Talvez uma das maiores capacidades do ser humano seja a sua habilidade de aprender a partir de observações e transmitir o que aprendeu para outros humanos. Durante séculos, a humanidade vem tentado compreender o mundo em que vive e, a partir desse novo conhecimento adquirido, melhorar o mundo em que vive. O desenvolvimento da tecnologia colocou a descoberta de conhecimento em um momento ímpar na história da humanidade. Com os progressos da Ciência da Computação, e, em particular, da Inteligência Artificial - IA - e Aprendizado de Máquina -AM, hoje em dia é possível, a partir de métodos de inferência indutiva e utilizando um conjunto de exemplos, descobrir algum tipo de conhecimento implícito nesses exemplos. Entretanto, por ser uma área de pesquisa relativamente nova, e por envolver um processo tanto iterativo quanto interativo, atualmente existem poucas ferramentas que suportam eficientemente a descoberta de conhecimento a partir dos dados. Essa falta de ferramentas se agrava ainda mais no que se refere ao seu uso por pesquisadores em Aprendizado de Máquina e Aquisição de Conhecimento. Esses fatores, além do fato que algumas pesquisas em nosso Laboratório de Inteligência Computacional - LABIC - têm alguns componentes em comum, motivaram a elaboração do projeto Discover, que consiste em uma estratégia de trabalho em conjunto, envolvendo um conjunto de ferramentas que se integram e interajam, e que supram as necessidades de pesquisa dos integrantes do nosso laboratório. O Discover também pode ser utilizado como um campo de prova para desenvolver novas ferramentas e testar novas idéias. Como o Discover tem como principal finalidade o seu uso e extensão por pesquisadores, uma questão principal é que a arquitetura do projeto seja flexível o suficiente para permitir que novas pesquisas sejam englobadas e, simultaneamente, deve impor determinados padrões que permitam a integração eficiente de seus componentes. Neste trabalho, é proposto um framework de integração de componentes que tem como principal objetivo possibilitar a criação de um sistema computacional a partir das ferramentas desenvolvidas para serem utilizadas no projeto Discover. Esse framework compreende um mecanismo de adaptação de interface que cria uma camada (interface horizontal) sobre essas ferramentas, um poderoso mecanismo de metadados, que é utilizado para descrever tanto os componentes que implementam as funcionalidades do sistema quanto as configurações de experimentos criadas pelos usuário, que serão executadas pelo framework, e um ambiente de execução para essas configurações de experimentos. / One of human greatest capability is the ability to learn from observed instances of the world and to transmit what have been learnt to others. For thousands of years, we have tried to understand the world, and used the acquired knowledge to improve it. Nowadays, due to the progress in digital data acquisition and storage technology as well as significant progress in the field of Artificial Intelligence - AI, particularly Machine Learning - ML, it is possible to use inductive inference in huge databases in order to find, or discover, new knowledge from these data. The discipline concerned with this task has become known as Knowledge Discovery from Databases - KDD. However, this relatively new research area offers few tools that can efficiently be used to acquire knowledge from data. With these in mind, a group of researchers at the Computational Intelligence Laboratory - LABIC - is working on a system, called Discover, in order to help our research activities in KDD and ML. The aim of the system is to integrate ML algorithms mostly used by the community with the data and knowledge processing tools developed as the results of our work. The system can also be used as a workbench for new tools and ideas. As the main concern of the Discover is related to its use and extension by researches, an important question is related to the flexibility of its architecture. Furthermore, the Discover architecture should allow new tools be easily incorporated. Also, it should impose strong patterns to guarantee efficient component integration. In this work, we propose a component integration framework that aims the development of an integrated computational environment using the tools already implemented in the Discover project. The proposed component integration framework has been developed keeping in mind its future integration with new tools. This framework offers an interface adapter mechanism that creates a layer (horizontal interface) over these tools, a powerful metadata mechanism, which is used to describe both components implementing systems' functionalities and experiment configurations created by the user, and an environment that enables these experiment execution.

A presente tese analisa a maneira como a probabilidade influencia a formação da decisão sobre os fatos (contexto de descobrimento), bem como a motivação acerca dessas decisões (contexto justificativo). Mediante prévia análise da relevância da verdade no processo judicial, demonstra-se também que no terreno processual somente é possível falar em probabilidade, o que implica a ideia de um modelo probabilístico do juízo de fato, cujo núcleo é o módulo da escolha entre as alternativas possíveis. Portanto, são oferecidos critérios para a escolha das alternativas, os quais são denominados como diretrizes probatórias. De outro lado, a fim de que o convencimento do juiz a respeito dos fatos seja o mais racional possível, também é examinada a obrigatoriedade da motivação das decisões judiciais. Para tanto, é realizada abordagem à luz do Estado Constitucional e, ao final, demonstra-se que a probabilidade igualmente conforma o contexto justificativo, pois faz com que a motivação seja um discurso probatório racional. / This thesis examines how probability influences the fact-finding process (context of discovery) and the motivation about the trial of facts (context of justification). Considering the analysis of the relevance of truth in the judicial process, also in the procedural field only probability is taken into account, which implies the idea of a probabilistic model of factual judgment, whose core is the module of choice among the possible alternatives. Therefore, guidelines are offered for the choice of alternatives, which are called as evidentiary guidelines. On the other hand, in order to achieve the most rational conviction of the trier, mandatory legal motivation is also examined. The approach focuses on the Constitutional State and, in the end, is shown that the probability also conforms the context of justification, in order to make the legal motivation as a rational evidence speech.

O crescimento do uso de sistemas de posicionamento global (GPS) e outros sistemas de localização espacial tornaram possível o rastreamento de objetos móveis, produzindo um grande volume de um novo tipo de dado, chamado trajetórias de objetos móveis. Existe, entretanto, uma forte lacuna entre a quantidade de dados extraídos destes dispositivos, dotados de sistemas GPS, e a descoberta de conhecimento que se pode inferir com estes dados. Um tipo de descoberta de conhecimento em dados de trajetórias de objetos móveis é a classificação. A classificação de trajetórias é um tema de pesquisa relativamente novo, e poucos métodos tem sido propostos até o presente momento. A maioria destes métodos foi desenvolvido para uma aplicação específica. Poucos propuseram um método mais geral, aplicável a vários domínios ou conjuntos de dados. Este trabalho apresenta um novo método de classificação que transforma as trajetórias em séries temporais, de forma a obter características mais discriminativas para a classificação. Experimentos com dados reais mostraram que o método proposto é melhor do que abordagens existentes. / The growing use of global positioning systems (GPS) and other location systems made the tracking of moving objects possible, producing a large volume of a new kind of data, called trajectories of moving objects. However, there is a large gap between the amount of data generated by these devices and the knowledge that can be inferred from these data. One type of knowledge discovery in trajectories of moving objects is classification. Trajectory classification is a relatively new research subject, and a few methods have been proposed so far. Most of these methods were developed for a specific application. Only a few have proposed a general method, applicable to multiple domains or datasets. This work presents a new classification method that transforms the trajectories into time series, in order to obtain more discriminative features for classification. Experiments with real trajectory data revealed that the proposed approach is more effective than existing approaches.

Orientador: João Carlos Kfouri Quartim de Moraes / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Filosofia e Ciencias Humanas / Made available in DSpace on 2018-08-06T23:22:23Z (GMT). No. of bitstreams: 1 Neves_Marcelo_D.pdf: 1383429 bytes, checksum: edd5322b0388165a252173cb547a5215 (MD5) Previous issue date: 2006 / Resumo: As reflexões desenvolvidas neste trabalho não têm como objetivo apresentar uma exposição completa do pensamento lascasiano e, nem mesmo, uma análise de sua complexa personalidade. Nosso objetivo é estudar a idéia de ¿tolerância¿ presente em sua Apologia e em seu De unico. Mais precisamente, o ¿método tolerável¿ de conduzir os povos à verdadeira religião. E, ainda, ver como, pelo menos em suas linhas essenciais, a questão permeia grande parte de sua obra, sobretudo os tratados publicados a partir de 1551. Buscamos mostrar que, embora a tolerância seja, num primeiro momento, definida de forma negativa, isto é, como ¿suportação¿, no entanto é positiva e ativa. Positiva, enquanto implica uma apreciação favorável do universo indígena, sobretudo religioso. Ativa, enquanto parte de sua Apologia, ou seja, de um discurso que visa defender os índios das agressões dos colonizadores. Ademais, é ¿tolerância¿ nos limites do cristianismo católico¿; isto porque o discurso lascasiano é desenvolvido numa perspectiva missionária e visa mostrar o caminho, a melhor forma, o melhor ¿método¿ para a comunicação da verdadeira religião. Nisto consiste, a novidade de Las Casas: seu pensamento não tem lugar contra, mas a partir de dentro do catolicismo, ou seja, o ¿método¿ por ele defendido, em pleno século XVI, é apresentado como uma exigência do cristianismo em geral, e do catolicismo em particular / Abstract: The purpose of the developed in this study is not to present a full exposition of Las Casas' thought and much less is it an analysus of is complex personality. Ou purpose is to study the idea of "tolerance" in is Apologia and in his De unico. Or more precisely, to consider the "tolerant method" of leading the peoples to true religion. Besides, we also want to see the way in which that question, in its essential lines, permeates a large parte of his work, particularly treatises published since 1551. We intend to show that a although tolerance is defined, at first, in a negative form, as "endurance", it is really positive and active. It is positive, because it implies a favorable appreciation of the natives' universe, the religious one in particular. It is active, because it arises from his Apologia, which is a discourse in defense of the American Indians from aggression by the colonizers. Moreover, this "tolerance" is thought of as within the limits of the "Catholic Christianity". And it is so because Las Casas' discourse is developed in a missionary perspective and aims at pointing the course, the better way, the best "method" to communicate true religion. In this resides the novelty of Las Casas: his thought is not placed against, but arises from within Catholicism, that is, the "method" proposed by him, in the middle of XVI century, is presented as an exigency of Christianity in general, and of Catholicism in particular / Doutorado / Filosofia / Doutor em Filosofia

Esta tese apresenta novos metodos baseados na teoria dos fractais e em tecnicas de mineração de dados para dar suporte ao monitoramento agrícola em escala regional, mais especicamente areas com plantações de cana-de-açucar que tem um papel importante na economia brasileira como uma alternativa viavel para a substituição de combustíveis fósseis. Uma vez que o clima tem um grande impacto na agricultura, os agrometeorologistas utilizam dados climáticos associados a índices agrometeorológicos e mais recentemente dados provenientes de satélites para apoiar a tomada de decisão. Neste sentido, foi proposto um método que utiliza a dimensão fractal para identicar mudanças de tendências nas séries climáticas juntamente com um módulo de análise estatística para definir quais atributos são responsáveis por essas alterações de comportamento. Além disso, foram propostos dois métodos de medidas de similaridade para auxiliar na comparação de diferentes regiões agrícolas representadas por múltiplas variáveis provenientes de dados meteorológicos e imagens de sensoriamento remoto. Diante da importância de se estudar os extremos climáticos que podem se intensicar dado os cenários que preveem mudanças globais no clima, foi proposto o algoritmo CLIPSMiner que identifica padrões relevantes e extremos em séries climáticas. CLIPSMiner também permite a identificação de correlação de múltiplas séries considerando defasagem de tempo e encontra padrões de acordo com parâmetros que podem ser calibrados pelos usuários. A busca por padrões de associação entre séries foi alcançada por meio de duas abordagens distintas. A primeira delas integrou o cálculo da correlação de dimensão fractal com uma técnica para tornar os valores contínuos das séries em intervalos discretos e um algoritmo de regras de associação gerando o método Apriori-FD. Embora tenha identificado padrões interessantes em relação a temperatura, este método não conseguiu lidar de forma apropriada com defasagem temporal. Foi proposto então o algoritmo CLEARMiner que de forma não-supervisionada minera padrões em uma série associando-os a padrões em outras séries considerando a possibilidade de defasagem temporal. Os métodos propostos foram comparados a técnicas similares e avaliados por um grupo composto por meteorologistas, agrometeorologistas e especialistas em sensoriamento remoto. Os experimentos realizados mostraram que a aplicação de técnicas de mineração de dados e fractais contribui para melhorar a análise dos dados agrometeorológicos e de satélite auxiliando no trabalho de pesquisadores, além de se configurar como uma ferramenta importante para apoiar a tomada de decisão no agronegócio / This thesis presents new methods based on fractal theory and data mining techniques to support agricultural monitoring in regional scale, specifically regions with sugar canefields. This commodity greatly contributes to the Brazilian economy since it is a viable alternative to replace fossil fuels. Since climate in uences the national agricultural production, researchers use climate data associated to agrometeorological indexes, and recently they also employed data from satellites to support decision making processes. In this context, we proposed a method that uses the fractal dimension to identify trend changes in climate series jointly with a statistical analysis module to define which attributes are responsible for the behavior alteration in the series. Moreover, we also proposed two methods of similarity measure to allow comparisons among different agricultural regions represented by multiples variables from meteorological data and remote sensing images. Given the importance of studying the extreme weather events, which could increase in intensity, duration and frequency according to different scenarios indicated by climate forecasting models, we proposed the CLIPSMiner algorithm to identify relevant patterns and extremes in climate series. CLIPSMiner also detects correlations among multiple time series considering time lag and finds patterns according to parameters, which can be calibrated by the users. We applied two distinct approaches in order to discover association patterns on time series. The first one is the Apriori-FD method that integrates an algorithm to perform attribute selection through applying the correlation fractal dimension, an algorithm of discretization to convert continuous values of series into discrete intervals, and a well-known association rules algorithm (Apriori). Although Apriori-FD has identified interesting patterns related to temperature, this method failed to appropriately deal with time lag. As a solution, we proposed CLEARMiner that is an unsupervised algorithm in order to mine the association patterns in one time series relating them to patterns in other series considering the possibility of time lag. The proposed methods were compared with similar techniques as well as assessed by a group of meteorologists, and specialists in agrometeorology and remote sensing. The experiments showed that applying data mining techniques and fractal theory can contribute to improve the analyses of agrometeorological and satellite data. These new techniques can aid researchers in their work on decision making and become important tools to support decision making in agribusiness

Submitted by Maria Dulce (mdulce@ndc.uff.br) on 2014-01-10T19:05:13Z No. of bitstreams: 2 Dutra, Diego-Dissert-2013.pdf: 835286 bytes, checksum: dbcbc2dc846023912e75cb7104c1b096 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-01-10T19:05:13Z (GMT). No. of bitstreams: 2 Dutra, Diego-Dissert-2013.pdf: 835286 bytes, checksum: dbcbc2dc846023912e75cb7104c1b096 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013 / Universidade Federal Fluminense. Programa de Pós-Graduação em História / Nesse trabalho abordaremos de que modo o processo de Expansão Ultramarina, com prioridade para o cenário português quinhentista, inaugurou uma nova modalidade de saber que, por sua vez, começou a ganhar espaço e, ao mesmo tempo, passou a dialogar diretamente com o conhecimento acadêmico renascentista: a Cultura dos Descobrimentos. Por meio de um estudo sobre a Sabedoria do Mar, isto é, do campo científico pertencente à Cultura dos Descobrimentos, buscaremos analisar de que forma se apresentavam seus postulados, métodos e teorias, a fim de compreender quais as suas principais contribuições para a eclosão da Ciência Moderna. / In this dissertation we discuss how the process of Overseas Expansion, with priority given to the sixteenth century Portuguese scenario, inaugurated a new mode of knowing that, in turn, began to gain space and at the same time, he began to talk directly with the academic knowledge Renaissance: the Culture of Discovery. Through a study of the Wisdom of the Sea, that is, the scientific field belonging to the Culture of Discovery, will seek to examine how it presented its principles, methods and theories in order to understand what their major contributions to the outbreak of Modern Science.

Due to the inherent problems with their structural elucidation in the laboratory, the computational prediction of membrane protein structure is an essential step toward understanding the function of these leading targets for drug discovery. In this work, the development of a genetic algorithm technique is described that is able to generate predictive 3D structures of membrane proteins in an ab initio fashion that possess high stability and similarity to the native structure. This is accomplished through optimisation of the distances between TM regions and the end-on rotation of each TM helix. The starting point for the genetic algorithm is from the model of general TM region arrangement predicted using the TMRelate program. From these approximate starting coordinates, the TMBuilder program is used to generate the helical backbone 3D coordinates. The amino acid side chains are constructed using the MaxSprout algorithm. The genetic algorithm is designed to represent a TM protein structure by encoding each alpha carbon atom starting position, the starting atom of the initial residue of each helix, and operates by manipulating these starting positions. To evaluate each predicted structure, the SwissPDBViewer software (incorporating the GROMOS force field software) is employed to calculate the free potential energy. For the first time, a GA has been successfully applied to the problem of predicting membrane protein structure. Comparison between newly predicted structures (tests) and the native structure (control) indicate that the developed GA approach represents an efficient and fast method for refinement of predicted TM protein structures. Further enhancement of the performance of the GA allows the TMGA system to generate predictive structures with comparable energetic stability and reasonable structural similarity to the native structure.

Context: Today, many organizations in global market now frequently scan and assess their environment as consumers’ taste and preference became the sole target. Consumers’ preferred product of yesterday might unexpectedly devalue or be perceived staled the next day, due to the varieties, quality options and advancement in information technology from other firms. 3D printing technology describes a series of digital manufacturing technologies, which produce component parts layer-by-layer through the additional use of materials. 3D printing technology consists of three core phases that is, the modelling, the printing and the finishing of the product. In the modelling, 3D printing technology could proffer additional improvements depending on the engaged manufacturing method. Objectives: This research seeks to critically evaluate the influence of information technology on 3D printing for product development in Lagos, Nigeria. In this project, variables such as product design tools, decision support systems and file transfer protocol were categorized into three phases, namely; discovery, development and commercialization as the major sub-construct measuring the independent variable (Information Technology) on the dependent variable (3D printing and product development). Methods: The research was purely quantitative as questionnaires were used as the major evaluating instrument under descriptive and cross sectional research design (survey methods). The population consisted of seven selected printing press companies in Lagos, Nigeria. The survey was used to generate responses related to the research questions and objectives. Results: The result of the study reveals that product design tools in the discovery and development phase, the decision support system in the development and commercialization phase, and the file transfer protocols in the discovery, development and commercialization phase have significant influence on 3D printing for product development. Also, it was found that product design tools in the commercialization phase and in the discovery phase of decision support system do not have significant influence on 3D printing for product development. Conclusions: The study concludes that product design tools in the discovery and development phase, the decision support system in the development and commercialization phase, and the file transfer protocols in the discovery, development and commercialization phase have significant influence on 3D printing for product development. Thus, the study recommends that there is need for more innovations, there is need to standardise packages for loan applications, which will act as a decision support system for the employees in order to make consistent applications for loans, credit analysis, etc. Finally, more research work can be devoted through the use of other related textbooks and journals.

Over three decades ago, W.H.O. declared infertility as a public health issue; due to its impact on millions of people worldwide. While cases of infertility could be multifactorial (affecting both male and female), 50% of cases are due to male factor infertility and this is mostly characterised by reduced sperm motility (asthenozoospermia). Assisted Reproduction Technology (ART) is the only treatment option available for this condition. Over 20 years ago, non-selective phosphodiesterase inhibitors (PDEi), such as pentoxifylline, were shown to enhance motility of human spermatozoa; however, contradictory results and stimulation of premature acrosome reaction has precluded their clinical use. Advancement in our knowledge have now made it clear that human sperm express several different PDEs and these are compartmentalised at different regions of the cells. By using type-specific phosphodiesterase inhibitors, differential modulation of sperm motility can be achieved without affecting other sperm function such as acrosome reaction. Additionally, by enhancing sperm function through PDE inhibition, there is a possibility of increasing IVF rates. The objective of this thesis is to: (1) examine the effect of phosphodiesterase inhibitors on spermatozoa in order to identify compounds that have clinically relevant enhancement of human sperm motility; (2) identify the signalling pathway(s) involved in the motility enhancing effects of identified compounds by targeting the modulator and mediator of cyclic nucleotides; (3) develop an animal IVF model to assess effects of Ibudilast on fertilization; and (4) optimise high performance liquid chromatography (HPLC) techniques for routine detection of cyclic nucleotides in sperm cells. A two phase drug screening approach was used to systematically and comprehensively screen series of compounds in order to identify those that have clinically relevant enhancement of human sperm motility. In phase 1, 6 compounds (out of 43 compounds) were found to have strong effects on poor motility samples, with magnitude of response ≥60% increase in percentage total motility. Additionally, these compounds significantly enhanced sperm penetration into cervical mucus substitute (p≤0.05), and they did not affect sperm acrosomal integrity nor cause externalisation of phosphatidylserine (p=0.6 respectively). 63% of IVF samples treated with compounds #26, #37 and #38 had significant increase in percentage total motility. For ICSI samples, compounds #26, #37 and #38 were the most effective. In respect to total motility, 88%, 81% and 79% of samples treated with these compounds showed significant increases in total motility, and 94%, 93% and 81% of samples showed significant increases in percentage of progressive cells, respectively. Analysis of the signalling pathways, using PKA, sGC and PKG inhibitors, showed that chosen PDE inhibitors were working predominantly through PKA signalling pathways. Additionally, this study revealed that this pathway is needed for the maintenance of basal progressive motility and hyperactivation in human sperm. Animal IVF studies showed that addition of Ibudilast (compound #26) during sperm-oocyte incubation leads to higher IVF rates. Lastly, this study used an HPLC system to detect cAMP in boar sperm. This was done to explore if HPLC system can be used for high throughput detection of cyclic nucleotides in mammalian sperm.

This essay argues that The Awakening treats the 1890s “modern woman” that arose from feminist ideas and the women’s movement, challenging patriarchal society with an independent lifestyle. Following Ringe, this essay suggests that the novel has a purpose of showing the process and the development of the protagonist’s individual self. But rather than connect this theme to the transcendentalist notion of the self, as Ringe does, this essay looks at this theme in the light of the notion of the “modern woman”. By arguing that Edna develops into a modern woman during this process, the essay finds that she moves from the traditional position as a “patriarchal woman” towards the role of an “emancipated woman”. Further, the essay shows that Edna’s development and thereby her attempt to change her position fails as the process of self-discovery is conflicted, resulting in Edna’s suicide. Finally, by also arguing that the novel treats a woman’s self and the process of a development, the essay visualizes that the novel is built-up by seven steps that together constitute the process from “patriarchal woman” to “emancipated woman”. This process awakens a self-awareness and self-image within Edna that are strengthened with each of these step as she becomes a “modern woman”. / Denna uppsats argumenterar för att The Awakening skildrar 1890-talets “moderna kvinna” som uppstod från feministiska idéer samt kvinnorörelsen och utmanade det patriarkaliska samhället med en självständig livsstil. Då jag följer Ringe påvisar den här uppsatsen att romanen har ett syfte att visa processen och utvecklingen av huvudpersonens individuella jag. Men istället för att koppla detta till den transcendentalistiska uppfattningen av jaget som Ringe gör, så kopplar denna uppsats detta till begreppet den “moderna kvinnan”. Genom att argumentera för att Edna utvecklas till en modern kvinna under denna process finner uppsatsen att hon flyttar från den traditionella rollen som en “patriarkalisk kvinna” mot rollen som en “emanciperad kvinna”. Uppsatsen visar vidare att Ednas utveckling och således hennes försök att ändra sin roll misslyckas då självupptäcktsprocessen står under konflikt, vilket resulterar i att Edna tar självmord. Genom att också argumentera för att romanen skildrar en kvinnas jag och processen av en utveckling visar slutligen uppsatsen att romanen är uppbyggd av sju olika steg som tillsammans utgör processen från ”patriarkalisk kvinna” till ”emanciperad kvinna”. Denna process väcker en självmedvetenhet samt en självbild inom Edna som förstärks med varje steg medan hon blir en “modern kvinna”.