Relevant bibliographies by topics / Structure representations

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  2. Dissertations / Theses
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Academic literature on the topic 'Structure representations'

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Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Structure representations"

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Singer, W. "Consciousness and the structure of neuronal representations." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 353, no. 1377 (November 29, 1998): 1829–40. http://dx.doi.org/10.1098/rstb.1998.0335.

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The hypothesis is defended that brains expressing phenomenal awareness are capable of generating metarepresentations of their cognitive processes, these metarepresentations resulting from an iteration of self–similar cortical operations. Search for the neuronal substrate of awareness therefore converges with the search for the nature of neuronal representations. It is proposed that evolved brains use two complementary representational strategies. One consists of the generation of neurons responding selectively to a particular constellation of features and is based on selective recombination of inputs in hierarchically structured feedforward architectures. The other relies on the dynamic association of feature–specific cells into functionally coherent cell assemblies that, as a whole, represent the constellation of features defining a particular perceptual object. Arguments are presented that favour the notion that the metarepresentations supporting awareness are established in accordance with the second strategy. Experimental data are reviewed that are compatible with the hypothesis that evolved brains use assembly codes for the representation of contents and that these assemblies become organized through transient synchronization of the discharges of associated neurons. It is argued that central states favouring the formation of assembly–based representations are similar to those favouring awareness.
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Viswanath, Shruthi, and Andrej Sali. "Optimizing model representation for integrative structure determination of macromolecular assemblies." Proceedings of the National Academy of Sciences 116, no. 2 (December 26, 2018): 540–45. http://dx.doi.org/10.1073/pnas.1814649116.

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Integrative structure determination of macromolecular assemblies requires specifying the representation of the modeled structure, a scoring function for ranking alternative models based on diverse types of data, and a sampling method for generating these models. Structures are often represented at atomic resolution, although ad hoc simplified representations based on generic guidelines and/or trial and error are also used. In contrast, we introduce here the concept of optimizing representation. To illustrate this concept, the optimal representation is selected from a set of candidate representations based on an objective criterion that depends on varying amounts of information available for different parts of the structure. Specifically, an optimal representation is defined as the highest-resolution representation for which sampling is exhaustive at a precision commensurate with the precision of the representation. Thus, the method does not require an input structure and is applicable to any input information. We consider a space of representations in which a representation is a set of nonoverlapping, variable-length segments (i.e., coarse-grained beads) for each component protein sequence. We also implement a method for efficiently finding an optimal representation in our open-source Integrative Modeling Platform (IMP) software (https://integrativemodeling.org/). The approach is illustrated by application to three complexes of two subunits and a large assembly of 10 subunits. The optimized representation facilitates exhaustive sampling and thus can produce a more accurate model and a more accurate estimate of its uncertainty for larger structures than were possible previously.
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Garnham, Alan. "Opinion Piece: How People Structure Representations of Discourse." Dialogue & Discourse 12, no. 1 (February 25, 2021): 1–20. http://dx.doi.org/10.5210/dad.2021.101.

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Mental models or situation models include representations of people, but much of the literature about such models focuses on the representation of eventualities (events, states, and processes) or (small-scale) situations. In the well-known event-indexing model of Zwaan, Langston, and Graesser (1995), for example, protagonists are just one of five dimensions on which situation models are indexed. They are not given any additional special status. Consideration of longer narratives, and the ways in which readers or listeners relate to them, suggest that people have a more central status in the way we think about texts, and hence in discourse representations, Indeed, such considerations suggest that discourse representations are organised around (the representations of) central characters. The paper develops the idea of the centrality of main characters in representations of longer texts, by considering, among other things, the way information is presented in novels, with L’Éducation Sentimentale by Gustav Flaubert as a case study. Conclusions are also drawn about the role of representations of people in the representation of other types of text.
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Ibarra, Andoni, and Thomas Mormann. "Una teoría combinatoria de las representaciones científicas." Crítica (México D. F. En línea) 32, no. 95 (January 7, 2000): 3–46. http://dx.doi.org/10.22201/iifs.18704905e.2000.874.

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The aim of this paper is to introduce a new concept of scientific representation into philosophy of science. The new concept -to be called homological or functorial representation- is a genuine generalization of the received notion of representation as a structure preserving map as it is used, for example, in the representational theory of measurement. It may be traced back, at least implicitly, to the works of Hertz and Duhem. A modern elaboration may be found in the foundational discipline of mathematical category theory. In contrast to the familiar concepts of representations, functorial representations do not depend on any notion of similarity, neither structural nor objectual one. Rather, functorial representation establish correlations between the structures of the representing and the represented domains. Thus, they may be said to form a class of quite "non-isomorphic" representations. Nevertheless, and this is the central claim of this paper, they are the most common type of representations used in science. In our paper we give some examples from mathematics and empirical science. One of the most interesting features of the new concept is that it leads in a natural way to a combinatorial theory of scientific representations, i.e. homological or functorial representations do not live in insulation, rather, they may be combined and connected in various ways thereby forming a net of interrelated representations. One of the most important tasks of a theory of scientific representations is to describe this realm of combinatorial possibilities in detail. Some first tentative steps towards this endeavour are done in our paper.
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Ibort, Alberto, and Miguel Rodríguez. "On the Structure of Finite Groupoids and Their Representations." Symmetry 11, no. 3 (March 20, 2019): 414. http://dx.doi.org/10.3390/sym11030414.

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In this paper, both the structure and the theory of representations of finite groupoids are discussed. A finite connected groupoid turns out to be an extension of the groupoids of pairs of its set of units by its canonical totally disconnected isotropy subgroupoid. An extension of Maschke’s theorem for groups is proved showing that the algebra of a finite groupoid is semisimple and all finite-dimensional linear representations of finite groupoids are completely reducible. The theory of characters for finite-dimensional representations of finite groupoids is developed and it is shown that irreducible representations of the groupoid are in one-to-one correspondence with irreducible representation of its isotropy groups, with an extension of Burnside’s theorem describing the decomposition of the regular representation of a finite groupoid. Some simple examples illustrating these results are exhibited with emphasis on the groupoids interpretation of Schwinger’s description of quantum mechanical systems.
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Schwartz, Geoffrey. "Refining representations for L2 phonology." Second Language Research 36, no. 4 (June 9, 2019): 691–707. http://dx.doi.org/10.1177/0267658319852383.

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This article discusses the implications of phonological representation for the study of L2 speech acquisition. It is argued, on the basis of empirical findings from diverse phenomena in L2 phonology, that refined representations in which ‘segments’ have internal prosodic structure offer a more insightful view of cross-linguistic phonetic interaction than traditional phonological models. These refinements may be implemented in the Onset Prominence representational environment, in which diverse structural parses affect sub-segmental phonetic properties, transitions between segments, and the formation of prosodic boundaries.
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Carlson, Thomas A., J. Brendan Ritchie, Nikolaus Kriegeskorte, Samir Durvasula, and Junsheng Ma. "Reaction Time for Object Categorization Is Predicted by Representational Distance." Journal of Cognitive Neuroscience 26, no. 1 (January 2014): 132–42. http://dx.doi.org/10.1162/jocn_a_00476.

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How does the brain translate an internal representation of an object into a decision about the object's category? Recent studies have uncovered the structure of object representations in inferior temporal cortex (IT) using multivariate pattern analysis methods. These studies have shown that representations of individual object exemplars in IT occupy distinct locations in a high-dimensional activation space, with object exemplar representations clustering into distinguishable regions based on category (e.g., animate vs. inanimate objects). In this study, we hypothesized that a representational boundary between category representations in this activation space also constitutes a decision boundary for categorization. We show that behavioral RTs for categorizing objects are well described by our activation space hypothesis. Interpreted in terms of classical and contemporary models of decision-making, our results suggest that the process of settling on an internal representation of a stimulus is itself partially constitutive of decision-making for object categorization.
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Csaszar, Felipe A., and James Ostler. "A Contingency Theory of Representational Complexity in Organizations." Organization Science 31, no. 5 (September 2020): 1198–219. http://dx.doi.org/10.1287/orsc.2019.1346.

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A long-standing question in the organizations literature is whether firms are better off by using simple or complex representations of their task environment. We address this question by developing a formal model of how firm performance depends on the process by which firms learn and use representations. Building on ideas from cognitive science, our model conceptualizes this process in terms of how firms construct a representation of the environment and then use that representation when making decisions. Our model identifies the optimal level of representational complexity as a function of (a) the environment’s complexity and uncertainty and (b) the firm’s experience and knowledge about the environment’s deep structure. We use this model to delineate the conditions under which firms should use simple versus complex representations; in doing so, we provide a coherent framework that integrates previous conflicting results on which type of representation leaves firms better off. Among other results, we show that the optimal representational complexity generally depends more on the firm’s knowledge about the environment than it does on the environment’s actual complexity. We also show that the relative advantage of heuristics vis-à-vis more complex representations critically depends on an unstated assumption of “informedness”: that managers can know what are the most relevant variables to pay attention to. We show that when this assumption does not hold, complex representations are usually better than simpler ones.
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Spinks, Graham, and Marie-Francine Moens. "Structured (De)composable Representations Trained with Neural Networks." Computers 9, no. 4 (October 2, 2020): 79. http://dx.doi.org/10.3390/computers9040079.

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This paper proposes a novel technique for representing templates and instances of concept classes. A template representation refers to the generic representation that captures the characteristics of an entire class. The proposed technique uses end-to-end deep learning to learn structured and composable representations from input images and discrete labels. The obtained representations are based on distance estimates between the distributions given by the class label and those given by contextual information, which are modeled as environments. We prove that the representations have a clear structure allowing decomposing the representation into factors that represent classes and environments. We evaluate our novel technique on classification and retrieval tasks involving different modalities (visual and language data). In various experiments, we show how the representations can be compressed and how different hyperparameters impact performance.
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Jha, Kishlay, Guangxu Xun, and Aidong Zhang. "Continual representation learning for evolving biomedical bipartite networks." Bioinformatics 37, no. 15 (February 3, 2021): 2190–97. http://dx.doi.org/10.1093/bioinformatics/btab067.

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Abstract Motivation Many real-world biomedical interactions such as ‘gene-disease’, ‘disease-symptom’ and ‘drug-target’ are modeled as a bipartite network structure. Learning meaningful representations for such networks is a fundamental problem in the research area of Network Representation Learning (NRL). NRL approaches aim to translate the network structure into low-dimensional vector representations that are useful to a variety of biomedical applications. Despite significant advances, the existing approaches still have certain limitations. First, a majority of these approaches do not model the unique topological properties of bipartite networks. Consequently, their straightforward application to the bipartite graphs yields unsatisfactory results. Second, the existing approaches typically learn representations from static networks. This is limiting for the biomedical bipartite networks that evolve at a rapid pace, and thus necessitate the development of approaches that can update the representations in an online fashion. Results In this research, we propose a novel representation learning approach that accurately preserves the intricate bipartite structure, and efficiently updates the node representations. Specifically, we design a customized autoencoder that captures the proximity relationship between nodes participating in the bipartite bicliques (2 × 2 sub-graph), while preserving both the global and local structures. Moreover, the proposed structure-preserving technique is carefully interleaved with the central tenets of continual machine learning to design an incremental learning strategy that updates the node representations in an online manner. Taken together, the proposed approach produces meaningful representations with high fidelity and computational efficiency. Extensive experiments conducted on several biomedical bipartite networks validate the effectiveness and rationality of the proposed approach.
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Dissertations / Theses on the topic "Structure representations"

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Fiorentino, Robert D. "Lexical structure and the nature of linguistic representations." College Park, Md. : University of Maryland, 2006. http://hdl.handle.net/1903/3896.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Linguistics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Moore, Barbara Kirsten. "An analysis of representations for protein structure prediction." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/32620.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
Includes bibliographical references (p. 270-279).
by Barbara K. Moore Bryant.
Ph.D.
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LeBlanc, David C. "The generation of phrase-structure representations from principles." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/29338.

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Implementations of grammatical theory have traditionally been based upon Context- Free Grammar (CFG) formalisms which all but ignore questions of learnability. Even implementations which are based upon theories of Generative Grammar (GG), a paradigm which is supposedly motivated by learnability, rarely address such questions. In this thesis we will examine a GG theory which has been formulated primarily to address questions of learnability and present an implementation based upon this theory. The theory argues from Chomsky's definition of epistemological priority that principles which match elements and structures from prelinguistic systems with elements and structures in linguistic systems are preferable to those which are defined purely linguistically or non-linguistically. A procedure for constructing phrase-structure representations from prelinguistic relations using principles of node percolation (rather than the traditional X-theory of GG theories or phrase-structure rules of CFG theories) is presented and this procedure integrated into a left-right, primarily bottom-up parsing mechanism. Specifically, we present a parsing mechanism which derives phrase-structure representations of sentences from Case- and 0-relations using a small number of Percolation Principles. These Percolation Principles simply determine the categorial features of the dominant node of any two adjacent nodes in a representational tree, doing away with explicit phrase structure rules altogether. The parsing mechanism also instantiates appropriate empty categories using a filler-driven paradigm for leftward argument and non-argument movement. Procedures modelling learnability are not implemented in this work, but the applicability of the presented model to a computational model of language is discussed.
Science, Faculty of
Computer Science, Department of
Graduate
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Rateau, Patrick. "Structure et fonctionnement du systeme central des representations sociales." Montpellier 3, 1995. http://www.theses.fr/1995MON30002.

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Un point fondamental de la theorie du noyau central des representations sociales est que le noyau a avant tout une dimension qualitative. Ce n'est pas l'importance quantitative d'un element qui definit sa centralite, mais c'est le fait qu'il donne sa signification a la representation. Ceci explique que l'on peut observer deux elements dont l'importance quantitative est identique et tres forte mais dont l'un est dans le noyau central et l'autre non. Or, l'etude des travaux portant sur la representation du groupe (flament, 1971, 1984 ; moliner, 1988) et la mise en oeuvre d'une serie d'experience amenent a poser l'existence d'une difference qualitative de deux elements pourtant centraux de la representation : l'un serait prioritaire, c'est lui qui gererait veritablement sa signification. Ses liens avec l'ideologie, la culture et l'histoire des sujets semblent par ailleurs tres fort, il s'agirait d'un element normatif. L'autre serait adjoint et aurait davantage un role de mediateur, il specifierait le sens de la representation et serait lie aux pratiques sociales que les sujets developpent frequemment envers l'objet (il s'agirait donc d'un element fonctionnel). On abandonnerait ainsi la notion classique de noyau, pour lui substituer celle de systeme central hierarchise, impliquant un certain nombre de visees theoriques nouvelles
One fundamental point of the social representations' central core theory is that the core gets a quantative dimension above all. This is not the quantitative importance of an element which define is centrality but the fact that it gives sens to the representation. That's why it can be observed two elements quantitatively equals and strong with one in the central core and the other not. However, both the study of works about social representation of an ideal group (flament, 1971,1984 ; moliner, 1988) and the implementation of a series of experimentations, lead to the conclusion that there is a qualitative difference between the two central elements of the representation : one would be an "having priority element". It would really generate the meaning of the representation. Its relation with ideology, culture and history of the group seems to be strong. Then, it would have a normative function. The other one should be an "adjunct element". It would have a mediating role, specificating the meaning of the representation in relation with the social practices that subjects frequently entertain with the object (then it would have a functional function). The classical notion of "core" should be replace with the term of hierarchical central system which implies some new theorical developments
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Livingstone, Sonia M. "Social knowledge and programme structure in representations of television characters." Thesis, University of Oxford, 1987. http://ora.ox.ac.uk/objects/uuid:2adf1878-f117-4c32-870c-9d0ec539bb11.

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It was argued that the social psychology of person perception, mass communications and cultural studies can be related to viewers' representations of television characters. Mass communications needs to incorporate viewers' interpretations and programme structure. Social cognition could satisfy the former need and cultural studies the latter. A literature review showed little research on viewers' interpretations of television programmes. There is a considerable body of research on person perception, gender stereotypes, the effects of viewing and programme structure. A study of viewers' accounts of viewing soap opera showed that they become involved with the characters and find the programmes realistic. Soap opera plays an important role in their lives. Viewers' representations of soap opera characters were examined using multidimensional scaling. This revealed stable, replicable character representations for Dallas, Coronation Street and EastEnders. The representations were compared with the oppositions which structure the programmes, Implicit Personality Theory and Gender Schema Theory. Dallas characters were represented by themes of morality and power/activity. Power was correlated with gender, with some counter-stereotypic females. Coronation Street characters were organised around morality/potency, gender (matriarchal) and approach to life. This related to person prototypes and contrasted with interaction patterns between characters. EastEnders characters were represented by themes of morality/power, gender and approach to life/centrality. Free descriptions validated the attribute ratings and showed further features of the representation. No socio-structural group differences in representation were found. Viewers' character representations were a constructive integration of programme structure and social knowledge. The application of abstract knowledge to a structured domain was discussed. Textual analysis of a narrative identified the 'role of the reader' and textual openness. This was related to stereotypes, narrative expectancies, myth and character representation. Distinct types of divergence in viewers' interpretations of narrative were discovered. Further, a narrative containing two readings was interpreted in four distinct ways by viewers, depending on their perceived relationships with characters. The conclusions and limitations of the research were discussed. Implications for person perception, stereotyping and textual analysis were examined. A taxonomy of factors relating to the interpretation and representation of television drama was presented.
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Peche, Irissarry Macarena. "The reduction of G-ordinary crystalline representations with G-structure." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066467/document.

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Le foncteur D_cris de Fontaine nous permet d'obtenir des isocristaux à partir des représentations cristallines. Pour un groupe reductif G, on s'intéresse à étudier la réduction des réseaux dans une représentation cristalline avec G-structure V, vers les cristaux avec G-structure contenus dans D_cris(V). En utilisant la théorie des modules de Kisin, on donne une description de cette réduction en termes du groupe G, dans le cas où la représentation est (G-)ordinaire. Pour cela, il faut d'abord généraliser la construction de la filtration de Harder-Narasimhan des groupes p-divisibles, donnée par Fargues, aux modules de Kisin
Fontaine’s D_cris functor allows us to associate an isocrystal to any crystalline representation. For a reductive group G, we study the reduction of lattices inside a germ of crystalline representations with G-structure V, to lattices (which are crystals) with G-structure inside D_cris(V). Using Kisin modules theory, we give a description of this reduction in terms of G, in the case when the representation V is (G-)ordinary. In order to do that, first we need to generalize Fargues’ construction of the Harder-Narasimhan filtration for p-divisible groups to Kisin modules
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Hall, Johan. "Transition-Based Natural Language Parsing with Dependency and Constituency Representations." Doctoral thesis, Växjö : Växjö University Press, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-2367.

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Komninos, Alexandros. "Leveraging structure for learning representations of words, sentences and knowledge bases." Thesis, University of York, 2018. http://etheses.whiterose.ac.uk/21616/.

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This thesis presents work on learning representations of text and Knowledge Bases by taking into consideration their respective structures. The tasks for which the methods are developed and evaluated on are: Short-text classification, Word Sense Induction and Disambiguation, Knowledge Base Completion with linked text corpora, and large-scale Knowledge Base Question Answering. An introductory chapter states the aims and scope of the thesis, followed by a chapter on technical background and definitions. In chapter 3, the impact of dependency syntax on word representation learning in the context of short-text classification is investigated. A new definition of context in dependency graphs is proposed, which generalizes and extends previous definitions used in word representation learning. The resulting word and dependency feature embeddings are used together to represent dependency graph substructures in text classifiers. In chapter 4, a probabilistic latent variable model for Word Sense Induction and Disambiguation is presented. The model estimates sense clusters using pretrained continuous feature vectors of multiple context types: syntactic, local lexical and global lexical, while the number of sense clusters is determined by the Integrated Complete Likelihood criterion. A model for Knowledge Base Completion with linked text corpora is presented in chapter 5. The proposed model represents potential facts by merging subgraphs of the knowledge base with text through linked entities. The model learns to embed the merged graphs into a lower dimensional space and score the plausibility of the fact with a Multilayer Perceptron. Chapter 6 presents a system for Question Answering on Knowledge Bases. The system learns to decompose questions into entity and relation mentions and score their compatibility with queries on the knowledge base expressed as subgraphs. The model consists of several components trained jointly in order to match parts of the question with parts of a potential query by embedding their corresponding structures in lower dimensional spaces.
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Feiman, Roman. "The Structure and Development of Logical Representations in Thought and Language." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:23845487.

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The expressive power of human thought and language comes from the ability to systematically combine a finite vocabulary of concepts into a boundless number of meaningful thoughts. What properties of conceptual representations enable their combination? Three papers investigate different aspects of the combinatorial system in the context of a single general approach – taking logical concepts as a special case of concepts whose content is completely specified by their combinatorial properties. The first paper looks at infants’ ability to represent two types of goals: approach and avoid, where each goal-type could be represented as the negation of the other. Consistent with past literature, we find evidence of children representing approach at 7 month, but failing to represent avoid at both 7 and 14 months. This suggests that these children cannot combine their representation of approach with a negation operator, possibly because they do not yet have this operator. In the second paper, we continue to look at the emergence of logical negation through the relationship between the emergence of the concept and the words that label it. We find that, although 15-month-olds say the word “no”, they do not understand its logical meaning until 24 months. This is the same age at which they begin to produce the word “not”, comprehend its logical meaning, and use both “no” and “not” to deny the truth of others’ statements. This pattern of results suggest a common limiting factor on the mapping of any word to the concept of logical negation. This factor could be the emergence of the concept, or a linguistic limitation common to both “no” and “not”. The third paper looks at the properties of the combinatorial system in adults, taking linguistic quantifier scope ambiguity phenomena as a case study. Using a priming paradigm, we find evidence for independent combinatorial operations for the universal quantifiers EACH, EVERY and ALL, but common operations for the numbers THREE, FOUR and FIVE. We also find that the semantic operations that compose quantifier meanings abstract away from the verb and noun content of sentences. This suggests a division of labor in adult combinatorial thought, with conceptual content represented separately from the combinatorial properties of concepts.
Psychology
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Iyer, Preeti Ramesh [Verfasser]. "Multi-faceted Structure-Activity Relationship Analysis Using Graphical Representations / Preeti Ramesh Iyer." Bonn : Universitäts- und Landesbibliothek Bonn, 2014. http://d-nb.info/1048091465/34.

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Books on the topic "Structure representations"

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Plate, Tony A. Distributed representations and nested compositional structure. Toronto: University of Toronto, Dept. of Computer Science, 1994.

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Huckleberry, Alan, Ivan Penkov, and Gregg Zuckerman, eds. Lie Groups: Structure, Actions, and Representations. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7193-6.

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Jacobson, Nathan. Structure and representations of Jordan algebras. Providence: American Mathematical Society, 2008.

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Dinsmore, John. Partitioned Representations: A Study in Mental Representation, Language Understanding and Linguistic Structure. Dordrecht: Springer Netherlands, 1991.

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Partitioned representations: A study in mental representation, language understanding, and linguistic structure. Dordrecht: Kluwer Academic Publishers, 1991.

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Karpilovsky, Gregory. Structure of blocks of group algebras. Harlow, Essex, England: Longman Scientific & Technical, 1987.

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The analytic theory of multiplicative Galois structure. Providence, R.I., USA: American Mathematical Society, 1989.

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Puig, Lluis. On the local structure of Morita and Rickard equivalences between Brauer blocks. Basel: Springer, 1999.

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On the local structure of Morita and Rickard equivalences between Brauer blocks. Basel: Birkhäuser, 1999.

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Cornwall County Council. Planning Directorate. Cornwall structure plan: Statement of decisions in respect of objections and representations to the proposed modifications : March 1997. Truro: Cornwall County Council, 1996.

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Book chapters on the topic "Structure representations"

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Alperin, J. L., and Rowen B. Bell. "Local Structure." In Groups and Representations, 63–87. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-0799-3_3.

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Alperin, J. L., and Rowen B. Bell. "Normal Structure." In Groups and Representations, 89–105. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-0799-3_4.

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Dinsmore, John. "Language: Process and Structure." In Partitioned Representations, 93–114. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3574-0_3.

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Borg, I., and J. Lingoes. "Construction of SSA Representations." In Multidimensional Similarity Structure Analysis, 1–11. New York, NY: Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4612-4768-5_1.

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Jiang, Xiaoyi, Martin Lambers, and Horst Bunke. "Structure-Based Evaluation Methodology for Curvilinear Structure Detection Algorithms." In Graph-Based Representations in Pattern Recognition, 305–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20844-7_31.

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Gasteiger, Johann. "A Hierarchy of Structure Representations." In Handbook of Chemoinformatics, 1034–61. Weinheim, Germany: Wiley-VCH Verlag GmbH, 2008. http://dx.doi.org/10.1002/9783527618279.ch38.

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Aizawa, Kenneth. "The Structure of Cognitive Representations." In The Systematicity Arguments, 1–18. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0275-3_1.

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Bonnafé, Cédric. "Structure of $\mathrm{SL}_{2}({\mathbb{F}_{\!q}})$." In Representations of SL2(Fq), 3–14. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-157-8_1.

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Leonardis, Aleš. "Hierarchical Compositional Representations of Object Structure." In Lecture Notes in Computer Science, 31–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34166-3_3.

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Brown, Ken A., and Ken R. Goodearl. "Structure and Representations of O ∈ (G)." In Lectures on Algebraic Quantum Groups, 289–302. Basel: Birkhäuser Basel, 2002. http://dx.doi.org/10.1007/978-3-0348-8205-7_33.

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Conference papers on the topic "Structure representations"

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Kalm, Pavlina, Michael Regan, and William Croft. "Event Structure Representation: Between Verbs and Argument Structure Constructions." In Proceedings of the First International Workshop on Designing Meaning Representations. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-3311.

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Blelloch, Paul A., Jeffrey W. Young, and Kelly S. Carney. "Modal Representations in Control/Structure Interaction." In 1989 American Control Conference. IEEE, 1989. http://dx.doi.org/10.23919/acc.1989.4790667.

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RETAKH, ALEXANDER. "STRUCTURE AND REPRESENTATIONS OF CONFORMAL ALGEBRAS." In Proceedings of the International Conference on Algebras, Modules and Rings. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812774552_0018.

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Vigus, Meagan, Jens E. L. Van Gysel, and William Croft. "A Dependency Structure Annotation for Modality." In Proceedings of the First International Workshop on Designing Meaning Representations. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-3321.

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Molloy, Kevin, M. Jennifer Van, Daniel Barbara, and Amarda Shehu. "Higher-order representations of protein structure space." In 2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences (ICCABS). IEEE, 2013. http://dx.doi.org/10.1109/iccabs.2013.6629202.

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Andreas, Jacob, and Dan Klein. "Analogs of Linguistic Structure in Deep Representations." In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/d17-1311.

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Busemann, Stephan. "Structure-driven generation from separate semantic representations." In the fifth conference. Morristown, NJ, USA: Association for Computational Linguistics, 1991. http://dx.doi.org/10.3115/977180.977200.

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Chapman, Colin D., Kazuhiro Saitou, and Mark J. Jakiela. "Genetic Algorithms As an Approach to Configuration and Topology Design." In ASME 1993 Design Technical Conferences. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/detc1993-0338.

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Abstract The Genetic Algorithm, a search and optimization technique based on the theory of natural selection, is applied to problems of structural topology optimization. Given a structure’s boundary conditions and maximum allowable design domain, a discretized design representation is created. Populations of genetic algorithm “chromosomes” are then mapped into the design representation, creating potentially optimal structure topologies. Utilizing genetics-based operators such as crossover and mutation, generations of increasingly-desirable structure topologies are created. In this paper, the use of the genetic algorithm (GA) in structural topology optimization is presented. An overview of the genetic algorithm will describe the genetics-based representations and operators used in a typical genetic algorithm search. After defining topology optimization and its relation to the broader area of structural optimization, a review of previous research in GA-based and non-GA-based structural optimization is provided. The design representations, and methods for mapping genetic algorithm “chromosomes” into structure topology representations, are then detailed. Several examples of genetic algorithm-based structural topology optimization are provided: we address the optimization of beam cross-section topologies and cantilevered plate topologies, and we also investigate efficient techniques for using finite element analysis in a genetic algorithm-based search. Finally, a description of potential future work in genetic algorithm-based structural topology optimization is offered.
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Maren, A. J., and M. Ali. "Hierarchical scene structure representations to facilitate image understanding." In the first international conference. New York, New York, USA: ACM Press, 1988. http://dx.doi.org/10.1145/55674.55678.

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Cheng, Zhou, Chun Yuan, Jiancheng Li, and Haiqin Yang. "TreeNet: Learning Sentence Representations with Unconstrained Tree Structure." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/557.

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Recursive neural network (RvNN) has been proved to be an effective and promising tool to learn sentence representations by explicitly exploiting the sentence structure. However, most existing work can only exploit simple tree structure, e.g., binary trees, or ignore the order of nodes, which yields suboptimal performance. In this paper, we proposed a novel neural network, namely TreeNet, to capture sentences structurally over the raw unconstrained constituency trees, where the number of child nodes can be arbitrary. In TreeNet, each node is learning from its left sibling and right child in a bottom-up left-to-right order, thus enabling the net to learn over any tree. Furthermore, multiple soft gates and a memory cell are employed in implementing the TreeNet to determine to what extent it should learn, remember and output, which proves to be a simple and efficient mechanism for semantic synthesis. Moreover, TreeNet significantly suppresses convolutional neural networks (CNN) and Long Short-Term Memory (LSTM) with fewer parameters. It improves the classification accuracy by 2%-5% with 42% of the best CNN’s parameters or 94% of standard LSTM’s. Extensive experiments demonstrate TreeNet achieves the state-of-the-art performance on all four typical text classification tasks.
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Reports on the topic "Structure representations"

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Elman, Jeffrey L. Representation and Structure in Connectionist Models. Fort Belvoir, VA: Defense Technical Information Center, August 1989. http://dx.doi.org/10.21236/ada259504.

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Groeber, Michael A. Digital Representation of Materials Grain Structure. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada523965.

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Salata, Steven E., and Clive L. Dym. Representation of Strategic Choices in Structural Modeling. Fort Belvoir, VA: Defense Technical Information Center, June 1990. http://dx.doi.org/10.21236/ada226437.

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Sakhanenko, Nikita A., and George F. Luger. Using Structured Knowledge Representation for Context-Sensitive Probabilistic Modeling. Fort Belvoir, VA: Defense Technical Information Center, January 2008. http://dx.doi.org/10.21236/ada491876.

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Lansky, Amy L. A Representation of Parallel Activity Based on Events, Structure, and Causality. Fort Belvoir, VA: Defense Technical Information Center, December 1986. http://dx.doi.org/10.21236/ada461769.

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Currie, A., and B. Ady. GEOSIS project: knowledge representation and data structures for geoscience data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128053.

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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, May 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.
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Yager, Ronald R. The Development of Structure for the Representation and Manipulation of Sophisticated Knowledge in Intelligent Systems. Fort Belvoir, VA: Defense Technical Information Center, March 1990. http://dx.doi.org/10.21236/ada229114.

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Chervinchuk, Alina. THE CONCEPT OF ENEMY: REPRESENTATION IN THE UKRAINIAN MILITARY DOCUMENTARIES. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11063.

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Research methodology. The following methods were used in this research: general scientific methods (descriptive, analysis, synthesis, comparison) and special (structural, hermeneutic, narrative, method of content analysis). We identified words related to the concept of the enemy and determined the context in which they are used by the authors of the collections Results. The formats of reflection of military reality in collections of military documentaries are investigated. It is emphasized that the authors-observers of events as professional communicators form a vision of events based on categories understandable to the audience – «own» and «others». Instead, the authors-participants go events have more creative space and pay more attention to their own emotional state and reflections. It is defined how the enemy is depicted and what place he occupies in the military reality represented by the authors. It is emphasized that the authors reflect the enemy in different ways. In particular, the authors-observers of the events tried to form a comprehensive vision of the events, and therefore paid much attention to the opposite side of the military conflict. Authors-participants of the events tend to show the enemy as a mass to be opposed. In such collections, the enemy is specified only in the presence of evidence confirming the presence of Russians or militants. Novelty. The research for the first time investigates the methods of representation of mi­litary activity in the collections of Ukrainian military documentaries. The article is devoted to the analysis of how the authors represent the enemy. Practical importance. The analysis of collections of military documentaries will allow to study the phenomenon of war and to trace the peculiarities of the authors’ representation of military reality.
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Jerzykiewicz, T., and M. Labonte. Representation and Statistical Analysis of Directional Sedimentary Structures in the Uppermost Cretaceous - Paleocene of the Alberta Foreland Basin. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1991. http://dx.doi.org/10.4095/132546.

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