998 resultados para Solution mining.


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A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

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: In this work we derive an analytical solution given by Bessel series to the transient and one-dimensional (1D) bioheat transfer equation in a multi-layer region with spatially dependent heat sources. Each region represents an independent biological tissue characterized by temperature-invariant physiological parameters and a linearly temperature dependent metabolic heat generation. Moreover, 1D Cartesian, cylindrical or spherical coordinates are used to define the geometry and temperature boundary conditions of first, second and third kinds are assumed at the inner and outer surfaces. We present two examples of clinical applications for the developed solution. In the first one, we investigate two different heat source terms to simulate the heating in a tumor and its surrounding tissue, induced during a magnetic fluid hyperthermia technique used for cancer treatment. To obtain an accurate analytical solution, we determine the error associated with the truncated Bessel series that defines the transient solution. In the second application, we explore the potential of this model to study the effect of different environmental conditions in a multi-layered human head model (brain, bone and scalp). The convective heat transfer effect of a large blood vessel located inside the brain is also investigated. The results are further compared with a numerical solution obtained by the Finite Element Method and computed with COMSOL Multi-physics v4.1 (c). (c) 2013 Elsevier Ltd. All rights reserved.

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TRANSCREA, Convertir la investigación y el conocimiento en innovación, propiedad intelectual e industrial. Terceira, 16 e 17 Fevereiro, 2011.

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Purpose: The sorption of sulfamethoxazole, a frequently detected pharmaceutical compound in the environment, onto walnut shells was evaluated. Methods: The sorption proprieties of the raw sorbent were chemically modified and two additional samples were obtained, respectively HCl and NaOH treated. Scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and thermogravimetric (TG/DTG) techniques were applied to investigate the effect of the chemical treatments on the shell surface morphology and chemistry. Sorption experiments to investigate the pH effect on the process were carried out between pH 2 and 8. Results: The chemical treatment did not substantially alter the structure of the sorbent (physical and textural characteristics) but modified the surface chemistry of the sorbent (acid–base properties, point of zero charge—pHpzc). The solution pH influences both the sorbent’s surface charge and sulfamethoxazole speciation. The best removal efficiencies were obtained for lower pH values where the neutral and cationic sulfamethoxazole forms are present in the solution. Langmuir and Freundlich isotherms were applied to the experimental adsorption data for sulfamethoxazole sorption at pH 2, 4, and 7 onto raw walnut shell. No statistical difference was found between the two models except for the pH 2 experimental data to which the Freundlich model fitted better. Conclusion: Sorption of sulfamethoxazole was found to be highly pH dependent in the entire pH range studied and for both raw and treated sorbent.

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PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

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Dissertação para obtenção do grau de Mestre em Engenharia Informática

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Solution enthalpies of 1,4-dioxane have been obtained in 15 protic and aprotic solvents at 298.15 K. Breaking the overall process through the use of Solomonov's methodology the cavity term was calculated and interaction enthalpies (Delta H-int) were determined. Main factors involved in the interaction enthalpy have been identified and quantified using a QSPR approach based on the TAKA model equation. The relevant descriptors were found to be pi* and beta, which showed, respectively, exothermic and endothermic contributions. The magnitude of pi* coefficient points toward non-specific solute-solvent interactions playing a major role in the solution process. The positive value of the beta coefficient reflects the endothermic character of the solvents' hydrogen bond acceptor (HBA) basicity contribution, indicating that solvent molecules engaged in hydrogen bonding preferentially interact with each other rather than with 1,4-dioxane. (C) 2013 Elsevier B.V. All rights reserved.

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The presented work was conducted within the Dissertation / Internship, branch of Environmental Protection Technology, associated to the Master thesis in Chemical Engineering by the Instituto Superior de Engenharia do Porto and it was developed in the Aquatest a.s, headquartered in Prague, in Czech Republic. The ore mining exploitation in the Czech Republic began in the thirteenth century, and has been extended until the twentieth century, being now evident the consequences of the intensive extraction which includes contamination of soil and sub-soil by high concentrations of heavy metals. The mountain region of Zlaté Hory was chosen for the implementation of the remediation project, which consisted in the construction of three cells (tanks), the first to raise the pH, the second for the sedimentation of the formed precipitates and a third to increase the process efficiency in order to reduce high concentrations of metals, with special emphasis on iron, manganese and sulfates. This project was initiated in 2005, being pioneer in this country and is still ongoing due to the complex chemical and biological phenomenon’s inherent to the system. At the site where the project was implemented, there is a natural lagoon, thereby enabling a comparative study of the two systems (natural and artificial) regarding the efficiency of both in the reduction/ removal of the referred pollutants. The study aimed to assist and cooperate in the ongoing investigation at the company Aquatest, in terms of field work conducted in Zlaté Hory and in terms of research methodologies used in it. Thereby, it was carried out a survey and analysis of available data from 2005 to 2008, being complemented by the treatment of new data from 2009 to 2010. Moreover, a theoretical study of the chemical and biological processes that occurs in both systems was performed. Regarding the field work, an active participation in the collection and in situ sample analyzing of water and soil from the natural pond has been attained, with the supervision of Engineer, Irena Šupiková. Laboratory analysis of water and soil were carried out by laboratory technicians. It was found that the natural lagoon is more efficient in reducing iron and manganese, being obtained removal percentages of 100%. The artificial lagoon had a removal percentage of 90% and 33% for iron and manganese respectively. Despite the minor efficiency of the constructed wetland, it must be pointed out that this system was designed for the treatment and consequent reduction of iron. In this context, it can conclude that the main goal has been achieved. In the case of sulphates, the removal optimization is yet a goal to be achieved not only in the Czech Republic but also in other places where this type of contamination persists. In fact, in the natural lagoon and in the constructed wetland, removal efficiencies of 45% and 7% were obtained respectively. It has been speculated that the water at the entrance of both systems has different sources. The analysis of the collected data shows at the entrance of the natural pond, a concentration of 4.6 mg/L of total iron, 14.6 mg/L of manganese and 951 mg/L of sulphates. In the artificial pond, the concentrations are 27.7 mg/L, 8.1 mg/L and 382 mg/L respectively for iron, manganese and sulphates. During 2010 the investigation has been expanded. The study of soil samples has started in order to observe and evaluate the contribution of bacteria in the removal of heavy metals being in its early phase. Summarizing, this technology has revealed to be an interesting solution, since in addition to substantially reduce the mentioned contaminants, mostly iron, it combines the low cost of implementation with an reduced maintenance, and it can also be installed in recreation parks, providing habitats for plants and birds.

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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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Perante a evolução constante da Internet, a sua utilização é quase obrigatória. Através da web, é possível conferir extractos bancários, fazer compras em países longínquos, pagar serviços sem sair de casa, entre muitos outros. Há inúmeras alternativas de utilização desta rede. Ao se tornar tão útil e próxima das pessoas, estas começaram também a ganhar mais conhecimentos informáticos. Na Internet, estão também publicados vários guias para intrusão ilícita em sistemas, assim como manuais para outras práticas criminosas. Este tipo de informação, aliado à crescente capacidade informática do utilizador, teve como resultado uma alteração nos paradigmas de segurança informática actual. Actualmente, em segurança informática a preocupação com o hardware é menor, sendo o principal objectivo a salvaguarda dos dados e continuidade dos serviços. Isto deve-se fundamentalmente à dependência das organizações nos seus dados digitais e, cada vez mais, dos serviços que disponibilizam online. Dada a mudança dos perigos e do que se pretende proteger, também os mecanismos de segurança devem ser alterados. Torna-se necessário conhecer o atacante, podendo prever o que o motiva e o que pretende atacar. Neste contexto, propôs-se a implementação de sistemas de registo de tentativas de acesso ilícitas em cinco instituições de ensino superior e posterior análise da informação recolhida com auxílio de técnicas de data mining (mineração de dados). Esta solução é pouco utilizada com este intuito em investigação, pelo que foi necessário procurar analogias com outras áreas de aplicação para recolher documentação relevante para a sua implementação. A solução resultante revelou-se eficaz, tendo levado ao desenvolvimento de uma aplicação de fusão de logs das aplicações Honeyd e Snort (responsável também pelo seu tratamento, preparação e disponibilização num ficheiro Comma Separated Values (CSV), acrescentando conhecimento sobre o que se pode obter estatisticamente e revelando características úteis e previamente desconhecidas dos atacantes. Este conhecimento pode ser utilizado por um administrador de sistemas para melhorar o desempenho dos seus mecanismos de segurança, tais como firewalls e Intrusion Detection Systems (IDS).

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Introdução Actualmente, as mensagens electrónicas são consideradas um importante meio de comunicação. As mensagens electrónicas – vulgarmente conhecidas como emails – são utilizadas fácil e frequentemente para enviar e receber o mais variado tipo de informação. O seu uso tem diversos fins gerando diariamente um grande número de mensagens e, consequentemente um enorme volume de informação. Este grande volume de informação requer uma constante manipulação das mensagens de forma a manter o conjunto organizado. Tipicamente esta manipulação consiste em organizar as mensagens numa taxonomia. A taxonomia adoptada reflecte os interesses e as preferências particulares do utilizador. Motivação A organização manual de emails é uma actividade morosa e que consome tempo. A optimização deste processo através da implementação de um método automático, tende a melhorar a satisfação do utilizador. Cada vez mais existe a necessidade de encontrar novas soluções para a manipulação de conteúdo digital poupando esforços e custos ao utilizador; esta necessidade, concretamente no âmbito da manipulação de emails, motivou a realização deste trabalho. Hipótese O objectivo principal deste projecto consiste em permitir a organização ad-hoc de emails com um esforço reduzido por parte do utilizador. A metodologia proposta visa organizar os emails num conjunto de categorias, disjuntas, que reflectem as preferências do utilizador. A principal finalidade deste processo é produzir uma organização onde as mensagens sejam classificadas em classes apropriadas requerendo o mínimo número esforço possível por parte do utilizador. Para alcançar os objectivos estipulados, este projecto recorre a técnicas de mineração de texto, em especial categorização automática de texto, e aprendizagem activa. Para reduzir a necessidade de inquirir o utilizador – para etiquetar exemplos de acordo com as categorias desejadas – foi utilizado o algoritmo d-confidence. Processo de organização automática de emails O processo de organizar automaticamente emails é desenvolvido em três fases distintas: indexação, classificação e avaliação. Na primeira fase, fase de indexação, os emails passam por um processo transformativo de limpeza que visa essencialmente gerar uma representação dos emails adequada ao processamento automático. A segunda fase é a fase de classificação. Esta fase recorre ao conjunto de dados resultantes da fase anterior para produzir um modelo de classificação, aplicando-o posteriormente a novos emails. Partindo de uma matriz onde são representados emails, termos e os seus respectivos pesos, e um conjunto de exemplos classificados manualmente, um classificador é gerado a partir de um processo de aprendizagem. O classificador obtido é então aplicado ao conjunto de emails e a classificação de todos os emails é alcançada. O processo de classificação é feito com base num classificador de máquinas de vectores de suporte recorrendo ao algoritmo de aprendizagem activa d-confidence. O algoritmo d-confidence tem como objectivo propor ao utilizador os exemplos mais significativos para etiquetagem. Ao identificar os emails com informação mais relevante para o processo de aprendizagem, diminui-se o número de iterações e consequentemente o esforço exigido por parte dos utilizadores. A terceira e última fase é a fase de avaliação. Nesta fase a performance do processo de classificação e a eficiência do algoritmo d-confidence são avaliadas. O método de avaliação adoptado é o método de validação cruzada denominado 10-fold cross validation. Conclusões O processo de organização automática de emails foi desenvolvido com sucesso, a performance do classificador gerado e do algoritmo d-confidence foi relativamente boa. Em média as categorias apresentam taxas de erro relativamente baixas, a não ser as classes mais genéricas. O esforço exigido pelo utilizador foi reduzido, já que com a utilização do algoritmo d-confidence obteve-se uma taxa de erro próxima do valor final, mesmo com um número de casos etiquetados abaixo daquele que é requerido por um método supervisionado. É importante salientar, que além do processo automático de organização de emails, este projecto foi uma excelente oportunidade para adquirir conhecimento consistente sobre mineração de texto e sobre os processos de classificação automática e recuperação de informação. O estudo de áreas tão interessantes despertou novos interesses que consistem em verdadeiros desafios futuros.

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A descoberta de conhecimento em dados hoje em dia é um ponto forte para as empresas. Atualmente a CardMobili não dispõe de qualquer sistema de mineração de dados, sendo a existência deste uma mais-valia para as suas operações de marketing diárias, nomeadamente no lançamento de cupões a um grupo restrito de clientes com uma elevada probabilidade que os mesmos os utilizem. Para isso foi analisada a base de dados da aplicação tentando extrair o maior número de dados e aplicadas as transformações necessárias para posteriormente serem processados pelos algoritmos de mineração de dados. Durante a etapa de mineração de dados foram aplicadas as técnicas de associação e classificação, sendo que os melhores resultados foram obtidos com técnicas de associação. Desta maneira pretende-se que os resultados obtidos auxiliem o decisor na sua tomada de decisões.

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In this paper the adequacy and the benefit of incorporating glass fibre reinforced polymer (GFRP) waste materials into polyester based mortars, as sand aggregates and filler replacements, are assessed. Different weight contents of mechanically recycled GFRP wastes with two particle size grades are included in the formulation of new materials. In all formulations, a polyester resin matrix was modified with a silane coupling agent in order to improve binder-aggregates interfaces. The added value of the recycling solution was assessed by means of both flexural and compressive strengths of GFRP admixed mortars with regard to those of the unmodified polymer mortars. Planning of experiments and data treatment were performed by means of full factorial design and through appropriate statistical tools based on analyses of variance (ANOVA). Results show that the partial replacement of sand aggregates by either type of GFRP recyclates improves the mechanical performance of resultant polymer mortars. In the case of trial formulations modified with the coarser waste mix, the best results are achieved with 8% waste weight content, while for fine waste based polymer mortars, 4% in weight of waste content leads to the higher increases on mechanical strengths. This study clearly identifies a promising waste management solution for GFRP waste materials by developing a cost-effective end-use application for the recyclates, thus contributing to a more sustainable fibre-reinforced polymer composites industry.

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The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database. In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%. In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem. In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models. The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work. The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.