Theses and Dissertations

2017

ABSTRACTS

Departamento de Informática 
Pontifícia Universidade Católica do Rio de Janeiro - PUC-Rio
Rio de Janeiro - Brazil
 

This file contains the list of the MSc. Dissertations and PhD. Thesis presented to the Departmento de Informática, Pontifícia Universidade Católica do Janeiro - PUC-Rio, Brazil, in 2017.  They are all available in print format and, according to the authors' preference, some of them are freely available for download, while others are freely available for download to the PUC-Rio community exclusively(*). 

For any requests, questions, or suggestions, please contact:
Rosane Castilho bib-di@inf.puc-rio.br

Last update: 22/MARCH/2018
 

INDEX

[In construction; sometimes, digital versions may not be available yet]

[17_MSc_garcia]
Adriel GARCIA HERNÁNDEZ. Coreference resolution for the English language. [Title in Portuguese: Resolução de co-referência para a língua inglesa]. M.Sc Diss. Port. Presentation: 26/04/2017. 62 p. Advisor: Ruy Luiz Milidiú. DOI

Abstract: One of the problems found in natural language processing systems, is the difficulty to identify textual elements referring to the same entity; this task is called coreference. Solving this problem is an integral part of discourse comprehension since it allows language users to connect the pieces of speech information concerning to the same entity. Consequently, coreference resolution is a key task in natural language processing.  Despite the large effort of existing research, the current performance of coreference resolution systems has not reached a satisfactory level yet. In this work, we describe a structure learning system for unrestricted coreference resolution that explores two techniques: latent coreference trees and automatic entropy-guided feature induction. The latent tree modeling makes the learning problem computationally feasible, since it incorparates a relevant hidden structure. Additionally, using an automatic feature induction method, we can efficeintly build non-linear model learning algorithms, namely, the structure and sparse perceptron algorithm.  We evaluate the system in the CoNLL-2012 Shared Task closed track data set, for the English portion.  The proposed system obtains a 62.24% value on the competitition's official score. This result is bellow the 65.73%, the state-of-the-art performance for this task. Nevertheless, our solution significantly reduces the time to obtain the clusters of a document, since, our systems takes 0.35 seconds per document in the testing set, while in the state-of-the-art, it takes 5 seconds for each one. 

[17_MSc_mustelier]
Alejandro MUSTELIER MENÉS. Avaliação da qualidade da montagem de fragmentos de sequências biológicas. [Title in English: Quality evaluation for fragments assembly of biological sequence]. M.Sc. Diss. Port. Presentation: 06/10/2017. 61 p. Advisor: Sérgio Lifschitz. DOI

Abstract: New DNA sequencing technologies, known as NGS - Next-Generation Sequencing, are responsible for making the sequencing process more efficient. However, they generate a result with very small DNA fragments, known as reads. We consider the genome assembly from these fragments a complex problem due to its combinatorial nature and the large volume of reads produced. In general, biologists and bioinformatics experts choose the sequence assembler program with no regard to the computational efficiency or even the quality of the biological result information. This research aims to assist users in the interpretation of assembly results, including effectiveness and efficiency. In addition, this may sometimes increase the quality of the results obtained. Firstly, we propose an algorithm to obtain information about the genes present in the result assembly. We enumerate the identified genes, those that have the correct size and the correct base pair sequence. Next, exhaustive experimental tests involving five of the main genome assemblers in the literature which are based on the use of graphs of Bruijn and eight bacterial genomes data set were ran. We have performed statistical comparisons of results using QUAST and REAPR tools. We have also obtained qualitative information for the genes using the proposed algorithm and some computational efficiency metrics. Based on the collected results, we present a comparative analysis that allows users to understand further the behavior of the tools considered in the tests. Finally, we propose a tool that receives different assemblies of the same genome and produces a qualitative and quantitative report for the user, enabling the interpretation of the results in an integrated way.

[17_PhD_mera]
Alexander Arturo MERA CARABALLO. Clustering and dataset interlinking recommendation in the linked open data cloud. [Title in Portuguese: Clusterização e recomendação de interligação de conjunto de dados na nuvem de dados abertos conectados.]. Ph.D. Thesis. Eng. Presentation: 17/03/2017. 89 p. Advisor: Marco Antonio Casanova. DOI

Abstract: The volume of RDF data published on the Web increased considerably, which stressed the importance of following the Linked Data principles to foster interoperability. One of the principles requires that a new dataset should be interlinked with other datasets published on the Web. This thesis contributes to addressing this principle in two ways. First, it uses community detection algorithms and profiling techniques for the automatic creation and analysis of a Linked Open Data (LOD) diagram, which facilitates locating datasets in the LOD cloud. Second, it describes three approaches, backed up by fully implemented tools, to recommend datasets to be interlinked with a new dataset, a problem known as the dataset interlinking recommendation problem. The first approach uses link prediction measures to provide a list of datasets recommendations for interlinking. The second approach employs supervised learning algorithms, jointly with link prediction measures. The third approach uses clustering algorithms and profiling techniques to produce dataset interlinking recommendations. These approaches are backed up, respectively, by the TRT, TRTML and DRX tools. Finally, the thesis extensively evaluates these tools, using real-world datasets, reporting results that show that they facilitate the process of creating links between disparate datasets.

[17_MSc_chavez]
Alexander CHÁVEZ LÓPEZ. How does refactoring affect internal quality attributes? A multi-project study. [Title in Portuguese:  Como a refatoração afeta os atributos de qualidade interna? Um estudo multi-projeto]. M.Sc. Diss. Eng. Presentation: 23/09/2017. 80 p. Advisor: Alessandro Fabrício Garcia. DOI

Abstract: Developers often apply code refactoring to improve the internal quality attributes of a program, such as coupling and size. Given the structural decay of certain program elements, developers may need to apply multiple refactorings to these elements to achieve quality attribute improvements. We call re-refactoring when developers refactor again a previously refactored element in a program, such as a method or a class. There is limited empirical knowledge on to what extent developers successfully improve internal quality attributes through (re-)refactoring in their actual software projects. This dissertation addresses this limitation by investigating the impact of (re-)refactoring on five well-known internal quality attributes: cohesion, complexity, coupling, inheritance, and size. We also rely on the version history of 23 open source projects, which have 29,303 refactoring operations and 49.55% of re-refactoring operations. Our analysis revealed relevant findings. First, developers apply more than 93.45% of refactoring and re-refactoring operations to code elements with at least one critical internal quality attribute, as oppositely found in previous work. Second, 65% of the operations actually improve the relevant attributes, i.e. those attributes that are actually related to the refactoring type being applied; the remaining 35% operations keep the relevant quality attributes unaffected. Third, whenever refactoring operations are applied without additional changes,whichwecallroot-canal refactoring,theinternalqualityattributes are either frequently improved or at least not worsened. Contrarily, 55% of the refactoring operations with additional changes, such as bug fixes, surprisingly improve internal quality attributes, with only 10% of the quality decline. This finding is also valid for re-refactoring. Finally, we also summarize our findings as concrete recommendations for both practitioners and researchers.

[17_MSc_herrera]
Alice HERRERA DE FIGUEIREDO. Campos de direcionalidade na geração e avaliação de malhas de quadriláteros. [Title in English:  Directionality fields in generation and evaluation of quadrilateral meshes]. M.Sc. Diss. Port. Presentation: 29/09/2017. 59 p. Advisor:  Waldemar Celes Filho. DOI

Abstract: One of the main challenges in quadrilateral mesh generation is to ensure the alignment of the elements with respect to domain constraints. Unaligned meshes insert numerical problems in simulations that use these meshes as a domain discretization. However, there is no alignment metric for evaluating the quality of quadrilateral meshes. A directionality field represents the diffusion of the constraints orientation to the interior of the domain. Kowalski et al. use a directionality field for domain partitioning into quadrilateral regions. In this work, we reproduce their partitioning method with some modifications, aiming to reduce the final number of partitions. We also propose a metric to evaluate the quality of a quadrilateral mesh with respect to the alignment with domain constraints.

[17_PhD_guedes]
Álan Lívio Vasconcelos GUEDES. Extending multimedia languages to support multimodal user interactions. [Title in Portuguese: Estendendo linguagens multimídia para suportar interações multimodais]. Ph.D. Thesis. Eng. Presentation: 29/09/2017. 111 p. Advisor:  Simone Diniz Junqueira Barbosa. DOI

Abstract: Recent advances in recognition technologies, such as speech, touch and gesture, have given rise to a new class of user interfaces that does not only explore multiple modalities but also allows for multiple interacting users. The development of applications with both multimodal and multiuser interactions arise new specification and execution issues. The specification of multimodal application is commonly the focus of multimodal interaction research, while the specification of the synchronization of audiovisual media is usually the focus of multimedia research. In this thesis, aiming to assist the specification of such applications, we propose to integrate concepts from those two research areas and to extend multimedia languages with first-class entities to support multiuser and multimodal features. Those entities were instantiated in NCL and HTML. To evaluate our approach, we performed an evaluation with NCL and HTML developers to capture evidences of their acceptance of the proposed entities and instantiations in those languages.

[17_MSc_medeiros]
Anthony Seabra MEDEIROS. Particionamento como ação de sintonia fina em Bancos de Dados Relacionais. [Title in English: Partitioning as a tuning action for Relational Databases]. M.Sc. Diss. Port. Presentation: 04/04/2017. 156 p. Advisor: Sérgio Lifschitz.

Abstract: The main fine tuning strategies used by relational database administrators are the construction of access structures, such as indexes, partial indexes and materialized views, and techniques such as denormalization and query rewriting. These techniques and access structures, together or separately, can improve the performance of queries submitted to the database. Database partitioning, a technique traditionally used for data distribution, has also the potential for fine tuning, since it allows the scanning of tables to be performed only on partitions that satisfy query predicates. Even in queries with high selectivity predicates, whose execution plans often use indexes, partitioning can offer even greater benefit. This dissertation proposes to evaluate the partitioning as a fine tuning action of relational databases and, for that, develops heuristics for selection of partitioning strategies and evaluation of its benefit. An evaluation of the quality of the results obtained is carried out through experiments with a standard benchmark for this type of research and we have shown that, in certain cases, it is advantageous to partition data.

[17_MSc_martinez]
Armando Enrique MARTINEZ GONZALEZ. Fall risk analysis during VR interaction. [Title in Portuguese: Análise do risco de queda durante a interação com realidade virtual]. M.Sc. Diss. Eng. Presentation: 17/03/2017. 56 p. Advisor: Alberto Barbosa Raposo.

Abstract: With the increasing popularity and accessibility of high-quality Virtual Reality (VR) systems, concerns have been raised about the propensity of VR to induce balance loss. Balance is essential for safe use of VR experience and its loss can result in severe injury. This project is set to create a system able to measure the impact of VR in the human balance system. In this work, we design and conduct an experiment making use of the Oculus Rift VR headset and MS Kinect Sensor. In this experiment, we are able to visualize, quantify, and compare the effect of different VR scenes on the balance of the experiment subjects as well as the effect of visual and auditory warnings of balance loss.

[17_PhD_mendes]
Carlos Raoni de Alencar MENDES. Effective resource allocation for planning and control project portfolios under uncertainty: a robust optimization approach. [Title in Portuguese: Alocação efetiva de recursos para planejamento e controle de portfolios de projetos sob incerteza: uma abordagem de otimização robusta]. Ph.D. Thesis. Eng. Presentation: 24/08/2017. 112 p. Advisor: Marcus Vinicius Soledade Poggi de Aragão and Bruno da Costa Flach (IBM). DOI

Abstract: Planning and controlling complex project portfolios is a challenging task. These portfolios are subject to a number of potential risk sources coupled with resource constraints, intricate precedence relationships, and penalties for project delays. For this reason, it is fundamental that optimal strategies for the allocation of the available resources are constantly adopted by the decision makers to ensure that their projects are completed within limits of time and cost. Moreover, the uncertainty that affects these projects has to be taken into account for effective resource allocation decisions. Within this context, this work proposes a robust optimization-based methodology for planning and controlling project portfolios under uncertainty. The method combines models and algorithms for multiple resource allocation problems under the same robust optimization framework. In this approach, the uncertainty environment is modeled as an adversary that selects the worst-case combination of risks for any decision maker’s actions. Subsequently, the main goal of the decision maker is to determine optimal resource allocation plans for minimizing a particular objective subject to the assumption that the adversary’s worst-combination of risks will materialize. The approach also provides a way to control the degree of conservatism of the solutions. For each studied problem, a solution strategy is developed through a reformulation scheme from a compact min-max formulation to a cut-generation algorithm. Several computational experiments are conducted, providing key insights that drive the design of the referred portfolio planning and control methodology. The ineffectiveness of traditional critical path analysis under worst-case realizations of uncertain activities’ durations and the importance of taking integrated resource allocation decisions in the context of project portfolios, are examples of the key findings of the experiments. The application of the methodology is demonstrated in a case study of a portfolio aimed at the construction of two refineries. This example presents the capabilities of the developed techniques in a practical context.

[17_PhD_almeida]
Cassio Freitas Pereira de ALMEIDA. Mapeamento da distribuição populacional através da detecção de áreas edificadas em imagens de regiões heterogêneas do Google Earth usando Deep Learning. [Title in English: Population distribution mapping through the detection of building areas in Google Earth images of heterogeneous regions using Deep Learning]. Ph.D. Thesis. Port. Presentation: 26/10/2017. 72 p. Advisor: Hélio Côrtes Vieira Lopes. DOI

Abstract: The importance of precise information about the population distribution is widely acknowledged. The census is considered the most reliable and complete source of this information, and its data are delivered in an aggregated form in sectors. These sectors are operational units with irregular shapes, which hinder the spatial analysis of the data. Thus, the transformation of sectors onto a regular grid would facilitate such analysis. A methodology to achieve this transformation could be based on remote sensing image classification to identify building where the population lives. The building detection is considered a complex task since there is a great variability of building characteristics and on the images quality themselves. The majority of methods are complex and very specialist dependent. The automatic methods require a large annotated dataset for training and they are sensitive to the image quality, to the building characteristics, and to the environment. In this thesis, we propose an automatic method for building detection based on a deep learning architecture that uses a relative small dataset with a large variability. The proposed method shows good results when compared to the state of the art. An annotated dataset has been built that covers 12 cities distributed in different regions of Brazil. Such images not only have different qualities, but also shows a large variability on the building characteristics and geographic environments. A very important application of this method is the use of the building area classification in the dasimetric methods for the population estimation into grid. The concept proof in this application showed a promising result when compared to the usual method allowing the improvement of the quality of the estimates.

[17_MSc_gribel]
Daniel Lemes GRIBEL. Hybrid genetic algorithm for the Minimum Sum-of-Squares clustering problem. [Title in Portuguese: Algoritmo genético híbrido para o problema de clusterização Minimum Sum-of-Squares]. M.Sc. Diss. Eng. Presentation: 20/03/2017. 54 p. Advisor: Thibaut Victor Gaston Vidal.

Abstract: Clustering plays an important role in data mining, being useful in many fields that deal with exploratory data analysis, such as information retrieval, document extraction, and image segmentation. Although they are essential in data mining applications, most clustering algorithms are adhoc methods. They have a lack of guarantee on the solution quality, which in many cases is related to a premature convergence to a local minimum of the search space. In this research, we address the problem of data clustering from an optimization perspective, where we propose a hybrid genetic algorithm to solve the Minimum Sum-of-Squares Clustering (MSSC) problem. This meta-heuristic is capable of escaping from local minima and generating near-optimal solutions to the MSSC problem. Results show that the proposed method outperformed the best current literature results – in terms of solution quality – for almost all considered sets of benchmark instances for the MSSC objective.

[17_MSc_carvalho]
Felipe Oliveira CARVALHO. Descoberta contínua de serviços em IoT. [Title in English: Continuous service discovery in IoT]. M.Sc. Diss. Eng. Presentation: 26/04/2017. 65 p. Advisor: Markus Endler.

Abstract: The popularization of the Internet of Things sparked a growing opportunity for the creation of applications in various areas, by combining the use of sensors and/or actuators. In IoT environments, the role of elements called gateways is to provide an intermediate communication layer between IoT devices and cloud services. A crucial factor for the construction of large-scale applications is to allow the use of IoT devices in a transparent manner, in a service-oriented paradigm, where details of communication and configuration are handled by the gateways. In service model, applications must discover the high-level interfaces of the devices and do not have to deal with underlying details that are handled by gateways. In scenarios of high dynamism and mobility (with connections and disconnections of devices occuring all the time), this discovery and configuration must occur continuously. Traditional service discovery protocols, such as Universal Plug and Play (UPnP) or Service Location Protocol (SLP), have not been developed taking into consideration the high dinamicity of IoT environments. In this sense, we introduce complex event processing (CEP), which is a technology for real-time processing of heterogeneous event flows, which allows the use of CQL (Continuous Query Language for the search of events of interest. In a model where events related to sensor discovery are sent to a CEP flow, expressive queries are written for an application to continuously discover services of interest. This work presents the extension of MHub /CDDL to support continuous service discovery in IoT, using CEP. The MHub / CDDL (Mobile Hub / Context Data Distribution Layer) is a middleware for service discovery and quality context management in IoT, developed in a partnership between the Laboratory for Advanced Collaboration (LAC) from PUC-Rio and the Laboratório de Sistemas Distribuídos Inteligentes (LSDi) from Universidade Federal do Maranhão (UFMA). The implementation of this work is done in Android (Java) platform and a case study in the domain of smart parking is conducted and implemented, elucidating the use of the continuous discovery mechanism.

[17_MSc_santosjunior]
Fernando Alberto Correia dos SANTOS JUNIOR. Geração automática de exemplos de uso a partir da descrição textual de casos de uso. [Title in English: Automatic generation of examples of use from the textual description
of use cases]. M.Sc. Diss. Eng. Presentation: 24/04/2017. 128 p. Advisor: Arndt von Staa.

Abstract: This master's dissertation presents a solution for the automatic generation of examples of use from the textual description of use cases. Use cases describe specifications in a sufficiently formal way that is enough to automatically generate usage examples. A generated example is a text in a natural language which is the paraphrase of one possible manner to use the software, extracted from the use case and applied to a real context where actors are converted into fictitious personas and attributes are valued according to the business rules specified in the use case. The proposed format to present the example aims to allow clients to read, to understand
and to judge whether the expressed behavior is in fact what he wants. With this approach, it is expected that the customer himself can approve the specifications and when defects are found, so the specification can quickly be corrected and reflected in the examples. At the same time, the formalized specification in the form of a use case will help developers create solutions that are by construction closer to the correct one when compared to conventional textual specifications.

[17_MSc_guillot]
Haydée GUILLOT JIMÉNEZ.  Applying process mining to the academic administration domain . [Title in Portuguese:  Aplicação de mineração de processos ao domínio acadêmico administrativo]. M.Sc. Diss. Port. Presentation: 21/09/2017. 67 p. Advisor:  Antonio Luz Furtado. DOI

Abstract: Higher Education Institutions keep a sizable amount of data, including student records and the structure of degree curricula. This work, adopting a process mining approach, focuses on the problem of identifying how closely students follow the recommended order of the courses in a degree curriculum, and to what extent their performance is affected by the order they actually adopt. It addresses this problem by applying to student records two already existing techniques: process discovery and conformance checking, and frequent itemsets. Finally, the dissertation covers experiments performed by applying these techniques to a case study involving over 60,000 student records from PUC-Rio. The experiments show that the frequent itemsets technique performs better than the process discovery and conformance checking techniques. They equally confirm the relevance of analyses based on the process mining approach to help academic coordinators in their quest for better degree curricula.

[17_MSc_paucar]
Herminio PAUCAR CURASMA.  Uma ferramenta para a introdução à programação e pensamento computacional com motivação usando realidade virtual. [Title in English:  A tool for the introduction of programming and computational thinking with motivation using virtual reality]. M.Sc. Diss. Port. Presentation: 24/10/2017. 111 p. Advisor:  Alberto Barbosa Raposo. DOI

Abstract: Nowadays, we often hear about the importance of Information and Communication Technologies (ICT) by various social actors. The influence of ICT crosses the various areas of society as agriculture, services, trade, industry, research, among others. If we do an inverse reasoning, it will be difficult to name social fields that are not directly or indirectly influenced by ICTs. In addition, the demand for workers in Computer Science and areas related to the STEM (Science, Technology, Engineering, and Mathematics) is on the rise. That is why it is important to make the young person interested in technology (Computer programming) and participate in it in a fun and playful way. The present work proposes the creation of a Virtual Reality tool that allows students to learn basic concepts of programming and computational thinking with the purpose that they enjoy the technology and feel motivated to learn more. The tool is a Visual Programming Language; the algorithms are formed by block-assembly, thereby solving one of the students' main problems, which are "syntax errors". In addition, the tool brings with it a set of level-ordered challenges aimed at teaching students basic principles of programming and logic (sequential programming, repetitive and conditional data structure), where at each level the student will learn the different concepts and behaviors of computational thinking. For the evaluations with the users we counted on the participation of 18 students between 12 and 15 years old coming from two public institutions of Rio de Janeiro. In these evaluations it was also considered to measure the sensation of immersion through Telepresence, Social Presence and Usability.

[17_PhD_muhammad]
Hisham Hashem MUHAMMAD. Dataflow semantics for end-user programmable applications. [Title in Portuguese: Semânticas de dataflow para aplicações programáveis por usuários finais]. Ph.D. Thesis. Eng. Presentation: 28/04/2017. 184 p. Advisor: Roberto Ierusalimschy. DOI

Abstract: Many applications are made programmable for advanced end-users by adding facilities such as scripting and macros. Other applications take a programming language to the center stage of its UI. That is the case, for
example, of the spreadsheet formula language. While scripting has benefited from the advances of programming language research, producing mature and reusable languages, the state of UI-level languages lags behind. We claim that a better understanding of such languages is necessary. In this work, we model the semantics of existing end-user programming languages in three different domains: multimedia, spreadsheets and engineering. Our focus is on dataflow languages, a representative paradigm for end-user programmable applications. Based on this analysis, we aim to provide a better understanding of dataflow semantics as used in the context of end-user programming and propose guidelines for the design of UI-level languages for end-user programmable applications.

[17_PhD_vasconcelos]
Igor Oliveira VASCONCELOS. Detecção móvel e online de anomalia em múltiplos fluxos de dados: uma abordagem baseada em processamento de eventos complexos para detecção de comportamento de condução. [Title in English: A mobile and online outlier detection over multiple data streams: a complex event processing approach for driving behavior detection]. Ph.D. Thesis. Port. Presentation: 31/03/2017. 102 p. Advisor: Markus Endler. DOI

Abstract: Driving is a daily task that allows individuals to travel faster and more comfortably, however, more than half of fatal crashes are related to recklessness driving behaviors. Reckless maneuvers can be detected with accuracy by analyzing data related to driver-vehicle interactions, abrupt turns, acceleration, and deceleration, for instance. Although there are algorithms for online anomaly detection, they are usually designed to run on computers with high computational power. In addition, they typically target scale through parallel computing, grid computing, or cloud computing. This thesis presents an online anomaly detection approach based on complex event processing to enable driving behavior classification. In addition, we investigate if mobile devices with limited computational power, such as smartphones, can be used for online detection of driving behavior. To do so, we first model and evaluate three online anomaly detection algorithms in the data stream processing paradigm, which receive data from the smartphone and the in-vehicle embedded sensors as input. The advantages that stream processing provides lies in the fact that reduce the amount of data transmitted from the mobile device to servers/the cloud, as well as reduce the energy/battery usage due to transmission of sensor data and possibility to operate even if the mobile device is disconnected. To classify the drivers, a statistical mechanism used in document mining that evaluates the importance of a word in a collection of documents, called inverse document frequency, has been adapted to identify the importance of an anomaly in a data stream, and then quantitatively evaluate how cautious or reckless drivers' maneuvers are. Finally, an evaluation of the approach (using the algorithm that achieved better result in the first step) was carried out through a case study of the 25 drivers’ driving behavior. The results show an accuracy of 84% and an average processing time of 100 milliseconds.

[17_PhD_santos]
Jefferson de Barros SANTOS. Systems for provability and countermodel generation in propositional minimal implicational Logic. [Title in Portuguese: Sistemas de prova e geração de contra exemplo para Lógica Proposicional Minimal Implicacional]. Ph.D. Thesis. Port. Presentation: 18/05/2017. 82 p. Advisor: Edward Hermann Haeusler.

Abstract: This thesis presents a new sequent calculus called LMT! that has the properties to be terminating, sound and complete for Propositional Implicational Minimal Logic (M!). LMT! is aimed to be used for proof search in M!, in a bottom-up approach. Termination of the calculus is guaranteed by a strategy of rule application that forces an ordered way to search for proofs such that all possible combinations are stressed. For an initial formula, proofs in LMT! has an upper bound of jj 2j j+1+2
log2j, which together with the system strategy ensure decidability. System rules are conceived to deal with the necessity of hypothesis repetition and the contextsplitting nature of !-left, avoiding the occurrence of loops and the usage of backtracking. Therefore, LMT! steers the proof search always in a forward, deterministic manner. LMT! has the property to allow extractability of counter-models from failed proof searches (bicompleteness), i.e., the attempt proof tree of an expanded branch produces a Kripke model that falsifies the initial formula. Counter-model generation (using Kripke semantics) is achieved as a consequence of the completeness of the system. LMT! is implemented as an interactive theorem prover based on the calculus proposed here. We compare our calculus with other known deductive systems for M!, especially with Fitting's Tableaux, a method that also has the bicompleteness property. We also proposed here a translation of LMT! to the Dedukti proof checker as a way to evaluate the correctness of the implementation regarding the system specification and to make our system easier to compare to others.

[17_MSc_grosman]
Jonatas dos Santos GROSMAN. LER: anotação e classificação automática de entidades e relações. [Title in English: LER: Annotation and automatic classification of entities and relations]. M.Sc. Diss. Port. Presentation: 20/04/2017. 196 p. Advisor: Hélio Côrtes Vieira Lopes. DOI

Abstract: Many techniques for the structured information extraction from natural language data have been developed and have demonstrated their potentials yielding satisfactory results. Nevertheless, to obtain such results, they require some activities that are usually done separately, such as text annotation to generate corpora, Part-Of- Speech tagging, features engineering and extraction, machine learning models’ training etc., making the information extraction task a costly activity due to the effort and time spent on this. The present work proposes and develops a web based platform called LER (Learning Entities and Relations), that integrates the needed workflow for these activities, with an interface that aims the ease of use. The work also shows the platform implementation and its use.

[17_PhD_rodriguez]
Kathrin RODRIGUEZ LLANES. Bus network analysis and monitoring. [Title in Portuguese: Análise e monitoramento de redes de ônibus]. Ph.D. Thesis. Eng. Presentation: 26/05/2017. 137 p. Advisor: Marco Antonio Casanova.

Abstract: Buses, equipped with active GPS devices that continuously transmit their position, can be understood as mobile traffic sensors. Indeed, bus trajectories provide a useful data source for analyzing traffic in the bus network of a city, if the city traffic authority makes the bus trajectories available openly, timely and in a continuous way. In this context, this thesis proposes a bus GPS data-driven approach for analyzing and monitoring the bus network of a city. It combines graph algorithms, geospatial data mining techniques and statistical methods. The major contribution of this thesis is a detailed discussion of key operations and algorithms for modeling, analyzing and monitoring bus network traffic, specifically: (1) modelling, analyzing, and segmentation of the bus network; (2) mining the bus trajectory dataset to uncover traffic patterns; (3) detecting traffic anomalies, classifying them according to their severity, and estimating their impact; (4) maintaining and comparing different versions of the bus network and traffic patterns to help urban planners assess changes. Another contribution is the description of experiments conducted for the bus network of the City of Rio de Janeiro, using bus trajectories obtained from June 2014 to February 2017, which have been made available by the City Hall of Rio de Janeiro. The results obtained corroborate the usefulness of the proposed approach for analyzing and monitoring the bus network of a city, which may help traffic managers and city authorities improve traffic control and urban mobility plans.

[17_MSc_castro]
Liester Cruz CASTRO. Sintonia fina de sistemas de gerenciamento de banco de dados em ambientes virtualizados. [Title in English: Tuning of database management systems in virtualized environments]. M.Sc. Diss. Port. Presentation: 26/04/2017. 84 p. Advisor: Sérgio Lifschitz. DOI

Abstract: Due to the huge amount of data present in current applications there is a growing use of Relational Database Management Systems (RDBMS) in virtualized environments. This fact increases the workloads' input/output (I/O) requirements with respect to the corresponding workloads. This is due to resources virtualization and virtual machines scheduling. Our work’s goal is to propose strategies that enable better performances for the I/O operations managed by the RDBMS. Considering an intelligent assignment of computational resources, we have executed fine tuning actions at the virtualized environment and on database parameters. We consider a system that works coordinately with distinct virtualization layers. We show some experimental results that evaluate and measure the impact of our proposed approach.

[17_PhD_rodrigues]
Lívia Couto Ruback RODRIGUES. Enriching and analyzing semantic trajectories with linked open data. [Title in Portuguese: Enriquecendo e analisando trajetórias semânticas com dados abertos interligados]. Ph.D. Thesis. Port. Presentation: 15/12/2017. 104 p. Advisor: Marco Antonio Casanova and Chiara Renso (ISTI/CNR, Pisa, Italy). DOI

Abstract: The last years witnessed a growing number of devices that track moving objects: personal GPS equipped devices and GSM mobile phones, vehicles or other sensors from the Internet of Things but also the location data deriving from the Social Networks check-ins. These mobility data are represented as trajectories, recording the sequence of locations of the moving object. However, these sequences only represent the raw location data and they need to be semantically enriched to be meaningful in the analysis tasks and to support a deep understanding of the movement behavior. Another unprecedented global space that is also growing at a fast pace is the Web of Data, thanks to the emergence of the Linked Data initiative. These freely available semantic rich datasets provide a novel way to enhance trajectory data. This thesis presents a contribution to the many challenges that arise from this scenario. First, it investigates how trajectory data may benefit from the Linked Data Initiative by guiding the whole trajectory enrichment process with the use of external datasets. Then, it addresses the pivotal topic of the similarity computation between Linked Data entities with the final objective of computing the similarity between semantically enriched trajectories. The novelty of our approach is that the thesis considers the relevant entity features as a ranked list. Finally, the thesis targets the computation of the similarity between enriched trajectories by comparing the similarity of the Linked Data entities that represent the enriched trajectories.

[17_MSc_figueiredo]
Lucas Caracas de FIGUEIREDO. Remoção de superfícies encobertas no cálculo de área de pintura em modelos CAD. [Title in English: Hidden surfaces removal in painting area calculation on CAD models]. M.Sc. Diss. Port. Presentation: 18/08/2017. 53 p. Advisor: Waldemar Celes Filho. DOI

Abstract: CAD Systems – Computer-Aided Design Systems – are widely used in the different life cycle stages of an engineering enterprise, such as conceptual design, physical structure construction, and plant operation. The maintenance of the facility is a very important task during the operation, where painting the equipments and structures is essential. Estimating the painting area of the different objects has a high cost if done manually, using measuring tapes and lasers. A more efficiently way to calculate these areas is through the use of CAD tools. However, the modeling process of the CAD model, using parametric objects and three-dimensional meshes, inserts surfaces that are hidden by other objects. These hidden surfaces are not painted, and considering their areas in the painting budgeting leads to considerable errors. Therefore, the use of a simple calculation of all the surfaces areas that compose the objects is not adequate. With the objective of eliminating the hidden surfaces of the painting area computation, this work proposes an approach based on adaptive distance fields together with constructive solid geometry operations. Firstly, the meshes pass through a preprocessing phase, in which they are adjusted to fulfill the requirements for the adaptive distance field construction, and then their fields are computed. Parametrized objects do not need this step because they already have an implicit distance field. Constructive solid geometry operations were then used to obtain the difference and the intersection fields of each object with the scene. With this data, the painting areas are calculated considering the areas of the difference with the scene, the intersection and the surface area of each object. In controlled tests, the painting areas obtained differs of a maximum of 0.84% of the real areas. In tests with real models, a reduction of up to 38% of the estimated area was obtained in relation to the simplistic approach of not treating hidden surfaces.

[17_MSc_henriques]
Luis Felipe Müller de Oliveira HENRIQUES. Deep architecture for quotation extraction. [Title in Portuguese:  Arquitetura profunda para extração de citações]. M.Sc. Diss. Eng. Presentation: 08/03/2017. 68 p. Advisor: Ruy Luiz Milidiú. DOI

Abstract: Quotation Extraction and Attribution is the task of identifying quotations from a given text and associating them to their authors. In this work, we present a Quotation Extraction and Attribution system for the Portuguese language. The Quotation Extraction and Attribution task has been previously approached using various techniques and for a variety of languages and datasets. Traditional models to this task consist of extracting a rich set of hand-designed features and using them to feed a shallow classifier. In this work, unlike the traditional approach, we avoid using hand-designed features using unsupervised learning techniques and deep neural networks to automatically learn relevant features to solve the task. By avoiding design features by hand, our machine learning model became easily adaptable to other languages and domains. Our model is trained and evaluated at the GloboQuotes corpus, and its F1 performance metric is equal to 89.43%.
 

[17_MSc_fonseca]
Luís Marcelo Vital Abreu FONSECA. Classificação de objetos em contexto real por redes neurais convolutivas. [Title in English: Classification of objects in real context by convolutional neural networks]. M.Sc. Diss. Port. Presentation: 07/03/2017. 56 p. Advisor: Ruy Luiz Milidiú.

Abstract: The classification of objects in real contexts is the technological apex of object recognition. This type of classification is complex, containing diverse computer vision problems in abundance. This project proposes to solve that type of classification through the use of machine learning knowledge applied to the MS COCO dataset. The implemented algorithm in this project consists of a Convolutional Neural Network model that is able to learn characteristics of the objects and predict their classes. Some experiments are made that compare different results of predictions using different techniques of learning. There is also a comparison of the results from the implementation with state of art in contextual objects segmentation.

[17_PhD_cunha]
Marcio Luiz Coelho CUNHA. Software of places: toward a self-learning closed plant production system. [Title in Portuguese:  Software dos Lugares: em direção a um sistema fechado para produção de plantas com autoaprendizado]. Ph.D. Thesis. Eng. Presentation: 20/12/2017. 111 p. Advisor: Hugo Fuks. DOI

Abstract: As the population grows, more food will need to be produced in the next four decades than has been in the past 10,000 years. However, the modern world still depends on high yield monoculture production which is increasingly threatened by unusual weather, water shortages, and insufficient land. In order to overcome these problems and feed the world, a practical path to provide quality fresh healthy food at scale with minimal weather dependency, water usage and reduced carbon footprint is necessary. One reasonable approach is to build vertical farms inside the cities in a close environment full of sensors and artificial lighting controlled by software for efficient production of food crops. This thesis proposes a model, entitled Software of Places Cycle (SoPC), that should be able to answer to environmental stimuli in a closed plant production system using artificial lighting in order to create a self-learning environment. This thesis describes the SoPC, the approaches and processes of implementing a mini Plant Factory using Artificial Lighting based on the discussion on five action-research cycles. The thesis main contribution is a conceptual model to guide the development and maintenance of a mini-PFAL (m-PFAL), a minor contribution is the deployment of the SoP, i.e., the very notion of having software dedicated to a specific place.

[17_PhD_rorizjunior]
Marcos Paulino RORIZ JUNIOR. DG2CEP: an on-line algorithm for real-time detection of spatial clusters from large data streams through complex event processing. [Title in English: DG2CEP: um algoritmo on-line para detecção em tempo real de aglomerados espaciais em grandes fluxos de dados através de processamento de fluxo de dados]. Ph.D. Thesis. Eng. Presentation: 22/03/2017. 121 p. Advisor: Markus Endler.

Abstract: Spatial concentrations (or spatial clusters) of moving objects, such as vehicles and humans, is a mobility pattern that is relevant to many applications. A fast detection of this pattern and its evolution, e.g., if the cluster is shrinking or growing, is useful in numerous scenarios, such as detecting the formation of traffic jams or detecting a fast dispersion of people in a music concert. An on-line detection of this pattern is a challenging task because it requires algorithms that are capable of continuously and efficiently processing the high volume of position updates in a timely manner. Currently, the majority of approaches for spatial cluster detection operate in batch mode, where moving objects location updates are recorded during time periods of certain length and then batch-processed by an external routine, thus delaying the result of the cluster detection until the end of the time period. Further, they extensively use spatial data structures and operators, which can be troublesome to maintain or parallelize in on-line scenarios. To address these issues, in this thesis we propose DG2CEP, an algorithm that combines the well-known density-based clustering algorithm DBSCAN with the data stream processing paradigm Complex Event Processing (CEP) to achieve continuous and timely detection of spatial clusters. Our experiments with real world data streams indicate that DG2CEP is able to detect the formation and dispersion of clusters with small latency while having a higher similarity to DBSCAN than batch-based approaches.

[17_MSc_alves]
Paulo Henrique Cardoso ALVES. Agentes de software com traços de personalidade baseados na arquitetura BDI para tomada de decisões normativas. [Title in English: Software agents with personality traits based on BDI architecture to improve normative decision making process]. M.Sc. Diss. Port. Presentation: 02/08/2017. 57 p. Advisor: Carlos José Pereira de Lucena. DOI

Abstract: Norms are applied in multiagent systems as mechanisms capable of restricting the behavior of software agents in order to achieve a desirable social order. However, norms eventually can be conflicting — for example, when there is a norm that prohibits an agent to perform a particular action and another norm that obligates the same agent to perform the same action in the same period of time. The agent’s decision about which norms to fulfill can be defined based on rewards, punishments and agent goals. Sometimes, this balance will not be enough to allow the agent to make the best decision. In this context, this proposal introduces an approach that considers the agent’s personality traits in order to improve the plan decision-making process and resolving normative conflicts. Our approach’s applicability and validation is demonstrated by an experiment that reinforces the importance of considering the norms both in the agent’ and society’s points of view.

[17_MSc_furtado]
Pedro Henrique Thompson FURTADO. Interpretação automática de relatórios de operação de equipamentos. [Title in Portuguese: Automatic interpretation of equipment operation reports]. M.Sc. Diss. Port. Presentation: 20/04/2017. 130 p. Advisor: Hélio Côrtes Vieira Lopes.

Abstract: The operational units at the Exploration and Production (E&P) area at PETROBRAS make use of daily reports to register situations and events from their Stationary Production Units (SPUs), the well-known petroleum
production platforms. One of these reports, called SITOP (the Portuguese acronym for Offshore Unities’ Operational Situation), is a daily document in free text format that presents numerical information and, mainly, textual
information about operational situation of offshore units. The textual section, although unstructured, stores a valuable database with historical events in the production environment, such as: valve breakages, failures in processing equipment, beginning and end of maintenance activities, actions executed, responsibilities, etc. The value of these data is high, as well as the costs of searching relevant information, consuming many hours of attention from technicians and engineers to read the large number of documents. The goal of this dissertation is to develop a model of natural language processing to recognize named entities and extract relations among them, described formally as a domain ontology applied to events in offshore oil and gas processing units. After all, there will be a method for automatic structuring of the information from these operational reports. Our results show that this methodology is useful in SITOP’s case, also indicating some possible enhancements. Relation extraction showed better results than named entity recognition, what can be explained by the difference in the amount of classes in these tasks. We also verified that the increase in the amount of data was one of the most important factors for the improvement in learning and methodology efficiency as a whole.

[17_PhD_moura]
Pedro Nuno de Souza MOURA. LSHSIM: A Locality Sensitive Hashing Based Method for Multiple-Point Geostatistics. [Title in Portuguese: LSHSIM: Um Método de Geoestatística Multiponto Baseado em Locality Sensitivity Hashing]. Ph.D. Thesis. Eng. Presentation: 21/09/2017. 93 p. Advisor: Eduardo Sany Laber. DOI

Abstract: Reservoir modeling is a very important task that permits the representation of a geological region of interest. Given the uncertainty involved in the process, one wants to generate a considerable number of possible scenarios so as to find those which best represent this region. Then, there is a strong demand for quickly generating each simulation. Since its inception, many methodologies have been proposed for this purpose and, in the last two decades, multiple-point geostatistics (MPS) has been the dominant one. This methodology is strongly based on the concept of training image (TI) and the use of its characteristics, which are called patterns. In this work, we propose a new MPS method that combines the application of a technique called Locality Sensitive Hashing (LSH), which permits to accelerate the search for patterns similar to a target one, with a Run-Length Encoding (RLE) compression technique that speeds up the calculation of the Hamming similarity. We have performed experiments with both categorical and continuous images which showed that LSHSIM is computationally efficient and produce good quality realizations, while achieving a reasonable space of uncertainty. In particular, for categorical data, the results suggest that LSHSIM is faster than MS-CCSIM, one of the state-of-the-art methods.

[17_PhD_alves]
Priscilla Fonseca de Abreu BRAZ. Uma análise do espaço do problema End User Development no domínio de tecnologias para terapeutas do Transtorno do Espectro do Autismo. [Title in English: An analysis of the End User Development's problem space in the domain of technologies for Autism Spectrum Disorder's therapists]. Ph.D. Thesis. Port. Presentation: 11/01/2017. 160 p. Advisor: Alberto Barbosa Raposo and Clarisse Sieckenius de Souza.

Abstract: This thesis presents a study on the problem space in the context of development of technologies for Autism Spectrum Disorder's (ASD) therapists and it aims to contribute to the design of technologies in this area. Although there is a large number of technologies to the audience with ASD, such technologies usually allow a limited use, given the extent of the Autism Spectrum and the variety of disorders that people with ASD diagnosis can have. Thus, it is essential to develop more flexible technologies that meet the needs of each individual with ASD. Moreover, the literature presents specific reports (of success or failure) about the developed technologies, but there is no organization of the domain. Therefore, we consider that there is a gap regarding the problem characterization in this area, and it is important to explore the problem space before proposing new solutions. There are several challenges related to the adoption of technologies for generating adaptable software by ASD therapists, such as the lack or little knowledge of the therapists about this kind of technology, the limited time for learning and using these technologies and even the lack of interest. We conducted studies in order to explore the problem space in the context of the End User Development (EUD) and to raise the main meanings, questions and difficulties of the therapists related to adaptable and/or extensible technologies and they showed us that the use of the design probes concept was essential for the approximation of the therapists with such technology type and a deepening understanding of their own difficulties and needs, and the challenges placed in this context. Moreover, these studies have allowed us to raise a set of possible changes and adaptations that a technology targeted for this audience could do in order to address the needs of therapists and their patients. From this achieved set, we have analyzed these possible changes based on the Semiotic Engineering theory for EUD context and we have investigated how existing technologies enable or not these kinds of changes. Thus, this research has enabled us to identify the ASD domain as an EUD application area with several challenges, to analyze them in greater depth and to identify possible ways to overcome them, contributing to the design of technologies for the ASD audience.

[17_MSc_silva]
Rafael dos Reis SILVA. Direct and indirect quotation extraction for Portuguese. [Title in Portuguese: Extração de citações diretas e indiretas para o Português]. M.Sc. Diss. Eng. Presentation: 08/02/2017. 59 p. Advisor: Ruy Luiz Milidiú.

Abstract: Quotation Extraction consists of identifying quotations from a text and associating them to their authors. In this work, we present a Direct and Indirect Quotation Extraction System for Portuguese. Quotation Extraction has been previously approached using different techniques and for several languages. Our proposal differs from previous work, because we build a Machine Learning model that, besides recognizing direct quotations, it also recognizes indirect ones in Portuguese. Indirect quotations are hard to be identified in a text, due to the lack of explicit delimitation. Nevertheless, they happen more often then the delimited ones and, for this reason, have an huge importance on information extraction. Due to the fact that we use a Machine Learning model based, we can easily adapt it to other languages, needing only a list of verbs of speech for a given language. Few were the previously proposed systems that tackled the task of indirect quotations and neither of them for Portuguese using a Machine Learning approach. We build a Quotation Extractor using a model for the Structured Perceptron algorithm. In order to train and evaluate the system, we build QuoTrees 1.0 corpus. We annotate it to tackle the indirect quotation problem. The Structured Perceptron based on weight interval scheduling obtains an F1 score of 66% for QuoTrees 1.0 corpus.

[17_PhD_vasconcelos]
Rafael Oliveira VASCONCELOS. Uma abordagem eficiente para reconfiguração coordenada em sistemas distribuídos de processamento de data streams. [Title in English: An efficient approach to coordinated reconfiguration in distributed data stream systems]. Ph.D. Thesis. Port. Presentation: 07/04/2017. 74 p. Advisor: Markus Endler.

Abstract: While many data stream systems have to provide continuous (24x7) services with no acceptable downtime, they also have to cope with changes in their execution environments and in the requirements that they must comply (e.g., moving from on-premises architecture to a cloud system, changing the network technology, adding new functionality or modifying existing parts). On one hand, dynamic software reconfiguration (i.e., the capability of evolving on the fly) is a desirable feature. On the other hand, stream systems may suffer from the disruption and overhead caused by the reconfiguration. Due to the necessity of reconfiguring (i.e., evolving) the system whilst the system must not be disrupted (i.e., blocked), consistent and non-disruptive reconfiguration is still considered an open problem. This thesis presents and validates a non-quiescent approach for dynamic software reconfiguration that preserves the consistency of distributed data stream processing systems. Unlike many works that require the system to reach a safe state (e.g., quiescence) before performing a reconfiguration, the proposed approach enables the system to smoothly evolve (i.e., be reconfigured) in a non-disruptive way without reaching quiescence. The evaluation indicates that the proposed approach supports consistent distributed reconfiguration and has negligible impact on availability and performance. Furthermore, the implementation of the proposed approach showed better performance results in all experiments than the quiescent approach and Upstart.

[17_PhD_oliveira]
Roberto Felício de OLIVEIRA. To collaborate or not to collaborate? Improving the identification of code smells. [Title in Portuguese: Colaborar ou não colaborar? Melhorando a identificação de anomalias de código]. Ph.D. Thesis. Eng. Presentation: 21/08/2017. 143 p. Advisor: Carlos José Pereira de Lucena and Alessandro Fabricio Garcia. DOI

Abstract: Code smells are anomalous code structures which often indicate maintenance problems in software systems. The identification of code smells is required to reveal code elements, such as classes and methods, that are poorly structured. Some examples of code smell types perceived as critical by developers include God Classes and Feature Envy. However, the individual smell identification, which is performed by a single developer, may be ineective. Several studies have reported limitations of individual smell identification. For instance, the smell identification usually requires an indepth understanding of multiple elements scattered in a program, and each of these elements is better understood by a dierent developer. As a consequence, a single developer often struggles and to find to confirm or refute a code smell suspect. Collaborative smell identification, which is performed together by two or more collaborators, has the potential to address this problem. However, there is little empirical evidence on the eectiveness of collaborative smell identification. In this thesis, we addressed the aforementioned limitations as follows. First, we conducted empirical studies aimed at understanding the eectiveness of both collaborative and individual smell identification. We computed and compared the eectiveness of collaborators and single developers based on the number of correctly identified code smells. We conducted these studies in both industry’s companies and research laboratories with 67 developers, including novice and professional developers. Second, we defined some influential factors on the eectiveness of collaborative smell identification, such as the smell granularity. Third, we revealed and characterized some collaborative activities which improve the developers’ eectiveness for identifying code smells. Fourth, we also characterized opportunities for further improving the eectiveness of certain collaborative activities. Our results suggest that collaborators are more effective than single developers in: (i) both professional and academic settings, and (ii) identifying a wide range of code smell types.

[17_MSc_motta]
Thiago Ribeiro MOTTA. Uma avaliação de filtros 2D para remoção de ruído speckle em exames de ultrasom. [Title in English: An evaluation of 2D filters for Speckle denoising ultrasound exams]. M.Sc. Diss. Port. Presentation: 12/04/2017. 127 p. Advisor: Alberto Barbosa Raposo. DOI

Abstract: Ultrasound exams are a popular tool for image acquisition in day-to-day medicine, since it is a noninvasive, safe and cheap procedure. However, speckle noise is intrinsic to any ultrasound exam, and it is responsible for image quality degradation and for hindering its interpretation by doctors and patients alike, while also impairing the accuracy of post processing computational methods, such as classification, reconstruction, tissue characterization and segmentation, among others. Hence, smoothing or denoising methods that preserves the observed content core attributes are essential for those processes. Defined as a multiplicative noise, following non-Gaussian statistics and as strongly correlated, its solution today is still a matter of debates and research. In this work, several 2D filters that aim to smooth or remove speckle noise along with qualitative methods to evaluate their performances and means of choosing their best parameters are presented.

[17_PhD_nunes]
Thiago Ribeiro NUNES. A model for exploration of semi-structured datasets. [Title in Portuguese: Um modelo para exploração de dados semiestruturados]. Ph.D. Thesis. Eng. Presentation: 06/08/2017. 144 p. Advisor: Daniel Schwabe. DOI

Abstract: Information exploration processes are usually recognized by their inherent complexity, lack of knowledge and uncertainty, concerning both the domain and the solution strategies. Even though there has been much work on the development of computational systems supporting exploration tasks, such as faceted search and set-oriented interfaces, the lack of a formal understanding of the exploration process and the absence of a proper separation of concerns approach in the design phase is the cause of many expressivity issues and serious limitations. This work proposes a novel design approach of exploration tools based on a formal framework for representing exploration actions and processes. Moreover, we present a new exploration system that generalizes the majority of the state-of-the art exploration tools. The evaluation of the proposed framework is guided by case studies and comparisons with state-of-the-art tools. The results show the relevance of our approach both for the design of new exploration tools with higher expressiveness, and formal assessments and comparisons between different tools.

[17_MSc_tavares]
Vinícius Gama TAVARES. Sistema eficiente de otimização topológica estrutural utilizando o método de malha densa de barras. [Title in Portuguese: Efficient structural topology optimization system using the ground structure method]. M.Sc. Diss. Port. Presentation: 31/03/2017. 68 p. Advisor: Waldemar Celes Filho.

Abstract: Structural topology optimization methods are used to find the optimal material distribution within a given domain, subject to loading, boundary conditions and design constraints, in order to minimize some specified measure. Structural topology optimization can be divided into two types: continuum and discrete, with the discrete type being the research focus of this dissertation. The goal of this work is the creation of a system to achieve all the steps of this optimization process, aiming problems with large dimensions. In order to perform the optimization, it is necessary create a ground structure, defined as a set of nodes covering the entire domain, connected by bars, with the supports and the applied loads. This work proposes a new method for the ground structure generation, using as input only the domain boundary, in contrast with methods that require a domain already discretized, such as a polyhedron mesh. With the generated mesh, this work has implemented the topological optimization, needing to solve a linear programming problem. All the optimization part was performed within the TopSim framework, implementing the interior point method for the linear programming resolution. The results presented have good quality, both in generation and optimization, for 2D and 3D cases, considering cases with more than 68 million bars.

[17_MSc_garnica]
Yadira GARNICA BONOME. Proposing two new handling interaction techniques for 3D virtual objects using the Myo armband. [Title in English: Proposta de duas novas técnicas de manipulação de objetos virtuais 3D usando o bracelete Myo]. M.Sc. Diss. Port. Presentation: 17/05/2017. 73 p. Advisor: Alberto Barbosa Raposo.

Abstract: Flexibility and freedom are always desired in virtual reality environments. Traditional inputs, like mouse or keyboard, hamper the interactions between the user and the virtual environment. To improve the interaction in qualitative terms in a virtual environment, the interaction must be as natural as possible, and because of that, hand gestures have become a popular means to the human-computer interaction. The development of immersion devices like head-mounted displays brought the need for a new way of interaction and a challenge to developers. Hand gestures recognition using electromyography signals (EMG) has increased the attention because the rise of cheaper wearable devices that can record accurate EMG data. One of the outstanding devices in this area is Myo armband, equipped with eight EMG sensors and a nineaxis inertial measurement unit (IMU). The objective of this work is to evaluate the usability of the Myo armband as a device for selection and manipulation of 3D objects in virtual reality environments, aiming to improve the user experience, taking advantage of the possibility to measure the force applied to a gesture and to use Myo vibrations as a feedback system. This study aims to answer the following question: Has Myo armband high grade of usability for selection/manipulation of 3D objects in Virtual Reality Environments? And to achieve that purpose, four sub-questions were proposed to guide this research: I) Which resources of Myo can be used in Virtual Reality Environments (VRE)? II) What are the limitations of the Myo armband? III) Can selection and manipulation tasks be performed using Myo armband? IV) How can Myo armband enrich the selection and manipulation tasks? To answer to the first two sub-questions, we conducted a literature review that covers Myo technology, its advantages and limitations, and related works. Also, it includes basic concepts about Interactions in VRE. To answer to the last two sub-questions, we proposed two selection/manipulation techniques using Myo, which were tested with users and the results were compared, evaluating their usability.

[17_MSc_torres]
Yenier TORRES IZQUIERDO. Keyword search over federated RDF graphs by exploring their schemas. [Title in Portuguese: Busca por Palavras-chave sobre grafos RDF Federados explorando seus esquemas]. M.Sc. Diss. Port. Presentation: 31/03/2017. 66 p. Advisor: Marco Antonio Casanova.

Abstract: The Resource Description Framework (RDF) was adopted as a W3C recommendation in 1999 and today is a standard for exchanging data in the Web. Indeed, a large amount of data has been converted to RDF, often as multiple datasets physically distributed over different locations. The SPARQL Protocol and RDF Query Language (SPARQL) was officially introduced in 2008 to retrieve RDF datasets and provide endpoints to query distributed sources. An alternative way to access RDF datasets is to use keyword-based queries, an area that has been extensively researched, with a recent focus on Web content. This dissertation describes a strategy to compile keyword-based queries into federated SPARQL queries over distributed RDF datasets, under the assumption that each RDF dataset has a schema and that the federation has a mediated schema. The compilation process of the federated SPARQL query is explained in detail, including how to compute a set of external joins between the local subqueries, how to combine, with the help of the UNION clauses, the results of local queries which have no external joins between them, and how to construct the TARGET clause, according to the structure of the WHERE clause. Finally, the dissertation covers experiments with real-world data to validate the implementation.