In the video game industry, developers utilize game engines to bring their creations from concept to reality. However, the most widely used engine in the industry currently is Unreal Engine 5 or UE5, which has challenged established practices used by game developers since the early creation of 3D interactive media. One of these challenges is eliminating LODs or Level of Detail-based asset integration with the introduction of Nanite, an automatic LOD creation tool introduced in Unreal Engine 5. With this development, it is still being determined whether Nanite should immediately replace LODs due to its ability to cut out work required for LOD-based integration. This uncertainty has led to the purpose of this study, which is to research and understand the background and utilization of LODs and Nanite in 3D game asset creation while showcasing how both processes intertwine inside UE5.The following research questions will guide this study in answering questions and setting up foundation knowledge into LODs and Nanite to understand the importance of each optimization technique and why their usage matters to the future of 3D asset creation. First, what are LODs, and why are they used in 3D asset creation within the video game industry? Second, what is Nanite, and how does this process differentiate itself from the methods utilized in LOD creation? Third, what are the benefits and consequences of using either LODs or Nanite in 3D asset creation? Lastly, can both processes be utilized in tandem inside Unreal Engine 5.2.1 to allow developers to use the best abilities of both methods in their 3D asset creation pipelines?

The modular design methodology has been widely adopted to harness the complexity of large FPGA-based systems. As a result, a number of commercial and academic tool flows emerged to support modular design including Hierarchical Design Flow and Partial Reconfiguration Flow, OpenPR, HMFlow, PARBIT, REPLICA, GoAhead and QFlow frameworks. As all of these projects have shown, a modular approach raises the abstraction level, provides clear boundaries for incremental design, reduces placement complexity, and improves productivity. At the physical layer, modules can be compiled into rectangular regions, suitable for placement on the FPGA fabric. Creating a design then becomes the process of placing all of the modules on the FPGA, followed by inter-module routing. FPGAs, however, are not homogenous, and the shape of individual modules could greatly impact overall device utilization. Prior work in modular assembly utilize modules with a single shape and aspect ratio in the assembly process. Due to the increasing size and heterogeneity of contemporary FPGAs, the placement flexibility of such a module is becoming increasingly limited. This thesis introduces a process that exploits offline shape generation and exploration, enabling the selection of shapes using criterias such as resource usage efficiency, placement flexibility, and device utilization. Module shapes can be generated with these criterias in mind while still taking advantage of the reduced placement complexity of modular design and assembly / Master of Science

By researching natural disaster displacement and the process in which we rebuild, I have found that by creating a modular prefabricate unit that is both cost efficient and easy to construct, we can significantly reduce the rebuild time, reduce people from leaving, as well as encourage new residents to move to the effected area. It is important as an architect and designer to use our skills to better help humanity. By focusing on the effects of Hurricane Harvey in the Houston Area, I have developed a unit design, and infrastructure plan that can be used universally around the world to help effected cities and people survive after a natural disaster. These findings are useful in the fact that the United State has no universal plan when dealing with disaster events. By creating a plan to provide single and multi family units, and incorporating them within close distance to necessary needs and infrastructure, this plan has the potential to reduce rebuild time, and encourage economy growth. / Master of Architecture

With the deployment of sensors in hardware equipment and advanced metering infrastructure, system operators have access to unprecedented amounts of data. Simultaneously, grid-connected power electronics technology has had a large impact on the way electrical energy is generated, transmitted, and delivered to consumers. Artificial intelligence and machine learning can help address the new power grid challenges with enhanced computational abilities and access to large amounts of data. This thesis discusses the fundamentals of neural networks and their applications in power systems such as load forecasting, power system stability analysis, and fault diagnosis. It extends application of neural networks to inverter-based resources by studying the implementation and performance of a neural network controller emulator for voltage-sourced converters. It delves into how neural networks could enhance cybersecurity of a component through multiple hardware and software implementations of the same component. This ensures that vulnerabilities inherent in one form of implementation do not affect the system as a whole. The thesis also proposes a comprehensive support vector classifier (SVC)--based submodule open-circuit fault detection and localization method for modular multilevel converters. This method eliminates the need for extra hardware. Its efficacy is discussed through simulation studies in PSCAD/EMTDC software. To ensure efficient usage of neural networks in power system simulation softwares, this thesis entails the step by step implementation of a neural network custom component in PSCAD/EMTDC. The custom component simplifies the process of recreating a neural network in PSCAD/EMTDC by eliminating the manual assembly of predefined library components such as summers, multipliers, comparators, and other miscellaneous blocks. / Master of Science / Data analytics and machine learning play an important role in the power grids of today, which are continuously evolving with the integration of renewable energy resources. It is expected that by 2030 most of the electric power generated will be processed by some form of power electronics, e.g., inverters, from the point of its generation. Machine learning has been applied to various fields of power systems such as load forecasting, stability analysis, and fault diagnosis. This work extends machine learning applications to inverter-based resources by using artificial neural networks to perform controller emulation for an inverter, provide cybersecurity through heterogeneity, and perform submodule fault detection in modular multilevel converters. The thesis also discusses the step by step implementation of a neural network custom component in PSCAD/EMTDC software. This custom component simplifies the process of creating a neural network in PSCAD/EMTDC by eliminating the manual assembly of predefined library components.

This thesis presents a component-based approach to proving the correctness of programs involving pointers. Unlike previous work, our component-based approach supports modular reasoning, which is essential to the scalability of systems. Specifically, we specify the behavior of a graph-marking algorithm known as the Schorr-Waite algorithm, implement it using a component that captures the behavior and performance benefits of pointers, and prove that the implementation is correct with respect to the specification. We use the Resolve language in our example, which is an integrated programming and specification language that supports modular reasoning. The behavior of the algorithm is fully specified using custom definitions, pre- and post-conditions, and a complex loop invariant. Additional operations for the Resolve pointer component are introduced that preserve the accessibility of a system. These operations are used in the implementation of the algorithm. They simplify the proof of correctness and make the code shorter. / Master of Science

A estampagem incremental é um processo de deformação incremental de chapa que pode ser classificado em três modos distintos: estampagem incremental sem matriz, estampagem incremental com matriz parcial e estampagem com matriz total. A deformação ocorre devido ao contato entre a ferramenta e a chapa, localmente e progressivamente, ao longo de uma trajetória pré-definida. A chapa permanece presa a suportes que fixam as suas extremidades de maneira a impedir os deslocamentos provocados pela passagem da ferramenta. A primeira parte deste trabalho compreende estudos em elementos finitos, usando o software LS-Dyna, sobre a trajetória das deformações na estampagem incremental para a fabricação de flanges em chapas previamente furadas de liga de alumínio AA1050. Foram realizados testes de contato e de linha que permitiram definir parâmetros da simulação. Os resultados para as deformações foram confrontados com os resultados obtidos experimentalmente por outros autores e permitiram verificar o comportamento das deformações nos flanges. As deformações crescem montonicamente até os valores máximos. Este resultado confirma a teoria de que na estampagem incremental de chapas a fratura ocorre sem o prévio aparecimento da estricção. A segunda parte deste trabalho trata do desenvolvimento de um suporte modular aplicável a estampagem incremental, tanto na sua variante sem matriz quanto com matriz, com o intuito de aumentar a flexibilidade do processo com relação à geometria da peça a ser deformada. Foi empregada a técnica de análise de valor objetivando alcançar a melhor funcionalidade do sistema. Como resultado foi obtido um suporte modular que atende os requisitos de rigidez, flexibilidade, modularidade, agilidade na troca da chapa a ser deformada e simplicidade construtiva. / The sheet incremental forming can be classified into three basic configurations, depending on the number of contact points between the sheet, tool and die (when present). Single incremental forming (absence of specific dies) and two point incremental forming (presence of a partial or full die) can be distinguished. The process makes use of a simple, low-cost, hemispherical tipped tool to precisely and progressively shape a blank into a metal sheet along a predefined tool path. The sheet is fixed onto the rig to prevent lateral displacements caused by tool movement. The first part of this work includes studies about finite elements, using the LS-Dyna software, applied to deformation path in hole-flanging produced by incremental sheet forming. The investigation was carried out using aluminum alloy AA1050. Contact and line numerical results support simulation parameters choices. The results from the strains were compared with empirical ones obtained by other authors. The results showed the deformation mechanics behavior of the hole-flanging. The strain paths of hole-flanging produced by incremental sheet forming grew linearly and monotonically from the origin to the maximum achievable strains. This result confirms the absence of local necking along plane strain directions. The second part of this work deals with the development of a modular rig that can be applied to dieless, partial or total die single point incremental forming in order to increase the flexibility of the process concerning the geometry of the part to be deformed. The result was a modular rig with constructive simplicity and requirements of stiffness, flexibility and modularity when exchanging sheets.

O objetivo desta tese foi desenvolver um procedimento para projeto de arranjo físico modular. O procedimento usa um algoritmo genético de agrupamento para gerar módulos de arranjo físico em manufatura. Um módulo é um grupo de máquinas com um fluxo característico. O algoritmo genético de agrupamento (AGA) permite ao usuário especificar a priori o número desejado de módulos (problema de K-agrupamentos), e também trabalhar de forma que o número e formação dos módulos seja uma otimização do problema (problema de agrupamento automático). Uma característica importante do AGA é sua flexibilidade, pois fornece possibilidade ao usuário de dirigir seu raciocínio através da escolha de diferentes codificações do cromossomo, de funções de aptidão para avaliar a qualidade da solução, de medidas de similaridade para comparação de seqüências de operações e de métodos de geração da nova população. Para tal foram desenvolvidos três operadores de cruzamento e quatro operadores de mutação. Os experimentos permitiram avaliar o comportamento do AGA com diferentes operadores e configurações de parâmetros, através do número de vezes em que a melhor solução foi encontrada. Os módulos de arranjo físico gerados pelo AGA e o arranjo físico final da fábrica foram comparados aqueles da principal referência encontrada na bibliografia em projeto de arranjo físico modular. No arranjo físico final da fábrica, elaborado a partir das soluções do AGA, houve importante redução da distância total percorrida pelo conjunto de peças, demonstrando a eficácia do algoritmo genético de agrupamento. Dessa forma, os resultados apontaram o algoritmo genético de agrupamento como uma alternativa à geração de módulos de arranjo físico em projeto de arranjo físico modular. / The objective of this thesis was the development of a procedure to the design of modular facility layouts. The procedure uses a clustering genetic algorithm to generate layout modules. A module is a group of machines with a specific patterned flow. The clustering genetic algorithm (CGA) allows the specification of the desired number of modules (K-grouping problem) and also the optimization of the number of modules (automatic clustering problem). The genetic algorithm is very flexible and the user can guide his reasoning. It supplies different options of chromosome encoding, generation of the initial population, fitness function to evaluate the solution quality, different similarity measures for comparison of operation sequences and methods for generation of the new population. Three crossover operators and four mutation operators have been developed. The experiments have allowed evaluating the behavior of the CGA with different operators and parameters configurations, through the number of times in which the best solution was found. The layout modules generated by the CGA and the block layout were compared with the main reference which was found in literature in the design of modular facility layouts. In the block layout elaborated from the solutions of the CGA there was an important reduction of the total distance traveled by the set of parts, demonstrating the effectiveness of the clustering genetic algorithm. The results indicated that the clustering genetic algorithm is an alternative for generation of layout modules in the design of modular facility layouts.

Made available in DSpace on 2016-04-27T16:57:24Z (GMT). No. of bitstreams: 1 Helena Tavares de Souza.pdf: 3383599 bytes, checksum: 5db003708b9ac748a1318d7e06cdc12c (MD5) Previous issue date: 2013-03-14 / The purpose of the present paper is to investigate possible contributions to the Basic Education in the teaching of Modular function. To attend such purpose, the investigations were designed in a way so they answer to the research question: In what way the use of a pedagogical strategy based on the problem solving approach of with the software GeoGebra concur to amplify the understanding of High Schools teachers about the Modular Function theme under the algebraic and geometric points of view? This research has a qualitative approach with a content analysis made with four public and private High School teachers, who are also students of a Mathematic Education postgraduate course from a São Paulo s University. The instruments applied to this paper correspond to a semi structured questionnaire divided in four parts and non-structured interviews. The analyses are described under the light of Mathematic Education perspective by solving problems. This research does not focus mainly in the use of technologies, howeveroffers the software GeoGebra as a pedagogical strategy to the teaching of the issue in question. The results point to no differences in the investigated people s ideas related to mathematic problems and exercises; mathematic exercises, for some teachers are exercises, and for others they are mathematic problems, so this also shows that the use of the GeoGebra software concurs to amplify the understanding of some High School teachers about the Modular Function theme / Este trabalho tem como objetivo investigar possíveis contribuições a Educação Básica para o ensino de função modular. Para atender tal objetivo, as investigações foram delineadas de forma a responder à questão de pesquisa: De que forma o uso de uma estratégia pedagógica baseada em Resolução de Problemas com o emprego do software GeoGebra concorre para ampliar a compreensão de professores do Ensino Médio sobre o tema função modular dos pontos de vista algébrico e geométrico? A pesquisa tem uma abordagem qualitativa com análise de conteúdo realizada com quatro professores do Ensino Médio de escolas da rede pública e privada de São Paulo e que também são estudantes do curso de Pós-Graduação em Educação Matemática de uma universidade do Estado de São Paulo. Os instrumentos aplicados correspondem a um questionário semiestruturado dividido em quatro partes e entrevistas não-estruturadas. As análises são descritas na perspectiva da Resolução de Problemas sob à luz da Educação Matemática. A pesquisa não tem como foco principal analisar o uso das tecnologias, mas propõe a utilização do software GeoGebra como estratégia pedagógica para o ensino do tema em questão. Os resultados apontam que há diferenças nas concepções dos sujeitos da pesquisa quanto a exercícios e problemas matemáticos (o que é exercício matemático para alguns professores para outros é problema matemático) e também mostram que o emprego do software GeoGebra concorre para ampliar a compreensão de alguns professores do Ensino Médio quanto ao tema função modular

Estudamos a criptografia RSA como uma importante aplicação dos números primos e da aritmética modular. Apresentamos algumas sugestões de atividades relacionadas ao tema a serem desenvolvidas em sala de aula nas séries finais do ensino fundamental / We studied RSA cryptography as an important application to prime numbers and modular arithmetic. We present some suggestions of activities related to the subject to be developed in classrooms of the final years of elementary school vii

O objetivo desta tese foi desenvolver um procedimento para projeto de arranjo físico modular. O procedimento usa um algoritmo genético de agrupamento para gerar módulos de arranjo físico em manufatura. Um módulo é um grupo de máquinas com um fluxo característico. O algoritmo genético de agrupamento (AGA) permite ao usuário especificar a priori o número desejado de módulos (problema de K-agrupamentos), e também trabalhar de forma que o número e formação dos módulos seja uma otimização do problema (problema de agrupamento automático). Uma característica importante do AGA é sua flexibilidade, pois fornece possibilidade ao usuário de dirigir seu raciocínio através da escolha de diferentes codificações do cromossomo, de funções de aptidão para avaliar a qualidade da solução, de medidas de similaridade para comparação de seqüências de operações e de métodos de geração da nova população. Para tal foram desenvolvidos três operadores de cruzamento e quatro operadores de mutação. Os experimentos permitiram avaliar o comportamento do AGA com diferentes operadores e configurações de parâmetros, através do número de vezes em que a melhor solução foi encontrada. Os módulos de arranjo físico gerados pelo AGA e o arranjo físico final da fábrica foram comparados aqueles da principal referência encontrada na bibliografia em projeto de arranjo físico modular. No arranjo físico final da fábrica, elaborado a partir das soluções do AGA, houve importante redução da distância total percorrida pelo conjunto de peças, demonstrando a eficácia do algoritmo genético de agrupamento. Dessa forma, os resultados apontaram o algoritmo genético de agrupamento como uma alternativa à geração de módulos de arranjo físico em projeto de arranjo físico modular. / The objective of this thesis was the development of a procedure to the design of modular facility layouts. The procedure uses a clustering genetic algorithm to generate layout modules. A module is a group of machines with a specific patterned flow. The clustering genetic algorithm (CGA) allows the specification of the desired number of modules (K-grouping problem) and also the optimization of the number of modules (automatic clustering problem). The genetic algorithm is very flexible and the user can guide his reasoning. It supplies different options of chromosome encoding, generation of the initial population, fitness function to evaluate the solution quality, different similarity measures for comparison of operation sequences and methods for generation of the new population. Three crossover operators and four mutation operators have been developed. The experiments have allowed evaluating the behavior of the CGA with different operators and parameters configurations, through the number of times in which the best solution was found. The layout modules generated by the CGA and the block layout were compared with the main reference which was found in literature in the design of modular facility layouts. In the block layout elaborated from the solutions of the CGA there was an important reduction of the total distance traveled by the set of parts, demonstrating the effectiveness of the clustering genetic algorithm. The results indicated that the clustering genetic algorithm is an alternative for generation of layout modules in the design of modular facility layouts.