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.

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

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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.

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.

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

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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.

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 ...

THE COMMON AND PROPER NOUNS BETWEEN ALBANIAN AND ENGLISH

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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...

Verb-Noun Collocations in Written Discourse of Iranian EFL Learners

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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.

Noun complement clauses as referential modifiers

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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.

Semantic and syntactic forces in noun phrase production

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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

Layers of root nouns in Germanic

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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...

Representations of abstract grammatical feature agreement in young children.

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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.

Investigating differences between proper and common nouns using novel word learning

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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

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

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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.

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.

Noun-Verb Ambiguity in Chronic Undifferentiated Schizophrenia

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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…

Explaining word order in the noun phrase

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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...

Representation of grammatical categories of words in the brain.

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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.

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

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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.

An Analysis of Noun Definition in Cantonese

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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…

Old Romanian pluralized mass and abstract nouns

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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.

Noun combination in interlanguage typology effects in complex determiner phrases

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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.

The Treatment of Borrowed Nouns in Isichazamazwi SesiNdebele and Isichazamazwi SezoMculo

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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.

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 ...

Verb-Noun Collocation Proficiency and Academic Years

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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.

Shell Nouns as Cohesive Devices in Published and ESL Student Writing

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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…

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

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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…

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 ...

Exploring Noun Bias in Filipino-English Bilingual Children

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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…

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…

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

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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…

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

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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.

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

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M.H. Mpungose

2012-09-01

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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

Acquisition of noun derivation in Estonian and Russian L1

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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.

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...

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

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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.

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

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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.

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

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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.

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 ...

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...

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

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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

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

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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.

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

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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.

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.

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...

The prosody of Swedish underived nouns: No lexical tones required

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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.

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...

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 ...

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...

The Mental Representation of Polysemy across Word Classes

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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

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

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

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

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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.

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)

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.…

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

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

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...

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

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

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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.

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

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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.

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.

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.

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…

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,.

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 ...

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.

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 ...

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

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.

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.

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

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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%).

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.

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.

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

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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.

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...

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 ...

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…

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,…

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.

Dissociable neural representations of grammatical gender in Broca's area investigated by the combination of satiation and TMS.

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Cattaneo, Zaira; Devlin, Joseph T; Vecchi, Tomaso; Silvanto, Juha

2009-08-15

Along with meaning and form, words can be described on the basis of their grammatical properties. Grammatical gender is often used to investigate the latter as it is a grammatical property that is independent of meaning. The left inferior frontal gyrus (IFG) has been implicated in the encoding of grammatical gender, but its causal role in this process in neurologically normal observers has not been demonstrated. Here we combined verbal satiation with transcranial magnetic stimulation (TMS) to demonstrate that subpopulations of neurons within Broca's area respond preferentially to different classes of grammatical gender. Subjects were asked to classify Italian nouns into living and nonliving categories; half of these words were of masculine and the other half of feminine grammatical gender. Prior to each test block, a satiation paradigm (a phenomenon in which verbal repetition of a category name leads to a reduced access to that category) was used to modulate the initial state of the representations of either masculine or feminine noun categories. In the No TMS condition, subjects were slower in responding to exemplars to the satiated category relative to exemplars of the nonsatiated category, implying that the neural representations for different classes of grammatical gender are partly dissociable. The application of TMS over Broca's area removed the behavioral impact of verbal (grammatical) satiation, demonstrating the causal role of this region in the encoding of grammatical gender. These results show that the neural representations for different cases of a grammatical property within Broca's area are dissociable.

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 ...

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

Supervised Filter Learning for Representation Based Face Recognition.

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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.

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

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.

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.

Grammatical categories in the brain: the role of morphological structure.

Science.gov (United States)

Longe, O; Randall, B; Stamatakis, E A; Tyler, L K

2007-08-01

The current study addresses the controversial issue of how different grammatical categories are neurally processed. Several lesion-deficit studies suggest that distinct neural substrates underlie the representation of nouns and verbs, with verb deficits associated with damage to left inferior frontal gyrus (LIFG) and noun deficits with damage to left temporal cortex. However, this view is not universally shared by neuropsychological and neuroimaging studies. We have suggested that these inconsistencies may reflect interactions between the morphological structure of nouns and verbs and the processing implications of this, rather than differences in their neural representations (Tyler et al. 2004). We tested this hypothesis using event-related functional magnetic resonance imaging, to scan subjects performing a valence judgment on unambiguous nouns and verbs, presented as stems ('snail, hear') and inflected forms ('snails, hears'). We predicted that activations for noun and verb stems would not differ, whereas inflected verbs would generate more activation in left frontotemporal areas than inflected nouns. Our findings supported this hypothesis, with greater activation of this network for inflected verbs compared with inflected nouns. These results support the claim that form class is not a first-order organizing principle underlying the representation of words but rather interacts with the processes that operate over lexical representations.

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.

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…

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…

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)

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…

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.

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.

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.

Human action recognition using trajectory-based representation

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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.

Self-organising Logic of Structures as a Basis for a Dependency-based Dynamic Semantics Model

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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.

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....

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.

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

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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.

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...

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, ...

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.

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 ...

Integrating Globality and Locality for Robust Representation Based Classification

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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.

Semantic markup of nouns and adjectives for the Electronic corpus of texts in Tuvan language

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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.

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!’)....

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

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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…

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

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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…

Neural Representation. A Survey-Based Analysis of the Notion

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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.

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.

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

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

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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.

Les oasis de l'Oued Noun : dégradation du milieu naturel et perspectives de développement

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EL MAHJOUB CHMOURK

2011-08-01

Full Text Available The oases of Oued Noun: degradation of the natural environment and perspectives of development. An oasis is considered as a vital space and a fundamental natural resource in the Oued Noun area. Irrigation water scarcity, desertification, terminal illnesses of different civilizations, space division and tininess of farms are all natural and economic constraints providing the oasis area from growing and developing. Officials have to be aware of those constraints and they need to urgently recommend solutions in the process of updating the local territory and in its potentialities valorisation.

Use of nouns and verbs in the oral narrative of individuals with hearing impairment and normal hearing between 5 and 11 years of age

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Erica Endo Amemiya

Full Text Available CONTEXT AND OBJECTIVE: Nouns and verbs indicate actions in oral communication. However, hearing impairment can compromise the acquisition of oral language to such an extent that appropriate use of these can be challenging. The objective of this study was to compare the use of nouns and verbs in the oral narrative of hearing-impaired and hearing children. DESIGN AND SETTING: Analytical cross-sectional study at the Department of Speech-Language and Hearing Sciences, Universidade Federal de São Paulo. METHODS: Twenty-one children with moderate to profound bilateral neurosensory hearing impairment and twenty-one with normal hearing (controls were matched according to sex, school year and school type. A board showing pictures was presented to each child, to elicit a narrative and measure their performance in producing nouns and verbs. RESULTS: Twenty-two (52.4% of the subjects were males. The mean age was 8 years (standard deviation, SD = 1.5. Comparing averages between the groups of boys and girls, we did not find any significant difference in their use of nouns, but among verbs, there was a significant difference regarding use of the imperative (P = 0.041: more frequent among boys (mean = 2.91. There was no significant difference in the use of nouns and verbs between deaf children and hearers, in relation to school type. Regarding use of the indicative, there was a nearly significant trend (P = 0.058. CONCLUSION: Among oralized hearing-impaired children who underwent speech therapy, their performance regarding verbs and noun use was similar to that of their hearing counterparts.

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

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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…

How are 'Barack Obama' and 'President Elect' differentially stored in the brain? An ERP investigation on the processing of proper and common noun pairs.

Science.gov (United States)

Proverbio, Alice Mado; Mariani, Serena; Zani, Alberto; Adorni, Roberta

2009-09-23

One of the most debated issues in the cognitive neuroscience of language is whether distinct semantic domains are differentially represented in the brain. Clinical studies described several anomic dissociations with no clear neuroanatomical correlate. Neuroimaging studies have shown that memory retrieval is more demanding for proper than common nouns in that the former are purely arbitrary referential expressions. In this study a semantic relatedness paradigm was devised to investigate neural processing of proper and common nouns. 780 words (arranged in pairs of Italian nouns/adjectives and the first/last names of well known persons) were presented. Half pairs were semantically related ("Woody Allen" or "social security"), while the others were not ("Sigmund Parodi" or "judicial cream"). All items were balanced for length, frequency, familiarity and semantic relatedness. Participants were to decide about the semantic relatedness of the two items in a pair. RTs and N400 data suggest that the task was more demanding for common nouns. The LORETA neural generators for the related-unrelated contrast (for proper names) included the left fusiform gyrus, right medial temporal gyrus, limbic and parahippocampal regions, inferior parietal and inferior frontal areas, which are thought to be involved in the conjoined processing a familiar face with the relevant episodic information. Person name was more emotional and sensory vivid than common noun semantic access. When memory retrieval is not required, proper name access (conspecifics knowledge) is not more demanding. The neural generators of N400 to unrelated items (unknown persons and things) did not differ as a function of lexical class, thus suggesting that proper and common nouns are not treated differently as belonging to different grammatical classes.

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

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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)…

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

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

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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.

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

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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.

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

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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.

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

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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.

Hierarchical levels of representation in language prediction: The influence of first language acquisition in highly proficient bilinguals.

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Molinaro, Nicola; Giannelli, Francesco; Caffarra, Sendy; Martin, Clara

2017-07-01

Language comprehension is largely supported by predictive mechanisms that account for the ease and speed with which communication unfolds. Both native and proficient non-native speakers can efficiently handle contextual cues to generate reliable linguistic expectations. However, the link between the variability of the linguistic background of the speaker and the hierarchical format of the representations predicted is still not clear. We here investigate whether native language exposure to typologically highly diverse languages (Spanish and Basque) affects the way early balanced bilingual speakers carry out language predictions. During Spanish sentence comprehension, participants developed predictions of words the form of which (noun ending) could be either diagnostic of grammatical gender values (transparent) or totally ambiguous (opaque). We measured electrophysiological prediction effects time-locked both to the target word and to its determiner, with the former being expected or unexpected. Event-related (N200-N400) and oscillatory activity in the low beta-band (15-17Hz) frequency channel showed that both Spanish and Basque natives optimally carry out lexical predictions independently of word transparency. Crucially, in contrast to Spanish natives, Basque natives displayed visual word form predictions for transparent words, in consistency with the relevance that noun endings (post-nominal suffixes) play in their native language. We conclude that early language exposure largely shapes prediction mechanisms, so that bilinguals reading in their second language rely on the distributional regularities that are highly relevant in their first language. More importantly, we show that individual linguistic experience hierarchically modulates the format of the predicted representation. Copyright © 2017 Elsevier B.V. All rights reserved.

Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

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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.

A Scandinavian Island in a Slavonic Linguistic Environment. The Dialect of Gammalsvenskby: Nouns (Paper 2

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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.

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...

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....

Inflection of modern Icelandic nouns, adjectives and adverbs

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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.

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...

A developmental analysis of generic nouns in Southern Peruvian Quechua.

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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.

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

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

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

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,

Between-language repetition priming in antonym generation: evidence that translation-equivalent adjectives have shared conceptual representations across languages.

Science.gov (United States)

Taylor, Randolph S; Francis, Wendy S

2017-03-01

Previous literature has demonstrated conceptual repetition priming across languages in bilinguals. This between-language priming effect is taken as evidence that translation equivalents have shared conceptual representations across languages. However, the vast majority of this research has been conducted using only concrete nouns as stimuli. The present experiment examined conceptual repetition priming within and between languages in adjectives, a part of speech not previously investigated in studies of bilingual conceptual representation. The participants were 100 Spanish-English bilinguals who had regular exposure to both languages. At encoding, participants performed a shallow processing task and a deep-processing task on English and Spanish adjectives. At test, they performed an antonym-generation task in English, in which the target responses were either adjectives presented at encoding or control adjectives not previously presented. The measure of priming was the response time advantage for producing repeated adjectives relative to control adjectives. Significant repetition priming was observed both within and between languages under deep, but not shallow, encoding conditions. The results indicate that the conceptual representations of adjective translation equivalents are shared across languages.

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

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…

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 ...

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

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.

How Are ‘Barack Obama’ and ‘President Elect’ Differentially Stored in the Brain? An ERP Investigation on the Processing of Proper and Common Noun Pairs

Science.gov (United States)

Proverbio, Alice Mado; Mariani, Serena; Zani, Alberto; Adorni, Roberta

2009-01-01

Background One of the most debated issues in the cognitive neuroscience of language is whether distinct semantic domains are differentially represented in the brain. Clinical studies described several anomic dissociations with no clear neuroanatomical correlate. Neuroimaging studies have shown that memory retrieval is more demanding for proper than common nouns in that the former are purely arbitrary referential expressions. In this study a semantic relatedness paradigm was devised to investigate neural processing of proper and common nouns. Methodology/Principal Findings 780 words (arranged in pairs of Italian nouns/adjectives and the first/last names of well known persons) were presented. Half pairs were semantically related (“Woody Allen” or “social security”), while the others were not (“Sigmund Parodi” or “judicial cream”). All items were balanced for length, frequency, familiarity and semantic relatedness. Participants were to decide about the semantic relatedness of the two items in a pair. RTs and N400 data suggest that the task was more demanding for common nouns. The LORETA neural generators for the related-unrelated contrast (for proper names) included the left fusiform gyrus, right medial temporal gyrus, limbic and parahippocampal regions, inferior parietal and inferior frontal areas, which are thought to be involved in the conjoined processing a familiar face with the relevant episodic information. Person name was more emotional and sensory vivid than common noun semantic access. Conclusions/Significance When memory retrieval is not required, proper name access (conspecifics knowledge) is not more demanding. The neural generators of N400 to unrelated items (unknown persons and things) did not differ as a function of lexical class, thus suggesting that proper and common nouns are not treated differently as belonging to different grammatical classes. PMID:19774070

PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

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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.

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…

Modulation of the semantic system by word imageability.

Science.gov (United States)

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

2005-08-01

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

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...

3D ear identification based on sparse representation.

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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.

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

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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.

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.

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.

Gauging the impact of gender grammaticization in different languages: Application of a linguistic-visual paradigm

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Sayaka eSato

2016-02-01

Full Text Available Employing a linguistic-visual paradigm, we investigated whether the grammaticization of gender information impacts readers’ gender representations. French and German were taken as comparative languages, taking into account the male gender bias associated to both languages, as well as the comparative gender biases associated to their plural determiners (French: les [generic] vs. German: die [morphologically feminine]. Bilingual speakers of French and German had to judge whether a pair of facial images representing two men or a man and a woman could represent a gender stereotypical role noun prime (e.g., nurses. The prime was presented in the masculine plural form with or without a plural determiner. Results indicated that the overt grammaticization of the male gender in the masculine form dominated the representation of the role nouns (though interpretable as generic. However, the effect of the determiner was not found, indicating that only gender information associated to a human reference role noun had impacted readers’ representations. The results, discussed in the framework of the thinking-for-speaking hypothesis, demonstrated that linguistic-visual paradigms are well-suited to gauge the impact of both stereotype information and grammaticization when processing role nouns.Keywords: gender representation, gender stereotypes, grammatical gender, generic masculine, thinking-for-speaking hypothesis, bilingualism

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...

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

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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

Conformal-Based Surface Morphing and Multi-Scale Representation

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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.

Extracting Date/Time Expressions in Super-Function Based Japanese-English Machine Translation

Science.gov (United States)

Sasayama, Manabu; Kuroiwa, Shingo; Ren, Fuji

Super-Function Based Machine Translation(SFBMT) which is a type of Example-Based Machine Translation has a feature which makes it possible to expand the coverage of examples by changing nouns into variables, however, there were problems extracting entire date/time expressions containing parts-of-speech other than nouns, because only nouns/numbers were changed into variables. We describe a method for extracting date/time expressions for SFBMT. SFBMT uses noun determination rules to extract nouns and a bilingual dictionary to obtain correspondence of the extracted nouns between the source and the target languages. In this method, we add a rule to extract date/time expressions and then extract date/time expressions from a Japanese-English bilingual corpus. The evaluation results shows that the precision of this method for Japanese sentences is 96.7%, with a recall of 98.2% and the precision for English sentences is 94.7%, with a recall of 92.7%.

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

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…

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),…

Order-based representation in random networks of cortical neurons.

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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.

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.

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

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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

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...

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...

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...

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.

COGNITIVE LEARNING STRATEGIES OF NON-ENGLISH DEPARTMENT STUDENTS ON NOUN STRUCTURE

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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.

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.

Gauging the Impact of Gender Grammaticization in Different Languages: Application of a Linguistic-Visual Paradigm

Science.gov (United States)

Sato, Sayaka; Gygax, Pascal M.; Gabriel, Ute

2016-01-01

Employing a linguistic-visual paradigm, we investigated whether the grammaticization of gender information impacts readers’ gender representations. French and German were taken as comparative languages, taking into account the male gender bias associated to both languages, as well as the comparative gender biases associated to their plural determiners (French: les [generic] vs. German: die [morphologically feminine]). Bilingual speakers of French and German had to judge whether a pair of facial images representing two men or a man and a woman could represent a gender stereotypical role noun prime (e.g., nurses). The prime was presented in the masculine plural form with or without a plural determiner. Results indicated that the overt grammaticization of the male gender in the masculine form dominated the representation of the role nouns (though interpretable as generic). However, the effect of the determiner was not found, indicating that only gender information associated to a human reference role noun had impacted readers’ representations. The results, discussed in the framework of the thinking-for-speaking hypothesis, demonstrated that linguistic-visual paradigms are well-suited to gauge the impact of both stereotype information and grammaticization when processing role nouns. PMID:26941663

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.

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.

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.

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.

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.

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...

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

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.

Converting Biomolecular Modelling Data Based on an XML Representation

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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.

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.

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...

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

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

The processing of actions and action-words in amyotrophic lateral sclerosis patients.

Science.gov (United States)

Papeo, Liuba; Cecchetto, Cinzia; Mazzon, Giulia; Granello, Giulia; Cattaruzza, Tatiana; Verriello, Lorenzo; Eleopra, Roberto; Rumiati, Raffaella I

2015-03-01

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with prime consequences on the motor function and concomitant cognitive changes, most frequently in the domain of executive functions. Moreover, poorer performance with action-verbs versus object-nouns has been reported in ALS patients, raising the hypothesis that the motor dysfunction deteriorates the semantic representation of actions. Using action-verbs and manipulable-object nouns sharing semantic relationship with the same motor representations, the verb-noun difference was assessed in a group of 21 ALS-patients with severely impaired motor behavior, and compared with a normal sample's performance. ALS-group performed better on nouns than verbs, both in production (action and object naming) and comprehension (word-picture matching). This observation implies that the interpretation of the verb-noun difference in ALS cannot be accounted by the relatedness of verbs to motor representations, but has to consider the role of other semantic and/or morpho-phonological dimensions that distinctively define the two grammatical classes. Moreover, this difference in the ALS-group was not greater than the noun-verb difference in the normal sample. The mental representation of actions also involves an executive-control component to organize, in logical/temporal order, the individual motor events (or sub-goals) that form a purposeful action. We assessed this ability with action sequencing tasks, requiring participants to re-construct a purposeful action from the scrambled presentation of its constitutive motor events, shown in the form of photographs or short sentences. In those tasks, ALS-group's performance was significantly poorer than controls'. Thus, the executive dysfunction manifested in the sequencing deficit -but not the selective verb deficit- appears as a consistent feature of the cognitive profile associated with ALS. We suggest that ALS can offer a valuable model to study the relationship between

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

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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.

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.

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.

Research Notes ~ Combating HIV/AIDS Epidemic in Nigeria: Responses from National Open University of Nigeria (NOUN

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Terhemba Nom Ambe-Uva

2007-11-01

Full Text Available Universities have come under serious attack because of their lackluster response to HIV/AIDS. This article examines the response of National Open University of Nigeria (NOUN and its strategic responses in combating HIV/AIDS epidemic. This is achieved by examining NOUN’s basic structures that position the University to respond to the epidemic; and second, by assessing HIV/AIDS strategies and policy framework the University has put in place. An interpretative epistemological stance was used for this study, and a qualitative research involving focus group discussion (FGD and analysis of secondary data was carried out. Results showed that NOUN has identified the impact the epidemic has on the university, although it has yet to institutionalize an HIV/AIDS policy. NOUN’s Draft Service Charter, however, has identified the fight against HIV/AIDS as a core mandate of the University, and the introduction of HIV/AIDS certification programs can be viewed as proactive policies in response to the epidemic. Results of this study are discussed in terms of their relevance to future research and the impact such policy frameworks may have on combating the epidemic, both within the University and the wider community.

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...

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.

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.

Mixing positive and negative valence: Affective-semantic integration of bivalent words.

Science.gov (United States)

Kuhlmann, Michael; Hofmann, Markus J; Briesemeister, Benny B; Jacobs, Arthur M

2016-08-05

Single words have affective and aesthetic properties that influence their processing. Here we investigated the processing of a special case of word stimuli that are extremely difficult to evaluate, bivalent noun-noun-compounds (NNCs), i.e. novel words that mix a positive and negative noun, e.g. 'Bombensex' (bomb-sex). In a functional magnetic resonance imaging (fMRI) experiment we compared their processing with easier-to-evaluate non-bivalent NNCs in a valence decision task (VDT). Bivalent NNCs produced longer reaction times and elicited greater activation in the left inferior frontal gyrus (LIFG) than non-bivalent words, especially in contrast to words of negative valence. We attribute this effect to a LIFG-grounded process of semantic integration that requires greater effort for processing converse information, supporting the notion of a valence representation based on associations in semantic networks.

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…

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

Science.gov (United States)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Jianzhong Wang

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

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.

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

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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.

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.

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

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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.

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...

Towards the study of color naming in Portuguese: structure and meaning of constructed nouns and adjectives

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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.

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.

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.

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.

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

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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.

Mothers' Talk to Children with Down Syndrome, Language Impairment, or Typical Development about Familiar and Unfamiliar Nouns and Verbs

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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…

A SUFFIX USED TO FORM COLLECTIVE/FAMILY NOUN IN THE SOME DIALECTS OF TURKISH: +ēNi/+îNi / BAZI TÜRKIYE TÜRKÇESI AĞIZLARINDA TOPLULUK/AILE ADI YAPAN BIR EK: +ēNi / +îNi

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Dr. Serpil ERSÖZ

2008-08-01

Full Text Available There are two suffixes used to form collective/family nouns: +giland +lAr. These suffixes which also indicates plurality in nouns are used inalmost all dialects of Turkish. This essay’s topic is suffix +ēNi+/+îNi whichis used to form collective/family nouns as +gil and +lAr in some dialects ofTurkish. In this essay, we extrapolate that the form of the suffix +îN(i withclose unrounded vowel is used in dialect of immigrants whereas the form ofthe suffix +ēNi with open unrounded vowel is used in dialects of noimmigrants, of yoruk and some Oguz tribes.

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

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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.

Noun and verb knowledge in monolingual preschool children across 17 languages: Data from Cross-linguistic Lexical Tasks (LITMUS-CLT).

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Haman, Ewa; Łuniewska, Magdalena; Hansen, Pernille; Simonsen, Hanne Gram; Chiat, Shula; Bjekić, Jovana; Blažienė, Agnė; Chyl, Katarzyna; Dabašinskienė, Ineta; Engel de Abreu, Pascale; Gagarina, Natalia; Gavarró, Anna; Håkansson, Gisela; Harel, Efrat; Holm, Elisabeth; Kapalková, Svetlana; Kunnari, Sari; Levorato, Chiara; Lindgren, Josefin; Mieszkowska, Karolina; Montes Salarich, Laia; Potgieter, Anneke; Ribu, Ingeborg; Ringblom, Natalia; Rinker, Tanja; Roch, Maja; Slančová, Daniela; Southwood, Frenette; Tedeschi, Roberta; Tuncer, Aylin Müge; Ünal-Logacev, Özlem; Vuksanović, Jasmina; Armon-Lotem, Sharon

2017-01-01

This article investigates the cross-linguistic comparability of the newly developed lexical assessment tool Cross-linguistic Lexical Tasks (LITMUS-CLT). LITMUS-CLT is a part the Language Impairment Testing in Multilingual Settings (LITMUS) battery (Armon-Lotem, de Jong & Meir, 2015). Here we analyse results on receptive and expressive word knowledge tasks for nouns and verbs across 17 languages from eight different language families: Baltic (Lithuanian), Bantu (isiXhosa), Finnic (Finnish), Germanic (Afrikaans, British English, South African English, German, Luxembourgish, Norwegian, Swedish), Romance (Catalan, Italian), Semitic (Hebrew), Slavic (Polish, Serbian, Slovak) and Turkic (Turkish). The participants were 639 monolingual children aged 3;0-6;11 living in 15 different countries. Differences in vocabulary size were small between 16 of the languages; but isiXhosa-speaking children knew significantly fewer words than speakers of the other languages. There was a robust effect of word class: accuracy was higher for nouns than verbs. Furthermore, comprehension was more advanced than production. Results are discussed in the context of cross-linguistic comparisons of lexical development in monolingual and bilingual populations.

Features based approach for indexation and representation of unstructured Arabic documents

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

The role of representation in experience-based choice

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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.

Distinguishing Representations as Origin and Representations as Input: Roles for Individual Cells

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Jonathan C.W. Edwards

2016-09-01

Full Text Available It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with meaning, interpretation or significance (semantic content. It is suggested here that this problem may arise partly from the conflation of two vernacular senses of representation: representation-as-origin and representation-as-input. The flash of a neon sign may in one sense represent a popular drink, but to function as representation it must provide an input to a ‘consumer’ in the street. The arguments presented draw on two principles – the neuron doctrine and the need for a venue for ‘presentation’ or ‘reception’ of a representation at a specified site, consistent with the locality principle. It is also argued that domains of representation cannot be defined by signal traffic, since they can be expected to include ‘null’ elements based on non-firing cells. In this analysis, mental representations-as-origin are distributed patterns of cell firing. Each firing cell is given semantic value in its own right - some form of atomic propositional significance – since different axonal branches may contribute to integration with different populations of signals at different downstream sites. Representations-as-input are patterns of local co-arrival of signals in the form of synaptic potentials in dendrites. Meaning then draws on the relationships between active and null inputs, forming ‘scenarios’ comprising a molecular combination of ‘premises’ from which a new output with atomic propositional significance is generated. In both types of representation, meaning, interpretation or significance pivots on events in an individual cell. (This analysis only applies to ‘occurrent’ representations based on current neural activity. The concept of representations-as-input emphasises the need for a ‘consumer’ of a representation and the dependence of meaning on the co-relationships involved in an

Video rate morphological processor based on a redundant number representation

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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.

Sparse representation based image interpolation with nonlocal autoregressive modeling.

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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.

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.

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

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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.

The Morphosyntactic Structure of the Noun and Verb Phrases in Dholuo/Kiswahili Code Switching

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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

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

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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.

Facial expression recognition based on weber local descriptor and sparse representation

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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.

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

Cognitive categories and noun classification. Romance neuter: from [passivity] to [indifference

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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

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...

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.

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

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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.

الاسماء المربكة في اللغة الانكليزية: تحليل الاخطاء Confusing Nouns in English: An Error Analysis

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Sabeeha Hamza Dehham Al- Jobouri أ.م. صبيحة حمزة دحام

2016-10-01

Full Text Available The present study is an attempt to identify the errors made by Iraqi EFL learners in the Department of English / College of Basic Education, University of Babylon in using confusing nouns .The Classification of English Nouns is as diverse and varied as English Grammar. The researcher in the paper under review has sought to examine in details how nouns are a source of confusion for EFL learners. This study aims at (1 investigating the difficulties faced Iraqi EFL university learners in using confusing nouns and (2 identifying the errors made by EFL learners in using confusing nouns . To achieve the two goals mentioned above, the study hypothesizes that Iraqi EFL University Learners committed errors in using confusing nouns because of their intralingual transference. The Hypothesis has been verified through adopted a diagnostic test of two questions .The test has been applied to a sample of 100 Iraqi EFL university learners at their fourth year from Department of English, College of Basic Education, University of Babylon during the academic year 2014-2015. Errors have been pointed and results have been analyzed statistically. The analysis gives the following results: (1 EFL University learners face difficulties in recognizing and producing confusing nouns . This is indicated by their low performance in the test as the, rate. of their correct responses (782, 39.1% is lower significantly than that of their incorrect ones (1218, 60.9 %. (2 The subjects' performance in the test has also revealed that EFL university learners encounter more difficulties in using confusing nouns at the production level than at the recognition one. This is due to the fact that the total number and the percentage of the correct responses at the production level (349, 34.9 % is lower than the total the total number and the percentage of the correct responses at the recognition level which are equal (433, 43.3 % and (3 Some of errors are due to the student's lack knowledge

Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

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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.

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

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...

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

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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.

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.

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.

Inter-subject variability modulates phonological advance planning in the production of adjective-noun phrases.

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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.

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.

AHP 1:A RESPONSE TO WAYS AND THE SYNTAX OF NOUN PHRASES IN QĪNGHĂI CHINESE DIALECTS

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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.

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

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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.

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

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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.

Agreement Attraction in Comprehension: Representations and Processes

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Wagers, Matthew W.; Lau, Ellen F.; Phillips, Colin

2009-01-01

Much work has demonstrated so-called attraction errors in the production of subject-verb agreement (e.g., "The key to the cabinets are on the table", [Bock, J. K., & Miller, C. A. (1991). "Broken agreement." "Cognitive Psychology, 23", 45-93]), in which a verb erroneously agrees with an intervening noun. Six self-paced reading experiments examined…

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

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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.

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

Great expectations: Specific lexical anticipation influences the processing of spoken language

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Nieuwland Mante S

2007-10-01

Full Text Available Abstract Background Recently several studies have shown that people use contextual information to make predictions about the rest of the sentence or story as the text unfolds. Using event related potentials (ERPs we tested whether these on-line predictions are based on a message-level representation of the discourse or on simple automatic activation by individual words. Subjects heard short stories that were highly constraining for one specific noun, or stories that were not specifically predictive but contained the same prime words as the predictive stories. To test whether listeners make specific predictions critical nouns were preceded by an adjective that was inflected according to, or in contrast with, the gender of the expected noun. Results When the message of the preceding discourse was predictive, adjectives with an unexpected gender inflection evoked a negative deflection over right-frontal electrodes between 300 and 600 ms. This effect was not present in the prime control context, indicating that the prediction mismatch does not hinge on word-based priming but is based on the actual message of the discourse. Conclusion When listening to a constraining discourse people rapidly make very specific predictions about the remainder of the story, as the story unfolds. These predictions are not simply based on word-based automatic activation, but take into account the actual message of the discourse.

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).

A CONTRASTIVE ANALYSIS OF ARABIC AND ENGLISH NOUN PLURAL MARKERS

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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

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

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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.

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

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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.

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.

Mental Representation and Motor Imagery Training

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Thomas eSchack

2014-05-01

Full Text Available Research in sports, dance and rehabilitation has shown that Basic Action Concepts (BACs are fundamental building blocks of mental action representations. BACs are based on chunked body postures related to common functions for realizing action goals. In this paper, we outline issues in research methodology and an experimental method, SDA-M (structural dimensional analysis of mental representation, to assess action-relevant representational structures that reflect the organization of BACs. The SDA-M reveals a strong relationship between cognitive representation and performance if complex actions are performed. We show how the SDA-M can improve motor imagery training and how it contributes to our understanding of coaching processes. The SDA-M capitalizes on the objective measurement of individual mental movement representations before training and the integration of these results into the motor imagery training. Such motor imagery training based on mental representations has been applied successfully in professional sports such as golf, volleyball, gymnastics, windsurfing, and recently in the rehabilitation of patients who have suffered a stroke.

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...

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...

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.

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

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.

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

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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.

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

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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.

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.

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

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.

Representations for Supporting Students' Context Awareness

DEFF Research Database (Denmark)

Demetriadis, Stavros N.; Papadopoulos, Pantelis M.

2005-01-01

The context of the specific situation where knowledge is applied affects significantly the problem solving process by forcing people to negotiate and reconsider the priorities of their mental representations and problem solving operators, in relation to this process. In this work we argue...... that students’ context awareness can significantly be enhanced by the use of appropriate external representations which guide them to activate context inducing cognitive processes. By embedding such representations in a case based learning environment we expect to guide students’ processing of the rich...... in contextual information material, in a way that improves both their context awareness and metacontextual competence. After presenting a context model, we discuss the design of such representations based on this model and explain why we expect that their use in a learning situation would enhance context...

Exploring the Structure of Spatial Representations

Science.gov (United States)

Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

2016-01-01

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

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.

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.

(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...

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

Grammatical distinctions in the left frontal cortex.

Science.gov (United States)

Shapiro, K A; Pascual-Leone, A; Mottaghy, F M; Gangitano, M; Caramazza, A

2001-08-15

Selective deficits in producing verbs relative to nouns in speech are well documented in neuropsychology and have been associated with left hemisphere frontal cortical lesions resulting from stroke and other neurological disorders. The basis for these impairments is unresolved: Do they arise because of differences in the way grammatical categories of words are organized in the brain, or because of differences in the neural representation of actions and objects? We used repetitive transcranial magnetic stimulation (rTMS) to suppress the excitability of a portion of left prefrontal cortex and to assess its role in producing nouns and verbs. In one experiment subjects generated real words; in a second, they produced pseudowords as nouns or verbs. In both experiments, response latencies increased for verbs but were unaffected for nouns following rTMS. These results demonstrate that grammatical categories have a neuroanatomical basis and that the left prefrontal cortex is selectively engaged in processing verbs as grammatical objects.

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).

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.

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...

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.

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…

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.

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.

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.

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…

An XML Representation for Crew Procedures

Science.gov (United States)

Simpson, Richard C.

2005-01-01

NASA ensures safe operation of complex systems through the use of formally-documented procedures, which encode the operational knowledge of the system as derived from system experts. Crew members use procedure documentation on the ground for training purposes and on-board space shuttle and space station to guide their activities. Investigators at JSC are developing a new representation for procedures that is content-based (as opposed to display-based). Instead of specifying how a procedure should look on the printed page, the content-based representation will identify the components of a procedure and (more importantly) how the components are related (e.g., how the activities within a procedure are sequenced; what resources need to be available for each activity). This approach will allow different sets of rules to be created for displaying procedures on a computer screen, on a hand-held personal digital assistant (PDA), verbally, or on a printed page, and will also allow intelligent reasoning processes to automatically interpret and use procedure definitions. During his NASA fellowship, Dr. Simpson examined how various industries represent procedures (also called business processes or workflows), in areas such as manufacturing, accounting, shipping, or customer service. A useful method for designing and evaluating workflow representation languages is by determining their ability to encode various workflow patterns, which depict abstract relationships between the components of a procedure removed from the context of a specific procedure or industry. Investigators have used this type of analysis to evaluate how well-suited existing workflow representation languages are for various industries based on the workflow patterns that commonly arise across industry-specific procedures. Based on this type of analysis, it is already clear that existing workflow representations capture discrete flow of control (i.e., when one activity should start and stop based on when other

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.

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

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.

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.

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.

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.

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

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.

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.

(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 ...

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%.

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

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.

Knowledge Representation Using Multilevel Flow Model in Expert System

International Nuclear Information System (INIS)

Wang, Wenlin; Yang, Ming

2015-01-01

As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available

Knowledge Representation Using Multilevel Flow Model in Expert System

Energy Technology Data Exchange (ETDEWEB)

Wang, Wenlin; Yang, Ming [Harbin Engineering University, Harbin (China)

2015-05-15

As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available.

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.

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.

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.

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.

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.

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

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...

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…

Spatially variant morphological restoration and skeleton representation.

Science.gov (United States)

Bouaynaya, Nidhal; Charif-Chefchaouni, Mohammed; Schonfeld, Dan

2006-11-01

The theory of spatially variant (SV) mathematical morphology is used to extend and analyze two important image processing applications: morphological image restoration and skeleton representation of binary images. For morphological image restoration, we propose the SV alternating sequential filters and SV median filters. We establish the relation of SV median filters to the basic SV morphological operators (i.e., SV erosions and SV dilations). For skeleton representation, we present a general framework for the SV morphological skeleton representation of binary images. We study the properties of the SV morphological skeleton representation and derive conditions for its invertibility. We also develop an algorithm for the implementation of the SV morphological skeleton representation of binary images. The latter algorithm is based on the optimal construction of the SV structuring element mapping designed to minimize the cardinality of the SV morphological skeleton representation. Experimental results show the dramatic improvement in the performance of the SV morphological restoration and SV morphological skeleton representation algorithms in comparison to their translation-invariant counterparts.

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...

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...

Conceptual plural information is used to guide early parsing decisions: Evidence from garden-path sentences with reciprocal verbs.

Science.gov (United States)

Patson, Nikole D; Ferreira, Fernanda

2009-05-01

In three eyetracking studies, we investigated the role of conceptual plurality in initial parsing decisions in temporarily ambiguous sentences with reciprocal verbs (e.g., While the lovers kissed the baby played alone). We varied the subject of the first clause using three types of plural noun phrases: conjoined noun phrases (the bride and the groom), plural definite descriptions (the lovers), and numerically quantified noun phrases (the two lovers). We found no evidence for garden-path effects when the subject was conjoined (Ferreira & McClure, 1997), but traditional garden-path effects were found with the other plural noun phrases. In addition, we tested plural anaphors that had a plural antecedent present in the discourse. We found that when the antecedent was conjoined, garden-path effects were absent compared to cases in which the antecedent was a plural definite description. Our results indicate that the parser is sensitive to the conceptual representation of a plural constituent. In particular, it appears that a Complex Reference Object (Moxey et al., 2004) automatically activates a reciprocal reading of a reciprocal verb.

Robust Face Recognition Via Gabor Feature and Sparse Representation

Directory of Open Access Journals (Sweden)

Hao Yu-Juan

2016-01-01

Full Text Available Sparse representation based on compressed sensing theory has been widely used in the field of face recognition, and has achieved good recognition results. but the face feature extraction based on sparse representation is too simple, and the sparse coefficient is not sparse. In this paper, we improve the classification algorithm based on the fusion of sparse representation and Gabor feature, and then improved algorithm for Gabor feature which overcomes the problem of large dimension of the vector dimension, reduces the computation and storage cost, and enhances the robustness of the algorithm to the changes of the environment.The classification efficiency of sparse representation is determined by the collaborative representation,we simplify the sparse constraint based on L1 norm to the least square constraint, which makes the sparse coefficients both positive and reduce the complexity of the algorithm. Experimental results show that the proposed method is robust to illumination, facial expression and pose variations of face recognition, and the recognition rate of the algorithm is improved.

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.

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....

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.

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

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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.

AudioPairBank: Towards A Large-Scale Tag-Pair-Based Audio Content Analysis

OpenAIRE

Sager, Sebastian; Elizalde, Benjamin; Borth, Damian; Schulze, Christian; Raj, Bhiksha; Lane, Ian

2016-01-01

Recently, sound recognition has been used to identify sounds, such as car and river. However, sounds have nuances that may be better described by adjective-noun pairs such as slow car, and verb-noun pairs such as flying insects, which are under explored. Therefore, in this work we investigate the relation between audio content and both adjective-noun pairs and verb-noun pairs. Due to the lack of datasets with these kinds of annotations, we collected and processed the AudioPairBank corpus cons...

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

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.

Inequivalent coherent state representations in group field theory

Science.gov (United States)

Kegeles, Alexander; Oriti, Daniele; Tomlin, Casey

2018-06-01

In this paper we propose an algebraic formulation of group field theory and consider non-Fock representations based on coherent states. We show that we can construct representations with an infinite number of degrees of freedom on compact manifolds. We also show that these representations break translation symmetry. Since such representations can be regarded as quantum gravitational systems with an infinite number of fundamental pre-geometric building blocks, they may be more suitable for the description of effective geometrical phases of the theory.

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.

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.

Strong systematicity through sensorimotor conceptual grounding: an unsupervised, developmental approach to connectionist sentence processing

Science.gov (United States)

Jansen, Peter A.; Watter, Scott

2012-03-01

Connectionist language modelling typically has difficulty with syntactic systematicity, or the ability to generalise language learning to untrained sentences. This work develops an unsupervised connectionist model of infant grammar learning. Following the semantic boostrapping hypothesis, the network distils word category using a developmentally plausible infant-scale database of grounded sensorimotor conceptual representations, as well as a biologically plausible semantic co-occurrence activation function. The network then uses this knowledge to acquire an early benchmark clausal grammar using correlational learning, and further acquires separate conceptual and grammatical category representations. The network displays strongly systematic behaviour indicative of the general acquisition of the combinatorial systematicity present in the grounded infant-scale language stream, outperforms previous contemporary models that contain primarily noun and verb word categories, and successfully generalises broadly to novel untrained sensorimotor grounded sentences composed of unfamiliar nouns and verbs. Limitations as well as implications to later grammar learning are discussed.

Preservation of memory-based automaticity in reading for older adults.

Science.gov (United States)

Rawson, Katherine A; Touron, Dayna R

2015-12-01

Concerning age-related effects on cognitive skill acquisition, the modal finding is that older adults do not benefit from practice to the same extent as younger adults in tasks that afford a shift from slower algorithmic processing to faster memory-based processing. In contrast, Rawson and Touron (2009) demonstrated a relatively rapid shift to memory-based processing in the context of a reading task. The current research extended beyond this initial study to provide more definitive evidence for relative preservation of memory-based automaticity in reading tasks for older adults. Younger and older adults read short stories containing unfamiliar noun phrases (e.g., skunk mud) followed by disambiguating information indicating the combination's meaning (either the normatively dominant meaning or an alternative subordinate meaning). Stories were repeated across practice blocks, and then the noun phrases were presented in novel sentence frames in a transfer task. Both age groups shifted from computation to retrieval after relatively few practice trials (as evidenced by convergence of reading times for dominant and subordinate items). Most important, both age groups showed strong evidence for memory-based processing of the noun phrases in the transfer task. In contrast, older adults showed minimal shifting to retrieval in an alphabet arithmetic task, indicating that the preservation of memory-based automaticity in reading was task-specific. Discussion focuses on important implications for theories of memory-based automaticity in general and for specific theoretical accounts of age effects on memory-based automaticity, as well as fruitful directions for future research. (c) 2015 APA, all rights reserved).

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...

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.

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).

Mental Representations Formed From Educational Website Formats

Energy Technology Data Exchange (ETDEWEB)

Elizabeth T. Cady; Kimberly R. Raddatz; Tuan Q. Tran; Bernardo de la Garza; Peter D. Elgin

2006-10-01

The increasing popularity of web-based distance education places high demand on distance educators to format web pages to facilitate learning. However, limited guidelines exist regarding appropriate writing styles for web-based distance education. This study investigated the effect of four different writing styles on reader’s mental representation of hypertext. Participants studied hypertext written in one of four web-writing styles (e.g., concise, scannable, objective, and combined) and were then administered a cued association task intended to measure their mental representations of the hypertext. It is hypothesized that the scannable and combined styles will bias readers to scan rather than elaborately read, which may result in less dense mental representations (as identified through Pathfinder analysis) relative to the objective and concise writing styles. Further, the use of more descriptors in the objective writing style will lead to better integration of ideas and more dense mental representations than the concise writing style.

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…

The semantic representation of prejudice and stereotypes.

Science.gov (United States)

Bhatia, Sudeep

2017-07-01

We use a theory of semantic representation to study prejudice and stereotyping. Particularly, we consider large datasets of newspaper articles published in the United States, and apply latent semantic analysis (LSA), a prominent model of human semantic memory, to these datasets to learn representations for common male and female, White, African American, and Latino names. LSA performs a singular value decomposition on word distribution statistics in order to recover word vector representations, and we find that our recovered representations display the types of biases observed in human participants using tasks such as the implicit association test. Importantly, these biases are strongest for vector representations with moderate dimensionality, and weaken or disappear for representations with very high or very low dimensionality. Moderate dimensional LSA models are also the best at learning race, ethnicity, and gender-based categories, suggesting that social category knowledge, acquired through dimensionality reduction on word distribution statistics, can facilitate prejudiced and stereotyped associations. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

Using noun phrases for navigating biomedical literature on Pubmed: how many updates are we losing track of?

Science.gov (United States)

Srikrishna, Devabhaktuni; Coram, Marc A

2011-01-01

Author-supplied citations are a fraction of the related literature for a paper. The "related citations" on PubMed is typically dozens or hundreds of results long, and does not offer hints why these results are related. Using noun phrases derived from the sentences of the paper, we show it is possible to more transparently navigate to PubMed updates through search terms that can associate a paper with its citations. The algorithm to generate these search terms involved automatically extracting noun phrases from the paper using natural language processing tools, and ranking them by the number of occurrences in the paper compared to the number of occurrences on the web. We define search queries having at least one instance of overlap between the author-supplied citations of the paper and the top 20 search results as citation validated (CV). When the overlapping citations were written by same authors as the paper itself, we define it as CV-S and different authors is defined as CV-D. For a systematic sample of 883 papers on PubMed Central, at least one of the search terms for 86% of the papers is CV-D versus 65% for the top 20 PubMed "related citations." We hypothesize these quantities computed for the 20 million papers on PubMed to differ within 5% of these percentages. Averaged across all 883 papers, 5 search terms are CV-D, and 10 search terms are CV-S, and 6 unique citations validate these searches. Potentially related literature uncovered by citation-validated searches (either CV-S or CV-D) are on the order of ten per paper--many more if the remaining searches that are not citation-validated are taken into account. The significance and relationship of each search result to the paper can only be vetted and explained by a researcher with knowledge of or interest in that paper.

How initial representations shape coupled learning processes

DEFF Research Database (Denmark)

Puranam, Phanish; Swamy, M.

2016-01-01

Coupled learning processes, in which specialists from different domains learn how to make interdependent choices among alternatives, are common in organizations. We explore the role played by initial representations held by the learners in coupled learning processes using a formal agent-based model....... We find that initial representations have important consequences for the success of the coupled learning process, particularly when communication is constrained and individual rates of learning are high. Under these conditions, initial representations that generate incorrect beliefs can outperform...... one that does not discriminate among alternatives, or even a mix of correct and incorrect representations among the learners. We draw implications for the design of coupled learning processes in organizations. © 2016 INFORMS....

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.

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.

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.

General regression and representation model for classification.

Directory of Open Access Journals (Sweden)

Jianjun Qian

Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.

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.

Analisando representações sociais através de elementos gramaticais: compondo representações sobre música Analyzing social representations with grammatical elements: composing representations about music

Directory of Open Access Journals (Sweden)

Anderson Scardua

2010-08-01

Full Text Available O objetivo deste trabalho foi o de apresentar uma forma de análise de representações sociais (RS baseada em elementos gramaticais. Descrevemos este método através de uma pesquisa feita sobre as RS da música entre músicos (N=57 e ouvintes (N=234 da cidade do Rio de Janeiro. Foram feitas perguntas sobre a definição de música e sobre a descrição dos gostos e desgostos para ouvir e produzir música. Foi feita uma análise de conteúdo gramatical/temática em que várias categorias foram descritas e agrupadas em três grupos de acordo com a prevalência dos elementos gramaticais: Descritivas/objetivas - baseadas em substantivos; Efeitos/usos - prevalência de verbos e expressões (e.g., "é para", "me faz"; e Retóricas - baseadas em advérbios e adjetivos. Essas categorias nos permitiram observar de forma mais específica os processos de objetivação (Descritivas, a ancoragem (Efeitos/usos e o elemento atitudinal (Retóricas. Foi feita também uma discussão sobre o processo de análise, suas implicações e limites.The aim of this study was to present a method of analysis for social representations (SR based on grammatical elements. This method was described through a research about SR of music among musicians (N=57 and listeners (N=234 from the city Rio de Janeiro. Questions were asked about the definition of music and the description of likes and dislikes regarding music production and consumption. Drawing on grammatical/thematic content analysis many categories were described and clustered in three groups according to the prevalence of grammatical elements: descriptive/objective - based on nouns; Effects/uses - prevalence of verbs and expressions (e.g. "it is to", "it makes me"; and Rhetorical - based on adverbs and adjectives. These categories allowed us to observe more specifically the processes of objectivation (Descriptive, and anchoring (Effects/uses, as well as attitudinal elements (Rhetorical. Further, the process of analysis

Anaphoric Reference to Instances, Instantiated and Non-Instantiated Categories: A Reading Time Study.

Science.gov (United States)

Garnham, Alan

1981-01-01

Experiments using memory paradigms have shown that general terms receive context-dependent encodings. This experiment investigates the encoding of category and instance nouns. The results indicate that representations set up during reading are the product of both the linguistic input and of general knowledge. (Author/KC)

Content-adaptive pyramid representation for 3D object classification

DEFF Research Database (Denmark)

Kounalakis, Tsampikos; Boulgouris, Nikolaos; Triantafyllidis, Georgios

2016-01-01

In this paper we introduce a novel representation for the classification of 3D images. Unlike most current approaches, our representation is not based on a fixed pyramid but adapts to image content and uses image regions instead of rectangular pyramid scales. Image characteristics, such as depth...... and color, are used for defining regions within images. Multiple region scales are formed in order to construct the proposed pyramid image representation. The proposed method achieves excellent results in comparison to conventional representations....

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.

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.

Analysis of graphic representations of activity theory in international journals

Directory of Open Access Journals (Sweden)

Marco André Mazzarotto

2016-05-01

Full Text Available Activity theory is a relevant framework for the Design field, and their graphic representations are cognitive artifacts that aid the understanding, use and communication of this theory. However, there is a lack of consistency around the graphics and labels used in these representations. Based on this, the aim of this study was to identify, analyze and evaluate these differences and propose a representation that aims to be more suitable for the theory. For this, uses as method a literature review based on Engeström (2001 and its three generations of visual models, combined with graphical analysis of representations collected in a hundred papers from international journals.

Representations of quantum algebras and combinatorics of Young tableaux

CERN Document Server

Ariki, Susumu

2002-01-01

Among several tools used in studying representations of quantum groups (or quantum algebras) are the notions of Kashiwara's crystal bases and Lusztig's canonical bases. Mixing both approaches allows us to use a combinatorial approach to representations of quantum groups and to apply the theory to representations of Hecke algebras. The primary goal of this book is to introduce the representation theory of quantum groups using quantum groups of type A_{r-1}^{(1)} as a main example. The corresponding combinatorics, developed by Misra and Miwa, turns out to be the combinatorics of Young tableaux. The second goal of this book is to explain the proof of the (generalized) Leclerc-Lascoux-Thibon conjecture. This conjecture, which is now a theorem, is an important breakthrough in the modular representation theory of the Hecke algebras of classical type. The book contains most of the nonstandard material necessary to get acquainted with this new rapidly developing area. It can be used as a good entry point into the stu...

Qualitative aspects of representational competence among college chemistry students: Multiple representations and their role in the understanding of ideal gases

Science.gov (United States)

Madden, Sean Patrick

This study examined the role of multiple representations of chemical phenomena, specifically, the temperature-pressure relationship of ideal gases, in the problem solving strategies of college chemistry students. Volunteers included students enrolled in a first semester general chemistry course at a western university. Two additional volunteers from the same university were asked to participate and serve as models of greater sophistication. One was a senior chemistry major; another was a junior science writing major. Volunteers completed an initial screening task involving multiple representations of concentration and dilution concepts. Based on the results of this screening instrument a smaller set of subjects were asked to complete a think aloud session involving multiple representations of the temperature-pressure relationship. Data consisted of the written work of the volunteers and transcripts from videotaped think aloud sessions. The data were evaluated by the researcher and two other graduate students in chemical education using a coding scheme (Kozma, Schank, Coppola, Michalchik, and Allen. 2000). This coding scheme was designed to identify essential features of representational competence and differences in uses of multiple representations. The results indicate that students tend to have a strong preference for one type of representation. Students scoring low on representational competence, as measured by the rubric, ignored important features of some representations or acknowledged them only superficially. Students scoring higher on representational competence made meaningful connections among representations. The more advanced students, those who rated highly on representational competence, tended to use their preferred representation in a heuristic manner to establish meaning for other representations. The more advanced students also reflected upon the problem at greater length before beginning work. Molecular level sketches seemed to be the most

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

Representations of braid group obtained from quantum sl(3) enveloping algebra

International Nuclear Information System (INIS)

Ma Zhongqi.

1989-07-01

The quantum Clebsch-Gordan coefficients for the coproduct 6x6 of the quantum sl(3) enveloping algebra are computed. Based on the representation 6, the representation of the braid group and the corresponding link polynomial are obtained. The link polynomials based on the representations of the quantum sl(3) enveloping algebra with one row Young tableau are discussed. (author). 11 refs, 3 tabs

Representations of G+++ and the role of space-time

International Nuclear Information System (INIS)

Kleinschmidt, A.; West, P.

2004-01-01

We consider the decomposition of the adjoint and fundamental representations of very extended Kac-Moody algebras G+++ with respect to their regular A type subalgebra which, in the corresponding non-linear realisation, is associated with gravity. We find that for many very extended algebras almost all the A type representations that occur in the decomposition of the fundamental representations also occur in the adjoint representation of G+++ . In particular, for E 8 +++ , this applies to all its fundamental representations. However, there are some important examples, such as A N-3 +++ , where this is not true and indeed the adjoint representation contains no generator that can be identified with a space-time translation. We comment on the significance of these results for how space-time can occur in the non-linear realisation based on G+++ . Finally we show that there is a correspondence between the A representations that occur in the fundamental representation associated with the very extended node and the adjoint representation of G+++ which is consistent with the interpretation of the former as charges associated with brane solutions. (author)

Advances in visual representation of molecular potentials.

Science.gov (United States)

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

A generative representation for the evolution of jazz solos

DEFF Research Database (Denmark)

Bäckman, Kjell; Dahlstedt, Palle

2008-01-01

This paper describes a system developed to create computer based jazz improvisation solos. The generation of the improvisation material uses interactive evolution, based on a dual genetic representation: a basic melody line representation, with energy constraints ("rubber band") and a hierarchic...... developed for this specific type of music. This is the first published part of an ongoing research project in generative jazz, based on probabilistic and evolutionary strategies....

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.

Translation Ambiguity but Not Word Class Predicts Translation Performance

Science.gov (United States)

Prior, Anat; Kroll, Judith F.; Macwhinney, Brian

2013-01-01

We investigated the influence of word class and translation ambiguity on cross-linguistic representation and processing. Bilingual speakers of English and Spanish performed translation production and translation recognition tasks on nouns and verbs in both languages. Words either had a single translation or more than one translation. Translation…

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)

Public Library Representations and Internet Appropriations

Directory of Open Access Journals (Sweden)

Paula Sequeiros

2013-11-01

Full Text Available May the changes in the representations of the public library be propitiated by readers' appropriations of the Internet? To answer this question, a theoretically-driven and empirically-based research was developed in a public library in Portugal, combining the analysis of documents uses, the ethnography of space and Internet use, of social relations developed while reading, with the analysis of representations of the public library. No clear-cut association emerged between social-demographics or user profiles, and representations, in general. No disruptive Internet "impact" was found: Internet use may contribute to reinforce traditional representations of the library, while it may also update and democratise other representations. If the library and the Internet are represented as synonymous, the former does not make sense without the latter; but an Internet widespread and intensive use conflicts with the image of an institution dedicated to high-brow culture. Changes in uses of the public library are, instead, clearly associated with new types of readers, which in their turn reflect changes in urban social composition. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1401141

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

Violence against women: adolescents’ social representations

Directory of Open Access Journals (Sweden)

Ana Márcia de Almeida Rezende

2018-02-01

Full Text Available Violence against women in affectionate intimate relationships is a serious problem that causes damages to its victims. In the social imaginary there are ways of thinking and representations that tend to trivialize this type of violence, considering it a natural practice. In this sense, this article brings a study that aimed to know the social representations elaborated by adolescents on violence against women in affectionate relationships. Data were collected through a semi-structured interview conducted with 22 adolescents, and analyzed through the content analysis technique (BARDIN, 2011. The results revealed that the adolescents represent violence against women objectified in an everyday phenomenon, which happens even in their families. They have also elaborated social representations anchored in patriarchy, in which men use violence as means to dominate partners. It was observed the need for preventive work that would make adolescents aware of patriarchal ideologies present in the society, helping them to construct social representations based on respect and gender equity.

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.

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.

Minutia-pair spectral representations for fingerprint template protection

NARCIS (Netherlands)

Stanko, T.; Skoric, B.

2017-01-01

We introduce a new fixed-length representation of fingerprint minutiae, for use in template protection. It is similar to the `spectral minutiae' representation of Xu et al. but is based on coordinate differences between pairs of minutiae. Our technique has the advantage that it does not discard the

Propositional matrices as alternative representation of truth values ...

African Journals Online (AJOL)

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

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.

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.

Preexisting semantic representation improves working memory performance in the visuospatial domain.

Science.gov (United States)

Rudner, Mary; Orfanidou, Eleni; Cardin, Velia; Capek, Cheryl M; Woll, Bencie; Rönnberg, Jerker

2016-05-01

Working memory (WM) for spoken language improves when the to-be-remembered items correspond to preexisting representations in long-term memory. We investigated whether this effect generalizes to the visuospatial domain by administering a visual n-back WM task to deaf signers and hearing signers, as well as to hearing nonsigners. Four different kinds of stimuli were presented: British Sign Language (BSL; familiar to the signers), Swedish Sign Language (SSL; unfamiliar), nonsigns, and nonlinguistic manual actions. The hearing signers performed better with BSL than with SSL, demonstrating a facilitatory effect of preexisting semantic representation. The deaf signers also performed better with BSL than with SSL, but only when WM load was high. No effect of preexisting phonological representation was detected. The deaf signers performed better than the hearing nonsigners with all sign-based materials, but this effect did not generalize to nonlinguistic manual actions. We argue that deaf signers, who are highly reliant on visual information for communication, develop expertise in processing sign-based items, even when those items do not have preexisting semantic or phonological representations. Preexisting semantic representation, however, enhances the quality of the gesture-based representations temporarily maintained in WM by this group, thereby releasing WM resources to deal with increased load. Hearing signers, on the other hand, may make strategic use of their speech-based representations for mnemonic purposes. The overall pattern of results is in line with flexible-resource models of WM.

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…

Stable Kernel Representations as Nonlinear Left Coprime Factorizations

NARCIS (Netherlands)

Paice, A.D.B.; Schaft, A.J. van der

1994-01-01

A representation of nonlinear systems based on the idea of representing the input-output pairs of the system as elements of the kernel of a stable operator has been recently introduced. This has been denoted the kernel representation of the system. In this paper it is demonstrated that the kernel

Court representation in Russia before 1917 (historical aspect

Directory of Open Access Journals (Sweden)

Konstantin V. Ilyashenko

2015-12-01

Full Text Available Objective basing on the research and analysis of the legislation historical legal sources and other materials to study the process of formation and development of the institution of legal representation in Russia before 1917. Methods the theoretical basis of research is the works of Russian scientists on various aspects of formation development and functioning of the institution of legal representation in Russia from ancient times till 1917. The methodological basis of the research is general scientific methods historical formallogical system and general logical methods analysis synthesis induction and deduction synthesis analogy abstraction. Historicallegal formallegal logicallegal comparative legal methods were applied in the study. The author used the retrospective approach to the study of the issues of legal representation in Russia. Results basing on analysis of normative legal acts regulating relations in the sphere of judicial representation and various doctrinal sources the author has examined the process of the formation and development of the legal representation institution in Russia before 1917 raised the question of providing legal assistance in prerevolutionary Russia. An analogy is drawn between the prerevolutionary legal regulation of the legal representation institution and the modern legislation regulating this legal institution. The conclusion is made about the inadequacy of prerevolutionary legislation regulating relations in the sphere of judicial representation as well as the modern legal regulation of relations in this sphere. It is established that the judicial reform of 1864 improved regulation in this sphere but still did not solve all the problems in this area. The relevance of the study is due to the topicality and the constitutional importance of legal representation for the entire Russian society the need to examine the origins of this legal phenomenon as well as the fact that the institution of legal representation

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.

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...

LGBT Representations on Facebook : Representations of the Self and the Content

OpenAIRE

Chu, Yawen

2017-01-01

The topic of LGBT rights has been increasingly discussed and debated over recent years. More and more scholars show their interests in the field of LGBT representations in media. However, not many studies involved LGBT representations in social media. This paper explores LGBT representations on Facebook by analysing posts on an open page and in a private group, including both representations of the self as the identity of sexual minorities, content that is displayed on Facebook and the simila...

Poincaré Embeddings for Learning Hierarchical Representations

CERN Multimedia

CERN. Geneva

2018-01-01

Abstracts: Representation learning has become an invaluable approach for learning from symbolic data such as text and graphs. However, while complex symbolic datasets often exhibit a latent hierarchical structure, state-of-the-art methods typically do not account for this property. In this talk, I will discuss a new approach for learning hierarchical representations of symbolic data by embedding them into hyperbolic space -- or more precisely into an n-dimensional Poincaré ball. Due to the underlying hyperbolic geometry, this allows us to learn parsimonious representations of symbolic data by simultaneously capturing hierarchy and similarity. We introduce an efficient algorithm to learn the embeddings based on Riemannian optimization and show experimentally that Poincaré embeddings outperform Euclidean embeddings significantly on data with latent hierarchies, both in terms of representation capacity and in terms of generalization ability.      &...

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.

Acoustic and Lexical Representations for Affect Prediction in Spontaneous Conversations.

Science.gov (United States)

Cao, Houwei; Savran, Arman; Verma, Ragini; Nenkova, Ani

2015-01-01

In this article we investigate what representations of acoustics and word usage are most suitable for predicting dimensions of affect|AROUSAL, VALANCE, POWER and EXPECTANCY|in spontaneous interactions. Our experiments are based on the AVEC 2012 challenge dataset. For lexical representations, we compare corpus-independent features based on psychological word norms of emotional dimensions, as well as corpus-dependent representations. We find that corpus-dependent bag of words approach with mutual information between word and emotion dimensions is by far the best representation. For the analysis of acoustics, we zero in on the question of granularity. We confirm on our corpus that utterance-level features are more predictive than word-level features. Further, we study more detailed representations in which the utterance is divided into regions of interest (ROI), each with separate representation. We introduce two ROI representations, which significantly outperform less informed approaches. In addition we show that acoustic models of emotion can be improved considerably by taking into account annotator agreement and training the model on smaller but reliable dataset. Finally we discuss the potential for improving prediction by combining the lexical and acoustic modalities. Simple fusion methods do not lead to consistent improvements over lexical classifiers alone but improve over acoustic models.

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.

The Schrödinger representation and its relation to the holomorphic representation in linear and affine field theory

International Nuclear Information System (INIS)

Oeckl, Robert

2012-01-01

We establish a precise isomorphism between the Schrödinger representation and the holomorphic representation in linear and affine field theory. In the linear case, this isomorphism is induced by a one-to-one correspondence between complex structures and Schrödinger vacua. In the affine case we obtain similar results, with the role of the vacuum now taken by a whole family of coherent states. In order to establish these results we exhibit a rigorous construction of the Schrödinger representation and use a suitable generalization of the Segal-Bargmann transform. Our construction is based on geometric quantization and applies to any real polarization and its pairing with any Kähler polarization.

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.

Social representation of the kinesiotherapist profession

Directory of Open Access Journals (Sweden)

Beatrice ABALAŞE

2017-03-01

Full Text Available The scientific approach is focused on identifying the social representation of the profession of physical therapist referring to mental images of social reality to a group consensus meeting. The goal of research identifies social representation of the profession of physical therapist, on the premise that students of the Faculty of Physical Education and Sport have made a social representation of the profession of physical therapist in accordance with the description of the occupation of COR. Working method was based on the questionnaire. Interpretation of results, the first two items of the questionnaire was done through word association technique, developed by P. Verges (1 and an alternative method for determining the structure and organization of elements representation proposed by. C. Havârneanu (2. Qualitative analysis reveals that students’ specialization Physical Therapy and Special Motricity believes that a therapist uses therapy as a strategy to work, and it must be applied professionally. Respondents considered, as shown in the data collected, that this profession is subject to skills, education, cognitive baggage, all sending to knowledge, experience and passion. The core refers to the complex representation obtained thanks cognitive process by which individuals or groups in familiar transforms abstract and it integrates knowledge of their system.

Representing number in the real-time processing of agreement: Self-paced reading evidence from Arabic

Directory of Open Access Journals (Sweden)

Matthew A. Tucker

2015-04-01

Full Text Available In the processing of subject-verb agreement, non-subject plural nouns following a singular subject sometimes attract the agreement with the verb, despite not being grammatically licensed to do so. This phenomenon generates agreement errors in production and an increased tendency to fail to notice such errors in comprehension, thereby providing a window into the representation of grammatical number in working memory during sentence processing. Research in this topic, however, is primarily done in related languages with similar agreement systems. In order to increase the cross-linguistic coverage of the processing of agreement, we conducted a self-paced reading study in Modern Standard Arabic. We report robust agreement attraction errors in relative clauses, a configuration not particularly conducive to the generation of such errors for all possible lexicalizations. In particular, we examined the speed with which readers retrieve a subject controller for both grammatical and ungrammatical agreeing verbs in sentences where verbs are preceded by two NPs, one of which is a local non-subject NP that can act as a distractor for the successful resolution of subject-verb agreement. Our results suggest that the frequency of errors is modulated by the kind of plural formation strategy used on the attractor noun: nouns which form plurals by suffixation condition high rates of attraction, whereas nouns which form their plurals by internal vowel change (ablaut generate lower rates of errors and reading-time attraction effects of smaller magnitudes. Furthermore, we show some evidence that these agreement attraction effects are mostly contained in the right tail of reaction time distributions. We also present modeling data in the ACT-R framework which supports a view of these ablauting patterns wherein they are differentially specified for number and evaluate the consequences of possible representations for theories of grammar and parsing.

Using Distributed Representations to Disambiguate Biomedical and Clinical Concepts

OpenAIRE

Tulkens, Stéphan; Šuster, Simon; Daelemans, Walter

2016-01-01

In this paper, we report a knowledge-based method for Word Sense Disambiguation in the domains of biomedical and clinical text. We combine word representations created on large corpora with a small number of definitions from the UMLS to create concept representations, which we then compare to representations of the context of ambiguous terms. Using no relational information, we obtain comparable performance to previous approaches on the MSH-WSD dataset, which is a well-known dataset in the bi...

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

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

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.

Representation Elements of Spatial Thinking

Science.gov (United States)

Fiantika, F. R.

2017-04-01

This paper aims to add a reference in revealing spatial thinking. There several definitions of spatial thinking but it is not easy to defining it. We can start to discuss the concept, its basic a forming representation. Initially, the five sense catch the natural phenomenon and forward it to memory for processing. Abstraction plays a role in processing information into a concept. There are two types of representation, namely internal representation and external representation. The internal representation is also known as mental representation; this representation is in the human mind. The external representation may include images, auditory and kinesthetic which can be used to describe, explain and communicate the structure, operation, the function of the object as well as relationships. There are two main elements, representations properties and object relationships. These elements play a role in forming a representation.

Design Case Retrieval by Generic Representations

NARCIS (Netherlands)

Achten, H.H.; Gero, J.S.

2000-01-01

Case-Based Reasoning and Case-Based Design have been proposed to utilize knowledge of previous design solutions to understand or solve current design problems. Case retrieval is often performed on the basis of verbal indexing systems, whereas in design the use of graphic representations is

Superalgebras, their quantum deformations and the induced representation method

International Nuclear Information System (INIS)

Nguyen Anh Ky.

1996-08-01

In this paper some introductory concepts and basic definitions of the Lie superalgebras and their quantum deformations are exposed. Especially the induced representation methods in both cases are described. Up to now, based on the Kac representation theory we have succeeded in constructing representations of several higher rank superalgebras. When representations of quantum superalgebras are concerned, we develop a method which can be applied not only to the one-parametric quantum deformations but also to the multi-parametric ones. Here, being illustrations of the above-mentioned methods, the superalgebra gl(2/1) and its (one-parametric) quantum deformation U q [gl(2/1)] are considered as their finite-dimensional representations are investigated in detail and constructed explicitly. Also, it is shown that the finite-dimensional representations obtained constitute classes of all irreducible (typical and non-typical) finite-dimensional representations of gl(2/1) and U q [gl(2/1)]. Some of the detailed results may be simple but they are given for the first time. (author). 64 refs

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

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.

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)

Frame representations of quantum mechanics and the necessity of negativity in quasi-probability representations

International Nuclear Information System (INIS)

Ferrie, Christopher; Emerson, Joseph

2008-01-01

Several finite-dimensional quasi-probability representations of quantum states have been proposed to study various problems in quantum information theory and quantum foundations. These representations are often defined only on restricted dimensions and their physical significance in contexts such as drawing quantum-classical comparisons is limited by the non-uniqueness of the particular representation. Here we show how the mathematical theory of frames provides a unified formalism which accommodates all known quasi-probability representations of finite-dimensional quantum systems. Moreover, we show that any quasi-probability representation is equivalent to a frame representation and then prove that any such representation of quantum mechanics must exhibit either negativity or a deformed probability calculus. (fast track communication)

Paired structures and bipolar knowledge representation

DEFF Research Database (Denmark)

Montero, Javier; Bustince, Humberto; Franco, Camilo

In this strictly positional paper we propose a general approach to bipolar knowledge representation, where the meaning of concepts can be modelled by examining their decomposition into opposite and neutral categories. In particular, it is the semantic relationship between the opposite categories...... and at the same time the type of neutrality rising in between opposites. Based on this first level of bipolar knowledge representation, paired structures in fact offer the means to characterize a specific bipolar valuation scale depending on the meaning of the concept that has to be verified. In this sense...

Usage of semantic representations in recognition memory.

Science.gov (United States)

Nishiyama, Ryoji; Hirano, Tetsuji; Ukita, Jun

2017-11-01

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

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...

A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs.

Science.gov (United States)

Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

2018-02-28

We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the $\\mathcal {E}$SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base-phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.

A Possible Neural Representation of Mathematical Group Structures.

Science.gov (United States)

Pomi, Andrés

2016-09-01

Every cognitive activity has a neural representation in the brain. When humans deal with abstract mathematical structures, for instance finite groups, certain patterns of activity are occurring in the brain that constitute their neural representation. A formal neurocognitive theory must account for all the activities developed by our brain and provide a possible neural representation for them. Associative memories are neural network models that have a good chance of achieving a universal representation of cognitive phenomena. In this work, we present a possible neural representation of mathematical group structures based on associative memory models that store finite groups through their Cayley graphs. A context-dependent associative memory stores the transitions between elements of the group when multiplied by each generator of a given presentation of the group. Under a convenient election of the vector basis mapping the elements of the group in the neural activity, the input of a vector corresponding to a generator of the group collapses the context-dependent rectangular matrix into a virtual square permutation matrix that is the matrix representation of the generator. This neural representation corresponds to the regular representation of the group, in which to each element is assigned a permutation matrix. This action of the generator on the memory matrix can also be seen as the dissection of the corresponding monochromatic subgraph of the Cayley graph of the group, and the adjacency matrix of this subgraph is the permutation matrix corresponding to the generator.

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.

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.

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)

Cortical Representations of Speech in a Multitalker Auditory Scene.

Science.gov (United States)

Puvvada, Krishna C; Simon, Jonathan Z

2017-09-20

The ability to parse a complex auditory scene into perceptual objects is facilitated by a hierarchical auditory system. Successive stages in the hierarchy transform an auditory scene of multiple overlapping sources, from peripheral tonotopically based representations in the auditory nerve, into perceptually distinct auditory-object-based representations in the auditory cortex. Here, using magnetoencephalography recordings from men and women, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in distinct hierarchical stages of the auditory cortex. Using systems-theoretic methods of stimulus reconstruction, we show that the primary-like areas in the auditory cortex contain dominantly spectrotemporal-based representations of the entire auditory scene. Here, both attended and ignored speech streams are represented with almost equal fidelity, and a global representation of the full auditory scene with all its streams is a better candidate neural representation than that of individual streams being represented separately. We also show that higher-order auditory cortical areas, by contrast, represent the attended stream separately and with significantly higher fidelity than unattended streams. Furthermore, the unattended background streams are more faithfully represented as a single unsegregated background object rather than as separated objects. Together, these findings demonstrate the progression of the representations and processing of a complex acoustic scene up through the hierarchy of the human auditory cortex. SIGNIFICANCE STATEMENT Using magnetoencephalography recordings from human listeners in a simulated cocktail party environment, we investigate how a complex acoustic scene consisting of multiple speech sources is represented in separate hierarchical stages of the auditory cortex. We show that the primary-like areas in the auditory cortex use a dominantly spectrotemporal-based representation of the entire auditory

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

Covariant representations of nuclear *-algebras

International Nuclear Information System (INIS)

Moore, S.M.

1978-01-01

Extensions of the Csup(*)-algebra theory for covariant representations to nuclear *-algebra are considered. Irreducible covariant representations are essentially unique, an invariant state produces a covariant representation with stable vacuum, and the usual relation between ergodic states and covariant representations holds. There exist construction and decomposition theorems and a possible relation between derivations and covariant representations

Profile of biology prospective teachers’ representation on plant anatomy learning

Science.gov (United States)

Ermayanti; Susanti, R.; Anwar, Y.

2018-04-01

This study aims to obtaining students’ representation ability in understanding the structure and function of plant tissues in plant anatomy course. Thirty students of The Biology Education Department of Sriwijaya University were involved in this study. Data on representation ability were collected using test and observation. The instruments had been validated by expert judgment. Test scores were used to represent students’ ability in 4 categories: 2D-image, 3D-image, spatial, and verbal representations. The results show that students’ representation ability is still low: 2D-image (40.0), 3D-image (25.0), spatial (20.0), and verbal representation (45.0). Based on the results of this study, it is suggested that instructional strategies be developed for plant anatomy course.

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.

Orienting Attention to Sound Object Representations Attenuates Change Deafness

Science.gov (United States)

Backer, Kristina C.; Alain, Claude

2012-01-01

According to the object-based account of attention, multiple objects coexist in short-term memory (STM), and we can selectively attend to a particular object of interest. Although there is evidence that attention can be directed to visual object representations, the assumption that attention can be oriented to sound object representations has yet…

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

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...

Bio-SimVerb and Bio-SimLex: wide-coverage evaluation sets of word similarity in biomedicine.

Science.gov (United States)

Chiu, Billy; Pyysalo, Sampo; Vulić, Ivan; Korhonen, Anna

2018-02-05

Word representations support a variety of Natural Language Processing (NLP) tasks. The quality of these representations is typically assessed by comparing the distances in the induced vector spaces against human similarity judgements. Whereas comprehensive evaluation resources have recently been developed for the general domain, similar resources for biomedicine currently suffer from the lack of coverage, both in terms of word types included and with respect to the semantic distinctions. Notably, verbs have been excluded, although they are essential for the interpretation of biomedical language. Further, current resources do not discern between semantic similarity and semantic relatedness, although this has been proven as an important predictor of the usefulness of word representations and their performance in downstream applications. We present two novel comprehensive resources targeting the evaluation of word representations in biomedicine. These resources, Bio-SimVerb and Bio-SimLex, address the previously mentioned problems, and can be used for evaluations of verb and noun representations respectively. In our experiments, we have computed the Pearson's correlation between performances on intrinsic and extrinsic tasks using twelve popular state-of-the-art representation models (e.g. word2vec models). The intrinsic-extrinsic correlations using our datasets are notably higher than with previous intrinsic evaluation benchmarks such as UMNSRS and MayoSRS. In addition, when evaluating representation models for their abilities to capture verb and noun semantics individually, we show a considerable variation between performances across all models. Bio-SimVerb and Bio-SimLex enable intrinsic evaluation of word representations. This evaluation can serve as a predictor of performance on various downstream tasks in the biomedical domain. The results on Bio-SimVerb and Bio-SimLex using standard word representation models highlight the importance of developing dedicated

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

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

Motor memory is encoded as a gain-field combination of intrinsic and extrinsic action representations.

Science.gov (United States)

Brayanov, Jordan B; Press, Daniel Z; Smith, Maurice A

2012-10-24

Actions can be planned in either an intrinsic (body-based) reference frame or an extrinsic (world-based) frame, and understanding how the internal representations associated with these frames contribute to the learning of motor actions is a key issue in motor control. We studied the internal representation of this learning in human subjects by analyzing generalization patterns across an array of different movement directions and workspaces after training a visuomotor rotation in a single movement direction in one workspace. This provided a dense sampling of the generalization function across intrinsic and extrinsic reference frames, which allowed us to dissociate intrinsic and extrinsic representations and determine the manner in which they contributed to the motor memory for a trained action. A first experiment showed that the generalization pattern reflected a memory that was intermediate between intrinsic and extrinsic representations. A second experiment showed that this intermediate representation could not arise from separate intrinsic and extrinsic learning. Instead, we find that the representation of learning is based on a gain-field combination of local representations in intrinsic and extrinsic coordinates. This gain-field representation generalizes between actions by effectively computing similarity based on the (Mahalanobis) distance across intrinsic and extrinsic coordinates and is in line with neural recordings showing mixed intrinsic-extrinsic representations in motor and parietal cortices.

Interactive Shape Modeling using a Skeleton-Mesh Co-Representation

DEFF Research Database (Denmark)

Bærentzen, Jacob Andreas; Abdrashitov, Rinat; Singh, Karan

2014-01-01

We introduce the Polar-Annular Mesh representation (PAM). A PAM is a mesh-skeleton co-representation designed for the modeling of 3D organic, articulated shapes. A PAM represents a manifold mesh as a partition of polar (triangle fans) and annular (rings of quads) regions. The skeletal topology of...... a PAM to a quad-only mesh. We further present a PAM-based multi-touch sculpting application in order to demonstrate its utility as a shape representation for the interactive modeling of organic, articulated figures as well as for editing and posing of pre-existing models....

Taking representation seriously: rethinking bioethics through Clint Eastwood's Million Dollar Baby.

Science.gov (United States)

Braswell, Harold

2011-06-01

In this article, I propose a new model for understanding the function of representation in bioethics. Bioethicists have traditionally judged representations according to a mimetic paradigm, in which representations of bioethical dilemmas are assessed based on their correspondence to the "reality" of bioethics itself. In this article, I argue that this mimetic paradigm obscures the interaction between representation and reality and diverts bioethicists from analyzing the tensions in the representational object itself. I propose an anti-mimetic model of representation that is attuned to how representations can both maintain and potentially subvert dominant conceptions of bioethics. I illustrate this model through a case study of Clint Eastwood's film Million Dollar Baby. By focusing attention on the film's lack of adherence bioethical procedures and medical science, critics missed how an analysis of its representational logic provides a means of reimagining both bioethics and medical practice. In my conclusion, I build off this case study to assess how an incorporation of representational studies can deepen-and be deepened by-recent calls for interdisciplinarity in bioethics.

Social representations about religion and spirituality.

Science.gov (United States)

Borges, Moema da Silva; Santos, Marília Borges Couto; Pinheiro, Tiago Gomes

2015-01-01

to identify the social representations about the concepts of spirituality and religion of of health teachers. exploratory and descriptive study, based on a qualitative approach. 25 subjects participated in it. The following instruments were used to collect data: questionnaire to identify the profile; questionnaire of free association, whose inducing words were religion and spirituality, and an interview based on the scale FICA (Puchalski, 2006). the representations about religion and spirituality, for professors, are forged around the faith in God and it gives them meaning and purpose to deal with the challenges of personal and professional living. there are still barriers that need to be overcome with a view to a comprehensive care. For this, it is essential to incorporate spirituality in the process in the curricula of health courses.

Standard model of knowledge representation

Science.gov (United States)

Yin, Wensheng

2016-09-01

Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.

Representing sentence information

Science.gov (United States)

Perkins, Walton A., III

1991-03-01

This paper describes a computer-oriented representation for sentence information. Whereas many Artificial Intelligence (AI) natural language systems start with a syntactic parse of a sentence into the linguist's components: noun, verb, adjective, preposition, etc., we argue that it is better to parse the input sentence into 'meaning' components: attribute, attribute value, object class, object instance, and relation. AI systems need a representation that will allow rapid storage and retrieval of information and convenient reasoning with that information. The attribute-of-object representation has proven useful for handling information in relational databases (which are well known for their efficiency in storage and retrieval) and for reasoning in knowledge- based systems. On the other hand, the linguist's syntactic representation of the works in sentences has not been shown to be useful for information handling and reasoning. We think it is an unnecessary and misleading intermediate form. Our sentence representation is semantic based in terms of attribute, attribute value, object class, object instance, and relation. Every sentence is segmented into one or more components with the form: 'attribute' of 'object' 'relation' 'attribute value'. Using only one format for all information gives the system simplicity and good performance as a RISC architecture does for hardware. The attribute-of-object representation is not new; it is used extensively in relational databases and knowledge-based systems. However, we will show that it can be used as a meaning representation for natural language sentences with minor extensions. In this paper we describe how a computer system can parse English sentences into this representation and generate English sentences from this representation. Much of this has been tested with computer implementation.

Anticipation in cybernetic systems : A case against mindless anti-representationalism

NARCIS (Netherlands)

Schomaker, L

2004-01-01

The developments in behavior-based robotics and in ecological psychology have had a strong effect on theoretical development in some research communities. A new belief has emerged under the name of anti-representationalism, which is strongly opposed to the notion of representations in cognition.

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

Converting boundary representation solid models to half-space representation models for Monte Carlo analysis

International Nuclear Information System (INIS)

Davis, J. E.; Eddy, M. J.; Sutton, T. M.; Altomari, T. J.

2007-01-01

Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces - a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation. (authors)

An Integrated Textual Case-Based System A. Almu

African Journals Online (AJOL)

Almu: An Integrated Textual Case-Based System. 66. The semantic relationship in WordNet links the Four-. Part-Of-Speech of Nouns, Verbs, Adverbs and. Adjectives together to synonyms sets (Miller 1995). Therefore, the words or terms of the problem have to be tagged with their appropriate POS before passing them to the ...

Multimodal semantic quantity representations: further evidence from Korean Sign Language

Directory of Open Access Journals (Sweden)

Frank eDomahs

2012-01-01

Full Text Available Korean deaf signers performed a number comparison task on pairs of Arabic digits. In their RT profiles, the expected magnitude effect was systematically modified by properties of number signs in Korean Sign Language in a culture-specific way (not observed in hearing and deaf Germans or hearing Chinese. We conclude that finger-based quantity representations are automatically activated even in simple tasks with symbolic input although this may be irrelevant and even detrimental for task performance. These finger-based numerical representations are accessed in addition to another, more basic quantity system which is evidenced by the magnitude effect. In sum, these results are inconsistent with models assuming only one single amodal representation of numerical quantity.

The Past Is Present: Representations of Parents, Friends, and Romantic Partners Predict Subsequent Romantic Representations.

Science.gov (United States)

Furman, Wyndol; Collibee, Charlene

2018-01-01

This study examined how representations of parent-child relationships, friendships, and past romantic relationships are related to subsequent romantic representations. Two-hundred 10th graders (100 female; M age  = 15.87 years) from diverse neighborhoods in a Western U.S. city were administered questionnaires and were interviewed to assess avoidant and anxious representations of their relationships with parents, friends, and romantic partners. Participants then completed similar questionnaires and interviews about their romantic representations six more times over the next 7.5 years. Growth curve analyses revealed that representations of relationships with parents, friends, and romantic partners each uniquely predicted subsequent romantic representations across development. Consistent with attachment and behavioral systems theory, representations of romantic relationships are revised by representations and experiences in other relationships. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

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

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.

Reliability in the Location of Hindlimb Motor Representations in Fischer-344 Rats

Science.gov (United States)

Frost, Shawn B.; Iliakova, Maria; Dunham, Caleb; Barbay, Scott; Arnold, Paul; Nudo, Randolph J.

2014-01-01

Object The purpose of the present study was to determine the feasibility of using a common laboratory rat strain for locating cortical motor representations of the hindlimb reliably. Methods Intracortical Microstimulation (ICMS) techniques were used to derive detailed maps of the hindlimb motor representations in six adult Fischer-344 rats. Results The organization of the hindlimb movement representation, while variable across individuals in topographic detail, displayed several commonalities. The hindlimb representation was positioned posterior to the forelimb motor representation and postero-lateral to the motor trunk representation. The areal extent of the hindlimb representation across the cortical surface averaged 2.00 +/− 0.50 mm2. Superimposing individual maps revealed an overlapping area measuring 0.35 mm2, indicating that the location of the hindlimb representation can be predicted reliably based on stereotactic coordinates. Across the sample of rats, the hindlimb representation was found 1.25–3.75 mm posterior to Bregma, with an average center location ~ 2.6 mm posterior to Bregma. Likewise, the hindlimb representation was found 1–3.25 mm lateral to the midline, with an average center location ~ 2 mm lateral to midline. Conclusions The location of the cortical hindlimb motor representation in Fischer-344 rats can be reliably located based on its stereotactic position posterior to Bregma and lateral to the longitudinal skull suture at midline. The ability to accurately predict the cortical localization of functional hindlimb territories in a rodent model is important, as such animal models are being used increasingly in the development of brain-computer interfaces for restoration of function after spinal cord injury. PMID:23725395

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.

Characterizing representational learning: A combined simulation and tutorial on perturbation theory

Directory of Open Access Journals (Sweden)

Antje Kohnle

2017-11-01

Full Text Available Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them (“representational competence” is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students’ spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

Characterizing representational learning: A combined simulation and tutorial on perturbation theory

Science.gov (United States)

Kohnle, Antje; Passante, Gina

2017-12-01

Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them ("representational competence") is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students' spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

Feature-Specific Event-Related Potential Effects to Action- and Sound-Related Verbs during Visual Word Recognition.

Science.gov (United States)

Popp, Margot; Trumpp, Natalie M; Kiefer, Markus

2016-01-01

Grounded cognition theories suggest that conceptual representations essentially depend on modality-specific sensory and motor systems. Feature-specific brain activation across different feature types such as action or audition has been intensively investigated in nouns, while feature-specific conceptual category differences in verbs mainly focused on body part specific effects. The present work aimed at assessing whether feature-specific event-related potential (ERP) differences between action and sound concepts, as previously observed in nouns, can also be found within the word class of verbs. In Experiment 1, participants were visually presented with carefully matched sound and action verbs within a lexical decision task, which provides implicit access to word meaning and minimizes strategic access to semantic word features. Experiment 2 tested whether pre-activating the verb concept in a context phase, in which the verb is presented with a related context noun, modulates subsequent feature-specific action vs. sound verb processing within the lexical decision task. In Experiment 1, ERP analyses revealed a differential ERP polarity pattern for action and sound verbs at parietal and central electrodes similar to previous results in nouns. Pre-activation of the meaning of verbs in the preceding context phase in Experiment 2 resulted in a polarity-reversal of feature-specific ERP effects in the lexical decision task compared with Experiment 1. This parallels analogous earlier findings for primed action and sound related nouns. In line with grounded cognitions theories, our ERP study provides evidence for a differential processing of action and sound verbs similar to earlier observation for concrete nouns. Although the localizational value of ERPs must be viewed with caution, our results indicate that the meaning of verbs is linked to different neural circuits depending on conceptual feature relevance.

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

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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.

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

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

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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.

Decoding the dynamic representation of musical pitch from human brain activity.

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Sankaran, N; Thompson, W F; Carlile, S; Carlson, T A

2018-01-16

In music, the perception of pitch is governed largely by its tonal function given the preceding harmonic structure of the music. While behavioral research has advanced our understanding of the perceptual representation of musical pitch, relatively little is known about its representational structure in the brain. Using Magnetoencephalography (MEG), we recorded evoked neural responses to different tones presented within a tonal context. Multivariate Pattern Analysis (MVPA) was applied to "decode" the stimulus that listeners heard based on the underlying neural activity. We then characterized the structure of the brain's representation using decoding accuracy as a proxy for representational distance, and compared this structure to several well established perceptual and acoustic models. The observed neural representation was best accounted for by a model based on the Standard Tonal Hierarchy, whereby differences in the neural encoding of musical pitches correspond to their differences in perceived stability. By confirming that perceptual differences honor those in the underlying neuronal population coding, our results provide a crucial link in understanding the cognitive foundations of musical pitch across psychological and neural domains.

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. 

Introduction to computer data representation

CERN Document Server

Fenwick, Peter

2014-01-01

Introduction to Computer Data Representation introduces readers to the representation of data within computers. Starting from basic principles of number representation in computers, the book covers the representation of both integer and floating point numbers, and characters or text. It comprehensively explains the main techniques of computer arithmetic and logical manipulation. The book also features chapters covering the less usual topics of basic checksums and 'universal' or variable length representations for integers, with additional coverage of Gray Codes, BCD codes and logarithmic repre

An evaluation of space time cube representation of spatiotemporal patterns.

Science.gov (United States)

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

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.

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

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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.

Embedded data representations

DEFF Research Database (Denmark)

Willett, Wesley; Jansen, Yvonne; Dragicevic, Pierre

2017-01-01

We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles...

Categorification and higher representation theory

CERN Document Server

Beliakova, Anna

2017-01-01

The emergent mathematical philosophy of categorification is reshaping our view of modern mathematics by uncovering a hidden layer of structure in mathematics, revealing richer and more robust structures capable of describing more complex phenomena. Categorified representation theory, or higher representation theory, aims to understand a new level of structure present in representation theory. Rather than studying actions of algebras on vector spaces where algebra elements act by linear endomorphisms of the vector space, higher representation theory describes the structure present when algebras act on categories, with algebra elements acting by functors. The new level of structure in higher representation theory arises by studying the natural transformations between functors. This enhanced perspective brings into play a powerful new set of tools that deepens our understanding of traditional representation theory. This volume exhibits some of the current trends in higher representation theory and the diverse te...

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.

Representational Approach: A Conceptual Framework to Guide Patient Education Research and Practice.

Science.gov (United States)

Arida, Janet A; Sherwood, Paula R; Flannery, Marie; Donovan, Heidi S

2016-11-01

Illness representations are cognitive structures that individuals rely on to understand and explain their illnesses and associated symptoms. The Representational Approach (RA) to patient education offers a theoretically based, clinically useful model that can support oncology nurses to develop a shared understanding of patients' illness representations to collaboratively develop highly personalized plans for symptom management and other important self-management behaviors. This article discusses theoretical underpinnings, practical applications, challenges, and future directions for incorporating illness representations and the RA in clinical and research endeavors.

Action simulation: time course and representational mechanisms

Science.gov (United States)

Springer, Anne; Parkinson, Jim; Prinz, Wolfgang

2013-01-01

The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others' actions implies a mirroring of their activities, based on one's own sensorimotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the future course of actions that are temporarily occluded from view. We address transitions between perceptual mechanisms (referring to action representation before and after occlusion) and simulation mechanisms (referring to action representation during occlusion). Findings suggest that action simulation runs in real-time; acting on newly created action representations rather than relying on continuous visual extrapolations. A further focus of our discussion pertains to the functional characteristics of the mechanisms involved in predicting other people's actions. We propose that two processes are engaged, dynamic updating and static matching, which may draw on both semantic and motor information. In a concluding section, we discuss these findings in the context of broader theoretical issues related to action and event representation, arguing that a detailed functional analysis of action simulation in cognitive, neural, and computational terms may help to further advance our understanding of action cognition and motor control. PMID:23847563

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.

Representation and alignment of sung queries for music information retrieval

Science.gov (United States)

Adams, Norman H.; Wakefield, Gregory H.

2005-09-01

The pursuit of robust and rapid query-by-humming systems, which search melodic databases using sung queries, is a common theme in music information retrieval. The retrieval aspect of this database problem has received considerable attention, whereas the front-end processing of sung queries and the data structure to represent melodies has been based on musical intuition and historical momentum. The present work explores three time series representations for sung queries: a sequence of notes, a ``smooth'' pitch contour, and a sequence of pitch histograms. The performance of the three representations is compared using a collection of naturally sung queries. It is found that the most robust performance is achieved by the representation with highest dimension, the smooth pitch contour, but that this representation presents a formidable computational burden. For all three representations, it is necessary to align the query and target in order to achieve robust performance. The computational cost of the alignment is quadratic, hence it is necessary to keep the dimension small for rapid retrieval. Accordingly, iterative deepening is employed to achieve both robust performance and rapid retrieval. Finally, the conventional iterative framework is expanded to adapt the alignment constraints based on previous iterations, further expediting retrieval without degrading performance.

Linking Video and Text via Representations of Narrative

OpenAIRE

Salway, Andrew; Graham, Mike; Tomadaki, Eleftheria; Xu, Yan

2003-01-01

The ongoing TIWO project is investigating the synthesis of language technologies, like information extraction and corpus-based text analysis, video data modeling and knowledge representation. The aim is to develop a computational account of how video and text can be integrated by representations of narrative in multimedia systems. The multimedia domain is that of film and audio description – an emerging text type that is produced specifically to be informative about the events and objects dep...

Consultation system with knowledge representation by decision rules

Energy Technology Data Exchange (ETDEWEB)

Senne, E L.F.; Simoni, P O

1982-04-01

The use of decision rules in the representation of empirical knowledge supplied by application domain experts is discussed. Based on this representation, a system is described which employs artificial intelligence techniques to yield inferences within a specific domain. Three modules composing the system are described: the acquisition one, that allows the insertion of new rules; the diagnostic one, that uses rules in the inference process; and the explanation one, that exhibits reasons for each system action.

Discrete variable representation for singular Hamiltonians

DEFF Research Database (Denmark)

Schneider, B. I.; Nygaard, Nicolai

2004-01-01

We discuss the application of the discrete variable representation (DVR) to Schrodinger problems which involve singular Hamiltonians. Unlike recent authors who invoke transformations to rid the eigenvalue equation of singularities at the cost of added complexity, we show that an approach based...

Intrinsic resonance representation of quantum mechanics

DEFF Research Database (Denmark)

Carioli, M.; Heller, E.J.; Møller, Klaus Braagaard

1997-01-01