Berlin, Freie Univ., Diss., 2002. / Dateiformat: zip, Dateien im PDF-Format.

Berlin, Freie Univ., Diss., 2002. / Dateiformat: zip, Dateien im PDF-Format.

Wuppertal, Universiẗat, Diss., 2004.

Berlin, Freie Universiẗat, Diss., 2002. / Dateiformat: zip, Dateien im PDF-Format.

Magdeburg, Universiẗat, Diss., 2002.

Made available in DSpace on 2014-06-12T17:42:31Z (GMT). No. of bitstreams: 2 arquivo7477_1.pdf: 749025 bytes, checksum: a128b453a9ec69c7c0235ae388ca5a67 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2005 / A lógica de cluster oferece a arranjos empresariais uma organização e sinergia entre seus membros, que permite alcançar vantagens que isoladamente seriam inatingíveis dada a dinâmica do mercado mundial. Este estudo teve como objetivo verificar se a cidade de Belém do Pará é um cluster turístico, visto que a mesma dispõe de diversos atrativos, estrutura e interesse em alavancar este ramo econômico do setor de serviços. No referencial teórico se abordou temas de relevância essencial para a execução da pesquisa, sendo apresentados os conceitos de serviços turísticos, seu funcionamento e a definição de seus agentes envolvidos, também se definiu e caracterizou cluster e inovação como pontos importantes para o desenvolvimento local, ressaltou-se o diferencial que se pode atingir por meio de um bom produto e marca regional, estratégia eficiente e um espírito empreendedor por parte dos empresários que devem buscar a qualidade em seus serviços e ações. O estudo iniciou-se com um histórico da capital paraense a caracterizando, depois com base em dados e informações provenientes de entrevistas feitas com estudiosos e elementos chaves do setor de turismo da cidade, se definiu o conceito de cluster a ser adotado e qual deveria ser a relação de seus membros. Elaborou-se, também, proposta de um modelo de identificação de cluster turísticos para se averiguar o objetivo da pesquisa. Como resultado, chegou-se à conclusão de que a referida cidade é somente um potencial cluster, sugerindo-se medidas, tanto do setor público como privado, que permitam a Belém tornar-se realmente um cluster, valorizando sinergias entre os agentes e potencialidades locais

In this Thesis, we propose a Cluster-based TDMA (CBT) scheme for Vehicular Ad-hoc Networks (VANET). In the CBT, the collision problems can be solved when packets are transmitted at the same time. In the Intra-cluster communications, the VANET Coordinator (VC) is determined by randomly choosing a number of zero or one. Other VANET Nodes (VNs) then randomly select different time slots to transmit their Bandwidth Requests (BRs). If more than two VNs choose the same slots for BRs, collision will occur. The failed VNs will continue to issue BRs in the next TDMA frames. After the time slots are scheduled by VC, all VNs can use the designated time slots to send data. In the Inter-cluster communications, when two clusters are approaching to each other, two VCs must exchange Slot Allocation MAP (SAM) using the random zero-or-one scheme. The VCs successfully receive SAM must reschedule the time slots. For the purpose of performance evaluation, we calculate the average time slots of selecting VC and the average time slots required for successful BRs. We also compute the average time slots required for successfully transmitting SAM and the average time slots required for broadcasting SAM to all VNs. Finally, we calculate the average time slots required for waiting before data transmission. To validate the mathematical results, we perform a simulation written in C++. When comparing the mathematical results to the simulation results, we observe that in the average time slots required for BR, the former is larger than the latter. This is because in the mathematical equations it is difficult to specify which time slots are used by VNs to transmit BRs. However, the rest of performance comparisons, the two results are very close.

This study examines the role of voiceless and voiced fricatives as the first consonant in word-initial true consonant clusters and adjunct clusters. Specifically, this study sought evidence to determine whether the lack of voiced fricatives, such as /z/ and /v/, in English word-initial true and adjunct clusters is due to an active ban or an accidental gap in the language's phonotactics. This study also looked into whether the voiceless alveolar fricative /s/ is the only fricative that can play the role of adjunct segment in word-initial adjunct clusters, or whether other fricatives, such as the voiced alveolar fricative /z/, or the voiceless and voiced labiodental fricatives /f/ and /v/ could also be adjunct segments in word-initial adjunct clusters. Fourteen native English speakers were asked to pronounce a list of non-words containing word-initial clusters with /s/, /f/, /z/, and /v/ as the first consonant and /r/, /l/, /n/, /k/, and /g/ as the second consonant. The clusters were chosen to represent different voicing statuses and places of articulation for the first consonant in the cluster, in addition to differing sonority distances between the first consonant and the second consonant of the word-initial cluster. The native English speaker productions were recorded and acoustically analyzed in order to determine the exact pronunciations each speaker used for each target cluster. The results were then statistically analyzed to reveal patterns. Results showed that the lack of voiced fricatives as the first consonant in word-initial position of true clusters in English is due to an accidental gap, due to the relatively numerous correct productions of such clusters. The the lack of voiced fricatives as the first consonant in word-initial position of adjunct clusters in English, however, is due to an active ban, due to the difficulty that the native English speakers had in correctly producing such clusters. This study also concluded that while /s/ is the only adjunct segment in English, /f/ could also play that role.

Exemplos de clusters existentes em todo o mundo comprovam a eficácia da organização empresarial em ambiente de concentração geográfica. Adotando um modelo de intervenção em clusters, a governança normalmente estabelece uma seqüência de atividades que começa pelo diagnóstico e culmina em ações conjuntas e políticas públicas. Entretanto, ao analisar os estudos de caso encontrados na literatura, verifica-se que os métodos de diagnóstico comumente adotados pela governança não estão orientados aos pilares que sustentam desenvolvimento do cluster. Isto estimulou a busca de uma resposta às perguntas: Quais são os fatores que influenciam o desenvolvimento de um cluster? Como elaborar um roteiro de diagnóstico orientado a estes fatores? Inicialmente 11 fatores que influenciam o desenvolvimento de um cluster foram encontrados e se estabelece um roteiro com questões orientadas para o diagnóstico destes fatores. Para analisar a validade destes fatores e sua aplicação para o diagnóstico em clusters, realiza-se uma pesquisa de campo, de abordagem quantitativa e qualitativa. Na pesquisa de campo, são utilizadas técnicas de observação participante e entrevistas semiestruturadas, com utilização de formulários. O procedimento é o estudo de caso, sendo realizado no cluster metal mecânico de Sertãozinho. Analisa-se a relação entre os fatores e o desenvolvimento do cluster, bem como a capacidade do instrumento em avaliar corretamente cada fator. Ao final da aplicação, o roteiro ficou composto por 10 fatores: cooperação; gestão; competição; fornecedores; instituições de apoio e governança; pessoas e conhecimento; infra-estrutura local; inovação; energia empreendedora; e cultura comunitária. A principal contribuição desta tese é o desenvolvimento de uma ferramenta que dê suporte à governança em sua pretensão de criar ações voltadas ao desenvolvimento de um cluster. / Existing examples of clusters in the whole world prove the effectiveness of the enterprise organization in environment of geographic concentration. Adopting a model of intervention in clusters, the government normally establishes a sequence of activities that starts by the diagnosis and culminates in joint actions and public policies. However, when analyzing the case studies found in literature, are verified that the most adopted method of diagnosis are not guided to the pillars that can support development of cluster. This stimulated the search of a reply to the questions: Which are the factors that influence cluster development? How to elaborate a script of diagnosis guided from these factors? Initially 11 factors that influence cluster development had been found and established a script with questions for the diagnosis of these factors. To analyze the validity of these factors and its application for the cluster diagnosis, a quantitative and qualitative field research was done. In the field research, techniques of participant comment were adopted and interviews were done using semi structuralized questionnaires. The procedure is case study, done in mechanical and metal cluster of Sertãozinho. Were analyzed the relation between the factors and cluster development, as well as the capacity of the instrument in evaluating each factor correctly. In the end of the application, the script had been composed for 10 factors: cooperation; management; competition; suppliers; support and government institutions; people and knowledge; local infrastructure; Innovation; entrepreneurship energy; and communitarian culture. The main contribution of this thesis is the development of a tool that can support the government in its pretension to create joint actions and public policies for the cluster development.

Pervasive Developmental Disorders (PDDs) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behaviour [Str04]. Given the diversity and varying severity of PDDs, diagnostic tools attempt to identify homogeneous subtypes within PDDs. The diagnostic system Diagnostic and Statistical Manual of Mental Disorders - Fourth Edition (DSM-IV) divides PDDs into five subtypes. Several limitations have been identified with the categorical diagnostic criteria of the DSM-IV. The goal of this study is to identify putative subtypes in the multidimensional data collected from a group of patients with PDDs, by using cluster analysis. Cluster analysis is an unsupervised machine learning method. It offers a way to partition a dataset into subsets that share common patterns. We apply cluster analysis to data collected from 358 children with PDDs, and validate the resulting clusters. Notably, there are many cluster analysis algorithms to choose from, each making certain assumptions about the data and about how clusters should be formed. A way to arrive at a meaningful solution is to use consensus clustering to integrate results from several clustering attempts that form a cluster ensemble into a unified consensus answer, and can provide robust and accurate results [TJPA05]. In this study, using cluster analysis, cluster validation, and consensus clustering, we identify four clusters that are similar to – and further refine  three of the five subtypes defined in the DSM-IV. This study thus confirms the existence of these three subtypes among patients with PDDs. / Thesis (Master, Computing) -- Queen's University, 2007-11-15 23:34:36.62 / OGS, QGA