Domain-specific, “little” languages are commonplace in computing. So too is the need to implement such languages; to meet this need, we have created SPARK (Scanning, Parsing, And Rewriting Kit), a toolkit for little language implementation in Python, an object-oriented scripting language. SPARK greatly simplifies the task of little language implementation. It requires little code to be written, and accommodates a wide range of users—even those without a background in compiler theory. Our toolkit is seeing increasing use on a variety of diverse projects. SPARK was designed to be easy-to-use with few limitations, and relies heavily on Earley's general parsing algorithm internally, which helps in meeting these design goals. Earley's algorithm, in its standard form, can be hard to use; indeed, experience with SPARK has highlighted several problems with the practical use of Earley's algorithm. Our research addresses and provides solutions for these problems, making some significant improvements to the implementation and use of Earley's algorithm. First, Earley's algorithm suffers from the performance problem . Even under optimum conditions, a standard Earley parser is burdened with overhead. We extend directly-executable parsing techniques for use in Earley parsers, the results of which run in time comparable to the much-more-specialized LALR(1) parsing algorithm. Second is what we call the delayed action problem. General parsers like Earley must, in the worst case, read the entire input before executing any semantic actions associated with the grammar rules. We attack this problem in two ways. We have identified conditions under which it is safe to execute semantic actions on the fly during recognition; as a side effect, this has yielded space savings of over 90% for some grammars. The other approach to the delayed action problem deals with the difficulty of handling context-dependent tokens. Such tokens are easy to handle using what we call “Schrödinger's tokens,” a superposition of token types. Finally, Earley parsers are complicated by the need to process grammar rules with empty right-hand sides. We present a simple, efficient way to handle these empty rules, and prove that our new method is correct. We also show how our method may be used to create a new type of LR(0) automaton which is ideally suited for use in Earley parsers. Our work has made Earley parsing faster and more space-efficient, turning it into an excellent candidate for practical use in many applications. / Graduate

Resumo: A operação de retificação cilíndrica externa de mergulho têm sido bastante empregada no processo de fabricação de componentes que necessitem de excelente qualidade superficial obtida dentro de baixos níveis de tolerância dimensional. O tempo de centelhamento spark-out) é um parâmetro que permite que se alcance as dimensões desejadas, por meio da eliminação das deformações elásticas oriundas das intensas forças que agem na interface de contato peçaferramenta. O tempo de spark-out é definido como um período de inexistência de avanços do rebolo, todavia com remoção de material da peça que busca o posicionamento real. A experimentação envolvendo o tempo de centelhamento será aplicada na operação de retificação utilizando três métodos de lubri-refrigeração, sendo eles convencional, otimizado e MQL (Mínima Quantidade de Lubrificação) para que, desta forma, seja possível fazer uma otimização global do processo. Optou-se por trabalhar com a técnica de MQL pelo fato desta se apresentar como uma nova tendência capaz de proporcionar redução de custos e ainda evitar uma intensa degradação do meio-ambiente, ocasionada por fluidos convencionais. O desempenho do processo foi verificado por meio dos seguintes parâmetros de saída: força tangencial de corte, emissão acústica, rugosidade, desvios de circularidade e desgaste diametral da ferramenta abrasiva. Analisando-se os resultados constatou-se quais os tempos de spark-out mais adequados para o processo de retificação e também em quais condições de trabalho a técnica de MQL pode ser eficazmente empregada. / Abstract: The cylindrical plunge grinding operation has been used in the process of manufacture of components that need excellent gotten superficial quality of low levels of dimensional accuracy. Spark-out time is a parameter that has been sufficiently used exactly for contributing for the attainment of good surfaces with satisfactory geometric precision. This time is defined as a period of inexistence of advances of abrasive tool, and has as purpose to allow that the elastic deformations appeared at the moment of the advance of abrasive tool are eliminated. The experimentation involving spark-out was applied in the grinding operation using three types of coolant application, conventional and optimized and the Minimum Quantity of Lubrification (MQL), witch has been seen as environmentally correctly way, joining a little quantity of lubrificant oil with an intensive flow of compressed air. The performance of the process was verified by the following parameters: tangential cutting force, acoustic emission, roughness, roundness and wear of abrasive tool. The results shows what the most efficient spark-out applied in the grinding process and either conditions MQL can be well applied. / Orientador: Eduardo Carlos Bianchi / Coorientador: Paulo Roberto de Aguiar / Banca: Olívio Novaski / Banca: Luiz Eduardo de Angelo Sanchez / Mestre

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-03-14T23:51:19Z No. of bitstreams: 1 ArlindoRodriguesDaSilvaNeto_DISSERT.pdf: 3147140 bytes, checksum: 65ec83f6b7b7603769da720a2273e85b (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-03-16T23:01:46Z (GMT) No. of bitstreams: 1 ArlindoRodriguesDaSilvaNeto_DISSERT.pdf: 3147140 bytes, checksum: 65ec83f6b7b7603769da720a2273e85b (MD5) / Made available in DSpace on 2017-03-16T23:01:46Z (GMT). No. of bitstreams: 1 ArlindoRodriguesDaSilvaNeto_DISSERT.pdf: 3147140 bytes, checksum: 65ec83f6b7b7603769da720a2273e85b (MD5) Previous issue date: 2016-08-26 / Este trabalho consiste em criar uma ferramenta de BI (Business Intelligence) dispon?vel em nuvem (cloud computing) atrav?s de SaaS (Software as Service) utilizando t?cnicas de ETL (Extract, Transform, Load) e tecnologias de Big Data, com a inten??o de facilitar a extra??o descentralizada e o processamento de dados em grande quantidade. Atualmente, constata-se que ? praticamente invi?vel realizar uma an?lise consistente sem o aux?lio de um software para gera??o de relat?rios e estat?sticas. Para tais fins, a obten??o de resultados concretos com a tomada de decis?o exige estrat?gias de an?lise de dados e vari?veis consolidadas. Partindo dessa vis?o, enfatiza-se neste estudo o Business Intelligence (BI) com o objetivo de simplificar a an?lise de informa??es gerenciais e estat?sticas para propiciar indicadores atrav?s de gr?ficos ou listagens din?micas de dados gerenciais. Assim, ? poss?vel inferir que, com o crescimento exponencial dos dados torna-se cada vez mais dif?cil a obten??o de resultados de forma r?pida e consistente, tornando necess?rio atuar com novas t?cnicas e ferramentas para tratamentos de dados em larga escala. Este trabalho ? de natureza t?cnica de cria??o de um produto de Engenharia de Software, fundamentado a partir do estudo da arte da ?rea, e de um comparativo com as principais ferramentas existentes no mercado, evidenciando vantagens e desvantagens da solu??o criada. / This work is to create a BI tool (Business Intelligence) available in the cloud (cloud computing) through SaaS (Software as Service) using ETL techniques (extract, transform, load) and Big Data technologies, with the intention of facilitating decentralized extraction and data processing in large quantities. Currently, it appears that it is practically impossible conduct a consistent analysis without the aid of a software for reporting and statistics. For these purposes, the achievement of concrete results with decision making requires data analysis strategies and consolidated variable. From this view, it is emphasized in this study Business Intelligence (BI) in order to simplify the analysis of management information and statistics to provide indicators through graphs or dynamic lists of data management. Thus, it is possible to infer that with the exponential growth of data becomes increasingly difficult to obtain results quickly and consistently, making it necessary to work with new techniques and tools for large-scale data processing. This work is technical in nature to create a product of Software Engineering, based from the study of art in the area, and a comparison with the main existing tools on the market, showing advantages and disadvantages of the created solution. / 2020-12-31

O processo de microestampagem permite a fabricação de peças ou microcomponentes, podendo ser aplicado a diversas áreas da engenharia. Logo, este trabalho tem por objetivo desenvolver um micromotor de passo e avaliar os efeitos da miniaturização de seus componentes. A simulação computacional foi utilizada neste trabalho de forma a avaliar os defeitos surgidos com a miniaturização, através do software de elementos finitos DYNAFORM com “solver” LS-DYNA. O material empregado na carcaça foi o aço de baixo carbono ABNT 1010 e o aço inoxidável ABNT 304, e para o núcleo magnético do micromotor, composto pelo rotor e estator, utilizou-se o aço elétrico ABNT 35F 420M. A simulação computacional, além de identificar os problemas oriundos da miniaturização dos componentes, também foi utilizada para otimizar as ferramentas de microestampagem, demonstrando desta forma ser uma grande aliada para o desenvolvimento do processo. O processo de corte convencional em matriz não foi aplicado no corte do rotor e do estator, pois produziu defeitos como empenamento e rebarbas. Ao invés disso, empregou-se o processo de corte por eletroerosão a fio, que produziu peças planas e superfícies lisas. / The process of micro deep drawing is a micro-technology which allows the fabrication of microcomponents and can be applied to various fields of engineering. This study aims to develop the components of a micromotor step using this technology and to evaluate the effects of the microfabrication of the motor frame, rotor and stator. A computer simulation was carried out in order to evaluate miniaturization of the components trough the finite element software DYNAFORM with “Solver” LS-DYNA. The material used in the motor housing was low carbon steel ABNT 1010 and stainless steel ABNT 304. However, in magnetic core, comprising the rotor and stator, the electric steel ABNT 35F 420M was employed. Micro deep drawing tools were developed based on the results obtained through simulation is a great ally to create microcomponents. The cutting process in the matrix was not employed to cut de rotor and the stator, because it produced defects such as warping and butts along the surface. Instead, wire cutting spark erosion was used and resulted in hat part and surfaces.

Uma maneira ecologicamente correta de manejar os recursos energéticos disponíveis e reduzir as emissões de gases de efeito estufa é utilizar biocombustíveis ao invés de combustíveis de origem fóssil em motores de combustão interna. Entretanto, o preço mais alto dos biocombustíveis pode ser um fator limitante para o aumento e viabilização do seu uso. Em relação ao etanol, para se obter misturas com mais de 80% de etanol em água o custo de produção cresce exponencialmente. Assim, se misturas de etanol com alto percentual de água, de menor custo, puderem ser utilizadas em motores de combustão interna com sucesso, esse combustível pode se tornar mais atrativo e mais amplamente utilizado. Este trabalho analisa o desempenho de um motor de ignição por centelha operando com etanol em diferentes percentuais de hidratação, através de simulações computacionais e procedimentos experimentais. Foi utilizado um motor monocilíndrico de 0,668L e naturalmente aspirado, com relação de compressão de 19:1 e injeção direta em pré-câmara, ciclo Diesel, foi modificado para operação em ciclo Otto - injeção de combustível no duto de admissão e relação de compressão de 12:1. Testes em dinamômetro foram conduzidos com o etanol hidratado comercial (95% de etanol e 5% de água) e com misturas de etanol e água com maiores percentuais de hidratação (conteúdo volumétrico de até 60% de etanol e 40% de água). Simulação computacional através de software de volumes finitos unidimensional foi utilizada para realizar a análise da combustão. Foi possível alcançar operação estável com misturas de até 40% de água em etanol e ocorreu aumento de eficiência térmica para misturas de até 30% de água. / An environmentally friendly way to manage the available energetic resources and to reduce greenhouse gas emissions is to use bio instead of fossil fuels in internal combustion engines. However, the sometimes higher prices of biofuels can be a limiting factor for their widespread and viable use. Concerning ethanol and its production costs, to obtain above 80% ethanol-in-water mixtures demands an exponentially increasing energy supply. Hence, if a low-cost high water content ethanol could be successfully burned in internal combustion engines it would be even more attractive and extensively used. This work analyzes the performance of a spark ignition engine running with ethanol with different percentages of hydration through numeric and experimental simulations. To achieve this goal, a 0,668L naturally aspirated single cylinder engine, with compression ratio of 19:1 and pre-chamber direct injection, operating at Diesel cycle was modified to operate in Otto cycle - port fuel injection, with a compression ratio of 12:1. Dynamometer tests were carried out with commercial hydrous ethanol (95% ethanol and 5% water) and water-in-ethanol blends with higher hydration levels (volumetric content up to 60% ethanol and 40% water). Computer simulation through one-dimensional finite volume software was carried out to perform a heat release analysis. It was possible to achieve stable operation with up to 40% water-in-ethanol blends and thermal efficiency increase was achieved for blends with up to 30% of water.

abstract: As the size and scope of valuable datasets has exploded across many industries and fields of research in recent years, an increasingly diverse audience has sought out effective tools for their large-scale data analytics needs. Over this period, machine learning researchers have also been very prolific in designing improved algorithms which are capable of finding the hidden structure within these datasets. As consumers of popular Big Data frameworks have sought to apply and benefit from these improved learning algorithms, the problems encountered with the frameworks have motivated a new generation of Big Data tools to address the shortcomings of the previous generation. One important example of this is the improved performance in the newer tools with the large class of machine learning algorithms which are highly iterative in nature. In this thesis project, I set about to implement a low-rank matrix completion algorithm (as an example of a highly iterative algorithm) within a popular Big Data framework, and to evaluate its performance processing the Netflix Prize dataset. I begin by describing several approaches which I attempted, but which did not perform adequately. These include an implementation of the Singular Value Thresholding (SVT) algorithm within the Apache Mahout framework, which runs on top of the Apache Hadoop MapReduce engine. I then describe an approach which uses the Divide-Factor-Combine (DFC) algorithmic framework to parallelize the state-of-the-art low-rank completion algorithm Orthogoal Rank-One Matrix Pursuit (OR1MP) within the Apache Spark engine. I describe the results of a series of tests running this implementation with the Netflix dataset on clusters of various sizes, with various degrees of parallelism. For these experiments, I utilized the Amazon Elastic Compute Cloud (EC2) web service. In the final analysis, I conclude that the Spark DFC + OR1MP implementation does indeed produce competitive results, in both accuracy and performance. In particular, the Spark implementation performs nearly as well as the MATLAB implementation of OR1MP without any parallelism, and improves performance to a significant degree as the parallelism increases. In addition, the experience demonstrates how Spark's flexible programming model makes it straightforward to implement this parallel and iterative machine learning algorithm. / Dissertation/Thesis / M.S. Computer Science 2014

Determinação do desempenho de um motor à combustão interna com ignição por centelha, sem modificação em sua taxa de compressão volumétrica, usando álcool etílico vaporizado como combustível. Para facilidade de obtenção de dados usou-se um sistema de aquecimento elétrico para a geração do vapor do álcool etílico. Mediu-se as descargas de ar e combustível, a potência no eixo e a temperatura dos gases de escape para vários ângulos de avanço de centelha e rotações do eixo do motor. Os resultados obtidos foram comparados com o desempenho do mesmo motor funcionando com gasolina e álcool, pelo sistema de mistura usando carburador. O processo de vaporização pode ser aplicado a motores do tipo ciclo Otto , que poderão funcionar com álcool etílico ou gasolina, com poucas alterações em seu desempenho. / Performance determination of a spark-ignition combustion-engine, without modification in compression ratio, fueled with etanol vapours. The data acquisition was simplified by the use of an electric heater to generate the etanol vapours. The data acquired are flow of air and fuel, net power and escape gases temperature to various spark advance angles and engine speed. The performance was compared with those obtained with the carburator system motor, gasoline and etanol as fuel. The vaporization process will be applied in Otto cycle engines that may work with etanol or gasoline as fuels, with few performance alterations.

Uma maneira ecologicamente correta de manejar os recursos energéticos disponíveis e reduzir as emissões de gases de efeito estufa é utilizar biocombustíveis ao invés de combustíveis de origem fóssil em motores de combustão interna. Entretanto, o preço mais alto dos biocombustíveis pode ser um fator limitante para o aumento e viabilização do seu uso. Em relação ao etanol, para se obter misturas com mais de 80% de etanol em água o custo de produção cresce exponencialmente. Assim, se misturas de etanol com alto percentual de água, de menor custo, puderem ser utilizadas em motores de combustão interna com sucesso, esse combustível pode se tornar mais atrativo e mais amplamente utilizado. Este trabalho analisa o desempenho de um motor de ignição por centelha operando com etanol em diferentes percentuais de hidratação, através de simulações computacionais e procedimentos experimentais. Foi utilizado um motor monocilíndrico de 0,668L e naturalmente aspirado, com relação de compressão de 19:1 e injeção direta em pré-câmara, ciclo Diesel, foi modificado para operação em ciclo Otto - injeção de combustível no duto de admissão e relação de compressão de 12:1. Testes em dinamômetro foram conduzidos com o etanol hidratado comercial (95% de etanol e 5% de água) e com misturas de etanol e água com maiores percentuais de hidratação (conteúdo volumétrico de até 60% de etanol e 40% de água). Simulação computacional através de software de volumes finitos unidimensional foi utilizada para realizar a análise da combustão. Foi possível alcançar operação estável com misturas de até 40% de água em etanol e ocorreu aumento de eficiência térmica para misturas de até 30% de água. / An environmentally friendly way to manage the available energetic resources and to reduce greenhouse gas emissions is to use bio instead of fossil fuels in internal combustion engines. However, the sometimes higher prices of biofuels can be a limiting factor for their widespread and viable use. Concerning ethanol and its production costs, to obtain above 80% ethanol-in-water mixtures demands an exponentially increasing energy supply. Hence, if a low-cost high water content ethanol could be successfully burned in internal combustion engines it would be even more attractive and extensively used. This work analyzes the performance of a spark ignition engine running with ethanol with different percentages of hydration through numeric and experimental simulations. To achieve this goal, a 0,668L naturally aspirated single cylinder engine, with compression ratio of 19:1 and pre-chamber direct injection, operating at Diesel cycle was modified to operate in Otto cycle - port fuel injection, with a compression ratio of 12:1. Dynamometer tests were carried out with commercial hydrous ethanol (95% ethanol and 5% water) and water-in-ethanol blends with higher hydration levels (volumetric content up to 60% ethanol and 40% water). Computer simulation through one-dimensional finite volume software was carried out to perform a heat release analysis. It was possible to achieve stable operation with up to 40% water-in-ethanol blends and thermal efficiency increase was achieved for blends with up to 30% of water.

Large amounts of data in various forms are generated at a fast pace in today´s society. This is commonly referred to as “Big Data”. Making use of Big Data has been increasingly important for both business and in research. The forest industry is generating big amounts of data during the different processes of forest harvesting. In Sweden, forest infor-mation is sent to SDC, the information hub for the Swedish forest industry. In 2014, SDC received reports on 75.5 million m3fub from harvester and forwarder machines. These machines use a global stand-ard called StanForD 2010 for communication and to create reports about harvested stems. The arrival of scalable cloud technologies that com-bines Big Data with machine learning makes it interesting to develop an application to analyze the large amounts of data produced by the forest industry. In this study, a proof-of-concept has been implemented to be able to analyze harvest production reports from the StanForD 2010 standard. The system consist of a back-end and front-end application and is built using cloud technologies such as Apache Spark and Ha-doop. System tests have proven that the concept is able to successfully handle storage, processing and machine learning on gigabytes of HPR files. It is capable of extracting information from raw HPR data into datasets and support a machine learning pipeline with pre-processing and K-Means clustering. The proof-of-concept has provided a code base for further development of a system that could be used to find valuable knowledge for the forest industry.

Spark plasma sintering (SPS), also known as direct current sintering (DCS) is an advanced sintering technique that and uses a continuous pulsed direct current to rapidly process materials through Joule heating and offers significant advantages and versatility over conventional sintering methods. The technique features in energy saving owing to high heating rates and is very suitable for consolidation as well as diffusion bonding of electrical conductive advanced ceramic materials such as ultra high temperature ceramics (UHTCs). However, cooling rate in SPS also plays an important role as it directly influences the generation of residual stress especially for specimens consist of dissimilar phases such as composites and laminates primarily due to CTE mismatch. Therefore, in order to produce high quality materials, a zirconium diboride with addition of silicon carbide (ZrB2-SiC) ultra high temperature ceramic composite is selected to investigate the effect of cooling rate in SPS on microstructure and mechanical properties. After being densified at the target temperature, ZrB2-25vol%SiC specimens are cooled from 1800°C using controlled cooling rates of 10 °C/minute to ~225.5 °C/minute (free cooling). A time dependent finite element analysis (FEA) model is used to simulate the temperature gradients across the specimens at dwell times and during the cooling processes. The residual stress within the specimens are experimentally verified using X-ray diffraction (XRD) and Raman spectrometry, and found maximum residual stress within the specimen cooled at 225.5 °C/minute. Peak Hardness and moderate elastic modulus is found for specimen sintered at 1800 °C and cooled at 100 °C/minute, which make this temperature and cooling rate appropriate conditions for future fabrication of UHTCs with similar thermal and electrical properties. These materials are of great interest for their excellent high-temperature capabilities, wear and corrosion resistance, and are regarded as material candidates for engineering applications in extreme environments. Therefore, development of an effective joining technique is important since near-net shape fabrication is challenging, and joints formed by brazing or conventional solid-state diffusion bonding limit the mechanical strength and high temperature applications of the base materials. Using SPS we have rapidly and successfully joined ZrB2 to hafnium diboride (HfB2) at 1750 and 1800 °C within a minute through electric current assisted solid-state diffusion bonding. The electric current enables localized Joule heating as well as plastic deformation of the mating surface asperities, and enhances the elemental interdiffusion process at the HfB2/ZrB2 interfaces owing to electromigration, which leads to the formation of ZrxHf1-xB2 solid solution. A series of characterization and analytical techniques including scanning electron microscopy (SEM), wavelength dispersive spectroscopy (WDS), electron backscatter diffraction (EBSD), and scanning transmission electron microscopy (S/TEM) are employed to study the microstructure and chemical composition at of the HfB2/ZrB2 interfaces. Apart from enhanced diffusion as a result of electromigration, the applied electric current can also be use to promote plastic deformation in ZrB2, which does not go through gross plastic deformation due to its extremely high melting point and brittle nature even when elevated temperature and pressure are applied. Through “electroplastic effect” (an effect based on electromigration) the mobility and multiplication of the existing dislocations in ZrB2 is enhanced, and a “metal-like” primary recrystallization phenomenon in the ZrB2 is observed meaning the material has experienced a sufficient amount of plastic deformation and reached the critical dislocation density and configuration for nucleation of “strain-free” grains. The average grain size of the recrystallized grain is only ½ of its original value. These findings suggest great potentials in microstructural tailoring and grain refinement of conductive advanced ceramics using SPS, and provide promising ideas for future fabrications and applications.