The aim of thiswork is to locate a semi-obnoxious facility, i.e. tominimize the distances to a given set of customers in order to save transportation costs on the one hand and to avoid undesirable interactions with other facilities within the region by maximizing the distances to the corresponding facilities on the other hand. Hence, the goal is to satisfy economic and environmental issues simultaneously. Due to the contradicting character of these goals, we obtain a non-convex objective function. We assume that distances can be measured by rectilinear distances and exploit the structure of this norm to obtain a very efficient dual pair of algorithms.

Submitted by Priscilla Araujo (priscilla@ibict.br) on 2016-08-03T20:34:50Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Leandra_de_Oliveira_Dissertação.pdf: 1982019 bytes, checksum: c5e769e816cb9d0e781ab2ea7362a04e (MD5) / Made available in DSpace on 2016-08-03T20:34:50Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Leandra_de_Oliveira_Dissertação.pdf: 1982019 bytes, checksum: c5e769e816cb9d0e781ab2ea7362a04e (MD5) Previous issue date: 2014-03-19 / Pesquisa exploratória que tem como objetivo principal investigar modelos representacionais, visando evidenciar particularidades da Agricultura como domínio do conhecimento. Para isso, foram realizadas pesquisas bibliográfica e documental para atender os objetivos específicos que são: identificar a origem etimológica e os aspectos históricos da Agricultura, investigar a área de Agricultura em classificações nacionais e internacionais de conhecimento e observar num contexto diferente de aplicação, outro modelo referencial da Agricultura. Apresentam-se como modelos representacionais do domínio da Agricultura: o AGRIS/CARIS: Categorization scheme da FAO, a Tabela de Áreas do Conhecimento do CNPq e a representação presente nos dados da pós-graduação brasileira na Grande Área „Ciências Agrárias‟ da CAPES. A partir da descrição e análise dos modelos, observou-se proximamente a complexidade que cerca a representação de um domínio do conhecimento. No caso da Agricultura, a dificuldade reside na pluralidade de objetos de estudo que transcendem a disciplinaridade e a interdisciplinaridade do domínio. Essa característica, se por um lado, motiva e enriquece o desenvolvimento científico e tecnológico, por outro, leva a dificuldades de representação da Agricultura nos modelos referenciais e representacionais de organização do conhecimento. Conclui-se que a análise de diferentes modelos representacionais se coloca como uma abordagem para perceber as diferentes visões existentes no domínio por refletir a organização e representação do conhecimento praticada pela comunidade discursiva. / This work is an exploratory research that has as main objective to investigate representational models, aiming to obtain particularities of Agriculture as a knowledge domain. Bibliographic and documentary search were done in order to achieve the specific objectives to identify the etymological origin and the historical aspects of Agriculture, to investigate the area of Agriculture in national and international classifications of knowledge, and to observe another reference model application within an educational context. The classificatory instruments analised were: the FAO Categorization scheme AGRIS/CARIS, the CNPq‟s Tabela de Áreas de Conhecimento, and the representation of the Brazilian post-graduate programs in „Agricultural Sciences' in CAPES classification. The analyses revealed the complexity surrounding the representation of a knowledge domain. In the case of Agriculture, the difficulty lies in the plurality of objects of study that transcend disciplinary and interdisciplinary domains. This feature, on one hand, motivates and enriches the scientific and technological development. On the other hand it leads to difficulties in the representation of Agriculture referential and representational knowledge organization models. We conclude that the analysis of different representational models is a valid approach to grasp different visions for the area reflected by the organization and representation of knowledge as practiced by communities of discourse.

A set of vertices in a graph G is a global dominating set of G if it dominates both G and its complement G. The minimum cardinality of a global dominating set of G is the global domination number of G. We explore the effects of graph modifications (edge removal, vertex removal, and edge addition) on the global domination number. In particular, for each graph modification, we study the global domination stable trees, that is, the trees whose global domination number remains the same upon the modification. We characterize these stable trees having small global domination numbers.

A set of vertices in a graph G is a global dominating set of G if it dominates both G and its complement G. The minimum cardinality of a global dominating set of G is the global domination number of G. We explore the effects of graph modifications (edge removal, vertex removal, and edge addition) on the global domination number. In particular, for each graph modification, we study the global domination stable trees, that is, the trees whose global domination number remains the same upon the modification. We characterize these stable trees having small global domination numbers.

In this thesis text categorization is investigated in four dimensions of analysis: theoretically as well as empirically, and as a manual as well as a machine-based process. In the first four chapters we look at the theoretical foundation of subject classification of text documents, with a certain focus on classification as a procedure for organizing documents in libraries. A working hypothesis used in the theoretical analysis is that classification of documents is a process that involves translations between statements in different languages, both natural and artificial. We further investigate the close relationships between structures in classification languages and the order relations and topological structures that arise from classification. A classification algorithm that gets a special focus in the subsequent chapters is the support vector machine (SVM), which in its original formulation is a binary classifier in linear vector spaces, but has been extended to handle classification problems for which the categories are not linearly separable. To this end the algorithm utilizes a category of functions called kernels, which induce feature spaces by means of high-dimensional and often non-linear maps. For the empirical part of this study we investigate the classification performance of semantic kernels generated by different measures of semantic similarity. One category of such measures is based on the latent semantic analysis and the random indexing methods, which generates term vectors by using co-occurrence data from text collections. Another semantic measure used in this study is pointwise mutual information. In addition to the empirical study of semantic kernels we also investigate the performance of a term weighting scheme called divergence from randomness, that has hitherto received little attention within the area of automatic text categorization. The result of the empirical part of this study shows that the semantic kernels generally outperform the “standard” (non-semantic) linear kernel, especially for small training sets. A conclusion that can be drawn with respect to the investigated datasets is therefore that semantic information in the kernel in general improves its classification performance, and that the difference between the standard kernel and the semantic kernels is particularly large for small training sets. Another clear trend in the result is that the divergence from randomness weighting scheme yields a classification performance surpassing that of the common tf-idf weighting scheme.

By using innovative methods, such as the automated transfer of corporate electronic data to National Statistical Institutions, official transport data can be significantly improved in terms of reliability, costs and the burden on respondents. In this paper, we show that the automated compilation of statistical reports is possible and feasible. Based on previous findings, a new method and tool were developed in cooperation with two business partners from the logistics sector in Austria. The results show that the prototype could successfully be implemented at the partner companies. Improved data quality can lead to more reliable analyses in various fields. Compared to actual volumes of investments into transport, the costs of transport statistics are limited. By using the new and innovative data collection techniques, these costs can even be reduced in the long run; at the same time, the risk of bad investments and wrong decisions caused by analyses relying on poor data quality can be reduced. This results in a substantial value for business, research, the economy and the society.

In model-based clustering mixture models are used to group data points into clusters. A useful concept introduced for Gaussian mixtures by Malsiner Walli et al. (Stat Comput 26:303-324, 2016) are sparse finite mixtures, where the prior distribution on the weight distribution of a mixture with K components is chosen in such a way that a priori the number of clusters in the data is random and is allowed to be smaller than K with high probability. The number of clusters is then inferred a posteriori from the data. The present paper makes the following contributions in the context of sparse finite mixture modelling. First, it is illustrated that the concept of sparse finite mixture is very generic and easily extended to cluster various types of non-Gaussian data, in particular discrete data and continuous multivariate data arising from non-Gaussian clusters. Second, sparse finite mixtures are compared to Dirichlet process mixtures with respect to their ability to identify the number of clusters. For both model classes, a random hyper prior is considered for the parameters determining the weight distribution. By suitable matching of these priors, it is shown that the choice of this hyper prior is far more influential on the cluster solution than whether a sparse finite mixture or a Dirichlet process mixture is taken into consideration.

A method for implicit variable selection in mixture-of-experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariates. Robust class membership predictors are identified using a normal gamma prior. The resulting model setup is used in a finite mixture of Bernoulli distributions to find homogenous clusters of women in Mozambique based on their information sources on HIV. Fully Bayesian inference is carried out via the implementation of a Gibbs sampler.

Orientador: Mariângela Spotti Lopes Fujita / Banca: Johanna Wilhelmina Smit / Banca: José Augusto Chaves Guimarães / Resumo: A organização da informação tem nas bibliotecas digitais um importante movimento mundial em torno do armazenamento, preservação, acesso e divulgação da produção científica. Considerando o crescimento do acervo eletrônico a ser organizado, propõe-se investigar os princípios para uma estruturação temática adequada ao ambiente das bibliotecas digitais de teses e dissertações, com os objetivos de fornecer subsídios para elaboração de estruturas temáticas dentro do contexto da Ciência da Informação e identificar aspectos teórico-metodológicos de teorias com abordagem de categorização de assuntos aplicáveis à organização de conteúdos das bibliotecas digitais de teses e dissertações em instituições de ensino superior. Identificou-se na literatura, proposta de sistematização das tendências teóricas em organização do conhecimento em duas teorias: a macroestrutural e a microestrutural. Na teoria macroestrutural, os aspectos teórico-metodológicos são mais apropriados ao alcance dos objetivos, por proporcionar um agrupamento das teorias que parte das disciplinas até os âmbitos temáticos mais gerais para explicar a estruturação de conceitos, ao invés da teoria microestrutural que trata do corpus teórico como unidade mínima do conhecimento estudando, assim, a relação entre conceitos. As tendências teóricas existentes dentro da teoria macroestrutural, são: mapa conceitual; domínio temático; campos semânticos e as teorias terminológicas. A avaliação dessas teorias revelou a importância do contexto social e cultural, salientada em entrevistas realizadas com pesquisadores do Instituto de Física Teórica da Universidade Estadual Paulista / UNESP, na construção das relações conceituais da organização do conhecimento a serem aplicadas em ambientes digitais movidos por ações de interação, tanto no seu uso individual como na multiplicidade de atores envolvidos como são as bibliotecas digitais. / Abstract: Organizing the knowledge acquired in digital libraries is a global movement, which entails storing, preserving, providing access and disseminating scientific production. Considering the growing amount of electronic documents to organize, we propose to investigate and lay down the principles for a proper thematic structuring of the theses and dissertations in digital libraries. Our purpose is to provide help tools to elaborate those thematic structures within the field of Information Science and identify the theoretical and methodological aspects of the theories on thematic classification that can be applied when organizing the contents of theses and dissertations of the digital libraries of higher education institutions. Regarding the organization of knowledge in literature, two theoretical trends were systematized: the micro - and the macro - structural theory. The theoretical and methodological aspects of the macrostructural theory are more appropriate to reach goals, as they enable the gathering of theories from disciplines down to more general themes to explain how concepts are structured. The microstructural theory, on the contrary, concerns the theoretical corpus as the minimal unit of knowledge, and thus enables a study of the relationship between concepts. The theoretical trends within the macrostructural theory currently study the use of conceptual mapping, thematic domains, semantic fields, and terminological theories. The evaluation of those theories revealed how important the social and cultural contexts pointed out in interviews done with researchers of Instituto de Física Teórica da Universidade Estadual Paulista / UNESP, in the construction of conceptual relations of knowledge organization to be applied in digital environments moved by interactions, both in is individual use and in the multiple actors envolved - like digital libraries are. / Mestre

Made available in DSpace on 2014-06-11T19:26:45Z (GMT). No. of bitstreams: 0 Previous issue date: 2005-08-09Bitstream added on 2014-06-13T18:55:07Z : No. of bitstreams: 1 bastos_fm_me_mar.pdf: 474437 bytes, checksum: d14feece02728003509797261c5fffd5 (MD5) / Universidade Estadual Paulista (UNESP) / A organização da informação tem nas bibliotecas digitais um importante movimento mundial em torno do armazenamento, preservação, acesso e divulgação da produção científica. Considerando o crescimento do acervo eletrônico a ser organizado, propõe-se investigar os princípios para uma estruturação temática adequada ao ambiente das bibliotecas digitais de teses e dissertações, com os objetivos de fornecer subsídios para elaboração de estruturas temáticas dentro do contexto da Ciência da Informação e identificar aspectos teórico-metodológicos de teorias com abordagem de categorização de assuntos aplicáveis à organização de conteúdos das bibliotecas digitais de teses e dissertações em instituições de ensino superior. Identificou-se na literatura, proposta de sistematização das tendências teóricas em organização do conhecimento em duas teorias: a macroestrutural e a microestrutural. Na teoria macroestrutural, os aspectos teórico-metodológicos são mais apropriados ao alcance dos objetivos, por proporcionar um agrupamento das teorias que parte das disciplinas até os âmbitos temáticos mais gerais para explicar a estruturação de conceitos, ao invés da teoria microestrutural que trata do corpus teórico como unidade mínima do conhecimento estudando, assim, a relação entre conceitos. As tendências teóricas existentes dentro da teoria macroestrutural, são: mapa conceitual; domínio temático; campos semânticos e as teorias terminológicas. A avaliação dessas teorias revelou a importância do contexto social e cultural, salientada em entrevistas realizadas com pesquisadores do Instituto de Física Teórica da Universidade Estadual Paulista / UNESP, na construção das relações conceituais da organização do conhecimento a serem aplicadas em ambientes digitais movidos por ações de interação, tanto no seu uso individual como na multiplicidade de atores envolvidos como são as bibliotecas digitais. / Organizing the knowledge acquired in digital libraries is a global movement, which entails storing, preserving, providing access and disseminating scientific production. Considering the growing amount of electronic documents to organize, we propose to investigate and lay down the principles for a proper thematic structuring of the theses and dissertations in digital libraries. Our purpose is to provide help tools to elaborate those thematic structures within the field of Information Science and identify the theoretical and methodological aspects of the theories on thematic classification that can be applied when organizing the contents of theses and dissertations of the digital libraries of higher education institutions. Regarding the organization of knowledge in literature, two theoretical trends were systematized: the micro - and the macro - structural theory. The theoretical and methodological aspects of the macrostructural theory are more appropriate to reach goals, as they enable the gathering of theories from disciplines down to more general themes to explain how concepts are structured. The microstructural theory, on the contrary, concerns the theoretical corpus as the minimal unit of knowledge, and thus enables a study of the relationship between concepts. The theoretical trends within the macrostructural theory currently study the use of conceptual mapping, thematic domains, semantic fields, and terminological theories. The evaluation of those theories revealed how important the social and cultural contexts pointed out in interviews done with researchers of Instituto de Física Teórica da Universidade Estadual Paulista / UNESP, in the construction of conceptual relations of knowledge organization to be applied in digital environments moved by interactions, both in is individual use and in the multiple actors envolved - like digital libraries are.