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1

Starr, I. M. "Multidimensional relativity." Thesis, University of Leeds, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.235269.

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2

García, Díaz Rocío. "Multidimensional poverty." Thesis, University of York, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.437569.

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3

Colthurst, Thomas. "Multidimensional wavelets." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43934.

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4

Tybusch, Jerônimo Siqueira. "Sustentabilidade multidimensional." Florianópolis, 2011. http://repositorio.ufsc.br/handle/123456789/103349.

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Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Filosofia e Ciências Humanas. Programa de Pós-Graduação Interdisciplinar em Ciências Humanas
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A abordagem de observação dessa tese de doutoramento tem o enfoque nitidamente interdisciplinar, comunicando percepções diferenciadas de fenômenos econômicos, políticos, tecnológicos e jurídicos para compreensão da questão ambiental na atualidade. O objetivo principal concentra-se em compreender a Sustentabilidade Multidimensional como condição de possibilidade para uma proposta reflexiva na produção da Técnica Jurídico-Ambiental. Neste sentido, a abordagem que produz comunicações entre o direito e a economia, acoplando-os às temáticas da Ecologia, Sociedade Moderna e Política implicam, como característica peculiar da pesquisa em Ciências Humanas,uma direta relação com o sujeito e suas diversidades no que concerne à percepção da comunicação ecológica. A perspectiva amplia-se também para o estudo da produção discursiva referente à racionalidade econômica, ao modelo do Homo Oeconomicus, frente aos desafios ecológicos, bem como a produção da técnica e discursos da governamentalidade em relação ao meio ambiente. Assim, a presente proposta congrega o estudo das transformações ecológicas e sua percepção pela técnica jurídico-ambiental em sua direta relação com a composição das singularidades individuais e coletivas frente às modificações na política, técnica e percepções da cena ecológica (problemática ambiental). Nesta perspectiva, compreende-se que existe uma maior influência do saber e poder econômicos na questão ambiental. Ou seja, as práticas discursivas, no que tangem a questão ambiental, partem, na realidade das políticas públicas, de orientações desenvolvimentistas, resultando em ações que operam a partir de uma lógica de custo e benefício ou de um código valor/não-valor para, em um segundo momento, tentar adequá-las na perspectiva da sustentabilidade. Tal análise demonstra a histórica dificuldade metodológica na aplicabilidade do conceito de desenvolvimento sustentável para salvaguarda do meio ambiente, bem como na formulação de uma técnica jurídico-ambiental capaz de perceber e incorporar, na sua elaboração e aplicação, as diferentes dimensões da sustentabilidade. A metodologia e estratégia de ação para viabilizar essa tese orientaram-se pelo trinômio: Teoria de Base; Procedimento e Técnica. Os elementos trabalhados interpenetram-se em uma relação sistêmico-complexa para configuração de um método que permita uma abordagem de pesquisa interdisciplinar e em sinergia com as diferentes áreas do conhecimento: Ciências Exatas, Sociais Aplicadas e Ciências Humanas. O trabalho teve como referencial teórico a matriz epistemológica pragmático-sistêmica, que permite um enfoque complexo e interdisciplinar acerca do tema proposto. Como A Sustentabilidade Multidimensional obedece a três pilares para sua possibilidade de aplicação: 1) A compreensão da necessidade de Politizar as Novas Tecnologias; 2) A observação de uma Epistemologia Ambiental Complexa e 3) A percepção das perspectivas do Sócio-Ambientalismo e da Sóciobiodiversidade. A comunicação entre estes elementos conferem um caráter multidimensional ao conceito de Sustentabilidade, permitindo, ao sistema do direito, no caso de estar aberto a esta perspectiva, uma atitude reflexiva frente às suas técnicas tradicionais de decisão.
The approach of looking at the doctoral thesis is clearly interdisciplinary approach, communicating different perceptions of economic phenomena, political, technological and legal means to understanding the environmental issue today. The main objective focuses on understanding the Multidimensional Sustainability as a condition of possibility for a proposal reflecting the production of Technical and Environmental Law. In this sense, the approach that produces communications between law and economics, engaging them to the themes of ecology, Modern Society and Politics involve a peculiar characteristic of social science research, a direct relationship to the subject and their diversity with regard to perception of ecological communication. The prospect also extends to the study of discourse production on the economic rationality, the model of homo economicus, to the ecological challenges ahead, as well as production technique and discourses of governmentality in relation to the environment. Thus, this proposal brings together the study of ecological changes and their perception by the legal and technical environment in its direct relation to the composition of individual and collective singularities in the face of changes in policy, technical and ecological perceptions of the scene (environmental issues). In this perspective, it is understood that there is a greater influence of knowledge and economic power in environmental issues. In other words, the discursive practices in environmental issues that concern, they depart, the reality of public policy, developmental guidance, resulting in actions that operate from a logic of cost-benefit or value from a code / no-value for in a second time, trying to fit them all in the perspective of sustainability. This historical analysis demonstrates the methodological difficulty in the applicability of the concept of sustainable development to safeguard the environment and the formulation of an environmental legal and technical ability to perceive and incorporate in its design and implementation, the various dimensions of sustainability. The methodology and strategy for action to make this thesis were guided by the trinomial: Base Theory, Procedure and Technique. The elements worked interpenetrate in a complex relationship to systemic-setting up a method that allows an interdisciplinary research approach and in synergy with the different areas of knowledge: Exact Sciences, Applied Social and Human Sciences. The work has a theoretical to pragmatic-systemic epistemology, which allows a complex interdisciplinary focus on the theme proposed. How Sustainability has three pillars Multidimensional its possible application to: 1) Understanding the need to politicize the New Technologies, 2) the observation of a Complex Environmental Epistemology and 3) The perception of the prospects for socio-environmental and socio-biodiversity. Communication between these elements give a multidimensional nature to the concept of sustainability, allowing the system of law, should be open to this perspective, a reflective front of their traditional techniques of decision.
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5

Haglund, Leif. "Adaptive Multidimensional Filtering." Doctoral thesis, Linköpings universitet, Bildbehandling, 1991. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54339.

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This thesis contains a presentation and an analysis of adaptive filtering strategies for multidimensional data. The size, shape and orientation of the flter are signal controlled and thus adapted locally to each neighbourhood according to a predefined model. The filter is constructed as a linear weighting of fixed oriented bandpass filters having the same shape but different orientations. The adaptive filtering methods have been tested on both real data and synthesized test data in 2D, e.g. still images, 3D, e.g. image sequences or volumes, with good results. In 4D, e.g. volume sequences, the algorithm is given in its mathematical form. The weighting coefficients are given by the inner products of a tensor representing the local structure of the data and the tensors representing the orientation of the filters. The procedure and lter design in estimating the representation tensor are described. In 2D, the tensor contains information about the local energy, the optimal orientation and a certainty of the orientation. In 3D, the information in the tensor is the energy, the normal to the best ftting local plane and the tangent to the best fitting line, and certainties of these orientations. In the case of time sequences, a quantitative comparison of the proposed method and other (optical flow) algorithms is presented. The estimation of control information is made in different scales. There are two main reasons for this. A single filter has a particular limited pass band which may or may not be tuned to the different sized objects to describe. Second, size or scale is a descriptive feature in its own right. All of this requires the integration of measurements from different scales. The increasing interest in wavelet theory supports the idea that a multiresolution approach is necessary. Hence the resulting adaptive filter will adapt also in size and to different orientations in different scales.
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6

Schlachter, Simon Christopher. "Quantitative multidimensional microscopy." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609221.

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7

Vorland, Corey. "Multidimensional Toggle Dynamics." Diss., North Dakota State University, 2018. https://hdl.handle.net/10365/28766.

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J. Propp and T. Roby isolated a phenomenon in which a statistic on a set has the same average value over any orbit as its global average, naming it homomesy. One set they investigated was order ideals of partially ordered sets (posets). They proved that the cardinality statistic on order ideals of the product of two chains poset under rowmotion or promotion exhibits homomesy. We prove an analogous result in the case of the product of three chains where one chain has two elements. In order to prove this result, we generalize from two to n dimensions the recombination technique that D. Einstein and Propp developed to study homomesy. We see that our main homomesy result does not fully generalize to an arbitrary product of three chains, nor to larger products of chains; however, we have a partial generalization to an arbitrary product of three chains. Additional corollaries include refined homomesy results in the product of three chains and a new result on increasing tableaux. We also generalize recombination to any ranked poset and from this, obtain a homomesy result for a type B minuscule poset cross a two-element chain. We conclude by extending the definition of promotion to infinite posets, exploring homomesy, recombination, and a connection to monomial ideals.
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8

Boquet, Grant Michael. "Multidimensional Behavioral Complexes." Thesis, Virginia Tech, 2008. http://hdl.handle.net/10919/31528.

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In a preprint by J. Wood, V. Lomadze, and E. Rogers, chains and boundary maps were defined for 2-D discrete behavioral systems. The corresponding homology groups were studied and tied to trajectory properties. Indeed, the homology groups encapsulated the concepts of autonomy, controllability, and signal restriction. We shall present an extension of their work to n-D discrete behavioral systems. In particular, we shall streamline the construction of the chain groups, the boundary maps between chains, and the study of the resultant homology groups. While constructing this machinery, we shall point out intrinsic flaws in their approach that make extension of their results less systematic. Finishing remarks shall be made on using the homology groups to determine system properties and potentially classify forms of controllability.
Master of Science
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9

Martins, Rafael Messias. "Explanatory visualization of multidimensional prejections." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-30092016-133421/.

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Visual analytics tools play an important role in the scenario of big data solutions, combining data analysis and interactive visualization techniques in effective ways to support the incremental exploration of large data collections from a wide range of domains. One particular challenge for visual analytics is the analysis of multidimensional datasets, which consist of many observations, each being described by a large number of dimensions, or attributes. Finding and understanding data-related patterns present in such spaces, such as trends, correlations, groups of related observations, and outliers, is hard. Dimensionality reduction methods, or projections, can be used to construct low (two or three) dimensional representations of high-dimensional datasets. The resulting representation can then be used as a proxy for the visual interpretation of the high-dimensional space to efficiently and effectively support the above-mentioned data analysis tasks. Projections have important advantages over other visualization techniques for multidimensional data, such as visual scalability, high degree of robustness to noise and low computational complexity. However, a major obstacle to the effective practical usage of projections relates to their difficult interpretation. Two main types of interpretation challenges for projections are studied in this thesis. First, while projection techniques aim to preserve the so-called structure of the original dataset in the final produced layout, and effectively achieve the proxy effect mentioned earlier, they may introduce a certain amount of errors that influence the interpretation of their results. However, it is hard to convey to users where such errors occur in the projection, how large they are, and which specific data-interpretation aspects they affect. Secondly, interpreting the visual patterns that appear in the projection space is far from trivial, beyond the projections ability to show groups of similar observations. In particular, it is hard to explain these patterns in terms of the meaning of the original data dimensions. In this thesis we focus on the design and development of novel visual explanatory techniques to address the two interpretation challenges of multidimensional projections outlined above. We propose several methods to quantify, classify, and visually represent several types of projection errors, and how their explicit depiction helps interpreting data patterns. Next we show how projections can be visually explained in terms of the highdimensional data attributes, both in a global and a local way. Our proposals are designed to be easily added, and used with, any projection technique, and in any application context using such techniques. Their added value is demonstrated by presenting several exploration scenarios involving various types of multidimensional datasets, ranging from measurements, scientific simulations, software quality metrics, software system structure, and networks.
Ferramentas de análise visual desempenham um papel importante no cenário de soluções para grandes volumes de dados (big data), combinando análise de dados e técnicas interativas de visualização de forma eficaz para apoiar a exploração incremental de coleções de dados em diversos domínios. Um desafio importante em análise visual é a exploração de conjuntos de dados multidimensionais, que consistem em muitas observações, sendo cada uma descrita por um grande número de dimensões, ou atributos. Encontrar e compreender os padrões presentes em tais espaços, tais como tendências, correlações, grupos de observações relacionadas e valores extremos, é difícil. Técnicas de redução de dimensionalidade ou projeções são utilizadas para construir, a partir de conjuntos de dados multidimensionais, representações de duas ou três dimensões que podem então ser utilizadas com substitutas do espaço original para sua interpretação visual, apoiando de forma eficiente as tarefas de análise de dados acima mencionadas. Projeções apresentam vantagens importantes sobre outras técnicas de visualização para dados multidimensionais, tais como escalabilidade visual, resistência a ruídos e baixa complexidade computacional. No entanto, um grande obstáculo para o uso prático de projeções vem da sua difícil interpretação. Dois principais tipos de desafios de interpretação de projeções são estudados nesta tese. Em primeiro lugar, mesmo que as técnicas de projeção tenham como objetivo preservar, na representação final, a estrutura do conjunto de dados original, elas podem introduzir uma certa quantidade de erros que influenciam a interpretação dos seus resultados. No entanto, é difícil transmitir aos usuários onde tais erros ocorrem na projeção, quão severos eles são e que aspectos específicos da interpretação dos dados eles afetam. Em segundo lugar, interpretar os padrões visuais que aparecem em uma projeção, além da percepção de grupos de observações semelhantes, está longe de ser trivial. Em particular, é difícil explicar tais padrões em termos do significado das dimensões dos dados originais. O trabalho desenvolvido nesta tese concentra-se no projeto e desenvolvimento de novas técnicas visuais explicativas para lidar com os dois desafios de interpretação de projeções multidimensionais descritos acima. São propostos alguns métodos para quantificar, classificar e representar visualmente diversos tipos de erros de projeção, e é descrito como essas representações explícitas ajudam na interpretação dos padrões dos dados. Além disso, também são propostas técnicas visuais para explicar projeções em termos dos atributos dos dados multidimensionais, tanto de forma global quanto local. As propostas apresentadas foram concebidas para serem facilmente incorporadas e usadas com qualquer técnica de projeção e em qualquer contexto de aplicação. As contribuições são demonstradas pela apresentação de vários cenários de exploração, envolvendo vários tipos de conjuntos de dados multidimensionais, desde medições e simulações científicas até métricas de qualidade de software, estruturas de sistema de software e redes.
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10

Zheglov, Alexander. "Multidimensional local skew-fields." Doctoral thesis, [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=965411923.

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11

King, Gregory B. (Gregory Blaine). "Explicit Multidimensional Solitary Waves." Thesis, University of North Texas, 1990. https://digital.library.unt.edu/ark:/67531/metadc504381/.

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In this paper we construct explicit examples of solutions to certain nonlinear wave equations. These semilinear equations are the simplest equations known to possess localized solitary waves in more that one spatial dimension. We construct explicit localized standing wave solutions, which generate multidimensional localized traveling solitary waves under the action of velocity boosts. We study the case of two spatial dimensions and a piecewise-linear nonlinearity. We obtain a large subset of the infinite family of standing waves, and we exhibit several interesting features of the family. Our solutions include solitary waves that carry nonzero angular momenta in their rest frames. The spatial profiles of these solutions also furnish examples of symmetry breaking for nonlinear elliptic equations.
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12

Karoui, Abderrazek. "Multidimensional wavelets and applications." Thesis, University of Ottawa (Canada), 1995. http://hdl.handle.net/10393/9492.

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In this thesis, one- as well as multi-dimensional biorthogonal wavelet filters are designed and used for the construction of compactly supported wavelet bases. In particular, an adaptation of the McClellan transformation is used to design nonseparable 2-D biorthogonal wavelet bases. Some examples of 2-D biorthogonal wavelet filters are given in the case of the quincunx sampling lattice. Some theoretical and technical results known in the one-dimensional case have been generalized to the n-dimensional case. This generalization leads to a better understanding of the theory and design of multidimensional biorthogonal wavelets. An important part of the thesis devoted to the design of fast discrete wavelet transforms. The main ingredient of the algorithms is the use of a one-point quadrature formula for approximating the nest coefficients of the signals together with a suitable design and implementation of symmetric biorthogonal filters. Special attention is given to the case where the signals have sharp transition points. In this case, a smoothing process has been used to obtain an accurate reconstruction of the signal.
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13

Borga, Magnus. "Learning Multidimensional Signal Processing." Doctoral thesis, Linköpings universitet, Bildbehandling, 1998. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54341.

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The subject of this dissertation is to show how learning can be used for multidimensional signal processing, in particular computer vision. Learning is a wide concept, but it can generally be defined as a system’s change of behaviour in order to improve its performance in some sense. Learning systems can be divided into three classes: supervised learning, reinforcement learning and unsupervised learning. Supervised learning requires a set of training data with correct answers and can be seen as a kind of function approximation. A reinforcement learning system does not require a set of answers. It learns by maximizing a scalar feedback signal indicating the system’s performance. Unsupervised learning can be seen as a way of finding a good representation of the input signals according to a given criterion. In learning and signal processing, the choice of signal representation is a central issue. For high-dimensional signals, dimensionality reduction is often necessary. It is then important not to discard useful information. For this reason, learning methods based on maximizing mutual information are particularly interesting. A properly chosen data representation allows local linear models to be used in learning systems. Such models have the advantage of having a small number of parameters and can for this reason be estimated by using relatively few samples. An interesting method that can be used to estimate local linear models is canonical correlation analysis (CCA). CCA is strongly related to mutual information. The relation between CCA and three other linear methods is discussed. These methods are principal component analysis (PCA), partial least squares (PLS) and multivariate linear regression (MLR). An iterative method for CCA, PCA, PLS and MLR, in particular low-rank versions of these methods, is presented. A novel method for learning filters for multidimensional signal processing using CCA is presented. By showing the system signals in pairs, the filters can be adapted to detect certain features and to be invariant to others. A new method for local orientation estimation has been developed using this principle. This method is significantly less sensitive to noise than previously used methods. Finally, a novel stereo algorithm is presented. This algorithm uses CCA and phase analysis to detect the disparity in stereo images. The algorithm adapts filters in each local neighbourhood of the image in a way which maximizes the correlation between the filtered images. The adapted filters are then analysed to find the disparity. This is done by a simple phase analysis of the scalar product of the filters. The algorithm can even handle cases where the images have different scales. The algorithm can also handle depth discontinuities and give multiple depth estimates for semi-transparent images.
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Scolamiero, Martina. "Invariants for Multidimensional Persistence." Doctoral thesis, KTH, Matematik (Avd.), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-167644.

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The amount of data that our digital society collects is unprecedented. This represents a valuable opportunity to improve our quality of life by gaining insights about complex problems related to neuroscience, medicine and biology among others. Topological methods, in combination with classical statistical ones, have proven to be a precious resource in understanding and visualizing data. Multidimensional persistence is a method in topological data analysis which allows a multi-parameter analysis of a dataset through an algebraic object called multidimensional persistence module. Multidimensional persistence modules are complicated and contain a lot of information about the input data. This thesis deals with the problem of algorithmically describing multidimensional persistence modules and extracting information that can be used in applications. The information we extract, through invariants, should not only be efficiently computable and informative but also robust to noise. In Paper A we describe in an explicit and algorithmic way multidimensional persistence modules. This is achieved by studying the multifiltration of simplicial complexes defining multidimensional persistence modules. In particular we identify the special structure underlying the modules of n-chains of such multifiltration and exploit it to write multidimensional persistence modules as the homology of a chain complex of free modules. Both the free modules and the homogeneous matrices in such chain complex can be directly read off the multifiltration of simplicial complexes. Paper B deals with identifying stable invariants for multidimensional persistence. We introduce an algebraic notion of noise and use it to compare multidimensional persistence modules. Such definition allows not only to specify the properties of a dataset we want to study but also what should be neglected. By disregarding noise the, so called, persistent features are identified. We also propose a stable discrete invariant which collects properties of persistent features in a multidimensional persistence module.

QC 20150525

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Rozenes, Shai. "Multidimensional project control system." Thesis, Coventry University, 2004. http://curve.coventry.ac.uk/open/items/462120e8-7a38-a662-149a-8d8320ba4cf4/1.

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Project control systems often fail to support management in achieving their global project goals. This thesis proposes a Multidimensional Project Control System (MPCS) as an approach for quantifying deviations from the planning phase to the execution phase with respect to the global project control specification (GPCS). The projects' current state must be translated into yield terms, which are expressed as a gap vector that represents the multidimensional deviation from the global project control specification. The MPCS methodology allows the project manager to determine: integrated project status; where problems exist in the project; when and where to take corrective action; and how to measure improvement. However, implementing the MPCS methodology does not require extra data collation. MPCS deals with the control of a single project and defines the project performances in comparison with the plan. The progression of several projects in parallel is a common situation in organizations, therefore a comparison of the various project performances is required. It is proposed that a comparison process be performed using the data envelope analysis (DEA) approach. The reference points for examining the performances of different projects and the directions of improvement for the projects are not necessarily found on the efficiency frontier. An algorithm is developed for applying multi-project system control having a relatively large number of inputs and outputs while maintaining the validity of the DEA methodology. The DEA output allows the diagnosis of those found on the efficiency frontier and those that need improvement.
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Welch, John. "Multidimensional in vivo NMR." Thesis, University of Oxford, 2001. http://ora.ox.ac.uk/objects/uuid:876ed795-9e23-4d53-a407-0a29f7c9ea21.

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A proton nuclear magnetic resonance spectrum of the brain in vivo contains peaks from every proton-containing molecule in the brain. Sensitivity limitations mean that only those molecules present at concentrations of at least a few millimolar are detectable in a reasonable period of time; this still leaves many important molecules such as amino acids and other small metabolites. Most of their resonance frequencies fall in the region between 1.0 and 4.5 p.p.m. A typical linewidth in vivo is about 0.05 p.p.m., so the number of distinct peaks observable is restricted. The use of two-dimensional NMR techniques such as COSY can spread peaks out into a second dimension enabling otherwise overlapping peaks to be resolved. This thesis describes the development, testing and application of two such 2D NMR pulse sequences, dubbed ISIS-COSY and ISIS-JRES. They are based on an existing magnetisation localisation sequence and excite detected magnetisation in a manner analogous to the high-resolution sequences COSY and 2D J-resolved spectroscopy. A method for quantifying the metabolites visible in an ISIS-COSY spectrum from their cross-peak intensities is described, and results presented from both control rat brains and those of animals treated with vigabatrin, an inhibitor of GABA-transaminase that has the effect of increasing brain γ-amino butyric acid (GABA) levels. Further applications mentioned are in the study of neutrophil-infiltrated rat brain and adaptation of the ISIS-COSY technique for human use.
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Braumann, Andreas. "Multidimensional modelling of granulation." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609355.

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18

Gäfvert, Oliver. "Algorithms for Multidimensional Persistence." Thesis, KTH, Matematik (Avd.), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-188849.

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The theory of multidimensional persistence was introduced in a paper by G. Carlsson and A. Zomorodian as an extension to persistent homology. The central object in multidimensional persistence is the persistence module, which represents the homology of a multi filtered space. In this thesis, a novel algorithm for computing the persistence module is described in the case where the homology is computed with coefficients in a field. An algorithm for computing the feature counting invariant, introduced by Chachólski et al., is investigated. It is shown that its computation is in general NP-hard, but some special cases for which it can be computed efficiently are presented. In addition, a generalization of the barcode for persistent homology is defined and conditions for when it can be constructed uniquely are studied. Finally, a new topology is investigated, defined for fields of characteristic zero which, via the feature counting invariant, leads to a unique denoising of a tame and compact functor.
Teorin om multidimensionell persistens introduserades i en artikel av G. Carlsson och A. Zomorodian som en generalisering av persistent homologi. Det centrala objektet i multidimensionell persistens är persistensmodulen, som representerar homologin av ett multifilterat rum. I denna uppsats beskrivs en ny algoritm för beräkning av persistensmodulen i fallet där homologin beräknas med koefficienter i en kropp. En algoritm för beräkning av karaktäristik-räknings-invarianten, som introducerade av Chachólski et al., utforskas och det visar sig att dess beräkning i allmänhet är NP-svår. Några specialfall för vilka den kan beräknas effektivt presenteras. Vidare definieras en generalisering av stäckkoden för persistent homologi och kraven för när den kan konstrueras unikt studeras. Slutligen undersöks en ny topologi, definierad för kroppar av karaktäristik noll, som via karaktäristik-räknings-invarianten leder till en unik avbränning.
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Fadel, Samuel Gomes. "Understanding interactive multidimensional projections." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-16012017-095849/.

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The large amount of available data on a diverse range of human activities provides many opportunities for understanding, improving and revealing unknown patterns in them. Powerful automatic methods for extracting this knowledge from data are already available from machine learning and data mining. They, however, rely on the expertise of analysts to improve their results when those are not satisfactory. In this context, interactive multidimensional projections are a useful tool for the analysis of multidimensional data by revealing their underlying structure while allowing the user to manipulate the results to provide further insight into this structure. This manipulation, however, has received little attention regarding their influence on the mappings, as they can change the final layout in unpredictable ways. This is the main motivation for this research: understanding the effects caused by changes in these mappings. We approach this problem from two perspectives. First, the user perspective, we designed and developed visualizations that help reduce the trial and error in this process by providing the right piece of information for performing manipulations. Furthermore, these visualizations help explain the changes in the map caused by such manipulations. Second, we defined the effectiveness of manipulation in quantitative terms, then developed an experimental framework for assessing manipulations in multidimensional projections under this view. This framework is based on improving mappings using known evaluation measures for these techniques. Using the improvement of measures as different types of manipulations, we perform a series of experiments on five datasets, five measures, and four techniques. Our experimental results show that there are possible types of manipulations that can happen effectively, with some techniques being more susceptible to manipulations than others.
O grande volume de dados disponíveis em uma diversa gama de atividades humanas cria várias oportunidades para entendermos, melhorarmos e revelarmos padrões previamente desconhecidos em tais atividades. Métodos automáticos para extrair esses conhecimentos a partir de dados já existem em áreas como aprendizado de máquina e mineração de dados. Entretanto, eles dependem da perícia do analista para obter melhores resultados quando estes não são satisfatórios. Neste contexto, técnicas de projeção multidimensional interativas são uma ferramenta útil para a análise de dados multidimensionais, revelando sua estrutura subjacente ao mesmo tempo que permite ao analista manipular os resultados interativamente, estendendo o processo de exploração. Essa interação, entretanto, não foi estudada com profundidade com respeito à sua real influência nos mapeamentos, já que podem causar mudanças não esperadas no mapeamento final. Essa é a principal motivação desta pesquisa: entender os efeitos causados pelas mudanças em tais mapeamentos. Abordamos o problema de duas perspectivas. Primeiro, da perspectiva do usuário, desenvolvemos visualizações que ajudam a diminuir tentativas e erros neste processo provendo a informação necessária a cada passo da interação. Além disso, essas visualizações ajudam a explicar as mudanças causadas no mapeamento pela manipulação. A segunda perspectiva é a efetividade da manipulação. Definimos de forma quantitativa a efetividade da manipulação, e então desenvolvemos um arcabouço para avaliar manipulações sob a visão da efetividade. Este arcabouço é baseado em melhorias nos mapeamentos usando medidas de avaliação conhecidas para tais técnicas. Usando tais melhorias como diferentes formas de manipulação, realizamos uma série de experimentos em cinco bases de dados, cinco medidas e quatro técnicas. Nossos resultados experimentais nos dão evidências que existem certos tipos de manipulação que podem acontecer efetivamente, com algumas técnicas sendo mais suscetíveis a manipulações do que outras.
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20

Abade, Maíra Coelho. "Cálculo mecânico quântico multidimensional." reponame:Repositório Institucional da UnB, 2007. http://repositorio.unb.br/handle/10482/2702.

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Dissertação (mestrado)—Universidade de Brasília, Instituto de Física, 2007.
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Neste trabalho serão apresentadas metodologias numéricas para o estudo da dinâmica dos núcleos de uma molécula. Utilizando a aproximação adiabática de Born-Oppenheimer, é possível estudar, como uma boa aproximação, o movimento dos elétrons e dos núcleos de uma molécula, separadamente. Utilizando o método variacional, que funciona como uma ponte entre a mecânica ondulatória e a mecânica matricial, é possível tratar a equação de Schrödinger nuclear numericamente. As metodologias estudadas, que têm como objetivo tornar viável o cálculo de sistemas com muitas dimensões, foram testadas para potenciais unidimensionais e bidimensionais, largamente conhecidos na literatura. _______________________________________________________________________________________ ABSTRACT
In this work, will be presented numerical methods for the study of the nuclear dynamic of a molecule. Using the Born-Oppenheimer approximation is possible to study, as a good approach, the movement of electrons and the nuclei, separately. Using the variacional method, that provides a bridge frow wave mechanics to matrix mechanics, is possible to deal with the nuclear Schrodinger equation numerically. The methods and the performance of the programs are examined in one two-dimensional potentials, well Know in the literature.
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21

Thokala, Kalyan Chakravarthy. "Haptic Enabled Multidimensional Canvas." University of Akron / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=akron1312424725.

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22

Terwilleger, Erin. "Multidimensional time-frequency analysis /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3052223.

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23

Terry, Justin. "Indexing Multidimensional Point Data." Thesis, Griffith University, 2010. http://hdl.handle.net/10072/365419.

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In current database applications there is a large and growing amount of multidimensional data that is not well supported. Modern database applications are turning more often to multidimensional data for a more sophisticated representation and reasoning of their universe. The amount of data collected, processed and stored continues to grow as new technologies emerge. Even relational data can be seen to be multidimensional as each attribute corresponds to a dimension. Despite the large and growing data sets, multidimensional data is not well supported above low dimensionality and there is no index available in current commercial RDBMS that can scale up well beyond low dimensionality. A major problem with multidimensional data is that it has no true order. Space filling curves are an elegant solution to organizing multidimensional space. In this work we adapt and further develop this concept further to create a curve that connects all regions in space and the regions can be of various hyper-cubic-like sizes, not just points. This allows an efficient transformation of interval queries into regions of physically clustered data. We therefore present the Variable Granularity Curve (VG-Curve), a symmetrical index for multidimensional points, spatially extended objects and general database relations. We show that our method is applicable to a variety of multidimensional database applications. The method is immediately able to be constructed within current commercial database systems and thus inherits industrial strength concurrency and recovery services. The main contributions of this study are summarized as follows: • We propose a novel twist on indexing that allows improved support for multidimensional point data. Our method ensures an efficient clustering of multidimensional data that allows for primary index style storage and utilizes a two stage filtering that efficiently prunes the search space. In an extensive empirical study on up to 18 dimensions we show that the VG-Curve represents a significant improvement over the currently available access methods for managing multidimensional point data, and scales well with an increasing number of dimensions (Terry, Stantic & Sattar 2008). In addition we also investigate the applicability of the proposed method to manage spatially extended data, identifying its suitability to index both interval and point attributes together. • We show that the VC-curve can be effectively and efficiently applied to the emerging technology of Radio Frequency Identification (RFID) that generates huge amounts of spatio-temporal data. We show empirically, on data sets of three, five and nine dimensional data, that our method is an efficient replacement for the best of currently available off-the-shelf index methods, i.e, the set of compound indices representing all combinations of dimensions.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Institute for Integrated and Intelligent Systems
Science, Environment, Engineering and Technology
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24

Col, Júnior Alcebíades Dal. "Métodos de Projeção Multidimensional." Universidade Federal do Espírito Santo, 2013. http://repositorio.ufes.br/handle/10/6469.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
O problema que estamos interessados em resolver provém de uma área do conhecimento denominada visualização de dados. Nos nossos estudos, grupos de objetos são analisados para produzir os dados de entrada do nosso problema, cada um dos objetos é representado por atributos, temos assim uma lista de atributos para cada objeto. A ideia é representar, através dessas listas de atributos, os objetos através de pontos em R2 para que possamos realizar um estudo do grupo de objetos. Como dissemos cada objeto é representado por uma lista de atributos, esta pode ser interpretada como um ponto de um espaço multidimensional. Por exemplo, se são considerados m atributos valorados para todos os objetos podemos interpretá-los como sendo pontos de um espaço de imensão m, ou m dimensional. Mas, queremos produzir uma visualização dos dados na tela do computador através de pontos em R2, realiza-se então um processo conhecido como projeção multidimensional, que é a obtenção de pontos em um espaço de baixa dimensão que represente pontos de um espaço de alta dimensão preservando relações de vizinhaça tanto quanto possível. Diversos métodos de projeção multidimensional são encontrados na literatura. Neste trabalho, estudamos e implementamos os métodos NNP, Force, LSP, PLP e LAMP. Estes métodos abordam o problema de diferentes formas: geometricamente; sistemas lineares, em particular, sistemas laplacianos; e mapeamentos ortogonais afins. As listas de atributos associadas aos grupos de objetos recebem o nome de conjuntos de dados. Dois dos conjuntos de dados abordados neste trabalho apresentam tendências de agrupamento conhecidas a priori, portanto foram utilizados para dar credibilidade as nossas implementações dos métodos. Outros dois conjuntos de dados são estudados e esses não eram dotados de tal característica, os métodos de projeção multidimensional são então utilizados para definir tendências de agrupamento para esses dois conjuntos de dados OBS: Os Gráficos de dispersão das projeções dos conjuntos de dados Iris, Wine, Housing (de cima para baixo) através dos métodos NNP, Force, LSP, PLP e LAMP (da esquerda para a direita) não foram anexados por terem mais de 2 KB, excedendo o limite do site.
The problem we are interested in solving comes from a area of knowledge called data visualization. In our studies, groups of objects are analyzed to produce the input data of our problem, each object is represented by attributes, have so a list of attributes for each object. The idea is to represent, through these lists of attributes, objects through points in R2 so that we can conduct a group of objects. As we said each object is represented by a list of attributes, this may be interpreted as a point of a multidimensional space. For example, if they are considered m valued attributes for all objects can interpret them as points in a space of dimension m, or m-dimensional. But we want to produce a visualization of the data on the computer screen through points in R2, it was then performs a process known as multidimensional projection, that is obtaining points in a low dimensional space representing points in a high dimensional space preserving neighborhood relations as much as possible. Various methods of multidimensional projection are found in the literature. In this work, study and implement methods NNP, Force, LSP, PLP and LAMP. These methods deal with the problem in different ways: geometrically; linear systems, in particular, laplacian systems; and mappings related orthogonal. The lists of attributes associated with the groups of objects are called dataset. Two sets of data in this paper present trends grouping known a priori, therefore were used to give credibility to our implementations of the methods. Two other data set are studied and these were not provided with such feature, the methods of multidimensional projection are then used to define trends grouping for these two data sets
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25

Silva, Renato Rodrigues Oliveira da. "Visualizing multidimensional data similarities: improvements and applications." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-15022017-162359/.

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Multidimensional datasetsare increasingly more prominent and important in data science and many application domains. Such datasets typically consist of a large set of observations, or data points, each which is described by several measurements, or dimensions. During the design of techniques and tools to process such datasets, a key component is to gather insights into their structure and patterns, a goal which is targeted by multidimensional visualization methods. Structures and patterns of high-dimensional data can be described, at a core level, by the notion of similarity of observations. Hence, to visualize such patterns, we need effective and efficient ways to depict similarity relations between a large number of observations, each having a potentially large number of dimensions. Within the realm of multidimensional visualization methods, two classes of techniques exist projections and similarity trees which effectively capture similarity patterns and also scale well to the number of observations and dimensions of the data. However, while such techniques show similarity patterns, understanding and interpreting these patterns in terms of the original data dimensions is still hard. This thesis addresses the development of visual explanatory techniques for the easy interpretation of similarity patterns present in multidimensional projections and similarity trees, by several contributions. First, we proposemethodsthat make the computation of similarity treesefficient for large datasets, and also allow their visual explanation on a multiscale, or several levels of detail. We also propose ways to construct simplified representations of similarity trees, thereby extending their visual scalability even further. Secondly, we propose methods for the visual explanation of multidimensional projections in terms of automatically detected groups of related observations which are also automatically annotated in terms of their similarity in the high-dimensional data space. We show next how these explanatory mechanismscan be adapted to handle both static and time-dependent multidimensional datasets. Our proposed techniques are designed to be easy to use, work nearly automatically, handle any typesof quantitativemultidimensional datasets and multidimensional projection techniques, and are demonstrated on a variety of real-world large datasets obtained from image collections, text archives, scientific measurements, and software engineeering.
Conjuntos de dados multidimensionais são cada vez mais proeminentes e importantes em data science e muitos domínios de aplicação. Esses conjuntos de dados são tipicamente constituídos de um grande número de observações, ou objetos, cada qual descrito por várias medidas, ou dimensões. Durante o projeto de técnicas e ferramentas para processar tais dados, um dos focos principais é prover meios para análise e levantamento de hipóteses a partir das principais estruturas e padrões. Esse objetivo é perseguido por métodos de visualização multidimensional. Estruturas e padrões em dados multidimensionais podem ser descritos, em linhas gerais, pela noção de similaridade das observações. Portanto, para visualizar esses padrões, precisamos de meios efetivos e eficientes para retratar relações de similaridade dentre um grande número de observações, que potencialmente possuem um grande número de dimensões cada. No contexto dos métodos de visualização multidimensional, existem duas categorias de técnicas projeções e árvores de similaridade que efetivamente capturam padrões de similaridade e oferecem boa escalabilidade, tanto para o número de observações e quanto de dimensões. No entanto, embora essas técnicas exibam padrões de similaridade, o entendimento e interpretação desses padrões, em termos das dimensões originais dos dados, ainda é difícil. O trabalho desenvolvido nessa tese visa o desenvolvimento de técnicas explicativas para a fácil interpretação de padrões de similaridade presentes em projeções multidimensionais e árvores de similaridade. Primeiro, propomos métodos que possibilitam a computação eficiente de árvores de similaridade para grandes conjuntos de dados, e também a sua explicação visual em multiescala, ou seja, em vários níveis de detalhe. Também propomos modos de construir representações simplificadas de árvores de similaridade, e desse modo estender ainda mais a sua escalabilidade visual. Segundo, propomos métodos para explicar visualmente projeções multidimensionais em termos de grupos de observações relacionadas, detectadas e anotadas automaticamente para explicitar aspectos de sua similaridade no espaço de alta dimensionalidade. Mostramos em seguida como esses mecanismos explicativos podem ser adaptados para lidar com dados de natureza estática e dependentes no tempo. Nossas técnicas sã construídas visando fácil utilização, funcionamento semi automático, aplicação em quaisquer tipos de dados multidimensionais quantitativos e quaisquer técnicas de projeção multidimensional. Demonstramos a sua utilização em uma variedade de conjuntos de dados reais, obtidos a partir de coleções de imagens, arquivos textuais, medições científicas e de engenharia de software.
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26

Silva, Luiz Carlos de Paiva e. "Análise psicométrica do Inventário Multidimensional do Estilo de Dirigir (MDSI - Multidimensional Driving Style Inventory)." Universidade de São Paulo, 2004. http://www.teses.usp.br/teses/disponiveis/59/59137/tde-12102004-212408/.

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Trata-se de uma investigação de desenvolvimento metodológico cujo objetivo foram adaptação, validação e verificar a fidedignidade do Inventário Multidimensional do Estilo de Dirigir (MDSI – Multidimensional Driving Style Inventory) para a língua portuguesa, aplicada para condutores que possuem Carteira Nacional de Habilitação ou Permissão para Dirigir. No instrumento foram realizados os procedimentos de tradução - versão e retroversão; analise do instrumento de acordo com os critérios comportamental, de objetividade, de clareza, de simplicidade, de relevância, de precisão, de variabilidade, de modalidade, bem como critérios de amplitude e de equilíbrio; adequação do construto; análise semântica por parte dos alunos-avaliadores; definição e delimitação de amostras; escolha do método de aplicação do instrumento; e aplicação do MDSI. Através do programa de estatística “SPSS” os 44 itens definiram os 08 fatores: estressado, agressivo, negligente, perigoso, senso-emocional, preventivo, relaxante e desatento. A análise dos 206 questionários aplicados nos motoristas da cidade de Ribeirão Preto e região, utilizando uma escala Likert, variando de nunca até sempre, concluiu que quando os condutores apresentarem características de serem negligentes, percebe-se que há maior possibilidade de ser um motorista relaxante e menor possibilidade de ser um motorista preventivo; conforme aumenta o índice do motorista perigoso, maiores serão os índices do senso-emocional e desatento e menor o índice do fator preventivo; o motorista preventivo está negativamente associado ao fator desatento; os motoristas homens têm comprovadamente índices mais elevados nos estilo relaxante; as mulheres apresentam maiores índices no estilo desatento; na variável idade, quando mais alta a idade do sujeito maior será o seu índice do estilo preventivo e quando menor for a idade maiores serão os índices dos fatores perigoso, senso-emocional e desatento. Foi realizada a análise de fidedignidade de cada item, onde 77,27% não apresentaram variação significativa; na análise da fidedignidade de cada sujeito: apresentou um alto índice de correlação de 0,6198. O teste MDSI deve ser aplicado em todos os motoristas que irão renovar a Carteira Nacional de Habilitação ou que tiveram sua Carteira Nacional de Habilitação suspensa ou cassada, pois servirá de aconselhamento, sem caráter reprovativo, apenas informativo.
This is about an inquiry of methodological development whose objective was adaptation, validation and to verify the reliability of the Multidimensional Driving Style Inventory (MDSI - Multidimensional Driving Style Inventory) for the Portuguese language, applied in conductors who possess National Wallet of Qualification or Permission To Drive. In the instrument had been carried through the translation procedures – in both directions; analyzes of the instrument in accordance with the criteria of behavior, of objectivity, clarity, simplicity, relevance, precision, variability, modality, as well as criteria of amplitude and balance; adequacy of construct; analysis semantics on the part of the pupil-appraisers; definition and delimitation of samples; choice of the method of application of the instrument; and application of the MDSI. Through the program of the 44 statistics \"SPSS\" item had defined the 08 factors: stressed, aggressive, negligent, dangerous, sense-emotional, preventive, relaxing and neglect. The analysis of the 206 questionnaires applies in drivers of Ribeirão Preto city, using a Likert scale, varied of never until always, concluded that when the conductors to present characteristics to be negligent, perceived that he has greater possibility of being a relaxing driver and lesser possibility of being a preventive driver; as it increases the index of the dangerous driver, bigger will be the indices of sense-emotional and neglect and lesser the index of the preventive factor; the preventive driver is negatively associated with the negligent factor; the men drivers confirmedly have elevated indices in the relaxing style; the women present greater indices in the negligent style; in the variable age, when higher the age of the citizen biggest will be its index of the preventive style and when lesser it will be the age biggest will be the indices of the factors dangerous, sense-emotional and neglect. The analysis of reliability of each item was carried through, where 77.27% had not presented significant variation; in the analysis of the reliability of each citizen: it presented a high index of correlation of 0,6198. Test MDSI must be applied in all the drivers who will go to renew the Wallet National of Qualification or that they had its National Wallet Qualification suspended or annulled, therefore will serve of advising , without reprobation character, only informative.
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27

Lundqvist, Johannes. "On Amoebas and Multidimensional Residues." Doctoral thesis, Stockholms universitet, Matematiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-82843.

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This thesis consists of four papers and an introduction.  In Paper I we calculate the second order derivatives of the Ronkin function of an affine polynomial in three variables. This gives an expression for the real Monge-Ampére measure associated to the hyperplane amoeba. The measure is expressed in terms of complete elliptic integrals and hypergeometric functions.  In Paper II and III we prove that a certain semi-explicit cohomological residue associated to a Cohen-Macaulay ideal or more generally an ideal of pure dimension, respectively, is annihilated precisely by the given ideal. This is a generalization of the local duality principle for the Grothendieck residue and the cohomological residue of Passare. These results follow from residue calculus, due to Andersson and Wulcan, but the point here is that our proof is more elementary. In particular, it does not rely on the desingularization theorem of Hironaka. In Paper IV we prove a global uniform Artin-Rees lemma for sections of ample line bundles over smooth projective varieties. We also prove an Artin-Rees lemma for the polynomial ring with uniform degree bounds. The proofs are based on multidimensional residue calculus.

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 3: Manuscript. Paper 4. Manuscript.

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Velde, Antoine van de. "A multidimensional boundary sources method." Doctoral thesis, Universite Libre de Bruxelles, 1994. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/212674.

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29

Miri, Seyed Ali. "Modeling of multidimensional linear systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ30631.pdf.

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30

Itoh, Kazuhito, and Masaki Sasai. "Multidimensional theory of protein folding." American Institite of Physics, 2009. http://hdl.handle.net/2237/12626.

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31

Kotsis, Nikolaos. "Multidimensional aggregation in OLAP systems." Thesis, University of Strathclyde, 2000. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21149.

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On-line analytical processing (OLAP) provides multidimensional data analysis to support decision making. OLAP queries require extensive computation based on aggregation along many dimensions and hierarchies. The time required to process these queries has traditionally prevented the interactive analysis of large databases and in order to accelerate query-response time, precomputed results are often stored as materialised views for later retrieval. This adds a prohibitive storage overhead when applied to the whole set of aggregates, known as the data cube. Storage space and computation time can be significantly reduced by partial computation. The challenge in implementing the data cube has been to select the minimum number of views for materialisation, while retaining fast query response time. This thesis makes significant contributions to this area by introducing the Low Redundancy (L-R) approach which provides the means for the selection, computation and storage of nonredu ndant aggregates. Firstly, through the introduction of a novel technique, redundant aggregates are identified thus allowing only distinct aggregates to be computed and stored. Secondly, further redundancy is identified and eliminated using a second novel technique which stores these distinct aggregates in a compact differential form. Novel algorithms were introduced to implement these techniques and provide a solution which is both scalable and low in complexity. Both techniques have been evaluated using real and synthetic datasets with experimental results, and have achieved significant savings in computation time and storage space compared to the conventional approach. Savings have been shown to increase as dimensionality increases. Existing techniques for implementing the data cube differ from the L-R approach but they can be integrated with it to achieve faster query-response time. Finally, the implications of this work reach beyond the area of OLAP to the fields of decision support systems, user interfaces and data mining.
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32

Åklint, Richard, and Muhammad Farhan Khan. "Multidimensional Visualization of News Articles." Thesis, Linköpings universitet, Informationskodning, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-118707.

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Large data sets are difficult to visualize. For a human to find structures and understand the data, good visualization tools are required. In this project a technique will be developed that makes it possible for a user to look at complex data at different scales. This technique is obvious when viewing geographical data where zooming in and out gives a good feeling for the spatial relationships in map data or satellite images. However, for other types of data it is not obvious how much scaling should be done. In this project, an experimental application is developed that visualizes data in multiple dimensions from a large news article database. Using this experimental application, the user can select multiple keywords on different axis and then can create a visualization containing news articles with those keywords. The user is able to move around the visualization. If the camera is far away from the document icons then they are clustered using red coloured spheres. If the user moves the camera closer to the clusters they will pop up into single document icons. If the camera is very close to the document icons it is possible to read the news articles
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Bell, Paul W. "Statistical inference for multidimensional scaling." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327197.

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34

Radakovic, Ratko. "Multidimensional apathy in neurodegenerative disease." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/25959.

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Apathy is characterised by a lack of motivation towards goal directed behaviour and is a symptom of various neurodegenerative diseases. There are various tools that can be used to assess apathy but a caveat of these is that they usually assess it as a unidimensional concept. Apathy has been recognised to have a multidimensional substructure. The Dimensional Apathy Scale is the only comprehensive measure designed to quantify neurobiologically-based subtypes, called Executive, Emotional and Initiation apathy. The first aim of this study was to explore multidimensional apathy, and its associations with demographic variables, in healthy, community dwelling adults. Secondly, multidimensional apathy was explored in neurodegenerative diseases, specifically Amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD) and Alzheimer’s disease (AD). For each disease group, the validity and reliability of both the self rated and carer rated DAS were also determined. Finally, the association between specific apathy subtype impairments and executive dysfunction was explored in ALS patients. Four hundred healthy community dwelling adults, eighty-three ALS patients (seventy-five carers), thirty-four PD patients (thirty carers) and forty-nine AD patients (eighty-nine carers) were recruited for the questionnaire study. In the healthy community dwelling adults, Executive apathy decreased with age, whereas Emotional increased with age. Gender differences were also shown with higher apathy in males on Emotional apathy. There were also employment differences, in that Executive apathy was higher in unemployed individuals compared to those who were employed. Emotional apathy showed difference in type of employment, where full time employed individuals were significantly more apathetic than those employed part time. These findings were taken into account in selecting the appropriate control samples to match our patient groups. In the patient groups, ALS patients were found to be significantly more impaired on the Initiation subscale when compared to controls. Furthermore, Initiation apathy was found to be the most frequent impairment above abnormality cut-off on the carer rated DAS. PD patients were significantly more impaired on Executive and Initiation apathy when compared to controls. These two subscales were most frequently above abnormality cut-off in the carer rated DAS. Finally, AD patients were significantly more impaired on all subscales when compared to controls and, on the carer rated DAS, global impairment over all subscales was most often reported as above abnormality cut-off. Additionally in AD, there was a significant disparity between carer and patient ratings on Executive and Initiation apathy, indicating patients’ impaired awareness. When comparing patient groups, there was a significant difference between carer rated apathy subtype impairments for each patient group. Validity and reliability of the DAS was found to be robust when compared to standard measures of apathy and depression. In the experimental study, a sample of ALS patients (and their carers) and healthy controls (and their informants) were recruited to complete a battery of neuropsychological tests, the DAS, other apathy and depression measures. ALS patients were impaired on tasks of executive functioning when compared to controls. Furthermore, apathy subtype deficits were associated with executive dysfunction in ALS. In conclusion, apathy is a multidimensional concept that manifests in different subtype profiles dependent on neurodegenerative disease. This has further implications for understanding and assessment of cognitive dysfunction and neuropsychiatric symptoms, such as apathy, in ALS and other neurodegenerative disease patient groups.
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35

Pond, Kevin R. "Multidimensional Adaptive Quadrature Over Simplices." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/28699.

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The objective of this work is the development of novel, efficient and reliable multidi- mensional adaptive quadrature routines defined over simplices (MAQS). MAQS pro- vides an approximation to the integral of a function defined over the unit hypercube and provides an error estimate that is used to drive a global subdivision strategy. The quadrature estimate is based on Lagrangian interpolation defined by using the vertices, edge nodes and interior points of a given simplex. The subdivision of a given simplex is chosen to allow for the reuse of points (thus function evaluations at those points) in successive refinements of the initial tessellation. While theory is developed for smooth functions, this algorithm is well suited for functions with discontinuities in dimensions three through six. Other advantages of this approach include straight-forward parallel implementation and application to integrals over polyhedral domains.
Ph. D.
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36

Chakilam, Krishna Chaitanya. "Representing and Minimizing Multidimensional Dependencies." University of Akron / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=akron1249315061.

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37

Butt, Joanne. "Exploring Multidimensional Anxiety throughout Competition." Miami University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=miami1123181095.

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38

Easwaran, Hiranmoy. "Multidimensional Khintchine-Marstrand-type Problems." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1343853458.

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39

Westerlund, Per. "Business Intelligence: Multidimensional Data Analysis." Thesis, Umeå universitet, Institutionen för datavetenskap, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-138758.

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The relational database model is probably the most frequently used database model today. It has its strengths, but it doesn’t perform very well with complex queries and analysis of very large sets of data. As computers have grown more potent, resulting in the possibility to store very large data volumes, the need for efficient analysis and processing of such data sets has emerged. The concept of Online Analytical Processing (OLAP) was developed to meet this need. The main OLAP component is the data cube, which is a multidimensional database model that with various techniques has accomplished an incredible speed-up of analysing and processing large data sets. A concept that is advancing in modern computing industry is Business Intelligence (BI), which is fully dependent upon OLAP cubes. The term refers to a set of tools used for multidimensional data analysis, with the main purpose to facilitate decision making. This thesis looks into the concept of BI, focusing on the OLAP technology and date cubes. Two different approaches to cubes are examined and compared; Multidimensiona lOnline Analytical Processing (MOLAP) and Relational Online Analytical Processing (ROLAP). As a practical part of the thesis, a BI project was implemented for the consulting company Sogeti Sverige AB. The aim of the project was to implement a prototype for easy access to, and visualisation of their internal economical data. There was no easy way for the consultants to view their reported data, such as how many hours they have been working every week, so the prototype was intended to propose a possible method. Finally, a performance study was conducted, including a small scale experiment comparing the performance of ROLAP, MOLAP and querying against the data warehouse. The results of the experiment indicates that ROLAP is generally the better choice for data cubing.
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40

Lindau, Jules Washington. "Multidimensional dynamic compression system modeling." Diss., This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-02132009-171914/.

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41

Abbott, Carmen Casanova Waigandt Alex. "Community multidimensional fall risk screening." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6136.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on Feb. 10, 2010). Thesis advisor: Alex Waigandt. Vita. Includes bibliographical references.
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42

Lobb, Sarah Beverley. "Lagrangian structures and multidimensional consistency." Thesis, University of Leeds, 2010. http://etheses.whiterose.ac.uk/1921/.

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The conventional point of view is that the Lagrangian is a scalar object (or equivalently a volume form), which through the Euler-Lagrange equations provides us with one single equation (i.e., one per component of the dependent variable). Multidimensional consistency is a key integrability property of certain discrete systems; it implies that we are dealing with infinite hierarchies of compatible equations rather than with one single equation. Requiring the property of multidimensional consistency to be reflected also in the Lagrangian formulation of such systems, we arrive naturally at the construction of Lagrangian multiforms, i.e., Lagrangians which are the components of a form and satisfy a closure relation. We demonstrate that the Lagrangians of many important examples fit into this framework: the so-called ABS list of systems on quad graphs, which includes the discrete Korteweg-de Vries equation; the Gel'fand-Dikii hierarchy, which includes the discrete Boussinesq equation; and the bilinear discrete Kadomtsev-Petviashvili equation. On the basis of this we propose a new variational principle for integrable systems which brings in the geometry of the space of independent variables, and from this principle we can then derive any equation in the hierarchy. We also extend the notion of Lagrangian forms, and the corresponding new variational principle, to continuous systems, using the example of the generating partial dierential equation for the Korteweg-de Vries hierarchy.
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43

Lau, Kwok-Ho. "Dependence structures in multidimensional arrays." Diss., University of Pretoria, 2016. http://hdl.handle.net/2263/60821.

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In the process of data acquisition the information obtained are more than often contaminated by noise. To purify the data smoothers are designed to remove the noise. The LULU operators are such smoothers, more speci cally, they are designed to remove impulsive noise. Carl Rohwer and his collaborators devel- oped the LULU operators in one dimension in the last four decades and, more recently, the operators have been extended to higher dimensions by Roumen Anguelov and Inger Fabris-Rotelli [2]. The prop- erties in shape preservation and total variation preservation are extended from one-dimensional LULU operators. This allows for smoothing with the operators in images. However, because their de nition uses a morphological concept of a connection, the question of how complex the connectivity should be therefore arises. Using the results from correlation analysis, we explore the extent at which the pixels of an image depend on its neighbours and establish the complexity of the connectivity for LULU operators in two-dimensions. In addition, as a measure of how e ective the LULU smoothers remove noise, we examine the noise extractions by the operators for images.
Dissertation (MSc)--University of Pretoria, 2016.
Statistics
MSc
Unrestricted
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44

James, Jenee. "A Multidimensional Model of Sociosexuality." W&M ScholarWorks, 2004. https://scholarworks.wm.edu/etd/1539626468.

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45

Possamai, Lino <1978&gt. "Multidimensional analysis of complex networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5389/1/possamai_lino_tesi.pdf.

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Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.
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46

Possamai, Lino <1978&gt. "Multidimensional analysis of complex networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5389/.

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Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.
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47

BELLANI, LUNA FRANCESCA. "Essays on multidimensional well-being." Doctoral thesis, Università Bocconi, 2011. https://hdl.handle.net/11565/4054124.

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48

CUGNATA, FEDERICA. "Bayesian three-way multidimensional scaling." Doctoral thesis, Università Bocconi, 2012. https://hdl.handle.net/11565/4054285.

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49

Fransman, Tina. "Investigating multidimensional poverty in South Africa in 2001-2016: The multidimensional poverty index (MPI) approach." University of the Western Cape, 2017. http://hdl.handle.net/11394/6158.

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Magister Commercii - MCom (Economics)
Since the dawn of democracy, South Africa has come a long way in trying to eradicate problems relating to poverty and inequality that the apartheid system left deeply engraved within the midst of our society. To date we however still live in a society characterised by severe socio-economic challenges. Most of these challenges are not straight fold, onedimensional issues. Instead, in most cases one would find that with each challenge, stem even more interrelated challenges. Up to now, poverty, associated with notions relating to scarcity, insufficiency and deficiency, is still one of these major challenges South Africa seems to be grappling with.
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50

Castillo, Luis Jaime, B. Francesca Fernandini, and Y. Luis Muro. "The multidimensional relations between the Wari and the Moche states of Northern Peru." Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/113342.

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This paper explores how archaeology can study the relationships between complex multidimensional societies in critical periods of their development through an analysis of the multiple variables, circumstances and contingencies that define social interactions. By focusing on the archaeological record of San José de Moro, an important funerary and ceremonial center in the Jequetepeque valley, the authors approach the multifaceted natures and purposes behind the relationships between the Moche States of northern coastal Peru and the southern Andean Wari during the end of the Early Intermediate Period and the Middle Horizon.
El presente artículo explora cómo la arqueología puede estudiar las relaciones entre sociedades complejas durante periodos críticos de su desarrollo, a través del análisis de las múltiples variables, circunstancias y contingencias que definen las interacciones sociales. Mediante el estudio de los contextos y objetos provenientes de San José de Moro, un importante centro funerario y ceremonial en el valle del Jequetepeque, los autores abordan las naturalezas y propósitos que se traslapan detrás de las relaciones entre los Estados mochica del norte del Perú y la sociedad wari de la sierra sur, durante el Periodo Intermedio Temprano y el Horizonte Medio.
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