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Sample records for noun representation based

  1. Translation of Japanese Noun Compounds at Super-Function Based MT System

    Science.gov (United States)

    Zhao, Xin; Ren, Fuji; Kuroiwa, Shingo

    Noun compounds are frequently encountered construction in nature language processing (NLP), consisting of a sequence of two or more nouns which functions syntactically as one noun. The translation of noun compounds has become a major issue in Machine Translation (MT) due to their frequency of occurrence and high productivity. In our previous studies on Super-Function Based Machine Translation (SFBMT), we have found that noun compounds are very frequently used and difficult to be translated correctly, the overgeneration of noun compounds can be dangerous as it may introduce ambiguity in the translation. In this paper, we discuss the challenges in handling Japanese noun compounds in an SFBMT system, we present a shallow method for translating noun compounds by using a word level translation dictionary and target language monolingual corpus.

  2. Rule-based Approach on Extraction of Malay Compound Nouns in Standard Malay Document

    Science.gov (United States)

    Abu Bakar, Zamri; Kamal Ismail, Normaly; Rawi, Mohd Izani Mohamed

    2017-08-01

    Malay compound noun is defined as a form of words that exists when two or more words are combined into a single syntax and it gives a specific meaning. Compound noun acts as one unit and it is spelled separately unless an established compound noun is written closely from two words. The basic characteristics of compound noun can be seen in the Malay sentences which are the frequency of that word in the text itself. Thus, this extraction of compound nouns is significant for the following research which is text summarization, grammar checker, sentiments analysis, machine translation and word categorization. There are many research efforts that have been proposed in extracting Malay compound noun using linguistic approaches. Most of the existing methods were done on the extraction of bi-gram noun+noun compound. However, the result still produces some problems as to give a better result. This paper explores a linguistic method for extracting compound Noun from stand Malay corpus. A standard dataset are used to provide a common platform for evaluating research on the recognition of compound Nouns in Malay sentences. Therefore, an improvement for the effectiveness of the compound noun extraction is needed because the result can be compromised. Thus, this study proposed a modification of linguistic approach in order to enhance the extraction of compound nouns processing. Several pre-processing steps are involved including normalization, tokenization and tagging. The first step that uses the linguistic approach in this study is Part-of-Speech (POS) tagging. Finally, we describe several rules-based and modify the rules to get the most relevant relation between the first word and the second word in order to assist us in solving of the problems. The effectiveness of the relations used in our study can be measured using recall, precision and F1-score techniques. The comparison of the baseline values is very essential because it can provide whether there has been an improvement

  3. ABSTRACT NOUNS IN THE SPEECH OF THE EMGLISHMEN (BASED ON FICTION WORKS AND BRITISH NATIONAL CORPUS

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    Natalia Veniaminovna Khokhlova

    2015-01-01

    Full Text Available The research aimed at studying the use of abstract nouns in the Englishmen’s speech from the standpoint of sociolinguistics. The article introduces a new, sociolinguistic, approach to research of abstract nouns; it is also the first time they are studied in a language corpus. The first stage of the research was based on fiction literary works: abstract nouns were extracted of analysis from the statements of the characters belonging to the opposite social classes. Later, these data was compared with the results of the original corpus research based on the British national corpus: sentences with nouns were selected out of the conversational subcorpus of BNC and were further sorted into abstract, concrete and words denoting people. Then, their frequency and vocabulary was studied with regards to speakers’ age, gender and social standing. The results revealed that abstract words are used more often that concrete ones regardless of the speaker’s social characteristics, however, the size and content of vocabulary is different (it is generally more substantial in the speech of women and representatives of higher social classes. The results of this research can be used in elaborating a course of the English language or in teaching general linguistics, sociolinguistics and country studies. 

  4. Count Nouns - Mass Nouns, Neat Nouns - Mess Nouns

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    Fred Landman

    2010-12-01

    Full Text Available In this paper I propose and formalize a theory of the mass-count distinction in which the denotations of count nouns are built from non-overlapping generators, while the denotations of mass nouns are built from overlapping generators. Counting is counting of generators, and it will follow that counting is only correct on count denotations. I will show that the theory allows two kinds of mass nouns: mess mass nouns with denotations built from overlapping minimal generators, and neat mass nouns with denotations built from overlapping generators, where the overlap is not located in the minimal generators. Prototypical mass nouns like meat and mud are of the first kind. I will argue that mass nouns like furniture and kitchenware are of the second type. I will discuss several phenomena—all involving one way or the other explicitly or implicitly individual classifiers like stuks in Dutch—that show that both distinctions mass/count and mess/neat are linguistically robust. I will show in particular that nouns like kitchenware pattern in various ways like count nouns, and not like mess mass nouns, and that these ways naturally involve the neat structure of their denotation. I will also show that they are real mass nouns: they can involve measures in the way mess mass nouns can and count nouns cannot. I will discuss grinding interpretations of count nouns, here rebaptized fission interpretations, and argue that these interpretations differ in crucial ways from the interpretations of lexical mass nouns. The paper will end with a foundational problem raised by fission interpretations, and in the course of this, atomless interpretation domains will re-enter the scene through the back door.ReferencesBarner, D. & Snedeker, J. 2005. ‘Quantity judgements and individuation: evidence that mass nouns count’. Cognition 97: 41–66.http://dx.doi.org/10.1016/j.cognition.2004.06.009PMid:16139586Bunt, H. 1985. Mass Terms and Model Theoretic Semantics. Cambridge

  5. Unpacking Noun-Noun Compounds

    DEFF Research Database (Denmark)

    Smith, Viktor; Barratt, Daniel; Zlatev, Jordan

    2014-01-01

    In two complementary experiments we took an integrated approach to a set of tightly interwoven, yet rarely combined questions concerning the spontaneous interpretation of novel (unfamiliar) noun-noun compounds (NNCs) when encountered in isolation, and possible (re)interpretations of novel as well...... concerning the relations between semantics and pragmatics, as well as system and usage, and psycholinguistic issues concerning the processing of NNCs. New insights and methodological tools are also provided for supporting future best practices in the field of food naming and labelling...

  6. NOUN CLASSIFICATION IN ESAHIE

    African Journals Online (AJOL)

    The present work deals with noun classification in Esahie (Kwa, Niger ... phonological information influences the noun (form) class system of Esahie. ... between noun classes and (grammatical) Gender is interrogated (in the light of ..... the (A) argument6 precedes the verb and the (P) argument7 follows the verb in a simple.

  7. Stereotype or grammar? The representation of gender when two-year-old and three-year-old French-speaking toddlers listen to role nouns.

    Science.gov (United States)

    Lévy, Arik; Gygax, Pascal; Gabriel, Ute; Zesiger, Pascal

    2016-11-01

    Using a preferential looking paradigm, the current study examined the role that grammatical gender plays when preschool French-speaking toddlers process role nouns in the masculine form (e.g., chanteurs masculine 'singers'). While being auditorily prompted with "Look at the 'a role noun'!", two- and three-year-olds were presented with two pictures of two characters ('boy-boy' versus 'girl-boy') with attributes of the given role noun (e.g., singers with microphone and music notes). All role nouns were presented in the masculine plural form, which, despite its use to refer to mixed-gender groups, can be interpreted as referring to men. We expected toddlers to be biased by stereotypes, yet when non-stereotypical role nouns were presented, toddlers were not influenced by grammatical gender, but by their own sex (even more so for three-year-old toddlers). The absence of sensitivity to grammatical cues for either age group is discussed in terms of the developmental awareness of grammatical gender.

  8. Learning to categorize verbs and nouns : studies on Dutch

    NARCIS (Netherlands)

    Erkelens, M.A.

    2009-01-01

    Verbs and nouns are elementary notions in linguistics, so the question how children learn to categorize verbs and nouns in their first language is an intriguing one. Children not only have to learn to identify verbs and nouns as belonging to different categories based on perception, they also have

  9. Usage-Based Account of the Acquisition of Liaison: Evidence from Sensitivity to the Singular/Plural Orientation of Nouns

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    Dugua, Celine; Spinelli, Elsa; Chevrot, Jean-Pierre; Fayol, Michel

    2009-01-01

    This study investigates whether children's production and recognition of obligatory liaison sequences in French depend on the singular/plural orientation of nouns. Certain nouns occur more frequently in the plural (e.g., "arbre" "tree"), whereas others are found more often in the singular (e.g., "arc-en-ciel" "rainbow"). In the input, children…

  10. Noun and verb processing in aphasia: Behavioural profiles and neural correlates

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    Reem S.W. Alyahya

    Full Text Available The behavioural and neural processes underpinning different word classes, particularly nouns and verbs, have been a long-standing area of interest in psycholinguistic, neuropsychology and aphasiology research. This topic has theoretical implications concerning the organisation of the language system, as well as clinical consequences related to the management of patients with language deficits. Research findings, however, have diverged widely, which might, in part, reflect methodological differences, particularly related to controlling the psycholinguistic variations between nouns and verbs. The first aim of this study, therefore, was to develop a set of neuropsychological tests that assessed single-word production and comprehension with a matched set of nouns and verbs. Secondly, the behavioural profiles and neural correlates of noun and verb processing were explored, based on these novel tests, in a relatively large cohort of 48 patients with chronic post-stroke aphasia. A data-driven approach, principal component analysis (PCA, was also used to determine how noun and verb production and comprehension were related to the patients' underlying fundamental language domains. The results revealed no performance differences between noun and verb production and comprehension once matched on multiple psycholinguistic features including, most critically, imageability. Interestingly, the noun-verb differences found in previous studies were replicated in this study once un-matched materials were used. Lesion-symptom mapping revealed overlapping neural correlates of noun and verb processing along left temporal and parietal regions. These findings support the view that the neural representation of noun and verb processing at single-word level are jointly-supported by distributed cortical regions. The PCA generated five fundamental language and cognitive components of aphasia: phonological production, phonological recognition, semantics, fluency, and

  11. Grammatical-gender effects in noun-noun compound production: Evidence from German.

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    Lorenz, Antje; Mädebach, Andreas; Jescheniak, Jörg D

    2018-05-01

    We examined how noun-noun compounds and their syntactic properties are lexically stored and processed in speech production. Using gender-marked determiner primes ( der masc , die fem , das neut [the]) in a picture naming task, we tested for specific effects from determiners congruent with either the modifier or the head of the compound target (e.g., Tee masc kanne fem [teapot]) to examine whether the constituents are processed independently at the syntactic level. Experiment 1 assessed effects of auditory gender-marked determiner primes in bare noun picture naming, and Experiment 2 assessed effects of visual gender-marked determiner primes in determiner-noun picture naming. Three prime conditions were implemented: (a) head-congruent determiner (e.g., die fem ), (b) modifier-congruent determiner (e.g., der masc ), and (c) incongruent determiner (e.g., das neuter ). We observed a facilitation effect of head congruency but no effect of modifier congruency. In Experiment 3, participants produced novel noun-noun compounds in response to two pictures, demanding independent processing of head and modifier at the syntactic level. Now, head and modifier congruency effects were obtained, demonstrating the general sensitivity of our task. Our data support the notion of a single-lemma representation of lexically stored compound nouns in the German production lexicon.

  12. Recently learned foreign abstract and concrete nouns are represented in distinct cortical networks similar to the native language.

    Science.gov (United States)

    Mayer, Katja M; Macedonia, Manuela; von Kriegstein, Katharina

    2017-09-01

    In the native language, abstract and concrete nouns are represented in distinct areas of the cerebral cortex. Currently, it is unknown whether this is also the case for abstract and concrete nouns of a foreign language. Here, we taught adult native speakers of German 45 abstract and 45 concrete nouns of a foreign language. After learning the nouns for 5 days, participants performed a vocabulary translation task during functional magnetic resonance imaging. Translating abstract nouns in contrast to concrete nouns elicited responses in regions that are also responsive to abstract nouns in the native language: the left inferior frontal gyrus and the left middle and superior temporal gyri. Concrete nouns elicited larger responses in the angular gyri bilaterally and the left parahippocampal gyrus than abstract nouns. The cluster in the left angular gyrus showed psychophysiological interaction (PPI) with the left lingual gyrus. The left parahippocampal gyrus showed PPI with the posterior cingulate cortex. Similar regions have been previously found for concrete nouns in the native language. The results reveal similarities in the cortical representation of foreign language nouns with the representation of native language nouns that already occur after 5 days of vocabulary learning. Furthermore, we showed that verbal and enriched learning methods were equally suitable to teach foreign abstract and concrete nouns. Hum Brain Mapp 38:4398-4412, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  13. Designing a noun guesser for part of speech tagging in Northern ...

    African Journals Online (AJOL)

    AFRICAN JOURNALS ONLINE (AJOL) · Journals · Advanced Search · USING ... used to recognize nouns that are not contained in the noun lexicon of the system. ... Our implementation is a symbolic, voting-based process: together, all tests ...

  14. Are French -ité Suffixed Nouns Property Nouns?

    OpenAIRE

    Koehl, Aurore

    2008-01-01

    International audience; The aim of this paper is to analyse French deadjectival –ité nouns construction (AitéN), from a lexematic point of view. –ité nouns are the most frequent deadjectival nouns stored in French dictionaries. Most of the time, these nouns are analysed as denoting properties. The present analysis will show that it is not always the case. We propose here a study conducted on 499 AitéN coined on denominal adjectives. We will make use of both syntactic and semantic adjectival p...

  15. On flexible and rigid nouns

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    2008-01-01

    Studies in Language 32-3 (2008), 727-752. Special issue: Parts of Speech: Descriptive tools, theoretical constructs Jan Rijkhoff - On flexible and rigid nouns This article argues that in addition to the flexible lexical categories in Hengeveld’s classification of parts-of-speech systems (Contentive......, Non-Verb, Modifier), there are also flexible word classes within the rigid lexical category Noun (Set Noun, Sort Noun, General Noun). Members of flexible word classes are characterized by their vague semantics, which in the case of nouns means that values for the semantic features Shape...... and Homogeneity are either left undetermined or they are specified in such a way that they do not quite match the properties of the kind of entity denoted by the flexible item in the external world. I will then argue that flexible word classes constitute a proper category (i.e. they are not the result of a merger...

  16. Exploration of solids based on representation systems

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    Publio Suárez Sotomonte

    2011-01-01

    Full Text Available This article refers to some of the findings of a research project implemented as a teaching strategy to generate environments for the learning of platonic and archimedean solids, with a group of eighth grade students. This strategy was based on the meaningful learning approach and on the use of representation systems using the ontosemiotic approach in mathematical education, as a framework for the construction of mathematical concepts. This geometry teaching strategy adopts the stages of exploration, representation-modeling, formal construction and study of applications. It uses concrete, physical and tangible materials for origami, die making, and structures for the construction of threedimensional solids considered external tangible solid representation systems, as well as computer based educational tools to design dynamic geometry environments as intangible external representation systems.These strategies support both the imagination and internal systems of representation, fundamental to the comprehension of geometry concepts.

  17. On flexible and rigid nouns

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    2010-01-01

    classes. Finally this article wants to claim that the distinction between rigid and flexible noun categories (a) adds a new dimension to current classifications of parts of speech systems, (b) correlates with certain grammatical phenomena (e.g. so-called number discord), and (c) helps to explain the parts......This article argues that in addition to the major flexible lexical categories in Hengeveld’s classification of parts of speech systems (Contentive, Non-Verb, Modifier), there are also flexible word classes within the rigid lexical category Noun (Set Noun, Sort Noun, General Noun). Members...... by the flexible item in the external world. I will then argue that flexible word classes constitute a proper category (i.e. they are not the result of a merger of some rigid word classes) in that members of flexible word categories display the same properties regarding category membership as members of rigid word...

  18. Noun Countability; Count Nouns and Non-count Nouns, What are the Syntactic Differences Between them?

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    Azhar A. Alkazwini

    2016-11-01

    Full Text Available Words that function as the subjects of verbs, objects of verbs or prepositions and which can have a plural form and possessive ending are known as nouns. They are described as referring to persons, places, things, states, or qualities and might also be used as an attributive modifier. In this paper, classes and subclasses of nouns shall be presented, then, noun countability branching into count and non-count nous shall be discussed. A number of present examples illustrating differences between count and non-count nouns and this includes determiner-head-co-occurrence restrictions of number, subject-verb agreement, in addition to some exceptions to this agreement rule shall be discussed. Also, the lexically inherent number in nouns and how inherently plural nouns are classified in terms of (+/- count are illustrated. This research will discuss partitive construction of count and non-count nouns, nouns as attributive modifier and, finally, conclude with the fact that there are syntactic difference between count and non-count in the English Language.

  19. Representations of space based on haptic input

    NARCIS (Netherlands)

    Zuidhoek, S.

    2005-01-01

    The present thesis focused on the representations of grasping space based on haptic input. We aimed at identifying their characteristics, and the underlying neurocognitive processes and mechanisms. To this end, we studied the systematic distortions in performance on several orientation perception

  20. Group representations, error bases and quantum codes

    Energy Technology Data Exchange (ETDEWEB)

    Knill, E

    1996-01-01

    This report continues the discussion of unitary error bases and quantum codes. Nice error bases are characterized in terms of the existence of certain characters in a group. A general construction for error bases which are non-abelian over the center is given. The method for obtaining codes due to Calderbank et al. is generalized and expressed purely in representation theoretic terms. The significance of the inertia subgroup both for constructing codes and obtaining the set of transversally implementable operations is demonstrated.

  1. Noun morphophonemics and noun class restructuring: The case of ...

    African Journals Online (AJOL)

    The article seeks to address the plural forms of class 11/10 nouns in Meru dialects. These are Bantu dialects spoken in the eastern province of Kenya. The dialects build the plural forms in this class in various ways. Sometimes the entire word is treated as a root and in other cases the word is considered to have two parts: a ...

  2. Multi-representation based on scientific investigation for enhancing students’ representation skills

    Science.gov (United States)

    Siswanto, J.; Susantini, E.; Jatmiko, B.

    2018-03-01

    This research aims to implementation learning physics with multi-representation based on the scientific investigation for enhancing students’ representation skills, especially on the magnetic field subject. The research design is one group pretest-posttest. This research was conducted in the department of mathematics education, Universitas PGRI Semarang, with the sample is students of class 2F who take basic physics courses. The data were obtained by representation skills test and documentation of multi-representation worksheet. The Results show gain analysis value of .64 which means some medium improvements. The result of t-test (α = .05) is shows p-value = .001. This learning significantly improves students representation skills.

  3. A proposal of methodology for automatic indexation using noun phrases

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    Renato Rocha Souza

    2006-07-01

    Full Text Available It can be noticed that the indexing and representation strategies nowadays seems to be near the exhaustion, and it is worth to investigate new approaches to the indexing and information retrieving systems. Among these, a branch tries to consider the intrinsic semantics of the textual documents using noun phrases as descriptors instead of single keywords. We present in this article a methodology that was developed in the scope of a doctorate research.

  4. Problem of the Classification of Quantitative Noun in the German Language

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    Elvira L. Shubina

    2015-01-01

    Full Text Available This work is dedicated to the semantic classification of quantitative noun on the basis of a structural study (Nquant + (Adj +N (ein Glas frisches Wasser, since this model reveals the greatest variety of grammatical formulation. These word combinations can form by the genitive government eine Tasse starken Kaffees by the grammatical agreement ein Eimer kaltes Wasser, or by the adjunction mit einem Korb reife Apfel. The suggested classification of the noun performing the function of the first components is based on the form of the noun acting as the first component. Types of the first components fall into three groups: 1. The nouns, which specify quantitative characteristics of objects and substances. Two subgroups are also distingshed: word combinations with a noun in a singular form Nquant1a as the second component and word combinations with a noun in a plural form as the second component Nquant1b; 2. The nouns defining a group of living beings and objects Nquant2; 3. The nouns which formation is grounded on quantitative nouns Nquant3. Normative recommendations on the choice of subordinate connection type should be connected at least at the present stage of existence of German literary language, exactly with the semantics of the nouns which are the first components in these word combinations. The article illustrates that all types of constructions (organizes whether on the basis of government, agreement and or adjunction are connected with the completely specific semantic characteristics of the name, i.e., these nouns belong to one of three groups of noun - first components.

  5. Volta-Based Cells Materials Chemical Multiple Representation to Improve Ability of Student Representation

    Science.gov (United States)

    Helsy, I.; Maryamah; Farida, I.; Ramdhani, M. A.

    2017-09-01

    This study aimed to describe the application of teaching materials, analyze the increase in the ability of students to connect the three levels of representation and student responses after application of multiple representations based teaching materials chemistry. The method used quasi one-group pretest-posttest design to 71 students. The results showed the application of teaching materials carried 88% with very good category. A significant increase ability to connect the three levels of representation of students after the application of multiple representations based teaching materials chemistry with t-value > t-crit (11.402 > 1.991). Recapitulation N-gain pretest and posttest showed relatively similar for all groups is 0.6 criterion being achievement. Students gave a positive response to the application of multiple representations based teaching materials chemistry. Students agree teaching materials used in teaching chemistry (88%), and agrees teaching materials to provide convenience in connecting the three levels of representation (95%).

  6. Nouns and verbs in the vocabulary acquisition of Italian children.

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    D'Odorico, Laura; Fasolo, Mirco

    2007-11-01

    The vocabulary development of 24 Italian children aged between 1;4 and 1;6 at the beginning of the study was longitudinally monitored on a monthly basis using the Italian version of the MacArthur Communicative Development Inventory drawn up by their mothers. This study analyzes data from children for whom two sampling stages were available; the first corresponding to a vocabulary size as close as possible to 200 words (mean 217, range 167-281), the second to a vocabulary size ranging from 400 to 650 words (mean 518, range 416-648). The children's vocabulary composition was analyzed by calculating, for each sampling stage, the percentage of common nouns, verbs and closed-class words. The increase in percentage points of the various lexical items between the first and second sampling stages was also analyzed. Data confirmed the predominance of nouns over verbs and closed-class words at both sampling stages, while verbs and closed-class words showed a higher percentage increase than nouns. The results provide evidence that children who reached the first sampling point at an earlier age had a higher percentage of nouns than children who reached the same stage at an older age. However, in the passage from the first to the second sampling point no relationship emerged between a style of acquisition based on the acquisition of nouns and an increase in the rate of vocabulary growth.

  7. Nouns referring to tools and natural objects differentially modulate the motor system.

    Science.gov (United States)

    Gough, Patricia M; Riggio, Lucia; Chersi, Fabian; Sato, Marc; Fogassi, Leonardo; Buccino, Giovanni

    2012-01-01

    While increasing evidence points to a critical role for the motor system in language processing, the focus of previous work has been on the linguistic category of verbs. Here we tested whether nouns are effective in modulating the motor system and further whether different kinds of nouns - those referring to artifacts or natural items, and items that are graspable or ungraspable - would differentially modulate the system. A Transcranial Magnetic Stimulation (TMS) study was carried out to compare modulation of the motor system when subjects read nouns referring to objects which are Artificial or Natural and which are Graspable or Ungraspable. TMS was applied to the primary motor cortex representation of the first dorsal interosseous (FDI) muscle of the right hand at 150 ms after noun presentation. Analyses of Motor Evoked Potentials (MEPs) revealed that across the duration of the task, nouns referring to graspable artifacts (tools) were associated with significantly greater MEP areas. Analyses of the initial presentation of items revealed a main effect of graspability. The findings are in line with an embodied view of nouns, with MEP measures modulated according to whether nouns referred to natural objects or artifacts (tools), confirming tools as a special class of items in motor terms. Additionally our data support a difference for graspable versus non graspable objects, an effect which for natural objects is restricted to initial presentation of items. Copyright © 2011 Elsevier Ltd. All rights reserved.

  8. OVERGENERALIZATION IN SINGULAR/PLURAL NOUNS AND SUFFIXED NOUNS OF IELTS COURSE STUDENTS

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    Gharizi Matiini

    2016-12-01

    Full Text Available This study aims to investigate the morphological overgeneralization of IELTS students. It focuses on the singular/plural nouns and suffixed nouns that are overgeneralized by those students. Three students are chosen as the participants of the study by collecting their writing exercises. Three writing texts are gathered taken from several weeks and materials. The writings are analyzed by sorting the nouns they produced and categorizing them according to the singular/plural nouns and suffixed nouns. The results reveal that the students over extended the rules of singular/plural nouns and suffixed nouns. However, recovery occurs very varied in both singular/plural nouns and suffixed nouns. They tend to be better in mentioning singular/plural nouns, yet they are being selective and careful in writing suffixed nouns. In conclusion, even though the language learners can mark their overgeneralization, it is still difficult for them to recover their errors. It is recommended here that longitudinal study that has more time to examine students recovery from overgeneralization can be conducted for the further study to give more detail evidence in students’ overgeneralizations. Keywords: overgeneralization, singular/plural nouns, suffixed nouns

  9. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    International Nuclear Information System (INIS)

    Chang, Heyou; Zheng, Hao

    2017-01-01

    Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)

  10. Nouns in apposition : Portuguese data

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    Graça Rio-Torto

    2013-01-01

    Full Text Available The nature of N1N2 constructions, or nouns in apposition, is controversial: depending on the theoretical framework, they can be considered as compounds or as syntactic constructions. Indeed, nouns in apposition function as a hybrid category, in a double way: (i the same lexical structure in apposition is viewed either as a coordinative construction, as a subordinative or as an attributive construction. (ii N2 functions as a modifier or as an attributive item of N1; in Portuguese, when plural is syntactically mandatory, N1 (the head is systematically pluralized; N2 either rejects inflection or behaves as a predicator, allowing inflectional marks. We claim that Romance NN behave as a specific type of compounds. This assumption is grounded on their behaviour by contrast with phrasal properties. Portuguese compounds are characterized by a narrow relationship between internal structure, headness and inflectional patterns. In Portuguese, by default, the head of compound is inflected. NN related by an attributive semantic link are nowadays particularly unstable and problematic regarding inflection. Inflectional variation — widely attested — helps in determining the status of NN in apposition: as two inflectional patterns are available, we must verify if they correspond to two different constructions or to one structure with two readings. The analysis addressed is supported by empirical data of contemporary Portuguese language extracted from Brazilian and European databases, and requires the theoretical articulation of a double predicative class of N2 (holistic and partitive with inflectional fluctuation of attributive N2 in the second situation: performing a continuum, double inflection is close to holistic predication and single inflection (of N1 is close to partitive predication; systematic double inflection is close to coordination and inflectional oscillation is close to attribution. The predicative power of nouns in apposition supports their

  11. THE COMMON AND PROPER NOUNS BETWEEN ALBANIAN AND ENGLISH

    OpenAIRE

    Shkelqim Millaku

    2017-01-01

    The noun in Albanian language classified as common and proper. The common nouns in turn divide into countable and uncountable. Collective nouns and substance nouns are subclasses of the other classes. The structure of noun formation between Albanian and English on the general aspect of morphology and syntax still didn’t study in the way of comparative, contrast and generative. Those fields are our object of study. In Albanian and English we find some concepts of studies for noun for exam...

  12. An Analysis of Noun Definition in Cantonese

    Science.gov (United States)

    To, Carol Kit Sum; Stokes, Stephanie; Man, Yonnie; T'Sou, Benjamin

    2013-01-01

    This study investigated the noun definitions given by Cantonese speakers at different ages. Definitional responses on six concrete nouns from 1075 children aged 4;10 to 12;01 and 15 adults were analyzed with reference to the semantic content and the syntactic form. Results showed that conventional definitions produced by Cantonese adult speakers…

  13. Explaining word order in the noun phrase

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    1990-01-01

    This article argues that word order in the noun phrase is largely determined by three iconic principles of constituent ordering. The patterns that these principles predict for simple noun phrases are tested against data from various existing samples. It appears that the predicted patterns are all...

  14. Layers of root nouns in Germanic

    DEFF Research Database (Denmark)

    Hansen, Bjarne Simmelkjær Sandgaard

    2017-01-01

    The root-noun declension became productive in early Germanic, containing (I) inherited root nouns, (IIa) original substrate or loan words, and transitions from other declensions in (IIb) Proto-Germanic and (III) North Germanic. As ablaut was abolished, the inherited type would display ablaut grades...

  15. Value representations: a value based dialogue tool

    DEFF Research Database (Denmark)

    Petersen, Marianne Graves; Rasmussen, Majken Kirkegaard

    2011-01-01

    Stereotypic presumptions about gender affect the design process, both in relation to how users are understood and how products are designed. As a way to decrease the influence of stereotypic presumptions in design process, we propose not to disregard the aspect of gender in the design process......, as the perspective brings valuable insights on different approaches to technology, but instead to view gender through a value lens. Contributing to this perspective, we have developed Value Representations as a design-oriented instrument for staging a reflective dialogue with users. Value Representations...

  16. Representation

    National Research Council Canada - National Science Library

    Little, Daniel

    2006-01-01

    ...). The reason this is so is due to hierarchies that we take for granted. By hierarchies I mean that there is a layer of representation of us as individuals, as military professional, as members of a military unit and as citizens of an entire nation...

  17. Infants use known verbs to learn novel nouns: evidence from 15- and 19-month-olds.

    Science.gov (United States)

    Ferguson, Brock; Graf, Eileen; Waxman, Sandra R

    2014-04-01

    Fluent speakers' representations of verbs include semantic knowledge about the nouns that can serve as their arguments. These "selectional restrictions" of a verb can in principle be recruited to learn the meaning of a novel noun. For example, the sentence He ate the carambola licenses the inference that carambola refers to something edible. We ask whether 15- and 19-month-old infants can recruit their nascent verb lexicon to identify the referents of novel nouns that appear as the verbs' subjects. We compared infants' interpretation of a novel noun (e.g., the dax) in two conditions: one in which dax is presented as the subject of animate-selecting construction (e.g., The dax is crying), and the other in which dax is the subject of an animacy-neutral construction (e.g., The dax is right here). Results indicate that by 19months, infants use their representations of known verbs to inform the meaning of a novel noun that appears as its argument. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Representation

    Science.gov (United States)

    2006-09-01

    two weeks to arrive. Source: http://beergame.mit.edu/ Permission Granted – MIT Supply Chain Forum 2005 Professor Sterman –Sloan School of...Management - MITSource: http://web.mit.edu/jsterman/www/ SDG /beergame.html Rules of Engagement The MIT Beer Game Simulation 04-04 Slide Number 10 Professor...Sterman –Sloan School of Management - MITSource: http://web.mit.edu/jsterman/www/ SDG /beergame.html What is the Significance of Representation

  19. Integrating Globality and Locality for Robust Representation Based Classification

    Directory of Open Access Journals (Sweden)

    Zheng Zhang

    2014-01-01

    Full Text Available The representation based classification method (RBCM has shown huge potential for face recognition since it first emerged. Linear regression classification (LRC method and collaborative representation classification (CRC method are two well-known RBCMs. LRC and CRC exploit training samples of each class and all the training samples to represent the testing sample, respectively, and subsequently conduct classification on the basis of the representation residual. LRC method can be viewed as a “locality representation” method because it just uses the training samples of each class to represent the testing sample and it cannot embody the effectiveness of the “globality representation.” On the contrary, it seems that CRC method cannot own the benefit of locality of the general RBCM. Thus we propose to integrate CRC and LRC to perform more robust representation based classification. The experimental results on benchmark face databases substantially demonstrate that the proposed method achieves high classification accuracy.

  20. Neural Representation. A Survey-Based Analysis of the Notion

    Directory of Open Access Journals (Sweden)

    Oscar Vilarroya

    2017-08-01

    Full Text Available The word representation (as in “neural representation”, and many of its related terms, such as to represent, representational and the like, play a central explanatory role in neuroscience literature. For instance, in “place cell” literature, place cells are extensively associated with their role in “the representation of space.” In spite of its extended use, we still lack a clear, universal and widely accepted view on what it means for a nervous system to represent something, on what makes a neural activity a representation, and on what is re-presented. The lack of a theoretical foundation and definition of the notion has not hindered actual research. My aim here is to identify how active scientists use the notion of neural representation, and eventually to list a set of criteria, based on actual use, that can help in distinguishing between genuine or non-genuine neural-representation candidates. In order to attain this objective, I present first the results of a survey of authors within two domains, place-cell and multivariate pattern analysis (MVPA research. Based on the authors’ replies, and on a review of neuroscientific research, I outline a set of common properties that an account of neural representation seems to require. I then apply these properties to assess the use of the notion in two domains of the survey, place-cell and MVPA studies. I conclude by exploring a shift in the notion of representation suggested by recent literature.

  1. Simultaneous Processing of Noun Cue and to-be-Produced Verb in Verb Generation Task: Electromagnetic Evidence

    Directory of Open Access Journals (Sweden)

    Anna V. Butorina

    2017-05-01

    Full Text Available A long-standing but implicit assumption is that words strongly associated with a presented cue are automatically activated in the memory through rapid spread of activation within brain semantic networks. The current study was aimed to provide direct evidence of such rapid access to words’ semantic representations and to investigate its neural sources using magnetoencephalography (MEG and distributed source localization technique. Thirty-three neurotypical subjects underwent the MEG recording during verb generation task, which was to produce verbs related to the presented noun cues. Brain responses evoked by the noun cues were examined while manipulating the strength of association between the noun and the potential verb responses. The strong vs. weak noun-verb association led to a greater noun-related neural response at 250–400 ms after cue onset, and faster verb production. The cortical sources of the differential response were localized in left temporal pole, previously implicated in semantic access, and left ventrolateral prefrontal cortex (VLPFC, thought to subserve controlled semantic retrieval. The strength of the left VLPFC’s response to the nouns with strong verb associates was positively correlated to the speed of verbs production. Our findings empirically validate the theoretical expectation that in case of a strongly connected noun-verb pair, successful access to target verb representation may occur already at the stage of lexico-semantic analysis of the presented noun. Moreover, the MEG results suggest that contrary to the previous conclusion derived from fMRI studies left VLPFC supports selection of the target verb representations, even if they were retrieved from semantic memory rapidly and effortlessly. The discordance between MEG and fMRI findings in verb generation task may stem from different modes of neural activation captured by phase-locked activity in MEG and slow changes of blood-oxygen-level-dependent (BOLD signal

  2. Signal- and Symbol-based Representations in Computer Vision

    DEFF Research Database (Denmark)

    Krüger, Norbert; Felsberg, Michael

    We discuss problems of signal-- and symbol based representations in terms of three dilemmas which are faced in the design of each vision system. Signal- and symbol-based representations are opposite ends of a spectrum of conceivable design decisions caught at opposite sides of the dilemmas. We make...... inherent problems explicit and describe potential design decisions for artificial visual systems to deal with the dilemmas....

  3. EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

    Science.gov (United States)

    Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin

    2018-05-01

    Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  5. Learning word vector representations based on acoustic counts

    OpenAIRE

    Ribeiro, Sam; Watts, Oliver; Yamagishi, Junichi

    2017-01-01

    This paper presents a simple count-based approach to learning word vector representations by leveraging statistics of cooccurrences between text and speech. This type of representation requires two discrete sequences of units defined across modalities. Two possible methods for the discretization of an acoustic signal are presented, which are then applied to fundamental frequency and energy contours of a transcribed corpus of speech, yielding a sequence of textual objects (e.g. words, syllable...

  6. Viewing photos and reading nouns of natural graspable objects similarly modulate motor responses

    Directory of Open Access Journals (Sweden)

    Barbara FM Marino

    2014-12-01

    Full Text Available It is well known that the observation of graspable objects recruits the same motor representations involved in their actual manipulation. Recent evidence suggests that the presentation of nouns referring to graspable objects may exert similar effects. So far, however, it is not clear to what extent the modulation of the motor system during object observation overlaps with that related to noun processing. To address this issue, 2 behavioral experiments were carried out using a go-no go paradigm. Healthy participants were presented with photos and nouns of graspable and non-graspable natural objects. Also scrambled images and pseudowords obtained from the original stimuli were used. At a go-signal onset (150 ms after stimulus presentation participants had to press a key when the stimulus referred to a real object, using their right (Experiment 1 or left (Experiment 2 hand, and refrain from responding when a scrambled image or a pseudoword was presented. Slower responses were found for both photos and nouns of graspable objects as compared to non-graspable objects, independent of the responding hand. These findings suggest that processing seen graspable objects and written nouns referring to graspable objects similarly modulates the motor system.

  7. Part-based deep representation for product tagging and search

    Science.gov (United States)

    Chen, Keqing

    2017-06-01

    Despite previous studies, tagging and indexing the product images remain challenging due to the large inner-class variation of the products. In the traditional methods, the quantized hand-crafted features such as SIFTs are extracted as the representation of the product images, which are not discriminative enough to handle the inner-class variation. For discriminative image representation, this paper firstly presents a novel deep convolutional neural networks (DCNNs) architect true pre-trained on a large-scale general image dataset. Compared to the traditional features, our DCNNs representation is of more discriminative power with fewer dimensions. Moreover, we incorporate the part-based model into the framework to overcome the negative effect of bad alignment and cluttered background and hence the descriptive ability of the deep representation is further enhanced. Finally, we collect and contribute a well-labeled shoe image database, i.e., the TBShoes, on which we apply the part-based deep representation for product image tagging and search, respectively. The experimental results highlight the advantages of the proposed part-based deep representation.

  8. Supervised Filter Learning for Representation Based Face Recognition.

    Directory of Open Access Journals (Sweden)

    Chao Bi

    Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

  9. High-frequency collocations of nouns in research articles across eight disciplines

    Directory of Open Access Journals (Sweden)

    Matthew Peacock

    2012-04-01

    Full Text Available This paper describes a corpus-based analysis of the distribution of the high-frequency collocates of abstract nouns in 320 research articles across eight disciplines: Chemistry, Computer Science, Materials Science, Neuroscience, Economics, Language and Linguistics, Management, and Psychology. Disciplinary variation was also examined – very little previous research seems to have investigated this. The corpus was analysed using WordSmith Tools. The 16 highest-frequency nouns across all eight disciplines were identified, followed by the highest-frequency collocates for each noun. Five disciplines showed over 50% variance from the overall results. Conclusions are that the differing patterns revealed are disciplinary norms and represent standard terminology within the disciplines arising from the topics discussed, research methods, and content of discussions. It is also concluded that the collocations are an important part of the meanings and functions of the nouns, and that this evidence of sharp discipline differences underlines the importance of discipline-specific collocation research.

  10. The representation of knowledge within model-based control systems

    International Nuclear Information System (INIS)

    Weygand, D.P.; Koul, R.

    1987-01-01

    Representation of knowledge in artificially intelligent systems is discussed. Types of knowledge that might need to be represented in AI systems are listed, and include knowledge about objects, events, knowledge about how to do things, and knowledge about what human beings know (meta-knowledge). The use of knowledge in AI systems is discussed in terms of acquiring and retrieving knowledge and reasoning about known facts. Different kinds of reasonings or representations are ghen described with some examples given. These include formal reasoning or logical representation, which is related to mathematical logic, production systems, which are based on the idea of condition-action pairs (production), procedural reasoning, which uses pre-formed plans to solve problems, frames, which provide a structure for representing knowledge in an organized manner, direct analogical representations, which represent knowledge in such a manner that permits some observation without deduction

  11. The representation of knowledge within model-based control systems

    International Nuclear Information System (INIS)

    Weygand, D.P.; Koul, R.

    1987-01-01

    The ability to represent knowledge is often considered essential to build systems with reasoning capabilities. In computer science, a good solution often depends on a good representation. The first step in development of most computer applications is selection of a representation for the input, output, and intermediate results that the program will operate upon. For applications in artificial intelligence, this initial choice of representation is especially important. This is because the possible representational paradigms are diverse and the forcing criteria for the choice are usually not clear in the beginning. Yet, the consequences of an inadequate choice can be devastating in the later state of a project if it is discovered that critical information cannot be encoded within the chosen representational paradigm. Problems arise when designing representational systems to support any kind of Knowledge-Base System, that is a computer system that uses knowledge to perform some task. The general case of knowledge-based systems can be thought of as reasoning agents applying knowledge to achieve goals. Artificial Intelligence (AI) research involves building computer systems to perform tasks of perception and reasoning, as well as storage and retrieval of data. The problem of automatically perceiving large patterns in data is a perceptual task that begins to be important for many expert systems applications. Most of AI research assumes that what needs to be represented is known a priori; an AI researcher's job is just figuring out how to encode the information in the system's data structure and procedures. 10 refs

  12. Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

    Directory of Open Access Journals (Sweden)

    Xiangwei Xing

    2014-01-01

    Full Text Available As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC has attracted much attention in synthetic aperture radar (SAR automatic target recognition (ATR recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA, in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

  13. Noun complement clauses as referential modifiers

    Directory of Open Access Journals (Sweden)

    Carlos de Cuba

    2017-01-01

    Full Text Available A number of recent analyses propose that so-called noun complement clauses should be analyzed as a type of relative clause. In this paper, I present a number of complications for any analysis that equates noun complement clauses to relative clauses, and conclude that this type of analysis is on the wrong track. I present cross-linguistic evidence showing that the syntactic behavior of noun complement clauses does not pattern with relative clauses. Patterns of complementizer choice and complementizer drop as well as patterns involving main clause phenomena and extraction differ in the two constructions, which I argue is unexpected under a relative clause analysis that involves operator movement. Instead I present an alternative analysis in which I propose that the referentiality of a noun complement clause is linked to its syntactic behavior. Following recent work, I claim that referential clauses have a syntactically truncated left-periphery, and this truncation can account for the lack of main clause phenomena in noun complement clauses. I argue that the truncation analysis is also able to accommodate complementizer data patterns more easily than relative clause analyses that appeal to operator movement.

  14. Acquisition of noun derivation in Estonian and Russian L1

    Directory of Open Access Journals (Sweden)

    Reili Argus

    2018-04-01

    Full Text Available Acquisition of derivation is not a well-studied area in first language research and a comparative approach to the acquisition of derivation in different languages doesn’t exist. There is no information on how a child acquires derivation in a language with a rich and regular system of derivational patterns, or in a language where derivation is productive, but the system of derivational patterns is opaque. According to general ideas of complexity in a language, the child should start to use simplex stems first and, only after that, complex ones, that is, complexity should increase in the course of acquisition. Our paper is intended to address these issues, based on longitudinal child data from typologically different languages, Estonian and Russian. The results revealed significant differences in the acquisition of noun derivation in the two languages under observation. The system of noun derivation is acquired at a faster pace in Russian, while Estonian children have far fewer noun derivatives in their speech and they use different derivation suffixes with less regularity. Even so, the so-called building block model may be applied for both languages only partially.

  15. Danish children's acquisition of noun plurals: the role of methodology

    DEFF Research Database (Denmark)

    Kjærbæk, Laila; Basbøll, Hans

    In an earlier study we investigated the development of noun plurals in Danish children aged 0-10 years using a multi method research approach comparing five different data types: 1) lexical data; 2) reported data; 3) naturalistic spontaneous child language input and output; 4) semi-naturalistic/s......In an earlier study we investigated the development of noun plurals in Danish children aged 0-10 years using a multi method research approach comparing five different data types: 1) lexical data; 2) reported data; 3) naturalistic spontaneous child language input and output; 4) semi...... the experimental data and we therefore predict a lower percentage of incorrectly produced PL forms in the semi-naturalistic/semi-experimental than in the experimental data. 3) In the experimental data the children are to produce the PL form of nouns given by the investigator. We expect children to produce a large...... amount of sg. instead of PL forms, either as a repetition of the sg. form given by the investigator or as a PL error form irreguralizing the “Ø” PL marker (pure zero, e.g. sg. mus ‘mouse’ – PL mus ‘mice’). 4) The experimental data is based on a fixed number of specific pre-selected items and we therefore...

  16. Primitive Based Action Representation and Recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan; Krüger, Volker

    2009-01-01

    a sequential and statistical     learning algorithm for   automatic detection of the action primitives and the action grammar   based on these primitives.  We model a set of actions using a   single HMM whose structure is learned incrementally as we observe   new types.   Actions are modeled with sufficient...

  17. Old Romanian pluralized mass and abstract nouns

    Directory of Open Access Journals (Sweden)

    Gabriela Pană Dindelegan

    2017-09-01

    Full Text Available The analysis of a rich old Romanian corpus shows that the ‘pluralization’ of mass and abstract nouns is extremely frequent in old Romanian. The semantic effects of pluralization are similar for mass and abstract nouns, consisting in the creation of denotative and/or connotative semantic variants. Of the plural endings, –uri is specialized for the pluralization of mass nouns in Daco-Romanian. The evolution of the ending –uri illustrates the specific process by which a grammatical (plural morpheme is converted into a lexical morpheme (the so-called ‘lexical plurals’. ‘Lexical plurals’ have isolated occurrences in other Romance languages, but they have not reached the spread and regularity they display in Romanian.

  18. Primitive Based Action Representation and recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan

    The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human-machine i......The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human......-machine interface, entertainment, biomechanics etc. Recent developments in neuroscience suggest that all actions are a compositions of smaller units called primitives. Current works based on primitives for action recognition uses a supervised framework for specifying the primitives. We propose a method to extract...... primitives automatically. These primitives are to be used to generate actions based on certain rules for combining. These rules are expressed as a stochastic context free grammar. A model merging approach is adopted to learn a Hidden Markov Model to t the observed data sequences. The states of the HMM...

  19. Conformal-Based Surface Morphing and Multi-Scale Representation

    Directory of Open Access Journals (Sweden)

    Ka Chun Lam

    2014-05-01

    Full Text Available This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively. Surface morphing refers to the process of interpolating between two geometric shapes, which has been widely applied to estimate or analyze deformations in computer graphics, computer vision and medical imaging. In this work, we propose two geometric models for surface morphing and multi-scale representation for 3D surfaces. The basic idea is to represent a 3D surface by its mean curvature function, H, and conformal factor function λ, which uniquely determine the geometry of the surface according to Riemann surface theory. Once we have the (λ, H parameterization of the surface, post-processing of the surface can be done directly on the conformal parameter domain. In particular, the problem of multi-scale representations of shapes can be reduced to the signal filtering on the λ and H parameters. On the other hand, the surface morphing problem can be transformed to an interpolation process of two sets of (λ, H parameters. We test the proposed algorithms on 3D human face data and MRI-derived brain surfaces. Experimental results show that our proposed methods can effectively obtain multi-scale surface representations and give natural surface morphing results.

  20. A Description Logic Based Knowledge Representation Model for Concept Understanding

    DEFF Research Database (Denmark)

    Badie, Farshad

    2017-01-01

    This research employs Description Logics in order to focus on logical description and analysis of the phenomenon of ‘concept understanding’. The article will deal with a formal-semantic model for figuring out the underlying logical assumptions of ‘concept understanding’ in knowledge representation...... systems. In other words, it attempts to describe a theoretical model for concept understanding and to reflect the phenomenon of ‘concept understanding’ in terminological knowledge representation systems. Finally, it will design an ontology that schemes the structure of concept understanding based...

  1. Smooth Particle Hydrodynamics-based Wind Representation

    Energy Technology Data Exchange (ETDEWEB)

    Prescott, Steven [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hess, Stephen [Idaho National Lab. (INL), Idaho Falls, ID (United States); Lin, Linyu [Idaho National Lab. (INL), Idaho Falls, ID (United States); Sampath, Ram [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-12-01

    As a result of the 2011 accident at the Fukushima Dai-ichi NPP and other operational NPP experience, there is an identified need to better characterize and evaluate the potential impacts of externally generated hazards on NPP safety. Due to the ubiquitous occurrence of high winds around the world and the possible extreme magnitude of the hazard that has been observed, the assessment of the impact of the high-winds hazard has been identified as an important activity by both NPP owner-operators and regulatory authorities. However, recent experience obtained from the conduct of high-winds risk assessments indicates that such activities have been both labor-intensive and expensive to perform. Additionally, the existing suite of methods and tools to conduct such assessments (which were developed decades ago) do not make use of modern computational architectures (e.g., parallel processing, object-oriented programming techniques, or simple user interfaces) or methods (e.g., efficient and robust numerical-solution schemes). As a result, the current suite of methods and tools will rapidly become obsolete. Physics-based 3D simulation methods can provide information to assist in the RISMC PRA methodology. This research is intended to determine what benefits SPH methods could bring to high-winds simulations for the purposes of assessing their potential impact on NPP safety. The initial investigation has determined that SPH can simulate key areas of high-wind events with reasonable accuracy, compared to other methods. Some problems, such as simulation voids, need to be addressed, but possible solutions have been identified and will be tested with continued work. This work also demonstrated that SPH simulations can provide a means for simulating debris movement; however, further investigations into the capability to determine the impact of high winds and the impacts of wind-driven debris that lead to SSC failures need to be done. SPH simulations alone would be limited in size

  2. Human action recognition using trajectory-based representation

    Directory of Open Access Journals (Sweden)

    Haiam A. Abdul-Azim

    2015-07-01

    Full Text Available Recognizing human actions in video sequences has been a challenging problem in the last few years due to its real-world applications. A lot of action representation approaches have been proposed to improve the action recognition performance. Despite the popularity of local features-based approaches together with “Bag-of-Words” model for action representation, it fails to capture adequate spatial or temporal relationships. In an attempt to overcome this problem, a trajectory-based local representation approaches have been proposed to capture the temporal information. This paper introduces an improvement of trajectory-based human action recognition approaches to capture discriminative temporal relationships. In our approach, we extract trajectories by tracking the detected spatio-temporal interest points named “cuboid features” with matching its SIFT descriptors over the consecutive frames. We, also, propose a linking and exploring method to obtain efficient trajectories for motion representation in realistic conditions. Then the volumes around the trajectories’ points are described to represent human actions based on the Bag-of-Words (BOW model. Finally, a support vector machine is used to classify human actions. The effectiveness of the proposed approach was evaluated on three popular datasets (KTH, Weizmann and UCF sports. Experimental results showed that the proposed approach yields considerable performance improvement over the state-of-the-art approaches.

  3. Converting biomolecular modelling data based on an XML representation.

    Science.gov (United States)

    Sun, Yudong; McKeever, Steve

    2008-08-25

    Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language). BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

  4. Towards Web-based representation and processing of health information

    DEFF Research Database (Denmark)

    Gao, S.; Mioc, Darka; Yi, X.L.

    2009-01-01

    facilitated the online processing, mapping and sharing of health information, with the use of HERXML and Open Geospatial Consortium (OGC) services. It brought a new solution in better health data representation and initial exploration of the Web-based processing of health information. Conclusion: The designed......Background: There is great concern within health surveillance, on how to grapple with environmental degradation, rapid urbanization, population mobility and growth. The Internet has emerged as an efficient way to share health information, enabling users to access and understand data....... For the representation of health information through Web-mapping applications, there still lacks a standard format to accommodate all fixed (such as location) and variable (such as age, gender, health outcome, etc) indicators in the representation of health information. Furthermore, net-centric computing has not been...

  5. Video based object representation and classification using multiple covariance matrices.

    Science.gov (United States)

    Zhang, Yurong; Liu, Quan

    2017-01-01

    Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

  6. A Representation System User Interface for Knowledge Base Designers

    OpenAIRE

    Fikes, Richard E.

    1982-01-01

    A major strength of frame-based knowledge representation languages is their ability to provide the knowledge base designer with a concise and intuitively appealing means expression. The claim of intuitive appeal is based on the observation that the object -centered style of description provided by these languages often closely matches a designer's understanding of the domain being modeled and therefore lessens the burden of reformulation involved in developing a formal description. To be effe...

  7. Knowledge representation and knowledge base design for operator advisor system

    International Nuclear Information System (INIS)

    Hangos, K.M.; Sziano, T.; Tapolcai, L.

    1990-01-01

    The problems of knowledge representation, knowledge base handling and design has been described for an Operator Advisor System in the Paks Nuclear Power Plant. The Operator Advisor System is to be implemented as a part of the 5th and 6th unit. The knowledge of the Operator Advisor system is described by a few elementary knowledge items (diagnostic event functions, fault graph, action trees), weighted directed graphs have been found as their common structure. List-type and relational representation of these graphs have been used for the on-line and off-line part of the knowledge base respectively. A uniform data base design and handling has been proposed which consists of a design system, a knowledge base editor and a knowledge base compiler

  8. Noun combination in interlanguage typology effects in complex determiner phrases

    CERN Document Server

    Bongartz, Christiane

    2002-01-01

    This study examines effects of L1 typology on the interlanguage of L2 learners of English. Czech learners use phrasal constructs (the song about love) significantly more often than Chinese learners, who prefer noun+noun compounds (the love song). Determiner properties and the process of noun incorporation systematically relate both options.

  9. Semantic and syntactic forces in noun phrase production

    NARCIS (Netherlands)

    Vigliocco, G.; Lauer, M.; Damian, M.F.; Levelt, W.J.M.

    2002-01-01

    Three experiments investigated semantic and syntactic effects in the production of phrases in Dutch. Bilingual participants were presented with English nouns and were asked to produce an adjective + noun phrase in Dutch including the translation of the noun. In 2 experiments, the authors blocked

  10. DOCUMENT REPRESENTATION FOR CLUSTERING OF SCIENTIFIC ABSTRACTS

    Directory of Open Access Journals (Sweden)

    S. V. Popova

    2014-01-01

    Full Text Available The key issue of the present paper is clustering of narrow-domain short texts, such as scientific abstracts. The work is based on the observations made when improving the performance of key phrase extraction algorithm. An extended stop-words list was used that was built automatically for the purposes of key phrase extraction and gave the possibility for a considerable quality enhancement of the phrases extracted from scientific publications. A description of the stop- words list creation procedure is given. The main objective is to investigate the possibilities to increase the performance and/or speed of clustering by the above-mentioned list of stop-words as well as information about lexeme parts of speech. In the latter case a vocabulary is applied for the document representation, which contains not all the words that occurred in the collection, but only nouns and adjectives or their sequences encountered in the documents. Two base clustering algorithms are applied: k-means and hierarchical clustering (average agglomerative method. The results show that the use of an extended stop-words list and adjective-noun document representation makes it possible to improve the performance and speed of k-means clustering. In a similar case for average agglomerative method a decline in performance quality may be observed. It is shown that the use of adjective-noun sequences for document representation lowers the clustering quality for both algorithms and can be justified only when a considerable reduction of feature space dimensionality is necessary.

  11. A Subdivision-Based Representation for Vector Image Editing.

    Science.gov (United States)

    Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou

    2012-11-01

    Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.

  12. Verb-Noun Collocations in Written Discourse of Iranian EFL Learners

    Directory of Open Access Journals (Sweden)

    Fatemeh Ebrahimi-Bazzaz

    2015-07-01

    Full Text Available When native speakers of English write, they employ both grammatical rules and collocations. Collocations are words that are present in the memory of native speakers as ready-made prefabricated chunks. Non-native speakers who wish to acquire native-like fluency should give appropriate attention to collocations in writing in order not to produce sentences that native speakers may consider odd. The present study tries to explore the use of verb-noun collocations in written discourse of English as foreign language (EFL among Iranian EFL learners from one academic year to the next in Iran. To measure the use of verb-noun collocations in written discourse, there was a 60-minute task of writing story  based on a series of six pictures whereby for each picture, three verb-noun collocations were measured, and nouns were provided to limit the choice of collocations. The results of the statistical analysis of ANOVA for the research question indicated that there was a significant difference in the use of lexical verb-noun collocations in written discourse both between and within the four academic years. The results of a post hoc multiple comparison tests confirmed that the means are significantly different between the first year and the third and fourth years, between the second and the fourth, and between the third and the fourth academic year which indicate substantial development in verb-noun collocation proficiency.  The vital implication is that the learners could use verb-noun collocations in productive skill of writing.

  13. Order-based representation in random networks of cortical neurons.

    Directory of Open Access Journals (Sweden)

    Goded Shahaf

    2008-11-01

    Full Text Available The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen.

  14. An Improved Information Hiding Method Based on Sparse Representation

    Directory of Open Access Journals (Sweden)

    Minghai Yao

    2015-01-01

    Full Text Available A novel biometric authentication information hiding method based on the sparse representation is proposed for enhancing the security of biometric information transmitted in the network. In order to make good use of abundant information of the cover image, the sparse representation method is adopted to exploit the correlation between the cover and biometric images. Thus, the biometric image is divided into two parts. The first part is the reconstructed image, and the other part is the residual image. The biometric authentication image cannot be restored by any one part. The residual image and sparse representation coefficients are embedded into the cover image. Then, for the sake of causing much less attention of attackers, the visual attention mechanism is employed to select embedding location and embedding sequence of secret information. Finally, the reversible watermarking algorithm based on histogram is utilized for embedding the secret information. For verifying the validity of the algorithm, the PolyU multispectral palmprint and the CASIA iris databases are used as biometric information. The experimental results show that the proposed method exhibits good security, invisibility, and high capacity.

  15. Teaching object concepts for XML-based representations.

    Energy Technology Data Exchange (ETDEWEB)

    Kelsey, R. L. (Robert L.)

    2002-01-01

    Students learned about object-oriented design concepts and knowledge representation through the use of a set of toy blocks. The blocks represented a limited and focused domain of knowledge and one that was physical and tangible. The blocks helped the students to better visualize, communicate, and understand the domain of knowledge as well as how to perform object decomposition. The blocks were further abstracted to an engineering design kit for water park design. This helped the students to work on techniques for abstraction and conceptualization. It also led the project from tangible exercises into software and programming exercises. Students employed XML to create object-based knowledge representations and Java to use the represented knowledge. The students developed and implemented software allowing a lay user to design and create their own water slide and then to take a simulated ride on their slide.

  16. EEG source reconstruction evidence for the noun-verb neural dissociation along semantic dimensions.

    Science.gov (United States)

    Zhao, Bin; Dang, Jianwu; Zhang, Gaoyan

    2017-09-17

    One of the long-standing issues in neurolinguistic research is about the neural basis of word representation, concerning whether grammatical classification or semantic difference causes the neural dissociation of brain activity patterns when processing different word categories, especially nouns and verbs. To disentangle this puzzle, four orthogonalized word categories in Chinese: unambiguous nouns (UN), unambiguous verbs (UV), ambiguous words with noun-biased semantics (AN), and ambiguous words with verb-biased semantics (AV) were adopted in an auditory task for recording electroencephalographic (EEG) signals from 128 electrodes on the scalps of twenty-two subjects. With the advanced current density reconstruction (CDR) algorithm and the constraint of standardized low-resolution electromagnetic tomography, the spatiotemporal brain dynamics of word processing were explored with the results that in multiple time periods including P1 (60-90ms), N1 (100-140ms), P200 (150-250ms) and N400 (350-450ms), noun-verb dissociation over the parietal-occipital and frontal-central cortices appeared not only between the UN-UV grammatical classes but also between the grammatically identical but semantically different AN-AV pairs. The apparent semantic dissociation within one grammatical class strongly suggests that the semantic difference rather than grammatical classification could be interpreted as the origin of the noun-verb neural dissociation. Our results also revealed that semantic dissociation occurs from an early stage and repeats in multiple phases, thus supporting a functionally hierarchical word processing mechanism. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  17. Sparse representation based image interpolation with nonlocal autoregressive modeling.

    Science.gov (United States)

    Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

    2013-04-01

    Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

  18. Converting Biomolecular Modelling Data Based on an XML Representation

    Directory of Open Access Journals (Sweden)

    Sun Yudong

    2008-06-01

    Full Text Available Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language. BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

  19. 3D ear identification based on sparse representation.

    Directory of Open Access Journals (Sweden)

    Lin Zhang

    Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

  20. Adaptation of Proper Nouns in Czech-American Periodicals at the End of the 19th Century

    OpenAIRE

    Burdová, Kateřina

    2016-01-01

    The bachelor's thesis focuses on the process of adaptation of proper nouns in chosen periodicals of the end of the 19th century that were published in the USA by Czech immigrants. Based on the analysis of periodicals collected from the Library of the Naprstek Museum of Prague there originated a list of proper nouns that has been studied from various points of view, namely the phonetics and phonology, morphology including the word-class competition (Cedar Rapidský - Cedar Rapids), translatedan...

  1. Video rate morphological processor based on a redundant number representation

    Science.gov (United States)

    Kuczborski, Wojciech; Attikiouzel, Yianni; Crebbin, Gregory A.

    1992-03-01

    This paper presents a video rate morphological processor for automated visual inspection of printed circuit boards, integrated circuit masks, and other complex objects. Inspection algorithms are based on gray-scale mathematical morphology. Hardware complexity of the known methods of real-time implementation of gray-scale morphology--the umbra transform and the threshold decomposition--has prompted us to propose a novel technique which applied an arithmetic system without carrying propagation. After considering several arithmetic systems, a redundant number representation has been selected for implementation. Two options are analyzed here. The first is a pure signed digit number representation (SDNR) with the base of 4. The second option is a combination of the base-2 SDNR (to represent gray levels of images) and the conventional twos complement code (to represent gray levels of structuring elements). Operation principle of the morphological processor is based on the concept of the digit level systolic array. Individual processing units and small memory elements create a pipeline. The memory elements store current image windows (kernels). All operation primitives of processing units apply a unified direction of digit processing: most significant digit first (MSDF). The implementation technology is based on the field programmable gate arrays by Xilinx. This paper justified the rationality of a new approach to logic design, which is the decomposition of Boolean functions instead of Boolean minimization.

  2. Representations of coherent states in non-orthogonal bases

    International Nuclear Information System (INIS)

    Ali, S Twareque; Roknizadeh, R; Tavassoly, M K

    2004-01-01

    Starting with the canonical coherent states, we demonstrate that all the so-called nonlinear coherent states, used in the physical literature, as well as large classes of other generalized coherent states, can be obtained by changes of bases in the underlying Hilbert space. This observation leads to an interesting duality between pairs of generalized coherent states, bringing into play a Gelfand triple of (rigged) Hilbert spaces. Moreover, it is shown that in each dual pair of families of nonlinear coherent states, at least one family is related to a (generally) non-unitary projective representation of the Weyl-Heisenberg group, which can then be thought of as characterizing the dual pair

  3. Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Yidong Tang

    2016-01-01

    Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.

  4. Switching Between Noun and Verb Agreement Rules Comes at a Cost: Cross-Sectional and Interventional Studies in a Developmental Sample

    Directory of Open Access Journals (Sweden)

    Van Reybroeck Marie

    2014-11-01

    Full Text Available This study clarifies the impact of switching context between noun and verb number agreement rules in written language production. In Experiment 1, children from grade 3 to 6 were asked to fill in sentences with nouns and verbs in either a switching condition (noun followed by verb or a repeating condition (noun followed by noun. The results showed that third- and fourth-grade children produced more erroneous agreements in the switching condition than in the repeating condition, showing that switching between rules comes at a cost, whereas fifth- and sixth-grade participants’ performance was not affected by the switching context. Based on these findings, Experiment 2 aimed to assess whether a switching treatment offers a greater opportunity to improve the acquisition of grammatical agreement production, as compared to a simple treatment. Teachers from grade 3 gave either a switching treatment (mixed noun and verb exercises or a simple treatment (noun exercises followed by verb exercises. The results show that children learned better from the switching treatment than from the simple treatment. These findings highlight the cost of switching between noun and verb agreement rules during the acquisition of grammatical number agreement and also how grammatical spelling acquisition can be improved at school.

  5. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

    Directory of Open Access Journals (Sweden)

    Rui Sun

    2016-08-01

    Full Text Available Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

  6. ZHE: [Noun] Undefined--An Interview with Performers Antonia Kemi Coker and Tonderai Munyevu

    Science.gov (United States)

    Shaskan, Victoria

    2013-01-01

    In February 2012, London-based theatre company Collective Artistes previewed "ZHE: [noun] Undefined," a new play created by director Chuck Mike and performers Tonderai Munyevu and Antonia Kemi Coker. The play follows the true life stories of the two performers, both British Africans, living at the intersections of culture, nationality, gender and…

  7. Machine translation of noun phrases from English to Igala using the ...

    African Journals Online (AJOL)

    Due to the structural differences between English and Igala, noun phrases coupled with the non- availability of large amount of parallel aligned corpus for English and Igala language, the rule based technology was adopted to develop the model. The model was implemented using VB.net programming language as front ...

  8. The role of representation in experience-based choice

    Directory of Open Access Journals (Sweden)

    Ben R. Newell

    2009-12-01

    Full Text Available Recently it has been observed that different choices can be made about structurally identical risky decisions depending on whether information about outcomes and their probabilities is learned by description or from experience. Current evidence is equivocal with respect to whether this choice ``gap'' is entirely an artefact of biased samples. The current experiment investigates whether a representational bias exists at the point of encoding by examining choice in light of decision makers' mental representations of the alternatives, measured with both verbal and nonverbal judgment probes. We found that, when estimates were gauged by the nonverbal probe, participants presented with information in description format (as opposed to experience had a greater tendency to overestimate rare events and underestimate common events. The choice gap, however, remained even when accounting for this judgment distortion and the effects of sampling bias. Indeed, participants' estimation of the outcome distribution did not mediate their subsequent choice. It appears that experience-based choices may derive from a process that does not explicitly use probability information.

  9. Effects of Computer-Based Visual Representation on Mathematics Learning and Cognitive Load

    Science.gov (United States)

    Yung, Hsin I.; Paas, Fred

    2015-01-01

    Visual representation has been recognized as a powerful learning tool in many learning domains. Based on the assumption that visual representations can support deeper understanding, we examined the effects of visual representations on learning performance and cognitive load in the domain of mathematics. An experimental condition with visual…

  10. Example-Based Image Colorization Using Locality Consistent Sparse Representation.

    Science.gov (United States)

    Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

    2017-11-01

    Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

  11. Analysis of the Word-Initial Segment with Reference to Lemmatising Zulu Nasal Nouns

    Directory of Open Access Journals (Sweden)

    M.H. Mpungose

    2012-09-01

    Full Text Available

    The process of lemmatising nasal nouns in the Zulu lexicon is problematic. The traditional method is to lemmatise a Zulu lexical noun by etymological noun-stem. This practice creates difficulties in harmonising lexical nouns with their syntactic application. Most authors and dictionary-makers are inconsistent in identifying the word-initial segment which determines the letter of the alphabet under which the lexical noun should be included. Consequently, dictionary users do not find Zulu dictionaries user-friendly. This article therefore proposes the principle of "a noun without initial vowel" as a method for lemmatising Zulu nasal nouns. It concludes that it is not necessary to delve into the derivational history of a lexical noun, but rather to focus on the product of the operation of morphophonological rules. The article also suggests the need to identify the distinctiveness of the segments of a syllable and to acknowledge that identical forms of a segment do occur at different segmental positions (initial, medial and final. Finally it is argued that the Zulu nasal noun class prefix is constructed according to an open syllable pattern defined by a general CV-formula based on a VCV noun prefix open syllable pattern.

    Keywords: adjoined letter; compound; composite; consonant; element; etymological; evolutionary; homorganic; initial; intravowel; lemma; lemmatise; lexical; morphophonological; nasal; noun class prefix; segment; syllable; vowel

     

    Die proses van lemmatisering van nasale naamwoorde in die Zoeloeleksikon is problematies. Die tradisionele metode is om leksikale selfstandige naamwoorde in Zoeloe volgens die etimologiese naamwoordstam te lemmatiseer. Hierdie gebruik veroorsaak moeilikhede by die harmonisering van leksikale selfstandige naamwoorde met hul sintaktiese toepassing. Die meeste outeurs en leksikograwe is inkonsekwent in die identifisering van die woordinisiële segment wat die letter van die alfabet bepaal

  12. Heavy noun phrase constructions in the Afrikaans novel 'n Ander ...

    African Journals Online (AJOL)

    Heavy noun phrase constructions in the Afrikaans novel 'n Ander Land: a cognitive account of a stylistic feature. Luna Beard. Abstract. This article focusses on one grammatical construction, namely heavy noun phrase (NP) constructions in Afrikaans, and more specifically on those instances encountered in the Afrikaans ...

  13. Noun-Verb Ambiguity in Chronic Undifferentiated Schizophrenia

    Science.gov (United States)

    Goldfarb, Robert; Bekker, Natalie

    2009-01-01

    This study investigated noun-verb retrieval patterns of 30 adults with chronic undifferentiated schizophrenia and 67 typical adults, to determine if schizophrenia affected nouns (associated with temporal lobe function) differently from verbs (associated with frontal lobe function). Stimuli were homophonic homographic homonyms, balanced according…

  14. Broohm: Noun Classification in Esahie | Broohm | Ghana Journal of ...

    African Journals Online (AJOL)

    Tano, Kwa, Niger-Congo). It contends that, though the noun class system of Esahie per se is morpho-syntactically vestigial, hence differing from other African languages (e.g. most Bantu languages) where noun classes can be assimilated with ...

  15. Exploring Noun Bias in Filipino-English Bilingual Children

    Science.gov (United States)

    Lucas, Rochelle Irene G.; Bernardo, Allan B. I.

    2008-01-01

    Researchers have suggested that there is a noun bias in children's early vocabularies brought about by features of adults' child-directed utterances, which may vary across languages (E. V. Bates et al., 1994; D. Gentner, 1982). In the present study, the authors explored noun bias in 60 Filipino-English bilingual children whose 2 languages differed…

  16. A robust probabilistic collaborative representation based classification for multimodal biometrics

    Science.gov (United States)

    Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

    2018-04-01

    Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.

  17. Object-Based Benefits without Object-Based Representations

    OpenAIRE

    Alvarez, George Angelo; Fougnie, Daryl; Cormiea, Sarah M

    2012-01-01

    The organization of visual information into objects strongly influences visual memory: Displays with objects defined by two features (e.g. color, orientation) are easier to remember than displays with twice as many objects defined by one feature (Olson & Jiang, 2002). Existing theories suggest that this ‘object-benefit’ is based on object-based limitations in working memory: because a limited number of objects can be stored, packaging features together so that fewer objects have to be remembe...

  18. Knowledge representation to support reasoning based on multiple models

    Science.gov (United States)

    Gillam, April; Seidel, Jorge P.; Parker, Alice C.

    1990-01-01

    Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

  19. The prosody of Swedish underived nouns: No lexical tones required

    Directory of Open Access Journals (Sweden)

    Bruce Morén-Duolljá

    2013-02-01

    Full Text Available This paper provides a detailed representational analysis of the morpho-prosodic system of underived nouns in a dialect of Swedish.  It shows that the morphology, stress and tonal patterns are not as complex as they first appear once the data are looked at in sufficient detail.  Further, it shows that the renowned Swedish "lexical pitch accent" is not the result of lexical tones/tonemes.  Rather, Swedish is like all other languages and uses tones to mark the edges of prosodic constituents on the surface. "Accent 2" occurs when tones mark the edge of a structural uneven trochee (i.e. recursive foot and "accent 1" occurs elsewhere. This analysis is counter all other treatments of North Germanic tones and denies the almost unquestioned assumption that there is an underlying tone specification on roots and/or affixes in many North Germanic varieties. At the same time, it unifies the intuitions behind the three previous approaches found in the literature.

  20. Iceberg Semantics For Count Nouns And Mass Nouns: Classifiers, measures and portions

    Directory of Open Access Journals (Sweden)

    Fred Landman

    2016-12-01

    It is the analysis of complex NPs and their mass-count properties that is the focus of the second part of this paper. There I develop an analysis of English and Dutch pseudo- partitives, in particular, measure phrases like three liters of wine and classifier phrases like three glasses of wine. We will study measure interpretations and classifier interpretations of measures and classifiers, and different types of classifier interpretations: container interpretations, contents interpretations, and - indeed - portion interpretations. Rothstein 2011 argues that classifier interpretations (including portion interpretations of pseudo partitives pattern with count nouns, but that measure interpretations pattern with mass nouns. I will show that this distinction follows from the very basic architecture of Iceberg semantics.

  1. Pedestrian detection from thermal images: A sparse representation based approach

    Science.gov (United States)

    Qi, Bin; John, Vijay; Liu, Zheng; Mita, Seiichi

    2016-05-01

    Pedestrian detection, a key technology in computer vision, plays a paramount role in the applications of advanced driver assistant systems (ADASs) and autonomous vehicles. The objective of pedestrian detection is to identify and locate people in a dynamic environment so that accidents can be avoided. With significant variations introduced by illumination, occlusion, articulated pose, and complex background, pedestrian detection is a challenging task for visual perception. Different from visible images, thermal images are captured and presented with intensity maps based objects' emissivity, and thus have an enhanced spectral range to make human beings perceptible from the cool background. In this study, a sparse representation based approach is proposed for pedestrian detection from thermal images. We first adopted the histogram of sparse code to represent image features and then detect pedestrian with the extracted features in an unimodal and a multimodal framework respectively. In the unimodal framework, two types of dictionaries, i.e. joint dictionary and individual dictionary, are built by learning from prepared training samples. In the multimodal framework, a weighted fusion scheme is proposed to further highlight the contributions from features with higher separability. To validate the proposed approach, experiments were conducted to compare with three widely used features: Haar wavelets (HWs), histogram of oriented gradients (HOG), and histogram of phase congruency (HPC) as well as two classification methods, i.e. AdaBoost and support vector machine (SVM). Experimental results on a publicly available data set demonstrate the superiority of the proposed approach.

  2. Face antispoofing based on frame difference and multilevel representation

    Science.gov (United States)

    Benlamoudi, Azeddine; Aiadi, Kamal Eddine; Ouafi, Abdelkrim; Samai, Djamel; Oussalah, Mourad

    2017-07-01

    Due to advances in technology, today's biometric systems become vulnerable to spoof attacks made by fake faces. These attacks occur when an intruder attempts to fool an established face-based recognition system by presenting a fake face (e.g., print photo or replay attacks) in front of the camera instead of the intruder's genuine face. For this purpose, face antispoofing has become a hot topic in face analysis literature, where several applications with antispoofing task have emerged recently. We propose a solution for distinguishing between real faces and fake ones. Our approach is based on extracting features from the difference between successive frames instead of individual frames. We also used a multilevel representation that divides the frame difference into multiple multiblocks. Different texture descriptors (local binary patterns, local phase quantization, and binarized statistical image features) have then been applied to each block. After the feature extraction step, a Fisher score is applied to sort the features in ascending order according to the associated weights. Finally, a support vector machine is used to differentiate between real and fake faces. We tested our approach on three publicly available databases: CASIA Face Antispoofing database, Replay-Attack database, and MSU Mobile Face Spoofing database. The proposed approach outperforms the other state-of-the-art methods in different media and quality metrics.

  3. The Noun Phrase in Functional Discourse Grammar

    DEFF Research Database (Denmark)

    reintroduce Dik’s idea of Dynamic Term Construction and extend the current ontology of entities. The result would be a more cogent treatment of scope and NP syntax, which does not force the theory to abandon any of its fundamental methodological principles. Evelien Keizer (University of Amsterdam...... can account for NP-internal agreement phenomena, including speech errors, as attested in a large corpus of spoken German. Daniel García Velasco (University of Oviedo) examines the so-called Complex Noun Phrase Constraint within the context of FDG. The existence of restrictions on the displacement......, with regard to both form and content. Daniel García Velasco also wishes to acknowledge the financial support of the Dept. of Anglogermanic and French Studies and the Research Vice-Rectorate of the University of Oviedo....

  4. THE GENDER OF COUNTABLE AND UNCOUNTABLE NOUNS

    OpenAIRE

    Shkelqim Millaku; Xhevahire Topanica

    2016-01-01

    In Albanian and English we have three kinds of gender: masculine, feminine and neuter. In Albanian language we have this concept for gender: “Gjinia është një nga kategoritë gramatikore më karakteristikë për emrat në gjuhën shqipe. Nga natyra e saj, ajo dallohet nga kategoritë e tjera të emrit, nga numri, rasa dhe nga kategoritë e shquarsisë dhe të pashquarsisë, sepse i kundërvihet mashkullore-femërore dhe asnjanëse...”[1], it’s same and with English: “a grouping of nouns and pronouns into c...

  5. Familiarity and Voice Representation: From Acoustic-Based Representation to Voice Averages

    Directory of Open Access Journals (Sweden)

    Maureen Fontaine

    2017-07-01

    Full Text Available The ability to recognize an individual from their voice is a widespread ability with a long evolutionary history. Yet, the perceptual representation of familiar voices is ill-defined. In two experiments, we explored the neuropsychological processes involved in the perception of voice identity. We specifically explored the hypothesis that familiar voices (trained-to-familiar (Experiment 1, and famous voices (Experiment 2 are represented as a whole complex pattern, well approximated by the average of multiple utterances produced by a single speaker. In experiment 1, participants learned three voices over several sessions, and performed a three-alternative forced-choice identification task on original voice samples and several “speaker averages,” created by morphing across varying numbers of different vowels (e.g., [a] and [i] produced by the same speaker. In experiment 2, the same participants performed the same task on voice samples produced by familiar speakers. The two experiments showed that for famous voices, but not for trained-to-familiar voices, identification performance increased and response times decreased as a function of the number of utterances in the averages. This study sheds light on the perceptual representation of familiar voices, and demonstrates the power of average in recognizing familiar voices. The speaker average captures the unique characteristics of a speaker, and thus retains the information essential for recognition; it acts as a prototype of the speaker.

  6. Reference Frame Fields based on Quantum Theory Representations of Real and Complex Numbers

    OpenAIRE

    Benioff, Paul

    2007-01-01

    A quantum theory representations of real (R) and complex (C) numbers is given that is based on states of single, finite strings of qukits for any base k > 1. Both unary representations and the possibility that qukits with k a prime number are elementary and the rest composite are discussed. Cauchy sequences of qukit string states are defined from the arithmetic properties. The representations of R and C, as equivalence classes of these sequences, differ from classical kit string state represe...

  7. A communication-channel-based representation system for software

    NARCIS (Netherlands)

    Demirezen, Zekai; Tanik, Murat M.; Aksit, Mehmet; Skjellum, Anthony

    We observed that before initiating software development the objectives are minimally organized and developers introduce comparatively higher organization throughout the design process. To be able to formally capture this observation, a new communication channel representation system for software is

  8. Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

    Science.gov (United States)

    Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

  9. Volume-based Representation of the Magnetic Field

    CERN Document Server

    Amapane, N; Drollinger, V; Karimäki, V; Klyukhin, V; Todorov, T

    2005-01-01

    Simulation and reconstruction of events in high-energy experiments require the knowledge of the value of the magnetic field at any point within the detector. The way this information is extracted from the actual map of the magnetic field and served to simulation and reconstruction applications has a large impact on accuracy and performance in terms of speed. As an example, the CMS high level trigger performs on-line tracking of muons within the magnet yoke, where the field is discontinuous and largely inhomogeneous. In this case the high level trigger execution time is dominated by the time needed to access the magnetic field map.For this reason, an optimized approach for the access to the CMS field was developed, based on a dedicated representation of thedetector geometry. The detector is modeled in terms of volumes, constructed in such a way that their boundaries correspond to the fiel d discontinuities due to changes in the magnetic permeability of the materials. The field within each volume is therefore c...

  10. Designing electronic module based on learning content development system in fostering students’ multi representation skills

    Science.gov (United States)

    Resita, I.; Ertikanto, C.

    2018-05-01

    This study aims to develop electronic module design based on Learning Content Development System (LCDS) to foster students’ multi representation skills in physics subject material. This study uses research and development method to the product design. This study involves 90 students and 6 physics teachers who were randomly chosen from 3 different Senior High Schools in Lampung Province. The data were collected by using questionnaires and analyzed by using quantitative descriptive method. Based on the data, 95% of the students only use one form of representation in solving physics problems. Representation which is tend to be used by students is symbolic representation. Students are considered to understand the concept of physics if they are able to change from one form to the other forms of representation. Product design of LCDS-based electronic module presents text, image, symbolic, video, and animation representation.

  11. The roles of word-form frequency and phonological neighbourhood density in the acquisition of Lithuanian noun morphology.

    Science.gov (United States)

    Savičiūtė, Eglė; Ambridge, Ben; Pine, Julian M

    2018-05-01

    Four- and five-year-old children took part in an elicited familiar and novel Lithuanian noun production task to test predictions of input-based accounts of the acquisition of inflectional morphology. Two major findings emerged. First, as predicted by input-based accounts, correct production rates were correlated with the input frequency of the target form, and with the phonological neighbourhood density of the noun. Second, the error patterns were not compatible with the systematic substitution of target forms by either (a) the most frequent form of that noun or (b) a single morphosyntactic default form, as might be predicted by naive versions of a constructivist and generativist account, respectively. Rather, most errors reflected near-miss substitutions of singular for plural, masculine for feminine, or nominative/accusative for a less frequent case. Together, these findings provide support for an input-based approach to morphological acquisition, but are not adequately explained by any single account in its current form.

  12. A Knowledge-Based Representation Scheme for Environmental Science Models

    Science.gov (United States)

    Keller, Richard M.; Dungan, Jennifer L.; Lum, Henry, Jr. (Technical Monitor)

    1994-01-01

    One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.

  13. Mathematical Representation Ability by Using Project Based Learning on the Topic of Statistics

    Science.gov (United States)

    Widakdo, W. A.

    2017-09-01

    Seeing the importance of the role of mathematics in everyday life, mastery of the subject areas of mathematics is a must. Representation ability is one of the fundamental ability that used in mathematics to make connection between abstract idea with logical thinking to understanding mathematics. Researcher see the lack of mathematical representation and try to find alternative solution to dolve it by using project based learning. This research use literature study from some books and articles in journals to see the importance of mathematical representation abiliy in mathemtics learning and how project based learning able to increase this mathematical representation ability on the topic of Statistics. The indicators for mathematical representation ability in this research classifies namely visual representation (picture, diagram, graph, or table); symbolize representation (mathematical statement. Mathematical notation, numerical/algebra symbol) and verbal representation (written text). This article explain about why project based learning able to influence student’s mathematical representation by using some theories in cognitive psychology, also showing the example of project based learning that able to use in teaching statistics, one of mathematics topic that very useful to analyze data.

  14. The Intonation of Noun Phrase Subjects and Clause- Modifying ...

    African Journals Online (AJOL)

    FIRST LADY

    Oladipupo, Rotimi O. - Centre for Foundation Education, Bells University of. Technology ... native Englishes, especially at the level of phonology, this study investigates ... Keywords: Intonation tunes, Nigerian English, Noun Phrase Subjects,.

  15. Nicht-referentielle Nominalphrasen (Non-Referential Noun Phrases)

    Science.gov (United States)

    Leys, Odo

    1973-01-01

    Appeared as Working Report No. 21 of the Linguistic Institute of the University of Cologne; critical observations on S. Kuno's Some Properties of Non-Refential Noun Phrases,'' in Studies in General and Oriental Linguistics, 1970. (RS)

  16. LPS: a rule-based, schema-oriented knowledge representation system

    Energy Technology Data Exchange (ETDEWEB)

    Anzai, Y; Mitsuya, Y; Nakajima, S; Ura, S

    1981-01-01

    A new knowledge representation system called LPS is presented. The global control structure of LPS is rule-based, but the local representational structure is schema-oriented. The present version of LPS was designed to increase the understandability of representation while keeping time efficiency reasonable. Pattern matching through slot-networks and meta-actions from among the implemented facilities of LPS, are especially described in detail. 7 references.

  17. Energetic macroscopic representation and inversion-based control of a CVT-based HEV

    NARCIS (Netherlands)

    Chouhou, M.; Grée, F.; Jivan, C.; Bouscayrol, A.; Hofman, T.

    2014-01-01

    A Continuous Variable Transmission (CVT) is introduced in the simulation model of a Hybrid Electric Vehicle (HEV). The CVT-based vehicle simulation and its control are deduced from the Energetic Macroscopic Representation (EMR). Simulations are provided to show the interest of the CVT in term of

  18. Energetic macroscopic representation and inversion- based control of a CVT-based HEV

    NARCIS (Netherlands)

    Chouhou, M.; Grée, F.; Jivan, C.; Bouscayrol, A.; Hofman, T.

    2013-01-01

    A Continuous Variable Transmission (CVT) is introduced in the simulation model of a Hybrid Electric Vehicle (HEV). The CVT-based vehicle simulation and its control are deduced from the Energetic Macroscopic Representation (EMR). Simulations are provided to show the interest of the CVT in term of

  19. Convolution-based classification of audio and symbolic representations of music

    DEFF Research Database (Denmark)

    Velarde, Gissel; Cancino Chacón, Carlos; Meredith, David

    2018-01-01

    We present a novel convolution-based method for classification of audio and symbolic representations of music, which we apply to classification of music by style. Pieces of music are first sampled to pitch–time representations (piano-rolls or spectrograms) and then convolved with a Gaussian filter......-class composer identification, methods specialised for classifying symbolic representations of music are more effective. We also performed experiments on symbolic representations, synthetic audio and two different recordings of The Well-Tempered Clavier by J. S. Bach to study the method’s capacity to distinguish...

  20. Towards a Script-Based Representation Language for Educational Films.

    Science.gov (United States)

    Parkes, Alan P.

    1987-01-01

    Discusses aspects of the syntax and semantics of film, and presents a scenario for the use of film by intelligent computer assisted instruction (ICAI) systems. An outline of a representation language for educational films on videodisc is presented, and an appendix provides conceptual graphs that explain notations used in examples. (Author/LRW)

  1. A Constrained Algorithm Based NMFα for Image Representation

    Directory of Open Access Journals (Sweden)

    Chenxue Yang

    2014-01-01

    Full Text Available Nonnegative matrix factorization (NMF is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.

  2. Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers

    Directory of Open Access Journals (Sweden)

    Ting Shu

    2017-01-01

    Full Text Available At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

  3. The Treatment of Borrowed Nouns in Isichazamazwi SesiNdebele and Isichazamazwi SezoMculo

    Directory of Open Access Journals (Sweden)

    Eventhough Ndlovu

    2011-10-01

    Full Text Available Abstract: This article focuses on the lemmatisation of vowel-commencing borrowed nouns and the allo-cation of borrowed nouns to noun class prefixes in Isichazamazwi SesiNdebele, the first monolingual general-purpose Ndebele dictionary, and Isichazamazwi SezoMculo, the first specialised Ndebele dictionary of musical terms. It adopts a comparative approach, also highlighting the controversies surrounding the status of the initial vowel of the prefix or the pre-prefix in Ndebele and other Nguni languages. It further looks at the challenges and limitations of lemmatising the noun using either the initial vowel of the prefix or the initial letter of the noun stem. It is found that there are some inconsistencies in the lemmatisation of vowel-com-mencing borrowed nouns and the allocation of borrowed nouns to noun class prefixes in the two dictionar-ies. These inconsistencies impact negatively on the standardisation and treatment of borrowed nouns.

  4. A Study on Noun Suffixes: Accounting for the Vernacularisation of English in Late Medieval Medical Texts

    Directory of Open Access Journals (Sweden)

    Begoña Crespo

    2012-01-01

    Full Text Available This paper seeks to contribute to the study of the vernacularisation process in late Middle English by measuring up to what an extent concrete and abstract noun suffixes (in line with Dalton-Puffer 1996 attach to either Germanic or Romance bases in the medical texts extracted from the MEMT (Middle English Medical Texts corpus. The findings obtained have been further described according to text type or genre and to target audience/readership. The description of these suffixes in relation to all the parameters already mentioned has confirmed the predominance of abstract suffixes of Romance origin although Germanic abstract suffixes are also abundant. More hybrid formations have been found with Germanic noun suffixes than with Romance ones which might be indicative of their versatility towards vernacularisation.

  5. Order in the noun phrase of the languages of Europe

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    1998-01-01

    The current investigation of the word order characteristics of the constituents of the noun phrase (NP) differs from other typological investigations of the issue in two major respects. First of all, it does not take for granted the existence of NPs or of the various NP-internal categories...... that it also has noun phrases: it may use a string of appositives rather than a proper, integral NP. The existence of NPs and the presence of various NP-internal categories is not an issue that has received considerable attention in typological word order studies. Yet how can we hope to establish the cross...... in a representative sample of European languages (Appendix 1), we first need to devote some attention to such basic questions as: Do all European languages have nouns? Do all European languages have proper NPs? Which NP-internal modifiers are attested in the European languages, and which are absent? These issues...

  6. Representation of grammatical categories of words in the brain.

    Science.gov (United States)

    Hillis, A E; Caramazza, A

    1995-01-01

    We report the performance of a patient who, as a consequence of left frontal and temporoparietal strokes, makes far more errors on nouns than on verbs in spoken output tasks, but makes far more errors on verbs than on nouns in written input tasks. This double dissociation within a single patient with respect to grammatical category provides evidence for the hypothesis that phonological and orthographic representations of nouns and verbs are processed by independent neural mechanisms. Furthermore, the opposite dissociation in the verbal output modality, an advantage for nouns over verbs in spoken tasks, by a different patient using the same stimuli has also been reported (Caramazza & Hillis, 1991). This double dissociation across patients on the same task indicates that results cannot be ascribed to "greater difficulty" with one type of stimulus, and provides further evidence for the view that grammatical category information is an important organizational principle of lexical knowledge in the brain.

  7. Differential Impairment of Noun and Verb Consequent to LH Lesions in Persian Aphasic Patients

    Directory of Open Access Journals (Sweden)

    Dr. Reza Nilipour

    2003-08-01

    Full Text Available The major focus of this research is on the differential disruption of language abilities subsequent to brain damages as they relate to site and size of lesion, especially left hemisphere lesions which disrupt the production and processing of "Nouns" vs. "Verbs" as two functionally different lexical categories. Several clinical as well as experimental studies reported on different language have shown that nouns and verbs can be independently disrupted due to brain damage. A prevalent impairment in naming actions (Producing verbs is reported in non-fluent aphasic patients, with lesions involving left frontal lobe, whereas a selective in naming objects (Producing nouns has been observed in amnesic patients, with lesions involving the temporal lobe and the temporal lobe and the posterior association aresas. This research is a theoretical and fundamental based on descriptive and analytical method. The aphasic data in this research were obtained by assessing each patient's aphasic symptoms using a standard Persian aphasia test (Paradis, Nilipoure, Paribakht, 1989 as well as post-test analysis of each patient' connected descriptive speech. The subjects were selected form among aphasics who referred to speech therapy centers in Tehran during a pe5iod of one year since autumn 1999. The subjects selected in the study were a homogenous group with left hemisphere lesions due to CVA. They were educated adult right handed. Speakers of Persian without any risk factor such as nicotine, alcohol or any addiction and diabetes with no gross depression or anxiety problems or face and oral paralysis and hemiaopsia. The subjects in this study comprised to adults ranging between 33 and 76 years of age. The results indicated that there are significant correlation between: 1 The production of nouns and left hemisphere lesion. 2 The production of verbs and left hemisphere lesion. 3 Brain lesion and language deficits. 4 The site of lesion and language abilities

  8. Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning

    Directory of Open Access Journals (Sweden)

    Yingfeng Cai

    2017-01-01

    Full Text Available Discriminative tracking methods use binary classification to discriminate between the foreground and background and have achieved some useful results. However, the use of labeled training samples is insufficient for them to achieve accurate tracking. Hence, discriminative classifiers must use their own classification results to update themselves, which may lead to feedback-induced tracking drift. To overcome these problems, we propose a semisupervised tracking algorithm that uses deep representation and transfer learning. Firstly, a 2D multilayer deep belief network is trained with a large amount of unlabeled samples. The nonlinear mapping point at the top of this network is subtracted as the feature dictionary. Then, this feature dictionary is utilized to transfer train and update a deep tracker. The positive samples for training are the tracked vehicles, and the negative samples are the background images. Finally, a particle filter is used to estimate vehicle position. We demonstrate experimentally that our proposed vehicle tracking algorithm can effectively restrain drift while also maintaining the adaption of vehicle appearance. Compared with similar algorithms, our method achieves a better tracking success rate and fewer average central-pixel errors.

  9. Shell Nouns as Cohesive Devices in Published and ESL Student Writing

    Science.gov (United States)

    Aktas, Rahime Nur; Cortes, Viviana

    2008-01-01

    This paper analyzes the use of a special type of unspecific noun, called "shell nouns" [Hunston, S., & Francis, G. (1999). "Pattern grammar". Amsterdam: Benjamins; Schmid, H. (2000). "English abstract nouns as conceptual shells: From corpus to cognition". Berlin: Walter de Gruyter], which are frequently used as cohesive devices, in the written…

  10. Categorical Structure among Shared Features in Networks of Early-Learned Nouns

    Science.gov (United States)

    Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

    2009-01-01

    The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…

  11. A Common Mechanism in Verb and Noun Naming Deficits in Alzheimer's Patients

    Science.gov (United States)

    Almor, Amit; Aronoff, Justin M.; MacDonald, Maryellen C.; Gonnerman, Laura M.; Kempler, Daniel; Hintiryan, Houri; Hayes, UnJa L.; Arunachalam, Sudha; Andersen, Elaine S.

    2009-01-01

    We tested the ability of Alzheimer's patients and elderly controls to name living and non-living nouns, and manner and instrument verbs. Patients' error patterns and relative performance with different categories showed evidence of graceful degradation for both nouns and verbs, with particular domain-specific impairments for living nouns and…

  12. Learning connective-based word representations for implicit discourse relation identification

    DEFF Research Database (Denmark)

    Braud, Chloé Elodie; Denis, Pascal

    2016-01-01

    We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represen...... their simplicity, these connective-based rep-resentations outperform various off-the-shelf word embeddings, and achieve state-of-the-art performance on this problem.......We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represent...... words in the space of discourse connectives as a way to directly encode their rhetorical function. Experiments on the Penn Discourse Treebank demonstrate the effectiveness of these task-tailored repre-sentations in predicting implicit discourse re-lations. Our results indeed show that, despite...

  13. The Contrastive Study of Igbo and English Denominal Nouns ...

    African Journals Online (AJOL)

    The teaching of nominalization has not been all smooth for an Igbo second language learner of English language. That is why this study is set to contrast English and Igbo Denominal nouns. The objective is to find out the similarities and differences between the nominalization process in Igbo and that of the English ...

  14. National open university of Nigeria (noun) students' perception of ...

    African Journals Online (AJOL)

    This paper studied the perception and challenges of students of open and distance learning (ODL) mode. ODL is a welcome development in Nigeria educational system. Participants in this study were 500 NOUN students that were randomly selected from Abuja study center. A well structured and validated questionnaire ...

  15. Exploring Atypical Verb+Noun Combinations in Learner Technical Writing

    Science.gov (United States)

    Luzon Marco, Maria Jose

    2011-01-01

    Professional and academic discourse is characterised by a specific phraseology, which usually poses problems for students. This paper investigates atypical verb+noun collocations in a corpus of English technical writing of Spanish students. I focus on the type of verbs that most frequently occurred in these awkward or questionable combinations and…

  16. Collocations of High Frequency Noun Keywords in Prescribed Science Textbooks

    Science.gov (United States)

    Menon, Sujatha; Mukundan, Jayakaran

    2012-01-01

    This paper analyses the discourse of science through the study of collocational patterns of high frequency noun keywords in science textbooks used by upper secondary students in Malaysia. Research has shown that one of the areas of difficulty in science discourse concerns lexis, especially that of collocations. This paper describes a corpus-based…

  17. Lemmatisation of Vowel Commencing Borrowed Nouns and the ...

    African Journals Online (AJOL)

    Riette Ruthven

    its noun class prefixes, the presence of the initial vowel or pre-prefix, or the augment, as ..... Grammatical information has to be as accurate as the defini- ... achieve a semantic ordering of entries gives the impression that language con- sists of ...

  18. Nouns cut slices: Effects of linguistic forms on intergroup bias

    Czech Academy of Sciences Publication Activity Database

    Graf, Sylvie; Bilewicz, M.; Finell, E.; Geschke, D.

    2013-01-01

    Roč. 32, č. 1 (2013), s. 46-61 ISSN 0261-927X R&D Projects: GA ČR GA13-25656S Institutional support: RVO:68081740 Keywords : nouns * adjectives * intergroup bias * intergroup attitudes Subject RIV: AN - Psychology Impact factor: 0.872, year: 2013

  19. Refining the Construct of Classroom-Based Writing-from-Readings Assessment: The Role of Task Representation

    Science.gov (United States)

    Wolfersberger, Mark

    2013-01-01

    This article argues that task representation should be considered as part of the construct of classroom-based academic writing. Task representation is a process that writers move through when creating a unique mental model of the requirements for each new writing task they encounter. Writers' task representations evolve throughout the composing…

  20. Verb-Noun Collocation Proficiency and Academic Years

    Directory of Open Access Journals (Sweden)

    Fatemeh Ebrahimi-Bazzaz

    2014-01-01

    Full Text Available Generally vocabulary and collocations in particular have significant roles in language proficiency. A collocation includes two words that are frequently joined concurrently in the memory of native speakers. There have been many linguistic studies trying to define, to describe, and to categorise English collocations. It contains grammatical collocations and lexical collocations which include nouns, adjectives, verbs, and adverb. In the context of a foreign language environment such as Iran, collocational proficiency can be useful because it helps the students improve their language proficiency. This paper investigates the possible relationship between verb-noun collocation proficiency among students from one academic year to the next. To reach this goal, a test of verb-noun collocations was administered to Iranian learners. The participants in the study were 212 Iranian students in an Iranian university. They were selected from the second term of freshman, sophomore, junior, and senior years. The students’ age ranged from 18 to 35.The results of ANOVA showed there was variability in the verb-noun collocations proficiency within each academic year and between the four academic years. The results of a post hoc multiple comparison tests demonstrated that the means are significantly different between the first year and the third and fourth years, and between the third and the fourth academic year; however, students require at least two years to show significant development in verb-noun collocation proficiency. These findings provided a vital implication that lexical collocations are learnt and developed through four academic years of university, but requires at least two years showing significant development in the language proficiency.

  1. Developing young adults' representational competence through infographic-based science news reporting

    Science.gov (United States)

    Gebre, Engida H.; Polman, Joseph L.

    2016-12-01

    This study presents descriptive analysis of young adults' use of multiple representations in the context of science news reporting. Across one semester, 71 high school students, in a socioeconomically diverse suburban secondary school in Midwestern United States, participated in activities of researching science topics of their choice and producing infographic-based science news for possible online publication. An external editor reviewed their draft infographics and provided comments for subsequent revision. Students also provided peer feedback to the draft version of infographics using an online commentary tool. We analysed the nature of representations students used as well as the comments from peer and the editor feedback. Results showed both students' capabilities and challenges in learning with representations in this context. Students frequently rely on using certain kinds of representations that are depictive in nature, and supporting their progress towards using more abstract representations requires special attention and identifying learning gaps. Results also showed that students were able to determine representational adequacy in the context of providing peer feedback. The study has implication for research and instruction using infographics as expressive tools to support learning.

  2. Multi-Frequency Polarimetric SAR Classification Based on Riemannian Manifold and Simultaneous Sparse Representation

    Directory of Open Access Journals (Sweden)

    Fan Yang

    2015-07-01

    Full Text Available Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach. As classical descriptors of polarimetric SAR, covariance and coherency matrices are Hermitian semidefinite and form a Riemannian manifold. Conventional Euclidean metrics are not suitable for a Riemannian manifold, and hence, normal sparse representation classification cannot be applied to polarimetric SAR directly. This paper proposes a new land cover classification approach for polarimetric SAR. There are two principal novelties in this paper. First, a Stein kernel on a Riemannian manifold instead of Euclidean metrics, combined with sparse representation, is employed for polarimetric SAR land cover classification. This approach is named Stein-sparse representation-based classification (SRC. Second, using simultaneous sparse representation and reasonable assumptions of the correlation of representation among different frequency bands, Stein-SRC is generalized to simultaneous Stein-SRC for multi-frequency polarimetric SAR classification. These classifiers are assessed using polarimetric SAR images from the Airborne Synthetic Aperture Radar (AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the Electromagnetics Institute Synthetic Aperture Radar (EMISAR sensor of the Technical University of Denmark (DTU. Experiments on single-band and multi-band data both show that these approaches acquire more accurate classification results in comparison to many conventional and advanced classifiers.

  3. Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition

    Directory of Open Access Journals (Sweden)

    Qi Jia

    2015-03-01

    Full Text Available In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.

  4. 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.

  5. PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

    Directory of Open Access Journals (Sweden)

    Xingxing Zhu

    2018-05-01

    Full Text Available Nonrigid multimodal image registration remains a challenging task in medical image processing and analysis. The structural representation (SR-based registration methods have attracted much attention recently. However, the existing SR methods cannot provide satisfactory registration accuracy due to the utilization of hand-designed features for structural representation. To address this problem, the structural representation method based on the improved version of the simple deep learning network named PCANet is proposed for medical image registration. In the proposed method, PCANet is firstly trained on numerous medical images to learn convolution kernels for this network. Then, a pair of input medical images to be registered is processed by the learned PCANet. The features extracted by various layers in the PCANet are fused to produce multilevel features. The structural representation images are constructed for two input images based on nonlinear transformation of these multilevel features. The Euclidean distance between structural representation images is calculated and used as the similarity metrics. The objective function defined by the similarity metrics is optimized by L-BFGS method to obtain parameters of the free-form deformation (FFD model. Extensive experiments on simulated and real multimodal image datasets show that compared with the state-of-the-art registration methods, such as modality-independent neighborhood descriptor (MIND, normalized mutual information (NMI, Weber local descriptor (WLD, and the sum of squared differences on entropy images (ESSD, the proposed method provides better registration performance in terms of target registration error (TRE and subjective human vision.

  6. Time-Frequency Distribution of Music based on Sparse Wavelet Packet Representations

    DEFF Research Database (Denmark)

    Endelt, Line Ørtoft

    We introduce a new method for generating time-frequency distributions, which is particularly useful for the analysis of music signals. The method presented here is based on $\\ell1$ sparse representations of music signals in a redundant wavelet packet dictionary. The representations are found using...... the minimization methods basis pursuit and best orthogonal basis. Visualizations of the time-frequency distribution are constructed based on a simplified energy distribution in the wavelet packet decomposition. The time-frequency distributions emphasizes structured musical content, including non-stationary content...

  7. Investigating differences between proper and common nouns using novel word learning

    Directory of Open Access Journals (Sweden)

    Anastasiya Romanova

    2014-04-01

    Full Text Available Empirical studies have shown higher rates of tip-of-the-tongue states for proper nouns, in comparison to common nouns, in non-brain-damaged speakers (e.g., Valentine & Moore, 1995, and higher retrieval failure rates for proper nouns relative to common nouns in people with aphasia (e.g., Semenza, 2009. Some authors suggest the source of these differences lies in logical properties (e.g., Semenza, 2009. That is, common nouns refer to a category of beings or objects that share certain semantic properties, while proper nouns designate specific individual beings or objects with unique features. Other authors attribute the distinction in processing to a number of statistical properties that differ across common and proper nouns (Kay, Hanley, & Miles, 2001. The aims of the present study were: 1 to dissociate the effects of logical and statistical properties by using novel words with equal statistical properties; 2 to determine whether people with aphasia show disproportionate impairments in learning proper nouns relative to common nouns, compared to aged-matched subjects. Methods We tested young (n=16 and elderly (n=14 adult non-brain-damaged participants and people with aphasia (n=2. Items-to-be-learnt were given as representatives of an unknown species (n=10 in the common noun condition, or as individual creatures (n=10 in the proper noun condition. The experiment consisted of 5 sessions. Each session included a learning phase and a test phase with naming and word-picture verification tasks. Results and Discussion Preliminary analysis showed learning of both common and proper nouns for both younger (F(4=140.68, p<.01 and elderly (F(4=34.87, p<.01 non-brain-damaged participants, with learning being significantly better for the younger group (F(4=6.5, p<.01. Contrary to expectations, performance on proper nouns was better than that for common nouns for both young and elderly subjects (F(1=6.47, p=.02 and F(1=9.75, p<.01, respectively, possibly due to

  8. A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2015-08-01

    Full Text Available In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.

  9. Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

    Science.gov (United States)

    Bing, Lu; Wang, Wei

    2017-01-01

    We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

  10. Generating concept representations from examples, using set-based notation

    DEFF Research Database (Denmark)

    Galle, Per

    2000-01-01

    A database or knowledge-based system must draw on a conceptual schema that defines the domain concepts with which its user works. In the case of a system for architectural design support, for example, this might be concepts of walls, windows etc. However, making concepts explicit and expressing t...

  11. Representability in DL-Lite_R knowledge base exchange

    NARCIS (Netherlands)

    Arenas, M.; Botoeva, E.; Calvanese, D.; Ryzhikov, V.; Sherkhonov, E.

    2012-01-01

    Knowledge base exchange can be considered as a generalization of data exchange in which the aim is to exchange between a source and a target connected through mappings, not only explicit knowledge, i.e., data, but also implicit knowledge in the form of axioms. Such problem has been investigated

  12. TARGET-ORIENTED GENERIC FINGERPRINT-BASED MOLECULAR REPRESENTATION

    OpenAIRE

    Petr Skoda; David Hoksza

    2014-01-01

    The screening of chemical libraries is an important step in the drug discovery process. The existing chemical libraries contain up to millions of compounds. As the screening at such scale is expensive, the virtual screening is often utilized. There exist several variants of virtual screening and ligand-based virtual screening is one of them. It utilizes the similarity of screened chemical compounds to known compounds. Besides the employed similarity measure, another aspect grea...

  13. Classification of forensic autopsy reports through conceptual graph-based document representation model.

    Science.gov (United States)

    Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

    2018-06-01

    Text categorization has been used extensively in recent years to classify plain-text clinical reports. This study employs text categorization techniques for the classification of open narrative forensic autopsy reports. One of the key steps in text classification is document representation. In document representation, a clinical report is transformed into a format that is suitable for classification. The traditional document representation technique for text categorization is the bag-of-words (BoW) technique. In this study, the traditional BoW technique is ineffective in classifying forensic autopsy reports because it merely extracts frequent but discriminative features from clinical reports. Moreover, this technique fails to capture word inversion, as well as word-level synonymy and polysemy, when classifying autopsy reports. Hence, the BoW technique suffers from low accuracy and low robustness unless it is improved with contextual and application-specific information. To overcome the aforementioned limitations of the BoW technique, this research aims to develop an effective conceptual graph-based document representation (CGDR) technique to classify 1500 forensic autopsy reports from four (4) manners of death (MoD) and sixteen (16) causes of death (CoD). Term-based and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) based conceptual features were extracted and represented through graphs. These features were then used to train a two-level text classifier. The first level classifier was responsible for predicting MoD. In addition, the second level classifier was responsible for predicting CoD using the proposed conceptual graph-based document representation technique. To demonstrate the significance of the proposed technique, its results were compared with those of six (6) state-of-the-art document representation techniques. Lastly, this study compared the effects of one-level classification and two-level classification on the experimental results

  14. Ontology and modeling patterns for state-based behavior representation

    Science.gov (United States)

    Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.; hide

    2015-01-01

    This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.

  15. Representation of Students in Solving Simultaneous Linear Equation Problems Based on Multiple Intelligence

    Science.gov (United States)

    Yanti, Y. R.; Amin, S. M.; Sulaiman, R.

    2018-01-01

    This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.

  16. A Walk-based Semantically Enriched Tree Kernel Over Distributed Word Representations

    DEFF Research Database (Denmark)

    Srivastava, Shashank; Hovy, Dirk

    2013-01-01

    We propose a walk-based graph kernel that generalizes the notion of tree-kernels to continuous spaces. Our proposed approach subsumes a general framework for word-similarity, and in particular, provides a flexible way to incorporate distributed representations. Using vector representations......, such an approach captures both distributional semantic similarities among words as well as the structural relations between them (encoded as the structure of the parse tree). We show an efficient formulation to compute this kernel using simple matrix multiplication operations. We present our results on three...

  17. Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning

    NARCIS (Netherlands)

    Miao, Yongwu; Burgos, Daniel; Griffiths, David; Koper, Rob

    2007-01-01

    Miao, Y., Burgos, D., Griffiths, D., & Koper, R. (2008). Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In L. Lockyer, S. Bennet, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design and Learning Objects: Issues, Applications and

  18. No functional role of attention-based rehearsal in maintenance of spatial working memory representations

    NARCIS (Netherlands)

    Belopolsky, A.V.; Theeuwes, J.

    2009-01-01

    The present study systematically examined the role of attention in maintenance of spatial representations in working memory as proposed by the attention-based rehearsal hypothesis [Awh, E., Jonides, J., & Reuter-Lorenz, P. A. (1998). Rehearsal in spatial working memory. Journal of Experimental

  19. Training data representation in a neural based robot position estimation system

    International Nuclear Information System (INIS)

    Taraglio, S.; Di Fonzo, F.; Burrascano, P.

    1997-03-01

    The vision subsystem of an autonomous vehicle is studies. It is based on a multi layer perceptron that uses TV images to estimate the position of the vehicle. A comparative study of the effects of output data representation and input data processing is presented and discussed

  20. Multi-stream CNN: Learning representations based on human-related regions for action recognition

    NARCIS (Netherlands)

    Tu, Zhigang; Xie, Wei; Qin, Qianqing; Poppe, R.W.; Veltkamp, R.C.; Li, Baoxin; Yuan, Junsong

    2018-01-01

    The most successful video-based human action recognition methods rely on feature representations extracted using Convolutional Neural Networks (CNNs). Inspired by the two-stream network (TS-Net), we propose a multi-stream Convolutional Neural Network (CNN) architecture to recognize human actions. We

  1. The Effect of Project-Based Learning on Students' Statistical Literacy Levels for Data Representation

    Science.gov (United States)

    Koparan, Timur; Güven, Bülent

    2015-01-01

    The point of this study is to define the effect of project-based learning approach on 8th Grade secondary-school students' statistical literacy levels for data representation. To achieve this goal, a test which consists of 12 open-ended questions in accordance with the views of experts was developed. Seventy 8th grade secondary-school students, 35…

  2. Ontology-Based Vaccine Adverse Event Representation and Analysis.

    Science.gov (United States)

    Xie, Jiangan; He, Yongqun

    2017-01-01

    Vaccine is the one of the greatest inventions of modern medicine that has contributed most to the relief of human misery and the exciting increase in life expectancy. In 1796, an English country physician, Edward Jenner, discovered that inoculating mankind with cowpox can protect them from smallpox (Riedel S, Edward Jenner and the history of smallpox and vaccination. Proceedings (Baylor University. Medical Center) 18(1):21, 2005). Based on the vaccination worldwide, we finally succeeded in the eradication of smallpox in 1977 (Henderson, Vaccine 29:D7-D9, 2011). Other disabling and lethal diseases, like poliomyelitis and measles, are targeted for eradication (Bonanni, Vaccine 17:S120-S125, 1999).Although vaccine development and administration are tremendously successful and cost-effective practices to human health, no vaccine is 100% safe for everyone because each person reacts to vaccinations differently given different genetic background and health conditions. Although all licensed vaccines are generally safe for the majority of people, vaccinees may still suffer adverse events (AEs) in reaction to various vaccines, some of which can be serious or even fatal (Haber et al., Drug Saf 32(4):309-323, 2009). Hence, the double-edged sword of vaccination remains a concern.To support integrative AE data collection and analysis, it is critical to adopt an AE normalization strategy. In the past decades, different controlled terminologies, including the Medical Dictionary for Regulatory Activities (MedDRA) (Brown EG, Wood L, Wood S, et al., Drug Saf 20(2):109-117, 1999), the Common Terminology Criteria for Adverse Events (CTCAE) (NCI, The Common Terminology Criteria for Adverse Events (CTCAE). Available from: http://evs.nci.nih.gov/ftp1/CTCAE/About.html . Access on 7 Oct 2015), and the World Health Organization (WHO) Adverse Reactions Terminology (WHO-ART) (WHO, The WHO Adverse Reaction Terminology - WHO-ART. Available from: https://www.umc-products.com/graphics/28010.pdf

  3. Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns.

    Directory of Open Access Journals (Sweden)

    Hiroyuki Akama

    Full Text Available In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF. This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk and co-occurrence adjustment (degree balance and distribution. We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

  4. 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.

  5. Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.

    Science.gov (United States)

    Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen

    2017-08-29

    In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.

  6. SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

    Directory of Open Access Journals (Sweden)

    Wu Yiquan

    2017-08-01

    Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

  7. 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.

  8. Fast and accurate grid representations for atom-based docking with partner flexibility.

    Science.gov (United States)

    de Vries, Sjoerd J; Zacharias, Martin

    2017-06-30

    Macromolecular docking methods can broadly be divided into geometric and atom-based methods. Geometric methods use fast algorithms that operate on simplified, grid-like molecular representations, while atom-based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid-based and atom-based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom-based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid-based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse-grained forcefield, the average speed improvement was >100x. Grid-based representations may allow atom-based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  9. Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

    Science.gov (United States)

    Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

    2015-11-01

    One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Improving the learning of clinical reasoning through computer-based cognitive representation.

    Science.gov (United States)

    Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

    2014-01-01

    Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

  11. Improving the learning of clinical reasoning through computer-based cognitive representation

    Directory of Open Access Journals (Sweden)

    Bian Wu

    2014-12-01

    Full Text Available Objective: Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods: Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results: A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions: The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge

  12. Integration of object-oriented knowledge representation with the CLIPS rule based system

    Science.gov (United States)

    Logie, David S.; Kamil, Hasan

    1990-01-01

    The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

  13. Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

    Science.gov (United States)

    Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

    2016-07-07

    Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

  14. Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI

    Directory of Open Access Journals (Sweden)

    José Manuel Molina

    2012-09-01

    Full Text Available Recent advances in technologies for capturing video data have opened a vast amount of new application areas in visual sensor networks. Among them, the incorporation of light wave cameras on Ambient Intelligence (AmI environments provides more accurate tracking capabilities for activity recognition. Although the performance of tracking algorithms has quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted to smart environments. This lack of representation does not allow to take advantage of the semantic quality of the information provided by new sensors. This paper advocates for the introduction of a part-based representational level in cognitive-based systems in order to accurately represent the novel sensors’ knowledge. The paper also reviews the theoretical and practical issues in part-whole relationships proposing a specific taxonomy for computer vision approaches. General part-based patterns for human body and transitive part-based representation and inference are incorporated to an ontology-based previous framework to enhance scene interpretation in the area of video-based AmI. The advantages and new features of the model are demonstrated in a Social Signal Processing (SSP application for the elaboration of live market researches.

  15. Reexamining the language account of cross-national differences in base-10 number representations.

    Science.gov (United States)

    Vasilyeva, Marina; Laski, Elida V; Ermakova, Anna; Lai, Weng-Feng; Jeong, Yoonkyung; Hachigian, Amy

    2015-01-01

    East Asian students consistently outperform students from other nations in mathematics. One explanation for this advantage is a language account; East Asian languages, unlike most Western languages, provide cues about the base-10 structure of multi-digit numbers, facilitating the development of base-10 number representations. To test this view, the current study examined how kindergartners represented two-digit numbers using single unit-blocks and ten-blocks. The participants (N=272) were from four language groups (Korean, Mandarin, English, and Russian) that vary in the extent of "transparency" of the base-10 structure. In contrast to previous findings with older children, kindergartners showed no cross-language variability in the frequency of producing base-10 representations. Furthermore, they showed a pattern of within-language variability that was not consistent with the language account and was likely attributable to experiential factors. These findings suggest that language might not play as critical a role in the development of base-10 representations as suggested in earlier research. Copyright © 2014 Elsevier Inc. All rights reserved.

  16. Object-based attention: strength of object representation and attentional guidance.

    Science.gov (United States)

    Shomstein, Sarah; Behrmann, Marlene

    2008-01-01

    Two or more features belonging to a single object are identified more quickly and more accurately than are features belonging to different objects--a finding attributed to sensory enhancement of all features belonging to an attended or selected object. However, several recent studies have suggested that this "single-object advantage" may be a product of probabilistic and configural strategic prioritizations rather than of object-based perceptual enhancement per se, challenging the underlying mechanism that is thought to give rise to object-based attention. In the present article, we further explore constraints on the mechanisms of object-based selection by examining the contribution of the strength of object representations to the single-object advantage. We manipulated factors such as exposure duration (i.e., preview time) and salience of configuration (i.e., objects). Varying preview time changes the magnitude of the object-based effect, so that if there is ample time to establish an object representation (i.e., preview time of 1,000 msec), then both probability and configuration (i.e., objects) guide attentional selection. If, however, insufficient time is provided to establish a robust object-based representation, then only probabilities guide attentional selection. Interestingly, at a short preview time of 200 msec, when the two objects were sufficiently different from each other (i.e., different colors), both configuration and probability guided attention selection. These results suggest that object-based effects can be explained both in terms of strength of object representations (established at longer exposure durations and by pictorial cues) and probabilistic contingencies in the visual environment.

  17. User-based representation of time-resolved multimodal public transportation networks.

    Science.gov (United States)

    Alessandretti, Laura; Karsai, Márton; Gauvin, Laetitia

    2016-07-01

    Multimodal transportation systems, with several coexisting services like bus, tram and metro, can be represented as time-resolved multilayer networks where the different transportation modes connecting the same set of nodes are associated with distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geo-localized transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, we provide a novel user-based representation of public transportation systems, which combines representations, accounting for the presence of multiple lines and reducing the effect of spatial embeddedness, while considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. After the adjustment of earlier techniques to the novel representation framework, we analyse the public transportation systems of several French municipal areas and identify hidden patterns of privileged connections. Furthermore, we study their efficiency as compared to the commuting flow. The proposed representation could help to enhance resilience of local transportation systems to provide better design policies for future developments.

  18. Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

    Science.gov (United States)

    Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

    2017-11-01

    The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

  19. An analysis of primary school students’ representational ability in mathematics based on gender perspective

    Science.gov (United States)

    Kowiyah; Mulyawati, I.

    2018-01-01

    Mathematic representation is one of the basic mathematic skills that allows students to communicate their mathematic ideas through visual realities such as pictures, tables, mathematic expressions and mathematic equities. The present research aims at: 1) analysing students’ mathematic representation ability in solving mathematic problems and 2) examining the difference of students’ mathematic ability based on their gender. A total of sixty primary school students participated in this study comprising of thirty males and thirty females. Data required in this study were collected through mathematic representation tests, interviews and test evaluation rubric. Findings of this study showed that students’ mathematic representation of visual realities (image and tables) was reported higher at 62.3% than at in the form of description (or statement) at 8.6%. From gender perspective, male students performed better than the females at action planning stage. The percentage of males was reported at 68% (the highest), 33% (medium) and 21.3% (the lowest) while the females were at 36% (the highest), 37.7% (medium) and 32.6% (the lowest).

  20. Committee Representation and Medicare Reimbursements-An Examination of the Resource-Based Relative Value Scale.

    Science.gov (United States)

    Gao, Y Nina

    2018-04-06

    The Resource-Based Relative Value Scale Update Committee (RUC) submits recommended reimbursement values for physician work (wRVUs) under Medicare Part B. The RUC includes rotating representatives from medical specialties. To identify changes in physician reimbursements associated with RUC rotating seat representation. Relative Value Scale Update Committee members 1994-2013; Medicare Part B Relative Value Scale 1994-2013; Physician/Supplier Procedure Summary Master File 2007; Part B National Summary Data File 2000-2011. I match service and procedure codes to specialties using 2007 Medicare billing data. Subsequently, I model wRVUs as a function of RUC rotating committee representation and level of code specialization. An annual RUC rotating seat membership is associated with a statistically significant 3-5 percent increase in Medicare expenditures for codes billed to that specialty. For codes that are performed by a small number of physicians, the association between reimbursement and rotating subspecialty representation is positive, 0.177 (SE = 0.024). For codes that are performed by a large number of physicians, the association is negative, -0.183 (SE = 0.026). Rotating representation on the RUC is correlated with overall reimbursement rates. The resulting differential changes may exacerbate existing reimbursement discrepancies between generalist and specialist practitioners. © Health Research and Educational Trust.

  1. A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Allah Bux Sargano

    2017-01-01

    Full Text Available Human activity recognition (HAR is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human computer interaction, human-robot interaction, entertainment, and intelligent driving. Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR. However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition. However, approaches based on handcrafted representation are not able to handle complex scenarios due to their limitations and incapability; therefore, resorting to deep learning-based techniques is a natural option. This review paper presents a comprehensive survey of both handcrafted and learning-based action representations, offering comparison, analysis, and discussions on these approaches. In addition to this, the well-known public datasets available for experimentations and important applications of HAR are also presented to provide further insight into the field. This is the first review paper of its kind which presents all these aspects of HAR in a single review article with comprehensive coverage of each part. Finally, the paper is concluded with important discussions and research directions in the domain of HAR.

  2. Multi-Label Classification Based on Low Rank Representation for Image Annotation

    Directory of Open Access Journals (Sweden)

    Qiaoyu Tan

    2017-01-01

    Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

  3. Noun phrases: with or without an article

    Directory of Open Access Journals (Sweden)

    Sonia Montero Gálvez

    2014-12-01

    The proposed approaches and suggestions are in line with those proposed in a doctoral thesis that is currently in progress. Therefore, we should take into account that both this didactical proposal as well as the doctoral thesis on which it is based are not legitimised yet by the academic and scientific community. However, we are venturing to share this work because it may be helpful in the teaching and learning of Spanish as a Second Language.

  4. Features based approach for indexation and representation of unstructured Arabic documents

    Directory of Open Access Journals (Sweden)

    Mohamed Salim El Bazzi

    2017-06-01

    Full Text Available The increase of textual information published in Arabic language on the internet, public libraries and administrations requires implementing effective techniques for the extraction of relevant information contained in large corpus of texts. The purpose of indexing is to create a document representation that easily find and identify the relevant information in a set of documents. However, mining textual data is becoming a complicated task, especially when taking semantic into consideration. In this paper, we will present an indexation system based on contextual representation that will take the advantage of semantic links given in a document. Our approach is based on the extraction of keyphrases. Then, each document is represented by its relevant keyphrases instead of its simple keywords. The experimental results confirms the effectiveness of our approach.

  5. Top-down attention based on object representation and incremental memory for knowledge building and inference.

    Science.gov (United States)

    Kim, Bumhwi; Ban, Sang-Woo; Lee, Minho

    2013-10-01

    Humans can efficiently perceive arbitrary visual objects based on an incremental learning mechanism with selective attention. This paper proposes a new task specific top-down attention model to locate a target object based on its form and color representation along with a bottom-up saliency based on relativity of primitive visual features and some memory modules. In the proposed model top-down bias signals corresponding to the target form and color features are generated, which draw the preferential attention to the desired object by the proposed selective attention model in concomitance with the bottom-up saliency process. The object form and color representation and memory modules have an incremental learning mechanism together with a proper object feature representation scheme. The proposed model includes a Growing Fuzzy Topology Adaptive Resonance Theory (GFTART) network which plays two important roles in object color and form biased attention; one is to incrementally learn and memorize color and form features of various objects, and the other is to generate a top-down bias signal to localize a target object by focusing on the candidate local areas. Moreover, the GFTART network can be utilized for knowledge inference which enables the perception of new unknown objects on the basis of the object form and color features stored in the memory during training. Experimental results show that the proposed model is successful in focusing on the specified target objects, in addition to the incremental representation and memorization of various objects in natural scenes. In addition, the proposed model properly infers new unknown objects based on the form and color features of previously trained objects. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. INVESTIGATING SHAPE REPRESENTATION USING SENSITIVITY TO PART- AND AXIS-BASED TRANSFORMATIONS

    OpenAIRE

    Denisova, Kristina; Feldman, Jacob; Su, Xiaotao; Singh, Manish

    2016-01-01

    Part -and axis-based approaches organize shape representations in terms of simple parts and their spatial relationships. Shape transformations that alter qualitative part structure have been shown to be more detectable than those that preserve it. We compared sensitivity to various transformations that change quantitative properties of parts and their spatial relationships, while preserving qualitative part structure. Shape transformations involving changes in length, width, curvature, orient...

  7. Internal representations for face detection: an application of noise-based image classification to BOLD responses.

    Science.gov (United States)

    Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

    2013-11-01

    What basic visual structures underlie human face detection and how can we extract such structures directly from the amplitude of neural responses elicited by face processing? Here, we address these issues by investigating an extension of noise-based image classification to BOLD responses recorded in high-level visual areas. First, we assess the applicability of this classification method to such data and, second, we explore its results in connection with the neural processing of faces. To this end, we construct luminance templates from white noise fields based on the response of face-selective areas in the human ventral cortex. Using behaviorally and neurally-derived classification images, our results reveal a family of simple but robust image structures subserving face representation and detection. Thus, we confirm the role played by classical face selective regions in face detection and we help clarify the representational basis of this perceptual function. From a theory standpoint, our findings support the idea of simple but highly diagnostic neurally-coded features for face detection. At the same time, from a methodological perspective, our work demonstrates the ability of noise-based image classification in conjunction with fMRI to help uncover the structure of high-level perceptual representations. Copyright © 2012 Wiley Periodicals, Inc.

  8. Improved Collaborative Representation Classifier Based on l2-Regularized for Human Action Recognition

    Directory of Open Access Journals (Sweden)

    Shirui Huo

    2017-01-01

    Full Text Available Human action recognition is an important recent challenging task. Projecting depth images onto three depth motion maps (DMMs and extracting deep convolutional neural network (DCNN features are discriminant descriptor features to characterize the spatiotemporal information of a specific action from a sequence of depth images. In this paper, a unified improved collaborative representation framework is proposed in which the probability that a test sample belongs to the collaborative subspace of all classes can be well defined and calculated. The improved collaborative representation classifier (ICRC based on l2-regularized for human action recognition is presented to maximize the likelihood that a test sample belongs to each class, then theoretical investigation into ICRC shows that it obtains a final classification by computing the likelihood for each class. Coupled with the DMMs and DCNN features, experiments on depth image-based action recognition, including MSRAction3D and MSRGesture3D datasets, demonstrate that the proposed approach successfully using a distance-based representation classifier achieves superior performance over the state-of-the-art methods, including SRC, CRC, and SVM.

  9. Determination of the noun in Biblical Hebrew

    DEFF Research Database (Denmark)

    Ehrensvärd, Martin Gustaf

    2000-01-01

    The article investigates the claim that the definite article in biblical Hebrew can be unrelated to determination. This claim is found in the standard grammars of Joüon/Muraoka and Gesenius/Kautzsch and in an article by James Barr. Barr argues that it is a diachronic feature, the biblical texts...... showing the use of the article in a process of change during the biblical period, so that only in later times it acquires a close connection with determination. The article argues that this interpretation of the use of the article is based on a misunderstanding, and the instances of article use that might...... seem to be unrelated to determination in fact are perfectly related to determination when analysed carefully....

  10. Functional categories in the noun phrase: on jacks-of-all-trades and one-trick-ponies in Danish, Dutch and German

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    2010-01-01

    This paper deals with functionally defined modifier categories of the noun phrase in some Germanic languages, in particular Danish, Dutch and German. It is argued that functional categories, unlike semantic or form-based categories, are the only categories that can be applied within and across...... in German: attitudinal arm (e.g. Der arme Junge! ‘The poor boy!’)....

  11. Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

    Directory of Open Access Journals (Sweden)

    Lu Bing

    2017-01-01

    Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

  12. Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging

    Directory of Open Access Journals (Sweden)

    Xiaodong Zhang

    2016-01-01

    Full Text Available Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L0-norm/L1-norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118 than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610. The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.

  13. DEVELOPMENT OF INTERACTIVE E-BOOK BASED ON CHEMICAL REPRESENTATION REFER TO CURRICULUM 2013

    Directory of Open Access Journals (Sweden)

    L. Tania

    2015-11-01

    Full Text Available This research aimed to develop an interactive e-book based representations of chemistry; describes the characteristics of the interactive e-book developed; the teachers responses in content suitability with curriculum and graphics aspects; and student responses in readibility aspects. The method used was research and development. The characteristics of interactive e-book: it was developed referring to the core competencies (KI and basic competence (KD in the curriculum 2013, allowed active interaction between students and e-book, completed with pictures, animations or videos in three levels of the chemical representation. Teachers’ responses to the content suitability and graphic aspects were very good with the percentage of each 98.46% and 97.5%. The students’ responses in readibility aspects was very good with percentage of 88.5%.

  14. Optimal Meter Placement for Distribution Network State Estimation: A Circuit Representation Based MILP Approach

    DEFF Research Database (Denmark)

    Chen, Xiaoshuang; Lin, Jin; Wan, Can

    2016-01-01

    State estimation (SE) in distribution networks is not as accurate as that in transmission networks. Traditionally, distribution networks (DNs) are lack of direct measurements due to the limitations of investments and the difficulties of maintenance. Therefore, it is critical to improve the accuracy...... of SE in distribution networks by placing additional physical meters. For state-of-the-art SE models, it is difficult to clearly quantify measurements' influences on SE errors, so the problems of optimal meter placement for reducing SE errors are mostly solved by heuristic or suboptimal algorithms....... Under this background, this paper proposes a circuit representation model to represent SE errors. Based on the matrix formulation of the circuit representation model, the problem of optimal meter placement can be transformed to a mixed integer linear programming problem (MILP) via the disjunctive model...

  15. Right-Linear Languages Generated in Systems of Knowledge Representation based on LSG

    Directory of Open Access Journals (Sweden)

    Daniela Danciulescu

    2017-04-01

    Full Text Available In Tudor (Preda (2010 a method for formal languages generation based on labeled stratified graph representations is sketched. The author proves that the considered method can generate regular languages and context-sensitive languages by considering an exemplification of the proposed method for a particular regular language and another one for a particular contextsensitive language. At the end of the study, the author highlights some open problems for future research among which we remind: (1 The study of the language families that can be generated by means of these structures; (2 The study of the infiniteness of the languages that can be represented in stratified graphs. In this paper, we extend the method presented in Tudor (Preda(2010, by considering the stratified graph formalism in a system of knowledge representation and reasoning. More precisely, we propose a method that can be applied for generating any Right Linear Language construction. Our method is proved and exemplified in several cases.

  16. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    Directory of Open Access Journals (Sweden)

    YANG Zhaoxia

    2015-07-01

    Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

  17. Merger of noun classes 3 and 1: A case study with bilingual isiXhosa ...

    African Journals Online (AJOL)

    Class reduction (the loss of a noun class) in Southern Bantu languages is an acknowledged but under-researched phenomenon. A recent study of isiXhosa concords suggests an incipient merger of noun classes 11 and 5, but no research to date has examined other possible concord mergers or concord flux in the ...

  18. Onondaga Noun Incorporation: Some Notes on the Interdependence of Syntax and Semantics

    Science.gov (United States)

    Woodbury, Hanni

    1975-01-01

    In Onondaga and all northern Iroquoian languages, nouns can be incorporated into verbs. The function of this is semantic as well as syntactic. It is semantic in that the sense of an incorporated noun will be narrower than its unincorporated counterpart regardless of modifiers. Incorporation changes the transformational structure of the sentence.…

  19. A developmental analysis of generic nouns in Southern Peruvian Quechua.

    Science.gov (United States)

    Mannheim, Bruce; Gelman, Susan A; Escalante, Carmen; Huayhua, Margarita; Puma, Rosalía

    2010-01-01

    Generic noun phrases (e.g., "Cats like to drink milk") are a primary means by which adults express generalizations to children, yet they pose a challenging induction puzzle for learners. Although prior research has established that English speakers understand and produce generic noun phrases by preschool age, little is known regarding the cross-cultural generality of generic acquisition. Southern Peruvian Quechua provides a valuable comparison because, unlike English, it is a highly inflected language in which generics are marked by the absence rather than the presence of any linguistic markers. Moreover, Quechua is spoken in a cultural context that differs markedly from the highly educated, middle-class contexts within which earlier research on generics was conducted. We presented participants from 5 age groups (3-6, 7-9, 10-12, 14-35, and 36-90 years of age) with two tasks that examined the ability to distinguish generic from non-generic utterances. In Study 1, even the youngest children understood generics as applying broadly to a category (like "all") and distinct from indefinite reference ("some"). However, there was a developmental lag before children understood that generics, unlike "all", can include exceptions. Study 2 revealed that generic interpretations are more frequent for utterances that (a) lack specifying markers and (b) are animate. Altogether, generic interpretations are found among the youngest participants, and may be a default mode of quantification. These data demonstrate the cross-cultural importance of generic information in linguistic expression.

  20. Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation.

    Science.gov (United States)

    Yang, Jian-Yi; Peng, Zhen-Ling; Yu, Zu-Guo; Zhang, Rui-Jie; Anh, Vo; Wang, Desheng

    2009-04-21

    In this paper, we intend to predict protein structural classes (alpha, beta, alpha+beta, or alpha/beta) for low-homology data sets. Two data sets were used widely, 1189 (containing 1092 proteins) and 25PDB (containing 1673 proteins) with sequence homology being 40% and 25%, respectively. We propose to decompose the chaos game representation of proteins into two kinds of time series. Then, a novel and powerful nonlinear analysis technique, recurrence quantification analysis (RQA), is applied to analyze these time series. For a given protein sequence, a total of 16 characteristic parameters can be calculated with RQA, which are treated as feature representation of protein sequences. Based on such feature representation, the structural class for each protein is predicted with Fisher's linear discriminant algorithm. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies with step-by-step procedure are 65.8% and 64.2% for 1189 and 25PDB data sets, respectively. With one-against-others procedure used widely, we compare our method with five other existing methods. Especially, the overall accuracies of our method are 6.3% and 4.1% higher for the two data sets, respectively. Furthermore, only 16 parameters are used in our method, which is less than that used by other methods. This suggests that the current method may play a complementary role to the existing methods and is promising to perform the prediction of protein structural classes.

  1. Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

    Science.gov (United States)

    An, Gary

    2009-01-01

    The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

  2. A kernel-based multi-feature image representation for histopathology image classification

    International Nuclear Information System (INIS)

    Moreno J; Caicedo J Gonzalez F

    2010-01-01

    This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  3. A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    J Carlos Moreno

    2010-09-01

    Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

  4. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

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

    Science.gov (United States)

    Cuppini, C; Magosso, E; Ursino, M

    2009-06-01

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

  6. Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

    Science.gov (United States)

    Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

    2017-05-01

    Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.

  7. Inadequacy representation of flamelet-based RANS model for turbulent non-premixed flame

    Science.gov (United States)

    Lee, Myoungkyu; Oliver, Todd; Moser, Robert

    2017-11-01

    Stochastic representations for model inadequacy in RANS-based models of non-premixed jet flames are developed and explored. Flamelet-based RANS models are attractive for engineering applications relative to higher-fidelity methods because of their low computational costs. However, the various assumptions inherent in such models introduce errors that can significantly affect the accuracy of computed quantities of interest. In this work, we develop an approach to represent the model inadequacy of the flamelet-based RANS model. In particular, we pose a physics-based, stochastic PDE for the triple correlation of the mixture fraction. This additional uncertain state variable is then used to construct perturbations of the PDF for the instantaneous mixture fraction, which is used to obtain an uncertain perturbation of the flame temperature. A hydrogen-air non-premixed jet flame is used to demonstrate the representation of the inadequacy of the flamelet-based RANS model. This work was supported by DARPA-EQUiPS(Enabling Quantification of Uncertainty in Physical Systems) program.

  8. Experience-driven formation of parts-based representations in a model of layered visual memory

    Directory of Open Access Journals (Sweden)

    Jenia Jitsev

    2009-09-01

    Full Text Available Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.

  9. Knowledge Representation and Inference for Analysis and Design of Database and Tabular Rule-Based Systems

    Directory of Open Access Journals (Sweden)

    Antoni Ligeza

    2001-01-01

    Full Text Available Rulebased systems constitute a powerful tool for specification of knowledge in design and implementation of knowledge based systems. They provide also a universal programming paradigm for domains such as intelligent control, decision support, situation classification and operational knowledge encoding. In order to assure safe and reliable performance, such system should satisfy certain formal requirements, including completeness and consistency. This paper addresses the issue of analysis and verification of selected properties of a class of such system in a systematic way. A uniform, tabular scheme of single-level rule-based systems is considered. Such systems can be applied as a generalized form of databases for specification of data pattern (unconditional knowledge, or can be used for defining attributive decision tables (conditional knowledge in form of rules. They can also serve as lower-level components of a hierarchical multi-level control and decision support knowledge-based systems. An algebraic knowledge representation paradigm using extended tabular representation, similar to relational database tables is presented and algebraic bases for system analysis, verification and design support are outlined.

  10. Computational neuroanatomy: ontology-based representation of neural components and connectivity.

    Science.gov (United States)

    Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

    2009-02-05

    A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

  11. The Role of Familiarity for Representations in Norm-Based Face Space.

    Science.gov (United States)

    Faerber, Stella J; Kaufmann, Jürgen M; Leder, Helmut; Martin, Eva Maria; Schweinberger, Stefan R

    2016-01-01

    According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991), any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face) should be equidistant to a hypothetical prototype face (norm), such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent) from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV), and distinctiveness (face in the crowd: FITC) for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV). In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1) that familiarity needs to be considered in studies of mental representations of faces, and (2) that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations.

  12. The Role of Familiarity for Representations in Norm-Based Face Space.

    Directory of Open Access Journals (Sweden)

    Stella J Faerber

    Full Text Available According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991, any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face should be equidistant to a hypothetical prototype face (norm, such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV, and distinctiveness (face in the crowd: FITC for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV. In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1 that familiarity needs to be considered in studies of mental representations of faces, and (2 that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations.

  13. A searching and reporting system for relational databases using a graph-based metadata representation.

    Science.gov (United States)

    Hewitt, Robin; Gobbi, Alberto; Lee, Man-Ling

    2005-01-01

    Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.

  14. Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts.

    Science.gov (United States)

    Gómez-Adorno, Helena; Markov, Ilia; Sidorov, Grigori; Posadas-Durán, Juan-Pablo; Sanchez-Perez, Miguel A; Chanona-Hernandez, Liliana

    2016-01-01

    We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available.

  15. Clustering, Hierarchical Organization, and the Topography of Abstract and Concrete Nouns

    Directory of Open Access Journals (Sweden)

    Joshua eTroche

    2014-04-01

    Full Text Available The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are disembodied in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N=365 rated target words (n=400 English nouns across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence. Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

  16. Clustering, hierarchical organization, and the topography of abstract and concrete nouns.

    Science.gov (United States)

    Troche, Joshua; Crutch, Sebastian; Reilly, Jamie

    2014-01-01

    The empirical study of language has historically relied heavily upon concrete word stimuli. By definition, concrete words evoke salient perceptual associations that fit well within feature-based, sensorimotor models of word meaning. In contrast, many theorists argue that abstract words are "disembodied" in that their meaning is mediated through language. We investigated word meaning as distributed in multidimensional space using hierarchical cluster analysis. Participants (N = 365) rated target words (n = 400 English nouns) across 12 cognitive dimensions (e.g., polarity, ease of teaching, emotional valence). Factor reduction revealed three latent factors, corresponding roughly to perceptual salience, affective association, and magnitude. We plotted the original 400 words for the three latent factors. Abstract and concrete words showed overlap in their topography but also differentiated themselves in semantic space. This topographic approach to word meaning offers a unique perspective to word concreteness.

  17. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed; Zhang, Xiangliang

    2017-01-01

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals's mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users' check-ins and their network of friends, without impairing the model's complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  18. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed

    2017-02-07

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  19. Facial expression recognition based on weber local descriptor and sparse representation

    Science.gov (United States)

    Ouyang, Yan

    2018-03-01

    Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.

  20. On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

    Science.gov (United States)

    Jan, A.; Painter, S. L.; Coon, E. T.

    2017-12-01

    Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the

  1. A Nakanishi-based model illustrating the covariant extension of the pion GPD overlap representation and its ambiguities

    Science.gov (United States)

    Chouika, N.; Mezrag, C.; Moutarde, H.; Rodríguez-Quintero, J.

    2018-05-01

    A systematic approach for the model building of Generalized Parton Distributions (GPDs), based on their overlap representation within the DGLAP kinematic region and a further covariant extension to the ERBL one, is applied to the valence-quark pion's case, using light-front wave functions inspired by the Nakanishi representation of the pion Bethe-Salpeter amplitudes (BSA). This simple but fruitful pion GPD model illustrates the general model building technique and, in addition, allows for the ambiguities related to the covariant extension, grounded on the Double Distribution (DD) representation, to be constrained by requiring a soft-pion theorem to be properly observed.

  2. Inflection of modern Icelandic nouns, adjectives and adverbs

    Directory of Open Access Journals (Sweden)

    Janez Orešnik

    1976-12-01

    Full Text Available The present paper is a list of Modern Icelandic nouns, adjectives, and adverbs, analysed into their respective stems and endings; the declension of the suffixed definite article is also included. Under each item it is stated which rules, if any, apply in the derivation of its grammatical forms. The following items of the list should be consulted for new phonological rules: (3, (11, (12, and (133. A grammatical innovation has been implemented in the list, namely the so-called REPLACING ENDINGS. These are not added after the last segment of the stem, as endings usually are, but replace the last segment(s of the stem. More is said on replacing endings in the Introduction.

  3. An analysis of Pitch Patterns of English Adjective + Noun Pharases in Model Reading and Some Educational Implications

    OpenAIRE

    Iwai, Mie; Yamada, Jun

    2009-01-01

    A basic English accent rule for a noun phrase consisting of an adjective and a noun is that the head,o r noun,is accented unless the adjective is contrastively focused in the context. A question of interest for Japanese learners of English is to what extent this basic principle is observed in model reading to which the learners may be exposed in their English classrooms. This study measured F0 values of adjectives and nouns in noun phrases which appeared in model English reading on commercial...

  4. Comparison of single-word and adjective-noun phrase production using event-related brain potentials

    DEFF Research Database (Denmark)

    Lange, Violaine Michel

    2015-01-01

    stimuli varying in complexity -black and white line drawings, coloured line drawings, and arrays of drawings-in participants producing single nouns. Whilst naming latencies were similar for single noun production between visual stimuli conditions, ERPs differed between drawing arrays and single drawings...... in a time-window extending beyond early visual analysis. In a second experiment, different participants were asked to produce either single noun or adjective-noun dual-word phrases to black-and-white and coloured line drawings, respectively. Adjective-noun phrase production (2W) resulted in naming latencies...

  5. Model's sparse representation based on reduced mixed GMsFE basis methods

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn [Institute of Mathematics, Hunan University, Changsha 410082 (China); Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn [College of Mathematics and Econometrics, Hunan University, Changsha 410082 (China)

    2017-06-01

    In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in

  6. Model-based object classification using unification grammars and abstract representations

    Science.gov (United States)

    Liburdy, Kathleen A.; Schalkoff, Robert J.

    1993-04-01

    The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

  7. A fast image encryption system based on chaotic maps with finite precision representation

    International Nuclear Information System (INIS)

    Kwok, H.S.; Tang, Wallace K.S.

    2007-01-01

    In this paper, a fast chaos-based image encryption system with stream cipher structure is proposed. In order to achieve a fast throughput and facilitate hardware realization, 32-bit precision representation with fixed point arithmetic is assumed. The major core of the encryption system is a pseudo-random keystream generator based on a cascade of chaotic maps, serving the purpose of sequence generation and random mixing. Unlike the other existing chaos-based pseudo-random number generators, the proposed keystream generator not only achieves a very fast throughput, but also passes the statistical tests of up-to-date test suite even under quantization. The overall design of the image encryption system is to be explained while detail cryptanalysis is given and compared with some existing schemes

  8. Force Concept Inventory-Based Multiple-Choice Test for Investigating Students' Representational Consistency

    Science.gov (United States)

    Nieminen, Pasi; Savinainen, Antti; Viiri, Jouni

    2010-01-01

    This study investigates students' ability to interpret multiple representations consistently (i.e., representational consistency) in the context of the force concept. For this purpose we developed the Representational Variant of the Force Concept Inventory (R-FCI), which makes use of nine items from the 1995 version of the Force Concept Inventory…

  9. Rigid Body Attitude Control Based on a Manifold Representation of Direction Cosine Matrices

    International Nuclear Information System (INIS)

    Nakath, David; Clemens, Joachim; Rachuy, Carsten

    2017-01-01

    Autonomous systems typically actively observe certain aspects of their surroundings, which makes them dependent on a suitable controller. However, building an attitude controller for three degrees of freedom is a challenging task, mainly due to singularities in the different parametrizations of the three dimensional rotation group SO (3). Thus, we propose an attitude controller based on a manifold representation of direction cosine matrices: In state space, the attitude is globally and uniquely represented as a direction cosine matrix R ∈ SO (3). However, differences in the state space, i.e., the attitude errors, are exposed to the controller in the vector space ℝ 3 . This is achieved by an operator, which integrates the matrix logarithm mapping from SO (3) to so(3) and the map from so(3) to ℝ 3 . Based on this representation, we derive a proportional and derivative feedback controller, whose output has an upper bound to prevent actuator saturation. Additionally, the feedback is preprocessed by a particle filter to account for measurement and state transition noise. We evaluate our approach in a simulator in three different spacecraft maneuver scenarios: (i) stabilizing, (ii) rest-to-rest, and (iii) nadir-pointing. The controller exhibits stable behavior from initial attitudes near and far from the setpoint. Furthermore, it is able to stabilize a spacecraft and can be used for nadir-pointing maneuvers. (paper)

  10. Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

    Science.gov (United States)

    Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.

    2018-02-01

    The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental design study to test the effectiveness of a model-based curriculum focused on the concepts of natural selection and population ecology that makes use of Excel modeling tools (Modeling Instruction in Biology with Excel, MBI-E). The curriculum revolves around the bio-engineering practice of controlling an invasive species. The study takes place in the Midwest within ten high schools teaching a regular-level introductory biology class. A post-test was designed that targeted a number of common misconceptions in both concept areas as well as representational usage. The results of a post-test demonstrate that the MBI-E students significantly outperformed the traditional classes in both natural selection and population ecology concepts, thus overcoming a number of misconceptions. In addition, implementing students made use of more multiple representations as well as demonstrating greater fascination for science.

  11. Improving Mobility Performance in Low Vision With a Distance-Based Representation of the Visual Scene.

    Science.gov (United States)

    van Rheede, Joram J; Wilson, Iain R; Qian, Rose I; Downes, Susan M; Kennard, Christopher; Hicks, Stephen L

    2015-07-01

    Severe visual impairment can have a profound impact on personal independence through its effect on mobility. We investigated whether the mobility of people with vision low enough to be registered as blind could be improved by presenting the visual environment in a distance-based manner for easier detection of obstacles. We accomplished this by developing a pair of "residual vision glasses" (RVGs) that use a head-mounted depth camera and displays to present information about the distance of obstacles to the wearer as brightness, such that obstacles closer to the wearer are represented more brightly. We assessed the impact of the RVGs on the mobility performance of visually impaired participants during the completion of a set of obstacle courses. Participant position was monitored continuously, which enabled us to capture the temporal dynamics of mobility performance. This allowed us to find correlates of obstacle detection and hesitations in walking behavior, in addition to the more commonly used measures of trial completion time and number of collisions. All participants were able to use the smart glasses to navigate the course, and mobility performance improved for those visually impaired participants with the worst prior mobility performance. However, walking speed was slower and hesitations increased with the altered visual representation. A depth-based representation of the visual environment may offer low vision patients improvements in independent mobility. It is important for further work to explore whether practice can overcome the reductions in speed and increased hesitation that were observed in our trial.

  12. Alchemical and structural distribution based representation for universal quantum machine learning

    Science.gov (United States)

    Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole

    2018-06-01

    We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.

  13. The effect of project-based learning on students' statistical literacy levels for data representation

    Science.gov (United States)

    Koparan, Timur; Güven, Bülent

    2015-07-01

    The point of this study is to define the effect of project-based learning approach on 8th Grade secondary-school students' statistical literacy levels for data representation. To achieve this goal, a test which consists of 12 open-ended questions in accordance with the views of experts was developed. Seventy 8th grade secondary-school students, 35 in the experimental group and 35 in the control group, took this test twice, one before the application and one after the application. All the raw scores were turned into linear points by using the Winsteps 3.72 modelling program that makes the Rasch analysis and t-tests, and an ANCOVA analysis was carried out with the linear points. Depending on the findings, it was concluded that the project-based learning approach increases students' level of statistical literacy for data representation. Students' levels of statistical literacy before and after the application were shown through the obtained person-item maps.

  14. Problem solving based learning model with multiple representations to improve student's mental modelling ability on physics

    Science.gov (United States)

    Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran

    2017-08-01

    Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.

  15. A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, J. D. (Prostat, Mesa, AZ); Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)

    2006-10-01

    Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.

  16. Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Chen, Ken Chung [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Stomatology, National Cheng Kung University Medical College and Hospital, Tainan, Taiwan 70403 (China); Shen, Steve G. F.; Yan, Jin [Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Lee, Philip K. M.; Chow, Ben [Hong Kong Dental Implant and Maxillofacial Centre, Hong Kong, China 999077 (China); Liu, Nancy X. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing, China 100050 (China); Xia, James J. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 (United States); Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, New York 10065 (United States); Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul, 136701 (Korea, Republic of)

    2014-04-15

    Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

  17. Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

    International Nuclear Information System (INIS)

    Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang; Chen, Ken Chung; Shen, Steve G. F.; Yan, Jin; Lee, Philip K. M.; Chow, Ben; Liu, Nancy X.; Xia, James J.; Shen, Dinggang

    2014-01-01

    Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

  18. A Discussion on Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

    Data.gov (United States)

    National Aeronautics and Space Administration — This article presented a discussion on uncertainty representation and management for model-based prog- nostics methodologies based on the Bayesian tracking framework...

  19. Descriptive and discourse-referential modifiers in a layered model of the noun phrase

    DEFF Research Database (Denmark)

    Rijkhoff, Jan

    2008-01-01

    This article argues that adnominal modifiers in a layered model of the noun phrase can be divided into two major subcategories: descriptive modifiers and discourse-referential modifiers. Whereas descriptive modifiers can be subdivided into classifying, qualifying, quantifying and localizing...... modifiers (section 2), discourse-referential modifiers in the noun phrase are concerned with the status of entities as referents in the world of discourse (section 3). I will pay particular attention to three issues: (i) formal reflections of the layered, semantic structure of the noun phrase (section 4...

  20. Locality-preserving sparse representation-based classification in hyperspectral imagery

    Science.gov (United States)

    Gao, Lianru; Yu, Haoyang; Zhang, Bing; Li, Qingting

    2016-10-01

    This paper proposes to combine locality-preserving projections (LPP) and sparse representation (SR) for hyperspectral image classification. The LPP is first used to reduce the dimensionality of all the training and testing data by finding the optimal linear approximations to the eigenfunctions of the Laplace Beltrami operator on the manifold, where the high-dimensional data lies. Then, SR codes the projected testing pixels as sparse linear combinations of all the training samples to classify the testing pixels by evaluating which class leads to the minimum approximation error. The integration of LPP and SR represents an innovative contribution to the literature. The proposed approach, called locality-preserving SR-based classification, addresses the imbalance between high dimensionality of hyperspectral data and the limited number of training samples. Experimental results on three real hyperspectral data sets demonstrate that the proposed approach outperforms the original counterpart, i.e., SR-based classification.

  1. Tensor-based cortical surface morphometry via weighted spherical harmonic representation.

    Science.gov (United States)

    Chung, Moo K; Dalton, Kim M; Davidson, Richard J

    2008-08-01

    We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric tensors, which are obtained from the smooth functional parametrization of a cortical mesh. For the smooth parametrization, we have developed a novel weighted spherical harmonic (SPHARM) representation, which generalizes the traditional SPHARM as a special case. For a specific choice of weights, the weighted-SPHARM is shown to be the least squares approximation to the solution of an isotropic heat diffusion on a unit sphere. The main aims of this paper are to present the weighted-SPHARM and to show how it can be used in the tensor-based morphometry. As an illustration, the methodology has been applied in the problem of detecting abnormal cortical regions in the group of high functioning autistic subjects.

  2. Coupling ontology driven semantic representation with multilingual natural language generation for tuning international terminologies.

    Science.gov (United States)

    Rassinoux, Anne-Marie; Baud, Robert H; Rodrigues, Jean-Marie; Lovis, Christian; Geissbühler, Antoine

    2007-01-01

    The importance of clinical communication between providers, consumers and others, as well as the requisite for computer interoperability, strengthens the need for sharing common accepted terminologies. Under the directives of the World Health Organization (WHO), an approach is currently being conducted in Australia to adopt a standardized terminology for medical procedures that is intended to become an international reference. In order to achieve such a standard, a collaborative approach is adopted, in line with the successful experiment conducted for the development of the new French coding system CCAM. Different coding centres are involved in setting up a semantic representation of each term using a formal ontological structure expressed through a logic-based representation language. From this language-independent representation, multilingual natural language generation (NLG) is performed to produce noun phrases in various languages that are further compared for consistency with the original terms. Outcomes are presented for the assessment of the International Classification of Health Interventions (ICHI) and its translation into Portuguese. The initial results clearly emphasize the feasibility and cost-effectiveness of the proposed method for handling both a different classification and an additional language. NLG tools, based on ontology driven semantic representation, facilitate the discovery of ambiguous and inconsistent terms, and, as such, should be promoted for establishing coherent international terminologies.

  3. Radiation exposure map based on fuzzy logic for the representation of areas with high natural background

    International Nuclear Information System (INIS)

    Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira

    2009-01-01

    The identification of areas with high concentrations of natural radionuclides is an important task in classifying these areas in relation to the health risk for residents in the region. The aim of this work is to identify areas of high exposure to nuclear radiation using a geographic representation based on the theory of fuzzy sets. Radiometric data obtained from previous works developed in a region of high concentrations in natural uranium were used to create a fuzzy map of the local radiation levels. During the image processing, a nonlinear filter was applied to eliminate noise i.e. to reduce isolated pixels that would eventually cause major uncertainties in the results. A resulting image was geographically positioned (WGS40) and obtained in gray scale. This image was fuzzified for membership functions that represent linguistic variables as low exposure, medium exposure and high exposure. After representing the membership grade in a RGB (red, green and blue) image it was possible to visualize the radiation level in the area of exposure. When compared to data from the region, results demonstrated the good efficiency of the technique here employed for the representation of areas with high radioactivity levels. The image obtained also provided important information about those areas where exposure to radiation is more pronounced. Hence, the fuzzy map can be applied in decision-making of experts when a risk situation is identified. (author)

  4. Prediction of Protein-Protein Interaction By Metasample-Based Sparse Representation

    Directory of Open Access Journals (Sweden)

    Xiuquan Du

    2015-01-01

    Full Text Available Protein-protein interactions (PPIs play key roles in many cellular processes such as transcription regulation, cell metabolism, and endocrine function. Understanding these interactions takes a great promotion to the pathogenesis and treatment of various diseases. A large amount of data has been generated by experimental techniques; however, most of these data are usually incomplete or noisy, and the current biological experimental techniques are always very time-consuming and expensive. In this paper, we proposed a novel method (metasample-based sparse representation classification, MSRC for PPIs prediction. A group of metasamples are extracted from the original training samples and then use the l1-regularized least square method to express a new testing sample as the linear combination of these metasamples. PPIs prediction is achieved by using a discrimination function defined in the representation coefficients. The MSRC is applied to PPIs dataset; it achieves 84.9% sensitivity, and 94.55% specificity, which is slightly lower than support vector machine (SVM and much higher than naive Bayes (NB, neural networks (NN, and k-nearest neighbor (KNN. The result shows that the MSRC is efficient for PPIs prediction.

  5. Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach.

    Science.gov (United States)

    Li, Qing; Liang, Steven Y

    2018-04-20

    Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method.

  6. Structure-reactivity modeling using mixture-based representation of chemical reactions.

    Science.gov (United States)

    Polishchuk, Pavel; Madzhidov, Timur; Gimadiev, Timur; Bodrov, Andrey; Nugmanov, Ramil; Varnek, Alexandre

    2017-09-01

    We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn't need an explicit labeling of a reaction center. The rigorous "product-out" cross-validation (CV) strategy has been suggested. Unlike the naïve "reaction-out" CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new "mixture" approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling.

  7. Attention-spreading based on hierarchical spatial representations for connected objects.

    Science.gov (United States)

    Kasai, Tetsuko

    2010-01-01

    Attention selects objects or groups as the most fundamental unit, and this may be achieved through a process in which attention automatically spreads throughout their entire region. Previously, we found that a lateralized potential relative to an attended hemifield at occipito-temporal electrode sites reflects attention-spreading in response to connected bilateral stimuli [Kasai, T., & Kondo, M. Electrophysiological correlates of attention-spreading in visual grouping. NeuroReport, 18, 93-98, 2007]. The present study examined the nature of object representations by manipulating the extent of grouping through connectedness, while controlling the symmetrical structure of bilateral stimuli. The electrophysiological results of two experiments consistently indicated that attention was guided twice in association with perceptual grouping in the early phase (N1, 150-200 msec poststimulus) and with the unity of an object in the later phase (N2pc, 310/330-390 msec). This suggests that there are two processes in object-based spatial selection, and these are discussed with regard to their cognitive mechanisms and object representations.

  8. No functional role of attention-based rehearsal in maintenance of spatial working memory representations.

    Science.gov (United States)

    Belopolsky, Artem V; Theeuwes, Jan

    2009-10-01

    The present study systematically examined the role of attention in maintenance of spatial representations in working memory as proposed by the attention-based rehearsal hypothesis [Awh, E., Jonides, J., & Reuter-Lorenz, P. A. (1998). Rehearsal in spatial working memory. Journal of Experimental Psychology--Human Perception and Performance, 24(3), 780-790]. Three main issues were examined. First, Experiments 1-3 demonstrated that inhibition and not facilitation of visual processing is often observed at the memorized location during the retention interval. This inhibition was caused by keeping a location in memory and not by the exogenous nature of the memory cue. Second, Experiment 4 showed that inhibition of the memorized location does not lead to any significant impairment in memory accuracy. Finally, Experiment 5 connected current results to the previous findings and demonstrated facilitation of processing at the memorized location. Importantly, facilitation of processing did not lead to more accurate memory performance. The present results challenge the functional role of attention in maintenance of spatial working memory representations.

  9. Aspect-Aided Dynamic Non-Negative Sparse Representation-Based Microwave Image Classification

    Directory of Open Access Journals (Sweden)

    Xinzheng Zhang

    2016-09-01

    Full Text Available Classification of target microwave images is an important application in much areas such as security, surveillance, etc. With respect to the task of microwave image classification, a recognition algorithm based on aspect-aided dynamic non-negative least square (ADNNLS sparse representation is proposed. Firstly, an aspect sector is determined, the center of which is the estimated aspect angle of the testing sample. The training samples in the aspect sector are divided into active atoms and inactive atoms by smooth self-representative learning. Secondly, for each testing sample, the corresponding active atoms are selected dynamically, thereby establishing dynamic dictionary. Thirdly, the testing sample is represented with ℓ 1 -regularized non-negative sparse representation under the corresponding dynamic dictionary. Finally, the class label of the testing sample is identified by use of the minimum reconstruction error. Verification of the proposed algorithm was conducted using the Moving and Stationary Target Acquisition and Recognition (MSTAR database which was acquired by synthetic aperture radar. Experiment results validated that the proposed approach was able to capture the local aspect characteristics of microwave images effectively, thereby improving the classification performance.

  10. Gender in facial representations: a contrast-based study of adaptation within and between the sexes.

    Science.gov (United States)

    Oruç, Ipek; Guo, Xiaoyue M; Barton, Jason J S

    2011-01-18

    Face aftereffects are proving to be an effective means of examining the properties of face-specific processes in the human visual system. We examined the role of gender in the neural representation of faces using a contrast-based adaptation method. If faces of different genders share the same representational face space, then adaptation to a face of one gender should affect both same- and different-gender faces. Further, if these aftereffects differ in magnitude, this may indicate distinct gender-related factors in the organization of this face space. To control for a potential confound between physical similarity and gender, we used a Bayesian ideal observer and human discrimination data to construct a stimulus set in which pairs of different-gender faces were equally dissimilar as same-gender pairs. We found that the recognition of both same-gender and different-gender faces was suppressed following a brief exposure of 100 ms. Moreover, recognition was more suppressed for test faces of a different-gender than those of the same-gender as the adaptor, despite the equivalence in physical and psychophysical similarity. Our results suggest that male and female faces likely occupy the same face space, allowing transfer of aftereffects between the genders, but that there are special properties that emerge along gender-defining dimensions of this space.

  11. Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery.

    Science.gov (United States)

    Xie, Qi; Zhao, Qian; Meng, Deyu; Xu, Zongben

    2017-08-02

    It is well known that the sparsity/low-rank of a vector/matrix can be rationally measured by nonzero-entries-number ($l_0$ norm)/nonzero- singular-values-number (rank), respectively. However, data from real applications are often generated by the interaction of multiple factors, which obviously cannot be sufficiently represented by a vector/matrix, while a high order tensor is expected to provide more faithful representation to deliver the intrinsic structure underlying such data ensembles. Unlike the vector/matrix case, constructing a rational high order sparsity measure for tensor is a relatively harder task. To this aim, in this paper we propose a measure for tensor sparsity, called Kronecker-basis-representation based tensor sparsity measure (KBR briefly), which encodes both sparsity insights delivered by Tucker and CANDECOMP/PARAFAC (CP) low-rank decompositions for a general tensor. Then we study the KBR regularization minimization (KBRM) problem, and design an effective ADMM algorithm for solving it, where each involved parameter can be updated with closed-form equations. Such an efficient solver makes it possible to extend KBR to various tasks like tensor completion and tensor robust principal component analysis. A series of experiments, including multispectral image (MSI) denoising, MSI completion and background subtraction, substantiate the superiority of the proposed methods beyond state-of-the-arts.

  12. Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

    Science.gov (United States)

    Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

    2015-10-30

    Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Design of multiple representations e-learning resources based on a contextual approach for the basic physics course

    Science.gov (United States)

    Bakri, F.; Muliyati, D.

    2018-05-01

    This research aims to design e-learning resources with multiple representations based on a contextual approach for the Basic Physics Course. The research uses the research and development methods accordance Dick & Carey strategy. The development carried out in the digital laboratory of Physics Education Department, Mathematics and Science Faculty, Universitas Negeri Jakarta. The result of the process of product development with Dick & Carey strategy, have produced e-learning design of the Basic Physics Course is presented in multiple representations in contextual learning syntax. The appropriate of representation used in the design of learning basic physics include: concept map, video, figures, data tables of experiment results, charts of data tables, the verbal explanations, mathematical equations, problem and solutions example, and exercise. Multiple representations are presented in the form of contextual learning by stages: relating, experiencing, applying, transferring, and cooperating.

  14. Sparse Representation Based Range-Doppler Processing for Integrated OFDM Radar-Communication Networks

    Directory of Open Access Journals (Sweden)

    Bo Kong

    2017-01-01

    Full Text Available In an integrated radar-communication network, multiuser access techniques with minimal performance degradation and without range-Doppler ambiguities are required, especially in a dense user environment. In this paper, a multiuser access scheme with random subcarrier allocation mechanism is proposed for orthogonal frequency division multiplexing (OFDM based integrated radar-communication networks. The expression of modulation Symbol-Domain method combined with sparse representation (SR for range-Doppler estimation is introduced and a parallel reconstruction algorithm is employed. The radar target detection performance is improved with less spectrum occupation. Additionally, a Doppler frequency detector is exploited to decrease the computational complexity. Numerical simulations show that the proposed method outperforms the traditional modulation Symbol-Domain method under ideal and realistic nonideal scenarios.

  15. Hologram representation of design data in an expert system knowledge base

    Science.gov (United States)

    Shiva, S. G.; Klon, Peter F.

    1988-01-01

    A novel representational scheme for design object descriptions is presented. An abstract notion of modules and signals is developed as a conceptual foundation for the scheme. This abstraction relates the objects to the meaning of system descriptions. Anchored on this abstraction, a representational model which incorporates dynamic semantics for these objects is presented. This representational model is called a hologram scheme since it represents dual level information, namely, structural and semantic. The benefits of this scheme are presented.

  16. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    Directory of Open Access Journals (Sweden)

    Su Yang

    Full Text Available Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1 Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2 The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3 The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  17. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    Science.gov (United States)

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  18. Efficient Online Aggregates in Dense-Region-Based Data Cube Representations

    Science.gov (United States)

    Haddadin, Kais; Lauer, Tobias

    In-memory OLAP systems require a space-efficient representation of sparse data cubes in order to accommodate large data sets. On the other hand, most efficient online aggregation techniques, such as prefix sums, are built on dense array-based representations. These are often not applicable to real-world data due to the size of the arrays which usually cannot be compressed well, as most sparsity is removed during pre-processing. A possible solution is to identify dense regions in a sparse cube and only represent those using arrays, while storing sparse data separately, e.g. in a spatial index structure. Previous dense-region-based approaches have concentrated mainly on the effectiveness of the dense-region detection (i.e. on the space-efficiency of the result). However, especially in higher-dimensional cubes, data is usually more cluttered, resulting in a potentially large number of small dense regions, which negatively affects query performance on such a structure. In this paper, our focus is not only on space-efficiency but also on time-efficiency, both for the initial dense-region extraction and for queries carried out in the resulting hybrid data structure. We describe two methods to trade available memory for increased aggregate query performance. In addition, optimizations in our approach significantly reduce the time to build the initial data structure compared to former systems. Also, we present a straightforward adaptation of our approach to support multi-core or multi-processor architectures, which can further enhance query performance. Experiments with different real-world data sets show how various parameter settings can be used to adjust the efficiency and effectiveness of our algorithms.

  19. Differential Impairment of Noun and Verb Consequent to LH Lesions in Persian Aphasic Patients

    OpenAIRE

    Dr. Reza Nilipour; Rabeeh Ariaei; Dr. Hassan Ashayeri

    2003-01-01

    The major focus of this research is on the differential disruption of language abilities subsequent to brain damages as they relate to site and size of lesion, especially left hemisphere lesions which disrupt the production and processing of "Nouns" vs. "Verbs" as two functionally different lexical categories. Several clinical as well as experimental studies reported on different language have shown that nouns and verbs can be independently disrupted due to brain damage. A prevalent impairmen...

  20. Noun and verb differences in picture naming: past studies and new evidence.

    Science.gov (United States)

    Mätzig, Simone; Druks, Judit; Masterson, Jackie; Vigliocco, Gabriella

    2009-06-01

    We re-examine the double dissociation view of noun-verb differences by critically reviewing past lesion studies reporting selective noun or verb deficits in picture naming, and reporting the results of a new picture naming study carried out with aphasic patients and comparison participants. Since there are theoretical arguments and empirical evidence that verb processing is more demanding than noun processing, in the review we distinguished between cases that presented with large and small differences between nouns and verbs. We argued that the latter cases may be accounted for in terms of greater difficulty in processing verbs than nouns. For the cases reporting large differences between nouns and verbs we assessed consistency in lesion localization and consistency in diagnostic classification. More variability both in terms of diagnostic category and lesion sites was found among the verb impaired than the noun impaired patients. In the experimental study, nine aphasic patients and nine age matched neurologically unimpaired individuals carried out a picture naming study that used a large set of materials matched for age of acquisition and in addition to accuracy measures, latencies were also recorded. Despite the patients' variable language deficits, diagnostic category and the matched materials, all patients performed faster and more accurately in naming the object than the action pictures. The comparison participants performed similarly. We also carried out a qualitative analysis of the errors patients made and showed that different types of errors were made in response to object and action pictures. We concluded that action naming places more and different demands on the language processor than object naming. The conclusions of the literature review and the results of the experimental study are discussed in relation to claims previous studies have made on the basis of the double dissociation found between nouns and verbs. We argue that these claims are only

  1. Neural overlap of L1 and L2 semantic representations in speech: A decoding approach.

    Science.gov (United States)

    Van de Putte, Eowyn; De Baene, Wouter; Brass, Marcel; Duyck, Wouter

    2017-11-15

    Although research has now converged towards a consensus that both languages of a bilingual are represented in at least partly shared systems for language comprehension, it remains unclear whether both languages are represented in the same neural populations for production. We investigated the neural overlap between L1 and L2 semantic representations of translation equivalents using a production task in which the participants had to name pictures in L1 and L2. Using a decoding approach, we tested whether brain activity during the production of individual nouns in one language allowed predicting the production of the same concepts in the other language. Because both languages only share the underlying semantic representation (sensory and lexical overlap was maximally avoided), this would offer very strong evidence for neural overlap in semantic representations of bilinguals. Based on the brain activation for the individual concepts in one language in the bilateral occipito-temporal cortex and the inferior and the middle temporal gyrus, we could accurately predict the equivalent individual concepts in the other language. This indicates that these regions share semantic representations across L1 and L2 word production. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Transient Variable Caching in Java’s Stack-Based Intermediate Representation

    Directory of Open Access Journals (Sweden)

    Paul Týma

    1999-01-01

    Full Text Available Java’s stack‐based intermediate representation (IR is typically coerced to execute on register‐based architectures. Unoptimized compiled code dutifully replicates transient variable usage designated by the programmer and common optimization practices tend to introduce further usage (i.e., CSE, Loop‐invariant Code Motion, etc.. On register based machines, often transient variables are cached within registers (when available saving the expense of actually accessing memory. Unfortunately, in stack‐based environments because of the need to push and pop the transient values, further performance improvement is possible. This paper presents Transient Variable Caching (TVC, a technique for eliminating transient variable overhead whenever possible. This optimization would find a likely home in optimizers attached to the back of popular Java compilers. Side effects of the algorithm include significant instruction reordering and introduction of many stack‐manipulation operations. This combination has proven to greatly impede the ability to decompile stack‐based IR code sequences. The code that results from the transform is faster, smaller, and greatly impedes decompilation.

  3. Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation.

    Science.gov (United States)

    Yuan, Shasha; Zhou, Weidong; Wu, Qi; Zhang, Yanli

    2016-05-01

    Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

  4. Representational Thickness

    DEFF Research Database (Denmark)

    Mullins, Michael

    Contemporary communicational and informational processes contribute to the shaping of our physical environment by having a powerful influence on the process of design. Applications of virtual reality (VR) are transforming the way architecture is conceived and produced by introducing dynamic...... elements into the process of design. Through its immersive properties, virtual reality allows access to a spatial experience of a computer model very different to both screen based simulations as well as traditional forms of architectural representation. The dissertation focuses on processes of the current...... representation? How is virtual reality used in public participation and how do virtual environments affect participatory decision making? How does VR thus affect the physical world of built environment? Given the practical collaborative possibilities of immersive technology, how can they best be implemented...

  5. Enhancing students’ mathematical representation and selfefficacy through situation-based learning assisted by geometer’s sketchpad program

    Science.gov (United States)

    Sowanto; Kusumah, Y. S.

    2018-05-01

    This research was conducted based on the problem of a lack of students’ mathematical representation ability as well as self-efficacy in accomplishing mathematical tasks. To overcome this problem, this research used situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP). This research investigated students’ improvement of mathematical representation ability who were taught under situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP) and regular method that viewed from the whole students’ prior knowledge (high, average, and low level). In addition, this research investigated the difference of students’ self-efficacy after learning was given. This research belongs to quasi experiment research using non-equivalent control group design with purposive sampling. The result of this research showed that students’ enhancement in their mathematical representation ability taught under SBL assisted by GSP was better than the regular method. Also, there was no interaction between learning methods and students prior knowledge in student’ enhancement of mathematical representation ability. There was significant difference of students’ enhancement of mathematical representation ability taught under SBL assisted by GSP viewed from students’ prior knowledge. Furthermore, there was no significant difference in terms of self-efficacy between those who were taught by SBL assisted by GSP with the regular method.

  6. Patent Keyword Extraction Algorithm Based on Distributed Representation for Patent Classification

    Directory of Open Access Journals (Sweden)

    Jie Hu

    2018-02-01

    Full Text Available Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM classification, which are valuable when human-annotated keywords are not available. We used a standard benchmark dataset and a homemade patent dataset to evaluate the performance of PKEA. Our patent dataset includes 2500 patents from five distinct technological fields related to autonomous cars (GPS systems, lidar systems, object recognition systems, radar systems, and vehicle control systems. We compared our method with Frequency, Term Frequency-Inverse Document Frequency (TF-IDF, TextRank and Rapid Automatic Keyword Extraction (RAKE. The experimental results show that our proposed algorithm provides a promising way to extract keywords from patent texts for patent classification.

  7. A CONTRASTIVE ANALYSIS OF ARABIC AND ENGLISH NOUN PLURAL MARKERS

    Directory of Open Access Journals (Sweden)

    Aliyatul Himmah

    2015-01-01

    Full Text Available This paper is attempting to explore the plural markers in both Arabic and English. The data collected qualitatively are sorted to meet the scope of this paper. Through contrastive analysis, it is discovered that there are numerous significant differences rather than similarities in terms of syllable count start, patterns of plural nouns in relation to gender, regularity, regular vs irregular plural and internal vowel change. Moreover, Arabic has some uniqueness in its plural marking system. Being well informed on all of these might pave the way for second or foreign language learners to comprehensively understand the plural marking system in Arabic and English.   Tulisan ini mencoba untuk mengeksplorasi penanda jamak dalam bahasa Arab dan bahasa Inggris. Data yang dikumpulkan secara kualitatif diurutkan untuk memenuhi cakupan makalah ini. Melalui analisis kontrastif, ditemukan banyak perbedaan yang signifikan daripada kesamaan dalam segi jumlah awal suku kata, pola kata benda jamak dalam kaitannya dengan gender, keteraturan dan ketidakteraturan jamak, serta perubahan vokal. Selain itu, bahasa Arab memiliki beberapa keunikan dalam sistem menandai jamaknya. Memahami informasi hal tersebut dengan baik mungkin memudahkan pembelajar bahasa kedua atau asing untuk memahami secara komprehensif sistem penanda jamak dalam bahasa Arab dan Inggris

  8. Research-Based Worksheets on Using Multiple Representations in Science Classrooms

    Science.gov (United States)

    Hill, Matthew; Sharma, Manjula

    2015-01-01

    The ability to represent the world like a scientist is difficult to teach; it is more than simply knowing the representations (e.g., graphs, words, equations and diagrams). For meaningful science learning to take place, consideration needs to be given to explicitly integrating representations into instructional methods, linked to the content, and…

  9. Interleaved Practice with Multiple Representations: Analyses with Knowledge Tracing Based Techniques

    Science.gov (United States)

    Rau, Martina A.; Pardos, Zachary A.

    2012-01-01

    The goal of this paper is to use Knowledge Tracing to augment the results obtained from an experiment that investigated the effects of practice schedules using an intelligent tutoring system for fractions. Specifically, this experiment compared different practice schedules of multiple representations of fractions: representations were presented to…

  10. Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA

    Directory of Open Access Journals (Sweden)

    Shunfang Wang

    2015-12-01

    Full Text Available An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC, pseudo-amino acid composition (PseAAC and position specific scoring matrix (PSSM, are insufficient to represent protein sequence due to their single perspectives. Thus, this paper proposes two fusion feature representations of DipPSSM and PseAAPSSM to integrate PSSM with DipC and PseAAC, respectively. When constructing each fusion representation, we introduce the balance factors to value the importance of its components. The optimal values of the balance factors are sought by genetic algorithm. Due to the high dimensionality of the proposed representations, linear discriminant analysis (LDA is used to find its important low dimensional structure, which is essential for classification and location prediction. The numerical experiments on two public datasets with KNN classifier and cross-validation tests showed that in terms of the common indexes of sensitivity, specificity, accuracy and MCC, the proposed fusing representations outperform the traditional representations in protein sub-nuclear localization, and the representation treated by LDA outperforms the untreated one.

  11. Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA.

    Science.gov (United States)

    Wang, Shunfang; Liu, Shuhui

    2015-12-19

    An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC), pseudo-amino acid composition (PseAAC) and position specific scoring matrix (PSSM), are insufficient to represent protein sequence due to their single perspectives. Thus, this paper proposes two fusion feature representations of DipPSSM and PseAAPSSM to integrate PSSM with DipC and PseAAC, respectively. When constructing each fusion representation, we introduce the balance factors to value the importance of its components. The optimal values of the balance factors are sought by genetic algorithm. Due to the high dimensionality of the proposed representations, linear discriminant analysis (LDA) is used to find its important low dimensional structure, which is essential for classification and location prediction. The numerical experiments on two public datasets with KNN classifier and cross-validation tests showed that in terms of the common indexes of sensitivity, specificity, accuracy and MCC, the proposed fusing representations outperform the traditional representations in protein sub-nuclear localization, and the representation treated by LDA outperforms the untreated one.

  12. An application to pulmonary emphysema classification based on model of texton learning by sparse representation

    Science.gov (United States)

    Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2012-03-01

    We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

  13. Investigating shape representation using sensitivity to part- and axis-based transformations.

    Science.gov (United States)

    Denisova, Kristina; Feldman, Jacob; Su, Xiaotao; Singh, Manish

    2016-09-01

    Part- and axis-based approaches organize shape representations in terms of simple parts and their spatial relationships. Shape transformations that alter qualitative part structure have been shown to be more detectable than those that preserve it. We compared sensitivity to various transformations that change quantitative properties of parts and their spatial relationships, while preserving qualitative part structure. Shape transformations involving changes in length, width, curvature, orientation and location were applied to a small part attached to a larger base of a two-part shape. Increment thresholds were estimated for each transformation using a 2IFC procedure. Thresholds were converted into common units of shape difference to enable comparisons across transformations. Higher sensitivity was consistently found for transformations involving a parameter of a single part (length, width, curvature) than those involving spatial relations between two parts (relative orientation and location), suggesting a single-part superiority effect. Moreover, sensitivity to shifts in part location - a biomechanically implausible shape transformation - was consistently poorest. The influence of region-based geometry was investigated via stereoscopic manipulation of figure and ground. Sensitivity was compared across positive parts (protrusions) and negative parts (indentations) for transformations involving a change in orientation or location. For changes in part orientation (biomechanically plausible), sensitivity was better for positive than negative parts; whereas for changes in part location (biomechanically implausible), no systematic difference was observed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Speckle Reduction on Ultrasound Liver Images Based on a Sparse Representation over a Learned Dictionary

    Directory of Open Access Journals (Sweden)

    Mohamed Yaseen Jabarulla

    2018-05-01

    Full Text Available Ultrasound images are corrupted with multiplicative noise known as speckle, which reduces the effectiveness of image processing and hampers interpretation. This paper proposes a multiplicative speckle suppression technique for ultrasound liver images, based on a new signal reconstruction model known as sparse representation (SR over dictionary learning. In the proposed technique, the non-uniform multiplicative signal is first converted into additive noise using an enhanced homomorphic filter. This is followed by pixel-based total variation (TV regularization and patch-based SR over a dictionary trained using K-singular value decomposition (KSVD. Finally, the split Bregman algorithm is used to solve the optimization problem and estimate the de-speckled image. The simulations performed on both synthetic and clinical ultrasound images for speckle reduction, the proposed technique achieved peak signal-to-noise ratios of 35.537 dB for the dictionary trained on noisy image patches and 35.033 dB for the dictionary trained using a set of reference ultrasound image patches. Further, the evaluation results show that the proposed method performs better than other state-of-the-art denoising algorithms in terms of both peak signal-to-noise ratio and subjective visual quality assessment.

  15. Action Priority: Early Neurophysiological Interaction of Conceptual and Motor Representations

    Science.gov (United States)

    Koester, Dirk; Schack, Thomas

    2016-01-01

    Handling our everyday life, we often react manually to verbal requests or instruction, but the functional interrelations of motor control and language are not fully understood yet, especially their neurophysiological basis. Here, we investigated whether specific motor representations for grip types interact neurophysiologically with conceptual information, that is, when reading nouns. Participants performed lexical decisions and, for words, executed a grasp-and-lift task on objects of different sizes involving precision or power grips while the electroencephalogram was recorded. Nouns could denote objects that require either a precision or a power grip and could, thus, be (in)congruent with the performed grasp. In a control block, participants pointed at the objects instead of grasping them. The main result revealed an event-related potential (ERP) interaction of grip type and conceptual information which was not present for pointing. Incongruent compared to congruent conditions elicited an increased positivity (100–200 ms after noun onset). Grip type effects were obtained in response-locked analyses of the grasping ERPs (100–300 ms at left anterior electrodes). These findings attest that grip type and conceptual information are functionally related when planning a grasping action but such an interaction could not be detected for pointing. Generally, the results suggest that control of behaviour can be modulated by task demands; conceptual noun information (i.e., associated action knowledge) may gain processing priority if the task requires a complex motor response. PMID:27973539

  16. Force Concept Inventory-based multiple-choice test for investigating students’ representational consistency

    Directory of Open Access Journals (Sweden)

    Pasi Nieminen

    2010-08-01

    Full Text Available This study investigates students’ ability to interpret multiple representations consistently (i.e., representational consistency in the context of the force concept. For this purpose we developed the Representational Variant of the Force Concept Inventory (R-FCI, which makes use of nine items from the 1995 version of the Force Concept Inventory (FCI. These original FCI items were redesigned using various representations (such as motion map, vectorial and graphical, yielding 27 multiple-choice items concerning four central concepts underpinning the force concept: Newton’s first, second, and third laws, and gravitation. We provide some evidence for the validity and reliability of the R-FCI; this analysis is limited to the student population of one Finnish high school. The students took the R-FCI at the beginning and at the end of their first high school physics course. We found that students’ (n=168 representational consistency (whether scientifically correct or not varied considerably depending on the concept. On average, representational consistency and scientifically correct understanding increased during the instruction, although in the post-test only a few students performed consistently both in terms of representations and scientifically correct understanding. We also compared students’ (n=87 results of the R-FCI and the FCI, and found that they correlated quite well.

  17. Students Mental Representation of Biology Diagrams/Pictures Conventions Based on Formation of Causal Network

    Science.gov (United States)

    Sampurno, A. W.; Rahmat, A.; Diana, S.

    2017-09-01

    Diagrams/pictures conventions is one form of visual media that often used to assist students in understanding the biological concepts. The effectiveness of use diagrams/pictures in biology learning at school level has also been mostly reported. This study examines the ability of high school students in reading diagrams/pictures biological convention which is described by Mental Representation based on formation of causal networks. The study involved 30 students 11th grade MIA senior high school Banten Indonesia who are studying the excretory system. MR data obtained by Instrument worksheet, developed based on CNET-protocol, in which there are diagrams/drawings of nephron structure and urinary mechanism. Three patterns formed MR, namely Markov chain, feedback control with a single measurement, and repeated feedback control with multiple measurement. The third pattern is the most dominating pattern, differences in the pattern of MR reveal the difference in how and from which point the students begin to uncover important information contained in the diagram to establish a causal networks. Further analysis shows that a difference in the pattern of MR relate to how complex the students process the information contained in the diagrams/pictures.

  18. Media Representations of Breech Birth: A Prospective Analysis of Web-Based News Reports.

    Science.gov (United States)

    Petrovska, Karolina; Sheehan, Athena; Homer, Caroline S E

    2017-07-01

    Recent research has demonstrated that the media presentation of childbirth is highly medicalized, often portraying birth as risky and dramatic. Media representation of breech presentation and birth is unexplored in this context. This study aimed to explore the content and tone of news media reports relating to breech presentation and breech birth. Google alerts were created using the terms breech and breech birth in online English-language news sites over a 3-year period from January 1, 2013, to December 31, 2015. Alerts were received daily and filed for analysis, and data were analyzed to generate themes. A total of 138 web-based news reports were gathered from 9 countries. Five themes that arose from the data included the problem of breech presentation, the high drama of vaginal breech birth, the safe option of cesarean birth versus dangers of vaginal breech birth, the defiant mother versus the saintly mother, and vaginal breech birth and medical misadventure. Media reports in this study predominantly demonstrated negative views toward breech presentation and vaginal breech birth. Cesarean birth was portrayed as the safe option for breech birth, while vaginal breech birth was associated with poor outcomes. Media presentations may impact decision making about mode of birth for pregnant women with a breech fetus. Health care providers can play an important role in balancing the media depiction of planned vaginal breech birth by providing nonjudgmental, evidence-based information to such women to facilitate informed decision making for birth. © 2017 by the American College of Nurse-Midwives.

  19. An Address Event Representation-Based Processing System for a Biped Robot

    Directory of Open Access Journals (Sweden)

    Uziel Jaramillo-Avila

    2016-02-01

    Full Text Available In recent years, several important advances have been made in the fields of both biologically inspired sensorial processing and locomotion systems, such as Address Event Representation-based cameras (or Dynamic Vision Sensors and in human-like robot locomotion, e.g., the walking of a biped robot. However, making these fields merge properly is not an easy task. In this regard, Neuromorphic Engineering is a fast-growing research field, the main goal of which is the biologically inspired design of hybrid hardware systems in order to mimic neural architectures and to process information in the manner of the brain. However, few robotic applications exist to illustrate them. The main goal of this work is to demonstrate, by creating a closed-loop system using only bio-inspired techniques, how such applications can work properly. We present an algorithm using Spiking Neural Networks (SNN for a biped robot equipped with a Dynamic Vision Sensor, which is designed to follow a line drawn on the floor. This is a commonly used method for demonstrating control techniques. Most of them are fairly simple to implement without very sophisticated components; however, it can still serve as a good test in more elaborate circumstances. In addition, the locomotion system proposed is able to coordinately control the six DOFs of a biped robot in switching between basic forms of movement. The latter has been implemented as a FPGA-based neuromorphic system. Numerical tests and hardware validation are presented.

  20. Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism.

    Science.gov (United States)

    Liu, Qingping; Wang, Jiahao; Zhu, Yan; He, Yongqun

    2017-12-21

    Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive information source for these drugs is still missing, and their anti-rheumatism mechanisms remain unclear. An ontology for anti-rheumatism traditional Chinese drugs would strongly support the representation, analysis, and understanding of these drugs. In this study, we first systematically collected reported information about 26 traditional Chinese decoction pieces drugs, including their chemical ingredients and adverse events (AEs). By mostly reusing terms from existing ontologies (e.g., TCMDPO for traditional Chinese medicines, NCBITaxon for taxonomy, ChEBI for chemical elements, and OAE for adverse events) and making semantic axioms linking different entities, we developed the Ontology of Chinese Medicine for Rheumatism (OCMR) that includes over 3000 class terms. Our OCMR analysis found that these 26 traditional Chinese decoction pieces are made from anatomic entities (e.g., root and stem) from 3 Bilateria animals and 23 Mesangiospermae plants. Anti-inflammatory and antineoplastic roles are important for anti-rheumatism drugs. Using the total of 555 unique ChEBI chemical entities identified from these drugs, our ChEBI-based classification analysis identified 18 anti-inflammatory, 33 antineoplastic chemicals, and 9 chemicals (including 3 diterpenoids and 3 triterpenoids) having both anti-inflammatory and antineoplastic roles. Furthermore, our study detected 22 diterpenoids and 23 triterpenoids, including 16 pentacyclic triterpenoids that are likely bioactive against rheumatism. Six drugs were found to be associated with 184 unique AEs, including three AEs (i.e., dizziness, nausea and vomiting, and anorexia) each associated with 5 drugs. Several chemical entities are classified as neurotoxins (e.g., diethyl phthalate) and allergens (e

  1. Morpho-semantic properties of Serbian nouns: Animacy and gender pairs

    Directory of Open Access Journals (Sweden)

    Radanović Jelena

    2011-01-01

    Full Text Available In this study we investigated whether and how the cognitive system uses morphological markedness of animacy and gender pairs. In the Serbian language masculine nouns are marked for animacy (i.e., genitive-accusative syncretism, while for feminine nouns the animacy distinction is purely semantic. Thus, in Experiment 1 we used this natural, linguistic differentiation to test whether morphological markedness of animacy influences lexical processing. In the same experiment, we tested whether the cognitive system is sensitive to the fact that some animate nouns have a sibling in the other gender (e.g., dečak /”boy”/ - devojčica /”girl”/, while others do not have it (e.g., vojnik /”soldier”/ or žirafa /”giraffe”/. We labeled this indicator sibling presence. The analysis did not confirm the effect of animacy, neither between nor within genders. However, animate nouns with a sibling were processed faster than those without a sibling. Since the majority of sibling nouns are morphologically related (like konobar /”waiter”/ - konobarica /”waitress”/, while the rest are not (e.g., petao /”rooster”/ - kokoška /”hen”/, in Experiment 2 we tested whether morphological relatedness contributed to the effect of sibling presence. Results showed that this is not the case: morphologically related and unrelated masculine-feminine pairs of nouns (siblings were processed equally fast. Furthermore, an interaction between the target’s frequency and the frequency of its sibling was observed: nouns with a more frequent sibling benefited more from their own frequency than those with a less frequent sibling. We argue that sibling support is realized through semantic, not morphological relations. Taken together, our findings suggest that morphological markedness is not used in lexical processing, which is in line with an amorphous approach to lexical processing.

  2. Comprehensive evaluation of SNP identification with the Restriction Enzyme-based Reduced Representation Library (RRL method

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    Du Ye

    2012-02-01

    Full Text Available Abstract Background Restriction Enzyme-based Reduced Representation Library (RRL method represents a relatively feasible and flexible strategy used for Single Nucleotide Polymorphism (SNP identification in different species. It has remarkable advantage of reducing the complexity of the genome by orders of magnitude. However, comprehensive evaluation for actual efficacy of SNP identification by this method is still unavailable. Results In order to evaluate the efficacy of Restriction Enzyme-based RRL method, we selected Tsp 45I enzyme which covers 266 Mb flanking region of the enzyme recognition site according to in silico simulation on human reference genome, then we sequenced YH RRL after Tsp 45I treatment and obtained reads of which 80.8% were mapped to target region with an 20-fold average coverage, about 96.8% of target region was covered by at least one read and 257 K SNPs were identified in the region using SOAPsnp software. Compared with whole genome resequencing data, we observed false discovery rate (FDR of 13.95% and false negative rate (FNR of 25.90%. The concordance rate of homozygote loci was over 99.8%, but that of heterozygote were only 92.56%. Repeat sequences and bases quality were proved to have a great effect on the accuracy of SNP calling, SNPs in recognition sites contributed evidently to the high FNR and the low concordance rate of heterozygote. Our results indicated that repeat masking and high stringent filter criteria could significantly decrease both FDR and FNR. Conclusions This study demonstrates that Restriction Enzyme-based RRL method was effective for SNP identification. The results highlight the important role of bias and the method-derived defects represented in this method and emphasize the special attentions noteworthy.

  3. Applying representational state transfer (REST) architecture to archetype-based electronic health record systems

    Science.gov (United States)

    2013-01-01

    Background The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content. The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored. Results The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored. A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping. Conclusions Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications. PMID:23656624

  4. A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

    Science.gov (United States)

    Fiannaca, Antonino; La Rosa, Massimo; Rizzo, Riccardo; Urso, Alfonso

    2015-07-01

    In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed. In the proposed methodology, distinctive words are identified from a spectral representation of DNA sequences. A taxonomic classification of the DNA sequence is then performed using the sequence signature, i.e., the smallest set of k-mers that can assign a DNA sequence to its proper taxonomic category. Experiments were then performed to compare our method with other supervised machine learning classification algorithms, such as support vector machine, random forest, ripper, naïve Bayes, ridor, and classification tree, which also consider short DNA sequence fragments of 200 and 300 base pairs (bp). The experimental tests were conducted over 10 real barcode datasets belonging to different animal species, which were provided by the on-line resource "Barcode of Life Database". The experimental results showed that our k-mer-based approach is directly comparable, in terms of accuracy, recall and precision metrics, with the other classifiers when considering full-length sequences. In addition, we demonstrate the robustness of our method when a classification is performed task with a set of short DNA sequences that were randomly extracted from the original data. For example, the proposed method can reach the accuracy of 64.8% at the species level with 200-bp fragments. Under the same conditions, the best other classifier (random forest) reaches the accuracy of 20.9%. Our results indicate that we obtained a clear improvement over the other classifiers for the study of short DNA barcode sequence fragments. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Ontology-based data integration from heterogeneous urban systems : A knowledge representation framework for smart cities

    NARCIS (Netherlands)

    Psyllidis, A.

    2015-01-01

    This paper presents a novel knowledge representation framework for smart city planning and management that enables the semantic integration of heterogeneous urban data from diverse sources. Currently, the combination of information across city agencies is cumbersome, as the increasingly available

  6. Ontology-based representation and analysis of host-Brucella interactions.

    Science.gov (United States)

    Lin, Yu; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Biomedical ontologies are representations of classes of entities in the biomedical domain and how these classes are related in computer- and human-interpretable formats. Ontologies support data standardization and exchange and provide a basis for computer-assisted automated reasoning. IDOBRU is an ontology in the domain of Brucella and brucellosis. Brucella is a Gram-negative intracellular bacterium that causes brucellosis, the most common zoonotic disease in the world. In this study, IDOBRU is used as a platform to model and analyze how the hosts, especially host macrophages, interact with virulent Brucella strains or live attenuated Brucella vaccine strains. Such a study allows us to better integrate and understand intricate Brucella pathogenesis and host immunity mechanisms. Different levels of host-Brucella interactions based on different host cell types and Brucella strains were first defined ontologically. Three important processes of virulent Brucella interacting with host macrophages were represented: Brucella entry into macrophage, intracellular trafficking, and intracellular replication. Two Brucella pathogenesis mechanisms were ontologically represented: Brucella Type IV secretion system that supports intracellular trafficking and replication, and Brucella erythritol metabolism that participates in Brucella intracellular survival and pathogenesis. The host cell death pathway is critical to the outcome of host-Brucella interactions. For better survival and replication, virulent Brucella prevents macrophage cell death. However, live attenuated B. abortus vaccine strain RB51 induces caspase-2-mediated proinflammatory cell death. Brucella-associated cell death processes are represented in IDOBRU. The gene and protein information of 432 manually annotated Brucella virulence factors were represented using the Ontology of Genes and Genomes (OGG) and Protein Ontology (PRO), respectively. Seven inference rules were defined to capture the knowledge of host

  7. Pulmonary emphysema classification based on an improved texton learning model by sparse representation

    Science.gov (United States)

    Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2013-03-01

    In this paper, we present a texture classification method based on texton learned via sparse representation (SR) with new feature histogram maps in the classification of emphysema. First, an overcomplete dictionary of textons is learned via KSVD learning on every class image patches in the training dataset. In this stage, high-pass filter is introduced to exclude patches in smooth area to speed up the dictionary learning process. Second, 3D joint-SR coefficients and intensity histograms of the test images are used for characterizing regions of interest (ROIs) instead of conventional feature histograms constructed from SR coefficients of the test images over the dictionary. Classification is then performed using a classifier with distance as a histogram dissimilarity measure. Four hundreds and seventy annotated ROIs extracted from 14 test subjects, including 6 paraseptal emphysema (PSE) subjects, 5 centrilobular emphysema (CLE) subjects and 3 panlobular emphysema (PLE) subjects, are used to evaluate the effectiveness and robustness of the proposed method. The proposed method is tested on 167 PSE, 240 CLE and 63 PLE ROIs consisting of mild, moderate and severe pulmonary emphysema. The accuracy of the proposed system is around 74%, 88% and 89% for PSE, CLE and PLE, respectively.

  8. Information dimension analysis of bacterial essential and nonessential genes based on chaos game representation

    International Nuclear Information System (INIS)

    Zhou, Qian; Yu, Yong-ming

    2014-01-01

    Essential genes are indispensable for the survival of an organism. Investigating features associated with gene essentiality is fundamental to the prediction and identification of the essential genes. Selecting features associated with gene essentiality is fundamental to predict essential genes with computational techniques. We use fractal theory to make comparative analysis of essential and nonessential genes in bacteria. The information dimensions of essential genes and nonessential genes available in the DEG database for 27 bacteria are calculated based on their gene chaos game representations (CGRs). It is found that weak positive linear correlation exists between information dimension and gene length. Moreover, for genes of similar length, the average information dimension of essential genes is larger than that of nonessential genes. This indicates that essential genes show less regularity and higher complexity than nonessential genes. Our results show that for bacterium with a similar number of essential genes and nonessential genes, the CGR information dimension is helpful for the classification of essential genes and nonessential genes. Therefore, the gene CGR information dimension is very probably a useful gene feature for a genetic algorithm predicting essential genes. (paper)

  9. Foundations for Reasoning in Cognition-Based Computational Representations of Human Decision Making; TOPICAL

    International Nuclear Information System (INIS)

    SENGLAUB, MICHAEL E.; HARRIS, DAVID L.; RAYBOURN, ELAINE M.

    2001-01-01

    In exploring the question of how humans reason in ambiguous situations or in the absence of complete information, we stumbled onto a body of knowledge that addresses issues beyond the original scope of our effort. We have begun to understand the importance that philosophy, in particular the work of C. S. Peirce, plays in developing models of human cognition and of information theory in general. We have a foundation that can serve as a basis for further studies in cognition and decision making. Peircean philosophy provides a foundation for understanding human reasoning and capturing behavioral characteristics of decision makers due to cultural, physiological, and psychological effects. The present paper describes this philosophical approach to understanding the underpinnings of human reasoning. We present the work of C. S. Peirce, and define sets of fundamental reasoning behavior that would be captured in the mathematical constructs of these newer technologies and would be able to interact in an agent type framework. Further, we propose the adoption of a hybrid reasoning model based on his work for future computational representations or emulations of human cognition

  10. Emotional noun processing: an ERP study with rapid serial visual presentation.

    Directory of Open Access Journals (Sweden)

    Shengnan Yi

    Full Text Available Reading is an important part of our daily life, and rapid responses to emotional words have received a great deal of research interest. Our study employed rapid serial visual presentation to detect the time course of emotional noun processing using event-related potentials. We performed a dual-task experiment, where subjects were required to judge whether a given number was odd or even, and the category into which each emotional noun fit. In terms of P1, we found that there was no negativity bias for emotional nouns. However, emotional nouns elicited larger amplitudes in the N170 component in the left hemisphere than did neutral nouns. This finding indicated that in later processing stages, emotional words can be discriminated from neutral words. Furthermore, positive, negative, and neutral words were different from each other in the late positive complex, indicating that in the third stage, even different emotions can be discerned. Thus, our results indicate that in a three-stage model the latter two stages are more stable and universal.

  11. Emotional noun processing: an ERP study with rapid serial visual presentation.

    Science.gov (United States)

    Yi, Shengnan; He, Weiqi; Zhan, Lei; Qi, Zhengyang; Zhu, Chuanlin; Luo, Wenbo; Li, Hong

    2015-01-01

    Reading is an important part of our daily life, and rapid responses to emotional words have received a great deal of research interest. Our study employed rapid serial visual presentation to detect the time course of emotional noun processing using event-related potentials. We performed a dual-task experiment, where subjects were required to judge whether a given number was odd or even, and the category into which each emotional noun fit. In terms of P1, we found that there was no negativity bias for emotional nouns. However, emotional nouns elicited larger amplitudes in the N170 component in the left hemisphere than did neutral nouns. This finding indicated that in later processing stages, emotional words can be discriminated from neutral words. Furthermore, positive, negative, and neutral words were different from each other in the late positive complex, indicating that in the third stage, even different emotions can be discerned. Thus, our results indicate that in a three-stage model the latter two stages are more stable and universal.

  12. A three-dimensional approach to the gender/sex of nouns in Biblical Hebrew

    Directory of Open Access Journals (Sweden)

    J. H. Kroeze

    1994-05-01

    Full Text Available The phenomenon of the gender/sex of nouns is normally handled two-dimensionally. Two levels are distinguished: (grammatical gender and sex. Gender refers to the morphological and syntactic features of the noun, sex to the extralingual reality. This use of the term gender rests on the assumption that the morphological and syntactic features o f a noun are normally consistent. This assumption is tested and the results show that a three-dimensional approach would he better. In the relevant literature, there are indications of such a three-dimensional differentiation, where gender is used to indicate only the syntactic features of a noun. In this article it is proposed that morphological gender, syntactic gender and semantic gender (sex should be distinguished consistently. A list of 23 different combinations were found among nouns occurring most frequently. These combinations are illustrated with examples. Morphological, syntactic and semantic statistics are also given which illustrate the unique characteristics of the three levels.

  13. Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree

    Science.gov (United States)

    Chen, Qiyu; Liu, Gang; Ma, Xiaogang; Mariethoz, Gregoire; He, Zhenwen; Tian, Yiping; Weng, Zhengping

    2018-05-01

    Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently.

  14. Representation Discovery using Harmonic Analysis

    CERN Document Server

    Mahadevan, Sridhar

    2008-01-01

    Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particu

  15. Concreteness and relational effects on recall of adjective-noun pairs.

    Science.gov (United States)

    Paivio, A; Khan, M; Begg, I

    2000-09-01

    Extending previous research on the problem, we studied the effects of concreteness and relatedness of adjective-noun pairs on free recall, cued recall, and memory integration. Two experiments varied the attributes in paired associates lists or sentences. Consistent with predictions from dual coding theory and prior results with noun-noun pairs, both experiments showed that the effects of concreteness were strong and independent of relatedness in free recall and cued recall. The generally positive effects of relatedness were absent in the case of free recall of sentences. The two attributes also had independent (additive) effects on integrative memory as measured by conditionalized free recall of pairs. Integration as measured by the increment from free to cued recall occurred consistently only when pairs were high in both concreteness and relatedness. Explanations focused on dual coding and relational-distinctiveness processing theories as well as task variables that affect integration measures.

  16. Exploring atypical verb+noun combinations in learner technical writing

    Directory of Open Access Journals (Sweden)

    María José Luzón Marco

    2011-12-01

    Full Text Available Professional and academic discourse is characterised by a specific phraseology, which usually poses problems for students. This paper investigates atypical verb+noun collocations in a corpus of English technical writing of Spanish students. I focus on the type of verbs that most frequently occurred in these awkward or questionable combinations and attempt to explore the reasons why the learners deviate from NS's norms. The analysis indicates that these learners tend to have problems with a set of sub-technical and high-frequency verbs. Deviant combinations involving these verbs are frequently the result of a deficient knowledge of the phraseology of academic and technical discourse. The unawareness of collocations that are typical of this discourse often leads students to create V+N combinations by relying on the “Open Choice Principle” (Sinclair, 1991 or by using patterns from their mother tongue.El discurso profesional y académico se caracteriza por una fraseología específica, que suele plantear problemas a los estudiantes. Este artículo investiga colocaciones de verbo+nombre atípicas en un corpus de textos técnicos en inglés escritos por estudiantes españoles. El estudio se centra en los verbos que más frecuentemente aparecen en estas combinaciones atípicas y explora las razones por las que los estudiantes se desvían de la norma. El análisis indica que estos estudiantes suelen tener problemas con un grupo de verbos sub-técnicos y verbos de alta frecuencia. Las combinaciones atípicas en las que estos verbos aparecen son frecuentemente el resultado de un conocimiento deficiente de la fraseología del discurso académico y técnico. El desconocimiento de colocaciones que son típicas de este discurso a menudo lleva a los estudiantes a crear combinaciones basándose en el “principio de opción abierta” (Sinclair, 1991 o a usar colocaciones prestadas de su lengua materna.

  17. Visual tracking based on the sparse representation of the PCA subspace

    Science.gov (United States)

    Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

    2017-09-01

    We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

  18. Representations of abstract grammatical feature agreement in young children.

    Science.gov (United States)

    Melançon, Andréane; Shi, Rushen

    2015-11-01

    A fundamental question in language acquisition research is whether young children have abstract grammatical representations. We tested this question experimentally. French-learning 30-month-olds were first taught novel word-object pairs in the context of a gender-marked determiner (e.g., un MASC ravole 'a ravole'). Test trials presented the objects side-by-side while one of them was named in new phrases containing other determiners and an adjective (e.g., le MASC joli ravole MASC 'the pretty ravole'). The gender agreement between the new determiner and the non-adjacent noun was manipulated in different test trials (e.g., le MASC __ravole MASC; *la FEM __ravole MASC). We found that online comprehension of the named target was facilitated in gender-matched trials but impeded in gender-mismatched trials. That is, children assigned the determiner genders to the novel nouns during word learning. They then processed the non-adjacent gender agreement between the two categories (Det, Noun) during test. The results demonstrate abstract featural representation and grammatical productivity in young children.

  19. The construction of semantic memory: grammar based representations learned from relational episodic information

    Directory of Open Access Journals (Sweden)

    Francesco P Battaglia

    2011-08-01

    Full Text Available After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation, collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside-outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of ``sleep replay'' of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata.

  20. Multi-scale Gaussian representation and outline-learning based cell image segmentation

    Science.gov (United States)

    2013-01-01

    Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

  1. The Construction of Semantic Memory: Grammar-Based Representations Learned from Relational Episodic Information

    Science.gov (United States)

    Battaglia, Francesco P.; Pennartz, Cyriel M. A.

    2011-01-01

    After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation), collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside–outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of “sleep replay” of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata. PMID:21887143

  2. Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

    Science.gov (United States)

    Zou, Zhenzhen; Luo, Xinghong; Yu, Qiang

    2018-05-01

    Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to measure the changes of sample temperature, morphology and volume. Then, the specific heat, surface tension, viscosity changes and sample density can be obtained. Considering that the falling speed of the material sample droplet is approximately 31.3 m/s when it reaches the bottom of a 50-meter-high drop tube, a high-speed camera with a collection rate of up to 106 frames/s is required to image the falling droplet. However, at the high-speed mode, very few pixels, approximately 48-120, will be obtained in each exposure time, which results in low image quality. Super-resolution image reconstruction is an algorithm that provides finer details than the sampling grid of a given imaging device by increasing the number of pixels per unit area in the image. In this work, we demonstrate the application of single image-resolution reconstruction in the microgravity and electrostatic levitation for the first time. Here, using the image super-resolution method based on sparse representation, a low-resolution droplet image can be reconstructed. Employed Yang's related dictionary model, high- and low-resolution image patches were combined with dictionary training, and high- and low-resolution-related dictionaries were obtained. The online double-sparse dictionary training algorithm was used in the study of related dictionaries and overcome the shortcomings of the traditional training algorithm with small image patch. During the stage of image reconstruction, the algorithm of kernel regression is added, which effectively overcomes the shortcomings of the Yang image's edge blurs.

  3. The application of brain-based learning principles aided by GeoGebra to improve mathematical representation ability

    Science.gov (United States)

    Priatna, Nanang

    2017-08-01

    The use of Information and Communication Technology (ICT) in mathematics instruction will help students in building conceptual understanding. One of the software products used in mathematics instruction is GeoGebra. The program enables simple visualization of complex geometric concepts and helps improve students' understanding of geometric concepts. Instruction applying brain-based learning principles is one oriented at the efforts of naturally empowering the brain potentials which enable students to build their own knowledge. One of the goals of mathematics instruction in school is to develop mathematical communication ability. Mathematical representation is regarded as a part of mathematical communication. It is a description, expression, symbolization, or modeling of mathematical ideas/concepts as an attempt of clarifying meanings or seeking for solutions to the problems encountered by students. The research aims to develop a learning model and teaching materials by applying the principles of brain-based learning aided by GeoGebra to improve junior high school students' mathematical representation ability. It adopted a quasi-experimental method with the non-randomized control group pretest-posttest design and the 2x3 factorial model. Based on analysis of the data, it is found that the increase in the mathematical representation ability of students who were treated with mathematics instruction applying the brain-based learning principles aided by GeoGebra was greater than the increase of the students given conventional instruction, both as a whole and based on the categories of students' initial mathematical ability.

  4. The representation of grammatical categories in the brain.

    Science.gov (United States)

    Shapiro, Kevin; Caramazza, Alfonso

    2003-05-01

    Language relies on the rule-based combination of words with different grammatical properties, such as nouns and verbs. Yet most research on the problem of word retrieval has focused on the production of concrete nouns, leaving open a crucial question: how is knowledge about different grammatical categories represented in the brain, and what components of the language production system make use of it? Drawing on evidence from neuropsychology, electrophysiology and neuroimaging, we argue that information about a word's grammatical category might be represented independently of its meaning at the levels of word form and morphological computation.

  5. Why Are Verbs so Hard to Remember? Effects of Semantic Context on Memory for Verbs and Nouns

    Science.gov (United States)

    Earles, Julie L.; Kersten, Alan W.

    2017-01-01

    Three experiments test the theory that verb meanings are more malleable than noun meanings in different semantic contexts, making a previously seen verb difficult to remember when it appears in a new semantic context. Experiment 1 revealed that changing the direct object noun in a transitive sentence reduced recognition of a previously seen verb,…

  6. How Do Children Ascribe Gender to Nouns? A Study of Spanish-Speaking Children with and without Specific Language Impairment

    Science.gov (United States)

    Anderson, Raquel T.; Lockowitz, Alison

    2009-01-01

    The purpose of this investigation was to identify how Spanish-speaking preschool children with and without specific language impairment (SLI) use the various cues available for ascribing a noun's inherent gender in the language. Via an invented word task, four types of cues were isolated and presented to each child: (1) two types of noun-internal…

  7. Memory-Based Shallow Parsing

    NARCIS (Netherlands)

    Tjong Kim Sang, E.F.

    2002-01-01

    We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving

  8. 3D base: a geometrical data base system for the analysis and visualisation of 3D-shapes obtained from parallel serial sections including three different geometrical representations

    NARCIS (Netherlands)

    Verbeek, F. J.; de Groot, M. M.; Huijsmans, D. P.; Lamers, W. H.; Young, I. T.

    1993-01-01

    In this paper we discuss a geometrical data base that includes three different geometrical representations of one and the same reconstructed 3D shape: the contour-pile, the voxel enumeration, and the triangulation of a surface. The data base is tailored for 3D shapes obtained from plan-parallel

  9. Understanding representations in design

    DEFF Research Database (Denmark)

    Bødker, Susanne

    1998-01-01

    Representing computer applications and their use is an important aspect of design. In various ways, designers need to externalize design proposals and present them to other designers, users, or managers. This article deals with understanding design representations and the work they do in design....... The article is based on a series of theoretical concepts coming out of studies of scientific and other work practices and on practical experiences from design of computer applications. The article presents alternatives to the ideas that design representations are mappings of present or future work situations...... and computer applications. It suggests that representations are primarily containers of ideas and that representation is situated at the same time as representations are crossing boundaries between various design and use activities. As such, representations should be carriers of their own contexts regarding...

  10. MAP-Motivated Carrier Synchronization of GMSK Based on the Laurent AMP Representation

    Science.gov (United States)

    Simon, M. K.

    1998-01-01

    Using the MAP estimation approach to carrier synchronization of digital modulations containing ISI together with a two pulse stream AMP representation of GMSK, it is possible to obtain an optimum closed loop configuration in the same manner as has been previously proposed for other conventional modulations with ISI.

  11. Embodied Numerosity: Implicit Hand-Based Representations Influence Symbolic Number Processing across Cultures

    Science.gov (United States)

    Domahs, Frank; Moeller, Korbinian; Huber, Stefan; Willmes, Klaus; Nuerk, Hans-Christoph

    2010-01-01

    In recent years, a strong functional relationship between finger counting and number processing has been suggested. Developmental studies have shown specific effects of the structure of the individual finger counting system on arithmetic abilities. Moreover, the orientation of the mental quantity representation ("number line") seems to be…

  12. Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations

    NARCIS (Netherlands)

    van Noord, Rik; Bos, Johannes

    2017-01-01

    We evaluate the character-level translation method for neural semantic parsing on a large corpus of sentences annotated with Abstract Meaning Representations (AMRs). Using a sequence-to-sequence model, and some trivial preprocessing and postprocessing of AMRs, we obtain a baseline accuracy of 53.1

  13. Mis/Representations in School-Based Digital Media Production: An Ethnographic Exploration with Muslim Girls

    Science.gov (United States)

    Dahya, Negin; Jenson, Jennifer

    2015-01-01

    In this article, the authors discuss findings from a digital media production club with racialized girls in a low-income school in Toronto, Ontario. Specifically, the authors consider how student-produced media is impacted by ongoing postcolonial structures relating to power and representation in the school and in the media production work of…

  14. Getting the picture: The role of external representations in simulation-based inquiry learning.

    NARCIS (Netherlands)

    Kolloffel, Bas Jan

    2008-01-01

    Three studies were performed to examine the effects of formats of ‘pre-fabricated’ and learner-generated representations on learning outcomes of pupils learning combinatorics and probability theory. In Study I, the effects of different formats on learning outcomes were examined. Learners in five

  15. Quantum Computation-Based Image Representation, Processing Operations and Their Applications

    Directory of Open Access Journals (Sweden)

    Fei Yan

    2014-10-01

    Full Text Available A flexible representation of quantum images (FRQI was proposed to facilitate the extension of classical (non-quantum-like image processing applications to the quantum computing domain. The representation encodes a quantum image in the form of a normalized state, which captures information about colors and their corresponding positions in the images. Since its conception, a handful of processing transformations have been formulated, among which are the geometric transformations on quantum images (GTQI and the CTQI that are focused on the color information of the images. In addition, extensions and applications of FRQI representation, such as multi-channel representation for quantum images (MCQI, quantum image data searching, watermarking strategies for quantum images, a framework to produce movies on quantum computers and a blueprint for quantum video encryption and decryption have also been suggested. These proposals extend classical-like image and video processing applications to the quantum computing domain and offer a significant speed-up with low computational resources in comparison to performing the same tasks on traditional computing devices. Each of the algorithms and the mathematical foundations for their execution were simulated using classical computing resources, and their results were analyzed alongside other classical computing equivalents. The work presented in this review is intended to serve as the epitome of advances made in FRQI quantum image processing over the past five years and to simulate further interest geared towards the realization of some secure and efficient image and video processing applications on quantum computers.

  16. Developing Young Adults' Representational Competence through Infographic-Based Science News Reporting

    Science.gov (United States)

    Gebre, Engida H.; Polman, Joseph L.

    2016-01-01

    This study presents descriptive analysis of young adults' use of multiple representations in the context of science news reporting. Across one semester, 71 high school students, in a socioeconomically diverse suburban secondary school in Midwestern United States, participated in activities of researching science topics of their choice and…

  17. Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions

    Science.gov (United States)

    Ziegler, Benjamin; Rauhut, Guntram

    2016-03-01

    The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

  18. Heart rate variability analysis based on time–frequency representation and entropies in hypertrophic cardiomyopathy patients

    International Nuclear Information System (INIS)

    Clariá, F; Vallverdú, M; Caminal, P; Baranowski, R; Chojnowska, L

    2008-01-01

    In hypertrophic cardiomyopathy (HCM) patients there is an increased risk of premature death, which can occur with little or no warning. Furthermore, classification for sudden cardiac death on patients with HCM is very difficult. The aim of our study was to improve the prognostic value of heart rate variability (HRV) in HCM patients, giving insight into changes of the autonomic nervous system. In this way, the suitability of linear and nonlinear measures was studied to assess the HRV. These measures were based on time–frequency representation (TFR) and on Shannon and Rényi entropies, and compared with traditional HRV measures. Holter recordings of 64 patients with HCM and 55 healthy subjects were analyzed. The HCM patients consisted of two groups: 13 high risk patients, after aborted sudden cardiac death (SCD); 51 low risk patients, without SCD. Five-hour RR signals, corresponding to the sleep period of the subjects, were considered for the analysis as a comparable standard situation. These RR signals were filtered in the three frequency bands: very low frequency band (VLF, 0–0.04 Hz), low frequency band (LF, 0.04–0.15 Hz) and high frequency band (HF, 0.15–0.45 Hz). TFR variables based on instantaneous frequency and energy functions were able to classify HCM patients and healthy subjects (control group). Results revealed that measures obtained from TFR analysis of the HRV better classified the groups of subjects than traditional HRV parameters. However, results showed that nonlinear measures improved group classification. It was observed that entropies calculated in the HF band showed the highest statistically significant levels comparing the HCM group and the control group, p-value < 0.0005. The values of entropy measures calculated in the HCM group presented lower values, indicating a decreasing of complexity, than those calculated from the control group. Moreover, similar behavior was observed comparing high and low risk of premature death, the values of

  19. A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

    Science.gov (United States)

    Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

  20. Concise and Accessible Representations for Multidimensional Datasets: Introducing a Framework Based on the nD-EVM and Kohonen Networks

    Directory of Open Access Journals (Sweden)

    Ricardo Pérez-Aguila

    2015-01-01

    Full Text Available A new framework intended for representing and segmenting multidimensional datasets resulting in low spatial complexity requirements and with appropriate access to their contained information is described. Two steps are going to be taken in account. The first step is to specify (n-1D hypervoxelizations, n≥2, as Orthogonal Polytopes whose nth dimension corresponds to color intensity. Then, the nD representation is concisely expressed via the Extreme Vertices Model in the n-Dimensional Space (nD-EVM. Some examples are presented, which, under our methodology, have storing requirements minor than those demanded by their original hypervoxelizations. In the second step, 1-Dimensional Kohonen Networks (1D-KNs are applied in order to segment datasets taking in account their geometrical and topological properties providing a non-supervised way to compact even more the proposed n-Dimensional representations. The application of our framework shares compression ratios, for our set of study cases, in the range 5.6496 to 32.4311. Summarizing, the contribution combines the power of the nD-EVM and 1D-KNs by producing very concise datasets’ representations. We argue that the new representations also provide appropriate segmentations by introducing some error functions such that our 1D-KNs classifications are compared against classifications based only in color intensities. Along the work, main properties and algorithms behind the nD-EVM are introduced for the purpose of interrogating the final representations in such a way that it efficiently obtains useful geometrical and topological information.

  1. Regional Densification of a Global VTEC Model Based on B-Spline Representations

    Science.gov (United States)

    Erdogan, Eren; Schmidt, Michael; Dettmering, Denise; Goss, Andreas; Seitz, Florian; Börger, Klaus; Brandert, Sylvia; Görres, Barbara; Kersten, Wilhelm F.; Bothmer, Volker; Hinrichs, Johannes; Mrotzek, Niclas

    2017-04-01

    The project OPTIMAP is a joint initiative of the Bundeswehr GeoInformation Centre (BGIC), the German Space Situational Awareness Centre (GSSAC), the German Geodetic Research Institute of the Technical University Munich (DGFI-TUM) and the Institute for Astrophysics at the University of Göttingen (IAG). The main goal of the project is the development of an operational tool for ionospheric mapping and prediction (OPTIMAP). Two key features of the project are the combination of different satellite observation techniques (GNSS, satellite altimetry, radio occultations and DORIS) and the regional densification as a remedy against problems encountered with the inhomogeneous data distribution. Since the data from space-geoscientific mission which can be used for modeling ionospheric parameters, such as the Vertical Total Electron Content (VTEC) or the electron density, are distributed rather unevenly over the globe at different altitudes, appropriate modeling approaches have to be developed to handle this inhomogeneity. Our approach is based on a two-level strategy. To be more specific, in the first level we compute a global VTEC model with a moderate regional and spectral resolution which will be complemented in the second level by a regional model in a densification area. The latter is a region characterized by a dense data distribution to obtain a high spatial and spectral resolution VTEC product. Additionally, the global representation means a background model for the regional one to avoid edge effects at the boundaries of the densification area. The presented approach based on a global and a regional model part, i.e. the consideration of a regional densification is called the Two-Level VTEC Model (TLVM). The global VTEC model part is based on a series expansion in terms of polynomial B-Splines in latitude direction and trigonometric B-Splines in longitude direction. The additional regional model part is set up by a series expansion in terms of polynomial B-splines for

  2. Wigner functions for noncommutative quantum mechanics: A group representation based construction

    Energy Technology Data Exchange (ETDEWEB)

    Chowdhury, S. Hasibul Hassan, E-mail: shhchowdhury@gmail.com [Chern Institute of Mathematics, Nankai University, Tianjin 300071 (China); Department of Mathematics and Statistics, Concordia University, Montréal, Québec H3G 1M8 (Canada); Ali, S. Twareque, E-mail: twareque.ali@concordia.ca [Department of Mathematics and Statistics, Concordia University, Montréal, Québec H3G 1M8 (Canada)

    2015-12-15

    This paper is devoted to the construction and analysis of the Wigner functions for noncommutative quantum mechanics, their marginal distributions, and star-products, following a technique developed earlier, viz, using the unitary irreducible representations of the group G{sub NC}, which is the three fold central extension of the Abelian group of ℝ{sup 4}. These representations have been exhaustively studied in earlier papers. The group G{sub NC} is identified with the kinematical symmetry group of noncommutative quantum mechanics of a system with two degrees of freedom. The Wigner functions studied here reflect different levels of non-commutativity—both the operators of position and those of momentum not commuting, the position operators not commuting and finally, the case of standard quantum mechanics, obeying the canonical commutation relations only.

  3. Early Acquisition of Gender Agreement in the Spanish Noun Phrase: Starting Small

    Science.gov (United States)

    Mariscal, Sonia

    2009-01-01

    Nativist and constructivist accounts differ in their characterization of children's knowledge of grammatical categories. In this paper we present research on the process of acquisition of a particular grammatical system, gender agreement in the Spanish noun phrase, in children under three years of age. The design of the longitudinal study employed…

  4. Prosodic Disambiguation of Noun/Verb Homophones in Child-Directed Speech

    Science.gov (United States)

    Conwell, Erin

    2017-01-01

    One strategy that children might use to sort words into grammatical categories such as noun and verb is distributional bootstrapping, in which local co-occurrence information is used to distinguish between categories. Words that can be used in more than one grammatical category could be problematic for this approach. Using naturalistic corpus…

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

    Science.gov (United States)

    Moseley, Rachel L; Pulvermüller, Friedemann

    2014-05-01

    Noun/verb dissociations in the literature defy interpretation due to the confound between lexical category and semantic meaning; nouns and verbs typically describe concrete objects and actions. Abstract words, pertaining to neither, are a critical test case: dissociations along lexical-grammatical lines would support models purporting lexical category as the principle governing brain organisation, whilst semantic models predict dissociation between concrete words but not abstract items. During fMRI scanning, participants read orthogonalised word categories of nouns and verbs, with or without concrete, sensorimotor meaning. Analysis of inferior frontal/insula, precentral and central areas revealed an interaction between lexical class and semantic factors with clear category differences between concrete nouns and verbs but not abstract ones. Though the brain stores the combinatorial and lexical-grammatical properties of words, our data show that topographical differences in brain activation, especially in the motor system and inferior frontal cortex, are driven by semantics and not by lexical class. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Difference between Written and Spoken Czech: The Case of Verbal Nouns Denoting an Action

    Czech Academy of Sciences Publication Activity Database

    Kolářová, V.; Kolář, Jan; Mikulová, M.

    2017-01-01

    Roč. 107, č. 1 (2017), s. 19-38 ISSN 0032-6585 Institutional support: RVO:67985840 Keywords : written Czech * spoken Czech * verbal nouns Subject RIV: AI - Linguistics OBOR OECD: Pure mathematics https://www.degruyter.com/view/j/pralin.2017.107.issue-1/pralin-2017-0002/pralin-2017-0002.xml

  7. Does Lexical Stress Influence 17-Month-Olds' Mapping of Verbs and Nouns?

    Science.gov (United States)

    Campbell, Jennifer; Mihalicz, Patrick; Thiessen, Erik; Curtin, Suzanne

    2018-01-01

    English-learning infants attend to lexical stress when learning new words. Attention to lexical stress might be beneficial for word learning by providing an indication of the grammatical class of that word. English disyllabic nouns commonly have trochaic (strong-weak) stress, whereas English disyllabic verbs commonly have iambic (weak-strong)…

  8. The Role of Sustained Attention in the Production of Conjoined Noun Phrases: An Individual Differences Study.

    Science.gov (United States)

    Jongman, Suzanne R; Meyer, Antje S; Roelofs, Ardi

    2015-01-01

    It has previously been shown that language production, performed simultaneously with a nonlinguistic task, involves sustained attention. Sustained attention concerns the ability to maintain alertness over time. Here, we aimed to replicate the previous finding by showing that individuals call upon sustained attention when they plan single noun phrases (e.g., "the carrot") and perform a manual arrow categorization task. In addition, we investigated whether speakers also recruit sustained attention when they produce conjoined noun phrases (e.g., "the carrot and the bucket") describing two pictures, that is, when both the first and second task are linguistic. We found that sustained attention correlated with the proportion of abnormally slow phrase-production responses. Individuals with poor sustained attention displayed a greater number of very slow responses than individuals with better sustained attention. Importantly, this relationship was obtained both for the production of single phrases while performing a nonlinguistic manual task, and the production of noun phrase conjunctions in referring to two spatially separated objects. Inhibition and updating abilities were also measured. These scores did not correlate with our measure of sustained attention, suggesting that sustained attention and executive control are distinct. Overall, the results suggest that planning conjoined noun phrases involves sustained attention, and that language production happens less automatically than has often been assumed.

  9. Acute cortisol effects on immediate free recall and recognition of nouns depend on stimulus valence

    NARCIS (Netherlands)

    Tops, M.; van der Pompe, G.; Baas, D; Mulder, L.J.M.; Den Boer, J.A.; Meijman, T.F.; Korf, J

    The present study investigated the acute effects of cortisol administration in normal healthy male volunteers on immediate free recall and recognition of pleasant, unpleasant, and neutral nouns using a between-subjects double-blind design. Two hours after cortisol (10 mg) or placebo administration,

  10. Subsequent to suppression: Downstream comprehension consequences of noun/verb ambiguity in natural reading

    Science.gov (United States)

    Stites, Mallory C.; Federmeier, Kara D.

    2015-01-01

    We used eye-tracking to investigate the downstream processing consequences of encountering noun/verb (NV) homographs (i.e., park) in semantically neutral but syntactically constraining contexts. Target words were followed by a prepositional phrase containing a noun that was plausible for only one meaning of the homograph. Replicating previous work, we found increased first fixation durations on NV homographs compared to unambiguous words, which persisted into the next sentence region. At the downstream noun, we found plausibility effects following ambiguous words that were correlated with the size of a reader's first fixation effect, suggesting that this effect reflects the recruitment of processing resources necessary to suppress the homograph's context-inappropriate meaning. Using these same stimuli, Lee and Federmeier (2012) found a sustained frontal negativity to the NV homographs, and, on the downstream noun, found a plausibility effect that was also positively correlated with the size of a reader's ambiguity effect. Together, these findings suggest that when only syntactic constraints are available, meaning selection recruits inhibitory mechanisms that can be measured in both first fixation slowdown and ERP ambiguity effects. PMID:25961358

  11. Noun or Verb? Adult Readers' Sensitivity to Spelling Cues to Grammatical Category in Word Endings

    Science.gov (United States)

    Kemp, Nenagh; Nilsson, Jodi; Arciuli, Joanne

    2009-01-01

    The spelling of many disyllabic English word endings holds cues to their grammatical category, beyond obvious inflectional endings such as "-ing" for verbs. For example, some letter sequences are clearly associated with nouns (e.g., "-oon") and others with verbs (e.g., "-erge"). This study extended recent research by Arciuli and Cupples (2006),…

  12. Dissociable intrinsic functional networks support noun-object and verb-action processing.

    Science.gov (United States)

    Yang, Huichao; Lin, Qixiang; Han, Zaizhu; Li, Hongyu; Song, Luping; Chen, Lingjuan; He, Yong; Bi, Yanchao

    2017-12-01

    The processing mechanism of verbs-actions and nouns-objects is a central topic of language research, with robust evidence for behavioral dissociation. The neural basis for these two major word and/or conceptual classes, however, remains controversial. Two experiments were conducted to study this question from the network perspective. Experiment 1 found that nodes of the same class, obtained through task-evoked brain imaging meta-analyses, were more strongly connected with each other than nodes of different classes during resting-state, forming segregated network modules. Experiment 2 examined the behavioral relevance of these intrinsic networks using data from 88 brain-damaged patients, finding that across patients the relative strength of functional connectivity of the two networks significantly correlated with the noun-object vs. verb-action relative behavioral performances. In summary, we found that verbs-actions and nouns-objects are supported by separable intrinsic functional networks and that the integrity of such networks accounts for the relative noun-object- and verb-action-selective deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Non-Adherence to Study Time Management Strategies among NOUN Students and Implications for Academic Stress

    Science.gov (United States)

    Okopi, Fidel O.

    2011-01-01

    The study was designed to investigate the NOUN students' non-adherence to their time management strategies (TMS) during the course of their studies. The researcher also wanted to find out whether their gender, age, marital and employment statuses have influence on their adherence/non-adherence to the plan or not. The researcher also examined the…

  14. Distributional structure in language: contributions to noun-verb difficulty differences in infant word recognition.

    Science.gov (United States)

    Willits, Jon A; Seidenberg, Mark S; Saffran, Jenny R

    2014-09-01

    What makes some words easy for infants to recognize, and other words difficult? We addressed this issue in the context of prior results suggesting that infants have difficulty recognizing verbs relative to nouns. In this work, we highlight the role played by the distributional contexts in which nouns and verbs occur. Distributional statistics predict that English nouns should generally be easier to recognize than verbs in fluent speech. However, there are situations in which distributional statistics provide similar support for verbs. The statistics for verbs that occur with the English morpheme -ing, for example, should facilitate verb recognition. In two experiments with 7.5- and 9.5-month-old infants, we tested the importance of distributional statistics for word recognition by varying the frequency of the contextual frames in which verbs occur. The results support the conclusion that distributional statistics are utilized by infant language learners and contribute to noun-verb differences in word recognition. Copyright © 2014. Published by Elsevier B.V.

  15. Decomposition into Multiple Morphemes during Lexical Access: A Masked Priming Study of Russian Nouns

    Science.gov (United States)

    Kazanina, Nina; Dukova-Zheleva, Galina; Geber, Dana; Kharlamov, Viktor; Tonciulescu, Keren

    2008-01-01

    The study reports the results of a masked priming experiment with morphologically complex Russian nouns. Participants performed a lexical decision task to a visual target that differed from its prime in one consonant. Three conditions were included: (1) "transparent," in which the prime was morphologically related to the target and contained the…

  16. Translating Proper Nouns: A Case Study on English Translation of Hafez's Lyrics

    Science.gov (United States)

    Shirinzadeh, Seyed Alireza; Mahadi, Tengku Sepora Tengku

    2014-01-01

    Proper nouns are regarded so simple that they might be taken for granted in translation explorations. Some may believe that they should not be translated in transmitting source texts to target texts. But, it is not the case; if one looks at present translations, he will notice that different strategies might be applied for translating proper…

  17. Difference between Written and Spoken Czech: The Case of Verbal Nouns Denoting an Action

    Czech Academy of Sciences Publication Activity Database

    Kolářová, V.; Kolář, Jan; Mikulová, M.

    2017-01-01

    Roč. 107, č. 1 (2017), s. 19-38 ISSN 0032-6585 Institutional support: RVO:67985840 Keywords : written Czech * spoken Czech * verbal nouns Subject RIV: AI - Linguistics OBOR OECD: Pure mathematics https://www.degruyter.com/view/j/pralin.2017.107.issue-1/pralin-2017-0002/pralin-2017-0002. xml

  18. An analysis of the status of the secondary noun prefixes in Ndebele ...

    African Journals Online (AJOL)

    The article probes into the nature of secondary noun class prefixes in the morphology of some Nguni languages and Ndebele in particular. The secondary prefixes are known as commentary prefixes mainly because they carry overtones of sarcasm, criticism and caricature among other elements, through loading an implied ...

  19. Processing graspable object images and their nouns is impaired in Parkinson's disease patients.

    Science.gov (United States)

    Buccino, Giovanni; Dalla Volta, Riccardo; Arabia, Gennarina; Morelli, Maurizio; Chiriaco, Carmelina; Lupo, Angela; Silipo, Franco; Quattrone, Aldo

    2018-03-01

    According to embodiment, the recruitment of the motor system is necessary to process language material expressing a motor content. Coherently, an impairment of the motor system should affect the capacity to process language items with a motor content. The aim of the present study was to assess the capacity to process graspable objects and their nouns in Parkinson's disease (PD) patients and healthy controls. Participants saw photos and nouns depicting graspable and non-graspable objects. Scrambled images and pseudo-words served as control stimuli. At 150 msec after stimulus presentation, they had to respond when the stimulus referred to a real object, and refrain from responding when it was meaningless (go-no go paradigm). In the control group, participants gave slower motor responses for stimuli (both photos and nouns) related to graspable objects as compared to non-graspable ones. This in keeping with data obtained in a previous study with young healthy participants. In the PD group, motor responses were similar for both graspable and non-graspable items. Moreover, error number was significantly greater than in controls. These findings support the notion that when the motor circuits are lesioned, like in PD, patients do not show the typical modulation of motor responses and have troubles in processing graspable objects and their nouns. Copyright © 2017. Published by Elsevier Ltd.

  20. The production and processing of determiner-noun agreement in child L2 Dutch

    NARCIS (Netherlands)

    Blom, E.; Vasić, N.

    2011-01-01

    Recent research has shown that children who learn Dutch as their second language (L2) have difficulties with Dutch grammatical gender. This study shows that six to nine year old L2 Dutch children whose first language (L1) is Turkish noticed incorrect gender agreement between determiner and noun only

  1. Problems in the acquisition of Noun Class 11 among Xhosa children ...

    African Journals Online (AJOL)

    While there has been research on the partial or complete merger of Noun Classes 5 and 11 in a number of Bantu languages, no study has focused specifically on the acquisition of Cl. 11 by Xhosa-speaking children. In this paper we test our hypothesis that Xhosa-speaking children in both urban and rural areas no longer, ...

  2. Vantage Theory and the Use of English Demonstrative Determiners with Proper Nouns

    Science.gov (United States)

    Riddle, Elizabeth M.

    2010-01-01

    This article discusses some apparently paradoxical behavior of the English demonstratives "this/these" and "that/those" as determiners of proper nouns and as metaphorical signals of epistemic and affective stance within the proximal-distal opposition. It is argued that the apparent paradoxes are actually cases of shifting perspectives or points of…

  3. A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

    Directory of Open Access Journals (Sweden)

    Yubao Sun

    2015-01-01

    Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

  4. Integral representations of solutions of the wave equation based on relativistic wavelets

    International Nuclear Information System (INIS)

    Perel, Maria; Gorodnitskiy, Evgeny

    2012-01-01

    A representation of solutions of the wave equation with two spatial coordinates in terms of localized elementary ones is presented. Elementary solutions are constructed from four solutions with the help of transformations of the affine Poincaré group, i.e. with the help of translations, dilations in space and time and Lorentz transformations. The representation can be interpreted in terms of the initial-boundary value problem for the wave equation in a half-plane. It gives the solution as an integral representation of two types of solutions: propagating localized solutions running away from the boundary under different angles and packet-like surface waves running along the boundary and exponentially decreasing away from the boundary. Properties of elementary solutions are discussed. A numerical investigation of coefficients of the decomposition is carried out. An example of the decomposition of the field created by sources moving along a line with different speeds is considered, and the dependence of coefficients on speeds of sources is discussed. (paper)

  5. Evidence for similar patterns of neural activity elicited by picture- and word-based representations of natural scenes.

    Science.gov (United States)

    Kumar, Manoj; Federmeier, Kara D; Fei-Fei, Li; Beck, Diane M

    2017-07-15

    A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g., pictures and words evoke a similar pattern of activity, such that the patterns that separate categories in one modality transfer to the other. Prior work using this method has found support for a common code, but has two limitations: they have either only examined disparate categories (e.g. animals vs. tools) that are known to activate different brain regions, raising the possibility that the pattern separation and inferred similarity reflects only large scale differences between the categories or they have been limited to individual object representations. By using natural scene categories, we not only extend the current literature on cross-modal representations beyond objects, but also, because natural scene categories activate a common set of brain regions, we identify a more fine-grained (i.e. higher spatial resolution) common representation. Specifically, we studied picture- and word-based representations of natural scene stimuli from four different categories: beaches, cities, highways, and mountains. Participants passively viewed blocks of either phrases (e.g. "sandy beach") describing scenes or photographs from those same scene categories. To determine whether the phrases and pictures evoke a common code, we asked whether a classifier trained on one stimulus type (e.g. phrase stimuli) would transfer (i.e. cross-decode) to the other stimulus type (e.g. picture stimuli). The analysis revealed cross-decoding in the occipitotemporal, posterior parietal and

  6. Poetic representation

    DEFF Research Database (Denmark)

    Wulf-Andersen, Trine Østergaard

    2012-01-01

    , and dialogue, of situated participants. The article includes a lengthy example of a poetic representation of one participant’s story, and the author comments on the potentials of ‘doing’ poetic representations as an example of writing in ways that challenges what sometimes goes unasked in participative social...

  7. Lexical development of noun and predicate comprehension and production in isiZulu.

    Science.gov (United States)

    Nicolas, Ramona Kunene; Ahmed, Saaliha

    2016-07-28

    This study seeks to investigate the development of noun and predicate comprehension and production in isiZulu-speaking children between the ages of 25 and 36 months. It compares lexical comprehension and production in isiZulu, using an Italian developed and validated vocabulary assessment tool: The Picture Naming Game (PiNG) developed by Bello, Giannantoni, Pettenati, Stefanini and Caselli (2012). The PiNG tool includes four subtests, one each for subnoun comprehension (NC), noun production (NP), predicate comprehension (PC), and predicate production (PP). Children are shown these lexical items and then asked to show comprehension and produce certain lexical items. After adaptation into the South African context, the adapted version of PiNG was used to directly assess the lexical development of isiZulu with the three main objectives to (1) test the efficiency of the adaptation of a vocabulary tool to measure isiZulu comprehension and production development, (2) test previous findings done in many cross-linguistic comparisons that have found that both comprehension and production performance increase with age for a lesser-studied language, and (3) present our findings around the comprehension and production of the linguistic categories of nouns and predicates. An analysis of the results reported in this study show an age effect throughout the entire sample. Across all the age groups, the comprehension of the noun and predicate subtests was better performed than the production of noun and predicate subtests. With regard to lexical items, the responses of children showed an influence of various factors, including the late acquisition of items, possible problems with stimuli presented to them, and the possible input received by the children from their home environment.

  8. Lexical development of noun and predicate comprehension and production in isiZulu

    Directory of Open Access Journals (Sweden)

    Ramona Kunene Nicolas

    2016-07-01

    Full Text Available This study seeks to investigate the development of noun and predicate comprehension and production in isiZulu-speaking children between the ages of 25 and 36 months. It compares lexical comprehension and production in isiZulu, using an Italian developed and validated vocabulary assessment tool: The Picture Naming Game (PiNG developed by Bello, Giannantoni, Pettenati, Stefanini and Caselli (2012. The PiNG tool includes four subtests, one each for subnoun comprehension (NC, noun production (NP, predicate comprehension (PC, and predicate production (PP. Children are shown these lexical items and then asked to show comprehension and produce certain lexical items. After adaptation into the South African context, the adapted version of PiNG was used to directly assess the lexical development of isiZulu with the three main objectives to (1 test the efficiency of the adaptation of a vocabulary tool to measure isiZulu comprehension and production development, (2 test previous findings done in many cross-linguistic comparisons that have found that both comprehension and production performance increase with age for a lesser-studied language, and (3 present our findings around the comprehension and production of the linguistic categories of nouns and predicates. An analysis of the results reported in this study show an age effect throughout the entire sample. Across all the age groups, the comprehension of the noun and predicate subtests was better performed than the production of noun and predicate subtests. With regard to lexical items, the responses of children showed an influence of various factors, including the late acquisition of items, possible problems with stimuli presented to them, and the possible input received by the children from their home environment.

  9. Scenarios, personas and user stories from design ethnography: Evidence-based design representations of communicable disease investigations

    Science.gov (United States)

    Turner, Anne M; Reeder, Blaine; Ramey, Judith

    2014-01-01

    Purpose Despite years of effort and millions of dollars spent to create a unified electronic communicable disease reporting systems, the goal remains elusive. A major barrier has been a lack of understanding by system designers of communicable disease (CD) work and the public health workers who perform this work. This study reports on the application of User Center Design representations, traditionally used for improving interface design, to translate the complex CD work identified through ethnographic studies to guide designers and developers of CD systems. The purpose of this work is to: (1) better understand public health practitioners and their information workflow with respect to communicable disease (CD) monitoring and control at a local health department, and (2) to develop evidence-based design representations that model this CD work to inform the design of future disease surveillance systems. Methods We performed extensive onsite semi-structured interviews, targeted work shadowing and a focus group to characterize local health department communicable disease workflow. Informed by principles of design ethnography and user-centered design (UCD) we created persona, scenarios and user stories to accurately represent the user to system designers. Results We sought to convey to designers the key findings from ethnographic studies: 1) that public health CD work is mobile and episodic, in contrast to current CD reporting systems, which are stationary and fixed 2) health department efforts are focused on CD investigation and response rather than reporting and 3) current CD information systems must conform to PH workflow to ensure their usefulness. In an effort to illustrate our findings to designers, we developed three contemporary design-support representations: persona, scenario, and user story. Conclusions Through application of user centered design principles, we were able to create design representations that illustrate complex public health communicable

  10. Scenarios, personas and user stories: user-centered evidence-based design representations of communicable disease investigations.

    Science.gov (United States)

    Turner, Anne M; Reeder, Blaine; Ramey, Judith

    2013-08-01

    Despite years of effort and millions of dollars spent to create unified electronic communicable disease reporting systems, the goal remains elusive. A major barrier has been a lack of understanding by system designers of communicable disease (CD) work and the public health workers who perform this work. This study reports on the application of user-centered design representations, traditionally used for improving interface design, to translate the complex CD work identified through ethnographic studies to guide designers and developers of CD systems. The purpose of this work is to: (1) better understand public health practitioners and their information workflow with respect to CD monitoring and control at a local health agency, and (2) to develop evidence-based design representations that model this CD work to inform the design of future disease surveillance systems. We performed extensive onsite semi-structured interviews, targeted work shadowing and a focus group to characterize local health agency CD workflow. Informed by principles of design ethnography and user-centered design we created persona, scenarios and user stories to accurately represent the user to system designers. We sought to convey to designers the key findings from ethnographic studies: (1) public health CD work is mobile and episodic, in contrast to current CD reporting systems, which are stationary and fixed, (2) health agency efforts are focused on CD investigation and response rather than reporting and (3) current CD information systems must conform to public health workflow to ensure their usefulness. In an effort to illustrate our findings to designers, we developed three contemporary design-support representations: persona, scenario, and user story. Through application of user-centered design principles, we were able to create design representations that illustrate complex public health communicable disease workflow and key user characteristics to inform the design of CD information

  11. Adaptive structured dictionary learning for image fusion based on group-sparse-representation

    Science.gov (United States)

    Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

    2018-04-01

    Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

  12. Seismic detection method for small-scale discontinuities based on dictionary learning and sparse representation

    Science.gov (United States)

    Yu, Caixia; Zhao, Jingtao; Wang, Yanfei

    2017-02-01

    Studying small-scale geologic discontinuities, such as faults, cavities and fractures, plays a vital role in analyzing the inner conditions of reservoirs, as these geologic structures and elements can provide storage spaces and migration pathways for petroleum. However, these geologic discontinuities have weak energy and are easily contaminated with noises, and therefore effectively extracting them from seismic data becomes a challenging problem. In this paper, a method for detecting small-scale discontinuities using dictionary learning and sparse representation is proposed that can dig up high-resolution information by sparse coding. A K-SVD (K-means clustering via Singular Value Decomposition) sparse representation model that contains two stage of iteration procedure: sparse coding and dictionary updating, is suggested for mathematically expressing these seismic small-scale discontinuities. Generally, the orthogonal matching pursuit (OMP) algorithm is employed for sparse coding. However, the method can only update one dictionary atom at one time. In order to improve calculation efficiency, a regularized version of OMP algorithm is presented for simultaneously updating a number of atoms at one time. Two numerical experiments demonstrate the validity of the developed method for clarifying and enhancing small-scale discontinuities. The field example of carbonate reservoirs further demonstrates its effectiveness in revealing masked tiny faults and small-scale cavities.

  13. Spectrum recovery method based on sparse representation for segmented multi-Gaussian model

    Science.gov (United States)

    Teng, Yidan; Zhang, Ye; Ti, Chunli; Su, Nan

    2016-09-01

    Hyperspectral images can realize crackajack features discriminability for supplying diagnostic characteristics with high spectral resolution. However, various degradations may generate negative influence on the spectral information, including water absorption, bands-continuous noise. On the other hand, the huge data volume and strong redundancy among spectrums produced intense demand on compressing HSIs in spectral dimension, which also leads to the loss of spectral information. The reconstruction of spectral diagnostic characteristics has irreplaceable significance for the subsequent application of HSIs. This paper introduces a spectrum restoration method for HSIs making use of segmented multi-Gaussian model (SMGM) and sparse representation. A SMGM is established to indicating the unsymmetrical spectral absorption and reflection characteristics, meanwhile, its rationality and sparse property are discussed. With the application of compressed sensing (CS) theory, we implement sparse representation to the SMGM. Then, the degraded and compressed HSIs can be reconstructed utilizing the uninjured or key bands. Finally, we take low rank matrix recovery (LRMR) algorithm for post processing to restore the spatial details. The proposed method was tested on the spectral data captured on the ground with artificial water absorption condition and an AVIRIS-HSI data set. The experimental results in terms of qualitative and quantitative assessments demonstrate that the effectiveness on recovering the spectral information from both degradations and loss compression. The spectral diagnostic characteristics and the spatial geometry feature are well preserved.

  14. Social representations of adolescents on quality of life: structurally-based study

    Directory of Open Access Journals (Sweden)

    Ramon Missias Moreira

    2015-01-01

    Full Text Available This study sought to conduct a comparatively analysis and describe the contents of the structure of the social representations of adolescents on quality of life. It involves descriptive, quantitative research, with the benchmark of a structural approach to social representations. The informants included 316 adolescents from three public schools in Jequié in the State of Bahia. The Spontaneous Word-Choice Eliciting Technique using the key expression "Quality of Life" was used for data collection. The responses were processed using Evoc 2003 software, which generated the Four-House Chart. The results reveal the core nucleus of the terms: healthy eating; physical activity; money; and sex. In the 1st outer circle, the words absence of disease, condoms, liberty, marijuana, housing, work and living well are featured. In the 2nd outer circle, there appeared the words difficulty, family, peace and power, and the contrasting elements of well-being and soccer. The overall consensus is that adolescents associate quality of life with sports and other healthy behavior activities, and are influenced by the desires and curiosities of adolescence.

  15. Non-Markovian reduced dynamics based upon a hierarchical effective-mode representation

    Energy Technology Data Exchange (ETDEWEB)

    Burghardt, Irene [Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Max-von-Laue-Str. 7, 60438 Frankfurt (Germany); Martinazzo, Rocco [Dipartimento di Chimica, Universita degli Studi di Milano, v. Golgi 19, 20133 Milano (Italy); Hughes, Keith H. [School of Chemistry, Bangor University, Bangor, Gwynedd LL57 2UW (United Kingdom)

    2012-10-14

    A reduced dynamics representation is introduced which is tailored to a hierarchical, Mori-chain type representation of a bath of harmonic oscillators which are linearly coupled to a subsystem. We consider a spin-boson system where a single effective mode is constructed so as to absorb all system-environment interactions, while the residual bath modes are coupled bilinearly to the primary mode and among each other. Using a cumulant expansion of the memory kernel, correlation functions for the primary mode are obtained, which can be suitably approximated by truncated chains representing the primary-residual mode interactions. A series of reduced-dimensional bath correlation functions is thus obtained, which can be expressed as Fourier-Laplace transforms of spectral densities that are given in truncated continued-fraction form. For a master equation which is second order in the system-bath coupling, the memory kernel is re-expressed in terms of local-in-time equations involving auxiliary densities and auxiliary operators.

  16. Analysis Sparse Representation for Nonnegative Signals Based on Determinant Measure by DC Programming

    Directory of Open Access Journals (Sweden)

    Yujie Li

    2018-01-01

    Full Text Available Analysis sparse representation has recently emerged as an alternative approach to the synthesis sparse model. Most existing algorithms typically employ the l0-norm, which is generally NP-hard. Other existing algorithms employ the l1-norm to relax the l0-norm, which sometimes cannot promote adequate sparsity. Most of these existing algorithms focus on general signals and are not suitable for nonnegative signals. However, many signals are necessarily nonnegative such as spectral data. In this paper, we present a novel and efficient analysis dictionary learning algorithm for nonnegative signals with the determinant-type sparsity measure which is convex and differentiable. The analysis sparse representation can be cast in three subproblems, sparse coding, dictionary update, and signal update, because the determinant-type sparsity measure would result in a complex nonconvex optimization problem, which cannot be easily solved by standard convex optimization methods. Therefore, in the proposed algorithms, we use a difference of convex (DC programming scheme for solving the nonconvex problem. According to our theoretical analysis and simulation study, the main advantage of the proposed algorithm is its greater dictionary learning efficiency, particularly compared with state-of-the-art algorithms. In addition, our proposed algorithm performs well in image denoising.

  17. Virtual terrain: a security-based representation of a computer network

    Science.gov (United States)

    Holsopple, Jared; Yang, Shanchieh; Argauer, Brian

    2008-03-01

    Much research has been put forth towards detection, correlating, and prediction of cyber attacks in recent years. As this set of research progresses, there is an increasing need for contextual information of a computer network to provide an accurate situational assessment. Typical approaches adopt contextual information as needed; yet such ad hoc effort may lead to unnecessary or even conflicting features. The concept of virtual terrain is, therefore, developed and investigated in this work. Virtual terrain is a common representation of crucial information about network vulnerabilities, accessibilities, and criticalities. A virtual terrain model encompasses operating systems, firewall rules, running services, missions, user accounts, and network connectivity. It is defined as connected graphs with arc attributes defining dynamic relationships among vertices modeling network entities, such as services, users, and machines. The virtual terrain representation is designed to allow feasible development and maintenance of the model, as well as efficacy in terms of the use of the model. This paper will describe the considerations in developing the virtual terrain schema, exemplary virtual terrain models, and algorithms utilizing the virtual terrain model for situation and threat assessment.

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

    Science.gov (United States)

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

    2010-05-21

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

  19. Fall Detection for Elderly from Partially Observed Depth-Map Video Sequences Based on View-Invariant Human Activity Representation

    Directory of Open Access Journals (Sweden)

    Rami Alazrai

    2017-03-01

    Full Text Available This paper presents a new approach for fall detection from partially-observed depth-map video sequences. The proposed approach utilizes the 3D skeletal joint positions obtained from the Microsoft Kinect sensor to build a view-invariant descriptor for human activity representation, called the motion-pose geometric descriptor (MPGD. Furthermore, we have developed a histogram-based representation (HBR based on the MPGD to construct a length-independent representation of the observed video subsequences. Using the constructed HBR, we formulate the fall detection problem as a posterior-maximization problem in which the posteriori probability for each observed video subsequence is estimated using a multi-class SVM (support vector machine classifier. Then, we combine the computed posteriori probabilities from all of the observed subsequences to obtain an overall class posteriori probability of the entire partially-observed depth-map video sequence. To evaluate the performance of the proposed approach, we have utilized the Kinect sensor to record a dataset of depth-map video sequences that simulates four fall-related activities of elderly people, including: walking, sitting, falling form standing and falling from sitting. Then, using the collected dataset, we have developed three evaluation scenarios based on the number of unobserved video subsequences in the testing videos, including: fully-observed video sequence scenario, single unobserved video subsequence of random lengths scenarios and two unobserved video subsequences of random lengths scenarios. Experimental results show that the proposed approach achieved an average recognition accuracy of 93 . 6 % , 77 . 6 % and 65 . 1 % , in recognizing the activities during the first, second and third evaluation scenario, respectively. These results demonstrate the feasibility of the proposed approach to detect falls from partially-observed videos.

  20. Multiscale sample entropy and cross-sample entropy based on symbolic representation and similarity of stock markets

    Science.gov (United States)

    Wu, Yue; Shang, Pengjian; Li, Yilong

    2018-03-01

    A modified multiscale sample entropy measure based on symbolic representation and similarity (MSEBSS) is proposed in this paper to research the complexity of stock markets. The modified algorithm reduces the probability of inducing undefined entropies and is confirmed to be robust to strong noise. Considering the validity and accuracy, MSEBSS is more reliable than Multiscale entropy (MSE) for time series mingled with much noise like financial time series. We apply MSEBSS to financial markets and results show American stock markets have the lowest complexity compared with European and Asian markets. There are exceptions to the regularity that stock markets show a decreasing complexity over the time scale, indicating a periodicity at certain scales. Based on MSEBSS, we introduce the modified multiscale cross-sample entropy measure based on symbolic representation and similarity (MCSEBSS) to consider the degree of the asynchrony between distinct time series. Stock markets from the same area have higher synchrony than those from different areas. And for stock markets having relative high synchrony, the entropy values will decrease with the increasing scale factor. While for stock markets having high asynchrony, the entropy values will not decrease with the increasing scale factor sometimes they tend to increase. So both MSEBSS and MCSEBSS are able to distinguish stock markets of different areas, and they are more helpful if used together for studying other features of financial time series.

  1. Perception of oyster-based products by French consumers. The effect of processing and role of social representations.

    Science.gov (United States)

    Debucquet, Gervaise; Cornet, Josiane; Adam, Isabelle; Cardinal, Mireille

    2012-12-01

    The search for new markets in the seafood sector, associated with the question of the continuity of raw oyster consumption over generations can be an opportunity for processors to extend their ranges with oyster-based products. The twofold aim of this study was to evaluate the impact of processing and social representation on perception of oyster-based products by French consumers and to identify the best means of development in order to avoid possible failure in the market. Five products with different degrees of processing (cooked oysters in a half-shell, hot preparation for toast, potted oyster, oyster butter and oyster-based soup) were presented within focus groups and consumer tests, at home and in canteens with the staff of several companies in order to reach consumers with different ages and professional activities. The results showed that social representation had a strong impact and that behaviours were contrasted according to the initial profile of the consumer (traditional raw oyster consumers or non-consumers) and their age distribution (younger and older people). The degree of processing has to be adapted to each segment. It is suggested to develop early exposure to influence the food choices and preferences of the youngest consumers on a long-term basis. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Dynamics of random Boolean networks under fully asynchronous stochastic update based on linear representation.

    Directory of Open Access Journals (Sweden)

    Chao Luo

    Full Text Available A novel algebraic approach is proposed to study dynamics of asynchronous random Boolean networks where a random number of nodes can be updated at each time step (ARBNs. In this article, the logical equations of ARBNs are converted into the discrete-time linear representation and dynamical behaviors of systems are investigated. We provide a general formula of network transition matrices of ARBNs as well as a necessary and sufficient algebraic criterion to determine whether a group of given states compose an attractor of length[Formula: see text] in ARBNs. Consequently, algorithms are achieved to find all of the attractors and basins in ARBNs. Examples are showed to demonstrate the feasibility of the proposed scheme.

  3. Adaptive compressive ghost imaging based on wavelet trees and sparse representation.

    Science.gov (United States)

    Yu, Wen-Kai; Li, Ming-Fei; Yao, Xu-Ri; Liu, Xue-Feng; Wu, Ling-An; Zhai, Guang-Jie

    2014-03-24

    Compressed sensing is a theory which can reconstruct an image almost perfectly with only a few measurements by finding its sparsest representation. However, the computation time consumed for large images may be a few hours or more. In this work, we both theoretically and experimentally demonstrate a method that combines the advantages of both adaptive computational ghost imaging and compressed sensing, which we call adaptive compressive ghost imaging, whereby both the reconstruction time and measurements required for any image size can be significantly reduced. The technique can be used to improve the performance of all computational ghost imaging protocols, especially when measuring ultra-weak or noisy signals, and can be extended to imaging applications at any wavelength.

  4. A novel collaborative representation and SCAD based classification method for fibrosis and inflammatory activity analysis of chronic hepatitis C

    Science.gov (United States)

    Cai, Jiaxin; Chen, Tingting; Li, Yan; Zhu, Nenghui; Qiu, Xuan

    2018-03-01

    In order to analysis the fibrosis stage and inflammatory activity grade of chronic hepatitis C, a novel classification method based on collaborative representation (CR) with smoothly clipped absolute deviation penalty (SCAD) penalty term, called CR-SCAD classifier, is proposed for pattern recognition. After that, an auto-grading system based on CR-SCAD classifier is introduced for the prediction of fibrosis stage and inflammatory activity grade of chronic hepatitis C. The proposed method has been tested on 123 clinical cases of chronic hepatitis C based on serological indexes. Experimental results show that the performance of the proposed method outperforms the state-of-the-art baselines for the classification of fibrosis stage and inflammatory activity grade of chronic hepatitis C.

  5. Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

    Science.gov (United States)

    Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

    2001-03-01

    This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

  6. Trait-based representation of hydrological functional properties of plants in weather and ecosystem models

    Directory of Open Access Journals (Sweden)

    Ashley M. Matheny

    2017-02-01

    Full Text Available Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types (PFTs and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

  7. Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

    Science.gov (United States)

    He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

    2014-12-01

    Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

  8. Semi-analytical Karhunen-Loeve representation of irregular waves based on the prolate spheroidal wave functions

    Science.gov (United States)

    Lee, Gibbeum; Cho, Yeunwoo

    2018-01-01

    A new semi-analytical approach is presented to solving the matrix eigenvalue problem or the integral equation in Karhunen-Loeve (K-L) representation of random data such as irregular ocean waves. Instead of direct numerical approach to this matrix eigenvalue problem, which may suffer from the computational inaccuracy for big data, a pair of integral and differential equations are considered, which are related to the so-called prolate spheroidal wave functions (PSWF). First, the PSWF is expressed as a summation of a small number of the analytical Legendre functions. After substituting them into the PSWF differential equation, a much smaller size matrix eigenvalue problem is obtained than the direct numerical K-L matrix eigenvalue problem. By solving this with a minimal numerical effort, the PSWF and the associated eigenvalue of the PSWF differential equation are obtained. Then, the eigenvalue of the PSWF integral equation is analytically expressed by the functional values of the PSWF and the eigenvalues obtained in the PSWF differential equation. Finally, the analytically expressed PSWFs and the eigenvalues in the PWSF integral equation are used to form the kernel matrix in the K-L integral equation for the representation of exemplary wave data such as ordinary irregular waves. It is found that, with the same accuracy, the required memory size of the present method is smaller than that of the direct numerical K-L representation and the computation time of the present method is shorter than that of the semi-analytical method based on the sinusoidal functions.

  9. Procedural Media Representation

    OpenAIRE

    Henrysson, Anders

    2002-01-01

    We present a concept for using procedural techniques to represent media. Procedural methods allow us to represent digital media (2D images, 3D environments etc.) with very little information and to render it photo realistically. Since not all kind of content can be created procedurally, traditional media representations (bitmaps, polygons etc.) must be used as well. We have adopted an object-based media representation where an object can be represented either with a procedure or with its trad...

  10. New solutions of the Yang-Baxter equation based on root of 1 representations of the Para-Bose superalgebra Uq[osp(1/2)

    International Nuclear Information System (INIS)

    Palev, T.D.; Stoilova, N.I.

    1995-07-01

    New solutions of the quantum Yang-Baxter equation, depending in general on three arbitrary parameters, are written down. They are based on the root of unity representations of the quantum orthosymplectic superalgebra U q [osp(1/2)], which were found recently. Representations of the braid group B N are defined within any N th tensorial power of root of 1 U q [osp(1/2)] modules. (author). 40 refs

  11. A Scandinavian Island in a Slavonic Linguistic Environment. The Dialect of Gammalsvenskby: Nouns (Paper 2

    Directory of Open Access Journals (Sweden)

    Alexander E. Mankov

    2014-08-01

    Full Text Available This paper continues the series of publications on the morphology of the dialect of Staroshvedskoye (Sw. Gammalsvenskby, which is the only surviving Scandinavian dialect in the territory of the former Soviet Union. The village of Staroshvedskoye is located in the Kherson region, Ukraine. Its Swedish dialect historically belongs to the group of Swedish dialects of Estonia and goes back to the dialect of the island of Dagö (Hiiumaa. The dialect of Gammalsvenskby is of interest to slavists as an example of a language island in the Slavonic environment. From around the 1950s, the main spoken language of all village residents, including dialect speakers, has been surzhik. Due to the complete lack of studies of the present-day dialect and because of the severe endangerment in which the dialect is currently situated, the most urgent task is to collect, classify, and publish the factual material. This paper introduces comprehensive material on nouns in the conservative variety of the present-day dialect. It lists all masculine nouns of types 1b, c, d, and e together with their cognates from Estonian Swedish dialects; comments on the history of the forms are given as well. The sources for the material presented here are interviews with speakers of the conservative variety of the dialect recorded by the author during fieldwork in the village from 2004 to 2013. We plan to publish nouns of other types in later articles.

  12. Semantic markup of nouns and adjectives for the Electronic corpus of texts in Tuvan language

    Directory of Open Access Journals (Sweden)

    Bajlak Ch. Oorzhak

    2016-12-01

    Full Text Available The article examines the progress of semantic markup of the Electronic corpus of texts in Tuvan language (ECTTL, which is another stage of adding Tuvan texts to the database and marking up the corpus. ECTTL is a collaborative project by researchers from Tuvan State University (Research and Education Center of Turkic Studies and Department of Information Technologies. Semantic markup of Tuvan lexis will come as a search engine and reference system which will help users find text snippets containing words with desired meanings in ECTTL. The first stage of this process is setting up databases of basic lexemes of Tuvan language. All meaningful lexemes were classified into the following semantic groups: humans, animals, objects, natural objects and phenomena, and abstract concepts. All Tuvan object nouns, as well as both descriptive and relative adjectives, were assigned to one of these lexico-semantic classes. Each class, sub-class and descriptor is tagged in Tuvan, Russian and English; these tags, in turn, will help automatize searching. The databases of meaningful lexemes of Tuvan language will also outline their lexical combinations. The automatized system will contain information on semantic combinations of adjectives with nouns, adverbs with verbs, nouns with verbs, as well as on the combinations which are semantically incompatible.

  13. Quiver representations

    CERN Document Server

    Schiffler, Ralf

    2014-01-01

    This book is intended to serve as a textbook for a course in Representation Theory of Algebras at the beginning graduate level. The text has two parts. In Part I, the theory is studied in an elementary way using quivers and their representations. This is a very hands-on approach and requires only basic knowledge of linear algebra. The main tool for describing the representation theory of a finite-dimensional algebra is its Auslander-Reiten quiver, and the text introduces these quivers as early as possible. Part II then uses the language of algebras and modules to build on the material developed before. The equivalence of the two approaches is proved in the text. The last chapter gives a proof of Gabriel’s Theorem. The language of category theory is developed along the way as needed.

  14. Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.

    Science.gov (United States)

    Cang, Zixuan; Mu, Lin; Wei, Guo-Wei

    2018-01-01

    This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination.

  15. Three-dimensional plasma equilibrium model based on the poloidal representation of the magnetic field

    International Nuclear Information System (INIS)

    Gruber, R.; Degtyarev, L.M.; Kuper, A.; Martynov, A.A.; Medvedev, S.Yu.; Shafranov, V.D.

    1996-01-01

    Equations for the three-dimensional equilibrium of a plasma are formulated in the poloidal representation. The magnetic field is expressed in terms of the poloidal magnetic flux Ψ and the poloidal electric current F. As a result, three-dimensional equilibrium configurations are analyzed with the help of a set of equations including the elliptical equation for the poloidal flux, the magnetic differential equation for the parallel current, and the equations for the basis vector field b. To overcome the difficulties associated with peculiarities that can arise in solving the magnetic differential equation at rational toroidal magnetic surfaces, small regulating corrections are introduced into the proposed set of equations. In this case, second-order differential terms with a small parameter appear in the magnetic differential equations. As a result, these equations take the form of elliptical equations. Three versions of regulating corrections are proposed. The equations obtained can be used to develop numerical codes for calculating three-dimensional equilibrium plasma configurations with an island structure

  16. Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

    Science.gov (United States)

    Mu, Lin

    2018-01-01

    This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination. PMID:29309403

  17. Structure factors for tunneling ionization rates of molecules: General Hartree-Fock-based integral representation

    Science.gov (United States)

    Madsen, Lars Bojer; Jensen, Frank; Dnestryan, Andrey I.; Tolstikhin, Oleg I.

    2017-07-01

    In the leading-order approximation of the weak-field asymptotic theory (WFAT), the dependence of the tunneling ionization rate of a molecule in an electric field on its orientation with respect to the field is determined by the structure factor of the ionizing molecular orbital. The WFAT yields an expression for the structure factor in terms of a local property of the orbital in the asymptotic region. However, in general quantum chemistry approaches molecular orbitals are expanded in a Gaussian basis which does not reproduce their asymptotic behavior correctly. This hinders the application of the WFAT to polyatomic molecules, which are attracting increasing interest in strong-field physics. Recently, an integral-equation approach to the WFAT for tunneling ionization of one electron from an arbitrary potential has been developed. The structure factor is expressed in an integral form as a matrix element involving the ionizing orbital. The integral is not sensitive to the asymptotic behavior of the orbital, which resolves the difficulty mentioned above. Here, we extend the integral representation for the structure factor to many-electron systems treated within the Hartree-Fock method and show how it can be implemented on the basis of standard quantum chemistry software packages. We validate the methodology by considering noble-gas atoms and the CO molecule, for which accurate structure factors exist in the literature. We also present benchmark results for CO2 and for NH3 in the pyramidal and planar geometries.

  18. Representational Machines

    DEFF Research Database (Denmark)

    Photography not only represents space. Space is produced photographically. Since its inception in the 19th century, photography has brought to light a vast array of represented subjects. Always situated in some spatial order, photographic representations have been operatively underpinned by social...... to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...... possibilities, and genre distinctions. Presenting several distinct ways of producing space photographically, this book opens a new and important field of inquiry for photography research....

  19. Group representations

    CERN Document Server

    Karpilovsky, G

    1994-01-01

    This third volume can be roughly divided into two parts. The first part is devoted to the investigation of various properties of projective characters. Special attention is drawn to spin representations and their character tables and to various correspondences for projective characters. Among other topics, projective Schur index and projective representations of abelian groups are covered. The last topic is investigated by introducing a symplectic geometry on finite abelian groups. The second part is devoted to Clifford theory for graded algebras and its application to the corresponding theory

  20. Value Representations

    DEFF Research Database (Denmark)

    Rasmussen, Majken Kirkegaard; Petersen, Marianne Graves

    2011-01-01

    Stereotypic presumptions about gender affect the design process, both in relation to how users are understood and how products are designed. As a way to decrease the influence of stereotypic presumptions in design process, we propose not to disregard the aspect of gender in the design process......, as the perspective brings valuable insights on different approaches to technology, but instead to view gender through a value lens. Contributing to this perspective, we have developed Value Representations as a design-oriented instrument for staging a reflective dialogue with users. Value Representations...

  1. A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

    Science.gov (United States)

    Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

    2016-02-19

    In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

  2. A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

    Directory of Open Access Journals (Sweden)

    Zutao Zhang

    2016-02-01

    Full Text Available In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT is adopted to extract the EEG power spectrum density (PSD. In this step, sparse representation classification combined with k-singular value decomposition (KSVD is firstly introduced in PSD to estimate the driver’s vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

  3. Lambert W-function based exact representation for double diode model of solar cells: Comparison on fitness and parameter extraction

    International Nuclear Information System (INIS)

    Gao, Xiankun; Cui, Yan; Hu, Jianjun; Xu, Guangyin; Yu, Yongchang

    2016-01-01

    Highlights: • Lambert W-function based exact representation (LBER) is presented for double diode model (DDM). • Fitness difference between LBER and DDM is verified by reported parameter values. • The proposed LBER can better represent the I–V and P–V characteristics of solar cells. • Parameter extraction difference between LBER and DDM is validated by two algorithms. • The parameter values extracted from LBER are more accurate than those from DDM. - Abstract: Accurate modeling and parameter extraction of solar cells play an important role in the simulation and optimization of PV systems. This paper presents a Lambert W-function based exact representation (LBER) for traditional double diode model (DDM) of solar cells, and then compares their fitness and parameter extraction performance. Unlike existing works, the proposed LBER is rigorously derived from DDM, and in LBER the coefficients of Lambert W-function are not extra parameters to be extracted or arbitrary scalars but the vectors of terminal voltage and current of solar cells. The fitness difference between LBER and DDM is objectively validated by the reported parameter values and experimental I–V data of a solar cell and four solar modules from different technologies. The comparison results indicate that under the same parameter values, the proposed LBER can better represent the I–V and P–V characteristics of solar cells and provide a closer representation to actual maximum power points of all module types. Two different algorithms are used to compare the parameter extraction performance of LBER and DDM. One is our restart-based bound constrained Nelder-Mead (rbcNM) algorithm implemented in Matlab, and the other is the reported R_c_r-IJADE algorithm executed in Visual Studio. The comparison results reveal that, the parameter values extracted from LBER using two algorithms are always more accurate and robust than those from DDM despite more time consuming. As an improved version of DDM, the

  4. Design and Development of a Linked Open Data-Based Health Information Representation and Visualization System: Potentials and Preliminary Evaluation

    Science.gov (United States)

    Kauppinen, Tomi; Keßler, Carsten; Fritz, Fleur

    2014-01-01

    Background Healthcare organizations around the world are challenged by pressures to reduce cost, improve coordination and outcome, and provide more with less. This requires effective planning and evidence-based practice by generating important information from available data. Thus, flexible and user-friendly ways to represent, query, and visualize health data becomes increasingly important. International organizations such as the World Health Organization (WHO) regularly publish vital data on priority health topics that can be utilized for public health policy and health service development. However, the data in most portals is displayed in either Excel or PDF formats, which makes information discovery and reuse difficult. Linked Open Data (LOD)—a new Semantic Web set of best practice of standards to publish and link heterogeneous data—can be applied to the representation and management of public level health data to alleviate such challenges. However, the technologies behind building LOD systems and their effectiveness for health data are yet to be assessed. Objective The objective of this study is to evaluate whether Linked Data technologies are potential options for health information representation, visualization, and retrieval systems development and to identify the available tools and methodologies to build Linked Data-based health information systems. Methods We used the Resource Description Framework (RDF) for data representation, Fuseki triple store for data storage, and Sgvizler for information visualization. Additionally, we integrated SPARQL query interface for interacting with the data. We primarily use the WHO health observatory dataset to test the system. All the data were represented using RDF and interlinked with other related datasets on the Web of Data using Silk—a link discovery framework for Web of Data. A preliminary usability assessment was conducted following the System Usability Scale (SUS) method. Results We developed an LOD-based

  5. Design and development of a linked open data-based health information representation and visualization system: potentials and preliminary evaluation.

    Science.gov (United States)

    Tilahun, Binyam; Kauppinen, Tomi; Keßler, Carsten; Fritz, Fleur

    2014-10-25

    Healthcare organizations around the world are challenged by pressures to reduce cost, improve coordination and outcome, and provide more with less. This requires effective planning and evidence-based practice by generating important information from available data. Thus, flexible and user-friendly ways to represent, query, and visualize health data becomes increasingly important. International organizations such as the World Health Organization (WHO) regularly publish vital data on priority health topics that can be utilized for public health policy and health service development. However, the data in most portals is displayed in either Excel or PDF formats, which makes information discovery and reuse difficult. Linked Open Data (LOD)-a new Semantic Web set of best practice of standards to publish and link heterogeneous data-can be applied to the representation and management of public level health data to alleviate such challenges. However, the technologies behind building LOD systems and their effectiveness for health data are yet to be assessed. The objective of this study is to evaluate whether Linked Data technologies are potential options for health information representation, visualization, and retrieval systems development and to identify the available tools and methodologies to build Linked Data-based health information systems. We used the Resource Description Framework (RDF) for data representation, Fuseki triple store for data storage, and Sgvizler for information visualization. Additionally, we integrated SPARQL query interface for interacting with the data. We primarily use the WHO health observatory dataset to test the system. All the data were represented using RDF and interlinked with other related datasets on the Web of Data using Silk-a link discovery framework for Web of Data. A preliminary usability assessment was conducted following the System Usability Scale (SUS) method. We developed an LOD-based health information representation, querying

  6. Numerical model of the nanoindentation test based on the digital material representation of the Ti/TiN multilayers

    Directory of Open Access Journals (Sweden)

    Perzyński Konrad

    2015-06-01

    Full Text Available The developed numerical model of a local nanoindentation test, based on the digital material representation (DMR concept, has been presented within the paper. First, an efficient algorithm describing the pulsed laser deposition (PLD process was proposed to realistically recreate the specific morphology of a nanolayered material in an explicit manner. The nanolayered Ti/TiN composite was selected for the investigation. Details of the developed cellular automata model of the PLD process were presented and discussed. Then, the Ti/TiN DMR was incorporated into the finite element software and numerical model of the nanoindentation test was established. Finally, examples of obtained results presenting capabilities of the proposed approach were highlighted.

  7. Representation of Block-Based Image Features in a Multi-Scale Framework for Built-Up Area Detection

    Directory of Open Access Journals (Sweden)

    Zhongwen Hu

    2016-02-01

    Full Text Available The accurate extraction and mapping of built-up areas play an important role in many social, economic, and environmental studies. In this paper, we propose a novel approach for built-up area detection from high spatial resolution remote sensing images, using a block-based multi-scale feature representation framework. First, an image is divided into small blocks, in which the spectral, textural, and structural features are extracted and represented using a multi-scale framework; a set of refined Harris corner points is then used to select blocks as training samples; finally, a built-up index image is obtained by minimizing the normalized spectral, textural, and structural distances to the training samples, and a built-up area map is obtained by thresholding the index image. Experiments confirm that the proposed approach is effective for high-resolution optical and synthetic aperture radar images, with different scenes and different spatial resolutions.

  8. MORPHOLOGICAL REPRESENTATION AND SEMANTIC ...

    African Journals Online (AJOL)

    The present paper deals with the question of whether the Compositionality. Condition can be ... Selkirk's rule for assigning grammatical functions to the nonhead of .... the meaning of Godel numbering is strictly compositional, a simple ... ennoble, encase), and (ii) nouns of the form V P which are headless ..... *v --> her Prt.

  9. House, a feminine noun: representating architectural spaces in Casa e Jardim and Casa Claudia in age the great magazines

    Directory of Open Access Journals (Sweden)

    Rafael Alves Pinto Junior

    2011-12-01

    Full Text Available The emergence of magazines focusing on architecture and aimed at the general public, such as Casa e jardim in the 1950s and Casa Claudia in the 1970s, represented the creation of a culture of living associated with domestic spaces and the values this space represents as a typological object after the second half of the 20th century. Among other things, it affirmed the values of the social roles of women and architecture as the depository of the attributes of privacy and intimacy: the locus of family, memory and affection. The magazines set the tone for representing the architectural space as an area for living, legitimizing behaviors while exercising an aesthetic pedagogy, ushering in a culture associated with living and establishing a source for imagined ways of building in Brazil. By affirming an image of civilization, both Casa e jardim and Casa Claudia became a benchmark for other periodicals devoted to this theme.

  10. The Mental Representation of Polysemy across Word Classes

    Science.gov (United States)

    Lopukhina, Anastasiya; Laurinavichyute, Anna; Lopukhin, Konstantin; Dragoy, Olga

    2018-01-01

    Experimental studies on polysemy have come to contradictory conclusions on whether words with multiple senses are stored as separate or shared mental representations. The present study examined the semantic relatedness and semantic similarity of literal and non-literal (metonymic and metaphorical) senses of three word classes: nouns, verbs, and adjectives. Two methods were used: a psycholinguistic experiment and a distributional analysis of corpus data. In the experiment, participants were presented with 6–12 short phrases containing a polysemous word in literal, metonymic, or metaphorical senses and were asked to classify them so that phrases with the same perceived sense were grouped together. To investigate the impact of professional background on their decisions, participants were controlled for linguistic vs. non-linguistic education. For nouns and verbs, all participants preferred to group together phrases with literal and metonymic senses, but not any other pairs of senses. For adjectives, two pairs of senses were often grouped together: literal with metonymic, and metonymic with metaphorical. Participants with a linguistic background were more accurate than participants with non-linguistic backgrounds, although both groups shared principal patterns of sense classification. For the distributional analysis of corpus data, we used a semantic vector approach to quantify the similarity of phrases with literal, metonymic, and metaphorical senses in the corpora. We found that phrases with literal and metonymic senses had the highest degree of similarity for the three word classes, and that metonymic and metaphorical senses of adjectives had the highest degree of similarity among all word classes. These findings are in line with the experimental results. Overall, the results suggest that the mental representation of a polysemous word depends on its word class. In nouns and verbs, literal and metonymic senses are stored together, while metaphorical senses are

  11. The Mental Representation of Polysemy across Word Classes

    Directory of Open Access Journals (Sweden)

    Anastasiya Lopukhina

    2018-02-01

    Full Text Available Experimental studies on polysemy have come to contradictory conclusions on whether words with multiple senses are stored as separate or shared mental representations. The present study examined the semantic relatedness and semantic similarity of literal and non-literal (metonymic and metaphorical senses of three word classes: nouns, verbs, and adjectives. Two methods were used: a psycholinguistic experiment and a distributional analysis of corpus data. In the experiment, participants were presented with 6–12 short phrases containing a polysemous word in literal, metonymic, or metaphorical senses and were asked to classify them so that phrases with the same perceived sense were grouped together. To investigate the impact of professional background on their decisions, participants were controlled for linguistic vs. non-linguistic education. For nouns and verbs, all participants preferred to group together phrases with literal and metonymic senses, but not any other pairs of senses. For adjectives, two pairs of senses were often grouped together: literal with metonymic, and metonymic with metaphorical. Participants with a linguistic background were more accurate than participants with non-linguistic backgrounds, although both groups shared principal patterns of sense classification. For the distributional analysis of corpus data, we used a semantic vector approach to quantify the similarity of phrases with literal, metonymic, and metaphorical senses in the corpora. We found that phrases with literal and metonymic senses had the highest degree of similarity for the three word classes, and that metonymic and metaphorical senses of adjectives had the highest degree of similarity among all word classes. These findings are in line with the experimental results. Overall, the results suggest that the mental representation of a polysemous word depends on its word class. In nouns and verbs, literal and metonymic senses are stored together, while

  12. The Mental Representation of Polysemy across Word Classes.

    Science.gov (United States)

    Lopukhina, Anastasiya; Laurinavichyute, Anna; Lopukhin, Konstantin; Dragoy, Olga

    2018-01-01

    Experimental studies on polysemy have come to contradictory conclusions on whether words with multiple senses are stored as separate or shared mental representations. The present study examined the semantic relatedness and semantic similarity of literal and non-literal (metonymic and metaphorical) senses of three word classes: nouns, verbs, and adjectives. Two methods were used: a psycholinguistic experiment and a distributional analysis of corpus data. In the experiment, participants were presented with 6-12 short phrases containing a polysemous word in literal, metonymic, or metaphorical senses and were asked to classify them so that phrases with the same perceived sense were grouped together. To investigate the impact of professional background on their decisions, participants were controlled for linguistic vs. non-linguistic education. For nouns and verbs, all participants preferred to group together phrases with literal and metonymic senses, but not any other pairs of senses. For adjectives, two pairs of senses were often grouped together: literal with metonymic, and metonymic with metaphorical. Participants with a linguistic background were more accurate than participants with non-linguistic backgrounds, although both groups shared principal patterns of sense classification. For the distributional analysis of corpus data, we used a semantic vector approach to quantify the similarity of phrases with literal, metonymic, and metaphorical senses in the corpora. We found that phrases with literal and metonymic senses had the highest degree of similarity for the three word classes, and that metonymic and metaphorical senses of adjectives had the highest degree of similarity among all word classes. These findings are in line with the experimental results. Overall, the results suggest that the mental representation of a polysemous word depends on its word class. In nouns and verbs, literal and metonymic senses are stored together, while metaphorical senses are stored

  13. Discovery Learning, Representation, and Explanation within a Computer-Based Simulation: Finding the Right Mix

    Science.gov (United States)

    Rieber, Lloyd P.; Tzeng, Shyh-Chii; Tribble, Kelly

    2004-01-01

    The purpose of this research was to explore how adult users interact and learn during an interactive computer-based simulation supplemented with brief multimedia explanations of the content. A total of 52 college students interacted with a computer-based simulation of Newton's laws of motion in which they had control over the motion of a simple…

  14. Deriving ontological semantic relations between Arabic compound nouns concepts

    Directory of Open Access Journals (Sweden)

    Imen Bouaziz Mezghanni

    2017-04-01

    Experiments carried out on Arabic legal dataset showed that the proposed approach reached encouraging performance through achieving high precision and recall scores. This performance affects positively the retrieval results of legal documents based on a powerful ontology, which presents our main objective.

  15. DEVS representation of dynamical systems - Event-based intelligent control. [Discrete Event System Specification

    Science.gov (United States)

    Zeigler, Bernard P.

    1989-01-01

    It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

  16. LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

    Science.gov (United States)

    Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

    2016-01-11

    Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.

  17. Geometric representation of the mean-variance-skewness portfolio frontier based upon the shortage function

    OpenAIRE

    Kerstens, Kristiaan; Mounier, Amine; Van de Woestyne, Ignace

    2008-01-01

    The literature suggests that investors prefer portfolios based on mean, variance and skewness rather than portfolios based on mean-variance (MV) criteria solely. Furthermore, a small variety of methods have been proposed to determine mean-variance-skewness (MVS) optimal portfolios. Recently, the shortage function has been introduced as a measure of efficiency, allowing to characterize MVS optimalportfolios using non-parametric mathematical programming tools. While tracing the MV portfolio fro...

  18. Sinusoidal Representation of Acoustic Signals

    Science.gov (United States)

    Honda, Masaaki

    Sinusoidal representation of acoustic signals has been an important tool in speech and music processing like signal analysis, synthesis and time scale or pitch modifications. It can be applicable to arbitrary signals, which is an important advantage over other signal representations like physical modeling of acoustic signals. In sinusoidal representation, acoustic signals are composed as sums of sinusoid (sine wave) with different amplitudes, frequencies and phases, which is based on the timedependent short-time Fourier transform (STFT). This article describes the principles of acoustic signal analysis/synthesis based on a sinusoid representation with focus on sine waves with rapidly varying frequency.

  19. A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

    Directory of Open Access Journals (Sweden)

    Hossien Pourghassem

    2011-04-01

    Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

  20. Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images

    Science.gov (United States)

    Barmpoutis, Angelos

    2009-01-01

    Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…

  1. Improving Conceptual Understanding and Representation Skills through Excel-Based Modeling

    Science.gov (United States)

    Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.

    2018-01-01

    The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental…

  2. Scale space representations locally adapted to the geometry of base and target manifold

    NARCIS (Netherlands)

    Florack, L.M.J.

    2010-01-01

    We generalize the Gaussian multi-resolution image paradigm for a Euclidean domain to general Riemannian base manifolds and also account for the codomain by considering the extension into a fibre bundle structure. We elaborate on aspects of parametrization and gauge, as these are important in

  3. Image denoising using new pixon representation based on fuzzy filtering and partial differential equations

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Nikpour, Mohsen

    2012-01-01

    In this paper, we have proposed two extensions to pixon-based image modeling. The first one is using bicubic interpolation instead of bilinear interpolation and the second one is using fuzzy filtering method, aiming to improve the quality of the pixonal image. Finally, partial differential...

  4. Memory-Based Decision-Making with Heuristics: Evidence for a Controlled Activation of Memory Representations

    Science.gov (United States)

    Khader, Patrick H.; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rosler, Frank

    2011-01-01

    Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by…

  5. Computer-Based Learning: Interleaving Whole and Sectional Representation of Neuroanatomy

    Science.gov (United States)

    Pani, John R.; Chariker, Julia H.; Naaz, Farah

    2013-01-01

    The large volume of material to be learned in biomedical disciplines requires optimizing the efficiency of instruction. In prior work with computer-based instruction of neuroanatomy, it was relatively efficient for learners to master whole anatomy and then transfer to learning sectional anatomy. It may, however, be more efficient to continuously…

  6. Effective representation and storage of mass spectrometry-based proteomic data sets for the scientific community

    DEFF Research Database (Denmark)

    Olsen, Jesper V; Mann, Matthias

    2011-01-01

    Mass spectrometry-based proteomics has emerged as a technology of choice for global analysis of cell signaling networks. However, reporting and sharing of MS data are often haphazard, limiting the usefulness of proteomics to the signaling community. We argue that raw data should always be provided...... mechanisms for community-wide sharing of these data....

  7. Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios.

    Science.gov (United States)

    Hristozov, Dimitar P; Oprea, Tudor I; Gasteiger, Johann

    2007-01-01

    Four different ligand-based virtual screening scenarios are studied: (1) prioritizing compounds for subsequent high-throughput screening (HTS); (2) selecting a predefined (small) number of potentially active compounds from a large chemical database; (3) assessing the probability that a given structure will exhibit a given activity; (4) selecting the most active structure(s) for a biological assay. Each of the four scenarios is exemplified by performing retrospective ligand-based virtual screening for eight different biological targets using two large databases--MDDR and WOMBAT. A comparison between the chemical spaces covered by these two databases is presented. The performance of two techniques for ligand--based virtual screening--similarity search with subsequent data fusion (SSDF) and novelty detection with Self-Organizing Maps (ndSOM) is investigated. Three different structure representations--2,048-dimensional Daylight fingerprints, topological autocorrelation weighted by atomic physicochemical properties (sigma electronegativity, polarizability, partial charge, and identity) and radial distribution functions weighted by the same atomic physicochemical properties--are compared. Both methods were found applicable in scenario one. The similarity search was found to perform slightly better in scenario two while the SOM novelty detection is preferred in scenario three. No method/descriptor combination achieved significant success in scenario four.

  8. Nouns and verbs in Chintang: children's usage and surrounding adult speech

    OpenAIRE

    Stoll, Sabine; Bickel, Balthasar; Lieven, Elena; Banjade, Goma; Bhatta, Toya Nath; Gaenszle, Martin; Paudyal, Netra P; Pettigrew, Judith; Rai, Ichchha Purna; Rai, Manoj; Rai, Novel Kishore

    2012-01-01

    peer-reviewed Analyzing the development of the noun-to-verb ratio in a longitudinal corpus of four Chintang (Sino-Tibetan) children, we find that up to about age four, children have a significantly higher ratio than adults. Previous cross-linguistic research rules out an explanation of this in [*] This research was made by possible by Grant Nos. BI 799/1-2 and II/81 961 from the Volkswagen Foundation (DoBeS program). Author contributions: Stoll designed the study; Bickel ...

  9. COGNITIVE LEARNING STRATEGIES OF NON-ENGLISH DEPARTMENT STUDENTS ON NOUN STRUCTURE

    Directory of Open Access Journals (Sweden)

    Shierly Novalita Yappy

    2006-01-01

    Full Text Available Learning English for non-English department students is not as easy as it seems. Besides, as much as it is necessary to know how successful learners learn, not less important is to know how less successful learners learn. Using think aloud method, this study aims at finding out the cognitive strategies used by the engineering department students in answering incorrectly problems on TOEFL noun structure-the grammar point in which students made the most errors. Findings uncover the students' strategies and reasoning upon which pedagogical implications can be put forth so that more effective and fruitful instruction can be tailored.

  10. Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

    Science.gov (United States)

    Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

    2014-03-01

    We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

  11. Knowledge Representation and Reasoning in Personalized Web-Based e-Learning Applications

    DEFF Research Database (Denmark)

    Dolog, Peter

    2006-01-01

    a user inferred from user interactions with the eLeanrning systems is used to adapt o®ered learning resources and guide a learner through them. This keynote gives an overview about knowledge and rules taken into account in current adaptive eLearning prototypes when adapting learning instructions....... Adaptation is usually based on knowledge about learning esources and users. Rules are used for heuristics to match the learning resources with learners and infer adaptation decisions.......Adaptation that is so natural for teaching by humans is a challenging issue for electronic learning tools. Adaptation in classic teaching is based on observations made about students during teaching. Similar idea was employed in user-adapted (personalized) eLearning applications. Knowledge about...

  12. Tuning of methods for offset free MPC based on ARX model representations

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay

    2010-01-01

    In this paper we investigate model predictive control (MPC) based on ARX models. ARX models can be identified from data using convex optimization technologies and is linear in the system parameters. Compared to other model parameterizations this feature is an advantage in embedded applications...... for robust and automatic system identification. Standard MPC is not able to reject a sustained, unmeasured, non zero mean disturbance and will therefore not provide offset free tracking. Offset free tracking can be guaranteed for this type of disturbances if Δ variables are used or if the state space...... is extended with a disturbance model state. The relation between the base case and the two extended methods are illustrated which provides good understanding and a platform for discussing tuning for good closed loop performance....

  13. ORTHOGONAL REPRESENTATION OF THE PROPER TRANSFORMATION OF A PERSYMMETRIC MATRIX BASED ON ROTATION OPERATORS

    Directory of Open Access Journals (Sweden)

    V. M. Demko

    2018-01-01

    Full Text Available The mathematical substantiation of the algorithm for synthesis of the proper transformation and finding the eigenvalue formulae of a persymmetric matrix of dimension N = 2 k ( k =1, 4 based on orthogonal rotation operators is given. The proposed algorithm made it possible to improve the author's approach to calculating eigenvalues based on numerical examples for the maximal dimension of matrices 64×64, resulting the possibility to obtain analytical relations for calculating the eigenvalues of the persymmetric matrix. It is shown that the proper transformation has a factorized structure in the form of a product of rotation operators, each of which is a direct sum of elementary Givens and Jacobian rotation matrices. 

  14. Object-based selection from spatially-invariant representations: evidence from a feature-report task.

    Science.gov (United States)

    Matsukura, Michi; Vecera, Shaun P

    2011-02-01

    Attention selects objects as well as locations. When attention selects an object's features, observers identify two features from a single object more accurately than two features from two different objects (object-based effect of attention; e.g., Duncan, Journal of Experimental Psychology: General, 113, 501-517, 1984). Several studies have demonstrated that object-based attention can operate at a late visual processing stage that is independent of objects' spatial information (Awh, Dhaliwal, Christensen, & Matsukura, Psychological Science, 12, 329-334, 2001; Matsukura & Vecera, Psychonomic Bulletin & Review, 16, 529-536, 2009; Vecera, Journal of Experimental Psychology: General, 126, 14-18, 1997; Vecera & Farah, Journal of Experimental Psychology: General, 123, 146-160, 1994). In the present study, we asked two questions regarding this late object-based selection mechanism. In Part I, we investigated how observers' foreknowledge of to-be-reported features allows attention to select objects, as opposed to individual features. Using a feature-report task, a significant object-based effect was observed when to-be-reported features were known in advance but not when this advance knowledge was absent. In Part II, we examined what drives attention to select objects rather than individual features in the absence of observers' foreknowledge of to-be-reported features. Results suggested that, when there was no opportunity for observers to direct their attention to objects that possess to-be-reported features at the time of stimulus presentation, these stimuli must retain strong perceptual cues to establish themselves as separate objects.

  15. Virtual Reality Based Accurate Radioactive Source Representation and Dosimetry for Training Applications

    International Nuclear Information System (INIS)

    Molto-Caracena, T.; Vendrell Vidal, E.; Goncalves, J.G.M.; Peerani, P.; )

    2015-01-01

    Virtual Reality (VR) technologies have much potential for training applications. Success relies on the capacity to provide a real-time immersive effect to a trainee. For a training application to be an effective/meaningful tool, 3D realistic scenarios are not enough. Indeed, it is paramount having sufficiently accurate models of the behaviour of the instruments to be used by a trainee. This will enable the required level of user's interactivity. Specifically, when dealing with simulation of radioactive sources, a VR model based application must compute the dose rate with equivalent accuracy and in about the same time as a real instrument. A conflicting requirement is the need to provide a smooth visual rendering enabling spatial interactivity and interaction. This paper presents a VR based prototype which accurately computes the dose rate of radioactive and nuclear sources that can be selected from a wide library. Dose measurements reflect local conditions, i.e., presence of (a) shielding materials with any shape and type and (b) sources with any shape and dimension. Due to a novel way of representing radiation sources, the system is fast enough to grant the necessary user interactivity. The paper discusses the application of this new method and its advantages in terms of time setting, cost and logistics. (author)

  16. Detecting Activation in fMRI Data: An Approach Based on Sparse Representation of BOLD Signal

    Directory of Open Access Journals (Sweden)

    Blanca Guillen

    2018-01-01

    Full Text Available This paper proposes a simple yet effective approach for detecting activated voxels in fMRI data by exploiting the inherent sparsity property of the BOLD signal in temporal and spatial domains. In the time domain, the approach combines the General Linear Model (GLM with a Least Absolute Deviation (LAD based regression method regularized by the pseudonorm l0 to promote sparsity in the parameter vector of the model. In the spatial domain, detection of activated regions is based on thresholding the spatial map of estimated parameters associated with a particular stimulus. The threshold is calculated by exploiting the sparseness of the BOLD signal in the spatial domain assuming a Laplacian distribution model. The proposed approach is validated using synthetic and real fMRI data. For synthetic data, results show that the proposed approach is able to detect most activated voxels without any false activation. For real data, the method is evaluated through comparison with the SPM software. Results indicate that this approach can effectively find activated regions that are similar to those found by SPM, but using a much simpler approach. This study may lead to the development of robust spatial approaches to further simplifying the complexity of classical schemes.

  17. Incidence of a didactic sequence, based on multiple representations, for the strengthening of argumentative competence in high school students

    Directory of Open Access Journals (Sweden)

    Gustavo Bonilla

    2018-01-01

    Full Text Available The present article; seeks to identify the way in which a didactic sequence, based on the implementation of multiple representations, can have an impact on the strengthening of the argumentative competence in basic secondary school students. The methodological foundation on which is based the research, taking into account the mixed approach as a perspective that properly oriented, the exercise of research in the field of education. In view of the above, it performs a process of pedagogical intervention related to the general law of ideal gases, through the implementation of the elements presented in the didactic cycle with a research approach and with the application of a pretest and posttest. The techniques to be used for the process of intervention are the participant observation, the discussion group and the survey. Specifically, as instruments for the collection of information; the interview focused, semi-structured interview and the questions guide. The unit of work corresponds to 36 students --240, six students per each group of 9°-- the basic secondary educational institutions belonging to the Citadel New West, located in the Commune 60 and The Heart, located in the commune 13; both in the city of Medellín.

  18. Automatic media-adventitia IVUS image segmentation based on sparse representation framework and dynamic directional active contour model.

    Science.gov (United States)

    Zakeri, Fahimeh Sadat; Setarehdan, Seyed Kamaledin; Norouzi, Somayye

    2017-10-01

    Segmentation of the arterial wall boundaries from intravascular ultrasound images is an important image processing task in order to quantify arterial wall characteristics such as shape, area, thickness and eccentricity. Since manual segmentation of these boundaries is a laborious and time consuming procedure, many researchers attempted to develop (semi-) automatic segmentation techniques as a powerful tool for educational and clinical purposes in the past but as yet there is no any clinically approved method in the market. This paper presents a deterministic-statistical strategy for automatic media-adventitia border detection by a fourfold algorithm. First, a smoothed initial contour is extracted based on the classification in the sparse representation framework which is combined with the dynamic directional convolution vector field. Next, an active contour model is utilized for the propagation of the initial contour toward the interested borders. Finally, the extracted contour is refined in the leakage, side branch openings and calcification regions based on the image texture patterns. The performance of the proposed algorithm is evaluated by comparing the results to those manually traced borders by an expert on 312 different IVUS images obtained from four different patients. The statistical analysis of the results demonstrates the efficiency of the proposed method in the media-adventitia border detection with enough consistency in the leakage and calcification regions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Machinery vibration signal denoising based on learned dictionary and sparse representation

    International Nuclear Information System (INIS)

    Guo, Liang; Gao, Hongli; Li, Jun; Huang, Haifeng; Zhang, Xiaochen

    2015-01-01

    Mechanical vibration signal denoising has been an import problem for machine damage assessment and health monitoring. Wavelet transfer and sparse reconstruction are the powerful and practical methods. However, those methods are based on the fixed basis functions or atoms. In this paper, a novel method is presented. The atoms used to represent signals are learned from the raw signal. And in order to satisfy the requirements of real-time signal processing, an online dictionary learning algorithm is adopted. Orthogonal matching pursuit is applied to extract the most pursuit column in the dictionary. At last, denoised signal is calculated with the sparse vector and learned dictionary. A simulation signal and real bearing fault signal are utilized to evaluate the improved performance of the proposed method through the comparison with kinds of denoising algorithms. Then Its computing efficiency is demonstrated by an illustrative runtime example. The results show that the proposed method outperforms current algorithms with efficiency calculation. (paper)

  20. XML representation and management of temporal information for web-based cultural heritage applications

    Directory of Open Access Journals (Sweden)

    Fabio Grandi

    2006-01-01

    Full Text Available In this paper we survey the recent activities and achievements of our research group in the deployment of XMLrelated technologies in Cultural Heritage applications concerning the encoding of temporal semantics in Web documents. In particular we will review "The Valid Web", which is an XML/XSL infrastructure we defined and implemented for the definition and management of historical information within multimedia documents available on the Web, and its further extension to the effective encoding of advanced temporal features like indeterminacy, multiple granularities and calendars, enabling an efficient processing in a user-friendly Web-based environment. Potential uses of the developed infrastructures include a broad range of applications in the cultural heritage domain, where the historical perspective is relevant, with potentially positive impacts on E-Education and E-Science.

  1. Status of the phenomena representation, 3D modeling, and cloud-based software architecture development

    International Nuclear Information System (INIS)

    Smith, Curtis L.; Prescott, Steven; Kvarfordt, Kellie; Sampath, Ram; Larson, Katie

    2015-01-01

    Early in 2013, researchers at the Idaho National Laboratory outlined a technical framework to support the implementation of state-of-the-art probabilistic risk assessment to predict the safety performance of advanced small modular reactors. From that vision of the advanced framework for risk analysis, specific tasks have been underway in order to implement the framework. This report discusses the current development of a several tasks related to the framework implementation, including a discussion of a 3D physics engine that represents the motion of objects (including collision and debris modeling), cloud-based analysis tools such as a Bayesian-inference engine, and scenario simulations. These tasks were performed during 2015 as part of the technical work associated with the Advanced Reactor Technologies Program.

  2. A Physics-Based Deep Learning Approach to Shadow Invariant Representations of Hyperspectral Images.

    Science.gov (United States)

    Windrim, Lloyd; Ramakrishnan, Rishi; Melkumyan, Arman; Murphy, Richard J

    2018-02-01

    This paper proposes the Relit Spectral Angle-Stacked Autoencoder, a novel unsupervised feature learning approach for mapping pixel reflectances to illumination invariant encodings. This work extends the Spectral Angle-Stacked Autoencoder so that it can learn a shadow-invariant mapping. The method is inspired by a deep learning technique, Denoising Autoencoders, with the incorporation of a physics-based model for illumination such that the algorithm learns a shadow invariant mapping without the need for any labelled training data, additional sensors, a priori knowledge of the scene or the assumption of Planckian illumination. The method is evaluated using datasets captured from several different cameras, with experiments to demonstrate the illumination invariance of the features and how they can be used practically to improve the performance of high-level perception algorithms that operate on images acquired outdoors.

  3. [Research of electroencephalography representational emotion recognition based on deep belief networks].

    Science.gov (United States)

    Yang, Hao; Zhang, Junran; Jiang, Xiaomei; Liu, Fei

    2018-04-01

    In recent years, with the rapid development of machine learning techniques,the deep learning algorithm has been widely used in one-dimensional physiological signal processing. In this paper we used electroencephalography (EEG) signals based on deep belief network (DBN) model in open source frameworks of deep learning to identify emotional state (positive, negative and neutrals), then the results of DBN were compared with support vector machine (SVM). The EEG signals were collected from the subjects who were under different emotional stimuli, and DBN and SVM were adopted to identify the EEG signals with changes of different characteristics and different frequency bands. We found that the average accuracy of differential entropy (DE) feature by DBN is 89.12%±6.54%, which has a better performance than previous research based on the same data set. At the same time, the classification effects of DBN are better than the results from traditional SVM (the average classification accuracy of 84.2%±9.24%) and its accuracy and stability have a better trend. In three experiments with different time points, single subject can achieve the consistent results of classification by using DBN (the mean standard deviation is1.44%), and the experimental results show that the system has steady performance and good repeatability. According to our research, the characteristic of DE has a better classification result than other characteristics. Furthermore, the Beta band and the Gamma band in the emotional recognition model have higher classification accuracy. To sum up, the performances of classifiers have a promotion by using the deep learning algorithm, which has a reference for establishing a more accurate system of emotional recognition. Meanwhile, we can trace through the results of recognition to find out the brain regions and frequency band that are related to the emotions, which can help us to understand the emotional mechanism better. This study has a high academic value and

  4. Trait-based representation of biological nitrification: Model development, testing, and predicted community composition

    Directory of Open Access Journals (Sweden)

    Nick eBouskill

    2012-10-01

    Full Text Available Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an ‘organism’ in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait focused on nitrification (MicroTrait-N that represents the ammonia-oxidizing bacteria (AOB and ammonia-oxidizing archaea (AOA and nitrite oxidizing bacteria (NOB using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH3 oxidation rates and nitrous oxide (N2O production across pH, temperature and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N2O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N2O by AOB. However, cumulative N2O production (over six month simulations is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH3 oxidation and N2O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH3 oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models.

  5. A Matrix-Based Structure for Vario-Scale Vector Representation over a Wide Range of Map Scales : The Case of River Network Data

    NARCIS (Netherlands)

    Huang, L.; Ai, Tinghua; van Oosterom, P.J.M.; Yan, Xiongfeng; Yang, Min

    2017-01-01

    The representation of vector data at variable scales has been widely applied in geographic information systems and map-based services. When the scale changes across a wide range, a complex generalization that involves multiple operations is required to transform the data. To present such complex

  6. Using listener-based perceptual features as intermediate representations in music information retrieval.

    Science.gov (United States)

    Friberg, Anders; Schoonderwaldt, Erwin; Hedblad, Anton; Fabiani, Marco; Elowsson, Anders

    2014-10-01

    The notion of perceptual features is introduced for describing general music properties based on human perception. This is an attempt at rethinking the concept of features, aiming to approach the underlying human perception mechanisms. Instead of using concepts from music theory such as tones, pitches, and chords, a set of nine features describing overall properties of the music was selected. They were chosen from qualitative measures used in psychology studies and motivated from an ecological approach. The perceptual features were rated in two listening experiments using two different data sets. They were modeled both from symbolic and audio data using different sets of computational features. Ratings of emotional expression were predicted using the perceptual features. The results indicate that (1) at least some of the perceptual features are reliable estimates; (2) emotion ratings could be predicted by a small combination of perceptual features with an explained variance from 75% to 93% for the emotional dimensions activity and valence; (3) the perceptual features could only to a limited extent be modeled using existing audio features. Results clearly indicated that a small number of dedicated features were superior to a "brute force" model using a large number of general audio features.

  7. Dynamic detection-rate-based bit allocation with genuine interval concealment for binary biometric representation.

    Science.gov (United States)

    Lim, Meng-Hui; Teoh, Andrew Beng Jin; Toh, Kar-Ann

    2013-06-01

    Biometric discretization is a key component in biometric cryptographic key generation. It converts an extracted biometric feature vector into a binary string via typical steps such as segmentation of each feature element into a number of labeled intervals, mapping of each interval-captured feature element onto a binary space, and concatenation of the resulted binary output of all feature elements into a binary string. Currently, the detection rate optimized bit allocation (DROBA) scheme is one of the most effective biometric discretization schemes in terms of its capability to assign binary bits dynamically to user-specific features with respect to their discriminability. However, we learn that DROBA suffers from potential discriminative feature misdetection and underdiscretization in its bit allocation process. This paper highlights such drawbacks and improves upon DROBA based on a novel two-stage algorithm: 1) a dynamic search method to efficiently recapture such misdetected features and to optimize the bit allocation of underdiscretized features and 2) a genuine interval concealment technique to alleviate crucial information leakage resulted from the dynamic search. Improvements in classification accuracy on two popular face data sets vindicate the feasibility of our approach compared with DROBA.

  8. Structural damage detection in wind turbine blades based on time series representations of dynamic responses

    Science.gov (United States)

    Hoell, Simon; Omenzetter, Piotr

    2015-03-01

    The development of large wind turbines that enable to harvest energy more efficiently is a consequence of the increasing demand for renewables in the world. To optimize the potential energy output, light and flexible wind turbine blades (WTBs) are designed. However, the higher flexibilities and lower buckling capacities adversely affect the long-term safety and reliability of WTBs, and thus the increased operation and maintenance costs reduce the expected revenue. Effective structural health monitoring techniques can help to counteract this by limiting inspection efforts and avoiding unplanned maintenance actions. Vibration-based methods deserve high attention due to the moderate instrumentation efforts and the applicability for in-service measurements. The present paper proposes the use of cross-correlations (CCs) of acceleration responses between sensors at different locations for structural damage detection in WTBs. CCs were in the past successfully applied for damage detection in numerical and experimental beam structures while utilizing only single lags between the signals. The present approach uses vectors of CC coefficients for multiple lags between measurements of two selected sensors taken from multiple possible combinations of sensors. To reduce the dimensionality of the damage sensitive feature (DSF) vectors, principal component analysis is performed. The optimal number of principal components (PCs) is chosen with respect to a statistical threshold. Finally, the detection phase uses the selected PCs of the healthy structure to calculate scores from a current DSF vector, where statistical hypothesis testing is performed for making a decision about the current structural state. The method is applied to laboratory experiments conducted on a small WTB with non-destructive damage scenarios.

  9. Representation of physiological drought at ecosystem level based on model and eddy covariance measurements

    Science.gov (United States)

    Zhang, Y.; Novick, K. A.; Song, C.; Zhang, Q.; Hwang, T.

    2017-12-01

    Drought and heat waves are expected to increase both in frequency and amplitude, exhibiting a major disturbance to global carbon and water cycles under future climate change. However, how these climate anomalies translate into physiological drought, or ecosystem moisture stress are still not clear, especially under the co-limitations from soil moisture supply and atmospheric demand for water. In this study, we characterized the ecosystem-level moisture stress in a deciduous forest in the southeastern United States using the Coupled Carbon and Water (CCW) model and in-situ eddy covariance measurements. Physiologically, vapor pressure deficit (VPD) as an atmospheric water demand indicator largely controls the openness of leaf stomata, and regulates atmospheric carbon and water exchanges during periods of hydrological stress. Here, we tested three forms of VPD-related moisture scalars, i.e. exponent (K2), hyperbola (K3), and logarithm (K4) to quantify the sensitivity of light-use efficiency to VPD along different soil moisture conditions. The sensitivity indicators of K values were calibrated based on the framework of CCW using Monte Carlo simulations on the hourly scale, in which VPD and soil water content (SWC) are largely decoupled and the full carbon and water exchanging information are held. We found that three K values show similar performances in the predictions of ecosystem-level photosynthesis and transpiration after calibration. However, all K values show consistent gradient changes along SWC, indicating that this deciduous forest is less responsive to VPD as soil moisture decreases, a phenomena of isohydricity in which plants tend to close stomata to keep the leaf water potential constant and reduce the risk of hydraulic failure. Our study suggests that accounting for such isohydric information, or spectrum of moisture stress along different soil moisture conditions in models can significantly improve our ability to predict ecosystem responses to future

  10. Towards the study of color naming in Portuguese: structure and meaning of constructed nouns and adjectives

    Directory of Open Access Journals (Sweden)

    Margarita Correia

    2013-08-01

    Full Text Available Color naming is a central study subject in Lexicology, although its systematic morphological description in Portuguese is still lacking. In this study we describe the morphological and semantic aspects of complex nouns and adjectives constructed on the basis of the basic color terms from the Portuguese language. We focus on a description of the internal structure of these complex words, as well as on aspects concerning the productivity of the morphological processes, and attempt to associate those aspects with the referential capacities of the studied words. Lexicographical data were used, collected from the Vocabulário Ortográfico do Português, and the theoretical framework of this research is SILEX’s constructional model of Morphology. We verified that suffixation is the most productive process, followed by composition. Prefixation is rather unproductive. There are differences in the way that derived nouns and adjectives, on the one hand, and compounds, on the other, may name color tones and degrees of saturation. Derived words give rise to the naming of tones in a very imprecise manner, while compounds are much more effective and precise in the way they may name them, and composition is the most efficient resource available to denote degrees of brightness.

  11. Student Assessment of Quality of Access at the National Open University of Nigeria (NOUN

    Directory of Open Access Journals (Sweden)

    Juliet Obhajajie Inegbedion

    2016-12-01

    Full Text Available This paper presents a study conducted by Inegbedion, Adu and Ofulue from the National Open University of Nigeria. The study focused on the quality of access (admission and registration at NOUN from a student perspective. A survey design was used for the study while a multi-stage sampling technique was used to select the sample size. All the 78,555 registered students in all the 61 Study Centres of the University at the time of the study formed the population; out of which 3,060 students were sampled. The questionnaire instrument is the Institutional Internal QA Tools and Instrument developed by the African Council for Distance Education (ACDE as a regulatory mechanism. The data collected were analyzed using simple statistics. The result showed that 66% of the students confirmed that NOUN has published clear policies on the admission and registration of students. About 29.1% of the students were not satisfied with the transparency of the admission process. In conclusion, the study revealed high quality of access and some deficiencies in website and Internet connectivity.

  12. Memory-Based Shallow Parsing

    OpenAIRE

    Sang, Erik F. Tjong Kim

    2002-01-01

    We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving the performance of the memory-based learner. Our approach is evaluated on standard data sets and the results are compared with that of other systems. This reveals that our approach works well for ba...

  13. Knowledge Representation and Ontologies

    Science.gov (United States)

    Grimm, Stephan

    Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

  14. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

    Directory of Open Access Journals (Sweden)

    An Gary

    2008-05-01

    Full Text Available Abstract Background One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. Results and Discussion ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems Conclusion A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior

  15. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

    Science.gov (United States)

    An, Gary

    2008-05-27

    One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents

  16. Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

    Directory of Open Access Journals (Sweden)

    Jian Ou

    2017-03-01

    Full Text Available The extensive applications of multi-function radars (MFRs have presented a great challenge to the technologies of radar countermeasures (RCMs and electronic intelligence (ELINT. The recently proposed cognitive electronic warfare (CEW provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR. With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

  17. A Slicing Tree Representation and QCP-Model-Based Heuristic Algorithm for the Unequal-Area Block Facility Layout Problem

    Directory of Open Access Journals (Sweden)

    Mei-Shiang Chang

    2013-01-01

    Full Text Available The facility layout problem is a typical combinational optimization problem. In this research, a slicing tree representation and a quadratically constrained program model are combined with harmony search to develop a heuristic method for solving the unequal-area block layout problem. Because of characteristics of slicing tree structure, we propose a regional structure of harmony memory to memorize facility layout solutions and two kinds of harmony improvisation to enhance global search ability of the proposed heuristic method. The proposed harmony search based heuristic is tested on 10 well-known unequal-area facility layout problems from the literature. The results are compared with the previously best-known solutions obtained by genetic algorithm, tabu search, and ant system as well as exact methods. For problems O7, O9, vC10Ra, M11*, and Nug12, new best solutions are found. For other problems, the proposed approach can find solutions that are very similar to previous best-known solutions.

  18. Ionosonde-based indices for improved representation of solar cycle variation in the International Reference Ionosphere model

    Science.gov (United States)

    Brown, Steven; Bilitza, Dieter; Yiǧit, Erdal

    2018-06-01

    A new monthly ionospheric index, IGNS, is presented to improve the representation of the solar cycle variation of the ionospheric F2 peak plasma frequency, foF2. IGNS is calculated using a methodology similar to the construction of the "global effective sunspot number", IG, given by Liu et al. (1983) but selects ionosonde observations based on hemispheres. We incorporated the updated index into the International Reference Ionosphere (IRI) model and compared the foF2 model predictions with global ionospheric observations. We also investigated the influence of the underlying foF2 model on the IG index. IRI has two options for foF2 specification, the CCIR-66 and URSI-88 foF2 models. For the first time, we have calculated IG using URSI-88 and assessed the impact on model predictions. Through a retrospective model-data comparison, results show that the inclusion of the new monthly IGNS index in place of the current 12-month smoothed IG index reduce the foF2 model prediction errors by nearly a factor of two. These results apply to both day-time and nightime predictions. This is due to an overall improved prediction of foF2 seasonal and solar cycle variations in the different hemispheres.

  19. Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations.

    Science.gov (United States)

    Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

    2017-03-19

    The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

  20. A randomized trial of computer-based communications using imagery and text information to alter representations of heart disease risk and motivate protective behaviour.

    Science.gov (United States)

    Lee, Tarryn J; Cameron, Linda D; Wünsche, Burkhard; Stevens, Carey

    2011-02-01

    Advances in web-based animation technologies provide new opportunities to develop graphic health communications for dissemination throughout communities. We developed imagery and text contents of brief, computer-based programmes about heart disease risk, with both imagery and text contents guided by the common-sense model (CSM) of self-regulation. The imagery depicts a three-dimensional, beating heart tailored to user-specific information. A 2 × 2 × 4 factorial design was used to manipulate concrete imagery (imagery vs. no imagery) and conceptual information (text vs. no text) about heart disease risk in prevention-oriented programmes and assess changes in representations and behavioural motivations from baseline to 2 days, 2 weeks, and 4 weeks post-intervention. Sedentary young adults (N= 80) were randomized to view one of four programmes: imagery plus text, imagery only, text only, or control. Participants completed measures of risk representations, worry, and physical activity and healthy diet intentions and behaviours at baseline, 2 days post-intervention (except behaviours), and 2 weeks (intentions and behaviours only) and 4 weeks later. The imagery contents increased representational beliefs and mental imagery relating to heart disease, worry, and intentions at post-intervention. Increases in sense of coherence (understanding of heart disease) and worry were sustained after 1 month. The imagery contents also increased healthy diet efforts after 2 weeks. The text contents increased beliefs about causal factors, mental images of clogged arteries, and worry at post-intervention, and increased physical activity 2 weeks later and sense of coherence 1 month later. The CSM-based programmes induced short-term changes in risk representations and behaviour motivation. The combination of CSM-based text and imagery appears to be most effective in instilling risk representations that motivate protective behaviour. ©2010 The British Psychological Society.

  1. Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum.

    Directory of Open Access Journals (Sweden)

    Makoto Ito

    2015-11-01

    Full Text Available Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the "win-stay, lose-switch" strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS, the dorsomedial striatum (DMS, and the ventral striatum (VS identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum.

  2. Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum.

    Science.gov (United States)

    Ito, Makoto; Doya, Kenji

    2015-11-01

    Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the "win-stay, lose-switch" strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum.

  3. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

    KAUST Repository

    Smaili, Fatima Z.; Gao, Xin; Hoehndorf, Robert

    2018-01-01

    We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

  4. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

    KAUST Repository

    Smaili, Fatima Zohra

    2018-01-31

    We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

  5. The semantic representation of event information depends on the cue modality: an instance of meaning-based retrieval.

    Science.gov (United States)

    Karlsson, Kristina; Sikström, Sverker; Willander, Johan

    2013-01-01

    The semantic content, or the meaning, is the essence of autobiographical memories. In comparison to previous research, which has mainly focused on the phenomenological experience and the age distribution of retrieved events, the present study provides a novel view on the retrieval of event information by quantifying the information as semantic representations. We investigated the semantic representation of sensory cued autobiographical events and studied the modality hierarchy within the multimodal retrieval cues. The experiment comprised a cued recall task, where the participants were presented with visual, auditory, olfactory or multimodal retrieval cues and asked to recall autobiographical events. The results indicated that the three different unimodal retrieval cues generate significantly different semantic representations. Further, the auditory and the visual modalities contributed the most to the semantic representation of the multimodally retrieved events. Finally, the semantic representation of the multimodal condition could be described as a combination of the three unimodal conditions. In conclusion, these results suggest that the meaning of the retrieved event information depends on the modality of the retrieval cues.

  6. The semantic representation of event information depends on the cue modality: an instance of meaning-based retrieval.

    Directory of Open Access Journals (Sweden)

    Kristina Karlsson

    Full Text Available The semantic content, or the meaning, is the essence of autobiographical memories. In comparison to previous research, which has mainly focused on the phenomenological experience and the age distribution of retrieved events, the present study provides a novel view on the retrieval of event information by quantifying the information as semantic representations. We investigated the semantic representation of sensory cued autobiographical events and studied the modality hierarchy within the multimodal retrieval cues. The experiment comprised a cued recall task, where the participants were presented with visual, auditory, olfactory or multimodal retrieval cues and asked to recall autobiographical events. The results indicated that the three different unimodal retrieval cues generate significantly different semantic representations. Further, the auditory and the visual modalities contributed the most to the semantic representation of the multimodally retrieved events. Finally, the semantic representation of the multimodal condition could be described as a combination of the three unimodal conditions. In conclusion, these results suggest that the meaning of the retrieved event information depends on the modality of the retrieval cues.

  7. Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

    Science.gov (United States)

    Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

    2017-02-01

    Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

  8. Mothers' Talk to Children with Down Syndrome, Language Impairment, or Typical Development about Familiar and Unfamiliar Nouns and Verbs

    Science.gov (United States)

    Bird, Elizabeth Kay-Raining; Cleave, Patricia

    2016-01-01

    This study investigated how forty-six mothers modified their talk about familiar and unfamiliar nouns and verbs when interacting with their children with Down Syndrome (DS), language impairment (LI), or typical development (TD). Children (MLUs < 2·7) were group-matched on expressive vocabulary size. Mother-child dyads were recorded playing with…

  9. Acquiring Knowledge in Learning Concepts from Electrical Circuits: The Use of Multiple Representations in Technology-Based Learning Environments

    Directory of Open Access Journals (Sweden)

    Abdeljalil Métioui

    2012-04-01

    Full Text Available The constructivists approach on the conception of relative software of modelling to training and teaching of the concepts of current and voltage requires appraisal of several disciplinary fields in order to provide to the learners a training adapted to their representations. Thus, this approach requires the researchers to have adequate knowledge or skills in data processing, didactics and science content. In this regard, several researches underline that the acquisition of basic concepts that span a field of a given knowledge, must take into account the student and the scientific representations. The present research appears in this perspective, and aims to present the interactive computer environments that take into account the students (secondary and college and scientific representations related to simple electric circuits. These computer environments will help the students to analyze the functions of the electric circuits adequately.

  10. Attention and Representational Momentum

    OpenAIRE

    Hayes, Amy; Freyd, Jennifer J

    1995-01-01

    Representational momentum, the tendency for memory to be distorted in the direction of an implied transformation, suggests that dynamics are an intrinsic part of perceptual representations. We examined the effect of attention on dynamic representation by testing for representational momentum under conditions of distraction. Forward memory shifts increase when attention is divided. Attention may be involved in halting but not in maintaining dynamic representations.

  11. Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

    Directory of Open Access Journals (Sweden)

    Chan-Uk Yeom

    2017-10-01

    Full Text Available This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK-based ELM to develop a systematic approach to generating if-then rules, while the conventional ELM operates without knowledge information. The TSK-ELM design includes a two-phase development. First, we generate an initial random-partition matrix and estimate cluster centers for random clustering. The obtained cluster centers are used to determine the premise parameters of fuzzy if-then rules. Next, the linear weights of the TSK fuzzy type are estimated using the least squares estimate (LSE method. These linear weights are used as the consequent parameters in the TSK-ELM design. The experiments were performed on short-term electricity-load data for forecasting. The electricity-load data were used to forecast hourly day-ahead loads given temperature forecasts; holiday information; and historical loads from the New England ISO. In order to quantify the performance of the forecaster, we use metrics and statistical characteristics such as root mean squared error (RMSE as well as mean absolute error (MAE, mean absolute percent error (MAPE, and R-squared, respectively. The experimental results revealed that the proposed method showed good performance when compared with a conventional ELM with four activation functions such sigmoid, sine, radial basis function, and rectified linear unit (ReLU. It possessed superior prediction performance and knowledge information and a small number of rules.

  12. Cognitive categories and noun classification. Romance neuter: from [passivity] to [indifference

    Directory of Open Access Journals (Sweden)

    Maria M. Manoliu

    2009-01-01

    Full Text Available The present contribution aims to reveal the ways in which the evolution of the grammatical category of gender from Latin to Romance reflects the dramatic changes undergone by its semantic domains. Arguments for the hypothesis that Latin gender oppositions were determined by the important role played by activeness (and not animacy in the interpretation of the state of affairs are brought into the picture in order to explain the subcategorization of nouns in both Latin and in Romance. The term activeness is to be understood as a reflection of the ‘capacity of referents for influencing human life in positive or negative ways’. The changes undergone by grammatical gender in Romance languages were triggered not only by a morpho-syntactic reorganization of case and number, but also by social and pragmatic factors that triggered a reorganization of cognitive categories and their linguistic encoding

  13. A generalized wavelet extrema representation

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Jian; Lades, M.

    1995-10-01

    The wavelet extrema representation originated by Stephane Mallat is a unique framework for low-level and intermediate-level (feature) processing. In this paper, we present a new form of wavelet extrema representation generalizing Mallat`s original work. The generalized wavelet extrema representation is a feature-based multiscale representation. For a particular choice of wavelet, our scheme can be interpreted as representing a signal or image by its edges, and peaks and valleys at multiple scales. Such a representation is shown to be stable -- the original signal or image can be reconstructed with very good quality. It is further shown that a signal or image can be modeled as piecewise monotonic, with all turning points between monotonic segments given by the wavelet extrema. A new projection operator is introduced to enforce piecewise inonotonicity of a signal in its reconstruction. This leads to an enhancement to previously developed algorithms in preventing artifacts in reconstructed signal.

  14. An Ontology-Based Approach to Enable Knowledge Representation and Reasoning in Worker–Cobot Agile Manufacturing

    Directory of Open Access Journals (Sweden)

    Ahmed R. Sadik

    2017-11-01

    accomplish the cooperative manufacturing concept, a proper approach is required to describe the shared environment between the worker and the cobot. The cooperative manufacturing shared environment includes the cobot, the co-worker, and other production components such as the product itself. Furthermore, the whole cooperative manufacturing system components need to communicate and share their knowledge, to reason and process the shared information, which eventually gives the control solution the capability of obtaining collective manufacturing decisions. Putting into consideration that the control solution should also provide a natural language which is human readable and in the same time can be understood by the machine (i.e., the cobot. Accordingly, a distributed control solution which combines an ontology-based Multi-Agent System (MAS and a Business Rule Management System (BRMS is proposed, in order to solve the mentioned challenges in the cooperative manufacturing, which are: manufacturing knowledge representation, sharing, and reasoning.

  15. The Morphosyntactic Structure of the Noun and Verb Phrases in Dholuo/Kiswahili Code Switching

    Directory of Open Access Journals (Sweden)

    Jael Anyango Ojanga

    2015-04-01

    Full Text Available Code switching, the use of any two or more languages or dialects interchangeably in a single communication context, is a common linguistic practice owing to the trend of multilingualism in the world today. In many situations of language in contact, constituents of one language can be found within the constituents of another language in a number of linguistic phenomenon namely lexical borrowing, transferring, interference, code switching and diffusion (Annamalai, 1989. Codeswitching is one of the linguistic phenomenon claimed to be the most prevalent and common mode of interaction among multilingual speakers. Brock and Eastman (1971 suggest that topic discussed influences the choice of the language. Nouns and verbs have been found to be the most code switched elements in bilingual exchange. The study took a qualitative approach with the descriptive research design. It was guided by the Matrix Language Frame Model which was formulated by Myers-Scotton in1993. This model expounds on the realization and structure of the major word classes as used in code switching. Data was collected in Nyangeta Zone, Winam Division of Kisumu East District. Winam Division is mostly inhabited by elite Dholuo L1 speakers. A sample of twenty four teachers was purposively selected to provide data needed for the study. Focus group discussion was used to collect a corpus of Dholuo/Kiswahili data which was recorded through audio taping. The recorded data was then analyzed morphosyntactaically using the Matrix Language Frame Model. The data revealed that the noun and verb phrases were realized under three categories: Matrix Language Island constituent (ML Island ML+EL and Embedded Language Island (EL Island. Keywords: Code switching, multilingualism, morphosyntactic

  16. Inter-subject variability modulates phonological advance planning in the production of adjective-noun phrases.

    Science.gov (United States)

    Michel Lange, Violaine; Laganaro, Marina

    2014-01-01

    The literature on advance phonological planning in adjective-noun phrases (NPs) presents diverging results: while many experimental studies suggest that the entire NP is encoded before articulation, other results favor a span of encoding limited to the first word. Although cross-linguistic differences in the structure of adjective-NPs may account for some of these contrasting results, divergences have been reported even among similar languages and syntactic structures. Here we examined whether inter-individual differences account for variability in the span of phonological planning in the production of French NPs, where previous results indicated encoding limited to the first word. The span of phonological encoding is tested with the picture-word interference (PWI) paradigm using phonological distractors related to the noun or to the adjective of the NPs. In Experiment 1, phonological priming effects were limited to the first word in adjective NPs whichever the position of the adjective (pre-nominal or post-nominal). Crucially, phonological priming effects on the second word interacted with speakers' production speed suggesting different encoding strategies for participants. In Experiment 2, we tested this hypothesis further with a larger group of participants. Results clearly showed that slow and fast initializing participants presented different phonological priming patterns on the last element of adjective-NPs: while the first word was primed by a distractor for all speakers, only the slow speaker group presented a priming effect on the second element of the NP. These results show that the span of phonological encoding is modulated by inter-individual strategies: in experimental paradigms some speakers plan word by word whereas others encode beyond the initial word. We suggest that the diverging results reported in the literature on advance phonological planning may partly be reconciled in light of the present results.

  17. Alternative approach to nuclear data representation

    International Nuclear Information System (INIS)

    Pruet, J.; Brown, D.; Beck, B.; McNabb, D.P.

    2006-01-01

    This paper considers an approach for representing nuclear data that is qualitatively different from the approach currently adopted by the nuclear science community. Specifically, we examine a representation in which complicated data is described through collections of distinct and self-contained simple data structures. This structure-based representation is compared with the ENDF and ENDL formats, which can be roughly characterized as dictionary-based representations. A pilot data representation for replacing the format currently used at LLNL is presented. Examples are given as is a discussion of promises and shortcomings associated with moving from traditional dictionary-based formats to a structure-rich or class-like representation

  18. Tracking the time course of multi-word noun phrase production with ERPs or on when (and why) cat is faster than the big cat.

    Science.gov (United States)

    Bürki, Audrey; Laganaro, Marina

    2014-01-01

    Words are rarely produced in isolation. Yet, our understanding of multi-word production, and especially its time course, is still rather poor. In this research, we use event-related potentials to examine the production of multi-word noun phrases in the context of overt picture naming. We track the processing costs associated with the production of these noun phrases as compared with the production of bare nouns, from picture onset to articulation. Behavioral results revealed longer naming latencies for French noun phrases with determiners and pre-nominal adjectives (D-A-N, the big cat) than for noun phrases with a determiner (D-N, the cat), or bare nouns (N, cat). The spatio-temporal analysis of the ERPs revealed differences in the duration of stable global electrophysiological patterns as a function of utterance format in two time windows, from ~190 to 300 ms after picture onset, and from ~530 ms after picture onset to 100 ms before articulation. These findings can be accommodated in the following model. During grammatical encoding (here from ~190 to 300 ms), the noun and adjective lemmas are accessed in parallel, followed by the selection of the gender-agreeing determiner. Phonological encoding (after ~530 ms) operates sequentially. As a consequence, the phonological encoding process is longer for longer utterances. In addition, when determiners are repeated across trials, their phonological encoding can be anticipated or primed, resulting in a shortened encoding process.

  19. Tracking the time course of multi-word noun phrase production with ERPs or on when (and why cat is faster than the big cat

    Directory of Open Access Journals (Sweden)

    Audrey eBürki

    2014-07-01

    Full Text Available Words are rarely produced in isolation. Yet, our understanding of multi-word production, and especially its time course, is still rather poor. In this research, we use event-related potentials to examine the production of multi-word noun phrases in the context of overt picture naming. We track the processing costs associated with the production of these noun phrases as compared with the production of bare nouns, from picture onset to articulation. Behavioral results revealed longer naming latencies for French noun phrases with determiners and pre-nominal adjectives (D-A-N, the big cat than for noun phrases with a determiner (D-N, the cat or bare nouns (N, cat. The spatio-temporal analysis of the ERPs revealed differences in the duration of stable global electrophysiological patterns as a function of utterance format in two time windows, from ~190 ms to 300 ms after picture onset, and from ~530 ms after picture onset to 100 ms before articulation. These findings can be accommodated in the following model. During grammatical encoding (here from ~190 ms to 300 ms, the noun and adjective lemmas are accessed in parallel, followed by the selection of the gender-agreeing determiner. Phonological encoding (after ~530 ms operates sequentially. As a consequence, the phonological encoding process is longer for longer utterances. In addition, when determiners are repeated across trials, their phonological encoding can be anticipated or primed, resulting in a shortened encoding process.

  20. Teaching Problem Solving to Students Receiving Tiered Interventions Using the Concrete-Representational-Abstract Sequence and Schema-Based Instruction

    Science.gov (United States)

    Flores, Margaret M.; Hinton, Vanessa M.; Burton, Megan E.

    2016-01-01

    Mathematical word problems are the most common form of mathematics problem solving implemented in K-12 schools. Identifying key words is a frequent strategy taught in classrooms in which students struggle with problem solving and show low success rates in mathematics. Researchers show that using the concrete-representational-abstract (CRA)…

  1. Representations for the decay parameter of a birth-death process based on the Courant-Fischer theorem

    NARCIS (Netherlands)

    van Doorn, Erik A.

    2015-01-01

    We study the decay parameter (the rate of convergence of the transition probabilities) of a birth-death process on $\\{0,1,...\\}$, which we allow to evanesce by escape, via state 0, to an absorbing state -1. Our main results are representations for the decay parameter under four different scenarios,

  2. Representations for the decay parameter of a birth-death process based on the Courant-Fischer Theorem

    NARCIS (Netherlands)

    van Doorn, Erik A.

    We study the decay parameter (the rate of convergence of the transition probabilities) of a birth-death process on $\\{0,1,...\\}$, which we allow to evanesce by escape, via state 0, to an absorbing state -1. Our main results are representations for the decay parameter under four different scenarios,

  3. Impossibility Theorem in Proportional Representation Problem

    International Nuclear Information System (INIS)

    Karpov, Alexander

    2010-01-01

    The study examines general axiomatics of Balinski and Young and analyzes existed proportional representation methods using this approach. The second part of the paper provides new axiomatics based on rational choice models. New system of axioms is applied to study known proportional representation systems. It is shown that there is no proportional representation method satisfying a minimal set of the axioms (monotonicity and neutrality).

  4. Computability and Representations of the Zero Set

    NARCIS (Netherlands)

    P.J. Collins (Pieter)

    2008-01-01

    htmlabstractIn this note we give a new representation for closed sets under which the robust zero set of a function is computable. We call this representation the component cover representation. The computation of the zero set is based on topological index theory, the most powerful tool for finding

  5. Constructing visual representations

    DEFF Research Database (Denmark)

    Huron, Samuel; Jansen, Yvonne; Carpendale, Sheelagh

    2014-01-01

    tangible building blocks. We learned that all participants, most of whom had little experience in visualization authoring, were readily able to create and talk about their own visualizations. Based on our observations, we discuss participants’ actions during the development of their visual representations......The accessibility of infovis authoring tools to a wide audience has been identified as a major research challenge. A key task in the authoring process is the development of visual mappings. While the infovis community has long been deeply interested in finding effective visual mappings......, comparatively little attention has been placed on how people construct visual mappings. In this paper, we present the results of a study designed to shed light on how people transform data into visual representations. We asked people to create, update and explain their own information visualizations using only...

  6. Developmental Changes in the Profiles of Dyscalculia: An Explanation Based on a Double Exact-and-Approximate Number Representation Model.

    Science.gov (United States)

    Noël, Marie-Pascale; Rousselle, Laurence

    2011-01-01

    Studies on developmental dyscalculia (DD) have tried to identify a basic numerical deficit that could account for this specific learning disability. The first proposition was that the number magnitude representation of these children was impaired. However, Rousselle and Noël (2007) brought data showing that this was not the case but rather that these children were impaired when processing the magnitude of symbolic numbers only. Since then, incongruent results have been published. In this paper, we will propose a developmental perspective on this issue. We will argue that the first deficit shown in DD regards the building of an exact representation of numerical value, thanks to the learning of symbolic numbers, and that the reduced acuity of the approximate number magnitude system appears only later and is secondary to the first deficit.

  7. Impacts of the aerodynamic force representation on the stability and performance of a galloping-based energy harvester

    Science.gov (United States)

    Javed, U.; Abdelkefi, A.

    2017-07-01

    One of the challenging tasks in the analytical modeling of galloping systems is the representation of the galloping force. In this study, the impacts of using different aerodynamic load representations on the dynamics of galloping oscillations are investigated. A distributed-parameter model is considered to determine the response of a galloping energy harvester subjected to a uniform wind speed. For the same experimental data and conditions, various polynomial expressions for the galloping force are proposed in order to determine the possible differences in the variations of the harvester's outputs as well as the type of instability. For the same experimental data of the galloping force, it is demonstrated that the choice of the coefficients of the polynomial approximation may result in a change in the type of bifurcation, the tip displacement and harvested power amplitudes. A parametric study is then performed to investigate the effects of the electrical load resistance on the harvester's performance when considering different possible representations of the aerodynamic force. It is indicated that for low and high values of the electrical resistance, there is an increase in the range of wind speeds where the response of the energy harvester is not affected. The performed analysis shows the importance of accurately representing the galloping force in order to efficiently design piezoelectric energy harvesters.

  8. Vietnamese Document Representation and Classification

    Science.gov (United States)

    Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

    Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

  9. The Study of the Effect of Syntactic Complexity of Noun and Verb Phrase Structure on the Occurrence of Stuttering in 4-6 Year Pre-School Stuttering Persian Children

    Directory of Open Access Journals (Sweden)

    Abbas Ali Ahangar

    2013-04-01

    Full Text Available Objective: The purpose of the present research was to investigate the effect of syntactic complexity of noun phrase and verb phrase on the occurrence of stuttering in 4-6 year Persian speaking children with stuttering. Materials & Methods: This descriptive-analytic research was done on 15 stuttering children, consisting of 12 boys and 3 girls, 4 to 6 years old monolingual Persian speaking who referred to Javad-Ol-Aemmeh speech therapy clinic in Mashhad city. The sampling approach was simple (available sampling method. To do this research, sampling was carried out in a quiet home of speech therapy where there were just the speech therapist, the parent, the child and the researcher. While speaking, the speech of the children was recorded by an MP3 with Creative brand. Finally, a 30-minute spontaneous speech sample was gathered from each of the given stuttering children. The children produced around 60 utterances during a verbal interaction with the speech therapist, parents (mother or father or the researcher. Then the produced spontaneous speech sample by any of these stuttering children was transcribed on paper. The data were analyzed only as groups and not individually. The data were analyzed using SPSS software and Paired T-test method. Results: The group analyses showed significant differences between fluent and stuttered utterances in terms of syntactic complexity of noun and verb phrase structures. Also, the results confirm that at phrasal level, in noun phrases, based on their three functions as subject, direct object and object of preposition, there is a meaningful relationship between the number of subject (P<0.001 and object of preposition (P=0.050 with the stuttering frequency. In verb phrases, based on the presence of the auxiliary verb, copula verb, and negative prefix, just there is a meaningful relationship between the presence of the auxiliary verb and the stuttering frequency (P=0.010. Conclusion: The research findings indicate

  10. Paired structures in knowledge representation

    DEFF Research Database (Denmark)

    Montero, J.; Bustince, H.; Franco de los Ríos, Camilo

    2016-01-01

    In this position paper we propose a consistent and unifying view to all those basic knowledge representation models that are based on the existence of two somehow opposite fuzzy concepts. A number of these basic models can be found in fuzzy logic and multi-valued logic literature. Here...... of the relationships between several existing knowledge representation formalisms, providing a basis from which more expressive models can be later developed....

  11. Factorizations and physical representations

    International Nuclear Information System (INIS)

    Revzen, M; Khanna, F C; Mann, A; Zak, J

    2006-01-01

    A Hilbert space in M dimensions is shown explicitly to accommodate representations that reflect the decomposition of M into prime numbers. Representations that exhibit the factorization of M into two relatively prime numbers: the kq representation (Zak J 1970 Phys. Today 23 51), and related representations termed q 1 q 2 representations (together with their conjugates) are analysed, as well as a representation that exhibits the complete factorization of M. In this latter representation each quantum number varies in a subspace that is associated with one of the prime numbers that make up M

  12. Self-organising Logic of Structures as a Basis for a Dependency-based Dynamic Semantics Model

    Directory of Open Access Journals (Sweden)

    Maciej Piasecki

    2015-06-01

    Full Text Available Self-organising Logic of Structures as a Basis for a Dependency-based Dynamic Semantics Model We present Self-organising Logic of Structures (SLS, a semantic representation language of high expressive power, which was designed for a fully compositional representation of discourse anaphora following the Dynamic Semantics paradigm. The application of SLS to the description of possible meanings of Polish multiple quantifier sentences is discussed. Special attention is paid to the phenomena of: cardinality dependency/independency of Noun Phrase quantifiers and variety of quantification. Semantic representation based on several formal operators is proposed. They can be combined in many different ways, if one takes a purely theoretical perspective. However, in the paper we show that this huge number is practically reduced in the language use and is governed by several constraints motivated by the analysis of Polish language data. The Hypothesis of Local Range of Cardinality Dependency is formulated as an alternative to representations based on quantifier rising technique. SLS provides a multi-layered language description of inter-linked representation of sever antification, reference, presupposition and anaphora.

  13. RNA-TVcurve: a Web server for RNA secondary structure comparison based on a multi-scale similarity of its triple vector curve representation.

    Science.gov (United States)

    Li, Ying; Shi, Xiaohu; Liang, Yanchun; Xie, Juan; Zhang, Yu; Ma, Qin

    2017-01-21

    RNAs have been found to carry diverse functionalities in nature. Inferring the similarity between two given RNAs is a fundamental step to understand and interpret their functional relationship. The majority of functional RNAs show conserved secondary structures, rather than sequence conservation. Those algorithms relying on sequence-based features usually have limitations in their prediction performance. Hence, integrating RNA structure features is very critical for RNA analysis. Existing algorithms mainly fall into two categories: alignment-based and alignment-free. The alignment-free algorithms of RNA comparison usually have lower time complexity than alignment-based algorithms. An alignment-free RNA comparison algorithm was proposed, in which novel numerical representations RNA-TVcurve (triple vector curve representation) of RNA sequence and corresponding secondary structure features are provided. Then a multi-scale similarity score of two given RNAs was designed based on wavelet decomposition of their numerical representation. In support of RNA mutation and phylogenetic analysis, a web server (RNA-TVcurve) was designed based on this alignment-free RNA comparison algorithm. It provides three functional modules: 1) visualization of numerical representation of RNA secondary structure; 2) detection of single-point mutation based on secondary structure; and 3) comparison of pairwise and multiple RNA secondary structures. The inputs of the web server require RNA primary sequences, while corresponding secondary structures are optional. For the primary sequences alone, the web server can compute the secondary structures using free energy minimization algorithm in terms of RNAfold tool from Vienna RNA package. RNA-TVcurve is the first integrated web server, based on an alignment-free method, to deliver a suite of RNA analysis functions, including visualization, mutation analysis and multiple RNAs structure comparison. The comparison results with two popular RNA

  14. AHP 1:A RESPONSE TO WAYS AND THE SYNTAX OF NOUN PHRASES IN QĪNGHĂI CHINESE DIALECTS

    Directory of Open Access Journals (Sweden)

    Keith Dede

    2009-06-01

    Full Text Available In the course of offering a review of Zhāng Chéngcái's Ways, this paper describes the syntax of noun phrases in the Chinese dialect of Huángshuĭ, in Qīnghăi Province. Unlike other Chinese dialects, this dialect employs several postpositions for indicating syntactic nominal relationships. The origin of this phenomenon in contact with non-Sinitic languages in the region and its significance are also explored.

  15. PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

    Science.gov (United States)

    Lutich, Andrey

    2017-07-01

    This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

  16. Symbolic Play and Novel Noun Learning in Deaf and Hearing Children: Longitudinal Effects of Access to Sound on Early Precursors of Language

    Science.gov (United States)

    Quittner, Alexandra L.; Cejas, Ivette; Wang, Nae-Yuh; Niparko, John K.; Barker, David H.

    2016-01-01

    In the largest, longitudinal study of young, deaf children before and three years after cochlear implantation, we compared symbolic play and novel noun learning to age-matched hearing peers. Participants were 180 children from six cochlear implant centers and 96 hearing children. Symbolic play was measured during five minutes of videotaped, structured solitary play. Play was coded as "symbolic" if the child used substitution (e.g., a wooden block as a bed). Novel noun learning was measured in 10 trials using a novel object and a distractor. Cochlear implant vs. normal hearing children were delayed in their use of symbolic play, however, those implanted before vs. after age two performed significantly better. Children with cochlear implants were also delayed in novel noun learning (median delay 1.54 years), with minimal evidence of catch-up growth. Quality of parent-child interactions was positively related to performance on the novel noun learning, but not symbolic play task. Early implantation was beneficial for both achievement of symbolic play and novel noun learning. Further, maternal sensitivity and linguistic stimulation by parents positively affected noun learning skills, although children with cochlear implants still lagged in comparison to hearing peers. PMID:27228032

  17. Symbolic Play and Novel Noun Learning in Deaf and Hearing Children: Longitudinal Effects of Access to Sound on Early Precursors of Language.

    Science.gov (United States)

    Quittner, Alexandra L; Cejas, Ivette; Wang, Nae-Yuh; Niparko, John K; Barker, David H

    2016-01-01

    In the largest, longitudinal study of young, deaf children before and three years after cochlear implantation, we compared symbolic play and novel noun learning to age-matched hearing peers. Participants were 180 children from six cochlear implant centers and 96 hearing children. Symbolic play was measured during five minutes of videotaped, structured solitary play. Play was coded as "symbolic" if the child used substitution (e.g., a wooden block as a bed). Novel noun learning was measured in 10 trials using a novel object and a distractor. Cochlear implant vs. normal hearing children were delayed in their use of symbolic play, however, those implanted before vs. after age two performed significantly better. Children with cochlear implants were also delayed in novel noun learning (median delay 1.54 years), with minimal evidence of catch-up growth. Quality of parent-child interactions was positively related to performance on the novel noun learning, but not symbolic play task. Early implantation was beneficial for both achievement of symbolic play and novel noun learning. Further, maternal sensitivity and linguistic stimulation by parents positively affected noun learning skills, although children with cochlear implants still lagged in comparison to hearing peers.

  18. (Self)-representations on youtube

    DEFF Research Database (Denmark)

    Simonsen, Thomas Mosebo

    This paper examines forms of self-representation on YouTube with specific focus on Vlogs (Video blogs). The analytical scope of the paper is on how User-generated Content on YouTube initiates a certain kind of audiovisual representation and a particular interpretation of reality that can...... be distinguished within Vlogs. This will be analysed through selected case studies taken from a representative sample of empirically based observations of YouTube videos. The analysis includes a focus on how certain forms of representation can be identified as representations of the self (Turkle 1995, Scannell...... 1996, Walker 2005) and further how these forms must be comprehended within a context of technological constrains, institutional structures and social as well as economical practices on YouTube (Burgess and Green 2009, Van Dijck 2009). It is argued that these different contexts play a vital part...

  19. Triple representation of language, working memory, social and emotion processing in the cerebellum: convergent evidence from task and seed-based resting-state fMRI analyses in a single large cohort.

    Science.gov (United States)

    Guell, Xavier; Gabrieli, John D E; Schmahmann, Jeremy D

    2018-05-15

    Delineation of functional topography is critical to the evolving understanding of the cerebellum's role in a wide range of nervous system functions. We used data from the Human Connectome Project (n = 787) to analyze cerebellar fMRI task activation (motor, working memory, language, social and emotion processing) and resting-state functional connectivity calculated from cerebral cortical seeds corresponding to the peak Cohen's d of each task contrast. The combination of exceptional statistical power, activation from both motor and multiple non-motor tasks in the same participants, and convergent resting-state networks in the same participants revealed novel aspects of the functional topography of the human cerebellum. Consistent with prior studies there were two distinct representations of motor activation. Newly revealed were three distinct representations each for working memory, language, social, and emotional task processing that were largely separate for these four cognitive and affective domains. In most cases, the task-based activations and the corresponding resting-network correlations were congruent in identifying the two motor representations and the three non-motor representations that were unique to working memory, language, social cognition, and emotion. The definitive localization and characterization of distinct triple representations for cognition and emotion task processing in the cerebellum opens up new basic science questions as to why there are triple representations (what different functions are enabled by the different representations?) and new clinical questions (what are the differing consequences of lesions to the different representations?). Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Tools for language: patterned iconicity in sign language nouns and verbs.

    Science.gov (United States)

    Padden, Carol; Hwang, So-One; Lepic, Ryan; Seegers, Sharon

    2015-01-01

    When naming certain hand-held, man-made tools, American Sign Language (ASL) signers exhibit either of two iconic strategies: a handling strategy, where the hands show holding or grasping an imagined object in action, or an instrument strategy, where the hands represent the shape or a dimension of the object in a typical action. The same strategies are also observed in the gestures of hearing nonsigners identifying pictures of the same set of tools. In this paper, we compare spontaneously created gestures from hearing nonsigning participants to commonly used lexical signs in ASL. Signers and gesturers were asked to respond to pictures of tools and to video vignettes of actions involving the same tools. Nonsigning gesturers overwhelmingly prefer the handling strategy for both the Picture and Video conditions. Nevertheless, they use more instrument forms when identifying tools in pictures, and more handling forms when identifying actions with tools. We found that ASL signers generally favor the instrument strategy when naming tools, but when describing tools being used by an actor, they are significantly more likely to use more handling forms. The finding that both gesturers and signers are more likely to alternate strategies when the stimuli are pictures or video suggests a common cognitive basis for differentiating objects from actions. Furthermore, the presence of a systematic handling/instrument iconic pattern in a sign language demonstrates that a conventionalized sign language exploits the distinction for grammatical purpose, to distinguish nouns and verbs related to tool use. Copyright © 2014 Cognitive Science Society, Inc.

  1. Index finger motor imagery EEG pattern recognition in BCI applications using dictionary cleaned sparse representation-based classification for healthy people

    Science.gov (United States)

    Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Fengkui; Liu, Feixiang

    2017-09-01

    Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface (BCI) has shown its effectiveness for the control of rehabilitation devices designed for large body parts of the patients with neurologic impairments. In order to validate the feasibility of using EEG to decode the MI of a single index finger and constructing a BCI-enhanced finger rehabilitation system, we collected EEG data during right hand index finger MI and rest state for five healthy subjects and proposed a pattern recognition approach for classifying these two mental states. First, Fisher's linear discriminant criteria and power spectral density analysis were used to analyze the event-related desynchronization patterns. Second, both band power and approximate entropy were extracted as features. Third, aiming to eliminate the abnormal samples in the dictionary and improve the classification performance of the conventional sparse representation-based classification (SRC) method, we proposed a novel dictionary cleaned sparse representation-based classification (DCSRC) method for final classification. The experimental results show that the proposed DCSRC method gives better classification accuracies than SRC and an average classification accuracy of 81.32% is obtained for five subjects. Thus, it is demonstrated that single right hand index finger MI can be decoded from the sensorimotor rhythms, and the feature patterns of index finger MI and rest state can be well recognized for robotic exoskeleton initiation.

  2. The Transition from New Spain to Republican Mexico Based on The Concept of Representation, 1750-1850

    Directory of Open Access Journals (Sweden)

    Aquiles Omar Ávila Quijas

    2011-01-01

    Full Text Available This paper analyzes the semantic trajectory of the conceot of representation, from the late viceroyal period until republican Mexico. The reader will realize that the change towards its modern and politicial connotation is related to a series of events that took place in the Ibeian Peninsula during 1808 and to the influence of the postulates of political liberalism in the 18th century. He will also be able to notice that a new meaning requires a long term process to settle in the political worldview and language. Therefore, we also try to relate this concept to others that emerged as satellites, with views to offer an explanation for the construction process of Mexico's institutional arrangement in the 19th century.

  3. [Biometric identification method for ECG based on the piecewise linear representation (PLR) and dynamic time warping (DTW)].

    Science.gov (United States)

    Yang, Licai; Shen, Jun; Bao, Shudi; Wei, Shoushui

    2013-10-01

    To treat the problem of identification performance and the complexity of the algorithm, we proposed a piecewise linear representation and dynamic time warping (PLR-DTW) method for ECG biometric identification. Firstly we detected R peaks to get the heartbeats after denoising preprocessing. Then we used the PLR method to keep important information of an ECG signal segment while reducing the data dimension at the same time. The improved DTW method was used for similarity measurements between the test data and the templates. The performance evaluation was carried out on the two ECG databases: PTB and MIT-BIH. The analystic results showed that compared to the discrete wavelet transform method, the proposed PLR-DTW method achieved a higher accuracy rate which is nearly 8% of rising, and saved about 30% operation time, and this demonstrated that the proposed method could provide a better performance.

  4. STUDENT MISCONCEPTION ON REDOX TITRATION (A CHALLENGE ON THE COURSE IMPLEMENTATION THROUGH COGNITIVE DISSONANCE BASED ON THE MULTIPLE REPRESENTATIONS

    Directory of Open Access Journals (Sweden)

    H. R. Widarti

    2016-04-01

    Full Text Available The misconception is one of the obstacles in the concept mastery that needed to be minimalized. This descriptive study was conducted to find the patterns of misconceptions which have occurred on college students who participating in the redox titration course subject. Efforts to minimize misconceptions have been conducted through lectures using the multiple representations with the cognitive dissonance strategies on the 30 students who joined the Fundamentals of Analytical Chemistry course. The research instrument used in this study was 6 multiple-choice tests with reasons. In order to detect the misconception, Certainty of Response Index technique was performed. The preliminary study results showed that 34.30% of students experiencing the misconceptions on redox titration. After treatments, the misconceptions reduced to 28.17%. A misconception that cannot be eliminated was related to the concepts involving in the microscopic and symbolic appearances.

  5. Code conversion from signed-digit to complement representation based on look-ahead optical logic operations

    Science.gov (United States)

    Li, Guoqiang; Qian, Feng

    2001-11-01

    We present, for the first time to our knowledge, a generalized lookahead logic algorithm for number conversion from signed-digit to complement representation. By properly encoding the signed-digits, all the operations are performed by binary logic, and unified logical expressions can be obtained for conversion from modified-signed- digit (MSD) to 2's complement, trinary signed-digit (TSD) to 3's complement, and quarternary signed-digit (QSD) to 4's complement. For optical implementation, a parallel logical array module using an electron-trapping device is employed and experimental results are shown. This optical module is suitable for implementing complex logic functions in the form of the sum of the product. The algorithm and architecture are compatible with a general-purpose optoelectronic computing system.

  6. A Gray-code-based color image representation method using TSNAM%TSNAM彩色图像的格雷码表示

    Institute of Scientific and Technical Information of China (English)

    郑运平; 张佳婧

    2012-01-01

    为了提高彩色图像模式的表示效率,借助于三角形和正方形布局问题的思想,将格雷码和位平面分解方法应用到彩色图像的三角形和正方形NAM表示方法(TSNAM)中,提出了一种基于格雷码的TSNAM彩色图像表示方法(GTSNAM).给出了GTSNAM表示算法的形式化描述,并对其存储结构、总数据量和时空复杂性进行了分析.理论分析和实验结果表明,与最新提出的TSNAM表示方法和经典的线性四元树(LQT)表示方法相比,GTSNAM表示方法具有更少的子模式数(或节点数),能够更有效地减少数据存储空间,因而是一种有效的彩色图像表示方法.%Inspired by an idea obtained from the triangle and the square packing problems, a new Gray-code-based color image representation method using a non-symmetry and anti-packing pattern representation model with the triangle and the square subpatterns (TSNAM) , also called the GTSNAM representation method, was proposed to improve the representation efficiency of color images by applying the Gray code and the bit-plane decomposition method. Also, a concrete algorithm of GTSNAM for color images was presented, and the storage structure, the total data amount, and the time and space complexities of the proposed algorithm were analyzed. By comparing the GTSNAM algorithm with those of the classic linear quadtree (LQT) and the latest TSNAM, which is not based on the Gray code, the theoretical and experimental results show that the former can greatly reduce the number of subpatterns or nodes and simultaneously save the storage space much more effectively than the latter ones. The GTSNAM algorithm is therefore shown to be a better method to represent color images.

  7. Representation in Memory.

    Science.gov (United States)

    Rumelhart, David E.; Norman, Donald A.

    This paper reviews work on the representation of knowledge from within psychology and artificial intelligence. The work covers the nature of representation, the distinction between the represented world and the representing world, and significant issues concerned with propositional, analogical, and superpositional representations. Specific topics…

  8. Social Representations of Intelligence

    Directory of Open Access Journals (Sweden)

    Elena Zubieta

    2016-02-01

    Full Text Available The article stresses the relationship between Explicit and Implicit theories of Intelligence. Following the line of common sense epistemology and the theory of Social Representations, a study was carried out in order to analyze naive’s explanations about Intelligence Definitions. Based on Mugny & Carugati (1989 research, a self-administered questionnaire was designed and filled in by 286 subjects. Results are congruent with the main hyphotesis postulated: A general overlap between explicit and implicit theories showed up. According to the results Intelligence appears as both, a social attribute related to social adaptation and as a concept defined in relation with contextual variables similar to expert’s current discourses. Nevertheless, conceptions based on “gifted ideology” still are present stressing the main axes of Intelligence debate: biological and sociological determinism. In the same sense, unfamiliarity and social identity are reaffirmed as organizing principles of social representation. The distance with the object -measured as the belief in intelligence differences as a solve/non solve problem- and the level of implication with the topic -teachers/no teachers- appear as discriminating elements at the moment of supporting specific dimensions. 

  9. Development of Mole Concept Module Based on Structured Inquiry with Interconection of Macro, Submicro, and Symbolic Representation for Grade X of Senior High School

    Science.gov (United States)

    Sagita, R.; Azra, F.; Azhar, M.

    2018-04-01

    The research has created the module of mole concept based on structured inquiry with interconection of macro, submicro, and symbolic representation and determined the validity and practicality of the module. The research type was Research and Development (R&D). The development model was 4-D models that consist of four steps: define, design, develop, and disseminate. The research was limited on develop step. The instrument of the research was questionnaire form that consist of validity and practicality sheets. The module was validated by 5 validators. Practicality module was tested by 2 chemistry teachers and 28 students of grade XI MIA 5 at SMAN 4 of Padang. Validity and practicality data were analysed by using the kappa Cohen formula. The moment kappa average of 5 validators was 0,95 with highest validity category. The moment kappa average of teachers and students were 0,89 and 0,91 praticality with high category. The result of the research showed that the module of mole concept based on structured inquiry with interconection of macro, submicro, and symbolic representation was valid and practice to be used on the learning chemistry.

  10. Early sensitivity of left perisylvian cortex to relationality in nouns and verbs.

    Science.gov (United States)

    Williams, Adina; Reddigari, Samir; Pylkkänen, Liina

    2017-06-01

    The ability to track the relationality of concepts, i.e., their capacity to encode a relationship between entities, is one of the core semantic abilities humans possess. In language processing, we systematically leverage this ability when computing verbal argument structure, in order to link participants to the events they participate in. Previous work has converged on a large region of left posterior perisylvian cortex as a locus for such processing, but the wide range of experimental stimuli and manipulations has yielded an unclear picture of the region's exact role(s). Importantly, there is a tendency for effects of relationality in single-word studies to localize to posterior temporo-parietal cortex, while argument structure effects in sentences appear in left superior temporal cortex. To characterize these sensitivities, we designed two MEG experiments that cross the factors relationality and eventivity. The first used minimal noun phrases and tested for an effect of semantic composition, while the second employed full sentences and a manipulation of grammatical category. The former identified a region of the left inferior parietal lobe sensitive to relationality, but not eventivity or combination, beginning at 170ms. The latter revealed a similarly-timed effect of relationality in left mid-superior temporal cortex, independent of eventivity and category. The results suggest that i) multiple sub-regions of perisylvian cortex are sensitive to the relationality carried by concepts even in the absence of arguments, ii) linguistic context modulates the locus of this sensitivity, consistent with prior studies, and iii) relationality information is accessed early - before 200ms - regardless of the concept's event status or syntactic category. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. An introduction to quiver representations

    CERN Document Server

    Derksen, Harm

    2017-01-01

    This book is an introduction to the representation theory of quivers and finite dimensional algebras. It gives a thorough and modern treatment of the algebraic approach based on Auslander-Reiten theory as well as the approach based on geometric invariant theory. The material in the opening chapters is developed starting slowly with topics such as homological algebra, Morita equivalence, and Gabriel's theorem. Next, the book presents Auslander-Reiten theory, including almost split sequences and the Auslander-Reiten transform, and gives a proof of Kac's generalization of Gabriel's theorem. Once this basic material is established, the book goes on with developing the geometric invariant theory of quiver representations. The book features the exposition of the saturation theorem for semi-invariants of quiver representations and its application to Littlewood-Richardson coefficients. In the final chapters, the book exposes tilting modules, exceptional sequences and a connection to cluster categories. The book is su...

  12. Preon representations and composite models

    International Nuclear Information System (INIS)

    Kang, Kyungsik

    1982-01-01

    This is a brief report on the preon models which are investigated by In-Gyu Koh, A. N. Schellekens and myself and based on complex, anomaly-free and asymptotically free representations of SU(3) to SU(8), SO(4N+2) and E 6 with no more than two different preons. Complete list of the representations that are complex anomaly-free and asymptotically free has been given by E. Eichten, I.-G. Koh and myself. The assumptions made about the ground state composites and the role of Fermi statistics to determine the metaflavor wave functions are discussed in some detail. We explain the method of decompositions of tensor products with definite permutation properties which has been developed for this purpose by I.-G. Koh, A.N. Schellekens and myself. An example based on an anomaly-free representation of the confining metacolor group SU(5) is discussed

  13. The Extension of Quality Function Deployment Based on 2-Tuple Linguistic Representation Model for Product Design under Multigranularity Linguistic Environment

    Directory of Open Access Journals (Sweden)

    Ming Li

    2012-01-01

    Full Text Available Quality function deployment (QFD is a customer-driven approach for product design and development. A QFD analysis process includes a series of subprocesses, such as determination of the importance of customer requirements (CRs, the correlation among engineering characteristics (ECs, and the relationship between CRs and ECs. Usually more than group of one decision makers are involved in the subprocesses to make the decision. In most decision making problems, they often provide their evaluation information in the linguistic form. Moreover, because of different knowledge, background, and discrimination ability, decision makers may express their linguistic preferences in multigranularity linguistic information. Therefore, an effective approach to deal with the multi-granularity linguistic information in QFD analysis process is highly needed. In this study, the QFD methodology is extended with 2-tuple linguistic representation model under multi-granularity linguistic environment. The extended QFD methodology can cope with multi-granularity linguistic evaluation information and avoid the loss of information. The applicability of the proposed approach is demonstrated with a numerical example.

  14. Multi-View Multi-Instance Learning Based on Joint Sparse Representation and Multi-View Dictionary Learning.

    Science.gov (United States)

    Li, Bing; Yuan, Chunfeng; Xiong, Weihua; Hu, Weiming; Peng, Houwen; Ding, Xinmiao; Maybank, Steve

    2017-12-01

    In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many applications. Previous studies on MIL either ignore such relations or simply model them with a fixed graph structure so that the overall performance inevitably degrades in complex environments. To address this problem, this paper proposes a novel multi-view multi-instance learning algorithm (MIL) that combines multiple context structures in a bag into a unified framework. The novel aspects are: (i) we propose a sparse -graph model that can generate different graphs with different parameters to represent various context relations in a bag, (ii) we propose a multi-view joint sparse representation that integrates these graphs into a unified framework for bag classification, and (iii) we propose a multi-view dictionary learning algorithm to obtain a multi-view graph dictionary that considers cues from all views simultaneously to improve the discrimination of the MIL. Experiments and analyses in many practical applications prove the effectiveness of the M IL.

  15. Family farming and areas of permanent preservation: an analysis based on the colonos’ social representations in Botuverá/SC.

    Directory of Open Access Journals (Sweden)

    Cíntia Uller-Gómez

    2009-07-01

    Full Text Available The purpose of this study is to analyse the colonos’ social representations in Botuverá (SC, concerning the use of the margins of the water courses and the meanings of exotic forestry species planting (eucalyptus, above all in their rural establishments. Examining the heart of peasantry values in general and, in particular, the values expressed by the colonos, we found that the margins of water courses are considered as productive areas for the family. On the other hand, the planting of exotic forestry species appears with more intensity in the rural establishments where the above-mentioned peasant values do not greatly influence the decision-making process, as well as in those establishments that do not exclusively depend on the use of the land. We have concluded that the strategies for environmental preservation should take into account the family farmer’s practical needs and symbolic aspects, creating joint alternatives of conservative use, valuing the fact that there was a greater interest in preserving the biodiversity in the establishments where the peasant categories were more evident. Key-words: Family farming; Riparian vegetation; Permanent preservation areas.

  16. Children's grammatical categories of verb and noun: a comparative look at children with specific language impairment (SLI) and normal language (NL).

    Science.gov (United States)

    Skipp, Amy; Windfuhr, Kirsten L; Conti-Ramsden, Gina

    2002-01-01

    The study investigated the development of grammatical categories (noun and verb) in young language learners. Twenty-eight children with specific language impairment (SLI) with a mean language age of 35 months and 28 children with normal language (NL) with a mean language age of 34 months were exposed to four novel verbs and four novel nouns during 10 experimental child-directed play sessions. The lexical items were modelled with four experimentally controlled argument structures. Both groups of children showed little productivity with syntactic marking of arguments in the novel verb conditions. Thus, both groups of children mostly followed the surface structure of the model presented to them, regardless of the argument they were trying to express. Therefore, there was little evidence of verb-general processes. In contrast, both groups used nouns in semantic roles that had not been modelled for them. Importantly, however, children with SLI still appeared to be more input dependent than NL children. This suggests that children with NL were working with a robust noun schema, whereas children with SLI were not. Taken together, the findings suggest that neither group of children had a grammatical category of verb, but demonstrated a general knowledge of the grammatical category of noun. These findings are discussed in relation to current theories of normal and impaired language development.

  17. (Self)-representations on youtube

    OpenAIRE

    Simonsen, Thomas Mosebo

    2011-01-01

    This paper examines forms of self-representation on YouTube with specific focus on Vlogs (Video blogs). The analytical scope of the paper is on how User-generated Content on YouTube initiates a certain kind of audiovisual representation and a particular interpretation of reality that can be distinguished within Vlogs. This will be analysed through selected case studies taken from a representative sample of empirically based observations of YouTube videos. The analysis includes a focus on how ...

  18. Reusable Lexical Representations for Idioms

    NARCIS (Netherlands)

    Odijk, J.E.J.M.

    2004-01-01

    In this paper I introduce (1) a technically simple and highly theory-independent way for lexically representing flexible idiomatic expressions, and (2) a procedure to incorporate these lexical representations in a wide variety of NLP systems. The method is based on Structural EQuivalence Classes

  19. Conceptual Knowledge Representation and Reasoning

    DEFF Research Database (Denmark)

    Oldager, Steen Nikolaj

    2003-01-01

    One of the main areas in knowledge representation and logic-based artificial intelligence concerns logical formalisms that can be used for representing and reasoning with concepts. For almost 30 years, since research in this area began, the issue of intensionality has had a special status...

  20. Asymptotical representation of discrete groups

    International Nuclear Information System (INIS)

    Mishchenko, A.S.; Mohammad, N.

    1995-08-01

    If one has a unitary representation ρ: π → U(H) of the fundamental group π 1 (M) of the manifold M then one can do may useful things: 1. To construct a natural vector bundle over M; 2. To construct the cohomology groups with respect to the local system of coefficients; 3. To construct the signature of manifold M with respect to the local system of coefficients; and others. In particular, one can write the Hirzebruch formula which compares the signature with the characteristic classes of the manifold M, further based on this, find the homotopy invariant characteristic classes (i.e. the Novikov conjecture). Taking into account that the family of known representations is not sufficiently large, it would be interesting to extend this family to some larger one. Using the ideas of A.Connes, M.Gromov and H.Moscovici a proper notion of asymptotical representation is defined. (author). 7 refs