Doutorado em Ciência da Computação em Rede - UFMS/UFG (INF)
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Item Um método de interação com reconhecimento contínuo de gestos de toque para uso em smartwatch(Universidade Federal de Goiás, 2021-12-06) Nascimento, Thamer Horbylon; Soares, Fabrízzio Alphonsus Alves de Melo Nunes; http://lattes.cnpq.br/7206645857721831; Soares, Fabrízzio Alphonsus Alves de Melo Nunes; Cardoso, Alexandre; Marques, Fátima de Lourdes dos Santos Nunes; Fernandes, Deborah Silva Alves; Bulcão Neto, Renato de FreitasSmartwatches are wearable and smart watch-shaped devices that aim to facilitate the daily lives of users, however, as they have small screens, the traditional mechanisms of interaction with touch-sensitive screens may not be efficient on these devices. Thus, it is important to develop new interaction methods that use the touchscreens of smartwatches. Therefore, in this work a method was developed that uses simple gestures, based on geometric shapes with continuous recognition of gestures on smartwatches touchscreens as an interaction mechanism. The results obtained with usability and/or experience tests of the method developed in case studies carried out in four segments are presented: text input in smartwatches and in virtual environments, interaction with platform games, video players and interactive movies and home appliances. During the development of this work, adaptations were made to the continuous gesture recognition algorithm: the recognition step was parallelized, which allows using threads to calculate the gesture probabilities; A technique was developed that allows detecting the change in gestures, allowing the user to initiate a new gesture without having to remove their finger from the screen. The results show that the continuous gesture recognition algorithm can be used in smartwatches and that with a small set of gestures it is possible to perform different actions. Thus, the developed method expands the possibilities of interaction with devices and environments using the smartwatches touch-sensitive screens and continuous recognition of gestures.Item Classificação de tecidos epiteliais tumorais empregando imagens hiperespectrais e infravermelho de ondas curtas(Universidade Federal de Goiás, 2021-08-04) Lucena, Daniel Vitor de; Coelho, Clarimar José; http://lattes.cnpq.br/1350166605717268; Soares, Anderson da Silva; http://lattes.cnpq.br/1096941114079527; Soares, Anderson da Silva; Coelho, Clarimar José; Wastowski, Isabela Jubé; Laureano, Gustavo Teodoro; Soares, Fabrízzio Alphonsus Alves de Melo NunesHyperspectral Imaging (HSI) is a new concept of disease diagnosis by image analysis. Although there are many approaches for HSI image analysis, the classification of spatial informations to tumor classification is still limited. In this thesis is proposed the building of a new method of analysis and classification of present objects in HSI based on techniques of machine learning to understand the molecular vibrational behavior of healthy and tumoral human epithelial tissue by means of short-wave infrared (SWIR) spectroscopy. In the experimental study is analyzed samples of Melanoma, Dysplastic Nevus and healthy skin. Results show that human epithelial tissue is sensitive to SWIR to the point of making possible the differentiation between healthy and tumor tissues. It can be concluded that HSI-SWIR can be used to build new methods for tumor classification.Item Mínimos quadrados para problemas de múltiplas classes envolvendo twin support vector machine e aplicações de mineração de dados(Universidade Federal de Goiás, 2018-12-07) Lima, Márcio Dias de; Barbosa, Rommel Melgaço; http://lattes.cnpq.br/6228227125338610; Barbosa, Rommel Melgaço; Santos, Helton Saulo Bezerra dos; Lozano, Kátia Kelvis Cassiano; Costa, Ronaldo Martins da; Rosa, Thierson CoutoData mining is an emerging area due to the increasing amount of data available in a variety of fields. In this context twin support vector machine (TWSVM) has attracted the attention of several researchers. In this thesis, we developed a feature selector algorithm and an algorithm for multi-class problems based on TWSVM. This learning algorithm with ternary outputs {- 1,0,+1 } is based on the Vapnik support vector theory, and evaluates all training samples with a 1-×-1-×-rest structure during the decomposition phase. One of the main advantages of the proposed algorithm is the use of the least squares version for multi-class problems, where it is necessary to solve two systems of linear equations instead of two quadratic programming problems in TWSVM. We also implemented the principle of minimization of structural risk in order to improve the generalizability. The Sherman-Morisson-Woodbury formula is applied to reduce the complexity of the non-linear formulation of the algorithm. We also apply data mining techniques that combine the use of analytical technique with data mining algorithms in the classification of several samples. The developed framework could be an excellent tool for detecting different types of fraud, verifying if products were grown in organic or conventional systems, as well as tracing the region of origin of wine made from a given type of grape.Item Balanceamento de dados com base em oversampling em dados transformados(Universidade Federal de Goiás, 2020-08-17) Maione, Camila; Barbosa, Rommel Melgaço; http://lattes.cnpq.br/6228227125338610; Barbosa, Rommel Melgaço; Leitão Júnior, Plínio; Costa, Ronaldo Martins da; Costa, Ana Paula Cabral Seixas; Lozano, Kátia Kelvis CassianoIntroduction: The efficiency and reliability of data analyses depends heavily on the quality of the analyzed data. The fundamental process of preparing databases in order to make them cleaner, more representative and improve their quality is called data preprocessing, during which data balancing is also performed. The importance of data balancing lies in the fact that several classification models commonly employed in enterprises and academic projects are designed to work with balanced data sets, and there are several factors which hinder classification performance which are associated to data imbalance. Objective: A new approach for data balancing based on data transformation combined with resampling of transformed data is proposed. The proposed approach transforms the original data set by transforming its input variables into new ones, therefore altering the data samples' position in the dimensional plane and consequently the choice that SMOTE-based resampling algorithms make over the initial samples, their nearest neighbours and where to place the generated synthetic samples. Methods: An initial implementation based on Principal Component Analysis (PCA) and SMOTE is presented, called PCA-SMOTE. In order to test the quality of the balancing performed by PCA-SMOTE, twelve test data sets were balanced through PCA-SMOTE and three other popular data balancing methods, and the performance of three classification models trained on these balanced sets are assessed and compared. Results: Several classification models trained on data sets which were balanced using the proposed method presented higher or similar performance measures in comparison to the same models trained on data sets that were balanced through the other evaluated algorithms, such as Borderline-SMOTE, Safe-Level-SMOTE and ADASYN. Conclusion: The satisfactory results obtained prove the potential of the proposed algorithm to improve learning of classifiers on imbalanced data sets.Item Reconhecimento de padrões por processos adaptativos de compressão(Universidade Federal de Goiás, 2020-03-02) Bailão, Adriano Soares de Oliveira; Delbem, Alexandre Cláudio Botazzo; http://lattes.cnpq.br/1201079310363734; Soares, Anderson da Silva; http://lattes.cnpq.br/1096941114079527; Soares, Anderson da Silva; Silva, Nadia Felix Felipe da; Duque, Cláudio Gottschalg; Costa, Ronaldo Martins da; Monaco, Francisco JoséData compression is a process widely used by the industry in the storage and transport of information and is applied to a variety of domains such as text, image, audio and video. The compression processes are a set of mathematical operations that aim to represent each sample of data in compressed form, or with a smaller size. Pattern recognition techniques can use compression properties and metrics to design machine learning models from adaptive algorithms that represent samples in compressed form. An advantage of adaptive compression models, is that they have dimensionality reduction techniques resulting from the compression properties. This thesis proposes a general unsupervised learning model (for different problem domains and different types of data), which combines adaptive compression strategies in two phases: granulation, responsible for the perception and representation of the knowledge necessary to solve a problem generalization, and the codification phase, responsible for structuring the reasoning of the model, based on the representation and organization of the problem objects. The reasoning expressed by the model denotes the ability to generalize data objects in the general context. Generic methods, based on compactors (without loss of information), lack generalization capacity for some types of data objects, and in this thesis, lossy compression techniques are also used, in order to circumvent the problem and increase the capacity of generalization of the model. Results demonstrate that the use of techniques and metrics based on adaptive compression produce a good approximation of the original data samples in data sources with high dimensionality. Tests point to good machine learning models with good generalization capabilities derived from the approach based on the reduction of dimensionality offered by adaptive compression processes.Item Explorando paralelismo em big data no processamento de séries temporais de imagens de sensoriamento remoto(Universidade Federal de Goiás, 2019-08-30) Oliveira, Sávio Salvarino Teles de; Rodrigues, Vagner José do Sacramento; http://lattes.cnpq.br/4148896613580056; Martins, Wellington Santos; http://lattes.cnpq.br/3041686206689904; Martins, Wellington Santos; Costa, Fábio Moreira; Carvalho, Sérgio Teixeira de; Silva, Nilton Correia da; Davis Júnior, Clodoveu AugustoThe surface of planet Earth is changing at an unprecedented rate and the land use and land cover classification using remote sensing time series is now essential for identifying these changes. The TWDTW algorithm stands out in this task, but it has a quadratic complexity and high computational cost, making it difficult to use with Big Data. In this paper we tackle these problems by exploiting parallelism at both the vertical (multicore / manycore) and horizontal (cluster - distributed system) levels, in an integrated way for high performance. In the vertical dimension, we propose a parallel algorithm (P- INDEX) for the calculation of remote sensing indices, and another (P-TWDTW) for the calculation of similarity between time series. The speedup of P-INDEX was up to 9 times relative to the sequential algorithm in processing all images, while P-TWDTW was up to 12 times faster than its C++ centralized version and 246 times faster than the original in R TWDTW algorithm. In addition to enabling the quick calculation of a more sophisticated similarity measure, P- TWDTW also contributed to the generation of meta-characteristics for more robust machine learning methods. This increased the accuracy of the time series classification from 78% using TWDTW with KNN to almost 94% using the meta-characteristics obtained from P-TWDTW with SVM. In the horizontal dimension, we propose a distributed platform (BigSensing) that enables efficient handling of large volumes of remote sensing data. The platform includes a smart query engine that is able to choose, in real time, the best system to filter and retrieve data according to the spatial and temporal constraints of the query, with a nearly 22% reduction in response time over SciDB.Item Estratégias para alocação de recursos de controle ótimo em cenários estocásticos(Universidade Federal de Goiás, 2019-06-10) Galvão Filho, Arlindo Rodrigues; Coelho, Clarimar José; http://lattes.cnpq.br/1350166605717268; Soares, Telma Woerle Lima; http://lattes.cnpq.br/6296363436468330; Soares, Telma Woerle Lima; Martins, Wellington; Soares, Anderson da Silva; Carvalho, Rafael Viana de; Laureano, Gustavo TeodoroApplication of computational models has contributed to understanding of different dynamics as well as possible more effective control strategies. Three widely used examples are deterministic formulations of compartmental models, individuals based models, and complex networks based models. An alternative to such models is a stochastic approach, which allows uncertainties insertion to models, providing more realistic results. In this context, this work proposes use of deterministic compartmental models to obtain optimum control policies, and later evaluation of such policy applied in a stochastic scenario using a equivalent individual based model. It also proposes three new control strategies based on dynamics and topology in complex network models. To models validation, a case study based on epidemiological dynamics was done, in which proposed strategies resulted in significant reductions in number of infected individuals, optimizing resource spending. Insertion of uncertainty in models was positive for average behavior analysis of dynamics. In addition, a parallel MBI model was proposed to be processed in graphic cards. With this improvement it was possible to obtain a reduction by a factor of twenty in processing time.Item Seleção de serviços sensível à QoS e à capacidade para implantação eficiente de múltiplas coreografias de serviços(Universidade Federal de Goiás, 2018-11-23) Lima, Júnio César de; Rocha, Ricardo Couto Antunes da; http://lattes.cnpq.br/4808440233209979; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; Rocha, Ricardo Couto Antunes da; Rosa, Nelson Souto; Madeira, Edmundo Roberto Mauro; Longo, Humberto JoséChoreographies are an approach for service composition in which coordination is performed in a decentralized way. To deploy a choreography, a set of services must be selected to perform the functionalities required in its specification, including ensuring its QoS requirements. However, existing approaches for QoS-aware service selection fail to explicitly consider service sharing, as they deal with each choreography in isolation. By dealing with a single choreography at a time, the service selection process may become less feasible in real scenarios, in which several choreographies, competing for the same set of services, must be deployed together. In this case, a given service that suits a role in more than one choreography may be shared. Unsupervised service sharing, however, may degrade the overall QoS provided for the choreographies, as the maximum capacity of the shared servicesmay be exceeded. In addition, such approaches tend to select services with higher QoS than necessary, leading to waste of resources. This thesis proposes an approach for QoS- and capacity-aware service selection for the combined deployment of multiple choreographies. This approach ensures the satisfaction of QoS requirements, even in the face of possible service sharing. To this end, we propose a model for the combined representation of multiple choreographies. This model is used as input for the service selection, which is solved by seeking a matching between of the choreographies roles and the candidate services to minimize the costs of the selected services in terms of resource usage. For this, a utility function is proposed to evaluate the QoS of the services, along with the extension of the matching algorithm. The thesis presents an architecture that combines all the elements of the proposed approach. A prototype implementation of the architecture was developed to enable its evaluation. The results of the evaluation indicate superior effectiveness and performance of the proposed approach as compared to related work.Item Variable selection in multivariate calibration considering non-decomposability assumption and building blocks hypothesis(Universidade Federal de Goiás, 2018-12-06) Paula, Lauro Cássio Martins de; Coelho, Clarimar José; http://lattes.cnpq.br/1350166605717268; Soares, Anderson da Silva; http://lattes.cnpq.br/1096941114079527; Soares, Anderson da Silva; Coelho, Clarimar José; Camilo Junior, Celso Gonçalves; Soares, Fabrízzio Alphonsus Alves de Melo Nunes; Oliveira, Anselmo Elcana deThe procedure used to select a subset of suitable features in a given data set consists in variable selection, which is important when the dataset contains large number of variables and many of them are redundant. Multivariate calibration combines variable selection with statistical techniques to build mathematical models which relate the data to a given property of interest in order to predict this property by selecting informative variables. In this context, variable selection techniques have been widely applied to the solution of several optimization problems. For instance, Genetic Algorithms (GAs) are easy to implement and consist in a population-based model that uses selection and recombination operators to generate new solutions. However, usually in multivariate calibration the dataset present a considerable correlation degree among variables and this provides an evidence about the problem not being properly decomposed. Moreover, some studies in literature have claimed genetic operators used by GAs can cause the building blocks (BBs) disruption of viable solutions. Therefore, this work aims to claim that selecting variables in multivariate calibration is a non-completely decomposable problem (hypothesis 1) as well as that recombination operators affects the non-decomposability assumption (hypothesis 2). Additionally, we are proposing two heuristics, one local search-based operator and two versions of an Epistasis-based Feature Selection Algorithm (EbFSA) to improve model prediction performance and avoid BBs disruption. Based on the performed inquiry and experimental results, we are able to endorse the viability of our hypotheses and demonstrate EbFSA can overcome some traditional algorithms.Item Problemas de otimização combinatória para união explícita de arestas(Universidade Federal de Goiás, 2018-03-21) Ferreira, Joelma de Moura; Foulds, Les; http://lattes.cnpq.br/3737395828552021; Nascimento, Hugo Alexandre Dantas do; http://lattes.cnpq.br/2920005922426876; Freitas, Carla Maria Dal Sasso; Paulovich, Fernando; Longo, Humberto José; Soares, Telma Woerle de LimaEdge bundling is a technique to group, align, coordinate and position the depiction of edges in a graph drawing, so that sets of edges appear to be brought together into shared visual structures, i.e. bundles. The ultimate goal is to reduce clutter to improve how it conveys information. This thesis provides a general formulation for the explicity edge bundling problems, as a formal combinatorial optimization problem. This allows for the definition and comparison of edge bundling problems. In addition, we present four explicity edge bundling optimization problems that address minimizing the total number of bundles, in conjunction with other aspects, as the main goal. An evolutionary edge bundling algorithm is described. The algorithm was successfully tested by solving three related problems applied to real-world instances. The reported experimental results demonstrate the effectiveness and the applicability of the proposed evolutionary algorithm to help resolve edge bundling problems formally defined as optimization models.Item Contribuições ao suporte cognitivo em teste de software unitário: um framework de tarefas e uma agenda de pesquisa(Universidade Federal de Goiás, 2018-03-16) Prado, Marllos Paiva; Vincenzi, Auri Marcelo Rizzo; http://lattes.cnpq.br/0611351138131709; Vincenzi, Auri Marcelo Rizzo; Fabbri, Sandra Camargo Pinto Ferraz; Jorge, Rodrigo Funabashi; Rodrigues, Cássio Leonardo; Bulcão Neto, Renato de FreitasUnit testing is an important activity for improving software quality. Over the years, numerous automated tools have been proposed by the testing research community to enhance this activity. However, this thesis' literature review revealed that several research efforts have not considered the human aspects in the proposal of such tools. Also, unit test practitioners are not having the support of the existing tools to solve some mental tasks associated with the activity. Motivated by this gap, this thesis describes a sequence of studies carried out with the purpose of understanding, characterizing and proposing improvements in the cognitive support provided by the test tools, considering a qualitative approach centered on the perspective of test professionals that work at the unit level. The results revealed some primary tasks that require cognitive support of the tools in unit test review practice, including monitoring of pending and executed unit test tasks and navigation between unit testing artifacts. A framework summarizes the results of this study. A research agenda is developed based on the framework and serves as an actionable instrument for the testing community. The contributions of this study include suggestions for practical improvements to current tools and describe new research opportunities in the topic. Also, the methods used in the research are explained in details.Item Efficient processing of multiway spatial join queries in distributed systems(Universidade Federal de Goiás, 2017-11-29) Oliveira, Thiago Borges de; Foulds, Leslie Richard; http://lattes.cnpq.br/3737395828552021; Rodrigues, Vagner José do Sacramento; http://lattes.cnpq.br/4148896613580056; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; Foulds, Leslie Richard; Rodrigues, Vagner José do Sacramento; Braghetto, Kelly Rosa; Meneses, Cláudio Nogueira deMultiway spatial join is an important type of query in spatial data processing, and its efficient execution is a requirement to move spatial data analysis to scalable platforms as has already happened with relational and unstructured data. In this thesis, we provide a set of comprehensive models and methods to efficiently execute multiway spatial join queries in distributed systems. We introduce a cost-based optimizer that is able to select a good execution plan for processing such queries in distributed systems taking into account: the partitioning of data based on the spatial attributes of datasets; the intra-operator level of parallelism, which enables high scalability; and the economy of cluster resources by appropriately scheduling the queries before execution. We propose a cost model based on relevant metadata about the spatial datasets and the data distribution, which identifies the pattern of costs incurred when processing a query in this environment. We formalized the distributed multiway spatial join plan scheduling problem as a bi-objective linear integer model, considering the minimization of both the makespan and the communication cost as objectives. Three methods are proposed to compute schedules based on this model that significantly reduce the resource consumption required to process a query. Although targeting multiway spatial join query scheduling, these methods can be applied to other kinds of problems in distributed systems, notably problems that require both the alignment of data partitions and the assignment of jobs to machines. Additionally, we propose a method to control the usage of resources and increase system throughput in the presence of constraints on the network or processing capacity. The proposed cost-based optimizer was able to select good execution plans for all queries in our experiments, using public datasets with a significant range of sizes and complex spatial objects. We also present an execution engine that is capable of performing the queries with near-linear scalability with respect to execution time.Item Programação de espaços inteligentes utilizando modelos em tempo de execução(Universidade Federal de Goiás, 2017-04-04) Freitas, Leandro Alexandre; Rocha, Ricardo Couto Antunes da; http://lattes.cnpq.br/4808440233209979; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Silva, Francisco José da Silva e; Ueyama, Jó; Ferreira, Ronaldo Alves; Soares, Fabrízzio Alphonsus Alves de Melo NunesThe growth and popularization of wireless connectivity and of mobile devices has allowed the development of smart spaces that were previously only envisaged in the approach proposed by Mark Weiser. These smart spaces are composed of many computational resources, such as devices, services and applications, along with users, who must be able to associate with these features. However, programming these environments is a challenging task, since smart spaces have a dynamic nature, resources are heterogeneous, and it is necessary that interactions between users and devices are coordinated with one another. In this work, we present a new approach for smart spaces programming using Models@RunTime. In this regard, we propose a high level modeling language, called Smart Spaces Modeling Language (2SML), in which the user is able to model the smart space with all elements that can be part of it. Such models are developed by the users, interpreted and effected in the physical space by a model execution engine, called Smart Space Virtual Machine (2SVM), whose development is part of this work.Item Implantação eficiente de múltiplas coreografias de serviços em nuvens híbridas(Universidade Federal de Goiás, 2017-04-06) Gomes, Raphael de Aquino; Rocha, Ricardo Couto Antunes da; http://lattes.cnpq.br/4808440233209979; Costa, Fábio Moreira; http://lattes.cnpq.br/0925150626762308; Costa, Fábio Moreira; Rocha, Ricardo Couto Antunes da; Schulze, Bruno Richard; Cordeiro, Daniel de Angelis; Cáceres, Edson NorbertoThis thesis proposes a model-based approach to abstracting, simplifying, and automating cloud resource management decisions to deploy a set of service choreographies subject to non-functional constraints. Given a high-level description of service choreographies and related constraints, the approach autonomously performs resource estimation, selection, and allocation in a hybrid cloud environment with multiple cloud providers whilst decreases resource utilization costs and inter-services communication overhead. The main motivation for this work is because service choreographies are widely used for the development of solutions with complex needs, with service sharing among them. This scenario turns resource management a challenging task, mainly due to the different roles that a service assumes, the interference among constraints, and a large number of available resource types. This thesis also proposes an architecture that extends the approach with strategies to dynamic resource management to face constraint violations. This architecture was partially implemented in a prototype that was used in the proposed approach evaluation.Item Application of GPU Computing to Some Urban Traffic Problems(Universidade Federal de Goiás, 2016-11-30) Jradi, Walid Abdala Rfaei; Martins, Wellington Santos; http://lattes.cnpq.br/3041686206689904; Nascimento, Hugo Alexandre Dantas do; http://lattes.cnpq.br/2920005922426876; Camponogara, Eduardo; Clua, Esteban Walter Gonzalez; Mongelli , Henrique; Costa, Fábio MoreiraThe present work studies and proposes GPU-based parallel algorithms and implementations for the problem of macroscopic assignment of urban traffic on large-scale networks, promoting an in-depth investigation on each sub-problem that must be efficiently solved during the traffic assignment process. Among the main contributions of this work, there are: 1) the first GPU-based algorithm for the enumeration of chordless cycles; 2) a new parallel GPU-based shortest path algorithm that takes advantage of some common properties of urban traffic networks; a refinement in the parallel reduction implementation proposed by one of the leaders in the GPU market, which resulted in a 2.8x speedup relative to its original version; and finally, 3) a parallel algorithm for the macroscopic traffic assignment problem, 39x faster than the equivalent sequential approach when applied to large scale networks. The main goal of this thesis is to contribute to the extension of the PET-Gyn software, proposing efficient GPU data structures and parallel algorithms for a faster resolution of two well known problems in the literature: The Traffic Assignment Problem (TAP) and the Enumeration of Chordless Cycles. When applied to difficult input sets, the performed experiments showed a clear advantage of the parallel algorithms over their sequential versions.Item Alocação de recursos em redes sem fio OFDM multiusuário utilizando modelagem multifractal adaptativa(Universidade Federal de Goiás, 2016-11-22) Rocha, Flávio Geraldo Coelho; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Cardoso, Kleber Vieira; Borges, Vinicius da Cunha Martins; Lemos, Rodrigo Pinto; Ling, Lee LuanIn this work, in order to describe network traffic characteristics, such as long-range dependence among samples, self-similarity and multiscale behavior, we propose a Multifractal Adaptive Model based on a multiscale cascade in the Wavelet Domain. We compare the proposed model performance with those of other models presented in the literature. It is also proposed an envelope process for the network traffic that takes into account parameters of the Multifractal Adaptive Model. Furthermore, we derive an equation in order to estimate the buffer overflow probability for both a simplified communication system with a single server, single queue and finite buffer, and to a wireless network multiuser scenario based on OFDM technology. To this end, we consider the service curve of the round-robin scheduling algorithm of the OFDM network. Taking into account the envelope process and the service curve we obtain, through the Network Calculus theory, the maximum delay experienced by users of the OFDM network. Moreover, assuming a similar network scenario to an LTE network, we propose a joint channel-aware and queue-aware resource scheduling algorithm. Based on the presented scheduler, we propose a minimum service curve for the LTE user and through this we propose an approach to accomplish maximum delay guarantee.Item Definitividade de formas quadráticas – uma abordagem polinomial(Universidade Federal de Goiás, 2016-11-18) Alves, Jesmmer da Silveira; Brustle, Thomas; http://www2.ubishops.ca/algebra/brustleCv.pdf; Castonguay, Diane; http://lattes.cnpq.br/4005898623592261; Castonguay, Diane; http://lattes.cnpq.br/4005898623592261; Centeno, Carmen; Alvares, Edson Ribeiro; Martinez, Fabio Henrique Viduani; Longo, Humberto JoséQuadratic forms are algebraic expressions that have important role in different areas of computer science, mathematics, physics, statistics and others. We deal with rational quadratic forms and integral quadratic forms, with rational and integer coefficients respectively. Existing methods for recognition of rational quadratic forms have exponential time complexity or use approximation that weaken the result reliability. We develop a polinomial algorithm that improves the best-case of rational quadratic forms recognition in constant time. In addition, new strategies were used to guarantee the results reliability, by representing rational numbers as a fraction of integers, and to identify linear combinations that are linearly independent, using Gauss reduction. About the recognition of integral quadratic forms, we identified that the existing algorithms have exponential time complexity for weakly nonnegative type and are polynomial for weakly positive type, however the degree of the polynomial depends on the algebra dimension and can be very large. We have introduced a polynomial algorithm for the recognition of weakly nonnegative quadratic forms. The related algorithm identify hypercritical restrictions testing every subgraph of 9 vertices of the quadratic form associated graph. By adding Depth First Search approach, a similar strategy was used in the recognition of weakly positive type. We have also shown that the recognition of integral quadratic forms can be done by mutations in the related exchange matrix.Item Construção de visualizações de matrizes origem-destino no cenário do tráfego urbano com foco em avaliação de usabilidade(Universidade Federal de Goiás, 2016-09-26) Gondim, Halley Wesley Alexandre Silva; Nascimento, Hugo Alexandre Dantas do; http://lattes.cnpq.br/2920005922426876; Carvalho, Cedric Luiz de; Freitas, Carla Maria Dal Sasso; Albuquerque, Eduardo Simões de; Soares, Fabrízzio Alphonsus Alves de Melo NunesMost of the medium and large cities in the world suffer from the problems related to the growth of the number of vehicles. Congestion, air pollution and weather are some examples of these problems, today constantly reminded of the great damage done to citizens. The use of Information Visualization techniques can serve to support the analysis of these problems and help identify viable and effective solutions for them. On the other hand, the application of Information Visualization to the problems of urban traffic is still a poorly explored area and generally focused on simple aspects of traffic. The present thesis thus addresses the lack of studies in this area, especially in the representation of data related to origin-destination (OD) matrices. In order to do so, a specific classification is proposed for visualizations aimed at the urban traffic scenario, with the purpose of facilitating the identification of works and authors related to the area. In addition, there is the creation of new visualizations, directed to OD arrays, in order to offer different alternatives in the representation of traffic data. Finally, an approach is proposed to evaluate visualizations of OD matrices and correlated information, with the intention of offering adequate feedback to interface designers and enabling the creation of more effective visualizations.Item SCOUT: a multi-objective method to select components in designing unit testing(Universidade Federal de Goiás, 2016-02-15) Freitas, Eduardo Noronha de Andrade; Camilo Júnior, Celso Gonçalves; http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4736184D1; Vincenzi, Auri Marcelo RIzzo; http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4763450Y6; Vincenzi, Auri Marcelo Rizzo; Camilo Júnior, Celso Gonçalves; Ferrari, Fabiano Cutigi; Dias Neto, Arilo Cláudio; Leitão Júnior, Plínio de SáThe creation of a suite of unit testing is preceded by the selection of which components (code units) should be tested. This selection is a significant challenge, usually made based on the team member’s experience or guided by defect prediction or fault localization models. We modeled the selection of components for unit testing with limited resources as a multi-objective problem, addressing two different objectives: maximizing benefits and minimizing cost. To measure the benefit of a component, we made use of important metrics from static analysis (cost of future maintenance), dynamic analysis (risk of fault, and frequency of calls), and business value. We tackled gaps and challenges in the literature to formulate an effective method, the Selector of Software Components for Unit testing (SCOUT). SCOUT was structured in two stages: an automated extraction of all necessary data and a multi-objective optimization process. The Android platform was chosen to perform our experiments, and nine leading open-source applications were used as our subjects. SCOUT was compared with two of the most frequently used strategies in terms of efficacy.We also compared the effectiveness and efficiency of seven algorithms in solving a multi-objective component selection problem: random technique; constructivist heuristic; Gurobi, a commercial tool; genetic algorithm; SPEA_II; NSGA_II; and NSGA_III. The results indicate the benefits of using multi-objective evolutionary approaches such as NSGA_II and demonstrate that SCOUT has a significant potential to reduce market vulnerability. To the best of our knowledge, SCOUT is the first method to assist software testing managers in selecting components at the method level for the development of unit testing in an automated way based on a multi-objective approach, exploring static and dynamic metrics and business value.Item Reconhecimento polinomial de álgebras cluster de tipo finito(Universidade Federal de Goiás, 2015-09-09) Dias, Elisângela SIlva; Castonguay, Diane; http://lattes.cnpq.br/4005898623592261; Castonguay, Diane; Schiffler, Ralf; Dourado, Mitre Costa; Carvalho, Marcelo Henrique de; Longo, Humberto JoséCluster algebras form a class of commutative algebra, introduced at the beginning of the millennium by Fomin and Zelevinsky. They are defined constructively from a set of generating variables (cluster variables) grouped into overlapping subsets (clusters) of fixed cardinality. Since its inception, the theory of cluster algebras found applications in many areas of science, specially in mathematics. In this thesis, we study, with computational focus, the recognition of cluster algebras of finite type. In 2006, Barot, Geiss and Zelevinsky showed that a cluster algebra is of finite type whether the associated graph is cyclically oriented, i.e., all chordless cycles of the graph are cyclically oriented, and whether the skew-symmetrizable matrix associated has a positive quasi-Cartan companion. At first, we studied the two topics independently. Related to the first part of the criteria, we developed an algorithm that lists all chordless cycles (polynomial on the length of those cycles) and another that checks whether a graph is cyclically oriented and, if so, list all their chordless cycles (polynomial on the number of vertices). Related to the second part of the criteria, we developed some theoretical results and we also developed a polynomial algorithm that checks whether a quasi-Cartan companion matrix is positive. The latter algorithm is used to prove that the problem of deciding whether a skew-symmetrizable matrix has a positive quasi-Cartan companion for general graphs is in NP class. We conjecture that this problem is in NP-complete class.We show that the same problem belongs to the class of polynomial problems for cyclically oriented graphs and, finally, we show that deciding whether a cluster algebra is of finite type also belongs to this class.