Investigando a compressão da percepção de distância em ambientes virtuais através da comparação entre dispositivos de visualização

The correct distance perception is important for executing various interactive tasks such as navigation, selection and manipulation. It is known, however, that, in general, there is a significant distance perception compression in virtual environments, mainly when using Head-Mounted Displays - HMDs. This perceived distance compression may bring various problems to the applications and even affect in a negative way the utility of those applications that depends on the correct judgment of distances. The scientific community, so far, have not been able to determine the causes of the distance perception compression in virtual environments. For this reason, it was the objective of this work to investigate, through experiments with users, the influence of both the field-of-view - FoV - and the distance estimation methods on this perceived compression. For that, an experimental comparison between the my3D device and a HMD, using 32 participants, seeking to find information on the causes of the compressed perception, was executed. The results showed that the my3D has inferior capabilities when compared to the HMD, resulting in worst estimations, on average, in both the tested estimation methods. The causes of that are believed to be the incorrect stimulus of the peripheral vision of the user, the smaller FoV and the smaller immersion sense, as described by the participants of the experiment.

Investigando o uso do sentido háptico na visualização de dados multivariados em gráficos de dispersão bidimensionais

Data Visualization is widely used to facilitate the comprehension of information and find relationships between data. One of the most widely used techniques for multivariate data (4 or more variables) visualization is the 2D scatterplot. This technique associates each data item to a visual mark in the following way: two variables are mapped to Cartesian coordinates so that a visual mark can be placed on the Cartesian plane; the others variables are mapped gradually to visual properties of the mark, such as size, color, shape, among others. As the number of variables to be visualized increases, the amount of visual properties associated to the mark increases as well. As a result, the complexity of the final visualization is higher. However, increasing the complexity of the visualization does not necessarily implies a better visualization and, sometimes, it provides an inverse situation, producing a visually polluted and confusing visualization—this problem is called visual properties overload. This work aims to investigate whether it is possible to work around the overload of the visual channel and improve insight about multivariate data visualized through a modification in the 2D scatterplot technique. In this modification, we map the variables from data items to multisensoriy marks. These marks are composed not only by visual properties, but haptic properties, such as vibration, viscosity and elastic resistance, as well. We believed that this approach could ease the insight process, through the transposition of properties from the visual channel to the haptic channel. The hypothesis was verified through experiments, in which we have analyzed (a) the accuracy of the answers; (b) response time; and (c) the grade of personal satisfaction with the proposed approach. However, the hypothesis was not validated. The results suggest that there is an equivalence between the investigated visual and haptic properties in all analyzed aspects, though in strictly numeric terms the multisensory visualization achieved better results in response time and personal satisfaction.

Infoestrutura: um sistema em nuvem para prover contexto como serviço no cenário de internet das coisas integrado a ambientes veiculares

Through numerous technological advances in recent years along with the popularization of computer devices, the company is moving towards a paradigm “always connected”. Computer networks are everywhere and the advent of IPv6 paves the way for the explosion of the Internet of Things. This concept enables the sharing of data between computing machines and objects of day-to-day. One of the areas placed under Internet of Things are the Vehicular Networks. However, the information generated individually for a vehicle has no large amount and does not contribute to an improvement in transit, once information has been isolated. This proposal presents the Infostructure, a system that has to facilitate the efforts and reduce costs for development of applications context-aware to high-level semantic for the scenario of Internet of Things, which allows you to manage, store and combine the data in order to generate broader context. To this end we present a reference architecture, which aims to show the major components of the Infostructure. Soon after a prototype is presented which is used to validate our work reaches the level of contextualization desired high level semantic as well as a performance evaluation, which aims to evaluate the behavior of the subsystem responsible for managing contextual information on a large amount of data. After statistical analysis is performed with the results obtained in the evaluation. Finally, the conclusions of the work and some problems such as no assurance as to the integrity of the sensory data coming Infostructure, and future work that takes into account the implementation of other modules so that we can conduct tests in real environments are presented.

Cloud Stratus: uma plataforma de middleware para desenvolvimento de aplicações em nuvem

Cloud Computing is a paradigm that enables the access, in a simple and pervasive way, through the network, to shared and configurable computing resources. Such resources can be offered on demand to users in a pay-per-use model. With the advance of this paradigm, a single service offered by a cloud platform might not be enough to meet all the requirements of clients. Ergo, it is needed to compose services provided by different cloud platforms. However, current cloud platforms are not implemented using common standards, each one has its own APIs and development tools, which is a barrier for composing different services. In this context, the Cloud Integrator, a service-oriented middleware platform, provides an environment to facilitate the development and execution of multi-cloud applications. The applications are compositions of services, from different cloud platforms and, represented by abstract workflows. However, Cloud Integrator has some limitations, such as: (i) applications are locally executed; (ii) users cannot specify the application in terms of its inputs and outputs, and; (iii) experienced users cannot directly determine the concrete Web services that will perform the workflow. In order to deal with such limitations, this work proposes Cloud Stratus, a middleware platform that extends Cloud Integrator and offers different ways to specify an application: as an abstract workflow or a complete/partial execution flow. The platform enables the application deployment in cloud virtual machines, so that several users can access it through the Internet. It also supports the access and management of virtual machines in different cloud platforms and provides services monitoring mechanisms and assessment of QoS parameters. Cloud Stratus was validated through a case study that consists of an application that uses different services provided by different cloud platforms. Cloud Stratus was also evaluated through computing experiments that analyze the performance of its processes.

Segmentação fuzzy de objetos tridimensionais com propriedades texturais

Digital image segmentation is the process of assigning distinct labels to different objects in a digital image, and the fuzzy segmentation algorithm has been used successfully in the segmentation of images from several modalities. However, the traditional fuzzy segmentation algorithm fails to segment objects that are characterized by textures whose patterns cannot be successfully described by simple statistics computed over a very restricted area. In this paper we present an extension of the fuzzy segmentation algorithm that achieves the segmentation of textures by employing adaptive affinity functions as long as we extend the algorithm to tridimensional images. The adaptive affinity functions change the size of the area where they compute the texture descriptors, according to the characteristics of the texture being processed, while three dimensional images can be described as a finite set of two-dimensional images. The algorithm then segments the volume image with an appropriate calculation area for each texture, making it possible to produce good estimates of actual volumes of the target structures of the segmentation process. We will perform experiments with synthetic and real data in applications such as segmentation of medical imaging obtained from magnetic rosonance

Uma máquina de redução de grafos extensível para a implementação de fluxos de trabalho

Graph Reduction Machines, are a traditional technique for implementing functional programming languages. They allow to run programs by transforming graphs by the successive application of reduction rules. Web service composition enables the creation of new web services from existing ones. BPEL is a workflow-based language for creating web service compositions. It is also the industrial and academic standard for this kind of languages. As it is designed to compose web services, the use of BPEL in a scenario where multiple technologies need to be used is problematic: when operations other than web services need to be performed to implement the business logic of a company, part of the work is done on an ad hoc basis. To allow heterogeneous operations to be part of the same workflow, may help to improve the implementation of business processes in a principled way. This work uses a simple variation of the BPEL language for creating compositions containing not only web service operations but also big data tasks or user-defined operations. We define an extensible graph reduction machine that allows the evaluation of BPEL programs and implement this machine as proof of concept. We present some experimental results.

An augmented reality pipeline to create scenes with coherent illumination using textured cuboids

Shadows and illumination play an important role when generating a realistic scene in computer graphics. Most of the Augmented Reality (AR) systems track markers placed in a real scene and retrieve their position and orientation to serve as a frame of reference for added computer generated content, thereby producing an augmented scene. Realistic depiction of augmented content with coherent visual cues is a desired goal in many AR applications. However, rendering an augmented scene with realistic illumination is a complex task. Many existent approaches rely on a non automated pre-processing phase to retrieve illumination parameters from the scene. Other techniques rely on specific markers that contain light probes to perform environment lighting estimation. This study aims at designing a method to create AR applications with coherent illumination and shadows, using a textured cuboid marker, that does not require a training phase to provide lighting information. Such marker may be easily found in common environments: most of product packaging satisfies such characteristics. Thus, we propose a way to estimate a directional light configuration using multiple texture tracking to render AR scenes in a realistic fashion. We also propose a novel feature descriptor that is used to perform multiple texture tracking. Our descriptor is an extension of the binary descriptor, named discrete descriptor, and outperforms current state-of-the-art methods in speed, while maintaining their accuracy.

Contribuições para o processo de verificação de satisfatibilidade módulo teoria em Event-B

Event-B is a formal method for modeling and verification of discrete transition systems. Event-B development yields proof obligations that must be verified (i.e. proved valid) in order to keep the produced models consistent. Satisfiability Modulo Theory solvers are automated theorem provers used to verify the satisfiability of logic formulas considering a background theory (or combination of theories). SMT solvers not only handle large firstorder formulas, but can also generate models and proofs, as well as identify unsatisfiable subsets of hypotheses (unsat-cores). Tool support for Event-B is provided by the Rodin platform: an extensible Eclipse based IDE that combines modeling and proving features. A SMT plug-in for Rodin has been developed intending to integrate alternative, efficient verification techniques to the platform. We implemented a series of complements to the SMT solver plug-in for Rodin, namely improvements to the user interface for when proof obligations are reported as invalid by the plug-in. Additionally, we modified some of the plug-in features, such as support for proof generation and unsat-core extraction, to comply with the SMT-LIB standard for SMT solvers. We undertook tests using applicable proof obligations to demonstrate the new features. The contributions described can potentially affect productivity in a positive manner.

Utilizando comitês de classificadores para predição de rendimento escolar

Educational Data Mining is an application domain in artificial intelligence area that has been extensively explored nowadays. Technological advances and in particular, the increasing use of virtual learning environments have allowed the generation of considerable amounts of data to be investigated. Among the activities to be treated in this context exists the prediction of school performance of the students, which can be accomplished through the use of machine learning techniques. Such techniques may be used for student’s classification in predefined labels. One of the strategies to apply these techniques consists in their combination to design multi-classifier systems, which efficiency can be proven by results achieved in other studies conducted in several areas, such as medicine, commerce and biometrics. The data used in the experiments were obtained from the interactions between students in one of the most used virtual learning environments called Moodle. In this context, this paper presents the results of several experiments that include the use of specific multi-classifier systems systems, called ensembles, aiming to reach better results in school performance prediction that is, searching for highest accuracy percentage in the student’s classification. Therefore, this paper presents a significant exploration of educational data and it shows analyzes of relevant results about these experiments.

Mecanismo de tolerância a falhas através de escalonamento para uma arquitetura reconfigurável de grão grosso

The continuous evolution of integrated circuit technology has allowed integrating thousands of transistors on a single chip. This is due to the miniaturization process, which reduces the diameter of wires and transistors. One drawback of this process is that the circuit becomes more fragile and susceptible to break, making the circuit more susceptible to permanent faults during the manufacturing process as well as during their lifetime. Coarse Grained Reconfigurable Architectures (CGRAs) have been used as an alternative to traditional architectures in an attempt to tolerate such faults due to its intrinsic hardware redundancy and high performance. This work proposes a fault tolerance mechanism in a CGRA in order to increase the architecture fault tolerance even considering a high fault rate. The proposed mechanism was added to the scheduler, which is the mechanism responsible for mapping instructions onto the architecture. The instruction mapping occurs at runtime, translating binary code without the need for recompilation. Furthermore, to allow faster implementation, instruction mapping is performed using a greedy module scheduling algorithm, which consists of a software pipeline technique for loop acceleration. The results show that, even with the proposed mechanism, the time for mapping instructions is still in order of microseconds. This result allows that instruction mapping process remains at runtime. In addition, a study was also carried out mapping scheduler rate. The results demonstrate that even at fault rates over 50% in functional units and interconnection components, the scheduler was able to map instructions onto the architecture in most of the tested applications.

Uma abordagem para avaliação e tratamento de exceções propagadas no uso de serviços Web em .Net

High dependability, availability and fault-tolerance are open problems in Service-Oriented Architecture (SOA). The possibility of generating software applications by integrating services from heterogeneous domains, in a reliable way, makes worthwhile to face the challenges inherent to this paradigm. In order to ensure quality in service compositions, some research efforts propose the adoption of verification techniques to identify and correct errors. In this context, exception handling is a powerful mechanism to increase SOA quality. Several research works are concerned with mechanisms for exception propagation on web services, implemented in many languages and frameworks. However, to the extent of our knowledge, no works found evaluates these mechanisms in SOA with regard to the .NET framework. The main contribution of this paper is to evaluate and to propose exception propagation mechanisms in SOA to applications developed within the .NET framework. In this direction, this work: (i)extends a previous study, showing the need to propose a solution to the exception propagation in SOA to applications developed in .NET, and (ii) show a solution, based in model obtained from the results found in (i) and that will be applied in real cases through of faults injections and AOP techniques.

Classificação de técnicas e auxílio à navegação de busca com base em sua carga cognitiva, precisão e eficiência

Navigation, in both virtual and real environments, is the process of a deliberated movement to a specific place that is usually away from the origin point, and that cannot be perceived from it. Navigation aid techniques (TANs) have as their main objective help finding a path through a virtual environment to a desired location and, are widely used because they ease the navigation on these unknown environments. Tools like maps, GPS (Global Positioning System) or even oral instructions are real world examples of TAN usage. Most of the works which propose new TANs for virtual environments aim to analyze their impact in efficiency gain on navigation tasks from a known place to an unknown place. However, such papers tend to ignore the effect caused by a TAN usage over the route knowledge acquisition process, which is important on virtual to real training transfer, for example. Based on a user study, it was possible to confirm that TANs with different strategies affects the performance of search tasks differently and that the efficiency of the help provided by a TAN is not inversely related to the cognitive load of the technique’s aids. A technique classification formula was created. This formula utilizes three factors instead of only efficiency. The experiment’s data were applied to the formula and we obtained a better refinement of help level provided by TANs.

Cloud query manager: uso de web semântica para evitar o problema de aprisionamento em IaaS

Cloud computing can be defined as a distributed computational model by through resources (hardware, storage, development platforms and communication) are shared, as paid services accessible with minimal management effort and interaction. A great benefit of this model is to enable the use of various providers (e.g a multi-cloud architecture) to compose a set of services in order to obtain an optimal configuration for performance and cost. However, the multi-cloud use is precluded by the problem of cloud lock-in. The cloud lock-in is the dependency between an application and a cloud platform. It is commonly addressed by three strategies: (i) use of intermediate layer that stands to consumers of cloud services and the provider, (ii) use of standardized interfaces to access the cloud, or (iii) use of models with open specifications. This paper outlines an approach to evaluate these strategies. This approach was performed and it was found that despite the advances made by these strategies, none of them actually solves the problem of lock-in cloud. In this sense, this work proposes the use of Semantic Web to avoid cloud lock-in, where RDF models are used to specify the features of a cloud, which are managed by SPARQL queries. In this direction, this work: (i) presents an evaluation model that quantifies the problem of cloud lock-in, (ii) evaluates the cloud lock-in from three multi-cloud solutions and three cloud platforms, (iii) proposes using RDF and SPARQL on management of cloud resources, (iv) presents the cloud Query Manager (CQM), an SPARQL server that implements the proposal, and (v) comparing three multi-cloud solutions in relation to CQM on the response time and the effectiveness in the resolution of cloud lock-in.

Proposta de um processador multithreading com características de previsibilidade

The real-time embedded systems design requires precise control of the passage of time in the computation performed by the modules and communication between them. Generally, these systems consist of several modules, each designed for a specific task and restricted communication with other modules in order to obtain the required timing. This strategy, called federated architecture, is already becoming unviable in front of the current demands of cost, required performance and quality of embedded system. To address this problem, it has been proposed the use of integrated architectures that consist of one or few circuits performing multiple tasks in parallel in a more efficient manner and with reduced costs. However, one has to ensure that the integrated architecture has temporal composability, ie the ability to design each task temporally isolated from the others in order to maintain the individual characteristics of each task. The Precision Timed Machines are an integrated architecture approach that makes use of multithreaded processors to ensure temporal composability. Thus, this work presents the implementation of a Precision Machine Timed named Hivek-RT. This processor which is a VLIW supporting Simultaneous Multithreading is capable of efficiently execute real-time tasks when compared to a traditional processor. In addition to the efficient implementation, the proposed architecture facilitates the implementation real-time tasks from a programming point of view.

Uma plataforma adaptável para localização em ambientes internos

Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.