Contribuições para verificação automática de applets javacard

The widespread growth in the use of smart cards (by banks, transport services, and cell phones, etc) has brought an important fact that must be addressed: the need of tools that can be used to verify such cards, so to guarantee the correctness of their software. As the vast majority of cards that are being developed nowadays use the JavaCard technology as they software layer, the use of the Java Modeling Language (JML) to specify their programs appear as a natural solution. JML is a formal language tailored to Java. It has been inspired by methodologies from Larch and Eiffel, and has been widely adopted as the de facto language when dealing with specification of any Java related program. Various tools that make use of JML have already been developed, covering a wide range of functionalities, such as run time and static checking. But the tools existent so far for static checking are not fully automated, and, those that are, do not offer an adequate level of soundness and completeness. Our objective is to contribute to a series of techniques, that can be used to accomplish a fully automated and confident verification of JavaCard applets. In this work we present the first steps to this. With the use of a software platform comprised by Krakatoa, Why and haRVey, we developed a set of techniques to reduce the size of the theory necessary to verify the specifications. Such techniques have yielded very good results, with gains of almost 100% in all tested cases, and has proved as a valuable technique to be used, not only in this, but in most real world problems related to automatic verification

Probabilidade no ensino médio

This thesis aims to show teachers and students in teaching and learning in a study of Probability High School, a subject that sharpens the perception and understanding of the phenomea of the random nature that surrounds us. The same aims do with people who are involved in this process understand basic ideas of probability and, when necessary, apply them in the real world. We seek to draw a matched between intuition and rigor and hope therebyto contribute to the work of the teacher in the classroom and the learning process of students, consolidating, deepening and expaning what they have learned in previous contents

Dynamics at infinity and other global dynamical aspects of Shimizu-Morioka equations

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Análise de decisão multicritério na localização de usinas termoelétricas utilizando SIG

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aplicação de programação por metas binária: mista em uma empresa do setor sucroenergético

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Feedforward neural networks based on PPS-wavelet activation functions

Function approximation is a very important task in environments where computation has to be based on extracting information from data samples in real world processes. Neural networks and wavenets have been recently seen as attractive tools for developing efficient solutions for many real world problems in function approximation. In this paper, it is shown how feedforward neural networks can be built using a different type of activation function referred to as the PPS-wavelet. An algorithm is presented to generate a family of PPS-wavelets that can be used to efficiently construct feedforward networks for function approximation.

Heterogeneous photocatalytic treatment of organic dyes in air and aqueous media

This review focuses on the heterogeneous photocatalytic treatment of organic dyes in air and water. Representative studies spanning approximately three decades are included in this review. These studies have mostly used titanium dioxide (TiO2) as the inorganic semiconductor photocatalyst of choice for decolorizing and decomposing the organic dye to mineralized products. Other semiconductors such as ZnO, CdS, WO3, and Fe2O3 have also been used, albeit to a much smaller extent. The topics covered include historical aspects, dark adsorption of the dye on the semiconductor surface and its role in the subsequent photoreaction, semiconductor preparation details, photoreactor configurations, photooxidation kinetics/mechanisms and comparison with other Advanced Oxidation Processes (e.g., UV/H2O2, ozonation, UV/O3, Fenton and photo-Fenton reactions), visible light-induced dye decomposition by sensitization mechanism, reaction intermediates and toxicity issues, and real-world process scenarios. © 2008 Elsevier B.V. All rights reserved.

Video target tracking by using competitive neural networks

A target tracking algorithm able to identify the position and to pursuit moving targets in video digital sequences is proposed in this paper. The proposed approach aims to track moving targets inside the vision field of a digital camera. The position and trajectory of the target are identified by using a neural network presenting competitive learning technique. The winning neuron is trained to approximate to the target and, then, pursuit it. A digital camera provides a sequence of images and the algorithm process those frames in real time tracking the moving target. The algorithm is performed both with black and white and multi-colored images to simulate real world situations. Results show the effectiveness of the proposed algorithm, since the neurons tracked the moving targets even if there is no pre-processing image analysis. Single and multiple moving targets are followed in real time.

Subjetividade sujeitada e prática psicológica: Perspectivas do sujeito da ação

Research problematizes readings on the so-called subject or agent of action as associated to group constitution and analyzes the implications of such interpretations in psychological practice and in the constitution of subjectivity. The article is based on interdisciplinary readings and on different areas of knowledge so that identity references overlying the modern subject of action may be problematized. Critical emphasis is foregrounded on the classical logic, identity and subjected subjectivity as a-temporal and universal factors of action in the real world. The problematization of subjectivity's construction and its relationships with modes of knowledge will contribute towards the establishment of critical theoretic and strategic interventions.

Is the Czech economy a success story?: the case of CzechInvest, the strategic promotion agency in Czech industrial restructuring

Includes Bibliography

Tabu search to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem

This paper proposes a tabu search approach to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). It is a real-world problem, often found in soft drink companies, where the production process has two integrated levels with decisions concerning raw material storage and soft drink bottling. Lot sizing and scheduling of raw materials in tanks and products in bottling lines must be simultaneously determined. Real data provided by a soft drink company is used to make comparisons with a previous genetic algorithm. Computational results have demonstrated that tabu search outperformed genetic algorithm in all instances. Copyright 2011 ACM.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

A redistricting problem applied to meter reading in power distribution networks

The capacitated redistricting problem (CRP) has the objective to redefine, under a given criterion, an initial set of districts of an urban area represented by a geographic network. Each node in the network has different types of demands and each district has a limited capacity. Real-world applications consider more than one criteria in the design of the districts, leading to a multicriteria CRP (MCRP). Examples are found in political districting, sales design, street sweeping, garbage collection and mail delivery. This work addresses the MCRP applied to power meter reading and two criteria are considered: compactness and homogeneity of districts. The proposed solution framework is based on a greedy randomized adaptive search procedure and multicriteria scalarization techniques to approximate the Pareto frontier. The computational experiments show the effectiveness of the method for a set of randomly generated networks and for a real-world network extracted from the city of São Paulo. © 2013 Elsevier Ltd.