A indústria de microeletrônica tem recorrido cada vez mais à metodologia de projeto baseado em células para fazer frente à crescente complexidade dos projetos de circuitos integrados digitais, uma vez que circuitos baseados em células são projetados mais rápida e economicamente que circuitos full-custom. Entretanto, apesar do progresso ocorrido na área de Electronic Design Automation, circuitos digitais baseados em células apresentam desempenho inferior ao de circuitos full-custom. Assim, torna-se interessante encontrar maneiras de se fazer com que circuitos baseados em células tenham desempenho próximo ao de circuitos full-custom, sem que isso implique elevação significativa nos custos do projeto. Com tal objetivo em vista, esta tese apresenta contribuições para um fluxo automático de otimização local para circuitos digitais baseados em células. Por otimização local se entende a otimização do circuito em pequenas janelas de contexto, onde são feitas otimizações considerando o contexto global. Deste modo, a otimização local pode incluir a detecção e isolamento de regiões críticas do circuito e a geração de redes lógicas e de redes de transistores de diferentes topologias que são dimensionadas de acordo com as restrições de projeto em questão. Como as otimizações locais atuam em um contexto reduzido, várias soluções podem ser obtidas considerando as restrições locais, entre as quais se escolhe a mais adequada para substituir o subcircuito (região crítica) original. A contribuição específica desta tese é o desenvolvimento de um método de dimensionamento de subcircuitos capaz de obter soluções com área ativa mínima, respeitando a capacitância máxima de entrada, a carga a ser acionada, e a restrição de atraso imposta. O método é baseado em uma formulação de logical effort, e a principal contribuição é calcular analiticamente a derivada da área para obter área mínima, ao invés de fazer a derivada do atraso para obter o atraso mínimo, como é feito na formulação tradicional do logical effort. Simulações elétricas mostram que o modelo proposto é muito preciso para uma abordagem de primeira ordem, uma vez que apresenta erros médios de 1,48% para dissipação de potência, 2,28% para atraso de propagação e 6,5% para os tamanhos dos transistores. / Microelectronics industry has been relying more and more upon cell-based design methodology to face the growing complexity in the design of digital integrated circuits, since cell-based integrated circuits are designed in a faster and cheaper way than fullcustom circuits. Nevertheless, in spite of the advancements in the field of Electronic Design Automation, cell-based digital integrated circuits show inferior performance when compared with full-custom circuits. Therefore, it is desirable to find ways to bring the performance of cell-based circuits closer to that of full-custom circuits without compromising the design costs of the former circuits. Bearing this goal in mind, this thesis presents contributions towards an automatic flow of local optimization for cellbased digital circuits. By local optimization, it is meant circuit optimization within small context windows, in which optimizations are done taking into account the global context. This way, local optimization may include the detection and isolation of critical regions of the circuit and the generation of logic and transistor networks; these networks are sized according to the existing design constraints. Since local optimizations act in a reduced context, several solutions may be obtained considering local constraints, out of which the fittest solution is chosen to replace the original subcircuit (critical region). The specific contribution of this thesis is the development of a subcircuit sizing method capable of obtaining minimum active area solutions, taking into account the maximum input capacitance, the output load to be driven, and the imposed delay constraint. The method is based on the logical effort formulation, and the main contribution is to compute the area derivative to obtain minimum area, instead of making the delay derivative to obtain minimum delay, as it is done in the traditional logical effort formulation. Electrical simulations show that the proposed method is very precise for a first order approach, as it presents average errors of 1.48% in power dissipation, 2.28% in propagation delay, and 6.5% in transistor sizes.

A programação orientada a aspectos é uma abordagem que utiliza conceitos da separação de interesses para modularizar o software de maneira mais adequada. Com o surgimento dessa abordagem vieram também novos desafios, dentre eles o teste de programas orientados a aspectos. Duas estratégias de ordenação de classes e aspectos para apoiar o teste de integração orientado a aspectos são propostas nesta tese. As estratégias de ordenação tem o objetivo de diminuir o custo da atividade de teste por meio da diminuição do número de stubs implementados durante o teste de integração. As estratégias utilizam um modelo de dependências aspectuais e um modelo que descreve dependências entre classes e aspectos denominado AORD (Aspect and Oriented Relation Diagram) também propostos neste trabalho. Tanto o modelo de dependências aspectuais como o AORD foram elaborados a partir da sintaxe e semântica da linguagem AspectJ. Para apoiar as estratégias de ordenação, idealmente aplicadas durante a fase de projeto, um processo de mapeamento de modelos de projeto que usam as notações UML e MATA para o AORD é proposto neste trabalho. O processo de mapeamento é composto de regras que mostram como mapear dependências advindas da programação orientada a objetos e também da programação orientada a aspectos. Como uma forma de validação das estratégias de ordenação, do modelo de dependências aspectuais e do AORD, um estudo exploratório de caracterização com três sistemas implementados em AspectJ foi conduzido. Durante o estudo foram coletadas amostras de casos de implementação de stubs e drivers de teste. Os casos de implementação foram analisados e classificados. A partir dessa análise e classificação, um catálogo de stubs e drivers de teste é apresentado / Aspect-oriented programming is an approach that uses principles of separation of concerns to improve the sofware modularization. Testing of aspect-oriented programs is a new challenge related to this approach. Two aspects and classes test order strategies to support integration testing of aspect-oriented programs are proposed in this thesis. The objective of these strategies is to reduce the cost of testing activities through the minimization of the number of implemented stubs during integration test. An aspectual dependency model and a diagram which describes dependencies among classes and aspects called AORD (Aspect and Object Relation Diagram) used by the ordering strategies are also proposed. The aspectual dependency model and the AORD were defined considering the syntax constructions and the semantics of AspectJ. As the proposed estrategies should be applied in design phase of software development, a process to map a desing model using UML and MATA notations into a AORD is proposed in order to support the ordering strategies. The mapping process is composed by rules that show how to map both aspect and object-oriented dependencies. A characterization exploratory study using three systems implemented with AspectJ was conducted to validate the ordering strategies, the aspectual dependency model and the AORD. Interesting samples of stubs implementations were collected during the study conduction. The stubs were analyzed and classified. Based on these analysis and classification a catalog of stubs and drivers is presented

No Brasil, a parcela orgânica dos resíduos sólidos urbanos (RSU) representa mais de 50% de sua composição, na grande maioria dos municípios. No entanto, a compostagem, como método de tratamento dos resíduos orgânicos, não é empregada como poderia, somente 1,5% dos RSU no país é compostados; mesmo a compostagem caseira sendo prática de baixo custo e apropriada a áreas residenciais não é usual. O presente trabalho enfatiza a educação ambiental (EA) como instrumento para a organização e participação social, visando à minimização de resíduos sólidos urbanos, através da implantação de composteiras caseiras. O enfoque é dado no envio dos resíduos orgânicos domiciliares para compostagem caseira e na incorporação de novos hábitos, após execução de programa de educação ambiental em uma comunidade, do município de Campos do Jordão, São Paulo, Brasil. No presente estudo, partiu-se das seguintes hipóteses; comunidades de baixos ingressos e pouca instrução, localizadas em bairros periféricos de centros urbanos, são capazes de se organizar e alterar seu comportamento com relação à questão da geração e descarte de RSU, quando convidados a integrar grupos submetidos a programa de Educação Ambiental, com metodologia participativa; aliando-se atividades teóricas e práticas elaborado de acordo com as necessidades específicas da comunidade e implantados considerando-se a realidade local. Os resultados alcançados foram a organização social da comunidade, com o desvio de 83,5% dos resíduos orgânicos do aterro para a compostagem, isso quando não foram minimizados antes, no aproveitamento completo dos alimentos. A prática da compostagem possibilitou testar vários tipos de composteira caseira e garantiu melhorias nas condições de disposição dos RSU, reduzindo os impactos ambientais. / In Brazil, the organic portion of the solid wastes represents more than 50% of its composition in most of the cities. However, the composting , as a method of organic wastes treatment, is not applied as it could be, only 1.5% of the Urban Solid Waste (USW or in Portuguese, RSU) is recycled; even the home composting, which has a low cost and is appropriated in residential areas, is not common. This current paper emphasizes the environmental education as an instrument for the social organization and participation as well as minimization of solid wastes, which are essential elements for a sustainable development. The approach is based on the reduction of solid wastes by sending the home organic waste to home composting and the incorporation of new habits after the execution of an environmental education program in a community from the city of Campos do Jordão (São Paulo - Brazil). The research was originated on the hypothesis that communities with lack of basic facilities and lower education rates located in surrounding areas of urban centers are capable of organizing and changing its habits in relation to production and discarding of USW. This is possible especially when people are invited to integrate groups committed to an environmental education program according to the specific needs of the community and considering the local reality. The obtained results were the social organization of the community, with the allocation of 83,5% of the organic wastes from landfills to composting, that is when it was not minimized before, with the complete use of food. The composting made it to possible to test various types of home composting and assured improvements in the disposal conditions of the USW, reducing environmental impact.

Den kommersiella fastighetsmarknaden är till skillnad från bostadsmarknaden, inte utsatt för högre efterfrågan än utbud. Istället finns det ett större utbud för hyresgästerna att välja mellan. För att locka nya kunder måste fastighetsbolagen vara tillräckligt flexibla för att tillgodose behoven hos den eventuellt nya hyresgästen. Genom att anpassa anläggningarna för kundens behov säkerställer fastighetsägaren möjligheten att maximera hyresgästens vinst vilket i sin tur ökar viljan till att betala en högre hyra. Studien syftar till att undersöka vilka faktorer fastighetsbolagen utgår ifrån gällande riskminimering vid bedömning av hyresgästanpassningar.Studien genomfördes med hjälp av en kvalitativ metod för att samla information, åsikter och erfarenheter från fem liknande men olika fastighetsbolag, som är aktiva på fastighetsmarknaden. Företagens struktur skiljer sig åt då de inte arbetar i samma område.Studien kom fram till att de flesta företag som arbetar på fastighetsmarknaden arbetar på ett liknande sätt. Vad som skiljer dem från varandra är det faktum att de undviker vissa typer av kunder, som till exempel restauranger, spa-anläggningar, eller call-center. Den gemensamma nämnaren är att samtliga fastighetsbolag försöker undvika de branscher där de besitter minst kunskap. Bristen på kunskap och erfarenhet inom vissa områden försvårar bedömningen och tvingar företagen att spendera mer tid och pengar på att minimera risken för en negativ investering. För att minimera riskerna lägger alla företag stor vikt vid att bibehålla goda relationer, skapa en god hyresgästmix, skapa rörlighet inom beståndet, samt genomför en genomgående ekonomisk prövning av hyresgästerna. / The commercial real estate market is, unlike the housing market not suffering from a higher demand than supply which gives the tenants the option of picking and choosing when considering new facilities. To attract new customers, real estate companies must be flexible enough to satisfy the needs of the possibly new tenant. By adapting the facilities to fit the needs of the customer the real estate owner ensures the possibilities of maximizing the tenants’ profits which in turn increases the will to pay a higher rent. The study aims to investigate what factors real estate companies focuses on while considering investing in facility adaptations. The study was conducted using a qualitative method in order to gather information, opinions and experiences from five, similar but different real estate companies that are present on and shaping the real estate market. The company’s business structure differs as they do not work entirely in the same field. The study came to the conclusion that most companies working on the real estate market operates similar to each other. What differentiates them from one and other is the fact that avoids certain types of customers, being restaurants, spa-facilities or call-centers. The common denominator is that they all chose to avoid the types they know the least about. The lack of knowledge, experience and confidence in certain fields prohibits companies to choose that kind of customer, or at least running the numbers an extra time to make sure to prevents future risks. The real estate companies are putting a lot of effort in maintaining good relations, a great mix of tenants, creating flexibility within their real estate portfolio and analyzing their future tenants economically.

Nous nous intéressons à estimer la moyenne d'une variable aléatoire de loi à queue lourde. Nous adoptons une approche plus robuste que la moyenne empirique classique communément utilisée. L'objectif est de développer des inégalités de concentration de type sous-gaussien sur l'erreur d'estimation. En d'autres termes, nous cherchons à garantir une forte concentration sous une hypothèse plus faible que la bornitude : une variance finie. Deux estimateurs de la moyenne pour une loi à support réel sont invoqués et leurs résultats de concentration sont rappelés. Plusieurs adaptations en dimension supérieure sont envisagées. L'utilisation appropriée de ces estimateurs nous permet d'introduire une nouvelle technique de minimisation du risque empirique pour des variables aléatoires à queue lourde. Quelques applications de cette technique sont développées. Nous appuyons ces résultats sur des simulations sur des jeux de données simulées. Dans un troisième temps, nous étudions un problème d'estimation multivarié dans le cadre des U-statistiques où les estimateurs précédents offrent, là aussi, une généralisation naturelle d'estimateurs présents dans la littérature. / In this thesis, we are interested in estimating the mean of heavy-tailed random variables. We focus on a robust estimation of the mean approach as an alternative to the classical empirical mean estimation. The goal is to develop sub-Gaussian concentration inequalities for the estimating error. In other words, we seek strong concentration results usually obtained for bounded random variables, in the context where the bounded condition is replaced by a finite variance condition. Two existing estimators of the mean of a real-valued random variable are invoked and their concentration results are recalled. Several new higher dimension adaptations are discussed. Using those estimators, we introduce a new version of empirical risk minimization for heavy-tailed random variables. Some applications are developed. These results are illustrated by simulations on artificial data samples. Lastly, we study the multivariate case in the U-statistics context. A natural generalization of existing estimators is offered, once again, by previous estimators.

Content distribution with mobile-to-mobile cooperation is studied. Data is sent to mobile terminals on a long range link then the terminals exchange the content using an appropriate short range wireless technology. Unicasting and multicasting are investigated, both on the long range and short range links. Energy minimization is formulated as an optimization problem for each scenario, and the optimal solutions are determined in closed form. Moreover, the schemes are applied in public safety vehicular networks, where Long Term Evolution (LTE) network is used for the long range link, while IEEE 802.11 p is considered for inter-vehicle collaboration on the short range links. Finally, relay-based multicasting is applied in high speed trains for energy and delay minimization. Results show that cooperative schemes outperform non-cooperative ones and other previous related work in terms of energy and delay savings. Furthermore, practical implementation aspects of the proposed methods are also discussed.

Topological evolution is a new dynamical systems model of biological evolution occurring within a genomic state space. It can be modeled equivalently as a stochastic dynamical system, a stochastic differential equation, or a partial differential equation drift-diffusion model. An application of this approach is a model of disease evolution tracing diseases in ways similar to standard functional traits (e.g., organ evolution). Genetically embedded diseases become evolving functional components of species-level genomes. The competition between species-level evolution (which tends to maintain diseases) and individual evolution (which acts to eliminate them), yields a novel structural topology for the stochastic dynamics involved. In particular, an unlimited set of dynamical time scales emerges as a means of timing different levels of evolution: from individual to group to species and larger units. These scales exhibit a dynamical tension between individual and group evolutions, which are modeled on very different (fast and slow, respectively) time scales. This is analyzed in the context of a potentially major constraint on evolution: the species-level enforcement of lifespan via (topological) barriers to genomic longevity. This species-enforced behavior is analogous to certain types of evolutionary altruism, but it is denoted here as extreme altruism based on its potential shaping through mass extinctions. We give examples of biological mechanisms implementing some of the topological barriers discussed and provide mathematical models for them. This picture also introduces an explicit basis for lifespan-limiting evolutionary pressures. This involves a species-level need to maintain flux in its genome via a paced turnover of its biomass. This is necessitated by the need for phenomic characteristics to keep pace with genomic changes through evolution. Put briefly, the phenome must keep up with the genome, which occurs with an optimized limited lifespan. An important consequence of this model is a new role for diseases in evolution. Rather than their commonly recognized role as accidental side-effects, they play a central functional role in the shaping of an optimal lifespan for a species implemented through the topology of their embedding into the genome state space. This includes cancers, which are known to be embedded into the genome in complex and sometimes hair-triggered ways arising from DNA damage. Such cancers are known also to act in engineered and teleological ways that have been difficult to explain using currently very popular theories of intra-organismic cancer evolution. This alternative inter-organismic picture presents cancer evolution as occurring over much longer (evolutionary) time scales rather than very shortened organic evolutions that occur in individual cancers. This in turn may explain some evolved, intricate, and seemingly engineered properties of cancer. This dynamical evolutionary model is framed in a multiscaled picture in which different time scales are almost independently active in the evolutionary process acting on semi-independent parts of the genome. We additionally move from natural evolution to artificial implementations of evolutionary algorithms. We study genetic programming for the structured construction of machine learning features in a new structural risk minimization environment. While genetic programming in feature engineering is not new, we propose a Lagrangian optimization criterion for defining new feature sets inspired by structural risk minimization in statistical learning. We bifurcate the optimization of this Lagrangian into two exhaustive categories involving local and global search. The former is accomplished through local descent with given basins of attraction while the latter is done through a combinatorial search for new basins via an evolution algorithm.

Two important developments are addressed by this dissertation. First, the Psychological Inventory of Criminal Thinking Styles-Simplified Version (PICTS-SV) was examined in relation to the original PICTS. Second, the vulnerability of the PICTS-SV to intentional risk minimization (RM) was tested. Two separate studies recruited a total of 150 offenders from a court-mandated residential substance use treatment facility. As expected, Study I established the PICTS-SV's good concurrent validity with the PICTS, especially at the broad composite scale level. For Study II, criminal thinking failed to show the anticipated convergence with HCR-20 risk classifications or forensic correlates. Potential explanations, including a restricted range of risk levels in this sample, are discussed. As a particular strength, the findings highlight that the PICTS-SV, in contrast to many risk measures, displays robust resistance to RM distortion, although revisions to its Df-r validity scale are warranted. These results overall demonstrate strong evidence of the PICTS-SV's utility for assessing a dynamic criminogenic need to inform effective interventions and accurate risk determinations.

Motivation: Improving the prediction of structures, especially those containing pseudoknots (structures with crossing base pairs) is an ongoing challenge. Current alignment-based prediction algorithms only find the consensus structure, and their alignments can come from structure-based alignment algorithms, which is more reliable, but come with an increased cost compared to sequence-based alignment algorithms. This step can be removed; however, non-alignment based algorithms neglect structural information that can be found within similar sequences. Results: We present a new method for prediction of RNA pseudoknotted secondary structures that combines the strengths of MFE prediction and alignment-based methods. KnotAli takes an RNA sequence alignment and uses covariation and thermodynamic energy minimization to predict secondary structures for each individual sequence in the alignment. We compared KnotAli's performance to that of three other alignment-based algorithms, on a large data set of 10 families with pseudoknotted and pseudoknot-free reference structures. We produced sequence alignments for each family using two well-known sequence aligners (MUSCLE and MAFFT). We found KnotAli to be superior in 6 of the 10 families for MUSCLE and 7 of the 10 for MAFFT. We find KnotAli's predictions to be less dependent on alignment quality. In particular, KnotAli is shown to have more accurate predictions compared to other leading methods as alignment quality deteriorates. Availability: The algorithm can be found online on Github at https://github.com/mateog4712/KnotAli / Graduate / 2022-08-16

This work deals with the possibilities of employing a genetic algorithm to edge detection. There is introduced a project which uses enhanced image divided into sub-regions, on which detection by genetic algorithm is applied. To achieving our goals are used individuals in two-dimensional bit arrays, for which are specially adjusted mutation and crossover operators. Cost minimization approach is used as fitness function. The project was created and tested in Matlab environment.