen Science for Mining the Biomedical Literature

Directory of Open Access Journals (Sweden)

Ginger Tsueng

2016-12-01

Full Text Available Biomedical literature represents one of the largest and fastest growing collections of unstructured biomedical knowledge. Finding critical information buried in the literature can be challenging. To extract information from free-flowing text, researchers need to: 1. identify the entities in the text (named entity recognition, 2. apply a standardized vocabulary to these entities (normalization, and 3. identify how entities in the text are related to one another (relationship extraction. Researchers have primarily approached these information extraction tasks through manual expert curation and computational methods. We have previously demonstrated that named entity recognition (NER tasks can be crowdsourced to a group of non-experts via the paid microtask platform, Amazon Mechanical Turk (AMT, and can dramatically reduce the cost and increase the throughput of biocuration efforts. However, given the size of the biomedical literature, even information extraction via paid microtask platforms is not scalable. With our web-based application Mark2Cure (http://mark2cure.org, we demonstrate that NER tasks also can be performed by volunteer citizen scientists with high accuracy. We apply metrics from the Zooniverse Matrices of Citizen Science Success and provide the results here to serve as a basis of comparison for other citizen science projects. Further, we discuss design considerations, issues, and the application of analytics for successfully moving a crowdsourcing workflow from a paid microtask platform to a citizen science platform. To our knowledge, this study is the first application of citizen science to a natural language processing task.

46 CFR 403.110 - Accounting entities.

Science.gov (United States)

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Accounting entities. 403.110 Section 403.110 Shipping COAST GUARD (GREAT LAKES PILOTAGE), DEPARTMENT OF HOMELAND SECURITY GREAT LAKES PILOTAGE UNIFORM ACCOUNTING SYSTEM General § 403.110 Accounting entities. Each Association shall be a separate accounting...

Code-first development with Entity Framework

CERN Document Server

Barskiy, Sergey

2015-01-01

This book is intended for software developers with some prior experience with the Microsoft .NET framework who want to learn how to use Entity Framework. This book will get you up and running quickly, providing many examples that illustrate all the key concepts of Entity Framework.

Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi

Science.gov (United States)

C.L. Schoch; B. Robbertse; V. Robert; R.G. Haight; K. Kovacs; B. Leung; W. Meyer; R.H. Nilsson; K. Hughes; A.N. Miller; P.M. Kirk; K. Abarenkov; M.C. Aime; H.A. Ariyawansa; M. Bidartondo; T. Boekhout; B. Buyck; Q. Cai; J. Chen; A. Crespo; P.W. Crous; U. Damm; Z.W. De Beer; B.T.M. Dentinger; P.K. Divakar; M. Duenas; N. Feau; K. Fliegerova; M.A. Garcia; Z.-W. Ge; G.W. Griffith; J.Z. Groenewald; M. Groenewald; M. Grube; M. Gryzenhout; C. Gueidan; L. Guo; S. Hambleton; R. Hamelin; K. Hansen; V. Hofstetter; S.-B. Hong; J. Houbraken; K.D. Hyde; P. Inderbitzin; P.R. Johnston; S.C. Karunarathna; U. Koljalg; G.M. Kovacs; E. Kraichak; K. Krizsan; C.P. Kurtzman; K.-H. Larsson; S. Leavitt; P.M. Letcher; K. Liimatainen; J.-K. Liu; D.J. Lodge; J. Jennifer Luangsa-ard; H.T. Lumbsch; S.S.N. Maharachchikumbura; D. Manamgoda; M.P. Martin; A.M. Minnis; J.-M. Moncalvo; G. Mule; K.K. Nakasone; T. Niskanen; I. Olariaga; T. Papp; T. Petkovits; R. Pino-Bodas; M.J. Powell; H.A. Raja; D. Redecker; J.M. Sarmiento-Ramirez; K.A. Seifert; B. Shrestha; S. Stenroos; B. Stielow; S.-O. Suh; K. Tanaka; L. Tedersoo; M.T. Telleria; D. Udayanga; W.A. Untereiner; J. Dieguez Uribeondo; K.V. Subbarao; C. Vagvolgyi; C. Visagie; K. Voigt; D.M. Walker; B.S. Weir; M. Weiss; N.N. Wijayawardene; M.J. Wingfield; J.P. Xu; Z.L. Yang; N. Zhang; W.-Y. Zhuang; S. Federhen

2014-01-01

DNA phylogenetic comparisons have shown that morphology-based species recognition often underestimates fungal diversity. Therefore, the need for accurate DNA sequence data, tied to both correct taxonomic names and clearly annotated specimen data, has never been greater. Furthermore, the growing number of molecular ecology and microbiome projects using high-throughput...

NetiNeti: discovery of scientific names from text using machine learning methods

Directory of Open Access Journals (Sweden)

Akella Lakshmi

2012-08-01

Full Text Available Abstract Background A scientific name for an organism can be associated with almost all biological data. Name identification is an important step in many text mining tasks aiming to extract useful information from biological, biomedical and biodiversity text sources. A scientific name acts as an important metadata element to link biological information. Results We present NetiNeti (Name Extraction from Textual Information-Name Extraction for Taxonomic Indexing, a machine learning based approach for recognition of scientific names including the discovery of new species names from text that will also handle misspellings, OCR errors and other variations in names. The system generates candidate names using rules for scientific names and applies probabilistic machine learning methods to classify names based on structural features of candidate names and features derived from their contexts. NetiNeti can also disambiguate scientific names from other names using the contextual information. We evaluated NetiNeti on legacy biodiversity texts and biomedical literature (MEDLINE. NetiNeti performs better (precision = 98.9% and recall = 70.5% compared to a popular dictionary based approach (precision = 97.5% and recall = 54.3% on a 600-page biodiversity book that was manually marked by an annotator. On a small set of PubMed Central’s full text articles annotated with scientific names, the precision and recall values are 98.5% and 96.2% respectively. NetiNeti found more than 190,000 unique binomial and trinomial names in more than 1,880,000 PubMed records when used on the full MEDLINE database. NetiNeti also successfully identifies almost all of the new species names mentioned within web pages. Conclusions We present NetiNeti, a machine learning based approach for identification and discovery of scientific names. The system implementing the approach can be accessed at http://namefinding.ubio.org.

Society as a crime victim of legal entities

Directory of Open Access Journals (Sweden)

Tanjević Nataša

2011-01-01

Full Text Available Tortious acts of legal entities have unforeseen harmful consequences in all areas. In the greedy desire to gain profit, certain legal entities do not have any regard for the most important resources of individuals and society. Damage resulting from the commission of criminal acts is very high for the whole society, especially when it comes to crimes against the environment. In order to prevent and combat corporate crime in criminal law, an increasingly wider acceptance of criminal liability of legal entities was adopted. This paper discusses the basic characteristics of corporate crime, as well as the reasons for the introduction of the criminal responsibility of legal entities. In this regard, we analyzed the law provisions regarding the liability of legal entities for criminal offenses, and concluded that despite the criminal-political need to react with more serious sanctions to the offenses of legal entities, there are certain obstacles and problems that stand in the way of introducing this responsibility.

Discrimination of legal entities: Phenomenological characteristics and legal protection

Directory of Open Access Journals (Sweden)

Petrušić Nevena

2017-01-01

Full Text Available Their social nature encourages people to associate and jointly achieve the goals that they would not be able to achieve individually. Legal entities are created as one of the legal modalities of that association, as separate entities that have their own legal personality independent of the subjectivity of their members. Legal entities are holders of some human rights, depending on the nature of the right, including the right to non-discrimination. All mechanisms envisaged for legal protection against discrimination in the national legislation are available to legal persons. On the other hand, the situation is quite different in terms of access to international forums competent to deal with cases of discrimination. Legal entities do not have access to some international forums, while they may have access to others under the same conditions prescribed for natural persons. Legal entities may be exposed to various forms of direct and indirect discrimination both in the private and in the public sphere of social relations. Phenomenological characteristics of discrimination against legal persons are not substantially different from discrimination against individuals. There are no significant differences regarding the application of discrimination test in cases of discrimination of legal entities as compared to the use of this test in cases involving discrimination of natural persons or groups of persons. Legal entities may be discriminated against on the basis of characteristics of their legal personality, such as those which are objective elements of the legal entity and part of its legal identity. Discrimination of legal entities may be based on personal characteristics of its members (i.e. people who make a personal essence of a legal entity because their characteristics can be 'transferred' to the legal entity and become part of its identity. Legal entities should also be protected from this special form of transferred (associative discrimination.

On the Meaning of Name in Plato’s Cratylus Dialogue and the Epic Tales of Dede Korkut

Directory of Open Access Journals (Sweden)

Vefa Taşdelen

2015-12-01

Full Text Available Being given a name and giving a name are the most basic features of human being. He gives a name to himself as well as other entities in the universe he lives; recognizes them with names and provides introduction; establishes a relationship with them over the names. Everything manifesting itself to human consciousness in the universe and having a relationship with people have a name. From this perspective, giving a name is a problem with language and the origin of language. Asking the origin of names is to ask the origin of language; asking the relationship between names with regard to objects is to ask the relationship between language and reality and increasingly truth. The first work on names hence the philosophy of language was of Plato. Cratylus dialogue among his age of maturity dialogues where he developed his idealistic philosophy was the first work on names and hence the philosophy of language.  In this dialogue, two points of view face each other. One of them is conventionalist approach of Hermogenes and the other is naturalist approach of Cratylus.   In this frame, the answer will be sought to the following questions: In Tales of Dede Korkut, (1 What is the function of names? (2 How many correct names does a thing/object have? (3 What kind of relationship can be achieved between objects and names? (4 Who gives the names?

A Calculus of Located Entities

Directory of Open Access Journals (Sweden)

Adriana Compagnoni

2014-03-01

Full Text Available We define BioScapeL, a stochastic pi-calculus in 3D-space. A novel aspect of BioScapeL is that entities have programmable locations. The programmer can specify a particular location where to place an entity, or a location relative to the current location of the entity. The motivation for the extension comes from the need to describe the evolution of populations of biochemical species in space, while keeping a sufficiently high level description, so that phenomena like diffusion, collision, and confinement can remain part of the semantics of the calculus. Combined with the random diffusion movement inherited from BioScape, programmable locations allow us to capture the assemblies of configurations of polymers, oligomers, and complexes such as microtubules or actin filaments. Further new aspects of BioScapeL include random translation and scaling. Random translation is instrumental in describing the location of new entities relative to the old ones. For example, when a cell secretes a hydronium ion, the ion should be placed at a given distance from the originating cell, but in a random direction. Additionally, scaling allows us to capture at a high level events such as division and growth; for example, daughter cells after mitosis have half the size of the mother cell.

Entity models for trigger-reaction documents

NARCIS (Netherlands)

Khalid, M.A.; Marx, M.; Makkes, M.X.

2008-01-01

We define the notion of an entity model for a special kind of document popular on the web: an article followed by a list of reactions on that article, usually by many authors, usually inverse chronologically ordered. We call these documents trigger-reactions pairs. The entity model describes which

The first does the work, but the third time's the charm: the effects of massed repetition on episodic encoding of multimodal face-name associations.

Science.gov (United States)

Mangels, Jennifer A; Manzi, Alberto; Summerfield, Christopher

2010-03-01

In social interactions, it is often necessary to rapidly encode the association between visually presented faces and auditorily presented names. The present study used event-related potentials to examine the neural correlates of associative encoding for multimodal face-name pairs. We assessed study-phase processes leading to high-confidence recognition of correct pairs (and consistent rejection of recombined foils) as compared to lower-confidence recognition of correct pairs (with inconsistent rejection of recombined foils) and recognition failures (misses). Both high- and low-confidence retrieval of face-name pairs were associated with study-phase activity suggestive of item-specific processing of the face (posterior inferior temporal negativity) and name (fronto-central negativity). However, only those pairs later retrieved with high confidence recruited a sustained centro-parietal positivity that an ancillary localizer task suggested may index an association-unique process. Additionally, we examined how these processes were influenced by massed repetition, a mnemonic strategy commonly employed in everyday situations to improve face-name memory. Differences in subsequent memory effects across repetitions suggested that associative encoding was strongest at the initial presentation, and thus, that the initial presentation has the greatest impact on memory formation. Yet, exploratory analyses suggested that the third presentation may have benefited later memory by providing an opportunity for extended processing of the name. Thus, although encoding of the initial presentation was critical for establishing a strong association, the extent to which processing was sustained across subsequent immediate (massed) presentations may provide additional encoding support that serves to differentiate face-name pairs from similar (recombined) pairs by providing additional encoding opportunities for the less dominant stimulus dimension (i.e., name).

The Neuropsychology of Familiar Person Recognition from Face and Voice

Directory of Open Access Journals (Sweden)

Guido Gainotti

2014-05-01

Full Text Available Prosopagnosia has been considered for a long period of time as the most important and almost exclusive disorder in the recognition of familiar people. In recent years, however, this conviction has been undermined by the description of patients showing a concomitant defect in the recognition of familiar faces and voices as a consequence of lesions encroaching upon the right anterior temporal lobe (ATL. These new data have obliged researchers to reconsider on one hand the construct of ‘associative prosopagnosia’ and on the other hand current models of people recognition. A systematic review of the patterns of familiar people recognition disorders observed in patients with right and left ATL lesions has shown that in patients with right ATL lesions face familiarity feelings and the retrieval of person-specific semantic information from faces are selectively affected, whereas in patients with left ATL lesions the defect selectively concerns famous people naming. Furthermore, some patients with right ATL lesions and intact face familiarity feelings show a defect in the retrieval of person-specific semantic knowledge greater from face than from name. These data are at variance with current models assuming: (a that familiarity feelings are generated at the level of person identity nodes (PINs where information processed by various sensory modalities converge, and (b that PINs provide a modality-free gateway to a single semantic system, where information about people is stored in an amodal format. They suggest, on the contrary: (a that familiarity feelings are generated at the level of modality-specific recognition units; (b that face and voice recognition units are represented more in the right than in the left ATLs; (c that in the right ATL are mainly stored person-specific information based on a convergence of perceptual information, whereas in the left ATLs are represented verbally-mediated person-specific information.

HWDA: A coherence recognition and resolution algorithm for hybrid web data aggregation

Science.gov (United States)

Guo, Shuhang; Wang, Jian; Wang, Tong

2017-09-01

Aiming at the object confliction recognition and resolution problem for hybrid distributed data stream aggregation, a distributed data stream object coherence solution technology is proposed. Firstly, the framework was defined for the object coherence conflict recognition and resolution, named HWDA. Secondly, an object coherence recognition technology was proposed based on formal language description logic and hierarchical dependency relationship between logic rules. Thirdly, a conflict traversal recognition algorithm was proposed based on the defined dependency graph. Next, the conflict resolution technology was prompted based on resolution pattern matching including the definition of the three types of conflict, conflict resolution matching pattern and arbitration resolution method. At last, the experiment use two kinds of web test data sets to validate the effect of application utilizing the conflict recognition and resolution technology of HWDA.

On the Evaluation of Entity Profiles

DEFF Research Database (Denmark)

de Rijke, Maarten; Balog, Krisztian; Bogers, Toine

be assessed by means of precision and recall values of the descriptive terms produced. However, recent evidence suggests that more sophisticated metrics are needed that go beyond mere lexical matching of system-produced descriptors against a ground truth, allowing for graded relevance and rewarding diversity......Entity profiling is the task of identifying and ranking descriptions of a given entity. The task may be viewed as one where the descriptions being sought are terms that need to be selected from a knowledge source (such as an ontology or thesaurus). In this case, entity profiling systems can...... in the list of descriptors returned. In this note, we motivate and propose such a metric....

It's all connected: Pathways in visual object recognition and early noun learning.

Science.gov (United States)

Smith, Linda B

2013-11-01

A developmental pathway may be defined as the route, or chain of events, through which a new structure or function forms. For many human behaviors, including object name learning and visual object recognition, these pathways are often complex and multicausal and include unexpected dependencies. This article presents three principles of development that suggest the value of a developmental psychology that explicitly seeks to trace these pathways and uses empirical evidence on developmental dependencies among motor development, action on objects, visual object recognition, and object name learning in 12- to 24-month-old infants to make the case. The article concludes with a consideration of the theoretical implications of this approach. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition

Directory of Open Access Journals (Sweden)

Bineng Zhong

2008-06-01

Full Text Available This paper proposes a new face recognition method, named kernel learning of histogram of local Gabor phase pattern (K-HLGPP, which is based on Daugman’s method for iris recognition and the local XOR pattern (LXP operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition, we encode the Gabor phase information for face classification by the quadrant bit coding (QBC method. Two schemes are proposed for face recognition. One is based on the nearest-neighbor classifier with chi-square as the similarity measurement, and the other makes kernel discriminant analysis for HLGPP (K-HLGPP using histogram intersection and Gaussian-weighted chi-square kernels. The comparative experiments show that K-HLGPP achieves a higher recognition rate than other well-known face recognition systems on the large-scale standard FERET, FERET200, and CAS-PEAL-R1 databases.

The effects of presentation methods and semantic information on multi-ethnicity face recognition

Directory of Open Access Journals (Sweden)

Kaarel Rundu

2012-01-01

Full Text Available Studies have shown that own-race faces are more accurately recognised than other-race faces. The present study examined the effects of own- and other-race face recognition when different ethnicity targets are presented to the participants together. Also the effect of semantic information on the recognition of different race faces was examined. The participants (N = 234 were presented with photos of own-race and other-race faces. For some participants the faces were presented with stereotypical names and for some not. As hypothesized, own-race faces were better recognised in target-present lineup and more correctly rejected in target-absent lineup than other-race faces. Concerning presentation method, both own-race and other-race faces were more correctly identified in target-present simultaneous than in target-present sequential lineups. No effects of stereotypical names on face recognition were found. The findings suggest that identifying multi-ethnicity perpetrators is a problematic and difficult task.

Scene recognition based on integrating active learning with dictionary learning

Science.gov (United States)

Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen

2018-04-01

Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

Entity Framework 4.0 Recipes A Problem-solution Approach

CERN Document Server

Tenny, L

2010-01-01

Entity Framework 4.0 Recipes provides an exhaustive collection of ready-to-use code solutions for Microsoft's Entity Framework, Microsoft's vision for the future of data access. Entity Framework is a model-centric data access platform with an ocean of new concepts and patterns for developers to learn. With this book, you will learn the core concepts of Entity Framework through a broad range of clear and concise solutions to everyday data access tasks. Armed with this experience, you will be ready to dive deep into Entity Framework, experiment with new approaches, and develop ways to solve even

The role of typography in differentiating look-alike/sound-alike drug names.

Science.gov (United States)

Gabriele, Sandra

2006-01-01

Until recently, when errors occurred in the course of caring for patients, blame was assigned to the healthcare professionals closest to the incident rather than examining the larger system and the actions that led up to the event. Now, the medical profession is embracing expertise and methodologies used in other fields to improve its own systems in relation to patient safety issues. This exploratory study, part of a Master's of Design thesis project, was a response to the problem of errors that occur due to confusion between look-alike/sound-alike drug names (medication names that have orthographic and/or phonetic similarities). The study attempts to provide a visual means to help differentiate problematic names using formal typographic and graphic cues. The FDA's Name Differentiation Project recommendations and other typographic alternatives were considered to address issues of attention and cognition. Eleven acute care nurses participated in testing that consisted of word-recognition tasks and questions intended to elicit opinions regarding the visual treatment of look-alike/sound-alike names in the context of a label prototype. Though limited in sample size, testing provided insight into the kinds of typographic differentiation that might be effective in a high-risk situation.

On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information

Science.gov (United States)

Stathopoulou, I.-O.; Alepis, E.; Tsihrintzis, G. A.; Virvou, M.

Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.

Mastering entity framework

CERN Document Server

Singh, Rahul Rajat

2015-01-01

This book is for .NET developers who are developing data-driven applications using ADO.NET or other data access technologies. This book is going to give you everything you need to effectively develop and manage data-driven applications using Entity Framework.

Cuticular hydrocarbons as potential kin recognition cues in a subsocial spider

DEFF Research Database (Denmark)

Grinsted, Lena; Bilde, Trine; D'Ettorre, Patrizia

2011-01-01

of recognition cues in subsocial species can provide insights into evolutionary pathways leading to permanent sociality and kin-selected benefits of cooperation. In subsocial spiders, empirical evidence suggests the existence of both kin recognition and benefits of cooperating with kin, whereas the cues for kin...... recognition have yet to be identified. However, cuticular hydrocarbons have been proposed to be involved in regulation of tolerance and interattraction in spider sociality. Here, we show that subsocial Stegodyphus lineatus spiderlings have cuticular hydrocarbon profiles that are sibling-group specific, making...... be branched alkanes that are influenced very little by rearing conditions and may be genetically determined. This indicates that a specific group of cuticular chemicals, namely branched alkanes, could have evolved to act as social recognition cues in both insects and spiders....

Very low resolution face recognition problem.

Science.gov (United States)

Zou, Wilman W W; Yuen, Pong C

2012-01-01

This paper addresses the very low resolution (VLR) problem in face recognition in which the resolution of the face image to be recognized is lower than 16 × 16. With the increasing demand of surveillance camera-based applications, the VLR problem happens in many face application systems. Existing face recognition algorithms are not able to give satisfactory performance on the VLR face image. While face super-resolution (SR) methods can be employed to enhance the resolution of the images, the existing learning-based face SR methods do not perform well on such a VLR face image. To overcome this problem, this paper proposes a novel approach to learn the relationship between the high-resolution image space and the VLR image space for face SR. Based on this new approach, two constraints, namely, new data and discriminative constraints, are designed for good visuality and face recognition applications under the VLR problem, respectively. Experimental results show that the proposed SR algorithm based on relationship learning outperforms the existing algorithms in public face databases.

RUTHERFORD APPLETON: What's in a name?!

International Nuclear Information System (INIS)

Anon.

1995-01-01

Full text: The initials 'RAU are well known in the world of particle physics, but recently the official name of the Laboratory has undergone several transmogrifications. To further complicate matters, the funding body for Particle Physics within the UK has changed too! On 1 April 1994 the Rutherford Appleton Laboratory combined with the Daresbury Laboratory to become a combined laboratory known as the Daresbury and Rutherford Appleton Laboratories (DRAL). At the same time the old Science and Engineering Research Council (SERC) was wound up, and funding was channelled through the newly formed Particle Physics and Astronomy Research Council (PPARC). Also, and just for an interim period, DRAL became part of the new Engineering and Physical Sciences Research Council (EPSRC). One year later a more profound change occurred when DRAL became a Research Council in its own right, and the legal entity created by Royal Charter was named The Council for the Central Laboratory of the Research Councils', abbreviated to CCLRC. On 1 April 1995, DRAL became The Central Laboratory of the Research Councils', and the abbreviation CLRC may be used. In spite of the changes to the official name, the laboratory sited at Chilton, The DAPNIA (Saclay, France) and Argonne transportable polarized target used in 1989- 1990 for a Fermi lab experiment has been used in a new experiment at Dubna. Gilles Durand from DAPNIA (right) and Yuri Usov of Dubna's Joint Institute for Nuclear Research (JINR) were responsible for construction. Oxfordshire, will continue to be known as the Rutherford Appleton Laboratory, or RAL

Declines in tobacco brand recognition and ever-smoking rates among young children following restrictions on tobacco advertisements in Hong Kong.

Science.gov (United States)

Fielding, R; Chee, Y Y; Choi, K M; Chu, T K; Kato, K; Lam, S K; Sin, K L; Tang, K T; Wong, H M; Wong, K M

2004-03-01

We compared the recognition of tobacco brands and ever-smoking rates in young children before (1991) and after (2001) the implementation of cigarette advertising restrictions in Hong Kong and identified continuing sources of tobacco promotion exposure. A cross-sectional survey of 824 primary school children aged from 8 to 11 (Primary classes 3-4) living in two Hong Kong districts was carried out using self-completed questionnaires examining smoking behaviour and recognition of names and logos from 18 tobacco, food, drink and other brands common in Hong Kong. Ever-smoking prevalence in 2001 was 3.8 per cent (1991, 7.8 per cent). Tobacco brand recognition rates ranged from 5.3 per cent (Viceroy name) to 72.8 per cent (Viceroy logo). Compared with 1991, in 2001 never-smoker children recognized fewer tobacco brand names and logos: Marlboro logo recognition rate fell by 55.3 per cent. Similar declines were also seen in ever-smoker children, with recognition of the Marlboro logo decreasing 48 per cent. Recognition rates declined amongst both boys and girls. Children from non-smoking families constituted 51 per cent (426) of the sample, whereas 34.5 per cent (284), 8.5 per cent (70), 1.7 per cent (14) and 4.4 per cent (36) of the children had one, two, three or more than three smoking family members at home, respectively. Tobacco brand recognition rates and ever-smoking prevalence were significantly higher among children with smoking family members compared with those without. Among 12 possible sources of exposure to cigarette brand names and logos, retail stalls (75.5 per cent; 622), indirect advertisements (71.5 per cent; 589) and magazines (65.3 per cent; 538) were ranked the most common. Advertising restrictions in Hong Kong have effectively decreased primary-age children's recognition of tobacco branding. However, these children remain vulnerable to branding, mostly through exposure from family smokers, point-of-sale tobacco advertisement and occasional promotions

17 CFR Appendix A to Part 420 - Separate Reporting Entity

Science.gov (United States)

2010-04-01

... 17 Commodity and Securities Exchanges 3 2010-04-01 2010-04-01 false Separate Reporting Entity A... Part 420—Separate Reporting Entity Subject to the following conditions, one or more aggregating entity(ies) (e.g., parent, subsidiary, or organizational component) in a reporting entity, either separately...

VALUE RELEVANCE OF GROUP FINANCIAL STATEMENTS BASED ON ENTITY VERSUS PARENT COMPANY THEORY: EVIDENCE FROM THE LARGEST THREE EUROPEAN CAPITAL MARKETS

Directory of Open Access Journals (Sweden)

Müller Victor-Octavian

2012-07-01

Full Text Available Financial statementsn#8217; main objective is to give information on the financial position, performance and changes in financial position of the reporting entity, which is useful to investors and other users in making economic decisions. In order to be useful, financial information needs to be relevant to the decision-making process of users in general, and investors in particular. Regarding consolidated financial statements, the accounting theory knows four perspectives (theories on which the preparation of those statements is based, namely, the proprietary theory, the parent company theory, the parent company extension theory and the entity theory (Baxter and Spinney, 1975. Of practical importance are especially the parent company extension perspective and the entity perspective. The IASB and FASB decided (within an ED regarding the Improvement of the Conceptual Framework that consolidated financial statements should be presented from the perspective of the group entity, and not from the perspective of the parent-company. However, this support for the entity theory is to our knowledge not backed by empirical findings in the academic literature. Therefore, in our paper we set to contribute with empirical arguments to finding an actual answer to the question about the superior market value relevance of one of the two concurrent perspectives (theories. We set to carry out an empirical association study on the problem of market value relevance of consolidated financial statements based on the entity theory respectively on the parent company (extension theory, searching for an answer to the above question. In this sense, we pursued an analysis of market value relevance of consolidated accounting information (based on the two perspectives of listed entities between 2003-2008 on the largest three European Stock Exchanges (London, Paris and Frankfurt. The obtained results showed that a n#8222;restrainedn#8221; entity perspective, which would combine

WCF multi-layer services development with Entity framework

CERN Document Server

Liu, Mike

2014-01-01

If you are a C#, VB.NET, or C++ developer and want to get started with WCF and Entity Framework, then this book is for you. Competence in Entity Framework will be needed to follow the examples in the book, but experience in creating WCF services using Entity Framework is not necessary. Developers and architects evaluating SOA implementation technologies for their company will find this book useful.

Single-Molecule View of Small RNA-Guided Target Search and Recognition.

Science.gov (United States)

Globyte, Viktorija; Kim, Sung Hyun; Joo, Chirlmin

2018-05-20

Most everyday processes in life involve a necessity for an entity to locate its target. On a cellular level, many proteins have to find their target to perform their function. From gene-expression regulation to DNA repair to host defense, numerous nucleic acid-interacting proteins use distinct target search mechanisms. Several proteins achieve that with the help of short RNA strands known as guides. This review focuses on single-molecule advances studying the target search and recognition mechanism of Argonaute and CRISPR (clustered regularly interspaced short palindromic repeats) systems. We discuss different steps involved in search and recognition, from the initial complex prearrangement into the target-search competent state to the final proofreading steps. We focus on target search mechanisms that range from weak interactions, to one- and three-dimensional diffusion, to conformational proofreading. We compare the mechanisms of Argonaute and CRISPR with a well-studied target search system, RecA.

Door recognition in cluttered building interiors using imagery and lidar data

Science.gov (United States)

Díaz-Vilariño, L.; Martínez-Sánchez, J.; Lagüela, S.; Armesto, J.; Khoshelham, K.

2014-06-01

Building indoors reconstruction is an active research topic due to the importance of the wide range of applications to which they can be subjected, from architecture and furniture design, to movies and video games editing, or even crime scene investigation. Among the constructive elements defining the inside of a building, doors are important entities in applications like routing and navigation, and their automated recognition is advantageous e.g. in case of large multi-storey buildings with many office rooms. The inherent complexity of the automation of the recognition process is increased by the presence of clutter and occlusions, difficult to avoid in indoor scenes. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors using information acquired in the form of point clouds and images. The methodology goes in depth with door detection and labelling as either opened, closed or furniture (false positive)

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

Directory of Open Access Journals (Sweden)

Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Responses to Co-workers Receiving Recognition at Work: A Case Study in Cameroon

OpenAIRE

Viviane, Che Mezoh Akuro

2014-01-01

ABSTRACT: The purpose of this study is to examine, the impact of co-workers receiving recognition on two types of responses namely, positive /negative and the resulting behavioral intentions (interpersonal counterproductive work behaviors and interpersonal citizenship behaviors). Employees might not only receive recognition themselves in their organizations and groups but often they witness others receiving it either directly by observation or indirectly through stories. This may lead to vari...

INTER–ORGANIZATIONAL COLLABORATIVE CAPACITY OF PUBLIC SECTOR INSTITUTIONS’CONTROL ENTITIES IN EMERGENCY SITUATIONS

Directory of Open Access Journals (Sweden)

Nikola T. STOYANOV

2015-10-01

Full Text Available Environmental challenges and natural disasters demand new tools to support the performance of public institutions in emergency situations. This paper contributes to one of the fundamental objectives – inter–organizational collaboration, namely to the objective to share experience from the implementation of methods and tools and latest research results in support of management in the new security environment. In addition, it focuses on the cognitive and human aspects of collaboration. The goal of the paper is to investigate the impact of different factors and tools for understanding, explaining, and measuring collaborative capacity of public sector institutions’ control organism in emergency situations. The paper will present intermediate results from the research on “Inter–organizational collaborative capacity of public sector institutions’ control entities in emergency situations”. Based on a theoretical model, a draft instrument was developed (i.e., a questionnaire for data collection that can be used to 1 investigate the impact of different factors, 2 localize inefficiencies in public sector institutions’ control organs, and 3 determine measures to achieve better organizational effectiveness of public sector institutions’ control entities in emergency situations.

Problematic issues of accounting reflection and accounting recognition of contributions while carrying out joint activities without forming a legal entity

OpenAIRE

Куришко, Лілія Анатоліївна

2015-01-01

The methodic of accounting reflection of the business transactions related to contributions into the joint activities without forming a legal entity has been studied; the types of contributions defined legally and the possibility of their reflection in accounting have been elucidated; the author’s understanding of the essence of contributions’ types has been formed as well as the approach towards their identification in accounting has been offered

Ranking Entities in Networks via Lefschetz Duality

DEFF Research Database (Denmark)

Aabrandt, Andreas; Hansen, Vagn Lundsgaard; Poulsen, Bjarne

2014-01-01

then be ranked according to how essential their positions are in the network by considering the effect of their respective absences. Defining a ranking of a network which takes the individual position of each entity into account has the purpose of assigning different roles to the entities, e.g. agents......, in the network. In this paper it is shown that the topology of a given network induces a ranking of the entities in the network. Further, it is demonstrated how to calculate this ranking and thus how to identify weak sub-networks in any given network....

Text mining in livestock animal science: introducing the potential of text mining to animal sciences.

Science.gov (United States)

Sahadevan, S; Hofmann-Apitius, M; Schellander, K; Tesfaye, D; Fluck, J; Friedrich, C M

2012-10-01

In biological research, establishing the prior art by searching and collecting information already present in the domain has equal importance as the experiments done. To obtain a complete overview about the relevant knowledge, researchers mainly rely on 2 major information sources: i) various biological databases and ii) scientific publications in the field. The major difference between the 2 information sources is that information from databases is available, typically well structured and condensed. The information content in scientific literature is vastly unstructured; that is, dispersed among the many different sections of scientific text. The traditional method of information extraction from scientific literature occurs by generating a list of relevant publications in the field of interest and manually scanning these texts for relevant information, which is very time consuming. It is more than likely that in using this "classical" approach the researcher misses some relevant information mentioned in the literature or has to go through biological databases to extract further information. Text mining and named entity recognition methods have already been used in human genomics and related fields as a solution to this problem. These methods can process and extract information from large volumes of scientific text. Text mining is defined as the automatic extraction of previously unknown and potentially useful information from text. Named entity recognition (NER) is defined as the method of identifying named entities (names of real world objects; for example, gene/protein names, drugs, enzymes) in text. In animal sciences, text mining and related methods have been briefly used in murine genomics and associated fields, leaving behind other fields of animal sciences, such as livestock genomics. The aim of this work was to develop an information retrieval platform in the livestock domain focusing on livestock publications and the recognition of relevant data from

FINGER KNUCKLE PRINT RECOGNITION WITH SIFT AND K-MEANS ALGORITHM

Directory of Open Access Journals (Sweden)

A. Muthukumar

2013-02-01

Full Text Available In general, the identification and verification are done by passwords, pin number, etc., which is easily cracked by others. Biometrics is a powerful and unique tool based on the anatomical and behavioral characteristics of the human beings in order to prove their authentication. This paper proposes a novel recognition methodology of biometrics named as Finger Knuckle print (FKP. Hence this paper has focused on the extraction of features of Finger knuckle print using Scale Invariant Feature Transform (SIFT, and the key points are derived from FKP are clustered using K-Means Algorithm. The centroid of K-Means is stored in the database which is compared with the query FKP K-Means centroid value to prove the recognition and authentication. The comparison is based on the XOR operation. Hence this paper provides a novel recognition method to provide authentication. Results are performed on the PolyU FKP database to check the proposed FKP recognition method.

Binomial model for measuring expected credit losses from trade receivables in non-financial sector entities

Directory of Open Access Journals (Sweden)

Branka Remenarić

2018-01-01

Full Text Available In July 2014, the International Accounting Standards Board (IASB published International Financial Reporting Standard 9 Financial Instruments (IFRS 9. This standard introduces an expected credit loss (ECL impairment model that applies to financial instruments, including trade and lease receivables. IFRS 9 applies to annual periods beginning on or after 1 January 2018 in the European Union member states. While the main reason for amending the current model was to require major banks to recognize losses in advance of a credit event occurring, this new model also applies to all receivables, including trade receivables, lease receivables, related party loan receivables in non-financial sector entities. The new impairment model is intended to result in earlier recognition of credit losses. The previous model described in International Accounting Standard 39 Financial instruments (IAS 39 was based on incurred losses. One of the major questions now is what models to use to predict expected credit losses in non-financial sector entities. The purpose of this paper is to research the application of the current impairment model, the extent to which the current impairment model can be modified to satisfy new impairment model requirements and the applicability of the binomial model for measuring expected credit losses from accounts receivable.

Reading in Developmental Prosopagnosia: Evidence for a Dissociation Between Word and Face Recognition

DEFF Research Database (Denmark)

Starrfelt, Randi; Klargaard, Solja; Petersen, Anders

2018-01-01

exposure durations (targeting the word superiority effect), and d) text reading. Results: Participants with developmental prosopagnosia performed strikingly similar to controls across the four reading tasks. Formal analysis revealed a significant dissociation between word and face recognition......, that is, impaired reading in developmental prosopagnosia. Method: We tested 10 adults with developmental prosopagnosia and 20 matched controls. All participants completed the Cambridge Face Memory Test, the Cambridge Face Perception test and a Face recognition questionnaire used to quantify everyday face...... recognition experience. Reading was measured in four experimental tasks, testing different levels of letter, word, and text reading: a) single word reading with words of varying length, b) vocal response times in single letter and short word naming, c) recognition of single letters and short words at brief...

Molecular recognition on a cavitand-functionalized silicon surface.

Science.gov (United States)

Biavardi, Elisa; Favazza, Maria; Motta, Alessandro; Fragalà, Ignazio L; Massera, Chiara; Prodi, Luca; Montalti, Marco; Melegari, Monica; Condorelli, Guglielmo G; Dalcanale, Enrico

2009-06-03

A Si(100) surface featuring molecular recognition properties was obtained by covalent functionalization with a tetraphosphonate cavitand (Tiiii), able to complex positively charged species. Tiiii cavitand was grafted onto the Si by photochemical hydrosilylation together with 1-octene as a spatial spectator. The recognition properties of the Si-Tiiii surface were demonstrated through two independent analytical techniques, namely XPS and fluorescence spectroscopy, during the course of reversible complexation-guest exchange-decomplexation cycles with specifically designed ammonium and pyridinium salts. Control experiments employing a Si(100) surface functionalized with a structurally similar, but complexation inactive, tetrathiophosphonate cavitand (TSiiii) demonstrated no recognition events. This provides evidence for the complexation properties of the Si-Tiiii surface, ruling out the possibility of nonspecific interactions between the substrate and the guests. The residual Si-O(-) terminations on the surface replace the guests' original counterions, thus stabilizing the complex ion pairs. These results represent a further step toward the control of self-assembly of complex supramolecular architectures on surfaces.

14 CFR Sec. 1-6 - Accounting entities.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Accounting entities. Sec. 1-6 Section 1-6... REGULATIONS UNIFORM SYSTEM OF ACCOUNTS AND REPORTS FOR LARGE CERTIFICATED AIR CARRIERS General Accounting Provisions Sec. 1-6 Accounting entities. (a) Separate accounting records shall be maintained for each air...

Ranking Very Many Typed Entities on Wikipedia

NARCIS (Netherlands)

Zaragoza, Hugo; Rode, H.; Mika, Peter; Atserias, Jordi; Ciaramita, Massimiliano; Attardi, Guiseppe

2007-01-01

We discuss the problem of ranking very many entities of different types. In particular we deal with a heterogeneous set of types, some being very generic and some very specific. We discuss two approaches for this problem: i) exploiting the entity containment graph and ii) using a Web search engine

Door recognition in cluttered building interiors using imagery and lidar data

Directory of Open Access Journals (Sweden)

L. Díaz-Vilariño

2014-06-01

Full Text Available Building indoors reconstruction is an active research topic due to the importance of the wide range of applications to which they can be subjected, from architecture and furniture design, to movies and video games editing, or even crime scene investigation. Among the constructive elements defining the inside of a building, doors are important entities in applications like routing and navigation, and their automated recognition is advantageous e.g. in case of large multi-storey buildings with many office rooms. The inherent complexity of the automation of the recognition process is increased by the presence of clutter and occlusions, difficult to avoid in indoor scenes. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors using information acquired in the form of point clouds and images. The methodology goes in depth with door detection and labelling as either opened, closed or furniture (false positive

Open-Source Data Collection Techniques for Weapons Transfer Information

Science.gov (United States)

2012-03-01

IR Infrared ISO International Organization for Standardization ITAR International Traffic in Arms Regulations NER Named Entity Recognition NLP ...Control Protocol UAE United Arab Emirates URI Uniform Resource Identifier URL Uniform Resource Locator USSR Union of Soviet Socialist Republics UTF...KOREA, DEMOCRATIC PEOPLE’S REPUBLIC OF North Korea KOREA, REPUBLIC OF South Korea LIBYAN ARAB JAMAHIRIYA Libya RUSSIAN FEDERATION Russia Table 3

Minimizing Co-location Potential of Moving Entities

NARCIS (Netherlands)

Evans, Will; Kirkpatrick, David; Löffler, Maarten; Staals, Frank

2016-01-01

We study the problem of maintaining knowledge of the locations of $n$ entities that are moving, each with some, possibly different, upper bound on their speed. We assume a setting where we can query the current location of any one entity, but this query takes a unit of time, during which we cannot

Chiral separation of α-cyclohexylmandelic acid enantiomers by high-speed counter-current chromatography with biphasic recognition

Science.gov (United States)

Tong, Shengqiang

2010-01-01

This work concentrates on a novel chiral separation technology named biphasic recognition applied to resolution of α-cyclohexylmandelic acid enantiomers by high-speed counter-current chromatography (HSCCC). The biphasic chiral recognition HSCCC was performed by adding lipophilic (−)-2-ethylhexyl tartrate in the organic stationary phase and hydrophilic hydroxypropyl-β-cyclodextrin in the aqueous mobile phase, which preferentially recognized the (−)-enantiomer and (+)-enantiomer, respectively. The two-phase solvent system composed of n-hexane-methyl tert-butyl ether-water (9:1:10, v/v/v) with the above chiral selectors was selected according to the partition coefficient and separation factor of the target enantiomers. Various parameters involved in the chiral separation were investigated, namely the types of the chiral selector (CS); the concentration of each chiral selector; pH of the mobile phase; and the separation temperature. The mechanism involved in this biphasic recognition chiral separation by HSCCC was discussed. Langmuirian isotherm was employed to estimate the loading limits for each chiral selector. The overall experimental results show that the HSCCC separation of enantiomer based on biphasic recognition is much more efficient than the traditional monophasic recognition chiral separation, since it utilizes the cooperation of both lipophilic and hydrophilic chiral selectors. PMID:20303497

EVALUATION METHODS USED FOR TANGIBLE ASSETS BY ECONOMIC ENTITIES

Directory of Open Access Journals (Sweden)

Csongor CSŐSZ

2014-06-01

Full Text Available At many entities the net asset value is influenced by the evaluation methods applied for tangible assets, because the value of intangible assets and financial assets is small in most cases. The objective of this paper is to analyze the differences between the procedures / methods of evaluation applied by micro and small entities and medium and large entities for tangible assets in Romania and Hungary. Furthermore, we analyze the differences between the procedures / methods of evaluation applied by micro and small entities in Romania and Hungary, respectively the differences between medium and large entities regarding de evaluation methods for tangible assets in Romania and Hungary. For this empirical study the questionnaire is used – as research technique, and to demonstrate the significant differences between the evaluation methods we used the Kolmogorov – Smirnov Z test.

Enhancement of chemical entity identification in text using semantic similarity validation.

Directory of Open Access Journals (Sweden)

Tiago Grego

Full Text Available With the amount of chemical data being produced and reported in the literature growing at a fast pace, it is increasingly important to efficiently retrieve this information. To tackle this issue text mining tools have been applied, but despite their good performance they still provide many errors that we believe can be filtered by using semantic similarity. Thus, this paper proposes a novel method that receives the results of chemical entity identification systems, such as Whatizit, and exploits the semantic relationships in ChEBI to measure the similarity between the entities found in the text. The method assigns a single validation score to each entity based on its similarities with the other entities also identified in the text. Then, by using a given threshold, the method selects a set of validated entities and a set of outlier entities. We evaluated our method using the results of two state-of-the-art chemical entity identification tools, three semantic similarity measures and two text window sizes. The method was able to increase precision without filtering a significant number of correctly identified entities. This means that the method can effectively discriminate the correctly identified chemical entities, while discarding a significant number of identification errors. For example, selecting a validation set with 75% of all identified entities, we were able to increase the precision by 28% for one of the chemical entity identification tools (Whatizit, maintaining in that subset 97% the correctly identified entities. Our method can be directly used as an add-on by any state-of-the-art entity identification tool that provides mappings to a database, in order to improve their results. The proposed method is included in a freely accessible web tool at www.lasige.di.fc.ul.pt/webtools/ice/.

On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment.

Science.gov (United States)

Cicirelli, Franco; Fortino, Giancarlo; Giordano, Andrea; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea

2016-09-01

A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.

26 CFR 301.6233-1 - Extension to entities filing partnership returns.

Science.gov (United States)

2010-04-01

... all items of the entity that would be partnership items, as defined in section 6231(a)(3) and the... 26 Internal Revenue 18 2010-04-01 2010-04-01 false Extension to entities filing partnership....6233-1 Extension to entities filing partnership returns. (a) Entities filing a partnership return...

Liponeurocytoma Cerebellar. A new entity; first national case

International Nuclear Information System (INIS)

Cordoba, A.; Tomorrow, G.; Saralegui, P.; Hernandez, P.; Lezue, B.

2004-01-01

The first case of this new entity is presented and accepted within the new SNC (Central nervous system) classification of OMS in 2000. This is about a patient with 52 years old with 9 month of evolution history who presents signs of weight loss and is hospitalized with HEC progressive elements, hydrocephalusand installled coma. The Computerized Axial Tomography reveals expansive process in the posterior fossa hemispheric and cerebellopontine angle 4x5 cms inhomogeneous with bleeding elements and lipid content areas. Is arises the probability of Epidermoid cyst. The surgery is carried out with complete excision of the encapsulated aspiratable lesion. Good postoperative course without gaps. The histopathology revealed typical elements described in the literature: presence of adipose cells and neurocytic proliferation with small elements.This led that the tumor received among others the adult lipomeduloblastoma name but showing a good prognosis in contrast with the classic medulloblastoma. Currently cataloged such as grade II and there are not statistics in the literature because there are only published isolated cases

A name is a name is a name: some thoughts and personal opinions about molluscan scientific names

NARCIS (Netherlands)

Dance, S.P.

2009-01-01

Since 1758, with the publication of Systema Naturae by Linnaeus, thousands of scientific names have been proposed for molluscs. The derivation and uses of many of them are here examined from various viewpoints, beginning with names based on appearance, size, vertical distribution, and location.

Programming Entity Framework Code First

CERN Document Server

Lerman, Julia

2011-01-01

Take advantage of the Code First data modeling approach in ADO.NET Entity Framework, and learn how to build and configure a model based on existing classes in your business domain. With this concise book, you'll work hands-on with examples to learn how Code First can create an in-memory model and database by default, and how you can exert more control over the model through further configuration. Code First provides an alternative to the database first and model first approaches to the Entity Data Model. Learn the benefits of defining your model with code, whether you're working with an exis

Controlled mutual quantum entity authentication using entanglement swapping

International Nuclear Information System (INIS)

Kang, Min-Sung; Hong, Chang-Ho; Heo, Jino; Lim, Jong-In; Yang, Hyung-Jin

2015-01-01

In this paper, we suggest a controlled mutual quantum entity authentication protocol by which two users mutually certify each other on a quantum network using a sequence of Greenberger–Horne–Zeilinger (GHZ)-like states. Unlike existing unidirectional quantum entity authentication, our protocol enables mutual quantum entity authentication utilizing entanglement swapping; moreover, it allows the managing trusted center (TC) or trusted third party (TTP) to effectively control the certification of two users using the nature of the GHZ-like state. We will also analyze the security of the protocol and quantum channel. (paper)

Name conditioning in event-related brain potentials.

Science.gov (United States)

Kotchoubey, Boris; Pavlov, Yuri G

2017-11-01

Four experiments are reported in which two harmonic tones (CS+ and CS-) were paired with a participant's own name (SON) and different names (DN), respectively. A third tone was not paired with any other stimulus and served as a standard (frequent stimulus) in a three-stimuli oddball paradigm. The larger posterior positivity (P3) to SON than DN, found in previous studies, was replicated in all experiments. Conditioning of the P3 response was albeit observed in two similar experiments (1 and 3), but the obtained effects were weak and not identical in the two experiments. Only Experiment 4, where the number of CS/UCS pairings and the Stimulus-Onset Asynchrony between CS and UCS were increased, showed clear CS+/CS- differences both in time and time-frequency domains. Surprisingly, differential responses to CS+ and CS- were also obtained in Experiment 2, although SON and DN in that experiment were masked and never consciously recognized as meaningful words (recognition rate 0/63 participants). The results are discussed in the context of other ERP conditioning experiments and, particularly, the studies of non-conscious effect on ERP. Several further experiments are suggested to replicate and extend the present findings and to remove the remaining methodological limitations. Copyright © 2017 Elsevier Inc. All rights reserved.

UTILIZATION OF QUALITY MANAGERIAL SYSTEMS IN BUSINESS ENTITIES IN THE SLOVAK REPUBLIC

Directory of Open Access Journals (Sweden)

Zuzana Kapsdorferová

2015-06-01

Full Text Available Current global trends force businesses to enhance their competitiveness via quality, innovations, leaning of production processes and shortening of production cycles, development of employees and satisfying of customer's needs. At the same time, the society demands from entities more emphasis on sustainable development, environmental protection, social responsibility and on other social aspects of the business. Many firms seek the ways how to master such important demands and gain the recognition on the market. One of the avenues how to achieve planned results resides in implementation of the Total Quality Management systems, which also provide grounds for reaching a status of reliable business partner. Presented research paper puts an emphasis on execution of research in order to find out about the situation with the status of implementation of the quality managerial systems in Slovak businesses as well as to recognize reasons and contributions of usage of these systems in their activities.

Structured prediction models for RNN based sequence labeling in clinical text.

Science.gov (United States)

Jagannatha, Abhyuday N; Yu, Hong

2016-11-01

Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application of sequence labeling involves extraction of medical entities such as medication, indication, and side-effects from Electronic Health Record narratives. Sequence labeling in this domain, presents its own set of challenges and objectives. In this work we experimented with various CRF based structured learning models with Recurrent Neural Networks. We extend the previously studied LSTM-CRF models with explicit modeling of pairwise potentials. We also propose an approximate version of skip-chain CRF inference with RNN potentials. We use these methodologies for structured prediction in order to improve the exact phrase detection of various medical entities.

7 CFR 652.23 - Certification process for private-sector entities.

Science.gov (United States)

2010-01-01

... 7 Agriculture 6 2010-01-01 2010-01-01 false Certification process for private-sector entities. 652... ASSISTANCE Certification § 652.23 Certification process for private-sector entities. (a) A private sector... individual basis as part of the private-sector entity's certification and ensures that the requirements set...

Engineering responsive polymer building blocks with host-guest molecular recognition for functional applications.

Science.gov (United States)

Hu, Jinming; Liu, Shiyong

2014-07-15

CONSPECTUS: All living organisms and soft matter are intrinsically responsive and adaptive to external stimuli. Inspired by this fact, tremendous effort aiming to emulate subtle responsive features exhibited by nature has spurred the invention of a diverse range of responsive polymeric materials. Conventional stimuli-responsive polymers are constructed via covalent bonds and can undergo reversible or irreversible changes in chemical structures, physicochemical properties, or both in response to a variety of external stimuli. They have been imparted with a variety of emerging applications including drug and gene delivery, optical sensing and imaging, diagnostics and therapies, smart coatings and textiles, and tissue engineering. On the other hand, in comparison with molecular chemistry held by covalent bonds, supramolecular chemistry built on weak and reversible noncovalent interactions has emerged as a powerful and versatile strategy for materials fabrication due to its facile accessibility, extraordinary reversibility and adaptivity, and potent applications in diverse fields. Typically involving more than one type of noncovalent interactions (e.g., hydrogen bonding, metal coordination, hydrophobic association, electrostatic interactions, van der Waals forces, and π-π stacking), host-guest recognition refers to the formation of supramolecular inclusion complexes between two or more entities connected together in a highly controlled and cooperative manner. The inherently reversible and adaptive nature of host-guest molecular recognition chemistry, stemming from multiple noncovalent interactions, has opened up a new platform to construct novel types of stimuli-responsive materials. The introduction of host-guest chemistry not only enriches the realm of responsive materials but also confers them with promising new applications. Most intriguingly, the integration of responsive polymer building blocks with host-guest recognition motifs will endow the former with

Face recognition based on two-dimensional discriminant sparse preserving projection

Science.gov (United States)

Zhang, Dawei; Zhu, Shanan

2018-04-01

In this paper, a supervised dimensionality reduction algorithm named two-dimensional discriminant sparse preserving projection (2DDSPP) is proposed for face recognition. In order to accurately model manifold structure of data, 2DDSPP constructs within-class affinity graph and between-class affinity graph by the constrained least squares (LS) and l1 norm minimization problem, respectively. Based on directly operating on image matrix, 2DDSPP integrates graph embedding (GE) with Fisher criterion. The obtained projection subspace preserves within-class neighborhood geometry structure of samples, while keeping away samples from different classes. The experimental results on the PIE and AR face databases show that 2DDSPP can achieve better recognition performance.

Event-Entity-Relationship Modeling in Data Warehouse Environments

DEFF Research Database (Denmark)

Bækgaard, Lars

We use the event-entity-relationship model (EVER) to illustrate the use of entity-based modeling languages for conceptual schema design in data warehouse environments. EVER is a general-purpose information modeling language that supports the specification of both general schema structures and multi...

Echinococcus canadensis, E. borealis, and E. intermedius. What's in a name?

Science.gov (United States)

Lymbery, Alan J; Jenkins, Emily J; Schurer, Janna M; Thompson, R C Andrew

2015-01-01

The phylogenetic relationships of the G6, G7, G8, and G10 genotypes of Echinococcus granulosus are well defined, but their taxonomic status is currently unresolved. We apply an evolutionary species concept to infer that the G6 and G7 genotypes represent a single species that is different to both the G8 and G10 genotypes, and that the G8 and G10 genotypes are also on different evolutionary trajectories and, therefore, should be regarded as separate species. The names Echinococcus intermedius, Echinococcus canadensis, and Echinococcus borealis have been previously proposed for these three taxa (G6/7, G10 and G8, respectively) and we argue that it may be appropriate to resurrect these names. The correct delimitation and formal recognition of species of Echinococcus may have important veterinary and public health consequences. Copyright © 2014 Elsevier Ltd. All rights reserved.

HuAc: Human Activity Recognition Using Crowdsourced WiFi Signals and Skeleton Data

Directory of Open Access Journals (Sweden)

Linlin Guo

2018-01-01

Full Text Available The joint of WiFi-based and vision-based human activity recognition has attracted increasing attention in the human-computer interaction, smart home, and security monitoring fields. We propose HuAc, the combination of WiFi-based and Kinect-based activity recognition system, to sense human activity in an indoor environment with occlusion, weak light, and different perspectives. We first construct a WiFi-based activity recognition dataset named WiAR to provide a benchmark for WiFi-based activity recognition. Then, we design a mechanism of subcarrier selection according to the sensitivity of subcarriers to human activities. Moreover, we optimize the spatial relationship of adjacent skeleton joints and draw out a corresponding relationship between CSI and skeleton-based activity recognition. Finally, we explore the fusion information of CSI and crowdsourced skeleton joints to achieve the robustness of human activity recognition. We implemented HuAc using commercial WiFi devices and evaluated it in three kinds of scenarios. Our results show that HuAc achieves an average accuracy of greater than 93% using WiAR dataset.

North-American norms for name disagreement: pictorial stimuli naming discrepancies.

Directory of Open Access Journals (Sweden)

Mary O'Sullivan

Full Text Available Pictorial stimuli are commonly used by scientists to explore central processes; including memory, attention, and language. Pictures that have been collected and put into sets for these purposes often contain visual ambiguities that lead to name disagreement amongst subjects. In the present work, we propose new norms which reflect these sources of name disagreement, and we apply this method to two sets of pictures: the Snodgrass and Vanderwart (S&V set and the Bank of Standardized Stimuli (BOSS. Naming responses of the presented pictures were classified within response categories based on whether they were correct, incorrect, or equivocal. To characterize the naming strategy where an alternative name was being used, responses were further divided into different sub-categories that reflected various sources of name disagreement. Naming strategies were also compared across the two sets of stimuli. Results showed that the pictures of the S&V set and the BOSS were more likely to elicit alternative specific and equivocal names, respectively. It was also found that the use of incorrect names was not significantly different across stimulus sets but that errors were more likely caused by visual ambiguity in the S&V set and by a misuse of names in the BOSS. Norms for name disagreement presented in this paper are useful for subsequent research for their categorization and elucidation of name disagreement that occurs when choosing visual stimuli from one or both stimulus sets. The sources of disagreement should be examined carefully as they help to provide an explanation of errors and inconsistencies of many concepts during picture naming tasks.

How Well can We Learn Interpretable Entity Types from Text?

DEFF Research Database (Denmark)

Hovy, Dirk

2014-01-01

We investigate a largely unsupervised approach to learning interpretable, domain-specific entity types from unlabeled text. It assumes that any common noun in a domain can function as potential entity type, and uses those nouns as hidden variables in a HMM. To constrain training, it extracts co......-occurrence dictionaries of entities and common nouns from the data. We evaluate the learned types by measuring their prediction accuracy for verb arguments in several domains. The results suggest that it is possible to learn domain-specific entity types from unlabeled data. We show significant improvements over...

Pengaruh Struktur Organisasi dan Ukuran Perusahaan Terhadap Penerapan Business Entity Concept

Directory of Open Access Journals (Sweden)

Widya Exsa Marita

2015-10-01

Full Text Available Masalah pengelolaan dana merupakan momok yang sering mengakibatkan kegagalan usaha pada suatu perusahaan terutama UMKM. Pengelolaan dana yang efektif dan efisien dapat tercapai jika suatu perusahaan mampu menerapkan akuntansi yang baik. Penerapan akuntansi yang baik haruslah diawali dengan penerapan konsep akuntansi, salah satunya yaitu business entity concept. Penelitian ini bertujuan untuk mengetahui adanya pengaruh struktur organisasi dan ukuran perusahaan terhadap penerapan business entity concept. Objek penelitian yang diambil adalah UD. Agung Mulia Jaya dengan sampel sebanyak 200 reponden yang diambil dengan menggunakan teknik simple random sampling. Variabel bebas dalam penelitian ini adalah struktur organisasi dan ukuran perusahaan, sedangkan variabel terikatnya adalah penerapan business entity concept. Untuk menguji adanya pengaruh struktur organisasi dan ukuran perusahaan terhadap penerapan business entity concept, maka dilakukan analisis regresi linier berganda. Hasil pengujian secara simultan menunjukkan bahwa kedua variabel bebas yaitu struktur organisasi dan ukuran perusahaan berpengaruh terhadap penerapan business entity concept. Secara parsial, struktur organisasi berpengaruh positif terhadap penerapan business entity concept, namun sebaliknya ukuran perusahaan berpengaruh negatif terhadap penerapan business entity concept. Koefisien determinasi menghasilkan nilai 67,4% yang berarti penerapan business entity concept dapat dijelaskan oleh variabel struktur organisasi dan ukuran perusahaan sebesar 67,4% atau bersifat kuat.

Supramolecular chemistry-general principles and selected examples from anion recognition and metallosupramolecular chemistry.

Science.gov (United States)

Albrecht, Markus

2007-12-01

This review gives an introduction into supramolecular chemistry describing in the first part general principles, focusing on terms like noncovalent interaction, molecular recognition, self-assembly, and supramolecular function. In the second part those will be illustrated by simple examples from our laboratories. Supramolecular chemistry is the science that bridges the gap between the world of molecules and nanotechnology. In supramolecular chemistry noncovalent interactions occur between molecular building blocks, which by molecular recognition and self-assembly form (functional) supramolecular entities. It is also termed the "chemistry of the noncovalent bond." Molecular recognition is based on geometrical complementarity based on the "key-and-lock" principle with nonshape-dependent effects, e.g., solvatization, being also highly influential. Self-assembly leads to the formation of well-defined aggregates. Hereby the overall structure of the target ensemble is controlled by the symmetry features of the certain building blocks. Finally, the aggregates can possess special properties or supramolecular functions, which are only found in the ensemble but not in the participating molecules. This review gives an introduction on supramolecular chemistry and illustrates the fundamental principles by recent examples from our group.

78 FR 45051 - Unincorporated Business Entities; Effective Date

Science.gov (United States)

2013-07-26

... under State law for certain business activities. In accordance with the law, the effective date of the...) institutions' use of unincorporated business entities (UBEs) organized under State law for certain business... business entities, such as unincorporated business trusts, organized under State law. The final rule does...

15 CFR 744.10 - Restrictions on certain entities in Russia.

Science.gov (United States)

2010-01-01

... Russia. 744.10 Section 744.10 Commerce and Foreign Trade Regulations Relating to Commerce and Foreign... REGULATIONS CONTROL POLICY: END-USER AND END-USE BASED § 744.10 Restrictions on certain entities in Russia. (a) General prohibition. Certain entities in Russia are included in Supplement No. 4 to this part 744 (Entity...

List of names of persons well informed on new energies; Shin energy yushikisha meibo

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-03-01

In order to establish an environment in which local public organizations and local business entities intending introduction of new energies can obtain easily the information about the technologies thereof and introduction examples, a 'list of names of persons well informed on new energies' was prepared. At the same time, a system was set up, with which these well-informed people can be introduced on NEDO home pages. The list of the names has collected data of the well-informed people granted with patents related to the fields defined in the new energy law as their specialty fields. The criterion for extracting the persons calls for persons who have experience of writing theses on new energies, and who have give lectures on the subject. Other new energy related experts acting in local areas, who were not able of having been extracted by using the above method, were extracted through hearings by key persons in each area. Questionnaire surveys were performed on the extracted specialists, whereas 495 effective answers permitting disclosure were obtained, and detailed items of information were collected on these specialists individually. The specialty fields include 23 new energy fields. The names of persons were arranged in the order of bureaus listed in the Ministry of International Trade and Industry. The names in the bureaus were arranged in the Japanese alphabetical order. (NEDO)

False feedback and beliefs influence name recall in younger and older adults.

Science.gov (United States)

Strickland-Hughes, Carla M; West, Robin Lea; Smith, Kimberly A; Ebner, Natalie C

2017-09-01

Feedback is an important self-regulatory process that affects task effort and subsequent performance. Benefits of positive feedback for list recall have been explored in research on goals and feedback, but the effect of negative feedback on memory has rarely been studied. The current research extends knowledge of memory and feedback effects by investigating face-name association memory and by examining the potential mediation of feedback effects, in younger and older adults, through self-evaluative beliefs. Beliefs were assessed before and after name recognition and name recall testing. Repeated presentation of false positive feedback was compared to false negative feedback and a no feedback condition. Results showed that memory self-efficacy declined over time for participants in the negative and no feedback conditions but was sustained for those receiving positive feedback. Furthermore, participants who received negative feedback felt older after testing than before testing. For name recall, the positive feedback group outperformed the negative feedback and no feedback groups combined, with no age interactions. The observed feedback-related effects on memory were fully mediated by changes in memory self-efficacy. These findings advance our understanding of how beliefs are related to feedback in memory and inform future studies examining the importance of self-regulation in memory.

26 CFR 1.892-5 - Controlled commercial entity.

Science.gov (United States)

2010-04-01

... 26 Internal Revenue 9 2010-04-01 2010-04-01 false Controlled commercial entity. 1.892-5 Section 1.892-5 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES Miscellaneous Provisions § 1.892-5 Controlled commercial entity. (a)-(a)(2...

Man-system interface based on automatic speech recognition: integration to a virtual control desk

Energy Technology Data Exchange (ETDEWEB)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C., E-mail: calexandre@ien.gov.b, E-mail: mol@ien.gov.b, E-mail: cmnap@ien.gov.b, E-mail: mag@ien.gov.b [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil); Nomiya, Diogo V., E-mail: diogonomiya@gmail.co [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

2009-07-01

This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

Man-system interface based on automatic speech recognition: integration to a virtual control desk

International Nuclear Information System (INIS)

Jorge, Carlos Alexandre F.; Mol, Antonio Carlos A.; Pereira, Claudio M.N.A.; Aghina, Mauricio Alves C.; Nomiya, Diogo V.

2009-01-01

This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented. (author)

Bayesian Modeling of Temporal Coherence in Videos for Entity Discovery and Summarization.

Science.gov (United States)

Mitra, Adway; Biswas, Soma; Bhattacharyya, Chiranjib

2017-03-01

A video is understood by users in terms of entities present in it. Entity Discovery is the task of building appearance model for each entity (e.g., a person), and finding all its occurrences in the video. We represent a video as a sequence of tracklets, each spanning 10-20 frames, and associated with one entity. We pose Entity Discovery as tracklet clustering, and approach it by leveraging Temporal Coherence (TC): the property that temporally neighboring tracklets are likely to be associated with the same entity. Our major contributions are the first Bayesian nonparametric models for TC at tracklet-level. We extend Chinese Restaurant Process (CRP) to TC-CRP, and further to Temporally Coherent Chinese Restaurant Franchise (TC-CRF) to jointly model entities and temporal segments using mixture components and sparse distributions. For discovering persons in TV serial videos without meta-data like scripts, these methods show considerable improvement over state-of-the-art approaches to tracklet clustering in terms of clustering accuracy, cluster purity and entity coverage. The proposed methods can perform online tracklet clustering on streaming videos unlike existing approaches, and can automatically reject false tracklets. Finally we discuss entity-driven video summarization- where temporal segments of the video are selected based on the discovered entities, to create a semantically meaningful summary.

Nature and Extent of Person Recognition Impairments Associated with Capgras Syndrome in Lewy Body Dementia

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Chris M. Fiacconi

2014-09-01

Full Text Available Patients with Capgras Syndrome (CS adopt the delusional belief that persons well-known to them have been replaced by an imposter. Several current theoretical models of CS attribute such misidentification problems to deficits in covert recognition processes related to the generation of appropriate affective autonomic signals. These models assume intact overt recognition processes for the imposter and, more broadly, for other individuals. As such, it has been suggested that CS could reflect the ‘mirror image’ of prosopagnosia. The purpose of the current study was to determine whether overt person recognition abilities are indeed always spared in CS. Furthermore, we examined whether CS might be associated with any impairments in overt affective judgments of facial expressions. We pursued these goals by studying a patient with Lewy Body Dementia (DLB who showed clear signs of CS, and by comparing him to another patient with DLB who did not experience CS, as well as to a group of healthy control participants. We assessed overt person recognition with three fame recognition tasks, using faces, voices, and names as cues. We also included measures of confidence and probed pertinent semantic knowledge. In addition, participants rated the intensity of fearful facial expressions. We found that CS was associated with overt person recognition deficits when probed with faces and voices, but not with names. Critically, these deficits were not present in the DLB patient without CS. In addition, CS was associated with impairments in overt judgments of affect intensity. Taken together, our findings cast doubt on the traditional view that CS is the mirror-image of prosopagnosia and that it spares overt recognition abilities. These findings can still be accommodated by models of CS that emphasize deficits in autonomic responding, to the extent that the potential role of interoceptive awareness in overt judgments is taken into account.

CONSIDERATION REGARDING CURRENT ASSETS IN THE CONSTRUCTION ENTITIES

Directory of Open Access Journals (Sweden)

Laura Adriana COJOCARU (ALIONESCU

2014-06-01

Full Text Available Accounting for current assets mainly aims to obtain useful information on the management of their best in order to make management decisions. Counting efficiency of these assets, their importance, provides improved performance of the entity. In this paper we want to study the degree of implementation of policies and accounting treatments on the current assets in the specific construction economic entities, the problems of implementation and thus better addressing their theoretical and procedural to improve the information provided by financial statements. Due to the importance of proper conduct of business owned entities, accounting current assets should result in optimal and efficient control of current assets.

Separating lexical-semantic access from other mnemonic processes in picture-name verification.

Directory of Open Access Journals (Sweden)

Jason Fitzgerald Smith

2013-10-01

Full Text Available We present a novel paradigm to identify shared and unique brain regions underlying non-semantic, non-phonological, abstract, audio-visual (AV memory versus naming using a longitudinal functional magnetic resonance imaging experiment. Participants were trained to associate novel AV stimulus pairs containing hidden linguistic content. Half of the stimulus pairs were distorted images of animals and sine-wave speech versions of the animal’s name. Images and sounds were distorted in such a way as to make their linguistic content easily recognizable only after being made aware of its existence. Memory for the pairings was tested by presenting an AV pair and asking participants to verify if the two stimuli formed a learned pairing. After memory testing, the hidden linguistic content was revealed and participants were tested again on their recollection of the pairings in this linguistically informed state. Once informed, the AV verification task could be performed by naming the picture. There was substantial overlap between the regions involved in recognition of nonlinguistic sensory memory and naming, suggesting a strong relation between them. Contrasts between sessions identified left angular gyrus and middle temporal gyrus as key additional players in the naming network. Left inferior frontal regions participated in both naming and nonlinguistic AV memory suggesting the region is responsible for AV memory independent of phonological content contrary to previous proposals. Functional connectivity between angular gyrus and left inferior frontal gyrus and left middle temporal gyrus increased when performing the AV task as naming. The results are consistent with the hypothesis that, at the spatial resolution of fMRI, the regions that facilitate nonlinguistic AV associations are a subset of those that facilitate naming though reorganized into distinct networks.

Prediction of Word Recognition in the First Half of Grade 1

Science.gov (United States)

Snel, M. J.; Aarnoutse, C. A. J.; Terwel, J.; van Leeuwe, J. F. J.; van der Veld, W. M.

2016-01-01

Early detection of reading problems is important to prevent an enduring lag in reading skills. We studied the relationship between speed of word recognition (after six months of grade 1 education) and four kindergarten pre-literacy skills: letter knowledge, phonological awareness and naming speed for both digits and letters. Our sample consisted…

Entity-Linking via Graph-Distance Minimization

Directory of Open Access Journals (Sweden)

Roi Blanco

2014-07-01

Full Text Available Entity-linking is a natural-language–processing task that consists in identifying the entities mentioned in a piece of text, linking each to an appropriate item in some knowledge base; when the knowledge base is Wikipedia, the problem comes to be known as wikification (in this case, items are wikipedia articles. One instance of entity-linking can be formalized as an optimization problem on the underlying concept graph, where the quantity to be optimized is the average distance between chosen items. Inspired by this application, we define a new graph problem which is a natural variant of the Maximum Capacity Representative Set. We prove that our problem is NP-hard for general graphs; nonetheless, under some restrictive assumptions, it turns out to be solvable in linear time. For the general case, we propose two heuristics: one tries to enforce the above assumptions and another one is based on the notion of hitting distance; we show experimentally how these approaches perform with respect to some baselines on a real-world dataset.

The Pathological Spectrum of Systemic Anaplastic Large Cell Lymphoma (ALCL

Directory of Open Access Journals (Sweden)

Ivonne A. Montes-Mojarro

2018-04-01

Full Text Available Anaplastic large cell lymphoma (ALCL represents a group of malignant T-cell lymphoproliferations that share morphological and immunophenotypical features, namely strong CD30 expression and variable loss of T-cell markers, but differ in clinical presentation and prognosis. The recognition of anaplastic lymphoma kinase (ALK fusion proteins as a result of chromosomal translocations or inversions was the starting point for the distinction of different subgroups of ALCL. According to their distinct clinical settings and molecular findings, the 2016 revised World Health Organization (WHO classification recognizes four different entities: systemic ALK-positive ALCL (ALK+ ALCL, systemic ALK-negative ALCL (ALK− ALCL, primary cutaneous ALCL (pC-ALCL, and breast implant-associated ALCL (BI-ALCL, the latter included as a provisional entity. ALK is rearranged in approximately 80% of systemic ALCL cases with one of its partner genes, most commonly NPM1, and is associated with favorable prognosis, whereas systemic ALK− ALCL shows heterogeneous clinical, phenotypical, and genetic features, underlining the different oncogenesis between these two entities. Recognition of the pathological spectrum of ALCL is crucial to understand its pathogenesis and its boundaries with other entities. In this review, we will focus on the morphological, immunophenotypical, and molecular features of systemic ALK+ and ALK− ALCL. In addition, BI-ALCL will be discussed.

Recognition and recall of product placements in films and broadcast programmes

Directory of Open Access Journals (Sweden)

D. L. R. van der Waldt

2008-06-01

Full Text Available The purpose of this article is to investigate product placements in films and broadcast programmes regarding recognition and recall of product names. The sample consisted of undergraduate male and female students aged 18 to 24 attending a tertiary level institution in Pretoria, South Africa. The findings showed that even though there was no perfectly positive relationship between the prominence and recognition of products placed in films, someone watching a film was more likely to recognise a product if it were to be shown audio-visually. It can therefore be concluded that if a product is placed more prominently in a film, the recognition thereof will be higher. This study can be a benchmark as it is one of the first studies conducted in South Africa regarding the perception of product placements in film.

Myalgic Encephalomyelitis, Chronic Fatigue Syndrome, and Systemic Exertion Intolerance Disease: Three Distinct Clinical Entities

Directory of Open Access Journals (Sweden)

Frank N.M. Twisk

2018-04-01

Full Text Available Many researchers consider chronic fatigue syndrome (CFS to be a synonym of Myalgic Encephalomyelitis (ME. However, the case criteria of ME and CFS define two distinct clinical entities. Although some patients will meet both case criteria, other patients can meet the diagnosis of ME and not fulfil the case criteria for CFS, while the diagnosis of CFS is largely insufficient to be qualified as a ME patient. ME is a neuromuscular disease with distinctive muscular symptoms, including prolonged muscle weakness after exertion, and neurological signs implicating cerebral dysfunction, including cognitive impairment and sensory symptoms. The only mandatory symptom of CFS is chronic fatigue. Chronic fatigue must be accompanied by at least four out of eight nonspecific symptoms: substantial impairment in short-term memory or concentration, a sore throat, tender lymph nodes, muscle pain, multijoint pain, a new type of headaches, unrefreshing sleep, and postexertional “malaise” lasting more than 24 h. So, regardless whether the name ME is appropriate or not, ME is not synonymous to CFS. That is not a matter of opinion, but a matter of definition. Due to the definitions of ME and CFS, “ME/CFS” does not exist and cannot be replaced by a new clinical entity (SEID: Systemic Exertion Intolerance Disease, as recently suggested.

8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

Unrealistic optimism and 'nosognosia': illness recognition in the healthy brain.

Science.gov (United States)

McKay, Ryan; Buchmann, Andreas; Germann, Nicole; Yu, Shancong; Brugger, Peter

2014-12-01

At the centenary of research on anosognosia, the time seems ripe to supplement work in anosognosic patients with empirical studies on nosognosia in healthy participants. To this end, we adopted a signal detection framework to investigate the lateralized recognition of illness words--an operational measure of nosognosia--in healthy participants. As positively biased reports about one's current health status (anosognosia) and future health status (unrealistic optimism) have both been associated with deficient right hemispheric functioning, and conversely with undisturbed left hemispheric functioning, we hypothesised that more optimistic participants would adopt a more conservative response criterion, and/or display less sensitivity, when identifying illnesses in our nosognosia task; especially harmful illnesses presented to the left hemisphere via the right visual field. Thirty-two healthy right-handed men estimated their own relative risk of contracting a series of illnesses in the future, and then completed a novel computer task assessing their recognition of illness names presented to the left or right visual field. To check that effects were specific to the recognition of illness (rather than reflecting recognition of lexical items per se), we also administered a standard lateralized lexical decision task. Highly optimistic participants tended to be more conservative in detecting illnesses, especially harmful illnesses presented to the right visual field. Contrary to expectation, they were also more sensitive to illness names in this half-field. We suggest that, in evolutionary terms, unrealistic optimism may be an adaptive trait that combines a high perceptual sensitivity to threat with a high threshold for acknowledging its presence. The signal detection approach to nosognosia developed here may open up new avenues for the understanding of anosognosia in neurological patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Threshold models of recognition and the recognition heuristic

Directory of Open Access Journals (Sweden)

Edgar Erdfelder

2011-02-01

Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.

Xanthogranulomatous Prostatitis, a Rare Prostatic Entity

Directory of Open Access Journals (Sweden)

Alejandro Noyola

2017-01-01

Full Text Available There are several benign prostatic pathologies that can clinically mimic a prostate adenocarcinoma. Xanthogranulomatous prostatitis is a benign inflammatory condition of the prostate and a rare entity. A 47-year old male, with 3 years of lower urinary tract symptoms, with a palpable hypogastric tumor, digital rectal examination: solid prostate, of approximately 60 g. Initial PSA was 0.90 ng/mL. He underwent surgical excision of the lower abdominal nodule and prostatectomy. Histopathology showed xanthogranulomatous prostatitis, without malignancy. Xanthogranulomatous prostatitis is an extremely rare entity that can simulate prostate adenocarcinoma, therefore having a correct histopathological diagnosis is essential.

Average Gait Differential Image Based Human Recognition

Directory of Open Access Journals (Sweden)

Jinyan Chen

2014-01-01

Full Text Available The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI, AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition.

PERLINDUNGAN HUKUM BLOGGER BERITIKAD BAIK TERHADAP DOMINE NAME MEREK TERKENAL DARI DUGAAN PEMBONCENGAN REPUTASI (PASSING OFF

Directory of Open Access Journals (Sweden)

DESY KUSUMA WARDHANI

2013-01-01

Full Text Available This Research entitled "Legal Protection Against Blogger Good Faith Domine Name Of Alleged Deception Famous Brand Reputation (Passing Off". The problem of this study was, first: How does the domain name in a legal setting in Indonesia. Second: What is the legal protection of domain name for blogger’s good faith if there are similarities with the domain name famous brand. This research method using normative methods, the legal research done by examining library materials. Which refers to the legal norms contained in the legislation, international conventions, international agreements and court decisions. The results showed, first: The domain name has been linked closely with the brand and copyright but the domain name is not synonymous with the brand and copyright, as it has a system and registration requirements as well as the recognition of the existence differently. So far there are kekososngan norms that specifically regulate the domain name issue in Indonesia. Until now, the settings used by the international ICANN (Internet Corporation for Assigned Names and Numbers, the competent authority dealing with internet IP Addres, and domain name system management. Second: Legal protection for bloggers acting in good faith if there are similarities regarding the domain name can be a famous brand is preventive legal protection and the protection of repressive laws which refers to the settlement of a litigation matter (referring to the legal protection of IPR, Civil, Criminal and Law ITE and non-litigation (both ADR and UDRP.

The three names

NARCIS (Netherlands)

Bas Jongenelen

2011-01-01

Two spectators are each asked to think of a girl's name (because your sister in law is pregnant and names are a big issue at the moment in your family.) You explain that you have a boy's name in your head, and you ask the spectators to think what this boy's name might be. You write three names on a

Facial Expression Recognition By Using Fisherface Methode With Backpropagation Neural Network

Directory of Open Access Journals (Sweden)

Zaenal Abidin

2011-01-01

Full Text Available Abstract— In daily lives, especially in interpersonal communication, face often used for expression. Facial expressions give information about the emotional state of the person. A facial expression is one of the behavioral characteristics. The components of a basic facial expression analysis system are face detection, face data extraction, and facial expression recognition. Fisherface method with backpropagation artificial neural network approach can be used for facial expression recognition. This method consists of two-stage process, namely PCA and LDA. PCA is used to reduce the dimension, while the LDA is used for features extraction of facial expressions. The system was tested with 2 databases namely JAFFE database and MUG database. The system correctly classified the expression with accuracy of 86.85%, and false positive 25 for image type I of JAFFE, for image type II of JAFFE 89.20% and false positive 15,  for type III of JAFFE 87.79%, and false positive for 16. The image of MUG are 98.09%, and false positive 5. Keywords— facial expression, fisherface method, PCA, LDA, backpropagation neural network.

Balancing exploration and exploitation in transferring research into practice: a comparison of five knowledge translation entity archetypes.

Science.gov (United States)

Oborn, Eivor; Barrett, Michael; Prince, Karl; Racko, Girts

2013-09-05

Translating knowledge from research into clinical practice has emerged as a practice of increasing importance. This has led to the creation of new organizational entities designed to bridge knowledge between research and practice. Within the UK, the Collaborations for Leadership in Applied Health Research and Care (CLAHRC) have been introduced to ensure that emphasis is placed in ensuring research is more effectively translated and implemented in clinical practice. Knowledge translation (KT) can be accomplished in various ways and is affected by the structures, activities, and coordination practices of organizations. We draw on concepts in the innovation literature--namely exploration, exploitation, and ambidexterity--to examine these structures and activities as well as the ensuing tensions between research and implementation. Using a qualitative research approach, the study was based on 106 semi-structured, in-depth interviews with the directors, theme leads and managers, key professionals involved in research and implementation in nine CLAHRCs. Data was also collected from intensive focus group workshops. In this article we develop five archetypes for organizing KT. The results show how the various CLAHRC entities work through partnerships to create explorative research and deliver exploitative implementation. The different archetypes highlight a range of structures that can achieve ambidextrous balance as they organize activity and coordinate practice on a continuum of exploration and exploitation. This work suggests that KT entities aim to reach their goals through a balance between exploration and exploitation in the support of generating new research and ensuring knowledge implementation. We highlight different organizational archetypes that support various ways to maintain ambidexterity, where both exploration and exploitation are supported in an attempt to narrow the knowledge gaps. The KT entity archetypes offer insights on strategies in structuring

Let your name be known. OB-GYN practice's marketing strategies keep it prominent in community.

Science.gov (United States)

Schneck, Lisa H

2003-08-01

Take a large dose of innovation, add a dollop of shrewd business sense and a heaping measure of community awareness, mix well, and you get the marketing success enjoyed by San Dimas Medical Group Inc. of Bakersfield, Calif. The practice has established wide name recognition, become a community benefactor and positioned itself as the practice that local women want to visit for a wide range of health concerns.

Differences in financial statements of business entities in the Czech Republic

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Jana Gláserová

2013-01-01

Full Text Available Ministry of Finance in the Czech Republic identifies and defines four types of accounting entities that are engaged in business activities. These are the “normal” business entities, business entities as banks, commercial insurance companies and health insurance companies. For each of these types of entities the Ministry of Finance issued relevant regulations that contain specific accounting policies arising mainly from the specifics of the scope of business activities of these entities. The effects of these specifics are ultimately shown also in the individual parts of the financial statement closing. In contrast the International Financial Reporting Standards (IFRS and also generally accepted accounting principles of the United States (U.S. GAAP are valid for all listed entities regardless of their size and scope of activities. The ongoing globalization of the world, transnational mergers and acquisitions of various companies brings the requirements for unification of accounting policies in order to achieve comparability of financial statements closing of companies from different countries, their transparency and completeness of published information in the individual countries. This paper deals with the definition of significant differences in the items of financial statement closing of different types of business entities in the Czech Republic and with the formulation of proposals for individual types of entities, which would contribute to easier orientation and grater comparability for the needs of different users of accounting information.

Intelligent Entity Behavior Within Synthetic Environments. Chapter 3

Science.gov (United States)

Kruk, R. V.; Howells, P. B.; Siksik, D. N.

2007-01-01

This paper describes some elements in the development of realistic performance and behavior in the synthetic entities (players) which support Modeling and Simulation (M&S) applications, particularly military training. Modern human-in-the-loop (virtual) training systems incorporate sophisticated synthetic environments, which provide: 1. The operational environment, including, for example, terrain databases; 2. Physical entity parameters which define performance in engineered systems, such as aircraft aerodynamics; 3. Platform/system characteristics such as acoustic, IR and radar signatures; 4. Behavioral entity parameters which define interactive performance, including knowledge/reasoning about terrain, tactics; and, 5. Doctrine, which combines knowledge and tactics into behavior rule sets. The resolution and fidelity of these model/database elements can vary substantially, but as synthetic environments are designed to be compose able, attributes may easily be added (e.g., adding a new radar to an aircraft) or enhanced (e.g. Amending or replacing missile seeker head/ Electronic Counter Measures (ECM) models to improve the realism of their interaction). To a human in the loop with synthetic entities, their observed veridicality is assessed via engagement responses (e.g. effect of countermeasures upon a closing missile), as seen on systems displays, and visual (image) behavior. The realism of visual models in a simulation (level of detail as well as motion fidelity) remains a challenge in realistic articulation of elements such as vehicle antennae and turrets, or, with human figures; posture, joint articulation, response to uneven ground. Currently the adequacy of visual representation is more dependant upon the quality and resolution of the physical models driving those entities than graphics processing power per Se. Synthetic entities in M&S applications traditionally have represented engineered systems (e.g. aircraft) with human-in-the-loop performance

Towards a Theory of Learning for Naming Rehabilitation: Retrieval Practice, Retrieval Effort, and Spacing Effects

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Erica Middleton

2015-04-01

Methods. Four PWA with naming impairment named and gave familiarity ratings to a corpus of 700 pictures of proper noun entities twice over two weeks. For each participant, we selected items the participant knew recognized but could not consistently name for assignment into the conditions, with a minimum of 36 (max=72 items per condition across participants. The design involved a 2-level factor of type of training (retrieval practice versus errorless learning, i.e., repetition and a factor of spacing, which included a massed condition (lag 1 and three spaced conditions (lags 5, 15, and 30. Lag corresponded to the number of training trials for other items that intervened between three presentations of an item for retrieval practice or repetition training. On a repetition trial, the name was presented (seen/heard and the participant repeated the name at picture onset. On a naming trial, only the picture was presented. All trials ended in feedback (i.e., the name was presented. Primary outcome was naming performance on a retention test administered 1-day following training, with a 1-week follow-up test administered to measure persistence of the effects. Results & Conclusions. Mixed regression analyses revealed that the naming condition was associated with superior performance over repetition, observed both at the retention test (p=.001 and follow-up (p=.01; Figure 1, left panel. Also, spaced training conferred superior benefits compared to massed, both at retention test (p<.001 and follow-up (p=.006; Figure 1, right panel. An analysis of the spaced lags in the naming condition revealed that though increasing lag made retrieval practice more effortful (i.e., error-prone during training, increasing lag conferred more powerful learning at retention test. The present study provides definitive evidence of the relevance of retrieval practice, retrieval effort, and spacing for optimizing existing treatments, their explanatory power, and their importance in driving future

49 CFR 37.41 - Construction of transportation facilities by public entities.

Science.gov (United States)

2010-10-01

... public entities. 37.41 Section 37.41 Transportation Office of the Secretary of Transportation... transportation facilities by public entities. (a) A public entity shall construct any new facility to be used in providing designated public transportation services so that the facility is readily accessible to and usable...

Compulsive buying: an overlooked entity.

Science.gov (United States)

Basu, Bishnupriya; Basu, Saikat; Basu, Jharna

2011-08-01

Compulsive buying is an under-recognised entity among Indian psychiatrists. A Medline search, hand searching of journals and direct communications with lead investigators in compulsive buying have generated numerous studies. Overseas data indicate a community prevalence between 1% and 8% . The phenomenon can be an independent entity or appears as a comorbidity with another axis I or axis II disorder. A degree of suspicion on part of clinician regarding its possible presence is the key to its detection. A few rating instruments are available to quantify the morbidity and screening for compulsive buying. Management involves pharmacotherapy with SSRIs, psychotherapy, self-help groups and self-help books. Epidemiological and clinical studies on compulsive buying should be undertaken by Indian psychiatrists to provide better services for people suffering from compulsive buying.

Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

Energy Technology Data Exchange (ETDEWEB)

Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P [College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha (China)

2006-10-15

Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method.

Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

International Nuclear Information System (INIS)

Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P

2006-01-01

Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method

FINANCIAL REPORTING IN PUBLIC INSTITUTIONS AND NON-FINANCIAL ENTITIES. SIMILARITIES AND DIFFERENCES

OpenAIRE

Daniela Vitan

2011-01-01

The present paperwork contains issues regarding financial reporting at the public institutions and non – financial entities. The main aspects are regarding the obligation of all entities to present the financial statements, the content of financial statements in public institutions and non-financial entities. Also, is presented the similarities and the differences aspects between financial reporting of these two patrimonial entities.

Special aspects of the reporting of capital in the budgetary entities

Directory of Open Access Journals (Sweden)

Nadezhda Popova-Yosifova

2018-05-01

Full Text Available The national and international accounting standards state that the equity of an entity is the residual interest in the assets of the entity that remains after deducting all of its liabilities. For that reason in the accounting theory could also be found the terms “net worth” and “net assets” which are used as synonyms. The term “equity” is not used adequately in this wording in respect of the budgetary entities because of some specific characteristics these entities possess. The purpose of this paper is, based on the legislative framework now in force in Bulgaria and the characteristic features of the public sector entities, to present the specific features of the capital reporting in these organizations.

Phoneme Awareness, Visual-Verbal Paired-Associate Learning, and Rapid Automatized Naming as Predictors of Individual Differences in Reading Ability

Science.gov (United States)

Warmington, Meesha; Hulme, Charles

2012-01-01

This study examines the concurrent relationships between phoneme awareness, visual-verbal paired-associate learning, rapid automatized naming (RAN), and reading skills in 7- to 11-year-old children. Path analyses showed that visual-verbal paired-associate learning and RAN, but not phoneme awareness, were unique predictors of word recognition,…

Selective attention and recognition: effects of congruency on episodic learning.

Science.gov (United States)

Rosner, Tamara M; D'Angelo, Maria C; MacLellan, Ellen; Milliken, Bruce

2015-05-01

Recent research on cognitive control has focused on the learning consequences of high selective attention demands in selective attention tasks (e.g., Botvinick, Cognit Affect Behav Neurosci 7(4):356-366, 2007; Verguts and Notebaert, Psychol Rev 115(2):518-525, 2008). The current study extends these ideas by examining the influence of selective attention demands on remembering. In Experiment 1, participants read aloud the red word in a pair of red and green spatially interleaved words. Half of the items were congruent (the interleaved words had the same identity), and the other half were incongruent (the interleaved words had different identities). Following the naming phase, participants completed a surprise recognition memory test. In this test phase, recognition memory was better for incongruent than for congruent items. In Experiment 2, context was only partially reinstated at test, and again recognition memory was better for incongruent than for congruent items. In Experiment 3, all of the items contained two different words, but in one condition the words were presented close together and interleaved, while in the other condition the two words were spatially separated. Recognition memory was better for the interleaved than for the separated items. This result rules out an interpretation of the congruency effects on recognition in Experiments 1 and 2 that hinges on stronger relational encoding for items that have two different words. Together, the results support the view that selective attention demands for incongruent items lead to encoding that improves recognition.

Automaticity of Basic-Level Categorization Accounts for Labeling Effects in Visual Recognition Memory

Science.gov (United States)

Richler, Jennifer J.; Gauthier, Isabel; Palmeri, Thomas J.

2011-01-01

Are there consequences of calling objects by their names? Lupyan (2008) suggested that overtly labeling objects impairs subsequent recognition memory because labeling shifts stored memory representations of objects toward the category prototype (representational shift hypothesis). In Experiment 1, we show that processing objects at the basic…

78 FR 21603 - Proposed Reporting Entity; Request for Comments

Science.gov (United States)

2013-04-11

... FEDERAL ACCOUNTING STANDARDS ADVISORY BOARD Proposed Reporting Entity; Request for Comments AGENCY... seeking input on a proposed Statement of Federal Financial Accounting Standards addressing the Reporting Entity. The Standard is available at http://www.fasab.gov/board-activities/documents-for-comment/exposure...

Cuban entities management. Cedrux just around the corner.

Directory of Open Access Journals (Sweden)

Tamara Rodríguez Sánchez

2011-12-01

Full Text Available The direction of the country as part of strengthening entities management and the informatization of Cuban society, presented the need to create a System of Enterprise Resource Planning (ERP, which would be able to computerize management processes of business and budgeted entities on national scale. It is in this way that since July 2008 CEDRUX product was developed composed by 15 subsystems. It will constitute the core on which new solutions will be developed that will extend its functionalities in a constantly way, including new entities management processes and allowing constant updating. In its first operational phase that will be in this very year 2011, Cedrux will only integrate 9 subsystems that will answer the economic needs of any organization.

THE EFFICIENCY OF FOREIGN INVESTMENTS IN THE FINANCING OF AUDITED ENTITIES

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Berinde Sorin

2013-07-01

Full Text Available The auditing of the financial statements is a certification service intended to offer the users more credibility regarding the quality of accounting information. This is the reason why the present study selected all the Cluj county entities that, according to the public information, between 2005-2012 were subject to financial audit in order to estimate, at this level, the influence of foreign investments in the financing structure. The information provided by the financial statements of these audited entities (with or without foreign participation in share capital was analyzed for the calculation of the relevant indicators to determine the evolution of the equity financing, the recourse to external financing funds, the ratio of external funds and equity funds used for financing and the assessment of the efficiency of foreign capital invested at the level of these entities. In order to meet this objective, we considered the information from the financial statements of the concerned entities, published between 2008-2011. For the relevance of the study, we eliminated the audited entities that did not have financial statements published in all of the four financial years for various reasons (dissolution, liquidation, merger, or temporary suspension of activity or had negative working capital. The financial statement information was analyzed in view of the calculation for each audited entity of the rate of financial autonomy, the debt ratio, the debt to equity ratio and of the rotation speed of equity. The audited entities were classified into 2 major categories: audited entities with a foreign participation in share capital and audited entities with the whole share capital financed by equity funds. We applied the simple average method at the level of the both audited entities categories for each of the four analyzed indicators. Furthermore, we performed an analysis from the static and dynamic point of view of the results. The conclusions that we

Public administration social responsibility of business entities

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N. H. Shpankovskaya

2016-03-01

Full Text Available Social responsibility of a business entity is seen as an effective tool of public administration. The current stage of development of social responsibility in Ukraine requires state involvement, as its vision by business entities are different, and there is also a need to develop a national model of social responsibility on the basis of international standards, because Ukraine, on the one hand, has the national characteristics of implementation of social initiatives and, on the other, the conditions and resources for their implementation is different from developed market economies. The visions of on social responsibility in the scientific literature are also different. This was the basis for the determination of her essence. We analyzed the interpretations of social responsibility and identified their advantages and disadvantages. Formulation of social responsibility, which is submitted in article, actualizes ecological orientation of the business entity taking into account the need for responsible behavior, and responsibility for actions, which violate the norms of society.

Learning Expressive Linkage Rules for Entity Matching using Genetic Programming

OpenAIRE

Isele, Robert

2013-01-01

A central problem in data integration and data cleansing is to identify pairs of entities in data sets that describe the same real-world object. Many existing methods for matching entities rely on explicit linkage rules, which specify how two entities are compared for equivalence. Unfortunately, writing accurate linkage rules by hand is a non-trivial problem that requires detailed knowledge of the involved data sets. Another important issue is the efficient execution of link...

FAST DISCRETE CURVELET TRANSFORM BASED ANISOTROPIC FEATURE EXTRACTION FOR IRIS RECOGNITION

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Amol D. Rahulkar

2010-11-01

Full Text Available The feature extraction plays a very important role in iris recognition. Recent researches on multiscale analysis provide good opportunity to extract more accurate information for iris recognition. In this work, a new directional iris texture features based on 2-D Fast Discrete Curvelet Transform (FDCT is proposed. The proposed approach divides the normalized iris image into six sub-images and the curvelet transform is applied independently on each sub-image. The anisotropic feature vector for each sub-image is derived using the directional energies of the curvelet coefficients. These six feature vectors are combined to create the resultant feature vector. During recognition, the nearest neighbor classifier based on Euclidean distance has been used for authentication. The effectiveness of the proposed approach has been tested on two different databases namely UBIRIS and MMU1. Experimental results show the superiority of the proposed approach.

Parents accidentally substitute similar sounding sibling names more often than dissimilar names.

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Zenzi M Griffin

Full Text Available When parents select similar sounding names for their children, do they set themselves up for more speech errors in the future? Questionnaire data from 334 respondents suggest that they do. Respondents whose names shared initial or final sounds with a sibling's reported that their parents accidentally called them by the sibling's name more often than those without such name overlap. Having a sibling of the same gender, similar appearance, or similar age was also associated with more frequent name substitutions. Almost all other name substitutions by parents involved other family members and over 5% of respondents reported a parent substituting the name of a pet, which suggests a strong role for social and situational cues in retrieving personal names for direct address. To the extent that retrieval cues are shared with other people or animals, other names become available and may substitute for the intended name, particularly when names sound similar.

Prediction of consonant recognition in quiet for listeners with normal and impaired hearing using an auditory model.

Science.gov (United States)

Jürgens, Tim; Ewert, Stephan D; Kollmeier, Birger; Brand, Thomas

2014-03-01

Consonant recognition was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in quiet as a function of speech level using a nonsense logatome test. Average recognition scores were analyzed and compared to recognition scores of a speech recognition model. In contrast to commonly used spectral speech recognition models operating on long-term spectra, a "microscopic" model operating in the time domain was used. Variations of the model (accounting for hearing impairment) and different model parameters (reflecting cochlear compression) were tested. Using these model variations this study examined whether speech recognition performance in quiet is affected by changes in cochlear compression, namely, a linearization, which is often observed in HI listeners. Consonant recognition scores for HI listeners were poorer than for NH listeners. The model accurately predicted the speech reception thresholds of the NH and most HI listeners. A partial linearization of the cochlear compression in the auditory model, while keeping audibility constant, produced higher recognition scores and improved the prediction accuracy. However, including listener-specific information about the exact form of the cochlear compression did not improve the prediction further.

49 CFR Appendix C to Part 209 - FRA's Policy Statement Concerning Small Entities

Science.gov (United States)

2010-10-01

... agency personnel respond in a timely and comprehensive fashion to the inquiries of small entities... history of compliance, FRA inspectors consider “such other factors as the immediate circumstances make... eliminating the safety hazard; the entity's culpability; the entity's compliance history; the entity's ability...

Search optimization of named entities from twitter streams

Science.gov (United States)

Fazeel, K. Mohammed; Hassan Mottur, Simama; Norman, Jasmine; Mangayarkarasi, R.

2017-11-01

With Enormous number of tweets, People often face difficulty to get exact information about those tweets. One of the approach followed for getting information about those tweets via Google. There is not any accuracy tool developed for search optimization and as well as getting information about those tweets. So, this system contains the search optimization and functionalities for getting information about those tweets. Another problem faced here are the tweets that contains grammatical errors, misspellings, non-standard abbreviations, and meaningless capitalization. So, these problems can be eliminated by the use of this tool. Lot of time can be saved and as well as by the use of efficient search optimization each information about those particular tweets can be obtained.

Emotion and language: Valence and arousal affect word recognition

Science.gov (United States)

Brysbaert, Marc; Warriner, Amy Beth

2014-01-01

Emotion influences most aspects of cognition and behavior, but emotional factors are conspicuously absent from current models of word recognition. The influence of emotion on word recognition has mostly been reported in prior studies on the automatic vigilance for negative stimuli, but the precise nature of this relationship is unclear. Various models of automatic vigilance have claimed that the effect of valence on response times is categorical, an inverted-U, or interactive with arousal. The present study used a sample of 12,658 words, and included many lexical and semantic control factors, to determine the precise nature of the effects of arousal and valence on word recognition. Converging empirical patterns observed in word-level and trial-level data from lexical decision and naming indicate that valence and arousal exert independent monotonic effects: Negative words are recognized more slowly than positive words, and arousing words are recognized more slowly than calming words. Valence explained about 2% of the variance in word recognition latencies, whereas the effect of arousal was smaller. Valence and arousal do not interact, but both interact with word frequency, such that valence and arousal exert larger effects among low-frequency words than among high-frequency words. These results necessitate a new model of affective word processing whereby the degree of negativity monotonically and independently predicts the speed of responding. This research also demonstrates that incorporating emotional factors, especially valence, improves the performance of models of word recognition. PMID:24490848

An effective XML based name mapping mechanism within StoRM

International Nuclear Information System (INIS)

Corso, E; Forti, A; Ghiselli, A; Magnoni, L; Zappi, R

2008-01-01

In a Grid environment the naming capability allows users to refer to specific data resources in a physical storage system using a high level logical identifier. This logical identifier is typically organized in a file system like structure, a hierarchical tree of names. Storage Resource Manager (SRM) services map the logical identifier to the physical location of data evaluating a set of parameters as the desired quality of services and the VOMS attributes specified in the requests. StoRM is a SRM service developed by INFN and ICTP-EGRID to manage file and space on standard POSIX and high performing parallel and cluster file systems. An upcoming requirement in the Grid data scenario is the orthogonality of the logical name and the physical location of data, in order to refer, with the same identifier, to different copies of data archived in various storage areas with different quality of service. The mapping mechanism proposed in StoRM is based on a XML document that represents the different storage components managed by the service, the storage areas defined by the site administrator, the quality of service they provide and the Virtual Organization that want to use the storage area. An appropriate directory tree is realized in each storage component reflecting the XML schema. In this scenario StoRM is able to identify the physical location of a requested data evaluating the logical identifier and the specified attributes following the XML schema, without querying any database service. This paper presents the namespace schema defined, the different entities represented and the technical details of the StoRM implementation

Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

DEFF Research Database (Denmark)

Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

2017-01-01

of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

IMPROVING PERFORMANCES BY USING COST CONTROLLING IN THE MINING INDUSTRY ENTITIES

Directory of Open Access Journals (Sweden)

SORINEL CĂPUŞNEANU

2016-06-01

Full Text Available The aim of this article is to highlight the improving performances of entities from mining industry entities by using cost controlling as an important tool of management accounting, applying the target costing method. The survey is based on questions that led investigation made in the Romanian entities from mining industry and based on data a thorough analysis was done for fulfillment of authors’ purpose. The results obtained by applying the target costing method has allowed a very strict cost control, which ultimately led to increased performances of economic entities from mining industry in Romania. The secondary purpose of this article is to try adjusting the target costing method to the specific of entities in the mining industry. According to studies of specialists this method based on target costing calculation is rather unusual in this sector of mining industry and it relies heavily on the activity-based costing method. The article ends with the authors' conclusions on improving the performances of entities from mining industry based on cost controlling and use of mix information obtained through the applied methods

A New Fuzzy Cognitive Map Learning Algorithm for Speech Emotion Recognition

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Wei Zhang

2017-01-01

Full Text Available Selecting an appropriate recognition method is crucial in speech emotion recognition applications. However, the current methods do not consider the relationship between emotions. Thus, in this study, a speech emotion recognition system based on the fuzzy cognitive map (FCM approach is constructed. Moreover, a new FCM learning algorithm for speech emotion recognition is proposed. This algorithm includes the use of the pleasure-arousal-dominance emotion scale to calculate the weights between emotions and certain mathematical derivations to determine the network structure. The proposed algorithm can handle a large number of concepts, whereas a typical FCM can handle only relatively simple networks (maps. Different acoustic features, including fundamental speech features and a new spectral feature, are extracted to evaluate the performance of the proposed method. Three experiments are conducted in this paper, namely, single feature experiment, feature combination experiment, and comparison between the proposed algorithm and typical networks. All experiments are performed on TYUT2.0 and EMO-DB databases. Results of the feature combination experiments show that the recognition rates of the combination features are 10%–20% better than those of single features. The proposed FCM learning algorithm generates 5%–20% performance improvement compared with traditional classification networks.

Incremental Nonnegative Matrix Factorization for Face Recognition

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Wen-Sheng Chen

2008-01-01

Full Text Available Nonnegative matrix factorization (NMF is a promising approach for local feature extraction in face recognition tasks. However, there are two major drawbacks in almost all existing NMF-based methods. One shortcoming is that the computational cost is expensive for large matrix decomposition. The other is that it must conduct repetitive learning, when the training samples or classes are updated. To overcome these two limitations, this paper proposes a novel incremental nonnegative matrix factorization (INMF for face representation and recognition. The proposed INMF approach is based on a novel constraint criterion and our previous block strategy. It thus has some good properties, such as low computational complexity, sparse coefficient matrix. Also, the coefficient column vectors between different classes are orthogonal. In particular, it can be applied to incremental learning. Two face databases, namely FERET and CMU PIE face databases, are selected for evaluation. Compared with PCA and some state-of-the-art NMF-based methods, our INMF approach gives the best performance.

Pattern recognition

CERN Document Server

Theodoridis, Sergios

2003-01-01

Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

Geographic Names

Data.gov (United States)

Minnesota Department of Natural Resources — The Geographic Names Information System (GNIS), developed by the United States Geological Survey in cooperation with the U.S. Board of Geographic Names, provides...

Spoof Detection for Finger-Vein Recognition System Using NIR Camera

Directory of Open Access Journals (Sweden)

Dat Tien Nguyen

2017-10-01

Full Text Available Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD, is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor based on the observations of the researchers about the difference between real (live and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR camera-based finger-vein recognition system using convolutional neural network (CNN to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA for dimensionality reduction of feature space and support vector machine (SVM for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared

Spoof Detection for Finger-Vein Recognition System Using NIR Camera.

Science.gov (United States)

Nguyen, Dat Tien; Yoon, Hyo Sik; Pham, Tuyen Danh; Park, Kang Ryoung

2017-10-01

Finger-vein recognition, a new and advanced biometrics recognition method, is attracting the attention of researchers because of its advantages such as high recognition performance and lesser likelihood of theft and inaccuracies occurring on account of skin condition defects. However, as reported by previous researchers, it is possible to attack a finger-vein recognition system by using presentation attack (fake) finger-vein images. As a result, spoof detection, named as presentation attack detection (PAD), is necessary in such recognition systems. Previous attempts to establish PAD methods primarily focused on designing feature extractors by hand (handcrafted feature extractor) based on the observations of the researchers about the difference between real (live) and presentation attack finger-vein images. Therefore, the detection performance was limited. Recently, the deep learning framework has been successfully applied in computer vision and delivered superior results compared to traditional handcrafted methods on various computer vision applications such as image-based face recognition, gender recognition and image classification. In this paper, we propose a PAD method for near-infrared (NIR) camera-based finger-vein recognition system using convolutional neural network (CNN) to enhance the detection ability of previous handcrafted methods. Using the CNN method, we can derive a more suitable feature extractor for PAD than the other handcrafted methods using a training procedure. We further process the extracted image features to enhance the presentation attack finger-vein image detection ability of the CNN method using principal component analysis method (PCA) for dimensionality reduction of feature space and support vector machine (SVM) for classification. Through extensive experimental results, we confirm that our proposed method is adequate for presentation attack finger-vein image detection and it can deliver superior detection results compared to CNN

Quality of the Accounting Information of Brazilian Third Sector Entities

Directory of Open Access Journals (Sweden)

Fernando Maciel Ramos

2015-08-01

Full Text Available In this study, the objective was to analyze the quality of accounting information of Brazilian non-profit organizations. As for the objective the research is characterized as a descriptive one; as for the research strategy it is documental and as for the approach it is quantitative. In order to measure the quality of the accounting information of the analyzed entities, it was prepared a checklist starting from the accounting rules that guide the accounting practice of the third sector entities made up of seven sections and 59 requisites, which enabled the construction of the Quality Index for Accounting Information. The data were analyzed through descriptive statistics (minimum, maximum, mean, standard deviation and the results indicated a low level of the accounting information quality reported by the analyzed entities, especially when compared to for-profit organizations. One comes to the conclusion, based on the findings, that the analyzed entities present a low level of quality as to the accounting information which may jeopardize the information usefulness reported by these entities users.

Diseño de un modelo específico para la predicción de la quiebra de micro-entities // Design of a Specific Model for Predicting Micro-Entities Failure

Directory of Open Access Journals (Sweden)

Antonio J. Blanco Oliver

2016-12-01

Full Text Available La importancia de las micro-entities como generadoras de empleo y propulsoras de la actividad económica conlleva, unida a sus mayores tasas de quiebra y a su dificultad para acceder a las fuentes de financiación, la necesidad de diseñar métodos apropiados que anticipen sus quiebras. Con este fin, en este trabajo se desarrolla un modelo híbrido mediante la combinación de enfoques paramétricos y no paramétricos para la detección de sus quiebras. Para ello, se seleccionan las variables con mayor poder predictivo para detectar la quiebra mediante un modelo híbrido de regresión logística (LR y árboles de regresión y clasificación (CART. Nuestros resultados muestran que este modelo híbrido obtiene una mejor performance que aquellos modelos implementados de forma aislada, además de tener una más fácil interpretación y una convergencia más rápida. Por otra parte, se constata la conveniencia de la introducción de variables no financieras y macroeconómicas que complementen a la información proporcionada por los ratios financieros para la predicción de la quiebra de las micro-entities, lo cual está en línea con las características propias e idiosincrasia de este tamaño empresarial recientemente definido por la Comisión Europea. ------------------------------------ The importance of micro-entities due to their generation of employment and propelling economic activity, together with the fact of their particularities, implies the need to design appropriate methods that anticipate their bankruptcies. For that purpose, a hybrid model by combining parametric and nonparametric approaches is developed in this paper. First, the variables with the highest predictive power to detect bankruptcy are selected using logistic regression (LR. Subsequently, a non-parametric method, namely regression trees and classification (CART, is then applied to companies classified as "bankruptcy" or "non-bankruptcy". Our results show that this model

NUI framework based on real-time head pose estimation and hand gesture recognition

Directory of Open Access Journals (Sweden)

Kim Hyunduk

2016-01-01

Full Text Available The natural user interface (NUI is used for the natural motion interface without using device or tool such as mice, keyboards, pens and markers. In this paper, we develop natural user interface framework based on two recognition module. First module is real-time head pose estimation module using random forests and second module is hand gesture recognition module, named Hand gesture Key Emulation Toolkit (HandGKET. Using the head pose estimation module, we can know where the user is looking and what the user’s focus of attention is. Moreover, using the hand gesture recognition module, we can also control the computer using the user’s hand gesture without mouse and keyboard. In proposed framework, the user’s head direction and hand gesture are mapped into mouse and keyboard event, respectively.

10 CFR 300.12 - Acceptance of reports and registration of entity emission reductions.

Science.gov (United States)

2010-01-01

... REPORTING PROGRAM: GENERAL GUIDELINES § 300.12 Acceptance of reports and registration of entity emission... provisions of this part. EIA will also review its records to verify that the reporting entity has submitted... credited to the entity as “registered reductions” which can be held by the reporting entity for use...

Entropy and Graph Based Modelling of Document Coherence using Discourse Entities

DEFF Research Database (Denmark)

Petersen, Casper; Lioma, Christina; Simonsen, Jakob Grue

2015-01-01

We present two novel models of document coherence and their application to information retrieval (IR). Both models approximate document coherence using discourse entities, e.g. the subject or object of a sentence. Our first model views text as a Markov process generating sequences of discourse...... entities (entity n-grams); we use the entropy of these entity n-grams to approximate the rate at which new information appears in text, reasoning that as more new words appear, the topic increasingly drifts and text coherence decreases. Our second model extends the work of Guinaudeau & Strube [28......] that represents text as a graph of discourse entities, linked by different relations, such as their distance or adjacency in text. We use several graph topology metrics to approximate different aspects of the discourse flow that can indicate coherence, such as the average clustering or betweenness of discourse...

Generic Entity Resolution in Relational Databases

Science.gov (United States)

Sidló, Csaba István

Entity Resolution (ER) covers the problem of identifying distinct representations of real-world entities in heterogeneous databases. We consider the generic formulation of ER problems (GER) with exact outcome. In practice, input data usually resides in relational databases and can grow to huge volumes. Yet, typical solutions described in the literature employ standalone memory resident algorithms. In this paper we utilize facilities of standard, unmodified relational database management systems (RDBMS) to enhance the efficiency of GER algorithms. We study and revise the problem formulation, and propose practical and efficient algorithms optimized for RDBMS external memory processing. We outline a real-world scenario and demonstrate the advantage of algorithms by performing experiments on insurance customer data.

The CALBC Silver Standard Corpus for Biomedical Named Entities - A Study in Harmonizing the Contributions from Four Independent Named Entity Taggers

NARCIS (Netherlands)

D. Rebholz-Schuhmann (Dietrich); A.J. Jimeno-Yepes (Antonio José); E.M. van Mulligen (Erik); N. Kang (Ning); J.A. Kors (Jan); D. Milward (David); P. Corbett (Peter); E. Buyko (Ekaterina); Tomanek (Katrin); E. Beisswanger (Elena); U. Hahn (Udo)

2010-01-01

textabstractThe production of gold standard corpora is time-consuming and costly. We propose an alternative: the 'silver standard corpus' (SSC), a corpus that has been generated by the harmonisation of the annotations that have been delivered from a selection of annotation systems. The systems have

Service quality measurement for non-executive directors in public entities

OpenAIRE

2012-01-01

D.Comm. In commercial corporations shareholders, at least in theory, evaluate the performance of the boards they have appointed. Such evaluation is mainly based on the financial performance of the entity. Public (state funded) entities have only the state as shareholder and the performance of their boards is not evaluated by the taxpayers who ultimately pay the directors' fees. The term "public entity" refers to 20 corporations with an annual turnover in excess of R 55 billion which are su...

Basic perceptual changes that alter meaning and neural correlates of recognition memory

Directory of Open Access Journals (Sweden)

Chuanji eGao

2015-02-01

Full Text Available It is difficult to pinpoint the border between perceptual and conceptual processing, despite their treatment as distinct entities in many studies of recognition memory. For instance, alteration of simple perceptual characteristics of a stimulus can radically change meaning, such as the color of bread changing from white to green. We sought to better understand the role of perceptual and conceptual processing in memory by identifying the effects of changing a basic perceptual feature (color on behavioral and neural correlates of memory in circumstances when this change would be expected to either change the meaning of a stimulus or to have no effect on meaning (i.e., to influence conceptual processing or not. Abstract visual shapes (squiggles were colorized during study and presented during test in either the same color or a different color. Those squiggles that subjects found to resemble meaningful objects supported behavioral measures of conceptual priming, whereas meaningless squiggles did not. Further, changing color from study to test had a selective effect on behavioral correlates of priming for meaningful squiggles, indicating that color change altered conceptual processing. During a recognition memory test, color change altered event-related brain potential correlates of memory for meaningful squiggles but not for meaningless squiggles. Specifically, color change reduced the amplitude of frontally distributed N400 potentials (FN400, indicating that these potentials indicated conceptual processing during recognition memory that was sensitive to color change. In contrast, color change had no effect on FN400 correlates of recognition for meaningless squiggles, which were overall smaller in amplitude than for meaningful squiggles (further indicating that these potentials signal conceptual processing during recognition. Thus, merely changing the color of abstract visual shapes can alter their meaning, changing behavioral and neural correlates

43 CFR 426.8 - Nonresident aliens and foreign entities.

Science.gov (United States)

2010-10-01

... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Nonresident aliens and foreign entities..., DEPARTMENT OF THE INTERIOR ACREAGE LIMITATION RULES AND REGULATIONS § 426.8 Nonresident aliens and foreign... reclamation law or these regulations, a nonresident alien or foreign entity that directly holds land in a...

Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model

Directory of Open Access Journals (Sweden)

Lokesh Selvaraj

2014-01-01

Full Text Available Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO is suggested. The suggested methodology contains four stages, namely, (i denoising, (ii feature mining (iii, vector quantization, and (iv IPSO based hidden Markov model (HMM technique (IP-HMM. At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC, mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

Logical Entity Level Sentiment Analysis

DEFF Research Database (Denmark)

Petersen, Niklas Christoffer; Villadsen, Jørgen

2017-01-01

We present a formal logical approach using a combinatory categorial grammar for entity level sentiment analysis that utilizes machine learning techniques for efficient syntactical tagging and performs a deep structural analysis of the syntactical properties of texts in order to yield precise resu...

8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

Is Alzheimer's disease a homogeneous disease entity?

Science.gov (United States)

Korczyn, Amos D

2013-10-01

The epidemic proportions of dementia in old age are a cause of great concern for the medical profession and the society at large. It is customary to consider Alzheimer's disease (AD) as the most common cause of dementia, and vascular dementia (VaD) as being the second. This dichotomous view of a primary neurodegenerative disease as opposed to a disorder where extrinsic factors cause brain damage led to separate lines of research in these two entities. New biomarkers, particularly the introduction of modern neuroimaging and cerebrospinal fluid changes, have, in recent years, helped to identify anatomical and chemical changes of VaD and of AD. Nevertheless, there is a substantial difference between the two entities. While it is clear that VaD is a heterogeneous entity, AD is supposed to be a single disorder. Nobody attempts to use CADASIL as a template to develops treatment for sporadic VaD. On the other hand, early-onset AD is used to develop therapy for sporadic AD. This paper will discuss the problems relating to this false concept and its consequences.

31 CFR 598.303 - Entity.

Science.gov (United States)

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 598.303 Section 598.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS..., organization, network, group, or subgroup, or any form of business collaboration. ...

What's in a Name? Interlocutors Dynamically Update Expectations about Shared Names.

Science.gov (United States)

Gegg-Harrison, Whitney M; Tanenhaus, Michael K

2016-01-01

In order to refer using a name, speakers must believe that their addressee knows about the link between the name and the intended referent. In cases where speakers and addressees learned a subset of names together, speakers are adept at using only the names their partner knows. But speakers do not always share such learning experience with their conversational partners. In these situations, what information guides speakers' choice of referring expression? A speaker who is uncertain about a names' common ground (CG) status often uses a name and description together. This N+D form allows speakers to demonstrate knowledge of a name, and could provide, even in the absence of miscommunication, useful evidence to the addressee regarding the speaker's knowledge. In cases where knowledge of one name is associated with knowledge of other names, this could provide indirect evidence regarding knowledge of other names that could support generalizations used to update beliefs about CG. Using Bayesian approaches to language processing as a guiding framework, we predict that interlocutors can use their partner's choice of referring expression, in particular their use of an N+D form, to generate more accurate beliefs regarding their partner's knowledge of other names. In Experiment 1, we find that domain experts are able to use their partner's referring expression choices to generate more accurate estimates of CG. In Experiment 2, we find that interlocutors are able to infer from a partner's use of an N+D form which other names that partner is likely to know or not know. Our results suggest that interlocutors can use the information conveyed in their partner's choice of referring expression to make generalizations that contribute to more accurate beliefs about what is shared with their partner, and further, that models of CG for reference need to account not just for the status of referents, but the status of means of referring to those referents.

Basic perceptual changes that alter meaning and neural correlates of recognition memory.

Science.gov (United States)

Gao, Chuanji; Hermiller, Molly S; Voss, Joel L; Guo, Chunyan

2015-01-01

It is difficult to pinpoint the border between perceptual and conceptual processing, despite their treatment as distinct entities in many studies of recognition memory. For instance, alteration of simple perceptual characteristics of a stimulus can radically change meaning, such as the color of bread changing from white to green. We sought to better understand the role of perceptual and conceptual processing in memory by identifying the effects of changing a basic perceptual feature (color) on behavioral and neural correlates of memory in circumstances when this change would be expected to either change the meaning of a stimulus or to have no effect on meaning (i.e., to influence conceptual processing or not). Abstract visual shapes ("squiggles") were colorized during study and presented during test in either the same color or a different color. Those squiggles that subjects found to resemble meaningful objects supported behavioral measures of conceptual priming, whereas meaningless squiggles did not. Further, changing color from study to test had a selective effect on behavioral correlates of priming for meaningful squiggles, indicating that color change altered conceptual processing. During a recognition memory test, color change altered event-related brain potential (ERP) correlates of memory for meaningful squiggles but not for meaningless squiggles. Specifically, color change reduced the amplitude of frontally distributed N400 potentials (FN400), implying that these potentials indicated conceptual processing during recognition memory that was sensitive to color change. In contrast, color change had no effect on FN400 correlates of recognition for meaningless squiggles, which were overall smaller in amplitude than for meaningful squiggles (further indicating that these potentials signal conceptual processing during recognition). Thus, merely changing the color of abstract visual shapes can alter their meaning, changing behavioral and neural correlates of memory

An Evaluation of Applying Knowledge Base to Academic Information Service

OpenAIRE

Seok-Hyoung Lee; Hwan-Min Kim; Ho-Seop Choe

2013-01-01

Through a series of precise text handling processes, including automatic extraction of information from documents with knowledge from various fields, recognition of entity names, detection of core topics, analysis of the relations between the extracted information and topics, and automatic inference of new knowledge, the most efficient knowledge base of the relevant field is created, and plans to apply these to the information knowledge management and service are the core requirements necessa...

Periocular xanthogranuloma: A forgotten entity?

Directory of Open Access Journals (Sweden)

Charalampos Papagoras

2010-03-01

Full Text Available Charalampos Papagoras1, George Kitsos2, Paraskevi V Voulgari1, Anastasia K Zikou3, Maria I Argyropoulou3, Aikaterini Zioga4, Alexandros A Drosos11Rheumatology Clinic, Department of Internal Medicine; 2Department of Ophthalmology; 3Department of Clinical Imaging and Radiology, 4Department of Pathology, Medical School, University of Ioannina, Ioannina, GreeceAbstract: Periocular xanthogranulomatous diseases are a rare group of disorders which are characterized by a predilection to affect the orbit and ocular adnexa and special histopathological features, in particular infiltrates comprising non-Langerhans-derived foamy histiocytes and Touton giant cells. The differential diagnosis is difficult and occasionally definite diagnosis cannot be established even after clinical and histopathological findings are taken together. We describe a case of a middle-aged man who presented with a 10-year history of voluminous eyelid swelling with concomitant late-onset atopic manifestations, namely bronchial asthma and allergic rhinitis with nasal polyps. After thorough clinical and laboratory investigation, including a biopsy of the eyelid, we classified the patient’s disease to a rare entity that has been relatively recently described: periocular xanthogranuloma associated with adult-onset asthma. In a review of the literature, no prospective trials concerning the treatment of this disease were found. The literature mainly contained case reports and case series in which corticosteroids and chemotherapy with alkylating agents have been reported to be beneficial. We treated our patient with a combination of oral corticosteroids and cyclophosphamide pulses and we observed substantial regression of the eyelid masses together with a normalization of systemic immunologic abnormalities.Keywords: periocular xanthogranuloma, adult-onset asthma, non-Langerhans histiocytoses, cyclophosphamide, methylprednisolone

Principles and tools for collaborative entity-based intelligence analysis.

Science.gov (United States)

Bier, Eric A; Card, Stuart K; Bodnar, John W

2010-01-01

Software tools that make it easier for analysts to collaborate as a natural part of their work will lead to better analysis that is informed by more perspectives. We are interested to know if software tools can be designed that support collaboration even as they allow analysts to find documents and organize information (including evidence, schemas, and hypotheses). We have modified the Entity Workspace system, described previously, to test such designs. We have evaluated the resulting design in both a laboratory study and a study where it is situated with an analysis team. In both cases, effects on collaboration appear to be positive. Key aspects of the design include an evidence notebook optimized for organizing entities (rather than text characters), information structures that can be collapsed and expanded, visualization of evidence that emphasizes events and documents (rather than emphasizing the entity graph), and a notification system that finds entities of mutual interest to multiple analysts. Long-term tests suggest that this approach can support both top-down and bottom-up styles of analysis.

Employee turnover and productivity among small business entities in Nigeria

Directory of Open Access Journals (Sweden)

John N. N. Ugoani

2016-12-01

Full Text Available This study was designed to evaluate the problems of employee turnover on productivity among small business entities in Nigeria, and recommend remedial actions. Employee turnover is the separation of employees from employers and replacement with other employees. Productive manpower is a critical element for the economic survival of any small business entity. The survey research design was used for the study. The sample comprised of 320 respondents. Data generated were analyzed by using descriptive, and Z-test statistical techniques. It was found that employee turnover adversely affects productivity in small business entities.

Categorizing terrorist entities listed by the European Union according to terrorist groups’ underlying motives

Directory of Open Access Journals (Sweden)

Liane Rothenberger

2015-10-01

Full Text Available States and international organizations have compiled lists of a great variety of terrorist groups. The current European Union list includes 44 entities. This study analyzes the underlying motives of the terrorist organizations named in this list. In order to understand the groups’ motivations and consequently be able to advise on methods of countering them with communication strategies, we employ a three-item typology provided by Waldmann (2001. The results show that only five of the 44 groups were religiously motivated to commit terrorism. Most of the groups (n=20 had nationalist-separatist motives, and 19 groups displayed social-revolutionary motives. Based on the respective motives, differing counter-terrorism strategies are proposed, e.g., developing rhetorical counter-narratives that address and reduce the groups’ motivational and identity-generating characteristics.

48 CFR 252.204-7001 - Commercial and Government Entity (CAGE) code reporting.

Science.gov (United States)

2010-10-01

... Entity (CAGE) code reporting. 252.204-7001 Section 252.204-7001 Federal Acquisition Regulations System... Entity (CAGE) Code Reporting (AUG 1999) (a) The offeror is requested to enter its CAGE code on its offer... AND CONTRACT CLAUSES Text of Provisions And Clauses 252.204-7001 Commercial and Government Entity...

Business Entity Selection: Why It Matters to Healthcare Practitioners. Part II--Corporations, Limited Liability Companies, and Professional Entities.

Science.gov (United States)

Nithman, Robert W

2015-01-01

The Bureau of Labor statistics indicates only a 50% four-year survivability rate among businesses classified as "education and health services." Gaining knowledge of IRS business entities can result in cost savings, operational efficiency, reduced liability, and enhanced sustainability. Each entity has unique disadvantages, depending on size, diversity of ownership, desire to expand, and profitability. Business structures should be compatible with organizational mission or vision statements, services and products, and professional codes of ethics. Healthcare reform will require greater business acumen. We have an ethical duty to disseminate and acquire the knowledge to properly establish and manage healthcare practices to ensure sustainable services that protect and serve the community.

Reflowing-driven paragraph recognition for electronic books in PDF

Science.gov (United States)

Fang, Jing; Tang, Zhi; Gao, Liangcai

2011-01-01

When reading electronic books on handheld devices, content sometimes should be reflowed and recomposed to adapt for small-screen mobile devices. According to people's reading practice, it is reasonable to reflow the text content based on paragraphs. Hence, this paper addresses the requirement and proposes a set of novel methods on paragraph recognition for electronic books in PDF. The proposed methods consist of three steps, namely, physical structure analysis, paragraph segmentation, and reading order detection. We make use of locally ordered property of PDF documents and layout style of books to improve traditional page recognition results. In addition, we employ the optimal matching of Bipartite Graph technology to detect paragraphs' reading order. Experiments show that our methods achieve high accuracy. It is noteworthy that, the research has been applied in a commercial software package for Chinese E-book production.

Face Detection and Face Recognition in Android Mobile Applications

Directory of Open Access Journals (Sweden)

Octavian DOSPINESCU

2016-01-01

Full Text Available The quality of the smartphone’s camera enables us to capture high quality pictures at a high resolution, so we can perform different types of recognition on these images. Face detection is one of these types of recognition that is very common in our society. We use it every day on Facebook to tag friends in our pictures. It is also used in video games alongside Kinect concept, or in security to allow the access to private places only to authorized persons. These are just some examples of using facial recognition, because in modern society, detection and facial recognition tend to surround us everywhere. The aim of this article is to create an appli-cation for smartphones that can recognize human faces. The main goal of this application is to grant access to certain areas or rooms only to certain authorized persons. For example, we can speak here of hospitals or educational institutions where there are rooms where only certain employees can enter. Of course, this type of application can cover a wide range of uses, such as helping people suffering from Alzheimer's to recognize the people they loved, to fill gaps persons who can’t remember the names of their relatives or for example to automatically capture the face of our own children when they smile.

Clarification of nuclear risk recognition scheme through dialogue forum

International Nuclear Information System (INIS)

Yagi, Ekou; Takahashi, Makoto; Kitamura, Masaharu

2007-01-01

The design framework and operational guidelines for conducting repetitive dialogue between public and nuclear engineers are described in this paper. An action research project named repetitive dialogue forum has been conducted in two municipalities where nuclear facilities were sited. The qualitative evaluation by public participants indicated that the public trust in the nuclear experts, known as the crucial factor for meaningful communication, was successfully established through the dialogue forum. In addition, the expert showed a marked psychological change from distrust to trust in public. Through a detailed analysis of the comments of the participants raised during the forums, the nuclear risk recognition scheme of the public was clarified. The constituents of the risk recognition scheme about nuclear facilities were identified as follows. The first is related to the technical risk recognition factor including purely technical risk, organizational elements and regulatory elements. The second is the social risk recognition factor including economical and mental elements. The last is the communication factor including the influence of mass media, difficulty in frank communication in local community etc. It became clear that the information provision activities conducted by the government and the nuclear industry were lack of in-depth understanding of actual information needs in the public. Provision of information contents consistent with our observations is recommended for reestablishment of public trust in expert and for more informative dialogical interactions. (author)

ANFIS Based Methodology for Sign Language Recognition and Translating to Number in Kannada Language

Directory of Open Access Journals (Sweden)

Ramesh Mahadev kagalkar

2017-03-01

Full Text Available In the world of signing and gestures, lots of analysis work has been done over the past three decades. This has led to a gradual transition from isolated to continuous, and static to dynamic gesture recognition for operations on a restricted vocabulary. In gift state of affairs, human machine interactive systems facilitate communication between the deaf, and hearing impaired in universe things. So as to boost the accuracy of recognition, several researchers have deployed strategies like HMM, Artificial Neural Networks, and Kinect platform. Effective algorithms for segmentation, classification, pattern matching and recognition have evolved. The most purpose of this paper is to investigate these strategies and to effectively compare them, which can alter the reader to succeed in associate in nursing optimum resolution. This creates each, challenges and opportunities for signing recognition connected analysis. Normal 0 false false false DE JA X-NONE Name

Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine

Science.gov (United States)

Yang, Zhutian; Wu, Zhilu; Yin, Zhendong; Quan, Taifan; Sun, Hongjian

2013-01-01

Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for recognizing radar emitter signals. In this paper, a hybrid recognition approach is presented that classifies radar emitter signals by exploiting the different separability of samples. The proposed approach comprises two steps, namely the primary signal recognition and the advanced signal recognition. In the former step, a novel rough k-means classifier, which comprises three regions, i.e., certain area, rough area and uncertain area, is proposed to cluster the samples of radar emitter signals. In the latter step, the samples within the rough boundary are used to train the relevance vector machine (RVM). Then RVM is used to recognize the samples in the uncertain area; therefore, the classification accuracy is improved. Simulation results show that, for recognizing radar emitter signals, the proposed hybrid recognition approach is more accurate, and presents lower computational complexity than traditional approaches. PMID:23344380

What’s in a Name? – Consequences of Naming Non-Human Animals

DEFF Research Database (Denmark)

Borkfelt, Sune

2011-01-01

have consequences for the way we think about animals (human and non-human), peoples, species, places, things etc. Through a blend of history, philosophy and representational theory—and using examples from, among other things, the Bible, Martin Luther, colonialism/imperialism and contemporary ways......The act of naming is among the most basic actions of language. Indeed, it is naming something that enables us to communicate about it in specific terms, whether the object named is human or non-human, animate or inanimate. However, naming is not as uncomplicated as we may usually think and names...... of keeping and regarding non-human animals—this paper attempts to trace the importance of (both specific and generic) naming to our relationships with the non-human. It explores this topic from the naming of the animals in Genesis to the names given and used by scientists, keepers of companion animals, media...

ECO: A Framework for Entity Co-Occurrence Exploration with Faceted Navigation

Energy Technology Data Exchange (ETDEWEB)

Halliday, K. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2010-08-20

Even as highly structured databases and semantic knowledge bases become more prevalent, a substantial amount of human knowledge is reported as written prose. Typical textual reports, such as news articles, contain information about entities (people, organizations, and locations) and their relationships. Automatically extracting such relationships from large text corpora is a key component of corporate and government knowledge bases. The primary goal of the ECO project is to develop a scalable framework for extracting and presenting these relationships for exploration using an easily navigable faceted user interface. ECO uses entity co-occurrence relationships to identify related entities. The system aggregates and indexes information on each entity pair, allowing the user to rapidly discover and mine relational information.

Entity versus incremental theories predict older adults' memory performance.

Science.gov (United States)

Plaks, Jason E; Chasteen, Alison L

2013-12-01

The authors examined whether older adults' implicit theories regarding the modifiability of memory in particular (Studies 1 and 3) and abilities in general (Study 2) would predict memory performance. In Study 1, individual differences in older adults' endorsement of the "entity theory" (a belief that one's ability is fixed) or "incremental theory" (a belief that one's ability is malleable) of memory were measured using a version of the Implicit Theories Measure (Dweck, 1999). Memory performance was assessed with a free-recall task. Results indicated that the higher the endorsement of the incremental theory, the better the free recall. In Study 2, older and younger adults' theories were measured using a more general version of the Implicit Theories Measure that focused on the modifiability of abilities in general. Again, for older adults, the higher the incremental endorsement, the better the free recall. Moreover, as predicted, implicit theories did not predict younger adults' memory performance. In Study 3, participants read mock news articles reporting evidence in favor of either the entity or incremental theory. Those in the incremental condition outperformed those in the entity condition on reading span and free-recall tasks. These effects were mediated by pretask worry such that, for those in the entity condition, higher worry was associated with lower performance. Taken together, these studies suggest that variation in entity versus incremental endorsement represents a key predictor of older adults' memory performance. PsycINFO Database Record (c) 2013 APA, all rights reserved.

47 CFR 22.229 - Designated entities.

Science.gov (United States)

2010-10-01

... entrepreneur is an entity that, together with its controlling interests and affiliates, has average annual... entrepreneur, as defined in this section, or a consortium of entrepreneurs may use the bidding credit specified...

47 CFR 101.538 - Designated entities.

Science.gov (United States)

2010-10-01

... entrepreneur is an entity that, together with its controlling interests and affiliates, has average gross... entrepreneur, as defined in this section, or a consortium of entrepreneurs may use the bidding credit specified...

What's in a Name? Interlocutors dynamically update expectations about shared names

Directory of Open Access Journals (Sweden)

Whitney Marie Gegg-Harrison

2016-02-01

Full Text Available In order to refer using a name, speakers must know that their addressee knows about the link between the name and the intended referent. In cases where speakers and addressees learned names together, speakers are adept at using names only when their addressee knows them. But speakers do not always share such learning experience with their conversational partners. In these situations, what information guides speakers’ choice of referring expression? A speaker who is uncertain about a names’ common ground (CG status often uses a name and description together. This N+D form allows speakers to demonstrate knowledge of a name, and could provide, even in the absence of miscommunication, useful evidence to the addressee regarding the speaker’s knowledge. In cases where knowledge of one name is associated with knowledge of other names, could provide indirect evidence regarding knowledge of other names that could support generalizations used to update beliefs about CG. Using data explanation approaches to language processing as a guiding framework, we predict that interlocutors can use their partner’s choice of referring expression, in particular their use of an N+D form, to generate more accurate beliefs regarding their partner’s knowledge of other names. In Experiment 1, we find that domain experts are able to use their partner’s referring expression choices to generate more accurate estimates of CG. In Experiment 2, we find that interlocutors are able to infer from a partner’s use of an N+D form which other names that partner is likely to know or not know. Our results suggest that interlocutors can use the information conveyed in their partner’s choice of referring expression to make generalizations that contribute to more accurate beliefs about what is shared with their partner, and further, that models of CG for reference need to account not just for the status of referents, but the status of means of referring to those referents.

31 CFR 594.303 - Entity.

Science.gov (United States)

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 594.303 Section 594.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY GLOBAL TERRORISM SANCTIONS REGULATIONS General Definitions § 594.303...

Identifying Human Phenotype Terms by Combining Machine Learning and Validation Rules

Directory of Open Access Journals (Sweden)

Manuel Lobo

2017-01-01

Full Text Available Named-Entity Recognition is commonly used to identify biological entities such as proteins, genes, and chemical compounds found in scientific articles. The Human Phenotype Ontology (HPO is an ontology that provides a standardized vocabulary for phenotypic abnormalities found in human diseases. This article presents the Identifying Human Phenotypes (IHP system, tuned to recognize HPO entities in unstructured text. IHP uses Stanford CoreNLP for text processing and applies Conditional Random Fields trained with a rich feature set, which includes linguistic, orthographic, morphologic, lexical, and context features created for the machine learning-based classifier. However, the main novelty of IHP is its validation step based on a set of carefully crafted manual rules, such as the negative connotation analysis, that combined with a dictionary can filter incorrectly identified entities, find missed entities, and combine adjacent entities. The performance of IHP was evaluated using the recently published HPO Gold Standardized Corpora (GSC, where the system Bio-LarK CR obtained the best F-measure of 0.56. IHP achieved an F-measure of 0.65 on the GSC. Due to inconsistencies found in the GSC, an extended version of the GSC was created, adding 881 entities and modifying 4 entities. IHP achieved an F-measure of 0.863 on the new GSC.

Utilization-based object recognition in confined spaces

Science.gov (United States)

Shirkhodaie, Amir; Telagamsetti, Durga; Chan, Alex L.

2017-05-01

Recognizing substantially occluded objects in confined spaces is a very challenging problem for ground-based persistent surveillance systems. In this paper, we discuss the ontology inference of occluded object recognition in the context of in-vehicle group activities (IVGA) and describe an approach that we refer to as utilization-based object recognition method. We examine the performance of three types of classifiers tailored for the recognition of objects with partial visibility, namely, (1) Hausdorff Distance classifier, (2) Hamming Network classifier, and (3) Recurrent Neural Network classifier. In order to train these classifiers, we have generated multiple imagery datasets containing a mixture of common objects appearing inside a vehicle with full or partial visibility and occultation. To generate dynamic interactions between multiple people, we model the IVGA scenarios using a virtual simulation environment, in which a number of simulated actors perform a variety of IVGA tasks independently or jointly. This virtual simulation engine produces the much needed imagery datasets for the verification and validation of the efficiency and effectiveness of the selected object recognizers. Finally, we improve the performance of these object recognizers by incorporating human gestural information that differentiates various object utilization or handling methods through the analyses of dynamic human-object interactions (HOI), human-human interactions (HHI), and human-vehicle interactions (HVI) in the context of IVGA.

Constraint-satisfaction inference for entity recognition

NARCIS (Netherlands)

Canisius, S.V.M.; Bosch, A.P.J. van den; Daelemans, W.M.P.; Bosch, A.P.J. van den; Bouma, G.

2011-01-01

One approach to QA answering is to match a question to candidate answers in a background corpus based on semantic overlap, possibly in combination with other levels of matching, such as lexical vector space similarity and syntactic similarity. While the computation of deep semantic similarity is as

47 CFR 27.209 - Designated entities; bidding credits; unjust enrichment.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Designated entities; bidding credits; unjust enrichment. 27.209 Section 27.209 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON... 2305-2320 MHz and 2345-2360 MHz Bands § 27.209 Designated entities; bidding credits; unjust enrichment...

Investigating the improvement of decoding abilities and working memory in children with Incremental or Entity personal conceptions of intelligence: two case reports

Directory of Open Access Journals (Sweden)

Marianna eAlesi

2016-01-01

Full Text Available One of the most significant current discussions has led to the hypothesis that domain-specific training programs alone are not enough to improve reading achievement or working memory abilities. Incremental or Entity personal conceptions of intelligence may be assumed to be an important prognostic factor to overcome domain-specific deficits. Specifically, incremental students tend to be more oriented toward change and autonomy and to adopt more efficacious strategies. This study aims at examining the efficacy of a multidimensional intervention program to improve decoding abilities and working memory. Participants were two children (M age = 10 yr. with developmental dyslexia and different conceptions of intelligence.Children were tested on a whole battery of reading and spelling tests commonly used in the assessment of reading disabilities in Italy. Then, they were given a multimedia test to measure motivational factors such as conceptions of intelligence and achievement goalsChildren took part in the T.I.R.D. Multimedia Training for the Rehabilitation of Dyslexia (Rappo & Pepi, 2010 reinforced by specific units to improve verbal working memory for three months. This training consisted of specific tasks to rehabilitate both visual and phonological strategies (sound blending, word segmentation, alliteration test and rhyme test, letter recognition, digraph recognition, trigraph recognition and word recognition are samples of visual tasks and verbal working memory (rapid words and non-words recognition.Posttest evaluations showed that the child holding the incremental theory of intelligence improved more than the child holding a static representation.On the whole this study highlights the importance of treatment programs in which account is taken of both specificity of deficits and motivational factors. There is a need to plan multifaceted intervention programs based on a transverse approach, looking at both cognitive and motivational factors.

Investigating the Improvement of Decoding Abilities and Working Memory in Children with Incremental or Entity Personal Conceptions of Intelligence: Two Case Reports

Science.gov (United States)

Alesi, Marianna; Rappo, Gaetano; Pepi, Annamaria

2016-01-01

One of the most significant current discussions has led to the hypothesis that domain-specific training programs alone are not enough to improve reading achievement or working memory abilities. Incremental or Entity personal conceptions of intelligence may be assumed to be an important prognostic factor to overcome domain-specific deficits. Specifically, incremental students tend to be more oriented toward change and autonomy and are able to adopt more efficacious strategies. This study aims at examining the effect of personal conceptions of intelligence to strengthen the efficacy of a multidimensional intervention program in order to improve decoding abilities and working memory. Participants included two children (M age = 10 years) with developmental dyslexia and different conceptions of intelligence. The children were tested on a whole battery of reading and spelling tests commonly used in the assessment of reading disabilities in Italy. Afterwards, they were given a multimedia test to measure motivational factors such as conceptions of intelligence and achievement goals. The children took part in the T.I.R.D. Multimedia Training for the Rehabilitation of Dyslexia (Rappo and Pepi, 2010) reinforced by specific units to improve verbal working memory for 3 months. This training consisted of specific tasks to rehabilitate both visual and phonological strategies (sound blending, word segmentation, alliteration test and rhyme test, letter recognition, digraph recognition, trigraph recognition, and word recognition as samples of visual tasks) and verbal working memory (rapid words and non-words recognition). Posttest evaluations showed that the child holding the incremental theory of intelligence improved more than the child holding a static representation. On the whole this study highlights the importance of treatment programs in which both specificity of deficits and motivational factors are both taken into account. There is a need to plan multifaceted intervention

Face Recognition Method Based on Fuzzy 2DPCA

Directory of Open Access Journals (Sweden)

Xiaodong Li

2014-01-01

Full Text Available 2DPCA, which is one of the most important face recognition methods, is relatively sensitive to substantial variations in light direction, face pose, and facial expression. In order to improve the recognition performance of the traditional 2DPCA, a new 2DPCA algorithm based on the fuzzy theory is proposed in this paper, namely, the fuzzy 2DPCA (F2DPCA. In this method, applying fuzzy K-nearest neighbor (FKNN, the membership degree matrix of the training samples is calculated, which is used to get the fuzzy means of each class. The average of fuzzy means is then incorporated into the definition of the general scatter matrix with anticipation that it can improve classification result. The comprehensive experiments on the ORL, the YALE, and the FERET face database show that the proposed method can improve the classification rates and reduce the sensitivity to variations between face images caused by changes in illumination, face expression, and face pose.

Event-Entity-Relationship Modeling in Data Warehouse Environments

DEFF Research Database (Denmark)

Bækgaard, Lars

We use the event-entity-relationship model (EVER) to illustrate the use of entity-based modeling languages for conceptual schema design in data warehouse environments. EVER is a general-purpose information modeling language that supports the specification of both general schema structures and multi......-dimensional schemes that are customized to serve specific information needs. EVER is based on an event concept that is very well suited for multi-dimensional modeling because measurement data often represent events in multi-dimensional databases...

[Legal recognition of transsexuality in Chile through the judicial procedure for name change].

Science.gov (United States)

Muñoz León, Fernando

2015-08-01

Do transsexual people in Chile have a right to have their gender identity or their sex reassignment legally recognized? The absence of any legislation on gender identity or transsexualism could lead us to believe that it is not the case. However, a quantitative review of decisions issued by Chilean courts during the last years on name-and sex-change requests filed by transsexual people reveals that most of these courts have accepted these requests. From the perspective of the well-being of transsexual people, this is a positive result. However, the fact that a few rejections exist reminds us of the need to enact an explicit legislation in this issue. Lastly, a qualitative analysis of those decisions suggests that the traditional reluctance of courts to interpret the law in a creative way has been overcome in these cases by the use of knowledge and discourses belonging to healthcare sciences. This is an example of an epistemological complementariness between medicine and law.

Colour agnosia impairs the recognition of natural but not of non-natural scenes.

Science.gov (United States)

Nijboer, Tanja C W; Van Der Smagt, Maarten J; Van Zandvoort, Martine J E; De Haan, Edward H F

2007-03-01

Scene recognition can be enhanced by appropriate colour information, yet the level of visual processing at which colour exerts its effects is still unclear. It has been suggested that colour supports low-level sensory processing, while others have claimed that colour information aids semantic categorization and recognition of objects and scenes. We investigated the effect of colour on scene recognition in a case of colour agnosia, M.A.H. In a scene identification task, participants had to name images of natural or non-natural scenes in six different formats. Irrespective of scene format, M.A.H. was much slower on the natural than on the non-natural scenes. As expected, neither M.A.H. nor control participants showed any difference in performance for the non-natural scenes. However, for the natural scenes, appropriate colour facilitated scene recognition in control participants (i.e., shorter reaction times), whereas M.A.H.'s performance did not differ across formats. Our data thus support the hypothesis that the effect of colour occurs at the level of learned associations.

Finding Related Entities by Retrieving Relations: UIUC at TREC 2009 Entity Track

Science.gov (United States)

2009-11-01

classes, depending on the categories they belong to. A music album could have any generic name, whereas a laptop model has a more generalizable name. A...names of music albums are simply plain text often capitalized, and so on. Thus, we feel that a better ap- proach would be to first identify the...origin domain of the text to be tagged (e.g., pharmaceutical, music , journal, etc.), and then apply tagging rules that are specific to that domain

Names of Southern African grasses: Name changes and additional ...

African Journals Online (AJOL)

The main reasons for changes in botanical names are briefly reviewed, with examples from the lists. At this time, about 1040 grass species and subspecific taxa are recognized in the subcontinent. Keywords: botanical research; botanical research institute; botany; grass; grasses; identification; name change; nomenclature; ...

45 CFR 2550.80 - What are the duties of the State entities?

Science.gov (United States)

2010-10-01

... 45 Public Welfare 4 2010-10-01 2010-10-01 false What are the duties of the State entities? 2550.80... ADMINISTRATIVE ENTITIES § 2550.80 What are the duties of the State entities? Both State commissions and AAEs have..., respite services for adults age 55 or older and caregivers, and transitions for older adults age 55 or...

26 CFR 301.7701-2T - Business entities; definitions (temporary).

Science.gov (United States)

2010-04-01

... 26 Internal Revenue 18 2010-04-01 2010-04-01 false Business entities; definitions (temporary). 301... (CONTINUED) PROCEDURE AND ADMINISTRATION PROCEDURE AND ADMINISTRATION Definitions § 301.7701-2T Business entities; definitions (temporary). (a) through (c)(2)(ii) [Reserved] For further guidance, see § 301.7701-2...

Real-Time Hand Posture Recognition Using a Range Camera

Science.gov (United States)

Lahamy, Herve

The basic goal of human computer interaction is to improve the interaction between users and computers by making computers more usable and receptive to the user's needs. Within this context, the use of hand postures in replacement of traditional devices such as keyboards, mice and joysticks is being explored by many researchers. The goal is to interpret human postures via mathematical algorithms. Hand posture recognition has gained popularity in recent years, and could become the future tool for humans to interact with computers or virtual environments. An exhaustive description of the frequently used methods available in literature for hand posture recognition is provided. It focuses on the different types of sensors and data used, the segmentation and tracking methods, the features used to represent the hand postures as well as the classifiers considered in the recognition process. Those methods are usually presented as highly robust with a recognition rate close to 100%. However, a couple of critical points necessary for a successful real-time hand posture recognition system require major improvement. Those points include the features used to represent the hand segment, the number of postures simultaneously recognizable, the invariance of the features with respect to rotation, translation and scale and also the behavior of the classifiers against non-perfect hand segments for example segments including part of the arm or missing part of the palm. A 3D time-of-flight camera named SR4000 has been chosen to develop a new methodology because of its capability to provide in real-time and at high frame rate 3D information on the scene imaged. This sensor has been described and evaluated for its capability for capturing in real-time a moving hand. A new recognition method that uses the 3D information provided by the range camera to recognize hand postures has been proposed. The different steps of this methodology including the segmentation, the tracking, the hand

Reading in developmental prosopagnosia: Evidence for a dissociation between word and face recognition.

Science.gov (United States)

Starrfelt, Randi; Klargaard, Solja K; Petersen, Anders; Gerlach, Christian

2018-02-01

Recent models suggest that face and word recognition may rely on overlapping cognitive processes and neural regions. In support of this notion, face recognition deficits have been demonstrated in developmental dyslexia. Here we test whether the opposite association can also be found, that is, impaired reading in developmental prosopagnosia. We tested 10 adults with developmental prosopagnosia and 20 matched controls. All participants completed the Cambridge Face Memory Test, the Cambridge Face Perception test and a Face recognition questionnaire used to quantify everyday face recognition experience. Reading was measured in four experimental tasks, testing different levels of letter, word, and text reading: (a) single word reading with words of varying length,(b) vocal response times in single letter and short word naming, (c) recognition of single letters and short words at brief exposure durations (targeting the word superiority effect), and d) text reading. Participants with developmental prosopagnosia performed strikingly similar to controls across the four reading tasks. Formal analysis revealed a significant dissociation between word and face recognition, as the difference in performance with faces and words was significantly greater for participants with developmental prosopagnosia than for controls. Adult developmental prosopagnosics read as quickly and fluently as controls, while they are seemingly unable to learn efficient strategies for recognizing faces. We suggest that this is due to the differing demands that face and word recognition put on the perceptual system. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2.

Science.gov (United States)

Sorokin, Anatoly; Le Novère, Nicolas; Luna, Augustin; Czauderna, Tobias; Demir, Emek; Haw, Robin; Mi, Huaiyu; Moodie, Stuart; Schreiber, Falk; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Agreeements between entities within the public sector and public procurement rules

Directory of Open Access Journals (Sweden)

Alejandro Huergo Lora

2017-11-01

Full Text Available This paper examines how European and Spanish public procurement rules tackle agreements between entities within the public sector. In Spain these agreemets were initially above those rules, but now they cannot have the same object as a contract. Spanish law is not in line with European law, since under European law agreements are valid even if their object could be attained with a contract, provided that they meet some requirements. On the other hand, attention is paid to these requisites, laid down by Eurepean law, in order to ascertain if agreements are asked to comply with harder rules than «in house providing», and if it has to be so. Public entities are not obliged to «buy» if they can fulfill their needs with their own resources. And «their own resources» include the resources of entities or bodies closely related, or even any entity within the public sector. Otherwise decentralized States, in which there are many autonomous entities whose cooperation involves agreements between independent bodies, would be impaired.

Knowledge environments representing molecular entities for the virtual physiological human.

Science.gov (United States)

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

A pattern recognition account of decision making.

Science.gov (United States)

Massaro, D W

1994-09-01

In the domain of pattern recognition, experiments have shown that perceivers integrate multiple sources of information in an optimal manner. In contrast, other research has been interpreted to mean that decision making is nonoptimal. As an example, Tversky and Kahneman (1983) have shown that subjects commit a conjunction fallacy because they judge it more likely that a fictitious person named Linda is a bank teller and a feminist than just a bank teller. This judgment supposedly violates probability theory, because the probability of two events can never be greater than the probability of either event alone. The present research tests the hypothesis that subjects interpret this judgment task as a pattern recognition task. If this hypothesis is correct, subjects' judgments should be described accurately by the fuzzy logical model of perception (FLMP)--a successful model of pattern recognition. In the first experiment, the Linda task was extended to an expanded factorial design with five vocations and five avocations. The probability ratings were described well by the FLMP and described poorly by a simple probability model. The second experiment included (1) two fictitious people, Linda and Joan, as response alternatives and (2) both ratings and categorization judgments. Although the ratings were accurately described by both the FLMP and an averaging of the sources of information, the categorization judgments were described better by the FLMP. These results reveal important similarities in recognizing patterns and in decision making. Given that the FLMP is an optimal method for combining multiple sources of information, the probability judgments appear to be optimal in the same manner as pattern-recognition judgments.

Using Direct Sub-Level Entity Access to Improve Nuclear Stockpile Simulation Modeling

Energy Technology Data Exchange (ETDEWEB)

Parker, Robert Y. [Brigham Young Univ., Provo, UT (United States)

1999-08-01

Direct sub-level entity access is a seldom-used technique in discrete-event simulation modeling that addresses the accessibility of sub-level entity information. The technique has significant advantages over more common, alternative modeling methods--especially where hierarchical entity structures are modeled. As such, direct sub-level entity access is often preferable in modeling nuclear stockpile, life-extension issues, an area to which it has not been previously applied. Current nuclear stockpile, life-extension models were demonstrated to benefit greatly from the advantages of direct sub-level entity access. In specific cases, the application of the technique resulted in models that were up to 10 times faster than functionally equivalent models where alternative techniques were applied. Furthermore, specific implementations of direct sub-level entity access were observed to be more flexible, efficient, functional, and scalable than corresponding implementations using common modeling techniques. Common modeling techniques (''unbatch/batch'' and ''attribute-copying'') proved inefficient and cumbersome in handling many nuclear stockpile modeling complexities, including multiple weapon sites, true defect analysis, and large numbers of weapon and subsystem types. While significant effort was required to enable direct sub-level entity access in the nuclear stockpile simulation models, the enhancements were worth the effort--resulting in more efficient, more capable, and more informative models that effectively addressed the complexities of the nuclear stockpile.

Avibase – a database system for managing and organizing taxonomic concepts

Directory of Open Access Journals (Sweden)

Denis Lepage

2014-06-01

Full Text Available Scientific names of biological entities offer an imperfect resolution of the concepts that they are intended to represent. Often they are labels applied to entities ranging from entire populations to individual specimens representing those populations, even though such names only unambiguously identify the type specimen to which they were originally attached. Thus the real-life referents of names are constantly changing as biological circumscriptions are redefined and thereby alter the sets of individuals bearing those names. This problem is compounded by other characteristics of names that make them ambiguous identifiers of biological concepts, including emendations, homonymy and synonymy. Taxonomic concepts have been proposed as a way to address issues related to scientific names, but they have yet to receive broad recognition or implementation. Some efforts have been made towards building systems that address these issues by cataloguing and organizing taxonomic concepts, but most are still in conceptual or proof-of-concept stage. We present the on-line database Avibase as one possible approach to organizing taxonomic concepts. Avibase has been successfully used to describe and organize 844,000 species-level and 705,000 subspecies-level taxonomic concepts across every major bird taxonomic checklist of the last 125 years. The use of taxonomic concepts in place of scientific names, coupled with efficient resolution services, is a major step toward addressing some of the main deficiencies in the current practices of scientific name dissemination and use.

Object-Relational Management of Multiply Represented Geographic Entities

DEFF Research Database (Denmark)

Friis-Christensen, Anders; Jensen, Christian Søndergaard

2003-01-01

Multiple representation occurs when information about the same geographic entity is represented electronically more than once. This occurs frequently in practice, and it invariably results in the occurrence of inconsistencies among the different representations. We propose to resolve this situation...... by introducing a multiple representation management system (MRMS), the schema of which includes rules that specify how to identify representations of the same entity, rules that specify consistency requirements, and rules used to restore consistency when necessary. In this paper, we demonstrate by means...

Semi-automated contour recognition using DICOMautomaton

International Nuclear Information System (INIS)

Clark, H; Duzenli, C; Wu, J; Moiseenko, V; Lee, R; Gill, B; Thomas, S

2014-01-01

Purpose: A system has been developed which recognizes and classifies Digital Imaging and Communication in Medicine contour data with minimal human intervention. It allows researchers to overcome obstacles which tax analysis and mining systems, including inconsistent naming conventions and differences in data age or resolution. Methods: Lexicographic and geometric analysis is used for recognition. Well-known lexicographic methods implemented include Levenshtein-Damerau, bag-of-characters, Double Metaphone, Soundex, and (word and character)-N-grams. Geometrical implementations include 3D Fourier Descriptors, probability spheres, boolean overlap, simple feature comparison (e.g. eccentricity, volume) and rule-based techniques. Both analyses implement custom, domain-specific modules (e.g. emphasis differentiating left/right organ variants). Contour labels from 60 head and neck patients are used for cross-validation. Results: Mixed-lexicographical methods show an effective improvement in more than 10% of recognition attempts compared with a pure Levenshtein-Damerau approach when withholding 70% of the lexicon. Domain-specific and geometrical techniques further boost performance. Conclusions: DICOMautomaton allows users to recognize contours semi-automatically. As usage increases and the lexicon is filled with additional structures, performance improves, increasing the overall utility of the system.

IDENTIFYING AND IMPLEMENTATION OF THE FINANCING SOURCES OF TOURIST ENTITIES

Directory of Open Access Journals (Sweden)

Gabriela DAVID

2015-12-01

Full Text Available Located at the intersection of the two spheres (tourism markets and financial ones, the tourism entity in Romania is interested in finding the formula to assure optimum financing by attracting financial resources in the field, on the one hand and on the other hand it is interested in meeting the high demand for profit from tourism and economic sphere. The objective determinant of Romanian tourism entity is to maximize the value by carrying out a profitable activity. The touristic entity must obtain profit to generate sufficient funds to distribute cash dividends to shareholders, while paying creditors at a favorable interest on borrowed funds.

26 CFR 301.7701-5 - Domestic and foreign business entities.

Science.gov (United States)

2010-04-01

... the laws of Country A as a public limited company. It is also an entity that is organized as a limited... or organized as any type of entity (including, but not limited to, a corporation, unincorporated association, general partnership, limited partnership, and limited liability company) in the United States, or...

Distribution of Chinese names

Science.gov (United States)

Huang, Ding-wei

2013-03-01

We present a statistical model for the distribution of Chinese names. Both family names and given names are studied on the same basis. With naive expectation, the distribution of family names can be very different from that of given names. One is affected mostly by genealogy, while the other can be dominated by cultural effects. However, we find that both distributions can be well described by the same model. Various scaling behaviors can be understood as a result of stochastic processes. The exponents of different power-law distributions are controlled by a single parameter. We also comment on the significance of full-name repetition in Chinese population.

Twisted speckle entities inside wave-front reversal mirrors

International Nuclear Information System (INIS)

Okulov, A. Yu

2009-01-01

The previously unknown property of the optical speckle pattern reported. The interference of a speckle with the counterpropagating phase-conjugated (PC) speckle wave produces a randomly distributed ensemble of a twisted entities (ropes) surrounding optical vortex lines. These entities appear in a wide range of a randomly chosen speckle parameters inside the phase-conjugating mirrors regardless to an internal physical mechanism of the wave-front reversal. These numerically generated interference patterns are relevant to the Brillouin PC mirrors and to a four-wave mixing PC mirrors based upon laser trapped ultracold atomic cloud.

Economic performance of Czech business entities in the context of CSRs’ implementation

Directory of Open Access Journals (Sweden)

Marcela Basovníková

2013-01-01

Full Text Available The term responsible entrepreneurship refers to economic success of a business by the inclusion of social and environmental considerations into a company’s operational processes. It satisfies customers’ demands, whilst also managing the expectations of employees, suppliers and the surrounding community. In general, the term Social Corporate Responsibility means a positive contribution to society including management of enterprise’s environmental impacts. The major determinants of the CSR values can be explored such as economic, cultural and leadership factors. Corporate Social Responsibility has been receiving increased attention also from bodies which give certification to companies with CSR in practice. There are different certificates which companies can apply for, if being „responsible“, such as SA 8000, GRI, AA1000, IiP or ISO26000. The aim of this paper is to introduce various certificates, namely SA 8000 and look in details on economic data of 9 companies, chosen from 25 in the Czech Republic, which received this label.Both traditional and modern indicators for assessment of business entities’ economic performance within the entity sample are employed as the inclusion of the economic factors on the CSR. Indices of credibility in order to evaluate the financial status of sample entities are utilised as well. The mentioned economic analysis is managed both in the period before the implementation of the certified CSR system and in the ex-post period. The results of economic analysis in the period before receiving the SA8000 certificate are evaluated using the mathematic-statistical methods to reveal development trend regarding their economic performance and to conduct comparison to respective industrial means.

The Recognition of Web Pages' Hyperlinks by People with Intellectual Disabilities: An Evaluation Study

Science.gov (United States)

Rocha, Tania; Bessa, Maximino; Goncalves, Martinho; Cabral, Luciana; Godinho, Francisco; Peres, Emanuel; Reis, Manuel C.; Magalhaes, Luis; Chalmers, Alan

2012-01-01

Background: One of the most mentioned problems of web accessibility, as recognized in several different studies, is related to the difficulty regarding the perception of what is or is not clickable in a web page. In particular, a key problem is the recognition of hyperlinks by a specific group of people, namely those with intellectual…

British Sign Name Customs

Science.gov (United States)

Day, Linda; Sutton-Spence, Rachel

2010-01-01

Research presented here describes the sign names and the customs of name allocation within the British Deaf community. While some aspects of British Sign Language sign names and British Deaf naming customs differ from those in most Western societies, there are many similarities. There are also similarities with other societies outside the more…

Preparation of the accounting entity for verification of the final accounts

OpenAIRE

Kučerová, Monika

2009-01-01

Bachelor's thesis deals with preparation of the accounting entity for verification of the final accounts. The work includes the definition of the accounting entity, also includes information about preparation of final accounts and deals with report of auditor.

Xanthogranulomatous endometritis: an unusual pathological entity ...

African Journals Online (AJOL)

Xanthogranulomatous endometritis is an unusual pathological entity mimicking endometrial carcinoma. This shows sheets of foamy histiocytes alongwith other inflammatory cells. We, hereby, report a case of 45 year multigravida female with irregular menstrual history, clinically diagnosed as carcinoma and ...

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Science.gov (United States)

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Directory of Open Access Journals (Sweden)

Jianzhong Wang

Full Text Available Recently, Sparse Representation-based Classification (SRC has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW demonstrate the effectiveness of LCJDSRC.

Optical Pattern Recognition

Science.gov (United States)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

Glutathione--hydroxyl radical interaction: a theoretical study on radical recognition process.

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Béla Fiser

Full Text Available Non-reactive, comparative (2 × 1.2 μs molecular dynamics simulations were carried out to characterize the interactions between glutathione (GSH, host molecule and hydroxyl radical (OH(•, guest molecule. From this analysis, two distinct steps were identified in the recognition process of hydroxyl radical by glutathione: catching and steering, based on the interactions between the host-guest molecules. Over 78% of all interactions are related to the catching mechanism via complex formation between anionic carboxyl groups and the OH radical, hence both terminal residues of GSH serve as recognition sites. The glycine residue has an additional role in the recognition of OH radical, namely the steering. The flexibility of the Gly residue enables the formation of further interactions of other parts of glutathione (e.g. thiol, α- and β-carbons with the lone electron pair of the hydroxyl radical. Moreover, quantum chemical calculations were carried out on selected GSH/OH(• complexes and on appropriate GSH conformers to describe the energy profile of the recognition process. The relative enthalpy and the free energy changes of the radical recognition of the strongest complexes varied from -42.4 to -27.8 kJ/mol and from -21.3 to 9.8 kJ/mol, respectively. These complexes, containing two or more intermolecular interactions, would be the starting configurations for the hydrogen atom migration to quench the hydroxyl radical via different reaction channels.

A new selective developmental deficit: Impaired object recognition with normal face recognition.

Science.gov (United States)

Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley

2011-05-01

Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual

Influence of color word availability on the Stroop color-naming effect.

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Kim, Hyosun; Cho, Yang Seok; Yamaguchi, Motonori; Proctor, Robert W

2008-11-01

Three experiments tested whether the Stroop color-naming effect is a consequence of word recognition's being automatic or of the color word's capturing visual attention. In Experiment 1, a color bar was presented at fixation as the color carrier, with color and neutral words presented in locations above or below the color bar; Experiment 2 was similar, except that the color carrier could occur in one of the peripheral locations and the color word at fixation. The Stroop effect increased as display duration increased, and the Stroop dilution effect (a reduced Stroop effect when a neutral word is also present) was an approximately constant proportion of the Stroop effect at all display durations, regardless of whether the color bar or color word was at fixation. In Experiment 3, the interval between the onsets of the to-be-named color and the color word was manipulated. The Stroop effect decreased with increasing delay of the color word onset, but the absolute amount of Stroop dilution produced by the neutral word increased. This study's results imply that an attention shift from the color carrier to the color word is an important factor modulating the size of the Stroop effect.

Merger and Centralisation : can We be Big AND Good

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Bill Simpson

2005-11-01

Full Text Available The merger of the Victoria University of Manchester and UMIST in 2004 to create Britain’s largest university (though the achievement of world-class status rather than mere size was the real objective of the merger raised a range of parallel issues for the libraries of the two universities and for the Manchester Business School (MBS Library, which had previously operated independently, but was also merged into the new University Library. The first issue was the name of the new library and here the shift was so subtle that few people notice it until it is pointed out to them. If the “John Rylands University Library, The University of Manchester” seems hardly to differ from the “John Rylands University Library of Manchester” (the name of the former Victoria University of Manchester’s Library, this is because the Rylands name already has global brand recognition and it would have been foolish to risk a major name change that might have put that recognition at risk. It was a case of subtly shifting the emphasis of the name to reflect the fact that we are a new entity whilst not creating confusion in relation to our great historic collections.

What's in a Name

Science.gov (United States)

Bush, Sarah B.; Albanese, Judith; Karp, Karen S.

2016-01-01

Historically, some baby names have been more popular during a specific time span, whereas other names are considered timeless. The Internet article, "How to Tell Someone's Age When All You Know Is Her Name" (Silver and McCann 2014), describes the phenomenon of the rise and fall of name popularity, which served as a catalyst for the…

UMass at TREC WEB 2014: Entity Query Feature Expansion using Knowledge Base Links

Science.gov (United States)

2014-11-01

task on the category A subset and demonstrate the benefit of entity-centric approaches even for non-entity queries like “dark chocolate health benefits ...category A subset and demonstrate the benefit of entity-centric approaches even for non-entity queries like ???dark chocolate health benefits ???. 15...rogers 289 benefits of yoga Model MAP ERR@20 NDCG@20 SDM 4.18 9.15 12.61 WikiRM1 4.00 9.31 12.80 SDM-RM3 3.53 7.61 11.00 EQFE 4.67 10.00 14.61 (a) Results

Entity information life cycle for big data master data management and information integration

CERN Document Server

Talburt, John R

2015-01-01

Entity Information Life Cycle for Big Data walks you through the ins and outs of managing entity information so you can successfully achieve master data management (MDM) in the era of big data. This book explains big data's impact on MDM and the critical role of entity information management system (EIMS) in successful MDM. Expert authors Dr. John R. Talburt and Dr. Yinle Zhou provide a thorough background in the principles of managing the entity information life cycle and provide practical tips and techniques for implementing an EIMS, strategies for exploiting distributed processing to hand