Taiwan¡¦s DRAM has high technology, strong capital, and standardized products, but it still can not be escaped from economic fluctuations. With this impact, Taiwan¡¦s DRAM has faced the problem of cash flow imbalance; moreover, the problem is going from bad to worse. The study is based on the view of system dynamics and focuses on fixed assets and investment skills of the investment-cash flow, operating cash flow, and business cycles of Taiwan¡¦s DRAM. It considers the features of dynamic complex, including loop, time delay and nonlinear and constructs a system dynamics model. The model would apply key elements to suppose an investment strategy and then to mimic an investment situation. The aim of the study will figure out the suitable investment strategy to assistant Taiwan¡¦s DRAM making the most of its inputs. The study discovers: (1) the best investment strategy for 10 year is 5.0 (to invest three fixed asset sets); for 30 year is 6.0 (to invest manufacturing skills and one fixed asset set) and 7.0 (to invest manufacturing skills and two fixed asset sets), (2) the most effective element for investment strategy in the long run is to invest fixed asset sets rather than upgrading manufacturing skills, (3) to keep investing in semiconductor fabrications would endanger Taiwan¡¦s DRAM itself; hence the superior limit investment quantity for fixed assets are five to six sets,(4) the best investment timing for Taiwan¡¦s DRAM is the first two business cycle season, and (5)when Taiwan¡¦s DRAM faces economic downturn, the effective investment strategy for it is few. If Taiwan¡¦s DRAM doesn¡¦t change its industrial structure, it will face the high risk of loss.

The major Hot-Mix Asphalt (HMA) input for mechanistic-empirical (M-E) flexible pavement design is the dynamic complex modulus obtained from either the uniaxial or triaxial compressive dynamic modulus test. Furthermore, as part of the performance-based mix design process, the triaxial dynamic modulus has been selected to predict rutting and fatigue cracking, and the Indirect Tension (IDT) creep compliance test to predict low-temperature thermal cracking. The creep compliance and dynamic modulus are measured responses (viscoelastic functions) of viscoelastic materials under transient and cyclic loading, respectively. Under the assumptions of linearity, linear viscoelastic functions are equivalent. Moreover, these properties should be the same whether they are obtained from a uniaxial compressive or IDT test. For this dissertation, we tested the applicability of linear viscoelastic (LVE) theory to HMA mixes and determined whether HMA need to be modeled as a bimodular material to analyze IDT creep compliance test results. The need to model HMA as a bimodular material is a result of a number of studies that suggest that HMA tensile and compressive properties are different. A testing program was developed to experimentally measure the uniaxial compression, and IDT creep compliance, and the uniaxial compression dynamic modulus for different HMA mixes. The uniaxial compressive creep compliance and dynamic modulus master curves are constructed and the shift factors obtained from each test are compared. Interconversion between the creep compliance and dynamic modulus experimental results confirm the applicability of LVE theory for the HMA mixes investigated. Based on the applicability of LVE theory, a methodology to determine HMA LVE properties from the combined creep compliance and dynamic modulus test results was developed. As a practical application that is relevant to the M-E flexible pavement design procedure, LVE theory was used and compared to proposed approximate methods to perform the conversion of testing frequency to loading time. Specifically, dynamic modulus results were converted to relaxation modulus, creep compliance, and resilient modulus. Finally, the HMA IDT creep compliance test results at low and intermediate temperature (<20oC) were successfully analyzed using a HMA bimodular material model based on the Ambartsumyan model. The difference between the compressive modulus and the modulus calculated from the IDT test using Hondros' stress distribution is calculated. In addition, a method to determine the compressive-to-tensile modulus ratio using uniaxial compressive and IDT test results is illustrated for one of the tested HMA mixes. / Ph. D.

Submitted by Cássia Santos (cassia.bcufg@gmail.com) on 2014-09-11T11:50:01Z No. of bitstreams: 2 Dissertacao Diego Americo Guedes.pdf: 971567 bytes, checksum: a39a61e190ff600e318da0dd24eb108c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-09-11T11:50:01Z (GMT). No. of bitstreams: 2 Dissertacao Diego Americo Guedes.pdf: 971567 bytes, checksum: a39a61e190ff600e318da0dd24eb108c (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / In this work we present and evaluate a modeling methodology that describes the creation of a topology for wireless mesh networks, and how this topology changes over time. The modeling methodology is based on network science, which is a multidisciplinary research area that has a lot of tools to help in the study and analysis of networks. In wireless mesh networks, the relative importance of the nodes is often related to the topological aspects, and data flow. However, due to the dynamics of the network, the relative importance of the nodes may vary in time. In the context of network science, the concept of centrality metric represents the relative importance of a node in the network. In this work we show also that the current centrality metrics are not able to rank properly the nodes in wireless mesh networks. Then we propose a new metric of centrality that ranks the most important nodes in a wireless mesh network over time. We evaluate our proposal using data from a case study of the proposed modeling methodology and also from real wireless mesh networks, achieving satisfactory performance. The characteristics of our metric make it a useful tool for monitoring dynamic networks. / Neste trabalho, apresentamos e avaliamos uma modelagem que descreve a criação de uma topologia para redes em malha sem fio e como essa se altera no tempo. A modelagem é baseada em ciência das redes (network science), uma área multidisciplinar de pesquisa que possui uma grande quantidade de ferramentas para auxiliar no estudo e análise de redes. Em redes em malha sem fio, a importância relativa dos nós é frequentemente relacionada a aspectos topológicos e ao fluxo de dados. Entretanto, devido à dinamicidade da rede, a importância relativa de um nó pode variar no tempo. No contexto de ciência de redes, o conceito de métricas de centralidade reflete a importância relativa de um nó na rede. Neste trabalho, mostramos também que as métricas atuais de centralidade não são capazes de classificar de maneira adequada os nós em redes em malha sem fio. Propomos então uma nova métrica de centralidade que classifica os nós mais importantes em uma rede em malha sem fio ao longo do tempo. Avaliamos nossa proposta com dados obtidos de um estudo de caso da modelagem proposta e de redes em malha sem fio reais, obtendo desempenho satisfatório. As características da nossa métrica a tornam uma ferramenta útil para monitoramento de redes dinâmicas.

Ces travaux abordent la problématique du contrôle endogène dans les Systèmes Multi-Agents (SMA) pour la résolution de problèmes complexes, que nous explorons grâce au problème de partage de ressources critiques. Les problèmes dits complexes que nous abordons se caractérisent par une explosion combinatoire du nombre de solutions avec la taille des problèmes, une forte dynamique des données du problème induite par un environnement ouvert dans lequel de nombreux événements peuvent avoir lieu, une grande complexité systémique issue des interdépendances entre les nombreuses variables du problèmes et enfin une décentralisation du processus de résolution imposée par une distribution physique et fonctionnelle des variables incompatible avec une vision centralisée du problème. Un parcours complet des espaces de recherche associés à de tels problèmes est irréaliste en un temps acceptable, il est alors nécessaire d'employer des méthodes de résolution dite incomplètes. Quelque soit l'approche incomplète considérée, le parcours incomplet de l'espace de recherche requiert un contrôle afin de maximiser la probabilité de converger vers une solution satisfaisante. Nous identifions trois niveaux de contrôle du parcours de l'espace de recherche indépendamment de l'approche utilisée : un contrôle statique (définition a priori du comportement du système), un contrôle dynamique (évoluant en cours de résolution selon des mécanismes préétablis) et un contrôle adaptatif (évoluant dynamiquement en cours de résolution). Nous montrons qu'un contrôle endogène de l'activité du système, c.-à-d. un contrôle adaptatif issu de l'activité même des agents, est nécessaire au guidage du parcours de l'espace de recherche dans le contexte de résolution de problèmes complexes. Ces travaux ayant été réalisés dans un contexte de collaboration industrielle, ils s'appuient sur une approche développée au cours de précédents travaux : CESNA (Complex Exchanges between Stigmergic Negotiating Agents). CESNA est une approche multi-agents auto-organisationnelle exploitant des agents situés dans un environnement matérialisant le problème et exploité par un processus de résolution basé sur une négociation stigmergique entre les agents. Le cas applicatif utilisé par l'approche CESNA et permettant d'illustrer ces travaux est le problème de partage de ressources critiques, caractérisé par un ensemble restreint de ressources exploitées par un grand nombre de consommateurs. Nos contributions sont de deux types : nous avons dans un premier temps proposé des évolutions de la représentation du problème exploitée par l'approche initiale (CESNA) afin d'en supprimer les limitations interdisant un passage à l'échelle, et dans un second temps, nous avons défini un nouveau modèle (MANA : Multi-level bAlancing Negotiating Agents) exploitant cette nouvelle représentation à l'aide d'un nouveau processus de résolution basé sur des mécanismes endogènes de contrôle de l'activité du système. Ces mécanismes reposent sur la matérialisation des effets microscopiques du phénomène macroscopique à orienter (le parcours de l'espace de recherche) afin de le rendre perceptible localement par les agents. Nos mesures montrent que ce nouveau modèle permet le passage à l'échelle (la résolution de problèmes industriels de grande taille) et une amélioration significative des performances de résolution par rapport à l'approche initiale montrant ainsi l'efficacité du guidage permis par les mécanismes utilisés. / This work addresses the issue of the endogenous control of Multi-Agents Systems (MAS) for solving complex problems, which we explore through the critical resources sharing problem. The complex problems we address are characterized by a combinatorial explosion of number of solutions with the size of the problems, a strong dynamic of the problem's data caused by an open environment in which many events can take place, a huge systemic complexity caused by the interdependencies between the many variables of the problem and a decentralization of the resolution process imposed by a physical and functional distribution of the variables incompatible with a centralized view of the problem. A complete course of the search space associated with such problems is unrealistic in an acceptable time, it is necessary to employ resolution methods known as incomplete. Whatever the incomplete approach considered, the incomplete course of the search space requires a control to maximize the probability of converging to a satisfactory solution. We identify three levels of control of the course of the search space regardless of the used approach : a static control (textit a priori definition of the behavior of the system), a dynamic control (evolving during the resolution according to pre-established mechanisms) and adaptive control (dynamically evolving during resolution). We show that an endogenous control of the system activity, ie. an adaptive control from the agents activity, is necessary to guide the course of the search space in the context of solving complex problems. This work was made in a context of industrial collaboration, they rely on an approach developed in previous work : CESNA (Complex Exchanges Between Stigmergic Negotiating Agents). CESNA is a multi-agent self-organizational approach using agents situated in an environment embodying the problem and used by a resolution process based on a stigmergic negotiation between agents. The application used by the CESNA approach allowing to illustrate this work is the critical resources sharing problem, characterized by a limited set of resources exploited by many consumers. Our contributions are of two kinds : we initially proposed changes in the representation of the problem used by the initial approach (CESNA) to remove restrictions prohibiting scalability, and in a second time we defined a new model (MANA : Multi-level balancing Negotiating Agents) using this new representation with a new resolution process based on endogenous control mechanisms of the system activity. These mechanisms are based on the materialization of the microscopic effects of the macroscopic phenomenon to direct (the path in the search space) to make it noticeable by agents. Our measurements show that this new model allows the scaling (the resolution of industrial problems) and a significant performances improvement of the resolution showing the effectiveness of the control allowed by the mechanisms used.