Greenow: um algoritmo de roteamento orientado a workspace para uma arquitetura de Internet do futuro

Current and future applications pose new requirements that Internet architecture is not able to satisfy, like Mobility, Multicast, Multihoming, Bandwidth Guarantee and so on. The Internet architecture has some limitations which do not allow all future requirements to be covered. New architectures were proposed considering these requirements when a communication is established. ETArch (Entity Title Architecture) is a new Internet architecture, clean slate, able to use application’s requirements on each communication, and flexible to work with several layers. The Routing has an important role on Internet, because it decides the best way to forward primitives through the network. In Future Internet, all requirements depend on the routing. Routing is responsible for deciding the best path and, in the future, a better route can consider Mobility aspects or Energy Consumption, for instance. In the dawn of ETArch, the Routing has not been defined. This work provides intra and inter-domain routing algorithms to be used in the ETArch. It is considered that the route should be defined completely before the data start to traffic, to ensure that the requirements are met. In the Internet, the Routing has two distinct functions: (i) run specific algorithms to define the best route; and (ii) to forward data primitives to the correct link. In traditional Internet architecture, the two Routing functions are performed in all routers everytime that a packet arrives. This work allows that the complete route is defined before the communication starts, like in the telecommunication systems. This work determined the Routing for ETArch and experiments were performed to demonstrate the control plane routing viability. The initial setup before a communication takes longer, then only forwarding of primitives is performed, saving processing time.

ToPI - uma abordagem online para identificar locais de interesse utilizando fotografias geo-referenciadas

Due to the growing use of social networks people no longer just consume data, they also produce and share it. Geo-tagged information, i.e., data with geographical location, have been used in many attempts to identify popular places and help tourists that will visit unfamiliar cities. This Master Thesis presents an online strategy that uses geo-tagged photos and their metadata in order to identify places of interest inside a given geographical area and retrieve relevant related information. The whole process runs automatically in real time, returning updated information about places. The proposed strategy takes into account the inherent dynamism of social media, and thus is robust under inconsistencies and/or outdated information, a common issue in solutions that rely on previously stored data. The analysis of the results showed that our approach is very promising, returning places that present high agreement with those from a popular travel website.

Documentação automatizada de APIs com tutoriais gerados a partir do Stack Overflow

One of the most common forms of reuse is through API usage. However, one of the main challenges to effective usage is an accessible and easy to understand documentation. Several papers have proposed alternatives to make more understandable API documentation, or even more detailed. However, these studies have not taken into account the complexity of understanding of the examples to make these documentations adaptable to different levels of experience of developers. In this work we developed and evaluated four different methodologies to generate tutorials for APIs from the contents of Stack Overflow and organizing them according to the complexity of understanding. The methodologies were evaluated through tutorials generated for the Swing API. A survey was conducted to evaluate eight different features of the generated tutorials. The overall outcome of the tutorials was positive on several characteristics, showing the feasibility of the use of tutorials generated automatically. In addition, the use of criteria for presentation of tutorial elements in order of complexity, the separation of the tutorial in basic and advanced parts, the nature of tutorial to the selected posts and existence of didactic source had significantly different results regarding a chosen generation methodology. A second study compared the official documentation of the Android API and tutorial generated by the best methodology of the previous study. A controlled experiment was conducted with students who had a first contact with the Android development. In the experiment these students developed two tasks, one using the official documentation of Android and using the generated tutorial. The results of this experiment showed that in most cases, the students had the best performance in tasks when they used the tutorial proposed in this work. The main reasons for the poor performance of students in tasks using the official API documentation were due to lack of usage examples, as well as its difficult use.

Uma abordagem baseada em filtragem colaborativa integrada a mapas de saliência para a recomendação de imagens

Nowadays, the amount of customers using sites for shopping is greatly increasing, mainly due to the easiness and rapidity of this way of consumption. The sites, differently from physical stores, can make anything available to customers. In this context, Recommender Systems (RS) have become indispensable to help consumers to find products that may possibly pleasant or be useful to them. These systems often use techniques of Collaborating Filtering (CF), whose main underlying idea is that products are recommended to a given user based on purchase information and evaluations of past, by a group of users similar to the user who is requesting recommendation. One of the main challenges faced by such a technique is the need of the user to provide some information about her preferences on products in order to get further recommendations from the system. When there are items that do not have ratings or that possess quite few ratings available, the recommender system performs poorly. This problem is known as new item cold-start. In this paper, we propose to investigate in what extent information on visual attention can help to produce more accurate recommendation models. We present a new CF strategy, called IKB-MS, that uses visual attention to characterize images and alleviate the new item cold-start problem. In order to validate this strategy, we created a clothing image database and we use three algorithms well known for the extraction of visual attention these images. An extensive set of experiments shows that our approach is efficient and outperforms state-of-the-art CF RS.

O uso da Divergência de Kullback-Leibler e da Divergência Generalizada como medida de similaridade em sistemas CBIR

The content-based image retrieval is important for various purposes like disease diagnoses from computerized tomography, for example. The relevance, social and economic of image retrieval systems has created the necessity of its improvement. Within this context, the content-based image retrieval systems are composed of two stages, the feature extraction and similarity measurement. The stage of similarity is still a challenge due to the wide variety of similarity measurement functions, which can be combined with the different techniques present in the recovery process and return results that aren’t always the most satisfactory. The most common functions used to measure the similarity are the Euclidean and Cosine, but some researchers have noted some limitations in these functions conventional proximity, in the step of search by similarity. For that reason, the Bregman divergences (Kullback Leibler and I-Generalized) have attracted the attention of researchers, due to its flexibility in the similarity analysis. Thus, the aim of this research was to conduct a comparative study over the use of Bregman divergences in relation the Euclidean and Cosine functions, in the step similarity of content-based image retrieval, checking the advantages and disadvantages of each function. For this, it was created a content-based image retrieval system in two stages: offline and online, using approaches BSM, FISM, BoVW and BoVW-SPM. With this system was created three groups of experiments using databases: Caltech101, Oxford and UK-bench. The performance of content-based image retrieval system using the different functions of similarity was tested through of evaluation measures: Mean Average Precision, normalized Discounted Cumulative Gain, precision at k, precision x recall. Finally, this study shows that the use of Bregman divergences (Kullback Leibler and Generalized) obtains better results than the Euclidean and Cosine measures with significant gains for content-based image retrieval.

Navegação de um robô móvel baseado em um modelo de consciência artificial

This work presents a study about a the Baars-Franklin architecture, which defines a model of computational consciousness, and use it in a mobile robot navigation task. The insertion of mobile robots in dynamic environments carries a high complexity in navigation tasks, in order to deal with the constant environment changes, it is essential that the robot can adapt to this dynamism. The approach utilized in this work is to make the execution of these tasks closer to how human beings react to the same conditions by means of a model of computational consci-ousness. The LIDA architecture (Learning Intelligent Distribution Agent) is a cognitive system that seeks tomodel some of the human cognitive aspects, from low-level perceptions to decision making, as well as attention mechanism and episodic memory. In the present work, a computa-tional implementation of the LIDA architecture was evaluated by means of a case study, aiming to evaluate the capabilities of a cognitive approach to navigation of a mobile robot in dynamic and unknown environments, using experiments both with virtual environments (simulation) and a real robot in a realistic environment. This study concluded that it is possible to obtain benefits by using conscious cognitive models in mobile robot navigation tasks, presenting the positive and negative aspects of this approach.

Avaliação de características que influenciam nos votos de utilidade de opiniões sobre serviços em português

The large number of opinions generated by online users made the former “word of mouth” find its way to virtual world. In addition to be numerous, many of the useful reviews are mixed with a large number of fraudulent, incomplete or duplicate reviews. However, how to find the features that influence on the number of votes received by an opinion and find useful reviews? The literature on opinion mining has several studies and techniques that are able to analyze of properties found in the text of reviews. This paper presents the application of a methodology for evaluation of usefulness of opinions with the aim of identifying which characteristics have more influence on the amount of votes: basic utility (e.g. ratings about the product and/or service, date of publication), textual (e.g.size of words, paragraphs) and semantics (e.g., the meaning of the words of the text). The evaluation was performed in a database extracted from TripAdvisor with opinionsabout hotels written in Portuguese. Results show that users give more attention to recent opinions with higher scores for value and location of the hotel and with lowest scores for sleep quality and service and cleanliness. Texts with positive opinions, small words, few adjectives and adverbs increase the chances of receiving more votes.

Estudo da efetividade dos mecanismos de compartilhamento de memória em hipervisores

The growing demand for large-scale virtualization environments, such as the ones used in cloud computing, has led to a need for efficient management of computing resources. RAM memory is the one of the most required resources in these environments, and is usually the main factor limiting the number of virtual machines that can run on the physical host. Recently, hypervisors have brought mechanisms for transparent memory sharing between virtual machines in order to reduce the total demand for system memory. These mechanisms “merge” similar pages detected in multiple virtual machines into the same physical memory, using a copy-on-write mechanism in a manner that is transparent to the guest systems. The objective of this study is to present an overview of these mechanisms and also evaluate their performance and effectiveness. The results of two popular hypervisors (VMware and KVM) using different guest operating systems (Linux and Windows) and different workloads (synthetic and real) are presented herein. The results show significant performance differences between hypervisors according to the guest system workloads and execution time.

Influência da revisão de atividades executadas para melhoria da acurácia na estimativa de software utilizando planning poker

Abstract – Background – The software effort estimation research area aims to improve the accuracy of this estimation in software projects and activities. Aims – This study describes the development and usage of a web application tocollect data generated from the Planning Poker estimation process and the analysis of the collected data to investigate the impact of revising previous estimates when conducting similar estimates in a Planning Poker context. Method – Software activities were estimated by Universidade Tecnológica Federal do Paraná (UTFPR) computer students, using Planning Poker, with and without revising previous similar activities, storing data regarding the decision-making process. And the collected data was used to investigate the impact that revising similar executed activities have in the software effort estimates' accuracy.Obtained Results – The UTFPR computer students were divided into 14 groups. Eight of them showed accuracy increase in more than half of their estimates. Three of them had almost the same accuracy in more than half of their estimates. And only three of them had loss of accuracy in more than half of their estimates. Conclusion – Reviewing the similar executed software activities, when using Planning Poker, led to more accurate software estimates in most cases, and, because of that, can improve the software development process.

Metodologia participativa para repositórios de recursos educacionais abertos

This research deals with the use of a participatory design methodology to develop a repository of open educational resources, the Arcaz. Discusses key aspects of neutrality and determinism of technology within the context of Social Studies of Science and Technology and presents some concepts of critical theory of technology related to the democratic construction of technological artifacts. Discusses the philosophical heritage of the movements that led to the emergence of free software, open education and open educational resources and argues that participatory design share similar ideals. It presents concepts of human-computer interaction, interaction design and user centered design, important to enhance the user experience in information systems. It addresses the participatory design as a methodology that allows the democratic participation of users in the technological construction, promoting mutual learning and active voice for the participants. Develops a participatory design methodology adapted to the Arcaz context of use and provides the procedures for the meetings conducted to apply participatory design techniques to the repository and the results obtained. It concludes with a study of some of the interventions suggested in the system and orientations for future applications of participatory practices in the development of the repository and a list of best practices, focusing on ethical principles that should guide the participatory design.

Know-cap: um método para capitalização de conhecimento no desenvolvimento de software

The intensive character in knowledge of software production and its rising demand suggest the need to establish mechanisms to properly manage the knowledge involved in order to meet the requirements of deadline, costs and quality. The knowledge capitalization is a process that involves from identification to evaluation of the knowledge produced and used. Specifically, for software development, capitalization enables easier access, minimize the loss of knowledge, reducing the learning curve, avoid repeating errors and rework. Thus, this thesis presents the know-Cap, a method developed to organize and guide the capitalization of knowledge in software development. The Know-Cap facilitates the location, preservation, value addition and updating of knowledge, in order to use it in the execution of new tasks. The method was proposed from a set of methodological procedures: literature review, systematic review and analysis of related work. The feasibility and appropriateness of Know-Cap were analyzed from an application study, conducted in a real case, and an analytical study of software development companies. The results obtained indicate the Know- Cap supports the capitalization of knowledge in software development.

A contribution to semantic description of images and videos: an application of soft biometrics

Humans have a high ability to extract visual data information acquired by sight. Trought a learning process, which starts at birth and continues throughout life, image interpretation becomes almost instinctively. At a glance, one can easily describe a scene with reasonable precision, naming its main components. Usually, this is done by extracting low-level features such as edges, shapes and textures, and associanting them to high level meanings. In this way, a semantic description of the scene is done. An example of this, is the human capacity to recognize and describe other people physical and behavioral characteristics, or biometrics. Soft-biometrics also represents inherent characteristics of human body and behaviour, but do not allow unique person identification. Computer vision area aims to develop methods capable of performing visual interpretation with performance similar to humans. This thesis aims to propose computer vison methods which allows high level information extraction from images in the form of soft biometrics. This problem is approached in two ways, unsupervised and supervised learning methods. The first seeks to group images via an automatic feature extraction learning , using both convolution techniques, evolutionary computing and clustering. In this approach employed images contains faces and people. Second approach employs convolutional neural networks, which have the ability to operate on raw images, learning both feature extraction and classification processes. Here, images are classified according to gender and clothes, divided into upper and lower parts of human body. First approach, when tested with different image datasets obtained an accuracy of approximately 80% for faces and non-faces and 70% for people and non-person. The second tested using images and videos, obtained an accuracy of about 70% for gender, 80% to the upper clothes and 90% to lower clothes. The results of these case studies, show that proposed methods are promising, allowing the realization of automatic high level information image annotation. This opens possibilities for development of applications in diverse areas such as content-based image and video search and automatica video survaillance, reducing human effort in the task of manual annotation and monitoring.

Protocolo de roteamento para redes oportunistas utilizando otimização por enxame de partículas

In this research work, a new routing protocol for Opportunistic Networks is presented. The proposed protocol is called PSONET (PSO for Opportunistic Networks) since the proposal uses a hybrid system composed of a Particle Swarm Optimization algorithm (PSO). The main motivation for using the PSO is to take advantage of its search based on individuals and their learning adaptation. The PSONET uses the Particle Swarm Optimization technique to drive the network traffic through of a good subset of forwarders messages. The PSONET analyzes network communication conditions, detecting whether each node has sparse or dense connections and thus make better decisions about routing messages. The PSONET protocol is compared with the Epidemic and PROPHET protocols in three different scenarios of mobility: a mobility model based in activities, which simulates the everyday life of people in their work activities, leisure and rest; a mobility model based on a community of people, which simulates a group of people in their communities, which eventually will contact other people who may or may not be part of your community, to exchange information; and a random mobility pattern, which simulates a scenario divided into communities where people choose a destination at random, and based on the restriction map, move to this destination using the shortest path. The simulation results, obtained through The ONE simulator, show that in scenarios where the mobility model based on a community of people and also where the mobility model is random, the PSONET protocol achieves a higher messages delivery rate and a lower replication messages compared with the Epidemic and PROPHET protocols.

Detecção de região saliente em imagens usando dissimilaridade de cor e amostragem por pixeis aleatórios

The purpose of this work is to demonstrate and to assess a simple algorithm for automatic estimation of the most salient region in an image, that have possible application in computer vision. The algorithm uses the connection between color dissimilarities in the image and the image’s most salient region. The algorithm also avoids using image priors. Pixel dissimilarity is an informal function of the distance of a specific pixel’s color to other pixels’ colors in an image. We examine the relation between pixel color dissimilarity and salient region detection on the MSRA1K image dataset. We propose a simple algorithm for salient region detection through random pixel color dissimilarity. We define dissimilarity by accumulating the distance between each pixel and a sample of n other random pixels, in the CIELAB color space. An important result is that random dissimilarity between each pixel and just another pixel (n = 1) is enough to create adequate saliency maps when combined with median filter, with competitive average performance if compared with other related methods in the saliency detection research field. The assessment was performed by means of precision-recall curves. This idea is inspired on the human attention mechanism that is able to choose few specific regions to focus on, a biological system that the computer vision community aims to emulate. We also review some of the history on this topic of selective attention.

Problem-Based SRS: método para especificação de requisitos de software baseado em problemas

Requirements specification has long been recognized as critical activity in software development processes because of its impact on project risks when poorly performed. A large amount of studies addresses theoretical aspects, propositions of techniques, and recommended practices for Requirements Engineering (RE). To be successful, RE have to ensure that the specified requirements are complete and correct what means that all intents of the stakeholders in a given business context are covered by the requirements and that no unnecessary requirement was introduced. However, the accurate capture the business intents of the stakeholders remains a challenge and it is a major factor of software project failures. This master’s dissertation presents a novel method referred to as “Problem-Based SRS” aiming at improving the quality of the Software Requirements Specification (SRS) in the sense that the stated requirements provide suitable answers to real customer ́s businesses issues. In this approach, the knowledge about the software requirements is constructed from the knowledge about the customer ́s problems. Problem-Based SRS consists in an organization of activities and outcome objects through a process that contains five main steps. It aims at supporting the software requirements engineering team to systematically analyze the business context and specify the software requirements, taking also into account a first glance and vision of the software. The quality aspects of the specifications are evaluated using traceability techniques and axiomatic design principles. The cases studies conducted and presented in this document point out that the proposed method can contribute significantly to improve the software requirements specification.